WorldWideScience

Sample records for network systems based

  1. Model-based control of networked systems

    CERN Document Server

    Garcia, Eloy; Montestruque, Luis A

    2014-01-01

    This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled.   The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control.   Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...

  2. WIRELESS SENSOR NETWORK BASED CONVEYOR SURVEILLANCE SYSTEM

    OpenAIRE

    Attila Trohák; Máté Kolozsi-Tóth; Péter Rádi

    2011-01-01

    In the paper we will introduce an intelligent conveyor surveillance system. We started a research project to design and develop a conveyor surveillance system based on wireless sensor network and GPRS communication. Our system is able to measure temperature on fixed and moving, rotating surfaces and able to detect smoke. We would like to introduce the developed devices and give an application example.

  3. ENERGY AWARE NETWORK: BAYESIAN BELIEF NETWORKS BASED DECISION MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Chaudhari

    2011-06-01

    Full Text Available A Network Management System (NMS plays a very important role in managing an ever-evolving telecommunication network. Generally an NMS monitors & maintains the health of network elements. The growing size of the network warrants extra functionalities from the NMS. An NMS provides all kinds of information about networks which can be used for other purposes apart from monitoring & maintaining networks like improving QoS & saving energy in the network. In this paper, we add another dimension to NMS services, namely, making an NMS energy aware. We propose a Decision Management System (DMS framework which uses a machine learning technique called Bayesian Belief Networks (BBN, to make the NMS energy aware. The DMS is capable of analysing and making control decisions based on network traffic. We factor in the cost of rerouting and power saving per port. Simulations are performed on standard network topologies, namely, ARPANet and IndiaNet. It is found that ~2.5-6.5% power can be saved.

  4. A network-based dynamical ranking system

    CERN Document Server

    Motegi, Shun

    2012-01-01

    Ranking players or teams in sports is of practical interests. From the viewpoint of networks, a ranking system is equivalent a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score (i.e., strength) of a player, for example, depends on time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. Our ranking system, also interpreted as a centrality measure for directed temporal networks, has two parameters. One parameter represents the exponential decay rate of the past score, and the other parameter controls the effect of indirect wins on the score. We derive a set of linear online update equ...

  5. Wireless Sensor Network Based Smart Parking System

    Directory of Open Access Journals (Sweden)

    Jeffrey JOSEPH

    2014-01-01

    Full Text Available Ambient Intelligence is a vision in which various devices come together and process information from multiple sources in order to exert control on the physical environment. In addition to computation and control, communication plays a crucial role in the overall functionality of such a system. Wireless Sensor Networks are one such class of networks, which meet these criteria. These networks consist of spatially distributed sensor motes which work in a co-operative manner to sense and control the environment. In this work, an implementation of an energy-efficient and cost-effective, wireless sensor networks based vehicle parking system for a multi-floor indoor parking facility has been introduced. The system monitors the availability of free parking slots and guides the vehicle to the nearest free slot. The amount of time the vehicle has been parked is monitored for billing purposes. The status of the motes (dead/alive is also recorded. Information like slot allocated, directions to the slot and billing data is sent as a message to customer’s mobile phones. This paper extends our previous work 1 with the development of a low cost sensor mote, about one tenth the cost of a commercially available mote, keeping in mind the price sensitive markets of the developing countries.

  6. Network video transmission system based on SOPC

    Science.gov (United States)

    Zhang, Zhengbing; Deng, Huiping; Xia, Zhenhua

    2008-03-01

    Video systems have been widely used in many fields such as conferences, public security, military affairs and medical treatment. With the rapid development of FPGA, SOPC has been paid great attentions in the area of image and video processing in recent years. A network video transmission system based on SOPC is proposed in this paper for the purpose of video acquisition, video encoding and network transmission. The hardware platform utilized to design the system is an SOPC board of model Altera's DE2, which includes an FPGA chip of model EP2C35F672C6, an Ethernet controller and a video I/O interface. An IP core, known as Nios II embedded processor, is used as the CPU of the system. In addition, a hardware module for format conversion of video data, and another module to realize Motion-JPEG have been designed with Verilog HDL. These two modules are attached to the Nios II processor as peripheral equipments through the Avalon bus. Simulation results show that these two modules work as expected. Uclinux including TCP/IP protocol as well as the driver of Ethernet controller is chosen as the embedded operating system and an application program scheme is proposed.

  7. Neural network based system for equipment surveillance

    Science.gov (United States)

    Vilim, R.B.; Gross, K.C.; Wegerich, S.W.

    1998-04-28

    A method and system are disclosed for performing surveillance of transient signals of an industrial device to ascertain the operating state. The method and system involves the steps of reading into a memory training data, determining neural network weighting values until achieving target outputs close to the neural network output. If the target outputs are inadequate, wavelet parameters are determined to yield neural network outputs close to the desired set of target outputs and then providing signals characteristic of an industrial process and comparing the neural network output to the industrial process signals to evaluate the operating state of the industrial process. 33 figs.

  8. 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.

  9. On Emulation-Based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Abbasi, Ali; Wetzel, Jos; Bokslag, Wouter; Zambon, Emmanuele; Etalle, Sandro

    2014-01-01

    Emulation-based network intrusion detection systems have been devised to detect the presence of shellcode in network traffic by trying to execute (portions of) the network packet payloads in an in- strumented environment and checking the execution traces for signs of shellcode activity.

  10. FIPA agent based network distributed control system

    Energy Technology Data Exchange (ETDEWEB)

    D. Abbott; V. Gyurjyan; G. Heyes; E. Jastrzembski; C. Timmer; E. Wolin

    2003-03-01

    A control system with the capabilities to combine heterogeneous control systems or processes into a uniform homogeneous environment is discussed. This dynamically extensible system is an example of the software system at the agent level of abstraction. This level of abstraction considers agents as atomic entities that communicate to implement the functionality of the control system. Agents' engineering aspects are addressed by adopting the domain independent software standard, formulated by FIPA. Jade core Java classes are used as a FIPA specification implementation. A special, lightweight, XML RDFS based, control oriented, ontology markup language is developed to standardize the description of the arbitrary control system data processor. Control processes, described in this language, are integrated into the global system at runtime, without actual programming. Fault tolerance and recovery issues are also addressed.

  11. A network-based dynamical ranking system for competitive sports

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-12-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  12. A network-based dynamical ranking system for competitive sports.

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-01-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  13. Applying Model Based Systems Engineering to NASA's Space Communications Networks

    Science.gov (United States)

    Bhasin, Kul; Barnes, Patrick; Reinert, Jessica; Golden, Bert

    2013-01-01

    System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its

  14. Virtualized Network Function Orchestration System and Experimental Network Based QR Recognition for a 5G Mobile Access Network

    Directory of Open Access Journals (Sweden)

    Misun Ahn

    2017-12-01

    Full Text Available This paper proposes a virtualized network function orchestration system based on Network Function Virtualization (NFV, one of the main technologies in 5G mobile networks. This system should provide connectivity between network devices and be able to create flexible network function and distribution. This system focuses more on access networks. By experimenting with various scenarios of user service established and activated in a network, we examine whether rapid adoption of new service is possible and whether network resources can be managed efficiently. The proposed method is based on Bluetooth transfer technology and mesh networking to provide automatic connections between network machines and on a Docker flat form, which is a container virtualization technology for setting and managing key functions. Additionally, the system includes a clustering and recovery measure regarding network function based on the Docker platform. We will briefly introduce the QR code perceived service as a user service to examine the proposal and based on this given service, we evaluate the function of the proposal and present analysis. Through the proposed approach, container relocation has been implemented according to a network device’s CPU usage and we confirm successful service through function evaluation on a real test bed. We estimate QR code recognition speed as the amount of network equipment is gradually increased, improving user service and confirm that the speed of recognition is increased as the assigned number of network devices is increased by the user service.

  15. A complex network-based importance measure for mechatronics systems

    Science.gov (United States)

    Wang, Yanhui; Bi, Lifeng; Lin, Shuai; Li, Man; Shi, Hao

    2017-01-01

    In view of the negative impact of functional dependency, this paper attempts to provide an alternative importance measure called Improved-PageRank (IPR) for measuring the importance of components in mechatronics systems. IPR is a meaningful extension of the centrality measures in complex network, which considers usage reliability of components and functional dependency between components to increase importance measures usefulness. Our work makes two important contributions. First, this paper integrates the literature of mechatronic architecture and complex networks theory to define component network. Second, based on the notion of component network, a meaningful IPR is brought into the identifying of important components. In addition, the IPR component importance measures, and an algorithm to perform stochastic ordering of components due to the time-varying nature of usage reliability of components and functional dependency between components, are illustrated with a component network of bogie system that consists of 27 components.

  16. Revisiting Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.

    2009-01-01

    Intrusion detection systems (IDSs) are well-known and widely-deployed security tools to detect cyber-attacks and malicious activities in computer systems and networks. A signature-based IDS works similar to anti-virus software. It employs a signature database of known attacks, and a successful match

  17. Network-based reading system for lung cancer screening CT

    Science.gov (United States)

    Fujino, Yuichi; Fujimura, Kaori; Nomura, Shin-ichiro; Kawashima, Harumi; Tsuchikawa, Megumu; Matsumoto, Toru; Nagao, Kei-ichi; Uruma, Takahiro; Yamamoto, Shinji; Takizawa, Hotaka; Kuroda, Chikazumi; Nakayama, Tomio

    2006-03-01

    This research aims to support chest computed tomography (CT) medical checkups to decrease the death rate by lung cancer. We have developed a remote cooperative reading system for lung cancer screening over the Internet, a secure transmission function, and a cooperative reading environment. It is called the Network-based Reading System. A telemedicine system involves many issues, such as network costs and data security if we use it over the Internet, which is an open network. In Japan, broadband access is widespread and its cost is the lowest in the world. We developed our system considering human machine interface and security. It consists of data entry terminals, a database server, a computer aided diagnosis (CAD) system, and some reading terminals. It uses a secure Digital Imaging and Communication in Medicine (DICOM) encrypting method and Public Key Infrastructure (PKI) based secure DICOM image data distribution. We carried out an experimental trial over the Japan Gigabit Network (JGN), which is the testbed for the Japanese next-generation network, and conducted verification experiments of secure screening image distribution, some kinds of data addition, and remote cooperative reading. We found that network bandwidth of about 1.5 Mbps enabled distribution of screening images and cooperative reading and that the encryption and image distribution methods we proposed were applicable to the encryption and distribution of general DICOM images via the Internet.

  18. Analog neural network-based helicopter gearbox health monitoring system.

    Science.gov (United States)

    Monsen, P T; Dzwonczyk, M; Manolakos, E S

    1995-12-01

    The development of a reliable helicopter gearbox health monitoring system (HMS) has been the subject of considerable research over the past 15 years. The deployment of such a system could lead to a significant saving in lives and vehicles as well as dramatically reduce the cost of helicopter maintenance. Recent research results indicate that a neural network-based system could provide a viable solution to the problem. This paper presents two neural network-based realizations of an HMS system. A hybrid (digital/analog) neural system is proposed as an extremely accurate off-line monitoring tool used to reduce helicopter gearbox maintenance costs. In addition, an all analog neural network is proposed as a real-time helicopter gearbox fault monitor that can exploit the ability of an analog neural network to directly compute the discrete Fourier transform (DFT) as a sum of weighted samples. Hardware performance results are obtained using the Integrated Neural Computing Architecture (INCA/1) analog neural network platform that was designed and developed at The Charles Stark Draper Laboratory. The results indicate that it is possible to achieve a 100% fault detection rate with 0% false alarm rate by performing a DFT directly on the first layer of INCA/1 followed by a small-size two-layer feed-forward neural network and a simple post-processing majority voting stage.

  19. Approaches in Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro

    Anomaly-based network intrusion detection systems (NIDSs) can take into consideration packet headers, the payload, or a combination of both. We argue that payload-based approaches are becoming the most effective methods to detect attacks. Nowadays, attacks aim mainly to exploit vulnerabilities at

  20. Combining Host-based and network-based intrusion detection system

    African Journals Online (AJOL)

    These attacks were simulated using hping. The proposed system is implemented in Java. The results show that the proposed system is able to detect attacks both from within (host-based) and outside sources (network-based). Key Words: Intrusion Detection System (IDS), Host-based, Network-based, Signature, Security log.

  1. Neural Network Based Intrusion Detection System for Critical Infrastructures

    Energy Technology Data Exchange (ETDEWEB)

    Todd Vollmer; Ondrej Linda; Milos Manic

    2009-07-01

    Resiliency and security in control systems such as SCADA and Nuclear plant’s in today’s world of hackers and malware are a relevant concern. Computer systems used within critical infrastructures to control physical functions are not immune to the threat of cyber attacks and may be potentially vulnerable. Tailoring an intrusion detection system to the specifics of critical infrastructures can significantly improve the security of such systems. The IDS-NNM – Intrusion Detection System using Neural Network based Modeling, is presented in this paper. The main contributions of this work are: 1) the use and analyses of real network data (data recorded from an existing critical infrastructure); 2) the development of a specific window based feature extraction technique; 3) the construction of training dataset using randomly generated intrusion vectors; 4) the use of a combination of two neural network learning algorithms – the Error-Back Propagation and Levenberg-Marquardt, for normal behavior modeling. The presented algorithm was evaluated on previously unseen network data. The IDS-NNM algorithm proved to be capable of capturing all intrusion attempts presented in the network communication while not generating any false alerts.

  2. Review of Recommender Systems Algorithms Utilized in Social Networks based e-Learning Systems & Neutrosophic System

    Directory of Open Access Journals (Sweden)

    A. A. Salama

    2015-03-01

    Full Text Available In this paper, we present a review of different recommender system algorithms that are utilized in social networks based e-Learning systems. Future research will include our proposed our e-Learning system that utilizes Recommender System and Social Network. Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache in [21, 22, 23] and Salama et al. in [24-66].The purpose of this paper is to utilize a neutrosophic set to analyze social networks data conducted through learning activities.

  3. Social network based dynamic transit service through the OMITS system.

    Science.gov (United States)

    2014-02-01

    The Open Mode Integrated Transportation System (OMITS) forms a sustainable information infrastructure for communication within and between the mobile/Internet network, the roadway : network, and the users social network. It manipulates the speed g...

  4. A graph-based system for network-vulnerability analysis

    Energy Technology Data Exchange (ETDEWEB)

    Swiler, L.P.; Phillips, C.

    1998-06-01

    This paper presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The graph-based tool can identify the set of attack paths that have a high probability of success (or a low effort cost) for the attacker. The system could be used to test the effectiveness of making configuration changes, implementing an intrusion detection system, etc. The analysis system requires as input a database of common attacks, broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.

  5. Sensor network based vehicle classification and license plate identification system

    Energy Technology Data Exchange (ETDEWEB)

    Frigo, Janette Rose [Los Alamos National Laboratory; Brennan, Sean M [Los Alamos National Laboratory; Rosten, Edward J [Los Alamos National Laboratory; Raby, Eric Y [Los Alamos National Laboratory; Kulathumani, Vinod K [WEST VIRGINIA UNIV.

    2009-01-01

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

  6. Design and Simulation Analysis for Integrated Vehicle Chassis-Network Control System Based on CAN Network

    Directory of Open Access Journals (Sweden)

    Wei Yu

    2016-01-01

    Full Text Available Due to the different functions of the system used in the vehicle chassis control, the hierarchical control strategy also leads to many kinds of the network topology structure. According to the hierarchical control principle, this research puts forward the integrated control strategy of the chassis based on supervision mechanism. The purpose is to consider how the integrated control architecture affects the control performance of the system after the intervention of CAN network. Based on the principle of hierarchical control and fuzzy control, a fuzzy controller is designed, which is used to monitor and coordinate the ESP, AFS, and ARS. And the IVC system is constructed with the upper supervisory controller and three subcontrol systems on the Simulink platform. The network topology structure of IVC is proposed, and the IVC communication matrix based on CAN network communication is designed. With the common sensors and the subcontrollers as the CAN network independent nodes, the network induced delay and packet loss rate on the system control performance are studied by simulation. The results show that the simulation method can be used for designing the communication network of the vehicle.

  7. A NEURAL NETWORK BASED IRIS RECOGNITION SYSTEM FOR PERSONAL IDENTIFICATION

    Directory of Open Access Journals (Sweden)

    Usham Dias

    2010-10-01

    Full Text Available This paper presents biometric personal identification based on iris recognition using artificial neural networks. Personal identification system consists of localization of the iris region, normalization, enhancement and then iris pattern recognition using neural network. In this paper, through results obtained, we have shown that a person’s left and right eye are unique. In this paper, we also show that the network is sensitive to the initial weights and that over-training gives bad results. We also propose a fast algorithm for the localization of the inner and outer boundaries of the iris region. Results of simulations illustrate the effectiveness of the neural system in personal identification. Finally a hardware iris recognition model is proposed and implementation aspects are discussed.

  8. CLIPS based decision support system for water distribution networks

    Directory of Open Access Journals (Sweden)

    K. Sandeep

    2011-10-01

    Full Text Available The difficulty in knowledge representation of a water distribution network (WDN problem has contributed to the limited use of artificial intelligence (AI based expert systems (ES in the management of these networks. This paper presents a design of a Decision Support System (DSS that facilitates "on-demand'' knowledge generation by utilizing results of simulation runs of a suitably calibrated and validated hydraulic model of an existing aged WDN corresponding to emergent or even hypothetical but likely scenarios. The DSS augments the capability of a conventional expert system by integrating together the hydraulic modelling features with heuristics based knowledge of experts under a common, rules based, expert shell named CLIPS (C Language Integrated Production System. In contrast to previous ES, the knowledge base of the DSS has been designed to be dynamic by superimposing CLIPS on Structured Query Language (SQL. The proposed ES has an inbuilt calibration module that enables calibration of an existing (aged WDN for the unknown, and unobservable, Hazen-Williams C-values. In addition, the daily run and simulation modules of the proposed ES further enable the CLIPS inference engine to evaluate the network performance for any emergent or suggested test scenarios. An additional feature of the proposed design is that the DSS integrates computational platforms such as MATLAB, open source Geographical Information System (GIS, and a relational database management system (RDBMS working under the umbrella of the Microsoft Visual Studio based common user interface. The paper also discusses implementation of the proposed framework on a case study and clearly demonstrates the utility of the application as an able aide for effective management of the study network.

  9. ANOMALY NETWORK INTRUSION DETECTION SYSTEM BASED ON DISTRIBUTED TIME-DELAY NEURAL NETWORK (DTDNN

    Directory of Open Access Journals (Sweden)

    LAHEEB MOHAMMAD IBRAHIM

    2010-12-01

    Full Text Available In this research, a hierarchical off-line anomaly network intrusion detection system based on Distributed Time-Delay Artificial Neural Network is introduced. This research aims to solve a hierarchical multi class problem in which the type of attack (DoS, U2R, R2L and Probe attack detected by dynamic neural network. The results indicate that dynamic neural nets (Distributed Time-Delay Artificial Neural Network can achieve a high detection rate, where the overall accuracy classification rate average is equal to 97.24%.

  10. COLLABORATIVE NETWORK SECURITY MANAGEMENT SYSTEM BASED ON ASSOCIATION MINING RULE

    Directory of Open Access Journals (Sweden)

    Nisha Mariam Varughese

    2014-07-01

    Full Text Available Security is one of the major challenges in open network. There are so many types of attacks which follow fixed patterns or frequently change their patterns. It is difficult to find the malicious attack which does not have any fixed patterns. The Distributed Denial of Service (DDoS attacks like Botnets are used to slow down the system performance. To address such problems Collaborative Network Security Management System (CNSMS is proposed along with the association mining rule. CNSMS system is consists of collaborative Unified Threat Management (UTM, cloud based security centre and traffic prober. The traffic prober captures the internet traffic and given to the collaborative UTM. Traffic is analysed by the Collaborative UTM, to determine whether it contains any malicious attack or not. If any security event occurs, it will reports to the cloud based security centre. The security centre generates security rules based on association mining rule and distributes to the network. The cloud based security centre is used to store the huge amount of tragic, their logs and the security rule generated. The feedback is evaluated and the invalid rules are eliminated to improve the system efficiency.

  11. Recommender systems for location-based social networks

    CERN Document Server

    Symeonidis, Panagiotis; Manolopoulos, Yannis

    2014-01-01

    Online social networks collect information from users' social contacts and their daily interactions (co-tagging of photos, co-rating of products etc.) to provide them with recommendations of new products or friends. Lately, technological progressions in mobile devices (i.e. smart phones) enabled the incorporation of geo-location data in the traditional web-based online social networks, bringing the new era of Social and Mobile Web. The goal of this book is to bring together important research in a new family of recommender systems aimed at serving Location-based Social Networks (LBSNs). The chapters introduce a wide variety of recent approaches, from the most basic to the state-of-the-art, for providing recommendations in LBSNs. The book is organized into three parts. Part 1 provides introductory material on recommender systems, online social networks and LBSNs. Part 2 presents a wide variety of recommendation algorithms, ranging from basic to cutting edge, as well as a comparison of the characteristics of t...

  12. A network-based dynamical ranking system for competitive sports

    National Research Council Canada - National Science Library

    Motegi, Shun; Masuda, Naoki

    2012-01-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game...

  13. A graph-based network-vulnerability analysis system

    Energy Technology Data Exchange (ETDEWEB)

    Swiler, L.P.; Phillips, C. [Sandia National Labs., Albuquerque, NM (United States); Gaylor, T. [3M, Austin, TX (United States). Visual Systems Div.

    1998-01-01

    This report presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The analysis system requires as input a database of common attacks, broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.

  14. A graph-based network-vulnerability analysis system

    Energy Technology Data Exchange (ETDEWEB)

    Swiler, L.P.; Phillips, C.; Gaylor, T.

    1998-05-03

    This paper presents a graph based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The analysis system requires as input a database of common attacks, broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level of effort for the attacker, various graph algorithms such as shortest path algorithms can identify the attack paths with the highest probability of success.

  15. The middleware architecture supports heterogeneous network systems for module-based personal robot system

    Science.gov (United States)

    Choo, Seongho; Li, Vitaly; Choi, Dong Hee; Jung, Gi Deck; Park, Hong Seong; Ryuh, Youngsun

    2005-12-01

    On developing the personal robot system presently, the internal architecture is every module those occupy separated functions are connected through heterogeneous network system. This module-based architecture supports specialization and division of labor at not only designing but also implementation, as an effect of this architecture, it can reduce developing times and costs for modules. Furthermore, because every module is connected among other modules through network systems, we can get easy integrations and synergy effect to apply advanced mutual functions by co-working some modules. In this architecture, one of the most important technologies is the network middleware that takes charge communications among each modules connected through heterogeneous networks systems. The network middleware acts as the human nerve system inside of personal robot system; it relays, transmits, and translates information appropriately between modules that are similar to human organizations. The network middleware supports various hardware platform, heterogeneous network systems (Ethernet, Wireless LAN, USB, IEEE 1394, CAN, CDMA-SMS, RS-232C). This paper discussed some mechanisms about our network middleware to intercommunication and routing among modules, methods for real-time data communication and fault-tolerant network service. There have designed and implemented a layered network middleware scheme, distributed routing management, network monitoring/notification technology on heterogeneous networks for these goals. The main theme is how to make routing information in our network middleware. Additionally, with this routing information table, we appended some features. Now we are designing, making a new version network middleware (we call 'OO M/W') that can support object-oriented operation, also are updating program sources itself for object-oriented architecture. It is lighter, faster, and can support more operation systems and heterogeneous network systems, but other general

  16. A distributed data base management system. [for Deep Space Network

    Science.gov (United States)

    Bryan, A. I.

    1975-01-01

    Major system design features of a distributed data management system for the NASA Deep Space Network (DSN) designed for continuous two-way deep space communications are described. The reasons for which the distributed data base utilizing third-generation minicomputers is selected as the optimum approach for the DSN are threefold: (1) with a distributed master data base, valid data is available in real-time to support DSN management activities at each location; (2) data base integrity is the responsibility of local management; and (3) the data acquisition/distribution and processing power of a third-generation computer enables the computer to function successfully as a data handler or as an on-line process controller. The concept of the distributed data base is discussed along with the software, data base integrity, and hardware used. The data analysis/update constraint is examined.

  17. 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.

  18. Distributed Ship Navigation Control System Based on Dual Network

    Science.gov (United States)

    Yao, Ying; Lv, Wu

    2017-10-01

    Navigation system is very important for ship’s normal running. There are a lot of devices and sensors in the navigation system to guarantee ship’s regular work. In the past, these devices and sensors were usually connected via CAN bus for high performance and reliability. However, as the development of related devices and sensors, the navigation system also needs the ability of high information throughput and remote data sharing. To meet these new requirements, we propose the communication method based on dual network which contains CAN bus and industrial Ethernet. Also, we import multiple distributed control terminals with cooperative strategy based on the idea of synchronizing the status by multicasting UDP message contained operation timestamp to make the system more efficient and reliable.

  19. PZT Network and Phased Array Lamb Wave Based SHM Systems

    Energy Technology Data Exchange (ETDEWEB)

    Silva, C [Academia da Forca Aerea, Granja do Marques, 2715-021 Pero Pinheiro (Portugal); Rocha, B; Suleman, A, E-mail: cbsilva@emfa.pt [University of Victoria, Department of Mechanical Engineering, PO Box 3055, Stn.CSC, Victoria, BC, V8W 3P6 (Canada)

    2011-07-19

    With the application of newer materials, such as composite materials, and growing complexity and capacity of current aircraft structures, reliably and completely assess the condition of the total structures in real time is then of growing and utmost importance. PZT Network and Phased Array, Lamb wave based Structural Health Monitoring (SHM) systems were developed to be applied to thin panels. The selection of transducers, their size and selected locations for their installation are described. The development and selection of the signal generation and data acquisition systems is also presented in detail. The requirements conducing to the development and selection of these systems are laid and particularly the selection of the actuation signal applied is justified. The development of a damage detection algorithm based in the comparison of the current structural state to a reference state is described, to detect damage reflected Lamb waves. Such method was implemented in software and integrated in the SHM system developed. Subsequently the detection algorithm, based in discrete signals correlation, was further improved by incorporating statistical methods. For phased arrays, a novel damage location algorithm is presented based on the individual sensors response. A visualization method based concurrently in the statistical methods developed and superposition of the different results obtained from a test set was implemented. These tests conducted to the successful and repeatable detection of 1mm damages in a multiple damaged plate with great confidence. Finally, a brief comparison and a hybrid system implementation is presented.

  20. Investigation of network-based information system model

    Energy Technology Data Exchange (ETDEWEB)

    Konrad, A.M.; Perez, M.; Rivera, J.; Rodriguez, Y.; Durst, M.J.; Merrill, D.W.; Holmes, H.H.

    1996-09-01

    The objective of the DOE-LBNL summer student research program in computer and information sciences focused on investigating database- based http-based information architectures, and implementation of a prototype using DOE`s Comprehensive Epidemiologic Data Resource (CEDR) metadata or Epidemiology Guide content. We were successful in identifying the components of such an information system, and appropriate configuration given the requirements, and in implementing a prototype. This work comprised investigation of various information systems architectures or variants, evaluation and selection of various tools, products, and packages, preparation of databases, database content, output formats, and graphical (World Wide Web- compatible) interfaces. We successfully prepared and demonstrated network access to content from both the CEDR structured documentation and from the DOD Epidemiology Guides (site archive records).

  1. Intrusions Detection System Based on Ubiquitous Network Nodes

    OpenAIRE

    Sellami, Lynda; IDOUGHI, Djilali; Baadache, Abderahmane

    2014-01-01

    Ubiquitous computing allows to make data and services within the reach of users anytime and anywhere. This makes ubiquitous networks vulnerable to attacks coming from either inside or outside the network. To ensure and enhance networks security, several solutions have been implemented. These solutions are inefficient and or incomplete. Solving these challenges in security with new requirement of Ubicomp, could provide a potential future for such systems towards better mobility and higher conf...

  2. Model-based Compositional Design of Networked Control Systems

    Science.gov (United States)

    2013-12-01

    systems such as tele- robots for surgery , implanted heart monitors, nanoscale di- agnostic instruments, digital protheses and other medical devices, as...exploration, surgery , search and rescue missions, hazardous environment and other various military applications. An n-degrees of freedom robotic manipulator...lives. Examples of these systems include process control, automotive systems, networked robotics , medical systems, electrical power grids and

  3. An Evaluation and Demonstration of a Network Based Aircraft Telemetry System

    Science.gov (United States)

    Waldersen, Matt; Schnarr, Otto, III

    2017-01-01

    The primary topics of this presentation describe the testing of network based telemetry and RF modulation techniques. The overall intend is to aid the aerospace industry in transitioning to a network based telemetry system.

  4. Neural network based optimal control of HVAC&R systems

    Science.gov (United States)

    Ning, Min

    Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the

  5. A super base station based centralized network architecture for 5G mobile communication systems

    Directory of Open Access Journals (Sweden)

    Manli Qian

    2015-04-01

    Full Text Available To meet the ever increasing mobile data traffic demand, the mobile operators are deploying a heterogeneous network with multiple access technologies and more and more base stations to increase the network coverage and capacity. However, the base stations are isolated from each other, so different types of radio resources and hardware resources cannot be shared and allocated within the overall network in a cooperative way. The mobile operators are thus facing increasing network operational expenses and a high system power consumption. In this paper, a centralized radio access network architecture, referred to as the super base station (super BS, is proposed, as a possible solution for an energy-efficient fifth-generation (5G mobile system. The super base station decouples the logical functions and physical entities of traditional base stations, so different types of system resources can be horizontally shared and statistically multiplexed among all the virtual base stations throughout the entire system. The system framework and main functionalities of the super BS are described. Some key technologies for system implementation, i.e., the resource pooling, real-time virtualization, adaptive hardware resource allocation are also highlighted.

  6. A breathing circuit alarm system based on neural networks.

    Science.gov (United States)

    Orr, J A; Westenskow, D R

    1994-03-01

    The objectives of our study were (1) to implement intelligent respiratory alarms with a neural network; and (2) to increase alarm specificity and decrease false-alarm rates compared with current alarms. We trained a neural network to recognize 13 faults in an anesthesia breathing circuit. The system extracted 30 breath-to-breath features from the airway CO2, flow, and pressure signals. We created training data for the network by introducing 13 faults repeatedly in 5 dogs (616 total faults). We used the data to train the neural network using the backward error propagation algorithm. In animals, the trained network reported the alarms correctly for 95.0% of the faults when tested during controlled ventilation, and for 86.9% of the faults during spontaneous breathing. When tested in the operating room, the system found and correctly reported 54 of 57 faults that occurred during 43.6 hr of use. The alarm system produced a total of 74 false alarms during 43.6 hr of monitoring. Neural networks may be useful in creating intelligent anesthesia alarm systems.

  7. Neural-network-based fuzzy logic decision systems

    Science.gov (United States)

    Kulkarni, Arun D.; Giridhar, G. B.; Coca, Praveen

    1994-10-01

    During the last few years there has been a large and energetic upswing in research efforts aimed at synthesizing fuzzy logic with neural networks. This combination of neural networks and fuzzy logic seems natural because the two approaches generally attack the design of `intelligent' system from quite different angles. Neural networks provide algorithms for learning, classification, and optimization whereas fuzzy logic often deals with issues such as reasoning in a high (semantic or linguistic) level. Consequently the two technologies complement each other. In this paper, we combine neural networks with fuzzy logic techniques. We propose an artificial neural network (ANN) model for a fuzzy logic decision system. The model consists of six layers. The first three layers map the input variables to fuzzy set membership functions. The last three layers implement the decision rules. The model learns the decision rules using a supervised gradient descent procedure. As an illustration we considered two examples. The first example deals with pixel classification in multispectral satellite images. In our second example we used the fuzzy decision system to analyze data from magnetic resonance imaging (MRI) scans for tissue classification.

  8. CFD Optimization on Network-Based Parallel Computer System

    Science.gov (United States)

    Cheung, Samson H.; VanDalsem, William (Technical Monitor)

    1994-01-01

    Combining multiple engineering workstations into a network-based heterogeneous parallel computer allows application of aerodynamic optimization with advance computational fluid dynamics codes, which is computationally expensive in mainframe supercomputer. This paper introduces a nonlinear quasi-Newton optimizer designed for this network-based heterogeneous parallel computer on a software called Parallel Virtual Machine. This paper will introduce the methodology behind coupling a Parabolized Navier-Stokes flow solver to the nonlinear optimizer. This parallel optimization package has been applied to reduce the wave drag of a body of revolution and a wing/body configuration with results of 5% to 6% drag reduction.

  9. Lattice Based Mix Network for Location Privacy in Mobile System

    Directory of Open Access Journals (Sweden)

    Kunwar Singh

    2015-01-01

    Full Text Available In 1981, David Chaum proposed a cryptographic primitive for privacy called mix network (Mixnet. A mixnet is cryptographic construction that establishes anonymous communication channel through a set of servers. In 2004, Golle et al. proposed a new cryptographic primitive called universal reencryption which takes the input as encrypted messages under the public key of the recipients not the public key of the universal mixnet. In Eurocrypt 2010, Gentry, Halevi, and Vaikunthanathan presented a cryptosystem which is an additive homomorphic and a multiplicative homomorphic for only one multiplication. In MIST 2013, Singh et al. presented a lattice based universal reencryption scheme under learning with error (LWE assumption. In this paper, we have improved Singh et al.’s scheme using Fairbrother’s idea. LWE is a lattice hard problem for which till now there is no polynomial time quantum algorithm. Wiangsripanawan et al. proposed a protocol for location privacy in mobile system using universal reencryption whose security is reducible to Decision Diffie-Hellman assumption. Once quantum computer becomes a reality, universal reencryption can be broken in polynomial time by Shor’s algorithm. In postquantum cryptography, our scheme can replace universal reencryption scheme used in Wiangsripanawan et al. scheme for location privacy in mobile system.

  10. Neural network based system for script identification in Indian ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    environments. The system developed includes a feature extractor and a modular neural network. The feature extractor consists of two stages. In the first stage ... environments is script/language identification (Muthusamy et al 1994; Hochberg et al 1997). ... In order to take advantage of the learning and generalization abilities ...

  11. Design of IP-based element management system for SDH optical network

    Science.gov (United States)

    Chen, Junqiang; Zhang, Feng

    2004-04-01

    As large amount of SDH optical systems are deployed in metropolitan area network (MAN) and access network, the scale and complexity of SDH management network is increasing dramatically. It is a very challenging task to design a robust and effective element management system (EMS) for large-scale SDH network. As well known, OSI's network architecture has been adopted in traditional SDH network management system for a long time. But it has been proved that OSI stack has many limits, such as complexity of implementation, high resource consumption and low efficiency. This paper presents a method different from that of OSI to build SDH management network. The presented method is based on lightweight IP stack and layered routing scheme of OSPF. By this method, the number of network elements of the managed SDH network can be increased remarkably without loss of management performance. Analysis of other merits of this method is also given. The implementation of EMS based on this method is introduced.

  12. Security Concerns and Countermeasures in Network Coding Based Communications Systems

    DEFF Research Database (Denmark)

    Talooki, Vahid; Bassoli, Riccardo; Roetter, Daniel Enrique Lucani

    2015-01-01

    This survey paper shows the state of the art in security mechanisms, where a deep review of the current research and the status of this topic is carried out. We start by introducing network coding and its variety applications in enhancing current traditional networks. In particular, we analyze two...... key protocol types, namely, state-aware and stateless protocols, specifying the benefits and disadvantages of each one of them. We also present the key security assumptions of network coding (NC) systems as well as a detailed analysis of the security goals and threats, both passive and active....... This paper also presents a detailed taxonomy and a timeline of the different NC security mechanisms and schemes reported in the literature. Current proposed security mechanisms and schemes for NC in the literature are classified later. Finally a timeline of these mechanism and schemes is presented....

  13. Artificial Neural Network-Based System for PET Volume Segmentation

    Directory of Open Access Journals (Sweden)

    Mhd Saeed Sharif

    2010-01-01

    Full Text Available Tumour detection, classification, and quantification in positron emission tomography (PET imaging at early stage of disease are important issues for clinical diagnosis, assessment of response to treatment, and radiotherapy planning. Many techniques have been proposed for segmenting medical imaging data; however, some of the approaches have poor performance, large inaccuracy, and require substantial computation time for analysing large medical volumes. Artificial intelligence (AI approaches can provide improved accuracy and save decent amount of time. Artificial neural networks (ANNs, as one of the best AI techniques, have the capability to classify and quantify precisely lesions and model the clinical evaluation for a specific problem. This paper presents a novel application of ANNs in the wavelet domain for PET volume segmentation. ANN performance evaluation using different training algorithms in both spatial and wavelet domains with a different number of neurons in the hidden layer is also presented. The best number of neurons in the hidden layer is determined according to the experimental results, which is also stated Levenberg-Marquardt backpropagation training algorithm as the best training approach for the proposed application. The proposed intelligent system results are compared with those obtained using conventional techniques including thresholding and clustering based approaches. Experimental and Monte Carlo simulated PET phantom data sets and clinical PET volumes of nonsmall cell lung cancer patients were utilised to validate the proposed algorithm which has demonstrated promising results.

  14. Development of a Software Based Firewall System for Computer Network Traffic Control

    Directory of Open Access Journals (Sweden)

    Ikhajamgbe OYAKHILOME

    2009-12-01

    Full Text Available The connection of an internal network to an external network such as Internet has made it vulnerable to attacks. One class of network attack is unauthorized penetration into network due to the openness of networks. It is possible for hackers to sum access to an internal network, this pose great danger to the network and network resources. Our objective and major concern of network design was to build a secured network, based on software firewall that ensured the integrity and confidentiality of information on the network. We studied several mechanisms to achieve this; one of such mechanism is the implementation of firewall system as a network defence. Our developed firewall has the ability to determine which network traffic should be allowed in or out of the network. Part of our studied work was also channelled towards a comprehensive study of hardware firewall security system with the aim of developing this software based firewall system. Our software firewall goes a long way in protecting an internal network from external unauthorized traffic penetration. We included an anti virus software which is lacking in most firewalls.

  15. Power system cascading risk assessment based on complex network theory

    Science.gov (United States)

    Wang, Zhuoyang; Hill, David J.; Chen, Guo; Dong, Zhao Yang

    2017-09-01

    When a single failure occurs in a vulnerable part of a power system, this may cause a large area cascading event. Therefore, an advanced method that can assess the risks during cascading events is needed. In this paper, an improved complex network model for power system risk assessment is proposed. Risk is defined by consequence and probability of the failures in this model, which are affected by both power factors and network structure. Compared with existing risk assessment models, the proposed one can evaluate the risk of the system comprehensively during a cascading event by combining the topological and electrical information. A new cascading event simulation module is adopted to identify the power grid cascading chain from a system-level view. In addition, simulations are investigated on the IEEE 14 bus system and IEEE 39 bus system respectively to illustrate the performance of the proposed module. The simulation results demonstrate that the proposed method is effective in a power grid risk assessment during cascading event.

  16. E-commerce System Security Assessment based on Bayesian Network Algorithm Research

    OpenAIRE

    Ting Li; Xin Li

    2013-01-01

    Evaluation of e-commerce network security is based on assessment method Bayesian networks, and it first defines the vulnerability status of e-commerce system evaluation index and the vulnerability of the state model of e-commerce systems, and after the principle of the Bayesian network reliability of e-commerce system and the criticality of the vulnerabilities were analyzed, experiments show that the change method is a good evaluation of the security of e-commerce systems.

  17. Study on the complex network characteristics of urban road system based on GIS

    Science.gov (United States)

    Gao, Zhonghua; Chen, Zhenjie; Liu, Yongxue; Huang, Kang

    2007-06-01

    Urban road system is the basic bone of urban transportation and one of the most important factors that influent and controls the urban configuration. In this paper, an approach of modeling, analyzing and optimizing urban road system is described based on complex network theory and GIS technology. The urban road system is studied on three focuses: building the urban road network, modeling the computational procedures based on urban road networks and analyzing the urban road system of Changzhou City as the study case. The conclusion is that the urban road network is a scale-free network with small-world characteristic, and there is still space for development of the whole network as a small-world network, also the key road crosses should be kept expedite.

  18. Modelling intracellular signalling networks using behaviour-based systems and the blackboard architecture

    OpenAIRE

    Perez, Pedro Pablo Gonzalez; Gershenson, Carlos; Garcia, Maura Cardenas; Otero, Jaime Lagunez

    2002-01-01

    This paper proposes to model the intracellular signalling networks using a fusion of behaviour-based systems and the blackboard architecture. In virtue of this fusion, the model developed by us, which has been named Cellulat, allows to take account two essential aspects of the intracellular signalling networks: (1) the cognitive capabilities of certain types of networks' components and (2) the high level of spatial organization of these networks. A simple example of modelling of Ca2+ signalli...

  19. Stability Analysis of Neural Networks-Based System Identification

    Directory of Open Access Journals (Sweden)

    Talel Korkobi

    2008-01-01

    Full Text Available This paper treats some problems related to nonlinear systems identification. A stability analysis neural network model for identifying nonlinear dynamic systems is presented. A constrained adaptive stable backpropagation updating law is presented and used in the proposed identification approach. The proposed backpropagation training algorithm is modified to obtain an adaptive learning rate guarantying convergence stability. The proposed learning rule is the backpropagation algorithm under the condition that the learning rate belongs to a specified range defining the stability domain. Satisfying such condition, unstable phenomena during the learning process are avoided. A Lyapunov analysis leads to the computation of the expression of a convenient adaptive learning rate verifying the convergence stability criteria. Finally, the elaborated training algorithm is applied in several simulations. The results confirm the effectiveness of the CSBP algorithm.

  20. Proposal of Network-Based Multilingual Space Dictionary Database System

    Science.gov (United States)

    Yoshimitsu, T.; Hashimoto, T.; Ninomiya, K.

    2002-01-01

    The International Academy of Astronautics (IAA) is now constructing a multilingual dictionary database system of space-friendly terms. The database consists of a lexicon and dictionaries of multiple languages. The lexicon is a table which relates corresponding terminology in different languages. Each language has a dictionary which contains terms and their definitions. The database assumes the use on the internet. Updating and searching the terms and definitions are conducted via the network. Maintaining the database is conducted by the international cooperation. A new word arises day by day, thus to easily input new words and their definitions to the database is required for the longstanding success of the system. The main key of the database is an English term which is approved at the table held once or twice with the working group members. Each language has at lease one working group member who is responsible of assigning the corresponding term and the definition of the term of his/her native language. Inputting and updating terms and their definitions can be conducted via the internet from the office of each member which may be located at his/her native country. The system is constructed by freely distributed database server program working on the Linux operating system, which will be installed at the head office of IAA. Once it is installed, it will be open to all IAA members who can search the terms via the internet. Currently the authors are constructing the prototype system which is described in this paper.

  1. Multiagent Intrusion Detection Based on Neural Network Detectors and Artificial Immune System

    OpenAIRE

    Vaitsekhovich, L.; Golovko, V; Rubanau, V.

    2009-01-01

    In this article the artificial immune system and neural network techniques for intrusion detection have been addressed. The AIS allows detecting unknown samples of computer attacks. The integration of AIS and neural networks as detectors permits to increase performance of the system security. The detector structure is based on the integration of the different neural networks namely RNN and MLP. The KDD-99 dataset was used for experiments performing. The experimental results show that such int...

  2. Anomaly detection in SCADA systems: a network based approach

    NARCIS (Netherlands)

    Barbosa, R.R.R.

    2014-01-01

    Supervisory Control and Data Acquisition (SCADA) networks are commonly deployed to aid the operation of large industrial facilities, such as water treatment facilities. Historically, these networks were composed by special-purpose embedded devices communicating through proprietary protocols.

  3. Anomaly Detection in SCADA Systems - A Network Based Approach

    NARCIS (Netherlands)

    Barbosa, R.R.R.

    2014-01-01

    Supervisory Control and Data Acquisition (SCADA) networks are commonly deployed to aid the operation of large industrial facilities, such as water treatment facilities. Historically, these networks were composed by special-purpose embedded devices communicating through proprietary protocols.

  4. Using fuzzy logic to integrate neural networks and knowledge-based systems

    Science.gov (United States)

    Yen, John

    1991-01-01

    Outlined here is a novel hybrid architecture that uses fuzzy logic to integrate neural networks and knowledge-based systems. The author's approach offers important synergistic benefits to neural nets, approximate reasoning, and symbolic processing. Fuzzy inference rules extend symbolic systems with approximate reasoning capabilities, which are used for integrating and interpreting the outputs of neural networks. The symbolic system captures meta-level information about neural networks and defines its interaction with neural networks through a set of control tasks. Fuzzy action rules provide a robust mechanism for recognizing the situations in which neural networks require certain control actions. The neural nets, on the other hand, offer flexible classification and adaptive learning capabilities, which are crucial for dynamic and noisy environments. By combining neural nets and symbolic systems at their system levels through the use of fuzzy logic, the author's approach alleviates current difficulties in reconciling differences between low-level data processing mechanisms of neural nets and artificial intelligence systems.

  5. Overview of DFIG-based Wind Power System Resonances under Weak Networks

    DEFF Research Database (Denmark)

    Song, Yipeng; Blaabjerg, Frede

    2017-01-01

    The wind power generation techniques are continuing to develop and increasing numbers of Doubly Fed Induction Generator (DFIG)-based wind power systems are connecting to the on-shore and off-shore grids, local standalone weak networks, and also micro grid applications. The impedances of the weak...... weak network respectively. This paper will discuss the SSR and the HFR phenomena based on the impedance modeling of the DFIG system and the weak networks, and the cause of these two resonances will be explained in details. The following factors including 1) transformer configuration; 2) different power...... networks are too large to be neglected and require careful attention. Due to the impedance interaction between the weak network and the DFIG system, both Sub- Synchronous Resonance (SSR) and High Frequency Resonance (HFR) may occur when the DFIG system is connected to the series or parallel compensated...

  6. Active Power Distribution Network Security Monitoring System Based on PDMiner Platform

    National Research Council Canada - National Science Library

    CHANG Cheng

    2017-01-01

    ...,using the data mining technology and distributed parallel computing method,establishing an active distribution network security monitoring system model based on PDMiner large data mining platform...

  7. Animal Recognition System Based on Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Tibor Trnovszky

    2017-01-01

    Full Text Available In this paper, the performances of well-known image recognition methods such as Principal Component Analysis (PCA, Linear Discriminant Analysis (LDA, Local Binary Patterns Histograms (LBPH and Support Vector Machine (SVM are tested and compared with proposed convolutional neural network (CNN for the recognition rate of the input animal images. In our experiments, the overall recognition accuracy of PCA, LDA, LBPH and SVM is demonstrated. Next, the time execution for animal recognition process is evaluated. The all experimental results on created animal database were conducted. This created animal database consist of 500 different subjects (5 classes/ 100 images for each class. The experimental result shows that the PCA features provide better results as LDA and LBPH for large training set. On the other hand, LBPH is better than PCA and LDA for small training data set. For proposed CNN we have obtained a recognition accuracy of 98%. The proposed method based on CNN outperforms the state of the art methods.

  8. VISUAL UAV TRAJECTORY PLAN SYSTEM BASED ON NETWORK MAP

    Directory of Open Access Journals (Sweden)

    X. L. Li

    2012-07-01

    Full Text Available The base map of the current software UP-30 using in trajectory plan for Unmanned Aircraft Vehicle is vector diagram. UP-30 draws navigation points manually. But in the field of operation process, the efficiency and the quality of work is influenced because of insufficient information, screen reflection, calculate inconveniently and other factors. If we do this work in indoor, the effect of external factors on the results would be eliminated, the network earth users can browse the free world high definition satellite images through downloading a client software, and can export the high resolution image by standard file format. This brings unprecedented convenient of trajectory plan. But the images must be disposed by coordinate transformation, geometric correction. In addition, according to the requirement of mapping scale ,camera parameters and overlap degree we can calculate exposure hole interval and trajectory distance between the adjacent trajectory automatically . This will improve the degree of automation of data collection. Software will judge the position of next point according to the intersection of the trajectory and the survey area and ensure the position of point according to trajectory distance. We can undertake the points artificially. So the trajectory plan is automatic and flexible. Considering safety, the date can be used in flying after simulating flight. Finally we can export all of the date using a key

  9. 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...

  10. Enhancing Lifelong Competence Development and Management Systems with Social Network-based Concepts and Tools

    NARCIS (Netherlands)

    Cheak, Alicia; Angehrn, Albert; Sloep, Peter

    2006-01-01

    This paper addresses the challenge of enhancing the social dimension of lifelong Competence Development and Management Systems with social network-based concepts and tools. Our premise is that through a combination of social network visualization tools, simulations, stimulus agents and management

  11. A speech recognition system based on hybrid wavelet network including a fuzzy decision support system

    Science.gov (United States)

    Jemai, Olfa; Ejbali, Ridha; Zaied, Mourad; Ben Amar, Chokri

    2015-02-01

    This paper aims at developing a novel approach for speech recognition based on wavelet network learnt by fast wavelet transform (FWN) including a fuzzy decision support system (FDSS). Our contributions reside in, first, proposing a novel learning algorithm for speech recognition based on the fast wavelet transform (FWT) which has many advantages compared to other algorithms and in which major problems of the previous works to compute connection weights were solved. They were determined by a direct solution which requires computing matrix inversion, which may be intensive. However, the new algorithm was realized by the iterative application of FWT to compute connection weights. Second, proposing a new classification way for this speech recognition system. It operated a human reasoning mode employing a FDSS to compute similarity degrees between test and training signals. Extensive empirical experiments were conducted to compare the proposed approach with other approaches. Obtained results show that the new speech recognition system has a better performance than previously established ones.

  12. Service for fault tolerance in the Ad Hoc Networks based on Multi Agent Systems

    Directory of Open Access Journals (Sweden)

    Ghalem Belalem

    2011-02-01

    Full Text Available The Ad hoc networks are distributed networks, self-organized and does not require infrastructure. In such network, mobile infrastructures are subject of disconnections. This situation may concern a voluntary or involuntary disconnection of nodes caused by the high mobility in the Ad hoc network. In these problems we are trying through this work to contribute to solving these problems in order to ensure continuous service by proposing our service for faults tolerance based on Multi Agent Systems (MAS, which predict a problem and decision making in relation to critical nodes. Our work contributes to study the prediction of voluntary and involuntary disconnections in the Ad hoc network; therefore we propose our service for faults tolerance that allows for effective distribution of information in the Network by selecting some objects of the network to be duplicates of information.

  13. Design and evaluation of a wireless sensor network based aircraft strength testing system.

    Science.gov (United States)

    Wu, Jian; Yuan, Shenfang; Zhou, Genyuan; Ji, Sai; Wang, Zilong; Wang, Yang

    2009-01-01

    The verification of aerospace structures, including full-scale fatigue and static test programs, is essential for structure strength design and evaluation. However, the current overall ground strength testing systems employ a large number of wires for communication among sensors and data acquisition facilities. The centralized data processing makes test programs lack efficiency and intelligence. Wireless sensor network (WSN) technology might be expected to address the limitations of cable-based aeronautical ground testing systems. This paper presents a wireless sensor network based aircraft strength testing (AST) system design and its evaluation on a real aircraft specimen. In this paper, a miniature, high-precision, and shock-proof wireless sensor node is designed for multi-channel strain gauge signal conditioning and monitoring. A cluster-star network topology protocol and application layer interface are designed in detail. To verify the functionality of the designed wireless sensor network for strength testing capability, a multi-point WSN based AST system is developed for static testing of a real aircraft undercarriage. Based on the designed wireless sensor nodes, the wireless sensor network is deployed to gather, process, and transmit strain gauge signals and monitor results under different static test loads. This paper shows the efficiency of the wireless sensor network based AST system, compared to a conventional AST system.

  14. Design and Evaluation of a Wireless Sensor Network Based Aircraft Strength Testing System

    Directory of Open Access Journals (Sweden)

    Yang Wang

    2009-06-01

    Full Text Available The verification of aerospace structures, including full-scale fatigue and static test programs, is essential for structure strength design and evaluation. However, the current overall ground strength testing systems employ a large number of wires for communication among sensors and data acquisition facilities. The centralized data processing makes test programs lack efficiency and intelligence. Wireless sensor network (WSN technology might be expected to address the limitations of cable-based aeronautical ground testing systems. This paper presents a wireless sensor network based aircraft strength testing (AST system design and its evaluation on a real aircraft specimen. In this paper, a miniature, high-precision, and shock-proof wireless sensor node is designed for multi-channel strain gauge signal conditioning and monitoring. A cluster-star network topology protocol and application layer interface are designed in detail. To verify the functionality of the designed wireless sensor network for strength testing capability, a multi-point WSN based AST system is developed for static testing of a real aircraft undercarriage. Based on the designed wireless sensor nodes, the wireless sensor network is deployed to gather, process, and transmit strain gauge signals and monitor results under different static test loads. This paper shows the efficiency of the wireless sensor network based AST system, compared to a conventional AST system.

  15. System for Malicious Node Detection in IPv6-Based Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Kresimir Grgic

    2016-01-01

    Full Text Available The trend of implementing the IPv6 into wireless sensor networks (WSNs has recently occurred as a consequence of a tendency of their integration with other types of IP-based networks. The paper deals with the security aspects of these IPv6-based WSNs. A brief analysis of security threats and attacks which are present in the IPv6-based WSN is given. The solution to an adaptive distributed system for malicious node detection in the IPv6-based WSN is proposed. The proposed intrusion detection system is based on distributed algorithms and a collective decision-making process. It introduces an innovative concept of probability estimation for malicious behaviour of sensor nodes. The proposed system is implemented and tested through several different scenarios in three different network topologies. Finally, the performed analysis showed that the proposed system is energy efficient and has a good capability to detect malicious nodes.

  16. Urban Traffic Signal System Control Structural Optimization Based on Network Analysis

    Directory of Open Access Journals (Sweden)

    Li Wang

    2013-01-01

    Full Text Available Advanced urban traffic signal control systems such as SCOOT and SCATS normally coordinate traffic network using multilevel hierarchical control mechanism. In this mechanism, several key intersections will be selected from traffic signal network and the network will be divided into different control subareas. Traditionally, key intersection selection and control subareas division are executed according to dynamic traffic counts and link length between intersections, which largely rely on traffic engineers’ experience. However, it omits important inherent characteristics of traffic network topology. In this paper, we will apply network analysis approach into these two aspects for traffic system control structure optimization. Firstly, the modified C-means clustering algorithm will be proposed to assess the importance of intersections in traffic network and furthermore determine the key intersections based on three indexes instead of merely on traffic counts in traditional methods. Secondly, the improved network community discovery method will be used to give more reasonable evidence in traffic control subarea division. Finally, to test the effectiveness of network analysis approach, a hardware-in-loop simulation environment composed of regional traffic control system, microsimulation software and signal controller hardware, will be built. Both traditional method and proposed approach will be implemented on simulation test bed to evaluate traffic operation performance indexes, for example, travel time, stop times, delay and average vehicle speed. Simulation results show that the proposed network analysis approach can improve the traffic control system operation performance effectively.

  17. Fiber-optic subscriber system based on passive optical network architecture

    Energy Technology Data Exchange (ETDEWEB)

    Kitazawa, M.; Yamazaki, M.; Himi, S. (Hitachi, Ltd., Tokyo (Japan))

    1994-04-01

    The subscriber line terminal and optical network unit were developed for the fiber-optic subscriber system based on a passive double star (PDS) optical network architecture which allows narrowband ISDN (integrated services digital network) services and video image transmission. Various LSIs were developed to implement the major system functions such as fast bit-synchronization, time division multiple access control, subscriber multiplexing/demultiplexing and 16-channel multiprocessing. For the optical interface module, the wavelength division multiplexing chip was hermetically sealed together with laser diode and photodiode chips by adopting high-silica based optical-waveguide technology to reduce a system dimension. The PDS fiber-optic subscriber system is useful for construction of economic optical subscriber networks because it allows multiple subscribers to share a single optical transmission line and a central equipment unit through a star coupler. 4 refs., 10 figs., 1 tab.

  18. Collaborative Networked Organizations as System of Systems: A Model-Based Engineering Approach

    OpenAIRE

    Bilal, Mustapha; Daclin, Nicolas; Chapurlat, Vincent

    2014-01-01

    Part 6: Engineering and Implementation of Collaborative Networks; International audience; It is admitted that there is parallel between a System of Systems (SoS) and Collaborative Networked Organizations (CNOs). SoS Engineering (SoSE) carefully focuses on choosing, assembling and interfacing existing systems to build the so-called SoS. In this context, and as demonstrated by the literature and the System Engineering domain, interoperability takes on its full meaning and has to be fully consid...

  19. NETWORK TRAFFIC FORCASTING IN INFORMATION-TELECOMMUNICATION SYSTEM OF PRYDNIPROVSK RAILWAYS BASED ON NEURO-FUZZY NETWORK

    Directory of Open Access Journals (Sweden)

    V. M. Pakhomovа

    2016-12-01

    Full Text Available Purpose. Continuous increase in network traffic in the information-telecommunication system (ITS of Prydniprovsk Railways leads to the need to determine the real-time network congestion and to control the data flows. One of the possible solutions is a method of forecasting the volume of network traffic (inbound and outbound using neural network technology that will prevent from server overload and improve the quality of services. Methodology. Analysis of current network traffic in ITS of Prydniprovsk Railways and preparation of sets: learning, test and validation ones was conducted as well as creation of neuro-fuzzy network (hybrid system in Matlab program and organization of the following phases on the appropriate sets: learning, testing, forecast adequacy analysis. Findings. For the fragment (Dnipropetrovsk – Kyiv in ITS of Prydniprovsk Railways we made a forecast (day ahead for volume of network traffic based on the hybrid system created in Matlab program; MAPE values are as follows: 6.9% for volume of inbound traffic; 7.7% for volume of outbound traffic. It was found that the average learning error of the hybrid system decreases in case of increase in: the number of inputs (from 2 to 4; the number of terms (from 2 to 5 of the input variable; learning sample power (from 20 to 100. A significant impact on the average learning error of the hybrid system is caused by the number of terms of its input variable. It was determined that the lowest value of the average learning error is provided by 4-input hybrid system, it ensures more accurate learning of the neuro-fuzzy network by the hybrid method. Originality. The work resulted in the dependences for the average hybrid system error of the network traffic volume forecasting for the fragment (Dnipropetrovsk-Kyiv in ITS Prydniprovsk Railways on: the number of its inputs, the number of input variable terms, the learning sample power for different learning methods. Practical value. Forecasting of

  20. Construction of Network Management Information System of Agricultural Products Supply Chain Based on 3PLs

    OpenAIRE

    Gao, Shujin; Yang, Qiangxian

    2010-01-01

    The necessity to construct the network management information system of 3PLs agricultural supply chain is analyzed, showing that 3PLs can improve the overall competitive advantage of agricultural supply chain. 3PLs changes the homogeneity management into specialized management of logistics service and achieves the alliance of the subjects at different nodes of agricultural products supply chain. Network management information system structure of agricultural products supply chain based on 3PL...

  1. Design of Networked Home Automation System Based on μCOS-II and AMAZON

    Directory of Open Access Journals (Sweden)

    Liu Jianfeng

    2015-01-01

    Full Text Available In recent years, with the popularity of computers and smart phones and the development of intelligent building in electronics industry, people’s requirement of living environment is gradually changing. The intelligent home furnishing building has become the new focus of people purchasing. And the networked home automation system which relies on the advanced network technology to connect with air conditioning, lighting, security, curtains, TV, water heater and other home furnishing systems into a local area network becomes a networked control system. μC /OS is a real-time operating system with the free open-source code, the compact structure and the preemptive real-time kernel. In this paper, the author focuses on the design of home furnishing total controller based on AMAZON multimedia processor and μC/OS-II real-time operating system, and achieves the remote access connection and control through the Ethernet.

  2. Network-based Parallel Retrieval Onboard Computing Environment for Sensor Systems Deployed on NASA Unmanned Aircraft Systems Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Remote Sensing Solutions proposes to develop the Network-based Parallel Retrieval Onboard Computing Environment for Sensor Systems (nPROCESS) for deployment on...

  3. H∞ Guaranteed Cost Control for Networked Control Systems under Scheduling Policy Based on Predicted Error

    Directory of Open Access Journals (Sweden)

    Qixin Zhu

    2014-01-01

    Full Text Available Scheduling policy based on model prediction error is presented to reduce energy consumption and network conflicts at the actuator node, where the characters of networked control systems are considered, such as limited network bandwidth, limited node energy, and high collision probability. The object model is introduced to predict the state of system at the sensor node. And scheduling threshold is set at the controller node. Control signal is transmitted only if the absolute value of prediction error is larger than the threshold value. Furthermore, the model of networked control systems under scheduling policy based on predicted error is established by taking uncertain parameters and long time delay into consideration. The design method of H∞ guaranteed cost controller is presented by using the theory of Lyapunov and linear matrix inequality (LMI. Finally, simulations are included to demonstrate the theoretical results.

  4. Active Power Distribution Network Security Monitoring System Based on PDMiner Platform

    Directory of Open Access Journals (Sweden)

    CHANG Cheng

    2017-04-01

    Full Text Available Active distribution network system has the characteristics of complex structure,high DG permeability,large load fluctuation,strict control requirements. The data information of operation has the characteristics of high volume,high speed,diversity and value. For active distribution network data processing, according to the theory of cloud calculation,using the data mining technology and distributed parallel computing method,establishing an active distribution network security monitoring system model based on PDMiner large data mining platform. The processing of historical data and real time fault data are studied respectively. Research results show that the system by processing of historical data for risk zoning,development planning,operation state evaluation,by processing of fault data for fault analysis and processing,providing the basis for the distribution network security. The result of the system is verified by the simulation example.

  5. A Target Tracking System Based on Imaging Sensor Network with Wi-Fi

    Directory of Open Access Journals (Sweden)

    Aiqun Chen

    2014-05-01

    Full Text Available With the rapid development of network communication technology, a variety of network technology and communication technology has been integrated into our lives and work, bringing great convenience to our work and life. Current research in wireless sensor network technology in the field of communication technology is more popular because of the use of wireless sensor network technology can achieve the communication between objects and objects, people and things, the application of this technology has greatly expanded the ability for people to obtain information, have important significance to the development of people and society. Based on the powerful function of wireless sensor and bring the influence of people, this paper focuses on the design and implementation of the target tracking system based on image sensor networks with Wi-Fi.

  6. 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.

  7. A case for spiking neural network simulation based on configurable multiple-FPGA systems.

    Science.gov (United States)

    Yang, Shufan; Wu, Qiang; Li, Renfa

    2011-09-01

    Recent neuropsychological research has begun to reveal that neurons encode information in the timing of spikes. Spiking neural network simulations are a flexible and powerful method for investigating the behaviour of neuronal systems. Simulation of the spiking neural networks in software is unable to rapidly generate output spikes in large-scale of neural network. An alternative approach, hardware implementation of such system, provides the possibility to generate independent spikes precisely and simultaneously output spike waves in real time, under the premise that spiking neural network can take full advantage of hardware inherent parallelism. We introduce a configurable FPGA-oriented hardware platform for spiking neural network simulation in this work. We aim to use this platform to combine the speed of dedicated hardware with the programmability of software so that it might allow neuroscientists to put together sophisticated computation experiments of their own model. A feed-forward hierarchy network is developed as a case study to describe the operation of biological neural systems (such as orientation selectivity of visual cortex) and computational models of such systems. This model demonstrates how a feed-forward neural network constructs the circuitry required for orientation selectivity and provides platform for reaching a deeper understanding of the primate visual system. In the future, larger scale models based on this framework can be used to replicate the actual architecture in visual cortex, leading to more detailed predictions and insights into visual perception phenomenon.

  8. A web-based information system for a regional public mental healthcare service network in Brazil.

    Science.gov (United States)

    Yoshiura, Vinicius Tohoru; de Azevedo-Marques, João Mazzoncini; Rzewuska, Magdalena; Vinci, André Luiz Teixeira; Sasso, Ariane Morassi; Miyoshi, Newton Shydeo Brandão; Furegato, Antonia Regina Ferreira; Rijo, Rui Pedro Charters Lopes; Del-Ben, Cristina Marta; Alves, Domingos

    2017-01-01

    Regional networking between services that provide mental health care in Brazil's decentralized public health system is challenging, partly due to the simultaneous existence of services managed by municipal and state authorities and a lack of efficient and transparent mechanisms for continuous and updated communication between them. Since 2011, the Ribeirao Preto Medical School and the XIII Regional Health Department of the Sao Paulo state, Brazil, have been developing and implementing a web-based information system to facilitate an integrated care throughout a public regional mental health care network. After a profound on-site analysis, the structure of the network was identified and a web-based information system for psychiatric admissions and discharges was developed and implemented using a socio-technical approach. An information technology team liaised with mental health professionals, health-service managers, municipal and state health secretariats and judicial authorities. Primary care, specialized community services, general emergency and psychiatric wards services, that comprise the regional mental healthcare network, were identified and the system flow was delineated. The web-based system overcame the fragmentation of the healthcare system and addressed service specific needs, enabling: detailed patient information sharing; active coordination of the processes of psychiatric admissions and discharges; real-time monitoring; the patients' status reports; the evaluation of the performance of each service and the whole network. During a 2-year period of operation, it registered 137 services, 480 health care professionals and 4271 patients, with a mean number of 2835 accesses per month. To date the system is successfully operating and further expanding. We have successfully developed and implemented an acceptable, useful and transparent web-based information system for a regional mental healthcare service network in a medium-income country with a decentralized

  9. 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...

  10. Glycosylation Network Analysis Toolbox: a MATLAB-based environment for systems glycobiology

    Science.gov (United States)

    Liu, Gang; Neelamegham, Sriram

    2013-01-01

    Summary: Systems glycobiology studies the interaction of various pathways that regulate glycan biosynthesis and function. Software tools for the construction and analysis of such pathways are not yet available. We present GNAT, a platform-independent, user-extensible MATLAB-based toolbox that provides an integrated computational environment to construct, manipulate and simulate glycans and their networks. It enables integration of XML-based glycan structure data into SBML (Systems Biology Markup Language) files that describe glycosylation reaction networks. Curation and manipulation of networks is facilitated using class definitions and glycomics database query tools. High quality visualization of networks and their steady-state and dynamic simulation are also supported. Availability: The software package including source code, help documentation and demonstrations are available at http://sourceforge.net/projects/gnatmatlab/files/. Contact: neel@buffalo.edu or gangliu@buffalo.edu PMID:23230149

  11. In-House Communication Support System Based on the Information Propagation Model Utilizes Social Network

    Science.gov (United States)

    Takeuchi, Susumu; Teranishi, Yuuichi; Harumoto, Kaname; Shimojo, Shinji

    Almost all companies are now utilizing computer networks to support speedier and more effective in-house information-sharing and communication. However, existing systems are designed to support communications only within the same department. Therefore, in our research, we propose an in-house communication support system which is based on the “Information Propagation Model (IPM).” The IPM is proposed to realize word-of-mouth communication in a social network, and to support information-sharing on the network. By applying the system in a real company, we found that information could be exchanged between different and unrelated departments, and such exchanges of information could help to build new relationships between the users who are apart on the social network.

  12. An alternative wearable tracking system based on a low-power wide-area network

    OpenAIRE

    Raul Fernández-Garcia; Ignacio Gil

    2017-01-01

    This work presents an alternative wearable tracking system based on a low-power wide area network. A complete GPS receiver was integrated with a textile substrate, and the latitude and longitude coordinates were sent to the cloud by means of the SIM-less SIGFOX network. To send the coordinates over SIGFOX protocol, a specific codification algorithm was used and a customized UHF antenna on jeans fabric was designed, simulated and tested. Moreover, to guarantee the compliance to international r...

  13. A Survey of Wireless Sensor Network Based Air Pollution Monitoring Systems.

    Science.gov (United States)

    Yi, Wei Ying; Lo, Kin Ming; Mak, Terrence; Leung, Kwong Sak; Leung, Yee; Meng, Mei Ling

    2015-12-12

    The air quality in urban areas is a major concern in modern cities due to significant impacts of air pollution on public health, global environment, and worldwide economy. Recent studies reveal the importance of micro-level pollution information, including human personal exposure and acute exposure to air pollutants. A real-time system with high spatio-temporal resolution is essential because of the limited data availability and non-scalability of conventional air pollution monitoring systems. Currently, researchers focus on the concept of The Next Generation Air Pollution Monitoring System (TNGAPMS) and have achieved significant breakthroughs by utilizing the advance sensing technologies, MicroElectroMechanical Systems (MEMS) and Wireless Sensor Network (WSN). However, there exist potential problems of these newly proposed systems, namely the lack of 3D data acquisition ability and the flexibility of the sensor network. In this paper, we classify the existing works into three categories as Static Sensor Network (SSN), Community Sensor Network (CSN) and Vehicle Sensor Network (VSN) based on the carriers of the sensors. Comprehensive reviews and comparisons among these three types of sensor networks were also performed. Last but not least, we discuss the limitations of the existing works and conclude the objectives that we want to achieve in future systems.

  14. Control Method of Single-phase Inverter Based Grounding System in Distribution Networks

    OpenAIRE

    Wang, Wen; Yan, L.; Zeng, X.; Zhao, Xin; Wei, Baoze; Guerrero, Josep M.

    2016-01-01

    The asymmetry of the inherent distributed capacitances causes the rise of neutral-to-ground voltage in ungrounded system or high resistance grounded system. Overvoltage may occur in resonant grounded system if Petersen coil is resonant with the distributed capacitances. Thus, the restraint of neutral-to-ground voltage is critical for the safety of distribution networks. An active grounding system based on single-phase inverter is proposed to achieve this objective. Relationship between output...

  15. Expanding delivery system research in public health settings: lessons from practice-based research networks.

    Science.gov (United States)

    Mays, Glen P; Hogg, Rachel A

    2012-11-01

    Delivery system research to identify how best to organize, finance, and implement health improvement strategies has focused heavily on clinical practice settings, with relatively little attention paid to public health settings-where research is made more difficult by wide heterogeneity in settings and limited sources of existing data and measures. This study examines the approaches used by public health practice-based research networks (PBRNs) to expand delivery system research and evidence-based practice in public health settings. Practice-based research networks employ quasi-experimental research designs, natural experiments, and mixed-method analytic techniques to evaluate how community partnerships, economic shocks, and policy changes impact delivery processes in public health settings. In addition, network analysis methods are used to assess patterns of interaction between practitioners and researchers within PBRNs to produce and apply research findings. Findings from individual PBRN studies elucidate the roles of information exchange, community resources, and leadership and decision-making structures in shaping implementation outcomes in public health delivery. Network analysis of PBRNs reveals broad engagement of both practitioners and researchers in scientific inquiry, with practitioners in the periphery of these networks reporting particularly large benefits from research participation. Public health PBRNs provide effective mechanisms for implementing delivery system research and engaging practitioners in the process. These networks also hold promise for accelerating the translation and application of research findings into public health settings.

  16. Design and Implementation of Behavior Recognition System Based on Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Yu Bo

    2017-01-01

    Full Text Available We build a set of human behavior recognition system based on the convolution neural network constructed for the specific human behavior in public places. Firstly, video of human behavior data set will be segmented into images, then we process the images by the method of background subtraction to extract moving foreground characters of body. Secondly, the training data sets are trained into the designed convolution neural network, and the depth learning network is constructed by stochastic gradient descent. Finally, the various behaviors of samples are classified and identified with the obtained network model, and the recognition results are compared with the current mainstream methods. The result show that the convolution neural network can study human behavior model automatically and identify human’s behaviors without any manually annotated trainings.

  17. Support for Programming Models in Network-on-Chip-based Many-core Systems

    DEFF Research Database (Denmark)

    Rasmussen, Morten Sleth

    This thesis addresses aspects of support for programming models in Network-on- Chip-based many-core architectures. The main focus is to consider architectural support for a plethora of programming models in a single system. The thesis has three main parts. The first part considers parallelization...... models to be supported by a single architecture. The architecture features a specialized network interface processor which allows extensive configurability of the memory system. Based on this architecture, a detailed implementation of the cache coherent shared memory programming model is presented...

  18. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Wang, L [School of Aeronautics and Astronautics, Tongji University, Shanghai (China); Zhang, Y Y [Chinese-German School of Postgraduate Studies, Tongji University (China); Ding, L [Chinese-German School of Postgraduate Studies, Tongji University (China)

    2006-10-15

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module.

  19. Development of Novel Gas Brand Anti-Piracy System based on BP Neural Networks

    Science.gov (United States)

    Wang, L.; Zhang, Y. Y.; Ding, L.

    2006-10-01

    The Wireless-net Close-loop gas brand anti-piracy system introduced in this paper is a new type of brand piracy technical product based on BP neural network. It is composed by gas brand piracy label possessing gas exhalation resource, ARM embedded gas-detector, GPRS wireless module and data base of merchandise information. First, the system obtains the information on the special label through gas sensor array ,then the attained signals are transferred into ARM Embedded board and identified by artificial neural network, and finally turns back the outcome of data collection and identification to the manufactures with the help of GPRS module.

  20. Delay Analysis of Networked Control Systems Based on 100 M Switched Ethernet

    Science.gov (United States)

    2014-01-01

    For the delay may degrade the performance of networked control systems, networked control systems based on 100 M switched Ethernet are proposed in this paper. According to the working principle of Ethernet switch, the formulas of the upper bound delay of the single-level switched Ethernet and the multiple-level switched Ethernet are deduced by the timing diagram method, and the values of the upper bound delay are also given. The key factors that influence the upper bound delay of switched Ethernet are analyzed; then, the characteristics of the upper bound delay are presented, which show that the delay induced by the single-level 100 M switched Ethernet has little effect on the performance of control systems, while the delay induced by the multiple-level 100 M switched Ethernet may meet the time requirements of all classes of control systems if the numbers of levels and the numbers of nodes connecting to switches are set properly. Finally, the performance of networked control systems is simulated by TrueTime, and the results further show the feasibility and superiority of 100 M switched Ethernet based networked control systems without modification of the network protocols. PMID:25003152

  1. Proposed Network Intrusion Detection System ‎In Cloud Environment Based on Back ‎Propagation Neural Network

    Directory of Open Access Journals (Sweden)

    Shawq Malik Mehibs

    2017-12-01

    Full Text Available Cloud computing is distributed architecture, providing computing facilities and storage resource as a service over the internet. This low-cost service fulfills the basic requirements of users. Because of the open nature and services introduced by cloud computing intruders impersonate legitimate users and misuse cloud resource and services. To detect intruders and suspicious activities in and around the cloud computing environment, intrusion detection system used to discover the illegitimate users and suspicious action by monitors different user activities on the network .this work proposed based back propagation artificial neural network to construct t network intrusion detection in the cloud environment. The proposed module evaluated with kdd99 dataset the experimental results shows promising approach to detect attack with high detection rate and low false alarm rate

  2. Radial Basis Function Neural Network-based PID model for functional electrical stimulation system control.

    Science.gov (United States)

    Cheng, Longlong; Zhang, Guangju; Wan, Baikun; Hao, Linlin; Qi, Hongzhi; Ming, Dong

    2009-01-01

    Functional electrical stimulation (FES) has been widely used in the area of neural engineering. It utilizes electrical current to activate nerves innervating extremities affected by paralysis. An effective combination of a traditional PID controller and a neural network, being capable of nonlinear expression and adaptive learning property, supply a more reliable approach to construct FES controller that help the paraplegia complete the action they want. A FES system tuned by Radial Basis Function (RBF) Neural Network-based Proportional-Integral-Derivative (PID) model was designed to control the knee joint according to the desired trajectory through stimulation of lower limbs muscles in this paper. Experiment result shows that the FES system with RBF Neural Network-based PID model get a better performance when tracking the preset trajectory of knee angle comparing with the system adjusted by Ziegler- Nichols tuning PID model.

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

    Energy Technology Data Exchange (ETDEWEB)

    Li, B B; Yuan, Z F [School of Manufacture Sci.and Eng., Sichuan University, Chengdu 610065 (China)

    2006-10-15

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

  4. New elastomeric silicone based networks applicable as electroactive systems

    DEFF Research Database (Denmark)

    Bejenariu, Anca Gabriela; Boll, Mads; Lotz, Mikkel Rønne

    2011-01-01

    . In this study we focus on optimization of the mechanical properties of the elastomer and show that it is possible to lower the elastic modulus and still not compromise the other required mechanical properties such as fast response, stability, low degree of viscous dissipation and high extensibility....... The elastomers are prepared from a vinyl-terminated polydimethyl siloxane (PDMS) and a 4-functional crosslinker by a platinum-catalyzed hydrosilylation reaction between the two reactants. Traditionally, elastomers based on hydrosilylation are prepared via a ‘one-step two-pot’ procedure (with a mix A and a mix B...

  5. Development of an On-board Diagnostics System Based on Wireless Network

    Directory of Open Access Journals (Sweden)

    Guosheng FENG

    2014-02-01

    Full Text Available In order to control vehicle exhaust emission effectively, an OBD is developed based on Zigbee technology. Overall solution design of the system is proposed and the vehicle-mounted monitoring database is established. The wireless network communication hardware platform is set up by the MC9S08GT60 microcontroller and the MC13192 wireless module. The project document is produced with the help of BeeKit wireless connectivity toolkit. Under the CodeWarrior IDE development environment, the monitoring station coordinator networking program and the vehicle-mounted terminal device networking program are designed. Experimental results shows that this system complete data exchange between the monitoring station coordinator and the vehicle-mounted terminal device and transfer data into monitoring station computer. The wireless network of OBD is realized.

  6. Active-Varying Sampling-Based Fault Detection Filter Design for Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Yu-Long Wang

    2014-01-01

    Full Text Available This paper is concerned with fault detection filter design for continuous-time networked control systems considering packet dropouts and network-induced delays. The active-varying sampling period method is introduced to establish a new discretized model for the considered networked control systems. The mutually exclusive distribution characteristic of packet dropouts and network-induced delays is made full use of to derive less conservative fault detection filter design criteria. Compared with the fault detection filter design adopting a constant sampling period, the proposed active-varying sampling-based fault detection filter design can improve the sensitivity of the residual signal to faults and shorten the needed time for fault detection. The simulation results illustrate the merits and effectiveness of the proposed fault detection filter design.

  7. White blood cells identification system based on convolutional deep neural learning networks.

    Science.gov (United States)

    Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

    2017-11-16

    White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

  8. The Construction of Higher Education Entrepreneur Services Network System a Research Based on Ecological Systems Theory

    Science.gov (United States)

    Xue, Jingxin

    The article aims to completely, systematically and objectively analyze the current situation of Entrepreneurship Education in China with Ecological Systems Theory. From this perspective, the author discusses the structure, function and its basic features of higher education entrepreneur services network system, and puts forward the opinion that every entrepreneurship organization in higher education institution does not limited to only one platform. Different functional supporting platforms should be combined closed through composite functional organization to form an integrated network system, in which each unit would impels others' development.

  9. Neural network approximation of nonlinearity in laser nano-metrology system based on TLMI

    Science.gov (United States)

    Olyaee, Saeed; Hamedi, Samaneh

    2011-02-01

    In this paper, an approach based on neural network (NN) for nonlinearity modeling in a nano-metrology system using three-longitudinal-mode laser heterodyne interferometer (TLMI) for length and displacement measurements is presented. We model nonlinearity errors that arise from elliptically and non-orthogonally polarized laser beams, rotational error in the alignment of laser head with respect to the polarizing beam splitter, rotational error in the alignment of the mixing polarizer, and unequal transmission coefficients in the polarizing beam splitter. Here we use a neural network algorithm based on the multi-layer perceptron (MLP) network. The simulation results show that multi-layer feed forward perceptron network is successfully applicable to real noisy interferometer signals.

  10. Autoblocker: a system for detecting and blocking of network scanning based on analysis of netflow data

    Energy Technology Data Exchange (ETDEWEB)

    Bobyshev, A.; Lamore, D.; Demar, P.; /Fermilab

    2004-12-01

    In a large campus network, such at Fermilab, with tens of thousands of nodes, scanning initiated from either outside of or within the campus network raises security concerns. This scanning may have very serious impact on network performance, and even disrupt normal operation of many services. In this paper we introduce a system for detecting and automatic blocking excessive traffic of different kinds of scanning, DoS attacks, virus infected computers. The system, called AutoBlocker, is a distributed computing system based on quasi-real time analysis of network flow data collected from the border router and core switches. AutoBlocker also has an interface to accept alerts from IDS systems (e.g. BRO, SNORT) that are based on other technologies. The system has multiple configurable alert levels for the detection of anomalous behavior and configurable trigger criteria for automated blocking of scans at the core or border routers. It has been in use at Fermilab for about 2 years, and has become a very valuable tool to curtail scan activity within the Fermilab campus network.

  11. Network-Based Real-time Integrated Fire Detection and Alarm (FDA) System with Building Automation

    Science.gov (United States)

    Anwar, F.; Boby, R. I.; Rashid, M. M.; Alam, M. M.; Shaikh, Z.

    2017-11-01

    Fire alarm systems have become increasingly an important lifesaving technology in many aspects, such as applications to detect, monitor and control any fire hazard. A large sum of money is being spent annually to install and maintain the fire alarm systems in buildings to protect property and lives from the unexpected spread of fire. Several methods are already developed and it is improving on a daily basis to reduce the cost as well as increase quality. An integrated Fire Detection and Alarm (FDA) systems with building automation was studied, to reduce cost and improve their reliability by preventing false alarm. This work proposes an improved framework for FDA system to ensure a robust intelligent network of FDA control panels in real-time. A shortest path algorithmic was chosen for series of buildings connected by fiber optic network. The framework shares information and communicates with each fire alarm panels connected in peer to peer configuration and declare the network state using network address declaration from any building connected in network. The fiber-optic connection was proposed to reduce signal noises, thus increasing large area coverage, real-time communication and long-term safety. Based on this proposed method an experimental setup was designed and a prototype system was developed to validate the performance in practice. Also, the distributed network system was proposed to connect with an optional remote monitoring terminal panel to validate proposed network performance and ensure fire survivability where the information is sequentially transmitted. The proposed FDA system is different from traditional fire alarm and detection system in terms of topology as it manages group of buildings in an optimal and efficient manner.Introduction

  12. Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system

    Science.gov (United States)

    Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

    2017-10-01

    Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

  13. A New Method for Studying the Periodic System Based on a Kohonen Neural Network

    Science.gov (United States)

    Chen, David Zhekai

    2010-01-01

    A new method for studying the periodic system is described based on the combination of a Kohonen neural network and a set of chemical and physical properties. The classification results are directly shown in a two-dimensional map and easy to interpret. This is one of the major advantages of this approach over other methods reported in the…

  14. Neural Network Based Model of an Industrial Oil-Fired Boiler System ...

    African Journals Online (AJOL)

    In this study, an oil-fired boiler system is modeled as a multivariable plant with two inputs (feed water rate and oil-fired flow rate) and two outputs (steam temperature and pressure). The plant parameters are modeled using artificial neural network, based on experimental data collected directly from the physical plant.

  15. Implementation of a UNIX-Based Network Management System for English Instruction.

    Science.gov (United States)

    Schmitt, Lothar M.; Christianson, Kiel T.

    Pedagogical features and implementation of a UNIX-based management system (UNIEM) designed to support the instructor in teaching English as a second language using a network of workstations are described. The application discussed here is for teaching English composition to students at the University of Aizu (Japan). UNIEM is constructed to assist…

  16. Pedagogical Aspects of a UNIX-Based Network Management System of English Instruction.

    Science.gov (United States)

    Schmitt, Lothar M.; Christianson, Kiel T.

    1998-01-01

    Describes the justification for design and implementation of a UNIX-based computer-assisted language-instruction system using a network of workstations containing functions useful for instructors and students as well as researchers. The present investigation is aimed at teaching writing to Japanese students at the University of Aizu in Japan.…

  17. Image Classification System Based on Cortical Representations and Unsupervised Neural Network Learning

    NARCIS (Netherlands)

    Petkov, Nikolay

    1995-01-01

    A preprocessor based on a computational model of simple cells in the mammalian primary visual cortex is combined with a self-organising artificial neural network classifier. After learning with a sequence of input images, the output units of the system turn out to correspond to classes of input

  18. A network identity authentication protocol of bank account system based on fingerprint identification and mixed encryption

    Science.gov (United States)

    Zhu, Lijuan; Liu, Jingao

    2013-07-01

    This paper describes a network identity authentication protocol of bank account system based on fingerprint identification and mixed encryption. This protocol can provide every bank user a safe and effective way to manage his own bank account, and also can effectively prevent the hacker attacks and bank clerk crime, so that it is absolute to guarantee the legitimate rights and interests of bank users.

  19. Hybrid fuzzy charged system search algorithm based state estimation in distribution networks

    Directory of Open Access Journals (Sweden)

    Sachidananda Prasad

    2017-06-01

    Full Text Available This paper proposes a new hybrid charged system search (CSS algorithm based state estimation in radial distribution networks in fuzzy framework. The objective of the optimization problem is to minimize the weighted square of the difference between the measured and the estimated quantity. The proposed method of state estimation considers bus voltage magnitude and phase angle as state variable along with some equality and inequality constraints for state estimation in distribution networks. A rule based fuzzy inference system has been designed to control the parameters of the CSS algorithm to achieve better balance between the exploration and exploitation capability of the algorithm. The efficiency of the proposed fuzzy adaptive charged system search (FACSS algorithm has been tested on standard IEEE 33-bus system and Indian 85-bus practical radial distribution system. The obtained results have been compared with the conventional CSS algorithm, weighted least square (WLS algorithm and particle swarm optimization (PSO for feasibility of the algorithm.

  20. Critical Nodes Identification of Power Systems Based on Controllability of Complex Networks

    Directory of Open Access Journals (Sweden)

    Yu-Shuai Li

    2015-09-01

    Full Text Available This paper proposes a new method for assessing the vulnerability of power systems based on the controllability theories of complex networks. A novel controllability index is established, taking into consideration the full controllability of the power systems, for identifying critical nodes. The network controllability model is used to calculate the minimum number of driver nodes (ND, which can solve the computable problems of the controllability of power systems. The proposed approach firstly applies the network controllability theories to research the power systems' vulnerability, which can not only effectively reveal the important nodes but also maintain full control of the power systems. Meanwhile, the method can also overcome the limitation of the hypothesis that the weight of each link or transmission line must be known compared with the existing literature. In addition, the power system is considered as a directed network and the power system model is also redefined. The proposed methodology is then used to identify critical nodes of the IEEE 118 and 300 bus system. The results show that the failure of the critical nodes can clearly increase ND and lead a significant driver node shift. Thus, the rationality and validity are verified.

  1. A wireless sensor network-based portable vehicle detector evaluation system.

    Science.gov (United States)

    Yoo, Seong-eun

    2013-01-17

    In an upcoming smart transportation environment, performance evaluations of existing Vehicle Detection Systems are crucial to maintain their accuracy. The existing evaluation method for Vehicle Detection Systems is based on a wired Vehicle Detection System reference and a video recorder, which must be operated and analyzed by capable traffic experts. However, this conventional evaluation system has many disadvantages. It is inconvenient to deploy, the evaluation takes a long time, and it lacks scalability and objectivity. To improve the evaluation procedure, this paper proposes a Portable Vehicle Detector Evaluation System based on wireless sensor networks. We describe both the architecture and design of a Vehicle Detector Evaluation System and the implementation results, focusing on the wireless sensor networks and methods for traffic information measurement. With the help of wireless sensor networks and automated analysis, our Vehicle Detector Evaluation System can evaluate a Vehicle Detection System conveniently and objectively. The extensive evaluations of our Vehicle Detector Evaluation System show that it can measure the traffic information such as volume counts and speed with over 98% accuracy.

  2. Design and implementation of fingerprint access control system based on ZigBee wireless network

    Directory of Open Access Journals (Sweden)

    Zhang Jin

    2017-01-01

    Full Text Available this paper mainly introduces a kind of fingerprint access control system based on ZigBee wireless network design and implementation method, specify when passengers should fingerprints collected and stored in the system at the information desk PC, and then assign rooms;Guests entered the room according to the fingerprint module, the system will be fingerprint information through ZigBee coordinator node module and network to transmit the fingerprint characteristic value to management system and the fingerprint information stored, if consistent with the electromagnetic lock open, allowed to enter the room, does not conform to the issued a warning sound.Additional access control system can control the corresponding fingerprint information storage room and remove, such as is required for a security incident broke in situation is special open mode can be set up.System software design consists of two aspects of the bottom and upper machine.

  3. Fuzzy wavelet plus a quantum neural network as a design base for power system stability enhancement.

    Science.gov (United States)

    Ganjefar, Soheil; Tofighi, Morteza; Karami, Hamidreza

    2015-11-01

    In this study, we introduce an indirect adaptive fuzzy wavelet neural controller (IAFWNC) as a power system stabilizer to damp inter-area modes of oscillations in a multi-machine power system. Quantum computing is an efficient method for improving the computational efficiency of neural networks, so we developed an identifier based on a quantum neural network (QNN) to train the IAFWNC in the proposed scheme. All of the controller parameters are tuned online based on the Lyapunov stability theory to guarantee the closed-loop stability. A two-machine, two-area power system equipped with a static synchronous series compensator as a series flexible ac transmission system was used to demonstrate the effectiveness of the proposed controller. The simulation and experimental results demonstrated that the proposed IAFWNC scheme can achieve favorable control performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Landslide and Flood Warning System Prototypes based on Wireless Sensor Networks

    Science.gov (United States)

    Hloupis, George; Stavrakas, Ilias; Triantis, Dimos

    2010-05-01

    Wireless sensor networks (WSNs) are one of the emerging areas that received great attention during the last few years. This is mainly due to the fact that WSNs have provided scientists with the capability of developing real-time monitoring systems equipped with sensors based on Micro-Electro-Mechanical Systems (MEMS). WSNs have great potential for many applications in environmental monitoring since the sensor nodes that comprised from can host several MEMS sensors (such as temperature, humidity, inertial, pressure, strain-gauge) and transducers (such as position, velocity, acceleration, vibration). The resulting devices are small and inexpensive but with limited memory and computing resources. Each sensor node contains a sensing module which along with an RF transceiver. The communication is broadcast-based since the network topology can change rapidly due to node failures [1]. Sensor nodes can transmit their measurements to central servers through gateway nodes without any processing or they make preliminary calculations locally in order to produce results that will be sent to central servers [2]. Based on the above characteristics, two prototypes using WSNs are presented in this paper: A Landslide detection system and a Flood warning system. Both systems sent their data to central processing server where the core of processing routines exists. Transmission is made using Zigbee and IEEE 802.11b protocol but is capable to use VSAT communication also. Landslide detection system uses structured network topology. Each measuring node comprises of a columnar module that is half buried to the area under investigation. Each sensing module contains a geophone, an inclinometer and a set of strain gauges. Data transmitted to central processing server where possible landslide evolution is monitored. Flood detection system uses unstructured network topology since the failure rate of sensor nodes is expected higher. Each sensing module contains a custom water level sensor

  5. Review of Data Preprocessing Methods for Sign Language Recognition Systems based on Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Zorins Aleksejs

    2016-12-01

    Full Text Available The article presents an introductory analysis of relevant research topic for Latvian deaf society, which is the development of the Latvian Sign Language Recognition System. More specifically the data preprocessing methods are discussed in the paper and several approaches are shown with a focus on systems based on artificial neural networks, which are one of the most successful solutions for sign language recognition task.

  6. Mechanism Aligning (Gateway) Between Operating System Based on Computer Networks in Unocal

    OpenAIRE

    Vera Morina Oktavia Carla; Drs.Ida Ayu Wiastiti, M.KOM Drs.Ida Ayu Wiastiti, M.KOM

    1997-01-01

    Computer network is a system that allows for the sharing of information among users.Use of operating systems in the network settings is an absolute must. Replacement ofthe network operating system should really consider the possibility of impacts.Aligning is one solution in order to connect two different systems.

  7. Architecture and System Engineering Development Study of Space-Based Satellite Networks for NASA Missions

    Science.gov (United States)

    Ivancic, William D.

    2003-01-01

    Traditional NASA missions, both near Earth and deep space, have been stovepipe in nature and point-to-point in architecture. Recently, NASA and others have conceptualized missions that required space-based networking. The notion of networks in space is a drastic shift in thinking and requires entirely new architectures, radio systems (antennas, modems, and media access), and possibly even new protocols. A full system engineering approach for some key mission architectures will occur that considers issues such as the science being performed, stationkeeping, antenna size, contact time, data rates, radio-link power requirements, media access techniques, and appropriate networking and transport protocols. This report highlights preliminary architecture concepts and key technologies that will be investigated.

  8. Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

    Science.gov (United States)

    Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

    2015-03-01

    The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

  9. System and method for knowledge based matching of users in a network

    Science.gov (United States)

    Verspoor, Cornelia Maria [Santa Fe, NM; Sims, Benjamin Hayden [Los Alamos, NM; Ambrosiano, John Joseph [Los Alamos, NM; Cleland, Timothy James [Los Alamos, NM

    2011-04-26

    A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest selected from an. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more general concept. Similarity measures between profiles may then be calculated based on suitable distance formulas within this space.

  10. Neural Network-Based Receiver in Band-Limited Communication System with MPPSK Modulation

    Directory of Open Access Journals (Sweden)

    Wang Zixin

    2018-01-01

    Full Text Available As a type of the spectrally efficient modulation, the m-ary phase position shift keying (MPPSK has been considered to meet the increasing spectrum requirement in the future wireless system. To limit the signal bandwidth and cancel the out-band interference the band-pass filters are used, which introduce the waveform distortion and inter-symbol interference (ISI. Therefore, a single hidden-layer neural network (NN-based receiver is proposed to jointly equalize and demodulate the received signal. The impulse response of the system is static and the network parameters can be obtained after off-line training. The number of the hidden nodes is also determined through simulations. Simulation results show that the NN-based receiver works well in the communication system with different allocated bandwidths. By observing the modified confusion matrix, the false symbol decision is relevant to modulation index, waveform distortions and the ISI.

  11. Observer-based H(infinity) control for networked nonlinear systems with random packet losses.

    Science.gov (United States)

    Li, Jian Guo; Yuan, Jing Qi; Lu, Jun Guo

    2010-01-01

    This paper investigates the observer-based H(infinity) control problem of networked nonlinear systems with global Lipschitz nonlinearities and random communication packet losses. The random packet loss is modelled as a Bernoulli distributed white sequence with a known conditional probability distribution. In the presence of random packet losses, sufficient conditions for the existence of an observer-based feedback controller are derived, such that the closed-loop networked nonlinear system is exponentially stable in the mean-square sense, and a prescribed H(infinity) disturbance-rejection-attenuation performance is also achieved. Then a linear matrix inequality (LMI) approach for designing such an observer-based H(infinity) controller is presented. Finally, a simulation example is used to demonstrate the effectiveness of the proposed method. 2009. Published by Elsevier Ltd.

  12. RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sungwon Lee

    2009-05-01

    Full Text Available TheIP-based Ubiquitous Sensor Network (IP-USN is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System called RIDES (Robust Intrusion DEtection System for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

  13. RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks

    Science.gov (United States)

    Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

    2009-01-01

    The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the “Internet of things”. By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components. PMID:22412321

  14. RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

    Science.gov (United States)

    Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

    2009-01-01

    The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

  15. Network systems security analysis

    Science.gov (United States)

    Yilmaz, Ä.°smail

    2015-05-01

    Network Systems Security Analysis has utmost importance in today's world. Many companies, like banks which give priority to data management, test their own data security systems with "Penetration Tests" by time to time. In this context, companies must also test their own network/server systems and take precautions, as the data security draws attention. Based on this idea, the study cyber-attacks are researched throughoutly and Penetration Test technics are examined. With these information on, classification is made for the cyber-attacks and later network systems' security is tested systematically. After the testing period, all data is reported and filed for future reference. Consequently, it is found out that human beings are the weakest circle of the chain and simple mistakes may unintentionally cause huge problems. Thus, it is clear that some precautions must be taken to avoid such threats like updating the security software.

  16. Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

    Science.gov (United States)

    Williams-Hayes, Peggy S.

    2004-01-01

    The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

  17. Deployment strategy for battery energy storage system in distribution network based on voltage violation regulation

    Science.gov (United States)

    Wu, H.; Zhou, L.; Xu, T.; Fang, W. L.; He, W. G.; Liu, H. M.

    2017-11-01

    In order to improve the situation of voltage violation caused by the grid-connection of photovoltaic (PV) system in a distribution network, a bi-level programming model is proposed for battery energy storage system (BESS) deployment. The objective function of inner level programming is to minimize voltage violation, with the power of PV and BESS as the variables. The objective function of outer level programming is to minimize the comprehensive function originated from inner layer programming and all the BESS operating parameters, with the capacity and rated power of BESS as the variables. The differential evolution (DE) algorithm is applied to solve the model. Based on distribution network operation scenarios with photovoltaic generation under multiple alternative output modes, the simulation results of IEEE 33-bus system prove that the deployment strategy of BESS proposed in this paper is well adapted to voltage violation regulation invariable distribution network operation scenarios. It contributes to regulating voltage violation in distribution network, as well as to improve the utilization of PV systems.

  18. An Efficient Mesh Generation Method for Fractured Network System Based on Dynamic Grid Deformation

    Directory of Open Access Journals (Sweden)

    Shuli Sun

    2013-01-01

    Full Text Available Meshing quality of the discrete model influences the accuracy, convergence, and efficiency of the solution for fractured network system in geological problem. However, modeling and meshing of such a fractured network system are usually tedious and difficult due to geometric complexity of the computational domain induced by existence and extension of fractures. The traditional meshing method to deal with fractures usually involves boundary recovery operation based on topological transformation, which relies on many complicated techniques and skills. This paper presents an alternative and efficient approach for meshing fractured network system. The method firstly presets points on fractures and then performs Delaunay triangulation to obtain preliminary mesh by point-by-point centroid insertion algorithm. Then the fractures are exactly recovered by local correction with revised dynamic grid deformation approach. Smoothing algorithm is finally applied to improve the quality of mesh. The proposed approach is efficient, easy to implement, and applicable to the cases of initial existing fractures and extension of fractures. The method is successfully applied to modeling of two- and three-dimensional discrete fractured network (DFN system in geological problems to demonstrate its effectiveness and high efficiency.

  19. Wireless Sensor Network Based Smart Grid Communications: Cyber Attacks, Intrusion Detection System and Topology Control

    Directory of Open Access Journals (Sweden)

    Lipi Chhaya

    2017-01-01

    Full Text Available The existing power grid is going through a massive transformation. Smart grid technology is a radical approach for improvisation in prevailing power grid. Integration of electrical and communication infrastructure is inevitable for the deployment of Smart grid network. Smart grid technology is characterized by full duplex communication, automatic metering infrastructure, renewable energy integration, distribution automation and complete monitoring and control of entire power grid. Wireless sensor networks (WSNs are small micro electrical mechanical systems that are deployed to collect and communicate the data from surroundings. WSNs can be used for monitoring and control of smart grid assets. Security of wireless sensor based communication network is a major concern for researchers and developers. The limited processing capabilities of wireless sensor networks make them more vulnerable to cyber-attacks. The countermeasures against cyber-attacks must be less complex with an ability to offer confidentiality, data readiness and integrity. The address oriented design and development approach for usual communication network requires a paradigm shift to design data oriented WSN architecture. WSN security is an inevitable part of smart grid cyber security. This paper is expected to serve as a comprehensive assessment and analysis of communication standards, cyber security issues and solutions for WSN based smart grid infrastructure.

  20. Gene regulatory network identification from the yeast cell cycle based on a neuro-fuzzy system.

    Science.gov (United States)

    Wang, B H; Lim, J W; Lim, J S

    2016-08-30

    Many studies exist for reconstructing gene regulatory networks (GRNs). In this paper, we propose a method based on an advanced neuro-fuzzy system, for gene regulatory network reconstruction from microarray time-series data. This approach uses a neural network with a weighted fuzzy function to model the relationships between genes. Fuzzy rules, which determine the regulators of genes, are very simplified through this method. Additionally, a regulator selection procedure is proposed, which extracts the exact dynamic relationship between genes, using the information obtained from the weighted fuzzy function. Time-series related features are extracted from the original data to employ the characteristics of temporal data that are useful for accurate GRN reconstruction. The microarray dataset of the yeast cell cycle was used for our study. We measured the mean squared prediction error for the efficiency of the proposed approach and evaluated the accuracy in terms of precision, sensitivity, and F-score. The proposed method outperformed the other existing approaches.

  1. The Wireless Sensor Network (WSN) Based Coal Ash Impoundments Safety Monitoring System

    Science.gov (United States)

    Sun, E. J.; Nieto, A.; Zhang, X. K.

    2017-01-01

    Coal ash impoundments are inevitable production of the coal-fired power plants. All coal ash impoundments in North Carolina USA that tested for groundwater contamination are leaking toxic heavy metals and other pollutants. Coal ash impoundments are toxic sources of dangerous pollutants that pose a danger to human and environmental health if the toxins spread to adjacent surface waters and drinking water wells. Coal ash impoundments failures accidents resulted in serious water contamination along with toxic heavy metals. To improve the design and stability of coal ash impoundments, the Development of a Coal Ash Impoundment Safety Monitoring System (CAISM) was proposed based on the implementation of a wireless sensor network (WSN) with the ability to monitor the stability of coal ash impoundments, water level, and saturation levels on-demand and remotely. The monitoring system based on a robust Ad-hoc network could be adapted to different safety conditions.

  2. The Wireless Environment Monitoring Alarm System Based on Self-organizing Network

    Directory of Open Access Journals (Sweden)

    Zhang Huawei

    2016-01-01

    Full Text Available Under complicated conditions, it is necessary for environmental monitoring to design a wireless monitoring alarm system which can replace the wired system or as a supplement. The system discussed here bases on ARM7 microprocessor named LPC1114 and transceiver module named CC2530. With ZigBee, CSM/GPRS, this system uses multiple sensors to self-organized form a data acquisition and monitoring network system with variety of sensors fusion in the region. The system has some characteristics such as quick, convenient and accurate. Combining with the GSM SMS or GPRS alarm, the system can accurately and reliably monitor temperature, humidity and other environmental factors, and realize remote monitoring in large area and the complicated environment. Thus, this system has high practical value.

  3. Simulation and stability analysis of neural network based control scheme for switched linear systems.

    Science.gov (United States)

    Singh, H P; Sukavanam, N

    2012-01-01

    This paper proposes a new adaptive neural network based control scheme for switched linear systems with parametric uncertainty and external disturbance. A key feature of this scheme is that the prior information of the possible upper bound of the uncertainty is not required. A feedforward neural network is employed to learn this upper bound. The adaptive learning algorithm is derived from Lyapunov stability analysis so that the system response under arbitrary switching laws is guaranteed uniformly ultimately bounded. A comparative simulation study with robust controller given in [Zhang L, Lu Y, Chen Y, Mastorakis NE. Robust uniformly ultimate boundedness control for uncertain switched linear systems. Computers and Mathematics with Applications 2008; 56: 1709-14] is presented. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  4. An energy-efficient underground localization system based on heterogeneous wireless networks.

    Science.gov (United States)

    Yuan, Yazhou; Chen, Cailian; Guan, Xinping; Yang, Qiuling

    2015-05-26

    A precision positioning system with energy efficiency is of great necessity for guaranteeing personnel safety in underground mines. The location information of the miners' should be transmitted to the control center timely and reliably; therefore, a heterogeneous network with the backbone based on high speed Industrial Ethernet is deployed. Since the mobile wireless nodes are working in an irregular tunnel, a specific wireless propagation model cannot fit all situations. In this paper, an underground localization system is designed to enable the adaptation to kinds of harsh tunnel environments, but also to reduce the energy consumption and thus prolong the lifetime of the network. Three key techniques are developed and implemented to improve the system performance, including a step counting algorithm with accelerometers, a power control algorithm and an adaptive packets scheduling scheme. The simulation study and experimental results show the effectiveness of the proposed algorithms and the implementation.

  5. Control Strategy Based on Wavelet Transform and Neural Network for Hybrid Power System

    Directory of Open Access Journals (Sweden)

    Y. D. Song

    2013-01-01

    Full Text Available This paper deals with an energy management of a hybrid power generation system. The proposed control strategy for the energy management is based on the combination of wavelet transform and neural network arithmetic. The hybrid system in this paper consists of an emulated wind turbine generator, PV panels, DC and AC loads, lithium ion battery, and super capacitor, which are all connected on a DC bus with unified DC voltage. The control strategy is responsible for compensating the difference between the generated power from the wind and solar generators and the demanded power by the loads. Wavelet transform decomposes the power difference into smoothed component and fast fluctuated component. In consideration of battery protection, the neural network is introduced to calculate the reference power of battery. Super capacitor (SC is controlled to regulate the DC bus voltage. The model of the hybrid system is developed in detail under Matlab/Simulink software environment.

  6. Study on Network Error Analysis and Locating based on Integrated Information Decision System

    Science.gov (United States)

    Yang, F.; Dong, Z. H.

    2017-10-01

    Integrated information decision system (IIDS) integrates multiple sub-system developed by many facilities, including almost hundred kinds of software, which provides with various services, such as email, short messages, drawing and sharing. Because the under-layer protocols are different, user standards are not unified, many errors are occurred during the stages of setup, configuration, and operation, which seriously affect the usage. Because the errors are various, which may be happened in different operation phases, stages, TCP/IP communication protocol layers, sub-system software, it is necessary to design a network error analysis and locating tool for IIDS to solve the above problems. This paper studies on network error analysis and locating based on IIDS, which provides strong theory and technology supports for the running and communicating of IIDS.

  7. An Energy-Efficient Underground Localization System Based on Heterogeneous Wireless Networks

    Directory of Open Access Journals (Sweden)

    Yazhou Yuan

    2015-05-01

    Full Text Available A precision positioning system with energy efficiency is of great necessity for guaranteeing personnel safety in underground mines. The location information of the miners’ should be transmitted to the control center timely and reliably; therefore, a heterogeneous network with the backbone based on high speed Industrial Ethernet is deployed. Since the mobile wireless nodes are working in an irregular tunnel, a specific wireless propagation model cannot fit all situations. In this paper, an underground localization system is designed to enable the adaptation to kinds of harsh tunnel environments, but also to reduce the energy consumption and thus prolong the lifetime of the network. Three key techniques are developed and implemented to improve the system performance, including a step counting algorithm with accelerometers, a power control algorithm and an adaptive packets scheduling scheme. The simulation study and experimental results show the effectiveness of the proposed algorithms and the implementation.

  8. TCSC Nonlinear Adaptive Damping Controller Design Based on RBF Neural Network to Enhance Power System Stability

    DEFF Research Database (Denmark)

    Yao, Wei; Fang, Jiakun; Zhao, Ping

    2013-01-01

    In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have...... system and a four-machine two-area power system under different operating conditions in comparison with the lead-lag damping controller tuned by evolutionary algorithm (EA). Simulation results show that the proposed damping controller achieves good robust performance for damping the low frequency...

  9. Human Detection System by Fusing Depth Map-Based Method and Convolutional Neural Network-Based Method

    Directory of Open Access Journals (Sweden)

    Anh Vu Le

    2017-01-01

    Full Text Available In this paper, the depth images and the colour images provided by Kinect sensors are used to enhance the accuracy of human detection. The depth-based human detection method is fast but less accurate. On the other hand, the faster region convolutional neural network-based human detection method is accurate but requires a rather complex hardware configuration. To simultaneously leverage the advantages and relieve the drawbacks of each method, one master and one client system is proposed. The final goal is to make a novel Robot Operation System (ROS-based Perception Sensor Network (PSN system, which is more accurate and ready for the real time application. The experimental results demonstrate the outperforming of the proposed method compared with other conventional methods in the challenging scenarios.

  10. Computationally Efficient Power Allocation Algorithm in Multicarrier-Based Cognitive Radio Networks: OFDM and FBMC Systems

    Directory of Open Access Journals (Sweden)

    Shaat Musbah

    2010-01-01

    Full Text Available Cognitive Radio (CR systems have been proposed to increase the spectrum utilization by opportunistically access the unused spectrum. Multicarrier communication systems are promising candidates for CR systems. Due to its high spectral efficiency, filter bank multicarrier (FBMC can be considered as an alternative to conventional orthogonal frequency division multiplexing (OFDM for transmission over the CR networks. This paper addresses the problem of resource allocation in multicarrier-based CR networks. The objective is to maximize the downlink capacity of the network under both total power and interference introduced to the primary users (PUs constraints. The optimal solution has high computational complexity which makes it unsuitable for practical applications and hence a low complexity suboptimal solution is proposed. The proposed algorithm utilizes the spectrum holes in PUs bands as well as active PU bands. The performance of the proposed algorithm is investigated for OFDM and FBMC based CR systems. Simulation results illustrate that the proposed resource allocation algorithm with low computational complexity achieves near optimal performance and proves the efficiency of using FBMC in CR context.

  11. Self-Adaptive Strategy Based on Fuzzy Control Systems for Improving Performance in Wireless Sensors Networks.

    Science.gov (United States)

    Hernández Díaz, Vicente; Martínez, José-Fernán; Lucas Martínez, Néstor; del Toro, Raúl M

    2015-09-18

    The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN) are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container), and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

  12. Self-Adaptive Strategy Based on Fuzzy Control Systems for Improving Performance in Wireless Sensors Networks

    Directory of Open Access Journals (Sweden)

    Vicente Hernández Díaz

    2015-09-01

    Full Text Available The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT and Cyber-Physical Systems (CPS are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container, and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

  13. Application of wireless sensor network based on ZigBee technology in photo-bioreactors system

    Science.gov (United States)

    Liu, Bo; Chen, Ming; Chi, Tao

    2013-03-01

    A photo-bioreactor is a bioreactor that incorporates some types of light source to provide photonic energy input into the reactor[1][2]. In the situation of Large-scale industrialization production of micro-algae, hundreds of photo-bioreactors will be deployed in a factory, thus the design of entire system is based on the distribution theory and the remote monitoring must be deployed. So the communication in the entire photo-bioreactors system is very important. However, the recent solution of communication is based on RS-485 data bus, and the twisted-pair cable is used as the communication medium, so the flexibility and scalability of entire system reduce. In this paper, the wireless sensor network (WSN) based on ZigBee technology is applied to this photo-bioreactors system, and the related key problems include the architecture of entire system and the design of wireless sensor network nodes[3]~[6]. The application of this technology will also reduce the cost and effectively raise the intelligence level of the large-scale industrialization photo-bioreactors system.

  14. Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

    Science.gov (United States)

    Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

    2013-09-01

    In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

  15. ICE: A Scalable, Low-Cost FPGA-Based Telescope Signal Processing and Networking System

    Science.gov (United States)

    Bandura, K.; Bender, A. N.; Cliche, J. F.; de Haan, T.; Dobbs, M. A.; Gilbert, A. J.; Griffin, S.; Hsyu, G.; Ittah, D.; Parra, J. Mena; Montgomery, J.; Pinsonneault-Marotte, T.; Siegel, S.; Smecher, G.; Tang, Q. Y.; Vanderlinde, K.; Whitehorn, N.

    2016-03-01

    We present an overview of the ‘ICE’ hardware and software framework that implements large arrays of interconnected field-programmable gate array (FPGA)-based data acquisition, signal processing and networking nodes economically. The system was conceived for application to radio, millimeter and sub-millimeter telescope readout systems that have requirements beyond typical off-the-shelf processing systems, such as careful control of interference signals produced by the digital electronics, and clocking of all elements in the system from a single precise observatory-derived oscillator. A new generation of telescopes operating at these frequency bands and designed with a vastly increased emphasis on digital signal processing to support their detector multiplexing technology or high-bandwidth correlators — data rates exceeding a terabyte per second — are becoming common. The ICE system is built around a custom FPGA motherboard that makes use of an Xilinx Kintex-7 FPGA and ARM-based co-processor. The system is specialized for specific applications through software, firmware and custom mezzanine daughter boards that interface to the FPGA through the industry-standard FPGA mezzanine card (FMC) specifications. For high density applications, the motherboards are packaged in 16-slot crates with ICE backplanes that implement a low-cost passive full-mesh network between the motherboards in a crate, allow high bandwidth interconnection between crates and enable data offload to a computer cluster. A Python-based control software library automatically detects and operates the hardware in the array. Examples of specific telescope applications of the ICE framework are presented, namely the frequency-multiplexed bolometer readout systems used for the South Pole Telescope (SPT) and Simons Array and the digitizer, F-engine, and networking engine for the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and Hydrogen Intensity and Real-time Analysis eXperiment (HIRAX) radio

  16. An Alternative Wearable Tracking System Based on a Low-Power Wide-Area Network

    Directory of Open Access Journals (Sweden)

    Raul Fernández-Garcia

    2017-03-01

    Full Text Available This work presents an alternative wearable tracking system based on a low-power wide area network. A complete GPS receiver was integrated with a textile substrate, and the latitude and longitude coordinates were sent to the cloud by means of the SIM-less SIGFOX network. To send the coordinates over SIGFOX protocol, a specific codification algorithm was used and a customized UHF antenna on jeans fabric was designed, simulated and tested. Moreover, to guarantee the compliance to international regulations for human body exposure to electromagnetic radiation, the electromagnetic specific absorption rate of this antenna was analyzed. A specific remote server was developed to decode the latitude and longitude coordinates. Once the coordinates have been decoded, the remote server sends this information to the open source data viewer SENTILO to show the location of the sensor node in a map. The functionality of this system has been demonstrated experimentally. The results guarantee the utility and wearability of the proposed tracking system for the development of sensor nodes and point out that it can be a low cost alternative to other commercial products based on GSM networks.

  17. An Alternative Wearable Tracking System Based on a Low-Power Wide-Area Network.

    Science.gov (United States)

    Fernández-Garcia, Raul; Gil, Ignacio

    2017-03-14

    This work presents an alternative wearable tracking system based on a low-power wide area network. A complete GPS receiver was integrated with a textile substrate, and the latitude and longitude coordinates were sent to the cloud by means of the SIM-less SIGFOX network. To send the coordinates over SIGFOX protocol, a specific codification algorithm was used and a customized UHF antenna on jeans fabric was designed, simulated and tested. Moreover, to guarantee the compliance to international regulations for human body exposure to electromagnetic radiation, the electromagnetic specific absorption rate of this antenna was analyzed. A specific remote server was developed to decode the latitude and longitude coordinates. Once the coordinates have been decoded, the remote server sends this information to the open source data viewer SENTILO to show the location of the sensor node in a map. The functionality of this system has been demonstrated experimentally. The results guarantee the utility and wearability of the proposed tracking system for the development of sensor nodes and point out that it can be a low cost alternative to other commercial products based on GSM networks.

  18. A Framework for UWB-Based Communication and Location Tracking Systems for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Antonio Valdovinos

    2011-09-01

    Full Text Available Ultra wideband (UWB radio technology is nowadays one of the most promising technologies for medium-short range communications. It has a wide range of applications including Wireless Sensor Networks (WSN with simultaneous data transmission and location tracking. The combination of location and data transmission is important in order to increase flexibility and reduce the cost and complexity of the system deployment. In this scenario, accuracy is not the only evaluation criteria, but also the amount of resources associated to the location service, as it has an impact not only on the location capacity of the system but also on the sensor data transmission capacity. Although several studies can be found in the literature addressing UWB-based localization, these studies mainly focus on distance estimation and position calculation algorithms. Practical aspects such as the design of the functional architecture, the procedure for the transmission of the associated information between the different elements of the system, and the need of tracking multiple terminals simultaneously in various application scenarios, are generally omitted. This paper provides a complete system level evaluation of a UWB-based communication and location system for Wireless Sensor Networks, including aspects such as UWB-based ranging, tracking algorithms, latency, target mobility and MAC layer design. With this purpose, a custom simulator has been developed, and results with real UWB equipment are presented too.

  19. A framework for UWB-based communication and location tracking systems for wireless sensor networks.

    Science.gov (United States)

    Chóliz, Juan; Hernández, Angela; Valdovinos, Antonio

    2011-01-01

    Ultra wideband (UWB) radio technology is nowadays one of the most promising technologies for medium-short range communications. It has a wide range of applications including wireless sensor networks (WSN) with simultaneous data transmission and location tracking. The combination of location and data transmission is important in order to increase flexibility and reduce the cost and complexity of the system deployment. In this scenario, accuracy is not the only evaluation criteria, but also the amount of resources associated to the location service, as it has an impact not only on the location capacity of the system but also on the sensor data transmission capacity. Although several studies can be found in the literature addressing UWB-based localization, these studies mainly focus on distance estimation and position calculation algorithms. Practical aspects such as the design of the functional architecture, the procedure for the transmission of the associated information between the different elements of the system, and the need of tracking multiple terminals simultaneously in various application scenarios, are generally omitted. This paper provides a complete system level evaluation of a UWB-based communication and location system for Wireless Sensor Networks, including aspects such as UWB-based ranging, tracking algorithms, latency, target mobility and MAC layer design. With this purpose, a custom simulator has been developed, and results with real UWB equipment are presented too.

  20. Granger Causality Network Reconstruction of Conductance-Based Integrate-and-Fire Neuronal Systems

    Science.gov (United States)

    Zhou, Douglas; Xiao, Yanyang; Zhang, Yaoyu; Xu, Zhiqin; Cai, David

    2014-01-01

    Reconstruction of anatomical connectivity from measured dynamical activities of coupled neurons is one of the fundamental issues in the understanding of structure-function relationship of neuronal circuitry. Many approaches have been developed to address this issue based on either electrical or metabolic data observed in experiment. The Granger causality (GC) analysis remains one of the major approaches to explore the dynamical causal connectivity among individual neurons or neuronal populations. However, it is yet to be clarified how such causal connectivity, i.e., the GC connectivity, can be mapped to the underlying anatomical connectivity in neuronal networks. We perform the GC analysis on the conductance-based integrate-and-fire (IF) neuronal networks to obtain their causal connectivity. Through numerical experiments, we find that the underlying synaptic connectivity amongst individual neurons or subnetworks, can be successfully reconstructed by the GC connectivity constructed from voltage time series. Furthermore, this reconstruction is insensitive to dynamical regimes and can be achieved without perturbing systems and prior knowledge of neuronal model parameters. Surprisingly, the synaptic connectivity can even be reconstructed by merely knowing the raster of systems, i.e., spike timing of neurons. Using spike-triggered correlation techniques, we establish a direct mapping between the causal connectivity and the synaptic connectivity for the conductance-based IF neuronal networks, and show the GC is quadratically related to the coupling strength. The theoretical approach we develop here may provide a framework for examining the validity of the GC analysis in other settings. PMID:24586285

  1. A General Combinatorial Ant System-based Distributed Routing Algorithm for Communication Networks

    Directory of Open Access Journals (Sweden)

    Jose Aguilar

    2007-08-01

    Full Text Available In this paper, a general Combinatorial Ant System-based distributed routing algorithm modeled like a dynamic combinatorial optimization problem is presented. In the proposed algorithm, the solution space of the dynamic combinatorial optimization problem is mapped into the space where the ants will walk, and the transition probability and the pheromone update formula of the Ant System is defined according to the objective function of the communication problem. The general nature of the approach allows for the optimization of the routing function to be applied in different types of networks just changing the performance criteria to be optimized. In fact, we test and compare the performance of our routing algorithm against well-known routing schemes for wired and wireless networks, and show its superior performance in terms throughput, delay and energy efficiency.

  2. Based on Artificial Neural Network to Realize K-Parameter Analysis of Vehicle Air Spring System

    Science.gov (United States)

    Hung, San-Shan; Hsu, Chia-Ning; Hwang, Chang-Chou; Chen, Wen-Jan

    2017-10-01

    In recent years, because of the air-spring control technique is more mature, that air- spring suspension systems already can be used to replace the classical vehicle suspension system. Depend on internal pressure variation of the air-spring, thestiffnessand the damping factor can be adjusted. Because of air-spring has highly nonlinear characteristic, therefore it isn’t easy to construct the classical controller to control the air-spring effectively. The paper based on Artificial Neural Network to propose a feasible control strategy. By using offline way for the neural network design and learning to the air-spring in different initial pressures and different loads, offline method through, predict air-spring stiffness parameter to establish a model. Finally, through adjusting air-spring internal pressure to change the K-parameter of the air-spring, realize the well dynamic control performance of air-spring suspension.

  3. Chaotic Extension Neural Network-Based Fault Diagnosis Method for Solar Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Kuo-Nan Yu

    2014-01-01

    Full Text Available At present, the solar photovoltaic system is extensively used. However, once a fault occurs, it is inspected manually, which is not economical. In order to remedy the defect of unavailable fault diagnosis at any irradiance and temperature in the literature with chaos synchronization based intelligent fault diagnosis for photovoltaic systems proposed by Hsieh et al., this study proposed a chaotic extension fault diagnosis method combined with error back propagation neural network to overcome this problem. It used the nn toolbox of matlab 2010 for simulation and comparison, measured current irradiance and temperature, and used the maximum power point tracking (MPPT for chaotic extraction of eigenvalue. The range of extension field was determined by neural network. Finally, the voltage eigenvalue obtained from current temperature and irradiance was used for the fault diagnosis. Comparing the diagnostic rates with the results by Hsieh et al., this scheme can obtain better diagnostic rates when the irradiances or the temperatures are changed.

  4. Optimizing the MAC Protocol in Localization Systems Based on IEEE 802.15.4 Networks.

    Science.gov (United States)

    Pérez-Solano, Juan J; Claver, Jose M; Ezpeleta, Santiago

    2017-07-06

    Radio frequency signals are commonly used in the development of indoor localization systems. The infrastructure of these systems includes some beacons placed at known positions that exchange radio packets with users to be located. When the system is implemented using wireless sensor networks, the wireless transceivers integrated in the network motes are usually based on the IEEE 802.15.4 standard. But, the CSMA-CA, which is the basis for the medium access protocols in this category of communication systems, is not suitable when several users want to exchange bursts of radio packets with the same beacon to acquire the radio signal strength indicator (RSSI) values needed in the location process. Therefore, new protocols are necessary to avoid the packet collisions that appear when multiple users try to communicate with the same beacons. On the other hand, the RSSI sampling process should be carried out very quickly because some systems cannot tolerate a large delay in the location process. This is even more important when the RSSI sampling process includes measures with different signal power levels or frequency channels. The principal objective of this work is to speed up the RSSI sampling process in indoor localization systems. To achieve this objective, the main contribution is the proposal of a new MAC protocol that eliminates the medium access contention periods and decreases the number of packet collisions to accelerate the RSSI collection process. Moreover, the protocol increases the overall network throughput taking advantage of the frequency channel diversity. The presented results show the suitability of this protocol for reducing the RSSI gathering delay and increasing the network throughput in simulated and real environments.

  5. Optimizing the MAC Protocol in Localization Systems Based on IEEE 802.15.4 Networks

    Directory of Open Access Journals (Sweden)

    Juan J. Pérez-Solano

    2017-07-01

    Full Text Available Radio frequency signals are commonly used in the development of indoor localization systems. The infrastructure of these systems includes some beacons placed at known positions that exchange radio packets with users to be located. When the system is implemented using wireless sensor networks, the wireless transceivers integrated in the network motes are usually based on the IEEE 802.15.4 standard. But, the CSMA-CA, which is the basis for the medium access protocols in this category of communication systems, is not suitable when several users want to exchange bursts of radio packets with the same beacon to acquire the radio signal strength indicator (RSSI values needed in the location process. Therefore, new protocols are necessary to avoid the packet collisions that appear when multiple users try to communicate with the same beacons. On the other hand, the RSSI sampling process should be carried out very quickly because some systems cannot tolerate a large delay in the location process. This is even more important when the RSSI sampling process includes measures with different signal power levels or frequency channels. The principal objective of this work is to speed up the RSSI sampling process in indoor localization systems. To achieve this objective, the main contribution is the proposal of a new MAC protocol that eliminates the medium access contention periods and decreases the number of packet collisions to accelerate the RSSI collection process. Moreover, the protocol increases the overall network throughput taking advantage of the frequency channel diversity. The presented results show the suitability of this protocol for reducing the RSSI gathering delay and increasing the network throughput in simulated and real environments.

  6. A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments.

    Science.gov (United States)

    Sivasamy, Aneetha Avalappampatty; Sundan, Bose

    2015-01-01

    The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T(2) method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T(2) statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.

  7. A Novel Distributed Privacy Paradigm for Visual Sensor Networks Based on Sharing Dynamical Systems

    Directory of Open Access Journals (Sweden)

    Takis Zourntos

    2007-01-01

    Full Text Available Visual sensor networks (VSNs provide surveillance images/video which must be protected from eavesdropping and tampering en route to the base station. In the spirit of sensor networks, we propose a novel paradigm for securing privacy and confidentiality in a distributed manner. Our paradigm is based on the control of dynamical systems, which we show is well suited for VSNs due to its low complexity in terms of processing and communication, while achieving robustness to both unintentional noise and intentional attacks as long as a small subset of nodes are affected. We also present a low complexity algorithm called TANGRAM to demonstrate the feasibility of applying our novel paradigm to VSNs. We present and discuss simulation results of TANGRAM.

  8. A Parallel Strategy for Convolutional Neural Network Based on Heterogeneous Cluster for Mobile Information System

    Directory of Open Access Journals (Sweden)

    Jilin Zhang

    2017-01-01

    Full Text Available With the development of the mobile systems, we gain a lot of benefits and convenience by leveraging mobile devices; at the same time, the information gathered by smartphones, such as location and environment, is also valuable for business to provide more intelligent services for customers. More and more machine learning methods have been used in the field of mobile information systems to study user behavior and classify usage patterns, especially convolutional neural network. With the increasing of model training parameters and data scale, the traditional single machine training method cannot meet the requirements of time complexity in practical application scenarios. The current training framework often uses simple data parallel or model parallel method to speed up the training process, which is why heterogeneous computing resources have not been fully utilized. To solve these problems, our paper proposes a delay synchronization convolutional neural network parallel strategy, which leverages the heterogeneous system. The strategy is based on both synchronous parallel and asynchronous parallel approaches; the model training process can reduce the dependence on the heterogeneous architecture in the premise of ensuring the model convergence, so the convolution neural network framework is more adaptive to different heterogeneous system environments. The experimental results show that the proposed delay synchronization strategy can achieve at least three times the speedup compared to the traditional data parallelism.

  9. Software-based microwave CT system consisting of antennas and vector network analyzer.

    Science.gov (United States)

    Ogawa, Takahiro; Miyakawa, Michio

    2011-01-01

    We have developed a software-based microwave CT (SMCT) that consists of antennas and a vector network analyzer. Regardless of the scanner type, SMCT collects the S-parameters at each measurement position in the frequency range of interest. After collecting all the S-parameters, it calculates the shortest path to obtain the projection data for CPMCT. Because of the redundant data in SMCT, the calculation of the projection is easily optimized. Therefore, the system can improve the accuracy and stability of the measurement. Furthermore, the experimental system is constructed at a reasonable cost. Hence, SMCT is useful for imaging experiments for CP-MCT and particularly for basic studies. This paper describes the software-based microwave imaging system, and experimental results show the usefulness of the system.

  10. Wireless sensor network-based greenhouse environment monitoring and automatic control system for dew condensation prevention.

    Science.gov (United States)

    Park, Dae-Heon; Park, Jang-Woo

    2011-01-01

    Dew condensation on the leaf surface of greenhouse crops can promote diseases caused by fungus and bacteria, affecting the growth of the crops. In this paper, we present a WSN (Wireless Sensor Network)-based automatic monitoring system to prevent dew condensation in a greenhouse environment. The system is composed of sensor nodes for collecting data, base nodes for processing collected data, relay nodes for driving devices for adjusting the environment inside greenhouse and an environment server for data storage and processing. Using the Barenbrug formula for calculating the dew point on the leaves, this system is realized to prevent dew condensation phenomena on the crop's surface acting as an important element for prevention of diseases infections. We also constructed a physical model resembling the typical greenhouse in order to verify the performance of our system with regard to dew condensation control.

  11. Cloud networking understanding cloud-based data center networks

    CERN Document Server

    Lee, Gary

    2014-01-01

    Cloud Networking: Understanding Cloud-Based Data Center Networks explains the evolution of established networking technologies into distributed, cloud-based networks. Starting with an overview of cloud technologies, the book explains how cloud data center networks leverage distributed systems for network virtualization, storage networking, and software-defined networking. The author offers insider perspective to key components that make a cloud network possible such as switch fabric technology and data center networking standards. The final chapters look ahead to developments in architectures

  12. Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks.

    Science.gov (United States)

    Taniguchi, Yoshiaki; Tsutsumi, Hiroaki; Iguchi, Nobukazu; Watanabe, Kenzi

    2016-01-01

    Software-Defined Networking (SDN) has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator's configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.

  13. Design and Evaluation of a Proxy-Based Monitoring System for OpenFlow Networks

    Directory of Open Access Journals (Sweden)

    Yoshiaki Taniguchi

    2016-01-01

    Full Text Available Software-Defined Networking (SDN has attracted attention along with the popularization of cloud environment and server virtualization. In SDN, the control plane and the data plane are decoupled so that the logical topology and routing control can be configured dynamically depending on network conditions. To obtain network conditions precisely, a network monitoring mechanism is necessary. In this paper, we focus on OpenFlow which is a core technology to realize SDN. We propose, design, implement, and evaluate a network monitoring system for OpenFlow networks. Our proposed system acts as a proxy between an OpenFlow controller and OpenFlow switches. Through experimental evaluations, we confirm that our proposed system can capture packets and monitor traffic information depending on administrator’s configuration. In addition, we show that our proposed system does not influence significant performance degradation to overall network performance.

  14. VERIFICATION OF GRAPHEMES USING NEURAL NETWORKS IN AN HMM­BASED ON­LINE KOREAN HANDWRITING RECOGNITION SYSTEM

    NARCIS (Netherlands)

    So, S.J.; Kim, J.; Kim, J.H.

    2004-01-01

    This paper presents a neural network based verification method in an HMM­based on­line Korean handwriting recognition system. It penalizes unreasonable grapheme hypotheses and complements global and structural information to the HMM­based recognition system, which is intrinsically based on local

  15. A distributed monitoring system for photovoltaic arrays based on a two-level wireless sensor network

    Science.gov (United States)

    Su, F. P.; Chen, Z. C.; Zhou, H. F.; Wu, L. J.; Lin, P. J.; Cheng, S. Y.; Li, Y. F.

    2017-11-01

    In this paper, a distributed on-line monitoring system based on a two-level wireless sensor network (WSN) is proposed for real time status monitoring of photovoltaic (PV) arrays to support the fine management and maintenance of PV power plants. The system includes the sensing nodes installed on PV modules (PVM), sensing and routing nodes installed on combiner boxes of PV sub-arrays (PVA), a sink node and a data management centre (DMC) running on a host computer. The first level WSN is implemented by the low-cost wireless transceiver nRF24L01, and it is used to achieve single hop communication between the PVM nodes and their corresponding PVA nodes. The second level WSN is realized by the CC2530 based ZigBee network for multi-hop communication among PVA nodes and the sink node. The PVM nodes are used to monitor the PVM working voltage and backplane temperature, and they send the acquired data to their PVA node via the nRF24L01 based first level WSN. The PVA nodes are used to monitor the array voltage, PV string current and environment irradiance, and they send the acquired and received data to the DMC via the ZigBee based second level WSN. The DMC is designed using the MATLAB GUIDE and MySQL database. Laboratory experiment results show that the system can effectively acquire, display, store and manage the operating and environment parameters of PVA in real time.

  16. A new approach for sizing stand alone photovoltaic systems based in neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Hontoria, L.; Aguilera, J. [Universidad de Jaen, Dept. de Electronica, Jaen (Spain); Zufiria, P. [UPM Ciudad Universitaria, Dept. de Matematica Aplicada a las Tecnologias de la Informacion, Madrid (Spain)

    2005-02-01

    Several methods for sizing stand alone photovoltaic (pv) systems has been developed. The more simplistic are called intuitive methods. They are a useful tool for a first approach in sizing stand alone photovoltaic systems. Nevertheless they are very inaccurate. Analytical methods use equations to describe the pv system size as a function of reliability. These ones are more accurate than the previous ones but they are also not accurate enough for sizing of high reliability. In a third group there are methods which use system simulations. These ones are called numerical methods. Many of the analytical methods employ the concept of reliability of the system or the complementary term: loss of load probability (LOLP). In this paper an improvement for obtaining LOLP curves based on the neural network called Multilayer Perceptron (MLP) is presented. A unique MLP for many locations of Spain has been trained and after the training, the MLP is able to generate LOLP curves for any value and location. (Author)

  17. Control Method of Single-phase Inverter Based Grounding System in Distribution Networks

    DEFF Research Database (Denmark)

    Wang, Wen; Yan, L.; Zeng, X.

    2016-01-01

    The asymmetry of the inherent distributed capacitances causes the rise of neutral-to-ground voltage in ungrounded system or high resistance grounded system. Overvoltage may occur in resonant grounded system if Petersen coil is resonant with the distributed capacitances. Thus, the restraint...... of neutral-to-ground voltage is critical for the safety of distribution networks. An active grounding system based on single-phase inverter is proposed to achieve this objective. Relationship between output current of the system and neutral-to-ground voltage is derived to explain the principle of neutral-to-ground...... voltage compensation. Then, a current control method consisting of proportional resonant (PR) and proportional integral (PI) with capacitive current feedback is then proposed to guarantee sufficient output current accuracy and stability margin subjecting to large range of load change. The performance...

  18. Remote System Update for System on Programmable Chip Based on Controller Area Network

    Directory of Open Access Journals (Sweden)

    Lei Zhou

    2017-06-01

    Full Text Available In some application domains, using a download cable to update the system on a programmable chip (SoPC is infeasible, which reduces the maintainability and flexibility of the system. Hence the remote system update (RSU scheme is being studied. In this scheme, the serial configuration (EPCS device involves a factory mode configuration image, which acts as the baseline, and an application mode configuration image, which is used for some specific functions. Specifically, a new application mode image is delivered through the controller area network (CAN with the improved application layer protocol. Besides, the data flow and data check for transmitting a new image are constructed to combine the transmission reliability with efficiency. The boot sequence copying hardware configuration code and software configuration code is analyzed, and the advanced boot loader is carried out to specify boot address of the application mode image manually. Experiments have demonstrated the feasibility of updating and running a new application mode image, as well as rolling back into the factory mode image when no application mode image is available. This scheme applies a single CAN bus, which makes the system easy to construct and suitable for the field distributed control system.

  19. A Novel Secure IoT-Based Smart Home Automation System Using a Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Sandeep Pirbhulal

    2016-12-01

    Full Text Available Wireless sensor networks (WSNs provide noteworthy benefits over traditional approaches for several applications, including smart homes, healthcare, environmental monitoring, and homeland security. WSNs are integrated with the Internet Protocol (IP to develop the Internet of Things (IoT for connecting everyday life objects to the internet. Hence, major challenges of WSNs include: (i how to efficiently utilize small size and low-power nodes to implement security during data transmission among several sensor nodes; (ii how to resolve security issues associated with the harsh and complex environmental conditions during data transmission over a long coverage range. In this study, a secure IoT-based smart home automation system was developed. To facilitate energy-efficient data encryption, a method namely Triangle Based Security Algorithm (TBSA based on efficient key generation mechanism was proposed. The proposed TBSA in integration of the low power Wi-Fi were included in WSNs with the Internet to develop a novel IoT-based smart home which could provide secure data transmission among several associated sensor nodes in the network over a long converge range. The developed IoT based system has outstanding performance by fulfilling all the necessary security requirements. The experimental results showed that the proposed TBSA algorithm consumed less energy in comparison with some existing methods.

  20. A Novel Secure IoT-Based Smart Home Automation System Using a Wireless Sensor Network.

    Science.gov (United States)

    Pirbhulal, Sandeep; Zhang, Heye; E Alahi, Md Eshrat; Ghayvat, Hemant; Mukhopadhyay, Subhas Chandra; Zhang, Yuan-Ting; Wu, Wanqing

    2016-12-30

    Wireless sensor networks (WSNs) provide noteworthy benefits over traditional approaches for several applications, including smart homes, healthcare, environmental monitoring, and homeland security. WSNs are integrated with the Internet Protocol (IP) to develop the Internet of Things (IoT) for connecting everyday life objects to the internet. Hence, major challenges of WSNs include: (i) how to efficiently utilize small size and low-power nodes to implement security during data transmission among several sensor nodes; (ii) how to resolve security issues associated with the harsh and complex environmental conditions during data transmission over a long coverage range. In this study, a secure IoT-based smart home automation system was developed. To facilitate energy-efficient data encryption, a method namely Triangle Based Security Algorithm (TBSA) based on efficient key generation mechanism was proposed. The proposed TBSA in integration of the low power Wi-Fi were included in WSNs with the Internet to develop a novel IoT-based smart home which could provide secure data transmission among several associated sensor nodes in the network over a long converge range. The developed IoT based system has outstanding performance by fulfilling all the necessary security requirements. The experimental results showed that the proposed TBSA algorithm consumed less energy in comparison with some existing methods.

  1. Design and Implementation of e-Health System Based on Semantic Sensor Network Using IETF YANG.

    Science.gov (United States)

    Jin, Wenquan; Kim, Do Hyeun

    2018-02-20

    Recently, healthcare services can be delivered effectively to patients anytime and anywhere using e-Health systems. e-Health systems are developed through Information and Communication Technologies (ICT) that involve sensors, mobiles, and web-based applications for the delivery of healthcare services and information. Remote healthcare is an important purpose of the e-Health system. Usually, the eHealth system includes heterogeneous sensors from diverse manufacturers producing data in different formats. Device interoperability and data normalization is a challenging task that needs research attention. Several solutions are proposed in the literature based on manual interpretation through explicit programming. However, programmatically implementing the interpretation of the data sender and data receiver in the e-Health system for the data transmission is counterproductive as modification will be required for each new device added into the system. In this paper, an e-Health system with the Semantic Sensor Network (SSN) is proposed to address the device interoperability issue. In the proposed system, we have used IETF YANG for modeling the semantic e-Health data to represent the information of e-Health sensors. This modeling scheme helps in provisioning semantic interoperability between devices and expressing the sensing data in a user-friendly manner. For this purpose, we have developed an ontology for e-Health data that supports different styles of data formats. The ontology is defined in YANG for provisioning semantic interpretation of sensing data in the system by constructing meta-models of e-Health sensors. The proposed approach assists in the auto-configuration of eHealth sensors and querying the sensor network with semantic interoperability support for the e-Health system.

  2. Design and Implementation of e-Health System Based on Semantic Sensor Network Using IETF YANG

    Directory of Open Access Journals (Sweden)

    Wenquan Jin

    2018-02-01

    Full Text Available Recently, healthcare services can be delivered effectively to patients anytime and anywhere using e-Health systems. e-Health systems are developed through Information and Communication Technologies (ICT that involve sensors, mobiles, and web-based applications for the delivery of healthcare services and information. Remote healthcare is an important purpose of the e-Health system. Usually, the eHealth system includes heterogeneous sensors from diverse manufacturers producing data in different formats. Device interoperability and data normalization is a challenging task that needs research attention. Several solutions are proposed in the literature based on manual interpretation through explicit programming. However, programmatically implementing the interpretation of the data sender and data receiver in the e-Health system for the data transmission is counterproductive as modification will be required for each new device added into the system. In this paper, an e-Health system with the Semantic Sensor Network (SSN is proposed to address the device interoperability issue. In the proposed system, we have used IETF YANG for modeling the semantic e-Health data to represent the information of e-Health sensors. This modeling scheme helps in provisioning semantic interoperability between devices and expressing the sensing data in a user-friendly manner. For this purpose, we have developed an ontology for e-Health data that supports different styles of data formats. The ontology is defined in YANG for provisioning semantic interpretation of sensing data in the system by constructing meta-models of e-Health sensors. The proposed approach assists in the auto-configuration of eHealth sensors and querying the sensor network with semantic interoperability support for the e-Health system.

  3. Neural Network based Control of SG based Standalone Generating System with Energy Storage for Power Quality Enhancement

    Science.gov (United States)

    Nayar, Priya; Singh, Bhim; Mishra, Sukumar

    2017-08-01

    An artificial intelligence based control algorithm is used in solving power quality problems of a diesel engine driven synchronous generator with automatic voltage regulator and governor based standalone system. A voltage source converter integrated with a battery energy storage system is employed to mitigate the power quality problems. An adaptive neural network based signed regressor control algorithm is used for the estimation of the fundamental component of load currents for control of a standalone system with load leveling as an integral feature. The developed model of the system performs accurately under varying load conditions and provides good dynamic response to the step changes in loads. The real time performance is achieved using MATLAB along with simulink/simpower system toolboxes and results adhere to an IEEE-519 standard for power quality enhancement.

  4. 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...

  5. Wireless Sensor Network Operating System Design Rules Based on Real-World Deployment Survey

    Directory of Open Access Journals (Sweden)

    Leo Selavo

    2013-08-01

    Full Text Available Wireless sensor networks (WSNs have been a widely researched field since the beginning of the 21st century. The field is already maturing, and TinyOS has established itself as the de facto standard WSN Operating System (OS. However, the WSN researcher community is still active in building more flexible, efficient and user-friendly WSN operating systems. Often, WSN OS design is based either on practical requirements of a particular research project or research group's needs or on theoretical assumptions spread in the WSN community. The goal of this paper is to propose WSN OS design rules that are based on a thorough survey of 40 WSN deployments. The survey unveils trends of WSN applications and provides empirical substantiation to support widely usable and flexible WSN operating system design.

  6. Integrated System Based on Wireless Sensors Network for Cardiac Arrhythmia Monitoring

    Directory of Open Access Journals (Sweden)

    ROTARIU, C.

    2013-02-01

    Full Text Available This paper describes the research carried out for designing and producing an integrated system for monitoring patients suffering from cardiac arrhythmias. Our system is based on a wireless sensors network (WSN and can be used in hospital or at home. It is able to measure and transmit the patient's heart rate (HR by radio to a central telemonitoring station. The HR is continuously computed from the electrocardiographic signals using custom developed devices. These devices are attached to the patient and are based on low power microcontrollers and wireless transceivers. The data is uploaded through WSN on the central telemonitoring station. The software running on the telemonitoring station receives the HRs from monitored patients through WSN, displays them as temporal waveforms and activates the alerts when HR arrhythmia is detected. An experimental system for cardiac arrhythmia has been designed, implemented and tested.

  7. An Improved Green Energy Granary Monitoring System Based on Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Bin Wang

    2014-10-01

    Full Text Available In the study of granary monitoring, many research projects are involved in environmental monitoring in recent years. However, most existing studies are interested in the outdoor natural environment monitoring. Few of them focus on the indoor monitoring. This paper presents a system based on wireless sensor network (WSN for granary monitoring including grain temperature and humidity. The whole system adopts sensors DS18B20 to measure the granary temperature, DHT11 to measure humidity, and the data is processed by transceiver CC2530, which is a true system-on-chip (SoC solution for IEEE 802.15.4 applications. To deal with energy consumption problems effectively, the scheme of solar battery board is proposed in order to produce a kind of clean and renewable energy. In addition to showing the temperature and humidity monitoring and alarm mechanism, the system can set up or modify the working parameters through keywords at control terminals. The overall system architecture is described in detail. What is more, the network deployment and wireless communication protocol etc. are introduced. Experimental results in actual granary show that the proposed new system is convenient, efficient, and correct.

  8. Non-Contact Plant Growth Measurement Method and System Based on Ubiquitous Sensor Network Technologies

    Directory of Open Access Journals (Sweden)

    Intae Ryoo

    2011-04-01

    Full Text Available This paper proposes a non-contact plant growth measurement system using infrared sensors based on the ubiquitous sensor network (USN technology. The proposed system measures plant growth parameters such as the stem radius of plants using real-time non-contact methods, and generates diameter, cross-sectional area and thickening form of plant stems using this measured data. Non-contact sensors have been used not to cause any damage to plants during measurement of the growth parameters. Once the growth parameters are measured, they are transmitted to a remote server using the sensor network technology and analyzed in the application program server. The analyzed data are then provided for administrators and a group of interested users. The proposed plant growth measurement system has been designed and implemented using fixed-type and rotary-type infrared sensor based measurement methods and devices. Finally, the system performance is compared and verified with the measurement data that have been obtained by practical field experiments.

  9. Non-Contact Plant Growth Measurement Method and System Based on Ubiquitous Sensor Network Technologies

    Science.gov (United States)

    Suk, Jinweon; Kim, Seokhoon; Ryoo, Intae

    2011-01-01

    This paper proposes a non-contact plant growth measurement system using infrared sensors based on the ubiquitous sensor network (USN) technology. The proposed system measures plant growth parameters such as the stem radius of plants using real-time non-contact methods, and generates diameter, cross-sectional area and thickening form of plant stems using this measured data. Non-contact sensors have been used not to cause any damage to plants during measurement of the growth parameters. Once the growth parameters are measured, they are transmitted to a remote server using the sensor network technology and analyzed in the application program server. The analyzed data are then provided for administrators and a group of interested users. The proposed plant growth measurement system has been designed and implemented using fixed-type and rotary-type infrared sensor based measurement methods and devices. Finally, the system performance is compared and verified with the measurement data that have been obtained by practical field experiments. PMID:22163849

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

    Science.gov (United States)

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

    2010-01-01

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

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

    Science.gov (United States)

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

    2010-01-01

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

  12. Stabilization of Networked Distributed Systems with Partial and Event-Based Couplings

    Directory of Open Access Journals (Sweden)

    Sufang Zhang

    2015-01-01

    Full Text Available The stabilization problem of networked distributed systems with partial and event-based couplings is investigated. The channels, which are used to transmit different levels of information of agents, are considered. The channel matrix is introduced to indicate the work state of the channels. An event condition is designed for each channel to govern the sampling instants of the channel. Since the event conditions are separately given for different channels, the sampling instants of channels are mutually independent. To stabilize the system, the state feedback controllers are implemented in the system. The control signals also suffer from the two communication constraints. The sufficient conditions in terms of linear matrix equalities are proposed to ensure the stabilization of the controlled system. Finally, a numerical example is given to demonstrate the advantage of our results.

  13. Ground Control Point - Wireless System Network for UAV-based environmental monitoring applications

    Science.gov (United States)

    Mejia-Aguilar, Abraham

    2016-04-01

    In recent years, Unmanned Aerial Vehicles (UAV) have seen widespread civil applications including usage for survey and monitoring services in areas such as agriculture, construction and civil engineering, private surveillance and reconnaissance services and cultural heritage management. Most aerial monitoring services require the integration of information acquired during the flight (such as imagery) with ground-based information (such as GPS information or others) for improved ground truth validation. For example, to obtain an accurate 3D and Digital Elevation Model based on aerial imagery, it is necessary to include ground-based information of coordinate points, which are normally acquired with surveying methods based on Global Position Systems (GPS). However, GPS surveys are very time consuming and especially for longer time series of monitoring data repeated GPS surveys are necessary. In order to improve speed of data collection and integration, this work presents an autonomous system based on Waspmote technologies build on single nodes interlinked in a Wireless Sensor Network (WSN) star-topology for ground based information collection and later integration with surveying data obtained by UAV. Nodes are designed to be visible from the air, to resist extreme weather conditions with low-power consumption. Besides, nodes are equipped with GPS as well as Inertial Measurement Unit (IMU), accelerometer, temperature and soil moisture sensors and thus provide significant advantages in a broad range of applications for environmental monitoring. For our purpose, the WSN transmits the environmental data with 3G/GPRS to a database on a regular time basis. This project provides a detailed case study and implementation of a Ground Control Point System Network for UAV-based vegetation monitoring of dry mountain grassland in the Matsch valley, Italy.

  14. VA Suicide Prevention Applications Network: A National Health Care System-Based Suicide Event Tracking System.

    Science.gov (United States)

    Hoffmire, Claire; Stephens, Brady; Morley, Sybil; Thompson, Caitlin; Kemp, Janet; Bossarte, Robert M

    2016-11-01

    The US Department of Veterans Affairs' Suicide Prevention Applications Network (SPAN) is a national system for suicide event tracking and case management. The objective of this study was to assess data on suicide attempts among people using Veterans Health Administration (VHA) services. We assessed the degree of data overlap on suicide attempters reported in SPAN and the VHA's medical records from October 1, 2010, to September 30, 2014-overall, by year, and by region. Data on suicide attempters in the VHA's medical records consisted of diagnoses documented with E95 codes from the International Classification of Diseases, Ninth Revision. Of 50 518 VHA patients who attempted suicide during the 4-year study period, data on fewer than half (41%) were reported in both SPAN and the medical records; nearly 65% of patients whose suicide attempt was recorded in SPAN had no data on attempted suicide in the VHA's medical records. Evaluation of administrative data suggests that use of SPAN substantially increases the collection of data on suicide attempters as compared with the use of medical records alone, but neither SPAN nor the VHA's medical records identify all suicide attempters. Further research is needed to better understand the strengths and limitations of both systems and how to best combine information across systems.

  15. Computer network defense system

    Science.gov (United States)

    Urias, Vincent; Stout, William M. S.; Loverro, Caleb

    2017-08-22

    A method and apparatus for protecting virtual machines. A computer system creates a copy of a group of the virtual machines in an operating network in a deception network to form a group of cloned virtual machines in the deception network when the group of the virtual machines is accessed by an adversary. The computer system creates an emulation of components from the operating network in the deception network. The components are accessible by the group of the cloned virtual machines as if the group of the cloned virtual machines was in the operating network. The computer system moves network connections for the group of the virtual machines in the operating network used by the adversary from the group of the virtual machines in the operating network to the group of the cloned virtual machines, enabling protecting the group of the virtual machines from actions performed by the adversary.

  16. Point-Cloud Compression for Vehicle-Based Mobile Mapping Systems Using Portable Network Graphics

    Science.gov (United States)

    Kohira, K.; Masuda, H.

    2017-09-01

    A mobile mapping system is effective for capturing dense point-clouds of roads and roadside objects Point-clouds of urban areas, residential areas, and arterial roads are useful for maintenance of infrastructure, map creation, and automatic driving. However, the data size of point-clouds measured in large areas is enormously large. A large storage capacity is required to store such point-clouds, and heavy loads will be taken on network if point-clouds are transferred through the network. Therefore, it is desirable to reduce data sizes of point-clouds without deterioration of quality. In this research, we propose a novel point-cloud compression method for vehicle-based mobile mapping systems. In our compression method, point-clouds are mapped onto 2D pixels using GPS time and the parameters of the laser scanner. Then, the images are encoded in the Portable Networking Graphics (PNG) format and compressed using the PNG algorithm. In our experiments, our method could efficiently compress point-clouds without deteriorating the quality.

  17. Evaluation of a "Smart" Pedestrian Counting System Based on Echo State Networks

    Directory of Open Access Journals (Sweden)

    Poigné Axel

    2009-01-01

    Full Text Available Abstract We have designed an inexpensive intelligent pedestrian counting system. The pedestrian counting system consists of several counters that can be connected together in a distributed fashion and communicate over the wireless channel. The motion pattern is recorded using a set of passive infrared (PIR sensors. Each counter has one wireless sensor node that processes the PIR sensor data and transmits it to a base station. Then echo state network, a special kind of recurrent neural network, is used to predict the pedestrian count from the input pattern. The evaluation of the performance of such networks in a novel kind of application is one focus of this work. The counter gave a performance of 80.4% which is better than the commercially available low-priced pedestrian counters. The article reports the experiments we did for analyzing the counterperformance and lists the strengths and limitations of the current implementation. It will also report the preliminary test results obtained by substituting the PIR sensors with low-cost active IR distance sensors which can improve the counter performance further.

  18. Fuzzy Based Advanced Hybrid Intrusion Detection System to Detect Malicious Nodes in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Rupinder Singh

    2017-01-01

    Full Text Available In this paper, an Advanced Hybrid Intrusion Detection System (AHIDS that automatically detects the WSNs attacks is proposed. AHIDS makes use of cluster-based architecture with enhanced LEACH protocol that intends to reduce the level of energy consumption by the sensor nodes. AHIDS uses anomaly detection and misuse detection based on fuzzy rule sets along with the Multilayer Perceptron Neural Network. The Feed Forward Neural Network along with the Backpropagation Neural Network are utilized to integrate the detection results and indicate the different types of attackers (i.e., Sybil attack, wormhole attack, and hello flood attack. For detection of Sybil attack, Advanced Sybil Attack Detection Algorithm is developed while the detection of wormhole attack is done by Wormhole Resistant Hybrid Technique. The detection of hello flood attack is done by using signal strength and distance. An experimental analysis is carried out in a set of nodes; 13.33% of the nodes are determined as misbehaving nodes, which classified attackers along with a detection rate of the true positive rate and false positive rate. Sybil attack is detected at a rate of 99,40%; hello flood attack has a detection rate of 98, 20%; and wormhole attack has a detection rate of 99, 20%.

  19. A Multiobjective Fuzzy Inference System based Deployment Strategy for a Distributed Mobile Sensor Network

    Directory of Open Access Journals (Sweden)

    Amol P. Bhondekar

    2010-03-01

    Full Text Available Sensor deployment scheme highly governs the effectiveness of distributed wireless sensor network. Issues such as energy conservation and clustering make the deployment problem much more complex. A multiobjective Fuzzy Inference System based strategy for mobile sensor deployment is presented in this paper. This strategy gives a synergistic combination of energy capacity, clustering and peer-to-peer deployment. Performance of our strategy is evaluated in terms of coverage, uniformity, speed and clustering. Our algorithm is compared against a modified distributed self-spreading algorithm to exhibit better performance.

  20. An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

    Science.gov (United States)

    Butun, Ismail; Ra, In-Ho; Sankar, Ravi

    2015-01-01

    In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) “upward-IDS (U-IDS)” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. PMID:26593915

  1. An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks.

    Science.gov (United States)

    Butun, Ismail; Ra, In-Ho; Sankar, Ravi

    2015-11-17

    In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) "downward-IDS (D-IDS)" to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) "upward-IDS (U-IDS)" to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented.

  2. An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ismail Butun

    2015-11-01

    Full Text Available In this work, an intrusion detection system (IDS framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1 “downward-IDS (D-IDS” to detect the abnormal behavior (intrusion of the subordinate (member nodes; and (2 “upward-IDS (U-IDS” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops and U-IDS (monitoring group size of the framework are evaluated and presented.

  3. Network Security Risk Assessment System Based on Attack Graph and Markov Chain

    Science.gov (United States)

    Sun, Fuxiong; Pi, Juntao; Lv, Jin; Cao, Tian

    2017-10-01

    Network security risk assessment technology can be found in advance of the network problems and related vulnerabilities, it has become an important means to solve the problem of network security. Based on attack graph and Markov chain, this paper provides a Network Security Risk Assessment Model (NSRAM). Based on the network infiltration tests, NSRAM generates the attack graph by the breadth traversal algorithm. Combines with the international standard CVSS, the attack probability of atomic nodes are counted, and then the attack transition probabilities of ones are calculated by Markov chain. NSRAM selects the optimal attack path after comprehensive measurement to assessment network security risk. The simulation results show that NSRAM can reflect the actual situation of network security objectively.

  4. An Agent-Based Intrusion Detection System for Local Area Networks

    National Research Council Canada - National Science Library

    Jaydip Sen

    2010-01-01

    Since it is impossible to predict and identify all the vulnerabilities of a network beforehand, and penetration into a system by malicious intruders cannot always be prevented, intrusion detection systems (IDSs...

  5. WiSPH: A Wireless Sensor Network-Based Home Care Monitoring System

    Directory of Open Access Journals (Sweden)

    Pedro Magaña-Espinoza

    2014-04-01

    Full Text Available This paper presents a system based on WSN technology capable of monitoring heart rate and the rate of motion of seniors within their homes. The system is capable of remotely alerting specialists, caretakers or family members via a smartphone of rapid physiological changes due to falls, tachycardia or bradycardia. This work was carried out using our workgroup’s WiSe platform, which we previously developed for use in WSNs. The proposed WSN architecture is flexible, allowing for greater scalability to better allow event-based monitoring. The architecture also provides security mechanisms to assure that the monitored and/or stored data can only be accessed by authorized individuals or devices. The aforementioned characteristics provide the network versatility and solidity required for use in health applications.

  6. Low Power 24 GHz ad hoc Networking System Based on TDOA for Indoor Localization

    Directory of Open Access Journals (Sweden)

    Melanie Jung

    2013-12-01

    Full Text Available This paper introduces the key elements of a novel low-power, high precision localization system based on Time-Difference-of-Arrival (TDOA distance measurements. The combination of multiple localizable sensor nodes, leads to an ad hoc network. Besides the localization functionality this ad hoc network has the additional advantage of a communication interface. Due to this a flexible positioning of the master station for information collection and the detection of static and mobile nodes is possible. These sensor nodes work in the 24 GHz ISM (Industrial Scientific and Medical frequency range and address several use cases and are able to improve various processes for production scheduling, logistics, quality management, medical applications and collection of geo information. The whole system design is explained briefly. Its core component is the frequency modulated continuous wave (FMCW synthesizer suitable for high performance indoor localization. This research work focuses on power and size reduction of this crucial system component. The comparison of the first and second generation of the system shows a significant size and power reduction as well as an increased precision.

  7. A mobile network-based multimedia teleconference system for homecare services.

    Science.gov (United States)

    Zhang, Zhaomin; He, Aiguo; Wei, Daming

    2008-03-01

    Because most research and development for homecare services have focused on providing connections between home and service centers, the goal of the present work is to develop techniques and create realtime communications to connect service centers and homecare workers in mobile environments. A key technical issue for this research is how to overcome the limitation of bandwidth in mobile media and networks. An effort has been made to balance performance of communication and basic demands in telehealth through optimized system design and technical implementation. Implementations using third generation (3G) Freedom Of Mobile multimedia Access (FOMA) and Personal Handyphone System (PHS) were developed and evaluated. We conclude that the system we developed based on 3G FOMA provides sufficient and satisfactory functions for use in homecare services.

  8. ARTIFICIAL NEURAL NETWORK BASED ULTRASONIC SENSOR SYSTEM FOR DETECTION OF ADULTERATION IN EDIBLE OIL

    Directory of Open Access Journals (Sweden)

    TONY GEORGE

    2017-06-01

    Full Text Available This paper presents the design, development and experimental validation of an ultrasonic sensor system for the detection of adulteration in edible oil. Variation of ultrasonic wave propagation characteristics like attenuation coefficient, reflection coefficient and velocity of propagation in pure and adulterated oil were used for developing the algorithm to detect the adulteration. Measurement cell was designed for operating ultrasonic transducer at 1 MHz using COMSOL 4.4. Artificial Neural Network (ANN based algorithm was also developed for improving the efficiency of the sensor system. It is found that this system can detect adulteration with an accuracy of 99.53% for sunflower oil added in pure coconut oil, whereas 98.82% for palm oil added in pure coconut oil.

  9. Model-based design of self-Adapting networked signal processing systems

    NARCIS (Netherlands)

    Oliveira Filho, J.A. de; Papp, Z.; Djapic, R.; Oostveen, J.C.

    2013-01-01

    The paper describes a model based approach for architecture design of runtime reconfigurable, large-scale, networked signal processing applications. A graph based modeling formalism is introduced to describe all relevant aspects of the design (functional, concurrency, hardware, communication,

  10. Development of a Ground-Based Atmospheric Monitoring Network for the Global Mercury Observation System (GMOS

    Directory of Open Access Journals (Sweden)

    Sprovieri F.

    2013-04-01

    Full Text Available Consistent, high-quality measurements of atmospheric mercury (Hg are necessary in order to better understand Hg emissions, transport, and deposition on a global scale. Although the number of atmospheric Hg monitoring stations has increased in recent years, the available measurement database is limited and there are many regions of the world where measurements have not been extensively performed. Long-term atmospheric Hg monitoring and additional ground-based monitoring sites are needed in order to generate datasets that will offer new insight and information about the global scale trends of atmospheric Hg emissions and deposition. In the framework of the Global Mercury Observation System (GMOS project, a coordinated global observational network for atmospheric Hg is being established. The overall research strategy of GMOS is to develop a state-of-the-art observation system able to provide information on the concentration of Hg species in ambient air and precipitation on the global scale. This network is being developed by integrating previously established ground-based atmospheric Hg monitoring stations with newly established GMOS sites that are located both at high altitude and sea level locations, as well as in climatically diverse regions. Through the collection of consistent, high-quality atmospheric Hg measurement data, we seek to create a comprehensive assessment of atmospheric Hg concentrations and their dependence on meteorology, long-range atmospheric transport and atmospheric emissions.

  11. A Diagnostic System for Improving Biomass Quality Based on a Sensor Network

    Directory of Open Access Journals (Sweden)

    Claus G. Sørensen

    2011-05-01

    Full Text Available Losses during storage of biomass are the main parameter that defines the profitability of using preserved biomass as feed for animal husbandry. In order to minimize storage losses, potential changes in specific physicochemical properties must be identified to subsequently act as indicators of silage decomposition and form the basis for preventive measures. This study presents a framework for a diagnostic system capable of detecting potential changes in specific physicochemical properties, i.e., temperature and the oxygen content, during the biomass storage process. The diagnostic system comprises a monitoring tool based on a wireless sensors network and a prediction tool based on a validated computation fluid dynamics model. It is shown that the system can provide the manager (end-user with continuously updated information about specific biomass quality parameters. The system encompasses graphical visualization of the information to the end-user as a first step and, as a second step, the system identifies alerts depicting real differences between actual and predicted values of the monitored properties. The perspective is that this diagnostic system will provide managers with a solid basis for necessary preventive measures.

  12. Design of a water environment monitoring system based on wireless sensor networks.

    Science.gov (United States)

    Jiang, Peng; Xia, Hongbo; He, Zhiye; Wang, Zheming

    2009-01-01

    A water environmental monitoring system based on a wireless sensor network is proposed. It consists of three parts: data monitoring nodes, data base station and remote monitoring center. This system is suitable for the complex and large-scale water environment monitoring, such as for reservoirs, lakes, rivers, swamps, and shallow or deep groundwaters. This paper is devoted to the explanation and illustration for our new water environment monitoring system design. The system had successfully accomplished the online auto-monitoring of the water temperature and pH value environment of an artificial lake. The system's measurement capacity ranges from 0 to 80 °C for water temperature, with an accuracy of ±0.5 °C; from 0 to 14 on pH value, with an accuracy of ±0.05 pH units. Sensors applicable to different water quality scenarios should be installed at the nodes to meet the monitoring demands for a variety of water environments and to obtain different parameters. The monitoring system thus promises broad applicability prospects.

  13. A Network Intrusions Detection System based on a Quantum Bio Inspired Algorithm

    OpenAIRE

    Soliman, Omar S.; Rassem, Aliaa

    2014-01-01

    Network intrusion detection systems (NIDSs) have a role of identifying malicious activities by monitoring the behavior of networks. Due to the currently high volume of networks trafic in addition to the increased number of attacks and their dynamic properties, NIDSs have the challenge of improving their classification performance. Bio-Inspired Optimization Algorithms (BIOs) are used to automatically extract the the discrimination rules of normal or abnormal behavior to improve the classificat...

  14. A Network Based Theory of Health Systems and Cycles of Well-being.

    Science.gov (United States)

    Rhodes, Michael Grant

    2013-06-01

    There are two dominant approaches to describe and understand the anatomy of complete health and well-being systems internationally. Yet, neither approach has been able to either predict or explain occasional but dramatic crises in health and well-being systems around the world and in developed emerging market or developing country contexts. As the impacts of such events can be measured not simply in terms of their social and economic consequences but also public health crises, there is a clear need to look for and formulate an alternative approach. This paper examines multi-disciplinary theoretical evidence to suggest that health systems exhibit natural and observable systemic and long cycle characteristics that can be modelled. A health and well-being system model of two slowly evolving anthropological network sub-systems is defined. The first network sub-system consists of organised professional networks of exclusive suppliers of health and well-being services. The second network sub-system consists of communities organising themselves to resource those exclusive services. Together these two network sub-systems interact to form the specific (sovereign) health and well-being systems we know today. But the core of a truly 'complex adaptive system' can also be identified and a simplified two sub-system model of recurring Lotka-Volterra predator-prey cycles is specified. The implications of such an adaptive and evolving model of system anatomy for effective public health, social security insurance and well-being systems governance could be considerable.

  15. Optimization of steel casting feeding system based on BP neural network and genetic algorithm

    Directory of Open Access Journals (Sweden)

    Xue-dan Gong

    2016-05-01

    Full Text Available The trial-and-error method is widely used for the current optimization of the steel casting feeding system, which is highly random, subjective and thus inefficient. In the present work, both the theoretical and the experimental research on the modeling and optimization methods of the process are studied. An approximate alternative model is established based on the Back Propagation (BP neural network and experimental design. The process parameters of the feeding system are taken as the input, the volumes of shrinkage cavities and porosities calculated by simulation are simultaneously taken as the output. Thus, a mathematical model is established by the BP neural network to combine the input variables with the output response. Then, this model is optimized by the nonlinear optimization function of the genetic algorithm. Finally, a feeding system optimization of a steel traveling wheel is conducted. No shrinkage cavities and porosities are induced through the optimization. Compared to the initial design scheme, the process yield is increased by 4.1% and the volume of the riser is decreased by 5.48×106 mm3.

  16. Prediction of microRNAs involved in immune system diseases through network based features.

    Science.gov (United States)

    Prabahar, Archana; Natarajan, Jeyakumar

    2017-01-01

    MicroRNAs are a class of small non-coding regulatory RNA molecules that modulate the expression of several genes at post-transcriptional level and play a vital role in disease pathogenesis. Recent research shows that a range of miRNAs are involved in the regulation of immunity and its deregulation results in immune mediated diseases such as cancer, inflammation and autoimmune diseases. Computational discovery of these immune miRNAs using a set of specific features is highly desirable. In the current investigation, we present a SVM based classification system which uses a set of novel network based topological and motif features in addition to the baseline sequential and structural features to predict immune specific miRNAs from other non-immune miRNAs. The classifier was trained and tested on a balanced set of equal number of positive and negative examples to show the discriminative power of our network features. Experimental results show that our approach achieves an accuracy of 90.2% and outperforms the classification accuracy of 63.2% reported using the traditional miRNA sequential and structural features. The proposed classifier was further validated with two immune disease sub-class datasets related to multiple sclerosis microarray data and psoriasis RNA-seq data with higher accuracy. These results indicate that our classifier which uses network and motif features along with sequential and structural features will lead to significant improvement in classifying immune miRNAs and hence can be applied to identify other specific classes of miRNAs as an extensible miRNA classification system. Copyright © 2016 Elsevier Inc. All rights reserved.

  17. A Hypergraph and Arithmetic Residue-based Probabilistic Neural Network for classification in Intrusion Detection Systems.

    Science.gov (United States)

    Raman, M R Gauthama; Somu, Nivethitha; Kirthivasan, Kannan; Sriram, V S Shankar

    2017-08-01

    Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous efforts by the researchers have resulted in the development of several learning models based on Artificial Neural Network (ANN) to improve the performance of the IDSs. However, there exists a tradeoff with respect to the stability of ANN architecture and the detection rate for less frequent attacks. This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS. The Helly property of Hypergraph was exploited for the identification of the optimal feature subset and the arithmetic residue of the optimal feature subset was used to train the PNN. The performance of HG AR-PNN was evaluated using KDD CUP 1999 intrusion dataset. Experimental results prove the dominance of HG AR-PNN classifier over the existing classifiers with respect to the stability and improved detection rate for less frequent attacks. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Phoenix: A Collaborative Location-Based Notification System for Mobile Networks

    Directory of Open Access Journals (Sweden)

    Yongping Xiong

    2014-01-01

    Full Text Available Location-based notification (LBN aims to alert the users in a target area to their interested information. With a wide range of applications, LBN has been gaining more and more attraction among wireless users and service providers. The mainstream centralized solution based on cellular networks may incur high service cost. In this paper, we present an innovative scheme called Phoenix, which does not rely on any infrastructure, to implement location-based notification service. In our design, devices (users across the target area form a dynamic peer-to-peer network, where a user can be a message source, a message carrier, or a message subscriber. When a user meets the message carrier, he will get a copy of the message. Phoenix keeps messages of interest being circulated in the target area; hence users are being notified. To achieve desired notification performance, Phoenix adaptively controls when a user should take the carrier role and help disseminating a message in order to keep the message “alive,” given the fact that message carriers may leave the target area and drop the message. Extensive simulations have been conducted to show the efficacy of Phoenix notification system.

  19. An Unobtrusive Fall Detection and Alerting System Based on Kalman Filter and Bayes Network Classifier.

    Science.gov (United States)

    He, Jian; Bai, Shuang; Wang, Xiaoyi

    2017-06-16

    Falls are one of the main health risks among the elderly. A fall detection system based on inertial sensors can automatically detect fall event and alert a caregiver for immediate assistance, so as to reduce injuries causing by falls. Nevertheless, most inertial sensor-based fall detection technologies have focused on the accuracy of detection while neglecting quantization noise caused by inertial sensor. In this paper, an activity model based on tri-axial acceleration and gyroscope is proposed, and the difference between activities of daily living (ADLs) and falls is analyzed. Meanwhile, a Kalman filter is proposed to preprocess the raw data so as to reduce noise. A sliding window and Bayes network classifier are introduced to develop a wearable fall detection system, which is composed of a wearable motion sensor and a smart phone. The experiment shows that the proposed system distinguishes simulated falls from ADLs with a high accuracy of 95.67%, while sensitivity and specificity are 99.0% and 95.0%, respectively. Furthermore, the smart phone can issue an alarm to caregivers so as to provide timely and accurate help for the elderly, as soon as the system detects a fall.

  20. Artificial neural networks: Principle and application to model based control of drying systems -- A review

    Energy Technology Data Exchange (ETDEWEB)

    Thyagarajan, T.; Ponnavaikko, M. [Crescent Engineering Coll., Madras (India); Shanmugam, J. [Madras Inst. of Tech. (India); Panda, R.C.; Rao, P.G. [Central Leather Research Inst., Madras (India)

    1998-07-01

    This paper reviews the developments in the model based control of drying systems using Artificial Neural Networks (ANNs). Survey of current research works reveals the growing interest in the application of ANN in modeling and control of non-linear, dynamic and time-variant systems. Over 115 articles published in this area are reviewed. All landmark papers are systematically classified in chronological order, in three distinct categories; namely, conventional feedback controllers, model based controllers using conventional methods and model based controllers using ANN for drying process. The principles of ANN are presented in detail. The problems and issues of the drying system and the features of various ANN models are dealt with up-to-date. ANN based controllers lead to smoother controller outputs, which would increase actuator life. The paper concludes with suggestions for improving the existing modeling techniques as applied to predicting the performance characteristics of dryers. The hybridization techniques, namely, neural with fuzzy logic and genetic algorithms, presented, provide, directions for pursuing further research for the implementation of appropriate control strategies. The authors opine that the information presented here would be highly beneficial for pursuing research in modeling and control of drying process using ANN. 118 refs.

  1. Simulation-based Modeling Frameworks for Networked Multi-processor System-on-Chip

    DEFF Research Database (Denmark)

    Mahadevan, Shankar

    2006-01-01

    This thesis deals with modeling aspects of multi-processor system-on-chip (MpSoC) design affected by the on-chip interconnect, also called the Network-on-Chip (NoC), at various levels of abstraction. To begin with, we undertook a comprehensive survey of research and design practices of networked Mp......: namely ARTS and RIPE, that allows to model hardware (computation time, power consumption, network latency, caching effect, etc.) and software (application partition and mapping, operating system scheduling, interrupt handling, etc.) aspects from system-level to cycle-true abstraction. Thereby, we can...

  2. Network operating system

    Science.gov (United States)

    1985-01-01

    Long-term and short-term objectives for the development of a network operating system for the Space Station are stated. The short-term objective is to develop a prototype network operating system for a 100 megabit/second fiber optic data bus. The long-term objective is to establish guidelines for writing a detailed specification for a Space Station network operating system. Major milestones are noted. Information is given in outline form.

  3. Avoiding Message-Dependent Deadlock in Network-Based Systems on Chip

    NARCIS (Netherlands)

    Hansson, A.; Goossens, K.; Rãdulescu, A.

    2007-01-01

    Networks on chip (NoCs) are an essential component of systems on chip (SoCs) and much research is devoted to deadlock avoidance in NoCs. Prior work focuses on the router network while protocol interactions between NoC and intellectual property (IP) modules are not considered. These interactions

  4. Nitrate leaching from a potato field using adaptive network-based fuzzy inference system

    DEFF Research Database (Denmark)

    Shekofteh, Hosein; Afyuni, Majid M; Hajabbasi, Mohammad-Ali

    2013-01-01

    The conventional methods of application of nitrogen fertilizers might be responsible for the increased nitrate concentration in groundwater of areas dominated by irrigated agriculture. Appropriate water and nutrient management strategies are required to minimize groundwater pollution...... of nitrate (NO3) leaching from a potato field under a drip fertigation system. In the first part of the study, a two-dimensional solute transport model was used to simulate nitrate leaching from a sandy soil with varying emitter discharge rates and fertilizer doses. The results from the modeling were used...... to train and validate an adaptive network-based fuzzy inference system (ANFIS) in order to estimate nitrate leaching. Two performance functions, namely mean absolute percentage error (MAPE) and correlation coefficient (R), were used to evaluate the adequacy of the ANFIS. Results showed that ANFIS can...

  5. A Real-Time Monitoring System of Industry Carbon Monoxide Based on Wireless Sensor Networks.

    Science.gov (United States)

    Yang, Jiachen; Zhou, Jianxiong; Lv, Zhihan; Wei, Wei; Song, Houbing

    2015-11-20

    Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire CO concentration reliably, and a digital filtering method is adopted for noise filtering. According to the triangulation, the Wifi network is constructed to transmit information and determine the position of nodes. The measured data are displayed on a computer or smart phone by a graphical interface. The experiment shows that the monitoring system obtains excellent accuracy and stability in long-term continuous monitoring.

  6. PM2.5 monitoring system based on ZigBee wireless sensor network

    Science.gov (United States)

    Lin, Lukai; Li, Xiangshun; Gu, Weiying

    2017-06-01

    In the view of the haze problem, aiming at improving the deficiency of the traditional PM2.5 monitoring methods, such as the insufficient real-time monitoring, limited transmission distance, high cost and the difficulty to maintain, the atmosphere PM2.5 monitoring system based on ZigBee technology is designed. The system combines the advantages of ZigBee’s low cost, low power consumption, high reliability and GPRS/Internet’s capability of remote transmission of data. Furthermore, it adopts TI’s Z-Stack protocol stack, and selects CC2530 chip and TI’s MSP430 microcontroller as the core, which establishes the air pollution monitoring network that is helpful for the early prediction of major air pollution disasters.

  7. Domain management OSSs: bridging the gap between legacy and standards-based network management systems

    Science.gov (United States)

    Lemley, Todd A.

    1996-11-01

    The rapid change in the telecommunications environment is forcing carriers to re-assess not only their service offering, but also their network management philosophy. The competitive carrier environment has taken away the luxury of throwing technology at a problem by using legacy and proprietary systems and architectures. A more flexible management environment is necessary to effectively gain, and maintain operating margins in the new market era. Competitive forces are driving change which gives carriers more choices than those that are available in legacy and standards-based solutions alone. However, creating an operational support system (OSS) with this gap between legacy and standards has become as dynamic as the services which it supports. A philosophy which helps to integrate the legacy and standards systems is domain management. Domain management relates to a specific service or market 'domain,'and its associated operational support requirements. It supports a companies definition of its business model, which drives the definition of each domain. It also attempts to maximize current investment while injecting new technology available in a practical approach. The following paragraphs offer an overview of legacy systems, standards-based philosophy, and the potential of domain management to help bridge the gap between the two types of systems.

  8. Fuzzy Chance-constrained Programming Based Security Information Optimization for Low Probability of Identification Enhancement in Radar Network Systems

    Directory of Open Access Journals (Sweden)

    C. G. Shi

    2015-04-01

    Full Text Available In this paper, the problem of low probability of identification (LPID improvement for radar network systems is investigated. Firstly, the security information is derived to evaluate the LPID performance for radar network. Then, without any prior knowledge of hostile intercept receiver, a novel fuzzy chance-constrained programming (FCCP based security information optimization scheme is presented to achieve enhanced LPID performance in radar network systems, which focuses on minimizing the achievable mutual information (MI at interceptor, while the attainable MI outage probability at radar network is enforced to be greater than a specified confidence level. Regarding to the complexity and uncertainty of electromagnetic environment in the modern battlefield, the trapezoidal fuzzy number is used to describe the threshold of achievable MI at radar network based on the credibility theory. Finally, the FCCP model is transformed to a crisp equivalent form with the property of trapezoidal fuzzy number. Numerical simulation results demonstrating the performance of the proposed strategy are provided.

  9. A Comparative Experimental Design and Performance Analysis of Snort-Based Intrusion Detection System in Practical Computer Networks

    Directory of Open Access Journals (Sweden)

    Imdadul Karim

    2017-02-01

    Full Text Available As one of the most reliable technologies, network intrusion detection system (NIDS allows the monitoring of incoming and outgoing traffic to identify unauthorised usage and mishandling of attackers in computer network systems. To this extent, this paper investigates the experimental performance of Snort-based NIDS (S-NIDS in a practical network with the latest technology in various network scenarios including high data speed and/or heavy traffic and/or large packet size. An effective testbed is designed based on Snort using different muti-core processors, e.g., i5 and i7, with different operating systems, e.g., Windows 7, Windows Server and Linux. Furthermore, considering an enterprise network consisting of multiple virtual local area networks (VLANs, a centralised parallel S-NIDS (CPS-NIDS is proposed with the support of a centralised database server to deal with high data speed and heavy traffic. Experimental evaluation is carried out for each network configuration to evaluate the performance of the S-NIDS in different network scenarios as well as validating the effectiveness of the proposed CPS-NIDS. In particular, by analysing packet analysis efficiency, an improved performance of up to 10% is shown to be achieved with Linux over other operating systems, while up to 8% of improved performance can be achieved with i7 over i5 processors.

  10. Quorum system and random based asynchronous rendezvous protocol for cognitive radio ad hoc networks

    Directory of Open Access Journals (Sweden)

    Sylwia Romaszko

    2013-12-01

    Full Text Available This paper proposes a rendezvous protocol for cognitive radio ad hoc networks, RAC2E-gQS, which utilizes (1 the asynchronous and randomness properties of the RAC2E protocol, and (2 channel mapping protocol, based on a grid Quorum System (gQS, and taking into account channel heterogeneity and asymmetric channel views. We show that the combination of the RAC2E protocol with the grid-quorum based channel mapping can yield a powerful RAC2E-gQS rendezvous protocol for asynchronous operation in a distributed environment assuring a rapid rendezvous between the cognitive radio nodes having available both symmetric and asymmetric channel views. We also propose an enhancement of the protocol, which uses a torus QS for a slot allocation, dealing with the worst case scenario, a large number of channels with opposite ranking lists.

  11. First Steps Toward Incorporating Image Based Diagnostics Into Particle Accelerator Control Systems Using Convolutional Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Edelen, A. L.; Biedron, S. G.; Milton, S. V.; Edelen, J. P.

    2016-12-16

    At present, a variety of image-based diagnostics are used in particle accelerator systems. Often times, these are viewed by a human operator who then makes appropriate adjustments to the machine. Given recent advances in using convolutional neural networks (CNNs) for image processing, it should be possible to use image diagnostics directly in control routines (NN-based or otherwise). This is especially appealing for non-intercepting diagnostics that could run continuously during beam operation. Here, we show results of a first step toward implementing such a controller: our trained CNN can predict multiple simulated downstream beam parameters at the Fermilab Accelerator Science and Technology (FAST) facility's low energy beamline using simulated virtual cathode laser images, gun phases, and solenoid strengths.

  12. A Base Component for Network-Based Service-Oriented C4ISR Systems

    Science.gov (United States)

    2005-12-01

    access service. The main components of the service are given by two software modules, called front-end manager and service manager . A front-end...user, or by means of some installation wizard which downloads the most recent version from a designated network site. A service manager can be thought...of as a mediator between a front-end manager on the one hand and a set of network services on the other hand. A service manager is created by a

  13. System Error Compensation Methodology Based on a Neural Network for a Micromachined Inertial Measurement Unit

    Directory of Open Access Journals (Sweden)

    Shi Qiang Liu

    2016-01-01

    Full Text Available Errors compensation of micromachined-inertial-measurement-units (MIMU is essential in practical applications. This paper presents a new compensation method using a neural-network-based identification for MIMU, which capably solves the universal problems of cross-coupling, misalignment, eccentricity, and other deterministic errors existing in a three-dimensional integrated system. Using a neural network to model a complex multivariate and nonlinear coupling system, the errors could be readily compensated through a comprehensive calibration. In this paper, we also present a thermal-gas MIMU based on thermal expansion, which measures three-axis angular rates and three-axis accelerations using only three thermal-gas inertial sensors, each of which capably measures one-axis angular rate and one-axis acceleration simultaneously in one chip. The developed MIMU (100 × 100 × 100 mm3 possesses the advantages of simple structure, high shock resistance, and large measuring ranges (three-axes angular rates of ±4000°/s and three-axes accelerations of ±10 g compared with conventional MIMU, due to using gas medium instead of mechanical proof mass as the key moving and sensing elements. However, the gas MIMU suffers from cross-coupling effects, which corrupt the system accuracy. The proposed compensation method is, therefore, applied to compensate the system errors of the MIMU. Experiments validate the effectiveness of the compensation, and the measurement errors of three-axis angular rates and three-axis accelerations are reduced to less than 1% and 3% of uncompensated errors in the rotation range of ±600°/s and the acceleration range of ±1 g, respectively.

  14. System Error Compensation Methodology Based on a Neural Network for a Micromachined Inertial Measurement Unit.

    Science.gov (United States)

    Liu, Shi Qiang; Zhu, Rong

    2016-01-29

    Errors compensation of micromachined-inertial-measurement-units (MIMU) is essential in practical applications. This paper presents a new compensation method using a neural-network-based identification for MIMU, which capably solves the universal problems of cross-coupling, misalignment, eccentricity, and other deterministic errors existing in a three-dimensional integrated system. Using a neural network to model a complex multivariate and nonlinear coupling system, the errors could be readily compensated through a comprehensive calibration. In this paper, we also present a thermal-gas MIMU based on thermal expansion, which measures three-axis angular rates and three-axis accelerations using only three thermal-gas inertial sensors, each of which capably measures one-axis angular rate and one-axis acceleration simultaneously in one chip. The developed MIMU (100 × 100 × 100 mm³) possesses the advantages of simple structure, high shock resistance, and large measuring ranges (three-axes angular rates of ±4000°/s and three-axes accelerations of ± 10 g) compared with conventional MIMU, due to using gas medium instead of mechanical proof mass as the key moving and sensing elements. However, the gas MIMU suffers from cross-coupling effects, which corrupt the system accuracy. The proposed compensation method is, therefore, applied to compensate the system errors of the MIMU. Experiments validate the effectiveness of the compensation, and the measurement errors of three-axis angular rates and three-axis accelerations are reduced to less than 1% and 3% of uncompensated errors in the rotation range of ±600°/s and the acceleration range of ± 1 g, respectively.

  15. Asynchronous control for networked systems

    CERN Document Server

    Rubio, Francisco; Bencomo, Sebastián

    2015-01-01

    This book sheds light on networked control systems; it describes different techniques for asynchronous control, moving away from the periodic actions of classical control, replacing them with state-based decisions and reducing the frequency with which communication between subsystems is required. The text focuses specially on event-based control. Split into two parts, Asynchronous Control for Networked Systems begins by addressing the problems of single-loop networked control systems, laying out various solutions which include two alternative model-based control schemes (anticipatory and predictive) and the use of H2/H∞ robust control to deal with network delays and packet losses. Results on self-triggering and send-on-delta sampling are presented to reduce the need for feedback in the loop. In Part II, the authors present solutions for distributed estimation and control. They deal first with reliable networks and then extend their results to scenarios in which delays and packet losses may occur. The novel ...

  16. Stability analysis and compensation of network-induced delays in communication-based power system control: A survey.

    Science.gov (United States)

    Liu, Shichao; Liu, Peter Xiaoping; Wang, Xiaoyu

    2017-01-01

    This survey is to summarize and compare existing and recently emerging approaches for the analysis and compensation of the effects of network-induced delays on the stability and performance of communication-based power control systems. Several important communication-based power control systems are briefly introduced. The deterministic and stochastic methodologies of analyzing the impacts of network-induced delays on the stability of the communication-based power control systems are summarized and compared. A variety of control approaches are reviewed and compared for mitigating the effects of network-induced delays, depending on several design requirements, such as model dependence and design difficulty. The summary and comparison of these control approaches in this survey provide researchers and utilities valuable guidance for designing advanced communication-based power control systems in the future. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Design of the smart home system based on the optimal routing algorithm and ZigBee network

    Science.gov (United States)

    Xie, Xiaoxia

    2017-01-01

    To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system. PMID:29131868

  18. Design of the smart home system based on the optimal routing algorithm and ZigBee network.

    Science.gov (United States)

    Jiang, Dengying; Yu, Ling; Wang, Fei; Xie, Xiaoxia; Yu, Yongsheng

    2017-01-01

    To improve the traditional smart home system, its electric wiring, networking technology, information transmission and facility control are studied. In this paper, we study the electric wiring, networking technology, information transmission and facility control to improve the traditional smart home system. First, ZigBee is used to replace the traditional electric wiring. Second, a network is built to connect lots of wireless sensors and facilities, thanks to the capability of ZigBee self-organized network and Genetic Algorithm-Particle Swarm Optimization Algorithm (GA-PSOA) to search for the optimal route. Finally, when the smart home system is connected to the internet based on the remote server technology, home environment and facilities could be remote real-time controlled. The experiments show that the GA-PSOA reduce the system delay and decrease the energy consumption of the wireless system.

  19. An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network.

    Science.gov (United States)

    Taboun, Mohammed S; Brennan, Robert W

    2017-09-14

    With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

  20. An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Mohammed S. Taboun

    2017-09-01

    Full Text Available With the emergence of cyber-physical systems, there has been a growing interest in network-connected devices. One of the key requirements of a cyber-physical device is the ability to sense its environment. Wireless sensor networks are a widely-accepted solution for this requirement. In this study, an embedded multi-agent systems-managed wireless sensor network is presented. A novel architecture is proposed, along with a novel wireless sensor network architecture. Active and passive wireless sensor node types are defined, along with their communication protocols, and two application-specific examples are presented. A series of three experiments is conducted to evaluate the performance of the agent-embedded wireless sensor network.

  1. Network-based Type-2 Fuzzy System with Water Flow Like Algorithm for System Identification and Signal Processing

    Directory of Open Access Journals (Sweden)

    Che-Ting Kuo

    2015-02-01

    Full Text Available This paper introduces a network-based interval type-2 fuzzy inference system (NT2FIS with a dynamic solution agent algorithm water flow like algorithm (WFA, for nonlinear system identification and blind source separation (BSS problem. The NT2FIS consists of interval type-2 asymmetric fuzzy membership functions and TSK-type consequent parts to enhance the performance. The proposed scheme is optimized by a new heuristic learning algorithm, WFA, with dynamic solution agents. The proposed WFA is inspired by the natural behavior of water flow. Splitting, moving, merging, evaporation, and precipitation have all been introduced for optimization. Some modifications, including new moving strategies, such as the application of tabu searching and gradient-descent techniques, are proposed to enhance the performance of the WFA in training the NT2FIS systems. Simulation and comparison results for nonlinear system identification and blind signal separation are presented to illustrate the performance and effectiveness of the proposed approach.

  2. Data systems and computer science: Neural networks base R/T program overview

    Science.gov (United States)

    Gulati, Sandeep

    1991-01-01

    The research base, in the U.S. and abroad, for the development of neural network technology is discussed. The technical objectives are to develop and demonstrate adaptive, neural information processing concepts. The leveraging of external funding is also discussed.

  3. Risk and Resilience Analysis of Complex Network Systems Considering Cascading Failure and Recovery Strategy Based on Coupled Map Lattices

    Directory of Open Access Journals (Sweden)

    Fuchun Ren

    2015-01-01

    Full Text Available Risk and resilience are important and challenging issues in complex network systems since a single failure may trigger a whole collapse of the systems due to cascading effect. New theories, models, and methods are urgently demanded to deal with this challenge. In this paper, a coupled map lattices (CML based approach is adopted to analyze the risk of cascading process in Watts-Strogatz (WS small-world network and Barabási and Albert (BA scale-free network, respectively. Then, to achieve an effective and robust system and provide guidance in countering the cascading failure, a modified CML model with recovery strategy factor is proposed. Numerical simulations are put forward based on small-world CML and scale-free CML. The simulation results reveal that appropriate recovery strategies would significantly improve the resilience of networks.

  4. Risk and Resilience Analysis of Complex Network Systems Considering Cascading Failure and Recovery Strategy Based on Coupled Map Lattices

    OpenAIRE

    Fuchun Ren; Tingdi Zhao; Hongli Wang

    2015-01-01

    Risk and resilience are important and challenging issues in complex network systems since a single failure may trigger a whole collapse of the systems due to cascading effect. New theories, models, and methods are urgently demanded to deal with this challenge. In this paper, a coupled map lattices (CML) based approach is adopted to analyze the risk of cascading process in Watts-Strogatz (WS) small-world network and Barabási and Albert (BA) scale-free network, respectively. Then, to achieve an...

  5. Reverse engineering Boolean networks: from Bernoulli mixture models to rule based systems.

    Science.gov (United States)

    Saeed, Mehreen; Ijaz, Maliha; Javed, Kashif; Babri, Haroon Atique

    2012-01-01

    A Boolean network is a graphical model for representing and analyzing the behavior of gene regulatory networks (GRN). In this context, the accurate and efficient reconstruction of a Boolean network is essential for understanding the gene regulation mechanism and the complex relations that exist therein. In this paper we introduce an elegant and efficient algorithm for the reverse engineering of Boolean networks from a time series of multivariate binary data corresponding to gene expression data. We call our method ReBMM, i.e., reverse engineering based on Bernoulli mixture models. The time complexity of most of the existing reverse engineering techniques is quite high and depends upon the indegree of a node in the network. Due to the high complexity of these methods, they can only be applied to sparsely connected networks of small sizes. ReBMM has a time complexity factor, which is independent of the indegree of a node and is quadratic in the number of nodes in the network, a big improvement over other techniques and yet there is little or no compromise in accuracy. We have tested ReBMM on a number of artificial datasets along with simulated data derived from a plant signaling network. We also used this method to reconstruct a network from real experimental observations of microarray data of the yeast cell cycle. Our method provides a natural framework for generating rules from a probabilistic model. It is simple, intuitive and illustrates excellent empirical results.

  6. Neural feedback linearization adaptive control for affine nonlinear systems based on neural network estimator

    Directory of Open Access Journals (Sweden)

    Bahita Mohamed

    2011-01-01

    Full Text Available In this work, we introduce an adaptive neural network controller for a class of nonlinear systems. The approach uses two Radial Basis Functions, RBF networks. The first RBF network is used to approximate the ideal control law which cannot be implemented since the dynamics of the system are unknown. The second RBF network is used for on-line estimating the control gain which is a nonlinear and unknown function of the states. The updating laws for the combined estimator and controller are derived through Lyapunov analysis. Asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, the proposed method is applied to control and stabilize the inverted pendulum system.

  7. Adaptive-network-based fuzzy inference system (ANFIS modelbased prediction of the surface ozone concentration

    Directory of Open Access Journals (Sweden)

    Savić Marija

    2014-01-01

    Full Text Available This paper presents the results of the tropospheric ozone concentration modeling as the dependence on volatile organic compounds - VOCs (Benzene, Toluene, m,p-Xylene, o-Xylene, Ethylbenzene; nonorganic compounds - NOx (NO, NO2, NOx, CO, H2S, SO2 and PM10 in the ambient air in parallel with the meteorological parameters: temperature, solar radiation, relative humidity, wind speed and direction. Modeling is based on measured results obtained during the year 2009. The measurements were performed at the measuring station located within an agricultural area, in vicinity of city of Zrenjanin (Serbian Banat, Serbia. Statistical analysis of obtained data, based on bivariate correlation analysis indicated that accurate modeling cannot be performed using linear statistics approach. Also, considering that almost all input variables have wide range of relative change (ratio of variance compared to range, nonlinear statistic analysis method based on only one rule describing the behavior of input variable, most certainly wouldn’t present accurate enough results. From that reason, modeling approach was based on Adaptive-Network-Based Fuzzy Inference System (ANFIS. Model obtained using ANFIS methodology resulted with high accuracy, with prediction potential of above 80%, considering that obtained determination coefficient for the final model was R2=0.802.

  8. Visual evoked potential estimation by adaptive noise cancellation with neural-network-based fuzzy inference system.

    Science.gov (United States)

    Zeng, Y; Zhang, J; Yin, H; Pan, Y

    2007-01-01

    Visual evoked potentials (VEPs) are time-varying signals typically buried in relatively large background noise known as the electroencephalogram (EEG). In this paper, an adaptive noise cancellation with neural network-based fuzzy inference system (NNFIS) was used and the NNFIS was carefully designed to model the VEP signal. It is assumed that VEP responses can be modelled by NNFIS with the centres of its membership functions evenly distributed over time. The weights of NNFIS are adaptively determined by minimizing the variance of the error signal using the least mean squares (LMS) algorithm. As the NNFIS is dynamic to any change of VEP, the non-stationary characteristics of VEP can be tracked. Thus, this method should be able to track the VEP. Four sets of simulated data indicate that the proposed method is appropriate to estimate VEP. A total of 150 trials are processed to demonstrate the superior performance of the proposed method.

  9. A space weather forecasting system with multiple satellites based on a self-recognizing network.

    Science.gov (United States)

    Tokumitsu, Masahiro; Ishida, Yoshiteru

    2014-05-05

    This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV). The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  10. A Space Weather Forecasting System with Multiple Satellites Based on a Self-Recognizing Network

    Directory of Open Access Journals (Sweden)

    Masahiro Tokumitsu

    2014-05-01

    Full Text Available This paper proposes a space weather forecasting system at geostationary orbit for high-energy electron flux (>2 MeV. The forecasting model involves multiple sensors on multiple satellites. The sensors interconnect and evaluate each other to predict future conditions at geostationary orbit. The proposed forecasting model is constructed using a dynamic relational network for sensor diagnosis and event monitoring. The sensors of the proposed model are located at different positions in space. The satellites for solar monitoring equip with monitoring devices for the interplanetary magnetic field and solar wind speed. The satellites orbit near the Earth monitoring high-energy electron flux. We investigate forecasting for typical two examples by comparing the performance of two models with different numbers of sensors. We demonstrate the prediction by the proposed model against coronal mass ejections and a coronal hole. This paper aims to investigate a possibility of space weather forecasting based on the satellite network with in-situ sensing.

  11. Development of a Sensor Network-Based SMPS System: A Smart LED Monitoring Application Based on Wireless Sensor Network

    OpenAIRE

    Yoon Sang Kim; Junho Ko

    2014-01-01

    As the specifications of personal, industrial, and medical devices become increasingly sophisticated, the demand for high power devices is also growing rapidly. Because high power supply devices are needed in order to operate high power devices with high specifications, stability and reliability are important factors to consider when it comes to high power supply devices. Therefore, there have been calls for further research on high quality power supply and monitoring system for high power su...

  12. A wireless sensor network-based ubiquitous paprika growth management system.

    Science.gov (United States)

    Hwang, Jeonghwan; Shin, Changsun; Yoe, Hyun

    2010-01-01

    Wireless Sensor Network (WSN) technology can facilitate advances in productivity, safety and human quality of life through its applications in various industries. In particular, the application of WSN technology to the agricultural area, which is labor-intensive compared to other industries, and in addition is typically lacking in IT technology applications, adds value and can increase the agricultural productivity. This study attempts to establish a ubiquitous agricultural environment and improve the productivity of farms that grow paprika by suggesting a 'Ubiquitous Paprika Greenhouse Management System' using WSN technology. The proposed system can collect and monitor information related to the growth environment of crops outside and inside paprika greenhouses by installing WSN sensors and monitoring images captured by CCTV cameras. In addition, the system provides a paprika greenhouse environment control facility for manual and automatic control from a distance, improves the convenience and productivity of users, and facilitates an optimized environment to grow paprika based on the growth environment data acquired by operating the system.

  13. Reliability Evaluation of a Distribution Network with Microgrid Based on a Combined Power Generation System

    Directory of Open Access Journals (Sweden)

    Hao Bai

    2015-02-01

    Full Text Available Distributed generation (DG, battery storage (BS and electric vehicles (EVs in a microgrid constitute the combined power generation system (CPGS. A CPGS can be applied to achieve a reliable evaluation of a distribution network with microgrids. To model charging load and discharging capacity, respectively, the EVs in a CPGS can be divided into regular EVs and ruleless EVs, according to their driving behavior. Based on statistical data of gasoline-fueled vehicles and the probability distribution of charging start instant and charging time, a statistical model can be built to describe the charging load and discharging capacity of ruleless EVs. The charge and discharge curves of regular EVs can also be drawn on the basis of a daily dispatch table. The CPGS takes the charge and discharge curves of EVs, daily load and DG power generation into consideration to calculate its power supply time during islanding. Combined with fault duration, the power supply time during islanding will be used to analyze and determine the interruption times and interruption duration of loads in islands. Then the Sequential Monte Carlo method is applied to complete the reliability evaluation of the distribution system. The RBTS Bus 4 test system is utilized to illustrate the proposed technique. The effects on the system reliability of BS capacity and V2G technology, driving behavior, recharging mode and penetration of EVs are all investigated.

  14. Complementing ODE-Based System Analysis Using Boolean Networks Derived from an Euler-Like Transformation.

    Directory of Open Access Journals (Sweden)

    Claudia Stötzel

    Full Text Available In this paper, we present a systematic transition scheme for a large class of ordinary differential equations (ODEs into Boolean networks. Our transition scheme can be applied to any system of ODEs whose right hand sides can be written as sums and products of monotone functions. It performs an Euler-like step which uses the signs of the right hand sides to obtain the Boolean update functions for every variable of the corresponding discrete model. The discrete model can, on one hand, be considered as another representation of the biological system or, alternatively, it can be used to further the analysis of the original ODE model. Since the generic transformation method does not guarantee any property conservation, a subsequent validation step is required. Depending on the purpose of the model this step can be based on experimental data or ODE simulations and characteristics. Analysis of the resulting Boolean model, both on its own and in comparison with the ODE model, then allows to investigate system properties not accessible in a purely continuous setting. The method is exemplarily applied to a previously published model of the bovine estrous cycle, which leads to new insights regarding the regulation among the components, and also indicates strongly that the system is tailored to generate stable oscillations.

  15. A Network Based Theory of Health Systems and Cycles of Well-being

    Directory of Open Access Journals (Sweden)

    Michael Grant Rhodes

    2013-01-01

    Full Text Available There are two dominant approaches to describe and understand the anatomy of complete health and well-being systems internationally. Yet, neither approach has been able to either predict or explain occasional but dramatic crises in health and well-being systems around the world and in developed emerging market or developing country contexts. As the impacts of such events can be measured not simply in terms of their social and economic consequences but also public health crises, there is a clear need to look for and formulate an alternative approach. This paper examines multi-disciplinary theoretical evidence to suggest that health systems exhibit natural and observable systemic and long cycle characteristics that can be modelled. A health and well-being system model of two slowly evolving anthropological network sub-systems is defined. The first network sub-system consists of organised professional networks of exclusive suppliers of health and well-being services. The second network sub-system consists of communities organising themselves to resource those exclusive services. Together these two network sub-systems interact to form the specific (sovereign health and well-being systems we know today. But the core of a truly ‘complex adaptive system’ can also be identified and a simplified two sub-system model of recurring Lotka-Volterra predator-prey cycles is specified. The implications of such an adaptive and evolving model of system anatomy for effective public health, social security insurance and well-being systems governance could be considerable.

  16. A cost-effective traffic data collection system based on the iDEN mobile telecommunication network.

    Science.gov (United States)

    2008-10-01

    This report describes a cost-effective data collection system for Caltrans 170 traffic signal : controller. The data collection system is based on TCP/IP communication over existing : low-cost mobile communication networks and Motorola iDEN1 mobile...

  17. A MapReduce Based High Performance Neural Network in Enabling Fast Stability Assessment of Power Systems

    Directory of Open Access Journals (Sweden)

    Yang Liu

    2017-01-01

    Full Text Available Transient stability assessment is playing a vital role in modern power systems. For this purpose, machine learning techniques have been widely employed to find critical conditions and recognize transient behaviors based on massive data analysis. However, an ever increasing volume of data generated from power systems poses a number of challenges to traditional machine learning techniques, which are computationally intensive running on standalone computers. This paper presents a MapReduce based high performance neural network to enable fast stability assessment of power systems. Hadoop, which is an open-source implementation of the MapReduce model, is first employed to parallelize the neural network. The parallel neural network is further enhanced with HaLoop to reduce the computation overhead incurred in the iteration process of the neural network. In addition, ensemble techniques are employed to accommodate the accuracy loss of the parallelized neural network in classification. The parallelized neural network is evaluated with both the IEEE 68-node system and a real power system from the aspects of computation speedup and stability assessment.

  18. [Developing a high quality video transmission system based on mobile network].

    Science.gov (United States)

    Wen, Ming; Hu, Haibo

    2014-01-01

    To meet the demands of high definition of video and transmission at real-time during the surgery of endoscope, this paper designs an HD mobile video transmission system. This system uses H.264/AVC to encode the original video data and transports it in the network by RTP/RTCP protocol. Meanwhile, the system implements a stable video transmission in portable terminals (such as tablet PCs, mobile phones) under the 3G mobile network. The test result verifies the strong repair ability and stability under the conditions of low bandwidth, high packet loss rate, and high delay and shows a high practical value.

  19. Power Electronic Systems for Switched Reluctance Generator based Wind Farms and DC Networks

    DEFF Research Database (Denmark)

    Park, Kiwoo

    . Under these circumstances, research on dc network connection with a novel wind power generator system is presented in this thesis, which mainly consists of two major parts: control of a Switched Reluctance Generator (SRG) system and development of dc-dc converters for a dc network system in a wind farm...... components into the torque reference to compensate the ripples in the actual output torque. The effectiveness and resulting improvement in the performance of both the proposed speed controller and torque minimization technique are demonstrated by simulation results. The modern power electronic interfaces...

  20. A Social Learning Management System Supporting Feedback for Incorrect Answers Based on Social Network Services

    Science.gov (United States)

    Son, Jiseong; Kim, Jeong-Dong; Na, Hong-Seok; Baik, Doo-Kwon

    2016-01-01

    In this research, we propose a Social Learning Management System (SLMS) enabling real-time and reliable feedback for incorrect answers by learners using a social network service (SNS). The proposed system increases the accuracy of learners' assessment results by using a confidence scale and a variety of social feedback that is created and shared…

  1. A neural network-based exploratory learning and motor planning system for co-robots

    Directory of Open Access Journals (Sweden)

    Byron V Galbraith

    2015-07-01

    Full Text Available Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or learning by doing, an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

  2. A neural network-based exploratory learning and motor planning system for co-robots.

    Science.gov (United States)

    Galbraith, Byron V; Guenther, Frank H; Versace, Massimiliano

    2015-01-01

    Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or "learning by doing," an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

  3. Development and Evaluation of a Python Telecare System Based on a Bluetooth Body Area Network

    Directory of Open Access Journals (Sweden)

    Morón MJ

    2011-01-01

    Full Text Available This paper presents a prototype of a telemonitoring system, based on a BAN (Body Area Network that is integrated by a Bluetooth (BT pulse oximeter, a GPS (Global Positioning System unit, and a smartphone. The smartphone is the hardware platform for running a Python software that manages the Bluetooth piconet formed by the sensors. Thus the smartphone forwards the data received from the Bluetooth devices, encoded into JSON (JavaScript Object Notation, to a central server. This server provides universal access to the information of the patient's location and health status through a web application based on AJAX (Asynchronous JavaScript and XML technology. Additionally, for the described prototype, the study presents some performance analyses about several topics that are of great interest for the applicability of the prototype: (i the technique used to forward the patient's location and health status, (ii the power consumption of the smartphone (which is compared with the measurements of an equivalent software developed for Java Micro Edition platform, and (iii the web browser compatibility of the web application developed for the control and monitoring of the patients.

  4. New approach using Bayesian Network to improve content based image classification systems

    OpenAIRE

    jayech, Khlifia; mahjoub, mohamed ali

    2012-01-01

    This paper proposes a new approach based on augmented naive Bayes for image classification. Initially, each image is cutting in a whole of blocks. For each block, we compute a vector of descriptors. Then, we propose to carry out a classification of the vectors of descriptors to build a vector of labels for each image. Finally, we propose three variants of Bayesian Networks such as Naive Bayesian Network (NB), Tree Augmented Naive Bayes (TAN) and Forest Augmented Naive Bayes (FAN) to classify ...

  5. A Wireless Sensor Network-Based Ubiquitous Paprika Growth Management System

    Directory of Open Access Journals (Sweden)

    Jeonghwan Hwang

    2010-12-01

    Full Text Available Wireless Sensor Network (WSN technology can facilitate advances in productivity, safety and human quality of life through its applications in various industries. In particular, the application of WSN technology to the agricultural area, which is labor-intensive compared to other industries, and in addition is typically lacking in IT technology applications, adds value and can increase the agricultural productivity. This study attempts to establish a ubiquitous agricultural environment and improve the productivity of farms that grow paprika by suggesting a ‘Ubiquitous Paprika Greenhouse Management System’ using WSN technology. The proposed system can collect and monitor information related to the growth environment of crops outside and inside paprika greenhouses by installing WSN sensors and monitoring images captured by CCTV cameras. In addition, the system provides a paprika greenhouse environment control facility for manual and automatic control from a distance, improves the convenience and productivity of users, and facilitates an optimized environment to grow paprika based on the growth environment data acquired by operating the system.

  6. A LIGHTNING CONDUCTOR MONITORING SYSTEM BASED ON A WIRELESS SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    Jan Mikeš

    2013-12-01

    Full Text Available Automated heating, lighting and irrigation systems are nowadays standard features of industrial and commercial buildings, and are also increasingly found in ordinary housing. In addition to the benefits of user comfort, automated technology for buildings saves energy and, above all, it provides enhanced protection against leakage of water and hazardous gases, and against fire hazards. Lightning strikes are a natural phenomenon that poses a significant threat to the safety of buildings. The statistics of the Fire and Rescue Service of the Czech Republic show that buildings are in many cases inadequately protected against lightning strikes, or that systems have been damaged by previous strikes. A subsequent strike can occur within the period between regular inspections, which are normally made at intervals of 2–4 years. Over the whole of Europe, thousands of buildings are subjected to the effects of direct lightning strikes each year. This paper presents ways to carry out wireless monitoring of lightning strikes on buildings and to deal with their impact on lightning conductors. By intervening promptly (disconnecting the power supply, disconnecting the gas supply, sending an engineer to inspect the structure, submitting a report to ARC, etc. we can prevent many downstream effects of direct lightning strikes on buildings (fires, electric shocks, etc. This paper introduces a way to enhance contemporary home automation systems for monitoring lightning strikes based on wireless sensor networks technology.

  7. Identification of geomagnetic current systems from a ground-based network

    Science.gov (United States)

    Pereira, F.; Dudok de Wit, T.; Menvielle, M.

    2003-04-01

    The Earth's total magnetic field is a superposition of magnetic fields from a variety of sources. At the Earth's surface, the most important source is the internal field produced by currents within the Earth's liquid core. At high latitudes of our planet, magnetopheric and ionospheric current systems are other important sources of magnetic field. A large part of research in geomagnetism is devoted to the identification of these internal and external sources. The separation of current systems from ground-based measurements is a source separation problem. In this study, our approach consists in inferring from a statistical analysis of the data set what are the different contributing source terms. Our analysis will be done by a statistical method known as the Singular Value Decomposition. The SVD is widely used in multivariate analysis for reduction of dimensionality, which offers a more concise description of the observed data and helps to extract significant information from the data. From geomagnetic data provided by the INTERMAGNET global network, the results of the SVD analysis can be interpreted in terms of current systems such as the magnetic field declination, the separation of the auroral electrojets into quiet and intermittent components, the seasonal effects, the ring current signature, the observation of the polar cusp and the cross-tail currents, the displacement of the auroral oval (and even the detection of geomagnetic jerks ?).

  8. A Wireless Sensor Network-Based Ubiquitous Paprika Growth Management System

    Science.gov (United States)

    Hwang, Jeonghwan; Shin, Changsun; Yoe, Hyun

    2010-01-01

    Wireless Sensor Network (WSN) technology can facilitate advances in productivity, safety and human quality of life through its applications in various industries. In particular, the application of WSN technology to the agricultural area, which is labor-intensive compared to other industries, and in addition is typically lacking in IT technology applications, adds value and can increase the agricultural productivity. This study attempts to establish a ubiquitous agricultural environment and improve the productivity of farms that grow paprika by suggesting a ‘Ubiquitous Paprika Greenhouse Management System’ using WSN technology. The proposed system can collect and monitor information related to the growth environment of crops outside and inside paprika greenhouses by installing WSN sensors and monitoring images captured by CCTV cameras. In addition, the system provides a paprika greenhouse environment control facility for manual and automatic control from a distance, improves the convenience and productivity of users, and facilitates an optimized environment to grow paprika based on the growth environment data acquired by operating the system. PMID:22163543

  9. A Survey of System Architecture Requirements for Health Care-Based Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Abraham O. Fapojuwo

    2011-05-01

    Full Text Available Wireless Sensor Networks (WSNs have emerged as a viable technology for a vast number of applications, including health care applications. To best support these health care applications, WSN technology can be adopted for the design of practical Health Care WSNs (HCWSNs that support the key system architecture requirements of reliable communication, node mobility support, multicast technology, energy efficiency, and the timely delivery of data. Work in the literature mostly focuses on the physical design of the HCWSNs (e.g., wearable sensors, in vivo embedded sensors, et cetera. However, work towards enhancing the communication layers (i.e., routing, medium access control, et cetera to improve HCWSN performance is largely lacking. In this paper, the information gleaned from an extensive literature survey is shared in an effort to fortify the knowledge base for the communication aspect of HCWSNs. We highlight the major currently existing prototype HCWSNs and also provide the details of their routing protocol characteristics. We also explore the current state of the art in medium access control (MAC protocols for WSNs, for the purpose of seeking an energy efficient solution that is robust to mobility and delivers data in a timely fashion. Furthermore, we review a number of reliable transport layer protocols, including a network coding based protocol from the literature, that are potentially suitable for delivering end-to-end reliability of data transmitted in HCWSNs. We identify the advantages and disadvantages of the reviewed MAC, routing, and transport layer protocols as they pertain to the design and implementation of a HCWSN. The findings from this literature survey will serve as a useful foundation for designing a reliable HCWSN and also contribute to the development and evaluation of protocols for improving the performance of future HCWSNs. Open issues that required further investigations are highlighted.

  10. A survey of system architecture requirements for health care-based wireless sensor networks.

    Science.gov (United States)

    Egbogah, Emeka E; Fapojuwo, Abraham O

    2011-01-01

    Wireless Sensor Networks (WSNs) have emerged as a viable technology for a vast number of applications, including health care applications. To best support these health care applications, WSN technology can be adopted for the design of practical Health Care WSNs (HCWSNs) that support the key system architecture requirements of reliable communication, node mobility support, multicast technology, energy efficiency, and the timely delivery of data. Work in the literature mostly focuses on the physical design of the HCWSNs (e.g., wearable sensors, in vivo embedded sensors, et cetera). However, work towards enhancing the communication layers (i.e., routing, medium access control, et cetera) to improve HCWSN performance is largely lacking. In this paper, the information gleaned from an extensive literature survey is shared in an effort to fortify the knowledge base for the communication aspect of HCWSNs. We highlight the major currently existing prototype HCWSNs and also provide the details of their routing protocol characteristics. We also explore the current state of the art in medium access control (MAC) protocols for WSNs, for the purpose of seeking an energy efficient solution that is robust to mobility and delivers data in a timely fashion. Furthermore, we review a number of reliable transport layer protocols, including a network coding based protocol from the literature, that are potentially suitable for delivering end-to-end reliability of data transmitted in HCWSNs. We identify the advantages and disadvantages of the reviewed MAC, routing, and transport layer protocols as they pertain to the design and implementation of a HCWSN. The findings from this literature survey will serve as a useful foundation for designing a reliable HCWSN and also contribute to the development and evaluation of protocols for improving the performance of future HCWSNs. Open issues that required further investigations are highlighted.

  11. Energy Efficiency and Network Performance: A Reality Check in SDN-Based 5G Systems

    Directory of Open Access Journals (Sweden)

    Leonardo Ochoa-Aday

    2017-12-01

    Full Text Available The increasing power consumption and related environmental implications currently generated by large data networks have become a major concern over the last decade. Given the drastic traffic increase expected in 5G dense environments, the energy consumption problem becomes even more concerning and challenging. In this context, Software-Defined Networks (SDN, a key technology enabler for 5G systems, can be seen as an attractive solution. In these programmable networks, an energy-aware solution could be easily implemented leveraging the capabilities provided by control and data plane separation. This paper investigates the impact of energy-aware routing on network performance. To that end, we propose a novel energy-aware mechanism that reduces the number of active links in SDN with multiple controllers, considering in-band control traffic. The proposed strategy exploits knowledge of the network topology combined with traffic engineering techniques to reduce the overall power consumption. Therefore, two heuristic algorithms are designed: a static network configuration and a dynamic energy-aware routing. Significant values of switched-off links are reached in the simulations where real topologies and demands data are used. Moreover, the obtained results confirm that crucial network parameters such as control traffic delay, data path latency, link utilization and Ternary Content Addressable Memory (TCAM occupation are affected by the performance-agnostic energy-aware model.

  12. Car-to-Pedestrian Communication Safety System Based on the Vehicular Ad-Hoc Network Environment: A Systematic Review

    Directory of Open Access Journals (Sweden)

    Peng Jing

    2017-10-01

    Full Text Available With the unparalleled growth of motor vehicles, traffic accident between pedestrians and vehicles is one of the most serious issues in the word-wild. Plenty of injuries and fatalities are caused by the traffic accidents and crashes. The connected vehicular ad hoc network as an emerging approach which has the potential to reduce and even avoid accidents have been focused on by many researchers. A large number of car-to-pedestrian communication safety systems based on the vehicular ad hoc network are researching and developing. However, to our limited knowledge, a systematic review about the car-to-pedestrian communication safety system based on the vehicular ad-hoc network has not be written. The purpose and goal of this review is to systematically evaluate and access the reliability of car-to-pedestrian communication safety system based on the vehicular ad-hoc network environment and provide some recommendations for the future works according to throwing some light on the previous literatures. A quality evaluation was developed through established items and instruments tailored to this review. Future works are needed to focus on developing a valid as well as effective communication safety system based on the vehicular ad hoc network to protect the vulnerable road users.

  13. A study on efficient detection of network-based IP spoofing DDoS and malware-infected Systems.

    Science.gov (United States)

    Seo, Jung Woo; Lee, Sang Jin

    2016-01-01

    Large-scale network environments require effective detection and response methods against DDoS attacks. Depending on the advancement of IT infrastructure such as the server or network equipment, DDoS attack traffic arising from a few malware-infected systems capable of crippling the organization's internal network has become a significant threat. This study calculates the frequency of network-based packet attributes and analyzes the anomalies of the attributes in order to detect IP-spoofed DDoS attacks. Also, a method is proposed for the effective detection of malware infection systems triggering IP-spoofed DDoS attacks on an edge network. Detection accuracy and performance of the collected real-time traffic on a core network is analyzed thru the use of the proposed algorithm, and a prototype was developed to evaluate the performance of the algorithm. As a result, DDoS attacks on the internal network were detected in real-time and whether or not IP addresses were spoofed was confirmed. Detecting hosts infected by malware in real-time allowed the execution of intrusion responses before stoppage of the internal network caused by large-scale attack traffic.

  14. Triangulation positioning system network

    Directory of Open Access Journals (Sweden)

    Sfendourakis Marios

    2017-01-01

    Full Text Available This paper presents ongoing work on localization and positioning through triangulation procedure for a Fixed Sensors Network - FSN.The FSN has to work as a system.As the triangulation problem becomes high complicated in a case with large numbers of sensors and transmitters, an adequate grid topology is needed in order to tackle the detection complexity.For that reason a Network grid topology is presented and areas that are problematic and need further analysis are analyzed.The Network System in order to deal with problems of saturation and False Triangulations - FTRNs will have to find adequate methods in every sub-area of the Area Of Interest - AOI.Also, concepts like Sensor blindness and overall Network blindness, are presented. All these concepts affect the Network detection rate and its performance and ought to be considered in a way that the network overall performance won’t be degraded.Network performance should be monitored contentiously, with right algorithms and methods.It is also shown that as the number of TRNs and FTRNs is increased Detection Complexity - DC is increased.It is hoped that with further research all the characteristics of a triangulation system network for positioning will be gained and the system will be able to perform autonomously with a high detection rate.

  15. Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization(in English

    Directory of Open Access Journals (Sweden)

    Shi Chen-guang

    2014-08-01

    Full Text Available A novel optimal power allocation algorithm for radar network systems is proposed for Low Probability of Intercept (LPI technology in modern electronic warfare. The algorithm is based on the LPI optimization. First, the Schleher intercept factor for a radar network is derived, and then the Schleher intercept factor is minimized by optimizing the transmission power allocation among netted radars in the network to guarantee target-tracking performance. Furthermore, the Nonlinear Programming Genetic Algorithm (NPGA is used to solve the resulting nonconvex, nonlinear, and constrained optimization problem. Numerical simulation results show the effectiveness of the proposed algorithm.

  16. Improving Intrusion Detection System Based on Snort Rules for Network Probe Attacks Detection with Association Rules Technique of Data Mining

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

    Full Text Available The intrusion detection system (IDS is an important network security tool for securing computer and network systems. It is able to detect and monitor network traffic data. Snort IDS is an open-source network security tool. It can search and match rules with network traffic data in order to detect attacks, and generate an alert. However, the Snort IDS  can detect only known attacks. Therefore, we have proposed a procedure for improving Snort IDS rules, based on the association rules data mining technique for detection of network probe attacks.  We employed the MIT-DARPA 1999 data set for the experimental evaluation. Since behavior pattern traffic data are both normal and abnormal, the abnormal behavior data is detected by way of the Snort IDS. The experimental results showed that the proposed Snort IDS rules, based on data mining detection of network probe attacks, proved more efficient than the original Snort IDS rules, as well as icmp.rules and icmp-info.rules of Snort IDS.  The suitable parameters for the proposed Snort IDS rules are defined as follows: Min_sup set to 10%, and Min_conf set to 100%, and through the application of eight variable attributes. As more suitable parameters are applied, higher accuracy is achieved.

  17. System Analysis of LWDH Related Genes Based on Text Mining in Biological Networks

    Directory of Open Access Journals (Sweden)

    Mingzhi Liao

    2014-01-01

    Full Text Available Liuwei-dihuang (LWDH is widely used in traditional Chinese medicine (TCM, but its molecular mechanism about gene interactions is unclear. LWDH genes were extracted from the existing literatures based on text mining technology. To simulate the complex molecular interactions that occur in the whole body, protein-protein interaction networks (PPINs were constructed and the topological properties of LWDH genes were analyzed. LWDH genes have higher centrality properties and may play important roles in the complex biological network environment. It was also found that the distances within LWDH genes are smaller than expected, which means that the communication of LWDH genes during the biological process is rapid and effectual. At last, a comprehensive network of LWDH genes, including the related drugs and regulatory pathways at both the transcriptional and posttranscriptional levels, was constructed and analyzed. The biological network analysis strategy used in this study may be helpful for the understanding of molecular mechanism of TCM.

  18. Social networks and implementation of evidence-based practices in public youth-serving systems: a mixed-methods study

    Directory of Open Access Journals (Sweden)

    Fuentes Dahlia

    2011-09-01

    Full Text Available Abstract Background The present study examines the structure and operation of social networks of information and advice and their role in making decisions as to whether to adopt new evidence-based practices (EBPs among agency directors and other program professionals in 12 California counties participating in a large randomized controlled trial. Methods Interviews were conducted with 38 directors, assistant directors, and program managers of county probation, mental health, and child welfare departments. Grounded-theory analytic methods were used to identify themes related to EBP adoption and network influences. A web-based survey collected additional quantitative information on members of information and advice networks of study participants. A mixed-methods approach to data analysis was used to create a sociometric data set (n = 176 for examination of associations between advice seeking and network structure. Results Systems leaders develop and maintain networks of information and advice based on roles, responsibility, geography, and friendship ties. Networks expose leaders to information about EBPs and opportunities to adopt EBPs; they also influence decisions to adopt EBPs. Individuals in counties at the same stage of implementation accounted for 83% of all network ties. Networks in counties that decided not to implement a specific EBP had no extra-county ties. Implementation of EBPs at the two-year follow-up was associated with the size of county, urban versus rural counties, and in-degree centrality. Collaboration was viewed as critical to implementing EBPs, especially in small, rural counties where agencies have limited resources on their own. Conclusions Successful implementation of EBPs requires consideration and utilization of existing social networks of high-status systems leaders that often cut across service organizations and their geographic jurisdictions. Trial Registration NCT00880126

  19. Social networks and implementation of evidence-based practices in public youth-serving systems: a mixed-methods study.

    Science.gov (United States)

    Palinkas, Lawrence A; Holloway, Ian W; Rice, Eric; Fuentes, Dahlia; Wu, Qiaobing; Chamberlain, Patricia

    2011-09-29

    The present study examines the structure and operation of social networks of information and advice and their role in making decisions as to whether to adopt new evidence-based practices (EBPs) among agency directors and other program professionals in 12 California counties participating in a large randomized controlled trial. Interviews were conducted with 38 directors, assistant directors, and program managers of county probation, mental health, and child welfare departments. Grounded-theory analytic methods were used to identify themes related to EBP adoption and network influences. A web-based survey collected additional quantitative information on members of information and advice networks of study participants. A mixed-methods approach to data analysis was used to create a sociometric data set (n = 176) for examination of associations between advice seeking and network structure. Systems leaders develop and maintain networks of information and advice based on roles, responsibility, geography, and friendship ties. Networks expose leaders to information about EBPs and opportunities to adopt EBPs; they also influence decisions to adopt EBPs. Individuals in counties at the same stage of implementation accounted for 83% of all network ties. Networks in counties that decided not to implement a specific EBP had no extra-county ties. Implementation of EBPs at the two-year follow-up was associated with the size of county, urban versus rural counties, and in-degree centrality. Collaboration was viewed as critical to implementing EBPs, especially in small, rural counties where agencies have limited resources on their own. Successful implementation of EBPs requires consideration and utilization of existing social networks of high-status systems leaders that often cut across service organizations and their geographic jurisdictions. NCT00880126.

  20. World Cities of Scientific Knowledge: Systems, Networks and Potential Dynamics. An Analysis Based on Bibliometric Indicators

    DEFF Research Database (Denmark)

    Matthiessen, Christian Wichmann; Schwarz, Annette Winkel; Find, Søren

    2010-01-01

    This paper is based on identification of the pattern of the upper level of the world city network of knowledge as published in a series of earlier papers. It is our aim to update the findings and relate to the general world city discussion. The structure of the world cities of knowledge network has...... changed over the past decade in favour of south-east Asian and south European cities and in disfavour of the traditional centres of North America and north-western Europe. The analysis is based on bibliometric data on the world’s 100 largest cities measured in terms of research output. The level...

  1. World Cities of Scientific Knowledge: Systems, Networks and Potential Dynamics. An Analysis Based on Bibliometric Indicators

    DEFF Research Database (Denmark)

    Matthiessen, Christian Wichmann; Schwarz, Annette Winkel; Find, Søren

    2010-01-01

    This paper is based on identification of the pattern of the upper level of the world city network of knowledge as published in a series of papers.It is our aim to update the findings and relate to the general world city discussion. The structure of the world cities of knowledge network has changed...... over the last decade in favour of south east Asian and south European cities and in disfavour of the traditional centres of North America and north-western Europe. The analysis is based on bibliometric data on the world’s 100 largest cities measured in terms of research output. Then level of co...

  2. Network-Based Effectiveness

    National Research Council Canada - National Science Library

    Friman, Henrik

    2006-01-01

    ... (extended from Leavitt, 1965). This text identifies aspects of network-based effectiveness that can benefit from a better understanding of leadership and management development of people, procedures, technology, and organizations...

  3. A Measure of Systems Engineering Effectiveness in Government Acquisition of Complex Information Systems: A Bayesian Belief Network-Based Approach

    Science.gov (United States)

    Doskey, Steven Craig

    2014-01-01

    This research presents an innovative means of gauging Systems Engineering effectiveness through a Systems Engineering Relative Effectiveness Index (SE REI) model. The SE REI model uses a Bayesian Belief Network to map causal relationships in government acquisitions of Complex Information Systems (CIS), enabling practitioners to identify and…

  4. Structure and Connectivity Analysis of Financial Complex System Based on G-Causality Network

    Science.gov (United States)

    Xu, Chuan-Ming; Yan, Yan; Zhu, Xiao-Wu; Li, Xiao-Teng; Chen, Xiao-Song

    2013-11-01

    The recent financial crisis highlights the inherent weaknesses of the financial market. To explore the mechanism that maintains the financial market as a system, we study the interactions of U.S. financial market from the network perspective. Applied with conditional Granger causality network analysis, network density, in-degree and out-degree rankings are important indicators to analyze the conditional causal relationships among financial agents, and further to assess the stability of U.S. financial systems. It is found that the topological structure of G-causality network in U.S. financial market changed in different stages over the last decade, especially during the recent global financial crisis. Network density of the G-causality model is much higher during the period of 2007-2009 crisis stage, and it reaches the peak value in 2008, the most turbulent time in the crisis. Ranked by in-degrees and out-degrees, insurance companies are listed in the top of 68 financial institutions during the crisis. They act as the hubs which are more easily influenced by other financial institutions and simultaneously influence others during the global financial disturbance.

  5. Design of flood early warning system with wifi network based on smartphone

    Science.gov (United States)

    Supani, Ahyar; Andriani, Yuli; Taqwa, Ahmad

    2017-11-01

    Today, the development using internet of things enables activities surrounding us to be monitored, controlled, predicted and calculated remotely through connections to the internet network such as monitoring activities of long-distance flood warning with information technology. Applying an information technology in the field of flood early warning has been developed in the world, either connected to internet network or not. The internet network that has been done in this paper is the design of WiFi network to access data of rainfall, water level and flood status at any time with a smartphone coming from flood early warning system. The results obtained when test of data accessing with smartphone are in form of rainfall and water level graphs against time and flood status indicators consisting of 3 flood states: Standby 2, Standby 1 and Flood. It is concluded that data are from flood early warning system has been able to accessed and displayed on smartphone via WiFi network in any time and real time.

  6. Active vision and image/video understanding systems for UGV based on network-symbolic models

    Science.gov (United States)

    Kuvich, Gary

    2004-09-01

    Vision evolved as a sensory system for reaching, grasping and other motion activities. In advanced creatures, it has become a vital component of situation awareness, navigation and planning systems. Vision is part of a larger information system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. It is hard to split such a system apart. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for natural processing of visual information. It converts visual information into relational Network-Symbolic models, avoiding artificial precise computations of 3-dimensional models. Logic of visual scenes can be captured in such models and used for disambiguation of visual information. Network-Symbolic transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps create unambiguous network-symbolic models. This approach is consistent with NIST RCS. The UGV, equipped with such smart vision, will be able to plan path and navigate in a real environment, perceive and understand complex real-world situations and act accordingly.

  7. The Design of Data Transmission Terminal in Remote Warning Control System Based on CDMA 1X Network

    Directory of Open Access Journals (Sweden)

    Dan CHEN

    2014-03-01

    Full Text Available This study proposes a framework of data transmission terminal in remote warning control system based on CDMA 1X network. According to the functional requirements of wireless broadband communication system, the hardware interfaces and software of the CDMA 1X data transmission terminal are designed detailedly and the system is implemented using wireless access and embedded development technologies. It has good applicability and portability so that various wireless data transmissions can be achieved by replacing the data source module.

  8. A Path-Based Gradient Projection Algorithm for the Cost-Based System Optimum Problem in Networks with Continuously Distributed Value of Time

    Directory of Open Access Journals (Sweden)

    Wen-Xiang Wu

    2014-01-01

    Full Text Available The cost-based system optimum problem in networks with continuously distributed value of time is formulated as a path-based form, which cannot be solved by the Frank-Wolfe algorithm. In light of magnitude improvement in the availability of computer memory in recent years, path-based algorithms have been regarded as a viable approach for traffic assignment problems with reasonably large network sizes. We develop a path-based gradient projection algorithm for solving the cost-based system optimum model, based on Goldstein-Levitin-Polyak method which has been successfully applied to solve standard user equilibrium and system optimum problems. The Sioux Falls network tested is used to verify the effectiveness of the algorithm.

  9. A neural-network-based model for the dynamic simulation of the tire/suspension system while traversing road irregularities.

    Science.gov (United States)

    Guarneri, Paolo; Rocca, Gianpiero; Gobbi, Massimiliano

    2008-09-01

    This paper deals with the simulation of the tire/suspension dynamics by using recurrent neural networks (RNNs). RNNs are derived from the multilayer feedforward neural networks, by adding feedback connections between output and input layers. The optimal network architecture derives from a parametric analysis based on the optimal tradeoff between network accuracy and size. The neural network can be trained with experimental data obtained in the laboratory from simulated road profiles (cleats). The results obtained from the neural network demonstrate good agreement with the experimental results over a wide range of operation conditions. The NN model can be effectively applied as a part of vehicle system model to accurately predict elastic bushings and tire dynamics behavior. Although the neural network model, as a black-box model, does not provide a good insight of the physical behavior of the tire/suspension system, it is a useful tool for assessing vehicle ride and noise, vibration, harshness (NVH) performance due to its good computational efficiency and accuracy.

  10. Structural and Network-based Methods for Knowledge-Based Systems

    Science.gov (United States)

    2011-12-01

    was used in the Learning Reader system [Forbus et al 2007]. FIRE performs backchaining over Horn clauses, similar to Prolog but without clause...SATCHMO: a theorem prover implemented in Prolog . Proc. of 9th International Conference on Automated Deduction, pp. 415-434. 1988 C. E. Martin and C. K

  11. A New Intrusion Detection System Based on KNN Classification Algorithm in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Wenchao Li

    2014-01-01

    abnormal nodes from normal nodes by observing their abnormal behaviors, and we analyse parameter selection and error rate of the intrusion detection system. The paper elaborates on the design and implementation of the detection system. This system has achieved efficient, rapid intrusion detection by improving the wireless ad hoc on-demand distance vector routing protocol (Ad hoc On-Demand Distance the Vector Routing, AODV. Finally, the test results show that: the system has high detection accuracy and speed, in accordance with the requirement of wireless sensor network intrusion detection.

  12. 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.

  13. IMaxer: A Unified System for Evaluating Influence Maximization in Location-based Social Networks

    DEFF Research Database (Denmark)

    Saleem, Muhammad Aamir; Kumar, Rohit; Calders, Toon

    2017-01-01

    Due to the popularity of social networks with geo-tagged activities, so-called location-based social networks (LBSN), a number of methods have been proposed for influence maximization for applications such as word-of-mouth marketing (WOMM), and out-of-home marketing (OOH). It is thus important to...... nodes can be found and their potential influence can be simulated and visualized using Google Maps and graph visualization APIs. Thus, IMaxer allows users to compare and pick the most suitable IM method in terms of effectiveness and cost...

  14. A knowledge-based system with learning for computer communication network design

    Science.gov (United States)

    Pierre, Samuel; Hoang, Hai Hoc; Tropper-Hausen, Evelyne

    1990-01-01

    Computer communication network design is well-known as complex and hard. For that reason, the most effective methods used to solve it are heuristic. Weaknesses of these techniques are listed and a new approach based on artificial intelligence for solving this problem is presented. This approach is particularly recommended for large packet switched communication networks, in the sense that it permits a high degree of reliability and offers a very flexible environment dealing with many relevant design parameters such as link cost, link capacity, and message delay.

  15. Neural Network Based Finite-Time Stabilization for Discrete-Time Markov Jump Nonlinear Systems with Time Delays

    Directory of Open Access Journals (Sweden)

    Fei Chen

    2013-01-01

    Full Text Available This paper deals with the finite-time stabilization problem for discrete-time Markov jump nonlinear systems with time delays and norm-bounded exogenous disturbance. The nonlinearities in different jump modes are parameterized by neural networks. Subsequently, a linear difference inclusion state space representation for a class of neural networks is established. Based on this, sufficient conditions are derived in terms of linear matrix inequalities to guarantee stochastic finite-time boundedness and stochastic finite-time stabilization of the closed-loop system. A numerical example is illustrated to verify the efficiency of the proposed technique.

  16. Security Concerns and Countermeasures in Network Coding Based Communications Systems: A Survey

    DEFF Research Database (Denmark)

    Nazari Talooki, Vahid; Bassoli, Riccardo; Lucani Rötter, Daniel Enrique

    2015-01-01

    This survey paper shows the state of the art in security mechanisms, where a deep review of the current research and the status of this topic is carried out. We start by introducing network coding and its variety applications in enhancing current traditional networks. In particular, we analyze two...... key protocol types, namely, state-aware and stateless protocols, specifying the benefits and disadvantages of each one of them. We also present the key security assumptions of network coding (NC) systems as well as a detailed analysis of the security goals and threats, both passive and active....... This paper also presents a detailed taxonomy and a timeline of the different NC security mechanisms and schemes reported in the literature. Current proposed security mechanisms and schemes for NC in the literature are classified later. Finally a timeline of these mechanism and schemes is presented....

  17. Abstract Computation in Schizophrenia Detection through Artificial Neural Network Based Systems

    Directory of Open Access Journals (Sweden)

    L. Cardoso

    2015-01-01

    Full Text Available Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason of defective information.

  18. Designing Dietary Recommendations Using System Level Interactomics Analysis and Network-Based Inference

    Directory of Open Access Journals (Sweden)

    Tingting Zheng

    2017-09-01

    diet in disease development. Due to the complexity of analyzing the food composition and eating patterns of individuals our in silico analysis, using large-scale gene expression datasets and network-based topological features, may serve as a proof-of-concept in nutritional systems biology for identifying diet-disease relationships and subsequently designing dietary recommendations.

  19. Systems Bioinformatics: increasing precision of computational diagnostics and therapeutics through network-based approaches.

    Science.gov (United States)

    Oulas, Anastasis; Minadakis, George; Zachariou, Margarita; Sokratous, Kleitos; Bourdakou, Marilena M; Spyrou, George M

    2017-11-27

    Systems Bioinformatics is a relatively new approach, which lies in the intersection of systems biology and classical bioinformatics. It focuses on integrating information across different levels using a bottom-up approach as in systems biology with a data-driven top-down approach as in bioinformatics. The advent of omics technologies has provided the stepping-stone for the emergence of Systems Bioinformatics. These technologies provide a spectrum of information ranging from genomics, transcriptomics and proteomics to epigenomics, pharmacogenomics, metagenomics and metabolomics. Systems Bioinformatics is the framework in which systems approaches are applied to such data, setting the level of resolution as well as the boundary of the system of interest and studying the emerging properties of the system as a whole rather than the sum of the properties derived from the system's individual components. A key approach in Systems Bioinformatics is the construction of multiple networks representing each level of the omics spectrum and their integration in a layered network that exchanges information within and between layers. Here, we provide evidence on how Systems Bioinformatics enhances computational therapeutics and diagnostics, hence paving the way to precision medicine. The aim of this review is to familiarize the reader with the emerging field of Systems Bioinformatics and to provide a comprehensive overview of its current state-of-the-art methods and technologies. Moreover, we provide examples of success stories and case studies that utilize such methods and tools to significantly advance research in the fields of systems biology and systems medicine. © The Author 2017. Published by Oxford University Press.

  20. Mal-Netminer: Malware Classification Approach Based on Social Network Analysis of System Call Graph

    Directory of Open Access Journals (Sweden)

    Jae-wook Jang

    2015-01-01

    Full Text Available As the security landscape evolves over time, where thousands of species of malicious codes are seen every day, antivirus vendors strive to detect and classify malware families for efficient and effective responses against malware campaigns. To enrich this effort and by capitalizing on ideas from the social network analysis domain, we build a tool that can help classify malware families using features driven from the graph structure of their system calls. To achieve that, we first construct a system call graph that consists of system calls found in the execution of the individual malware families. To explore distinguishing features of various malware species, we study social network properties as applied to the call graph, including the degree distribution, degree centrality, average distance, clustering coefficient, network density, and component ratio. We utilize features driven from those properties to build a classifier for malware families. Our experimental results show that “influence-based” graph metrics such as the degree centrality are effective for classifying malware, whereas the general structural metrics of malware are less effective for classifying malware. Our experiments demonstrate that the proposed system performs well in detecting and classifying malware families within each malware class with accuracy greater than 96%.

  1. Image/video understanding systems based on network-symbolic models and active vision

    Science.gov (United States)

    Kuvich, Gary

    2004-07-01

    Vision is a part of information system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. It is hard to split the entire system apart, and vision mechanisms cannot be completely understood separately from informational processes related to knowledge and intelligence. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Vision is a component of situation awareness, motion and planning systems. Foveal vision provides semantic analysis, recognizing objects in the scene. Peripheral vision guides fovea to salient objects and provides scene context. Biologically inspired Network-Symbolic representation, in which both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, converts visual information into relational Network-Symbolic structures, avoiding precise artificial computations of 3-D models. Network-Symbolic transformations derive more abstract structures that allows for invariant recognition of an object as exemplar of a class and for a reliable identification even if the object is occluded. Systems with such smart vision will be able to navigate in real environment and understand real-world situations.

  2. Design and Implementation of a Web-based Greenhouse Remote Monitoring System with Zigbee Protocol and GSM Network

    Directory of Open Access Journals (Sweden)

    Abdolhamid Tabatabaeifar

    2014-10-01

    Full Text Available In modern and big greenhouses, it is necessary to measure several climate parameters to automate and control the greenhouse properly. Monitoring and transmitting by cable may lead to an expensive and stiff measurement system. Since, Wireless Sensor Network (WSN is a distributed system that consists of small-size wireless sensor nodes equipped with radio and one or several sensors; it is a low cost option to build the required monitoring system. In this paper, we introduce and implement an intelligent monitoring system based on WSN by using Xbee modules. The Xbee Series 2 hardware uses a microchip from Ember Networks that enables several different flavors of standards-based ZigBee mesh networking. All gathered information by sensors, are sent to a remote center in form of GPRS packets through a GSM network and viewed by monitoring software. The proposed system has low power consumption, low cost and simple driver circuits. Furthermore, it can support various types of digital and analog sensors.

  3. Mal-Netminer: Malware Classification Approach Based on Social Network Analysis of System Call Graph

    OpenAIRE

    Jae-wook Jang; Jiyoung Woo; Aziz Mohaisen; Jaesung Yun; Huy Kang Kim

    2015-01-01

    As the security landscape evolves over time, where thousands of species of malicious codes are seen every day, antivirus vendors strive to detect and classify malware families for efficient and effective responses against malware campaigns. To enrich this effort and by capitalizing on ideas from the social network analysis domain, we build a tool that can help classify malware families using features driven from the graph structure of their system calls. To achieve that, we first construct a ...

  4. Ad hoc network for emergency rescue system based on unmanned aerial vehicles

    OpenAIRE

    Cambra, Carlos; Sendra, Sandra; Lloret, Jaime; PARRA BORONAT, LORENA

    2015-01-01

    Intelligent Unmanned Aerial Vehicles (UAVs) on emergency rescue are widely used to detect injured mountaineers in inaccessible areas. These systems should satisfy several features. It is important to know the georeference of the injured mountaineers. It is also important to have real-time images of the area where people have suffered the accident. In this paper, we present the development of a UAV integrated within a wireless ad hoc network and the communication protocol that i...

  5. Design and Development of Water Quality Monitoring System Based on Wireless Sensor Network in Aquaculture

    OpenAIRE

    Zhang, Mingfei; Li, Daoliang; Wang, Lianzhi; Ma, Daokun; Ding, Qisheng

    2010-01-01

    International audience; This paper presents a system framework taking the advantages of the WSN for the real-time monitoring on the water quality in aquaculture. We design the structure of the wireless sensor network to collect and continuously transmit data to the monitoring software. Then we accomplish the configuration model in the software that enhances the reuse and facility of the monitoring project. Moreover, the monitoring software developed to represent the monitoring hardware and da...

  6. Inverse simulation system for manual-controlled rendezvous and docking based on artificial neural network

    Science.gov (United States)

    Zhou, Wanmeng; Wang, Hua; Tang, Guojin; Guo, Shuai

    2016-09-01

    The time-consuming experimental method for handling qualities assessment cannot meet the increasing fast design requirements for the manned space flight. As a tool for the aircraft handling qualities research, the model-predictive-control structured inverse simulation (MPC-IS) has potential applications in the aerospace field to guide the astronauts' operations and evaluate the handling qualities more effectively. Therefore, this paper establishes MPC-IS for the manual-controlled rendezvous and docking (RVD) and proposes a novel artificial neural network inverse simulation system (ANN-IS) to further decrease the computational cost. The novel system was obtained by replacing the inverse model of MPC-IS with the artificial neural network. The optimal neural network was trained by the genetic Levenberg-Marquardt algorithm, and finally determined by the Levenberg-Marquardt algorithm. In order to validate MPC-IS and ANN-IS, the manual-controlled RVD experiments on the simulator were carried out. The comparisons between simulation results and experimental data demonstrated the validity of two systems and the high computational efficiency of ANN-IS.

  7. MEDUSA - An overset grid flow solver for network-based parallel computer systems

    Science.gov (United States)

    Smith, Merritt H.; Pallis, Jani M.

    1993-01-01

    Continuing improvement in processing speed has made it feasible to solve the Reynolds-Averaged Navier-Stokes equations for simple three-dimensional flows on advanced workstations. Combining multiple workstations into a network-based heterogeneous parallel computer allows the application of programming principles learned on MIMD (Multiple Instruction Multiple Data) distributed memory parallel computers to the solution of larger problems. An overset-grid flow solution code has been developed which uses a cluster of workstations as a network-based parallel computer. Inter-process communication is provided by the Parallel Virtual Machine (PVM) software. Solution speed equivalent to one-third of a Cray-YMP processor has been achieved from a cluster of nine commonly used engineering workstation processors. Load imbalance and communication overhead are the principal impediments to parallel efficiency in this application.

  8. Design of FPGA Based Neural Network Controller for Earth Station Power System

    Directory of Open Access Journals (Sweden)

    Hassen T. Dorrah

    2012-06-01

    Full Text Available Automation of generating hardware description language code from neural networks models can highly decrease time of implementation those networks into a digital devices, thus significant money savings. To implement the neural network into hardware designer, it is required to translate generated model into device structure. VHDL language is used to describe those networks into hardware. VHDL code has been proposed to implement ANNs as well as to present simulation results with floating point arithmetic of the earth station and the satellite power systems using ModelSim PE 6.6 simulator tool. Integration between MATLAB and VHDL is used to save execution time of computation. The results shows that a good agreement between MATLAB and VHDL and a fast/flexible feed forward NN which is capable of dealing with floating point arithmetic operations; minimum number of CLB slices; and good speed of performance. FPGA synthesis results are obtained with view RTL schematic and technology schematic from Xilinix tool. Minimum number of utilized resources is obtained by using Xilinix VERTIX5.

  9. A radial basis function neural network based on artificial immune systems for remote sensing image classification

    Science.gov (United States)

    Yan, Qin; Zhong, Yanfei

    2008-12-01

    The radial basis function (RBF) neural network is a powerful method for remote sensing image classification. It has a simple architecture and the learning algorithm corresponds to the solution of a linear regression problem, resulting in a fast training process. The main drawback of this strategy is the requirement of an efficient algorithm to determine the number, position, and dispersion of the RBF. Traditional methods to determine the centers are: randomly choose input vectors from the training data set; vectors obtained from unsupervised clustering algorithms, such as k-means, applied to the input data. These conduce that traditional RBF neural network is sensitive to the center initialization. In this paper, the artificial immune network (aiNet) model, a new computational intelligence based on artificial immune networks (AIN), is applied to obtain appropriate centers for remote sensing image classification. In the aiNet-RBF algorihtm, each input pattern corresonds to an antigenic stimulus, while each RBF candidate center is considered to be an element, or cell, of the immune network model. The steps are as follows: A set of candidate centers is initialized at random, where the initial number of candidates and their positions is not crucial to the performance. Then, the clonal selection principle will control which candidates will be selected and how they will be upadated. Note that the clonal selection principle will be responsible for how the centers will represent the training data set. Finally, the immune network will identify and eliminate or suppress self-recognizing individuals to control the number of candidate centers. After the above learning phase, the aiNet network centers represent internal images of the inuput patterns presented to it. The algorithm output is taken to be the matrix of memory cells' coordinates that represent the final centers to be adopted by the RBF network. The stopping criterion of the proposed algorithm is given by a pre

  10. A Robust High-Accuracy Ultrasound Indoor Positioning System Based on a Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Jun Qi

    2017-11-01

    Full Text Available This paper describes the development and implementation of a robust high-accuracy ultrasonic indoor positioning system (UIPS. The UIPS consists of several wireless ultrasonic beacons in the indoor environment. Each of them has a fixed and known position coordinate and can collect all the transmissions from the target node or emit ultrasonic signals. Every wireless sensor network (WSN node has two communication modules: one is WiFi, that transmits the data to the server, and the other is the radio frequency (RF module, which is only used for time synchronization between different nodes, with accuracy up to 1 μs. The distance between the beacon and the target node is calculated by measuring the time-of-flight (TOF for the ultrasonic signal, and then the position of the target is computed by some distances and the coordinate of the beacons. TOF estimation is the most important technique in the UIPS. A new time domain method to extract the envelope of the ultrasonic signals is presented in order to estimate the TOF. This method, with the envelope detection filter, estimates the value with the sampled values on both sides based on the least squares method (LSM. The simulation results show that the method can achieve envelope detection with a good filtering effect by means of the LSM. The highest precision and variance can reach 0.61 mm and 0.23 mm, respectively, in pseudo-range measurements with UIPS. A maximum location error of 10.2 mm is achieved in the positioning experiments for a moving robot, when UIPS works on the line-of-sight (LOS signal.

  11. A Robust High-Accuracy Ultrasound Indoor Positioning System Based on a Wireless Sensor Network.

    Science.gov (United States)

    Qi, Jun; Liu, Guo-Ping

    2017-11-06

    This paper describes the development and implementation of a robust high-accuracy ultrasonic indoor positioning system (UIPS). The UIPS consists of several wireless ultrasonic beacons in the indoor environment. Each of them has a fixed and known position coordinate and can collect all the transmissions from the target node or emit ultrasonic signals. Every wireless sensor network (WSN) node has two communication modules: one is WiFi, that transmits the data to the server, and the other is the radio frequency (RF) module, which is only used for time synchronization between different nodes, with accuracy up to 1 μ s. The distance between the beacon and the target node is calculated by measuring the time-of-flight (TOF) for the ultrasonic signal, and then the position of the target is computed by some distances and the coordinate of the beacons. TOF estimation is the most important technique in the UIPS. A new time domain method to extract the envelope of the ultrasonic signals is presented in order to estimate the TOF. This method, with the envelope detection filter, estimates the value with the sampled values on both sides based on the least squares method (LSM). The simulation results show that the method can achieve envelope detection with a good filtering effect by means of the LSM. The highest precision and variance can reach 0.61 mm and 0.23 mm, respectively, in pseudo-range measurements with UIPS. A maximum location error of 10.2 mm is achieved in the positioning experiments for a moving robot, when UIPS works on the line-of-sight (LOS) signal.

  12. Leuconostoc Mesenteroides Growth in Food Products: Prediction and Sensitivity Analysis by Adaptive-Network-Based Fuzzy Inference Systems

    OpenAIRE

    Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

    2013-01-01

    BACKGROUND: An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. METHODS: THE ANFIS AND ANN MODELS WERE COMPARED IN TERMS OF SIX STATISTICAL INDICES CALCULATED B...

  13. Computer-assisted design for scaling up systems based on DNA reaction networks.

    Science.gov (United States)

    Aubert, Nathanaël; Mosca, Clément; Fujii, Teruo; Hagiya, Masami; Rondelez, Yannick

    2014-04-06

    In the past few years, there have been many exciting advances in the field of molecular programming, reaching a point where implementation of non-trivial systems, such as neural networks or switchable bistable networks, is a reality. Such systems require nonlinearity, be it through signal amplification, digitalization or the generation of autonomous dynamics such as oscillations. The biochemistry of DNA systems provides such mechanisms, but assembling them in a constructive manner is still a difficult and sometimes counterintuitive process. Moreover, realistic prediction of the actual evolution of concentrations over time requires a number of side reactions, such as leaks, cross-talks or competitive interactions, to be taken into account. In this case, the design of a system targeting a given function takes much trial and error before the correct architecture can be found. To speed up this process, we have created DNA Artificial Circuits Computer-Assisted Design (DACCAD), a computer-assisted design software that supports the construction of systems for the DNA toolbox. DACCAD is ultimately aimed to design actual in vitro implementations, which is made possible by building on the experimental knowledge available on the DNA toolbox. We illustrate its effectiveness by designing various systems, from Montagne et al.'s Oligator or Padirac et al.'s bistable system to new and complex networks, including a two-bit counter or a frequency divider as well as an example of very large system encoding the game Mastermind. In the process, we highlight a variety of behaviours, such as enzymatic saturation and load effect, which would be hard to handle or even predict with a simpler model. We also show that those mechanisms, while generally seen as detrimental, can be used in a positive way, as functional part of a design. Additionally, the number of parameters included in these simulations can be large, especially in the case of complex systems. For this reason, we included the

  14. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

    2018-02-01

    Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  15. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

    2018-02-01

    Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  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. Poseidon: a 2-tier Anomaly-based Network Intrusion Detection System

    OpenAIRE

    BOLZONI, D.; Zambon, Emmanuele; Etalle, Sandro; Hartel, Pieter H.

    2006-01-01

    We present Poseidon, a new anomaly based intrusion detection system. Poseidon is payload-based, and presents a two-tier architecture: the first stage consists of a Self-Organizing Map, while the second one is a modified PAYL system. Our benchmarks on the 1999 DARPA data set show a higher detection rate and lower number of false positives than PAYL and PHAD.

  19. Speech Intelligibility Potential of General and Specialized Deep Neural Network Based Speech Enhancement Systems

    DEFF Research Database (Denmark)

    Kolbæk, Morten; Tan, Zheng-Hua; Jensen, Jesper

    2017-01-01

    , and the signal-to-noise ratio (SNR). Furthermore, we investigate how specialized DNN-based SE systems, which have been trained to be either noise type specific, speaker specific or SNR specific, perform relative to DNN based SE systems that have been trained to be noise type general, speaker general, and SNR...

  20. Poseidon: a 2-tier Anomaly-based Network Intrusion Detection System

    NARCIS (Netherlands)

    Bolzoni, D.; Zambon, Emmanuele; Etalle, Sandro; Hartel, Pieter H.; Cole, Jack; Wolthusen, Stephen D.

    We present Poseidon, a new anomaly based intrusion detection system. Poseidon is payload-based, and presents a two-tier architecture: the first stage consists of a Self-Organizing Map, while the second one is a modified PAYL system. Our benchmarks on the 1999 DARPA data set show a higher detection

  1. Diagonal recurrent neural network based adaptive control of nonlinear dynamical systems using lyapunov stability criterion.

    Science.gov (United States)

    Kumar, Rajesh; Srivastava, Smriti; Gupta, J R P

    2017-03-01

    In this paper adaptive control of nonlinear dynamical systems using diagonal recurrent neural network (DRNN) is proposed. The structure of DRNN is a modification of fully connected recurrent neural network (FCRNN). Presence of self-recurrent neurons in the hidden layer of DRNN gives it an ability to capture the dynamic behaviour of the nonlinear plant under consideration (to be controlled). To ensure stability, update rules are developed using lyapunov stability criterion. These rules are then used for adjusting the various parameters of DRNN. The responses of plants obtained with DRNN are compared with those obtained when multi-layer feed forward neural network (MLFFNN) is used as a controller. Also, in example 4, FCRNN is also investigated and compared with DRNN and MLFFNN. Robustness of the proposed control scheme is also tested against parameter variations and disturbance signals. Four simulation examples including one-link robotic manipulator and inverted pendulum are considered on which the proposed controller is applied. The results so obtained show the superiority of DRNN over MLFFNN as a controller. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Development of Low Noise-Broadband Raman Amplification Systems Based on Photonic Crystal Fibers for High Capacity DWDM Networks

    Science.gov (United States)

    Elgamri, Abdelghafor

    The increased demand from IP traffic, video application and cell backhaul has placed fiber routes under severe stains. The high demands for large bandwidth from enormous numbers from cell sites on a network made the capacity of yesterday's networks not adequate for today's bandwidth demand. Carries considered Dense Wavelength Division Multiplexing (DWDM) network to overcome this issue. Recently, there has been growing interest in fiber Raman amplifiers due to their capability to upgrade the wavelength-division-multiplexing bandwidth, arbitrary gain bandwidth. In addition, photonic crystal fibers have been widely modeled, studied, and fabricated due to their peculiar properties that cannot be achieved with conventional fibers. The focus of this thesis is to develop a low-noise broadband Raman amplification system based on photonic crystal Fiber that can be implemented in high capacity DWDM network successfully. The design a module of photonic crystal fiber Raman amplifier is based on the knowledge of the fiber cross-sectional characteristics i.e. the geometric parameters and the Germania concentration in the dope area. The module allows to study different air-hole dimension and disposition, with or without a central doped area. In addition the design integrates distributed Raman amplifier and nonlinear optical loop mirror to improve the signal to noise ratio and overall gain in large capacity DWDM networks.

  3. Fault Tolerant Ethernet Based Network for Time Sensitive Applications in Electrical Power Distribution Systems

    Directory of Open Access Journals (Sweden)

    Leos Bohac

    2013-01-01

    Full Text Available The paper analyses and experimentally verifies deployment of Ethernet based network technology to enable fault tolerant and timely exchange of data among a number of high voltage protective relays that use proprietary serial communication line to exchange data in real time on a state of its high voltage circuitry facilitating a fast protection switching in case of critical failures. The digital serial signal is first fetched into PCM multiplexer where it is mapped to the corresponding E1 (2 Mbit/s time division multiplexed signal. Subsequently, the resulting E1 frames are then packetized and sent through Ethernet control LAN to the opposite PCM demultiplexer where the same but reverse processing is done finally sending a signal into the opposite protective relay. The challenge of this setup is to assure very timely delivery of the control information between protective relays even in the cases of potential failures of Ethernet network itself. The tolerance of Ethernet network to faults is assured using widespread per VLAN Rapid Spanning Tree Protocol potentially extended by 1+1 PCM protection as a valuable option.

  4. Self-Adapting Routing Overlay Network for Frequently Changing Application Traffic in Content-Based Publish/Subscribe System

    Directory of Open Access Journals (Sweden)

    Meng Chi

    2014-01-01

    Full Text Available In the large-scale distributed simulation area, the topology of the overlay network cannot always rapidly adapt to frequently changing application traffic to reduce the overall traffic cost. In this paper, we propose a self-adapting routing strategy for frequently changing application traffic in content-based publish/subscribe system. The strategy firstly trains the traffic information and then uses this training information to predict the application traffic in the future. Finally, the strategy reconfigures the topology of the overlay network based on this predicting information to reduce the overall traffic cost. A predicting path is also introduced in this paper to reduce the reconfiguration numbers in the process of the reconfigurations. Compared to other strategies, the experimental results show that the strategy proposed in this paper could reduce the overall traffic cost of the publish/subscribe system in less reconfigurations.

  5. The Research on Programmable Control System of Lithium-Bromide Absorption Refrigerating Air Conditioner Based on the Network

    Directory of Open Access Journals (Sweden)

    Sun Lunan

    2016-01-01

    Full Text Available This article regard the solar lithium-bromide absorption refrigerating air conditioning system as the research object, and it was conducting adequate research of the working principle of lithium bromide absorption refrigerating machine, also it was analyzing the requirements of control system about solar energy air conditioning. Then the solar energy air conditioning control system was designed based on PLC, this system was given priority to field bus control system, and the remote monitoring is complementary, which was combining the network remote monitoring technology. So that it realized the automatic control and intelligent control of new lithium bromide absorption refrigerating air conditioning system with solar energy, also, it ensured the control system can automatically detect and adjust when the external conditions was random changing, to make air conditioning work effectively and steadily, ultimately ,it has great research significance to research the air conditioning control system with solar energy.

  6. QuakeUp: An advanced tool for a network-based Earthquake Early Warning system

    Science.gov (United States)

    Zollo, Aldo; Colombelli, Simona; Caruso, Alessandro; Elia, Luca; Brondi, Piero; Emolo, Antonio; Festa, Gaetano; Martino, Claudio; Picozzi, Matteo

    2017-04-01

    The currently developed and operational Earthquake Early warning, regional systems ground on the assumption of a point-like earthquake source model and 1-D ground motion prediction equations to estimate the earthquake impact. Here we propose a new network-based method which allows for issuing an alert based upon the real-time mapping of the Potential Damage Zone (PDZ), e.g. the epicentral area where the peak ground velocity is expected to exceed the damaging or strong shaking levels with no assumption about the earthquake rupture extent and spatial variability of ground motion. The platform includes the most advanced techniques for a refined estimation of the main source parameters (earthquake location and magnitude) and for an accurate prediction of the expected ground shaking level. The new software platform (QuakeUp) is under development at the Seismological Laboratory (RISSC-Lab) of the Department of Physics at the University of Naples Federico II, in collaboration with the academic spin-off company RISS s.r.l., recently gemmated by the research group. The system processes the 3-component, real-time ground acceleration and velocity data streams at each station. The signal quality is preliminary assessed by checking the signal-to-noise ratio both in acceleration, velocity and displacement and through dedicated filtering algorithms. For stations providing high quality data, the characteristic P-wave period (τ_c) and the P-wave displacement, velocity and acceleration amplitudes (P_d, Pv and P_a) are jointly measured on a progressively expanded P-wave time window. The evolutionary measurements of the early P-wave amplitude and characteristic period at stations around the source allow to predict the geometry and extent of PDZ, but also of the lower shaking intensity regions at larger epicentral distances. This is done by correlating the measured P-wave amplitude with the Peak Ground Velocity (PGV) and Instrumental Intensity (I_MM) and by mapping the measured and

  7. Implementation and Analysis of a Wireless Sensor Network-Based Pet Location Monitoring System for Domestic Scenarios

    Directory of Open Access Journals (Sweden)

    Erik Aguirre

    2016-08-01

    Full Text Available The flexibility of new age wireless networks and the variety of sensors to measure a high number of variables, lead to new scenarios where anything can be monitored by small electronic devices, thereby implementing Wireless Sensor Networks (WSN. Thanks to ZigBee, RFID or WiFi networks the precise location of humans or animals as well as some biological parameters can be known in real-time. However, since wireless sensors must be attached to biological tissues and they are highly dispersive, propagation of electromagnetic waves must be studied to deploy an efficient and well-working network. The main goal of this work is to study the influence of wireless channel limitations in the operation of a specific pet monitoring system, validated at physical channel as well as at functional level. In this sense, radio wave propagation produced by ZigBee devices operating at the ISM 2.4 GHz band is studied through an in-house developed 3D Ray Launching simulation tool, in order to analyze coverage/capacity relations for the optimal system selection as well as deployment strategy in terms of number of transceivers and location. Furthermore, a simplified dog model is developed for simulation code, considering not only its morphology but also its dielectric properties. Relevant wireless channel information such as power distribution, power delay profile and delay spread graphs are obtained providing an extensive wireless channel analysis. A functional dog monitoring system is presented, operating over the implemented ZigBee network and providing real time information to Android based devices. The proposed system can be scaled in order to consider different types of domestic pets as well as new user based functionalities.

  8. Implementation and Analysis of a Wireless Sensor Network-Based Pet Location Monitoring System for Domestic Scenarios.

    Science.gov (United States)

    Aguirre, Erik; Lopez-Iturri, Peio; Azpilicueta, Leyre; Astrain, José Javier; Villadangos, Jesús; Santesteban, Daniel; Falcone, Francisco

    2016-08-30

    The flexibility of new age wireless networks and the variety of sensors to measure a high number of variables, lead to new scenarios where anything can be monitored by small electronic devices, thereby implementing Wireless Sensor Networks (WSN). Thanks to ZigBee, RFID or WiFi networks the precise location of humans or animals as well as some biological parameters can be known in real-time. However, since wireless sensors must be attached to biological tissues and they are highly dispersive, propagation of electromagnetic waves must be studied to deploy an efficient and well-working network. The main goal of this work is to study the influence of wireless channel limitations in the operation of a specific pet monitoring system, validated at physical channel as well as at functional level. In this sense, radio wave propagation produced by ZigBee devices operating at the ISM 2.4 GHz band is studied through an in-house developed 3D Ray Launching simulation tool, in order to analyze coverage/capacity relations for the optimal system selection as well as deployment strategy in terms of number of transceivers and location. Furthermore, a simplified dog model is developed for simulation code, considering not only its morphology but also its dielectric properties. Relevant wireless channel information such as power distribution, power delay profile and delay spread graphs are obtained providing an extensive wireless channel analysis. A functional dog monitoring system is presented, operating over the implemented ZigBee network and providing real time information to Android based devices. The proposed system can be scaled in order to consider different types of domestic pets as well as new user based functionalities.

  9. Robust Fault Detection of Wind Energy Conversion Systems Based on Dynamic Neural Networks

    Directory of Open Access Journals (Sweden)

    Nasser Talebi

    2014-01-01

    Full Text Available Occurrence of faults in wind energy conversion systems (WECSs is inevitable. In order to detect the occurred faults at the appropriate time, avoid heavy economic losses, ensure safe system operation, prevent damage to adjacent relevant systems, and facilitate timely repair of failed components; a fault detection system (FDS is required. Recurrent neural networks (RNNs have gained a noticeable position in FDSs and they have been widely used for modeling of complex dynamical systems. One method for designing an FDS is to prepare a dynamic neural model emulating the normal system behavior. By comparing the outputs of the real system and neural model, incidence of the faults can be identified. In this paper, by utilizing a comprehensive dynamic model which contains both mechanical and electrical components of the WECS, an FDS is suggested using dynamic RNNs. The presented FDS detects faults of the generator's angular velocity sensor, pitch angle sensors, and pitch actuators. Robustness of the FDS is achieved by employing an adaptive threshold. Simulation results show that the proposed scheme is capable to detect the faults shortly and it has very low false and missed alarms rate.

  10. Robust fault detection of wind energy conversion systems based on dynamic neural networks.

    Science.gov (United States)

    Talebi, Nasser; Sadrnia, Mohammad Ali; Darabi, Ahmad

    2014-01-01

    Occurrence of faults in wind energy conversion systems (WECSs) is inevitable. In order to detect the occurred faults at the appropriate time, avoid heavy economic losses, ensure safe system operation, prevent damage to adjacent relevant systems, and facilitate timely repair of failed components; a fault detection system (FDS) is required. Recurrent neural networks (RNNs) have gained a noticeable position in FDSs and they have been widely used for modeling of complex dynamical systems. One method for designing an FDS is to prepare a dynamic neural model emulating the normal system behavior. By comparing the outputs of the real system and neural model, incidence of the faults can be identified. In this paper, by utilizing a comprehensive dynamic model which contains both mechanical and electrical components of the WECS, an FDS is suggested using dynamic RNNs. The presented FDS detects faults of the generator's angular velocity sensor, pitch angle sensors, and pitch actuators. Robustness of the FDS is achieved by employing an adaptive threshold. Simulation results show that the proposed scheme is capable to detect the faults shortly and it has very low false and missed alarms rate.

  11. Development of a web-based support system for both homogeneous and heterogeneous air quality control networks: process and product.

    Science.gov (United States)

    Andrade, J; Ares, J; García, R; Presa, J; Rodríguez, S; Piñeiro-Iglesias, M; López-Mahía, P; Muniategui, S; Prada, D

    2007-10-01

    The Environmental Laboratories Automation Software System or PALMA (Spanish abbreviation) was developed by a multidisciplinary team in order to support the main tasks of heterogeneous air quality control networks. The software process for PALMA development, which can be perfectly applied to similar multidisciplinary projects, was (a) well-defined, (b) arranged between environmental technicians and informatics, (c) based on quality guides, and (d) clearly user-centred. Moreover, it introduces some interesting advantages with regard to the classical step-by-step approaches. PALMA is a web-based system that allows 'off-line' and automated telematic data acquisition from distributed inmission stations belonging not only to homogeneous but also to heterogeneous air quality control networks. It provides graphic and tabular representations for a comprehensive and centralised analysis of acquired data, and considers the daily work that is associated with such networks: validation of the acquired data, alerts with regard to (periodical) tasks (e.g., analysers verification), downloading of files with environmental information (e.g., dust forecasts), etc. The implantation of PALMA has provided qualitative and quantitative improvements in the work performed by the people in charge of the considered control network.

  12. Artificial neural network-based predictive emission monitoring system for NOx emissions

    Energy Technology Data Exchange (ETDEWEB)

    Ciccone, A.; Cinnamon, C.; Niejadlik, P.R. [TransCanada Energy Ltd., Toronto, ON (Canada)]|[Golder Associates, Toronto, ON (Canada)

    2005-07-01

    Considering the nature of long term power supply contracts that do not include mechanisms for cost recovery, developing cost-effective ways to handle changes in legislation impacting on facilities already in operation is extremely important. Also of importance is the age of the facilities, since continuous emissions monitoring (CEM) systems were not required when they were originally put into operation, but they are not yet old enough for capital stock turnover to allow for equipment changes or transition to new operations. An alternative monitoring method that is less expensive and as accurate as traditional (CEM) systems is discussed. TransCanada Energy Ltd., developed a predictive emission monitoring (PEM) system that achieved the required accuracy of the regulatory authorities using four of its gas turbine power plant facilities. Using the power plant operation variables to predict the nitric oxide (NO) portion of the exhaust emissions, the systems are founded on an artificial neural network (ANN). This paper provides a summary of the PEM system architecture and provides background information on the facilities used in the development of this approach. It was concluded that the PEM system provides a cost effective method to monitor emissions accurately and reliably at low emitting natural gas fired facilities. As well, there is a great potential for the system to be used by other industries to monitor and report emissions. The PEM system is an ideal system for the low emitting natural gas fired generating plants however the system could be adapted for other types of industries. 5 refs., 5 tabs., 2 figs.

  13. RBFNDOB-based neural network inverse control for non-minimum phase MIMO system with disturbances.

    Science.gov (United States)

    Li, Juan; Li, Shihua; Chen, Xisong; Yang, Jun

    2014-07-01

    An adaptive control strategy combining neural network inverse controller (NNIC) with RBFN disturbance observer (RBFNDOB) is developed for a multi-input-multi-output (MIMO) system with non-minimum phase, internal and external disturbances in this paper. Since the inverse model of system is unstable due to the non-minimum phase, a pseudo-plant is constructed, then the RBFN is used to identify the inverse model of pseudo-plant, which can track the parameter variations of system. By copying the structure and parameters of the identifier, the NNIC is obtained. Cascading the NNIC with the original plant, the MIMO system can be decoupled and linearized into independent SISO systems. For the independent decoupled system, the RBFNDOB employs a RBFN to observe the external disturbances and this estimate value is used as a feed-forward compensation term in controller. The case study on ball mill grinding circuit is presented. The effectiveness of the proposed method is demonstrated by simulation results and comparisons. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  14. Air-Sense: indoor environment monitoring evaluation system based on ZigBee network

    Science.gov (United States)

    Huang, Yang; Hu, Liang; Yang, Disheng; Liu, Hengchang

    2017-08-01

    In the modern life, people spend most of their time indoors. However, indoor environmental quality problems have always been affecting people’s social activities. In general, indoor environmental quality is also related to our indoor activities. Since most of the organic irritants and volatile gases are colorless, odorless and too tiny to be seen, because we have been unconsciously overlooked indoor environment quality. Consequently, our body suffer a great health problem. In this work, we propose Air-Sense system which utilizes the platform of ZigBee Network to collect and detect the real-time indoor environment quality. What’s more, Air-Sense system can also provide data analysis, and visualizing the results of the indoor environment to the user.

  15. Studying complex tourism systems: a novel approach based on networks derived from a time series

    CERN Document Server

    Baggio, Rodolfo

    2013-01-01

    A tourism destination is a complex dynamic system. As such it requires specific methods and tools to be analyzed and understood in order to better tailor governance and policy measures for steering the destination along an evolutionary growth path. Many proposals have been put forward for the investigation of complex systems and some have been successfully applied to tourism destinations. This paper uses a recent suggestion, that of transforming a time series into a network and analyzes it with the objective of uncovering the structural and dynamic features of a tourism destination. The algorithm, called visibility graph, is simple and its implementation straightforward, yet it is able to provide a number of interesting insights. An example is worked out using data from two destinations: Italy as a country and the island of Elba, one of its most known areas.

  16. Event-Based Impulsive Control of Continuous-Time Dynamic Systems and Its Application to Synchronization of Memristive Neural Networks.

    Science.gov (United States)

    Zhu, Wei; Wang, Dandan; Liu, Lu; Feng, Gang

    2017-08-18

    This paper investigates exponential stabilization of continuous-time dynamic systems (CDSs) via event-based impulsive control (EIC) approaches, where the impulsive instants are determined by certain state-dependent triggering condition. The global exponential stability criteria via EIC are derived for nonlinear and linear CDSs, respectively. It is also shown that there is no Zeno-behavior for the concerned closed loop control system. In addition, the developed event-based impulsive scheme is applied to the synchronization problem of master and slave memristive neural networks. Furthermore, a self-triggered impulsive control scheme is developed to avoid continuous communication between the master system and slave system. Finally, two numerical simulation examples are presented to illustrate the effectiveness of the proposed event-based impulsive controllers.

  17. A study and analysis of recommendation systems for location-based social network (LBSN with big data

    Directory of Open Access Journals (Sweden)

    Murale Narayanan

    2016-03-01

    Full Text Available Recommender systems play an important role in our day-to-day life. A recommender system automatically suggests an item to a user that he/she might be interested in. Small-scale datasets are used to provide recommendations based on location, but in real time, the volume of data is large. We have selected Foursquare dataset to study the need for big data in recommendation systems for location-based social network (LBSN. A few quality parameters like parallel processing and multimodal interface have been selected to study the need for big data in recommender systems. This paper provides a study and analysis of quality parameters of recommendation systems for LBSN with big data.

  18. Host Event Based Network Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Jonathan Chugg

    2013-01-01

    The purpose of INL’s research on this project is to demonstrate the feasibility of a host event based network monitoring tool and the effects on host performance. Current host based network monitoring tools work on polling which can miss activity if it occurs between polls. Instead of polling, a tool could be developed that makes use of event APIs in the operating system to receive asynchronous notifications of network activity. Analysis and logging of these events will allow the tool to construct the complete real-time and historical network configuration of the host while the tool is running. This research focused on three major operating systems commonly used by SCADA systems: Linux, WindowsXP, and Windows7. Windows 7 offers two paths that have minimal impact on the system and should be seriously considered. First is the new Windows Event Logging API, and, second, Windows 7 offers the ALE API within WFP. Any future work should focus on these methods.

  19. A Polynomial Subset-Based Efficient Multi-Party Key Management System for Lightweight Device Networks.

    Science.gov (United States)

    Mahmood, Zahid; Ning, Huansheng; Ghafoor, AtaUllah

    2017-03-24

    Wireless Sensor Networks (WSNs) consist of lightweight devices to measure sensitive data that are highly vulnerable to security attacks due to their constrained resources. In a similar manner, the internet-based lightweight devices used in the Internet of Things (IoT) are facing severe security and privacy issues because of the direct accessibility of devices due to their connection to the internet. Complex and resource-intensive security schemes are infeasible and reduce the network lifetime. In this regard, we have explored the polynomial distribution-based key establishment schemes and identified an issue that the resultant polynomial value is either storage intensive or infeasible when large values are multiplied. It becomes more costly when these polynomials are regenerated dynamically after each node join or leave operation and whenever key is refreshed. To reduce the computation, we have proposed an Efficient Key Management (EKM) scheme for multiparty communication-based scenarios. The proposed session key management protocol is established by applying a symmetric polynomial for group members, and the group head acts as a responsible node. The polynomial generation method uses security credentials and secure hash function. Symmetric cryptographic parameters are efficient in computation, communication, and the storage required. The security justification of the proposed scheme has been completed by using Rubin logic, which guarantees that the protocol attains mutual validation and session key agreement property strongly among the participating entities. Simulation scenarios are performed using NS 2.35 to validate the results for storage, communication, latency, energy, and polynomial calculation costs during authentication, session key generation, node migration, secure joining, and leaving phases. EKM is efficient regarding storage, computation, and communication overhead and can protect WSN-based IoT infrastructure.

  20. A Network Coverage Information-Based Sensor Registry System for IoT Environments

    Directory of Open Access Journals (Sweden)

    Hyunjun Jung

    2016-07-01

    Full Text Available The Internet of Things (IoT is expected to provide better services through the interaction of physical objects via the Internet. However, its limitations cause an interoperability problem when the sensed data are exchanged between the sensor nodes in wireless sensor networks (WSNs, which constitute the core infrastructure of the IoT. To address this problem, a Sensor Registry System (SRS is used. By using a SRS, the information of the heterogeneous sensed data remains pure. If users move along a road, their mobile devices predict their next positions and obtain the sensed data for that position from the SRS. If the WSNs in the location in which the users move are unstable, the sensed data will be lost. Consider a situation where the user passes through dangerous areas. If the user’s mobile device cannot receive information, they cannot be warned about the dangerous situation. To avoid this, two novel SRSs that use network coverage information have been proposed: one uses OpenSignal and the other uses the probabilistic distribution of the users accessing SRS. The empirical study showed that the proposed method can seamlessly provide services related to sensing data under any abnormal circumstance.

  1. A Network Coverage Information-Based Sensor Registry System for IoT Environments.

    Science.gov (United States)

    Jung, Hyunjun; Jeong, Dongwon; Lee, Sukhoon; On, Byung-Won; Baik, Doo-Kwon

    2016-07-25

    The Internet of Things (IoT) is expected to provide better services through the interaction of physical objects via the Internet. However, its limitations cause an interoperability problem when the sensed data are exchanged between the sensor nodes in wireless sensor networks (WSNs), which constitute the core infrastructure of the IoT. To address this problem, a Sensor Registry System (SRS) is used. By using a SRS, the information of the heterogeneous sensed data remains pure. If users move along a road, their mobile devices predict their next positions and obtain the sensed data for that position from the SRS. If the WSNs in the location in which the users move are unstable, the sensed data will be lost. Consider a situation where the user passes through dangerous areas. If the user's mobile device cannot receive information, they cannot be warned about the dangerous situation. To avoid this, two novel SRSs that use network coverage information have been proposed: one uses OpenSignal and the other uses the probabilistic distribution of the users accessing SRS. The empirical study showed that the proposed method can seamlessly provide services related to sensing data under any abnormal circumstance.

  2. Simulation of a Lunar Surface Base Power Distribution Network for the Constellation Lunar Surface Systems

    Science.gov (United States)

    Mintz, Toby; Maslowski, Edward A.; Colozza, Anthony; McFarland, Willard; Prokopius, Kevin P.; George, Patrick J.; Hussey, Sam W.

    2010-01-01

    The Lunar Surface Power Distribution Network Study team worked to define, breadboard, build and test an electrical power distribution system consistent with NASA's goal of providing electrical power to sustain life and power equipment used to explore the lunar surface. A testbed was set up to simulate the connection of different power sources and loads together to form a mini-grid and gain an understanding of how the power systems would interact. Within the power distribution scheme, each power source contributes to the grid in an independent manner without communication among the power sources and without a master-slave scenario. The grid consisted of four separate power sources and the accompanying power conditioning equipment. Overall system design and testing was performed. The tests were performed to observe the output and interaction of the different power sources as some sources are added and others are removed from the grid connection. The loads on the system were also varied from no load to maximum load to observe the power source interactions.

  3. A new and accurate fault location algorithm for combined transmission lines using Adaptive Network-Based Fuzzy Inference System

    Energy Technology Data Exchange (ETDEWEB)

    Sadeh, Javad; Afradi, Hamid [Electrical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, P.O. Box: 91775-1111, Mashhad (Iran)

    2009-11-15

    This paper presents a new and accurate algorithm for locating faults in a combined overhead transmission line with underground power cable using Adaptive Network-Based Fuzzy Inference System (ANFIS). The proposed method uses 10 ANFIS networks and consists of 3 stages, including fault type classification, faulty section detection and exact fault location. In the first part, an ANFIS is used to determine the fault type, applying four inputs, i.e., fundamental component of three phase currents and zero sequence current. Another ANFIS network is used to detect the faulty section, whether the fault is on the overhead line or on the underground cable. Other eight ANFIS networks are utilized to pinpoint the faults (two for each fault type). Four inputs, i.e., the dc component of the current, fundamental frequency of the voltage and current and the angle between them, are used to train the neuro-fuzzy inference systems in order to accurately locate the faults on each part of the combined line. The proposed method is evaluated under different fault conditions such as different fault locations, different fault inception angles and different fault resistances. Simulation results confirm that the proposed method can be used as an efficient means for accurate fault location on the combined transmission lines. (author)

  4. Immune system and zinc are associated with recurrent aphthous stomatitis. An assessment using a network-based approach.

    Directory of Open Access Journals (Sweden)

    César Rivera

    2017-09-01

    Full Text Available Objective: The aim of this research was to identify genes, proteins and processes from the biomedical information published on recurrent aphthous stomatitis (RAS using network-based foci. Methods: The clinical context was defined using MeSH terms for RAS and biomarkers, combined with words associated with risk. A set of protein coding genes was prioritized using the Génie web server and classified with PANTHER. For defining biologically relevant proteins, protein-protein interaction networks were constructed using Reactome database and Cytoscape. Top 20 proteins were then subjected to functional enrichment using STRING. Results: From 1,075,576 gene-abstract links, 1,491 genes were prioritized. Proteins were related to signaling molecule proteins (n=221, receptor proteins (n=221 and nucleic acid binding proteins (n=169. The network constructed with these proteins included 3,963 nodes and functional analysis showed that main processes involved immune system and zinc ion binding function. Conclusions: For the first time, bioinformatics tools were used for integrating pathways and networks associated with RAS. Molecules and processes associated with immune system recur robustly in all analyzed information. The molecular zinc ion binding function could be an area for exploring more specific and effective therapeutic interventions.

  5. Location based Network Optimizations for Mobile Wireless Networks

    DEFF Research Database (Denmark)

    Nielsen, Jimmy Jessen

    The availability of location information in mobile devices, e.g., through built-in GPS receivers in smart phones, has motivated the investigation of the usefulness of location based network optimizations. Since the quality of input information is important for network optimizations, a main focus...... of this work is to evaluate how location based network optimizations are affected by varying quality of input information such as location information and user movements. The first contribution in this thesis concerns cooperative network-based localization systems. The investigations focus on assessing...... the achievable accuracy of future localization system in mobile settings, as well as quantifying the impact of having a realistic model of the required measurement exchanges. Secondly, this work has considered different large scale and small scale location based network optimizations, namely centralized relay...

  6. 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.

  7. Design of FPGA Based Neural Network Controller for Earth Station Power System

    OpenAIRE

    Hassen T. Dorrah; Ninet M. A. El-Rahman; Faten H. Fahmy; Hanaa T. El-Madany

    2012-01-01

    Automation of generating hardware description language code from neural networks models can highly decrease time of implementation those networks into a digital devices, thus significant money savings. To implement the neural network into hardware designer, it is required to translate generated model into device structure. VHDL language is used to describe those networks into hardware. VHDL code has been proposed to implement ANNs as well as to present simulation results with floating point a...

  8. The spatial decision-supporting system combination of RBR & CBR based on artificial neural network and association rules

    Science.gov (United States)

    Tian, Yangge; Bian, Fuling

    2007-06-01

    The technology of artificial intelligence should be imported on the basis of the geographic information system to bring up the spatial decision-supporting system (SDSS). The paper discusses the structure of SDSS, after comparing the characteristics of RBR and CBR, the paper brings up the frame of a spatial decisional system that combines RBR and CBR, which has combined the advantages of them both. And the paper discusses the CBR in agriculture spatial decisions, the application of ANN (Artificial Neural Network) in CBR, and enriching the inference rule base based on association rules, etc. And the paper tests and verifies the design of this system with the examples of the evaluation of the crops' adaptability.

  9. A distributed topology information system for optical networks based on the semantic web

    NARCIS (Netherlands)

    van der Ham, J.; Dijkstra, F.; Grosso, P.; van der Pol, R.; Toonk, A.; de Laat, C.

    2008-01-01

    The research networking community has embraced novel network architectures to provide e-Science applications with dedicated connections instead of shared links. IP and optical services converge in these new infrastructures to form hybrid networks. Lightpaths are the services offered to clients in

  10. Computer-Aided Diagnosis Based on Convolutional Neural Network System for Colorectal Polyp Classification: Preliminary Experience.

    Science.gov (United States)

    Komeda, Yoriaki; Handa, Hisashi; Watanabe, Tomohiro; Nomura, Takanobu; Kitahashi, Misaki; Sakurai, Toshiharu; Okamoto, Ayana; Minami, Tomohiro; Kono, Masashi; Arizumi, Tadaaki; Takenaka, Mamoru; Hagiwara, Satoru; Matsui, Shigenaga; Nishida, Naoshi; Kashida, Hiroshi; Kudo, Masatoshi

    2017-01-01

    Computer-aided diagnosis (CAD) is becoming a next-generation tool for the diagnosis of human disease. CAD for colon polyps has been suggested as a particularly useful tool for trainee colonoscopists, as the use of a CAD system avoids the complications associated with endoscopic resections. In addition to conventional CAD, a convolutional neural network (CNN) system utilizing artificial intelligence (AI) has been developing rapidly over the past 5 years. We attempted to generate a unique CNN-CAD system with an AI function that studied endoscopic images extracted from movies obtained with colonoscopes used in routine examinations. Here, we report our preliminary results of this novel CNN-CAD system for the diagnosis of colon polyps. A total of 1,200 images from cases of colonoscopy performed between January 2010 and December 2016 at Kindai University Hospital were used. These images were extracted from the video of actual endoscopic examinations. Additional video images from 10 cases of unlearned processes were retrospectively assessed in a pilot study. They were simply diagnosed as either an adenomatous or nonadenomatous polyp. The number of images used by AI to learn to distinguish adenomatous from nonadenomatous was 1,200:600. These images were extracted from the videos of actual endoscopic examinations. The size of each image was adjusted to 256 × 256 pixels. A 10-hold cross-validation was carried out. The accuracy of the 10-hold cross-validation is 0.751, where the accuracy is the ratio of the number of correct answers over the number of all the answers produced by the CNN. The decisions by the CNN were correct in 7 of 10 cases. A CNN-CAD system using routine colonoscopy might be useful for the rapid diagnosis of colorectal polyp classification. Further prospective studies in an in vivo setting are required to confirm the effectiveness of a CNN-CAD system in routine colonoscopy. © 2017 S. Karger AG, Basel.

  11. Optimization on a Network-based Parallel Computer System for Supersonic Laminar Wing Design

    Science.gov (United States)

    Garcia, Joseph A.; Cheung, Samson; Holst, Terry L. (Technical Monitor)

    1995-01-01

    A set of Computational Fluid Dynamics (CFD) routines and flow transition prediction tools are integrated into a network based parallel numerical optimization routine. Through this optimization routine, the design of a 2-D airfoil and an infinitely swept wing will be studied in order to advance the design cycle capability of supersonic laminar flow wings. The goal of advancing supersonic laminar flow wing design is achieved by wisely choosing the design variables used in the optimization routine. The design variables are represented by the theory of Fourier series and potential theory. These theories, combined with the parallel CFD flow routines and flow transition prediction tools, provide a design space for a global optimal point to be searched. Finally, the parallel optimization routine enables gradient evaluations to be performed in a fast and parallel fashion.

  12. A Web of Things-Based Emerging Sensor Network Architecture for Smart Control Systems

    Directory of Open Access Journals (Sweden)

    Murad Khan

    2017-02-01

    Full Text Available The Web of Things (WoT plays an important role in the representation of the objects connected to the Internet of Things in a more transparent and effective way. Thus, it enables seamless and ubiquitous web communication between users and the smart things. Considering the importance of WoT, we propose a WoT-based emerging sensor network (WoT-ESN, which collects data from sensors, routes sensor data to the web, and integrate smart things into the web employing a representational state transfer (REST architecture. A smart home scenario is introduced to evaluate the proposed WoT-ESN architecture. The smart home scenario is tested through computer simulation of the energy consumption of various household appliances, device discovery, and response time performance. The simulation results show that the proposed scheme significantly optimizes the energy consumption of the household appliances and the response time of the appliances.

  13. A Web of Things-Based Emerging Sensor Network Architecture for Smart Control Systems

    Science.gov (United States)

    Khan, Murad; Silva, Bhagya Nathali; Han, Kijun

    2017-01-01

    The Web of Things (WoT) plays an important role in the representation of the objects connected to the Internet of Things in a more transparent and effective way. Thus, it enables seamless and ubiquitous web communication between users and the smart things. Considering the importance of WoT, we propose a WoT-based emerging sensor network (WoT-ESN), which collects data from sensors, routes sensor data to the web, and integrate smart things into the web employing a representational state transfer (REST) architecture. A smart home scenario is introduced to evaluate the proposed WoT-ESN architecture. The smart home scenario is tested through computer simulation of the energy consumption of various household appliances, device discovery, and response time performance. The simulation results show that the proposed scheme significantly optimizes the energy consumption of the household appliances and the response time of the appliances.  PMID:28208787

  14. A Web of Things-Based Emerging Sensor Network Architecture for Smart Control Systems.

    Science.gov (United States)

    Khan, Murad; Silva, Bhagya Nathali; Han, Kijun

    2017-02-09

    The Web of Things (WoT) plays an important role in the representation of the objects connected to the Internet of Things in a more transparent and effective way. Thus, it enables seamless and ubiquitous web communication between users and the smart things. Considering the importance of WoT, we propose a WoT-based emerging sensor network (WoT-ESN), which collects data from sensors, routes sensor data to the web, and integrate smart things into the web employing a representational state transfer (REST) architecture. A smart home scenario is introduced to evaluate the proposed WoT-ESN architecture. The smart home scenario is tested through computer simulation of the energy consumption of various household appliances, device discovery, and response time performance. The simulation results show that the proposed scheme significantly optimizes the energy consumption of the household appliances and the response time of the appliances.

  15. REMOTE, a Wireless Sensor Network Based System to Monitor Rowing Performance

    Directory of Open Access Journals (Sweden)

    Jordi Llosa

    2009-09-01

    Full Text Available In this paper, we take a hard look at the performance of REMOTE, a sensor network based application that provides a detailed picture of a boat movement, individual rower performance, or his/her performance compared with other crew members. The application analyzes data gathered with a WSN strategically deployed over a boat to obtain information on the boat and oar movements. Functionalities of REMOTE are compared to those of RowX [1] outdoor instrument, a commercial wired sensor instrument designed for similar purposes. This study demonstrates that with smart geometrical configuration of the sensors, rotation and translation of the oars and boat can be obtained. Three different tests are performed: laboratory calibration allows us to become familiar with the accelerometer readings and validate the theory, ergometer tests which help us to set the acquisition parameters, and on boat tests shows the application potential of this technologies in sports.

  16. A Digital Architecture for a Network-Based Learning Health System: Integrating Chronic Care Management, Quality Improvement, and Research.

    Science.gov (United States)

    Marsolo, Keith; Margolis, Peter A; Forrest, Christopher B; Colletti, Richard B; Hutton, John J

    2015-01-01

    We collaborated with the ImproveCareNow Network to create a proof-of-concept architecture for a network-based Learning Health System. This collaboration involved transitioning an existing registry to one that is linked to the electronic health record (EHR), enabling a "data in once" strategy. We sought to automate a series of reports that support care improvement while also demonstrating the use of observational registry data for comparative effectiveness research. We worked with three leading EHR vendors to create EHR-based data collection forms. We automated many of ImproveCareNow's analytic reports and developed an application for storing protected health information and tracking patient consent. Finally, we deployed a cohort identification tool to support feasibility studies and hypothesis generation. There is ongoing uptake of the system. To date, 31 centers have adopted the EHR-based forms and 21 centers are uploading data to the registry. Usage of the automated reports remains high and investigators have used the cohort identification tools to respond to several clinical trial requests. The current process for creating EHR-based data collection forms requires groups to work individually with each vendor. A vendor-agnostic model would allow for more rapid uptake. We believe that interfacing network-based registries with the EHR would allow them to serve as a source of decision support. Additional standards are needed in order for this vision to be achieved, however. We have successfully implemented a proof-of-concept Learning Health System while providing a foundation on which others can build. We have also highlighted opportunities where sponsors could help accelerate progress.

  17. Design and development of safety evaluation system of buildings on a seismic field based on the network platform

    Science.gov (United States)

    Sun, Baitao; Zhang, Lei; Chen, Xiangzhao; Zhang, Xinghua

    2015-03-01

    This paper describes a set of on-site earthquake safety evaluation systems for buildings, which were developed based on a network platform. The system embedded into the quantitative research results which were completed in accordance with the provisions from Post-earthquake Field Works, Part 2: Safety Assessment of Buildings, GB18208.2 -2001, and was further developed into an easy-to-use software platform. The system is aimed at allowing engineering professionals, civil engineeing technicists or earthquake-affected victims on site to assess damaged buildings through a network after earthquakes. The authors studied the function structure, process design of the safety evaluation module, and hierarchical analysis algorithm module of the system in depth, and developed the general architecture design, development technology and database design of the system. Technologies such as hierarchical architecture design and Java EE were used in the system development, and MySQL5 was adopted in the database development. The result is a complete evaluation process of information collection, safety evaluation, and output of damage and safety degrees, as well as query and statistical analysis of identified buildings. The system can play a positive role in sharing expert post-earthquake experience and promoting safety evaluation of buildings on a seismic field.

  18. An Efficient Network Coding-Based Fault-Tolerant Mechanism in WBAN for Smart Healthcare Monitoring Systems

    Directory of Open Access Journals (Sweden)

    Yuhuai Peng

    2017-08-01

    Full Text Available As a key technology in smart healthcare monitoring systems, wireless body area networks (WBANs can pre-embed sensors and sinks on body surface or inside bodies for collecting different vital signs parameters, such as human Electrocardiograph (ECG, Electroencephalograph (EEG, Electromyogram (EMG, body temperature, blood pressure, blood sugar, blood oxygen, etc. Using real-time online healthcare, patients can be tracked and monitored in normal or emergency conditions at their homes, hospital rooms, and in Intensive Care Units (ICUs. In particular, the reliability and effectiveness of the packets transmission will be directly related to the timely rescue of critically ill patients with life-threatening injuries. However, traditional fault-tolerant schemes either have the deficiency of underutilised resources or react too slowly to failures. In future healthcare systems, the medical Internet of Things (IoT for real-time monitoring can integrate sensor networks, cloud computing, and big data techniques to address these problems. It can collect and send patient’s vital parameter signal and safety monitoring information to intelligent terminals and enhance transmission reliability and efficiency. Therefore, this paper presents a design in healthcare monitoring systems for a proactive reliable data transmission mechanism with resilience requirements in a many-to-one stream model. This Network Coding-based Fault-tolerant Mechanism (NCFM first proposes a greedy grouping algorithm to divide the topology into small logical units; it then constructs a spanning tree based on random linear network coding to generate linearly independent coding combinations. Numerical results indicate that this transmission scheme works better than traditional methods in reducing the probability of packet loss, the resource redundant rate, and average delay, and can increase the effective throughput rate.

  19. Network operating system

    Science.gov (United States)

    Perotto, E.

    1987-08-01

    The Network Operating System is an addition to CMS designed to allow multitasking operation, while conserving all the facilities of CMS: file system, interactivity, high level language environment. Multitasking is useful for server virtual machines, e.g. Network Transport Managers, File Managers, Disk space Managers, Tape Unit Managers, where the execution of a task involves long waits due to I/O completion, VCMF communication delays or human responses, during which the task status stays as a control block in memory, while the virtual machine serves other users executing the same lines of code. Multitasking is not only for multi-user service: a big data reduction program may run as a main task, while a side task, connected to the virtual console, gives reports on the ongoing work of the main task in response to user commands and steers the main task through common data. All the service routines (Wait, Create and Delete Task, Get and Release Buffer, VMCF Open and Close Link, Send and Receive, I/O and Console Routines) are FORTRAN callable, and may be used from any language environment consistent with the same parameter passing conventions. The outstanding feature of this system is efficiency, no user defined SVC are used, and the use of other privileged instructions as LPSW or SSM is the bare necessary, so that CP (with the associated overhead) is not too involved. System code and read-only data are write-protected with a different storage key from CMS and user program.

  20. 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.

  1. Camera characterization using back-propagation artificial neutral network based on Munsell system

    Science.gov (United States)

    Liu, Ye; Yu, Hongfei; Shi, Junsheng

    2008-02-01

    The camera output RGB signals do not directly corresponded to the tristimulus values based on the CIE standard colorimetric observer, i.e., it is a device-independent color space. For achieving accurate color information, we need to do color characterization, which can be used to derive a transformation between camera RGB values and CIE XYZ values. In this paper we set up a Back-Propagation (BP) artificial neutral network to realize the mapping from camera RGB to CIE XYZ. We used the Munsell Book of Color with total number 1267 as color samples. Each patch of the Munsell Book of Color was recorded by camera, and the RGB values could be obtained. The Munsell Book of Color were taken in a light booth and the surround was kept dark. The viewing/illuminating geometry was 0/45 using D 65 illuminate. The lighting illuminating the reference target needs to be as uniform as possible. The BP network was a 5-layer one and (3-10-10-10-3), which was selected through our experiments. 1000 training samples were selected randomly from the 1267 samples, and the rest 267 samples were as the testing samples. Experimental results show that the mean color difference between the reproduced colors and target colors is 0.5 CIELAB color-difference unit, which was smaller than the biggest acceptable color difference 2 CIELAB color-difference unit. The results satisfy some applications for the more accurate color measurements, such as medical diagnostics, cosmetics production, the color reappearance of different media, etc.

  2. A method of groundwater quality assessment based on fuzzy network-CANFIS and geographic information system (GIS)

    Science.gov (United States)

    Gholami, V.; Khaleghi, M. R.; Sebghati, M.

    2016-12-01

    The process of water quality testing is money/time-consuming, quite important and difficult stage for routine measurements. Therefore, use of models has become commonplace in simulating water quality. In this study, the coactive neuro-fuzzy inference system (CANFIS) was used to simulate groundwater quality. Further, geographic information system (GIS) was used as the pre-processor and post-processor tool to demonstrate spatial variation of groundwater quality. All important factors were quantified and groundwater quality index (GWQI) was developed. The proposed model was trained and validated by taking a case study of Mazandaran Plain located in northern part of Iran. The factors affecting groundwater quality were the input variables for the simulation, whereas GWQI index was the output. The developed model was validated to simulate groundwater quality. Network validation was performed via comparison between the estimated and actual GWQI values. In GIS, the study area was separated to raster format in the pixel dimensions of 1 km and also by incorporation of input data layers of the Fuzzy Network-CANFIS model; the geo-referenced layers of the effective factors in groundwater quality were earned. Therefore, numeric values of each pixel with geographical coordinates were entered to the Fuzzy Network-CANFIS model and thus simulation of groundwater quality was accessed in the study area. Finally, the simulated GWQI indices using the Fuzzy Network-CANFIS model were entered into GIS, and hence groundwater quality map (raster layer) based on the results of the network simulation was earned. The study's results confirm the high efficiency of incorporation of neuro-fuzzy techniques and GIS. It is also worth noting that the general quality of the groundwater in the most studied plain is fairly low.

  3. A method of groundwater quality assessment based on fuzzy network-CANFIS and geographic information system (GIS)

    Science.gov (United States)

    Gholami, V.; Khaleghi, M. R.; Sebghati, M.

    2017-11-01

    The process of water quality testing is money/time-consuming, quite important and difficult stage for routine measurements. Therefore, use of models has become commonplace in simulating water quality. In this study, the coactive neuro-fuzzy inference system (CANFIS) was used to simulate groundwater quality. Further, geographic information system (GIS) was used as the pre-processor and post-processor tool to demonstrate spatial variation of groundwater quality. All important factors were quantified and groundwater quality index (GWQI) was developed. The proposed model was trained and validated by taking a case study of Mazandaran Plain located in northern part of Iran. The factors affecting groundwater quality were the input variables for the simulation, whereas GWQI index was the output. The developed model was validated to simulate groundwater quality. Network validation was performed via comparison between the estimated and actual GWQI values. In GIS, the study area was separated to raster format in the pixel dimensions of 1 km and also by incorporation of input data layers of the Fuzzy Network-CANFIS model; the geo-referenced layers of the effective factors in groundwater quality were earned. Therefore, numeric values of each pixel with geographical coordinates were entered to the Fuzzy Network-CANFIS model and thus simulation of groundwater quality was accessed in the study area. Finally, the simulated GWQI indices using the Fuzzy Network-CANFIS model were entered into GIS, and hence groundwater quality map (raster layer) based on the results of the network simulation was earned. The study's results confirm the high efficiency of incorporation of neuro-fuzzy techniques and GIS. It is also worth noting that the general quality of the groundwater in the most studied plain is fairly low.

  4. All-optical virtual private network system in OFDM based long-reach PON using RSOA re-modulation technique

    Science.gov (United States)

    Kim, Chang-Hun; Jung, Sang-Min; Kang, Su-Min; Han, Sang-Kook

    2015-01-01

    We propose an all-optical virtual private network (VPN) system in an orthogonal frequency division multiplexing (OFDM) based long reach PON (LR-PON). In the optical access network field, technologies based on fundamental upstream (U/S) and downstream (D/S) have been actively researched to accommodate explosion of data capacity. However, data transmission among the end users which is arisen from cloud computing, file-sharing and interactive game takes a large weight inside of internet traffic. Moreover, this traffic is predicted to increase more if Internet of Things (IoT) services are activated. In a conventional PON, VPN data is transmitted through ONU-OLT-ONU via U/S and D/S carriers. It leads to waste of bandwidth and energy due to O-E-O conversion in the OLT and round-trip propagation between OLT and remote node (RN). Also, it causes inevitable load to the OLT for electrical buffer, scheduling and routing. The network inefficiency becomes more critical in a LR-PON which has been researched as an effort to reduce CAPEX and OPEX through metro-access consolidation. In the proposed system, the VPN data is separated from conventional U/S and re-modulated on the D/S carrier by using RSOA in the ONUs to avoid bandwidth consumption of U/S and D/S unlike in previously reported system. Moreover, the transmitted VPN data is re-directed to the ONUs by wavelength selective reflector device in the RN without passing through the OLT. Experimental demonstration for the VPN communication system in an OFDM based LR-PON has been verified.

  5. Internet of Things (IoT Based Design of a Secure and Lightweight Body Area Network (BAN Healthcare System

    Directory of Open Access Journals (Sweden)

    Yong-Yuan Deng

    2017-12-01

    Full Text Available As sensor networks and cloud computation technologies have rapidly developed over recent years, many services and applications integrating these technologies into daily life have come together as an Internet of Things (IoT. At the same time, aging populations have increased the need for expanded and more efficient elderly care services. Fortunately, elderly people can now wear sensing devices which relay data to a personal wireless device, forming a body area network (BAN. These personal wireless devices collect and integrate patients’ personal physiological data, and then transmit the data to the backend of the network for related diagnostics. However, a great deal of the information transmitted by such systems is sensitive data, and must therefore be subject to stringent security protocols. Protecting this data from unauthorized access is thus an important issue in IoT-related research. In regard to a cloud healthcare environment, scholars have proposed a secure mechanism to protect sensitive patient information. Their schemes provide a general architecture; however, these previous schemes still have some vulnerability, and thus cannot guarantee complete security. This paper proposes a secure and lightweight body-sensor network based on the Internet of Things for cloud healthcare environments, in order to address the vulnerabilities discovered in previous schemes. The proposed authentication mechanism is applied to a medical reader to provide a more comprehensive architecture while also providing mutual authentication, and guaranteeing data integrity, user untraceability, and forward and backward secrecy, in addition to being resistant to replay attack.

  6. Internet of Things (IoT) Based Design of a Secure and Lightweight Body Area Network (BAN) Healthcare System.

    Science.gov (United States)

    Deng, Yong-Yuan; Chen, Chin-Ling; Tsaur, Woei-Jiunn; Tang, Yung-Wen; Chen, Jung-Hsuan

    2017-12-15

    As sensor networks and cloud computation technologies have rapidly developed over recent years, many services and applications integrating these technologies into daily life have come together as an Internet of Things (IoT). At the same time, aging populations have increased the need for expanded and more efficient elderly care services. Fortunately, elderly people can now wear sensing devices which relay data to a personal wireless device, forming a body area network (BAN). These personal wireless devices collect and integrate patients' personal physiological data, and then transmit the data to the backend of the network for related diagnostics. However, a great deal of the information transmitted by such systems is sensitive data, and must therefore be subject to stringent security protocols. Protecting this data from unauthorized access is thus an important issue in IoT-related research. In regard to a cloud healthcare environment, scholars have proposed a secure mechanism to protect sensitive patient information. Their schemes provide a general architecture; however, these previous schemes still have some vulnerability, and thus cannot guarantee complete security. This paper proposes a secure and lightweight body-sensor network based on the Internet of Things for cloud healthcare environments, in order to address the vulnerabilities discovered in previous schemes. The proposed authentication mechanism is applied to a medical reader to provide a more comprehensive architecture while also providing mutual authentication, and guaranteeing data integrity, user untraceability, and forward and backward secrecy, in addition to being resistant to replay attack.

  7. Artificial neural network modification of simulation-based fitting: application to a protein-lipid system

    NARCIS (Netherlands)

    Nazarov, P.V.; Apanasovich, V.V.; Lutkovski, V.M.; Yatskou, M.M.; Koehorst, R.B.M.; Hemminga, M.A.

    2004-01-01

    Simulation-based fitting has been applied to data analysis and parameter determination of complex experimental systems in many areas of chemistry and biophysics. However, this method is limited because of the time costs of the calculations. In this paper it is proposed to approximate and substitute

  8. An EEG-Based Biometric System Using Eigenvector Centrality in Resting State Brain Networks

    NARCIS (Netherlands)

    Fraschini, M.; Hillebrand, A.; Demuru, M.; Didaci, L.; Marcialis, G.L.

    2015-01-01

    Recently, there has been a growing interest in the use of brain activity for biometric systems. However, so far these studies have focused mainly on basic features of the Electroencephalography. In this study we propose an approach based on phase synchronization, to investigate personal distinctive

  9. Panacea: Automating Attack Classification for Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro; Hartel, Pieter H.

    2009-01-01

    Anomaly-based intrusion detection systems are usually criticized because they lack a classication of attack, thus security teams have to manually inspect any raised alert to classify it. We present a new approach, Panacea, to automatically and systematically classify attacks detected by an

  10. Panacea: Automating Attack Classification for Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro; Hartel, Pieter H.; Kirda, E.; Jha, S.; Balzarotti, D.

    Anomaly-based intrusion detection systems are usually criticized because they lack a classication of attack, thus security teams have to manually inspect any raised alert to classify it. We present a new approach, Panacea, to automatically and systematically classify attacks detected by an

  11. Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Xiaofei Yan

    2016-08-01

    Full Text Available Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN-based multi-sensor system and artificial neural network (ANN. Sensors (CO, CO2, smoke, air temperature and relative humidity were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO2 and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO2; smoke and temperature; smoke, CO2 and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5% than single-sensor input (50.9%–92.5%. Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

  12. Real-Time Identification of Smoldering and Flaming Combustion Phases in Forest Using a Wireless Sensor Network-Based Multi-Sensor System and Artificial Neural Network.

    Science.gov (United States)

    Yan, Xiaofei; Cheng, Hong; Zhao, Yandong; Yu, Wenhua; Huang, Huan; Zheng, Xiaoliang

    2016-08-04

    Diverse sensing techniques have been developed and combined with machine learning method for forest fire detection, but none of them referred to identifying smoldering and flaming combustion phases. This study attempts to real-time identify different combustion phases using a developed wireless sensor network (WSN)-based multi-sensor system and artificial neural network (ANN). Sensors (CO, CO₂, smoke, air temperature and relative humidity) were integrated into one node of WSN. An experiment was conducted using burning materials from residual of forest to test responses of each node under no, smoldering-dominated and flaming-dominated combustion conditions. The results showed that the five sensors have reasonable responses to artificial forest fire. To reduce cost of the nodes, smoke, CO₂ and temperature sensors were chiefly selected through correlation analysis. For achieving higher identification rate, an ANN model was built and trained with inputs of four sensor groups: smoke; smoke and CO₂; smoke and temperature; smoke, CO₂ and temperature. The model test results showed that multi-sensor input yielded higher predicting accuracy (≥82.5%) than single-sensor input (50.9%-92.5%). Based on these, it is possible to reduce the cost with a relatively high fire identification rate and potential application of the system can be tested in future under real forest condition.

  13. The efficiency of reactant site sampling in network-free simulation of rule-based models for biochemical systems.

    Science.gov (United States)

    Yang, Jin; Hlavacek, William S

    2011-10-01

    Rule-based models, which are typically formulated to represent cell signaling systems, can now be simulated via various network-free simulation methods. In a network-free method, reaction rates are calculated for rules that characterize molecular interactions, and these rule rates, which each correspond to the cumulative rate of all reactions implied by a rule, are used to perform a stochastic simulation of reaction kinetics. Network-free methods, which can be viewed as generalizations of Gillespie's method, are so named because these methods do not require that a list of individual reactions implied by a set of rules be explicitly generated, which is a requirement of other methods for simulating rule-based models. This requirement is impractical for rule sets that imply large reaction networks (i.e. long lists of individual reactions), as reaction network generation is expensive. Here, we compare the network-free simulation methods implemented in RuleMonkey and NFsim, general-purpose software tools for simulating rule-based models encoded in the BioNetGen language. The method implemented in NFsim uses rejection sampling to correct overestimates of rule rates, which introduces null events (i.e. time steps that do not change the state of the system being simulated). The method implemented in RuleMonkey uses iterative updates to track rule rates exactly, which avoids null events. To ensure a fair comparison of the two methods, we developed implementations of the rejection and rejection-free methods specific to a particular class of kinetic models for multivalent ligand-receptor interactions. These implementations were written with the intention of making them as much alike as possible, minimizing the contribution of irrelevant coding differences to efficiency differences. Simulation results show that performance of the rejection method is equal to or better than that of the rejection-free method over wide parameter ranges. However, when parameter values are such that

  14. Facsimile Network System in RCP

    Science.gov (United States)

    Muramatsu, Kazuya

    Recruit Computer Print Corp. has compiled Weekly Housing Magazine by use of its own CTS (Computerized Type Setting) resulting in the real estate database as byproduct. Based on the database it has made the network linking with sponsors, real estate companies. It has transmitted lists for data cleaning directly from computer enabling to save manpower and reduce time in the compilation process. The author describes the objectives, details, functions and promise of the system.

  15. Research on Fuzzy Immune Self-Adaptive PID Algorithm Based on New Smith Predictor for Networked Control System

    Directory of Open Access Journals (Sweden)

    Haitao Zhang

    2015-01-01

    Full Text Available We first analyze the effect of network-induced delay on the stability of networked control systems (NCSs. Then, aiming at stochastic characteristics of the time delay, we introduce a new Smith predictor to remove the exponential function with the time delay in the closed-loop characteristic equation of the NCS. Furthermore, we combine the fuzzy PID algorithm with the fuzzy immune control algorithm and present a fuzzy immune self-adaptive PID algorithm to compensate the influence of the model deviation of the controlled object. At last, a kind of fuzzy immune self-adaptive PID algorithm based on new Smith predictor is presented to apply to the NCS. The simulation research on a DC motor is given to show the effectiveness of the proposed algorithm.

  16. Performance of Network Based EEW Systems in Marmara Region; VS, ElarmS-2 and PRESTo

    Science.gov (United States)

    Kuyuk, H. S.; Pinar, A.; Comoglu, M.; Erdik, M. O.

    2015-12-01

    Several earthquake early warning algorithms are in operation in various countries. Kandilli Observatory and Earthquake Engineering Institute (KOERI) implemented and recently running three different EEWS within KOERI network in Marmara Region. Due to high probability of an earthquake with Mw > 7 in the next 30 years in the Marmara Sea, there is an urgent need to evaluate existing EEWS performance and to find out how reliable an EEW is in terms of calculating time, location, magnitude of an earthquake in the region. Here we assessed performance of Virtual Seismologist (VS), Earthquake Alarm System-2 (ElarmS-2) and PRobabilistic and Evolutionary early warning SysTem (PRESTo) which are developed at Caltech, UC Berkeley and University of Naples respectively and are being monitored for over six months. We choose four representative earthquakes that are detected by three algorithm and evaluated their performances. We found each algorithm has its own strengths and weakness in calculating source parameters. Even though, algorithms are not optimized, cities around the Marmara Sea could get up to 50 seconds warning time with existing infrastructure. First alert could be given in 12 seconds after origin time and blind-zone could get minimum 40 km radius. The main reason of delays on detecting earthquake is packet size of data (7 seconds in average). We confirm that SeisComp3 platform requires additional time to locate earthquakes and it needs to be optimized for EEWS. This study could help algorithm developer of three EEWS to optimize their systems in other seismically active region and different earthquake environment. We believe results derived from this study will provide precious information for both habitants in Marmara region and geo-scientist.

  17. Network Medicine: A Network-based Approach to Human Diseases

    Science.gov (United States)

    Ghiassian, Susan Dina

    With the availability of large-scale data, it is now possible to systematically study the underlying interaction maps of many complex systems in multiple disciplines. Statistical physics has a long and successful history in modeling and characterizing systems with a large number of interacting individuals. Indeed, numerous approaches that were first developed in the context of statistical physics, such as the notion of random walks and diffusion processes, have been applied successfully to study and characterize complex systems in the context of network science. Based on these tools, network science has made important contributions to our understanding of many real-world, self-organizing systems, for example in computer science, sociology and economics. Biological systems are no exception. Indeed, recent studies reflect the necessity of applying statistical and network-based approaches in order to understand complex biological systems, such as cells. In these approaches, a cell is viewed as a complex network consisting of interactions among cellular components, such as genes and proteins. Given the cellular network as a platform, machinery, functionality and failure of a cell can be studied with network-based approaches, a field known as systems biology. Here, we apply network-based approaches to explore human diseases and their associated genes within the cellular network. This dissertation is divided in three parts: (i) A systematic analysis of the connectivity patterns among disease proteins within the cellular network. The quantification of these patterns inspires the design of an algorithm which predicts a disease-specific subnetwork containing yet unknown disease associated proteins. (ii) We apply the introduced algorithm to explore the common underlying mechanism of many complex diseases. We detect a subnetwork from which inflammatory processes initiate and result in many autoimmune diseases. (iii) The last chapter of this dissertation describes the

  18. Anomaly based intrusion detection for a biometric identification system using neural networks

    CSIR Research Space (South Africa)

    Mgabile, T

    2012-10-01

    Full Text Available detection technique that analyses the fingerprint biometric network traffic for evidence of intrusion. The neural network algorithm that imitates the way a human brain works is used in this study to classify normal traffic and learn the correct traffic...

  19. Network Intrusion Detection System using Apache Storm

    Directory of Open Access Journals (Sweden)

    Muhammad Asif Manzoor

    2017-06-01

    Full Text Available Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various systems are proposed to enhance the network security. We are proposing to use anomaly based network intrusion detection system in this work. Anomaly based intrusion detection system can identify the new network threats. We also propose to use Real-time Big Data Stream Processing Framework, Apache Storm, for the implementation of network intrusion detection system. Apache Storm can help to manage the network traffic which is generated at enormous speed and size and the network traffic speed and size is constantly increasing. We have used Support Vector Machine in this work. We use Knowledge Discovery and Data Mining 1999 (KDD’99 dataset to test and evaluate our proposed solution.

  20. Recognition System of Indonesia Sign Language based on Sensor and Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Endang Supriyati

    2013-09-01

    Full Text Available Sign language as a kind of gestures is one of the most natural ways of communication for most people in deaf community. The aim of the sign language recognition is to provide a translation for sign gestures into meaningful text or speech so that communication between deaf and hearing society can easily be made. In this research, the Indonesian sign language recognition system based on flex sensors and an accelerometer is developed. This recognition system uses a sensory glove to capture data. The sensor data that are processed into feature vector are the 5-fingers bending andthe palm acceleration when performing the sign language. The most important part of the recognition system is a featureextraction. In this research, histogram is used as feature extraction. The extracted features are used as data training and data testing for Adaptive Neighborhood based Modified Backpropagation (ANMBP. The system is implemented andtested using a data set of 1000 samples of 50 Indonesia sign, 20 samples for each sign. Among these 500 data were usedas the training data, and the remaining 500 data were used as the testing data. The system obtains the recognition rate of91.60% in offline mode.

  1. Performance Analysis of Public Transport Systems in Nanjing Based on Network Topology

    Science.gov (United States)

    Li, Ping; Zhu, Zhen-Tao; Zhou, Jing; Ding, Jin-Yuan; Wang, Hong-Wei; Wei, Shan-Sen

    The urban public transport network (UPTN) in Nanjing is characterized by a complex network with topological pedestals. The empirical data indicates that it is a small-world network. Under malicious attack to the high connectivity nodes of the network, the average path-length will increase 2.5 times, the reliability and traffic capacity of the UPTN will greatly decline, and the travel expenditure will distinctively increase. The topological significance of stations and routes are redefined to help assess the small-world property of UPTNs, so as to improve city transportation. It is also found that if the urban rail transit, such as metro, is introduced to the UPTN, then the topological diameter of the network is reduced, and its structure is optimized.

  2. Computer Networks A Systems Approach

    CERN Document Server

    Peterson, Larry L

    2011-01-01

    This best-selling and classic book teaches you the key principles of computer networks with examples drawn from the real world of network and protocol design. Using the Internet as the primary example, the authors explain various protocols and networking technologies. Their systems-oriented approach encourages you to think about how individual network components fit into a larger, complex system of interactions. Whatever your perspective, whether it be that of an application developer, network administrator, or a designer of network equipment or protocols, you will come away with a "big pictur

  3. A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks.

    Science.gov (United States)

    Xiang, Zuoshuang; Qin, Tingting; Qin, Zhaohui S; He, Yongqun

    2013-10-16

    The large amount of literature in the post-genomics era enables the study of gene interactions and networks using all available articles published for a specific organism. MeSH is a controlled vocabulary of medical and scientific terms that is used by biomedical scientists to manually index articles in the PubMed literature database. We hypothesized that genome-wide gene-MeSH term associations from the PubMed literature database could be used to predict implicit gene-to-gene relationships and networks. While the gene-MeSH associations have been used to detect gene-gene interactions in some studies, different methods have not been well compared, and such a strategy has not been evaluated for a genome-wide literature analysis. Genome-wide literature mining of gene-to-gene interactions allows ranking of the best gene interactions and investigation of comprehensive biological networks at a genome level. The genome-wide GenoMesh literature mining algorithm was developed by sequentially generating a gene-article matrix, a normalized gene-MeSH term matrix, and a gene-gene matrix. The gene-gene matrix relies on the calculation of pairwise gene dissimilarities based on gene-MeSH relationships. An optimized dissimilarity score was identified from six well-studied functions based on a receiver operating characteristic (ROC) analysis. Based on the studies with well-studied Escherichia coli and less-studied Brucella spp., GenoMesh was found to accurately identify gene functions using weighted MeSH terms, predict gene-gene interactions not reported in the literature, and cluster all the genes studied from an organism using the MeSH-based gene-gene matrix. A web-based GenoMesh literature mining program is also available at: http://genomesh.hegroup.org. GenoMesh also predicts gene interactions and networks among genes associated with specific MeSH terms or user-selected gene lists. The GenoMesh algorithm and web program provide the first genome-wide, MeSH-based literature mining

  4. URBAN-NET: A Network-based Infrastructure Monitoring and Analysis System for Emergency Management and Public Safety

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Sangkeun (Matt) [ORNL; Chen, Liangzhe [ORNL; Duan, Sisi [ORNL; Chinthavali, Supriya [ORNL; Shankar, Mallikarjun (Arjun) [ORNL; Prakash, B. Aditya [Virginia Tech, Blacksburg, VA

    2016-01-01

    Abstract Critical Infrastructures (CIs) such as energy, water, and transportation are complex networks that are crucial for sustaining day-to-day commodity flows vital to national security, economic stability, and public safety. The nature of these CIs is such that failures caused by an extreme weather event or a man-made incident can trigger widespread cascading failures, sending ripple effects at regional or even national scales. To minimize such effects, it is critical for emergency responders to identify existing or potential vulnerabilities within CIs during such stressor events in a systematic and quantifiable manner and take appropriate mitigating actions. We present here a novel critical infrastructure monitoring and analysis system named URBAN-NET. The system includes a software stack and tools for monitoring CIs, pre-processing data, interconnecting multiple CI datasets as a heterogeneous network, identifying vulnerabilities through graph-based topological analysis, and predicting consequences based on what-if simulations along with visualization. As a proof-of-concept, we present several case studies to show the capabilities of our system. We also discuss remaining challenges and future work.

  5. A Cold Start Context-Aware Recommender System for Tour Planning Using Artificial Neural Network and Case Based Reasoning

    Directory of Open Access Journals (Sweden)

    Zahra Bahramian

    2017-01-01

    Full Text Available Nowadays, large amounts of tourism information and services are available over the Web. This makes it difficult for the user to search for some specific information such as selecting a tour in a given city as an ordered set of points of interest. Moreover, the user rarely knows all his needs upfront and his preferences may change during a recommendation process. The user may also have a limited number of initial ratings and most often the recommender system is likely to face the well-known cold start problem. The objective of the research presented in this paper is to introduce a hybrid interactive context-aware tourism recommender system that takes into account user’s feedbacks and additional contextual information. It offers personalized tours to the user based on his preferences thanks to the combination of a case based reasoning framework and an artificial neural network. The proposed method has been tried in the city of Tehran in Iran. The results show that the proposed method outperforms current artificial neural network methods and combinations of case based reasoning with k-nearest neighbor methods in terms of user effort, accuracy, and user satisfaction.

  6. Modeling of the nonlinearity in nano-displacement measuring system based on the neural network approaches

    Science.gov (United States)

    Olyaee, Saeed; Ebrahimpour, Reza; Hamedi, Samaneh; Jafarlou, Farzad M.

    2009-08-01

    Periodic nonlinearity is the main limitation on the accuracy of the nano-displacement measurements in the heterodyne interferometers. It is mainly produced by non-ideal polarized beams of the leaser and imperfect alignment of the optical components. In this paper, we model the periodic nonlinearity resulting from non-orthogonality and ellipticity of the laser beam by using combination of neural networks such as stacked generalization method and mixture of experts. The ensemble neural networks used for nonlinearity modeling are compared with single neural networks such as multi layer percepterons and radial basis function.

  7. Research on Adaptive Neural Network Control System Based on Nonlinear U-Model with Time-Varying Delay

    Directory of Open Access Journals (Sweden)

    Fengxia Xu

    2014-01-01

    Full Text Available U-model can approximate a large class of smooth nonlinear time-varying delay system to any accuracy by using time-varying delay parameters polynomial. This paper proposes a new approach, namely, U-model approach, to solving the problems of analysis and synthesis for nonlinear systems. Based on the idea of discrete-time U-model with time-varying delay, the identification algorithm of adaptive neural network is given for the nonlinear model. Then, the controller is designed by using the Newton-Raphson formula and the stability analysis is given for the closed-loop nonlinear systems. Finally, illustrative examples are given to show the validity and applicability of the obtained results.

  8. Control theory of digitally networked dynamic systems

    CERN Document Server

    Lunze, Jan

    2013-01-01

    The book gives an introduction to networked control systems and describes new modeling paradigms, analysis methods for event-driven, digitally networked systems, and design methods for distributed estimation and control. Networked model predictive control is developed as a means to tolerate time delays and packet loss brought about by the communication network. In event-based control the traditional periodic sampling is replaced by state-dependent triggering schemes. Novel methods for multi-agent systems ensure complete or clustered synchrony of agents with identical or with individual dynamic

  9. GIS BASED SYSTEM FOR POST-EARTHQUAKE CRISIS MANAGMENT USING CELLULAR NETWORK

    Directory of Open Access Journals (Sweden)

    M. Raeesi

    2013-09-01

    Full Text Available Earthquakes are among the most destructive natural disasters. Earthquakes happen mainly near the edges of tectonic plates, but they may happen just about anywhere. Earthquakes cannot be predicted. Quick response after disasters, like earthquake, decreases loss of life and costs. Massive earthquakes often cause structures to collapse, trapping victims under dense rubble for long periods of time. After the earthquake and destroyed some areas, several teams are sent to find the location of the destroyed areas. The search and rescue phase usually is maintained for many days. Time reduction for surviving people is very important. A Geographical Information System (GIS can be used for decreasing response time and management in critical situations. Position estimation in short period of time time is important. This paper proposes a GIS based system for post–earthquake disaster management solution. This system relies on several mobile positioning methods such as cell-ID and TA method, signal strength method, angel of arrival method, time of arrival method and time difference of arrival method. For quick positioning, the system can be helped by any person who has a mobile device. After positioning and specifying the critical points, the points are sent to a central site for managing the procedure of quick response for helping. This solution establishes a quick way to manage the post–earthquake crisis.

  10. GIS Based System for Post-Earthquake Crisis Managment Using Cellular Network

    Science.gov (United States)

    Raeesi, M.; Sadeghi-Niaraki, A.

    2013-09-01

    Earthquakes are among the most destructive natural disasters. Earthquakes happen mainly near the edges of tectonic plates, but they may happen just about anywhere. Earthquakes cannot be predicted. Quick response after disasters, like earthquake, decreases loss of life and costs. Massive earthquakes often cause structures to collapse, trapping victims under dense rubble for long periods of time. After the earthquake and destroyed some areas, several teams are sent to find the location of the destroyed areas. The search and rescue phase usually is maintained for many days. Time reduction for surviving people is very important. A Geographical Information System (GIS) can be used for decreasing response time and management in critical situations. Position estimation in short period of time time is important. This paper proposes a GIS based system for post-earthquake disaster management solution. This system relies on several mobile positioning methods such as cell-ID and TA method, signal strength method, angel of arrival method, time of arrival method and time difference of arrival method. For quick positioning, the system can be helped by any person who has a mobile device. After positioning and specifying the critical points, the points are sent to a central site for managing the procedure of quick response for helping. This solution establishes a quick way to manage the post-earthquake crisis.

  11. Design and Management of Networked Information Systems

    DEFF Research Database (Denmark)

    Havn, Erling; Bansler, Jørgen P.

    1996-01-01

    -based IS. There are several reasons for this: (a) Networked IS are large and complex systems; (b) in most cases, one has to deal with a number of existing - probably heterogenous - technical hardware and software platforms and link them together in a network; (c) differences in organizational culture, work......In this paper, we present a newly started research project at the Center for Tele-Information at the Technical University of Denmark. The project focuses on the design and management of networked information systems, that is computer-based IS linked by a wide area network and supporting...... communication between geographically dispersed organizational units. Examples include logistics systems, airline booking systems, and CSCW systems. We assume that the design and implementation of networked IS is significantly more difficult and risky than the development of traditional "stand-alone" computer...

  12. Evaluation of a Novel Computer Color Matching System Based on the Improved Back-Propagation Neural Network Model.

    Science.gov (United States)

    Wei, Jiaqiang; Peng, Mengdong; Li, Qing; Wang, Yining

    2016-11-09

    To explore the feasibility of a novel computer color-matching (CCM) system based on the improved back-propagation neural network (BPNN) model by comparing it with the traditional visual method. Forty-three metal-ceramic specimens were fabricated by proportionally mixing porcelain powders. Thirty-nine specimens were randomly selected to train the BPNN model, while the remaining four specimens were used to test and calibrate the model. A CCM system based on the improved BPNN model was constructed using MATLAB software. A comparison of the novel CCM system and the traditional visual method was conducted by evaluating the color reproduction results of 10 maxillary central incisors. Metal-ceramic specimens were fabricated using two color reproduction approaches. Color distributions (L*, a*, and b*) of the target teeth and of the corresponding metal-ceramic specimens were measured using a spectroradiometer. Color differences (ΔE) and color distributions (ΔL*, Δa*, and Δb*) between the teeth and their corresponding specimens were calculated. The average ΔE value of the CCM system was 1.89 ± 0.75, which was lower than that of the visual approach (3.54 ± 1.11, p systems, except for ΔL* (p > 0.05). The novel CCM system produced greater accuracy in color reproduction within the given color space than the traditional visual approach. © 2016 by the American College of Prosthodontists.

  13. Network repair based on community structure

    Science.gov (United States)

    Wang, Tianyu; Zhang, Jun; Sun, Xiaoqian; Wandelt, Sebastian

    2017-06-01

    Real-world complex systems are often fragile under disruptions. Accordingly, research on network repair has been studied intensively. Recently proposed efficient strategies for network disruption, based on collective influence, call for more research on efficient network repair strategies. Existing strategies are often designed to repair networks with local information only. However, the absence of global information impedes the creation of efficient repairs. Motivated by this limitation, we propose a concept of community-level repair, which leverages the community structure of the network during the repair process. Moreover, we devise a general framework of network repair, with in total six instances. Evaluations on real-world and random networks show the effectiveness and efficiency of the community-level repair approaches, compared to local and random repairs. Our study contributes to a better understanding of repair processes, and reveals that exploitation of the community structure improves the repair process on a disrupted network significantly.

  14. Network of networks in Linux operating system

    Science.gov (United States)

    Wang, Haoqin; Chen, Zhen; Xiao, Guanping; Zheng, Zheng

    2016-04-01

    Operating system represents one of the most complex man-made systems. In this paper, we analyze Linux Operating System (LOS) as a complex network via modeling functions as nodes and function calls as edges. It is found that for the LOS network and modularized components within it, the out-degree follows an exponential distribution and the in-degree follows a power-law distribution. For better understanding the underlying design principles of LOS, we explore the coupling correlations of components in LOS from aspects of topology and function. The result shows that the component for device drivers has a strong manifestation in topology while a weak manifestation in function. However, the component for process management shows the contrary phenomenon. Moreover, in an effort to investigate the impact of system failures on networks, we make a comparison between the networks traced from normal and failure status of LOS. This leads to a conclusion that the failure will change function calls which should be executed in normal status and introduce new function calls in the meanwhile.

  15. An e-consent-based shared EHR system architecture for integrated healthcare networks.

    Science.gov (United States)

    Bergmann, Joachim; Bott, Oliver J; Pretschner, Dietrich P; Haux, Reinhold

    2007-01-01

    Virtual integration of distributed patient data promises advantages over a consolidated health record, but raises questions mainly about practicability and authorization concepts. Our work aims on specification and development of a virtual shared health record architecture using a patient-centred integration and authorization model. A literature survey summarizes considerations of current architectural approaches. Complemented by a methodical analysis in two regional settings, a formal architecture model was specified and implemented. Results presented in this paper are a survey of architectural approaches for shared health records and an architecture model for a virtual shared EHR, which combines a patient-centred integration policy with provider-oriented document management. An electronic consent system assures, that access to the shared record remains under control of the patient. A corresponding system prototype has been developed and is currently being introduced and evaluated in a regional setting. The proposed architecture is capable of partly replacing message-based communications. Operating highly available provider repositories for the virtual shared EHR requires advanced technology and probably means additional costs for care providers. Acceptance of the proposed architecture depends on transparently embedding document validation and digital signature into the work processes. The paradigm shift from paper-based messaging to a "pull model" needs further evaluation.

  16. Computer networks ISE a systems approach

    CERN Document Server

    Peterson, Larry L

    2007-01-01

    Computer Networks, 4E is the only introductory computer networking book written by authors who have had first-hand experience with many of the protocols discussed in the book, who have actually designed some of them as well, and who are still actively designing the computer networks today. This newly revised edition continues to provide an enduring, practical understanding of networks and their building blocks through rich, example-based instruction. The authors' focus is on the why of network design, not just the specifications comprising today's systems but how key technologies and p

  17. Improving the Coefficients of Proportional-Integral Controller Based On System Identification Process on Doosti Irrigation Network

    Directory of Open Access Journals (Sweden)

    S. M. Seyedmousavi

    2016-02-01

    of irrigation network capacity. For this reason, it is recommended to custodians of irrigation networks to design and employment of these controllers in irrigation networks with more attention. In present control system IP controller was used. This controller requires the calculation of adjustment coefficients of control algorithm. For comparison between the calculation of these coefficients by trial and error and the identification system, the IP controller for EPC canal of Doosti Irrigation was designed. Then its performance was studied based on the method of canal operation and standard indices. The results indicated that the tuned algorithm control using SI has considerable accuracy and potential to control the flow and to damp the perturbations concluding from structural and hydraulic disturbances. Also this algorithm provides demand oriented distribution and performance promotion of water distribution system. Since in this study a relatively long canal includes multiple reaches and structures such as inverted siphon was studied, the capability of PI and SI process is also confirmed in these situations.

  18. Cloud-based Networked Visual Servo Control

    DEFF Research Database (Denmark)

    Wu, Haiyan; Lu, Lei; Chen, Chih-Chung

    2013-01-01

    feedback, ii) a stabilizing control law for the networked visual servo control system with time-varying feedback time delay, and iii) a sending rate scheduling strategy aiming at reducing the communication network load. The performance of the networked visual servo control system with sending rate......The performance of vision-based control systems, in particular of highly dynamic vision-based motion control systems, is often limited by the low sampling rate of the visual feedback caused by the long image processing time. In order to overcome this problem, the networked visual servo control......, which integrates networked computational resources for cloud image processing, is considered in this article. The main contributions of this article are i) a real-time transport protocol for transmitting large volume image data on a cloud computing platform, which enables high sampling rate visual...

  19. Views of wireless network systems.

    Energy Technology Data Exchange (ETDEWEB)

    Young, William Frederick; Duggan, David Patrick

    2003-10-01

    Wireless networking is becoming a common element of industrial, corporate, and home networks. Commercial wireless network systems have become reliable, while the cost of these solutions has become more affordable than equivalent wired network solutions. The security risks of wireless systems are higher than wired and have not been studied in depth. This report starts to bring together information on wireless architectures and their connection to wired networks. We detail information contained on the many different views of a wireless network system. The method of using multiple views of a system to assist in the determination of vulnerabilities comes from the Information Design Assurance Red Team (IDART{trademark}) Methodology of system analysis developed at Sandia National Laboratories.

  20. Mapping biological systems to network systems

    CERN Document Server

    Rathore, Heena

    2016-01-01

    The book presents the challenges inherent in the paradigm shift of network systems from static to highly dynamic distributed systems – it proposes solutions that the symbiotic nature of biological systems can provide into altering networking systems to adapt to these changes. The author discuss how biological systems – which have the inherent capabilities of evolving, self-organizing, self-repairing and flourishing with time – are inspiring researchers to take opportunities from the biology domain and map them with the problems faced in network domain. The book revolves around the central idea of bio-inspired systems -- it begins by exploring why biology and computer network research are such a natural match. This is followed by presenting a broad overview of biologically inspired research in network systems -- it is classified by the biological field that inspired each topic and by the area of networking in which that topic lies. Each case elucidates how biological concepts have been most successfully ...

  1. How the interbank market becomes systemically dangerous: an agent-based network model of financial distress propagation

    CERN Document Server

    Serri, Matteo; Cimini, Giulio

    2016-01-01

    Assessing the stability of economic systems is a fundamental research focus in economics, that has become increasingly interdisciplinary in the currently troubled economic situation. In particular, much attention has been devoted to the interbank lending market as an important diffusion channel for financial distress during the recent crisis. In this work we study the stability of the interbank market to exogenous shocks using an agent-based network framework. Our model encompasses several ingredients that have been recognized in the literature as pro-cyclical triggers of financial distress in the banking system: credit and liquidity shocks through bilateral exposures, liquidity hoarding due to counterparty creditworthiness deterioration, target leveraging policies and fire-sales spillovers. But we exclude the possibility of central authorities intervention. We implement this framework on a dataset of 183 European banks that were publicly traded between 2004 and 2013. We document the extreme fragility of the ...

  2. Implementation of Maintenance System Based on Bluetooth Low Energy for Hermetic Inline Amplifiers in CATV Networks

    Directory of Open Access Journals (Sweden)

    Katsuhiro Naito

    2016-02-01

    Full Text Available Cable television (CATV systems generally consist of a headend, trunk cables, distribution cables in the neighborhood, drop cables to a home and in-house wiring, and terminal equipment. Coaxial cables bring a CATV signal to customer premises through a service drop, an overhead or underground cable. Hermetic inline amplifiers are used to amplify the attenuated CATV signal due to propagation loss or splitting the coaxial cable. They are usually installed on utility poles. Therefore, maintenance methods for inline amplifiers on utility poles are important issues in CATV operations. This paper proposes a new maintenance system for inline amplifiers in CATV systems, and develops a prototype implementation. The proposed system consists of an amplifier gain analyser to measure amplification performance of inline amplifiers, a special smartphone application, and a cloud server. The proposed amplifier gain analyser is composed of three functions: a generation of high frequency signals for testing, measurement of the test signal gain, and wireless communication based on Bluetooth Low Energy (BLE. We develop a signal generation circuit for a test signal and a smoothing circuit for converting the high frequency test signals into DC signals. The amplifier gain analyser can evaluate an amplifier gain by comparing an input test signal from the signal generation circuit and an output test signal from an inline amplifier. The measurement function uses Nordic nRF51822, which is a System on Chip (SoC for BLE because Nordic nRF51822 has some AD converter ports for evaluating the DC signals. The smartphone application employs BLE communication function to collect the measured amplifier gain from the amplifier gain analyser. Therefore, we developed a special data collection application for iOS. The data collection application has a central function of BLE, and can find a target peripheral device that is the amplifier gain analyser in this paper. Therefore, technicians

  3. Process query systems for network security monitoring

    Science.gov (United States)

    Berk, Vincent; Fox, Naomi

    2005-05-01

    In this paper we present the architecture of our network security monitoring infrastructure based on a Process Query System (PQS). PQS offers a new and powerful way of efficiently processing data streams, based on process descriptions that are submitted as queries. In this case the data streams are familiar network sensors, such as Snort, Netfilter, and Tripwire. The process queries describe the dynamics of network attacks and failures, such as worms, multistage attacks, and router failures. Using PQS the task of monitoring enterprise class networks is simplified, offering a priority-based GUI to the security administrator that clearly outlines events that require immediate attention. The PQS-Net system is deployed on an unsecured production network; the system has successfully detected many diverse attacks and failures.

  4. A fuzzy logic based network intrusion detection system for predicting the TCP SYN flooding attack

    CSIR Research Space (South Africa)

    Mkuzangwe, Nenekazi NP

    2017-04-01

    Full Text Available Fuzzy logic is one of the powerful tools for reasoning under uncertainty and since uncertainty is an intrinsic characteristic of intrusion analysis, Fuzzy logic is therefore an appropriate tool to use to analyze intrusions in a Network. This paper...

  5. The Neural Bases of Reading: The Accommodation of the Brain's Reading Network to Writing Systems

    NARCIS (Netherlands)

    Perfetti, C.A.; Liu, Y.; Fiez, J.; Tan, L.H.; Cornelissen, P.; Hansen, P.; Kringelbach, M.; Pugh, K.

    2010-01-01

    This chapter explores the highly contrastive cases of English and Chinese to examine how the neural basis of reading accommodates variability in the structure of languages. The notion of accommodation, in fact, is central to the analysis. It argues that the reading network must accommodate variation

  6. Safety Assessment for Electrical Motor Drive System Based on SOM Neural Network

    Directory of Open Access Journals (Sweden)

    Linghui Meng

    2016-01-01

    Full Text Available With the development of the urban rail train, safety and reliability have become more and more important. In this paper, the fault degree and health degree of the system are put forward based on the analysis of electric motor drive system’s control principle. With the self-organizing neural network’s advantage of competitive learning and unsupervised clustering, the system’s health clustering and safety identification are worked out. With the switch devices’ faults data obtained from the dSPACE simulation platform, the health assessment algorithm is verified. And the results show that the algorithm can achieve the system’s fault diagnosis and health assessment, which has a point in the health assessment and maintenance for the train.

  7. Cognitive Radio-based Home Area Networks

    NARCIS (Netherlands)

    Sarijari, M.A.B.

    2016-01-01

    A future home area network (HAN) is envisaged to consist of a large number of devices that support various applications such as smart grid, security and safety systems, voice call, and video streaming. Most of these home devices are communicating based on various wireless networking technologies

  8. Systemic risk on different interbank network topologies

    Science.gov (United States)

    Lenzu, Simone; Tedeschi, Gabriele

    2012-09-01

    In this paper we develop an interbank market with heterogeneous financial institutions that enter into lending agreements on different network structures. Credit relationships (links) evolve endogenously via a fitness mechanism based on agents' performance. By changing the agent's trust on its neighbor's performance, interbank linkages self-organize themselves into very different network architectures, ranging from random to scale-free topologies. We study which network architecture can make the financial system more resilient to random attacks and how systemic risk spreads over the network. To perturb the system, we generate a random attack via a liquidity shock. The hit bank is not automatically eliminated, but its failure is endogenously driven by its incapacity to raise liquidity in the interbank network. Our analysis shows that a random financial network can be more resilient than a scale free one in case of agents' heterogeneity.

  9. Risks in Networked Computer Systems

    OpenAIRE

    Klingsheim, André N.

    2008-01-01

    Networked computer systems yield great value to businesses and governments, but also create risks. The eight papers in this thesis highlight vulnerabilities in computer systems that lead to security and privacy risks. A broad range of systems is discussed in this thesis: Norwegian online banking systems, the Norwegian Automated Teller Machine (ATM) system during the 90's, mobile phones, web applications, and wireless networks. One paper also comments on legal risks to bank cust...

  10. High-performance flat data center network architecture based on scalable and flow-controlled optical switching system

    Science.gov (United States)

    Calabretta, Nicola; Miao, Wang; Dorren, Harm

    2016-03-01

    Traffic in data centers networks (DCNs) is steadily growing to support various applications and virtualization technologies. Multi-tenancy enabling efficient resource utilization is considered as a key requirement for the next generation DCs resulting from the growing demands for services and applications. Virtualization mechanisms and technologies can leverage statistical multiplexing and fast switch reconfiguration to further extend the DC efficiency and agility. We present a novel high performance flat DCN employing bufferless and distributed fast (sub-microsecond) optical switches with wavelength, space, and time switching operation. The fast optical switches can enhance the performance of the DCNs by providing large-capacity switching capability and efficiently sharing the data plane resources by exploiting statistical multiplexing. Benefiting from the Software-Defined Networking (SDN) control of the optical switches, virtual DCNs can be flexibly created and reconfigured by the DCN provider. Numerical and experimental investigations of the DCN based on the fast optical switches show the successful setup of virtual network slices for intra-data center interconnections. Experimental results to assess the DCN performance in terms of latency and packet loss show less than 10^-5 packet loss and 640ns end-to-end latency with 0.4 load and 16- packet size buffer. Numerical investigation on the performance of the systems when the port number of the optical switch is scaled to 32x32 system indicate that more than 1000 ToRs each with Terabit/s interface can be interconnected providing a Petabit/s capacity. The roadmap to photonic integration of large port optical switches will be also presented.

  11. Environmental Assessment for Testing of the Network Embedded Systems Technology (NEST) at Eglin Air Force Base

    Science.gov (United States)

    2004-08-01

    with other sensors and with several hubs located within the network. The hubs (also called gateways) are slightly larger than the sensors and box ...and shallow water grasses. When they are juveniles, they feed on plants and organisms such as crabs, jellyfish , sponges, snails, and worms (Ernst...650 to 1,200 pounds (295 to 545 kilograms [kg]) (Bronsgerma 1976). Leatherbacks are omnivorous, with a diet consisting of sea grasses, jellyfish

  12. Associative network based on cyclodextrin polymer: a model system for drug delivery.

    Science.gov (United States)

    Layre, Anne-Magali; Volet, Gisèle; Wintgens, Véronique; Amiel, Catherine

    2009-12-14

    Associative networks have been elaborated by mixing in aqueous media a cyclodextrin polymer to a dextran bearing adamantyl groups. The two polymers interact mainly via inclusion complexes between adamantyl groups and cyclodextrin cavities, as evidenced by the high complexation constants determined by isothermal titration microcalorimetry (approximately 10(4) L mol(-1)). Additional interaction mechanisms participating in the strength of the network, mainly hydrogen bonding and electrostatic interactions, are sensitive to the pH and ionic strength of the medium, as shown by pH-dependent rheological properties. The loading and release of an apolar model drug, benzophenone, has been studied at two pH values and different cyclodextrin polymer content. Slow releases have been obtained (10-12 days) with slower kinetics at pH 2 than at pH 7. Analysis of the experiments at pH 7 shows that drug release is controlled both by diffusion in the network and by inclusion complex interactions with cyclodextrin cavities.

  13. Optimal Design of the Feeder-Bus Network Based on the Transfer System

    Directory of Open Access Journals (Sweden)

    Lianbo Deng

    2013-01-01

    Full Text Available This paper studied the classic feeder-bus network design problem (FBNDP, which can be described as follows: for the passenger travel demand between rail stations and bus stops on a given urban transit network, it designs the optimal feeder bus routes and frequencies so as to minimize the passengers’ travel expense and the operator’s cost. We extended the demand pattern of M-to-1 in most existing researches to M-to-M. We comprehensively considered the passenger travel cost, which includes the waiting and riding cost on the bus, riding cost on rail, and transfer cost between these two transportation modes, and presented a new genetic algorithm that determines the optimal feeder-bus operating frequencies under strict constraint conditions. The numerical examples under different demand patterns have been experienced and analysed, which showed the robustness and efficiency of the presented algorithm. We also found that the distribution pattern of the travel demand has a significant influence on the feeder-bus network construction.

  14. A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems

    Science.gov (United States)

    Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

    2017-01-01

    Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

  15. A spiking neural network model of 3D perception for event-based neuromorphic stereo vision systems.

    Science.gov (United States)

    Osswald, Marc; Ieng, Sio-Hoi; Benosman, Ryad; Indiveri, Giacomo

    2017-01-12

    Stereo vision is an important feature that enables machine vision systems to perceive their environment in 3D. While machine vision has spawned a variety of software algorithms to solve the stereo-correspondence problem, their implementation and integration in small, fast, and efficient hardware vision systems remains a difficult challenge. Recent advances made in neuromorphic engineering offer a possible solution to this problem, with the use of a new class of event-based vision sensors and neural processing devices inspired by the organizing principles of the brain. Here we propose a radically novel model that solves the stereo-correspondence problem with a spiking neural network that can be directly implemented with massively parallel, compact, low-latency and low-power neuromorphic engineering devices. We validate the model with experimental results, highlighting features that are in agreement with both computational neuroscience stereo vision theories and experimental findings. We demonstrate its features with a prototype neuromorphic hardware system and provide testable predictions on the role of spike-based representations and temporal dynamics in biological stereo vision processing systems.

  16. [Network structures in biological systems].

    Science.gov (United States)

    Oleskin, A V

    2013-01-01

    Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

  17. A Novel C2C E-Commerce Recommender System Based on Link Prediction: Applying Social Network Analysis

    OpenAIRE

    Bahabadi, Mohammad Dehghan; Golpayegani, Alireza Hashemi; Esmaeili, Leila

    2014-01-01

    Social network analysis emerged as an important research topic in sociology decades ago, and it has also attracted scientists from various fields of study like psychology, anthropology, geography and economics. In recent years, a significant number of researches has been conducted on using social network analysis to design e-commerce recommender systems. Most of the current recommender systems are designed for B2C e-commerce websites. This paper focuses on building a recommendation algorithm ...

  18. The Networking of Interactive Bibliographic Retrieval Systems.

    Science.gov (United States)

    Marcus, Richard S.; Reintjes, J. Francis

    Research in networking of heterogeneous interactive bibliographic retrieval systems is being conducted which centers on the concept of a virtual retrieval system. Such a virtual system would be created through a translating computer interface that would provide access to the different retrieval systems and data bases in a uniform and convenient…

  19. Language Networks as Complex Systems

    Science.gov (United States)

    Lee, Max Kueiming; Ou, Sheue-Jen

    2008-01-01

    Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

  20. Financial Network Systemic Risk Contributions

    NARCIS (Netherlands)

    Hautsch, N.; Schaumburg, J.; Schienle, M.

    2015-01-01

    We propose the realized systemic risk beta as a measure of financial companies' contribution to systemic risk, given network interdependence between firms' tail risk exposures. Conditional on statistically pre-identified network spillover effects and market and balance sheet information, we define

  1. 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...

  2. Barriers to healthcare coordination in market-based and decentralized public health systems: a qualitative study in healthcare networks of Colombia and Brazil

    Science.gov (United States)

    Vargas, Ingrid; Mogollón-Pérez, Amparo Susana; De Paepe, Pierre; Ferreira da Silva, Maria Rejane; Unger, Jean-Pierre; Vázquez, María-Luisa

    2016-01-01

    Although integrated healthcare networks (IHNs) are promoted in Latin America in response to health system fragmentation, few analyses on the coordination of care across levels in these networks have been conducted in the region. The aim is to analyse the existence of healthcare coordination across levels of care and the factors influencing it from the health personnel’ perspective in healthcare networks of two countries with different health systems: Colombia, with a social security system based on managed competition and Brazil, with a decentralized national health system. A qualitative, exploratory and descriptive–interpretative study was conducted, based on a case study of healthcare networks in four municipalities. Individual semi-structured interviews were conducted with a three stage theoretical sample of (a) health (112) and administrative (66) professionals of different care levels, and (b) managers of providers (42) and insurers (14). A thematic content analysis was conducted, segmented by cases, informant groups and themes. The results reveal poor clinical information transfer between healthcare levels in all networks analysed, with added deficiencies in Brazil in the coordination of access and clinical management. The obstacles to care coordination are related to the organization of both the health system and the healthcare networks. In the health system, there is the existence of economic incentives to compete (exacerbated in Brazil by partisan political interests), the fragmentation and instability of networks in Colombia and weak planning and evaluation in Brazil. In the healthcare networks, there are inadequate working conditions (temporary and/or part-time contracts) which hinder the use of coordination mechanisms, and inadequate professional training for implementing a healthcare model in which primary care should act as coordinator in patient care. Reforms are needed in these health systems and networks in order to modify incentives

  3. Barriers to healthcare coordination in market-based and decentralized public health systems: a qualitative study in healthcare networks of Colombia and Brazil.

    Science.gov (United States)

    Vargas, Ingrid; Mogollón-Pérez, Amparo Susana; De Paepe, Pierre; Ferreira da Silva, Maria Rejane; Unger, Jean-Pierre; Vázquez, María-Luisa

    2016-07-01

    Although integrated healthcare networks (IHNs) are promoted in Latin America in response to health system fragmentation, few analyses on the coordination of care across levels in these networks have been conducted in the region. The aim is to analyse the existence of healthcare coordination across levels of care and the factors influencing it from the health personnel' perspective in healthcare networks of two countries with different health systems: Colombia, with a social security system based on managed competition and Brazil, with a decentralized national health system. A qualitative, exploratory and descriptive-interpretative study was conducted, based on a case study of healthcare networks in four municipalities. Individual semi-structured interviews were conducted with a three stage theoretical sample of (a) health (112) and administrative (66) professionals of different care levels, and (b) managers of providers (42) and insurers (14). A thematic content analysis was conducted, segmented by cases, informant groups and themes. The results reveal poor clinical information transfer between healthcare levels in all networks analysed, with added deficiencies in Brazil in the coordination of access and clinical management. The obstacles to care coordination are related to the organization of both the health system and the healthcare networks. In the health system, there is the existence of economic incentives to compete (exacerbated in Brazil by partisan political interests), the fragmentation and instability of networks in Colombia and weak planning and evaluation in Brazil. In the healthcare networks, there are inadequate working conditions (temporary and/or part-time contracts) which hinder the use of coordination mechanisms, and inadequate professional training for implementing a healthcare model in which primary care should act as coordinator in patient care. Reforms are needed in these health systems and networks in order to modify incentives, strengthen

  4. Development of an indoor location based service test bed and geographic information system with a wireless sensor network.

    Science.gov (United States)

    Jan, Shau-Shiun; Hsu, Li-Ta; Tsai, Wen-Ming

    2010-01-01

    In order to provide the seamless navigation and positioning services for indoor environments, an indoor location based service (LBS) test bed is developed to integrate the indoor positioning system and the indoor three-dimensional (3D) geographic information system (GIS). A wireless sensor network (WSN) is used in the developed indoor positioning system. Considering the power consumption, in this paper the ZigBee radio is used as the wireless protocol, and the received signal strength (RSS) fingerprinting positioning method is applied as the primary indoor positioning algorithm. The matching processes of the user location include the nearest neighbor (NN) algorithm, the K-weighted nearest neighbors (KWNN) algorithm, and the probabilistic approach. To enhance the positioning accuracy for the dynamic user, the particle filter is used to improve the positioning performance. As part of this research, a 3D indoor GIS is developed to be used with the indoor positioning system. This involved using the computer-aided design (CAD) software and the virtual reality markup language (VRML) to implement a prototype indoor LBS test bed. Thus, a rapid and practical procedure for constructing a 3D indoor GIS is proposed, and this GIS is easy to update and maintenance for users. The building of the Department of Aeronautics and Astronautics at National Cheng Kung University in Taiwan is used as an example to assess the performance of various algorithms for the indoor positioning system.

  5. Development of an Indoor Location Based Service Test Bed and Geographic Information System with a Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Shau-Shiun Jan

    2010-03-01

    Full Text Available In order to provide the seamless navigation and positioning services for indoor environments, an indoor location based service (LBS test bed is developed to integrate the indoor positioning system and the indoor three-dimensional (3D geographic information system (GIS. A wireless sensor network (WSN is used in the developed indoor positioning system. Considering the power consumption, in this paper the ZigBee radio is used as the wireless protocol, and the received signal strength (RSS fingerprinting positioning method is applied as the primary indoor positioning algorithm. The matching processes of the user location include the nearest neighbor (NN algorithm, the K-weighted nearest neighbors (KWNN algorithm, and the probabilistic approach. To enhance the positioning accuracy for the dynamic user, the particle filter is used to improve the positioning performance. As part of this research, a 3D indoor GIS is developed to be used with the indoor positioning system. This involved using the computer-aided design (CAD software and the virtual reality markup language (VRML to implement a prototype indoor LBS test bed. Thus, a rapid and practical procedure for constructing a 3D indoor GIS is proposed, and this GIS is easy to update and maintenance for users. The building of the Department of Aeronautics and Astronautics at National Cheng Kung University in Taiwan is used as an example to assess the performance of various algorithms for the indoor positioning system.

  6. Design and Evaluation of the User-Adapted Program Scheduling system based on Bayesian Network and Constraint Satisfaction

    Science.gov (United States)

    Iwasaki, Hirotoshi; Sega, Shinichiro; Hiraishi, Hironori; Mizoguchi, Fumio

    In recent years, lots of music content can be stored in mobile computing devices, such as a portable digital music player and a car navigation system. Moreover, various information content like news or traffic information can be acquired always anywhere by a cellular communication and a wireless LAN. However, usability issues arise from the simple interfaces of mobile computing devices. Moreover, retrieving and selecting such content poses safety issues, especially while driving. Thus, it is important for the mobile system to recommend content automatically adapted to user's preference and situation. In this paper, we present the user-adapted program scheduling that generates sequences of content (Program) suiting user's preference and situation based on the Bayesian network and the Constraint Satisfaction Problem (CSP) technique. We also describe the design and evaluation of its realization system, the Personal Program Producer (P3). First, preference such as a genre ratio of content in a program is learned as a Bayesian network model using simple operations such as a skip behavior. A model including each content tends to become large-scale. In order to make it small, we present the model separation method that carries out losslessly compression of the model. Using the model, probabilistic distributions of preference to generate constraints are inferred. Finally satisfying the constraints, a program is produced. This kind of CSP has an issue of which the number of variables is not fixedness. In order to make it variable, we propose a method using metavariables. To evaluate the above methods, we applied them to P3 on a car navigation system. User evaluations helped us clarify that the P3 can produce the program that a user prefers and adapt it to the user.

  7. Networking systems design and development

    CERN Document Server

    Chao, Lee

    2009-01-01

    Effectively integrating theory and hands-on practice, Networking Systems Design and Development provides students and IT professionals with the knowledge and skills needed to design, implement, and manage fully functioning network systems using readily available Linux networking tools. Recognizing that most students are beginners in the field of networking, the text provides step-by-step instruction for setting up a virtual lab environment at home. Grounded in real-world applications, this book provides the ideal blend of conceptual instruction and lab work to give students and IT professional

  8. Cascaded evolutionary algorithm for nonlinear system identification based on correlation functions and radial basis functions neural networks

    Science.gov (United States)

    Ayala, Helon Vicente Hultmann; Coelho, Leandro dos Santos

    2016-02-01

    The present work introduces a procedure for input selection and parameter estimation for system identification based on Radial Basis Functions Neural Networks (RBFNNs) models with an improved objective function based on the residuals and its correlation function coefficients. We show the results when the proposed methodology is applied to model a magnetorheological damper, with real acquired data, and other two well-known benchmarks. The canonical genetic and differential evolution algorithms are used in cascade to decompose the problem of defining the lags taken as the inputs of the model and its related parameters based on the simultaneous minimization of the residuals and higher orders correlation functions. The inner layer of the cascaded approach is composed of a population which represents the lags on the inputs and outputs of the system and an outer layer represents the corresponding parameters of the RBFNN. The approach is able to define both the inputs of the model and its parameters. This is interesting as it frees the designer of manual procedures, which are time consuming and prone to error, usually done to define the model inputs. We compare the proposed methodology with other works found in the literature, showing overall better results for the cascaded approach.

  9. Leuconostoc mesenteroides growth in food products: prediction and sensitivity analysis by adaptive-network-based fuzzy inference systems.

    Directory of Open Access Journals (Sweden)

    Hue-Yu Wang

    Full Text Available BACKGROUND: An adaptive-network-based fuzzy inference system (ANFIS was compared with an artificial neural network (ANN in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C, pH level (5.5 to 7.5, sodium chloride level (0.25% to 6.25% and sodium nitrite level (0 to 200 ppm on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. METHODS: THE ANFIS AND ANN MODELS WERE COMPARED IN TERMS OF SIX STATISTICAL INDICES CALCULATED BY COMPARING THEIR PREDICTION RESULTS WITH ACTUAL DATA: mean absolute percentage error (MAPE, root mean square error (RMSE, standard error of prediction percentage (SEP, bias factor (Bf, accuracy factor (Af, and absolute fraction of variance (R (2. Graphical plots were also used for model comparison. CONCLUSIONS: The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions.

  10. Leuconostoc mesenteroides growth in food products: prediction and sensitivity analysis by adaptive-network-based fuzzy inference systems.

    Science.gov (United States)

    Wang, Hue-Yu; Wen, Ching-Feng; Chiu, Yu-Hsien; Lee, I-Nong; Kao, Hao-Yun; Lee, I-Chen; Ho, Wen-Hsien

    2013-01-01

    An adaptive-network-based fuzzy inference system (ANFIS) was compared with an artificial neural network (ANN) in terms of accuracy in predicting the combined effects of temperature (10.5 to 24.5°C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. THE ANFIS AND ANN MODELS WERE COMPARED IN TERMS OF SIX STATISTICAL INDICES CALCULATED BY COMPARING THEIR PREDICTION RESULTS WITH ACTUAL DATA: mean absolute percentage error (MAPE), root mean square error (RMSE), standard error of prediction percentage (SEP), bias factor (Bf), accuracy factor (Af), and absolute fraction of variance (R (2)). Graphical plots were also used for model comparison. The learning-based systems obtained encouraging prediction results. Sensitivity analyses of the four environmental factors showed that temperature and, to a lesser extent, NaCl had the most influence on accuracy in predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions. The observed effectiveness of ANFIS for modeling microbial kinetic parameters confirms its potential use as a supplemental tool in predictive mycology. Comparisons between growth rates predicted by ANFIS and actual experimental data also confirmed the high accuracy of the Gaussian membership function in ANFIS. Comparisons of the six statistical indices under both aerobic and anaerobic conditions also showed that the ANFIS model was better than all ANN models in predicting the four kinetic parameters. Therefore, the ANFIS model is a valuable tool for quickly predicting the growth rate of Leuconostoc mesenteroides under aerobic and anaerobic conditions.

  11. Communicating embedded systems networks applications

    CERN Document Server

    Krief, Francine

    2013-01-01

    Embedded systems become more and more complex and require having some knowledge in various disciplines such as electronics, data processing, telecommunications and networks. Without detailing all the aspects related to the design of embedded systems, this book, which was written by specialists in electronics, data processing and telecommunications and networks, gives an interesting point of view of communication techniques and problems in embedded systems. This choice is easily justified by the fact that embedded systems are today massively communicating and that telecommunications and network

  12. A Cyber Physical Model Based on a Hybrid System for Flexible Load Control in an Active Distribution Network

    Directory of Open Access Journals (Sweden)

    Yun Wang

    2017-02-01

    Full Text Available To strengthen the integration of the primary and secondary systems, a concept of Cyber Physical Systems (CPS is introduced to construct a CPS in Power Systems (Power CPS. The most basic work of the Power CPS is to build an integration model which combines both a continuous process and a discrete process. The advanced form of smart grid, the Active Distribution Network (ADN is a typical example of Power CPS. After designing the Power CPS model architecture and its application in ADN, a Hybrid System based model and control method of Power CPS is proposed in this paper. As an application example, ADN flexible load is modeled and controlled with ADN feeder power control by a control strategy which includes the normal condition and the underpowered condition. In this model and strategy, some factors like load power consumption and load functional demand are considered and optimized. In order to make up some of the deficiencies of centralized control, a distributed control method is presented to reduce model complexity and improve calculation speed. The effectiveness of all the models and methods are demonstrated in the case study.

  13. Neural Network-Based Passive Filtering for Delayed Neutral-Type Semi-Markovian Jump Systems.

    Science.gov (United States)

    Shi, Peng; Li, Fanbiao; Wu, Ligang; Lim, Cheng-Chew

    2017-09-01

    This paper investigates the problem of exponential passive filtering for a class of stochastic neutral-type neural networks with both semi-Markovian jump parameters and mixed time delays. Our aim is to estimate the states by designing a Luenberger-type observer, such that the filter error dynamics are mean-square exponentially stable with an expected decay rate and an attenuation level. Sufficient conditions for the existence of passive filters are obtained, and a convex optimization algorithm for the filter design is given. In addition, a cone complementarity linearization procedure is employed to cast the nonconvex feasibility problem into a sequential minimization problem, which can be readily solved by the existing optimization techniques. Numerical examples are given to demonstrate the effectiveness of the proposed techniques.

  14. Minimum Constructive Back Propagation Neural Network Based on Fuzzy Logic for Pattern Recognition of Electronic Nose System

    Directory of Open Access Journals (Sweden)

    Radi Radi

    2011-08-01

    Full Text Available Constructive Back Propagation Neural Network (CBPNN is a kind of back propagation neural network trained with constructive algorithm. Training of CBPNN is mainly conducted by developing the network’s architecture which commonly done by adding a number of new neuron units on learning process. Training of the network usually implements fixed method to develop its structure gradually by adding new units constantly. Although this method is simple and able to create an adaptive network for data pattern complexity, but it is wasteful and inefficient for computing. New unit addition affects directly to the computational load of training, speed of convergence, and structure of the final neural network. While increases training load significantly, excessive addition of units also tends to generate a large size of final network. Moreover, addition pattern with small unit number tends to drop off the adaptability of the network and extends time of training. Therefore, there is important to design an adaptive structure development pattern for CBPNN in order to minimize computing load of training. This study proposes Fuzzy Logic (FL algorithm to manage and develop structure of CBPNN. FL method was implemented on two models of CBPNN, i.e. designed with one and two hidden layers, used to recognize aroma patterns on an electronic nose system. The results showed that this method is effective to be applied due to its capability to minimize time of training, to reduce load of computational learning, and generate small size of network.

  15. Volunteer-Based System for classification of traffic in computer networks

    DEFF Research Database (Denmark)

    Bujlow, Tomasz; Balachandran, Kartheepan; Riaz, M. Tahir

    2011-01-01

    To overcome the drawbacks of existing methods for traffic classification (by ports, Deep Packet Inspection, statistical classification) a new system was developed, in which the data are collected from client machines. This paper presents design of the system, implementation, initial runs...... and obtained results. Furthermore, it proves that the system is feasible in terms of uptime and resource usage, assesses its performance and proposes future enhancements....

  16. Delays and networked control systems

    CERN Document Server

    Hetel, Laurentiu; Daafouz, Jamal; Johansson, Karl

    2016-01-01

    This edited monograph includes state-of-the-art contributions on continuous time dynamical networks with delays. The book is divided into four parts. The first part presents tools and methods for the analysis of time-delay systems with a particular attention on control problems of large scale or infinite-dimensional systems with delays. The second part of the book is dedicated to the use of time-delay models for the analysis and design of Networked Control Systems. The third part of the book focuses on the analysis and design of systems with asynchronous sampling intervals which occur in Networked Control Systems. The last part of the book exposes several contributions dealing with the design of cooperative control and observation laws for networked control systems. The target audience primarily comprises researchers and experts in the field of control theory, but the book may also be beneficial for graduate students. .

  17. An integrated model for simulating and diagnosing the water quality based on the system dynamics and Bayesian network.

    Science.gov (United States)

    Wang, Gengzhe; Wang, Shuo; Kang, Qiao; Duan, Haiyan; Wang, Xian'En

    2016-12-01

    An integrated model for simulating and diagnosing water quality based on the system dynamics and Bayesian network (BN) is presented in the paper. The research aims to connect water monitoring downstream with outlet management upstream in order to present an efficiency outlet management strategy. The integrated model was built from two components: the system dynamics were used to simulate the water quality and the BN was applied to diagnose the reason for water quality deterioration according to the water quality simulation. The integrated model was applied in a case study of the Songhua River from the Baiqi section to the Songlin section to prove its reasonability and accuracy. The results showed that the simulation fit to the variation trend of monitoring data, and the average relative error was less than 10%. The water quality deterioration in the Songlin section was mainly found to be caused by the water quality in the upper reach and Hadashan Reservoir drain by using the diagnosis function of the integrated model based on BN. The relevant result revealed that the integrated model could provide reasonable and quantitative support for the basin manager to make a reasonable outlet control strategy to avoid more serious water quality deterioration.

  18. Interorganizational Innovation in Systemic Networks

    DEFF Research Database (Denmark)

    Seemann, Janne; Dinesen, Birthe; Gustafsson, Jeppe

    2013-01-01

    that linear n-stage models by reducing complexity and flux end up focusing only on the surface of the network and are thus unable to grasp important aspects of network dynamics. The paper suggests that there is a need for a more dynamic innovation model able to grasp the whole picture of dynamics in systemic...... patients with chronic obstructive pulmonary disease (COPD) to avoid readmission, perform self monitoring and to maintain rehabilitation in their homes. The aim of the paper is to identify, analyze and discuss innovation dynamics in the COPD network and on a preliminary basis to identify implications...... for managing innovations in systemic networks. The main argument of this paper is that innovation dynamics in systemic networks should be understood as a complex interplay of four logics: 1) Fragmented innovation, 2) Interface innovation, 3) Competing innovation, 4) Co-innovation. The findings indicate...

  19. Performance of Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Yingwei Zhang

    2013-01-01

    Full Text Available Data packet dropout is a special kind of time delay problem. In this paper, predictive controllers for networked control systems (NCSs with dual-network are designed by model predictive control method. The contributions are as follows. (1 The predictive control problem of the dual-network is considered. (2 The predictive performance of the dual-network is evaluated. (3 Compared to the popular networked control systems, the optimal controller of the new NCSs with data packets dropout is designed, which can minimize infinite performance index at each sampling time and guarantee the closed-loop system stability. Finally, the simulation results show the feasibility and effectiveness of the controllers designed.

  20. Social networking-based personal home telehealth system: A pilot study

    Directory of Open Access Journals (Sweden)

    Yu-Chen Huang

    2014-12-01

    Conclusion: CDF presented in this paper extends the value of a home telehealth system from the provision of health care to enhancing older adults' interpersonal communication and social participation.

  1. An Intelligent Traffic Flow Control System Based on Radio Frequency Identification and Wireless Sensor Networks

    National Research Council Canada - National Science Library

    Chao, Kuei-Hsiang; Chen, Pi-Yun

    2014-01-01

    This study primarily focuses on the use of radio frequency identification (RFID) as a form of traffic flow detection, which transmits collected information related to traffic flow directly to a control system through an RS232 interface...

  2. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1999-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  3. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1998-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  4. Supporting interoperability of collaborative networks through engineering of a service-based Mediation Information System (MISE 2.0)

    Science.gov (United States)

    Benaben, Frederick; Mu, Wenxin; Boissel-Dallier, Nicolas; Barthe-Delanoe, Anne-Marie; Zribi, Sarah; Pingaud, Herve

    2015-08-01

    The Mediation Information System Engineering project is currently finishing its second iteration (MISE 2.0). The main objective of this scientific project is to provide any emerging collaborative situation with methods and tools to deploy a Mediation Information System (MIS). MISE 2.0 aims at defining and designing a service-based platform, dedicated to initiating and supporting the interoperability of collaborative situations among potential partners. This MISE 2.0 platform implements a model-driven engineering approach to the design of a service-oriented MIS dedicated to supporting the collaborative situation. This approach is structured in three layers, each providing their own key innovative points: (i) the gathering of individual and collaborative knowledge to provide appropriate collaborative business behaviour (key point: knowledge management, including semantics, exploitation and capitalisation), (ii) deployment of a mediation information system able to computerise the previously deduced collaborative processes (key point: the automatic generation of collaborative workflows, including connection with existing devices or services) (iii) the management of the agility of the obtained collaborative network of organisations (key point: supervision of collaborative situations and relevant exploitation of the gathered data). MISE covers business issues (through BPM), technical issues (through an SOA) and agility issues of collaborative situations (through EDA).

  5. Reconfigurable radio systems network architectures and standards

    CERN Document Server

    Iacobucci, Maria Stella

    2013-01-01

    This timely book provides a standards-based view of the development, evolution, techniques and potential future scenarios for the deployment of reconfigurable radio systems.  After an introduction to radiomobile and radio systems deployed in the access network, the book describes cognitive radio concepts and capabilities, which are the basis for reconfigurable radio systems.  The self-organizing network features introduced in 3GPP standards are discussed and IEEE 802.22, the first standard based on cognitive radio, is described. Then the ETSI reconfigurable radio systems functional ar

  6. Modeling complex metabolic reactions, ecological systems, and financial and legal networks with MIANN models based on Markov-Wiener node descriptors.

    Science.gov (United States)

    Duardo-Sánchez, Aliuska; Munteanu, Cristian R; Riera-Fernández, Pablo; López-Díaz, Antonio; Pazos, Alejandro; González-Díaz, Humberto

    2014-01-27

    The use of numerical parameters in Complex Network analysis is expanding to new fields of application. At a molecular level, we can use them to describe the molecular structure of chemical entities, protein interactions, or metabolic networks. However, the applications are not restricted to the world of molecules and can be extended to the study of macroscopic nonliving systems, organisms, or even legal or social networks. On the other hand, the development of the field of Artificial Intelligence has led to the formulation of computational algorithms whose design is based on the structure and functioning of networks of biological neurons. These algorithms, called Artificial Neural Networks (ANNs), can be useful for the study of complex networks, since the numerical parameters that encode information of the network (for example centralities/node descriptors) can be used as inputs for the ANNs. The Wiener index (W) is a graph invariant widely used in chemoinformatics to quantify the molecular structure of drugs and to study complex networks. In this work, we explore for the first time the possibility of using Markov chains to calculate analogues of node distance numbers/W to describe complex networks from the point of view of their nodes. These parameters are called Markov-Wiener node descriptors of order k(th) (W(k)). Please, note that these descriptors are not related to Markov-Wiener stochastic processes. Here, we calculated the W(k)(i) values for a very high number of nodes (>100,000) in more than 100 different complex networks using the software MI-NODES. These networks were grouped according to the field of application. Molecular networks include the Metabolic Reaction Networks (MRNs) of 40 different organisms. In addition, we analyzed other biological and legal and social networks. These include the Interaction Web Database Biological Networks (IWDBNs), with 75 food webs or ecological systems and the Spanish Financial Law Network (SFLN). The calculated W

  7. 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.

  8. Broadband network on-line data acquisition system with web based interface for control and basic analysis

    Science.gov (United States)

    Polkowski, Marcin; Grad, Marek

    2016-04-01

    Passive seismic experiment "13BB Star" is operated since mid 2013 in northern Poland and consists of 13 broadband seismic stations. One of the elements of this experiment is dedicated on-line data acquisition system comprised of both client (station) side and server side modules with web based interface that allows monitoring of network status and provides tools for preliminary data analysis. Station side is controlled by ARM Linux board that is programmed to maintain 3G/EDGE internet connection, receive data from digitizer, send data do central server among with additional auxiliary parameters like temperatures, voltages and electric current measurements. Station side is controlled by set of easy to install PHP scripts. Data is transmitted securely over SSH protocol to central server. Central server is a dedicated Linux based machine. Its duty is receiving and processing all data from all stations including auxiliary parameters. Server side software is written in PHP and Python. Additionally, it allows remote station configuration and provides web based interface for user friendly interaction. All collected data can be displayed for each day and station. It also allows manual creation of event oriented plots with different filtering abilities and provides numerous status and statistic information. Our solution is very flexible and easy to modify. In this presentation we would like to share our solution and experience. National Science Centre Poland provided financial support for this work via NCN grant DEC-2011/02/A/ST10/00284.

  9. A Proposed Scalable Design and Simulation of Wireless Sensor Network-Based Long-Distance Water Pipeline Leakage Monitoring System

    Directory of Open Access Journals (Sweden)

    Abdulaziz S. Almazyad

    2014-02-01

    Full Text Available Anomalies such as leakage and bursts in water pipelines have severe consequences for the environment and the economy. To ensure the reliability of water pipelines, they must be monitored effectively. Wireless Sensor Networks (WSNs have emerged as an effective technology for monitoring critical infrastructure such as water, oil and gas pipelines. In this paper, we present a scalable design and simulation of a water pipeline leakage monitoring system using Radio Frequency IDentification (RFID and WSN technology. The proposed design targets long-distance aboveground water pipelines that have special considerations for maintenance, energy consumption and cost. The design is based on deploying a group of mobile wireless sensor nodes inside the pipeline and allowing them to work cooperatively according to a prescheduled order. Under this mechanism, only one node is active at a time, while the other nodes are sleeping. The node whose turn is next wakes up according to one of three wakeup techniques: location-based, time-based and interrupt-driven. In this paper, mathematical models are derived for each technique to estimate the corresponding energy consumption and memory size requirements. The proposed equations are analyzed and the results are validated using simulation.

  10. Fault Detection and Location by Static Switches in Microgrids Using Wavelet Transform and Adaptive Network-Based Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Ying-Yi Hong

    2014-04-01

    Full Text Available Microgrids are a highly efficient means of embedding distributed generation sources in a power system. However, if a fault occurs inside or outside the microgrid, the microgrid should be immediately disconnected from the main grid using a static switch installed at the secondary side of the main transformer near the point of common coupling (PCC. The static switch should have a reliable module implemented in a chip to detect/locate the fault and activate the breaker to open the circuit immediately. This paper proposes a novel approach to design this module in a static switch using the discrete wavelet transform (DWT and adaptive network-based fuzzy inference system (ANFIS. The wavelet coefficient of the fault voltage and the inference results of ANFIS with the wavelet energy of the fault current at the secondary side of the main transformer determine the control action (open or close of a static switch. The ANFIS identifies the faulty zones inside or outside the microgrid. The proposed method is applied to the first outdoor microgrid test bed in Taiwan, with a generation capacity of 360.5 kW. This microgrid test bed is studied using the real-time simulator eMegaSim developed by Opal-RT Technology Inc. (Montreal, QC, Canada. The proposed method based on DWT and ANFIS is implemented in a field programmable gate array (FPGA by using the Xilinx System Generator. Simulation results reveal that the proposed method is efficient and applicable in the real-time control environment of a power system.

  11. Memristor-based neural networks

    Science.gov (United States)

    Thomas, Andy

    2013-03-01

    The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them.

  12. BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network.

    Science.gov (United States)

    Ishiwata, Ryosuke R; Morioka, Masaki S; Ogishima, Soichi; Tanaka, Hiroshi

    2009-02-15

    BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions. BioCichlid is freely available and can be accessed at http://newton.tmd.ac.jp/. Source codes for both biocichlid server and client are also available.

  13. Fuzzy-logic-based network for complex systems risk assessment: application to ship performance analysis.

    Science.gov (United States)

    Abou, Seraphin C

    2012-03-01

    In this paper, a new interpretation of intuitionistic fuzzy sets in the advanced framework of the Dempster-Shafer theory of evidence is extended to monitor safety-critical systems' performance. Not only is the proposed approach more effective, but it also takes into account the fuzzy rules that deal with imperfect knowledge/information and, therefore, is different from the classical Takagi-Sugeno fuzzy system, which assumes that the rule (the knowledge) is perfect. We provide an analytical solution to the practical and important problem of the conceptual probabilistic approach for formal ship safety assessment using the fuzzy set theory that involves uncertainties associated with the reliability input data. Thus, the overall safety of the ship engine is investigated as an object of risk analysis using the fuzzy mapping structure, which considers uncertainty and partial truth in the input-output mapping. The proposed method integrates direct evidence of the frame of discernment and is demonstrated through references to examples where fuzzy set models are informative. These simple applications illustrate how to assess the conflict of sensor information fusion for a sufficient cooling power system of vessels under extreme operation conditions. It was found that propulsion engine safety systems are not only a function of many environmental and operation profiles but are also dynamic and complex. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. Neural network web-based system for promoting rural education in ...

    African Journals Online (AJOL)

    Rural education is as important as its urban counterpart; therefore the need to promote it using the latest (IT) technology is also important. Now that student's enrollment increases and government base funding for education decreases, the use of technology becomes more important to both administrators and instructors in ...

  15. RECOMMENDER SYSTEMS IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Cleomar Valois Batista Jr

    2011-12-01

    Full Text Available The continued and diversified growth of social networks has changed the way in which users interact with them. With these changes, what once was limited to social contact is now used for exchanging ideas and opinions, creating the need for new features. Users have so much information at their fingertips that they are unable to process it by themselves; hence, the need to develop new tools. Recommender systems were developed to address this need and many techniques were used for different approaches to the problem. To make relevant recommendations, these systems use large sets of data, not taking the social network of the user into consideration. Developing a recommender system that takes into account the social network of the user is another way of tackling the problem. The purpose of this project is to use the theory of six degrees of separation (Watts 2003 amongst users of a social network to enhance existing recommender systems.

  16. An Integrated Mobile Phone Payment System Based on 3G Network

    OpenAIRE

    Weihui Dai; Xiang Cai; Haifeng Wu; Weidong Zhao; Xuan Li

    2011-01-01

    Along with globally approaching of the 3G era, the progress of mobile communication technology and the development of mobile terminal devices will rapidly promote the mobilization development of traditional E-commerce. In order to ensure it to achieve further development, secure, flexible and reliable mobile payment system is becoming more and more important. Compared with the payment pattern of ordinary commerce, there will be profound changes in the mobile payment, such as special payment c...

  17. TOWARDS A PARALLEL SYSTEM FOR DEMOGRAPHIC ZONIFICATION BASED ON COMPLEX NETWORKS

    Directory of Open Access Journals (Sweden)

    Alberto Ochoa

    2009-08-01

    Full Text Available This paper presents a novel method for the zone design problem that is based on a popular technique in the field of complexnetworks research: betweenness centrality. We use a parallel version of a community detection algorithm that outputs thegraph partitioning that maximizes the so‐called modularity metric. The method is put at the centre of an effort to build an opensource interactive high performance computing platform to assist researchers working with population data.

  18. PID Controller Based on Memristive CMAC Network

    Directory of Open Access Journals (Sweden)

    Lidan Wang

    2013-01-01

    Full Text Available Compound controller which consists of CMAC network and PID network is mainly used in control system, especially in robot control. It can realize nonlinear tracking control of the real-time dynamic trajectory and possesses good approximation effect. According to the structure and principle of the compound controller, memristor is introduced to CMAC network to be a compound controller in this paper. The new PID controller based on memristive CMAC network is built up by replacing the synapse in the original controller by memristors. The effect of curve approximation is obtained by MATLAB simulation experiments. This network improves the response and learning speed of the system and processes better robustness and antidisturbance performance.

  19. Designing a delay-based adaptive congestion control mechanism using control theory and system identification for TCP/IP networks

    Science.gov (United States)

    Morita, Mitsushige; Ohsaki, Hiroyuki; Murata, Masayuki

    2002-07-01

    In the Internet, TCP (Transmission Control Protocol) has been used as an end-to-end congestion control mechanism. Of all several TCP implementations, TCP Reno is the most popular implementation. TCP Reno uses a loss-based approach since it estimates the severity of congestion by detecting packet losses in the network. On the contrary, another implementation called TCP Vegas uses a delay-based approach. The main advantage of a delay-based approach is, if it is properly designed, packet losses can be prevented by anticipating impending congestion from increasing packet delays. However, TCP Vegas was designed using not a theoretical approach but an ad hock one. In this paper, we therefore design a delay-based congestion control mechanism by utilizing the classical control theory. Our rate-based congestion control mechanism dynamically adjusts the packet transmission rate to stabilize the round-trip time for utilizing the network resources and also for preventing packet losses in the network. Presenting several simulation results in two network configurations, we quantitatively show the robustness and the effectiveness of our delay-based congestion control mechanism.

  20. Silicon microgyroscope temperature prediction and control system based on BP neural network and Fuzzy-PID control method

    Science.gov (United States)

    Xia, Dunzhu; Kong, Lun; Hu, Yiwei; Ni, Peizhen

    2015-02-01

    We present a novel silicon microgyroscope (SMG) temperature prediction and control system in a narrow space. As the temperature of SMG is closely related to its drive mode frequency and driving voltage, a temperature prediction model can be established based on the BP neural network. The simulation results demonstrate that the established temperature prediction model can estimate the temperature in the range of -40 to 60 °C with an error of less than ±0.05 °C. Then, a temperature control system based on the combination of fuzzy logic controller and the increment PID control method is proposed. The simulation results prove that the Fuzzy-PID controller has a smaller steady state error, less rise time and better robustness than the PID controller. This is validated by experimental results that show the Fuzzy-PID control method can achieve high precision in keeping the SMG temperature stable at 55 °C with an error of less than 0.2 °C. The scale factor can be stabilized at 8.7 mV/°/s with a temperature coefficient of 33 ppm °C-1. ZRO (zero rate output) instability is decreased from 1.10°/s (9.5 mV) to 0.08°/s (0.7 mV) when the temperature control system is implemented over an ambient temperature range of -40 to 60 °C.

  1. Neuro-fuzzy controller of low head hydropower plants using adaptive-network based fuzzy inference system

    Energy Technology Data Exchange (ETDEWEB)

    Djukanovic, M.B. [Inst. Nikola Tesla, Belgrade (Yugoslavia). Dept. of Power Systems; Calovic, M.S. [Univ. of Belgrade (Yugoslavia). Dept. of Electrical Engineering; Vesovic, B.V. [Inst. Mihajlo Pupin, Belgrade (Yugoslavia). Dept. of Automatic Control; Sobajic, D.J. [Electric Power Research Inst., Palo Alto, CA (United States)

    1997-12-01

    This paper presents an attempt of nonlinear, multivariable control of low-head hydropower plants, by using adaptive-network based fuzzy inference system (ANFIS). The new design technique enhances fuzzy controllers with self-learning capability for achieving prescribed control objectives in a near optimal manner. The controller has flexibility for accepting more sensory information, with the main goal to improve the generator unit transients, by adjusting the exciter input, the wicket gate and runner blade positions. The developed ANFIS controller whose control signals are adjusted by using incomplete on-line measurements, can offer better damping effects to generator oscillations over a wide range of operating conditions, than conventional controllers. Digital simulations of hydropower plant equipped with low-head Kaplan turbine are performed and the comparisons of conventional excitation-governor control, state-feedback optimal control and ANFIS based output feedback control are presented. To demonstrate the effectiveness of the proposed control scheme and the robustness of the acquired neuro-fuzzy controller, the controller has been implemented on a complex high-order non-linear hydrogenerator model.

  2. Thermal Analysis of the Driving Component Based on the Thermal Network Method in a Lunar Drilling System and Experimental Verification

    Directory of Open Access Journals (Sweden)

    Dewei Tang

    2017-03-01

    Full Text Available The main task of the third Chinese lunar exploration project is to obtain soil samples that are greater than two meters in length and to acquire bedding information from the surface of the moon. The driving component is the power output unit of the drilling system in the lander; it provides drilling power for core drilling tools. High temperatures can cause the sensors, permanent magnet, gears, and bearings to suffer irreversible damage. In this paper, a thermal analysis model for this driving component, based on the thermal network method (TNM was established and the model was solved using the quasi-Newton method. A vacuum test platform was built and an experimental verification method (EVM was applied to measure the surface temperature of the driving component. Then, the TNM was optimized, based on the principle of heat distribution. Through comparative analyses, the reasonableness of the TNM is validated. Finally, the static temperature field of the driving component was predicted and the “safe working times” of every mode are given.

  3. Seasonal rainfall forecasting by adaptive network-based fuzzy inference system (ANFIS) using large scale climate signals

    Science.gov (United States)

    Mekanik, F.; Imteaz, M. A.; Talei, A.

    2016-05-01

    Accurate seasonal rainfall forecasting is an important step in the development of reliable runoff forecast models. The large scale climate modes affecting rainfall in Australia have recently been proven useful in rainfall prediction problems. In this study, adaptive network-based fuzzy inference systems (ANFIS) models are developed for the first time for southeast Australia in order to forecast spring rainfall. The models are applied in east, center and west Victoria as case studies. Large scale climate signals comprising El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Inter-decadal Pacific Ocean (IPO) are selected as rainfall predictors. Eight models are developed based on single climate modes (ENSO, IOD, and IPO) and combined climate modes (ENSO-IPO and ENSO-IOD). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Pearson correlation coefficient (r) and root mean square error in probability (RMSEP) skill score are used to evaluate the performance of the proposed models. The predictions demonstrate that ANFIS models based on individual IOD index perform superior in terms of RMSE, MAE and r to the models based on individual ENSO indices. It is further discovered that IPO is not an effective predictor for the region and the combined ENSO-IOD and ENSO-IPO predictors did not improve the predictions. In order to evaluate the effectiveness of the proposed models a comparison is conducted between ANFIS models and the conventional Artificial Neural Network (ANN), the Predictive Ocean Atmosphere Model for Australia (POAMA) and climatology forecasts. POAMA is the official dynamic model used by the Australian Bureau of Meteorology. The ANFIS predictions certify a superior performance for most of the region compared to ANN and climatology forecasts. POAMA performs better in regards to RMSE and MAE in east and part of central Victoria, however, compared to ANFIS it shows weaker results in west Victoria in terms of prediction errors and RMSEP skill

  4. A Novel Fault Line Selection Method Based on Improved Oscillator System of Power Distribution Network

    Directory of Open Access Journals (Sweden)

    Xiaowei Wang

    2014-01-01

    Full Text Available A novel method of fault line selection based on IOS is presented. Firstly, the IOS is established by using math model, which adopted TZSC signal to replace built-in signal of duffing chaotic oscillator by selecting appropriate parameters. Then, each line’s TZSC decomposed by db10 wavelet packet to get CFB with the maximum energy principle, and CFB was solved by IOS. Finally, maximum chaotic distance and average chaotic distance on the phase trajectory are used to judge fault line. Simulation results show that the proposed method can accurately judge fault line and healthy line in strong noisy background. Besides, the nondetection zones of proposed method are elaborated.

  5. 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.

  6. Pollution Monitoring System Using Gas Sensor based on Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    M. Udin Harun Al Rasyid

    2016-01-01

    Full Text Available Carbon monoxide (CO and carbon dioxide (CO2 gases are classified as colorless and odorless gas so we need special tools to monitor their concentration in the air. Concentration of air pollution of CO and CO2 that are high in the air will give serious effects for health status. CO is a poisonous gas that damages the circulation of oxygen in the blood when inhaled, while CO2 is one of the gases that causes global warming. In this paper, we developed an integrated pollution monitoring (IPOM system to monitor the concentration of air pollution. This research implemented three sensor nodes (end-device which each node contains CO and CO2 sensors on the gas sensors board to perform sensing from the environment. Furthermore, the data taken from the environment by the sensor will be sent to the meshlium gateway using IEEE 802.15.4 Zigbee communications and processed by the gateway in order to be sent to the computer server. The data is stored in meshlium gateway using MySQL database as a backup, and it will be synchronized to the MySQL database in the computer server. We provide services for public to access the information in database server through a desktop and website application.

  7. Network-based functional enrichment

    Directory of Open Access Journals (Sweden)

    Poirel Christopher L

    2011-11-01

    Full Text Available Abstract Background Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account. Results Our approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i determine which functions are enriched in a given network, ii given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms. Conclusions We presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are

  8. Multilevel Complex Networks and Systems

    Science.gov (United States)

    Caldarelli, Guido

    2014-03-01

    Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.

  9. Simulating an Impact of Road Network Improvements on the Performance of Transportation Systems under Critical Load: Agent-based Approach

    NARCIS (Netherlands)

    Milevich, D.; Melnikov, V.; Karbovskii, V.; Krzhizhanovskaya, V.

    2016-01-01

    In this paper, we analyze the impact of planned road network development on the dynamics of the automobile transportation system during the departure of visitors after the semifinal match of the 2018 FIFA World Cup, which will take place in the newly built stadium on Krestovsky Island. To perform

  10. Enabling application-level performance guarantees in network-based systems on chip by applying dataflow analysis

    NARCIS (Netherlands)

    Hansson, A.; Hansson, A.; Wiggers, M.H.; Moonen, A.; Goossens, K.; Bekooij, Marco Jan Gerrit; Bekooij, M.

    2009-01-01

    A growing number of applications, often with real-time requirements, are integrated on the same system on chip (SoC), in the form of hardware and software intellectual property (IP). To facilitate real-time applications, networks on chip (NoC) guarantee bounds on latency and throughput. These

  11. MYCONET : European network of information sources for an identification system of emerging mycotoxins in wheat based supply chains

    NARCIS (Netherlands)

    Fels-Klerx, van der H.J.; Booij, C.J.H.

    2008-01-01

    This report describes the results of the MYCONET project, an international research project aimed at initiating a sustainable platform (network) of information sources that proactively provides specified information for an emerging risk identification system. As a case study, the project focused on

  12. Dynamics-based centrality for directed networks.

    Science.gov (United States)

    Masuda, Naoki; Kori, Hiroshi

    2010-11-01

    Determining the relative importance of nodes in directed networks is important in, for example, ranking websites, publications, and sports teams, and for understanding signal flows in systems biology. A prevailing centrality measure in this respect is the PageRank. In this work, we focus on another class of centrality derived from the Laplacian of the network. We extend the Laplacian-based centrality, which has mainly been applied to strongly connected networks, to the case of general directed networks such that we can quantitatively compare arbitrary nodes. Toward this end, we adopt the idea used in the PageRank to introduce global connectivity between all the pairs of nodes with a certain strength. Numerical simulations are carried out on some networks. We also offer interpretations of the Laplacian-based centrality for general directed networks in terms of various dynamical and structural properties of networks. Importantly, the Laplacian-based centrality defined as the stationary density of the continuous-time random walk with random jumps is shown to be equivalent to the absorption probability of the random walk with sinks at each node but without random jumps. Similarly, the proposed centrality represents the importance of nodes in dynamics on the original network supplied with sinks but not with random jumps.

  13. Location-based Forwarding in Vehicular Networks

    NARCIS (Netherlands)

    Klein Wolterink, W.

    2013-01-01

    In this thesis we focus on location-based message forwarding in vehicular networks to support intelligent transportation systems (ITSs). ITSs are transport systems that utilise information and communication technologies to increase their level of automation, in this way levering the performance of

  14. Provisioning of large-scale systems: the interplay between network effects and strategic behavior in the user base

    NARCIS (Netherlands)

    J. Nair (Jayakrishnan); A. Wierman (Adam); A.P. Zwart (Bert)

    2016-01-01

    textabstractIn this paper, we consider the problem of capacity provisioning for an online service supported by advertising. We analyse the strategic interaction between the service provider and the user base in this setting, modeling positive network effects, as well as congestion sensitivity in

  15. Multiwavelength optical beam forming network with ring resonator-based binary-tree architecture for broadband phased array antenna systems

    NARCIS (Netherlands)

    Burla, M.; Khan, M.R.H.; Zhuang, L.; Roeloffzen, C.G.H.

    2008-01-01

    Integrated optical beam forming networks (OBFNs) offer many advantages for phased array applications. ORR-based true-time-delay units can be cascaded in a binary tree topology and tuned for continuously-adjustable broadband time delay. Nonetheless, with large number of antenna elements, the OBFN may

  16. MODELING AND STRUCTURING OF ENTERPRISE MANAGEMENT SYSTEM RESORT SPHERE BASED ON ELEMENTS OF NEURAL NETWORK THEORY: THE METHODOLOGICAL BASIS

    Directory of Open Access Journals (Sweden)

    Rena R. Timirualeeva

    2015-01-01

    Full Text Available The article describes the methodology of modeling andstructuring of business networks theory. Accounting ofenvironmental factors mega-, macro- and mesolevels, theinternal state of the managed system and the error management command execution by control system implemented inthis. The proposed methodology can improve the quality of enterprise management of resort complex through a moreflexible response to changes in the parameters of the internaland external environments.

  17. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number....... Such systems are known to be stabilized by spatial structure. Finally, I analyse data from a large mobile phone network and show that people who are topologically close in the network have similar communication patterns. This main part of the thesis is based on six different articles, which I have co...

  18. Network Management using Multi-Agents System

    Directory of Open Access Journals (Sweden)

    Nestor DUQUE

    2013-07-01

    Full Text Available This paper aims to present a multiagent system for network management. The models developed for the proposed system defines certain intelligent agents interact to achieve the objectives and requirements of the multiagent organization.These agents have the property of being adaptive, acquire knowledge and skills to make decisions according to the actual state of the network that is represented in the information base, MIB, SNMP devices. The ideal state of the network policy is defined by the end user entered, which contain the value that should have performance variables and other parameters such as the frequency with which these variables should be monitored.. An agent based architecture increase the integration, adaptability, cooperation, autonomy and the efficient operation in heterogeneous environment in the network supervision. 

  19. Network Management using Multi-Agents System

    Directory of Open Access Journals (Sweden)

    Gustavo ISAZA

    2012-12-01

    Full Text Available This paper aims to present a multiagent system for network management. The models developed for the proposed system defines certain intelligent agents interact to achieve the objectives and requirements of the multiagent organization.These agents have the property of being adaptive, acquire knowledge and skills to make decisions according to the actual state of the network that is represented in the information base, MIB, SNMP devices. The ideal state of the network policy is defined by the end user entered, which contain the value that should have performance variables and other parameters such as the frequency with which these variables should be monitored.. An agent based architecture increase the integration, adaptability, cooperation, autonomy and the efficient operation in heterogeneous environment in the network supervision. 

  20. The Artifical Neural Network as means for modeling Nonlinear Systems

    OpenAIRE

    Drábek Oldøich; Taufer Ivan

    1998-01-01

    The paper deals with nonlinear system identification based on neural network. The topic of this publication is simulation of training and testing a neural network. A contribution is assigned to technologists which are good at the clasical identification problems but their knowledges about identification based on neural network are only on the stage of theoretical bases.

  1. The Artifical Neural Network as means for modeling Nonlinear Systems

    Directory of Open Access Journals (Sweden)

    Drábek Oldøich

    1998-12-01

    Full Text Available The paper deals with nonlinear system identification based on neural network. The topic of this publication is simulation of training and testing a neural network. A contribution is assigned to technologists which are good at the clasical identification problems but their knowledges about identification based on neural network are only on the stage of theoretical bases.

  2. Smart Sensor Network System For Environment Monitoring

    Directory of Open Access Journals (Sweden)

    Javed Ali Baloch

    2012-07-01

    Full Text Available SSN (Smart Sensor Network systems could be used to monitor buildings with modern infrastructure, plant sites with chemical pollution, horticulture, natural habitat, wastewater management and modern transport system. To sense attributes of phenomena and make decisions on the basis of the sensed value is the primary goal of such systems. In this paper a Smart Spatially aware sensor system is presented. A smart system, which could continuously monitor the network to observe the functionality and trigger, alerts to the base station if a change in the system occurs and provide feedback periodically, on demand or even continuously depending on the nature of the application. The results of the simulation trials presented in this paper exhibit the performance of a Smart Spatially Aware Sensor Networks.

  3. Target recognition and scene interpretation in image/video understanding systems based on network-symbolic models

    Science.gov (United States)

    Kuvich, Gary

    2004-08-01

    Vision is only a part of a system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. These mechanisms provide a reliable recognition if the object is occluded or cannot be recognized as a whole. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, is the most feasible for such models. It converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Network-Symbolic Transformations derive abstract structures, which allows for invariant recognition of an object as exemplar of a class. Active vision helps creating consistent models. Attention, separation of figure from ground and perceptual grouping are special kinds of network-symbolic transformations. Such Image/Video Understanding Systems will be reliably recognizing targets.

  4. Target recognition with image/video understanding systems based on active vision principle and network-symbolic models

    Science.gov (United States)

    Kuvich, Gary

    2004-08-01

    Vision is only a part of a larger system that converts visual information into knowledge structures. These structures drive the vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, which is an interpretation of visual information in terms of these knowledge models. This mechanism provides a reliable recognition if the target is occluded or cannot be recognized. It is hard to split the entire system apart, and reliable solutions to the target recognition problems are possible only within the solution of a more generic Image Understanding Problem. Brain reduces informational and computational complexities, using implicit symbolic coding of features, hierarchical compression, and selective processing of visual information. Biologically inspired Network-Symbolic representation, where both systematic structural/logical methods and neural/statistical methods are parts of a single mechanism, converts visual information into relational Network-Symbolic structures, avoiding artificial precise computations of 3-dimensional models. Logic of visual scenes can be captured in Network-Symbolic models and used for disambiguation of visual information. Network-Symbolic Transformations derive abstract structures, which allow for invariant recognition of an object as exemplar of a class. Active vision helps build consistent, unambiguous models. Such Image/Video Understanding Systems will be able reliably recognizing targets in real-world conditions.

  5. Simulating light-weight Personalised Recommender Systems in Learning Networks: A case for Pedagogy-Oriented and Rating-based Hybrid Recommendation Strategies

    NARCIS (Netherlands)

    Nadolski, Rob; Van den Berg, Bert; Berlanga, Adriana; Drachsler, Hendrik; Hummel, Hans; Koper, Rob; Sloep, Peter

    2008-01-01

    Nadolski, R. J., Van den Berg, B., Berlanga, A. J., Drachsler, H., Hummel, H. G. K., Koper, R., & Sloep, P. B. (2009). Simulating Light-Weight Personalised Recommender Systems in Learning Networks: A Case for Pedagogy-Oriented and Rating-Based Hybrid Recommendation Strategies. Journal of Artificial

  6. Optimization of Indoor Thermal Comfort Parameters with the Adaptive Network-Based Fuzzy Inference System and Particle Swarm Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Jing Li

    2017-01-01

    Full Text Available The goal of this study is to improve thermal comfort and indoor air quality with the adaptive network-based fuzzy inference system (ANFIS model and improved particle swarm optimization (PSO algorithm. A method to optimize air conditioning parameters and installation distance is proposed. The methodology is demonstrated through a prototype case, which corresponds to a typical laboratory in colleges and universities. A laboratory model is established, and simulated flow field information is obtained with the CFD software. Subsequently, the ANFIS model is employed instead of the CFD model to predict indoor flow parameters, and the CFD database is utilized to train ANN input-output “metamodels” for the subsequent optimization. With the improved PSO algorithm and the stratified sequence method, the objective functions are optimized. The functions comprise PMV, PPD, and mean age of air. The optimal installation distance is determined with the hemisphere model. Results show that most of the staff obtain a satisfactory degree of thermal comfort and that the proposed method can significantly reduce the cost of building an experimental device. The proposed methodology can be used to determine appropriate air supply parameters and air conditioner installation position for a pleasant and healthy indoor environment.

  7. Ethical Issues in Network System Design

    Directory of Open Access Journals (Sweden)

    Duncan Langford

    1997-05-01

    Full Text Available Today, most desktop computers and PCs are networked that is, they have the ability to link to other machines, usually to access data and other information held remotely. Such machines may sometimes be connected directly to each other, as part of an office or company computer system. More frequently, however, connected machines are at a considerable distance from each other, typically connected through links to global systems such as the Internet, or World Wide Web (WWW. The networked machine itself may be anything from a powerful company computer with direct Internet connections, to a small hobbyist machine, accessing a bulletin board through telephone and modem. It is important to remember that, whatever the type or the location of networked machines, their access to the network, and the network itself, was planned and constructed following deliberate design considerations. In this paper I discuss some ways in which the technical design of computer systems might appropriately be influenced by ethical issues, and examine pressures on computer scientists and others to technically control network related actions perceived as 'unethical'. After examination of the current situation, I draw together the issues, and conclude by suggesting some ethically based recommendations for the future design of networked systems.

  8. Implementation of a Low-Cost Energy and Environment Monitoring System Based on a Hybrid Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Dong Sik Kim

    2017-01-01

    Full Text Available A low-cost hybrid wireless sensor network (WSN that utilizes the 917 MHz band Wireless Smart Utility Network (Wi-SUN and a 447 MHz band narrow bandwidth communication network is implemented for electric metering and room temperature, humidity, and CO2 gas measurements. A mesh network connection that is commonly utilized for the Internet of Things (IoT is used for the Wi-SUN under the Contiki OS, and a star connection is used for the narrow bandwidth network. Both a duty-cycling receiver algorithm and a digitally controlled temperature-compensated crystal oscillator algorithm for frequency reference are implemented at the physical layer of the receiver to accomplish low-power and low-cost wireless sensor node design. A two-level temperature-compensation approach, in which first a fixed third-order curve and then a sample-based first-order curve are applied, is proposed using a conventional AT-cut quartz crystal resonator. The developed WSN is installed in a home and provides reliable data collection with low construction complexity and power consumption.

  9. Promoting Social Network Awareness: A Social Network Monitoring System

    Science.gov (United States)

    Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

    2010-01-01

    To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

  10. Development of low-cost meteorological observation system based on wireless network for poor-visibility occurred by snowstorm

    Science.gov (United States)

    Kobayashi, Y.; Watanabe, K.; Imai, M.; Watanabe, K.; Naruse, N.; Takahashi, Y.

    2016-12-01

    Hyper-densely monitoring for poor-visibility occurred by snowstorm is needed to make an alert system, because the snowstorm is difficult to predict from the observation only at a representative point. There are some problems in the previous approaches for the poor-visibility monitoring using video analyses or visibility meters; these require a wired network monitoring (a large amount of data: 10MB/sec at least) and the system cost is high (10,000 at each point). Thus, the risk of poor-visibility has been mainly measured at specific point such as airport and mountain pass, and estimated by simulation two dimensionally. To predict it two dimensionally and accurately, we have developed a low-cost meteorological system to observe the snowstorm hyper-densely. We have developed a low-cost visibility meter which works as the reduced intensity of semiconducting laser light when snow particles block off. Our developed system also has a capability of extending a hyper-densely observation in real-time on wireless network using Zigbee; A/D conversion and wireless data sent from temperature and illuminance sensors. We use a semiconducting laser chip (5) for the light source and a reflection mechanism by the use of three mirrors so as to send the light to a non-sensitive illuminance sensor directly. Thus, our visibility detecting system ($500) becomes much cheaper than previous one. We have checked the correlation between the reduced intensity taken by our system and the visibility recorded by conventional video camera. The value for the correlation coefficient was -0.67, which indicates a strong correlation. It means that our developed system is practical. In conclusion, we have developed low-cost meteorological detecting system to observe poor-visibility occurred by snowstorm, having a potential of hyper-densely monitoring on wireless network, and have made sure the practicability.

  11. Understanding Supply Networks from Complex Adaptive Systems

    Directory of Open Access Journals (Sweden)

    Jamur Johnas Marchi

    2014-10-01

    Full Text Available This theoretical paper is based on complex adaptive systems (CAS that integrate dynamic and holistic elements, aiming to discuss supply networks as complex systems and their dynamic and co-evolutionary processes. The CAS approach can give clues to understand the dynamic nature and co-evolution of supply networks because it consists of an approach that incorporates systems and complexity. This paper’s overall contribution is to reinforce the theoretical discussion of studies that have addressed supply chain issues, such as CAS.

  12. Artificial Neural Networks, and Evolutionary Algorithms as a systems biology approach to a data-base on fetal growth restriction.

    Science.gov (United States)

    Street, Maria E; Buscema, Massimo; Smerieri, Arianna; Montanini, Luisa; Grossi, Enzo

    2013-12-01

    One of the specific aims of systems biology is to model and discover properties of cells, tissues and organisms functioning. A systems biology approach was undertaken to investigate possibly the entire system of intra-uterine growth we had available, to assess the variables of interest, discriminate those which were effectively related with appropriate or restricted intrauterine growth, and achieve an understanding of the systems in these two conditions. The Artificial Adaptive Systems, which include Artificial Neural Networks and Evolutionary Algorithms lead us to the first analyses. These analyses identified the importance of the biochemical variables IL-6, IGF-II and IGFBP-2 protein concentrations in placental lysates, and offered a new insight into placental markers of fetal growth within the IGF and cytokine systems, confirmed they had relationships and offered a critical assessment of studies previously performed. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Analyses of systems and their behaviour in extraordinary situations as based on the latest results in network sciences and extensive empirical investigations; Netzwerkanalyse fuer ein antizipatives Katastrophenmanagement

    Energy Technology Data Exchange (ETDEWEB)

    Ammoser, H. [Technische Univ. Dresden (Germany). Inst. fuer Wirtschaft und Verkehr; Kuehnert, C. [Technische Univ. Dresden (Germany). Inst. fuer Wirtschaft und Verkehr; Imperial College, London (United Kingdom); Buzna, L. [Zilina Univ. (Slovakia). Dept. of Transportation Networks

    2006-07-01

    In the context of a DFG research project, scientists of Prof. Helbing's chair at the Institute of Transport and Economics deal with the dynamics of disasters, being experienced in the modelling of complex systems and in the simulation of emergency scenarios. The analyses of systems and their behaviour in extraordinary events are based on the latest results of network sciences and on numerous empirical investigations. The results shall be used for precaution measures and innovations in disaster recovery. (orig.)

  14. Plant systems biology: network matters.

    Science.gov (United States)

    Lucas, Mikaël; Laplaze, Laurent; Bennett, Malcolm J

    2011-04-01

    Systems biology is all about networks. A recent trend has been to associate systems biology exclusively with the study of gene regulatory or protein-interaction networks. However, systems biology approaches can be applied at many other scales, from the subatomic to the ecosystem scales. In this review, we describe studies at the sub-cellular, tissue, whole plant and crop scales and highlight how these studies can be related to systems biology. We discuss the properties of system approaches at each scale as well as their current limits, and pinpoint in each case advances unique to the considered scale but representing potential for the other scales. We conclude by examining plant models bridging different scales and considering the future prospects of plant systems biology. © 2011 Blackwell Publishing Ltd.

  15. Bayesian Belief Networks (BBN) and Expert Systems for supporting model based sensor fault detection analysis of smart building systems

    NARCIS (Netherlands)

    Schagen, J.D.; Taal, A.; Itard, L.C.M.; Heiselberg, Per Kvols

    2016-01-01

    The Hague University in Delft uses an advanced climate control system. All sensors and actuators are monitored and deviations from the sensor data are reported daily. The building manager will have to combine the information from the sensor data in order to draw the right conclusions. In this paper,

  16. Networks, linkages, and migration systems.

    Science.gov (United States)

    Fawcett, J T

    1989-01-01

    Recent theoretical interest in migration systems calls attention to the functions of diverse linkages between countries in stimulating, directing,and maintaining international flows of people. This article proposes a conceptual framework for the non-people linkages in international migration systems and discusses the implications for population movement of the 4 categories and 3 types of linkages that define the network. The 4 categories include 1) state to state relations, 2) mass culture connections, 3) family and personal networks, and 4) migrant agency activities. The 3 types of linkages are 1) tangible linkages, 2) regulatory linkages, and 3) relational linkages.

  17. 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.

  18. Network operating system focus technology

    Science.gov (United States)

    1985-01-01

    An activity structured to provide specific design requirements and specifications for the Space Station Data Management System (DMS) Network Operating System (NOS) is outlined. Examples are given of the types of supporting studies and implementation tasks presently underway to realize a DMS test bed capability to develop hands-on understanding of NOS requirements as driven by actual subsystem test beds participating in the overall Johnson Space Center test bed program. Classical operating system elements and principal NOS functions are listed.

  19. Pedestrian Detection Based on Adaptive Selection of Visible Light or Far-Infrared Light Camera Image by Fuzzy Inference System and Convolutional Neural Network-Based Verification.

    Science.gov (United States)

    Kang, Jin Kyu; Hong, Hyung Gil; Park, Kang Ryoung

    2017-07-08

    A number of studies have been conducted to enhance the pedestrian detection accuracy of intelligent surveillance systems. However, detecting pedestrians under outdoor conditions is a challenging problem due to the varying lighting, shadows, and occlusions. In recent times, a growing number of studies have been performed on visible light camera-based pedestrian detection systems using a convolutional neural network (CNN) in order to make the pedestrian detection process more resilient to such conditions. However, visible light cameras still cannot detect pedestrians during nighttime, and are easily affected by shadows and lighting. There are many studies on CNN-based pedestrian detection through the use of far-infrared (FIR) light cameras (i.e., thermal cameras) to address such difficulties. However, when the solar radiation increases and the background temperature reaches the same level as the body temperature, it remains difficult for the FIR light camera to detect pedestrians due to the insignificant difference between the pedestrian and non-pedestrian features within the images. Researchers have been trying to solve this issue by inputting both the visible light and the FIR camera images into the CNN as the input. This, however, takes a longer time to process, and makes the system structure more complex as the CNN needs to process both camera images. This research adaptively selects a more appropriate candidate between two pedestrian images from visible light and FIR cameras based on a fuzzy inference system (FIS), and the selected candidate is verified with a CNN. Three types of databases were tested, taking into account various environmental factors using visible light and FIR cameras. The results showed that the proposed method performs better than the previously reported methods.

  20. Networked control of microgrid system of systems

    Science.gov (United States)

    Mahmoud, Magdi S.; Rahman, Mohamed Saif Ur; AL-Sunni, Fouad M.

    2016-08-01

    The microgrid has made its mark in distributed generation and has attracted widespread research. However, microgrid is a complex system which needs to be viewed from an intelligent system of systems perspective. In this paper, a network control system of systems is designed for the islanded microgrid system consisting of three distributed generation units as three subsystems supplying a load. The controller stabilises the microgrid system in the presence of communication infractions such as packet dropouts and delays. Simulation results are included to elucidate the effectiveness of the proposed control strategy.