Computational neural network regression model for Host based Intrusion Detection System

Directory of Open Access Journals (Sweden)

Sunil Kumar Gautam

2016-09-01

Full Text Available The current scenario of information gathering and storing in secure system is a challenging task due to increasing cyber-attacks. There exists computational neural network techniques designed for intrusion detection system, which provide security to single machine and entire network's machine. In this paper, we have used two types of computational neural network models, namely, Generalized Regression Neural Network (GRNN model and Multilayer Perceptron Neural Network (MPNN model for Host based Intrusion Detection System using log files that are generated by a single personal computer. The simulation results show correctly classified percentage of normal and abnormal (intrusion class using confusion matrix. On the basis of results and discussion, we found that the Host based Intrusion Systems Model (HISM significantly improved the detection accuracy while retaining minimum false alarm rate.

Approaches in anomaly-based network intrusion detection systems

NARCIS (Netherlands)

Bolzoni, D.; Etalle, S.; Di Pietro, R.; Mancini, L.V.

2008-01-01

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

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

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.

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.

Formal Specification Based Automatic Test Generation for Embedded Network Systems

Directory of Open Access Journals (Sweden)

Eun Hye Choi

2014-01-01

Full Text Available Embedded systems have become increasingly connected and communicate with each other, forming large-scaled and complicated network systems. To make their design and testing more reliable and robust, this paper proposes a formal specification language called SENS and a SENS-based automatic test generation tool called TGSENS. Our approach is summarized as follows: (1 A user describes requirements of target embedded network systems by logical property-based constraints using SENS. (2 Given SENS specifications, test cases are automatically generated using a SAT-based solver. Filtering mechanisms to select efficient test cases are also available in our tool. (3 In addition, given a testing goal by the user, test sequences are automatically extracted from exhaustive test cases. We’ve implemented our approach and conducted several experiments on practical case studies. Through the experiments, we confirmed the efficiency of our approach in design and test generation of real embedded air-conditioning network systems.

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.

Symptom based diagnostic system using artificial neural networks

International Nuclear Information System (INIS)

Santosh; Vinod, Gopika; Saraf, R.K.

2003-01-01

Nuclear power plant experiences a number of transients during its operations. In case of such an undesired plant condition generally known as an initiating event, the operator has to carry out diagnostic and corrective actions. The operator's response may be too late to mitigate or minimize the negative consequences in such scenarios. The objective of this work is to develop an operator support system based on artificial neural networks that will assist the operator to identify the initiating events at the earliest stages of their developments. A symptom based diagnostic system has been developed to investigate the initiating events. Neutral networks are utilized for carrying out the event identification by continuously monitoring process parameters. Whenever an event is detected, the system will display the necessary operator actions along with the initiating event. The system will also show the graphical trend of process parameters that are relevant to the event. This paper describes the features of the software that is used to monitor the reactor. (author)

Automated implementation of rule-based expert systems with neural networks for time-critical applications

Science.gov (United States)

Ramamoorthy, P. A.; Huang, Song; Govind, Girish

1991-01-01

In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

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.

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.

Study on shielded pump system failure analysis method based on Bayesian network

International Nuclear Information System (INIS)

Bao Yilan; Huang Gaofeng; Tong Lili; Cao Xuewu

2012-01-01

This paper applies Bayesian network to the system failure analysis, with an aim to improve knowledge representation of the uncertainty logic and multi-fault states in system failure analysis. A Bayesian network for shielded pump failure analysis is presented, conducting fault parameter learning, updating Bayesian network parameter based on new samples. Finally, through the Bayesian network inference, vulnerability in this system, the largest possible failure modes, and the fault probability are obtained. The powerful ability of Bayesian network to analyze system fault is illustrated by examples. (authors)

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.

Reliability estimation of safety-critical software-based systems using Bayesian networks

International Nuclear Information System (INIS)

Helminen, A.

2001-06-01

Due to the nature of software faults and the way they cause system failures new methods are needed for the safety and reliability evaluation of software-based safety-critical automation systems in nuclear power plants. In the research project 'Programmable automation system safety integrity assessment (PASSI)', belonging to the Finnish Nuclear Safety Research Programme (FINNUS, 1999-2002), various safety assessment methods and tools for software based systems are developed and evaluated. The project is financed together by the Radiation and Nuclear Safety Authority (STUK), the Ministry of Trade and Industry (KTM) and the Technical Research Centre of Finland (VTT). In this report the applicability of Bayesian networks to the reliability estimation of software-based systems is studied. The applicability is evaluated by building Bayesian network models for the systems of interest and performing simulations for these models. In the simulations hypothetical evidence is used for defining the parameter relations and for determining the ability to compensate disparate evidence in the models. Based on the experiences from modelling and simulations we are able to conclude that Bayesian networks provide a good method for the reliability estimation of software-based systems. (orig.)

Image/video understanding systems based on network-symbolic models

Science.gov (United States)

Kuvich, Gary

2004-03-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/network models is found. Symbols, predicates and grammars naturally emerge in such networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type relational structure created via multilevel hierarchical compression of visual information. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. Spatial logic and topology naturally present in such structures. Mid-level vision processes like perceptual grouping, separation of figure from ground, are special kinds of network transformations. They convert primary image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models combines learning, classification, and analogy together with higher-level model-based reasoning into a single framework, and it works similar to frames and agents. Computational intelligence methods transform images into model-based knowledge representation. Based on such principles, an Image/Video Understanding system can convert images into the knowledge models, and resolve uncertainty and ambiguity. This allows creating intelligent computer vision systems for design and manufacturing.

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. PMID:22408521

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.

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.

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

Institute of Scientific and Technical Information of China (English)

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

2007-01-01

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

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.

Study of Personalized Network Tutoring System Based on Emotional-cognitive Interaction

Science.gov (United States)

Qi, Manfei; Ma, Ding; Wang, Wansen

Aiming at emotion deficiency in present Network tutoring system, a lot of negative effects is analyzed and corresponding countermeasures are proposed. The model of Personalized Network tutoring system based on Emotional-cognitive interaction is constructed in the paper. The key techniques of realizing the system such as constructing emotional model and adjusting teaching strategies are also introduced.

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.

Network reliability analysis of complex systems using a non-simulation-based method

International Nuclear Information System (INIS)

Kim, Youngsuk; Kang, Won-Hee

2013-01-01

Civil infrastructures such as transportation, water supply, sewers, telecommunications, and electrical and gas networks often establish highly complex networks, due to their multiple source and distribution nodes, complex topology, and functional interdependence between network components. To understand the reliability of such complex network system under catastrophic events such as earthquakes and to provide proper emergency management actions under such situation, efficient and accurate reliability analysis methods are necessary. In this paper, a non-simulation-based network reliability analysis method is developed based on the Recursive Decomposition Algorithm (RDA) for risk assessment of generic networks whose operation is defined by the connections of multiple initial and terminal node pairs. The proposed method has two separate decomposition processes for two logical functions, intersection and union, and combinations of these processes are used for the decomposition of any general system event with multiple node pairs. The proposed method is illustrated through numerical network examples with a variety of system definitions, and is applied to a benchmark gas transmission pipe network in Memphis TN to estimate the seismic performance and functional degradation of the network under a set of earthquake scenarios.

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.

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

Arrester Resistive Current Measuring System Based on Heterogeneous Network

Science.gov (United States)

Zhang, Yun Hua; Li, Zai Lin; Yuan, Feng; Hou Pan, Feng; Guo, Zhan Nan; Han, Yue

2018-03-01

Metal Oxide Arrester (MOA) suffers from aging and poor insulation due to long-term impulse voltage and environmental impact, and the value and variation tendency of resistive current can reflect the health conditions of MOA. The common wired MOA detection need to use long cables, which is complicated to operate, and that wireless measurement methods are facing the problems of poor data synchronization and instability. Therefore a novel synchronous measurement system of arrester current resistive based on heterogeneous network is proposed, which simplifies the calculation process and improves synchronization, accuracy and stability and of the measuring system. This system combines LoRa wireless network, high speed wireless personal area network and the process layer communication, and realizes the detection of arrester working condition. Field test data shows that the system has the characteristics of high accuracy, strong anti-interference ability and good synchronization, which plays an important role in ensuring the stable operation of the power grid.

Decoupling control of vehicle chassis system based on neural network inverse system

Science.gov (United States)

Wang, Chunyan; Zhao, Wanzhong; Luan, Zhongkai; Gao, Qi; Deng, Ke

2018-06-01

Steering and suspension are two important subsystems affecting the handling stability and riding comfort of the chassis system. In order to avoid the interference and coupling of the control channels between active front steering (AFS) and active suspension subsystems (ASS), this paper presents a composite decoupling control method, which consists of a neural network inverse system and a robust controller. The neural network inverse system is composed of a static neural network with several integrators and state feedback of the original chassis system to approach the inverse system of the nonlinear systems. The existence of the inverse system for the chassis system is proved by the reversibility derivation of Interactor algorithm. The robust controller is based on the internal model control (IMC), which is designed to improve the robustness and anti-interference of the decoupled system by adding a pre-compensation controller to the pseudo linear system. The results of the simulation and vehicle test show that the proposed decoupling controller has excellent decoupling performance, which can transform the multivariable system into a number of single input and single output systems, and eliminate the mutual influence and interference. Furthermore, it has satisfactory tracking capability and robust performance, which can improve the comprehensive performance of the chassis system.

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.

Group Recommendation Systems Based on External Social-Trust Networks

Directory of Open Access Journals (Sweden)

Guang Fang

2018-01-01

Full Text Available With the development of social networks and online mobile communities, group recommendation systems support users’ interaction with similar interests or purposes with others. We often provide some advices to the close friends, such as listening to favorite music and sharing favorite dishes. However, users’ personalities have been ignored by the traditional group recommendation systems while the majority is satisfied. In this paper, a method of group recommendation based on external social-trust networks is proposed, which builds a group profile by analyzing not only users’ preferences, but also the social relationships between members inside and outside of the group. We employ the users’ degree of disagreement to adjust group preference rating by external information of social-trust network. Moreover, having a discussion about different social network utilization ratio, we proposed a method to work for smaller group size. The experimental results show that the proposed method has consistently higher precision and leads to satisfactory recommendations for groups.

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

Science.gov (United States)

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

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

Research of negotiation in network trade system based on multi-agent

Science.gov (United States)

Cai, Jun; Wang, Guozheng; Wu, Haiyan

2009-07-01

A construction and implementation technology of network trade based on multi-agent is described in this paper. First, we researched the technology of multi-agent, then we discussed the consumer's behaviors and the negotiation between purchaser and bargainer which emerges in the traditional business mode and analysed the key technology to implement the network trade system. Finally, we implement the system.

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.

Development of network-based multichannel neuromuscular electrical stimulation system for stroke rehabilitation.

Science.gov (United States)

Qu, Hongen; Xie, Yongji; Liu, Xiaoxuan; He, Xin; Hao, Manzhao; Bao, Yong; Xie, Qing; Lan, Ning

2016-01-01

Neuromuscular electrical stimulation (NMES) is a promising assistive technology for stroke rehabilitation. Here we present the design and development of a multimuscle stimulation system as an emerging therapy for people with paretic stroke. A network-based multichannel NMES system was integrated based on dual bus architecture of communication and an H-bridge current regulator with a power booster. The structure of the system was a body area network embedded with multiple stimulators and a communication protocol of controlled area network to transmit muscle stimulation parameter information to individual stimulators. A graphical user interface was designed to allow clinicians to specify temporal patterns and muscle stimulation parameters. We completed and tested a prototype of the hardware and communication software modules of the multichannel NMES system. The prototype system was first verified in nondisabled subjects for safety, and then tested in subjects with stroke for feasibility with assisting multijoint movements. Results showed that synergistic stimulation of multiple muscles in subjects with stroke improved performance of multijoint movements with more natural velocity profiles at elbow and shoulder and reduced acromion excursion due to compensatory trunk rotation. The network-based NMES system may provide an innovative solution that allows more physiological activation of multiple muscles in multijoint task training for patients with stroke.

Color Image Encryption Algorithm Based on TD-ERCS System and Wavelet Neural Network

Directory of Open Access Journals (Sweden)

Kun Zhang

2015-01-01

Full Text Available In order to solve the security problem of transmission image across public networks, a new image encryption algorithm based on TD-ERCS system and wavelet neural network is proposed in this paper. According to the permutation process and the binary XOR operation from the chaotic series by producing TD-ERCS system and wavelet neural network, it can achieve image encryption. This encryption algorithm is a reversible algorithm, and it can achieve original image in the rule inverse process of encryption algorithm. Finally, through computer simulation, the experiment results show that the new chaotic encryption algorithm based on TD-ERCS system and wavelet neural network is valid and has higher security.

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

Container-code recognition system based on computer vision and deep neural networks

Science.gov (United States)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

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.

Network based multi-channel digital flash X-ray imaging system

International Nuclear Information System (INIS)

Wang Jingjin; Yuan Jie; Liu Yaqiang; Lin Yong; Song Zheng; Liu Keyin; Zhang Qi; Zheng Futang

2000-01-01

A network based multi-channel digital flash X-ray imaging system has been developed. It can be used to acquire and digitize orthogonal flash X-ray images in multi-interval, and to distribute the images on the network. There is no need of films and chemical process, no anxiety of waiting and no trouble of film archiving. This system is useful for testing ballistics, jet, explode, armour-piercing and fast running machines. The system composing and acquired images are presented. The software for object separating, mass calculating, 3D positioning, speed determining and cavity reconstruction are described

Network based multi-channel digital flash X-ray imaging system

International Nuclear Information System (INIS)

Wang Jingjin; Yuan Jie; Liu Yaqiang; Lin Yong; Song Zheng; Liu Keyin

2003-01-01

A network based multi-channel digital flash X-ray imaging system has been developed. It can be used to acquire and digitize orthogonal flash X-ray images in multi-interval, and to distribute the images on the network. There is no need of films and chemical process, no anxiety of waiting and no trouble of film archiving. This system is useful for testing ballistics, jet, explode, armour-piercing and fast running machines. The system composing and acquired images of terminal ballistics are presented. The software for object separating, profile calculating and 3D cavity reconstruction are described

A Wildlife Monitoring System Based on Wireless Image Sensor Networks

Directory of Open Access Journals (Sweden)

Junguo Zhang

2014-10-01

Full Text Available Survival and development of wildlife sustains the balance and stability of the entire ecosystem. Wildlife monitoring can provide lots of information such as wildlife species, quantity, habits, quality of life and habitat conditions, to help researchers grasp the status and dynamics of wildlife resources, and to provide basis for the effective protection, sustainable use, and scientific management of wildlife resources. Wildlife monitoring is the foundation of wildlife protection and management. Wireless Sensor Networks (WSN technology has become the most popular technology in the field of information. With advance of the CMOS image sensor technology, wireless sensor networks combined with image sensors, namely Wireless Image Sensor Networks (WISN technology, has emerged as an alternative in monitoring applications. Monitoring wildlife is one of its most promising applications. In this paper, system architecture of the wildlife monitoring system based on the wireless image sensor networks was presented to overcome the shortcomings of the traditional monitoring methods. Specifically, some key issues including design of wireless image sensor nodes and software process design have been studied and presented. A self-powered rotatable wireless infrared image sensor node based on ARM and an aggregation node designed for large amounts of data were developed. In addition, their corresponding software was designed. The proposed system is able to monitor wildlife accurately, automatically, and remotely in all-weather condition, which lays foundations for applications of wireless image sensor networks in wildlife monitoring.

Real-time camera-based face detection using a modified LAMSTAR neural network system

Science.gov (United States)

Girado, Javier I.; Sandin, Daniel J.; DeFanti, Thomas A.; Wolf, Laura K.

2003-03-01

This paper describes a cost-effective, real-time (640x480 at 30Hz) upright frontal face detector as part of an ongoing project to develop a video-based, tetherless 3D head position and orientation tracking system. The work is specifically targeted for auto-stereoscopic displays and projection-based virtual reality systems. The proposed face detector is based on a modified LAMSTAR neural network system. At the input stage, after achieving image normalization and equalization, a sub-window analyzes facial features using a neural network. The sub-window is segmented, and each part is fed to a neural network layer consisting of a Kohonen Self-Organizing Map (SOM). The output of the SOM neural networks are interconnected and related by correlation-links, and can hence determine the presence of a face with enough redundancy to provide a high detection rate. To avoid tracking multiple faces simultaneously, the system is initially trained to track only the face centered in a box superimposed on the display. The system is also rotationally and size invariant to a certain degree.

A neural network based artificial vision system for licence plate recognition.

Science.gov (United States)

Draghici, S

1997-02-01

This paper presents a neural network based artificial vision system able to analyze the image of a car given by a camera, locate the registration plate and recognize the registration number of the car. The paper describes in detail various practical problems encountered in implementing this particular application and the solutions used to solve them. The main features of the system presented are: controlled stability-plasticity behavior, controlled reliability threshold, both off-line and on-line learning, self assessment of the output reliability and high reliability based on high level multiple feedback. The system has been designed using a modular approach. Sub-modules can be upgraded and/or substituted independently, thus making the system potentially suitable in a large variety of vision applications. The OCR engine was designed as an interchangeable plug-in module. This allows the user to choose an OCR engine which is suited to the particular application and to upgrade it easily in the future. At present, there are several versions of this OCR engine. One of them is based on a fully connected feedforward artificial neural network with sigmoidal activation functions. This network can be trained with various training algorithms such as error backpropagation. An alternative OCR engine is based on the constraint based decomposition (CBD) training architecture. The system has showed the following performances (on average) on real-world data: successful plate location and segmentation about 99%, successful character recognition about 98% and successful recognition of complete registration plates about 80%.

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

International Nuclear Information System (INIS)

Li, B B; Yuan, Z F

2006-01-01

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

Alerts Analysis and Visualization in Network-based Intrusion Detection Systems

Energy Technology Data Exchange (ETDEWEB)

Yang, Dr. Li [University of Tennessee

2010-08-01

The alerts produced by network-based intrusion detection systems, e.g. Snort, can be difficult for network administrators to efficiently review and respond to due to the enormous number of alerts generated in a short time frame. This work describes how the visualization of raw IDS alert data assists network administrators in understanding the current state of a network and quickens the process of reviewing and responding to intrusion attempts. The project presented in this work consists of three primary components. The first component provides a visual mapping of the network topology that allows the end-user to easily browse clustered alerts. The second component is based on the flocking behavior of birds such that birds tend to follow other birds with similar behaviors. This component allows the end-user to see the clustering process and provides an efficient means for reviewing alert data. The third component discovers and visualizes patterns of multistage attacks by profiling the attacker s behaviors.

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.

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.

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.

Resilient Coordination of Networked Multiagent Systems Based on Distributed State Emulators

OpenAIRE

Yucelen, Tansel; De La Torre, Gerardo

2014-01-01

This note studies resilient coordination of networked multiagent systems in the presence of misbehaving agents, i.e., agents that are subject to adversaries modeled as exogenous disturbances. Apart from the existing relevant literature that make specific assumptions on the graph topology and/or the fraction of misbehaving agents, we present an adaptive control architecture based on distributed state emulators and show that the nominal networked multiagent system behavior can be retrieved even...

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.

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...

High Frequency Resonance Damping of DFIG based Wind Power System under Weak Network

DEFF Research Database (Denmark)

Song, Yipeng; Wang, Xiongfei; Blaabjerg, Frede

2017-01-01

When operating in a micro or weak grid which has a relatively large network impedance, the Doubly Fed Induction Generator (DFIG) based wind power generation system is prone to suffer high frequency resonance due to the impedance interaction between DFIG system and the parallel compensated network...

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.

Adaptive mechanism-based congestion control for networked systems

Science.gov (United States)

Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

2013-03-01

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

A local-area-network based radiation oncology microcomputer system

International Nuclear Information System (INIS)

Chu, W.K.; Taylor, T.K.; Kumar, P.P.; Imray, T.J.

1985-01-01

The application of computerized technology in the medical specialty of radiation oncology has gained wide acceptance in the past decade. Recognizing that most radiation oncology department personnel are familiar with computer operations and terminology, it appears reasonable to attempt to expand the computer's applications to other departmental activities, such as scheduling, record keeping, billing, treatment regimen and status, etc. Instead of sharing the processing capability available on the existent treatment minicomputer, the radiation oncology computer system is based upon a microcomputer local area network (LAN). The system was conceptualized in 1984 and completed in March 1985. This article outlines the LAN-based radiation oncology computer system

A Neural Networks Based Operation Guidance System for Procedure Presentation and Validation

International Nuclear Information System (INIS)

Seung, Kun Mo; Lee, Seung Jun; Seong, Poong Hyun

2006-01-01

In this paper, a neural network based operator support system is proposed to reduce operator's errors in abnormal situations in nuclear power plants (NPPs). There are many complicated situations, in which regular and suitable operations should be done by operators accordingly. In order to regulate and validate operators' operations, it is necessary to develop an operator support system which includes computer based procedures with the functions for operation validation. Many computerized procedures systems (CPS) have been recently developed. Focusing on the human machine interface (HMI) design and procedures' computerization, most of CPSs used various methodologies to enhance system's convenience, reliability and accessibility. Other than only showing procedures, the proposed system integrates a simple CPS and an operation validation system (OVS) by using artificial neural network (ANN) for operational permission and quantitative evaluation

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

Indian Academy of Sciences (India)

2016-08-26

Aug 26, 2016 ... The paper describes a neural network-based script identification system which can be used in the machine reading of documents written in English, Hindi and Kannada language scripts. Script identification is a basic requirement in automation of document processing, in multi-script, multi-lingual ...

Large-scale computer networks and the future of legal knowledge-based systems

NARCIS (Netherlands)

Leenes, R.E.; Svensson, Jorgen S.; Hage, J.C.; Bench-Capon, T.J.M.; Cohen, M.J.; van den Herik, H.J.

1995-01-01

In this paper we investigate the relation between legal knowledge-based systems and large-scale computer networks such as the Internet. On the one hand, researchers of legal knowledge-based systems have claimed huge possibilities, but despite the efforts over the last twenty years, the number of

A web-based system for neural network based classification in temporomandibular joint osteoarthritis.

Science.gov (United States)

de Dumast, Priscille; Mirabel, Clément; Cevidanes, Lucia; Ruellas, Antonio; Yatabe, Marilia; Ioshida, Marcos; Ribera, Nina Tubau; Michoud, Loic; Gomes, Liliane; Huang, Chao; Zhu, Hongtu; Muniz, Luciana; Shoukri, Brandon; Paniagua, Beatriz; Styner, Martin; Pieper, Steve; Budin, Francois; Vimort, Jean-Baptiste; Pascal, Laura; Prieto, Juan Carlos

2018-07-01

The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans. The training dataset consisted of 259 condyles, 105 from control subjects and 154 from patients with diagnosis of TMJ OA. For the image analysis classification, 34 right and left condyles from 17 patients (39.9 ± 11.7 years), who experienced signs and symptoms of the disease for less than 5 years, were included as the testing dataset. For the integrative statistical model of clinical, biological and imaging markers, the sample consisted of the same 17 test OA subjects and 17 age and sex matched control subjects (39.4 ± 15.4 years), who did not show any sign or symptom of OA. For these 34 subjects, a standardized clinical questionnaire, blood and saliva samples were also collected. The technological methodologies in this study include a deep neural network classifier of 3D condylar morphology (ShapeVariationAnalyzer, SVA), and a flexible web-based system for data storage, computation and integration (DSCI) of high dimensional imaging, clinical, and biological data. The DSCI system trained and tested the neural network, indicating 5 stages of structural degenerative changes in condylar morphology in the TMJ with 91% close agreement between the clinician consensus and the SVA classifier. The DSCI remotely ran with a novel application of a statistical analysis, the Multivariate Functional Shape Data Analysis, that computed high dimensional correlations between shape 3D coordinates, clinical pain levels and levels of biological markers, and then graphically displayed the computation results. The findings of this

A Lindenmayer system-based approach for the design of nutrient delivery networks in tissue constructs

International Nuclear Information System (INIS)

Yasar, Ozlem; Starly, Binil; Lan, S-F

2009-01-01

Large thick tissue constructs have reported limited success primarily due to the inability of cells to survive deep within the scaffold. Without access to adequate nutrients, cells placed deep within the tissue construct will die out, leading to non-uniform tissue regeneration. Currently, there is a necessity to design nutrient conduit networks within the tissue construct to enable cells to survive in the matrix. However, the design of complex networks within a tissue construct is challenging. In this paper, we present the Lindenmayer system, an elegant fractal-based language algorithm framework, to generate conduit networks in two- and three-dimensional architecture with several degrees of complexity. The conduit network maintains a parent-child relationship between each branch of the network. Several L-system parameters have been studied-branching angle, branch length, ratio of parent to child branch diameter, etc-to simulate several architectures under a given L-system notation. We have also presented a layered manufacturing-based UV-photopolymerization process using the Texas Instruments DLP(TM) system to fabricate the branched structures. This preliminary work showcases the applicability of L-system-based construct designs to drive scaffold fabrication systems.

A Lindenmayer system-based approach for the design of nutrient delivery networks in tissue constructs

Energy Technology Data Exchange (ETDEWEB)

Yasar, Ozlem; Starly, Binil [School of Industrial Engineering, University of Oklahoma, Norman, OK 73019 (United States); Lan, S-F [University of Oklahoma Bioengineering Center, University of Oklahoma, Norman, OK 73019 (United States)

2009-12-15

Large thick tissue constructs have reported limited success primarily due to the inability of cells to survive deep within the scaffold. Without access to adequate nutrients, cells placed deep within the tissue construct will die out, leading to non-uniform tissue regeneration. Currently, there is a necessity to design nutrient conduit networks within the tissue construct to enable cells to survive in the matrix. However, the design of complex networks within a tissue construct is challenging. In this paper, we present the Lindenmayer system, an elegant fractal-based language algorithm framework, to generate conduit networks in two- and three-dimensional architecture with several degrees of complexity. The conduit network maintains a parent-child relationship between each branch of the network. Several L-system parameters have been studied-branching angle, branch length, ratio of parent to child branch diameter, etc-to simulate several architectures under a given L-system notation. We have also presented a layered manufacturing-based UV-photopolymerization process using the Texas Instruments DLP(TM) system to fabricate the branched structures. This preliminary work showcases the applicability of L-system-based construct designs to drive scaffold fabrication systems.

Ensemble of classifiers based network intrusion detection system performance bound

CSIR Research Space (South Africa)

Mkuzangwe, Nenekazi NP

2017-11-01

Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

Network Traffic Features for Anomaly Detection in Specific Industrial Control System Network

Directory of Open Access Journals (Sweden)

Matti Mantere

2013-09-01

Full Text Available The deterministic and restricted nature of industrial control system networks sets them apart from more open networks, such as local area networks in office environments. This improves the usability of network security, monitoring approaches that would be less feasible in more open environments. One of such approaches is machine learning based anomaly detection. Without proper customization for the special requirements of the industrial control system network environment, many existing anomaly or misuse detection systems will perform sub-optimally. A machine learning based approach could reduce the amount of manual customization required for different industrial control system networks. In this paper we analyze a possible set of features to be used in a machine learning based anomaly detection system in the real world industrial control system network environment under investigation. The network under investigation is represented by architectural drawing and results derived from network trace analysis. The network trace is captured from a live running industrial process control network and includes both control data and the data flowing between the control network and the office network. We limit the investigation to the IP traffic in the traces.

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.

Smart Home System Based on GSM Network

Directory of Open Access Journals (Sweden)

Bakhtiar Ali Karim

2018-04-01

Full Text Available Due to increasing robbery and intrusion, establishing home-security system has become a correlated part of the modern houses, buildings, and offices. As the family members are not at home all the time, the traditional home security system, which makes alarm sound only, may not be efficient enough. Alternatively, Global System for Mobile communications (GSM based security system can provide higher level of security and convenience compared to the traditionally used systems. The main objective of the current paper is to design and implement cost-efficient and reliable security, safety and home automation system for protection and occupants’ convenience. If any undesired events, such as intrusion, gas leakage and fire occurs in the house, our system warns the homeowner in real-time using Short Message Service (SMS. With the proposed system home appliances can also be controlled in three ways, namely sending SMS from the authorized numbers to the system through GSM network, smartphone app using Bluetooth module and infrared (IR control using IR module

A Sliding Mode Control-based on a RBF Neural Network for Deburring Industry Robotic Systems

OpenAIRE

Tao, Yong; Zheng, Jiaqi; Lin, Yuanchang

2016-01-01

A sliding mode control method based on radial basis function (RBF) neural network is proposed for the deburring of industry robotic systems. First, a dynamic model for deburring the robot system is established. Then, a conventional SMC scheme is introduced for the joint position tracking of robot manipulators. The RBF neural network based sliding mode control (RBFNN-SMC) has the ability to learn uncertain control actions. In the RBFNN-SMC scheme, the adaptive tuning algorithms for network par...

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.

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

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

Institute of Scientific and Technical Information of China (English)

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 3PLs is constructed,including the four layers (the network communication layer,the hardware and software environment layer,the database layer,and the application layer) and 7 function modules (centralized control,transportation process management,material and vehicle scheduling,customer relationship,storage management,customer inquiry,and financial management).Framework for the network management information system of agricultural products supply chain based on 3PLs is put forward.The management of 3PLs mainly includes purchasing management,supplier relationship management,planning management,customer relationship management,storage management and distribution management.Thus,a management system of internal and external integrated agricultural enterprises is obtained.The network management information system of agricultural products supply chain based on 3PLs has realized the effective sharing of enterprise information of agricultural products supply chain at different nodes,establishing a long-term partnership revolving around the 3PLs core enterprise,as well as a supply chain with stable relationship based on the supply chain network system,so as to improve the circulation efficiency of agricultural products,and to explore the sales market for agricultural products.

Networked Estimation for Event-Based Sampling Systems with Packet Dropouts

Directory of Open Access Journals (Sweden)

Young Soo Suh

2009-04-01

Full Text Available This paper is concerned with a networked estimation problem in which sensor data are transmitted over the network. In the event-based sampling scheme known as level-crossing or send-on-delta (SOD, sensor data are transmitted to the estimator node if the difference between the current sensor value and the last transmitted one is greater than a given threshold. Event-based sampling has been shown to be more efficient than the time-triggered one in some situations, especially in network bandwidth improvement. However, it cannot detect packet dropout situations because data transmission and reception do not use a periodical time-stamp mechanism as found in time-triggered sampling systems. Motivated by this issue, we propose a modified event-based sampling scheme called modified SOD in which sensor data are sent when either the change of sensor output exceeds a given threshold or the time elapses more than a given interval. Through simulation results, we show that the proposed modified SOD sampling significantly improves estimation performance when packet dropouts happen.

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

African Journals Online (AJOL)

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

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.

Investigation of the network delay on Profibus-DP based network

OpenAIRE

Yılmaz, C.; Gürdal, O.; Sayan, H.H.

2008-01-01

The mathematical model of the network-induced delay control systems (NDCS) is given. Also the role of the NDCS’s components such as controller, sensor and network environment on the network-induced delay are included in the mathematical model of the system. The network delay is investigated on Profibus-DP based network application and experimental results obtained are presented graphically. The experimental results obtained show that the network induced delay is randomly changed according to ...

Design of Mine Ventilators Monitoring System Based on Wireless Sensor Network

International Nuclear Information System (INIS)

Fu Sheng; Song Haiqiang

2012-01-01

A monitoring system for a mine ventilator is designed based on ZigBee wireless sensor network technology in the paper. The system consists of a sink node, sensor nodes, industrial personal computer and several sensors. Sensor nodes communicate with the sink node through the ZigBee wireless sensor network. The sink node connects with the configuration software on the pc via serial port. The system can collect or calculate vibration, temperature, negative pressure, air volume and other information of the mine ventilator. Meanwhile the system accurately monitors operating condition of the ventilator through these parameters. Especially it provides the most original information for potential faults of the ventilator. Therefore, there is no doubt that it improves the efficiency of fault diagnosis.

Design of Mine Ventilators Monitoring System Based on Wireless Sensor Network

Science.gov (United States)

Fu, Sheng; Song, Haiqiang

2012-05-01

A monitoring system for a mine ventilator is designed based on ZigBee wireless sensor network technology in the paper. The system consists of a sink node, sensor nodes, industrial personal computer and several sensors. Sensor nodes communicate with the sink node through the ZigBee wireless sensor network. The sink node connects with the configuration software on the pc via serial port. The system can collect or calculate vibration, temperature, negative pressure, air volume and other information of the mine ventilator. Meanwhile the system accurately monitors operating condition of the ventilator through these parameters. Especially it provides the most original information for potential faults of the ventilator. Therefore, there is no doubt that it improves the efficiency of fault diagnosis.

A Study on Recommendation Systems in Location Based Social Networking

Directory of Open Access Journals (Sweden)

Ranganath Ashok Kumar

2017-01-01

Full Text Available Smart devices in the hands of people are revolutionizing the social lifestyle of one's self. Everyone across the world are using smart devices linked to their social networking activities one such activity is to share location data by uploading the tagged media content like photos, videos. The data is of surroundings, events attended/attending and travel experiences. Users share their experiences at a given location through localization techniques. Using such data from social networks an attempt is made to analyse tagged media content to acquire information on user context, individual’s interests, tastes, behaviours and derive meaningful relationships amongst them are referred to as Location Based Social Networks (LBSNs. The resulting information can be used to market a product and to improve business, as well recommend a travel and plan an itinerary. This paper presents a comprehensive survey of recommended systems for LBSNs covering the concepts of LBSNs, terminologies of LBSN and various recommendation systems.

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 ...

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.

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

Energy Technology Data Exchange (ETDEWEB)

Olyaee, Saeed; Hamedi, Samaneh, E-mail: s_olyaee@srttu.edu [Nano-photonics and Optoelectronics Research Laboratory (NORLab), Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University (SRTTU), Lavizan, 16788, Tehran (Iran, Islamic Republic of)

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.

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

International Nuclear Information System (INIS)

Olyaee, Saeed; Hamedi, Samaneh

2011-01-01

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.

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.

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.

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

International Nuclear Information System (INIS)

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

2006-01-01

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

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.

Reliability analysis of a consecutive r-out-of-n: F system based on neural networks

International Nuclear Information System (INIS)

Habib, Aziz; Alsieidi, Ragab; Youssef, Ghada

2009-01-01

In this paper, we present a generalized Markov reliability and fault-tolerant model, which includes the effects of permanent fault and intermittent fault for reliability evaluations based on neural network techniques. The reliability of a consecutive r-out-of-n: F system was obtained with a three-layer connected neural network represents a discrete time state reliability Markov model of the system. Such that we fed the neural network with the desired reliability of the system under design. Then we extracted the parameters of the system from the neural weights at the convergence of the neural network to the desired reliability. Finally, we obtain simulation results.

Three neural network based sensor systems for environmental monitoring

International Nuclear Information System (INIS)

Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

1994-05-01

Compact, portable systems capable of quickly identifying contaminants in the field are of great importance when monitoring the environment. One of the missions of the Pacific Northwest Laboratory is to examine and develop new technologies for environmental restoration and waste management at the Hanford Site. In this paper, three prototype sensing systems are discussed. These prototypes are composed of sensing elements, data acquisition system, computer, and neural network implemented in software, and are capable of automatically identifying contaminants. The first system employs an array of tin-oxide gas sensors and is used to identify chemical vapors. The second system employs an array of optical sensors and is used to identify the composition of chemical dyes in liquids. The third system contains a portable gamma-ray spectrometer and is used to identify radioactive isotopes. In these systems, the neural network is used to identify the composition of the sensed contaminant. With a neural network, the intense computation takes place during the training process. Once the network is trained, operation consists of propagating the data through the network. Since the computation involved during operation consists of vector-matrix multiplication and application of look-up tables unknown samples can be rapidly identified in the field

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.

A Sliding Mode Control-Based on a RBF Neural Network for Deburring Industry Robotic Systems

Directory of Open Access Journals (Sweden)

Yong Tao

2016-01-01

Full Text Available A sliding mode control method based on radial basis function (RBF neural network is proposed for the deburring of industry robotic systems. First, a dynamic model for deburring the robot system is established. Then, a conventional SMC scheme is introduced for the joint position tracking of robot manipulators. The RBF neural network based sliding mode control (RBFNN-SMC has the ability to learn uncertain control actions. In the RBFNN-SMC scheme, the adaptive tuning algorithms for network parameters are derived by a Koski function algorithm to ensure the network convergences and enacts stable control. The simulations and experimental results of the deburring robot system are provided to illustrate the effectiveness of the proposed RBFNN-SMC control method. The advantages of the proposed RBFNN-SMC method are also evaluated by comparing it to existing control schemes.

ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

Institute of Scientific and Technical Information of China (English)

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

2003-01-01

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

An eConsent-based System Architecture Supporting Cooperation in Integrated Healthcare Networks.

Science.gov (United States)

Bergmann, Joachim; Bott, Oliver J; Hoffmann, Ina; Pretschner, Dietrich P

2005-01-01

The economical need for efficient healthcare leads to cooperative shared care networks. A virtual electronic health record is required, which integrates patient related information but reflects the distributed infrastructure and restricts access only to those health professionals involved into the care process. Our work aims on specification and development of a system architecture fulfilling these requirements to be used in concrete regional pilot studies. Methodical analysis and specification have been performed in a healthcare network using the formal method and modelling tool MOSAIK-M. The complexity of the application field was reduced by focusing on the scenario of thyroid disease care, which still includes various interdisciplinary cooperation. Result is an architecture for a secure distributed electronic health record for integrated care networks, specified in terms of a MOSAIK-M-based system model. The architecture proposes business processes, application services, and a sophisticated security concept, providing a platform for distributed document-based, patient-centred, and secure cooperation. A corresponding system prototype has been developed for pilot studies, using advanced application server technologies. The architecture combines a consolidated patient-centred document management with a decentralized system structure without needs for replication management. An eConsent-based approach assures, that access to the distributed health record remains under control of the patient. The proposed architecture replaces message-based communication approaches, because it implements a virtual health record providing complete and current information. Acceptance of the new communication services depends on compatibility with the clinical routine. Unique and cross-institutional identification of a patient is also a challenge, but will loose significance with establishing common patient cards.

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

DEFF Research Database (Denmark)

Park, Kiwoo

enable various renewable energy sources, such as Photovoltaic (PV) and wind, to produce dc power directly. In addition, battery-based energy storage systems inherently operate with dc power. Hence, dc network (dc-grid) systems which connect these dc sources and storages directly using dc networks...... are gaining much attention again. The dc network system has a great potential to outdo the traditional ac systems in many technical challenges and could be highly profitable especially for offshore wind farm applications, where the size and weight of the components are crucial to the entire system costs......Wind power technology, as the most competitive renewable energy technology, is quickly developing. The wind turbine size is growing and the grid penetration of wind power is increasing rapidly. Recently, the developments on wind power technology pay more attentions on efficiency and reliability...

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

OpenAIRE

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

2002-01-01

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

Social Network Analysis of the Caste-Based Reservation System in India

OpenAIRE

Iyengar, S. R. S.; Parasuram, Aishwarya; Saini, Jaspal Singh

2015-01-01

It has been argued that the reservation system in India, which has existed since the time of Indian Independence (1947), has caused more havoc and degradation than progress. This being a popular public opinion, these notions have not been based on any rigorous scientific study or research. In this paper, we revisit the cultural divide among the Indian population from a purely social networks based approach. We study the reservation system in detail, starting from its past and observing its ef...

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

Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

Science.gov (United States)

Shameldin, Ramez Ahmed; Bowling, Shannon R.

2010-01-01

The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

Signal-regulated systems and networks

CSIR Research Space (South Africa)

Van Zyl, TL

2010-07-01

Full Text Available The article presents the use of signal regulatory networks (SRNs), a biologically inspired model based on gene regulatory networks. SRNs are a way of understanding a class of self-organizing IT systems, signal-regulated systems (SRSs). This article...

The APS control system network

International Nuclear Information System (INIS)

Sidorowicz, K.V.; McDowell, W.P.

1995-01-01

The APS accelerator control system is a distributed system consisting of operator interfaces, a network, and computer-controlled interfaces to hardware. This implementation of a control system has come to be called the open-quotes Standard Model.close quotes The operator interface is a UNDC-based workstation with an X-windows graphical user interface. The workstation may be located at any point on the facility network and maintain full functionality. The function of the network is to provide a generalized communication path between the host computers, operator workstations, input/output crates, and other hardware that comprise the control system. The crate or input/output controller (IOC) provides direct control and input/output interfaces for each accelerator subsystem. The network is an integral part of all modem control systems and network performance will determine many characteristics of a control system. This paper will describe the overall APS network and examine the APS control system network in detail. Metrics are provided on the performance of the system under various conditions

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.

Research on Web-Based Networked Virtual Instrument System

International Nuclear Information System (INIS)

Tang, B P; Xu, C; He, Q Y; Lu, D

2006-01-01

The web-based networked virtual instrument (NVI) system is designed by using the object oriented methodology (OOM). The architecture of the NVI system consists of two major parts: client-web server interaction and instrument server-virtual instrument (VI) communication. The web server communicates with the instrument server and the clients connected to it over the Internet, and it handles identifying the user's name, managing the connection between the user and the instrument server, adding, removing and configuring VI's information. The instrument server handles setting the parameters of VI, confirming the condition of VI and saving the VI's condition information into the database. The NVI system is required to be a general-purpose measurement system that is easy to maintain, adapt and extend. Virtual instruments are connected to the instrument server and clients can remotely configure and operate these virtual instruments. An application of The NVI system is given in the end of the paper

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.

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.

Using adaptive network based fuzzy inference system to forecast regional electricity loads

International Nuclear Information System (INIS)

Ying, L.-C.; Pan, M.-C.

2008-01-01

Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads

Using adaptive network based fuzzy inference system to forecast regional electricity loads

Energy Technology Data Exchange (ETDEWEB)

Ying, Li-Chih [Department of Marketing Management, Central Taiwan University of Science and Technology, 11, Pu-tzu Lane, Peitun, Taichung City 406 (China); Pan, Mei-Chiu [Graduate Institute of Management Sciences, Nanhua University, 32, Chung Keng Li, Dalin, Chiayi 622 (China)

2008-02-15

Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads. (author)

Construct mine environment monitoring system based on wireless mesh network

Science.gov (United States)

Chen, Xin; Ge, Gengyu; Liu, Yinmei; Cheng, Aimin; Wu, Jun; Fu, Jun

2018-04-01

The system uses wireless Mesh network as a network transmission medium, and strive to establish an effective and reliable underground environment monitoring system. The system combines wireless network technology and embedded technology to monitor the internal data collected in the mine and send it to the processing center for analysis and environmental assessment. The system can be divided into two parts: the main control network module and the data acquisition terminal, and the SPI bus technology is used for mutual communication between them. Multi-channel acquisition and control interface design Data acquisition and control terminal in the analog signal acquisition module, digital signal acquisition module, and digital signal output module. The main control network module running Linux operating system, in which the transplant SPI driver, USB card driver and AODV routing protocol. As a result, the internal data collection and reporting of the mine are realized.

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.

Directory Enabled Policy Based Networking; TOPICAL

International Nuclear Information System (INIS)

KELIIAA, CURTIS M.

2001-01-01

This report presents a discussion of directory-enabled policy-based networking with an emphasis on its role as the foundation for securely scalable enterprise networks. A directory service provides the object-oriented logical environment for interactive cyber-policy implementation. Cyber-policy implementation includes security, network management, operational process and quality of service policies. The leading network-technology vendors have invested in these technologies for secure universal connectivity that transverses Internet, extranet and intranet boundaries. Industry standards are established that provide the fundamental guidelines for directory deployment scalable to global networks. The integration of policy-based networking with directory-service technologies provides for intelligent management of the enterprise network environment as an end-to-end system of related clients, services and resources. This architecture allows logical policies to protect data, manage security and provision critical network services permitting a proactive defense-in-depth cyber-security posture. Enterprise networking imposes the consideration of supporting multiple computing platforms, sites and business-operation models. An industry-standards based approach combined with principled systems engineering in the deployment of these technologies allows these issues to be successfully addressed. This discussion is focused on a directory-based policy architecture for the heterogeneous enterprise network-computing environment and does not propose specific vendor solutions. This document is written to present practical design methodology and provide an understanding of the risks, complexities and most important, the benefits of directory-enabled policy-based networking

Neural network based expert system for fault diagnosis of particle accelerators

International Nuclear Information System (INIS)

Dewidar, M.M.

1997-01-01

Particle accelerators are generators that produce beams of charged particles, acquiring different energies, depending on the accelerator type. The MGC-20 cyclotron is a cyclic particle accelerator used for accelerating protons, deuterons, alpha particles, and helium-3 to different energies. Its applications include isotope production, nuclear reaction, and mass spectroscopy studies. It is a complicated machine, it consists of five main parts, the ion source, the deflector, the beam transport system, the concentric and harmonic coils, and the radio frequency system. The diagnosis of this device is a very complex task. it depends on the conditions of 27 indicators of the control panel of the device. The accurate diagnosis can lead to a high system reliability and save maintenance costs. so an expert system for the cyclotron fault diagnosis is necessary to be built. In this thesis , a hybrid expert system was developed for the fault diagnosis of the MGC-20 cyclotron. Two intelligent techniques, multilayer feed forward back propagation neural network and the rule based expert system, are integrated as a pre-processor loosely coupled model to build the proposed hybrid expert system. The architecture of the developed hybrid expert system consists of two levels. The first level is two feed forward back propagation neural networks, used for isolating the faulty part of the cyclotron. The second level is the rule based expert system, used for troubleshooting the faults inside the isolated faulty part. 4-6 tabs., 4-5 figs., 36 refs

Logic-based models in systems biology: a predictive and parameter-free network analysis method.

Science.gov (United States)

Wynn, Michelle L; Consul, Nikita; Merajver, Sofia D; Schnell, Santiago

2012-11-01

Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network's dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples.

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.

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

Science.gov (United States)

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

2015-01-01

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. PMID:26016918

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

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

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.

Design of Early Warning System Based on Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Gan Bo

2018-01-01

Full Text Available In order to solve the shortcomings of the landslide monitoring technology method, a set of landslides monitoring and early warning system is designed. It can achieve real-time sensor data acquisition, remote transmission and query display. In addition, aiming at the harsh environment of landslide monitoring and the performance requirements of the monitoring system, an improved minimum hop routing protocol is proposed. It can reduce network energy consumption, enhance network robustness, and improve node layout and networking flexibility. In order to realize the remote transmission of data, GPRS wireless communication is used to transmit monitoring data. Combined with remote monitoring center, real-time data display, query, preservation and landslide warning and prediction are realized. The results show that the sensor data acquisition system is accurate, the system is stable, and the node network is flexible. Therefore, the monitoring system has a good use value.

COAP BASED ACUTE PARKING LOT MONITORING SYSTEM USING SENSOR NETWORKS

Directory of Open Access Journals (Sweden)

R. Aarthi

2014-06-01

Full Text Available Vehicle parking is the act of temporarily maneuvering a vehicle in to a certain location. To deal with parking monitoring system issue such as traffic, this paper proposes a vision of improvements in monitoring the vehicles in parking lots based on sensor networks. Most of the existing paper deals with that of the automated parking which is of cluster based and each has its own overheads like high power, less energy efficiency, incompatible size of lots, space. The novel idea in this work is usage of CoAP (Constrained Application Protocol which is recently created by IETF (draft-ietf-core-coap-18, June 28, 2013, CoRE group to develop RESTful application layer protocol for communications within embedded wireless networks. This paper deals with the enhanced CoAP protocol using multi hop flat topology, which makes the acuters feel soothe towards parking vehicles. We aim to minimize the time consumed for finding free parking lot as well as increase the energy efficiency

Optimising TCP for cloud-based mobile networks

DEFF Research Database (Denmark)

Artuso, Matteo; Christiansen, Henrik Lehrmann

2016-01-01

Cloud-based mobile networks are foreseen to be a technological enabler for the next generation of mobile networks. Their design requires substantial research as they pose unique challenges, especially from the point of view of additional delays in the fronthaul network. Commonly used network...... implementations of 3 popular operating systems are investigated in our network model. The results on the most influential parameters are used to design an optimized TCP for cloud-based mobile networks....

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.

Hydropower systems planning in distribution networks based on GIS

Energy Technology Data Exchange (ETDEWEB)

Ramirez-Rosado, I.J.; Zorzano-Santamaria, P.; Fernandez-Jiminez, L.A.; Garcia-Garrido, E.; Zorzano-Alba, E.; Lara-Santillan, P.M.; Mendoza-Villena, M. [La Rioja Univ., La Rioja (Spain). Dept. of Electrical Engineering

2005-07-01

Planning models for hydraulic energy systems developed with a new computational geographic information system (GIS) tool were presented. The GIS tool was used to identify sections of rivers that are suitable for small-scale run-of-river hydropower generation in the La Rioja region of Spain. The tool was also used to evaluate economic data related to financing grants, technological costs, installation costs, and forecast demands for various consumption scenarios. Case studies of 2 hydropower systems were used to test the tool. The planning models were based on levelized electric costs (LEC) of run-of-river hydropower systems, and enabled the systems to be analyzed in isolation as well as when connected to an existing electricity network. Results of the modelling studies showed that the tool is capable of analyzing the LEC of potential hydropower systems in a range of different scenarios while maintaining the geographic characteristics and requirements of individual regions. 7 refs., 4 figs.

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...

Network performance for graphical control systems

International Nuclear Information System (INIS)

Clout, P.; Geib, M.; Westervelt, R.

1992-01-01

Vsystem is a toolbox for building graphically-based control systems. The real-tiem database component, Vaccess, includes all the networking support necessary to build multi-computer control systems. Vaccess has two modes of database access, synchronous and asynchronous. Vdraw is another component of Vsystem that allows developers and users to develop control screens and windows by drawing rather than programming. Based on X-windows, Vsystem provides the possibility of running Vdraw either on the workstation with the graphics or on the computer with the database. We have made some measurements on the cpu loading, elapsed time and the network loading to give some guidance in system configuration performance. It will be seen that asynchronous network access gives large performance increases and that the network database change notification protocol can be either more or less efficient than the X-window network protocol, depending on the graphical representation of the data. (author)

An Embedded Multi-Agent Systems Based Industrial Wireless Sensor Network

Science.gov (United States)

Brennan, Robert W.

2017-01-01

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. PMID:28906452

The Design of Wireless Sensor Network System Based on ZigBee Technology for Greenhouse

International Nuclear Information System (INIS)

Zhu, Y W; Zhong, X X; Shi, J F

2006-01-01

Wireless sensor network is a new research field. It can be used in some special situation for signal collection, processing and transmitting. Zigbee is a new Wireless sensor network technology characteristic of less distance and low speed. It is a new wireless network protocol stack of IEEE 802.15.4. Lately traditional system to collects parameters for Greenhouse is widely used in agriculture. The traditional system adopts wired way wiring, which makes the system complex and expensive. Generally modern Greenhouse has hundreds of square meters and they may plant variety of plants depending on different seasons. So we need to adjust the sensors which collect parameters for Greenhouse to a better place to work more efficient. Adopting wireless way wiring is convenient and economical. This paper developed a wireless sensor network system based on ZigBee technology for greenhouse. It offers flexibility and mobility to save cost and energy spent on wiring. The framework hardware and software structure, related programming are also discussed in this paper. Comparing the system which uses ZigBee technology with traditional wired network system for greenhouse, it has advantage of low cost..low power and wider coverage. Additionally it complies with IEEE802.15.4 protocol, which makes it convenient to communicate with other products that comply with the protocol too

Research on continuous environmental radiation monitoring system for NPP based on wireless sensor network

International Nuclear Information System (INIS)

Fu Hailong; Jia Mingchun; Peng Guichu

2010-01-01

According to the characteristics of environmental gamma radiation monitoring and the requirement of nuclear power plant (NPP) developing, a new continuous environmental radiation monitoring system based on wireless sensor network (WSN) was presented. The basic concepts and application of WSN were introduced firstly. And then the characteristics of the new system were analyzed. At the same time the configuration of the WSN and the whole structure of the system were built. Finally, the crucial techniques used in system designing, such as the design of sensor node, the choice of communication mode and protocol, the time synchronization and space location, the security of the network and the faults tolerance were introduced. (authors)

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

Directory of Open Access Journals (Sweden)

Dengying Jiang

Full Text Available 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.

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.

Power Terminal Communication Access Network Monitoring System Scheme Based on Design Patterns

Science.gov (United States)

Yan, Shengchao; Wu, Desheng; Zhu, Jiang

2018-01-01

In order to realize patterns design for terminal communication monitoring system, this paper introduces manager-workers, tasks-workers design patterns, based on common design patterns such as factory method, chain of responsibility, facade. Using these patterns, the communication monitoring system which combines module-groups like networking communication, business data processing and the peripheral support has been designed successfully. Using these patterns makes this system have great flexibility and scalability and improves the degree of systematic pattern design structure.

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

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......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...

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.

Deep convolutional neural network based antenna selection in multiple-input multiple-output system

Science.gov (United States)

Cai, Jiaxin; Li, Yan; Hu, Ying

2018-03-01

Antenna selection of wireless communication system has attracted increasing attention due to the challenge of keeping a balance between communication performance and computational complexity in large-scale Multiple-Input MultipleOutput antenna systems. Recently, deep learning based methods have achieved promising performance for large-scale data processing and analysis in many application fields. This paper is the first attempt to introduce the deep learning technique into the field of Multiple-Input Multiple-Output antenna selection in wireless communications. First, the label of attenuation coefficients channel matrix is generated by minimizing the key performance indicator of training antenna systems. Then, a deep convolutional neural network that explicitly exploits the massive latent cues of attenuation coefficients is learned on the training antenna systems. Finally, we use the adopted deep convolutional neural network to classify the channel matrix labels of test antennas and select the optimal antenna subset. Simulation experimental results demonstrate that our method can achieve better performance than the state-of-the-art baselines for data-driven based wireless antenna selection.

Web of Things-Based Remote Monitoring System for Coal Mine Safety Using Wireless Sensor Network

OpenAIRE

Bo, Cheng; Xin, Cheng; Zhongyi, Zhai; Chengwen, Zhang; Junliang, Chen

2014-01-01

Frequent accidents have occurred in coal mine enterprises; therefore, raising the technological level of coal mine safety monitoring systems is an urgent problem. Wireless sensor networks (WSN), as a new field of research, have broad application prospects. This paper proposes a Web of Things- (WoT-) based remote monitoring system that takes full advantage of wireless sensor networks in combination with the CAN bus communication technique that abstracts the underground sensor data and capabili...

A novel prosodic-information synthesizer based on recurrent fuzzy neural network for the Chinese TTS system.

Science.gov (United States)

Lin, Chin-Teng; Wu, Rui-Cheng; Chang, Jyh-Yeong; Liang, Sheng-Fu

2004-02-01

In this paper, a new technique for the Chinese text-to-speech (TTS) system is proposed. Our major effort focuses on the prosodic information generation. New methodologies for constructing fuzzy rules in a prosodic model simulating human's pronouncing rules are developed. The proposed Recurrent Fuzzy Neural Network (RFNN) is a multilayer recurrent neural network (RNN) which integrates a Self-cOnstructing Neural Fuzzy Inference Network (SONFIN) into a recurrent connectionist structure. The RFNN can be functionally divided into two parts. The first part adopts the SONFIN as a prosodic model to explore the relationship between high-level linguistic features and prosodic information based on fuzzy inference rules. As compared to conventional neural networks, the SONFIN can always construct itself with an economic network size in high learning speed. The second part employs a five-layer network to generate all prosodic parameters by directly using the prosodic fuzzy rules inferred from the first part as well as other important features of syllables. The TTS system combined with the proposed method can behave not only sandhi rules but also the other prosodic phenomena existing in the traditional TTS systems. Moreover, the proposed scheme can even find out some new rules about prosodic phrase structure. The performance of the proposed RFNN-based prosodic model is verified by imbedding it into a Chinese TTS system with a Chinese monosyllable database based on the time-domain pitch synchronous overlap add (TD-PSOLA) method. Our experimental results show that the proposed RFNN can generate proper prosodic parameters including pitch means, pitch shapes, maximum energy levels, syllable duration, and pause duration. Some synthetic sounds are online available for demonstration.

Study on key technologies of vehicle networking system platform for electric automobiles based on micro-service

Science.gov (United States)

Ye, Fei

2018-04-01

With the rapid increase of electric automobiles and charging piles, the elastic expansion and online rapid upgrade were required for the vehicle networking system platform (system platform for short). At present, it is difficult to meet the operation needs due to the traditional huge rock architecture used by the system platform. This paper studied the system platform technology architecture based on "cloud platform +micro-service" to obtain a new generation of vehicle networking system platform with the combination of elastic expansion and application, thus significantly improving the service operation ability of system.

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.

Cloud-based Networked Visual Servo Control

OpenAIRE

Wu, Haiyan; Lu, Lei; Chen, Chih-Chung; Hirche, Sandra; Kühnlenz, Kolja

2013-01-01

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 transmitti...

Resilient Disaster Network Based on Software Defined Cognitive Wireless Network Technology

Directory of Open Access Journals (Sweden)

Goshi Sato

2015-01-01

Full Text Available In order to temporally recover the information network infrastructure in disaster areas from the Great East Japan Earthquake in 2011, various wireless network technologies such as satellite IP network, 3G, and Wi-Fi were effectively used. However, since those wireless networks are individually introduced and installed but not totally integrated, some of networks were congested due to the sudden network traffic generation and unbalanced traffic distribution, and eventually the total network could not effectively function. In this paper, we propose a disaster resilient network which integrates various wireless networks into a cognitive wireless network that users can use as an access network to the Internet at the serious disaster occurrence. We designed and developed the disaster resilient network based on software defined network (SDN technology to automatically select the best network link and route among the possible access networks to the Internet by periodically monitoring their network states and evaluate those using extended AHP method. In order to verify the usefulness of our proposed system, a prototype system is constructed and its performance is evaluated.

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.

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.

A network-based system of simulation, control and online assistance for HTR-10

Energy Technology Data Exchange (ETDEWEB)

Zhu Shutang [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China)], E-mail: zhust@tsinghua.edu.cn; Luo Shaojie; Shi Lei [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China)

2008-07-15

A network-based computer system has been developed for HTR-10. This system integrates three subsystems: the simulation subsystem (SIMUSUB), the visualized control designed subsystem (VCDSUB) and the online assistance subsystem (OASUB). The SIMUSUB consists of four functional elements: the simulation calculating server (SCS), the main control client (MCC), the data disposal client (DDC) and the results graphic display client (RGDC), all of which can communicate with each other via network. It is intended to analyze and calculate physical processes of the reactor core, the main loop system and the steam generator, etc., as well as to simulate the normal operational and transient accidents. The result data can be dynamically displayed through the RGDC. The VCDSUB provides a platform for control system modeling where the control flow systems can be automatically generated and graphically simulated. Based on the data from the field bus, the OASUB provides some of the reactor core parameters, which are difficult to measure. This integrated system can be used as an educational tool to understand the design and operational characteristics of the HTR-10, and can also provide online support for operators in the main control room, or as a convenient powerful tool for the control system design.

A network-based system of simulation, control and online assistance for HTR-10

International Nuclear Information System (INIS)

Zhu Shutang; Luo Shaojie; Shi Lei

2008-01-01

A network-based computer system has been developed for HTR-10. This system integrates three subsystems: the simulation subsystem (SIMUSUB), the visualized control designed subsystem (VCDSUB) and the online assistance subsystem (OASUB). The SIMUSUB consists of four functional elements: the simulation calculating server (SCS), the main control client (MCC), the data disposal client (DDC) and the results graphic display client (RGDC), all of which can communicate with each other via network. It is intended to analyze and calculate physical processes of the reactor core, the main loop system and the steam generator, etc., as well as to simulate the normal operational and transient accidents. The result data can be dynamically displayed through the RGDC. The VCDSUB provides a platform for control system modeling where the control flow systems can be automatically generated and graphically simulated. Based on the data from the field bus, the OASUB provides some of the reactor core parameters, which are difficult to measure. This integrated system can be used as an educational tool to understand the design and operational characteristics of the HTR-10, and can also provide online support for operators in the main control room, or as a convenient powerful tool for the control system design

Passivity-based control and estimation in networked robotics

CERN Document Server

Hatanaka, Takeshi; Fujita, Masayuki; Spong, Mark W

2015-01-01

Highlighting the control of networked robotic systems, this book synthesizes a unified passivity-based approach to an emerging cross-disciplinary subject. Thanks to this unified approach, readers can access various state-of-the-art research fields by studying only the background foundations associated with passivity. In addition to the theoretical results and techniques,  the authors provide experimental case studies on testbeds of robotic systems  including networked haptic devices, visual robotic systems,  robotic network systems and visual sensor network systems. The text begins with an introduction to passivity and passivity-based control together with the other foundations needed in this book. The main body of the book consists of three parts. The first examines how passivity can be utilized for bilateral teleoperation and demonstrates the inherent robustness of the passivity-based controller against communication delays. The second part emphasizes passivity’s usefulness for visual feedback control ...

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.

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.

Real-time object tracking system based on field-programmable gate array and convolution neural network

Directory of Open Access Journals (Sweden)

Congyi Lyu

2016-12-01

Full Text Available Vision-based object tracking has lots of applications in robotics, like surveillance, navigation, motion capturing, and so on. However, the existing object tracking systems still suffer from the challenging problem of high computation consumption in the image processing algorithms. The problem can prevent current systems from being used in many robotic applications which have limitations of payload and power, for example, micro air vehicles. In these applications, the central processing unit- or graphics processing unit-based computers are not good choices due to the high weight and power consumption. To address the problem, this article proposed a real-time object tracking system based on field-programmable gate array, convolution neural network, and visual servo technology. The time-consuming image processing algorithms, such as distortion correction, color space convertor, and Sobel edge, Harris corner features detector, and convolution neural network were redesigned using the programmable gates in field-programmable gate array. Based on the field-programmable gate array-based image processing, an image-based visual servo controller was designed to drive a two degree of freedom manipulator to track the target in real time. Finally, experiments on the proposed system were performed to illustrate the effectiveness of the real-time object tracking system.

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.

Elements of Network-Based Assessment

Science.gov (United States)

Gibson, David

2007-01-01

Elements of network-based assessment systems are envisioned based on recent advances in knowledge and practice in learning theory, assessment design and delivery, and semantic web interoperability. The architecture takes advantage of the meditating role of technology as well as recent models of assessment systems. This overview of the elements…

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...

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

All-optical virtual private network and ONUs communication in optical OFDM-based PON system.

Science.gov (United States)

Zhang, Chongfu; Huang, Jian; Chen, Chen; Qiu, Kun

2011-11-21

We propose and demonstrate a novel scheme, which enables all-optical virtual private network (VPN) and all-optical optical network units (ONUs) inter-communications in optical orthogonal frequency-division multiplexing-based passive optical network (OFDM-PON) system using the subcarrier bands allocation for the first time (to our knowledge). We consider the intra-VPN and inter-VPN communications which correspond to two different cases: VPN communication among ONUs in one group and in different groups. The proposed scheme can provide the enhanced security and a more flexible configuration for VPN users compared to the VPN in WDM-PON or TDM-PON systems. The all-optical VPN and inter-ONU communications at 10-Gbit/s with 16 quadrature amplitude modulation (16 QAM) for the proposed optical OFDM-PON system are demonstrated. These results verify that the proposed scheme is feasible. © 2011 Optical Society of America

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.

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

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.

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.

A Priority-aware Frequency Domain Polling MAC Protocol for OFDMA-based Networks in Cyber-physical Systems

Institute of Scientific and Technical Information of China (English)

Meng Zheng; Junru Lin; Wei Liang; Haibin Yu

2015-01-01

Wireless networking in cyber-physical systems(CPSs) is characteristically different from traditional wireless systems due to the harsh radio frequency environment and applications that impose high real-time and reliability constraints.One of the fundamental considerations for enabling CPS networks is the medium access control protocol. To this end, this paper proposes a novel priority-aware frequency domain polling medium access control(MAC) protocol, which takes advantage of an orthogonal frequency-division multiple access(OFDMA)physical layer to achieve instantaneous priority-aware polling.Based on the polling result, the proposed work then optimizes the resource allocation of the OFDMA network to further improve the data reliability. Due to the non-polynomial-complete nature of the OFDMA resource allocation, we propose two heuristic rules,based on which an efficient solution algorithm to the OFDMA resource allocation problem is designed. Simulation results show that the reliability performance of CPS networks is significantly improved because of this work.

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.

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. 

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. 

A gossip-based distributed social networking system

NARCIS (Netherlands)

Abbas, S.M.A.; Pouwelse, J.A.; Epema, D.H.J.; Sips, H.J.

2009-01-01

Social networking Web sites, which allow users to create identities and link them to friends who have also created identities, are highly popular. Systems such as Facebook and MySpace utilize a traditional client-server approach to achieve this, which means that all identities and their social links

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.

WiSPH: a wireless sensor network-based home care monitoring system.

Science.gov (United States)

Magaña-Espinoza, Pedro; Aquino-Santos, Raúl; Cárdenas-Benítez, Néstor; Aguilar-Velasco, José; Buenrostro-Segura, César; Edwards-Block, Arthur; Medina-Cass, Aldo

2014-04-22

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.

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.

Multi-agent system based active distribution networks

OpenAIRE

Nguyen, H.P.

2010-01-01

This thesis gives a particular vision of the future power delivery system with its main requirements. An investigation of suitable concepts and technologies which creates a road map forward the smart grid has been carried out. They should meet the requirements on sustainability, efficiency, flexibility and intelligence. The so called Active Distribution Network (ADN) is introduced as an important element of the future power delivery system. With an open architecture, the ADN is designed to in...

An FPGA bridge preserving traffing quality of service for on-chip network-based systems

NARCIS (Netherlands)

Nejad, A.B.; Escudero Martinez, M.; Goossens, K.G.W.

2011-01-01

FPGA prototyping of recent large Systems on Chip (SoCs) is very challenging due to the resource limitation of a single FPGA. Moreover, having external access to SoCs for verification and debug purposes is essential. In this paper, we suggest to partition a network-on-chip (NoC) based system into

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.

POINT-CLOUD COMPRESSION FOR VEHICLE-BASED MOBILE MAPPING SYSTEMS USING PORTABLE NETWORK GRAPHICS

Directory of Open Access Journals (Sweden)

K. Kohira

2017-09-01

Full Text Available 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.

Implementation of body area networks based on MICS/WMTS medical bands for healthcare systems.

Science.gov (United States)

Yuce, Mehmet R; Ho, Chee Keong

2008-01-01

A multi-hoping sensor network system has been implemented to monitor physiological parameters from multiple patient bodies by means of medical communication standards MICS (Medical Implant Communication Service) and WMTS (Wireless Medical Telemetry Service). Unlike the other medical sensor networks (they usually use 2.4 GHz ISM band), we used the two medical standards occupying the frequency bands that are mainly assigned to medical applications. The prototype system uses the MICS band (402-405 MHz) between the sensor nodes and a remote central control unit (CCU). And WMTS frequencies (608-614MHz) are used between the CCUs and the remote base stations allowing for a much larger range acting as an intermediate node. The sensor nodes in the prototype can measure up to four body signals (i.e. 4-channel) where one is dedicated to a continuous physiological signal such as ECC/EEG. The system includes firmware and software designs that can provide a long distance data transfer through the internet or a mobile network.

Matrix-based system reliability method and applications to bridge networks

International Nuclear Information System (INIS)

Kang, W.-H.; Song Junho; Gardoni, Paolo

2008-01-01

Using a matrix-based system reliability (MSR) method, one can estimate the probabilities of complex system events by simple matrix calculations. Unlike existing system reliability methods whose complexity depends highly on that of the system event, the MSR method describes any general system event in a simple matrix form and therefore provides a more convenient way of handling the system event and estimating its probability. Even in the case where one has incomplete information on the component probabilities and/or the statistical dependence thereof, the matrix-based framework enables us to estimate the narrowest bounds on the system failure probability by linear programming. This paper presents the MSR method and applies it to a transportation network consisting of bridge structures. The seismic failure probabilities of bridges are estimated by use of the predictive fragility curves developed by a Bayesian methodology based on experimental data and existing deterministic models of the seismic capacity and demand. Using the MSR method, the probability of disconnection between each city/county and a critical facility is estimated. The probability mass function of the number of failed bridges is computed as well. In order to quantify the relative importance of bridges, the MSR method is used to compute the conditional probabilities of bridge failures given that there is at least one city disconnected from the critical facility. The bounds on the probability of disconnection are also obtained for cases with incomplete information

Neural Network for Optimization of Existing Control Systems

DEFF Research Database (Denmark)

Madsen, Per Printz

1995-01-01

The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems.......The purpose of this paper is to develop methods to use Neural Network based Controllers (NNC) as an optimization tool for existing control systems....

A Scalable Policy and SNMP Based Network Management Framework

Institute of Scientific and Technical Information of China (English)

LIU Su-ping; DING Yong-sheng

2009-01-01

Traditional SNMP-based network management can not deal with the task of managing large-scaled distributed network,while policy-based management is one of the effective solutions in network and distributed systems management. However,cross-vendor hardware compatibility is one of the limitations in policy-based management. Devices existing in current network mostly support SNMP rather than Common Open Policy Service (COPS) protocol. By analyzing traditional network management and policy-based network management, a scalable network management framework is proposed. It is combined with Internet Engineering Task Force (IETF) framework for policybased management and SNMP-based network management. By interpreting and translating policy decision to SNMP message,policy can be executed in traditional SNMP-based device.

Bio-inspired spiking neural network for nonlinear systems control.

Science.gov (United States)

Pérez, Javier; Cabrera, Juan A; Castillo, Juan J; Velasco, Juan M

2018-08-01

Spiking neural networks (SNN) are the third generation of artificial neural networks. SNN are the closest approximation to biological neural networks. SNNs make use of temporal spike trains to command inputs and outputs, allowing a faster and more complex computation. As demonstrated by biological organisms, they are a potentially good approach to designing controllers for highly nonlinear dynamic systems in which the performance of controllers developed by conventional techniques is not satisfactory or difficult to implement. SNN-based controllers exploit their ability for online learning and self-adaptation to evolve when transferred from simulations to the real world. SNN's inherent binary and temporary way of information codification facilitates their hardware implementation compared to analog neurons. Biological neural networks often require a lower number of neurons compared to other controllers based on artificial neural networks. In this work, these neuronal systems are imitated to perform the control of non-linear dynamic systems. For this purpose, a control structure based on spiking neural networks has been designed. Particular attention has been paid to optimizing the structure and size of the neural network. The proposed structure is able to control dynamic systems with a reduced number of neurons and connections. A supervised learning process using evolutionary algorithms has been carried out to perform controller training. The efficiency of the proposed network has been verified in two examples of dynamic systems control. Simulations show that the proposed control based on SNN exhibits superior performance compared to other approaches based on Neural Networks and SNNs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neural Network Based Maximum Power Point Tracking Control with Quadratic Boost Converter for PMSG—Wind Energy Conversion System

Directory of Open Access Journals (Sweden)

Ramji Tiwari

2018-02-01

Full Text Available This paper proposes an artificial neural network (ANN based maximum power point tracking (MPPT control strategy for wind energy conversion system (WECS implemented with a DC/DC converter. The proposed topology utilizes a radial basis function network (RBFN based neural network control strategy to extract the maximum available power from the wind velocity. The results are compared with a classical Perturb and Observe (P&O method and Back propagation network (BPN method. In order to achieve a high voltage rating, the system is implemented with a quadratic boost converter and the performance of the converter is validated with a boost and single ended primary inductance converter (SEPIC. The performance of the MPPT technique along with a DC/DC converter is demonstrated using MATLAB/Simulink.

Network-assisted crop systems genetics: network inference and integrative analysis.

Science.gov (United States)

Lee, Tak; Kim, Hyojin; Lee, Insuk

2015-04-01

Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years. Copyright © 2015 Elsevier Ltd. All rights reserved.

A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

Science.gov (United States)

Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-10-01

This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

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

In this paper, we study aspects of single microphone speech enhancement (SE) based on deep neural networks (DNNs). Specifically, we explore the generalizability capabilities of state-of-the-art DNN-based SE systems with respect to the background noise type, the gender of the target speaker...... general. Finally, we compare how a DNN-based SE system trained to be noise type general, speaker general, and SNR general performs relative to a state-of-the-art short-time spectral amplitude minimum mean square error (STSA-MMSE) based SE algorithm. We show that DNN-based SE systems, when trained...... a state-of-the-art STSA-MMSE based SE method, when tested using a range of unseen speakers and noise types. Finally, a listening test using several DNN-based SE systems tested in unseen speaker conditions show that these systems can improve SI for some SNR and noise type configurations but degrade SI...

Portable pulsed X-ray digital radiographic system based on network transmission

International Nuclear Information System (INIS)

Tang Le; Li Yuanjing; Wang Yi; Cheng Jianping

2004-01-01

Network communication technology of TCP/IP protocol serves as application in pulse X-ray digital radiography system. The system radiographs synchronously with pulse X-ray and converts image signals to digital data, which are transmitted to computer for displaying and processing in network. The system composing structures are present and portable and other characteristics are introduced. (authors)

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...... scale of DFIG system with different parameters; 3) L or LCL filter adopted in the Grid Side Converter (GSC); 4) rotor speed; 5) current closed-loop controller parameters and 6) digital control delay will be discussed in this paper. On the basis of the analysis, active damping strategies for HFR using...

Networks as systems.

Science.gov (United States)

Best, Allan; Berland, Alex; Greenhalgh, Trisha; Bourgeault, Ivy L; Saul, Jessie E; Barker, Brittany

2018-03-19

Purpose The purpose of this paper is to present a case study of the World Health Organization's Global Healthcare Workforce Alliance (GHWA). Based on a commissioned evaluation of GHWA, it applies network theory and key concepts from systems thinking to explore network emergence, effectiveness, and evolution to over a ten-year period. The research was designed to provide high-level strategic guidance for further evolution of global governance in human resources for health (HRH). Design/methodology/approach Methods included a review of published literature on HRH governance and current practice in the field and an in-depth case study whose main data sources were relevant GHWA background documents and key informant interviews with GHWA leaders, staff, and stakeholders. Sampling was purposive and at a senior level, focusing on board members, executive directors, funders, and academics. Data were analyzed thematically with reference to systems theory and Shiffman's theory of network development. Findings Five key lessons emerged: effective management and leadership are critical; networks need to balance "tight" and "loose" approaches to their structure and processes; an active communication strategy is key to create and maintain support; the goals, priorities, and membership must be carefully focused; and the network needs to support shared measurement of progress on agreed-upon goals. Shiffman's middle-range network theory is a useful tool when guided by the principles of complex systems that illuminate dynamic situations and shifting interests as global alliances evolve. Research limitations/implications This study was implemented at the end of the ten-year funding cycle. A more continuous evaluation throughout the term would have provided richer understanding of issues. Experience and perspectives at the country level were not assessed. Practical implications Design and management of large, complex networks requires ongoing attention to key issues like leadership

Leo satellite-based telecommunication network concepts

Science.gov (United States)

Aiken, John G.; Swan, Peter A.; Leopold, Ray J.

1991-01-01

Design considerations are discussed for Low Earth Orbit (LEO) satellite based telecommunications networks. The satellites are assumed to be connected to each other via intersatellite links. They are connected to the end user either directly or through gateways to other networks. Frequency reuse, circuit switching, packet switching, call handoff, and routing for these systems are discussed by analogy with terrestrial cellular (mobile radio) telecommunication systems.

Novel Modified Elman Neural Network Control for PMSG System Based on Wind Turbine Emulator

OpenAIRE

Lin, Chih-Hong

2013-01-01

The novel modified Elman neural network (NN) controlled permanent magnet synchronous generator (PMSG) system, which is directly driven by a permanent magnet synchronous motor (PMSM) based on wind turbine emulator, is proposed to control output of rectifier (AC/DC power converter) and inverter (DC/AC power converter) in this study. First, a closed loop PMSM drive control based on wind turbine emulator is designed to generate power for the PMSG system according to different wind speeds. Then, t...

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

Modeling of a 5-cell direct methanol fuel cell using adaptive-network-based fuzzy inference systems

Science.gov (United States)

Wang, Rongrong; Qi, Liang; Xie, Xiaofeng; Ding, Qingqing; Li, Chunwen; Ma, ChenChi M.

The methanol concentrations, temperature and current were considered as inputs, the cell voltage was taken as output, and the performance of a direct methanol fuel cell (DMFC) was modeled by adaptive-network-based fuzzy inference systems (ANFIS). The artificial neural network (ANN) and polynomial-based models were selected to be compared with the ANFIS in respect of quality and accuracy. Based on the ANFIS model obtained, the characteristics of the DMFC were studied. The results show that temperature and methanol concentration greatly affect the performance of the DMFC. Within a restricted current range, the methanol concentration does not greatly affect the stack voltage. In order to obtain higher fuel utilization efficiency, the methanol concentrations and temperatures should be adjusted according to the load on the system.

Modeling of a 5-cell direct methanol fuel cell using adaptive-network-based fuzzy inference systems

Energy Technology Data Exchange (ETDEWEB)

Wang, Rongrong; Li, Chunwen [Department of Automation, Tsinghua University, Beijing 100084 (China); Qi, Liang; Xie, Xiaofeng [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China); Ding, Qingqing [Department of Electrical Engineering, Tsinghua University, Beijing 100084 (China); Ma, ChenChi M. [National Tsing Hua University, Hsinchu 300 (China)

2008-12-01

The methanol concentrations, temperature and current were considered as inputs, the cell voltage was taken as output, and the performance of a direct methanol fuel cell (DMFC) was modeled by adaptive-network-based fuzzy inference systems (ANFIS). The artificial neural network (ANN) and polynomial-based models were selected to be compared with the ANFIS in respect of quality and accuracy. Based on the ANFIS model obtained, the characteristics of the DMFC were studied. The results show that temperature and methanol concentration greatly affect the performance of the DMFC. Within a restricted current range, the methanol concentration does not greatly affect the stack voltage. In order to obtain higher fuel utilization efficiency, the methanol concentrations and temperatures should be adjusted according to the load on the system. (author)

Design and development of the network based system for the supervision of radioactive sources

International Nuclear Information System (INIS)

Yang Yaoyun; Su Genghua; Zhang Hui; Li Junli; Zhu Li

2010-01-01

Objective: To help the environmental protection authorities to upgrade the management of the related organizations and radioactive sources and improve the information level of nuclear technology utilization's supervision. Methods: On the basis of investigation of requirements, the network based system for the supervision of radioactive sources was divided into application system and supervision system, based on MYSQL and SQL Server2005 respectively. Results: The system satisfied the current requirements of the nuclear technology utilization's supervision and is in nationwide operation. Conclusion: The system achieved the dynamic tracking management of radioactive sources and improved the efficiency and level of radiation safety supervision in nuclear technology utilizations. (authors)

Optical network and FPGA/DSP based control system for free electron laser

International Nuclear Information System (INIS)

Romaniuk, R.S.; Pozniak, K.T.; Czarski, T.; Czuba, K.; Giergusiewicz, W.; Kasprowicz, G.; Koprek, W.

2005-01-01

The work presents a structural and functional model of a distributed low level radio frequency (LLRF) control, diagnostic and telemetric system for a large industrial object. An example of system implementation is the European TESLA-XFEL accelerator. The free electron laser is expected to work in the VUV region now and in the range of X-rays in the future. The design of a system based on the FPGA circuits and multi-gigabit optical network is discussed. The system design approach is fully parametric. The major emphasis is put on the methods of the functional and hardware concentration to use fully both: a very big transmission capacity of the optical fiber telemetric channels and very big processing power of the latest series of DSP/PC enhanced and optical I/O equipped, FPGA chips. The subject of the work is the design of a universal, laboratory module of the LLRF sub-system. The current parameters of the system model, under the design, are presented. The considerations are shown on the background of the system application in the hostile industrial environment. The work is a digest of a few development threads of the hybrid, optoelectronic, telemetric networks (HOTN). In particular, the outline of construction theory of HOTN node was presented as well as the technology of complex, modular, multilayer HOTN system PCBs. The PCBs contain critical sub-systems of the node and the network. The presented exemplary sub-systems are: fast optical data transmission of 2.5 Gbit/s, 3.125 Gbit/s and 10 Gbit/s; fast A/C and C/A multichannel data conversion managed by FPGA chip (40 MHz, 65 MHz, 105 MHz), data and functionality concentration, integration of floating point calculations in the DSP units of FPGA circuit, using now discrete and next integrated PC chip with embedded OS; optical distributed timing system of phase reference; and 1GbEth video interface (over UTP or FX) for CCD telemetry and monitoring. The data and functions concentration in the HOTN node is necessary to

New Smith Internal Model Control of Two-Motor Drive System Based on Neural Network Generalized Inverse

Directory of Open Access Journals (Sweden)

Guohai Liu

2016-01-01

Full Text Available Multimotor drive system is widely applied in industrial control system. Considering the characteristics of multi-input multioutput, nonlinear, strong-coupling, and time-varying delay in two-motor drive systems, this paper proposes a new Smith internal model (SIM control method, which is based on neural network generalized inverse (NNGI. This control strategy adopts the NNGI system to settle the decoupling issue and utilizes the SIM control structure to solve the delay problem. The NNGI method can decouple the original system into several composite pseudolinear subsystems and also complete the pole-zero allocation of subsystems. Furthermore, based on the precise model of pseudolinear system, the proposed SIM control structure is used to compensate the network delay and enhance the interference resisting the ability of the whole system. Both simulation and experimental results are given, verifying that the proposed control strategy can effectively solve the decoupling problem and exhibits the strong robustness to load impact disturbance at various operations.

Reconstruction of biological networks based on life science data integration.

Science.gov (United States)

Kormeier, Benjamin; Hippe, Klaus; Arrigo, Patrizio; Töpel, Thoralf; Janowski, Sebastian; Hofestädt, Ralf

2010-10-27

For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH--an integration toolkit for building life science data warehouses, CardioVINEdb--a information system for biological data in cardiovascular-disease and VANESA--a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

Scaling architecture-on-demand based optical networks

NARCIS (Netherlands)

Meyer, Hugo; Sancho, Jose Carlos; Mrdakovic, Milica; Peng, Shuping; Simeonidou, Dimitra; Miao, Wang; Calabretta, Nicola

2016-01-01

This paper analyzes methodologies that allow scaling properly Architecture-On-Demand (AoD) based optical networks. As Data Centers and HPC systems are growing in size and complexity, optical networks seem to be the way to scale the bandwidth of current network infrastructures. To scale the number of

Implementation of neural network based non-linear predictive

DEFF Research Database (Denmark)

Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

1998-01-01

The paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems including open loop unstable and non-minimum phase systems, but has also been proposed extended for the control of non......-linear systems. GPC is model-based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis on an efficient Quasi......-Newton optimization algorithm. The performance is demonstrated on a pneumatic servo system....

Neural Network Based Load Frequency Control for Restructuring ...

African Journals Online (AJOL)

Neural Network Based Load Frequency Control for Restructuring Power Industry. ... an artificial neural network (ANN) application of load frequency control (LFC) of a Multi-Area power system by using a neural network controller is presented.

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.

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.

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

Enhancing Network Data Obliviousness in Trusted Execution Environment-based Stream Processing Systems

KAUST Repository

Alsibyani, Hassan M.

2018-05-15

Cloud computing usage is increasing and a common concern is the privacy and security of the data and computation. Third party cloud environments are not considered fit for processing private information because the data will be revealed to the cloud provider. However, Trusted Execution Environments (TEEs), such as Intel SGX, provide a way for applications to run privately and securely on untrusted platforms. Nonetheless, using a TEE by itself for stream processing systems is not sufficient since network communication patterns may leak properties of the data under processing. This work addresses leaky topology structures and suggests mitigation techniques for each of these. We create specific metrics to evaluate leaks occurring from the network patterns; the metrics measure information leaked when the stream processing system is running. We consider routing techniques for inter-stage communication in a streaming application to mitigate this data leakage. We consider a dynamic policy to change the mitigation technique depending on how much information is currently leaking. Additionally, we consider techniques to hide irregularities resulting from a filtering stage in a topology. We also consider leakages resulting from applications containing cycles. For each of the techniques, we explore their effectiveness in terms of the advantage they provide in overcoming the network leakage. The techniques are tested partly using simulations and some were implemented in a prototype SGX-based stream processing system.

A fully automated entanglement-based quantum cryptography system for telecom fiber networks

International Nuclear Information System (INIS)

Treiber, Alexander; Ferrini, Daniele; Huebel, Hannes; Zeilinger, Anton; Poppe, Andreas; Loruenser, Thomas; Querasser, Edwin; Matyus, Thomas; Hentschel, Michael

2009-01-01

We present in this paper a quantum key distribution (QKD) system based on polarization entanglement for use in telecom fibers. A QKD exchange up to 50 km was demonstrated in the laboratory with a secure key rate of 550 bits s -1 . The system is compact and portable with a fully automated start-up, and stabilization modules for polarization, synchronization and photon coupling allow hands-off operation. Stable and reliable key exchange in a deployed optical fiber of 16 km length was demonstrated. In this fiber network, we achieved over 2 weeks an automatic key generation with an average key rate of 2000 bits s -1 without manual intervention. During this period, the system had an average entanglement visibility of 93%, highlighting the technical level and stability achieved for entanglement-based quantum cryptography.

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.

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.

A pervasive health monitoring service system based on ubiquitous network technology.

Science.gov (United States)

Lin, Chung-Chih; Lee, Ren-Guey; Hsiao, Chun-Chieh

2008-07-01

The phenomenon of aging society has derived problems such as shortage of medical resources and reduction of quality in healthcare services. This paper presents a system infrastructure for pervasive and long-term healthcare applications, i.e. a ubiquitous network composed of wireless local area network (WLAN) and cable television (CATV) network serving as a platform for monitoring physiological signals. Users can record vital signs including heart rate, blood pressure, and body temperature anytime either at home or at frequently visited public places in order to create a personal health file. The whole system was formally implemented in December 2004. Analysis of 2000 questionnaires indicates that 85% of users were satisfied with the provided community-wide healthcare services. Among the services provided by our system, health consultation services offered by family doctors was rated the most important service by 17.9% of respondents, and was followed by control of one's own health condition (16.4% of respondents). Convenience of data access was rated most important by roughly 14.3% of respondents. We proposed and implemented a long-term healthcare system integrating WLAN and CATV networks in the form of a ubiquitous network providing a service platform for physiological monitoring. This system can classify the health levels of the resident according to the variation tendency of his or her physiological signal for important reference of health management.

Novel flat datacenter network architecture based on scalable and flow-controlled optical switch system

NARCIS (Netherlands)

Miao, W.; Luo, J.; Di Lucente, S.; Dorren, H.J.S.; Calabretta, N.

2013-01-01

We propose and demonstrate an optical flat datacenter network based on scalable optical switch system with optical flow control. 4×4 dynamic switch operation at 40 Gb/s reported 300ns minimum end-to-end latency (including 25m transmission link) and

An Improved Car-Following Model in Vehicle Networking Based on Network Control

Directory of Open Access Journals (Sweden)

D. Y. Kong

2014-01-01

Full Text Available Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS. In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.

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.

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.

Advanced model for expansion of natural gas distribution networks based on geographic information systems

Energy Technology Data Exchange (ETDEWEB)

Ramirez-Rosado, I.J.; Fernandez-Jimenez, L.A.; Garcia-Garrido, E.; Zorzano-Santamaria, P.; Zorzano-Alba, E. [La Rioja Univ., La Rioja (Spain). Dept. of Electrical Engineering; Miranda, V.; Montneiro, C. [Porto Univ., Porto (Portugal). Faculty of Engineering]|[Inst. de Engenharia de Sistemas e Computadores do Porto, Porto (Portugal)

2005-07-01

An advanced geographic information system (GIS) model of natural gas distribution networks was presented. The raster-based model was developed to evaluate costs associated with the expansion of electrical networks due to increased demand in the La Rioja region of Spain. The model was also used to evaluate costs associated with maintenance and amortization of the already existing distribution network. Expansion costs of the distribution network were modelled in various demand scenarios. The model also considered a variety of technical factors associated with pipeline length and topography. Soil and slope data from previous pipeline projects were used to estimate real costs per unit length of pipeline. It was concluded that results obtained by the model will be used by planners to select zones where expansion is economically feasible. 4 refs., 5 figs.

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.

Delay Tolerant Networking with Data Triage Method based on Emergent User Policies for Disaster Information Network System

Directory of Open Access Journals (Sweden)

Noriki Uchida

2014-01-01

Full Text Available When Disaster Information Network System is considered in local areas that were heavy damaged by the East Japan Great Earthquake in 2011, the resiliency of the network system is one of significant subjects for the restoration of the areas. DTN (Delay Tolerant Network has been focused for the effective methods for such inoperable network circumstances. However, when DTN is applied for the local areas, there are some problems such as message delivery rate and latency because there are fewer roads, cars, and pedestrians than in urban areas. In this paper, we propose the Enhanced Media Coordinate System for its architecture, and Data Triage method by emergent user policies is introduced to improve the QoS in Disaster Information Network System in local areas. In the proposed method, every message is tagged with the priority levels by data types with considering emergent user policies, and the high priority messages are firstly duplicated to transmittable nodes. Then, the experimental results by the GIS map of a Japanese coastal town and the future studies are discussed.

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.

Evaluation of a “Smart” Pedestrian Counting System Based on Echo State Networks

Directory of Open Access Journals (Sweden)

2009-03-01

Full Text Available 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.

Research on Electronic-nose Application Based on Wireless Sensor Networks

International Nuclear Information System (INIS)

Zhao, A; Wang, L; Yao, C H

2006-01-01

The paper proposed a structure of Wireless Sensor Networks based Electronic-nose system to monitors air quality in the building. In the study, the authors researched a data processing algorithm: fuzzy neural network based on RBF(Radial Basis Function) network model, to quantitatively analyze the gas ingredient and put forward a routing protocol for the system

Reconstruction of biological networks based on life science data integration

Directory of Open Access Journals (Sweden)

Kormeier Benjamin

2010-06-01

Full Text Available For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH - an integration toolkit for building life science data warehouses, CardioVINEdb - a information system for biological data in cardiovascular-disease and VANESA- a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

A Red-Light Running Prevention System Based on Artificial Neural Network and Vehicle Trajectory Data

Directory of Open Access Journals (Sweden)

Pengfei Li

2014-01-01

Full Text Available The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems.

A red-light running prevention system based on artificial neural network and vehicle trajectory data.

Science.gov (United States)

Li, Pengfei; Li, Yan; Guo, Xiucheng

2014-01-01

The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems.

A Red-Light Running Prevention System Based on Artificial Neural Network and Vehicle Trajectory Data

Science.gov (United States)

Li, Pengfei; Li, Yan; Guo, Xiucheng

2014-01-01

The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems. PMID:25435870

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

NM-Net Gigabit-based Implementation on Core Network Facilities and Network Design Hierarchy

International Nuclear Information System (INIS)

Raja Murzaferi Raja Moktar; Mohd Fauzi Haris; Siti Nurbahyah Hamdan

2011-01-01

Nuclear Malaysia computing network or NM the main backbone of internet working on operational staffs. Main network operating center or NOC is situated in Block 15 and linkup via fiber cabling to adjacent main network blocks (18, 29, 11 connections. Pre 2009 infrastructure; together to form the core networking switch. of the core network infrastructure were limited by the up link between core switches that is the Pair (UTP) Category 6 Cable. Furthermore, majority of the networking infrastructure throughout the agency were mainly built with Fast Ethernet Based specifications to date. With current research and operational tasks highly dependent on IT infrastructure that is being enabled through NM-Net, the performance NM-Net implementing gigabit-based networking system achieve optimal performance of internet networking services in the agency thus catalyze initiative. (author)

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.

Neural network-based expert system for severe accident management

International Nuclear Information System (INIS)

Klopp, G.T.; Silverman, E.B.

1992-01-01

This paper presents the results of the second phase of a three-phase Severe Accident Management expert system program underway at Commonwealth Edison Company (CECo). Phase I successfully demonstrated the feasibility of Artificial Neural Networks to support several of the objectives of severe accident management. Simulated accident scenarios were generated by the Modular Accident Analysis Program (MAAP) code currently in use by CECo as part of their Individual Plant Evaluations (IPE)/Accident Management Program. The primary objectives of the second phase were to develop and demonstrate four capabilities of neural networks with respect to nuclear power plant severe accident monitoring and prediction. The results of this work would form the foundation of a demonstration system which included expert system performance features. These capabilities included the ability to: (1) Predict the time available prior to support plate (and reactor vessel) failure; (2) Calculate the time remaining until recovery actions were too late to prevent core damage; (3) Predict future parameter values of each of the MAAP parameter variables; and (4) Detect simulated sensor failure and provide best-value estimates for further processing in the presence of a sensor failure. A variety of accident scenarios for the Zion and Dresden plants were used to train and test the neural network expert system. These included large and small break LOCAs as well as a range of transient events. 3 refs., 1 fig., 1 tab

Logic-based models in systems biology: a predictive and parameter-free network analysis method†

Science.gov (United States)

Wynn, Michelle L.; Consul, Nikita; Merajver, Sofia D.

2012-01-01

Highly complex molecular networks, which play fundamental roles in almost all cellular processes, are known to be dysregulated in a number of diseases, most notably in cancer. As a consequence, there is a critical need to develop practical methodologies for constructing and analysing molecular networks at a systems level. Mathematical models built with continuous differential equations are an ideal methodology because they can provide a detailed picture of a network’s dynamics. To be predictive, however, differential equation models require that numerous parameters be known a priori and this information is almost never available. An alternative dynamical approach is the use of discrete logic-based models that can provide a good approximation of the qualitative behaviour of a biochemical system without the burden of a large parameter space. Despite their advantages, there remains significant resistance to the use of logic-based models in biology. Here, we address some common concerns and provide a brief tutorial on the use of logic-based models, which we motivate with biological examples. PMID:23072820

Forecasting building energy consumption with hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system

Energy Technology Data Exchange (ETDEWEB)

Li, Kangji [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China); School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013 (China); Su, Hongye [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China)

2010-11-15

There are several ways to forecast building energy consumption, varying from simple regression to models based on physical principles. In this paper, a new method, namely, the hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system (GA-HANFIS) model is developed. In this model, hierarchical structure decreases the rule base dimension. Both clustering and rule base parameters are optimized by GAs and neural networks (NNs). The model is applied to predict a hotel's daily air conditioning consumption for a period over 3 months. The results obtained by the proposed model are presented and compared with regular method of NNs, which indicates that GA-HANFIS model possesses better performance than NNs in terms of their forecasting accuracy. (author)

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

Network design consideration of a satellite-based mobile communications system

Science.gov (United States)

Yan, T.-Y.

1986-01-01

Technical considerations for the Mobile Satellite Experiment (MSAT-X), the ground segment testbed for the low-cost spectral efficient satellite-based mobile communications technologies being developed for the 1990's, are discussed. The Network Management Center contains a flexible resource sharing algorithm, the Demand Assigned Multiple Access scheme, which partitions the satellite transponder bandwidth among voice, data, and request channels. Satellite use of multiple UHF beams permits frequency reuse. The backhaul communications and the Telemetry, Tracking and Control traffic are provided through a single full-coverage SHF beam. Mobile Terminals communicate with the satellite using UHF. All communications including SHF-SHF between Base Stations and/or Gateways, are routed through the satellite. Because MSAT-X is an experimental network, higher level network protocols (which are service-specific) will be developed only to test the operation of the lowest three levels, the physical, data link, and network layers.

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.

[The Development of Information Centralization and Management Integration System for Monitors Based on Wireless Sensor Network].

Science.gov (United States)

Xu, Xiu; Zhang, Honglei; Li, Yiming; Li, Bin

2015-07-01

Developed the information centralization and management integration system for monitors of different brands and models with wireless sensor network technologies such as wireless location and wireless communication, based on the existing wireless network. With adaptive implementation and low cost, the system which possesses the advantages of real-time, efficiency and elaboration is able to collect status and data of the monitors, locate the monitors, and provide services with web server, video server and locating server via local network. Using an intranet computer, the clinical and device management staffs can access the status and parameters of monitors. Applications of this system provide convenience and save human resource for clinical departments, as well as promote the efficiency, accuracy and elaboration for the device management. The successful achievement of this system provides solution for integrated and elaborated management of the mobile devices including ventilator and infusion pump.

Implementation of a FPGA-Based Feature Detection and Networking System for Real-time Traffic Monitoring

OpenAIRE

Chen, Jieshi; Schafer, Benjamin Carrion; Ho, Ivan Wang-Hei

2016-01-01

With the growing demand of real-time traffic monitoring nowadays, software-based image processing can hardly meet the real-time data processing requirement due to the serial data processing nature. In this paper, the implementation of a hardware-based feature detection and networking system prototype for real-time traffic monitoring as well as data transmission is presented. The hardware architecture of the proposed system is mainly composed of three parts: data collection, feature detection,...

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.

Output power distributions of mobile radio base stations based on network measurements

International Nuclear Information System (INIS)

Colombi, D; Thors, B; Persson, T; Törnevik, C; Wirén, N; Larsson, L-E

2013-01-01

In this work output power distributions of mobile radio base stations have been analyzed for 2G and 3G telecommunication systems. The approach is based on measurements in selected networks using performance surveillance tools part of the network Operational Support System (OSS). For the 3G network considered, direct measurements of output power levels were possible, while for the 2G networks, output power levels were estimated from measurements of traffic volumes. Both voice and data services were included in the investigation. Measurements were conducted for large geographical areas, to ensure good overall statistics, as well as for smaller areas to investigate the impact of different environments. For high traffic hours, the 90th percentile of the averaged output power was found to be below 65% and 45% of the available output power for the 2G and 3G systems, respectively.

Output power distributions of mobile radio base stations based on network measurements

Science.gov (United States)

Colombi, D.; Thors, B.; Persson, T.; Wirén, N.; Larsson, L.-E.; Törnevik, C.

2013-04-01

In this work output power distributions of mobile radio base stations have been analyzed for 2G and 3G telecommunication systems. The approach is based on measurements in selected networks using performance surveillance tools part of the network Operational Support System (OSS). For the 3G network considered, direct measurements of output power levels were possible, while for the 2G networks, output power levels were estimated from measurements of traffic volumes. Both voice and data services were included in the investigation. Measurements were conducted for large geographical areas, to ensure good overall statistics, as well as for smaller areas to investigate the impact of different environments. For high traffic hours, the 90th percentile of the averaged output power was found to be below 65% and 45% of the available output power for the 2G and 3G systems, respectively.

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.

Neural Network-Based Resistance Spot Welding Control and Quality Prediction

Energy Technology Data Exchange (ETDEWEB)

Allen, J.D., Jr.; Ivezic, N.D.; Zacharia, T.

1999-07-10

This paper describes the development and evaluation of neural network-based systems for industrial resistance spot welding process control and weld quality assessment. The developed systems utilize recurrent neural networks for process control and both recurrent networks and static networks for quality prediction. The first section describes a system capable of both welding process control and real-time weld quality assessment, The second describes the development and evaluation of a static neural network-based weld quality assessment system that relied on experimental design to limit the influence of environmental variability. Relevant data analysis methods are also discussed. The weld classifier resulting from the analysis successfldly balances predictive power and simplicity of interpretation. The results presented for both systems demonstrate clearly that neural networks can be employed to address two significant problems common to the resistance spot welding industry, control of the process itself, and non-destructive determination of resulting weld quality.

Wearable computing from modeling to implementation of wearable systems based on body sensor networks

CERN Document Server

Fortino, Giancarlo; Galzarano, Stefano

2018-01-01

This book provides the most up-to-date research and development on wearable computing, wireless body sensor networks, wearable systems integrated with mobile computing, wireless networking and cloud computing. This book has a specific focus on advanced methods for programming Body Sensor Networks (BSNs) based on the reference SPINE project. It features an on-line website (http://spine.deis.unical.it) to support readers in developing their own BSN application/systems and covers new emerging topics on BSNs such as collaborative BSNs, BSN design methods, autonomic BSNs, integration of BSNs and pervasive environments, and integration of BSNs with cloud computing. The book provides a description of real BSN prototypes with the possibility to see on-line demos and download the software to test them on specific sensor platforms and includes case studies for more practical applications. * Provides a future roadmap by learning advanced technology and open research issues * Gathers the background knowledge to tackl...

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 ...

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.

Computer-aided diagnosis workstation and network system for chest diagnosis based on multislice CT images

Science.gov (United States)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

2008-03-01

Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The function to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and Success in login" effective. As a result, patients' private information is protected. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.

A community-based event delivery protocol in publish/subscribe systems for delay tolerant sensor networks.

Science.gov (United States)

Liu, Nianbo; Liu, Ming; Zhu, Jinqi; Gong, Haigang

2009-01-01

The basic operation of a Delay Tolerant Sensor Network (DTSN) is to finish pervasive data gathering in networks with intermittent connectivity, while the publish/subscribe (Pub/Sub for short) paradigm is used to deliver events from a source to interested clients in an asynchronous way. Recently, extension of Pub/Sub systems in DTSNs has become a promising research topic. However, due to the unique frequent partitioning characteristic of DTSNs, extension of a Pub/Sub system in a DTSN is a considerably difficult and challenging problem, and there are no good solutions to this problem in published works. To ad apt Pub/Sub systems to DTSNs, we propose CED, a community-based event delivery protocol. In our design, event delivery is based on several unchanged communities, which are formed by sensor nodes in the network according to their connectivity. CED consists of two components: event delivery and queue management. In event delivery, events in a community are delivered to mobile subscribers once a subscriber comes into the community, for improving the data delivery ratio. The queue management employs both the event successful delivery time and the event survival time to decide whether an event should be delivered or dropped for minimizing the transmission overhead. The effectiveness of CED is demonstrated through comprehensive simulation studies.

Networks in biological systems: An investigation of the Gene Ontology as an evolving network

International Nuclear Information System (INIS)

Coronnello, C; Tumminello, M; Micciche, S; Mantegna, R.N.

2009-01-01

Many biological systems can be described as networks where different elements interact, in order to perform biological processes. We introduce a network associated with the Gene Ontology. Specifically, we construct a correlation-based network where the vertices are the terms of the Gene Ontology and the link between each two terms is weighted on the basis of the number of genes that they have in common. We analyze a filtered network obtained from the correlation-based network and we characterize its evolution over different releases of the Gene Ontology.

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.

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.

Planning Optimization of the Distributed Antenna System in High-Speed Railway Communication Network Based on Improved Cuckoo Search

Directory of Open Access Journals (Sweden)

Zhaoyu Chen

2018-01-01

Full Text Available The network planning is a key factor that directly affects the performance of the wireless networks. Distributed antenna system (DAS is an effective strategy for the network planning. This paper investigates the antenna deployment in a DAS for the high-speed railway communication networks and formulates an optimization problem which is NP-hard for achieving the optimal deployment of the antennas in the DAS. To solve this problem, a scheme based on an improved cuckoo search based on dimension cells (ICSDC algorithm is proposed. ICSDC introduces the dimension cell mechanism to avoid the internal dimension interferences in order to improve the performance of the algorithm. Simulation results show that the proposed ICSDC-based scheme obtains a lower network cost compared with the uniform network planning method. Moreover, ICSDC algorithm has better performance in terms of the convergence rate and accuracy compared with the conventional cuckoo search algorithm, the particle swarm optimization, and the firefly algorithm.

T-S Fuzzy Model Based Control Strategy for the Networked Suspension Control System of Maglev Train

Directory of Open Access Journals (Sweden)

Guang He

2015-01-01

Full Text Available The control problem for the networked suspension control system of maglev train with random induced time delay and packet dropouts is investigated. First, Takagi-Sugeno (T-S fuzzy models are utilized to represent the discrete-time nonlinear networked suspension control system, and the parameters uncertainties of the nonlinear model have also been taken into account. The controllers take the form of parallel distributed compensation. Then, a sufficient condition for the stability of the networked suspension control system is derived. Based on the criteria, the state feedback fuzzy controllers are obtained, and the controller gains can be computed by using MATLAB LMI Toolbox directly. Finally, both the numerical simulations and physical experiments on the full-scale single bogie of CMS-04 maglev train have been accomplished to demonstrate the effectiveness of this proposed method.

Model-based Compositional Design of Networked Control Systems

Science.gov (United States)

2013-12-01

with event scheduling. In particular, the C++ source code for the ns-2 simulator scheduler is modi - fied to implement the time synchronization mechanism...pump: Security attacks and defenses for a diabetes therapy system. In: 2011 13th IEEE International Conference In e-Health Networking Applications and

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.

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.

Nonlinear Robust Observer-Based Fault Detection for Networked Suspension Control System of Maglev Train

Directory of Open Access Journals (Sweden)

Yun Li

2013-01-01

Full Text Available A fault detection approach based on nonlinear robust observer is designed for the networked suspension control system of Maglev train with random induced time delay. First, considering random bounded time-delay and external disturbance, the nonlinear model of the networked suspension control system is established. Then, a nonlinear robust observer is designed using the input of the suspension gap. And the estimate error is proved to be bounded with arbitrary precision by adopting an appropriate parameter. When sensor faults happen, the residual between the real states and the observer outputs indicates which kind of sensor failures occurs. Finally, simulation results using the actual parameters of CMS-04 maglev train indicate that the proposed method is effective for maglev train.

Time-varying causal network of the Korean financial system based on firm-specific risk premiums

Science.gov (United States)

Song, Jae Wook; Ko, Bonggyun; Cho, Poongjin; Chang, Woojin

2016-09-01

The aim of this paper is to investigate the Korean financial system based on time-varying causal network. We discover many stylized facts by utilizing the firm-specific risk premiums for measuring the causality direction from a firm to firm. At first, we discover that the interconnectedness of causal network is affected by the outbreak of financial events; the co-movement of firm-specific risk premium is strengthened after each positive event, and vice versa. Secondly, we find that the major sector of the Korean financial system is the Depositories, and the financial reform in June-2011 achieves its purpose by weakening the power of risk-spillovers of Broker-Dealers. Thirdly, we identify that the causal network is a small-world network with scale-free topology where the power-law exponents of out-Degree and negative event are more significant than those of in-Degree and positive event. Lastly, we discuss that the current aspects of causal network are closely related to the long-term future scenario of the KOSPI Composite index where the direction and stability are significantly affected by the power of risk-spillovers and the power-law exponents of degree distributions, respectively.

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

Modelling of P2P-Based Video Sharing Performance for Content-Oriented Community-Based VoD Systems in Wireless Mobile Networks

Directory of Open Access Journals (Sweden)

Shijie Jia

2016-01-01

Full Text Available The video sharing performance is a key factor for scalability and quality of service of P2P VoD systems in wireless mobile networks. There are some impact factors for the video sharing performance, such as available upload bandwidth, resource distribution in overlay networks, and mobility of mobile nodes. In this paper, we firstly model user behaviors: joining, playback, and departure for the content-oriented community-based VoD systems in wireless mobile networks and construct a resource assignment model by the analysis of transition of node state: suspend, wait, and playback. We analyze the influence of the above three factors: upload bandwidth, startup delay, and resource distribution for the sharing performance and QoS of systems. We further propose the improved resource sharing strategies from the perspectives of community architecture, resource distribution, and data transmission for the systems. Extensive tests show how the improved strategies achieve much better performance results in comparison with original strategies.

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.

Using a Control System Ethernet Network as a Field Bus

CERN Document Server

De Van, William R; Lawson, Gregory S; Wagner, William H; Wantland, David M; Williams, Ernest

2005-01-01

A major component of a typical accelerator distributed control system (DCS) is a dedicated, large-scale local area communications network (LAN). The SNS EPICS-based control system uses a LAN based on the popular IEEE-802.3 set of standards (Ethernet). Since the control system network infrastructure is available throughout the facility, and since Ethernet-based controllers are readily available, it is tempting to use the control system LAN for "fieldbus" communications to low-level control devices (e.g. vacuum controllers; remote I/O). These devices may or may not be compatible with the high-level DCS protocols. This paper presents some of the benefits and risks of combining high-level DCS communications with low-level "field bus" communications on the same network, and describes measures taken at SNS to promote compatibility between devices connected to the control system network.

Design of on-board Bluetooth wireless network system based on fault-tolerant technology

Science.gov (United States)

You, Zheng; Zhang, Xiangqi; Yu, Shijie; Tian, Hexiang

2007-11-01

In this paper, the Bluetooth wireless data transmission technology is applied in on-board computer system, to realize wireless data transmission between peripherals of the micro-satellite integrating electronic system, and in view of the high demand of reliability of a micro-satellite, a design of Bluetooth wireless network based on fault-tolerant technology is introduced. The reliability of two fault-tolerant systems is estimated firstly using Markov model, then the structural design of this fault-tolerant system is introduced; several protocols are established to make the system operate correctly, some related problems are listed and analyzed, with emphasis on Fault Auto-diagnosis System, Active-standby switch design and Data-Integrity process.

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.

Stabilization of Networked Control Systems Under Feedback-based Communication

National Research Council Canada - National Science Library

Zhang, Lei; Hristu-Varsakelis, Dimitrios

2004-01-01

We study the stabilization of a networked control system (NSC) in which multiple sensors and actuators of a physical plant share a communication medium to exchange information with a remote controller...

Research of user access control for networked manufacturing system

Institute of Scientific and Technical Information of China (English)

ZHENG Xiao-lin; LEI Yu; CHEN De-ren

2006-01-01

An integrated user access control method was proposed to address the issues of security and management in networked manufacturing systems (NMS).Based on the analysis of the security issues in networked manufacturing system,an integrated user access control method composed of role-based access control (RBAC),task-based access control (TBAC),relationship-driven access control (RDAC)and coalition-based access control (CBAC) was proposed,including the hierarchical user relationship model,the reference model and the process model.The elements and their relationships were defined,and the expressions of constraints authorization were given.The extensible access control markup language (XACML) was used to implement this method.This method was used in the networked manufacturing system in the Shaoxing spinning region of China.The results show that the integrated user access control method can reduce the costs of system security maintenance and management.

APEnet+: a 3D Torus network optimized for GPU-based HPC Systems

International Nuclear Information System (INIS)

Ammendola, R; Biagioni, A; Frezza, O; Lo Cicero, F; Lonardo, A; Paolucci, P S; Rossetti, D; Simula, F; Tosoratto, L; Vicini, P

2012-01-01

In the supercomputing arena, the strong rise of GPU-accelerated clusters is a matter of fact. Within INFN, we proposed an initiative — the QUonG project — whose aim is to deploy a high performance computing system dedicated to scientific computations leveraging on commodity multi-core processors coupled with latest generation GPUs. The inter-node interconnection system is based on a point-to-point, high performance, low latency 3D torus network which is built in the framework of the APEnet+ project. It takes the form of an FPGA-based PCIe network card exposing six full bidirectional links running at 34 Gbps each that implements the RDMA protocol. In order to enable significant access latency reduction for inter-node data transfer, a direct network-to-GPU interface was built. The specialized hardware blocks, integrated in the APEnet+ board, provide support for GPU-initiated communications using the so called PCIe peer-to-peer (P2P) transactions. This development is made in close collaboration with the GPU vendor NVIDIA. The final shape of a complete QUonG deployment is an assembly of standard 42U racks, each one capable of 80 TFLOPS/rack of peak performance, at a cost of 5 k€/T F LOPS and for an estimated power consumption of 25 kW/rack. In this paper we report on the status of final rack deployment and on the R and D activities for 2012 that will focus on performance enhancement of the APEnet+ hardware through the adoption of new generation 28 nm FPGAs allowing the implementation of PCIe Gen3 host interface and the addition of new fault tolerance-oriented capabilities.

APEnet+: a 3D Torus network optimized for GPU-based HPC Systems

Energy Technology Data Exchange (ETDEWEB)

Ammendola, R [INFN Tor Vergata (Italy); Biagioni, A; Frezza, O; Lo Cicero, F; Lonardo, A; Paolucci, P S; Rossetti, D; Simula, F; Tosoratto, L; Vicini, P [INFN Roma (Italy)

2012-12-13

In the supercomputing arena, the strong rise of GPU-accelerated clusters is a matter of fact. Within INFN, we proposed an initiative - the QUonG project - whose aim is to deploy a high performance computing system dedicated to scientific computations leveraging on commodity multi-core processors coupled with latest generation GPUs. The inter-node interconnection system is based on a point-to-point, high performance, low latency 3D torus network which is built in the framework of the APEnet+ project. It takes the form of an FPGA-based PCIe network card exposing six full bidirectional links running at 34 Gbps each that implements the RDMA protocol. In order to enable significant access latency reduction for inter-node data transfer, a direct network-to-GPU interface was built. The specialized hardware blocks, integrated in the APEnet+ board, provide support for GPU-initiated communications using the so called PCIe peer-to-peer (P2P) transactions. This development is made in close collaboration with the GPU vendor NVIDIA. The final shape of a complete QUonG deployment is an assembly of standard 42U racks, each one capable of 80 TFLOPS/rack of peak performance, at a cost of 5 k Euro-Sign /T F LOPS and for an estimated power consumption of 25 kW/rack. In this paper we report on the status of final rack deployment and on the R and D activities for 2012 that will focus on performance enhancement of the APEnet+ hardware through the adoption of new generation 28 nm FPGAs allowing the implementation of PCIe Gen3 host interface and the addition of new fault tolerance-oriented capabilities.

Implementation of neural network based non-linear predictive control

DEFF Research Database (Denmark)

Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

1999-01-01

This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...... on an efficient quasi-Newton algorithm. The performance is demonstrated on a pneumatic servo system....

Comprehensive evaluation index system of total supply capability in distribution network

Science.gov (United States)

Zhang, Linyao; Wu, Guilian; Yang, Jingyuan; Jia, Shuangrui; Zhang, Wei; Sun, Weiqing

2018-01-01

Aiming at the lack of a comprehensive evaluation of the distribution network, based on the existing distribution network evaluation index system, combined with the basic principles of constructing the evaluation index, put forward a new evaluation index system of distribution network capacity. This paper is mainly based on the total supply capability of the distribution network, combining single index and various factors, into a multi-evaluation index of the distribution network, thus forming a reasonable index system, and various indicators of rational quantification make the evaluation results more intuitive. In order to have a comprehensive judgment of distribution network, this paper uses weights to analyse the importance of each index, verify the rationality of the index system through the example, it is proved that the rationality of the index system, so as to guide the direction of distribution network planning.

NNSYSID and NNCTRL Tools for system identification and control with neural networks

DEFF Research Database (Denmark)

Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

2001-01-01

choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...... a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can...

NNSYSID and NNCTRL Tools for system identification and control with neural networks

DEFF Research Database (Denmark)

Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

2001-01-01

a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can...... choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...

Evaluating airline energy efficiency: An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure

International Nuclear Information System (INIS)

Xu, Xin; Cui, Qiang

2017-01-01

This paper focuses on evaluating airline energy efficiency, which is firstly divided into four stages: Operations Stage, Fleet Maintenance Stage, Services Stage and Sales Stage. The new four-stage network structure of airline energy efficiency is a modification of existing models. A new approach, integrated with Network Epsilon-based Measure and Network Slacks-based Measure, is applied to assess the overall energy efficiency and divisional efficiency of 19 international airlines from 2008 to 2014. The influencing factors of airline energy efficiency are analyzed through the regression analysis. The results indicate the followings: 1. The integrated model can identify the benchmarking airlines in the overall system and stages. 2. Most airlines' energy efficiencies keep steady during the period, except for some sharply fluctuations. The efficiency decreases mainly centralized in the year 2008–2011, affected by the financial crisis in the USA. 3. The average age of fleet is positively correlated with the overall energy efficiency, and each divisional efficiency has different significant influencing factors. - Highlights: • An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure is developed. • 19 airlines' energy efficiencies are evaluated. • Garuda Indonesia has the highest overall energy efficiency.

New neural-networks-based 3D object recognition system

Science.gov (United States)

Abolmaesumi, Purang; Jahed, M.

1997-09-01

Three-dimensional object recognition has always been one of the challenging fields in computer vision. In recent years, Ulman and Basri (1991) have proposed that this task can be done by using a database of 2-D views of the objects. The main problem in their proposed system is that the correspondent points should be known to interpolate the views. On the other hand, their system should have a supervisor to decide which class does the represented view belong to. In this paper, we propose a new momentum-Fourier descriptor that is invariant to scale, translation, and rotation. This descriptor provides the input feature vectors to our proposed system. By using the Dystal network, we show that the objects can be classified with over 95% precision. We have used this system to classify the objects like cube, cone, sphere, torus, and cylinder. Because of the nature of the Dystal network, this system reaches to its stable point by a single representation of the view to the system. This system can also classify the similar views to a single class (e.g., for the cube, the system generated 9 different classes for 50 different input views), which can be used to select an optimum database of training views. The system is also very flexible to the noise and deformed views.

Case-Based Fault Diagnostic System

International Nuclear Information System (INIS)

Mohamed, A.H.

2014-01-01

Nowadays, case-based fault diagnostic (CBFD) systems have become important and widely applied problem solving technologies. They are based on the assumption that “similar faults have similar diagnosis”. On the other hand, CBFD systems still suffer from some limitations. Common ones of them are: (1) failure of CBFD to have the needed diagnosis for the new faults that have no similar cases in the case library. (2) Limited memorization when increasing the number of stored cases in the library. The proposed research introduces incorporating the neural network into the case based system to enable the system to diagnose all the faults. Neural networks have proved their success in the classification and diagnosis problems. The suggested system uses the neural network to diagnose the new faults (cases) that cannot be diagnosed by the traditional CBR diagnostic system. Besides, the proposed system can use the another neural network to control adding and deleting the cases in the library to manage the size of the cases in the case library. However, the suggested system has improved the performance of the case based fault diagnostic system when applied for the motor rolling bearing as a case of study

Network Capacity Assessment of CHP-based Distributed Generation on Urban Energy Distribution Networks

Science.gov (United States)

Zhang, Xianjun

The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical

Application of wireless sensor network technology in logistics information system

Science.gov (United States)

Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2017-04-01

This paper introduces the basic concepts of active RFID (WSN-ARFID) based on wireless sensor networks and analyzes the shortcomings of the existing RFID-based logistics monitoring system. Integrated wireless sensor network technology and the scrambling point of RFID technology. A new real-time logistics detection system based on WSN and RFID, a model of logistics system based on WSN-ARFID is proposed, and the feasibility of this technology applied to logistics field is analyzed.

System crash as dynamics of complex networks.

Science.gov (United States)

Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim

2016-10-18

Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.

A link prediction method for heterogeneous networks based on BP neural network

Science.gov (United States)

Li, Ji-chao; Zhao, Dan-ling; Ge, Bing-Feng; Yang, Ke-Wei; Chen, Ying-Wu

2018-04-01

Most real-world systems, composed of different types of objects connected via many interconnections, can be abstracted as various complex heterogeneous networks. Link prediction for heterogeneous networks is of great significance for mining missing links and reconfiguring networks according to observed information, with considerable applications in, for example, friend and location recommendations and disease-gene candidate detection. In this paper, we put forward a novel integrated framework, called MPBP (Meta-Path feature-based BP neural network model), to predict multiple types of links for heterogeneous networks. More specifically, the concept of meta-path is introduced, followed by the extraction of meta-path features for heterogeneous networks. Next, based on the extracted meta-path features, a supervised link prediction model is built with a three-layer BP neural network. Then, the solution algorithm of the proposed link prediction model is put forward to obtain predicted results by iteratively training the network. Last, numerical experiments on the dataset of examples of a gene-disease network and a combat network are conducted to verify the effectiveness and feasibility of the proposed MPBP. It shows that the MPBP with very good performance is superior to the baseline methods.

Promoting sustainable energy systems through networks. A framework for network design developed using the case of BASE (Basel Agency for Sustainable Energy)

Energy Technology Data Exchange (ETDEWEB)

Schlup, M.

2001-09-01

implementing such projects to increase efficiency of the processing and thus effectiveness of promotional efforts. The demands and needs of a number of potential BASE network partners were evaluated through interviews. The statements were analysed to define a suitable objective for the BASE network, that states as network purpose the facilitation of investments in sustainable energy projects that provide additional benefits, e.g. through contributing to Sustainable Development and generating social capital for investors. Furthermore, it was evaluated to what extent the networking approach for potential participants is attractive. Knowledge exchange and potential synergies were among the reasons stated for making such a network attractive, although motivation differed significantly among the interviewed organisations. Competitive barriers, dependencies of various kinds and high coordination and consensus costs were mentioned as potential drawbacks. Services offered involved access to existing networks and provision of financial knowledge and in general matched with services expected from the network. A multilevel network was suggested as most appropriate structure, with BASE coordinating a decentralised network dedicated in facilitating investments in sustainable energies and at the same time being part of a network of 'Centres of Excellence' of international agencies promoting the transition towards Sustainable Energy Systems. Access to affiliated networks of participating organisations thus would maximise the outreach. A number of potential performance indicators were also suggested. Confidentiality and neutrality were identified as crucial for the formation of trust in such a network. Personal contacts were mentioned as being decisive for the building of trust. Also, trust was seen as only emerging if the network could present a successful track record of pilot projects. Such a record would thus greatly increase the likeliness of network institutionalisation and

Mitigation of the ground reflection effect in real-time locating systems based on wireless sensor networks by using artificial neural networks

OpenAIRE

de Paz Santana, Juan F.; Tapia Martínez, Dante I.; Alonso Rincón, Ricardo S.; Pinzón, Cristian; Bajo Pérez, Javier; Corchado Rodríguez, Juan M.

2017-01-01

Wireless sensor networks (WSNs) have become much more relevant in recent years, mainly because they can be used in a wide diversity of applications. Real-time locating systems (RTLSs) are one of the most promising applications based on WSNs and represent a currently growing market. Specifically, WSNs are an ideal alternative to develop RTLSs aimed at indoor environments where existing global navigation satellite systems, such as the global positioning system, do not work correctly due to the ...

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

A Community-Based Event Delivery Protocol in Publish/Subscribe Systems for Delay Tolerant Sensor Networks

Directory of Open Access Journals (Sweden)

Haigang Gong

2009-09-01

Full Text Available The basic operation of a Delay Tolerant Sensor Network (DTSN is to finish pervasive data gathering in networks with intermittent connectivity, while the publish/subscribe (Pub/Sub for short paradigm is used to deliver events from a source to interested clients in an asynchronous way. Recently, extension of Pub/Sub systems in DTSNs has become a promising research topic. However, due to the unique frequent partitioning characteristic of DTSNs, extension of a Pub/Sub system in a DTSN is a considerably difficult and challenging problem, and there are no good solutions to this problem in published works. To ad apt Pub/Sub systems to DTSNs, we propose CED, a community-based event delivery protocol. In our design, event delivery is based on several unchanged communities, which are formed by sensor nodes in the network according to their connectivity. CED consists of two components: event delivery and queue management. In event delivery, events in a community are delivered to mobile subscribers once a subscriber comes into the community, for improving the data delivery ratio. The queue management employs both the event successful delivery time and the event survival time to decide whether an event should be delivered or dropped for minimizing the transmission overhead. The effectiveness of CED is demonstrated through comprehensive simulation studies.

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.

Collaborative Recurrent Neural Networks forDynamic Recommender Systems

Science.gov (United States)

2016-11-22

JMLR: Workshop and Conference Proceedings 63:366–381, 2016 ACML 2016 Collaborative Recurrent Neural Networks for Dynamic Recommender Systems Young...an unprece- dented scale. Although such activity logs are abundantly available, most approaches to recommender systems are based on the rating...Recurrent Neural Network, Recommender System , Neural Language Model, Collaborative Filtering 1. Introduction As ever larger parts of the population

On Real-Time Systems Using Local Area Networks.

Science.gov (United States)

1987-07-01

87-35 July, 1987 CS-TR-1892 On Real - Time Systems Using Local Area Networks*I VShem-Tov Levi Department of Computer Science Satish K. Tripathit...1892 On Real - Time Systems Using Local Area Networks* Shem-Tov Levi Department of Computer Science Satish K. Tripathit Department of Computer Science...constraints and the clock systems that feed the time to real - time systems . A model for real-time system based on LAN communication is presented in

Network SCADA System

International Nuclear Information System (INIS)

Milivojevic, Dragan R.; Tasic, Visa; Karabasevic, Dejan

2003-01-01

Copper Institute, Industrial Informatics department, is developing and applying network real time process monitoring and control systems. Some of these systems are already in use. The paper presents some hardware and software general remarks and performances, with special regard to communication sub-systems and network possibilities. (Author)

Distribution network topology identification based on synchrophasor

Directory of Open Access Journals (Sweden)

Stefania Conti

2018-03-01

Full Text Available A distribution system upgrade moving towards Smart Grid implementation is necessary to face the proliferation of distributed generators and electric vehicles, in order to satisfy the increasing demand for high quality, efficient, secure, reliable energy supply. This perspective requires taking into account system vulnerability to cyber attacks. An effective attack could destroy stored information about network structure, historical data and so on. Countermeasures and network applications could be made impracticable since most of them are based on the knowledge of network topology. Usually, the location of each link between nodes in a network is known. Therefore, the methods used for topology identification determine if a link is open or closed. When no information on the location of the network links is available, these methods become totally unfeasible. This paper presents a method to identify the network topology using only nodal measures obtained by means of phasor measurement units.

Network-based recommendation algorithms: A review

Science.gov (United States)

Yu, Fei; Zeng, An; Gillard, Sébastien; Medo, Matúš

2016-06-01

Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use-such as the possible influence of recommendation on the evolution of systems that use it-and finally discuss open research directions and challenges.

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.

Physical parameters collection based on wireless senor network

Science.gov (United States)

Chen, Xin; Wu, Hong; Ji, Lei

2013-12-01

With the development of sensor technology, wireless senor network has been applied in the medical, military, entertainment field and our daily life. But the existing available wireless senor networks applied in human monitoring system still have some problems, such as big power consumption, low security and so on. To improve senor network applied in health monitoring system, the paper introduces a star wireless senor networks based on msp430 and DSP. We design a low-cost heart-rate monitor senor node. The communication between senor node and sink node is realized according to the newest protocol proposed by the IEEE 802.15.6 Task Group. This wireless senor network will be more energy-efficient and faster compared to traditional senor networks.

System-level Modeling of Wireless Integrated Sensor Networks

DEFF Research Database (Denmark)

Virk, Kashif M.; Hansen, Knud; Madsen, Jan

2005-01-01

Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...

Submodularity in dynamics and control of networked systems

CERN Document Server

Clark, Andrew; Bushnell, Linda; Poovendran, Radha

2016-01-01

This book presents a framework for the control of networked systems utilizing submodular optimization techniques. The main focus is on selecting input nodes for the control of networked systems, an inherently discrete optimization problem with applications in power system stability, social influence dynamics, and the control of vehicle formations. The first part of the book is devoted to background information on submodular functions, matroids, and submodular optimization, and presents algorithms for distributed submodular optimization that are scalable to large networked systems. In turn, the second part develops a unifying submodular optimization approach to controlling networked systems based on multiple performance and controllability criteria. Techniques are introduced for selecting input nodes to ensure smooth convergence, synchronization, and robustness to environmental and adversarial noise. Submodular optimization is the first unifying approach towards guaranteeing both performance and controllabilit...

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.

Strengthening regional innovation through network-based innovation brokering

OpenAIRE

Svare, Helge; Gausdal, Anne Haugen

2015-01-01

The primary objective of this paper is to demonstrate how regional innovation system theory may be translated into manageable micro-level methods with the potential for strengthening the productive dynamics of a regional innovation system. The paper meets this objective by presenting network-based innovation brokering (NBIB), a practical method designed using insights from regional innovation system theory and trust theory. Five cases from two Norwegian regional innovation networks show that ...

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.

Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks

Directory of Open Access Journals (Sweden)

Y.-M. Chiang

2011-01-01

Full Text Available Pumping stations play an important role in flood mitigation in metropolitan areas. The existing sewerage systems, however, are facing a great challenge of fast rising peak flow resulting from urbanization and climate change. It is imperative to construct an efficient and accurate operating prediction model for pumping stations to simulate the drainage mechanism for discharging the rainwater in advance. In this study, we propose two rule-based fuzzy neural networks, adaptive neuro-fuzzy inference system (ANFIS and counterpropagation fuzzy neural network for on-line predicting of the number of open and closed pumps of a pivotal pumping station in Taipei city up to a lead time of 20 min. The performance of ANFIS outperforms that of CFNN in terms of model efficiency, accuracy, and correctness. Furthermore, the results not only show the predictive water levels do contribute to the successfully operating pumping stations but also demonstrate the applicability and reliability of ANFIS in automatically controlling the urban sewerage systems.

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…

Ethernet-based test stand for a CAN network

Science.gov (United States)

Ziebinski, Adam; Cupek, Rafal; Drewniak, Marek

2017-11-01

This paper presents a test stand for the CAN-based systems that are used in automotive systems. The authors propose applying an Ethernet-based test system that supports the virtualisation of a CAN network. The proposed solution has many advantages compared to classical test beds that are based on dedicated CAN-PC interfaces: it allows the physical constraints associated with the number of interfaces that can be simultaneously connected to a tested system to be avoided, which enables the test time for parallel tests to be shortened; the high speed of Ethernet transmission allows for more frequent sampling of the messages that are transmitted by a CAN network (as the authors show in the experiment results section) and the cost of the proposed solution is much lower than the traditional lab-based dedicated CAN interfaces for PCs.

System Design for Nano-Network Communications

Science.gov (United States)

ShahMohammadian, Hoda

The potential applications of nanotechnology in a wide range of areas necessities nano-networking research. Nano-networking is a new type of networking which has emerged by applying nanotechnology to communication theory. Therefore, this dissertation presents a framework for physical layer communications in a nano-network and addresses some of the pressing unsolved challenges in designing a molecular communication system. The contribution of this dissertation is proposing well-justified models for signal propagation, noise sources, optimum receiver design and synchronization in molecular communication channels. The design of any communication system is primarily based on the signal propagation channel and noise models. Using the Brownian motion and advection molecular statistics, separate signal propagation and noise models are presented for diffusion-based and flow-based molecular communication channels. It is shown that the corrupting noise of molecular channels is uncorrelated and non-stationary with a signal dependent magnitude. The next key component of any communication system is the reception and detection process. This dissertation provides a detailed analysis of the effect of the ligand-receptor binding mechanism on the received signal, and develops the first optimal receiver design for molecular communications. The bit error rate performance of the proposed receiver is evaluated and the impact of medium motion on the receiver performance is investigated. Another important feature of any communication system is synchronization. In this dissertation, the first blind synchronization algorithm is presented for the molecular communication channels. The proposed algorithm uses a non-decision directed maximum likelihood criterion for estimating the channel delay. The Cramer-Rao lower bound is also derived and the performance of the proposed synchronization algorithm is evaluated by investigating its mean square error.

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.

Next Generation RFID-Based Medical Service Management System Architecture in Wireless Sensor Network

Science.gov (United States)

Tolentino, Randy S.; Lee, Kijeong; Kim, Yong-Tae; Park, Gil-Cheol

Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two important wireless technologies that have wide variety of applications and provide unlimited future potentials most especially in healthcare systems. RFID is used to detect presence and location of objects while WSN is used to sense and monitor the environment. Integrating RFID with WSN not only provides identity and location of an object but also provides information regarding the condition of the object carrying the sensors enabled RFID tag. However, there isn't any flexible and robust communication infrastructure to integrate these devices into an emergency care setting. An efficient wireless communication substrate for medical devices that addresses ad hoc or fixed network formation, naming and discovery, transmission efficiency of data, data security and authentication, as well as filtration and aggregation of vital sign data need to be study and analyze. This paper proposed an efficient next generation architecture for RFID-based medical service management system in WSN that possesses the essential elements of each future medical application that are integrated with existing medical practices and technologies in real-time, remote monitoring, in giving medication, and patient status tracking assisted by embedded wearable wireless sensors which are integrated in wireless sensor network.

Novel flat datacenter network architecture based on scalable and flow-controlled optical switch system.

Science.gov (United States)

Miao, Wang; Luo, Jun; Di Lucente, Stefano; Dorren, Harm; Calabretta, Nicola

2014-02-10

We propose and demonstrate an optical flat datacenter network based on scalable optical switch system with optical flow control. Modular structure with distributed control results in port-count independent optical switch reconfiguration time. RF tone in-band labeling technique allowing parallel processing of the label bits ensures the low latency operation regardless of the switch port-count. Hardware flow control is conducted at optical level by re-using the label wavelength without occupying extra bandwidth, space, and network resources which further improves the performance of latency within a simple structure. Dynamic switching including multicasting operation is validated for a 4 x 4 system. Error free operation of 40 Gb/s data packets has been achieved with only 1 dB penalty. The system could handle an input load up to 0.5 providing a packet loss lower that 10(-5) and an average latency less that 500 ns when a buffer size of 16 packets is employed. Investigation on scalability also indicates that the proposed system could potentially scale up to large port count with limited power penalty.

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

2016-01-01

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. PMID:28042831

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.

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.

TB-CA: A hybrid method based on trust and context-aware for recommender system in social networks

Directory of Open Access Journals (Sweden)

Fateme Keikha

2015-05-01

Full Text Available Recommender systems help users faced with the problem of information overflow and provide personalized recommendations. Social networks are used for providing variety of business or social activities, or sometimes a combination of both. In this paper, by considering social network of users and according to users’ context and items, a new method is introduced that is based on trust and context aware for recommender systems in social networks. The purpose of this paper is to create a recommender system which increases precision of predicted ratings for all users especially for cold start users. In the proposed method, walking on web of trust is done by neighbor users for finding rating of similar items and users’ preference is gotten of items’ context. The results show that suitable recommendation with user’s context is provided by using this method. Also, this system can increase precision of predicted rating for all users and cold starts too and however, do not decrease the rating’s coverage.

SIP-Based Single Neuron Stochastic Predictive Control for Non-Gaussian Networked Control Systems with Uncertain Metrology Delays

Directory of Open Access Journals (Sweden)

Xinying Xu

2018-06-01

Full Text Available In this paper, a novel data-driven single neuron predictive control strategy is proposed for non-Gaussian networked control systems with metrology delays in the information theory framework. Firstly, survival information potential (SIP, instead of minimum entropy, is used to formulate the performance index to characterize the randomness of the considered systems, which is calculated by oversampling method. Then the minimum values can be computed by optimizing the SIP-based performance index. Finally, the proposed strategy, minimum entropy method and mean square error (MSE are applied to a networked motor control system, and results demonstrated the effectiveness of the proposed strategy.

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.

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.

Individual heterogeneity generating explosive system network dynamics.

Science.gov (United States)

Manrique, Pedro D; Johnson, Neil F

2018-03-01

Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.

Individual heterogeneity generating explosive system network dynamics

Science.gov (United States)

Manrique, Pedro D.; Johnson, Neil F.

2018-03-01

Individual heterogeneity is a key characteristic of many real-world systems, from organisms to humans. However, its role in determining the system's collective dynamics is not well understood. Here we study how individual heterogeneity impacts the system network dynamics by comparing linking mechanisms that favor similar or dissimilar individuals. We find that this heterogeneity-based evolution drives an unconventional form of explosive network behavior, and it dictates how a polarized population moves toward consensus. Our model shows good agreement with data from both biological and social science domains. We conclude that individual heterogeneity likely plays a key role in the collective development of real-world networks and communities, and it cannot be ignored.

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,

The network-based energy management system for convenience stores

Energy Technology Data Exchange (ETDEWEB)

Wang, An-Ping; Hsu, Pau-Lo [Department of Electrical and Control Engineering, National Chiao-Tung University, 1001 Ta-Hsiue Road, Hsinchu City 310 (China)

2008-07-01

Convenience stores generally consume energy higher than other retailing merchants. As the problem of energy shortage becomes more serious during summer, almost all convenience stores sign a contract with power plants, which provides for fines if demand limiting occurs in Taiwan and many other countries. Therefore, a reliable and effective method to reduce their utility consumption is required for modern business and industry. This research integrates the remote sensors, the control network, and the embedded system technologies to construct a distributed energy management control system for dedicated convenience stores. Energy consumption can thus be reasonably managed with demand limits by measuring and analyzing the power consumption sources in four major subsystems of convenience stores, namely, (1) air-conditioning, (2) lighting, (3) heating, and (4) refrigeration. By applying the proposed demand prediction and control method, the demand limiting condition can be properly predicted, and the possible peak load can thus be eliminated via the network control mechanism. Moreover, by integrating the LonWork fieldbus and the WinCE operating system (OS), the proposed system has been successfully applied to a convenience store. The experimental results indicate that the proposed distributed energy management system suitably predicts the peak loading condition and successfully prevents its occurrence by switching the air-conditioning system without affecting the indoor temperature regulation. (author)

Risk-based design of process systems using discrete-time Bayesian networks

International Nuclear Information System (INIS)

Khakzad, Nima; Khan, Faisal; Amyotte, Paul

2013-01-01

Temporal Bayesian networks have gained popularity as a robust technique to model dynamic systems in which the components' sequential dependency, as well as their functional dependency, cannot be ignored. In this regard, discrete-time Bayesian networks have been proposed as a viable alternative to solve dynamic fault trees without resort to Markov chains. This approach overcomes the drawbacks of Markov chains such as the state-space explosion and the error-prone conversion procedure from dynamic fault tree. It also benefits from the inherent advantages of Bayesian networks such as probability updating. However, effective mapping of the dynamic gates of dynamic fault trees into Bayesian networks while avoiding the consequent huge multi-dimensional probability tables has always been a matter of concern. In this paper, a new general formalism has been developed to model two important elements of dynamic fault tree, i.e., cold spare gate and sequential enforcing gate, with any arbitrary probability distribution functions. Also, an innovative Neutral Dependency algorithm has been introduced to model dynamic gates such as priority-AND gate, thus reducing the dimension of conditional probability tables by an order of magnitude. The second part of the paper is devoted to the application of discrete-time Bayesian networks in the risk assessment and safety analysis of complex process systems. It has been shown how dynamic techniques can effectively be applied for optimal allocation of safety systems to obtain maximum risk reduction.

Hybrid energy system evaluation in water supply system energy production: neural network approach

Energy Technology Data Exchange (ETDEWEB)

Goncalves, Fabio V.; Ramos, Helena M. [Civil Engineering Department, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal); Reis, Luisa Fernanda R. [Universidade de Sao Paulo, EESC/USP, Departamento de Hidraulica e Saneamento., Avenida do Trabalhador Saocarlense, 400, Sao Carlos-SP (Brazil)

2010-07-01

Water supply systems are large consumers of energy and the use of hybrid systems for green energy production is this new proposal. This work presents a computational model based on neural networks to determine the best configuration of a hybrid system to generate energy in water supply systems. In this study the energy sources to make this hybrid system can be the national power grid, micro-hydro and wind turbines. The artificial neural network is composed of six layers, trained to use data generated by a model of hybrid configuration and an economic simulator - CES. The reason for the development of an advanced model of forecasting based on neural networks is to allow rapid simulation and proper interaction with hydraulic and power model simulator - HPS. The results show that this computational model is useful as advanced decision support system in the design of configurations of hybrid power systems applied to water supply systems, improving the solutions in the development of its global energy efficiency.

Patients’ Heart Monitoring System Based on Wireless Sensor Network

Science.gov (United States)

Sollu, T. S.; Alamsyah; Bachtiar, M.; Sooai, A. G.

2018-04-01

Wireless sensor network (WSN) has been utilized to support the health field such as monitoring the patient’s heartbeat. Heart health monitoring is essential in maintaining health, especially in the elderly. Such an arrangement is needed to understand the patient’s heart characteristics. The increasing number of patients certainly will enhance the burdens of doctors or nurses in dealing with the condition of the patients. Therefore, required a solution that could help doctors or nurses in monitoring the progress of patients’ health at a real time. This research proposes a design and application of a patient heart monitoring system based on WSN. This system with using electrocardiograph (ECG) mounted on the patients’ body and sent to the server through the ZigBee. The results indicated that the retrieval of data for 15 seconds in male patients, with the age of 25 years was 17 times rate or equal to 68 bpm. For 884 data packets sent for 15 minutes using ZigBee produce a data as much as 4488 bytes, throughput of 2.39 Kbps, and 0.24486 seconds of average delay. The measurement of the communication coverage based on the open space conditions within 15 seconds through ZigBee resulting throughput value of 4.19 Kbps, packet loss of 0 %, and 6.667 seconds of average delay. While, the measurement of communication range based on closed space condition through ZigBee resulting throughput of 4.27 Kbps, packet loss of 0 %, and 6.55 seconds of average delay.

An expert system for configuring a network for a Milstar terminal

Science.gov (United States)

Mahoney, Melissa J.; Wilson, Elizabeth J.

1994-01-01

This paper describes a rule-based expert system which assists the user in configuring a network for Air Force terminals using the Milstar satellite system. The network configuration expert system approach uses CLIPS. The complexity of network configuration is discussed, and the methods used to model it are described.

A Wearable Respiratory Biofeedback System Based on Generalized Body Sensor Network

Science.gov (United States)

Liu, Guan-Zheng; Huang, Bang-Yu

2011-01-01

Abstract Wearable medical devices have enabled unobtrusive monitoring of vital signs and emerging biofeedback services in a pervasive manner. This article describes a wearable respiratory biofeedback system based on a generalized body sensor network (BSN) platform. The compact BSN platform was tailored for the strong requirements of overall system optimizations. A waist-worn biofeedback device was designed using the BSN. Extensive bench tests have shown that the generalized BSN worked as intended. In-situ experiments with 22 subjects indicated that the biofeedback device was discreet, easy to wear, and capable of offering wearable respiratory trainings. Pilot studies on wearable training patterns and resultant heart rate variability suggested that paced respirations at abdominal level and with identical inhaling/exhaling ratio were more appropriate for decreasing sympathetic arousal and increasing parasympathetic activities. PMID:21545293

Examining the resilience of national energy systems: Measurements of diversity in production-based and consumption-based electricity in the globalization of trade networks

International Nuclear Information System (INIS)

Kharrazi, Ali; Sato, Masahiro; Yarime, Masaru; Nakayama, Hirofumi; Yu, Yadong; Kraines, Steven

2015-01-01

Energy is a critical component of achieving sustainable development. In addition to the three aspects of promoting access, renewables, and efficiency, the dimension of resilience in energy systems should also considered. The implementation of resilient energy systems requires a quantitative understanding of the socio-economic practices underlying such systems. Specifically, in line with the increasing globalization of trade, there remains a critical knowledge gap on the link between embodied energy in the production and consumption of traded goods. To bridge this knowledge gap, we investigate the resilience of global energy systems through an examination of a diversity measure of global embodied electricity trade based on multi-regional input-output (MRIO) networks. The significance of this research lies in its ability to utilize high resolution MRIO data sets in assessing the resilience of national energy systems. This research indicates that secure and responsible consumption requires the diversification of not only energy generation but also energy imports. This research will lay the ground for further research in the governance of resilience in global energy networks. - Highlights: • We examine the resilience of global embodied energy based on (MRIO) trade networks. • We propose a secure and responsible mode of thinking for national energy consumption. • Secure & responsible consumption requires diversity in energy generation and imports.

Location based Network Optimizations for Mobile Wireless Networks

DEFF Research Database (Denmark)

Nielsen, Jimmy Jessen

selection in Wi-Fi networks and predictive handover optimization in heterogeneous wireless networks. The investigations in this work have indicated that location based network optimizations are beneficial compared to typical link measurement based approaches. Especially the knowledge of geographical...

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks.

Science.gov (United States)

Artuñedo, Antonio; Del Toro, Raúl M; Haber, Rodolfo E

2017-04-26

Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller ( TLC ) network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

Consensus-Based Cooperative Control Based on Pollution Sensing and Traffic Information for Urban Traffic Networks

Directory of Open Access Journals (Sweden)

Antonio Artuñedo

2017-04-01

Full Text Available Nowadays many studies are being conducted to develop solutions for improving the performance of urban traffic networks. One of the main challenges is the necessary cooperation among different entities such as vehicles or infrastructure systems and how to exploit the information available through networks of sensors deployed as infrastructures for smart cities. In this work an algorithm for cooperative control of urban subsystems is proposed to provide a solution for mobility problems in cities. The interconnected traffic lights controller (TLC network adapts traffic lights cycles, based on traffic and air pollution sensory information, in order to improve the performance of urban traffic networks. The presence of air pollution in cities is not only caused by road traffic but there are other pollution sources that contribute to increase or decrease the pollution level. Due to the distributed and heterogeneous nature of the different components involved, a system of systems engineering approach is applied to design a consensus-based control algorithm. The designed control strategy contains a consensus-based component that uses the information shared in the network for reaching a consensus in the state of TLC network components. Discrete event systems specification is applied for modelling and simulation. The proposed solution is assessed by simulation studies with very promising results to deal with simultaneous responses to both pollution levels and traffic flows in urban traffic networks.

ATLANTIDES: An Architecture for Alert Verification in Network Intrusion Detection Systems

NARCIS (Netherlands)

Bolzoni, D.; Crispo, Bruno; Etalle, Sandro

2007-01-01

We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network

Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity

International Nuclear Information System (INIS)

Stern, R.E.; Song, J.; Work, D.B.

2017-01-01

The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.

Stability and stabilisation of a class of networked dynamic systems

Science.gov (United States)

Liu, H. B.; Wang, D. Q.

2018-04-01

We investigate the stability and stabilisation of a linear time invariant networked heterogeneous system with arbitrarily connected subsystems. A new linear matrix inequality based sufficient and necessary condition for the stability is derived, based on which the stabilisation is provided. The obtained conditions efficiently utilise the block-diagonal characteristic of system parameter matrices and the sparseness of subsystem connection matrix. Moreover, a sufficient condition only dependent on each individual subsystem is also presented for the stabilisation of the networked systems with a large scale. Numerical simulations show that these conditions are computationally valid in the analysis and synthesis of a large-scale networked system.

Development and Flight Testing of a Neural Network Based Flight Control System on the NF-15B Aircraft

Science.gov (United States)

Bomben, Craig R.; Smolka, James W.; Bosworth, John T.; Silliams-Hayes, Peggy S.; Burken, John J.; Larson, Richard R.; Buschbacher, Mark J.; Maliska, Heather A.

2006-01-01

The Intelligent Flight Control System (IFCS) project at the NASA Dryden Flight Research Center, Edwards AFB, CA, has been investigating the use of neural network based adaptive control on a unique NF-15B test aircraft. The IFCS neural network is a software processor that stores measured aircraft response information to dynamically alter flight control gains. In 2006, the neural network was engaged and allowed to learn in real time to dynamically alter the aircraft handling qualities characteristics in the presence of actual aerodynamic failure conditions injected into the aircraft through the flight control system. The use of neural network and similar adaptive technologies in the design of highly fault and damage tolerant flight control systems shows promise in making future aircraft far more survivable than current technology allows. This paper will present the results of the IFCS flight test program conducted at the NASA Dryden Flight Research Center in 2006, with emphasis on challenges encountered and lessons learned.

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.

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.

Nonbinary Tree-Based Phylogenetic Networks.

Science.gov (United States)

Jetten, Laura; van Iersel, Leo

2018-01-01

Rooted phylogenetic networks are used to describe evolutionary histories that contain non-treelike evolutionary events such as hybridization and horizontal gene transfer. In some cases, such histories can be described by a phylogenetic base-tree with additional linking arcs, which can, for example, represent gene transfer events. Such phylogenetic networks are called tree-based. Here, we consider two possible generalizations of this concept to nonbinary networks, which we call tree-based and strictly-tree-based nonbinary phylogenetic networks. We give simple graph-theoretic characterizations of tree-based and strictly-tree-based nonbinary phylogenetic networks. Moreover, we show for each of these two classes that it can be decided in polynomial time whether a given network is contained in the class. Our approach also provides a new view on tree-based binary phylogenetic networks. Finally, we discuss two examples of nonbinary phylogenetic networks in biology and show how our results can be applied to them.

On effectiveness of network sensor-based defense framework

Science.gov (United States)

Zhang, Difan; Zhang, Hanlin; Ge, Linqiang; Yu, Wei; Lu, Chao; Chen, Genshe; Pham, Khanh

2012-06-01

Cyber attacks are increasing in frequency, impact, and complexity, which demonstrate extensive network vulnerabilities with the potential for serious damage. Defending against cyber attacks calls for the distributed collaborative monitoring, detection, and mitigation. To this end, we develop a network sensor-based defense framework, with the aim of handling network security awareness, mitigation, and prediction. We implement the prototypical system and show its effectiveness on detecting known attacks, such as port-scanning and distributed denial-of-service (DDoS). Based on this framework, we also implement the statistical-based detection and sequential testing-based detection techniques and compare their respective detection performance. The future implementation of defensive algorithms can be provisioned in our proposed framework for combating cyber attacks.

Bandwidth Optimization On Design Of Visual Display Information System Based Networking At Politeknik Negeri Bali

Science.gov (United States)

Sudiartha, IKG; Catur Bawa, IGNB

2018-01-01

Information can not be separated from the social life of the community, especially in the world of education. One of the information fields is academic calendar information, activity agenda, announcement and campus activity news. In line with technological developments, text-based information is becoming obsolete. For that need creativity to present information more quickly, accurately and interesting by exploiting the development of digital technology and internet. In this paper will be developed applications for the provision of information in the form of visual display, applied to computer network system with multimedia applications. Network-based applications provide ease in updating data through internet services, attractive presentations with multimedia support. The application “Networking Visual Display Information Unit” can be used as a medium that provides information services for students and academic employee more interesting and ease in updating information than the bulletin board. The information presented in the form of Running Text, Latest Information, Agenda, Academic Calendar and Video provide an interesting presentation and in line with technological developments at the Politeknik Negeri Bali. Through this research is expected to create software “Networking Visual Display Information Unit” with optimal bandwidth usage by combining local data sources and data through the network. This research produces visual display design with optimal bandwidth usage and application in the form of supporting software.

Self-organized topology of recurrence-based complex networks

International Nuclear Information System (INIS)

Yang, Hui; Liu, Gang

2013-01-01

With the rapid technological advancement, network is almost everywhere in our daily life. Network theory leads to a new way to investigate the dynamics of complex systems. As a result, many methods are proposed to construct a network from nonlinear time series, including the partition of state space, visibility graph, nearest neighbors, and recurrence approaches. However, most previous works focus on deriving the adjacency matrix to represent the complex network and extract new network-theoretic measures. Although the adjacency matrix provides connectivity information of nodes and edges, the network geometry can take variable forms. The research objective of this article is to develop a self-organizing approach to derive the steady geometric structure of a network from the adjacency matrix. We simulate the recurrence network as a physical system by treating the edges as springs and the nodes as electrically charged particles. Then, force-directed algorithms are developed to automatically organize the network geometry by minimizing the system energy. Further, a set of experiments were designed to investigate important factors (i.e., dynamical systems, network construction methods, force-model parameter, nonhomogeneous distribution) affecting this self-organizing process. Interestingly, experimental results show that the self-organized geometry recovers the attractor of a dynamical system that produced the adjacency matrix. This research addresses a question, i.e., “what is the self-organizing geometry of a recurrence network?” and provides a new way to reproduce the attractor or time series from the recurrence plot. As a result, novel network-theoretic measures (e.g., average path length and proximity ratio) can be achieved based on actual node-to-node distances in the self-organized network topology. The paper brings the physical models into the recurrence analysis and discloses the spatial geometry of recurrence networks

Fuzzy Logic Based Anomaly Detection for Embedded Network Security Cyber Sensor

Energy Technology Data Exchange (ETDEWEB)

Ondrej Linda; Todd Vollmer; Jason Wright; Milos Manic

2011-04-01

Resiliency and security in critical infrastructure control systems in the modern world of cyber terrorism constitute a relevant concern. Developing a network security system specifically tailored to the requirements of such critical assets is of a primary importance. This paper proposes a novel learning algorithm for anomaly based network security cyber sensor together with its hardware implementation. The presented learning algorithm constructs a fuzzy logic rule based model of normal network behavior. Individual fuzzy rules are extracted directly from the stream of incoming packets using an online clustering algorithm. This learning algorithm was specifically developed to comply with the constrained computational requirements of low-cost embedded network security cyber sensors. The performance of the system was evaluated on a set of network data recorded from an experimental test-bed mimicking the environment of a critical infrastructure control system.

On Tree-Based Phylogenetic Networks.

Science.gov (United States)

Zhang, Louxin

2016-07-01

A large class of phylogenetic networks can be obtained from trees by the addition of horizontal edges between the tree edges. These networks are called tree-based networks. We present a simple necessary and sufficient condition for tree-based networks and prove that a universal tree-based network exists for any number of taxa that contains as its base every phylogenetic tree on the same set of taxa. This answers two problems posted by Francis and Steel recently. A byproduct is a computer program for generating random binary phylogenetic networks under the uniform distribution model.

Synthesis of recurrent neural networks for dynamical system simulation.

Science.gov (United States)

Trischler, Adam P; D'Eleuterio, Gabriele M T

2016-08-01

We review several of the most widely used techniques for training recurrent neural networks to approximate dynamical systems, then describe a novel algorithm for this task. The algorithm is based on an earlier theoretical result that guarantees the quality of the network approximation. We show that a feedforward neural network can be trained on the vector-field representation of a given dynamical system using backpropagation, then recast it as a recurrent network that replicates the original system's dynamics. After detailing this algorithm and its relation to earlier approaches, we present numerical examples that demonstrate its capabilities. One of the distinguishing features of our approach is that both the original dynamical systems and the recurrent networks that simulate them operate in continuous time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Design of real-time voice over internet protocol system under bandwidth network

Science.gov (United States)

Zhang, Li; Gong, Lina

2017-04-01

With the increasing bandwidth of the network and network convergence accelerating, VoIP means of communication across the network is becoming increasingly popular phenomenon. The real-time identification and analysis for VOIP flow over backbone network become the urgent needs and research hotspot of network operations management. Based on this, the paper proposes a VoIP business management system over backbone network. The system first filters VoIP data stream over backbone network and further resolves the call signaling information and media voice. The system can also be able to design appropriate rules to complete real-time reduction and presentation of specific categories of calls. Experimental results show that the system can parse and process real-time backbone of the VoIP call, and the results are presented accurately in the management interface, VoIP-based network traffic management and maintenance provide the necessary technical support.

Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network

Science.gov (United States)

Bhatia, Udit; Kumar, Devashish; Kodra, Evan; Ganguly, Auroop R.

2015-01-01

The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general. PMID:26536227

Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network.

Science.gov (United States)

Bhatia, Udit; Kumar, Devashish; Kodra, Evan; Ganguly, Auroop R

2015-01-01

The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general.

Network Science Based Quantification of Resilience Demonstrated on the Indian Railways Network.

Directory of Open Access Journals (Sweden)

Udit Bhatia

Full Text Available The structure, interdependence, and fragility of systems ranging from power-grids and transportation to ecology, climate, biology and even human communities and the Internet have been examined through network science. While response to perturbations has been quantified, recovery strategies for perturbed networks have usually been either discussed conceptually or through anecdotal case studies. Here we develop a network science based quantitative framework for measuring, comparing and interpreting hazard responses as well as recovery strategies. The framework, motivated by the recently proposed temporal resilience paradigm, is demonstrated with the Indian Railways Network. Simulations inspired by the 2004 Indian Ocean Tsunami and the 2012 North Indian blackout as well as a cyber-physical attack scenario illustrate hazard responses and effectiveness of proposed recovery strategies. Multiple metrics are used to generate various recovery strategies, which are simply sequences in which system components should be recovered after a disruption. Quantitative evaluation of these strategies suggests that faster and more efficient recovery is possible through network centrality measures. Optimal recovery strategies may be different per hazard, per community within a network, and for different measures of partial recovery. In addition, topological characterization provides a means for interpreting the comparative performance of proposed recovery strategies. The methods can be directly extended to other Large-Scale Critical Lifeline Infrastructure Networks including transportation, water, energy and communications systems that are threatened by natural or human-induced hazards, including cascading failures. Furthermore, the quantitative framework developed here can generalize across natural, engineered and human systems, offering an actionable and generalizable approach for emergency management in particular as well as for network resilience in general.

Friend suggestion in social network based on user log

Science.gov (United States)

Kaviya, R.; Vanitha, M.; Sumaiya Thaseen, I.; Mangaiyarkarasi, R.

2017-11-01

Simple friend recommendation algorithms such as similarity, popularity and social aspects is the basic requirement to be explored to methodically form high-performance social friend recommendation. Suggestion of friends is followed. No tags of character were followed. In the proposed system, we use an algorithm for network correlation-based social friend recommendation (NC-based SFR).It includes user activities like where one lives and works. A new friend recommendation method, based on network correlation, by considering the effect of different social roles. To model the correlation between different networks, we develop a method that aligns these networks through important feature selection. We consider by preserving the network structure for a more better recommendations so that it significantly improves the accuracy for better friend-recommendation.

SPECT detector system design based on embedded system

International Nuclear Information System (INIS)

Zhang Weizheng; Zhao Shujun; Zhang Lei; Sun Yuanling

2007-01-01

A single-photon emission computed tomography detector system based on embedded Linux designed. This system is composed of detector module, data acquisition module, ARM MPU module, network interface communication module and human machine interface module. Its software uses multithreading technology based on embedded Linux. It can achieve high speed data acquisition, real-time data correction and network data communication. It can accelerate the data acquisition and decrease the dead time. The accuracy and the stability of the system can be improved. (authors)

100 nm scale low-noise sensors based on aligned carbon nanotube networks: overcoming the fundamental limitation of network-based sensors

Science.gov (United States)

Lee, Minbaek; Lee, Joohyung; Kim, Tae Hyun; Lee, Hyungwoo; Lee, Byung Yang; Park, June; Jhon, Young Min; Seong, Maeng-Je; Hong, Seunghun

2010-02-01

Nanoscale sensors based on single-walled carbon nanotube (SWNT) networks have been considered impractical due to several fundamental limitations such as a poor sensitivity and small signal-to-noise ratio. Herein, we present a strategy to overcome these fundamental problems and build highly-sensitive low-noise nanoscale sensors simply by controlling the structure of the SWNT networks. In this strategy, we prepared nanoscale width channels based on aligned SWNT networks using a directed assembly strategy. Significantly, the aligned network-based sensors with narrower channels exhibited even better signal-to-noise ratio than those with wider channels, which is opposite to conventional random network-based sensors. As a proof of concept, we demonstrated 100 nm scale low-noise sensors to detect mercury ions with the detection limit of ~1 pM, which is superior to any state-of-the-art portable detection system and is below the allowable limit of mercury ions in drinking water set by most government environmental protection agencies. This is the first demonstration of 100 nm scale low-noise sensors based on SWNT networks. Considering the increased interests in high-density sensor arrays for healthcare and environmental protection, our strategy should have a significant impact on various industrial applications.

100 nm scale low-noise sensors based on aligned carbon nanotube networks: overcoming the fundamental limitation of network-based sensors

Energy Technology Data Exchange (ETDEWEB)

Lee, Minbaek; Lee, Joohyung; Kim, Tae Hyun; Lee, Hyungwoo; Lee, Byung Yang; Hong, Seunghun [Department of Physics and Astronomy, Seoul National University, Shilim-Dong, Kwanak-Gu, Seoul 151-742 (Korea, Republic of); Park, June; Seong, Maeng-Je [Department of Physics, Chung-Ang University, Heukseok-Dong, Dongjak-Gu, Seoul 156-756 (Korea, Republic of); Jhon, Young Min, E-mail: mseong@cau.ac.kr, E-mail: shong@phya.snu.ac.kr [Korea Institute of Science and Technology, Hawolgok-Dong, Seongbuk-Gu, Seoul 136-791 (Korea, Republic of)

2010-02-05

Nanoscale sensors based on single-walled carbon nanotube (SWNT) networks have been considered impractical due to several fundamental limitations such as a poor sensitivity and small signal-to-noise ratio. Herein, we present a strategy to overcome these fundamental problems and build highly-sensitive low-noise nanoscale sensors simply by controlling the structure of the SWNT networks. In this strategy, we prepared nanoscale width channels based on aligned SWNT networks using a directed assembly strategy. Significantly, the aligned network-based sensors with narrower channels exhibited even better signal-to-noise ratio than those with wider channels, which is opposite to conventional random network-based sensors. As a proof of concept, we demonstrated 100 nm scale low-noise sensors to detect mercury ions with the detection limit of {approx}1 pM, which is superior to any state-of-the-art portable detection system and is below the allowable limit of mercury ions in drinking water set by most government environmental protection agencies. This is the first demonstration of 100 nm scale low-noise sensors based on SWNT networks. Considering the increased interests in high-density sensor arrays for healthcare and environmental protection, our strategy should have a significant impact on various industrial applications.

100 nm scale low-noise sensors based on aligned carbon nanotube networks: overcoming the fundamental limitation of network-based sensors

International Nuclear Information System (INIS)

Lee, Minbaek; Lee, Joohyung; Kim, Tae Hyun; Lee, Hyungwoo; Lee, Byung Yang; Hong, Seunghun; Park, June; Seong, Maeng-Je; Jhon, Young Min

2010-01-01

Nanoscale sensors based on single-walled carbon nanotube (SWNT) networks have been considered impractical due to several fundamental limitations such as a poor sensitivity and small signal-to-noise ratio. Herein, we present a strategy to overcome these fundamental problems and build highly-sensitive low-noise nanoscale sensors simply by controlling the structure of the SWNT networks. In this strategy, we prepared nanoscale width channels based on aligned SWNT networks using a directed assembly strategy. Significantly, the aligned network-based sensors with narrower channels exhibited even better signal-to-noise ratio than those with wider channels, which is opposite to conventional random network-based sensors. As a proof of concept, we demonstrated 100 nm scale low-noise sensors to detect mercury ions with the detection limit of ∼1 pM, which is superior to any state-of-the-art portable detection system and is below the allowable limit of mercury ions in drinking water set by most government environmental protection agencies. This is the first demonstration of 100 nm scale low-noise sensors based on SWNT networks. Considering the increased interests in high-density sensor arrays for healthcare and environmental protection, our strategy should have a significant impact on various industrial applications.

Convolutional neural network-based classification system design with compressed wireless sensor network images.

Science.gov (United States)

Ahn, Jungmo; Park, JaeYeon; Park, Donghwan; Paek, Jeongyeup; Ko, JeongGil

2018-01-01

With the introduction of various advanced deep learning algorithms, initiatives for image classification systems have transitioned over from traditional machine learning algorithms (e.g., SVM) to Convolutional Neural Networks (CNNs) using deep learning software tools. A prerequisite in applying CNN to real world applications is a system that collects meaningful and useful data. For such purposes, Wireless Image Sensor Networks (WISNs), that are capable of monitoring natural environment phenomena using tiny and low-power cameras on resource-limited embedded devices, can be considered as an effective means of data collection. However, with limited battery resources, sending high-resolution raw images to the backend server is a burdensome task that has direct impact on network lifetime. To address this problem, we propose an energy-efficient pre- and post- processing mechanism using image resizing and color quantization that can significantly reduce the amount of data transferred while maintaining the classification accuracy in the CNN at the backend server. We show that, if well designed, an image in its highly compressed form can be well-classified with a CNN model trained in advance using adequately compressed data. Our evaluation using a real image dataset shows that an embedded device can reduce the amount of transmitted data by ∼71% while maintaining a classification accuracy of ∼98%. Under the same conditions, this process naturally reduces energy consumption by ∼71% compared to a WISN that sends the original uncompressed images.

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.

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.

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.

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

Directory of Open Access Journals (Sweden)