Search results for: Collaborative network

Authors: J. Augutis, R. Krikstolaitis, L. Martisauskas

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Recently global concerns for the energy security have steadily been on the increase and are expected to become a major issue over the next few decades. Energy security refers to a resilient energy system. This resilient system would be capable of withstanding threats through a combination of active, direct security measures and passive or more indirect measures such as redundancy, duplication of critical equipment, diversity in fuel, other sources of energy, and reliance on less vulnerable infrastructure. Threats and disruptions (disturbances) to one part of the energy system affect another. The paper presents methodology in theoretical background about energy system as an interconnected network and energy supply disturbances impact to the network. The proposed methodology uses a network flow approach to develop mathematical model of the energy system network as the system of nodes and arcs with energy flowing from node to node along paths in the network.

Keywords: Energy Security, Energy Supply Disturbances, Modeling of Energy System, Network Flow

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Authors: Efendi Zaenudin, Chien-Hung Huang, Ka-Lok Ng

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Essential genes play an important role in the survival of an organism. It has been shown that cancer-associated essential genes are genes necessary for cancer cell proliferation, where these genes are potential therapeutic targets. Also, it was demonstrated that mutations of the cancer-associated essential genes give rise to the resistance of immunotherapy for patients with tumors. In the present study, we focus on studying the biological effects of the essential genes from a network perspective. We hypothesize that one can analyze a biological molecular network by decomposing it into both three-node and four-node digraphs (subgraphs). These network subgraphs encode the regulatory interaction information among the network’s genetic elements. In this study, the frequency of occurrence of the subgraph-associated essential genes in a molecular network was quantified by using the statistical parameter, odds ratio. Biological effects of subgraph-associated essential genes are discussed. In summary, the subgraph approach provides a systematic method for analyzing molecular networks and it can capture useful biological information for biomedical research.

Keywords: Biological molecular networks, essential genes, graph theory, network subgraphs.

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Authors: Ekow A. Kwofie, Emmanuel K. Anto, Godfred Mensah

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In this paper, CYME Distribution software has been used to assess the impacts of solar Photovoltaic (PV) distributed generation (DG) plant on the Electricity Company of Ghana (ECG) 33 kV sub-transmission network at different PV penetration levels. As ECG begins to encourage DG PV interconnections within its network, there has been the need to assess the impacts on the sub-transmission losses and voltage contribution. In Tema, a city in Accra - Ghana, ECG has a 33 kV sub-transmission network made up of 20 No. 33 kV buses that was modeled. Three different locations were chosen: The source bus, a bus along the sub-transmission radial network and a bus at the tail end to determine the optimal location for DG PV interconnection. The optimal location was determined based on sub-transmission technical losses and voltage impact. PV capacities at different penetration levels were modeled at each location and simulations performed to determine the optimal PV penetration level. Interconnection at a bus along (or in the middle of) the sub-transmission network offered the highest benefits at an optimal PV penetration level of 80%. At that location, the maximum voltage improvement of 0.789% on the neighboring 33 kV buses and maximum loss reduction of 6.033% over the base case scenario were recorded. Hence, the optimal location for DG PV integration within the 33 kV sub-transmission utility network is at a bus along the sub-transmission radial network.

Keywords: Distributed generation photovoltaic, DG PV, optimal location, penetration level, sub-transmission network.

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Authors: G. Büyüközkan , O. Feyzioglu, Z. Vardaloglu

Abstract:

Collaborative planning, forecasting and replenishment (CPFR) coordinates the various supply chain management activities including production and purchase planning, demand forecasting and inventory replenishment between supply chain trading partners. This study proposes a systematic way of analyzing CPFR supporting factors using fuzzy cognitive map (FCM) approach. FCMs have proven particularly useful for solving problems in which a number of decision variables and uncontrollable variables are causally interrelated. Hence the FCMs of CPFR are created to show the relationships between the factors that influence on effective implementation of CPFR in the supply chain.

Keywords: Collaborative planning, forecasting and replenishment, fuzzy cognitive map, information sharing, decision synchronization, incentive alignment.

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Authors: Goran Djukanovic, Goran Popovic

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A special area in the study of Wireless Sensor Networks (WSNs) is how to move sensor nodes, as it expands the scope of application of wireless sensors and provides new opportunities to improve network performance. On the other side, it opens a set of new problems, especially if complete clusters are mobile. Node mobility can prolong the network lifetime. In such WSN, some nodes are possibly moveable or nomadic (relocated periodically), while others are static. This paper presents an idea of mobile, solar-powered CHs that relocate themselves inside clusters in such a way that the total energy consumption in the network reduces, and the lifetime of the network extends. Positioning of CHs is made in each round based on selfish herd hypothesis, where leader retreats to the center of gravity. Based on this idea, an algorithm, together with its modified version, has been presented and tested in this paper. Simulation results show that both algorithms have benefits in network lifetime, and prolongation of network stability period duration.

Keywords: CH-active algorithm, mobile cluster head, sensors, wireless sensor network.

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Authors: Nidhi Gupta, Sanjoy Das, Khushal Singh

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A Mobile Ad-hoc Network (MANET) is a self managing network consists of versatile nodes that are capable of communicating with each other without having any fixed infrastructure. These nodes may be routers and/or hosts. Due to this dynamic nature of the network, routing protocols are vulnerable to various kinds of attacks. The black hole attack is one of the conspicuous security threats in MANETs. As the route discovery process is obligatory and customary, attackers make use of this loophole to get success in their motives to destruct the network. In Black hole attack the packet is redirected to a node that actually does not exist in the network. Many researchers have proposed different techniques to detect and prevent this type of attack. In this paper, we have analyzed various routing protocols in this context. Further we have shown a critical comparison among various protocols. We have shown various routing metrics are required proper and significant analysis of the protocol.

Keywords: Black Hole, MANET, Performance Parameters, Routing Protocol.

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Authors: P. Latha, L. Ganesan, N. Ramaraj, P. V. Hari Venkatesh

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Motion detection is a basic operation in the selection of significant segments of the video signals. For an effective Human Computer Intelligent Interaction, the computer needs to recognize the motion and track the moving object. Here an efficient neural network system is proposed for motion detection from the static background. This method mainly consists of four parts like Frame Separation, Rough Motion Detection, Network Formation and Training, Object Tracking. This paper can be used to verify real time detections in such a way that it can be used in defense applications, bio-medical applications and robotics. This can also be used for obtaining detection information related to the size, location and direction of motion of moving objects for assessment purposes. The time taken for video tracking by this Neural Network is only few seconds.

Keywords: Frame separation, Correlation Network, Neural network training, Radial Basis Function, object tracking, Motion Detection.

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Authors: Anas Majeed, A. A. Zaidan, B. B. Zaidan, Laiha Mat Kiah

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WIMAX relay station mesh network has been approved by IEEE 802.16j as a standard to provide a highly data rate transmission, the RS was implemented to extend the coverage zone of the BS, for instance the MSs previously were out of the coverage of the BS they become in the coverage of the RS, therefore these MSs can have Admission control from the BS through the RS. This paper describe a problem in the mesh network Relay station, for instance the problem of how to serve the mobile stations (MSs) which are out of the Relay station coverage. This paper also proposed a solution for mobile stations out of the coverage of the WIMAX Relay stations mesh Network. Therefore Ad-hoc network defined as a solution by using its admission control schema and apply it on the mobiles inside and outside the Relay station coverage.

Keywords: WIMAX, relay station, mesh network, ad-hoc, WiFi, generic algorithm.

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Authors: Halabi Hasbullah, Irshad Ahmed Soomro, Jamalul-lail Ab Manan

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Vehicular Ad-hoc Network (VANET) is taking more attention in automotive industry due to the safety concern of human lives on roads. Security is one of the safety aspects in VANET. To be secure, network availability must be obtained at all times since availability of the network is critically needed when a node sends any life critical information to other nodes. However, it can be expected that security attacks are likely to increase in the coming future due to more and more wireless applications being developed and deployed onto the well-known expose nature of the wireless medium. In this respect, the network availability is exposed to many types of attacks. In this paper, Denial of Service (DOS) attack on network availability is presented and its severity level in VANET environment is elaborated. A model to secure the VANET from the DOS attacks has been developed and some possible solutions to overcome the attacks have been discussed.

Keywords: Vehicular Ad hoc Network (VANET); security;availability; security attack; Denial of Service (DOS).

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Authors: Svitov David, Alyamkin Sergey

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The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax.

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Authors: Feng-Chuan Pan, Fang-Yue Liu

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Hospitals in southern Hualien teamed with the Hypertension Joint Care Network. Working with the network, the team provided a special designed health education to the individual who had been identified as a hypertension patient in the outpatient department. Some metabolism improvements achieved. This is a retrospective study by purposively taking 106 patients from a hospital between 2008 and 2010. Records of before and after education intervention of the objects was collected and analyzed to see the how the intervention affected the patients- hypertension control via clinical parameter monitoring. The results showed that the clinical indicators, the LDL-C, the cholesterol and the systolic blood pressure were significantly improved. The study provides evidence for the effectiveness of the network in controlling hypertension.

Keywords: hypertension, joint care management network, cardiovascular diseases, metabolic syndrome.

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Authors: H. Soleimanimehr, M. J. Nategh , S. Amini

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Development of artificial neural network (ANN) for prediction of aluminum workpieces' surface roughness in ultrasonicvibration assisted turning (UAT) has been the subject of the present study. Tool wear as the main cause of surface roughness was also investigated. ANN was trained through experimental data obtained on the basis of full factorial design of experiments. Various influential machining parameters were taken into consideration. It was illustrated that a multilayer perceptron neural network could efficiently model the surface roughness as the response of the network, with an error less than ten percent. The performance of the trained network was verified by further experiments. The results of UAT were compared with the results of conventional turning experiments carried out with similar machining parameters except for the vibration amplitude whence considerable reduction was observed in the built-up edge and the surface roughness.

Keywords: Aluminum, Artificial Neural Network (ANN), BuiltupEdge, Surface Roughness, Tool Wear, Ultrasonic VibrationAssisted Turning (UAT).

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Authors: Kyoung-jae Kim, Hyunchul Ahn, Sangwon Jeong

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This study proposes a novel recommender system to provide the advertisements of context-aware services. Our proposed model is designed to apply a modified collaborative filtering (CF) algorithm with regard to the several dimensions for the personalization of mobile devices – location, time and the user-s needs type. In particular, we employ a classification rule to understand user-s needs type using a decision tree algorithm. In addition, we collect primary data from the mobile phone users and apply them to the proposed model to validate its effectiveness. Experimental results show that the proposed system makes more accurate and satisfactory advertisements than comparative systems.

Keywords: Location-based advertisement, Recommender system, Collaborative filtering, User needs type, Mobile user.

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Authors: Kuen-Long Leu, Yung-Yuan Chen, Chin-Long Wey, Jwu-E Chen, Chung-Hsien Hsu

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The increasing importance of FlexRay systems in automotive domain inspires unceasingly relative researches. One primary issue among researches is to verify the reliability of FlexRay systems either from protocol aspect or from system design aspect. However, research rarely discusses the effect of network topology on the system reliability. In this paper, we will illustrate how to model the reliability of FlexRay systems with various network topologies by a well-known probabilistic reasoning technology, Bayesian Network. In this illustration, we especially investigate the effectiveness of error containment built in star topology and fault-tolerant midpoint synchronization algorithm adopted in FlexRay communication protocol. Through a FlexRay steer-by-wire case study, the influence of different topologies on the failure probability of the FlexRay steerby- wire system is demonstrated. The notable value of this research is to show that the Bayesian Network inference is a powerful and feasible method for the reliability assessment of FlexRay systems.

Keywords: Bayesian Network, FlexRay, fault tolerance, network topology, reliability.

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Authors: Kai Qian, Ming Yang, Minzhe Guo, Prabir Bhattacharya, Lixin Tao

Abstract:

Computer network courses are essential parts of college computer science curriculum and hands-on networking experience is well recognized as an effective approach to help students understand better about the network concepts, the layered architecture of network protocols, and the dynamics of the networks. However, existing networking labs are usually server-based and relatively cumbersome, which require a certain level of specialty and resource to set up and maintain the lab environment. Many universities/colleges lack the resources and build-ups in this field and have difficulty to provide students with hands-on practice labs. A new affordable and easily-adoptable approach to networking labs is desirable to enhance network teaching and learning. In addition, current network labs are short on providing hands-on practice for modern wireless and mobile network learning. With the prevalence of smart mobile devices, wireless and mobile network are permeating into various aspects of our information society. The emerging and modern mobile technology provides computer science students with more authentic learning experience opportunities especially in network learning. A mobile device based hands-on labware can provide an excellent ‘real world’ authentic learning environment for computer network especially for wireless network study. In this paper, we present our mobile device-based hands-on labware (series of lab module) for computer network learning which is guided by authentic learning principles to immerse students in a real world relevant learning environment. We have been using this labware in teaching computer network, mobile security, and wireless network classes. The student feedback shows that students can learn more when they have hands-on authentic learning experience. 

Keywords: Mobile computing, android, network, labware.

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Authors: Kang Won Lee, Jung Won Lee

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Characterizing the network flow is of fundamental importance to understand the complex dynamics of networks. And passenger flow characteristics of the subway network are very relevant for an effective transportation management in urban cities. In this study, passenger flow of Seoul metropolitan subway network is investigated and characterized through statistical analysis. Traditional betweenness centrality measure considers only topological structure of the network and ignores the transportation factors. This paper proposes a weighted betweenness centrality measure that incorporates monthly passenger flow volume. We apply the proposed measure on the Seoul metropolitan subway network involving 493 stations and 16 lines. Several interesting insights about the network are derived from the new measures. Using Kolmogorov-Smirnov test, we also find out that monthly passenger flow between any two stations follows a power-law distribution and other traffic characteristics such as congestion level and throughflow traffic follow exponential distribution.

Keywords: Betweenness centrality, correlation coefficient, power-law distribution, Korea traffic data base.

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Authors: Saman M. Abdulla, Najla B. Al-Dabagh, Omar Zakaria

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The aim of this article is to explain how features of attacks could be extracted from the packets. It also explains how vectors could be built and then applied to the input of any analysis stage. For analyzing, the work deploys the Feedforward-Back propagation neural network to act as misuse intrusion detection system. It uses ten types if attacks as example for training and testing the neural network. It explains how the packets are analyzed to extract features. The work shows how selecting the right features, building correct vectors and how correct identification of the training methods with nodes- number in hidden layer of any neural network affecting the accuracy of system. In addition, the work shows how to get values of optimal weights and use them to initialize the Artificial Neural Network.

Keywords: Artificial Neural Network, Attack Features, MisuseIntrusion Detection System, Training Parameters.

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Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

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The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and the snapshot and hierarchical index are used in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: Agent, network backup system, three architecture model, NSBS.

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Authors: S. Swapna Kumar

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A Vehicular Ad-Hoc Network (VANET) is a mobile Ad-Hoc Network that provides connectivity moving device to fixed equipments. Such type of device is equipped with vehicle provides safety for the passengers. In the recent research areas of traffic management there observed the wide scope of design of new methodology of extension of wireless sensor networks and ad-hoc network principal for development of VANET technology. This paper provides the wide research view of the VANET and MANET concept for the researchers to contribute the better optimization technique for the development of effective and fast atomization technique for the large size of data exchange in this complex networks.

Keywords: Ad-Hoc, MANET, Sensors, Security, VANET

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Authors: N. Mahendran, R. Priya

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The mobile cloud computing (MCC) with wireless sensor networks (WSNs) technology gets more attraction by research scholars because its combines the sensors data gathering ability with the cloud data processing capacity. This approach overcomes the limitation of data storage capacity and computational ability of sensor nodes. Finally, the stored data are sent to the mobile users when the user sends the request. The most of the integrated sensor-cloud schemes fail to observe the following criteria: 1) The mobile users request the specific data to the cloud based on their present location. 2) Power consumption since most of them are equipped with non-rechargeable batteries. Mostly, the sensors are deployed in hazardous and remote areas. This paper focuses on above observations and introduces an approach known as collaborative location-based sleep scheduling (CLSS) scheme. Both awake and asleep status of each sensor node is dynamically devised by schedulers and the scheduling is done purely based on the of mobile users’ current location; in this manner, large amount of energy consumption is minimized at WSN. CLSS work depends on two different methods; CLSS1 scheme provides lower energy consumption and CLSS2 provides the scalability and robustness of the integrated WSN.

Keywords: Sleep scheduling, mobile cloud computing, wireless sensor network, integration, location, network lifetime.

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Authors: Khin Thanda Soe

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A model to identify the lifetime of target tracking wireless sensor network is proposed. The model is a static clusterbased architecture and aims to provide two factors. First, it is to increase the lifetime of target tracking wireless sensor network. Secondly, it is to enable good localization result with low energy consumption for each sensor in the network. The model consists of heterogeneous sensors and each sensing member node in a cluster uses two operation modes–active mode and sleep mode. The performance results illustrate that the proposed architecture consumes less energy and increases lifetime than centralized and dynamic clustering architectures, for target tracking sensor network.

Keywords: Network lifetime, Target Localization, TargetTracking, Wireless Sensor Networks.

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Authors: Leong Lee, Jennifer Leopold, Julia Albath, Alton Coalter

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As more people from non-technical backgrounds are becoming directly involved with large-scale ontology development, the focal point of ontology research has shifted from the more theoretical ontology issues to problems associated with the actual use of ontologies in real-world, large-scale collaborative applications. Recently the National Science Foundation funded a large collaborative ontology development project for which a new formal ontology model, the Ontology Abstract Machine (OAM), was developed to satisfy some unique functional and data representation requirements. This paper introduces the OAM model and the related algorithms that enable maintenance of an ontology that supports node-based user access. The successful software implementation of the OAM model and its subsequent acceptance by a large research community proves its validity and its real-world application value.

Keywords: Ontology, Abstract Machine, Ontology Editor, WebbasedOntology Management System.

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Authors: Swapnil Singh, Sanjoy Das

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Mobile Ad-Hoc Network (MANET) is a network without infrastructure dynamically formed by autonomous system of mobile nodes that are connected via wireless links. Mobile nodes communicate with each other on the fly. In this network each node also acts as a router. The battery power and the bandwidth are very scarce resources in this network. The network lifetime and connectivity of nodes depend on battery power. Therefore, energy is a valuable constraint which should be efficiently used. In this paper we survey various energy efficient routing protocols. The energy efficient routing protocols are classified on the basis of approaches they use to minimize the energy consumption. The purpose of this paper is to facilitate the research work and combine the existing solution and to develop a more energy efficient routing mechanism.

Keywords: Delaunay Triangulation, deployment, energy efficiency, MANET.

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Authors: Shehzad Ashraf Ch., Aftab Ahmed Khan, Zahid Mehmood, Muhammad Ahsan Habib, Qasim Mehmood

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Energy efficiency is the key requirement in wireless sensor network as sensors are small, cheap and are deployed in very large number in a large geographical area, so there is no question of replacing the batteries of the sensors once deployed. Different ways can be used for efficient energy transmission including Multi-Hop algorithms, collaborative communication, cooperativecommunication, Beam- forming, routing algorithm, phase, frequency and time synchronization. The paper reviews the need for time synchronization and proposed a BFS based synchronization algorithm to achieve energy efficiency. The efficiency of our protocol has been tested and verified by simulation

Keywords: time synchronization, sensor networks, energy efficiency, breadth first search

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Authors: Anita S. Gangal, P. K. Kalra, D. S. Chauhan

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The backpropagation algorithm in general employs quadratic error function. In fact, most of the problems that involve minimization employ the Quadratic error function. With alternative error functions the performance of the optimization scheme can be improved. The new error functions help in suppressing the ill-effects of the outliers and have shown good performance to noise. In this paper we have tried to evaluate and compare the relative performance of complex valued neural network using different error functions. During first simulation for complex XOR gate it is observed that some error functions like Absolute error, Cauchy error function can replace Quadratic error function. In the second simulation it is observed that for some error functions the performance of the complex valued neural network depends on the architecture of the network whereas with few other error functions convergence speed of the network is independent of architecture of the neural network.

Keywords: Complex backpropagation algorithm, complex errorfunctions, complex valued neural network, split activation function.

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Authors: M. Govindarajan, R. M. Chandrasekaran

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Text Mining is around applying knowledge discovery techniques to unstructured text is termed knowledge discovery in text (KDT), or Text data mining or Text Mining. In Neural Network that address classification problems, training set, testing set, learning rate are considered as key tasks. That is collection of input/output patterns that are used to train the network and used to assess the network performance, set the rate of adjustments. This paper describes a proposed back propagation neural net classifier that performs cross validation for original Neural Network. In order to reduce the optimization of classification accuracy, training time. The feasibility the benefits of the proposed approach are demonstrated by means of five data sets like contact-lenses, cpu, weather symbolic, Weather, labor-nega-data. It is shown that , compared to exiting neural network, the training time is reduced by more than 10 times faster when the dataset is larger than CPU or the network has many hidden units while accuracy ('percent correct') was the same for all datasets but contact-lences, which is the only one with missing attributes. For contact-lences the accuracy with Proposed Neural Network was in average around 0.3 % less than with the original Neural Network. This algorithm is independent of specify data sets so that many ideas and solutions can be transferred to other classifier paradigms.

Keywords: Back propagation, classification accuracy, textmining, time complexity.

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Authors: Mabel Ortiz, Claudio Díaz

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This paper explores Chilean pre-service teachers' perceptions about the provision of corrective feedback in a wiki environment during the collaborative writing of an argumentative essay. After conducting a semi-structured interview on 22 participants, the data were processed through the content analysis technique. The results show that students have positive perceptions about corrective feedback, provided through a wiki virtual environment, which in turn facilitates feedback provision and impacts language learning effectively. Some of the positive perceptions about virtual feedback refer to permanent access, efficiency, simultaneous revision and immediacy. It would then be advisable to integrate wiki-based feedback as a methodology for the language classroom and collaborative writing tasks.

Keywords: Argumentative essay, focused corrective feedback, perception, wiki environment.

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps.

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Authors: E. Ahvar, M. Fathy

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Ad hoc networks are characterized by multihop wireless connectivity, frequently changing network topology and the need for efficient dynamic routing protocols. We compare the performance of three routing protocols for mobile ad hoc networks: Dynamic Source Routing (DSR) , Ad Hoc On-Demand Distance Vector Routing (AODV), location-aided routing(LAR1).The performance differentials are analyzed using varying network load, mobility, and network size. We simulate protocols with GLOMOSIM simulator. Based on the observations, we make recommendations about when the performance of either protocol can be best.

Keywords: Ad hoc Network , Glomosim , routing protocols.

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Authors: F. Rasi Maezabadi, M. Masdari, M. R. Soltani

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Series of experimental tests were conducted on a section of a 660 kW wind turbine blade to measure the pressure distribution of this model oscillating in plunging motion. In order to minimize the amount of data required to predict aerodynamic loads of the airfoil, a General Regression Neural Network, GRNN, was trained using the measured experimental data. The network once proved to be accurate enough, was used to predict the flow behavior of the airfoil for the desired conditions. Results showed that with using a few of the acquired data, the trained neural network was able to predict accurate results with minimal errors when compared with the corresponding measured values. Therefore with employing this trained network the aerodynamic coefficients of the plunging airfoil, are predicted accurately at different oscillation frequencies, amplitudes, and angles of attack; hence reducing the cost of tests while achieving acceptable accuracy.

Keywords: Airfoil, experimental, GRNN, Neural Network, Plunging.

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