Search results for: patronage network
4693 An intelligent Troubleshooting System and Performance Evaluator for Computer Network
Authors: Iliya Musa Adamu
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This paper seeks to develop an expert system that would troubleshoot computer network and evaluate the network system performance so as to reduce the workload on technicians and increase the efficiency and effectiveness of solutions proffered to computer network problems. The platform of the system was developed using ASP.NET, whereas the codes are implemented in Visual Basic and integrated with SQL Server 2005. The knowledge base was represented using production rule, whereas the searching method that was used in developing the network troubleshooting expert system is the forward-chaining-rule-based-system. This software tool offers the advantage of providing an immediate solution to most computer network problems encountered by computer users.Keywords: expert system, forward chaining rule based system, network, troubleshooting
Procedia PDF Downloads 6374692 Key Technologies and Evolution Strategies for Computing Force Bearer Network
Authors: Zhaojunfeng
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Driven by the national policy of "East Data and Western Calculation", the computing first network will attract a new wave of development. As the foundation of the development of the computing first network, the computing force bearer network has become the key direction of technology research and development in the industry. This article will analyze typical computing force application scenarios and bearing requirements and sort out the SLA indicators of computing force applications. On this basis, this article carries out research and discussion on the key technologies of computing force bearer network in a slice packet network, and finally, gives evolution policy for SPN computing force bearer network to support the development of SPN computing force bearer network technology and network deployment.Keywords: component-computing force bearing, bearing requirements of computing force application, dual-SLA indicators for computing force applications, SRv6, evolution strategies
Procedia PDF Downloads 1264691 Optimizing the Probabilistic Neural Network Training Algorithm for Multi-Class Identification
Authors: Abdelhadi Lotfi, Abdelkader Benyettou
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In this work, a training algorithm for probabilistic neural networks (PNN) is presented. The algorithm addresses one of the major drawbacks of PNN, which is the size of the hidden layer in the network. By using a cross-validation training algorithm, the number of hidden neurons is shrunk to a smaller number consisting of the most representative samples of the training set. This is done without affecting the overall architecture of the network. Performance of the network is compared against performance of standard PNN for different databases from the UCI database repository. Results show an important gain in network size and performance.Keywords: classification, probabilistic neural networks, network optimization, pattern recognition
Procedia PDF Downloads 2554690 Universality and Synchronization in Complex Quadratic Networks
Authors: Anca Radulescu, Danae Evans
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The relationship between a network’s hardwiring and its emergent dynamics are central to neuroscience. We study the principles of this correspondence in a canonical setup (in which network nodes exhibit well-studied complex quadratic dynamics), then test their universality in biological networks. By extending methods from discrete dynamics, we study the effects of network connectivity on temporal patterns, encapsulating long-term behavior into the rich topology of network Mandelbrot sets. Then elements of fractal geometry can be used to predict and classify network behavior.Keywords: canonical model, complex dynamics, dynamic networks, fractals, Mandelbrot set, network connectivity
Procedia PDF Downloads 3014689 Identification of Bayesian Network with Convolutional Neural Network
Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz
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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference
Procedia PDF Downloads 1684688 An Adjusted Network Information Criterion for Model Selection in Statistical Neural Network Models
Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi
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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function
Procedia PDF Downloads 5594687 Fog Computing- Network Based Computing
Authors: Navaneeth Krishnan, Chandan N. Bhagwat, Aparajit P. Utpat
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Cloud Computing provides us a means to upload data and use applications over the internet. As the number of devices connecting to the cloud grows, there is undue pressure on the cloud infrastructure. Fog computing or Network Based Computing or Edge Computing allows to move a part of the processing in the cloud to the network devices present along the node to the cloud. Therefore the nodes connected to the cloud have a better response time. This paper proposes a method of moving the computation from the cloud to the network by introducing an android like appstore on the networking devices.Keywords: cloud computing, fog computing, network devices, appstore
Procedia PDF Downloads 3784686 Time Synchronization between the eNBs in E-UTRAN under the Asymmetric IP Network
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In this paper, we present a method for a time synchronization between the two eNodeBs (eNBs) in E-UTRAN (Evolved Universal Terrestrial Radio Access) network. The two eNBs are cooperating in so-called inter eNB CA (Carrier Aggregation) case and connected via asymmetrical IP network. We solve the problem by using broadcasting signals generated in E-UTRAN as synchronization signals. The results show that the time synchronization with the proposed method is possible with the error significantly less than 1 ms which is sufficient considering the time transmission interval is 1 ms in E-UTRAN. This makes this method (with low complexity) more suitable than Network Time Protocol (NTP) in the mobile applications with generated broadcasting signals where time synchronization in asymmetrical network is required.Keywords: IP scheduled throughput, E-UTRAN, Evolved Universal Terrestrial Radio Access Network, NTP, Network Time Protocol, assymetric network, delay
Procedia PDF Downloads 3564685 Value Co-Creation Model for Relationships Management
Authors: Kolesnik Nadezda A.
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The research aims to elaborate inter-organizational network relationships management model to maximize value co-creation. We propose a network management framework that requires evaluation of network partners with respect to their position and role in network; and elaboration of appropriate relationship development strategy with partners in network. Empirical research and approval is based on the case study method, including structured in-depth interviews with the companies from b2b market.Keywords: inter-organizational networks, value co-creation, model, B2B market
Procedia PDF Downloads 4504684 Modelling the Education Supply Chain with Network Data Envelopment Analysis
Authors: Sourour Ramzi, Claudia Sarrico
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Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.Keywords: supply chain, education, data envelopment analysis, network DEA
Procedia PDF Downloads 3634683 Orphan Node Inclusion Protocol for Wireless Sensor Network
Authors: Sandeep Singh Waraich
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Wireless sensor network (WSN ) consists of a large number of sensor nodes. The disparity in their energy consumption usually lead to the loss of equilibrium in wireless sensor network which may further results in an energy hole problem in wireless network. In this paper, we have considered the inclusion of orphan nodes which usually remain unutilized as intermediate nodes in multi-hop routing. The Orphan Node Inclusion (ONI) Protocol lets the cluster member to bring the orphan nodes into their clusters, thereby saving important resources and increasing network lifetime in critical applications of WSN.Keywords: wireless sensor network, orphan node, clustering, ONI protocol
Procedia PDF Downloads 4134682 Quoting Jobshops Due Dates Subject to Exogenous Factors in Developing Nations
Authors: Idris M. Olatunde, Kareem B.
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In manufacturing systems, especially job shops, service performance is a key factor that determines customer satisfaction. Service performance depends not only on the quality of the output but on the delivery lead times as well. Besides product quality enhancement, delivery lead time must be minimized for optimal patronage. Quoting accurate due dates is sine quo non for job shop operational survival in a global competitive environment. Quoting accurate due dates in job shops has been a herculean task that nearly defiled solutions from many methods employed due to complex jobs routing nature of the system. This class of NP-hard problems possessed no rigid algorithms that can give an optimal solution. Jobshop operational problem is more complex in developing nations due to some peculiar factors. Operational complexity in job shops emanated from political instability, poor economy, technological know-how, and the non-promising socio-political environment. The mentioned exogenous factors were hardly considered in the previous studies on scheduling problem related to due date determination in job shops. This study has filled the gap created in the past studies by developing a dynamic model that incorporated the exogenous factors for accurate determination of due dates for varying jobs complexity. Real data from six job shops selected from the different part of Nigeria, were used to test the efficacy of the model, and the outcomes were analyzed statistically. The results of the analyzes showed that the model is more promising in determining accurate due dates than the traditional models deployed by many job shops in terms of patronage and lead times minimization.Keywords: due dates prediction, improved performance, customer satisfaction, dynamic model, exogenous factors, job shops
Procedia PDF Downloads 4104681 Simulation Analysis of Optical Add Drop Multiplexer in a Ring Network
Authors: Surinder Singh, Meenakshi
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In this paper MZI-FBG based optical add drop multiplexer is designed and its performance is analyzed in the ring network. In the ring network nodes are composed of optical add drop multiplexer, transmitter and receiver. OADM is used to add or drop any frequency at intermediate nodes without affecting other channels. In this paper the performance of the ring network is carried out by varying various kinds of fiber with or without amplifiers.Keywords: OADM, ring network, MZI-FBG, transmitter
Procedia PDF Downloads 5664680 A Tutorial on Network Security: Attacks and Controls
Authors: Belbahi Ahlam
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With the phenomenal growth in the Internet, network security has become an integral part of computer and information security. In order to come up with measures that make networks more secure, it is important to learn about the vulnerabilities that could exist in a computer network and then have an understanding of the typical attacks that have been carried out in such networks. The first half of this paper will expose the readers to the classical network attacks that have exploited the typical vulnerabilities of computer networks in the past and solutions that have been adopted since then to prevent or reduce the chances of some of these attacks. The second half of the paper will expose the readers to the different network security controls including the network architecture, protocols, standards and software/ hardware tools that have been adopted in modern day computer networks.Keywords: network security, attacks and controls, computer and information, solutions
Procedia PDF Downloads 4494679 End-to-End Control and Management of Multi-AS Virtual Service Networks Using SDN and Autonomic Computing Architecture
Authors: Yong Xue, Daniel A. Menascé
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Automated and end-to-end network resource management and provisioning for virtual service networks in a multiple autonomous systems (a.k.a multi-AS) environment is a challenging and open problem. This paper proposes a novel, scalable and interoperable high-level architecture that incorporates a number of emerging enabling technologies including Software Defined Network (SDN), Network Function Virtualization (NFV), Service Oriented Architecture (SOA), and Autonomic Computing. The proposed architecture can be used to not only automate network resource management and provisioning for virtual service networks across multiple autonomous substrate networks, but also provide an adaptive capability for achieving optimal network resource management and maintaining network-level end-to-end network performance as well. The paper argues that this SDN and autonomic computing based architecture lays a solid foundation that can facilitate the development of the future Internet based on the pluralistic paradigm.Keywords: virtual network, software defined network, virtual service network, adaptive resource management, SOA, multi-AS, inter-domain
Procedia PDF Downloads 5224678 Implementation of an Associative Memory Using a Restricted Hopfield Network
Authors: Tet H. Yeap
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An analog restricted Hopfield Network is presented in this paper. It consists of two layers of nodes, visible and hidden nodes, connected by directional weighted paths forming a bipartite graph with no intralayer connection. An energy or Lyapunov function was derived to show that the proposed network will converge to stable states. By introducing hidden nodes, the proposed network can be trained to store patterns and has increased memory capacity. Training to be an associative memory, simulation results show that the associative memory performs better than a classical Hopfield network by being able to perform better memory recall when the input is noisy.Keywords: restricted Hopfield network, Lyapunov function, simultaneous perturbation stochastic approximation
Procedia PDF Downloads 1254677 Designing Directed Network with Optimal Controllability
Authors: Liang Bai, Yandong Xiao, Haorang Wang, Songyang Lao
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The directedness of links is crucial to determine the controllability in complex networks. Even the edge directions can determine the controllability of complex networks. Obviously, for a given network, we wish to design its edge directions that make this network approach the optimal controllability. In this work, we firstly introduce two methods to enhance network by assigning edge directions. However, these two methods could not completely mitigate the negative effects of inaccessibility and dilations. Thus, to approach the optimal network controllability, the edge directions must mitigate the negative effects of inaccessibility and dilations as much as possible. Finally, we propose the edge direction for optimal controllability. The optimal method has been found to be successfully useful on real-world and synthetic networks.Keywords: complex network, dynamics, network control, optimization
Procedia PDF Downloads 1754676 System Survivability in Networks
Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez
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We consider the problem of attacks on networks. We define the concept of system survivability in networks in the presence of intelligent threats. Our setting of the problem assumes a flow to be sent from one source node to a destination node. The attacker attempts to disable the network by preventing the flow to reach its destination while the defender attempts to identify the best path-set to use to maximize the chance of arrival of the flow to the destination node. Our concept is shown to be different from the classical concept of network reliability. We distinguish two types of network survivability related to the defender and to the attacker of the network, respectively. We prove that the defender-based-network survivability plays the role of a lower bound while the attacker-based-network survivability plays the role of an upper bound of network reliability. We also prove that both concepts almost never agree nor coincide with network reliability. Moreover, we use the shortest-path problem to determine the defender-based-network survivability and the min-cut problem to determine the attacker-based-network survivability. We extend the problem to a variety of models including the minimum-spanning-tree problem and the multiple source-/destination-network problems.Keywords: defense/attack strategies, information, networks, reliability, survivability
Procedia PDF Downloads 3834675 Impact Assessment of Information Communication, Network Providers, Teledensity, and Consumer Complaints on Gross Domestic Products
Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke
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The study used secondary data from foreign and local organizations to explore major challenges and opportunities abound in Information Communication. The study aimed at exploring the tie between tele density (network coverage area) and the number of network subscriptions, probing if the degree of consumer complaints varies significantly among network providers, and assessing if network subscriptions do significantly influence the sector’s GDP contribution. Methods used for data analysis include Pearson product-moment correlation and regression analysis, and the Analysis of Variance (ANOVA) as well. At a two-tailed test of 0.05 confidence level, the results of findings established about 85.6% of network subscriptions were explained by tele density (network coverage area), and the number of network subscriptions; Consumer Complaints’ degree varied significantly among network providers as 80.158291 (F calculated) > 3.490295 (F critical) with very high confidence associated p-value = 0.000000 which is < 0.05; and finally, 65% of the nation’s GDP was explained by network subscription to show a high association.Keywords: tele density, subscription, network coverage, information communication, consumer
Procedia PDF Downloads 304674 Multimodal Convolutional Neural Network for Musical Instrument Recognition
Authors: Yagya Raj Pandeya, Joonwhoan Lee
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The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean
Procedia PDF Downloads 2084673 Design of Distribution Network for Gas Cylinders in Jordan
Authors: Hazem J. Smadi
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Performance of a supply chain is directly related to a distribution network that entails the location of storing materials or products and how products are delivered to the end customer through different stages in the supply chain. This study analyses the current distribution network used for delivering gas cylinders to end customer in Jordan. Evaluation of current distribution has been conducted across customer service components. A modification on the current distribution network in terms of central warehousing in each city in the country improves the response time and customer experience.Keywords: distribution network, gas cylinder, Jordan, supply chain
Procedia PDF Downloads 4564672 A Survey of Novel Opportunistic Routing Protocols in Mobile Ad Hoc Networks
Authors: R. Poonkuzhali, M. Y. Sanavullah, M. R. Gurupriya
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Opportunistic routing is used, where the network has the features like dynamic topology changes and intermittent network connectivity. In Delay Tolerant network or Disruption tolerant network opportunistic forwarding technique is widely used. The key idea of opportunistic routing is selecting forwarding nodes to forward data and coordination among these nodes to avoid duplicate transmissions. This paper gives the analysis of pros and cons of various opportunistic routing techniques used in MANET.Keywords: ETX, opportunistic routing, PSR, throughput
Procedia PDF Downloads 4884671 Software-Defined Networks in Utility Power Networks
Authors: Ava Salmanpour, Hanieh Saeedi, Payam Rouhi, Elahe Hamzeil, Shima Alimohammadi, Siamak Hossein Khalaj, Mohammad Asadian
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Software-defined network (SDN) is a network architecture designed to control network using software application in a central manner. This ability enables remote control of the whole network regardless of the network technology. In fact, in this architecture network intelligence is separated from physical infrastructure, it means that required network components can be implemented virtually using software applications. Today, power networks are characterized by a high range of complexity with a large number of intelligent devices, processing both huge amounts of data and important information. Therefore, reliable and secure communication networks are required. SDNs are the best choice to meet this issue. In this paper, SDN networks capabilities and characteristics will be reviewed and different basic controllers will be compared. The importance of using SDNs to escalate efficiency and reliability in utility power networks is going to be discussed and the comparison between the SDN-based power networks and traditional networks will be explained.Keywords: software-defined network, SDNs, utility network, open flow, communication, gas and electricity, controller
Procedia PDF Downloads 1064670 The Theotokos of the Messina Missal as a Byzantine Icon in Norman Sicily: A Study on Patronage and Devotion
Authors: Jesus Rodriguez Viejo
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The aim of this paper is to study cross-cultural interactions between the West and Byzantium, in the fields of art and religion, by analyzing the decoration of one luxury manuscript. The Spanish National Library is home to one of the most extraordinary examples of illuminated manuscript production of Norman Sicily – the Messina Missal. Dating from the late twelfth century, this liturgical book was the result of the intense activity of artistic patronage of an Englishman, Richard Palmer. Appointed bishop of the Sicilian city in the second half of the century, Palmer set a painting workshop attached to his cathedral. The illuminated manuscripts produced there combine a clear Byzantine iconographic language with a myriad of elements imported from France, such as a large number of decorated initials. The most remarkable depiction contained in the Missal is that of the Theotokos (fol. 80r). Its appearance immediately recalls portative Byzantine icons of the Mother of God in South Italy and Byzantium and implies the intervention of an artist familiar with icon painting. The richness of this image is a clear proof of the prestige that Byzantine art enjoyed in the island after the Norman takeover. The production of the school of Messina under Richard Palmer could be considered a counterpart in the field of manuscript illumination of the court art of the Sicilian kings in Palermo and the impressive commissions for the cathedrals of Monreale and Cefalù. However, the ethnic composition of Palmer’s workshop has never been analyzed and therefore, we intend to shed light on the permanent presence of Greek-speaking artists in Norman Messina. The east of the island was the last stronghold of the Greeks and soon after the Norman conquest, the previous exchanges between the cities of this territory and Byzantium restarted again, mainly by way of trade. Palmer was not a Norman statesman, but a churchman and his love for religion and culture prevailed over the wars and struggles for power of the Sicilian kingdom in the central Mediterranean. On the other hand, the representation of the Theotokos can prove that Eastern devotional approaches to images were still common in the east of the island more than a century after the collapse of Byzantine rule. Local Norman lords repeatedly founded churches devoted to Greek saints and medieval Greek-speaking authors were widely copied in Sicilian scriptoria. The Madrid Missal and its Theotokos are doubtless the product of Western initiative but in a land culturally dominated by Byzantium. Westerners, such as Palmer and his circle, could have been immersed in this Hellenophile culture and therefore, naturally predisposed to perform prayers and rituals, in both public and private contexts, linked to ideas and practices of Greek origin, such as the concept of icon.Keywords: history of art, byzantine art, manuscripts, norman sicily, messina, patronage, devotion, iconography
Procedia PDF Downloads 3404669 Data Clustering in Wireless Sensor Network Implemented on Self-Organization Feature Map (SOFM) Neural Network
Authors: Krishan Kumar, Mohit Mittal, Pramod Kumar
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Wireless sensor network is one of the most promising communication networks for monitoring remote environmental areas. In this network, all the sensor nodes are communicated with each other via radio signals. The sensor nodes have capability of sensing, data storage and processing. The sensor nodes collect the information through neighboring nodes to particular node. The data collection and processing is done by data aggregation techniques. For the data aggregation in sensor network, clustering technique is implemented in the sensor network by implementing self-organizing feature map (SOFM) neural network. Some of the sensor nodes are selected as cluster head nodes. The information aggregated to cluster head nodes from non-cluster head nodes and then this information is transferred to base station (or sink nodes). The aim of this paper is to manage the huge amount of data with the help of SOM neural network. Clustered data is selected to transfer to base station instead of whole information aggregated at cluster head nodes. This reduces the battery consumption over the huge data management. The network lifetime is enhanced at a greater extent.Keywords: artificial neural network, data clustering, self organization feature map, wireless sensor network
Procedia PDF Downloads 5074668 Design and Implementation of a Cross-Network Security Management System
Authors: Zhiyong Shan, Preethi Santhanam, Vinod Namboodiri, Rajiv Bagai
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In recent years, the emerging network worms and attacks have distributive characteristics, which can spread globally in a very short time. Security management crossing networks to co-defense network-wide attacks and improve the efficiency of security administration is urgently needed. We propose a hierarchical distributed network security management system (HD-NSMS), which can integrate security management across multiple networks. First, we describe the system in macrostructure and microstructure; then discuss three key problems when building HD-NSMS: device model, alert mechanism, and emergency response mechanism; lastly, we describe the implementation of HD-NSMS. The paper is valuable for implementing NSMS in that it derives from a practical network security management system (NSMS).Keywords: network security management, device organization, emergency response, cross-network
Procedia PDF Downloads 1614667 Generalization of Clustering Coefficient on Lattice Networks Applied to Criminal Networks
Authors: Christian H. Sanabria-Montaña, Rodrigo Huerta-Quintanilla
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A lattice network is a special type of network in which all nodes have the same number of links, and its boundary conditions are periodic. The most basic lattice network is the ring, a one-dimensional network with periodic border conditions. In contrast, the Cartesian product of d rings forms a d-dimensional lattice network. An analytical expression currently exists for the clustering coefficient in this type of network, but the theoretical value is valid only up to certain connectivity value; in other words, the analytical expression is incomplete. Here we obtain analytically the clustering coefficient expression in d-dimensional lattice networks for any link density. Our analytical results show that the clustering coefficient for a lattice network with density of links that tend to 1, leads to the value of the clustering coefficient of a fully connected network. We developed a model on criminology in which the generalized clustering coefficient expression is applied. The model states that delinquents learn the know-how of crime business by sharing knowledge, directly or indirectly, with their friends of the gang. This generalization shed light on the network properties, which is important to develop new models in different fields where network structure plays an important role in the system dynamic, such as criminology, evolutionary game theory, econophysics, among others.Keywords: clustering coefficient, criminology, generalized, regular network d-dimensional
Procedia PDF Downloads 4004666 Retaining Users in a Commercially-Supported Social Network
Authors: Sasiphan Nitayaprapha
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A commercially-supported social network has become an emerging channel for an organization to communicate with and provide services to customers. The success of the commercially-supported social network depends on the ability of the organization to keep the customers in participating in the network. Drawing from the theories of information adoption, information systems continuance, and web usability, the author develops a model to explore how a commercially-supported social network can encourage customers to continue participating and using the information in the network. The theoretical model will be proved through an online survey of customers using the commercially-supported social networking sites of several high technology companies operating in the same sector. The result will be compared with previous studies to learn about the explanatory power of the research model, and to identify the main factors determining users’ intention to continue using a commercially-supported social network. Theoretical and practical implications, and limitations are discussed.Keywords: social network, information adoption, information systems continuance, web usability, user satisfaction
Procedia PDF Downloads 3124665 Prediction of Oil Recovery Factor Using Artificial Neural Network
Authors: O. P. Oladipo, O. A. Falode
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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger
Procedia PDF Downloads 4344664 Congestion Control in Mobile Network by Prioritizing Handoff Calls
Authors: O. A. Lawal, O. A Ojesanmi
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The demand for wireless cellular services continues to increase while the radio resources remain limited. Thus, network operators have to continuously manage the scarce radio resources in order to have an improved quality of service for mobile users. This paper proposes how to handle the problem of congestion in the mobile network by prioritizing handoff call, using the guard channel allocation scheme. The research uses specific threshold value for the time of allocation of the channel in the algorithm. The scheme would be simulated by generating various data for different traffics in the network as it would be in the real life. The result would be used to determine the probability of handoff call dropping and the probability of the new call blocking as a way of measuring the network performance.Keywords: call block, channel, handoff, mobile cellular network
Procedia PDF Downloads 390