Search results for: Industrial Networks
2645 An Organizational Strategic Analysis for Dynamics of Generating Firms- Alliance Networks
Authors: Takao Sakakura, Kazunori Fujimoto
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This paper proposes an analytical method for the dynamics of generating firms- alliance networks along with business phases. Dynamics in network developments have previously been discussed in the research areas of organizational strategy rather than in the areas of regional cluster, where the static properties of the networks are often discussed. The analytical method introduces the concept of business phases into innovation processes and uses relationships called prior experiences; this idea was developed in organizational strategy to investigate the state of networks from the viewpoints of tradeoffs between link stabilization and node exploration. This paper also discusses the results of the analytical method using five cases of the network developments of firms. The idea of Embeddedness helps interpret the backgrounds of the analytical results. The analytical method is useful for policymakers of regional clusters to establish concrete evaluation targets and a viewpoint for comparisons of policy programs.Keywords: Regional Clusters, Alliance Networks, Innovation Processes, Prior Experiences, Embeddedness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12282644 An Analysis of Global Stability of Cohen-Grossberg Neural Networks with Multiple Time Delays
Authors: Zeynep Orman, Sabri Arik
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This paper presents a new sufficient condition for the existence, uniqueness and global asymptotic stability of the equilibrium point for Cohen-Grossberg neural networks with multiple time delays. The results establish a relationship between the network parameters of the neural system independently of the delay parameters. The results are also compared with the previously reported results in the literature.Keywords: Equilibrium and stability analysis, Cohen-Grossberg Neural Networks, Lyapunov Functionals.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13362643 A Review of Coverage and Routing for Wireless Sensor Networks
Authors: Hamid Barati, Ali Movaghar, Ali Barati, Arash Azizi Mazreah
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The special constraints of sensor networks impose a number of technical challenges for employing them. In this review, we study the issues and existing protocols in three areas: coverage and routing. We present two types of coverage problems: to determine the minimum number of sensor nodes that need to perform active sensing in order to monitor a certain area; and to decide the quality of service that can be provided by a given sensor network. While most routing protocols in sensor networks are data-centric, there are other types of routing protocols as well, such as hierarchical, location-based, and QoS-aware. We describe and compare several protocols in each group. We present several multipath routing protocols and single-path with local repair routing protocols, which are proposed for recovering from sensor node crashes. We also discuss some transport layer schemes for reliable data transmission in lossy wireless channels.Keywords: Sensor networks, Coverage, Routing, Robustness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16292642 Secure Internet Connectivity for Dynamic Source Routing (DSR) based Mobile Ad hoc Networks
Authors: Ramanarayana Kandikattu, Lillykutty Jacob
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'Secure routing in Mobile Ad hoc networks' and 'Internet connectivity to Mobile Ad hoc networks' have been dealt separately in the past research. This paper proposes a light weight solution for secure routing in integrated Mobile Ad hoc Network (MANET)-Internet. The proposed framework ensures mutual authentication of Mobile Node (MN), Foreign Agent (FA) and Home Agent (HA) to avoid various attacks on global connectivity and employs light weight hop-by-hop authentication and end-to-end integrity to protect the network from most of the potential security attacks. The framework also uses dynamic security monitoring mechanism to monitor the misbehavior of internal nodes. Security and performance analysis show that our proposed framework achieves good security while keeping the overhead and latency minimal.Keywords: Internet, Mobile Ad hoc Networks, Secure routing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13932641 pth Moment Exponential Synchronization of a Class of Chaotic Neural Networks with Mixed Delays
Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye
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This paper studies the pth moment exponential synchronization of a class of stochastic neural networks with mixed delays. Based on Lyapunov stability theory, by establishing a new integrodifferential inequality with mixed delays, several sufficient conditions have been derived to ensure the pth moment exponential stability for the error system. The criteria extend and improve some earlier results. One numerical example is presented to illustrate the validity of the main results.
Keywords: pth Moment Exponential synchronization, Stochastic, Neural networks, Mixed time delays
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15392640 Face Recognition Using Morphological Shared-weight Neural Networks
Authors: Hossein Sahoolizadeh, Mahdi Rahimi, Hamid Dehghani
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We introduce an algorithm based on the morphological shared-weight neural network. Being nonlinear and translation-invariant, the MSNN can be used to create better generalization during face recognition. Feature extraction is performed on grayscale images using hit-miss transforms that are independent of gray-level shifts. The output is then learned by interacting with the classification process. The feature extraction and classification networks are trained together, allowing the MSNN to simultaneously learn feature extraction and classification for a face. For evaluation, we test for robustness under variations in gray levels and noise while varying the network-s configuration to optimize recognition efficiency and processing time. Results show that the MSNN performs better for grayscale image pattern classification than ordinary neural networks.Keywords: Face recognition, Neural Networks, Multi-layer Perceptron, masking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14742639 Alertness States Classification By SOM and LVQ Neural Networks
Authors: K. Ben Khalifa, M.H. Bédoui, M. Dogui, F. Alexandre
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Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.Keywords: Electroencephalogram interpretation, artificialneural networks, vigilance states, hardware implementation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14362638 Development of NOx Emission Model for a Tangentially Fired Acid Incinerator
Authors: Elangeshwaran Pathmanathan, Rosdiazli Ibrahim, Vijanth Sagayan Asirvadam
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This paper aims to develop a NOx emission model of an acid gas incinerator using Nelder-Mead least squares support vector regression (LS-SVR). Malaysia DOE is actively imposing the Clean Air Regulation to mandate the installation of analytical instrumentation known as Continuous Emission Monitoring System (CEMS) to report emission level online to DOE . As a hardware based analyzer, CEMS is expensive, maintenance intensive and often unreliable. Therefore, software predictive technique is often preferred and considered as a feasible alternative to replace the CEMS for regulatory compliance. The LS-SVR model is built based on the emissions from an acid gas incinerator that operates in a LNG Complex. Simulated Annealing (SA) is first used to determine the initial hyperparameters which are then further optimized based on the performance of the model using Nelder-Mead simplex algorithm. The LS-SVR model is shown to outperform a benchmark model based on backpropagation neural networks (BPNN) in both training and testing data.Keywords: artificial neural networks, industrial pollution, predictive algorithms, support vector machines
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19362637 Convergence Analysis of Training Two-Hidden-Layer Partially Over-Parameterized ReLU Networks via Gradient Descent
Authors: Zhifeng Kong
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Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.Keywords: Over-parameterization, Rectified Linear Units (ReLU), convergence, gradient descent, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8122636 Concepts for Designing Low Power Wireless Sensor Network
Authors: Bahareh Gholamzadeh, Hooman Nabovati
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Wireless sensor networks have been used in wide areas of application and become an attractive area for researchers in recent years. Because of the limited energy storage capability of sensor nodes, Energy consumption is one of the most challenging aspects of these networks and different strategies and protocols deals with this area. This paper presents general methods for designing low power wireless sensor network. Different sources of energy consumptions in these networks are discussed here and techniques for alleviating the consumption of energy are presented.Keywords: Energy consumption, MAC protocol, Routing protocol, Sensor node, Topology control, Wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21092635 A Mobile Agent-based Clustering Data Fusion Algorithm in WSN
Authors: Xiangbin Zhu, Wenjuan Zhang
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In wireless sensor networks,the mobile agent technology is used in data fusion. According to the node residual energy and the results of partial integration,we design the node clustering algorithm. Optimization of mobile agent in the routing within the cluster strategy for wireless sensor networks to further reduce the amount of data transfer. Through the experiments, using mobile agents in the integration process within the cluster can be reduced the path loss in some extent.
Keywords: wireless sensor networks, data fusion, mobile agent
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14672634 Energy Efficient Clustering and Data Aggregation in Wireless Sensor Networks
Authors: Surender Kumar Soni
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Wireless Sensor Networks (WSNs) are wireless networks consisting of number of tiny, low cost and low power sensor nodes to monitor various physical phenomena like temperature, pressure, vibration, landslide detection, presence of any object, etc. The major limitation in these networks is the use of nonrechargeable battery having limited power supply. The main cause of energy consumption WSN is communication subsystem. This paper presents an efficient grid formation/clustering strategy known as Grid based level Clustering and Aggregation of Data (GCAD). The proposed clustering strategy is simple and scalable that uses low duty cycle approach to keep non-CH nodes into sleep mode thus reducing energy consumption. Simulation results demonstrate that our proposed GCAD protocol performs better in various performance metrics.Keywords: Ad hoc network, Cluster, Grid base clustering, Wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30982633 A Materialized View Approach to Support Aggregation Operations over Long Periods in Sensor Networks
Authors: Minsoo Lee, Julee Choi, Sookyung Song
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The increasing interest on processing data created by sensor networks has evolved into approaches to implement sensor networks as databases. The aggregation operator, which calculates a value from a large group of data such as computing averages or sums, etc. is an essential function that needs to be provided when implementing such sensor network databases. This work proposes to add the DURING clause into TinySQL to calculate values during a specific long period and suggests a way to implement the aggregation service in sensor networks by applying materialized view and incremental view maintenance techniques that is used in data warehouses. In sensor networks, data values are passed from child nodes to parent nodes and an aggregation value is computed at the root node. As such root nodes need to be memory efficient and low powered, it becomes a problem to recompute aggregate values from all past and current data. Therefore, applying incremental view maintenance techniques can reduce the memory consumption and support fast computation of aggregate values.Keywords: Aggregation, Incremental View Maintenance, Materialized view, Sensor Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14962632 e-Service Innovation within Open Innovation Networks
Authors: Hung T. Tsou, Hsuan Y. Hsu
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Service innovations are central concerns in fast changing environment. Due to the fitness in customer demands and advances in information technologies (IT) in service management, an expanded conceptualization of e-service innovation is required. Specially, innovation practices have become increasingly more challenging, driving managers to employ a different open innovation model to maintain competitive advantages. At the same time, firms need to interact with external and internal customers in innovative environments, like the open innovation networks, to co-create values. Based on these issues, an important conceptual framework of e-service innovation is developed. This paper aims to examine the contributing factors on e-service innovation and firm performance, including financial and non-financial aspects. The study concludes by showing how e-service innovation will play a significant role in growing the overall values of the firm. The discussion and conclusion will lead to a stronger understanding of e-service innovation and co-creating values with customers within open innovation networks.Keywords: e-Service innovation, performance, open innovation networks, co-create value.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20672631 Function Approximation with Radial Basis Function Neural Networks via FIR Filter
Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim
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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore , the number of centers will be considered since it affects the performance of approximation.
Keywords: Extended kalmin filter (EKF), classification problem, radial basis function networks (RBFN), finite impulse response (FIR)filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23582630 Cryptanalysis of Chang-Chang-s EC-PAKA Protocol for Wireless Mobile Networks
Authors: Hae-Soon Ahn, Eun-Jun Yoon
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With the rapid development of wireless mobile communication, applications for mobile devices must focus on network security. In 2008, Chang-Chang proposed security improvements on the Lu et al.-s elliptic curve authentication key agreement protocol for wireless mobile networks. However, this paper shows that Chang- Chang-s improved protocol is still vulnerable to off-line password guessing attacks unlike their claims.
Keywords: Authentication, key agreement, wireless mobile networks, elliptic curve, password guessing attacks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14742629 The Role of Business Survey Measures in Forecasting Croatian Industrial Production
Authors: M. Cizmesija, N. Erjavec, V. Bahovec
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While the European Union (EU) harmonized methodology is a benchmark of worldwide used business survey (BS) methodology, the choice of variables that are components of the confidence indicators, as the leading indicators, is not strictly determined and unique. Therefore, the aim of this paper is to investigate and to quantify the relationship between all business survey variables in manufacturing industry and industrial production as a reference macroeconomic series in Croatia. The assumption is that there are variables in the business survey, that are not components of Industrial Confidence Indicator (ICI) and which can accurately (and sometimes better then ICI) predict changes in Croatian industrial production. Empirical analyses are conducted using quarterly data of BS variables in manufacturing industry and Croatian industrial production over the period from the first quarter 2005 to the first quarter 2013. Research results confirmed the assumption: three BS variables which is not components of ICI (competitive position, demand and liquidity) are the best leading indicator then ICI, in forecasting changes in Croatian industrial production instantaneously, with one, two or three quarter ahead.
Keywords: Balance, Business Survey, Confidence Indicators, Industrial Production, Forecasting.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18712628 Microservices-Based Provisioning and Control of Network Services for Heterogeneous Networks
Authors: Shameemraj M. Nadaf, Sipra Behera, Hemant K. Rath, Garima Mishra, Raja Mukhopadhyay, Sumanta Patro
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Microservices architecture has been widely embraced for rapid, frequent, and reliable delivery of complex applications. It enables organizations to evolve their technology stack in various domains. Today, the networking domain is flooded with plethora of devices and software solutions which address different functionalities ranging from elementary operations, viz., switching, routing, firewall etc., to complex analytics and insights based intelligent services. In this paper, we attempt to bring in the microservices based approach for agile and adaptive delivery of network services for any underlying networking technology. We discuss the life cycle management of each individual microservice and a distributed control approach with emphasis for dynamic provisioning, management, and orchestration in an automated fashion which can provide seamless operations in large scale networks. We have conducted validations of the system in lab testbed comprising of Traditional/Legacy and Software Defined Wireless Local Area networks.
Keywords: Microservices architecture, software defined wireless networks, traditional wireless networks, automation, orchestration, intelligent networks, network analytics, seamless management, single pane control, fine-grain control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7972627 Accelerating Integer Neural Networks On Low Cost DSPs
Authors: Thomas Behan, Zaiyi Liao, Lian Zhao, Chunting Yang
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In this paper, low end Digital Signal Processors (DSPs) are applied to accelerate integer neural networks. The use of DSPs to accelerate neural networks has been a topic of study for some time, and has demonstrated significant performance improvements. Recently, work has been done on integer only neural networks, which greatly reduces hardware requirements, and thus allows for cheaper hardware implementation. DSPs with Arithmetic Logic Units (ALUs) that support floating or fixed point arithmetic are generally more expensive than their integer only counterparts due to increased circuit complexity. However if the need for floating or fixed point math operation can be removed, then simpler, lower cost DSPs can be used. To achieve this, an integer only neural network is created in this paper, which is then accelerated by using DSP instructions to improve performance.Keywords: Digital Signal Processor (DSP), Integer Neural Network(INN), Low Cost Neural Network, Integer Neural Network DSPImplementation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17522626 Improved Exponential Stability Analysis for Delayed Recurrent Neural Networks
Authors: Miaomiao Yang, Shouming Zhong
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This paper studies the problem of exponential stability analysis for recurrent neural networks with time-varying delay.By establishing a suitable augmented LyapunovCKrasovskii function and a novel sufficient condition is obtained to guarantee the exponential stability of the considered system.In order to get a less conservative results of the condition,zero equalities and reciprocally convex approach are employed. The several exponential stability criterion proposed in this paper is simpler and effective. A numerical example is provided to demonstrate the feasibility and effectiveness of our results.
Keywords: Exponential stability , Neural networks, Linear matrix inequality, Lyapunov-Krasovskii, Time-varying.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17112625 An Adversarial Construction of Instability Bounds in LIS Networks
Authors: Dimitrios Koukopoulos
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In this work, we study the impact of dynamically changing link slowdowns on the stability properties of packetswitched networks under the Adversarial Queueing Theory framework. Especially, we consider the Adversarial, Quasi-Static Slowdown Queueing Theory model, where each link slowdown may take on values in the two-valued set of integers {1, D} with D > 1 which remain fixed for a long time, under a (w, ¤ü)-adversary. In this framework, we present an innovative systematic construction for the estimation of adversarial injection rate lower bounds, which, if exceeded, cause instability in networks that use the LIS (Longest-in- System) protocol for contention-resolution. In addition, we show that a network that uses the LIS protocol for contention-resolution may result in dropping its instability bound at injection rates ¤ü > 0 when the network size and the high slowdown D take large values. This is the best ever known instability lower bound for LIS networks.Keywords: Network stability, quality of service, adversarial queueing theory, greedy scheduling protocols.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11902624 Mining Implicit Knowledge to Predict Political Risk by Providing Novel Framework with Using Bayesian Network
Authors: Siavash Asadi Ghajarloo
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Nowadays predicting political risk level of country has become a critical issue for investors who intend to achieve accurate information concerning stability of the business environments. Since, most of the times investors are layman and nonprofessional IT personnel; this paper aims to propose a framework named GECR in order to help nonexpert persons to discover political risk stability across time based on the political news and events. To achieve this goal, the Bayesian Networks approach was utilized for 186 political news of Pakistan as sample dataset. Bayesian Networks as an artificial intelligence approach has been employed in presented framework, since this is a powerful technique that can be applied to model uncertain domains. The results showed that our framework along with Bayesian Networks as decision support tool, predicted the political risk level with a high degree of accuracy.Keywords: Bayesian Networks, Data mining, GECRframework, Predicting political risk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21332623 Knowledge Management in Cross- Organizational Networks as Illustrated by One of the Largest European ICT Associations A Case Study of the “METORA
Authors: Thomas Klauß
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In networks, mainly small and medium-sized businesses benefit from the knowledge, experiences and solutions offered by experts from industry and science or from the exchange with practitioners. Associations which focus, among other things, on networking, information and knowledge transfer and which are interested in supporting such cooperations are especially well suited to provide such networks and the appropriate web platforms. Using METORA as an example – a project developed and run by the Federal Association for Information Economy, Telecommunications and New Media e.V. (BITKOM) for the Federal Ministry of Economics and Technology (BMWi) – This paper will discuss how associations and other network organizations can achieve this task and what conditions they have to consider.
Keywords: Associations, collaboration, communities, crossdepartmental organizations, semantic web, web 2.0.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12632622 Enhancing the Connectedness in Ad–hoc Mesh Networks using the Terranet Technology
Authors: Obeidat I., Bsoul M., Khasawneh A., Kilani Y.
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This paper simulates the ad-hoc mesh network in rural areas, where such networks receive great attention due to their cost, since installing the infrastructure for regular networks in these areas is not possible due to the high cost. The distance between the communicating nodes is the most obstacles that the ad-hoc mesh network will face. For example, in Terranet technology, two nodes can communicate if they are only one kilometer far from each other. However, if the distance between them is more than one kilometer, then each node in the ad-hoc mesh networks has to act as a router that forwards the data it receives to other nodes. In this paper, we try to find the critical number of nodes which makes the network fully connected in a particular area, and then propose a method to enhance the intermediate node to accept to be a router to forward the data from the sender to the receiver. Much work was done on technological changes on peer to peer networks, but the focus of this paper will be on another feature which is to find the minimum number of nodes needed for a particular area to be fully connected and then to enhance the users to switch on their phones and accept to work as a router for other nodes. Our method raises the successful calls to 81.5% out of 100% attempt calls.
Keywords: Adjacency matrix, Ad-hoc mesh network, Connectedness, Terranet technology
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15732621 Improved Robust Stability Criteria for Discrete-time Neural Networks
Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye
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In this paper, the robust exponential stability problem of uncertain discrete-time recurrent neural networks with timevarying delay is investigated. By constructing a new augmented Lyapunov-Krasovskii function, some new improved stability criteria are obtained in forms of linear matrix inequality (LMI). Compared with some recent results in literature, the conservatism of the new criteria is reduced notably. Two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results.
Keywords: Robust exponential stability, delay-dependent stability, discrete-time neutral networks, time-varying delays.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14372620 Computational Networks for Knowledge Representation
Authors: Nhon Van Do
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In the artificial intelligence field, knowledge representation and reasoning are important areas for intelligent systems, especially knowledge base systems and expert systems. Knowledge representation Methods has an important role in designing the systems. There have been many models for knowledge such as semantic networks, conceptual graphs, and neural networks. These models are useful tools to design intelligent systems. However, they are not suitable to represent knowledge in the domains of reality applications. In this paper, new models for knowledge representation called computational networks will be presented. They have been used in designing some knowledge base systems in education for solving problems such as the system that supports studying knowledge and solving analytic geometry problems, the program for studying and solving problems in Plane Geometry, the program for solving problems about alternating current in physics.Keywords: Artificial intelligence, artificial intelligence and education, knowledge engineering, knowledge representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21762619 Stability Analysis of Neural Networks with Leakage, Discrete and Distributed Delays
Authors: Qingqing Wang, Baocheng Chen, Shouming Zhong
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This paper deals with the problem of stability of neural networks with leakage, discrete and distributed delays. A new Lyapunov functional which contains some new double integral terms are introduced. By using appropriate model transformation that shifts the considered systems into the neutral-type time-delay system, and by making use of some inequality techniques, delay-dependent criteria are developed to guarantee the stability of the considered system. Finally, numerical examples are provided to illustrate the usefulness of the proposed main results.
Keywords: Neural networks, Stability, Time-varying delays, Linear matrix inequality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15772618 Blockchain Security in MANETs
Authors: Nada Mouchfiq, Ahmed Habbani, Chaimae Benjbara
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The security aspect of the IoT occupies a place of great importance especially after the evolution that has known this field lastly because it must take into account the transformations and the new applications .Blockchain is a new technology dedicated to the data sharing. However, this does not work the same way in the different systems with different operating principles. This article will discuss network security using the Blockchain to facilitate the sending of messages and information, enabling the use of new processes and enabling autonomous coordination of devices. To do this, we will discuss proposed solutions to ensure a high level of security in these networks in the work of other researchers. Finally, our article will propose a method of security more adapted to our needs as a team working in the ad hoc networks, this method is based on the principle of the Blockchain and that we named ”MPR Blockchain”.Keywords: Ad hoc networks, blockchain, MPR, security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8482617 Improvement of the Reliability of the Industrial Electric Networks
Authors: M. Bouguerra, I. Habi
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The continuity in the electric supply of the electric installations is becoming one of the main requirements of the electric supply network (generation, transmission, and distribution of the electric energy). The achievement of this requirement depends from one side on the structure of the electric network and on the other side on the avaibility of the reserve source provided to maintain the supply in case of failure of the principal one. The avaibility of supply does not only depends on the reliability parameters of the both sources (principal and reserve) but it also depends on the reliability of the circuit breaker which plays the role of interlocking the reserve source in case of failure of the principal one. In addition, the principal source being under operation, its control can be ideal and sure, however, for the reserve source being in stop, a preventive maintenances which proceed on time intervals (periodicity) and for well defined lengths of time are envisaged, so that this source will always available in case of the principal source failure. The choice of the periodicity of preventive maintenance of the source of reserve influences directly the reliability of the electric feeder system In this work and on the basis of the semi- markovian's processes, the influence of the time of interlocking the reserve source upon the reliability of an industrial electric network is studied and is given the optimal time of interlocking the reserve source in case of failure the principal one, also the influence of the periodicity of the preventive maintenance of the source of reserve is studied and is given the optimal periodicity.Keywords: Semi-Markovians processes, reliability, optimization, industrial electric network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12352616 A Systematic Construction of Instability Bounds in LIS Networks
Authors: Dimitrios Koukopoulos
Abstract:
In this work, we study the impact of dynamically changing link slowdowns on the stability properties of packetswitched networks under the Adversarial Queueing Theory framework. Especially, we consider the Adversarial, Quasi-Static Slowdown Queueing Theory model, where each link slowdown may take on values in the two-valued set of integers {1, D} with D > 1 which remain fixed for a long time, under a (w, p)-adversary. In this framework, we present an innovative systematic construction for the estimation of adversarial injection rate lower bounds, which, if exceeded, cause instability in networks that use the LIS (Longest-in- System) protocol for contention-resolution. In addition, we show that a network that uses the LIS protocol for contention-resolution may result in dropping its instability bound at injection rates p > 0 when the network size and the high slowdown D take large values. This is the best ever known instability lower bound for LIS networks.
Keywords: Parallel computing, network stability, adversarial queuing theory, greedy scheduling protocols.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1376