Search results for: Network services.

Authors: Nasrin Bakhshizadeh, Ashkan Forootan

Abstract:

A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: Polyethylene, polymerization, density, melt index, neural network.

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Authors: S. Areerachakul

Abstract:

Nowadays, the increase of human population every year results in increasing of water usage and demand. Saen Saep canal is important canal in Bangkok. The main objective of this study is using Artificial Neural Network (ANN) model to estimate the Chemical Oxygen Demand (COD) on data from 11 sampling sites. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2007-2011. The twelve parameters of water quality are used as the input of the models. These water quality indices affect the COD. The experimental results indicate that the ANN model provides a high correlation coefficient (R=0.89).

Keywords: Artificial neural network, chemical oxygen demand, estimate, surface water.

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Authors: Mokrane Selma

Abstract:

The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: Bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network.

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Authors: Mujtaba Roshan, John A. Schormans

Abstract:

Quality of Experience (QoE) drives churn in the broadband networks industry, and good QoE plays a large part in the retention of customers. QoE is known to be affected by the Quality of Service (QoS) factors packet loss probability (PLP), delay and delay jitter caused by the network. Earlier results have shown that the relationship between these QoS factors and QoE is non-linear, and may vary from application to application. We use the network emulator Netem as the basis for experimentation, and evaluate how QoE varies as we change the emulated QoS metrics. Focusing on Video-on-Demand, we discovered that the reported QoE may differ widely for users of different age groups, and that the most demanding age group (the youngest) can require an order of magnitude lower PLP to achieve the same QoE than is required by the most widely studied age group of users. We then used a bottleneck TCP model to evaluate the capacity cost of achieving an order of magnitude decrease in PLP, and found it be (almost always) a 3-fold increase in link capacity that was required.

Keywords: Quality of experience, quality of service, packet loss probability, network capacity.

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Authors: C. C. Wong, P. L. Hiew

Abstract:

This research aims to examine the key success factors for the diffusion of mobile entertainment services in Malaysia. The drivers and barriers observed in this research include perceived benefit; concerns pertaining to pricing, product and technological standardization, privacy and security; as well as influences from peers and community. An analysis of a Malaysian survey of 384 respondents between 18 to 25 years shows that subscribers placed greater importance on perceived benefit of mobile entertainment services compared to other factors. Results of the survey also show that there are strong positive correlations between all the factors, with pricing issue–perceived benefit showing the strongest relationship. This paper aims to provide an extensive study on the drivers and barriers that could be used to derive architecture for entertainment service provision to serve as a guide for telcos to outline suitable approaches in order to encourage mass market adoption of mobile entertainment services in Malaysia.

Keywords: Barriers, Correlations, Diffusion, Drivers, Mobile Entertainment.

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Authors: Zongyan Li, Matt Best

Abstract:

This paper presents an optimization method for reducing the number of input channels and the complexity of the feed-forward NARX neural network (NN) without compromising the accuracy of the NN model. By utilizing the correlation analysis method, the most significant regressors are selected to form the input layer of the NN structure. An application of vehicle dynamic model identification is also presented in this paper to demonstrate the optimization technique and the optimal input layer structure and the optimal number of neurons for the neural network is investigated.

Keywords: Correlation analysis, F-ratio, Levenberg-Marquardt, MSE, NARX, neural network, optimisation.

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Authors: Doraid Dalalah

Abstract:

A topologically oriented neural network is very efficient for real-time path planning for a mobile robot in changing environments. When using a recurrent neural network for this purpose and with the combination of the partial differential equation of heat transfer and the distributed potential concept of the network, the problem of obstacle avoidance of trajectory planning for a moving robot can be efficiently solved. The related dimensional network represents the state variables and the topology of the robot's working space. In this paper two approaches to problem solution are proposed. The first approach relies on the potential distribution of attraction distributed around the moving target, acting as a unique local extreme in the net, with the gradient of the state variables directing the current flow toward the source of the potential heat. The second approach considers two attractive and repulsive potential sources to decrease the time of potential distribution. Computer simulations have been carried out to interrogate the performance of the proposed approaches.

Keywords: Mobile robot, Path Planning, Mesh, Potential field.

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Authors: Khemanand Moheeput, Smita S. D. Goorah, Satish K. Ramchurn

Abstract:

We report a computational study of the spreading dynamics of a viral infection in a complex (scale-free) network. The final epidemic size distribution (FESD) was found to be unimodal or bimodal depending on the value of the basic reproductive number R0 . The FESDs occurred on time-scales long enough for intermediate-time epidemic size distributions (IESDs) to be important for control measures. The usefulness of R0 for deciding on the timeliness and intensity of control measures was found to be limited by the multimodal nature of the IESDs and by its inability to inform on the speed at which the infection spreads through the population. A reduction of the transmission probability at the hubs of the scale-free network decreased the occurrence of the larger-sized epidemic events of the multimodal distributions. For effective epidemic control, an early reduction in transmission at the index cell and its neighbors was essential.

Keywords: Basic reproductive number, epidemic control, scalefree network, viral infection.

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Authors: Ashanie Guanathillake, Kithsiri Samarasinghe

Abstract:

Wireless Sensor Networks consist of inexpensive, low power sensor nodes deployed to monitor the environment and collect data. Gathering information in an energy efficient manner is a critical aspect to prolong the network lifetime. Clustering  algorithms have an advantage of enhancing the network lifetime. Current clustering algorithms usually focus on global re-clustering and local re-clustering separately. This paper, proposed a combination of those two reclustering methods to reduce the energy consumption of the network. Furthermore, the proposed algorithm can apply to homogeneous as well as heterogeneous wireless sensor networks. In addition, the cluster head rotation happens, only when its energy drops below a dynamic threshold value computed by the algorithm. The simulation result shows that the proposed algorithm prolong the network lifetime compared to existing algorithms.

Keywords: Energy efficient, Global re-clustering, Local re-clustering, Wireless sensor networks.

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Authors: O. Siriporn, S. Benjawan

Abstract:

This paper represents four unsupervised clustering algorithms namely sIB, RandomFlatClustering, FarthestFirst, and FilteredClusterer that previously works have not been used for network traffic classification. The methodology, the result, the products of the cluster and evaluation of these algorithms with efficiency of each algorithm from accuracy are shown. Otherwise, the efficiency of these algorithms considering form the time that it use to generate the cluster quickly and correctly. Our work study and test the best algorithm by using classify traffic anomaly in network traffic with different attribute that have not been used before. We analyses the algorithm that have the best efficiency or the best learning and compare it to the previously used (K-Means). Our research will be use to develop anomaly detection system to more efficiency and more require in the future.

Keywords: Unsupervised, clustering, anomaly, machine learning.

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Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti

Abstract:

Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.

Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety.

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Authors: Ali Keshavarzi, Fereydoon Sarmadian

Abstract:

Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. Then, multivariate regression and neural network model (feedforward back propagation network) were employed to develop a pedotransfer function for predicting soil parameter using easily measurable characteristics of clay and organic carbon. The performance of the multivariate regression and neural network model was evaluated using a test data set. In order to evaluate the models, root mean square error (RMSE) was used. The value of RMSE and R2 derived by ANN model for CEC were 0.47 and 0.94 respectively, while these parameters for multivariate regression model were 0.65 and 0.88 respectively. Results showed that artificial neural network with seven neurons in hidden layer had better performance in predicting soil cation exchange capacity than multivariate regression.

Keywords: Easily measurable characteristics, Feed-forwardback propagation, Pedotransfer functions, CEC.

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Authors: Hiroshi Yamakawa, Michiko Yoshida, Motohiro Tsuchiya

Abstract:

The recent development of Information and Communication Technology (ICT) enables new ways of "democratic" decision-making such as a page-ranking system, which estimates the importance of a web page based on indirect trust on that page shared by diverse group of unorganized individuals. These kinds of "democracy" have not been acclaimed yet in the world of real politics. On the other hand, a large amount of data about personal relations including trust, norms of reciprocity, and networks of civic engagement has been accumulated in a computer-readable form by computer systems (e.g., social networking systems). We can use these relations as a new type of social capital to construct a new democratic decision-making system based on a delegation network. In this paper, we propose an effective decision-making support system, which is based on empowering someone's vote whom you trust. For this purpose, we propose two new techniques: the first is for estimating entire vote distribution from a small number of votes, and the second is for estimating active voter choice to promote voting using a delegation network. We show that these techniques could increase the voting ratio and credibility of the whole decision by agent-based simulations.

Keywords: Delegation, network centrality, social network, voting ratio.

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Authors: Vedat Coskun, Fahri Soylemezgiller, Busra Ozdenizci, Kerem Ok

Abstract:

In recent years, several smart card solutions for transportation services of cities with different technical infrastructures and business models has emerged considerably, which triggers new business and technical opportunities. In order to create a unique system, we present a novel, promising system called Multifunctional City Smart Card System to be used in all cities that provides transportation and loyalty services based on the MasterCard M/Chip Advance standards. The proposed system provides a unique solution for transportation services of large cities over the world, aiming to answer all transportation needs of citizens. In this paper, development of the Multifunctional City Smart Card system and system requirements are briefly described. Moreover, performance analysis results of M/Chip Advance Compatible Validators which is the system's most important component are presented.

Keywords: Smart Card, M/Chip Advance Standard, City Transportation, Performance Analysis.

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Authors: Lo Kar Yin

Abstract:

In view of the increasing speed and quantity of the housing supply, building, and civil engineering infrastructure works triggered by the pandemic across the globe, contractors, professional services providers (PSP), including consultants (e.g., architect, project manager, civil/geotechnical/structural engineer, building services engineer, quantity surveyor/cost manager, etc.) and suppliers have faced tremendous challenges of the fierce market, limited manpower, and resources under contract prices fluctuation and competitive fee and price. With qualitative analysis, this paper is to identify the available information from the industry stakeholders with a view to finding solutions for enhancing efficiency, safety, and quality of construction value chain services for public and private organisations/companies’ sustainable growth, not limited to checking the deliverables and data transfer from multi-disciplinary parties. Technology, contracts, and people are the key requirements for shaping the construction industry. With the integration of a modern engineering contract (e.g., NEC) collaborative approach, practical workflows are designed to address loopholes together with different levels of people employment/retention and technology adoption to achieve the best value for money.

Keywords: Sustainable Development, Sustainable solutions, contract, construction value chain, Building Information Modelling, BIM integration.

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

Abstract:

In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network.

The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters.

Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output.

This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc.

From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: Project profitability, multi-objective optimization, genetic algorithm, Pareto set, Neural Networks.

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Authors: S. V. Kasmir Raja, P. Herbert Raj

Abstract:

The overlay approach has been widely used by many service providers for Traffic Engineering (TE) in large Internet backbones. In the overlay approach, logical connections are set up between edge nodes to form a full mesh virtual network on top of the physical topology. IP routing is then run over the virtual network. Traffic engineering objectives are achieved through carefully routing logical connections over the physical links. Although the overlay approach has been implemented in many operational networks, it has a number of well-known scaling issues. This paper proposes a new approach to achieve traffic engineering without full-mesh overlaying with the help of integrated approach and equal subset split method. Traffic engineering needs to determine the optimal routing of traffic over the existing network infrastructure by efficiently allocating resource in order to optimize traffic performance on an IP network. Even though constraint-based routing [1] of Multi-Protocol Label Switching (MPLS) is developed to address this need, since it is not widely tested or debugged, Internet Service Providers (ISPs) resort to TE methods under Open Shortest Path First (OSPF), which is the most commonly used intra-domain routing protocol. Determining OSPF link weights for optimal network performance is an NP-hard problem. As it is not possible to solve this problem, we present a subset split method to improve the efficiency and performance by minimizing the maximum link utilization in the network via a small number of link weight modifications. The results of this method are compared against results of MPLS architecture [9] and other heuristic methods.

Keywords: Constraint based routing, Link Utilization, Subsetsplit method and Traffic Engineering.

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Authors: S. Areerachakul, N. Ployong, S. Na Songkla

Abstract:

This research’s objective is to select the model with most accurate value by using Neural Network Technique as a way to filter potential students who enroll in IT course by Electronic learning at Suan Suanadha Rajabhat University. It is designed to help students selecting the appropriate courses by themselves. The result showed that the most accurate model was 100 Folds Cross-validation which had 73.58% points of accuracy.

Keywords: Artificial neural network, classification, students.

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Authors: Abhishek, Seema Devi, Jyoti Ohri

Abstract:

A mobile ad hoc network (MANET) represents a system of wireless mobile nodes that can self-organize freely and dynamically into arbitrary and temporary network topology. Unlike a wired network, wireless network interface has limited transmission range. Routing is the task of forwarding data packets from source to a given destination. Ad-hoc On Demand Distance Vector (AODV) routing protocol creates a path for a destination only when it required. This paper describes the implementation of AODV routing protocol using MATLAB-based Truetime simulator. In MANET's node movements are not fixed while they are random in nature. Hence intelligent techniques i.e. fuzzy and ANFIS are used to optimize the transmission range. In this paper, we compared the transmission range of AODV, fuzzy AODV and ANFIS AODV. For soft computing AODV, we have taken transmitted power and received threshold as input and transmission range as output. ANFIS gives better results as compared to fuzzy AODV.

Keywords: ANFIS, AODV, fuzzy, MANET, reactive routing protocol, routing protocol, Truetime.

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Authors: Vipin Pal, Girdhari Singh, R P Yadav

Abstract:

As wireless sensor networks are energy constraint networks so energy efficiency of sensor nodes is the main design issue. Clustering of nodes is an energy efficient approach. It prolongs the lifetime of wireless sensor networks by avoiding long distance communication. Clustering algorithms operate in rounds. Performance of clustering algorithm depends upon the round time. A large round time consumes more energy of cluster heads while a small round time causes frequent re-clustering. So existing clustering algorithms apply a trade off to round time and calculate it from the initial parameters of networks. But it is not appropriate to use initial parameters based round time value throughout the network lifetime because wireless sensor networks are dynamic in nature (nodes can be added to the network or some nodes go out of energy). In this paper a variable round time approach is proposed that calculates round time depending upon the number of active nodes remaining in the field. The proposed approach makes the clustering algorithm adaptive to network dynamics. For simulation the approach is implemented with LEACH in NS-2 and the results show that there is 6% increase in network lifetime, 7% increase in 50% node death time and 5% improvement over the data units gathered at the base station.

Keywords: Wireless Sensor Network, Clustering, Energy Efficiency, Round Time.

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Authors: Zulhadi Zakaria, Nor Ashidi Mat Isa, Shahrel A. Suandi

Abstract:

This paper reports the study results on neural network training algorithm of numerical optimization techniques multiface detection in static images. The training algorithms involved are scale gradient conjugate backpropagation, conjugate gradient backpropagation with Polak-Riebre updates, conjugate gradient backpropagation with Fletcher-Reeves updates, one secant backpropagation and resilent backpropagation. The final result of each training algorithms for multiface detection application will also be discussed and compared.

Keywords: training algorithm, multiface, static image, neural network

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Authors: Nelson F.F. Ebecken, Gilberto C. Pereira

Abstract:

The objective of this work is to explicit knowledge on the interactions between the chlorophyll-a and nine meroplankton larvae of epibenthonic fauna. The studied case is the Arraial do Cabo upwelling system, Southeastern of Brazil, which provides different environmental conditions. To assess this information a network approach based in probability estimative was used. Comparisons among the generated graphs are made in the light of different water masses, application of Shannon biodiversity index, and the closeness and betweenness centralities measurements. Our results show the main pattern among different water masses and how the core organisms belonging to the network skeleton are correlated to the main environmental variable. We conclude that the approach of complex networks is a promising tool for environmental diagnostic.

Keywords: Coastal upwelling, Ecological networks, Plankton - interactions, Environmental analysis.

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Authors: M. Hassani, Y. Hassani, N. Ajudanioskooei, N. N. Benvid

Abstract:

Laser Forming process as a non-contact thermal forming process is widely used to forming and bending of metallic and non-metallic sheets. In this process, according to laser irradiation along a specific path, sheet is bent. One of the most important output parameters in laser forming is bending angle that depends on process parameters such as physical and mechanical properties of materials, laser power, laser travel speed and the number of scan passes. In this paper, Artificial Neural Network and Fuzzy Logic System were used to predict of bending angle in laser forming process. Inputs to these models were laser travel speed and laser power. The comparison between artificial neural network and fuzzy logic models with experimental results has been shown both of these models have high ability to prediction of bending angles with minimum errors.

Keywords: Artificial neural network, bending angle, fuzzy logic, laser forming.

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Authors: Mahmoud Gilany, Wael Al-Hasawi

Abstract:

Preliminary studies on Kuwait high voltage transmission system show significant increase in the short circuit level at some of the grid substations and some generating stations. This increase results from the growth in the power transmission systems in size and complexity. New generating stations are expected to be added to the system within the next few years. This paper describes the study analysis performed to evaluate the available and potential solutions to control SC levels in Kuwait power system. It also presents a modified planning of the transmission network in order to fulfill this task.

Keywords: Short circuit current, network splitting, fault current limiter, power transmission planning.

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Authors: Pariwat Somnuek

Abstract:

This study focused on tourism logistic services in the border areas of Thailand by an analysis and comparison of the opinions of tourists, villagers, and entrepreneurs of these services. Sample representatives of this study were a total of 600 villagers and 15 entrepreneurs in the three border areas consisting of Chong Anma, Chong Sa-Ngam, and Chong Jom checkpoints. For methodology, survey questionnaires, situation analysis, TOWS matrix, and focus group discussions were used for data collection, as well as descriptive analysis and statistics such as arithmetic means and standard deviations, were employed for data analysis. The findings revealed that business potential was at the medium level and entrepreneurs were satisfied with their turnovers. However, perspectives of transportation and tourism services provided for tourists need to be immediately improved. Recommendations for the potential development included promotion of border tourism destinations and foreign investments into accommodation, restaurants, and transport, as well as the establishment of business networks between Thailand and Cambodia, along with the introduction of new tourism destinations by co-operation between entrepreneurs in both countries. These initiatives may lead to increased visitors, collaboration of security offices, and an improved image of tourism security.

Keywords: Business potential, potential development, tourism logistics, services.

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Authors: Abdussamad Ismail, Dong-Sheng Jeng

Abstract:

A self-evolution algorithm for optimizing neural networks using a combination of PSO and JPSO is proposed. The algorithm optimizes both the network topology and parameters simultaneously with the aim of achieving desired accuracy with less complicated networks. The performance of the proposed approach is compared with conventional back-propagation networks using several synthetic functions, with better results in the case of the former. The proposed algorithm is also implemented on slope stability problem to estimate the critical factor of safety. Based on the results obtained, the proposed self evolving network produced a better estimate of critical safety factor in comparison to conventional BPN network.

Keywords: Neural networks, Topology evolution, Particle swarm optimization.

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Authors: H. El-Madbouly

Abstract:

For future Broad band ISDN, Asynchronous Transfer Mode (ATM) is designed not only to support a wide range of traffic classes with diverse flow characteristics, but also to guarantee the different quality of service QOS requirements. The QOS may be measured in terms of cell loss probability and maximum cell delay. In this paper, ATM networks in which the virtual path (VP) concept is implemented are considered. By applying the Markov Deterministic process method, an efficient algorithm to compute the minimum capacity required to satisfy the QOS requirements when multiple classes of on-off are multiplexed on to a single VP. Using the result, we then proposed a simple algorithm to determine different combinations of VP to achieve the optimum of the total capacity required for satisfying the individual QOS requirements (loss- delay).

Keywords: Bandwidth allocation, Quality of services, ATMNetwork, virtual path.

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Authors: M. Santhalakshmi, P Suganthi

Abstract:

Wireless Sensor Networks (WSNs) have many advantages. Their deployment is easier and faster than wired sensor networks or other wireless networks, as they do not need fixed infrastructure. Nodes are partitioned into many small groups named clusters to aggregate data through network organization. WSN clustering guarantees performance achievement of sensor nodes. Sensor nodes energy consumption is reduced by eliminating redundant energy use and balancing energy sensor nodes use over a network. The aim of such clustering protocols is to prolong network life. Low Energy Adaptive Clustering Hierarchy (LEACH) is a popular protocol in WSN. LEACH is a clustering protocol in which the random rotations of local cluster heads are utilized in order to distribute energy load among all sensor nodes in the network. This paper proposes Connected Dominant Set (CDS) based cluster formation. CDS aggregates data in a promising approach for reducing routing overhead since messages are transmitted only within virtual backbone by means of CDS and also data aggregating lowers the ratio of responding hosts to the hosts existing in virtual backbones. CDS tries to increase networks lifetime considering such parameters as sensors lifetime, remaining and consumption energies in order to have an almost optimal data aggregation within networks. Experimental results proved CDS outperformed LEACH regarding number of cluster formations, average packet loss rate, average end to end delay, life computation, and remaining energy computation.

Keywords: Wireless sensor network, connected dominant set, clustering, data aggregation.

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Authors: Nophaket Napong

Abstract:

Rooted in the study of social functioning of space in architecture, Space Syntax (SS) and the more recent Network Pattern (NP) researches demonstrate the 'spatial structures' of city, i.e. the hierarchical patterns of streets, junctions and alley ends. Applying SS and NP models, planners can conceptualize the real city-s patterns. Although, both models yield the optimal path of the city their underpinning displays of the city-s spatial configuration differ. The Axial Map analyzes the topological non-distance-based connectivity structure, whereas, the Central-Node Map and the Shortcut-Path Map, in contrast, analyze the metrical distance-based structures. This research contrasts and combines them to understand various forms of city-s structures. It concludes that, while they reveal different spatial structures, Space Syntax and Network Pattern urban models support each the other. Combining together they simulate the global access and the locally compact structures namely the central nodes and the shortcuts for the city.

Keywords: Street pattern, space syntax, syntactic and metrical models, network pattern models.

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Authors: Michely Vargas Delpupo, José Geraldo Romanello Bueno

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The right to basic sanitation, was elevated to the category of fundamental right by the Constitution of 1988 to protect the ecologically balanced environment, ensuring social rights to health and adequate housing and put the dignity of the human person as the foundation of the Brazilian Democratic State. Before their essentiality to humans, this article seeks to understand why universal access to basic sanitation is a goal so difficult to achieve in Brazil. Therefore, this research uses the deductive and analytical method. Given the nature of the research literature, research techniques were centered in specialized books on the subject, journals, theses and dissertations, laws, relevant law case and raising social indicators relating to the theme. The relevance of the topic stems, among other things, the fact that sanitation services are essential for a dignified life, i.e., everyone is entitled to the maintenance of the necessary existence conditions are satisfied. However, the effectiveness of this right is undermined in society, since Brazil has huge deficit in sanitation services, denying thus a worthy life to most of the population. Thus, it can be seen that the provision of water and sewage services in Brazil is still characterized by a large imbalance, since the municipalities with lower population index have greater disability in the sanitation service. The truth is that the precariousness of water and sewage services in Brazil is still very concentrated in the North and Northeast regions, limiting the effective implementation of the Law 11.445/2007 in the country. Therefore, there is urgent need for a positive service by the State in the provision of sanitation services in order to prevent and control disease, improve quality of life and productivity of individuals, besides preventing contamination of water resources. More than just social and economic necessity, there is a government duty to implement such services. In this sense, given the current scenario, to achieve universal access to basic sanitation imposes many hurdles. These are mainly in the field of properly formulated and implemented public policies, i.e., it requires an excellent institutional organization, management services, strategic planning, social control, in order to provide answers to complex challenges.

Keywords: Fundamental rights, sanitation, universal access.

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