Search results for: network security theory.
4241 Imposter Detection Based on Location in Vehicular Ad-Hoc Network
Authors: Sanjoy Das, Akash Arya, Rishi Pal Singh
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Vehicular Ad hoc Network is basically the solution of several problems associated while vehicles are plying on the road. In this paper, we have focused on the detection of imposter node while it has stolen the ID's of the authenticated vehicle in the network. The purpose is to harm the network through imposter messages. Here, we have proposed a protocol namely Imposter Detection based on Location (IDBL), which will store the location coordinate of the each vehicle as the key of the authenticity of the message so that imposter node can be detected. The imposter nodes send messages from a stolen ID and show that it is from an authentic node ID. So, to detect this anomaly, the first location is checked and observed different from original vehicle location. This node is known as imposter node. We have implemented the algorithm through JAVA and tested various types of node distribution and observed the detection probability of imposter node.
Keywords: Authentication, detection, IDBL protocol, imposter node, node detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7874240 Developing a Statistical Model for Electromagnetic Environment for Mobile Wireless Networks
Authors: C. Temaneh Nyah
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The analysis of electromagnetic environment using deterministic mathematical models is characterized by the impossibility of analyzing a large number of interacting network stations with a priori unknown parameters, and this is characteristic, for example, of mobile wireless communication networks. One of the tasks of the tools used in designing, planning and optimization of mobile wireless network is to carry out simulation of electromagnetic environment based on mathematical modelling methods, including computer experiment, and to estimate its effect on radio communication devices. This paper proposes the development of a statistical model of electromagnetic environment of a mobile wireless communication network by describing the parameters and factors affecting it including the propagation channel and their statistical models.Keywords: Electromagnetic Environment, Statistical model, Wireless communication network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18974239 Network Reconfiguration for Load Balancing in Distribution System with Distributed Generation and Capacitor Placement
Authors: T. Lantharthong, N. Rugthaicharoencheep
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This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. A method based on Tabu search algorithm, The Tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system with distributed generations and capacitors placement. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.Keywords: Network reconfiguration, Distributed generation Capacitor placement, Load balancing, Optimization technique
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42064238 Coverage Probability Analysis of WiMAX Network under Additive White Gaussian Noise and Predicted Empirical Path Loss Model
Authors: Chaudhuri Manoj Kumar Swain, Susmita Das
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This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.
Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6954237 Application of Fuzzy Neural Network for Image Tumor Description
Authors: Nahla Ibraheem Jabbar, Monica Mehrotra
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This paper used a fuzzy kohonen neural network for medical image segmentation. Image segmentation plays a important role in the many of medical imaging applications by automating or facilitating the diagnostic. The paper analyses the tumor by extraction of the features of (area, entropy, means and standard deviation).These measurements gives a description for a tumor.
Keywords: FCM, features extraction, medical image processing, neural network, segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21024236 A Framework for Investigating Reverse Logistics Capability of E-Tailers
Authors: Wen-Shan Lin, Shu-Lu Hsu
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Environmental concern and consumer rights have entailed e-tailers to adopt better strategies to facilitate product returns from customers. As the demand for reverse logistics (RL) continues to grow, little is known about what motivates e-tailers to enhance their RL capabilities and about the role RL capabilities plays in enabling e-tailers to achieve better customer satisfaction and economic performance. Based on resource-based theory and institutional theory, this article proposes that the following factors play a critical role in influencing the RL capability of e-tailers: (a) Financial resource commitment to RL, (b) managerial resource commitment to RL, and (c) institutional pressure to implement RL. Based on the role of these factors, the study provides a framework and propositions that serve to guide future research addressing the link among resources, institutional pressure, and RL capability.Keywords: Reverse logistics, e-tailing, resource-based theory, institutional theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12224235 Kosovo- A Unique Experiment in Europe- in the International Context at the End of the Cold War?
Authors: Raluca Iulia Iulian
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The question of interethnic and interreligious conflicts in ex-Yugoslavia receives much attention within the framework of the international context created after 1991 because of the impact of these conflicts on the security and the stability of the region of Balkans and of Europe. This paper focuses on the rationales leading to the declaration of independence by Kosovo according to ethnic and religious criteria and analyzes why these same rationales were not applied in Bosnia and Herzegovina. The approach undertaken aims at comparatively examining the cases of Kosovo, and Bosnia and Herzegovina. At the same time, it aims at understanding the political decision making of the international community in the case of Kosovo. Specifically, was this a good political decision for the security and the stability of the region of Balkans, of Europe, or even for global security and stability? This research starts with an overview on the European security framework post 1991, paying particular attention to Kosovo and Bosnia and Herzegovina. It then presents the theoretical and methodological framework and compares the representative cases. Using the constructivism issue and the comparative methodology, it arrives at the results of the study. An important issue of the paper is the thesis that this event modifies the principles of international law and creates dangerous precedents for regional stability in the Balkans.Keywords: Interethnic and interreligious conflict, security andstability, superpower.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13894234 A Study on Application of Elastic Theory for Computing Flexural Stresses in Preflex Beam
Authors: Nasiri Ahmadullah, Shimozato Tetsuhiro, Masayuki Tai
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This paper presents the step-by-step procedure for using Elastic Theory to calculate the internal stresses in composite bridge girders prestressed by the Preflexing Technology, called Prebeam in Japan and Preflex beam worldwide. Elastic Theory approaches preflex beams the same way as it does the conventional composite girders. Since preflex beam undergoes different stages of construction, calculations are made using different sectional and material properties. Stresses are calculated in every stage using the properties of the specific section. Stress accumulation gives the available stress in a section of interest. Concrete presence in the section implies prestress loss due to creep and shrinkage, however; more work is required to be done in this field. In addition to the graphical presentation of this application, this paper further discusses important notes of graphical comparison between the results of an experimental-only research carried out on a preflex beam, with the results of simulation based on the elastic theory approach, for an identical beam using Finite Element Modeling (FEM) by the author.
Keywords: Composite girder, elastic theory, preflex beam, prestressing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8934233 Modified Functional Link Artificial Neural Network
Authors: Ashok Kumar Goel, Suresh Chandra Saxena, Surekha Bhanot
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In this work, a Modified Functional Link Artificial Neural Network (M-FLANN) is proposed which is simpler than a Multilayer Perceptron (MLP) and improves upon the universal approximation capability of Functional Link Artificial Neural Network (FLANN). MLP and its variants: Direct Linear Feedthrough Artificial Neural Network (DLFANN), FLANN and M-FLANN have been implemented to model a simulated Water Bath System and a Continually Stirred Tank Heater (CSTH). Their convergence speed and generalization ability have been compared. The networks have been tested for their interpolation and extrapolation capability using noise-free and noisy data. The results show that M-FLANN which is computationally cheap, performs better and has greater generalization ability than other networks considered in the work.Keywords: DLFANN, FLANN, M-FLANN, MLP
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17894232 Comparative Optical Analysis of Offset Reflector Antenna in GRASP
Authors: Ghulam Ahmad
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In this paper comparison of Reflector Antenna analyzing techniques based on wave and ray nature of optics is presented for an offset reflector antenna using GRASP (General Reflector antenna Analysis Software Package) software. The results obtained using PO (Physical Optics), PTD (Physical theory of Diffraction), and GTD (Geometrical Theory of Diffraction) are compared. The validity of PO and GTD techniques in regions around the antenna, caustic behavior of GTD in main beam, and deviation of GTD in case of near-in sidelobes of radiation pattern are discussed. The comparison for far-out sidelobes predicted by PO, PO + PTD and GTD is described. The effect of Direct Radiations from feed which results in feed selection for the system is addressed.Keywords: Geometrical optics & geometrical theory of diffraction, offset reflector antenna, physical optics & physical theory of diffraction, PO & GO comaprison.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21084231 Development of a Telemedical Network Supporting an Automated Flow Cytometric Analysis for the Clinical Follow-up of Leukaemia
Authors: Claude Takenga, Rolf-Dietrich Berndt, Erling Si, Markus Diem, Guohui Qiao, Melanie Gau, Michael Brandstoetter, Martin Kampel, Michael Dworzak
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In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide.Keywords: Data security, flow cytometry, leukaemia, telematics platform, telemedicine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15544230 Simplified 3R2C Building Thermal Network Model: A Case Study
Authors: S. M. Mahbobur Rahman
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Whole building energy simulation models are widely used for predicting future energy consumption, performance diagnosis and optimum control. Black box building energy modeling approach has been heavily studied in the past decade. The thermal response of a building can also be modeled using a network of interconnected resistors (R) and capacitors (C) at each node called R-C network. In this study, a model building, Case 600, as described in the “Standard Method of Test for the Evaluation of Building Energy Analysis Computer Program”, ASHRAE standard 140, is studied along with a 3R2C thermal network model and the ASHRAE clear sky solar radiation model. Although building an energy model involves two important parts of building component i.e., the envelope and internal mass, the effect of building internal mass is not considered in this study. All the characteristic parameters of the building envelope are evaluated as on Case 600. Finally, monthly building energy consumption from the thermal network model is compared with a simple-box energy model within reasonable accuracy. From the results, 0.6-9.4% variation of monthly energy consumption is observed because of the south-facing windows.
Keywords: ASHRAE case study, clear sky solar radiation model, energy modeling, thermal network model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11964229 Correlation of Viscosity in Nanofluids using Genetic Algorithm-neural Network (GA-NN)
Authors: Hajir Karimi, Fakheri Yousefi, Mahmood Reza Rahimi
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An accurate and proficient artificial neural network (ANN) based genetic algorithm (GA) is developed for predicting of nanofluids viscosity. A genetic algorithm (GA) is used to optimize the neural network parameters for minimizing the error between the predictive viscosity and the experimental one. The experimental viscosity in two nanofluids Al2O3-H2O and CuO-H2O from 278.15 to 343.15 K and volume fraction up to 15% were used from literature. The result of this study reveals that GA-NN model is outperform to the conventional neural nets in predicting the viscosity of nanofluids with mean absolute relative error of 1.22% and 1.77% for Al2O3-H2O and CuO-H2O, respectively. Furthermore, the results of this work have also been compared with others models. The findings of this work demonstrate that the GA-NN model is an effective method for prediction viscosity of nanofluids and have better accuracy and simplicity compared with the others models.Keywords: genetic algorithm, nanofluids, neural network, viscosity
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20724228 Authenticast: A Source Authentication Protocol for Multicast Flows and Streams
Authors: Yacine Challal, Abdelmadjid Bouabdallah
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The lack of security obstructs a large scale de- ployment of the multicast communication model. There- fore, a host of research works have been achieved in order to deal with several issues relating to securing the multicast, such as confidentiality, authentication, non-repudiation, in- tegrity and access control. Many applications require au- thenticating the source of the received traffic, such as broadcasting stock quotes and videoconferencing and hence source authentication is a required component in the whole multicast security architecture. In this paper, we propose a new and efficient source au- thentication protocol which guarantees non-repudiation for multicast flows, and tolerates packet loss. We have simu- lated our protocol using NS-2, and the simulation results show that the protocol allows to achieve improvements over protocols fitting into the same category.
Keywords: Source Authentication, Non-repudiation, Multicast Security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15124227 A Survey of Sentiment Analysis Based on Deep Learning
Authors: Pingping Lin, Xudong Luo, Yifan Fan
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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.Keywords: Natural language processing, sentiment analysis, document analysis, multimodal sentiment analysis, deep learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19724226 Bandwidth Estimation Algorithms for the Dynamic Adaptation of Voice Codec
Authors: Davide Pierattoni, Ivan Macor, Pier Luca Montessoro
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In the recent years multimedia traffic and in particular VoIP services are growing dramatically. We present a new algorithm to control the resource utilization and to optimize the voice codec selection during SIP call setup on behalf of the traffic condition estimated on the network path. The most suitable methodologies and the tools that perform realtime evaluation of the available bandwidth on a network path have been integrated with our proposed algorithm: this selects the best codec for a VoIP call in function of the instantaneous available bandwidth on the path. The algorithm does not require any explicit feedback from the network, and this makes it easily deployable over the Internet. We have also performed intensive tests on real network scenarios with a software prototype, verifying the algorithm efficiency with different network topologies and traffic patterns between two SIP PBXs. The promising results obtained during the experimental validation of the algorithm are now the basis for the extension towards a larger set of multimedia services and the integration of our methodology with existing PBX appliances.Keywords: Integrated voice-data communication, computernetwork performance, resource optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16834225 Application of Neural Network and Finite Element for Prediction the Limiting Drawing Ratio in Deep Drawing Process
Authors: H.Mohammadi Majd, M.Jalali Azizpour, A.V. Hoseini
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In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.Keywords: Back-propagation artificial neural network(BPANN), deep drawing, prediction, limiting drawing ratio (LDR).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17184224 Integrating Low and High Level Object Recognition Steps by Probabilistic Networks
Authors: András Barta, István Vajk
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In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem.
Keywords: Object recognition, Bayesian network, Wavelets, Document processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16594223 Proposal of a Model Supporting Decision-Making Based On Multi-Objective Optimization Analysis on Information Security Risk Treatment
Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu
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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.
Keywords: Information security risk treatment, Selection of risk measures, Risk acceptanceand Multi-objective optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17124222 Comparison between Beta Wavelets Neural Networks, RBF Neural Networks and Polynomial Approximation for 1D, 2DFunctions Approximation
Authors: Wajdi Bellil, Chokri Ben Amar, Adel M. Alimi
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This paper proposes a comparison between wavelet neural networks (WNN), RBF neural network and polynomial approximation in term of 1-D and 2-D functions approximation. We present a novel wavelet neural network, based on Beta wavelets, for 1-D and 2-D functions approximation. Our purpose is to approximate an unknown function f: Rn - R from scattered samples (xi; y = f(xi)) i=1....n, where first, we have little a priori knowledge on the unknown function f: it lives in some infinite dimensional smooth function space and second the function approximation process is performed iteratively: each new measure on the function (xi; f(xi)) is used to compute a new estimate f as an approximation of the function f. Simulation results are demonstrated to validate the generalization ability and efficiency of the proposed Beta wavelet network.
Keywords: Beta wavelets networks, RBF neural network, training algorithms, MSE, 1-D, 2D function approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19034221 Vague Multiple Criteria Decision Making Analysis Method for Fighter Aircraft Selection
Authors: C. Ardil
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Fighter aircraft selection is one of the most critical strategies for defense multiple criteria decision-making analysis to increase the decisive power of air defense and its superior power in the defense strategy. Vague set theory is an adequate approach for modeling vagueness, uncertainty, and imprecision in decision-making problems. This study integrates vague set theory and the technique for order of preference by similarity to ideal solution (TOPSIS) to support fighter aircraft selection. The proposed method is applied in the selection of fighter aircraft for the Air Force. In the proposed approach, the ratings of alternatives and the importance weights of criteria for fighter aircraft selection are represented by the vague set theory. Finally, an illustrative example for fighter aircraft selection is given to demonstrate the applicability and effectiveness of the proposed approach. The fighter aircraft candidates were selected under six criteria including costability, payloadability, maneuverability, speedability, stealthility, and survivability. Analysis results show that the best fighter aircraft is selected with the highest closeness coefficient value. The proposed method can also be applied to solve other multiple criteria decision analysis problems.
Keywords: fighter aircraft selection, vague set theory, fuzzy set theory, neutrosophic set theory, multiple criteria decision making analysis, MCDMA, TOPSIS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5114220 Predicting Extrusion Process Parameters Using Neural Networks
Authors: Sachin Man Bajimaya, SangChul Park, Gi-Nam Wang
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The objective of this paper is to estimate realistic principal extrusion process parameters by means of artificial neural network. Conventionally, finite element analysis is used to derive process parameters. However, the finite element analysis of the extrusion model does not consider the manufacturing process constraints in its modeling. Therefore, the process parameters obtained through such an analysis remains highly theoretical. Alternatively, process development in industrial extrusion is to a great extent based on trial and error and often involves full-size experiments, which are both expensive and time-consuming. The artificial neural network-based estimation of the extrusion process parameters prior to plant execution helps to make the actual extrusion operation more efficient because more realistic parameters may be obtained. And so, it bridges the gap between simulation and real manufacturing execution system. In this work, a suitable neural network is designed which is trained using an appropriate learning algorithm. The network so trained is used to predict the manufacturing process parameters.Keywords: Artificial Neural Network (ANN), Indirect Extrusion, Finite Element Analysis, MES.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23544219 Network of Coupled Stochastic Oscillators and One-way Quantum Computations
Authors: Eugene Grichuk, Margarita Kuzmina, Eduard Manykin
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A network of coupled stochastic oscillators is proposed for modeling of a cluster of entangled qubits that is exploited as a computation resource in one-way quantum computation schemes. A qubit model has been designed as a stochastic oscillator formed by a pair of coupled limit cycle oscillators with chaotically modulated limit cycle radii and frequencies. The qubit simulates the behavior of electric field of polarized light beam and adequately imitates the states of two-level quantum system. A cluster of entangled qubits can be associated with a beam of polarized light, light polarization degree being directly related to cluster entanglement degree. Oscillatory network, imitating qubit cluster, is designed, and system of equations for network dynamics has been written. The constructions of one-qubit gates are suggested. Changing of cluster entanglement degree caused by measurements can be exactly calculated.Keywords: network of stochastic oscillators, one-way quantumcomputations, a beam of polarized light.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13914218 The Truth about Good and Evil: A Mixed-Methods Approach to Color Theory
Authors: Raniya Alsharif
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The color theory of good and evil is the association of colors to the omnipresent concept of good and evil, where human behavior and perception can be highly influenced by seeing black and white, making these connotations almost dangerously distinctive where they can be very hard to distinguish. This theory is a human construct that dates back to ancient Egypt and has been used since then in almost all forms of communication and expression, such as art, fashion, literature, and religious manuscripts, helping the implantation of preconceived ideas that influence behavior and society. This is a mixed-methods research that uses both surveys to collect quantitative data related to the theory and a vignette to collect qualitative data by using a scenario where participants aged between 18-25 will style two characters of good and bad characteristics with color contrasting clothes, both yielding results about the nature of the preconceived perceptions associated with ‘black and white’ and ‘good and evil’, illustrating the important role of media and communications in human behavior and subconscious, and also uncover how far this theory goes in the age of social media enlightenment.
Keywords: Color perception, interpretivism, thematic analysis, vignettes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9834217 Food Security in Nigeria: An Examination of Food Availability and Accessibility in Nigeria
Authors: Chimaobi Valentine Okolo, Chizoba Obidigbo
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As a basic physiology need, threat to sufficient food production is threat to human survival. Food security has been an issue that has gained global concern. This paper looks at the food security in Nigeria by assessing the availability of food and accessibility of the available food. The paper employed multiple linear regression technique and graphic trends of growth rates of relevant variables to show the situation of food security in Nigeria. Results of the tests revealed that population growth rate was higher than the growth rate of food availability in Nigeria for the earlier period of the study. Commercial bank credit to agricultural sector, foreign exchange utilization for food and the Agricultural Credit Guarantee Scheme Fund (ACGSF) contributed significantly to food availability in Nigeria. Food prices grew at a faster rate than the average income level, making it difficult to access sufficient food. It implies that prior to the year 2012; there was insufficient food to feed the Nigerian populace. However, continued credit to the food and agricultural sector will ensure sustained and sufficient production of food in Nigeria. Microfinance banks should make sufficient credit available to smallholder farmer. Government should further control and subsidize the rising price of food to make it more accessible by the people.Keywords: Food security, food availability and food accessibility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 61264216 Description and Analysis of Embedded Firewall Techniques
Authors: Ahmed Abou Elfarag, A. Baith M., Hassan H. Alkhishali
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With the turn of this century, many researchers started showing interest in Embedded Firewall (EF) implementations. These are not the usual firewalls that are used as checkpoints at network gateways. They are, rather, applied near those hosts that need protection. Hence by using them, individual or grouped network components can be protected from the inside as well as from external attacks. This paper presents a study of EF-s, looking at their architecture and problems. A comparative study assesses how practical each kind is. It particularly focuses on the architecture, weak points, and portability of each kind. A look at their use by different categories of users is also presented.Keywords: Embedded Firewall (EF), Network Interface Card (NIC), Virtual Machine Software (VMware), Virtual Firewall (VF).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17044215 An Energy Efficient Algorithm for Distributed Mutual Exclusion in Mobile Ad-hoc Networks
Authors: Sayani Sil, Sukanta Das
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This paper reports a distributed mutual exclusion algorithm for mobile Ad-hoc networks. The network is clustered hierarchically. The proposed algorithm considers the clustered network as a logical tree and develops a token passing scheme to get the mutual exclusion. The performance analysis and simulation results show that its message requirement is optimal, and thus the algorithm is energy efficient.Keywords: Critical section, Distributed mutual exclusion, MobileAd-hoc network, Token-based algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17374214 Neural Network Ensemble-based Solar Power Generation Short-Term Forecasting
Authors: A. Chaouachi, R.M. Kamel, R. Ichikawa, H. Hayashi, K. Nagasaka
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This paper presents the applicability of artificial neural networks for 24 hour ahead solar power generation forecasting of a 20 kW photovoltaic system, the developed forecasting is suitable for a reliable Microgrid energy management. In total four neural networks were proposed, namely: multi-layred perceptron, radial basis function, recurrent and a neural network ensemble consisting in ensemble of bagged networks. Forecasting reliability of the proposed neural networks was carried out in terms forecasting error performance basing on statistical and graphical methods. The experimental results showed that all the proposed networks achieved an acceptable forecasting accuracy. In term of comparison the neural network ensemble gives the highest precision forecasting comparing to the conventional networks. In fact, each network of the ensemble over-fits to some extent and leads to a diversity which enhances the noise tolerance and the forecasting generalization performance comparing to the conventional networks.Keywords: Neural network ensemble, Solar power generation, 24 hour forecasting, Comparative study
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32624213 Arterial Stiffness Detection Depending on Neural Network Classification of the Multi- Input Parameters
Authors: Firas Salih, Luban Hameed, Afaf Kamil, Armin Bolz
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Diagnostic and detection of the arterial stiffness is very important; which gives indication of the associated increased risk of cardiovascular diseases. To make a cheap and easy method for general screening technique to avoid the future cardiovascular complexes , due to the rising of the arterial stiffness ; a proposed algorithm depending on photoplethysmogram to be used. The photoplethysmograph signals would be processed in MATLAB. The signal will be filtered, baseline wandering removed, peaks and valleys detected and normalization of the signals should be achieved .The area under the catacrotic phase of the photoplethysmogram pulse curve is calculated using trapezoidal algorithm ; then will used in cooperation with other parameters such as age, height, blood pressure in neural network for arterial stiffness detection. The Neural network were implemented with sensitivity of 80%, accuracy 85% and specificity of 90% were got from the patients data. It is concluded that neural network can detect the arterial STIFFNESS depending on risk factor parameters.Keywords: Arterial stiffness, area under the catacrotic phase of the photoplethysmograph pulse, neural network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16394212 Evaluation and Analysis of the Secure E-Voting Authentication Preparation Scheme
Authors: Nidal F. Shilbayeh, Reem A. Al-Saidi, Ahmed H. Alsswey
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In this paper, we presented an evaluation and analysis of E-Voting Authentication Preparation Scheme (EV-APS). EV-APS applies some modified security aspects that enhance the security measures and adds a strong wall of protection, confidentiality, non-repudiation and authentication requirements. Some of these modified security aspects are Kerberos authentication protocol, PVID scheme, responder certificate validation, and the converted Ferguson e-cash protocol. Authentication and privacy requirements have been evaluated and proved. Authentication guaranteed only eligible and authorized voters were permitted to vote. Also, the privacy guaranteed that all votes will be kept secret. Evaluation and analysis of some of these security requirements have been given. These modified aspects will help in filtering the counter buffer from unauthorized votes by ensuring that only authorized voters are permitted to vote.
Keywords: E-Voting preparation stage, blind signature protocol, nonce based authentication scheme, Kerberos authentication protocol, pseudo voter identity scheme PVID.
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