Search results for: Large scale networks

Authors: N.E.Galich

Abstract:

We develop new nonlinear methods of immunofluorescence analysis for a sensitive technology of respiratory burst reaction of DNA fluorescence due to oxidative activity in the peripheral blood neutrophils. Histograms in flow cytometry experiments represent a fluorescence flashes frequency as functions of fluorescence intensity. We used the Shannon-Weaver index for definition of neutrophils- biodiversity and Hurst index for definition of fractal-s correlations in immunofluorescence for different donors, as the basic quantitative criteria for medical diagnostics of health status. We analyze frequencies of flashes, information, Shannon entropies and their fractals in immunofluorescence networks due to reduction of histogram range. We found the number of simplest universal correlations for biodiversity, information and Hurst index in diagnostics and classification of pathologies for wide spectra of diseases. In addition is determined the clear criterion of a common immunity and human health status in a form of yes/no answers type. These answers based on peculiarities of information in immunofluorescence networks and biodiversity of neutrophils. Experimental data analysis has shown the existence of homeostasis for information entropy in oxidative activity of DNA in neutrophil nuclei for all donors.

Keywords: blood and cells fluorescence in diagnostics ofdiseases, cytometric histograms, entropy and information in fractalnetworks of oxidative activity of DNA, long-range chromosomalcorrelations in living cells.

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Authors: Arpiruk Hokpunna, Michael Manhart

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We present a Large-Eddy simulation of a vortex cell with circular shaped. The results show that the flow field can be sub divided into four important zones, the shear layer above the cavity, the stagnation zone, the vortex core in the cavity and the boundary layer along the wall of the cavity. It is shown that the vortex core consits of solid body rotation without much turbulence activity. The vortex is mainly driven by high energy packets that are driven into the cavity from the stagnation point region and by entrainment of fluid from the cavity into the shear layer. The physics in the boundary layer along the cavity-s wall seems to be far from that of a canonical boundary layer which might be a crucial point for modelling this flow.

Keywords: Turbulent flow, Large eddy simulations, boundary layer and cavity flow, vortex cell flow.

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Authors: B. Cynthia Sherin, E. A. Mary Anita

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Vehicular Ad-hoc Network (VANET) is an emerging and very promising technology that has great demand on the access capability of the existing wireless technology. VANETs help improve traffic safety and efficiency. Each vehicle can exchange their information to inform the other vehicles about the current status of the traffic flow or a dangerous situation such as an accident. To achieve these, a reliable and efficient Medium Access Control (MAC) protocol with minimal transmission collisions is required. High speed nodes, absence of infrastructure, variations in topology and their QoS requirements makes it difficult for designing a MAC protocol in vehicular networks. There are several MAC protocols proposed for VANETs to ensure that all the vehicles could send safety messages without collisions by reducing the end-to-end delay and packet loss ratio. This paper gives an overview of the several proposed MAC protocols for VANETs along with their benefits and limitations and presents an overall classification based on their characteristics.

Keywords: MAC Protocols, QoS, VANET, V2V, V2I.

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Authors: F. Matusek, G. Pujolle, R. Reda

Abstract:

Shadow detection is still considered as one of the potential challenges for intelligent automated video surveillance systems. A pre requisite for reliable and accurate detection and tracking is the correct shadow detection and classification. In such a landscape of conditions, privacy issues add more and more complexity and require reliable shadow detection. In this work the intertwining between security, accuracy, reliability and privacy is analyzed and, accordingly, a novel architecture for Privacy Enhancing Video Surveillance (PEVS) is introduced. Shadow detection and masking are dealt with through the combination of two different approaches simultaneously. This results in a unique privacy enhancement, without affecting security. Subsequently, the methodology was employed successfully in a large-scale wireless video surveillance system; privacy relevant information was stored and encrypted on the unit, without transferring it over an un-trusted network.

Keywords: Video Surveillance, Intelligent Video Surveillance, Physical Security, WSSU, Privacy, Shadow Detection.

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Authors: Tuba Tekin, Nurcan Baglam, Emine Dincer

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This study aimed to examine the effects of nutrition education received by university students on sustainable healthy eating behaviors and adherence to the Mediterranean diet. The 2nd, 3rd, and 4th-grade university students studying at the Faculty of Health Sciences, Nutrition and Dietetics, Midwifery, Nursing, Physical Therapy, and Rehabilitation departments of universities in Turkey were included in the study. Students' adherence to the Mediterranean diet was evaluated using the Mediterranean Diet Adherence Scale, and their sustainable and healthy eating behaviors were evaluated using the Sustainable and Healthy Eating Behaviors Scale. In addition, the body weight and height of the students were measured by the researchers, and the Body Mass Index (BMI) value was calculated. A total of 181 students, 85 of whom were studying in the Department of Nutrition and Dietetics and 96 of whom were educated in other departments, were included in the study; 75.7% of the students in the sample are female, while 24.3% are male. The average body weight of the students was 61.17 ± 10.87 kg, and the average BMI was 22.04 ± 3.40 kg/m2. While the mean score of the Mediterranean Diet Adherence Scale was 6.72 ± 1.84, in the evaluation of adherence to the Mediterranean diet, it was determined that 25.4% of the students had poor adherence and 66.9% needed improvement. When the adherence scores of students who received and did not receive nutrition education were compared, it was discovered that the students who received nutrition education had a higher score (p < 0.05). Students who received nutrition education had a higher total score on the Sustainable and Healthy Eating Behaviors scale (p < 0.05). A moderately positive correlation was found between the Sustainable and Healthy Eating Behaviors scale total score and the Mediterranean Diet Adherence scores (p < 0.05). As a result of the linear regression analysis, it was revealed that a 1-unit increase in the Mediterranean diet adherence score would result in a 1.3-point increase in the total score of the Sustainable and Healthy Eating Behaviors scale. Sustainable and healthy diets are important for improving and developing health and the prevention of diseases. The Mediterranean diet is defined as a sustainable diet model. The findings revealed the relationship between the Mediterranean diet and sustainable nutrition and showed that nutrition education increased knowledge and awareness about sustainable nutrition and increased adherence to the Mediterranean diet. For this reason, courses or seminars on sustainable nutrition can be organized during educational periods.

Keywords: Healthy eating, Mediterranean diet, nutrition education, sustainable nutrition.

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Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

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Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat, Malware, Network Security, Network Packet, Exploit Kits.

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Authors: Shuen-Tai Wang, Ying-Chuan Chen, Hsi-Ya Chang

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The rapid improvement of the microprocessor and network has made it possible for the PC cluster to compete with conventional supercomputers. Lots of high throughput type of applications can be satisfied by using the current desktop PCs, especially for those in PC classrooms, and leave the supercomputers for the demands from large scale high performance parallel computations. This paper presents our development on enabling an automated deployment mechanism for cluster computing to utilize the computing power of PCs such as reside in PC classroom. After well deployment, these PCs can be transformed into a pre-configured cluster computing resource immediately without touching the existing education/training environment installed on these PCs. Thus, the training activities will not be affected by this additional activity to harvest idle computing cycles. The time and manpower required to build and manage a computing platform in geographically distributed PC classrooms also can be reduced by this development.

Keywords: PC cluster, automated deployment, cluster computing, PC classroom.

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Authors: Anupama Pande, Vishik Goel

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A complex valued neural network is a neural network, which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in image and vision processing. In Neural networks, radial basis functions are often used for interpolation in multidimensional space. A Radial Basis function is a function, which has built into it a distance criterion with respect to a centre. Radial basis functions have often been applied in the area of neural networks where they may be used as a replacement for the sigmoid hidden layer transfer characteristic in multi-layer perceptron. This paper aims to present exhaustive results of using RBF units in a complex-valued neural network model that uses the back-propagation algorithm (called 'Complex-BP') for learning. Our experiments results demonstrate the effectiveness of a Radial basis function in a complex valued neural network in image recognition over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error on a neural network model with RBF units. Some inherent properties of this complex back propagation algorithm are also studied and discussed.

Keywords: Complex valued neural network, Radial BasisFunction, Image recognition.

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Authors: D.M. Weeraddana, K.S. Walgama, E.C. Kulasekere

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A framework to estimate the state of dynamically varying environment where data are generated from heterogeneous sources possessing partial knowledge about the environment is presented. This is entirely derived within Dempster-Shafer and Evidence Filtering frameworks. The belief about the current state is expressed as belief and plausibility functions. An addition to Single Input Single Output Evidence Filter, Multiple Input Single Output Evidence Filtering approach is introduced. Variety of applications such as situational estimation of an emergency environment can be developed within the framework successfully. Fire propagation scenario is used to justify the proposed framework, simulation results are presented.

Keywords: Dempster-Shafer Belief theory, Evidence Filtering, Evidence Fusion, Sensor Modalities, Wireless Sensor Networks

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Authors: Aleksandar Tsenov

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The main goal of this work is to propose a way for combined use of two nontraditional algorithms by solving topological problems on telecommunications concentrator networks. The algorithms suggested are the Simulated Annealing algorithm and the Genetic Algorithm. The Algorithm of Simulated Annealing unifies the well known local search algorithms. In addition - Simulated Annealing allows acceptation of moves in the search space witch lead to decisions with higher cost in order to attempt to overcome any local minima obtained. The Genetic Algorithm is a heuristic approach witch is being used in wide areas of optimization works. In the last years this approach is also widely implemented in Telecommunications Networks Planning. In order to solve less or more complex planning problem it is important to find the most appropriate parameters for initializing the function of the algorithm.

Keywords: Concentrator network, genetic algorithm, simulated annealing, UCPL.

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Authors: Amir Gholami Pastaki, Ali Reza Sahab, Seyed Mehdi Sadeghi

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LSP routing is among the prominent issues in MPLS networks traffic engineering. The objective of this routing is to increase number of the accepted requests while guaranteeing the quality of service (QoS). Requested bandwidth is the most important QoS criterion that is considered in literatures, and a various number of heuristic algorithms have been presented with that regards. Many of these algorithms prevent flows through bottlenecks of the network in order to perform load balancing, which impedes optimum operation of the network. Here, a modern routing algorithm is proposed as MIRAD: having a little information of the network topology, links residual bandwidth, and any knowledge of the prospective requests it provides every request with a maximum bandwidth as well as minimum end-to-end delay via uniform load distribution across the network. Simulation results of the proposed algorithm show a better efficiency in comparison with similar algorithms.

Keywords: new generation networks, QoS, traffic engineering, MPLS, QoS based routing, LSP

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Authors: Tomohiro Hachino, Kengo Nagatomo, Hitoshi Takata

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This paper deals with an on-line identification method of continuous-time Hammerstein systems by using the radial basis function (RBF) networks and immune algorithm (IA). An unknown nonlinear static part to be estimated is approximately represented by the RBF network. The IA is efficiently combined with the recursive least-squares (RLS) method. The objective function for the identification is regarded as the antigen. The candidates of the RBF parameters such as the centers and widths are coded into binary bit strings as the antibodies and searched by the IA. On the other hand, the candidates of both the weighting parameters of the RBF network and the system parameters of the linear dynamic part are updated by the RLS method. Simulation results are shown to illustrate the proposed method.

Keywords: Continuous-time System, Hammerstein System, OnlineIdentification, Immune Algorithm, RBF network.

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Authors: M. Behbahani-Nejad, A. Bagheri

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An efficient transient flow simulation for gas pipelines and networks is presented. The proposed transient flow simulation is based on the transfer function models and MATLABSimulink. The equivalent transfer functions of the nonlinear governing equations are derived for different types of the boundary conditions. Next, a MATLAB-Simulink library is developed and proposed considering any boundary condition type. To verify the accuracy and the computational efficiency of the proposed simulation, the results obtained are compared with those of the conventional finite difference schemes (such as TVD, method of lines, and other finite difference implicit and explicit schemes). The effects of the flow inertia and the pipeline inclination are incorporated in this simulation. It is shown that the proposed simulation has a sufficient accuracy and it is computationally more efficient than the other methods.

Keywords: Gas network, MATLAB-Simulink, transfer functions, transient flow.

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Authors: Audrey Heffron, Casserleigh, Jarrett Broder, Brad Skillman

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Traditionally, terror groups have been formed by ideologically aligned actors who perceive a lack of options for achieving political or social change. However, terrorist attacks have been increasingly carried out by small groups of actors or lone individuals who may be only ideologically affiliated with larger, formal terrorist organizations. The formation of these groups represents the inverse of traditional organizational growth, whereby structural de-evolution within issue-based organizations leads to the formation of small, independent terror cells. Ideological franchising – the bypassing of formal affiliation to the “parent" organization – represents the de-evolution of traditional concepts of organizational structure in favor of an organic, independent, and focused unit. Traditional definitions of dark networks that are issue-based include focus on an identified goal, commitment to achieving this goal through unrestrained actions, and selection of symbolic targets. The next step in the de-evolution of small dark networks is the miniorganization, consisting of only a handful of actors working toward a common, violent goal. Information-sharing through social media platforms, coupled with civil liberties of democratic nations, provide the communication systems, access to information, and freedom of movement necessary for small dark networks to flourish without the aid of a parent organization. As attacks such as the 7/7 bombings demonstrate the effectiveness of small dark networks, terrorist actors will feel increasingly comfortable aligning with an ideology only, without formally organizing. The natural result of this de-evolving organization is the single actor event, where an individual seems to subscribe to a larger organization-s violent ideology with little or no formal ties.

Keywords: Organizational de-evolution, single actor, small group, terrorism.

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Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

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For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: High-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network.

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Authors: Mujtaba Roshan, John A. Schormans

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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: Narendra Singh Yadav, R.P.Yadav

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Mobile ad hoc network is a collection of mobile nodes communicating through wireless channels without any existing network infrastructure or centralized administration. Because of the limited transmission range of wireless network interfaces, multiple "hops" may be needed to exchange data across the network. Consequently, many routing algorithms have come into existence to satisfy the needs of communications in such networks. Researchers have conducted many simulations comparing the performance of these routing protocols under various conditions and constraints. One question that arises is whether speed of nodes affects the relative performance of routing protocols being studied. This paper addresses the question by simulating two routing protocols AODV and DSDV. Protocols were simulated using the ns-2 and were compared in terms of packet delivery fraction, normalized routing load and average delay, while varying number of nodes, and speed.

Keywords: AODV, DSDV, MANET, relative performance

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Authors: Frank Emmert-Streib, Matthias Dehmer, Jing Liu, Max Muhlhauser

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The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Keywords: Graph similarity, generalized trees, graph alignment, DNA microarray data, cervical cancer.

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Authors: Chia-Feng Lu, Yuh-Jen Wang, Shin Teng, Yu-Te Wu, Sui-Hing Yan

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Brain functional networks based on resting-state EEG data were compared between patients with mild Alzheimer’s disease (mAD) and matched patients with amnestic subtype of mild cognitive impairment (aMCI). We integrated the time–frequency cross mutual information (TFCMI) method to estimate the EEG functional connectivity between cortical regions and the network analysis based on graph theory to further investigate the alterations of functional networks in mAD compared with aMCI group. We aimed at investigating the changes of network integrity, local clustering, information processing efficiency, and fault tolerance in mAD brain networks for different frequency bands based on several topological properties, including degree, strength, clustering coefficient, shortest path length, and efficiency. Results showed that the disruptions of network integrity and reductions of network efficiency in mAD characterized by lower degree, decreased clustering coefficient, higher shortest path length, and reduced global and local efficiencies in the delta, theta, beta2, and gamma bands were evident. The significant changes in network organization can be used in assisting discrimination of mAD from aMCI in clinical.

Keywords: EEG, functional connectivity, graph theory, TFCMI.

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Authors: Mehdi Saeidmanesh, Mojtaba Hajimohammadi, Ali Movaghar

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In this paper, we propose an energy efficient cluster based communication protocol for wireless sensor network. Our protocol considers both the residual energy of sensor nodes and the distance of each node from the BS when selecting cluster-head. This protocol can successfully prolong the network-s lifetime by 1) reducing the total energy dissipation on the network and 2) evenly distributing energy consumption over all sensor nodes. In this protocol, the nodes with more energy and less distance from the BS are probable to be selected as cluster-head. Simulation results with MATLAB show that proposed protocol could increase the lifetime of network more than 94% for first node die (FND), and more than 6% for the half of the nodes alive (HNA) factor as compared with conventional protocols.

Keywords: Clustering methods, energy efficiency, routing protocol, wireless sensor networks.

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Authors: Dana Madalina Pohrib, Elena Irina Ciobanu

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In compaction works, the most often used codes and standards are those for road embankments and refer to a maximum filling height of 3.00m. When filling a height greater than 3.00m, such codes are no longer valid and thus their application may lead to technical difficulties in the process of compaction and to the achievement of a sufficient degree of compaction. For this reason, in the case of controlled fillings with heights greater than 3.00m it is necessary to formulate and apply a number of special techniques, which can be determined by performing a full scale test. This paper presents the results of the studies and full scale tests conducted for the stabilization of a ravine with vertical banks and a depth of about 12.00m. The fillings will support a heavy traffic road connecting the two parts of a village in Vaslui County, Romania. After analyzing two comparative intervention solutions, the variant of a controlled filling bordered by a monolith concrete retaining wall was chosen. The results obtained by the authors highlighted the need to insert a geogrid reinforcement at every 2.00m for creating a 12.00m thick compacted fill.

Keywords: Compaction, dynamic probing, stability, soil stratification.

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Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil

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Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.

Keywords: Backpropagation algorithm, conjugacy condition, line search, matrix perturbation

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Authors: Khalide Jbilou

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In the present paper, we propose numerical methods for solving the Stein equation AXC - X - D = 0 where the matrix A is large and sparse. Such problems appear in discrete-time control problems, filtering and image restoration. We consider the case where the matrix D is of full rank and the case where D is factored as a product of two matrices. The proposed methods are Krylov subspace methods based on the block Arnoldi algorithm. We give theoretical results and we report some numerical experiments.

Keywords: IEEEtran, journal, LATEX, paper, template.

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Authors: Kurniawan D. Irianto, Demetres D. Kouvatsos

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The growth of wireless devices affects the availability of limited frequencies or spectrum bands as it has been known that spectrum bands are a natural resource that cannot be added. Meanwhile, the licensed frequencies are idle most of the time. Cognitive radio is one of the solutions to solve those problems. Cognitive radio is a promising technology that allows the unlicensed users known as secondary users (SUs) to access licensed bands without making interference to licensed users or primary users (PUs). As cloud computing has become popular in recent years, cognitive radio networks (CRNs) can be integrated with cloud platform. One of the important issues in CRNs is security. It becomes a problem since CRNs use radio frequencies as a medium for transmitting and CRNs share the same issues with wireless communication systems. Another critical issue in CRNs is performance. Security has adverse effect to performance and there are trade-offs between them. The goal of this paper is to investigate the performance related to security trade-off in CRNs with supporting cloud platforms. Furthermore, Queuing Network Models with preemptive resume and preemptive repeat identical priority are applied in this project to measure the impact of security to performance in CRNs with or without cloud platform. The generalized exponential (GE) type distribution is used to reflect the bursty inter-arrival and service times at the servers. The results show that the best performance is obtained when security is disabled and cloud platform is enabled.

Keywords: Cloud Platforms, Cognitive Radio Networks, GEtype Distribution, Performance Vs Security.

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Authors: Chutima Prommak, Airisa Jantaweetip

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In wireless networks, bandwidth is scare resource and it is essential to utilize it effectively. This paper analyses effects of using different bandwidth management techniques on the network performances of the Wireless Local Area Networks (WLANs) that use hybrid load balancing scheme. In particular, we study three bandwidth management schemes, namely Complete Sharing (CS), Complete Partitioning (CP), and Partial Sharing (PS). Performances of these schemes are evaluated by simulation experiments in term of percentage of network association blocking. Our results show that the CS scheme can provide relatively low blocking percentage in various network traffic scenarios whereas the PS scheme can enhance quality of services of the multimedia traffic with rather small expenses on the blocking percentage of the best effort traffic.

Keywords: Bandwidth management, Load Balancing, WLANs.

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Authors: Jatin Kumar Choudhary, Naren Rayala, Abbas Eslami Kiasari, Fahimeh Jafari

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Great Britain has one of the safest road networks in the world. However, the consequences of any death or serious injury are devastating for loved ones, as well as for those who help the severely injured. This paper aims to analyse Great Britain's road safety situation and show the response measures for areas where the total damage caused by accidents can be significantly and quickly reduced. For the past 30 years, the UK has had a good record in reducing fatalities over the past 30 years, there is still a considerable number of road deaths. The government continues to scale back road deaths empowering responsible road users by identifying and prosecuting the parameters that make the roads less safe. This study represents an exploratory analysis with deep insights which could provide policy makers with invaluable insights into how accidents happen and how they can be mitigated. We use STATS19 data published by the UK government. Since we need more information about locations which is not provided in STATA19, we first expand the features of the dataset using OpenStreetMap and Visual Crossing. This paper also provides a discussion regarding new road safety methods.

Keywords: Road safety, data analysis, OpenStreetMap, feature expanding.

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Authors: M. A. Bajaber, M. A. Taha

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Contractor selection in Saudi Arabia is very important due to the large construction boom and the contractor role to get over construction risks. The need for investigating contractor selection is due to the following reasons; large number of defaulted or failed projects (18%), large number of disputes attributed to contractor during the project execution stage (almost twofold), the extension of the General Agreement on Tariffs and Trade (GATT) into construction industry, and finally the few number of researches. The selection strategy is not perfect and considered as the reason behind irresponsible contractors. As a response, this research was conducted to review the contractor selection strategies as an integral part of a long advanced research to develop a good selection model. Many techniques can be used to form a selection strategy; multi criteria for optimizing decision, prequalification to discover contractor-s responsibility, bidding process for competition, third party guarantee to enhance the selection, and fuzzy techniques for ambiguities and incomplete information.

Keywords: Bidding, Construction industry, Contractor selection, Saudi Arabia.

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Authors: Han Park, JooSeok Song

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We propose an enhanced key management scheme based on Key Infection, which is lightweight scheme for tiny sensors. The basic scheme, Key Infection, is perfectly secure against node capture and eavesdropping if initial communications after node deployment is secure. If, however, an attacker can eavesdrop on the initial communications, they can take the session key. We use common neighbors for each node to generate the session key. Each node has own secret key and shares it with its neighbor nodes. Then each node can establish the session key using common neighbors- secret keys and a random number. Our scheme needs only a few communications even if it uses neighbor nodes- information. Without losing the lightness of basic scheme, it improves the resistance against eavesdropping on the initial communications more than 30%.

Keywords: Wireless Sensor Networks, Key Management

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Authors: Charalampos Saridakis, Stelios Tsafarakis

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Although environmental concern is on the rise across Europe, current market data indicate that adoption rates of environmentally friendly vehicles remain extremely low. Against this background, the aim of this paper is to a) assess preferences of European consumers for clean-fuel cars and their characteristics and b) design car lines that optimize the combination of fuel types among models in the line-up. In this direction, the authors introduce a new evolutionary mechanism and implement it to stated-preference data derived from a large-scale choice-based conjoint experiment that measures consumer preferences for various factors affecting clean-fuel vehicle (CFV) adoption. The proposed two-step methodology provides interesting insights into how new and existing fuel-types can be combined in a car line that maximizes customer satisfaction.

Keywords: Clean-fuel vehicles, product line design, conjoint analysis, choice experiment, differential evolution.

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Authors: Badr M. Alshammari, Mohamed A. El-Kady

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The paper presents new results of a recent industry supported research and development study in which an efficient framework for evaluating practical and meaningful power system reliability and quality indices was applied. The system-wide integrated performance indices are capable of addressing and revealing areas of deficiencies and bottlenecks as well as redundancies in the composite generation-transmission-demand structure of large-scale power grids. The technique utilizes a linear programming formulation, which simulates practical operating actions and offers a general and comprehensive framework to assess the harmony and compatibility of generation, transmission and demand in a power system. Practical applications to a reduced system model as well as a portion of the Saudi power grid are also presented in the paper for demonstration purposes.

Keywords: Power systems, Linear programming, Quality assessment, Reliability.

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