Search results for: Mobile Network Operator

Authors: DongHoon Shin, Yunmook Nah, HoSeong Kim, Gang Shin Lee, Jae-Il Lee

Abstract:

The rapid advance of communication technology is evolving the network environment into the broadband convergence network. Likewise, the IT services operated in the individual network are also being quickly converged in the broadband convergence network environment. VoIP and IPTV are two examples of such new services. Efforts are being made to develop the video phone service, which is an advanced form of the voice-oriented VoIP service. However, the new IT services will be subject to stability and reliability vulnerabilities if the relevant security issues are not answered during the convergence of the existing IT services currently being operated in individual networks within the wider broadband network environment. To resolve such problems, this paper attempts to analyze the possible threats and identify the necessary security measures before the deployment of the new IT services. Furthermore, it measures the quality of the encryption algorithm application example to describe the appropriate algorithm in order to present security technology that will have no negative impact on the quality of the video phone service.

Keywords: BcN, Security Measures, Video Phone.

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Authors: Mihails Kulikovs, Ernests Petersons

Abstract:

Network management techniques have long been of interest to the networking research community. The queue size plays a critical role for the network performance. The adequate size of the queue maintains Quality of Service (QoS) requirements within limited network capacity for as many users as possible. The appropriate estimation of the queuing model parameters is crucial for both initial size estimation and during the process of resource allocation. The accurate resource allocation model for the management system increases the network utilization. The present paper demonstrates the results of empirical observation of memory allocation for packet-based services.

Keywords: Queuing System, Packet Loss Probability, Measurement-Based Admission Control (MBAC), Performanceevaluation, Quality of Service (QoS).

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Authors: Maha Awad M. Almuttairi

Abstract:

This research aimed to measure the impact of the use of a mobile learning (iTunes U) app for the development of metacognition skills delivered in the enrichment program offered to gifted students at the secondary level in Jeddah. The author targeted a group of students on an experimental scale to evaluate the achievement. The research sample consisted of a group of 38 gifted female students. The scale of evaluation of the metacognition skills used to measure the performance of students in the enrichment program was as follows: Satisfaction scale for the assessment of the technique used and the final product form after completion of the program. Appropriate statistical treatment used includes Paired Samples T-Test Cronbach’s alpha formula and eta squared formula. It was concluded in the results the difference of α≤ 0.05, which means the performance of students in the skills of metacognition in favor of using iTunes U. In light of the conclusion of the experiment, a number of recommendations and suggestions were present; the most important benefit of mobile learning applications is to provide enrichment programs for gifted students in the Kingdom of Saudi Arabia, as well as conducting further research on mobile learning and gifted student teaching.

Keywords: Enrichment program, gifted students, metacognition skills.

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Authors: Guangzhuang Yu, Chun-Chu Liu

Abstract:

With the advent of the Internet era in recent years, social music education has gradually shifted from the original entity education mode to the mode of entity plus network teaching. No matter for school music education, professional music education or social music education, the teaching quality is the most important evaluation index. Regarding the research on teaching quality evaluation, scholars at home and abroad have contributed a lot of research results on the basis of multiple methods and evaluation subjects. However, to our best knowledge the complete evaluation model for the virtual teaching interaction mode of the emerging network music education Application (APP) has not been established. This research firstly found out the basic dimensions that accord with the teaching quality required by the three parties, constructing the quality evaluation index system; and then, on the basis of expounding the connotation of each index, it determined the weight of each index by using method of fuzzy analytic hierarchy process, providing ideas and methods for scientific, objective and comprehensive evaluation of the teaching quality of network education APP.

Keywords: Network music education APP, teaching quality evaluation, index, connotation.

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Authors: Sheng Fu, Yinbo Gao, Hao Lin

Abstract:

In the current mine air compressors monitoring system, there are some difficulties in the installation and maintenance because of the wired connection. To solve the problem, this paper introduces a new air compressors monitoring system based on ZigBee in which the monitoring parameters are transmitted wirelessly. The collecting devices are designed to form a cluster network to collect vibration, temperature, and pressure of air cylinders and other parameters. All these devices are battery-powered. Besides, the monitoring software in PC is developed using MFC. Experiments show that the designed wireless sensor network works well in the site environmental condition and the system is very convenient to be installed since the wireless connection. This monitoring system will have a wide application prospect in the upgrade of the old monitoring system of the air compressors.

Keywords: Condition monitoring, wireless sensor network, air compressor, ZigBee, data collecting

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Authors: P. Prasanna Murali Krishna, M. V. Subramanyam, K. Satya Prasad

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File sharing in networks is generally achieved using Peer-to-Peer (P2P) applications. Structured P2P approaches are widely used in adhoc networks due to its distributed and scalability features. Efficient mechanisms are required to handle the huge amount of data distributed to all peers. The intrinsic characteristics of P2P system makes for easier content distribution when compared to client-server architecture. All the nodes in a P2P network act as both client and server, thus, distributing data takes lesser time when compared to the client-server method. CHORD protocol is a resource routing based where nodes and data items are structured into a 1- dimensional ring. The structured lookup algorithm of Chord is advantageous for distributed P2P networking applications. However, structured approach improves lookup performance in a high bandwidth wired network it could contribute to unnecessary overhead in overlay networks leading to degradation of network performance. In this paper, the performance of existing CHORD protocol on Wireless Mesh Network (WMN) when nodes are static and dynamic is investigated.

Keywords: Wireless mesh network (WMN), structured P2P networks, peer to peer resource sharing, CHORD protocol, DHT.

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Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: Neural network, gravitational resistance, pattern recognition, non-linear.

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Authors: Ji-Young Song, Moon-Shuk Song, Hee-Seung Na

Abstract:

Recently, Northeast Asia has become one of the three largest trade areas, covering approximately 30% of the total trade volume of the world. However, the distribution facilities are saturated due to the increase in the transportation volume within the area and with the European countries. In order to accommodate the increase of the transportation volume, the transportation networking with the major countries in Northeast Asia and Europe is absolutely necessary. The Eurasian Logistics Network will develop into an international passenger transportation network covering the Northeast Asian region and an international freight transportation network connecting across Eurasia Continent. This paper surveys the changes and trend of the distribution network in the Eurasian Region according to the political, economic and environmental changes of the region, analyses the distribution network according to the changes in the transportation policies of the related countries, and provides the direction of the development of composite transportation on the basis of the present conditions of transportation means. The transportation means optimal for the efficiency of transportation system are suggested to be train ferries, sea & rail or sea & rail & sea. It is suggested to develop diversified composite transportation means and routes within the boundary of international cooperation system.

Keywords: Eurasian Logistics, Integrated Distribution Transport, Northeast Asia, Transportation Networking

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Authors: Abdallah Al Sabbagh

Abstract:

Next Generation Wireless Network (NGWN) is expected to be a heterogeneous network which integrates all different Radio Access Technologies (RATs) through a common platform. A major challenge is how to allocate users to the most suitable RAT for them. An optimized solution can lead to maximize the efficient use of radio resources, achieve better performance for service providers and provide Quality of Service (QoS) with low costs to users. Currently, Radio Resource Management (RRM) is implemented efficiently for the RAT that it was developed. However, it is not suitable for a heterogeneous network. Common RRM (CRRM) was proposed to manage radio resource utilization in the heterogeneous network. This paper presents a user level Markov model for a three co-located RAT networks. The load-balancing based and service based CRRM algorithms have been studied using the presented Markov model. A comparison for the performance of load-balancing based and service based CRRM algorithms is studied in terms of traffic distribution, new call blocking probability, vertical handover (VHO) call dropping probability and throughput.

Keywords: Heterogeneous Wireless Network, Markov chain model, load-balancing based and service based algorithm, CRRM algorithms, Beyond 3G network.

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Authors: Satien Janpla, Thanawan Boonpuck, Pattarapan Roonrakwit 

Abstract:

In this paper, we present a hamster knowledge system based on android application. The objective of this system is to advice user to upkeep and feed hamsters based on mobile application. We describe the design approaches and functional components of this system. The system was developed based on knowledge based of hamster experts. The results were divided by the research purposes into 2 parts: developing the mobile application for advice users and testing and evaluating the system. Black box technique was used to evaluate application performances and questionnaires were applied to measure user satisfaction with system usability by specialists and users.

Keywords: Hamster knowledge, android application, black box.

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Authors: J. L. Oliver, T. Agryzkov, L. Tortosa, J. Vicent, J. Santacruz

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This paper aims to demonstrate how the use of Network Theory can be applied to a very interesting and complex urban situation: The parts of a city which may have some patrimonial value, but because of their lack of relevant architectural elements, they are not considered to be historic in a conventional sense. In this paper, we use the suburb of La Villaflora in the city of Quito, Ecuador as our case study. We first propose a system of indicators as a tool to characterize and quantify the historic value of a geographic area. Then, we apply these indicators to the suburb of La Villaflora and use Network Theory to understand and propose actions.

Keywords: Data visualization, historic value, spatial analysis, urban networks.

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Authors: M. Miladi, T. Ezzedine, R. Bouallegue

Abstract:

In the current decade, wireless sensor networks are emerging as a peculiar multi-disciplinary research area. By this way, energy efficiency is one of the fundamental research themes in the design of Medium Access Control (MAC) protocols for wireless sensor networks. Thus, in order to optimize the energy consumption in these networks, a variety of MAC protocols are available in the literature. These schemes were commonly evaluated under simple network density and a few results are published on their robustness in realistic network-s size. We, in this paper, provide an analytical study aiming to highlight the energy waste sources in wireless sensor networks. Then, we experiment three energy efficient hybrid CSMA/CA based MAC protocols optimized for wireless sensor networks: Sensor-MAC (SMAC), Time-out MAC (TMAC) and Traffic aware Energy Efficient MAC (TEEM). We investigate these protocols with different network densities in order to discuss the end-to-end performances of these schemes (i.e. in terms of energy efficiency, delay and throughput). Through Network Simulator (NS- 2) implementations, we explore the behaviors of these protocols with respect to the network density. In fact, this study may help the multihops sensor networks designers to design or select the MAC layer which matches better their applications aims.

Keywords: Energy efficiency, medium access control, network density, wireless sensor networks.

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Authors: K. M. Faraoun, A. Boukelif

Abstract:

In the present work, we propose a new technique to enhance the learning capabilities and reduce the computation intensity of a competitive learning multi-layered neural network using the K-means clustering algorithm. The proposed model use multi-layered network architecture with a back propagation learning mechanism. The K-means algorithm is first applied to the training dataset to reduce the amount of samples to be presented to the neural network, by automatically selecting an optimal set of samples. The obtained results demonstrate that the proposed technique performs exceptionally in terms of both accuracy and computation time when applied to the KDD99 dataset compared to a standard learning schema that use the full dataset.

Keywords: Neural networks, Intrusion detection, learningenhancement, K-means clustering

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Authors: Rania Alshikhe, Vinita Jindal

Abstract:

Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from trav-eling vehicles, such as taxis through installed global positioning sys-tem (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

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This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: Simulation, visual navigation, mobile robot, data visualization.

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Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

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This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: Cyber-security, Intrusion Detection Systems, Temporal Graph Network, Anomaly Detection.

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Authors: Han Nguyen

Abstract:

The objectives of this study is to investigate the impact of culture on advertising appeals in mobile phone industry via social media channel in UK, Brazil and India. Content analysis on Samsung and Nokia commercials in YouTube is conducted. The result indicates that the advertising appeals are both congruent and incongruent with cultural dimensions in UK, Brazil and India. The result suggests that Hofstede and value paradoxes might be the tools to predict the relationship between cultural values and advertising appeals.

Keywords: Advertising appeal, international advertising, mobile phone advertising, social media advertising.

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Authors: A. Habiboghli, R. Mostafaei, M. R.Meybodi

Abstract:

Optical network uses a tool for routing which is called Latin router. These routers use particular algorithms for routing. In this paper, we present algorithm for configuration of optical network that is optimized regarding previous algorithm. We show that by decreasing the number of hops for source-destination in lightpath number of satisfied request is less. Also we had shown that more than single-hop lightpath relating single-hop lightpath is better.

Keywords: Latin Router, Constraint Satisfied, Wavelength, Optical Network

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Authors: Yalong Jiang, Zheru Chi

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In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, capsule network, capacity optimization, character recognition, data augmentation; semantic segmentation.

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Authors: Subariah Ibrahim, Mohd Aizaini Maarof

Abstract:

A generalization of the concepts of Feistel Networks (FN), known as Extended Feistel Network (EFN) is examined. EFN splits the input blocks into n > 2 sub-blocks. Like conventional FN, EFN consists of a series of rounds whereby at least one sub-block is subjected to an F function. The function plays a key role in the diffusion process due to its completeness property. It is also important to note that in EFN the F-function is the most computationally expensive operation in a round. The aim of this paper is to determine a suitable type of EFN for a scalable cipher. This is done by analyzing the threshold number of rounds for different types of EFN to achieve the completeness property as well as the number of F-function required in the network. The work focuses on EFN-Type I, Type II and Type III only. In the analysis it is found that EFN-Type II and Type III diffuses at the same rate and both are faster than Type-I EFN. Since EFN-Type-II uses less F functions as compared to EFN-Type III, therefore Type II is the most suitable EFN for use in a scalable cipher.

Keywords: Cryptography, Extended Feistel Network, Diffusion Analysis.

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Authors: B.Gokulnath

Abstract:

We see in the present day scenario that the Global positioning system (GPS) has been an effective tool to track the vehicle. However the adverse part of it is that it can only track a vehicle-s position. Our present work provides a better platform to track and disable a vehicle using wireless technology. In our system we embed a microcomputer which monitors the series of automotive systems like engine, fuel and braking system. The external USB modem is connected with the microcomputer to provide 24 x 7 internet accesses. The microcomputer is synchronized with the owner-s multimedia mobile by means of a software tool “REMOTE DESKTOP". A unique username and password is provided to the software tool, so that the owner can only access the microcomputer through the internet on owner-s mobile. The key fact is that our design is placed such that it is known only to the owner.

Keywords: GPS, Microcomputer, Multimedia Phone, REMOTEDESKTOP, USB Modem.

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Authors: Onkar Bhat Kodical, Sridhar Srinivasan, N.K. Srinath

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Tool Tracker is a client-server based application. It is essentially a catalogue of various network monitoring and management tools that are available online. There is a database maintained on the server side that contains the information about various tools. Several clients can access this information simultaneously and utilize this information. The various categories of tools considered are packet sniffers, port mappers, port scanners, encryption tools, and vulnerability scanners etc for the development of this application. This application provides a front end through which the user can invoke any tool from a central repository for the purpose of packet sniffing, port scanning, network analysis etc. Apart from the tool, its description and the help files associated with it would also be stored in the central repository. This facility will enable the user to view the documentation pertaining to the tool without having to download and install the tool. The application would update the central repository with the latest versions of the tools. The application would inform the user about the availability of a newer version of the tool currently being used and give the choice of installing the newer version to the user. Thus ToolTracker provides any network administrator that much needed abstraction and ease-ofuse with respect to the tools that he can use to efficiently monitor a network.

Keywords: Network monitoring, single platform, client/server application, version management.

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Authors: Hsien-Chou Liao, Yu-Shiang Wang

Abstract:

Surveillance system is widely used in the traffic monitoring. The deployment of cameras is moving toward a ubiquitous camera (UbiCam) environment. In our previous study, a novel service, called GPS-VT, was firstly proposed by incorporating global positioning system (GPS) and visual tracking techniques for the UbiCam environment. The first prototype is called GODTA (GPS-based Moving Object Detection and Tracking Approach). For a moving person carried GPS-enabled mobile device, he can be tracking when he enters the field-of-view (FOV) of a camera according to his real-time GPS coordinate. In this paper, GPS-VT service is applied to the tracking of vehicles. The moving speed of a vehicle is much faster than a person. It means that the time passing through the FOV is much shorter than that of a person. Besides, the update interval of GPS coordinate is once per second, it is asynchronous with the frame rate of the real-time image. The above asynchronous is worsen by the network transmission delay. These factors are the main challenging to fulfill GPS-VT service on a vehicle.In order to overcome the influence of the above factors, a back-propagation neural network (BPNN) is used to predict the possible lane before the vehicle enters the FOV of a camera. Then, a template matching technique is used for the visual tracking of a target vehicle. The experimental result shows that the target vehicle can be located and tracking successfully. The success location rate of the implemented prototype is higher than that of the previous GODTA.

Keywords: visual surveillance, visual tracking, globalpositioning system, intelligent transportation system

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Authors: Hsin-Yun Lee, Hao-Hsi Tseng

Abstract:

Previous studies mass evacuation route network does not fully reflect the step-by-step behavior and evacuees make routing decisions. Therefore, they do not work as expected when applied to the evacuation route planning is valid. This article describes where evacuees may have to make a direction to select all areas were identified as guiding points to improve evacuation routes network. This improved route network can be used as a basis for the layout can be used to guide the signs indicate that provides the required evacuation direction. This article also describes that combines simulation and artificial bee colony algorithm to provide the proposed routing solutions, to plan an integrated routing mode. The improved network and the model used is the cinema as a case study to assess the floor. The effectiveness of guidance solution in the total evacuation time is significant by verification.

Keywords: Artificial bee colony, Evacuation, Simulation.

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Authors: Muthana Saleh Alalaki, Michael Opoku Agyeman

Abstract:

The growth in the number of Intellectual Properties (IPs) or the number of cores on the same chip becomes a critical issue in System-on-Chip (SoC) due to the intra-communication problem between the chip elements. As a result, Network-on-Chip (NoC) has emerged as a system architecture to overcome intra-communication issues. This paper presents a study of recent contributions on simulation tools for NoC. Furthermore, an overview of NoC is covered as well as a comparison between some NoC simulators to help facilitate research in on-chip communication.

Keywords: Network-on-Chip, System-on-Chip, embedded systems, computer architecture.

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

Abstract:

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: Daxing Wang, Jikai Teng

Abstract:

An aggregate signature scheme can aggregate n signatures on n distinct messages from n distinct signers into a single signature. Thus, n verification equations can be reduced to one. So the aggregate signature adapts to Mobile Ad hoc Network (MANET). In this paper, we propose an efficient ID-based aggregate signature scheme with constant pairing computations. Compared with the existing ID-based aggregate signature scheme, this scheme greatly improves the efficiency of signature communication and verification. In addition, in this work, we apply our ID-based aggregate sig- nature to authenticated routing protocol to present a secure routing scheme. Our scheme not only provides sound authentication and a secure routing protocol in ad hoc networks, but also meets the nature of MANET.

Keywords: Identity-based cryptography, Aggregate signature, Bilinear pairings, Authenticated routing scheme.

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Authors: Ali Hussian Ali AlTimemy, Fawzi M. Al Naima

Abstract:

This paper presents the prediction of kidney dysfunction using different neural network (NN) approaches. Self organization Maps (SOM), Probabilistic Neural Network (PNN) and Multi Layer Perceptron Neural Network (MLPNN) trained with Back Propagation Algorithm (BPA) are used in this study. Six hundred and sixty three sets of analytical laboratory tests have been collected from one of the private clinical laboratories in Baghdad. For each subject, Serum urea and Serum creatinin levels have been analyzed and tested by using clinical laboratory measurements. The collected urea and cretinine levels are then used as inputs to the three NN models in which the training process is done by different neural approaches. SOM which is a class of unsupervised network whereas PNN and BPNN are considered as class of supervised networks. These networks are used as a classifier to predict whether kidney is normal or it will have a dysfunction. The accuracy of prediction, sensitivity and specificity were found for each type of the proposed networks .We conclude that PNN gives faster and more accurate prediction of kidney dysfunction and it works as promising tool for predicting of routine kidney dysfunction from the clinical laboratory data.

Keywords: Kidney Dysfunction, Prediction, SOM, PNN, BPNN, Urea and Creatinine levels.

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Authors: Chun-Yao Lee, Yao-chen Lee

Abstract:

This paper describes a method of signal process applied on an end effects of Hilbert-Huang transform (HHT) to provide an improvement in the reality of spectrum. The method is based on back-propagation network (BPN). To improve the effect, the end extension of the original signal is obtained by back-propagation network. A full waveform including origin and its extension is decomposed by using empirical mode decomposition (EMD) to obtain intrinsic mode functions (IMFs) of the waveform. Then, the Hilbert transform (HT) is applied to the IMFs to obtain the Hilbert spectrum of the waveform. As a result, the method is superiority of the processing of end effect of HHT to obtain the real frequency spectrum of signals.

Keywords: Neural network, back-propagation network, Hilbert-Huang transform

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Authors: A. Golmohammadi, B. Jahandideh

Abstract:

One of the determinants of a firm-s prosperity is the customers- perceived service quality and satisfaction. While service quality is wide in scope, and consists of various dimensions, there may be differences in the relative importance of these dimensions in affecting customers- overall satisfaction of service quality. Identifying the relative rank of different dimensions of service quality is very important in that it can help managers to find out which service dimensions have a greater effect on customers- overall satisfaction. Such an insight will consequently lead to more effective resource allocation which will finally end in higher levels of customer satisfaction. This issue –despite its criticality- has not received enough attention so far. Therefore, using a sample of 240 bank customers in Iran, an artificial neural network is developed to address this gap in the literature. As customers- evaluation of service quality is a subjective process, artificial neural networks –as a brain metaphor- may appear to have a potentiality to model such a complicated process. Proposing a neural network which is able to predict the customers- overall satisfaction of service quality with a promising level of accuracy is the first contribution of this study. In addition, prioritizing the service quality dimensions in affecting customers- overall satisfaction –by using sensitivity analysis of neural network- is the second important finding of this paper.

Keywords: service quality, customer satisfaction, relativeimportance, artificial neural network.

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