Search results for: Neural network computing

Authors: Awatef Chniguir, Tarek Farah, Zouhair Ben Jemaa, Safya Belguith

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Optimal routing allows minimizing energy consumption in wireless sensor networks (WSN). Clustering has proven its effectiveness in organizing WSN by reducing channel contention and packet collision and enhancing network throughput under heavy load. Therefore, nowadays, with the emergence of the Internet of Things, heterogeneity is essential. Stable election protocol (SEP) that has increased the network stability period and lifetime is the first clustering protocol for heterogeneous WSN. SEP and its descendants, namely SEP, Threshold Sensitive SEP (TSEP), Enhanced TSEP (ETSSEP) and Current Energy Allotted TSEP (CEATSEP), were studied. These algorithms’ performance was evaluated based on different metrics, especially first node death (FND), to compare their stability. Simulations were conducted on the MATLAB tool considering two scenarios: The first one demonstrates the fraction variation of advanced nodes by setting the number of total nodes. The second considers the interpretation of the number of nodes while keeping the number of advanced nodes permanent. CEATSEP outperforms its antecedents by increasing stability and, at the same time, keeping a low throughput. It also operates very well in a large-scale network. Consequently, CEATSEP has a useful lifespan and energy efficiency compared to the other routing protocol for heterogeneous WSN.

Keywords: Clustering, heterogeneous, stability, scalability, throughput, IoT, WSN.

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Authors: Shih-Yan Chen, Shin-Shin Kao

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In this paper, a thorough review about dual-cubes, DCn, the related studies and their variations are given. DCn was introduced to be a network which retains the pleasing properties of hypercube Qn but has a much smaller diameter. In fact, it is so constructed that the number of vertices of DCn is equal to the number of vertices of Q2n +1. However, each vertex in DCn is adjacent to n + 1 neighbors and so DCn has (n + 1) × 2^2n edges in total, which is roughly half the number of edges of Q2n+1. In addition, the diameter of any DCn is 2n +2, which is of the same order of that of Q2n+1. For selfcompleteness, basic definitions, construction rules and symbols are provided. We chronicle the results, where eleven significant theorems are presented, and include some open problems at the end.

Keywords: Hypercubes, dual-cubes, fault-tolerant hamiltonian property, dual-cube extensive networks, dual-cube-like networks.

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Authors: Jehad Al Dallal

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Program slicing is the task of finding all statements in a program that directly or indirectly influence the value of a variable occurrence. The set of statements that can affect the value of a variable at some point in a program is called a program slice. In several software engineering applications, such as program debugging and measuring program cohesion and parallelism, several slices are computed at different program points. In this paper, algorithms are introduced to compute all backward and forward static slices of a computer program by traversing the program representation graph once. The program representation graph used in this paper is called Program Dependence Graph (PDG). We have conducted an experimental comparison study using 25 software modules to show the effectiveness of the introduced algorithm for computing all backward static slices over single-point slicing approaches in computing the parallelism and functional cohesion of program modules. The effectiveness of the algorithm is measured in terms of time execution and number of traversed PDG edges. The comparison study results indicate that using the introduced algorithm considerably saves the slicing time and effort required to measure module parallelism and functional cohesion.

Keywords: Backward slicing, cohesion measure, forward slicing, parallelism measure, program dependence graph, program slicing, static slicing.

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Authors: Jörg Linde, Ekaterina Buyko, Robert Altwasser, Udo Hahn, Reinhard Guthke

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Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.

Keywords: Pathogen, network inference, text-mining, Candida albicans, LASSO, mutual information, reverse engineering, linear regression, modelling.

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Authors: Souleymane Oumtanaga, Prosper Kimou, Kouadio Gaza Kevin

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The security of their network remains the priorities of almost all companies. Existing security systems have shown their limit; thus a new type of security systems was born: honeypots. Honeypots are defined as programs or intended servers which have to attract pirates to study theirs behaviours. It is in this context that the leurre.com project of gathering about twenty platforms was born. This article aims to specify a model of honeypots attack. Our model describes, on a given platform, the evolution of attacks according to theirs hours. Afterward, we show the most attacked services by the studies of attacks on the various ports. It is advisable to note that this article was elaborated within the framework of the research projects on honeyspots within the LABTIC (Laboratory of Information Technologies and Communication).

Keywords: Honeypot, networks, attack, leurrecom, computer network

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Authors: Imen Aouini, Lamia Ben Azzouz

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The energy need is growing rapidly due to the population growth and the large new usage of power. Several works put considerable efforts to make the electricity grid more intelligent to reduce essentially energy consumption and provide efficiency and reliability of power systems. The Smart Grid is a complex architecture that covers critical devices and systems vulnerable to significant attacks. Hence, security is a crucial factor for the success and the wide deployment of Smart Grids. In this paper, we present security issues of the Smart Grid architecture and we highlight open issues that will make the Smart Grid security a challenging research area in the future.

Keywords: Smart grids, smart meters, home area network, neighbor area network.

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Authors: Michael K. Adu, Boniface K. Alese, Olumide S. Ogunnusi

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This paper brings to fore the inherent advantages in application of mobile agents to procure software products rather than downloading software content on the Internet. It proposes a system whereby the products come on compact disk with mobile agent as deliverable. The client/user purchases a software product, but must connect to the remote server of the software developer before installation. The user provides an activation code that activates mobile agent which is part of the software product on compact disk. The validity of the activation code is checked on connection at the developer’s end to ascertain authenticity and prevent piracy. The system is implemented by downloading two different software products as compare with installing same products on compact disk with mobile agent’s application. Downloading software contents from developer’s database as in the traditional method requires a continuously open connection between the client and the developer’s end, a fixed network is not economically or technically feasible. Mobile agent after being dispatched into the network becomes independent of the creating process and can operate asynchronously and autonomously. It can reconnect later after completing its task and return for result delivery. Response Time and Network Load are very minimal with application of Mobile agent.

Keywords: Activation code, internet, mobile agent, software developer, software products.

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Authors: Jimeng Shi, Mahek Jain, Giri Narasimhan

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Time Series Forecasting (TSF) is used to predict the target variables at a future time point based on the learning from previous time points. To keep the problem tractable, learning methods use data from a fixed length window in the past as an explicit input. In this paper, we study how the performance of predictive models change as a function of different look-back window sizes and different amounts of time to predict into the future. We also consider the performance of the recent attention-based transformer models, which had good success in the image processing and natural language processing domains. In all, we compare four different deep learning methods (Recurrent Neural Network (RNN), Long Short-term Memory (LSTM), Gated Recurrent Units (GRU), and Transformer) along with a baseline method. The dataset (hourly) we used is the Beijing Air Quality Dataset from the website of University of California, Irvine (UCI), which includes a multivariate time series of many factors measured on an hourly basis for a period of 5 years (2010-14). For each model, we also report on the relationship between the performance and the look-back window sizes and the number of predicted time points into the future. Our experiments suggest that Transformer models have the best performance with the lowest Mean   Absolute Errors (MAE = 14.599, 23.273) and Root Mean Square Errors (RSME = 23.573, 38.131) for most of our single-step and multi-steps predictions. The best size for the look-back window to predict 1 hour into the future appears to be one day, while 2 or 4 days perform the best to predict 3 hours into the future.

Keywords: Air quality prediction, deep learning algorithms, time series forecasting, look-back window.

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Authors: Ε. Giovanis

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In this paper we apply an Adaptive Network-Based Fuzzy Inference System (ANFIS) with one input, the dependent variable with one lag, for the forecasting of four macroeconomic variables of US economy, the Gross Domestic Product, the inflation rate, six monthly treasury bills interest rates and unemployment rate. We compare the forecasting performance of ANFIS with those of the widely used linear autoregressive and nonlinear smoothing transition autoregressive (STAR) models. The results are greatly in favour of ANFIS indicating that is an effective tool for macroeconomic forecasting used in academic research and in research and application by the governmental and other institutions

Keywords: Linear models, Macroeconomics, Neuro-Fuzzy, Non-Linear models

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Authors: Huan Chen, Bo-Chao Cheng, Chih-Chuan Cheng, Yi-Geng Chen, Yu Ling Chou

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Wireless Sensor Network (WSN) comprises of sensor nodes which are designed to sense the environment, transmit sensed data back to the base station via multi-hop routing to reconstruct physical phenomena. Since physical phenomena exists significant overlaps between temporal redundancy and spatial redundancy, it is necessary to use Redundancy Suppression Algorithms (RSA) for sensor node to lower energy consumption by reducing the transmission of redundancy. A conventional algorithm of RSAs is threshold-based RSA, which sets threshold to suppress redundant data. Although many temporal and spatial RSAs are proposed, temporal-spatial RSA are seldom to be proposed because it is difficult to determine when to utilize temporal or spatial RSAs. In this paper, we proposed a novel temporal-spatial redundancy suppression algorithm, Codebookbase Redundancy Suppression Mechanism (CRSM). CRSM adopts vector quantization to generate a codebook, which is easily used to implement temporal-spatial RSA. CRSM not only achieves power saving and reliability for WSN, but also provides the predictability of network lifetime. Simulation result shows that the network lifetime of CRSM outperforms at least 23% of that of other RSAs.

Keywords: Redundancy Suppression Algorithm (RSA), Threshold-based RSA, Temporal RSA, Spatial RSA and Codebookbase Redundancy Suppression Mechanism (CRSM)

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Authors: Eklas Hossain, Sheroz Khan, Ahad Ali

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Power line communications may be used as a data communication channel in public and indoor distribution networks so that it does not require the installing of new cables. Industrial low voltage distribution network may be utilized for data transfer required by the on-line condition monitoring of electric motors. This paper presents a pilot distribution network for modeling low voltage power line as data transfer channel. The signal attenuation in communication channels in the pilot environment is presented and the analysis is done by varying the corresponding parameters for the signal attenuation.

Keywords: Data communication, indoor distribution networks, low voltage, power line.

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Authors: Mohd Fairuz Iskandar Othman, Nazrulazhar Bahaman, Zulkiflee Muslim, Faizal Abdollah

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This paper discusses a curriculum approach that will give emphasis on practical portions of teaching network security subjects in information and communication technology courses. As we are well aware, the need to use a practice and application oriented approach in education is paramount. Research on active learning and cooperative groups have shown that students grasps more and have more tendency towards obtaining and realizing soft skills like leadership, communication and team work as opposed to the more traditional theory and exam based teaching and learning. While this teaching and learning paradigm is relatively new in Malaysia, it has been practiced widely in the West. This paper examines a certain approach whereby students learning wireless security are divided into and work in small and manageable groups where there will be 2 teams which consist of black hat and white hat teams. The former will try to find and expose vulnerabilities in a wireless network while the latter will try their best to prevent such attacks on their wireless networks using hardware, software, design and enforcement of security policy and etc. This paper will try to show that the approach taken plus the use of relevant and up to date software and hardware and with suitable environment setting will hopefully expose students to a more fruitful outcome in terms of understanding of concepts, theories and their motivation to learn.

Keywords: Curriculum approach, wireless networks, wirelesssecurity.

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Authors: J. Madureira, R. Lagido, I. Sousa

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Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU. 

Keywords: Inertial Measurement Unit (IMU), Global Positioning System (GPS), smartphone, surfing performance.

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Authors: Htay Htay Yi, Zin May Aye

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Network security is role of the ICT environment because malicious users are continually growing that realm of education, business, and then related with ICT. The network security contravention is typically described and examined centrally based on a security event management system. The firewalls, Intrusion Detection System (IDS), and Intrusion Prevention System are becoming essential to monitor or prevent of potential violations, incidents attack, and imminent threats. In this system, the firewall rules are set only for where the system policies are needed. Dataset deployed in this system are derived from the testbed environment. The traffic as in DoS and PortScan traffics are applied in the testbed with firewall and IDS implementation. The network traffics are classified as normal or attacks in the existing testbed environment based on six machine learning classification methods applied in the system. It is required to be tested to get datasets and applied for DoS and PortScan. The dataset is based on CICIDS2017 and some features have been added. This system tested 26 features from the applied dataset. The system is to reduce false positive rates and to improve accuracy in the implemented testbed design. The system also proves good performance by selecting important features and comparing existing a dataset by machine learning classifiers.

Keywords: False negative rate, intrusion detection system, machine learning methods, performance.

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Authors: Eylem Koç, Hasan Arda Burhan

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Location selection presents a crucial decision problem in today’s business world where strategic decision making processes have critical importance. Thus, location selection has strategic importance for companies in boosting their strength regarding competition, increasing corporate performances and efficiency in addition to lowering production and transportation costs. A right choice in location selection has a direct impact on companies’ commercial success. In this study, a store location selection problem of Carglass Turkey which operates in vehicle glass branch is handled. As this problem includes both tangible and intangible criteria, Analytic Network Process (ANP) was accepted as the main methodology. The model consists of control hierarchy and BOCR subnetworks which include clusters of actors, alternatives and criteria. In accordance with the management’s choices, five different locations were selected. In addition to the literature review, a strict cooperation with the actor group was ensured and maintained while determining the criteria and during whole process. Obtained results were presented to the management as a report and its feasibility was confirmed accordingly.

Keywords: Analytic Network Process, BOCR, location selection, multi-actor decision making, multi-criteria decision making, real life problem.

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Authors: Madhuri Bhavsar, Anupam K Singh, Shrikant Pradhan

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Long term rainfall analysis and prediction is a challenging task especially in the modern world where the impact of global warming is creating complications in environmental issues. These factors which are data intensive require high performance computational modeling for accurate prediction. This research paper describes a prototype which is designed and developed on grid environment using a number of coupled software infrastructural building blocks. This grid enabled system provides the demanding computational power, efficiency, resources, user-friendly interface, secured job submission and high throughput. The results obtained using sequential execution and grid enabled execution shows that computational performance has enhanced among 36% to 75%, for decade of climate parameters. Large variation in performance can be attributed to varying degree of computational resources available for job execution. Grid Computing enables the dynamic runtime selection, sharing and aggregation of distributed and autonomous resources which plays an important role not only in business, but also in scientific implications and social surroundings. This research paper attempts to explore the grid enabled computing capabilities on weather indices from HOAPS data for climate impact modeling and change detection.

Keywords: Climate model, Computational Grid, GridApplication, Heterogeneous Grid

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Authors: Ladan Darougaran, Hossein Shahinzadeh, Hajar Ghotb, Leila Ramezanpour

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In ad hoc networks, the main issue about designing of protocols is quality of service, so that in wireless sensor networks the main constraint in designing protocols is limited energy of sensors. In fact, protocols which minimize the power consumption in sensors are more considered in wireless sensor networks. One approach of reducing energy consumption in wireless sensor networks is to reduce the number of packages that are transmitted in network. The technique of collecting data that combines related data and prevent transmission of additional packages in network can be effective in the reducing of transmitted packages- number. According to this fact that information processing consumes less power than information transmitting, Data Aggregation has great importance and because of this fact this technique is used in many protocols [5]. One of the Data Aggregation techniques is to use Data Aggregation tree. But finding one optimum Data Aggregation tree to collect data in networks with one sink is a NP-hard problem. In the Data Aggregation technique, related information packages are combined in intermediate nodes and form one package. So the number of packages which are transmitted in network reduces and therefore, less energy will be consumed that at last results in improvement of longevity of network. Heuristic methods are used in order to solve the NP-hard problem that one of these optimization methods is to solve Simulated Annealing problems. In this article, we will propose new method in order to build data collection tree in wireless sensor networks by using Simulated Annealing algorithm and we will evaluate its efficiency whit Genetic Algorithm.

Keywords: Data aggregation, wireless sensor networks, energy efficiency, simulated annealing algorithm, genetic algorithm.

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Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

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Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: Causality, defect causes, social network analysis, association rule mining.

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Authors: M. Bouguerra, F. Laaouad, I. Habi, R. Azaizia

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In Algeria, now, the oil pumping plants are fed with electric power by independent local sources. This type of feeding has many advantages (little climatic influence, independent operation). However it requires a qualified maintenance staff, a rather high frequency of maintenance and repair and additional fuel costs. Taking into account the increasing development of the national electric supply network (Sonelgaz), a real possibility of transfer of the local sources towards centralized sources appears.These latter cannot only be more economic but more reliable than the independent local sources as well. In order to carry out this transfer, it is necessary to work out an optimal strategy to rebuilding these networks taking in account the economic parameters and the indices of reliability.

Keywords: Optimization, reliability, electric network.

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Authors: Aisha Othman, Crinela Pislaru, Ahmed Impes

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This paper provides an identification of the existing practical skills gap between school-based learning (SBL) and laboratory based learning (LBL) in the Computing Department within the Faculty of Science at Omar Al-Mukhtar University in Libya. A survey has been conducted and the first author has elicited the responses of two groups of stakeholders, namely the academic teachers and students.

The primary goal is to review the main strands of evidence available and argue that there is a gap between laboratory and school-based learning in terms of opportunities for experiment and application of skills. In addition, the nature of experimental work within the laboratory at Omar Al-Mukhtar University needs to be reconsidered. Another goal of our study was to identify the reasons for students’ poor performance in the laboratory and to determine how this poor performance can be eliminated by the modification of teaching methods. Bloom’s taxonomy of learning outcomes has been applied in order to classify questions and problems into categories, and the survey was formulated with reference to third year Computing Department students. Furthermore, to discover students’ opinions with respect to all the issues, an exercise was conducted. The survey provided questions related to what the students had learnt and how well they had learnt. We were also interested in feedback on how to improve the course and the final question provided an opportunity for such feedback.

Keywords: Bloom’s taxonomy, e-learning, Omar Al-Mukhtar University.

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Authors: A. Baith Mohamed, Ayman Abdel-Hamid, Kareem Youssri Mohamed

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Current proposals for E-passport or ID-Card is similar to a regular passport with the addition of tiny contactless integrated circuit (computer chip) inserted in the back cover, which will act as a secure storage device of the same data visually displayed on the photo page of the passport. In addition, it will include a digital photograph that will enable biometric comparison, through the use of facial recognition technology at international borders. Moreover, the e-passport will have a new interface, incorporating additional antifraud and security features. However, its problems are reliability, security and privacy. Privacy is a serious issue since there is no encryption between the readers and the E-passport. However, security issues such as authentication, data protection and control techniques cannot be embedded in one process. In this paper, design and prototype implementation of an improved E-passport reader is presented. The passport holder is authenticated online by using GSM network. The GSM network is the main interface between identification center and the e-passport reader. The communication data is protected between server and e-passport reader by using AES to encrypt data for protection will transferring through GSM network. Performance measurements indicate a 19% improvement in encryption cycles versus previously reported results.

Keywords: RFID "Radio Frequency Identification", EPC"Electronic Product Code", ICAO "International Civil Aviation Organization", IFF "Identify Friend or Foe"

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Authors: Mohamed A. Mahfouz, M. A. Ismail

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This paper introduces new algorithms (Fuzzy relative of the CLARANS algorithm FCLARANS and Fuzzy c Medoids based on randomized search FCMRANS) for fuzzy clustering of relational data. Unlike existing fuzzy c-medoids algorithm (FCMdd) in which the within cluster dissimilarity of each cluster is minimized in each iteration by recomputing new medoids given current memberships, FCLARANS minimizes the same objective function minimized by FCMdd by changing current medoids in such away that that the sum of the within cluster dissimilarities is minimized. Computing new medoids may be effected by noise because outliers may join the computation of medoids while the choice of medoids in FCLARANS is dictated by the location of a predominant fraction of points inside a cluster and, therefore, it is less sensitive to the presence of outliers. In FCMRANS the step of computing new medoids in FCMdd is modified to be based on randomized search. Furthermore, a new initialization procedure is developed that add randomness to the initialization procedure used with FCMdd. Both FCLARANS and FCMRANS are compared with the robust and linearized version of fuzzy c-medoids (RFCMdd). Experimental results with different samples of the Reuter-21578, Newsgroups (20NG) and generated datasets with noise show that FCLARANS is more robust than both RFCMdd and FCMRANS. Finally, both FCMRANS and FCLARANS are more efficient and their outputs are almost the same as that of RFCMdd in terms of classification rate.

Keywords: Data Mining, Fuzzy Clustering, Relational Clustering, Medoid-Based Clustering, Cluster Analysis, Unsupervised Learning.

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Authors: Faizal A. Samman, Thomas Hollstein, Manfred Glesner

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A synchronous network-on-chip using wormhole packet switching and supporting guaranteed-completion best-effort with low-priority (LP) and high-priority (HP) wormhole packet delivery service is presented in this paper. Both our proposed LP and HP message services deliver a good quality of service in term of lossless packet completion and in-order message data delivery. However, the LP message service does not guarantee minimal completion bound. The HP packets will absolutely use 100% bandwidth of their reserved links if the HP packets are injected from the source node with maximum injection. Hence, the service are suitable for small size messages (less than hundred bytes). Otherwise the other HP and LP messages, which require also the links, will experience relatively high latency depending on the size of the HP message. The LP packets are routed using a minimal adaptive routing, while the HP packets are routed using a non-minimal adaptive routing algorithm. Therefore, an additional 3-bit field, identifying the packet type, is introduced in their packet headers to classify and to determine the type of service committed to the packet. Our NoC prototypes have been also synthesized using a 180-nm CMOS standard-cell technology to evaluate the cost of implementing the combination of both services.

Keywords: Network-on-Chip, Parallel Pipeline Router Architecture, Wormhole Switching, Two-Level Priority Service.

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Authors: F. Sarabchi, A. H. Darvishan, H. Yeganeh, H. Ahmadian

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Next generation networks with the idea of convergence of service and control layer in existing networks (fixed, mobile and data) and with the intention of providing services in an integrated network, has opened new horizon for telecom operators. On the other hand, economic problems have caused operators to look for new source of income including consider new services, subscription of more users and their promotion in using morenetwork resources and easy participation of service providers or 3rd party operators in utilizing networks. With this requirement, an architecture based on next generation objectives for service layer is necessary. In this paper, a new architecture based on IMS model explains participation of 3rd party operators in creation and implementation of services on an integrated telecom network.

Keywords: Service model, IMS, API, Scripting language, JAIN, Parlay.

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Authors: Afif Saleh Abugharsa

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The IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPAN) with focus on enabling wireless sensor networks. It aims to give a low data rate, low power consumption, and low cost wireless networking on the device-level communication. The objective of this study is to investigate the performance of IEEE 802.15.4 based networks using simulation tool. In this project the network simulator 2 NS2 was used to several performance measures of wireless sensor networks. Three scenarios were considered, multi hop network with a single coordinator, star topology, and an ad hoc on demand distance vector AODV. Results such as packet delivery ratio, hop delay, and number of collisions are obtained from these scenarios.

Keywords: ZigBee, wireless sensor networks, IEEE 802.15.4, low power, low data rate

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Authors: Dinara F. Gaynutdinova, Vladimir Ya Modorsky, Nikolay A. Shevelev

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The problem under research is that of unpredictable modes occurring in two-stage centrifugal hydraulic pump as a result of hydraulic processes caused by vibrations of structural components. Numerical, analytical and experimental approaches are considered. A hypothesis was developed that the problem of unpredictable pressure decrease at the second stage of centrifugal pumps is caused by cavitation effects occurring upon vibration. The problem has been studied experimentally and theoretically as of today. The theoretical study was conducted numerically and analytically. Hydroelastic processes in dynamic “liquid – deformed structure” system were numerically modelled and analysed. Using ANSYS CFX program engineering analysis complex and computing capacity of a supercomputer the cavitation parameters were established to depend on vibration parameters. An influence domain of amplitudes and vibration frequencies on concentration of cavitation bubbles was formulated. The obtained numerical solution was verified using CFM program package developed in PNRPU. The package is based on a differential equation system in hyperbolic and elliptic partial derivatives. The system is solved by using one of finite-difference method options – the particle-in-cell method. The method defines the problem solution algorithm. The obtained numerical solution was verified analytically by model problem calculations with the use of known analytical solutions of in-pipe piston movement and cantilever rod end face impact. An infrastructure consisting of an experimental fast hydro-dynamic processes research installation and a supercomputer connected by a high-speed network, was created to verify the obtained numerical solutions. Physical experiments included measurement, record, processing and analysis of data for fast processes research by using National Instrument signals measurement system and Lab View software. The model chamber end face oscillated during physical experiments and, thus, loaded the hydraulic volume. The loading frequency varied from 0 to 5 kHz. The length of the operating chamber varied from 0.4 to 1.0 m. Additional loads weighed from 2 to 10 kg. The liquid column varied from 0.4 to 1 m high. Liquid pressure history was registered. The experiment showed dependence of forced system oscillation amplitude on loading frequency at various values: operating chamber geometrical dimensions, liquid column height and structure weight. Maximum pressure oscillation (in the basic variant) amplitudes were discovered at loading frequencies of approximately 1,5 kHz. These results match the analytical and numerical solutions in ANSYS and CFM.

Keywords: Computing experiment, hydroelasticity, physical experiment, vibration.

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Authors: Yoshimoto Kurihara, Tad Gonsalves

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Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: AlexNet, Deep learning, image recognition, 6D posture estimation.

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Authors: Abdoulaye Diop, Nahid Emad, Thierry Winter, Mohamed Hilia

Abstract:

Data assets protection is a crucial issue in the cybersecurity field. Companies use logical access control tools to vault their information assets and protect them against external threats, but they lack solutions to counter insider threats. Nowadays, insider threats are the most significant concern of security analysts. They are mainly individuals with legitimate access to companies information systems, which use their rights with malicious intents. In several fields, behavior anomaly detection is the method used by cyber specialists to counter the threats of user malicious activities effectively. In this paper, we present the step toward the construction of a user and entity behavior analysis framework by proposing a behavior anomaly detection model. This model combines machine learning classification techniques and graph-based methods, relying on linear algebra and parallel computing techniques. We show the utility of an ensemble learning approach in this context. We present some detection methods tests results on an representative access control dataset. The use of some explored classifiers gives results up to 99% of accuracy.

Keywords: Cybersecurity, data protection, access control, insider threat, user behavior analysis, ensemble learning, high performance computing.

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Authors: E. Khorram, S.M. Mirzababaei

Abstract:

Everyday the usages of the Internet increase and simply a world of the data become accessible. Network providers do not want to let the provided services to be used in harmful or terrorist affairs, so they used a variety of methods to protect the special regions from the harmful data. One of the most important methods is supposed to be the firewall. Firewall stops the transfer of such packets through several ways, but in some cases they do not use firewall because of its blind packet stopping, high process power needed and expensive prices. Here we have proposed a method to find a discriminate function to distinguish between usual packets and harmful ones by the statistical processing on the network router logs. So an administrator can alarm to the user. This method is very fast and can be used simply in adjacent with the Internet routers.

Keywords: Data Mining, Firewall, Optimization, Packetclassification, Statistical Pattern Recognition.

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Authors: Dávid Csercsik, Sándor Imre

Abstract:

The performance of state of the art worldwide telecommunication networks strongly depends on the efficiency of the applied routing mechanism. Game theoretical approaches to this problem offer new solutions. In this paper a new continuous network routing model is defined to describe data transfer in fixed telecommunication networks of multiple hosts. The nodes of the network correspond to routers whose latency is assumed to be traffic dependent. We propose that the whole traffic of the network can be decomposed to a finite number of tasks, which belong to various hosts. To describe the different latency-sensitivity, utility functions are defined for each task. The model is used to compare router and host intelligent types of routing methods, corresponding to various data transfer protocols. We analyze host intelligent routing as a transferable utility cooperative game with externalities. The main aim of the paper is to provide a framework in which the efficiency of various routing algorithms can be compared and the transferable utility game arising in the cooperative case can be analyzed.

Keywords: Routing, Telecommunication networks, Performance evaluation, Cooperative game theory, Partition function form games

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