bluuebunny/crossref_metadata_2025 huggingface dataset:
Clustering Batik Images using Fuzzy C-Means Algorithm Based on Log-Average Luminance
Authors: Sanmorino Ahmad
Published: October 2018

Batik is a fabric or clothes that are made with a special staining technique called wax-resist dyeing and is one of the cultural heritage which has high artistic value. In order to improve the efficiency and give better semantic to the image, some researchers apply clustering algorithm for managing images before they can be retrieved. Image clustering is a process of grouping images based on their similarity. In this paper we attempt to provide an alternative method of grouping batik image using fuzzy c-means (FCM) algorithm based on log-average luminance of the batik. FCM clustering algorithm is an algorithm that works using fuzzy models that allow all data from all cluster members are formed with different degrees of membership between 0 and 1. Log-average luminance (LAL) is the average value of the lighting in an image. We can compare different image lighting from one image to another using LAL. From the experiments that have been made, it can be concluded that fuzzy c-means algorithm can be used for batik image clustering based on log-average luminance of each image possessed.
Survey of Text Plagiarism Detection
Authors: Hamza Osman Ahmed , Salim Naomie , Abuobieda Albaraa
Published: October 2018

In this paper we are going to review and list the advantages and limitations of the significant effective techniques employed or developed in text plagiarism detection.Â  It was found that many of the proposed methods for plagiarism detection have a weakness and lacking for detecting some types of plagiarized text. This paper discussed several important issues in plagiarism detection such as; plagiarism detection Tasks, plagiarism detection process and some of the current plagiarism detection techniques.
Anomaly detection using clustering for ad hoc networks -behavioral approach-
Authors: Madani Belacel , Messabih B.
Published: October 2018

Mobile ad hoc networks (MANETs) are multi-hop wireless networks of autonomous mobile nodes without any fixed infrastructure. In MANETs, it is difficult to detect malicious nodes because the network topology constantly changes due to node mobility. Intrusion detection is the means to identify the intrusive behaviors and provide useful information to intruded systems to respond fast and to avoid or reduce damages. The anomaly detection algorithms have the advantage because they can detect new types of attacks (zero-day attacks).In this paper, the Intrusion Detection System clustering-based (ID-Cluster) that fits the requirement of MANET is presented. This work addresses both routing layer misbehaviors issues, with main focuses on thwarting routing disruption attack Dynamic Source Routing (DSR). To validate the research, a case study is presented using the simulation with GloMoSim at different mobility levels. Simulation results show that proposed system can achieve desirable performance and meet the security requirement of MANET.
Circularly Polarized Slotted Microstrip Patch Antenna with Finite Ground Plane
Authors: Rawat Sanyog , Sharma K K
Published: October 2018

In this paper a new geometry of circularly polarized patch antenna is proposed with improved bandwidth. The radiation performance of proposed patch antenna is investigated using IE3D simulation software and its performance is compared with that of conventional rectangular patch antenna. The simulated return loss, axial ratio and impedance with frequency for the proposed antenna are reported in this paper. It is shown that by selecting suitable ground-plane dimensions, air gap and location of the slots, the impedance bandwidth can be enhanced upto 10.15% as compared to conventional rectangular patch (4.24%) with an axial ratio bandwidth of 4.05%.DOI:Â 10.18495/comengapp.12.097106
Combined Classifier for Face Recognition using Legendre Moments
Authors: Dasari Sridhar , Krishna I.V. Murali
Published: October 2018

In this paper, a new combined Face Recognition method based on Legendre moments with Linear Discriminant Analysis and Probabilistic Neural Network is proposed. The Legendre moments are orthogonal and scale invariants hence they are suitable for representing the features of the face images. The proposed face recognition method consists of three steps, i) Feature extraction using Legendre moments ii) Dimensionality reduction using Linear Discrminant Analysis (LDA) and iii) classification using Probabilistic Neural Network (PNN). Linear Discriminant Analysis searches the directions for maximum discrimination of classes in addition to dimensionality reduction. Combination of Legendre moments and Linear Discriminant Analysis is used for improving the capability of Linear Discriminant Analysis when few samples of images are available. Probabilistic Neural network gives fast and accurate classification of face images. Evaluation was performed on two face data bases. First database of 400 face images from Olivetty Research Laboratories (ORL) face database, and the second database of thirteen students are taken. The proposed method gives fast and better recognition rate when compared to other classifiers.DOI:Â 10.18495/comengapp.12.107118
Monitoring and Resource Management in P2P Grid-Based Web Services
Authors: Laouni Djafri , Rachida Mekki
Published: October 2018

Grid computing has recently emerged as a response to the growing demand for resources (processing power, storage, etc.) exhibited by scientific applications. However, as grid sizes increase, the need for self-organization and dynamic reconfigurations is becoming more and more important. Since such properties are exhibited by P2P systems, the convergence of grid computing and P2P computing seems natural. However, using P2P systems (usually running on the Internet) on a grid infrastructure (generally available as a federation of SAN-based clusters interconnected by high-bandwidth WANs) may raise the issue of the adequacy of the P2P communication mechanisms. Among the interesting properties of P2P systems is theÂ  volatility ofÂ  peersÂ  whichÂ  causesÂ  theÂ  needÂ  forÂ  integrationÂ  ofÂ  aÂ  service fault tolerance. And service Load balancing,Â Â  As a solution, we proposed a mechanism of fault tolerance and model of Load balancingÂ  adapted to a grid P2P model, named SGRTE (Monitoring and Resource Management, Fault Tolerances and Load Balancing).DOI:Â 10.18495/comengapp.12.071084
Codes correcting and simultaneously detecting solid burst errors
Authors: Das P.K.
Published: October 2018

Detecting and correcting errors is one of the main tasks in coding theory. The bounds are important in terms of error-detecting and -correcting capabilities of the codes. Solid Burst error is common in several communication channels. This paper obtains lower and upper bounds on the number of parity-check digits required for linear codes capable of correcting any solid burst error of length b or less and simultaneously detecting any solid burst error of length s(>b) or less. Illustration of such a code is also provided.Keywords: Parity check matrix, Syndromes, Solid burst errors, Standard arrayDOI:Â 10.18495/comengapp.21.143150Â Â
On Constructing Static Evaluation Function using Temporal Difference Learning
Authors: Ping Man Samuel Choi
Published: October 2018

Programming computers to play board games against human players has long been used as a measure for the development of artificial intelligence. The standard approach for computer game playing is to search for the best move from a given game state by using minimax search with static evaluation function. The static evaluation function is critical to the game playing performance but its design often relies on human expert players. This paper discusses how temporal differences (TD) learning can be used to construct a static evaluation function through self-playing and evaluates the effects for various parameter settings. The game of Kalah, a non-chance game of moderate complexity, is chosen as a testbed. The empirical result shows that TD learning is particularly promising for constructing a good evaluation function for the end games and can substantially improve the overall game playing performance in learning the entire game.DOI:Â 10.18495/comengapp.21.175184
Codes Correcting and Simultaneously Detecting Solid Burst Errors
Authors: Das P. K.
Published: October 2018

Digital images are foremost source for information transfer. Due to advancement of the technology, images are now not treated as reliable source of information. Digital images can be edited according to the need. Adding and deleting content from an image is most easiest and popular way of creating image forgery, which is known as copy-move forgery. Digital Image Forensics is the field that deals with the authenticity of the images. Digital image forensics checks the integrity of the images by detecting various forgeries. In order to hide the traces of copy-move forgery there are editing operations like rotation, scaling, JPEG compression, Gaussian noise called as attacks, which are performed on the copied part of the image before pasting. Till now these attacks are not detected by the single method. The novel approach is proposed to detect image forgery by copy-move under above attacks by combining block-based and keypoint-based method.

Keywords: Digital image forensics, copy-move forgery, passive blind approach, keypoint-based, block-based methods
Automatic Iranian Vehicle License Plate Recognition System Based on Support Vector Machine (SVM) Algorithms
Authors: Aghaie Mahdi , Shokri Fatemeh , Zade Tabari Meisam Yadolah
Published: October 2018

In the emerging trends the pervasive nature across the computing environment shows that the system is platform independent and device independent. The system development is designed with the help of Structured Query Language and middleware infrastructure that are used to collect the information from various nodes. An essential feature of this proposed middleware architecture suites the device independent as the major supporting capability to the system. This facilitates to add new device types in the system feels easy through the use of device self-description.Â  It mainly focuses on the issues related to the heterogeneity of the different devices composing a pervasive system: This aspect is investigated both at data management and at physical integration levels. Using the nontrivial approach aims at handling the related issues are resolved with the corresponding solution.

Keyword: Perla, Cloud Monitoring, Middleware, Declarative Language
E-mail spam filtering by a new hybrid feature selection method using IG and CNB wrapper
Authors: Pourhashemi Seyed Mostafa
Published: October 2018

The growing volume of spam emails has resulted in the necessity for more accurate and efficient email classification system. The purpose of this research is presenting an machine learning approach for enhancing the accuracy of automatic spam detecting and filtering and separating them from legitimate messages. In this regard, for reducing the error rate and increasing the efficiency, the hybrid architecture on feature selection has been used. Features used in these systems, are the body of text messages. Proposed system of this research has used the combination of two filtering models, Filter and Wrapper, with Information Gain (IG) filter and Complement NaÃ¯ve Bayes (CNB) wrapper as feature selectors. In addition, Multinomial NaÃ¯ve Bayes (MNB) classifier, Discriminative Multinomial NaÃ¯ve Bayes (DMNB) classifier, Support Vector Machine (SVM) classifier and Random Forest classifier are used for classification. Finally, the output results of this classifiers and feature selection methods are examined and the best design is selected and it is compared with another similar works by considering different parameters. The optimal accuracy of the proposed system is evaluated equal to 99%.
Two phase privacy preserving data mining
Authors: Gupta Pooja , Kumar Ashish
Published: October 2018

The paper proposes a framework to improve the privacy preserving data mining. The approach adopted provides security at both the ends i.e. at the data transmission time as well as in the data mining process using two phases. The secure data transmission is handled using elliptic curve cryptography (ECC) and the privacy is preserved using k-anonymity. The proposed framework ensures highly secure environment. We observed that the framework outperforms other approaches [8] discussed in the literature at both ends i.e. at security and privacy of data. Since most of the approaches have considered either secure transmission or privacy preserving data mining but very few have considered both. We have used WEKA 3.6.9 for experimentation and analysis of our approach. We have also analyzed the case of k-anonymity when the numbers of records in a group are less than k (hiding factor) by inserting fake records. The obtained results have shown the pattern that the insertion of fake records leads to more accuracy as compared to full suppression of records. Since, full suppression may hide important information in cases where records are less than k, on the other hand in the process of fake records insertion; records are available even if number of records in a group is less than k.
How Networking Empirically Influences the Types of Innovation?: Pardis Technology Park as a Case Study
Authors: Phirouzabadi Amir Mirzadeh , Mahmoudian M , Asghari M
Published: October 2018

Nowadays, Innovation can be named as one of the best practices as quality, speed, dependability, flexibility and cost which it helps organization enter to new markets, increase the existing market share and provide it with a competitive edge. In addition, organizations have moved forward from â€œhiding idea (Closed Innovation)â€ to â€œopening them (Open Innovation)â€. Therefore, concepts such as â€œopen innovationâ€ and â€œinnovation networkâ€ have become important and beneficial to both academic and market society. Therefore, this study tried to empirically study the effects of networking on innovations. In this regard, in order to empirically explore how networking influences innovations, this paper used types of innovations based on OCED definition as organizational, marketing, process and product and compared their changes before and after networking of 45 companies in the network Pardis Technology Park as a case study. The results and findings showed that all of the innovation types were increased after jointing the companies to the network. In fact, we arranged these changing proportions from the most to the least change as marketing, process, organizational and product innovation respectively. Although there were some negative growth in some measures of these innovations after jointing into the network.
Performance evaluation of popular l1-minimization algorithms in the context of Compressed Sensing
Authors: TV Bijeesh
Published: October 2018

Compressed sensing (CS) is a data acquisition technique that is gaining popularity because of the fact that the reconstruction of the original signal is possible even if it was sampled at a sub-Nyquist rate. In contrast to the traditional sampling method, in CS we take a few measurements from the signal and the original signal can then be reconstructed from these measurements by using an optimization technique called l1-minimization. Computer engineers and mathematician have been equally fascinated by this latest trend in digital signal processing. In this work we perform an evaluation of different l1-minimization algorithms for their performance in reconstructing the signal in the context of CS. The algorithms that have been evaluated are PALM (Primal Augmented Lagrangian Multiplier method), DALM (Dual Augmented Lagrangian Multiplier method) and ISTA (Iterative Soft Thresholding Algorithm). The evaluation is done based on three parameters which are execution time, PSNR and RMSE.
Improve the Performance of Data Grids by Cost-Based Job Scheduling Strategy
Authors: Mansouri Najme
Published: October 2018

Grid environments have gain tremendous importance in recent years since application requirements increased drastically. The heterogeneity and geographic dispersion of grid resources and applications places some complex problems such as job scheduling. Most existing scheduling strategies in Grids only focus on one kind of Grid jobs which can be data-intensive or computation-intensive. However, only considering one kind of jobs in scheduling does not result in suitable scheduling in the viewpoint of all system, and sometimes causes wasting of resources on the other side. To address the challenge of simultaneously considering both kinds of jobs, a new Cost-Based Job Scheduling (CJS) strategy is proposed in this paper. At one hand, CJS algorithm considers both data and computational resource availability of the network, and on the other hand, considering the corresponding requirements of each job, it determines a value called W to the job. Using the W value, the importance of two aspects (being data or computation intensive) for each job is determined, and then the job is assigned to the available resources. The simulation results with OptorSim show that CJS outperforms comparing to the existing algorithms mentioned in literature as number of jobs increases.
W_SR: A QoS Based Ranking Approach for Cloud Computing Service
Authors: Jahani Arezoo , Mohammad Khanli Leyli , Razavi Seyed Naser
Published: October 2018

Cloud computing is a kind of computing model that promise accessing to information resources in request time and subscription basis. In this environment, there are different type of userâ€™s application with different requirements. In addition, there are different cloud Service providers which present spate services with various qualitative traits. Therefore determining the best cloud computing service for users with specific applications is a serious problem. Service ranking system compares the different services based on quality of services (QoS), in order to select the most appropriate service. In this paper, we propose a W_SR (Weight Service Rank) approach for cloud service ranking that uses from QoS features. Comprehensive experiments are conducted employing real-world QoS dataset, including more than 2500 web services over the world. The experimental results show that execution time of our approach is less than other approaches and it is more flexible and scalable than the others with increase in services or users.
Data Management Challenges in Cloud Environments
Authors: Javidi Mohamad Masood , Mansouri Najme , Asadi Karam Asghar
Published: October 2018

Recently the cloud computing paradigm has been receiving special excitement and attention in the new researches. Cloud computing has the potential to change a large part of the IT activity, making software even more interesting as a service and shaping the way IT hardware is proposed and purchased. Developers with novel ideas for new Internet services no longer require the large capital outlays in hardware to present their service or the human expense to do it. These cloud applications apply large data centers and powerful servers that host Web applications and Web services. This report presents an overview of what cloud computing means, its history along with the advantages and disadvantages. In this paper we describe the problems and opportunities of deploying data management issues on these emerging cloud computing platforms. We study that large scale data analysis jobs, decision support systems, and application specific data marts are more likely to take benefit of cloud computing platforms than operational, transactional database systems.
Fuzzy Expert Ants to speed up big TSP Problems using ACS
Authors: Abdali Mohammadi Fardin , Fathi Abdolhosein Fathi Abdolhosein
Published: October 2018

Ant colony algorithms are a group of heuristic optimization algorithms that have been inspired by behavior of real ants foraging for food. In these algorithms some simple agents (i.e. ants), search the solution space for finding the suitable solution. Ant colony algorithms have many applications to computer science problems especially in optimization, such as machine drill optimization, and routing. This group of algorithms have some sensitive parameters controlling the behavior of agents, like relative pheromone importance on trail and pheromone decay coefficient. Convergence and efficiency of algorithms is highly related to these parameters. Optimal value of these parameters for a specific problem is determined through trial and error and does not obey any rule. Some approaches proposed to adapt parameter of these algorithms for better answer. The most important feature of the current adaptation algorithms are complication and time overhead. In this paper we have presented a simple and efficient approach based on fuzzy logic for optimizing ACS algorithm and by using different experiments efficiency of this proposed approach has been evaluated and we have shown that the presented concept is one of the most important reasons in success for parameter adapting algorithms.
A New HadoopBased Network Management System withPolicy Approach
Authors: Namvarasl Sahar , Abdi Vajihe , Javidan Reza
Published: October 2018

In recent years with the improvement in the field of network technology and decreasing of technology cost, lots of data are produced. This massive amount of data needs mechanism for processing and mining information rapidly. In this paper a new Hadoop based network management system with policy approach which is considered hierarchical manager is presented. Storing and processing massive data efficiently are two capability of Hadoop technology by using HDFS and MapReduce. In this paper, processing time is considered as a main factor. As a result it is proved that this management system using policy approach increases the performance of entire system without putting on extra cost for implementation. This system in contrast with pure Hadoop and centralized system is several times more rapid.
Network Survivability Performance Evaluation in Underwater Surveillance System Using Markov Model
Authors: Nabavi Seyyed Yahya , Mohammadi Reza , Keshtgari Manijeh
Published: October 2018

Underwater Wireless Sensor Network (UWSN) is a useful technology that can be used in Underwater Surveillance System (USS). USSs are mostly used in military purposes for detecting underwater military activities. One of the most important issues in USS is mission reliability or survivability. Due to harsh underwater environment and mission critical nature of military applications, it is important to measure survivability of USS. Underwater sensor node failures can be detrimental for USS. To improve survivability in USS, we propose a fault-tolerant underwater sensor node model. To the best of our knowledge, this is the first fault-tolerant underwater sensor node model in USS that evaluates survivability of an USS. Â We develop Markov models for characterizing USS survivability and MTTF (Mean Time to Failure) to facilitate USS. Performance evaluation results show the effectiveness of proposed model.
Game Theory Approaches in Taxonomy of Intrusion Detection for MANETs
Authors: Javidi Mohammad Masoud , Aliahmadipour Laya
Published: October 2018

MANETs are self configuring networks that are formed by a set of wireless mobile nodes and have no fixed network infrastructure nor administrative support. Since transmission range of wireless network interfaces is limited, forwarding hosts may be needed. Each node in a wireless ad hoc network functions is as both a host and a router. Due to their communication type and resources constraint, MANETs are vulnerable to diverse types of attacks and intrusions so, security is a critical issue. Network security is usually provided in the three phases: intrusion prevention, intrusion detection and intrusion tolerance phase. However, the network security problem is far from completely solved. Researchers have been exploring the applicability of game theory approaches to address the network security issues. This paper reviews some existing game theory solutions which are designed to enhance network security in the intrusion detection phase. Keywords: Mobile Ad hoc Network (MANET), Intrusion detection system (IDS), Cluster head, host based, Game theory.
Dynamic Location Modelling in 3D Beamforming for 5G Mobile Communications
Authors: A Sasi , P Santhiya
Published: October 2018

Mobile communication system is designed to provide reliable communication with more number of services and with low cost among multiple users. Due to limited frequency spectrum and resources, mobile communication requires more development in case of both establishing communication and maintenance in service quality. To fulfill these requirements, 5G mobile communication is being developed to provide high quality reliable communication and quality of service, by using beamforming model. As the trend of next generation mobile communication, 3D directional transmission is considered to give enhanced coverage model and reusability of frequency. Phase arrayed antenna is used in this beamforming model to give orthogonal communication among users. In this paper, a new modeling of beamforming is applied to give a new dimension by considering altitude with potential field strategy. Here phase arrayed antenna is replaced by 3-D smart antenna to improve the performance of 5G mobile communications. Performance evaluation outcomes 3D beamforming leads 2D beamforming in terms of communication delay, and uplink downlink throughput.
Green Cloud and reduction of energy consumption
Authors: Khajehei Kamyab
Published: October 2018

By using global application environments, cloud computing based data centers growing every day and this exponentially grows definitely effect on our environment. Researchers that have a commitment to their environment and others which was concerned about the electricity bills came up with a solution which called â€œGreen Cloudâ€. Green cloud data centers based on how consume energy are known as high efficient data centers. In green cloud we try to reduce number of active devices and consume less electricity energy. In green data centers toke an advantage of VM and ability of copying, deleting and moving VMs over the data center and reduce energy consumption. This paper focused on which parts of data centers may change and how researchers found the suitable solution for each component of data centers. Also with all these problems why still the cloud data centers are the best technology for IT businesses.
Network Selection Problems - QoE vs QoS Who is the Winner?
Authors: Mohanan Vasuky Mohanan , Aldmour Ismat
Published: October 2018

In network selection problem (NSP), there are now two schools of thought. There are those who think using QoE (Quality of Experience) is the best yardstick to measure the suitability of a Candidate Network (CN) to handover to. On the other hand, Quality of Service (QoS) is also advocated as the solution for network selection problems. In this article, a comprehensive framework that supports effective and efficient network selection is presented. The frameworkÂ Â  attempts to provide a holistic solution to network selection problem that is achieved by combining both of the QoS and QoE measures.Â Â  Using this hybrid solution the best qualities in both methods are combined to overcome issues of the network selection problem According to ITU-R (International Telecommunications Union â€“ Radio Standardization Sector), a 4G network is defined as having peak data rates of 100Mb/s for mobile nodes with speed up to 250 km/hr and 1Gb/s for mobile nodes moving at pedestrian speed. Based on this definition, it is safe to say that mobile nodes that can go from pedestrian speed to speed of up to 250 km/hr will be the norm in future. This indicates that the MNâ€™s mobility will be highly dynamic. In particular, this article addresses the issue of network selection for high speed Mobile Nodes (MN) in 4G networks. The framework presented in this article also discusses how the QoS value collected from CNs can be fine-tuned to better reflect an MNâ€™s current mobility scenario.
Parallel Continuous Double Auction for Service Allocation in Cloud Computing
Authors: Farajian Nima , Ebrahim pour-komleh Hossein
Published: October 2018

Cloud Computing is a service oriented architecture in which every computing resources is delivered to users as a service. Nowadays market-oriented approach has attracted a lot of researchers because of its great ability to manage Cloud services efficiently and dynamically. Each service consists of various resources which all should be allocated to utilize the service. In this paper a parallel continuous double auction method for efficient service allocation in cloud computing is presented in which by using a novel parallel sorting algorithm at auctioneer, enables consumers to order various resources as workflow for utilizing requested services efficiently. Also in the presented method consumers and providers make bid and offer prices based on time factor. Experimental results show that proposed method is efficient in success rate, resource utilization and average connection time and also overall performance of system is improved by parallel approach.
Energy efficient virtual machine placement algorithm with balanced resource utilization based on priority of resources
Authors: Rahimi Amin , Mohammad Khanli Leili , Pashazadeh Saeid
Published: October 2018

The increasing energy consumption has become a major concern in cloud computing due to its cost and environmental damage. Virtual Machine placement algorithms have been proven to be very effective in increasing energy efficiency and thus reducing the costs. In this paper we have introduced a new priority routing VM placement algorithm and have compared it with PABFD (power-aware best fit decreasing) on CoMon dataset using CloudSim for simulation. Our experiments show the superiority of our new method with regards to energy consumption and level of SLA violations measures and prove that priority routing VM placement algorithm can be effectively utilized to increase energy efficiency in the clouds.
Fingerprint Enhancement Algorithm Based-on Gradient Magnitude for the Estimation of Orientation Fields
Authors: Saparudin Saparudin , Sulong Ghazali
Published: October 2018

An accurate estimation of fingerprint orientation fields is an important step in the fingerprint classification process. Gradient-based approaches are often used for estimating orientation fields of ridge structures but this method is susceptible to noise. Enhancement of fingerprint images improves the ridge-valley structure and increases the number of correct features thereby conducing the overall performance of the classification process. In this paper, we propose an algorithm to improve ridge orientation textures using gradient magnitude. That algorithm has four steps; firstly, normalization of fingerprint image, secondly, foreground extraction, thirdly, noise areas identification and marking using gradient coherence and finally, enhancement of grey level. We have used standard fingerprint database NIST-DB14 for testing of proposed algorithm to verify the degree of efficiency of algorithm. The experiment results suggest that our enhanced algorithm achieves visibly better noise resistance with other methods.
C4.5 Versus Other Decision Trees: A Review
Authors: Ã–zsoy Salih , Gumus Gokhan , Khalilov Savriddin
Published: October 2018

In this study, Data Mining, one of the latest technologies of the Information Systems, was introduced and Classification a Data Mining method and the Classification algorithms were discussed. A classification was applied by using C4.5 decision tree algorithm on a dataset about Labor Relations from http://archive.ics.uci.edu/ml/datasets.html. Finally, C4.5 algorithm was compared to some other decision tree algorithms. C4.5 was the one of the successful classifier.
A MATLAB-Based Interactive Environment for EMG Signal Decomposition Utilizing Matched Template Filters
Authors: Rasheed Sarbast
Published: October 2018

An interactive software package for analyzing and decomposing electromyographic (EMG) signals is designed, constructed, and implemented using the MATLAB high-level programming language and its interactive environment. EMG signal analysis in the form of signal decomposition into their constituent motor unit potential trains (MUPTs) is considered as a classification task. Matched template filter methods have been employed for the classification of motor unit potentials (MUPs) in which the assignment criterion used for MUPs is based on a combination of MUP shapes and motor unit firing pattern information. The developed software package consists of several graphical user interfaces used to detect individual MUP waveforms from raw EMG signals, extract relevant features, and classify MUPs into MUPTs using matched template filter classifiers. The proposed software package is useful for enhancing the analysis quality and providing a systematic approach to the EMG signal decomposition process. It also worked as a very helpful environment for testing and evaluating algorithms developed for EMG signal decomposition research.
Performance Analysis of Multiple Virtualized Servers
Authors: Homayoun Sajad , Jalili Ahmad , Keshtgari Manijeh
Published: October 2018

Server virtualization is considered as one of the most significant changes in IT operations in the past decade, making it possible to manage groups of servers with a greater degree of reliability at a lower cost. It is driven by the goal of reducing the total number of physical servers in an organization by consolidating multiple applications on shared servers. In this paper we construct several x86_64 servers based on VMware vSphere, and then analyze their performances using open source analyzing tools Pylot and Curl-loader. The results show that despite the enormous potential benefits of virtualization techniques, the efficiency decreased by increasing the number of virtual machines. So, a trade-off is needed between number of virtual machines and expected efficiency of servers.
Cloud based Smart Irrigation for Agricultural Area of Pakistan
Authors: Syed Darakhshan , Masood Usama Bin , Farwa Umme E , Khurram Muhammad
Published: October 2018

A beneficial product of Smart Irrigation for Agricultural Area of Pakistan has been presented in this paper. Pakistan stands in need of a participatory solution that is efficiently workable, sustainable, and profitable, to develop the way for the agricultural sector by improving crop productivity with minimum water loss. The goal of this project is to introduce Cloud support to the Smart Irrigation System for Agricultural Area of Pakistan. To achieve this objective Wireless Sensor Network (WSN) is used to determine how much water to apply and when to irrigate. The system is divided into four main modules, i.e. Sensor node, Coordinator node, Server Module and Web Application. On the basis of acquired parameters from the WSN, the software application is programmed to take intelligent decisions increase the efficiency of the agricultural system.
Data Mining Applications in Big Data
Authors: Wang Lidong , Wang Guanghui
Published: October 2018

Data mining is a process of extracting hidden, unknown, but potentially useful information from massive data. Big Data has great impacts on scientific discoveries and value creation. This paper introduces methods in data mining and technologies in Big Data. Challenges of data mining and data mining with big data are discussed. Some technology progress of data mining and data mining with big data are also presented.
An Analysis of Vulnerability Web Against Attack Unrestricted Image File Upload
Authors: Riadi Imam , Aristianto Eddy Irawan
Published: October 2018

The development of computer security technology is very rapidly. Web security is one of the areas that require particular attention related to the abundance of digital crimes conducted over the web. Unrestricted file upload image is a condition in the process of uploading pictures is not restricted. This can be used to make the attacker retrieve the information that is contained in a system. This research developed with several stages, such as, data collection, analysis of the current conditions, designing improvements to the program code, testing and implementation of the results of patch. Security testing is performed to find out the difference between before and after conditions applied patch unrestricted image file upload. Based on the results of testing done by the method of penetration testing results obtained before the application of patch unrestricted image file upload results respondents said 15% strongly disagree, 85% did not agree. Testing after applying patch unrestricted image file upload results respondents said 7.5% strongly agree, 92.5% agree, so it can be concluded that the development of the patch that has been done has been running smoothly as expected.
Balancing and Lucas-Balancing Numbers and their Application to Cryptography
Authors: Swain Sujata , Pratihary Chidananda , Kumar Ray Prasanta
Published: October 2018

It is well known that, a recursive relation for the sequence Â is an equation that relates Â to certain of its preceding terms . Initial conditions for the sequence Â are explicitly given values for a finite number of the terms of the sequence. The recurrence relation is useful in certain counting problems like Fibonacci numbers, Lucas numbers, balancing numbers, Lucas-balancing numbers etc. In this study, we use the recurrence relations for both balancing and Lucas-balancing numbers and examine their application to cryptography.
High Load Control Mechanism for SIP Servers
Authors: Montazerolghaem Ahmadreza , Hosseini-Seno Seyed-Amin , Hossein Yaghmaee Mohammad , Budiarto Rahmat
Published: October 2018

To start voice, image, instant messaging, and generally multimedia communication, session communication must begin between two participants. SIP (session initiation protocol) that is an application layer control induces management and terminates this kind of sessions. As far as the independence of SIP from transport layer protocols is concerned, SIP messages can be transferred on a variety of transport layer protocols including TCP or UDP. Mechanism of Retransmission that is embedded in SIP could compensate for the missing packet loss, in case of need. This mechanism is applied when SIP messages are transmitted on an unreliable transmission layer protocol like UDP. Also, while facing SIP proxy with overload, it could cause excessive filling of proxy queue, postpone increase of other contacts, and add to the amount of the proxy overload. In the present work, while using UDP as transport layer protocol, invite retransmission timer (T1) was appropriately regulated and SIP functionality was improved. Therefore, by proposing an adaptive timer of invite message retransmission, attempts were made to improve the time of session initiation and consequently improve the performance. Performance of the proposed SIP was implemented and evaluated by SIPP software in a real network environment and its accuracy and performance were demonstrated.
Peak to Average Power Ratio Reduction in OFDM Using Pulse Shaping Technique
Authors: Das Diptadeep
Published: October 2018

Orthogonal Frequency Division Multiplexing (OFDM) is a special type of multicarrier modulation in which a signal is split into several narrowband channels at different frequencies. Here data is divided into parallel data streams each transmitted on a separate band. One of the major drawbacks of multicarrier transmission is the high peak-to-average power ratio (PAPR) of the transmit signal. Nyquist filters provide ISI-free transmission. In this paper we are going to propose some new filters which can formulated in an effort to reduce the peak-to-average power ratio (PAPR) of the baseband signal. While maintaining the same excess bandwidth and the zero inter-symbol interference condition. The proposed filters contain various parameters which gives an additional degree of freedom to minimize PAPR for a given roll-off factor Î± .
A Proposed Software as a Service (SaaS) Toolkit for Cloud Multi- Tenancy
Authors: Imam Mohamed Osman , Yousif Adil , Bashir Mohammed Bakri
Published: October 2018

Cloud computing is a general term for anything that involves delivering hosted services over the Internet. It is a construct that allows you to access applications that actually reside at locations other than your computer or other Internet-connected devices. Software as a Service (SaaS) is a software delivery model in which software resources are accessed remotely by users over the internet. Enterprises prefer using SaaS because of its low cost. SaaS requires sharing of application servers among multiple tenants for low operational costs. Several SaaS Toolkits are available and used to develop cloud SaaS applications. However, most of these Toolkits are very complex. This paper aims to build a new simple and easy SaaS Toolkit to develop SaaS applications and to avoid the difficulties and complexity in the current cloud SaaS Toolkits. The proposed Toolkit is based on java virtual machine and the popular web programming languages HTML and PHP. To evaluate the proposed Toolkit an empirical study has been conducted. The result of the empirical study revealed that the proposed Toolkit outperforms the current Toolkits in terms of complexity, understandability and learnability.
A Modified Black Hole-Based Task Scheduling Technique for Cloud Computing Environment
Authors: Ebadifard Fatemeh , Borhanifard Zeinab
Published: October 2018

The issue of scheduling is one of the most important ones to be considered by providers of the cloud computing in the data center. Using a suitable solution lets the providers of cloud computing use the available resources more. Additionally, the satisfaction of clients is met through provision of service quality parameters. Most of the solutions for this problem aim at one of the service quality factors and in order to achieve this goal, variety of methods are used. Using the algorithm of modified black hole in this paper, a proper solution is presented to tackle the problem of scheduling the affairs in cloud environment. The proposed method reduces makespan, increases degree of load balancing, and improves the resource`s utilization by considering the capability of each virtual machine. We have compared the proposed algorithm with existing task scheduling algorithms. Simulation results indicate that the proposed algorithm makes a good improvement regarding the makespan and amount of resource utilization compared to schedulers based on Random assignment and particle swarm optimization Algorithms.
Boosting diagnosis accuracy of Alzheimer's disease using statistical and kernel-based feature selection techniques
Authors: Balafar M. A , Norzadeh Rouya
Published: October 2018

Alzheimer's disease (AD) is the most common type of dementia in the elderly. Approximately, 26 million people worldwide are affected by AD. Among the various diagnostic methods for Alzheimer's disease, MRI brain imaging can display sharp changes in brain tissues. It can be used as a method for early diagnosis of Alzheimer's disease. Considering the high volume of features related to brain tissue thickness, requires the using feature reduction methods. For this purpose, statistical tests pair sample test and Independent sample test was used. After careful selection of key features, for reducing the number of features, SAS which is a kernel-based feature selection algorithm is used in linear and nonlinear mode. At the end, neural network classification, decision trees, nearest neighbor and NaÃ¯ve Bayes algorithms are used for modeling. Results show that the classification accuracy of obtained feature subsets have better results compare to the original data set.
Dual Band Fractal Antenna Design for Wireless Application
Authors: Zakariyya O.S. , Sadiq Bashir Olaniyi , Olaniyan A.A , Salami A.F.
Published: October 2018

The objective of this paper was to design and analyze a dual wide band compact antenna for wireless application. Microstrip patch antenna limitation was overcome by using fractal geometry. The proposed antenna was designed with a radius of 15mm on a FR4 lossy substrate with relative permittivity of 4.4 and loss factor of 0.025. Measurement result showed that the antenna has a dual band of operation with bandwidth for return loss below -10dB of 1.84GHz (2.2GHz-4.07GHz) and 2GHz (6GHz-8GHz) which can be applied to wireless local area network (WLAN) and Ultra wide band applications.
Object Reconstruction from 2D Drawing sketch to 3D Object
Authors: Passarella Rossi , Arsalan Osvari
Published: October 2018

Design engineer in the early phase of building up another product is Â typically using a freehand sketching to communicate or illustrate the idea in the form of orthographic projection. This orthographic projection is based on viewpoint. A translation from 2D drawingÂ  view point to 3D models is needed to help engineer to imagine the product preview in 3D. This procedure includes a tedious, so that automation is needed. The way to deal with this reproduction issue begin straightforwardly from 2D freehand portraying, by using the camera, the 2D drawing is captured and then transferred to a Personal Computer. Inside the computer, the image is processed withÂ  filtering to find the view point zones. The view point zone than separate to 3 zones, each zone consists of the pixel coordinate. This coordinates are used to generated and processing of 3D voxel Image according to the form of geometries. A case study is presented in order to emphasize and discuss the proposed method
Multicast Energy Aware Routing in Wireless Networks
Authors: Karimi Ahmad
Published: October 2018

Multicasting is a service for disseminating data to a group of hostsand it is of paramount importance in applications with a close collabo-ration of network hosts. Due to limited energy available in the wirelessdevices, energy management is one of the most important problems inwireless networks. Energy aware routing strategies help us to mini-mize the energy costs for communication as much as possible and toincrease the network lifetime. In this paper, we address the problemof energy efficient routing to increase the lifetime of the network. Wepresent three new strategies for online multicast energy aware routingin wireless networks to increase the network lifetime.
Network-on-Chip Paradigm for System-on-Chip Communication
Authors: Budiarto Rahmat , Siregar Lelyzar , Stiawan Deris
Published: October 2018

Developments of modern technologies in electronics, such as communication, Internet, pervasive and ubiquitous computing and ambient intelligence have figured largely our life. In our day micro-electronic products inspire the ways of learning, communication and entertainment. These products such as laptop computer, mobile phones, and personal handheld sets are becoming faster, lighter in weight, smaller in size, larger in capacity, lower in power consumptions, cheaper and functionally enhanced. This trend will persistently continue. Following this trend, we could integrate more and more complex applications and even systems onto a single chip. The System-on-Chip (SoC) technologies, where complex applications are integrated onto single ULSI chips became key driving force for the developments.