Call for Papers - IJORCS - Volume 3, Issue 2

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Welcoming the research scholars, scientists around the globe in the Open Access Dimension, IJORCS is now accepting manuscripts for its next issue (Volume 3, Issue 2). Authors are encouraged to contribute to the research community by submitting to IJORCS, articles that clarify new research results, projects, surveying works and industrial experiences that describe significant advances in field of computer science.

Tecnología

White Globe Publications®
International Journal of Research in Computer Science
CALL FOR PAPERS – Volume 3, Issue 2
International Journal of Research in Computer Science
eISSN: 2249 – 8265 | ISSN: 2249 – 8257
IMPORTANT DATES
Deadline: 1st February 2013
Notification: 15th February 2013
Revision: 25th February 2013
Publication: 5th March 2013
It is our immense pleasure to invite you to submit your manuscripts for publication in International Journal of
Research in Computer Sciences, a double blind peer-reviewed journal dedicated to the propagation and elucidation
of scholarly research results.
IJORCS aims to disseminate quality research work and to enhance the ethics and morale of the research
community. Besides providing a platform for the reinforcement of science, fast operative publication, IJORCS
disseminates the published research work in major indexing databases all over the world which includes, Citeseer,
Microsoft Academic Research, BASE, Q-Sensei, Google Scholar, DOAJ, Cabell’s Directory and many more.
IJORCS is now associated with CrossRef (The Citation Linking Backbone) as a Member. A DOI Prefix: "10.7815"
has been assigned by CrossRef and as a result your manuscript, if published in IJORCS would be assigned a DOI
(Digital Object Identifier) number which would be unique in the world each article.
Welcoming the research scholars, scientists around the globe in the Open Access Dimension, IJORCS is now
accepting manuscripts for its next issue (Volume 3, Issue 2). Authors are encouraged to contribute to the research
community by submitting to IJORCS, articles that clarify new research results, projects, surveying works and
industrial experiences that describe significant advances in field of computer science.
Topic Coverage
• Ad Hoc networks • Autonomous Computing • Advanced Computing Architectures
• Bio-Informatics & Biotechnology • Cloud Computing and Applications • Computational intelligence
• Comp Architecture • Cryptography • Data Base Management
• Data Mining Data • Digital signal processing theory • E-Commerce
• Fuzzy algorithms & Fuzzy logics • Information Technology • Human Computer Interaction (HCI)
• Image analysis and processing • Multimedia applications • Neural networks
• Information and data security • Knowledge based systems • Medical imaging
• Natural Language Processing • Real-time systems • Remote Sensing
• Supply Chain Management • Virtual reality • Wireless technology
• Context-Aware Computing • Software Engineering • Embedded Systems

To view complete list of topics coverage of IJORCS, Aim & Scope, please visit, www.ijorcs.org/scope
Authors are requested to submit their papers through the submission form available at: www.ijorcs.org/submit-
paper or they can send it through email to: submission@ijorcs.org.
Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and
publish your scientific manuscripts.

For more information visit, www.ijorcs.org
Contacts: +918054039690, +919780335152
Email: info@ijorcs.org, editor@ijorcs.org, whiteglobepublications@gmail.com

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Control of traffic lights at the intersections of the main issues is the optimal traffic. Intersections to regulate traffic flow of vehicles and eliminate conflicting traffic flows are used. Modeling and simulation of traffic are widely used in industry. In fact, the modeling and simulation of an industrial system is studied before creating economically and when it is affordable. The aim of this article is a smart way to control traffic. The first stage of the project with the objective of collecting statistical data (cycle time of each of the intersection of the lights of vehicles is waiting for a red light) steps where the data collection found optimal amounts next it is. Introduced by genetic algorithm optimization of parameters is performed. GA begin with coding step as a binary variable (the range specified by the initial data set is obtained) will start with an initial population and then a new generation of genetic operators mutation and crossover and will Finally, the members of the optimal fitness values are selected as the solution set. The optimal output of Petri nets CPN TOOLS modeling and software have been implemented. The results indicate that the performance improvement project in intersections traffic control systems. It is known that other data collected and enforced intersections of evolutionary methods such as genetic algorithms to reduce the waiting time for traffic lights behind the red lights and to determine the appropriate cycle.

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License plate recognition system is one of the core technologies in intelligent traffic control. In this paper, a new and tunable algorithm which can detect multiple license plates in high resolution applications is proposed. The algorithm aims at investigation into and identification of the novel Iranian and some European countries plate, characterized by both inclusion of blue area on it and its geometric shape. Obviously, the suggested algorithm contains suitable velocity due to not making use of heavy pre-processing operation such as image-improving filters, edge-detection operation and omission of noise at the beginning stages. So, the recommended method of ours is compatible with model-adaptation, i.e., the very blue section of the plate so that the present method indicated the fact that if several plates are included in the image, the method can successfully manage to detect it. We evaluated our method on the two Persian single vehicle license plate data set that we obtained 99.33, 99% correct recognition rate respectively. Further we tested our algorithm on the Persian multiple vehicle license plate data set and we achieved 98% accuracy rate. Also we obtained approximately 99% accuracy in character recognition stage.

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This Paper is a review study of FPGA implementation of Finite Impulse response (FIR) with low cost and high performance. The key observation of this paper is an elaborate analysis about hardware implementations of FIR filters using different algorithm i.e., Distributed Arithmetic (DA), DA-Offset Binary Coding (DA-OBC), Common Sub-expression Elimination (CSE) and sum-of-power-of-two (SOPOT) with less resources and without affecting the performance of the original FIR Filter.

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An approach has been presented in this paper in order to generate a secure environment on internet Based Virtual Computing platform and also to reduce energy consumption in green cloud computing. The proposed approach constantly checks the accuracy of stored data by means of a central control service inside the network environment and also checks system security through isolating single virtual machines using a common virtual environment. This approach has been simulated on two types of Virtual Machine Manager (VMM) Quick EMUlator (Qemu), HVM (Hardware Virtual Machine) Xen and outputs of the simulation in VMInsight show that when service is getting singly used, the overhead of its performance will be increased. As a secure system, the proposed approach is able to recognize malicious behaviors and assure service security by means of operational integrity measurement. Moreover, the rate of system efficiency has been evaluated according to the amount of energy consumption on five applications (Defragmentation, Compression, Linux Boot Decompression and Kernel Boot). Therefore, this has been resulted that to secure multi-tenant environment, managers and supervisors should independently install a security monitoring system for each Virtual Machines (VMs) which will come up to have the management heavy workload of. While the proposed approach, can respond to all VM’s with just one virtual machine as a supervisor.

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The cryptographic hash function SHA-256 is one member of the SHA-2 hash family, which was proposed in 2000 and was standardized by NIST in 2002 as a successor of SHA-1. Although the differential fault attack on SHA-1compression function has been proposed, it seems hard to be directly adapted to SHA-256. In this paper, an efficient algebraic fault attack on SHA-256 compression function is proposed under the word-oriented random fault model. During the attack, an automatic tool STP is exploited, which constructs binary expressions for the word-based operations in SHA-256 compression function and then invokes a SAT solver to solve the equations. The simulation of the new attack needs about 65 fault injections to recover the chaining value and the input message block with about 200 seconds on average. Moreover, based on the attack on SHA-256 compression function, an almost universal forgery attack on HMAC-SHA-256 is presented. Our algebraic fault analysis is generic, automatic and can be applied to other ARX-based primitives.

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The principal goal to design any encryption algorithm must be the security against unauthorized access or attacks. Data Encryption Standard algorithm is a symmetric key algorithm and it is used to secure the data. Enhanced DES algorithm works on increasing the key length or complex S-BOX design or increased the number of states in which the information is to be represented or combination of above criteria. By increasing the key length, the number of combinations for key will increase which is hard for the intruder to do the brute force attack. As the S-BOX design will become the complex there will be a good avalanche effect. As the number of states increases in which the information is represented, it is hard for the intruder to crack the actual information. Proposed algorithm replace the predefined XOR operation applied during the 16 round of the standard algorithm by a new operation called “Hash function” depends on using two keys. One key used in “F” function and another key consists of a combination of 16 states (0,1,2…13,14,15) instead of the ordinary 2 state key (0, 1). This replacement adds a new level of protection strength and more robustness against breaking methods.

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This paper presents a new algorithm for solving large scale global optimization problems based on hybridization of simulated annealing and Nelder-Mead algorithm. The new algorithm is called simulated Nelder-Mead algorithm with random variables updating (SNMRVU). SNMRVU starts with an initial solution, which is generated randomly and then the solution is divided into partitions. The neighborhood zone is generated, random number of partitions are selected and variables updating process is starting in order to generate a trail neighbor solutions. This process helps the SNMRVU algorithm to explore the region around a current iterate solution. The Nelder- Mead algorithm is used in the final stage in order to improve the best solution found so far and accelerates the convergence in the final stage. The performance of the SNMRVU algorithm is evaluated using 27 scalable benchmark functions and compared with four algorithms. The results show that the SNMRVU algorithm is promising and produces high quality solutions with low computational costs.

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It is easy for human to recognize familiar voice but using computer programs to identify a voice when compared with others is a herculean task. This is due to the problem that is encountered when developing the algorithm to recognize human voice. It is impossible to say a word the same way in two different occasions. Human speech analysis by computer gives different interpretation based on varying speed of speech delivery. This research paper gives detail description of the process behind implementation of an effective voice recognition algorithm. The algorithm utilize discrete Fourier transform to compare the frequency spectra of two voice samples because it remained unchanged as speech is slightly varied. Chebyshev inequality is then used to determine whether the two voices came from the same person. The algorithm is implemented and tested using MATLAB.

Voice Recognition System using Template Matching

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The proper channel utilization and the queue length aware routing protocol is a challenging task in MANET. To overcome this drawback we are extending the previous work by improving the MAC protocol to maximize the Throughput and Fairness. In this work we are estimating the channel condition and Contention for a channel aware packet scheduling and the queue length is also calculated for the routing protocol which is aware of the queue length. The channel is scheduled based on the channel condition and the routing is carried out by considering the queue length. This queue length will provide a measurement of traffic load at the mobile node itself. Depending upon this load the node with the lesser load will be selected for the routing; this will effectively balance the load and improve the throughput of the ad hoc network.

Channel Aware Mac Protocol for Maximizing Throughput and Fairness

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Over a last decade, mobile telecommunication industry has observed a rapid growth, proved to be highly competitive, uncertain and dynamic environment. Besides its advancement, it has also raised number of questions and gained concern both in industry and research. The development process of mobile application differs from traditional softwares as the users expect same features similar to their desktop computer applications with additional mobile specific functionalities. Advanced mobile applications require assimilation with existing enterprise computing systems such as databases, legacy applications and Web services. In addition, the lifecycle of a mobile application moves much faster than that of a traditional Web application and therefore the lifecycle management associated therein must be adjusted accordingly. The Security and application testing are more stimulating and interesting in mobile application than in Web applications since the technology in mobile devices progresses rapidly and developers must stay in touch with the latest developments, news and trends in their area of work. With the rising competence of software market, researchers are seeking more flexible methods that can adjust to dynamic situations where software system requirements are changing over time, producing valuable software in short duration and within low budget. The intrinsic uncertainty and complexity in any software project therefore requires an iterative developmental plan to cope with uncertainty and a large number of unknown variables. Agile Methodologies were thus introduced to meet the new requirements of the software development companies. The agile methodologies aim at facilitating software development processes where changes are acceptable at any stage and provide a structure for highly collaborative software development. Therefore, the present paper aims in reviewing and analysing different prevalent methodologies utilizing agile techniques that are currently in use for the development of mobile applications. This paper provides a detailed review and analysis on the use of agile methodologies in the proposed processes associated with mobile application skills and highlights its benefit and constraints. In addition, based on this analysis, future research needs are identified and discussed.

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In general, nodes in Wireless Sensor Networks (WSNs) are equipped with limited battery and computation capabilities but the occurrence of congestion consumes more energy and computation power by retransmitting the data packets. Thus, congestion should be regulated to improve network performance. In this paper, we propose a congestion prediction and adaptive rate adjustment technique for Wireless Sensor Networks. This technique predicts congestion level using fuzzy logic system. Node degree, data arrival rate and queue length are taken as inputs to the fuzzy system and congestion level is obtained as an outcome. When the congestion level is amidst moderate and maximum ranges, adaptive rate adjustment technique is triggered. Our technique prevents congestion by controlling data sending rate and also avoids unsolicited packet losses. By simulation, we prove the proficiency our technique. It increases system throughput and network performance significantly.

Congestion Prediction and Adaptive Rate Adjustment Technique for Wireless Sen...

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A Mobile Ad hoc Network (MANET) is a self-configuring infrastructure less network of mobile devices connected by wireless. These are a kind of wireless Ad hoc Networks that usually has a routable networking environment on top of a Link Layer Ad hoc Network. The routing approach in MANET includes mainly three categories viz., Reactive Protocols, Proactive Protocols and Hybrid Protocols. These traditional routing schemes are not pertinent to the so called Intermittently Connected Mobile Ad hoc Network (ICMANET). ICMANET is a form of Delay Tolerant Network, where there never exists a complete end – to – end path between two nodes wishing to communicate. The intermittent connectivity araise when network is sparse or highly mobile. Routing in such a spasmodic environment is arduous. In this paper, we put forward the indication of prevailing routing approaches for ICMANET with their benefits and detriments

A Study of Routing Techniques in Intermittently Connected MANETs

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In the field of speech signal processing, Spectral subtraction method (SSM) has been successfully implemented to suppress the noise that is added acoustically. SSM does reduce the noise at satisfactory level but musical noise is a major drawback of this method. To implement spectral subtraction method, transformation of speech signal from time domain to frequency domain is required. On the other hand, Wavelet transform displays another aspect of speech signal. In this paper we have applied a new approach in which SSM is cascaded with wavelet thresholding technique (WTT) for improving the quality of speech signal by removing the problem of musical noise to a great extent. Results of this proposed system have been simulated on MATLAB.

Improving the Efficiency of Spectral Subtraction Method by Combining it with ...

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Due to the restriction of designing faster and faster computers, one has to find the ways to maximize the performance of the available hardware. A distributed system consists of several autonomous nodes, where some nodes are busy with processing, while some nodes are idle without any processing. To make better utilization of the hardware, the tasks or load of the overloaded node will be sent to the under loaded node that has less processing weight to minimize the response time of the tasks. Load balancing is a tool used effectively for balancing the load among the systems. Dynamic load balancing takes into account of the current system state for migration of the tasks from heavily loaded nodes to the lightly loaded nodes. In this paper, we devised an adaptive load-sharing algorithm to balance the load by taking into consideration of connectivity among the nodes, processing capacity of each node and link capacity.

An Adaptive Load Sharing Algorithm for Heterogeneous Distributed System

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Modeling the behavior of the cognitive architecture in the context of social simulation using statistical methodologies is currently a growing research area. Normally, a cognitive architecture for an intelligent agent involves artificial computational process which exemplifies theories of cognition in computer algorithms under the consideration of state space. More specifically, for such cognitive system with large state space the problem like large tables and data sparsity are faced. Hence in this paper, we have proposed a method using a value iterative approach based on Q-learning algorithm, with function approximation technique to handle the cognitive systems with large state space. From the experimental results in the application domain of academic science it has been verified that the proposed approach has better performance compared to its existing approaches.

The Design of Cognitive Social Simulation Framework using Statistical Methodo...

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To efficiently process continuous spatio-temporal queries, we need to efficiently and effectively handle large number of moving objects and continuous updates on these queries. In this paper, we propose a framework that employs a new indexing algorithm that is built on top of SQL Server 2008 and avoid the overhead related to R-Tree indexing. To answer range queries, we utilize dynamic materialized view concept to efficiently handle update queries. We propose an adaptive safe region to reduce communication costs between the client and the server and to minimize position update load. Caching of results was utilized to enhance the overall performance of the framework. To handle concurrent spatio-temporal queries, we utilize publish/subscribe paradigm to group similar queries and efficiently process these requests. Experiments show that the overall proposed framework performance was able to outperform R-Tree index and produce promising and satisfactory results.

An Enhanced Framework for Improving Spatio-Temporal Queries for Global Positi...

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There is a tremendous proliferation in the amount of information available on the largest shared information source, the World Wide Web. Fast and high-quality clustering algorithms play an important role in helping users to effectively navigate, summarize, and organize the information. Recent studies have shown that partitional clustering algorithms such as the k-means algorithm are the most popular algorithms for clustering large datasets. The major problem with partitional clustering algorithms is that they are sensitive to the selection of the initial partitions and are prone to premature converge to local optima. Subtractive clustering is a fast, one-pass algorithm for estimating the number of clusters and cluster centers for any given set of data. The cluster estimates can be used to initialize iterative optimization-based clustering methods and model identification methods. In this paper, we present a hybrid Particle Swarm Optimization, Subtractive + (PSO) clustering algorithm that performs fast clustering. For comparison purpose, we applied the Subtractive + (PSO) clustering algorithm, PSO, and the Subtractive clustering algorithms on three different datasets. The results illustrate that the Subtractive + (PSO) clustering algorithm can generate the most compact clustering results as compared to other algorithms.

A PSO-Based Subtractive Data Clustering Algorithm

IJORCS

In HMIPv6 Networks, most of the existing handoff decision mechanisms deal mainly with the selection of Mobility Anchor Point (MAP), ignoring the selection of access router (AR) under each MAP. In this paper, we propose a new mechanism called “Dynamic MAP and Diffserv based ARs selection for Handoff in HMIPv6 networks” and it deals with selecting the MAP as well as ARs. MAP will be selected dynamically by checking load, session mobility ratio (SMR), Binding update cost and Location Rate. After selecting the best MAP, the Diffserv approach is used to select the AR under the MAP, based on its resource availability. The AR is implemented at the edge router of Diffserv. DiffServ can be used to provide low-latency to critical network traffic such as voice or streaming media while providing simple best-effort service to non-critical services such as web traffic or file transfers. By using this mechanism, we can assure that better resource utilization and throughput can be attained during Handoff in HMIPv6 networks.

Dynamic Map and Diffserv Based AR Selection for Handoff in HMIPv6 Networks

IJORCS

In the modern world, billions of physical sensors are used for various dedications: Environment Monitoring, Healthcare, Education, Defense, Manufacturing, Smart Home, Agriculture Precision and others. Nonetheless, they are frequently utilized by their own applications and thereby snubbing the significant possibilities of sharing the resources in order to ensure the availability and performance of physical sensors. This paper assumes that the immense power of the Cloud can only be fully exploited if it is impeccably integrated into our physical lives. The principal merit of this work is a novel architecture where users can share several types of physical sensors easily and consequently many new services can be provided via a virtualized structure that allows allocation of sensor resources to different users and applications under flexible usage scenarios within which users can easily collect, access, process, visualize, archive, share and search large amounts of sensor data from different applications. Moreover, an implementation has been achieved using Arduino-Atmega328 as hardware platform and Eucalyptus/Open Stack with Orchestra-Juju for Private Sensor Cloud. Then this private Cloud has been connected to some famous public clouds such as Amazon EC2, ThingSpeak, SensorCloud and Pachube. The testing was successful at 80%. The recommendation for future work would be to improve the effectiveness of virtual sensors by applying optimization techniques and other methods.

From Physical to Virtual Wireless Sensor Networks using Cloud Computing

IJORCS

Prediction of Atmospheric Pressure is one important and challenging task that needs lot of attention and study for analyzing atmospheric conditions. Advent of digital computers and development of data driven artificial intelligence approaches like Artificial Neural Networks (ANN) have helped in numerical prediction of pressure. However, very few works have been done till now in this area. The present study developed an ANN model based on the past observations of several meteorological parameters like temperature, humidity, air pressure and vapour pressure as an input for training the model. The novel architecture of the proposed model contains several multilayer perceptron network (MLP) to realize better performance. The model is enriched by analysis of alternative hybrid model of k-means clustering and MLP. The improvement of the performance in the prediction accuracy has been demonstrated by the automatic selection of the appropriate cluster.

Prediction of Atmospheric Pressure at Ground Level using Artificial Neural Ne...

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