Informatics Publishing Limited

Anchugam Vangili ¹, K. Thangadurai ¹

Affiliations
1 P.G. and Research Department of Computer Science, Government Arts College (Autonomous), Karur - 639005, Tamil Nadu, IN

Abstract

Background: Security in Mobile Ad hoc Networks (MANETs) is an essential component for basic network function. Black hole attack may cause packet dropping, misrouting the information from source to destination. Methods: Biology-inspired techniques like as Ant Colony Optimization (ACO) is used to modify the Ad-hoc On Demand Distance Vector (AODV) routing protocol. The ant place of at each node calculates its pheromone value by using the forwarding ratio at node. This modified protocol is compared with existing protocol by using various parameters i.e. packet delivery ratio, end-to-end delay and throughput. Results: The results shows to increase in packet delivery ratio, throughput and decrease in end-to end delay show better performance of proposed work as compared existing.

Keywords

ACO, Black Hole Attack, Challenges, MANETs, Security

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K. Sekar ¹, K. Thangadurai ²

Affiliations
1 Department of Computer Application, Vivekanandha Institute of Information and Management Studies, Tiruchengode, Namakkal Dt, Tamilnadu, IN
2 Department of Computer Science, Government Arts College (Autonomous), Karur, Tamilnadu, Pincode–639 005, IN

Abstract

Network security is the process of preventing and detecting unauthorized use of your computer. Prevention measures help you to stop unauthorized users (also known as "intruders") from accessing any part of your network system. Detection helps you to determine whether or not someone attempted to break into your system, if they were successful, and what they may have done. We use computers for everything from banking and investing to shopping and communicating with others through email or chat programs. Although you may not consider your communications "top secret," you probably do not want strangers reading your email, using your network to attack other systems, sending forged email from your computer, or examining personal information stored on your network.

Keywords

NAT, TCP, UDP, DNS, SSH, POP3, IMAP, SMTP.

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G. Gopu ¹, K. Thangadurai ²

Affiliations
1 Dr. GRD College of Science, Avanashi Road, Coimbatore – 641014, Tamil Nadu, IN
2 Government Arts College, Karur - 639 005, Tamil Nadu, IN

Abstract

Objective: Phishing is a form of online identity theft that aims to acquire sensitive information from E-mail users such as password. E-mail users faces many security issues while they exchanging information. Methods/Statistical Analysis: In this paper we discussed the analysis of psychological and physicalconflicts from arrivals of new digital expertise. Due to thedesire knowledge of technology and its up-gradations which leads to commit a crime or may aim to target by others. Most of the cyber related crimes committed through E-Mail.To find E-mail phishing various view of analysis were adopted. Findings: With this analysis we found the role of phisher in an electronic mail and their way of thinking, planning and executing attacks for their personal gain and as well as for others benefit. Applications/Improvements: We improved the accuracy of findingswith PHP scriptand its impacts in India.

Keywords

Countermeasures,E-mail Networks, LAW and Punishments, Survey Finding.

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K. Padmavathi ¹, K. Thangadurai ²

Affiliations
1 Research and Development Centre, Bharathiar University, Coimbatore - 641046, Tamil Nadu, IN
2 PG and Research Department of Computer Science, Government Arts College (Autonomous), Karur - 639007, Tamil Nadu, IN

Abstract

Background/Objectives: Digital image processing is used various fields for analyzing different applications such as medical sciences, biological sciences. Various image types have been used to detect plant diseases. This work is analyzed and compared two types of images such as Grayscale, RGB images and the comparative result is given. Methods/Statistical Analysis: We examined and analyzed the Grayscale and RGB images using image techniques such as pre processing, segmentation, clustering for detecting leaves diseases. Results/Finding: In detecting the infected leaves, color becomes an important feature to identify the disease intensity. We have considered Grayscale and RGB images and used median filter for image enhancement and segmentation for extraction of the diseased portion which are used to identify the disease level. Conclusion: RGB image has given better clarity and noise free image which is suitable for infected leaf detection than Grayscale image.

Keywords

Comparison, Grayscale Images, Image Processing, Plant Leaves Disease Detection, RGB Images, Segmentation

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K. Thangadurai ¹, C. V. Anchugam ¹

Affiliations
1 P.G. and Research Department of Computer Science, Government Arts College (Autonomous), Karur, IN

Abstract

A Mobile Ad hoc Network (MANET) is a collection of wireless mobile nodes forming a network temporarily without any centralized administration of the mobile networks. Each node in MANET moves arbitrarily making the multi-hop network topology to change randomly at unpredictable times. Two nodes in such a network can communicate in a bidirectional manner if and only if the distance between them is at most the minimum of their transmission ranges. When a node wants to communicate with a node outside its transmission range, a multi-hop routing strategy is used which involves some intermediate nodes? Because of the movements of nodes, there is a constant possibility of topology change in MANET. There are several familiar routing protocols like DSDV, AODV, DSR, etc., Which have been proposed for providing communication among all the nodes in the network? This paper presents a performance comparison of proactive and reactive protocols AODV, DSDV and DSR based on metrics such as throughput, packet delivery ratio and average end-to-end delay by using the NS-2 simulator.

Keywords

MANET, DSDV, DSR, AODV, Throughput, Packet Delivery Ratio and Average End-to-End Delay.

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S. Francisca Rosario , K. Thangadurai

Abstract

Feature subset selection is a technique for reducing the attribute space of a feature set. In other words, it is identifying a subset of features by removing irrelevant or redundant features. A good feature set contains a highly relevant feature which helps to improve the efficiency of the classification algorithms and to classify accurately. Relief is a feature selection algorithm for random selection of instances for feature weight calculation. The Relief algorithm adopts the random selection of instances for weight estimation. It uses the Monte Carlo Approaches for randomization selection of instances in the Relief. The efficiency and effectiveness of proposed algorithm is evaluated with Cotton Disease  data sets  provided by cotton research  station  and WEKA tool. Naïve Bayes and J48 are used as the classifiers. The classification results, in terms of classification accuracy and size of  feature  subspace to show the performance of the Relief algorithm.

Keywords

Feature Selection, Relief, attribute, classification, randomization, Naïve Bayes, Weka, instances

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P. Menaka ¹, K. Thangadurai ²

Affiliations
1 Department of Computer Science, Manaonmaniam Sundaranar University, IN
2 Department of Computer Science, Government Arts College, Karur, IN

Abstract

Customer relation management is a significant feature in the business development which assists for business peoples to get the knowledge about the customer's opinions and can establish the profitable environment. Customer opinions were utilized to enhance the product, so that customer fulfilment and profit will rise desirably. So it is necessary to execute the functional design of customer opinions regarding the products which depends on the time duration. In the earlier work, Customer Knowledge Management (CKM) is established to raise the profit level of industries by tracking the entire regarding the product which is demanded by the customers. Nevertheless, creating and managing the CKM for the huge volume of the customer is a complex task. It results in inaccuracy, if in case it is done manually with less customer information. This issue is rectified in the proposed research methodology by bringing-in the methodology such as Neural Network based Social Customer Relation Management (NN-SCRM). This algorithm is utilized to examine the following factors by gathering the knowledge of the customer review information: "Predict the future, most profitable customers, maintaining quality of product development, customer life time value, identify customers and their products". This is done according to the information of the customer review, which, in turn, obtained from the customers opinions disclosed by their comments regarding the product. This proposed research work is executed and examined in the MATLAB simulation environment from which it is confirmed that the proposed research framework tends to give the best output than the current CKM frameworks.

Keywords

Knowledge Management, Review Analysis, Pre-Processing, Customer Opinions, Profit.

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V. Senthilkumar ¹, K. Thangadurai ², A. Asha ³

Affiliations
1 Dept. of Production Engg., National Institute of Technology, Trichy, IN
2 Dept. of Mech. Engg., Jayaram College of Engineering & Technology, Trichy, IN
3 Dept. of Mech. Engg., KLN College of Engineering & Technology, Sivagangai, IN

Abstract

Nowadays modern manufacturing system is enforced to find out the new material such as metal matrix composite or ceramic matrix composite. The aim of this research is to invent the aluminium based metal matrix composite such as 80% of Al 6061-20% of SiC and 90% of Al 6061-10% of SiC. The aluminum 6061 alloy based composite is prepared through stir casting route. Then the composite is heat treated at the critical temperature. After heat treatment, the mechanical properties of composite are compared before extrusion and after heat treatment. Mechanical properties of both heat-treated and as fabricated composites showed a high dependence on the ceramic content. The yield, ultimate tensile strength, and the elastic modulus of the material were increased with volume fraction of carbide, whereas the ductility was decreased. The tensile properties are seen to vary significantly with ageing treatment. The highest strengths were obtained for the solution heat-treated and naturally aged Al-6061: SiC composites containing 20 vol. % SiC.

Keywords

Plastic Deformation, Metal Matrix Composite, Microstructure.

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K. Thangadurai ¹, J. Jerald ¹, P. Satheesh ¹, R. Saravanan ²

Affiliations
1 School of Mechanical Engineering, Shanmugha Arts, Science, Technology & Research Academy, Thanjavur - 613 402, IN
2 Department of Mechanical Engineering, J.J. College of Engineering, Tiruchirappalli-620 009, IN

Abstract

Wire Electric Discharge Machining process is one of the important nontraditional machining process which is used to machine hard materials, complex shapes and contours which are difficult by conventional methods. In this paper Particle Swarm Optimization (PSO) and Memetic Algorithm (MA) based optimization procedures have been developed to optimize machining parameters viz machining speed, pulse on time, pulse off time, and peak current by using two response equations for material removal rate and surface roughness. The objective function considered for optimization is maximization of material removal rate and minimization of surface roughness. Here objective function is solved by taking combined objective function (weightage given 50% to material removal rate and 50% to surface roughness) i.e. minimization of material removal rate and surface roughness. The output results o f these two algorithms are compared.

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K. Thangadurai ¹, N. Nandhini ²

Affiliations
1 Department of Computer Science, Karur Arts and Science College, IN
2 Department of Computer Science, Periyar University, IN

Abstract

Diabetic diagnosis is an important research in health care domain to analyze relevant microorganisms at an earlier stage. Due to large growth in world’s population, feature subset selection model receives a great deal in any domain of research and also a reliable tool for diabetic diagnosis. Several data mining techniques have been developed to evaluate the significant causes of diabetes with least sets of risk factors. These minimum set is selected without considering the potential significance of the risk factors and optimal feature subset selection, hence it failed to diagnosis the pattern of diabetes accurately. In order to improve the feature subset selection, an Integration of Fuzzy Rough Set Theory and Optimized Genetic algorithm (IFRST-OGA) is introduced. The main objective of the IFRST-OGA is to find optimal risk factors for efficient pattern recognition on diabetes healthcare data. Initially, feature selection is performed using Fuzzy Rough Set Theory (FRST) for diagnosing the diabetes. After that, the Optimized Genetic Algorithm (OGA) is applied which mainly searches for an optimal feature subset through the selection, crossover, and mutation operations to diagnose the disease at an earlier stage. This helps to identify the risk factor and diagnosing the diabetes disease efficiently. Experimental results show that the proposed IFRST-OGA increases the performance in terms of true positive rate, computation time and diabetes diagnosing accuracy.

Keywords

Diabetic Diagnosis, Risk Factors Analysis, Rough Set Theory, Feature Selection, Optimized Genetic Algorithm, Selection, Crossover, Mutation, Optimal Feature Subset Selection.

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