Jayamukhi Institute of Technological science

Warangal, India

Jayamukhi Institute of Technological science

Warangal, India

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Reddy V.V.,Jayamukhi Institute of Technological science | Valli P.M.,A.I.T.S | Kumar A.,National Institute of Technology Warangal | Reddy C.S.,Jawaharlal Nehru Technological University Anantapur
Journal of Advanced Manufacturing Systems | Year: 2015

In the present work, an investigation has been made into the electrical discharge machining process during machining of precipitation hardening stainless steel PH17-4. Taguchi method is used to formulate the experimental layout, to analyze the effect of each process parameter on machining characteristics and to predict the optimal choice for each electrical discharge machining process parameters namely, peak current, pulse on time and pulse off time that give up optimal process performance characteristics such as material removal rate, surface roughness, tool wear rate and surface hardness. To identify the significance of parameters on measured response, the analysis of variance has been done. It is found that parameters peak current and pulse on time have the significant affect on material removal rate, surface roughness, tool wear rate and surface hardness. However, parameter pulse off time has significant affect on material removal rate. Confirmation tests are conducted at their respective optimum parametric settings to verify the predicted optimal values of performance characteristics. © 2015 World Scientific Publishing Company.


Reddy V.V.,Jayamukhi Institute of Technological science | Valli P.M.,Gandhi Institute of Technology and Management | Kumar A.,National Institute of Technology Warangal | Reddy C.S.,Jawaharlal Nehru Technological University Anantapur
Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture | Year: 2015

Electrical discharge machining is commonly used in manufacturing industry to make dies of complex cavities. This work investigates electric discharge machining of PH17-4 stainless steel when both graphite powder-mixed and surfactant-mixed dielectric fluid were used during electrical discharge machining. Taguchi method is used for conducting experiments with L9 orthogonal array by choosing electrical discharge machining process parameters, namely, peak current, surfactant concentration and graphite powder concentration. The process performance characteristics of electrical discharge machining such as material removal rate, surface roughness and tool wear rate are chosen for this study. The purpose of this work is to find significance of process parameters on performance characteristics and also get an optimal combination of these parameters using Taguchi-data envelopment analysis-based ranking multi-response optimization method. © IMechE 2014.


Bhaskar A.,Kakatiya Institute of Technology and Science | Gyani J.,Jayamukhi Institute of Technological science | Narsimha G.,JNTUH College of Engineering
IEEE TENSYMP 2014 - 2014 IEEE Region 10 Symposium | Year: 2014

Video classification is an emerging research area. Advertisement videos play a major role in improving targeted sales of a product. The popularity of the advertisement depends on the number of viewers attracted to that advertisement video in a short span of time. Popular advertisements have more impact on the sales of the product. In this paper, we propose a new measure called Video Differential Index(VDI) to analyze and classify advertisement videos to know whether that video attracts more number of viewers or not. By using VDI measure we can also predict the type of video i.e., action-oriented, theme or concept based without watching the content of the video. Our experimental results demonstrated that, action oriented videos have high Video Differential Index as compared to theme or concept based videos. The VDI can be directly related to the popularity of the video. © 2014 IEEE.


Reddy V.V.,Jayamukhi Institute of Technological science | Kumar A.,National Institute of Technology Warangal | Valli P.M.,GITAM Institute of Technology | Reddy C.S.,Jawaharlal Nehru Technological University Anantapur
Journal of the Brazilian Society of Mechanical Sciences and Engineering | Year: 2015

In the present work, an investigation has been made into the electrical discharge machining process (EDM) when both graphite powder and surfactant-mixed dielectric fluid were used during EDM of precipitation hardening stainless steel PH17-4. The addition of graphite powder in the dielectric fluid results in uniform distribution of discharge, which improves surface finish. However, agglomeration of graphite particles is found in the dielectric due to the electrostatic forces among the graphite powder particles. The addition of surfactant in the dielectric increases dielectric conductivity and in turn reduces relay time of discharge. This increases actual discharge time, which results in more material removal. At the same time, uniform distribution of graphite powder particles in the dielectric fluid is achieved. This leads to increase in discharge frequency, which results in increase in material removal rate and surface finish. Taguchi parameter design approach was used to get an optimal parametric setting of EDM process parameters namely: peak current, surfactant concentration and graphite powder concentration that yields to optimal process performance characteristics such as material removal rate, surface roughness, white layer thickness and surface crack density. Individual effect of process parameters on performance characteristics was also studied. To identify the significance of parameters on measured response, the analysis of variance has been carried out. Further, mathematical models were developed by performing nonlinear regression analysis to predict process performance characteristics. Confirmation tests were conducted at their respective optimal parametric settings to verify the predicted optimal values of performance characteristics. © 2014, The Brazilian Society of Mechanical Sciences and Engineering.


Kumar G.M.,Bhavans Vivekananda College | Ramachandram S.,Osmania University | Gyani J.,Jayamukhi Institute of Technological science
Souvenir of the 2015 IEEE International Advance Computing Conference, IACC 2015 | Year: 2015

Grid Computing pools the resources from various heterogeneous computers to solve a particular problem which requires huge computation. In a grid, a number of known and unknown entities from same or different domain participate in communication where in every entity need to undergo a strong authentication and authorization scheme. There is risk while making the communication among untrusted entities since there is a chance of misusing resources. So, in-order to avoid this problem a strong trust establishment phenomenon is required. This paper demonstrates a randomized algorithm for developing a trust model which makes the user and service provider to maintain consistency among their ratings from each other every time, so that they reach the eligible criteria for communication. © 2015 IEEE.


Bhukya R.,Kakatiya Institute of Technology and science | Gyani J.,Jayamukhi Institute of Technological science
2014 International Conference for Convergence of Technology, I2CT 2014 | Year: 2014

Distributed Data Mining (DDM) which is a process of extracting knowledge from distributed data without integrating them in a common database. Due to its vast application in real world application distributed data mining has been a most familiar research interest. As the associative classification technique proved to be most efficient classifier compare to other classifiers we can found certain proposals in literature which can perform associative classification over distributed databases. Even after incremental data mining proved to be most optimized way to upgrade mined rules when new set of transaction added to database, there are lack of proposals which can perform incremental mining over distributed databases. Considering these issues the article presents incremental associative classification model over horizontally distributed databases. Experimental conducted using synthesized datasets has shown encouraging results. © 2014 IEEE.


Sudhakar N.,Jayamukhi Institute of Technological science | Gyani J.,Jayamukhi Institute of Technological science
ICWET 2010 - International Conference and Workshop on Emerging Trends in Technology 2010, Conference Proceedings | Year: 2010

Refactoring using design patterns leads to production of high quality and easily maintainable software. Without an acceptable level of design patterns in the development of software, it will not be able to meet the demands of software industry. Promoting design patterns requires effective support. In this paper we propose a tool to extract few creational design patterns by detecting Intent Aspects(IA's) from Java source code by applying reverse engineering algorithms. This helps in refactoring the code and thus improves the quality of software, in terms of reusability, flexibility and extendibility. Copyright 2010 ACM.


Bhukya R.,Kakatiya Institute of Technology and Science | Gyani J.,Jayamukhi Institute of Technological science
Proceedings of the 2015 International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2015 | Year: 2015

The Hadoop distributed file system offers efficient Mapreduce frame work using which the big datasets can be processed with efficient time complexity. Capability to load on low-cost commodity hardware and greater extent of fault tolerance leading many business organizations to store data in Hadoop distributed file system. Considering the real-time importance of distributed file system in recent literature conventional data mining algorithms getting extended to scale in MapReduce architecture. In line to this trend we propose a fuzzy associative classification algorithm based on MapReduce framework to extract intuitive classification rules from data stored in distributed file systems. The experimental investigation shows that the proposed algorithm on MapReduce frame work can scale to effectively extract intuitive classification rules from training data stored in distributed file systems. © 2015 IEEE.


Aluvala S.,Jayamukhi Institute of Technological science | Rao P.S.,Jayamukhi Institute of Technological science
ICECT 2011 - 2011 3rd International Conference on Electronics Computer Technology | Year: 2011

IP spoofing is almost always used in what is currently one of the most difficult attacks to defend against-denial of service attacks, or DoS. Since crackers are concerned only with consuming bandwidth and resources, they need not worry about properly completing handshakes and transactions. Rather, they wish to flood the victim with as many packets as possible in a short amount of time. In order to prolong the effectiveness of the attack, they spoof source IP addresses to make tracing and stopping the DoS as difficult as possible. When multiple compromised hosts are participating in the attack, all sending spoofed traffic; it is very challenging to quickly block traffic. While some of the attacks described above are a bit outdated, Such as session hijacking for host-based authentication services, IP spoofing is still prevalent in network scanning and probes, as well as denial of service floods. However, the technique does not allow for anonymous Internet access, which is a common misconception for those unfamiliar with the practice. Any sort of spoofing beyond simple floods is relatively advanced and used in very specific instances such as evasion and connection hijacking. © 2011 IEEE.


Shazmeen S.F.,Jayamukhi Institute of Technological science | Gyani J.,Jayamukhi Institute of Technological science
ICECT 2011 - 2011 3rd International Conference on Electronics Computer Technology | Year: 2011

Emails have been considered as a useful resource for research in fields like link analysis, social network analysis and textual analysis, Email mining is a process of discovering useful patterns from emails. Clustering techniques can be applied over email data to create groups of similar emails. An email can be represented as an Object consisting of several attributes like sender email-id, receiver email-id Subject, message, sending-time, and attachments etc. clustering is used to discover email groups. Generally the most of the attributes in emails are text type, so text similarity techniques are used for measuring the similarity between pair of email objects. Clustering the emails and the user depend on the information they have exchanged and graphically representing Cluster. The Enron email dataset is a touchstone for such research. © 2011 IEEE.

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