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Search Results: 1 - 10 of 7949 matches for " Dr. Kanak Saxena "
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Fast and secure data transmission using symmetric encryption and lossless compression
Mohini Chaudhari,Dr. Kanak Saxena
International Journal of Computer Science and Mobile Computing , 2013,
Abstract: With the fast progression of data exchange in electronic way, information security is becoming more important in data storage and transmission. While storing and transmitting multimedia data are noteasy and they need large storage devices and high bandwidth network systems. Compression and encryption technologies are important to the efficient solving of network bandwidth and security issues. This paper focus on dual approach of compression and security where compression is achieved through lossless algorithm (either Huffman coding or LZW) according to size and type of image data and compressed data is encrypted using traditional DES Algorithm.
A Study of Various Pattern Mining Techniques for Selected Domains
Dr. Kanak Saxena,D.S Rajpoot
International Journal on Computer Science and Engineering , 2009,
Abstract: In classification/clustering we analyze a set of data and generate a set of grouping rules which can be used to classify future data. For example, one may classify diseases and provide the symptoms which describe each class or subclass. This has much in common with traditional work in statistics and machine learning. However, there are important new issues which arise because of the sheer size of the data.
A Way to Understand Various Patterns of Data Mining Techniques for Selected Domains
Dr. Kanak Saxena,D.S Rajpoot
International Journal of Computer Science and Information Security , 2009,
Abstract: This has much in common with traditional work in statistics and machine learning. However, there are important new issues which arise because of the sheer size of the data. One of the important problem in data mining is the Classification-rule learning which involves finding rules that partition given data into predefined classes. In the data mining domain where millions of records and a large number of attributes are involved, the execution time of existing algorithms can become prohibitive, particularly in interactive applications.
Improve Intrusion Detection for Decision Tree with Stratified Sampling
Devendra kailashiya Kanak Saxena
International Journal of Electronics Communication and Computer Engineering , 2011,
Abstract: The present paper aims to improve accuracy of intrusion detection for decision tree algorithm. A number of techniques available for intrusion detection. In this paper we have supervised learning with preprocessing step for intrusion detection. The database is generated i using the stratified sampling techniques and the classification algorithm is applied on the samples. The accuracy of proposed model is compared with existing results in order to verify the validity and accuracy of the proposed model.
A Software Architecture Style for Medical Process Re-engineering
Umesh Banodha,Kanak Saxena
Lecture Notes in Engineering and Computer Science , 2011,
Abstract:
Achieving Open-loop Insulin Delivery using ITM Designed for T1DM Patients
Akash Rajak,Kanak Saxena
International Journal of Computer Network and Information Security , 2012,
Abstract: To simulate the glucose-insulin concentration of type 1 diabetic patient an Intelligent Temporal Mediator (ITM) has been designed. The ITM integrates the tasks of temporal reasoning and temporal maintenance. The paper discusses the design of ITM reasoning system which was based on open-loop insulin delivery technique. The result shows that ITM successfully models the blood glucose profile of the diabetic patient. The designed ITM is also compared with existing open-loop simulator for checking its performance.
Significant Interval and Frequent Pattern Discovery in Web Log Data
Kanak Saxena,Rahul Shukla
International Journal of Computer Science Issues , 2010,
Abstract: There is a considerable body of work on sequence mining of Web Log Data We are using One Pass frequent Episode discovery (or FED) algorithm, takes a different approach than the traditional apriori class of pattern detection algorithms. In this approach significant intervals for each Website are computed first (independently) and these interval used for detecting frequent patterns/Episode and then the Analysis is performed on Significant Intervals and frequent patterns That can be used to forecast the user's behavior using previous trends and this can be also used for advertising purpose. This type of applications predicts the Website interest. In this approach, time-series data are folded over a periodicity (day, week, etc.) Which are used to form the Interval? Significant intervals are discovered from these time points that satisfy the criteria of minimum confidence and maximum interval length specified by the user.
Analysis of Data Mining Techniques on Real Estate
Geetali Banerji,Kanak Saxena
International Journal of Soft Computing & Engineering , 2012,
Abstract: Data mining techniques are broadly classified into two classes (i) Statistical Techniques and (ii) Knowledge Discovery. The continuing rapid growth of on-line data and the widespread use of databases necessitate the development of techniques for extracting useful knowledge and for facilitating database access. This paper analyzes the results of multilayer perceptron with pace regression and suggests a very efficient pattern which can be proved beneficial for knowledge discovery. The analysis is done using real estate data set which contains 5821 tuples and 43 attributes and determines that in India’s scenario the demographic details of a person plays a very prominent role in identifying the investment behavior of a customer. In multilayer perceptron model, input layer is followed by two hidden layers. The first hidden layer contains 21 nodes as per various attribute weight age followed by second hidden layer which assigns re-processed weights to each of the 21 nodes. If we are discarding the demographic details then the model which is available consists of 13 Sigmoid nodes and there is a major change in error rate and correlation. We have used WEKA for analysis and found that in general multilayer perceptron(selected) is more efficient then pace regression(complete) in terms of statistical methods, but in Indian perception pace regression(complete) is more efficient than multilayer(selected).
Significant Interval and Frequent Pattern Discovery in Web Log Data
Kanak Saxena,Rahul Shukla
Computer Science , 2010,
Abstract: There is a considerable body of work on sequence mining of Web Log Data. We are using One Pass frequent Episode discovery (or FED) algorithm, takes a different approach than the traditional apriori class of pattern detection algorithms. In this approach significant intervals for each Website are computed first (independently) and these interval used for detecting frequent patterns/Episode and then the Analysis is performed on Significant Intervals and frequent patterns That can be used to forecast the user's behavior using previous trends and this can be also used for advertising purpose. This type of applications predicts the Website interest. In this approach, time-series data are folded over a periodicity (day, week, etc.) Which are used to form the Interval? Significant intervals are discovered from these time points that satisfy the criteria of minimum confidence and maximum interval length specified by the user.
Load Balancing in IP/MPLS Networks: A Survey  [PDF]
Ravindra Kumar Singh, Narendra S. Chaudhari, Kanak Saxena
Communications and Network (CN) , 2012, DOI: 10.4236/cn.2012.42020
Abstract: The present era has witnessed tremendous growth of the Internet and various applications that are supported by it. There is an enormous pressure on Internet Service Providers (ISPs) to make available adequate services for the traffics like VoIP and Video on demand. Since the resources like computing power, bandwidth etc. are limited, the traffic needs to be engineered to properly exploit them. Due to these limitations, terms like Traffic Engineering, Quality of Service (QoS) came into existence. Traffic Engineering broadly includes techniques like multipath routing & traffic splitting to balance the load among different paths. In this document, we survey various techniques proposed for load balancing that are available on the Internet. We here try not to be exhaustive but analyze the important techniques in the literature. Present survey would help to give a new direction to the research in this realm.
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