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JournalISSN: 2319-8656

International Journal of Computer Applications Technology and Research 

Association of Technology and Science
About: International Journal of Computer Applications Technology and Research is an academic journal published by Association of Technology and Science. The journal publishes majorly in the area(s): Computer science & Cloud computing. It has an ISSN identifier of 2319-8656. Over the lifetime, 585 publications have been published receiving 1305 citations.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: There is a need to make practitioners aware of feature selection methods that have been successfully applied in medical data sets and highlight future trends in this area to develop a universal method that achieves the best classification accuracy with fewer features.
Abstract: In recent years, application of feature selection methods in medical datasets has greatly increased. The challenging task in feature selection is how to obtain an optimal subset of relevant and non redundant features which will give an optimal solution without increasing the complexity of the modeling task. Thus, there is a need to make practitioners aware of feature selection methods that have been successfully applied in medical data sets and highlight future trends in this area. The findings indicate that most existing feature selection methods depend on univariate ranking that does not take into account interactions between variables, overlook stability of the selection algorithms and the methods that produce good accuracy employ more number of features. However, developing a universal method that achieves the best classification accuracy with fewer features is still an open research area.

47 citations

Journal ArticleDOI
TL;DR: In this paper, Machine learning based methods which are one of the types of anomaly detection techniques is discussed. But the authors do not discuss the use of machine learning for anomaly detection.
Abstract: Intrusion detection is so much popular since the last two decades where intrusion is attempted to break into or misuse the system. It is mainly of two types based on the intrusions, first is Misuse or signature based detection and the other is Anomaly detection. In this paper Machine learning based methods which are one of the types of Anomaly detection techniques is discussed.

43 citations

Journal ArticleDOI
TL;DR: Different techniques of digital image watermarking based on spatial & frequency domain are presented, which shows that spatial domain technique provides security & successful recovery of watermark image and higher PSNR value compared to frequency domain.
Abstract: Digital watermarking is the processing of combined information into a digital signal. A watermark is a secondary image, which is overlaid on the host image, and provides a means of protecting the image. In order to provide high quality watermarked image, the watermarked image should be imperceptible. This paper presents different techniques of digital image watermarking based on spatial & frequency domain, which shows that spatial domain technique provides security & successful recovery of watermark image and higher PSNR value compared to frequency domain.

34 citations

Journal ArticleDOI
TL;DR: This paper includes the detail study of water marking definition and various watermarking applications and techniques used to enhance data security.
Abstract: The frequent availability of digital data such as audio, images and videos became possible to the public through the expansion of the internet. Digital watermarking technology is being adopted to ensure and facilitate data authentication, security and copyright protection of digital media. It is considered as the most important technology in today's world, to prevent illegal copying of data. Digital watermarking can be applied to audio, video, text or images. This paper includes the detail study of watermarking definition and various watermarking applications and techniques used to enhance data security.

23 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202391
202266
20211
20205
201918
201838