Volume-11 ~ Issue-6
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Abstract: This paper presents a fault prediction model using reliability relevant software metrics and fuzzy inference system. For this a new approach is discussed to develop fuzzy profile of software metrics which are more relevant for software fault prediction. The proposed model predicts the fault density at the end of each phase of software development using relevant software metrics. On the basis of fault density at the end of testing phase, total number of faults in the software is predicted. The model seems to useful for both software engineer as well as project manager to optimally allocate resources and achieve more reliable software within the time and cost constraints. To validate the prediction accuracy, the model results are validated using PROMISE Software Engineering Repository Data set.
Keywords: Reliability Relevant Software Metrics, Software Fault Prediction, Fault Density, Fuzzy profile, Fuzzy Inference System (FIS)
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Abstract: Data Compression is the technique through which, we can reduce the quantity of data, used to represent content without excessively reducing the quality of the content. This paper examines the performance of a set of lossless data compression algorithm, on different form of text data. A set of selected algorithms are implemented to evaluate the performance in compressing text data. A set of defined text file are used as test bed. The performance of different algorithms are measured on the basis of different parameter and tabulated in this article. The article is concluded by a comparison of these algorithms from different aspects.
Keywords - Encryption, Entropy Encoding, Dictionary Encoding, Compression Ratio, Compression time, Test Bed.
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| Paper Type | : | Research Paper |
| Title | : | Hiding Image within Video Clip |
| Country | : | Iraq |
| Authors | : | Nada Elya Tawfiq |
| : | 10.9790/0661-1162026 ![]() |
|
Abstract: Due to the huge development of computer science which was escorted by another vast development in the hiding techniques, which became of great possibilitiesin which it is difficult to break those techniques.Those techniques were classified depending on the method of embedding like inserting, replacing or exchange positions.
[1]. Refrence: book: ―DATA HIDING FUNDAMENTALS AND APPLICATRIONS‖ AUG-2004,HusrwSencar,
[2]. chin-Chen Chang, ― International Journal of Pattern Recognition and Artifitial Intelligence‖, Volume 16, Issue 04, June 2002.
[3]. ab Grady Booch,‖ Object-Oriented Analysis and Design with Applications‖, . Addison-Wesley, 2007, ISBN 0-201-89551-X, p. 51-52.
[4]. http://en,Wikipedia.org/wiki/Information_hiding.
[5]. Pahati, OJ (2001-11-29). "Confounding Carnivore: How to Protect Your Online Privacy". AlterNet.Archived from the original on 2007-07-16.http://web.archive.org/web/20070716093719/http://www.alternet.org/story/11986/. Retrieved 2008-09-02.
[6]. Chvarkova, Iryna; Tsikhanenka, Siarhei; Sadau, Vasili (15 February 2008). "Steganographic Data Embedding Security Schemes Classification".Steganography: Digital Data Embedding Techniques. Intelligent Systems Scientific Community, Belarus.http://scientist.by/index.php?option=com_content&view=article&id=37%3Asteganography-digital-data-embedding-techniques&catid=9&Itemid=27&limitstart=5. Retrieved 25 March 2011.
[7]. Joshua R. Smith and Barrett O. Comisky, ―Modulation and Information Hiding in Images‖, Cambridge, USA May 2009.
