International Journal of Advanced Studies in Computer Science and Engineering (IJASCSE)

                                                                                                                                                                                                   ISSN : 2278 7917 

Call For Papers

January 2019

  Submission         January 10

  Acceptance         January 20

  Publication          January 30

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International Journal of advanced studies in Computer Science and Engineering (IJASCSE) is here to provide a timely and broad coverage of research in ever-challenging field of Computer Science and Computer Science Engineering. IJASCSE is an interdisciplinary, peer reviewed, fully refereed, monthly, Open Access journal for research scholars with a mix of regular and theme based issues to share their new and advanced research in Computer Science and Engineering. 


The papers published at IJASCSE are currently Abstracted & Indexed by some world famous databases.

 Call For Papers

December  2018

     Submission            December 10

      Notification            December 20

      Publication            December 31

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Open Access Database


IJASCSE is an online peer reviewed quality publication, which publishes research papers from diverse fields in computers, sciences, engineering and technologies that emphasizes new research, development and their applications. It provides an open access database for all who are interested to exchange their research work, technical notes & surveying results among professionals through out the world.

 

 IJASCSE volume 7 issue 03 (Theme: Software Engineering & Information Security)                            

 

A Modified Image Comparison Algorithm Using Histogram Features
Anas M. Al-Oraiqat, Natalya S. Kostyukova


Abstract-This article discuss the problem of color image content comparison. Particularly, methods of image content comparison are analyzed, restrictions of color histogram are described and a modified method of images content comparison is proposed. This method uses the color histograms and considers color locations. Testing and analyzing of based and modified algorithms are performed.


A Survey on Reducing the Semantic Gap in Content Based Image Retrieval System
N Sathya, S Rathi

 

Abstract-In this article a review is made on how the pertinence criticism techniques will lessen the semantic gap. This work additionally concentrates on how the CBIR framework functions, how to separate the features by utilizing the best descriptors and enhance the image search process. To be specific, many machine learning procedures like semisupervised learning and active learning techniques that are used in CBIR are discussed.

 

An Efficient Pre-Processor by Multiple Fragmentations in Text Messages and Images for Steganography
Sanjay Bajpai


Abstract-This paper designs a pre-processor that can be applied on the text message prior to embedding in digital colored images. It encompasses two phases: first phase deals with designing the robust process to encode the text message using multiple fragments, and second phase deals with embedding the text of multiple fragments into the image. Prior to embedding, image is partitioned into number of blocks and size of each block is decided by a pseudo random number generator.

Data Security and Data Privacy in Cloud Computing Environment using Data Obfuscation Technique
Ramalingam Sugumar, K Raja

 

Abstract — This paper proposes an obfuscation technique to make stronger a numerical data in cloud data storage. This obfuscation technique is used to encrypt and decrypt the data. Microsoft Windows azure as the implementation tool for this proposed algorithm. In this paper proposes a confidentiality system to enhance the security of data in cloud computing environment.

 

KQML - From Scenario to Technology
Amandeep Kaur, Shaveta Jain

 

Abstract- This research work is concerned with communication between software agents using KQML that allow agents to communicate and find other agents suitable to process their requests. In particular, the semantics of KQML is investigated. We present a semantic description of KQML that associates states of the agent with the use of the language's primitives. We have used this approach to describe the semantics for the whole set of reserved KQML primitives.

 

SCRUTINZING AUTOMATED LOAD TESTING VIA BLAZMETER, APACHE JMETER AND HP LOADRUNNER
Pirah Memon, Sania Bhatti, Amirita Dewani, Tahseen Hafiz


Abstract: In this paper we have analyzed the performance of BlazeMeter, Apache JMeter, and HP loadrunner. The automated load testing tools use script for testing the applications, data services and apps. In this work, the performance evaluation of three load testing tools is achieved based on response time, number of samples, aggregate reports, latency, number of hits and throughput. The graphical representation of results perceptibly depicts the efficiency of BlazeMeter tool compared to Apache JMeter and HP loadrunner.

Keywords- image comparison, color histogram, color location, image database, color image retrieval.






Keywords — Content Based Image Retrieval; Semantic gap; Relevance Feedback; Collaborative Image Retrieval









Keywords- Distortion, Embedding capacity, Extraction, Permutation, Segmentation










Keywords- Cloud Computing, Cloud Storage, Security, obfuscation.








Keywords— MAS; KQML; Contract Net Interaction Protcol






Keywords-Load Testing, BlazeMeter, Apache
JMeter, HP loadrunner.





image comparison algorithm using histogram.pdf
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semantic gap.pdf
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embedding capacity.pdf
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data obfuscation technique.pdf
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kqml.pdf
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blazmeter.pdf
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