INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY Interested in submitting to this journal? We recommend that you review the About the Journal page for the journal's section policies, as well as the Author Guidelines. Authors need to register with the journal prior to submitting or, if already registered, can simply log in and begin the five-step process. P journals en-US INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2277-3061 <p>Authors retain the copyright of their manuscripts, and all Open Access articles are distributed under the terms of the&nbsp;<a href="">Creative Commons Attribution License</a>, which permits unrestricted use, distribution, and reproduction in any medium, provided that the original work is properly cited.</p> <p>&nbsp;</p> In-Silico Methodologies for Cancer Multidrug Optimization <p>Drug combinations is considered as an effective strategy designed to control complex diseases like cancer. Combinations of drugs can effectively decrease side effects and enhance adaptive resistance. Therefore, increasing the likelihood of defeating complex diseases in a synergistic way. This is due to overcoming factors such as off-target activities, network robustness, bypass mechanisms, cross-talk across compensatory escape pathways and the mutational heterogeneity which results in alterations within multiple molecular pathways. The plurality of effective drug combinations used in clinic were found out through experience. The molecular mechanisms underlying these drug combinations are often not clear, which makes it not easy to suggest new drug combinations. Computational approaches are proposed to reduce the search space for defining the most promising combinations and prioritizing their experimental evaluation. In this paper, we review methods, techniques and hypotheses developed for in silico methodologies for drug combination discovery in cancer, and discuss the limitations and challenges of these methods.</p> Doaa Mohamed Hasan Ahmed Sharaf Eldin Ayman Elsayed Khedr Hanan Fahmy ##submission.copyrightStatement## 2018-06-22 2018-06-22 17 2 7186 7205 10.24297/ijct.v17i2.7168 Data Security In Cloud Computing: A Review <p>Cloud computing is Internet ("cloud") based development and use of computer technology ("computing"). It is a style of computing in which dynamically scalable and often virtualized resources are provided as a service over the Internet. Cloud computing uses the internet and the central remote servers to support different data and applications. It is an internet based technology. It permits the users to approach their personal files at any computer with internet access. The cloud computing flexibility is a function of the allocation of resources on authority’s request. Cloud computing provides the act of uniting. Scientific computing in the 21st century has evolved from fixed to distributed work environment. The current trend of CloudComputing (CC) allows accessing business applications from anywhere just by connecting to the Internet. Evidence shows that, switching to CC organizations' annual expenditure and maintenance are being reduced to a greater extent. However, there are several challenges that come along with various benefits of cloud computing. Among these include securityaspects. Our aim is to identify security challenges for adapting cloud computing and their solutions from real world for the challenge that do not have any proper mitigation strategies identified. This non-existence of global standards and guidelines could be help academics to know the state of practice and formulatebetter methods/standards to provide secure interoperability. The identified cloud computing security challenges and solutions can be referred by practitioners to understand which areas of security need to be concentrated while adapting/migrating to a cloud computing environment.</p> Gurjeet Singh Dr. Mohita Garg ##submission.copyrightStatement## 2018-07-06 2018-07-06 17 2 7206 7214 10.24297/ijct.v17i2.7551 KNN AND STEERABLE PYRAMID BASED ENHANCED CONTENT BASED IMAGE RETRIEVAL MECHANISM <p>Recently, digital content has become a significant and inevitable asset of or any enterprise and the need for visual content management is on the rise as well. There has been an increase in attention towards the automated management and retrieval of digital images owing to the drastic development in the number and size of image databases. A significant and increasingly popular approach that aids in the retrieval of image data from a huge collection is called Content-based image retrieval (CBIR). Content-based image retrieval has attracted voluminous research in the last decade paving way for development of numerous techniques and systems besides creating interest on fields that support these systems. CBIR indexes the images based on the features obtained from visual content so as to facilitate speedy retrieval. Content based image retrieval from large resources has become an area of wide interest nowadays in many applications. In this thesis work, we present a steerable pyramid based image retrieval system that uses color, contours and texture as visual features to describe the content of an image region. To speed up retrieval and similarity computation, the database images are classified and the extracted regions are clustered according to their feature vectors using KNN algorithm We have used steerable pyramid to extract texture features from query image and classified database images and store them in feature features. Therefore to answer a query our system does not need to search the entire database images; instead just a number of candidate images are required to be searched for image similarity.&nbsp; Our proposed system has the advantage of increasing the retrieval accuracy and decreasing the retrieval time.</p> Bohar Singh Mrs. Mehak Aggarwal ##submission.copyrightStatement## 2018-07-06 2018-07-06 17 2 7215 7225 10.24297/ijct.v17i2.7606 A REVIEW ON CONTENT BASED IMAGE RETRIEVAL <p>In current years, very huge collections of images and videos have grown swiftly. In parallel with this boom, content-based image retrieval and querying the indexed collections of images from the large database are required to access visible facts and visual information. Three of the principle additives of the visual images are texture, shape and color. Content based image retrieval from big sources has a wide scope in many application areas and software’s.&nbsp; To accelerate retrieval and similarity computation, the database images are analyzed and the extracted regions are clustered or grouped together with their characteristic feature vectors. As a result of latest improvements in digital storage technology, it's easy and possible to create and store the large quantity of images inside the image database.&nbsp; These collections may additionally comprise thousands and thousands of images and terabytes of visual information like their shape, texture and color.&nbsp; For users to make the most from those image databases, efficient techniques and mechanisms of searching should be devised. Having a computer to do the indexing primarily based on a CBIR scheme attempts to deal with the shortcomings of human-based indexing.&nbsp; Since anautomated process on a computer can analyze and process the images at a very quick and efficient rate that human can never do alone. In this paper, we will discuss the structure of CBIR with their feature vectors.</p> Bohar Singh Mrs.Mehak Aggarwal ##submission.copyrightStatement## 2018-07-06 2018-07-06 17 2 7225 7235 10.24297/ijct.v17i2.7607