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their queries. In this case ,financial as well as human resources are consumed to a greater extent. In order to reduce this problem, there should be an efficient solution. There are some existing technologies which are used by modern enterprise centres. In an enterprise service centre, when the customer places his query, the frequently asked questions are displayed first. If the customer is not satisfied with the solution or if the required content is not available, then the call will be transferred to the enterprise service centre. As the call is placed, the human interaction between the customer and the enterprise service centre will be substantially increased. In this paper, we propose a system which reduces human interaction and provides automation for resolving queries. For this purpose we use the concept of enterprise mobility. Mobility provides exciting opportunities to interact with your customers, partners and suppliers, empower your employees and connect things to your business.

Knowledge management service, semantic web, data mining

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[4] Juan Li, Nazia Zaman, Ammar Rayes, Ernesto Custodio”Semantics- enhanced Online Intellectual Capital Mining Service for Enterprise Customer Centers ”2015
[5] Nidhin Thomas, Atharva Joshi, Rishikesh Misal and Dr Manjula R “Data Mining techniques used in software engineering: A Survey” 2016.
[6] https://www.ics.uci.edu/~eppstein/161/960227.html
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P.H. Wadekar, B.K.Wani, N.N.Joshi, A.W. Jadhav , "Automated Customer Query Resolver Using Data Mining," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.305-307, 2018.

Cloud computing provides resources or services both in terms of hardware and software using network (typically internet). Physical machines thus can perform operations beyond their capabilities. Cloud provides services including IaaS, PaaS and SaaS. Everything user needs is physically close to them hence extensive use of cloud is on the prospect. As users increases so does security threats. Cloud resources could be the target through application of attacks. Several techniques being suggested and research over to avoid critical consequence of threats. This paper provides comprehensive study of techniques used to enhance security within cloud computing environment. Comparative study also list best possible techniques which can work upon in the future.

Cloud, Services, Attacks, Threats

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[22] K. Hwang, X. Bai, Y. Shi, M. Li, W.-G. Chen, and Y. Wu, “Cloud Performance Modeling with Benchmark Evaluation of Elastic Scaling Strategies,” IEEE Trans. Parallel Distrib. Syst., vol. 27, no. 1, pp. 130–143, Jan. 2016.
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Jaya, Kiranbir Kaur, "Cloud Computing Security Techniques for Enhancing Utilization Efficiency," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.308-311, 2018.

As the interest for mobile cloud computing keeps on expanding, cloud specialist organizations confront the overwhelming test to meet the arranged SLA agreements, as far as dependability and convenient .execution, while accomplishing cost and energy efficiency. This paper proposes Shadow Replication, a novel fault-tolerance mechanism for Mobile cloud computing, which flawlessly address fault at scale, while limiting energy utilization and lessening its effect on cost. Energy conservation is achieved by creating dynamic cores rather than static cores. Cores are created by the application of cloudlets. In other words proportionate cores are created. Core failure metrics are considered to be memory capacity, energy and power consumption. In case any of the parameter exceeded threshold value, core is supposed to be faulted and progress is maintained within shadow which is maintained 1 per host. Progress of deteriorated Core is shifted to next core within other VM. In case all the core within VM deteriorated, VM migration is performed. Comparative study of techniques used to establish reliability within MCC is presented for future enhancements in terms of latency, downtime and migration time.

Mobile cloud computing, shadow Replication; fault tolerance; Energy Conservation

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Ramanpreet kaur, Kiranbir kaur, "Mobile Cloud Computing Reliability Enhancement: A Study Of Existing Techniques Including Shadow Cores," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.312-316, 2018.

Cloud Computing is one of the major emerging IT technologies and is highly promising in terms of resources provisioning, unlimited data storage, remote access to applications, easy data backup amenity etc. One of its emerging platforms is AWS S3. It provides storage for the web. It serves developers/users with easy web-scale computing platform. This platform is reliable, scalable, inexpensive and efficient and provides persistent cloud storage. Amazon S3 and amazon.com share common scalable storage root in terms of their infrastructure. The data here is stored in fundamental containers called buckets. A bucket has the capacity to store limitless data. Infinite objects can be stored in a bucket, with each object being able to store a maximum of 5 TB of data. These objects require a unique developer-assigned key to be stored and retrieved by the developers. The data stored this way can be downloaded any instant of time by any user. Permissions to upload or download data to one’s own bucket can be granted or denied. The web service always keeps the data secure from unauthorized access using its invulnerable authentication mechanism. Various operations can be executed through the API such as Read an object, delete an object, list keys etc. Amazon S3 associates REST and SOAP API interfaces.

Cloud Computing, Cloud Storage, Amazon Web Services, Bucket, Folder, File, Hierarchy, Flat File System

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S.Malhotra, V. Bali, "Amazon Backed File System: A Review," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.317-321, 2018.

Since the beginning of time the human brain has been the ultimate source for new information and ideas, that needs to be archived which is lost with time. With the advancements in sciences we are able to conduct this by the technology of Blue Brain to convert real mind data into virtual supercomputer memory. In this paper I discuss on the Blue Brain Project and its strategies, requirements, advantages and limitations. Also, further we discuss its future applications in which the technology can be used after further development of this technology.

Blue Brain, Supercomputer, Artificial Intelligence,Neurocomputing, Blue Brain Project, Blue Gene Supercomputer

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Harsh Ghelani , "The Blue Brain Technology: Study and Application Review," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.322-324, 2018.

Data science is the science of studying scientific data, business data and it’s an integration of Artificial Intelligence, statistics, computing technology. Data science is a field that relates to data cleansing, preparation and analysis. Data science algorithms are used in many industries like Internet searches, Digital Advertisements, Travelling, Healthcare, Gaming, Financial services etc. Data science can solve the problems like classification, identifying anomalies, to quantify, finding way of organization, decision making issues etc. In this paper, we have shown how python is useful and acts as a key to solve such problems. In addition to python, there are also some other platforms which are used to solve a task completely based on data science. Here we have focused on python and it’s packages that are highly useful for data science based problems. We have shown how python can be used for data analysis and data visualization.

Data Science, Python, Data analysis, Data Visualization

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[8]. Nurul Afiqah Mat Zaib , Nor Erne Nazira Bazin , Noorfa Haszlinna Mustaffa , Roselina Sallehuddin, “Integration of System Dynamics with Big Data Using Python: An Overview”, IEEE Conference, 978-1-5090-6255-3/17, May 2017.

Gaurav, Ritu Sindhu, "Python as a key for Data Science," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.325-328, 2018.

In this era of digital security, protection and illegal redistribution of digital media has become a major issue. The digital watermarking has been utilized to shield digital data from illicit redistribution and changes. In digital water denoting the image has been upgraded by installing commotion tolerant flag into transporter flag. Encryption procedures used to encode critical information has been inclined to assaults or attacks. Assist examination in encryption yields image encryption instrument as contrasting option to content encryption. The investigation of different system of digital watermarking as image encryption has been done in this paper to examine techniques which are better and can be used in future for enhancement; likewise the commitment of watermarking methods for security purposes has been broke down. The proposed literature provides comparative studies of techniques used in watermarking along with attributes considered including PSNR and MSE for enhancement.

Digital Security, Watermarking, Encryption, PSNR MSE

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Prabhpreet Kaur, Sonali Kanotra, "A Novel Approach for Security in Digital Image Processing Using Water Marking: Analysis," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.329-335, 2018.

Cloud computing is becoming need of the hour for providing resources at pay per use to users. Data migration is the mechanism of transferring data to cloud where it is stored in virtual environment. It is key consideration behind the active data migration process where users storage is preserved. Up gradation or consolidation is accomplished within cloud using the application of data migration. During migration process, parameters are required to be validated. These parameters involve downtime and migration time. As the migration is finished, organization validates the transfer process statistically. The accuracy of data migration process is also questioned by the organization. in case accuracy is low migration is rejected. Data and pre-processing and cleaning facilities improve data quality via removal of unnecessary or repeated data. This paper presents the distinct data migration techniques within cloud used to transfer Users data to data centers for effectively storing and servicing the user. Techniques presented are compared comprehensively for future enhancements.

Data migration, techniques, downtime, migration time, accuracy

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Kiranbir kaur, Harpreet kumari, "DATA MIGRATION TECHNQIUES WITHIN CLOUD COMPUTING: A COMPREHENSSIVE ANALYSIS," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.336-340, 2018.

Data mining is a process of extraction of useful information and patterns from huge data. It is also called as knowledge discovery process, knowledge mining from data, knowledge extraction or data pattern analysis. We present a improved approach to support nearest neighbor queries from mobile hosts by leveraging the sharing capabilities of wireless ad-hoc networks. We illustrate how previous query results cached in the local storage of neighboring mobile peers can be leveraged to either fully or partially compute and verify spatial queries at a local host. The feasibility and appeal of our technique is illustrated through extensive simulation results that indicate a considerable reduction of the query load on the remote database.

Mobile Services, CART, C45, EDTA

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Amarjeet Kaur, Ashok Jetawat2, Gurpreet Singh, "Implementation and Analysis of the Performance of EDTA (Enhanced Decision Tree Data Mining Algorithm) for diagnosis of Angioplasty and Stents for Heart Disease Treatment," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.541-543, 2018.

Networked data contain interconnected entities for which inferences are to be made. For example, web pages are interconnected by hyperlinks, research papers are associated by references, phone accounts are linked by calls, conceivable terrorists are linked by communications. Networks have turned out to be ubiquitous. Correspondence networks, financial transaction networks, networks portraying physical systems, and social networks are all ending up noticeably progressively important in our everyday life. Regularly, we are interested in models of how nodes in the system influence each other (for example, who taints whom in an epidemiological system), models for predicting an attribute of intrigue in light of observed attributes of objects in the system. The technique of SVM is applied which will classify the data into malicious and non-malicious. To increase the accuracy of classification technique Knn classier is applied which increase accuracy, execution time.

Data network, attacks, data mining,, IDS/IPS machine learning

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Renu Dewli, Anubhooti Papola, "Intruder Attack Detection In Data Network Organization Using Data Mining Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.4, pp.544-549, 2018.