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It is very important to find initial solution of transportation problems to reach optimal solution. In this paper Maximum Difference Method (MDM) is improved to get best initial solution of transportation problems. Our improved method overcomes the limitations of MDM given by Smita Sood and keerti Jain. This modified approach most of times give better solution than MDM specially in case of tie and very close to the optimal solution. Also sometimes gives optimal solution.

Transportation Problem, Optimal Solution, Initial Basic Feasible Solution, MDM

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Lakhveer kaur, Madhuchanda Rakshit, Sandeep Singh, "An Improvement in Maximum Difference Method to Find Initial Basic Feasible Solution for Transportation Problem," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.533-535, 2018.

Cloud computing is rapidly becoming an innovative and easy model for delivering the IT services along with dynamic infrastructure. Cloud computing uses Internet as communication media. It also transforming new idea to have centralized application and database servers. Water is a most essential resources and precious gift by nature on earth. It required in all fields viz. Industries, Agriculture, Irrigation, Domestic use, Plantation, Recreation, Wildlife etc. Water is in limited resource and required proper management. The advancement of Information and Communication Technology has significantly adopted for management of water resources. In this literature survey, we studied the work carried-out by the various researchers about the uses of cloud technology for water resource management.

Cloud Computing,Water Management, Software, Internet, ICT Infrastructures

[1] Z.Y. Wu, M.Khaliefa,“Cloud Computing for High Performance Optimization of Water Distribution Systems”, In the Proceedings of the Congress on World Environment and Water Resources Congress 2012: Crossing Boundaries, ASCE 2012. pp 679-686.
[2] A. T. Velte, T. J. Velte, R. Elsenpeter, “Cloud Computing: A Practical Approach”, McGraw-Hill Companies, Milan New Delhi San Juan, 29-31, 2010, ISBN: 978-0-07-162695-8.
[3] R. V. Dharmadhikari, S. S. Turambekar, S. C. Dolli, P K Akulwar, “Cloud Computing: Data Storage Protocols and Security Techniques”,International Journal of Computer Sciences and Engineering,Vol.6, Issue.2, pp.113-118, April 2018.
[4] M.Patidar, P. Bansal,“Cloud Forensics: An Overall Research Perspective”, International Journal of Scientific Research in Network Security and Communication (ISSN: 2321-3256),Vol-6, Issue.2, April 2018.
[5] S. Patidar,D. Rane, P. Jain,”A Survey Paper on Cloud Computing”,Second International Conference on Advanced Computing & Communication Technologies, 2012.
[6] S. Wadekar,V. Vakare,R. Prajapati,S. Yadav,V. Yadav,“Smart Water Management Using IOT”,2016.
[7] H. Afzaal,N.A. Zafar,”Cloud Computing Based Flood Detection and Management System using WSANs”,2016.
[8] M.Arangoa, J.S. Izquierdo, E.O.G. Campbell, R. Perez-Garcíab,“Cloud-Based Decision Making in Water Distribution Systems”, 16th Conference on Water Distribution System Analysis, WDSA, 2014.
[9] P. Alencar, D. Cowan, F. McGarry, R.M. Palmer,“Developing a Collaborative Cloud-Based Platform for Watershed Analysis and Management”, 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing, 2014.
[10] M. Xiaocong, Q.X. Jiao, S. Shaohong, “An IoT-based system for water resources monitoring and management”,7th International Conference on Intelligent Human-Machine Systems and Cybernetics, 2015.
[11] Andreja Jonoski,Blagoj Delipetrev,Dimitri P. Solomatine,“Development Of A Cloud Computing Application For Water Resources Modelling And Optimization Based On Open Source Software”,International Conference on Hydroinformatics,8-1-2014.
[12] George Suciu,“Unified Intelligent Water Management using Cyberinfrastructures based on Cloud Computing and IoT”,21stInternational Conference on Control Systems and Computer Science,2017.

Snehal V Chaskar, P.S. Solanki, P.R. Khatarkar, "Cloud Computing Technology for Efficient Water Resource Management: a Literature Survey," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.536-539, 2018.

Clustering is a separation of data into collections of parallel objects. Signifying the data by smaller amount of clusters automatically loses certain fine details, but attains simplification. It models data by its clusters. This paper aims to present a brief survey and comparative study on and based clustering theory based on distributed databases in which the goal is to minimize the amount of iterations and cluster sizes is needed to re-optimize the solution when the cluster changes. Number of relative studies namely hybrid, density, Pheromone based ant clustering and cluster analysis. To conclude the discussion, the ant based clustering algorithms are discussed and evaluate the processing time performance on the several distributed datasets. Comparing to these algorithms the efficient Ant based Multiple Pheromone techniques methods outperforms having better performance than other methods

Clustering, partitioning, data mining, Ant clustering, Particle Swarm Optimization

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[6] I. El-Feghi, M. Errateeb, M. Ahmadi and M.A. Sid-Ahmed, “An Adaptive Ant-Based Clustering Algorithm with Improved Environment Perception”, International Conference on Systems, Man, and Cybernetics, pp. 1431-1438, 2009.
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[13] Saroj Bala, S.I. Ahson and R.P. Agarwal, “An improved Model for Ant Based Clustering”, International Journal of Computer Applications, Vol. 59, No. 20, pp. 9-12, December 2012.
[14] Saroj Bala, S.I. Ahson and R.P. Agarwal, “Agglomerative Ants for Data Clustering”, International Journal of Computer Applications, Vol. 47, No. 21, pp. 1-4, June 2012.
[15] J. Chircop and C.D. Buckingham, “A multiple pheromone algorithm for cluster analysis”, Nature Inspired Cooperative Strategies for Optimization, Studies in Computational Intelligence, Vol. 512, pp. 13-27, 2013.

Dhivya. N, Sumangala. K, "A Brief Survey On Ant Based Clustering for Distributed Databases," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.540-544, 2018.

A set containment join is a join between set-valued attributes of two relations, whose join condition is specified using the subset (⊆) operator. Set containment joins are deployed in many database applications, even those that do not support set-valued attributes. In this paper, we study the problem of set containment join. Given two collections R and S of records, the set containment join R ⊆S retrieves all record pairs {(r,s)} ∈ R × S such that r ⊆ s . This problem has been extensively studied in the literature and has many important applications in commercial and scientific fields. Recent research focuses on the in set containment join algorithms, In this paper, we propose three novel partitioning algorithms, called the Adaptive Pick-and-Sweep Join (APSJ), the Adaptive Divide-and-Conquer Join (ADCJ), and Divide-and-Conquer Join (DCJ) which allow computing set containment joins efficiently. We present a detailed analysis of the algorithms and study their performance on real and synthetic data using an implemented of this algorithm.

Algorithms, Experimentation, Performance and Implementations

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G. Sakthivel, P. Madhubala, "An Extensive Survey on Various Set Containment Joins Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.545-555, 2018.

This paper aims to present a brief overview of the development of image fusion in various algorithms and applications in recent years, and to understand the challenges and ability of image fusion. Various algorithms that are typically employed are covered to comprehend the complexity of usage in different scenarios. The main objective of this paper has gone to explore different methods for efficiently fusing digital images. It`s been found that many the prevailing researchers have neglected many consequences; i.e. no technique is accurate for different type of circumstances.

Image Fusion, fusion algorithm; fusion applications, Pca, Dct, Dwt

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Vijayakumar. R, Karthikeyan. K, "Image Fusion: A Review of Methods and Applications," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.556-566, 2018.

With the explosion of the number of images in personal and on-line collections, efficient techniques for navigating, indexing, labelling and searching images become more and more important. In several studies, the representation of images by topic models in its various aspects and extend the current models. This paper aims to present a brief survey on knowledge based topic model for Unsupervised Object Discovery and Localization techniques in which the goal is to maximize the amount of work needed to re-optimize the solution when the object changes. Number of relative studies namely Latent Dirichlet allocation (LDA) with Multi-Domain Knowledge (MDK), Collaborative randomized search algorithm, Conditional random field and LDA with mixture of Dirichlet trees algorithms are discussed and evaluate the accuracy performance on the several datasets. Comparing to these algorithms the LDA with mixture of tree technique methods having better performance than other methods.

Object discovery, object localization, topic model, and latentDirichlet allocation

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Mereena Johny, L. Haldurai, "A Brief Survey Ondynamic Topic Model for Unsupervised Object Discovery and Localization," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.567-571, 2018.

In this article, sales forecast models for the automobile market are developed and tested. Enhanced sales forecast methodologies and models for the automobile market are presented. The methods used deliver highly accurate predictions while maintaining the ability to explain the underlying model at the same time. The representation of the economic training data is discussed, as well as its effects on the newly registered automobiles to be predicted. Our most important criteria for the assessment of these models are the quality of the prediction as well as an easy explicability.The automobile market are presented for the evaluation of the forecast models. The market demand for vehicles has increased in recent years everywhere in the world. We need suitable models to understand and forecast demand of vehicle. This study presents a singular spectrum analysis (SSA) as a univariate time-series model and vector autoregressive model (VAR) as a multivariate model. Empirical results suggest that SSA satisfactorily indicates the evolving trend and provides reasonable results. The VAR model, which comprised exogenous parameters related to the market on a monthly basis, can significantly improve the prediction accuracy. The vehicles sales in beautiful city Ranchi, Capital of Jharkhand, India, are predicted in both short term (up to December 2018) and long term (up to 2021), as proofs of the growth of the Motor Vehicles industry.

Sales Forecast; Automobile Industry; Information Technology; Retail; Decision Making; Data Mining; Business Environment; Retail Sales Forecasting; Vehicles Sales

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Gyaneshwar Mahto, Umesh Prasad, Rajiv Kumar Dwivedi, "Forecasting Automobile Retail Sales Using Data Mining: The Case of Ranchi, Jharkhand, India," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.572-574, 2018.

Unusual event detection is the task of identifying the unusual events in a given region or area. Over last few years, Unusual event detection has received much of attraction due to its wide range of applications like fall detection, accident detection, lane change detection, red light running, traffic video surveillance . It is a very consequential and efficacious research topic in field of computer vision and video processing. Consequently, identification of unusual event from a given sequence of video frames becomes pertinent. However, task of detecting unusual event in motion becomes tricky due to various challenges like dynamic scene changes, illumination variations, and presence of shadow, camouflage and bootstrapping problem. To lessen the consequences of these problems, researchers have proposed number of new approaches. This paper provides a brief classification of the classical approaches for unusual event detection. Further, paper reviews recent research trends to detect unusual events along with discussion of key points and limitations of each approach.

Lane Change Detection, Intelligent Video Surveillance, Moving Object Detection

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Sonam Kashyap, Mohit Gupta, "A Review on Various Traffic Event Detection Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.575-583, 2018.

The trend of shopping in current scenario has changed a lot, with the evolution of online shopping. Companies can thrive their business by maintaining robust relation with their customers, by keeping information of consumer behaviour to provide them personalised services. This can be done by data pre-processing which involves extracting the database about the needs of customer’s pattern (i.e. quality, quantity, price and item), followed by data transformation and data mining techniques. But, to extract the discovered patterns in a huge database is still a tedious task, especially in the field of text mining. This paper unfolds various data mining techniques (clustering, classification, decision trees) to discover useful patterns for improving customer’s database accuracy and efficiency taking into consideration, their past performance. Further, we try to present an efficient pattern discovery technique by optimizing the original K-means algorithm, which would perform better in global searching and finding the relevant information.

Data mining, Literature review, clustering, K-Means

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B.S. Rawat, K. Kumar, R.K. Mishra, "Optimizing Data Pattern of Targeted Customers Using Datamining Techniques: A Review," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.584-588, 2018.

The infrastructure of vehicular networks plays a major role in realizing the full potential of vehicular communications. More and more vehicles are connected to the Internet and to each other, driving new technological transformations in a multidisciplinary way. Researchers in automotive/telecom industries and academia are joining their effort to provide their visions and solutions to increasingly complex transportation systems, also envisioning an innumerable of applications to improve the driving experience and the mobility. These trends pretense significant challenges to the communication systems: low latency, higher throughput, and increased reliability have to be granted by the wireless access technologies and by a suitable (possibly dedicated) infrastructure. In this paper presents an in-depth survey of more than ten years of research on infrastructures, wireless access technologies and techniques, and deployment that make vehicular connectivity available. In addition, here identify the limitations of present technologies and infrastructures and the challenges associated with such infrastructure-based vehicular communications, also highlighting potential solutions.

Data dissemination, location-dependent, VANETs

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S. Parameswari, K. Kavitha, "A Survey on Data Dissemination Scheme for Location-Dependent Data in VANETs," International Journal of Computer Sciences and Engineering, Vol.6, Issue.9, pp.589-595, 2018.