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Cloud computing is a term generally used for the delivery of hosted services over the internet. In simple terms can be stated as “PAY-AND-USE Online Software resources”. Cloud computing makes to use the computing resource online. Balancing the load in the cloud is one of the important parameter which is to be focused. Hybrid Approach to Load balancing in Cloud Environment is a combination of two or more algorithms to achieve the betterment in the Cloud Service to the clients. With the observations it looks that RT Hybrid Algorithm would make the improvement for the better implementation.

Cloud computing, Servers, Virtual machine, Data centers, Load balancing, Hybrid approach

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[12] Ajeet Mishra, Prof. Umesh Kumar Lilhore, Prof. Nitesh Gupta," Review of Various Data Storage and Retrieval Method for Cloud Computing ",International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307,Volume 2 , Issue 5, PP 584-588

G.Srinivasa Rao , T. Anuradha, "Improved Hybrid Approach for Load Balancing In Virtual Machine," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.730-733, 2018.

Cloud Computing is expanding as the next generation platform which would ease the user on pay as you use mode as per requirement. Cloud incorporates a set of virtual machine which comprises equally storage and computational facility. Due to speedy increase in use of Cloud Computing, moving of more and more application on cloud and demand of customers for more services and enhanced results. The fundamental goal of cloud computing is to offer successful access to isolated and geographically circulated resources. Cloud is growing every day and experience many problems such as scheduling. Scheduling means a group of policies to regulate the order of task to be executed by a computer system.VM Scheduling is necessary for efficient operations in distributed environment. This paper combines ant colony optimization and BAT to solve the VM scheduling problem. We discuss and evaluate these techniques in regard of various performance matrices to give an overview of the latest approaches in the field.

CloudComputing,Scheduling,BAT,AntColonyOptimization

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Ritu Sharma, Palvinder Singh Mann, "Hybrid Metaheuristic for Virtual Machine Scheduling in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.734-740, 2018.

The significance of Urban heat island (UHI) is to space heater than the urban adjacent area. This heat energy creates by urban people, house, shops, cars, buses, trains, industrial zone, etc. The UHI be an vital occurrence of urban environment in addition to gives direct and circumlocutory effect lying on urban population. In UHI calculating using landsat thermal band, Landsat TM, ETM+ and OLI satellite image (2000, 2008, 2017 Year) data processed to obtain a atmoshphire window method use to retrieve the land surface temperature (LST) using specifically band-6 (TM, ETM+) and band 10 (OLI) for data procurement and investigation. UHI consequence related with rising impermeable surface both spatially and temporally. This study aims to analyze the changes in LST with advent of the Kolkata Metropolitan Area (KMA). The result found that the (LST) is increasing sharply. The mean temperature of the area was 22.33°C in 2000 which became 23.68°C in 2008 and 23.79°C in 2017. The relation of built-up (NDBI) and LST is found positively correlated with a r value of 0.96 in 2000 and 0.78in 2017 and the relation with vegetation (NDVI) is negatively related and the r value is -0.98 in the years of 2000 and the r value is -0.97 in 2017, several heat zones are highlight and have been identified on the map of the KMA area. The addition of Geospatial technology be set up in the direction of valuable in monitor and analyze urban expansion pattern and in evaluation urbanization collision on surface temperature. Finally, the study suggests considering the possible micro-climatic changes in Kolkata metropolitan area and planning for the sustainable improvement.

Urban Heat Island (UHI), land surface temperature (LST), Normalized differential build up index (NDBI), Normalized differential vegetation index (NDVI).

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Md Amir Ali Gazi, Ismail Mondal, "Urban Heat Island and its effect on Dweller of Kolkata Metropolitan area using Geospatial Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.741-753, 2018.

To enhance organize security diverse advances has been taken as size and significance of the system has builds step by step. Keeping in mind the end goal to discover interruption in the system Intrusion recognition frameworks were developed which were comprehensively arrange into two category first was misused based and other was anomaly based. In this paper review was done on the different methods of intrusion recognition framework where some of administered and unsupervised interruption location procedures were informed in detail. Here technique of different researcher are clarified with there ventures of working. Diverse kinds of attacks done by the interlopers were additionally surveyed.

Anomaly Detection, ANN, Clustering, Genetic Algorithm, Intrusion Detection

[1]. Shaohua Teng, Naiqi Wu, Senior, Haibin Zhu, Senior, Luyao Teng, And Wei Zhang. “SVM-DT-Based Adaptive And Collaborative Intrusion Detection”. IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 5, NO. 1, JANUARY 2018.
[2]. Aljurayban, N.S Emam, A. (21-23 March 2015). Framework For Cloud Intrusion Detection System Service. Web Applications And Networking (WSWAN), 2015 2nd World Symposium On, P1-5
[3]. Mr Mohit Tiwari,Raj Kumar, Akash Bharti, Jai Kishan. “Intrusion Detection System”. International Journal Of Technical Research And Applications E-ISSN: 2320-8163, Volume 5, Issue 2 (March - April 2017), PP. 38-44.
[4]. YU-XIN MENG,” The Practice On Using Machine Learning For Network Anomaly Intrusion Detection” Department Of Computer Science, City University Of Hong Kong, Kowloon, Hong Kong, 978-1-4577-0308-9/11/$26.00 ©2011 IEEE
[5]. Kai Peng, Victor C.M. Leung, Qingjia Huang. “Clustering Approach Based On Mini Batch Kmeans For Intrusion Detection System Over Big Data”. IEEE Transaction 2169-3536 © 2017. .
[6]. Chuanlong Yin , Yuefei Zhu, Jinlong Fei, And Xinzheng He. “A Deep Learning Approach For Intrusion Detection Using Recurrent Neural Networks” Current Version November 7, 2017. Digital Object Identifier 10.1109/ACCESS.2017.2762418.
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[18]. Nouf Saleh Aljurayban, Ahmed Emam “Framework For Cloud Intrusion Detection System Service”. DOI: 10.1109/ WSWAN.2015. 7210298, IEEE, 20 August 2015.

Jhalak Jain, Chetan Agarwal, Himanshu Yadav, "A Survey on Robust Intrusion Detection System Methodology and Features," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.754-760, 2018.

Internet of Things (IoT) refers to objects that have unique identities and are connected to the internet. While many existing devices, such as networked computers or 4G-enabled mobile phones, already have some form of unique identities and are also connected to internet. Internet of Things is a new revolution of the internet that is rapidly gathering momentum driven by the advancement in sensor networks, mobile devices, wireless communications, networking and cloud technologies. Experts forecast that in future there will be all devices/ things connected to internet. The aim of the Internet of Things (IoT) is to enable things to be connected anytime, anyplace with anything. The IoT is comprised of smart machines interacting and communicating with other machines, environments and infrastructures. As a result, huge volumes of data are being generated, and that data is being processed into useful actions that can make our lives much easier and safer and to reduce our impact on the environment. Internet of Things architecture is capable enough to improve the understanding of related tool, technology, and methodology to facilitate developer’s requirements. Various applications of IoT have been developed and researchers of IoT identified the opportunities and challenges used in IoT such as sensors, actuators, mobile phones. In this paper we discussed IoT, its architecture, and applications of IoT. The creativity of this new era is unlimited, with amazing potential to improve our lives. The following paper is an extensive reference to the utility, applications and an evolution of the Internet of Things.

Internet of Things (IoT), Layered Architecture, Sensors & Actuators

[1]. Luigi Atzori AI, Giacomo Morabito. “The Internet of Things: A Survey. Comput. Netw.” 2010; 54(15);2787−805.
[2]. Coetzee LE. “The Internet of Things - Promise for the Future? An Introduction” , IST-Africa Conference Proceedings, 2011.
[3]. Sarita Agrawal MLD. “ Internet of Things – A Paradigm Shift of Future Internet Applications” , International Conference on Current Trends in Technology, 2 Nuicone, 2011.
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[6]. Jason Healey NP, Beau Woods. “ The Healthcare Internet of Things -Rewards and Risks”, Intel Security, 2015.
[7]. Shivayogi Hiremath, Geng Yang, Kunal Mankodiya. “Wearable Internet of Things”, in International Conference on Wireless Mobile Communication and Healthcare. 2014.
[8]. Gigli MK, Simon. “Internet of Things: Services and Applications Categorization”, Advances in Internet of Things. 2011; 1(02):27.
[9]. Da Xu L, He W, Li S. “Internet of Things in Industries: A Survey”, Industrial Informatics, IEEE Transactions. 2014; 10(4):2233−43.
[10] Gurpreet Kaur1 , Manreet Sohal , “IOT Survey: The Phase Changer in Healthcare Industry “: IJSRNSC Volume-6, Issue-2, April 2018 ISSN: 2321-3256
[12] Mantripatjit Kaur1 , Anjum Mohd Aslam , “Big Data Analytics on IOT: Challenges, Open Research Issues and Tools”: International Journal of Scientific Research in Computer Science and Engineering Vol.6, Issue.3, pp.81-85 , June (2018) E-ISSN: 2320-7639

Kiran M. Pradhan, Suchitra K. Kasbe, Vaishnavi M. Pradhan, "Internet of Things Architecture and Applications : A Overview," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.761-766, 2018.

More than one transactions are executing simultaneously is known as concurrent executions. It implies interleaving execution of operations of a transaction. In this paper we will study the benefits of concurrent transactions and problems with concurrent transactions. We will study above with the help of the suitable examples. This paper will help to students and research scholars to understand the concurrent transactions executions.

Concurrent Transaction, throughput, response time, concurrency

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Anil Kumar Singh, "A study of Concurrent transaction execution and their problems in Distributed Database System," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.767-769, 2018.

This paper gives the review of different prediction and recommendation system associated with health related problems. Increasing cost of medicine which is not affordable to generalized people and they are always looking for low cost medicine with same content and its effect is the main motivation behind this work. Alternate Medicine System solves this problem by searching through large volume of dynamically generated information to provide users with personalized content and services. This work gives the use of Random Forest Algorithm for content based alternate medicine recommendation system in order to serve as a useful tool for everyone who is associated with the medicine. This paper includes the different classification technique which recommends the different alternative solution. This work explores the different methods and technique used for prediction and recommendation of different issues regarding illness by using different classification techniques in recommendation systems. This study reveals the use of Random Forest Algorithm in the recommendation system. This is gives fast response and fast to build. It is even faster to predict and requiring cross-validation alone for model selection.

Alternate Medicine, Content Based Recommendation, Random Forest, Algorithm, Healthcare

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[14] Soudabeh Khodambashi, Alexander Perry, Oystein Nytro, “Comparing User Experiences on the Search-based and Content-based Recommendation Ranking on Stroke Clinical Guidelines - A Case Study” Procedia Computer Science, Published by Elsevier, pp. 260-267, 2015.
[15] Kourosh Modarresi, “Recommendation System Based on Complete Personalization” Procedia Computer Science, Published by Elsevier, Vol. 80, pp. 2190-2204, 2016.
[16] Rubal, Dinesh Kumar, “Evolving Differential evolution method with random forest for prediction of Air Pollution” ” Procedia Computer Science, Published by Elsevier, Vol. 132, pp. 824–833, 2018.
[17] Mo Hai, You Zhangc, Yuejin Zhanga “A Performance Evaluation of Classification Algorithms for Big Data” Procedia Computer Science, Published by Elsevier Vol.122 pp. 1100-1107, 2017.
[18] Charu Kathuria, Deepti Mehrotra, Navnit Kumar Misra, “Predicting the protein structure using random forest approach” Procedia Computer Science, Published by Elsevier Vol.132, pp. 1654–1662, 2018.
[19] Meenu Shukla, Sanjiv Sharma “Analysis of Efficient Classification Algorithm for Detection of Phishing Site” International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.136-141, June 2017.
[20] J.V.N. Lakshmi, Ananthi Sheshasaayee “A Big Data Analytical Approach for Analyzing Temperature Dataset using Machine Learning Techniques” International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.3, pp.92-97, June 2017.

Ankita D. Rewade, Sudhir W. Mohod, "Content Based Alternate Medicine Recommendation By Using Random Forest Algorithm: A Review," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.770-775, 2018.

A tumor is a clot or growth of tissues in a brain, which is not normal and causes harm to the tissues. The identification of tumor in brain is a challenging task. MRI (Magnetic resonance image) is a strong radio waves and magnetic field is a type of scan used by MRI to produce diagnosed image of body. The biomedical image processing uses the method of segmentation to explore the useful segmentation. The segmentation method is used to identify the tumor in brain by using different methods such K-mean, Wavelet Statistically Textures Features, Fuzzy C means, Spatial FCM, Proximal Support Vector Machine. This paper gives the overview of the techniques for detection of tumor from MRI images. In this paper, different step are carried firstly preprocessing is used to remove noise from MRI image then Skull of the brain is detect and segmentation method are applied for identification of tumor from MRI image. By using median filter noise are removed from MRI image. The Classification of normal or abnormal brain tumor is carried out by using SVM classifier.

MRI images, Brain Tumor, Brain, and Segmentation, SVM, K-mean

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Shruti Reshmi, Rajashekhar D. Salagar, Shriharsha S. Veni, "A SURVEY ON BRAIN TUMOR DETECTION AND SEGMENTATION FROM MRI IMAGES," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.776-778, 2018.

About seventy percent of the Indian population lives in villages or in rural areas. Even after more than seventy years of Independence the rural India is lagging behind on the developmental index. So for the true of development of India the villages cannot be neglected rather the villages should be given special care. The Government of India is highly concerned for the development of rural India. Now a days technology is playing very important role in almost every walk of life. Accordingly the technology can be the real game changer for the development of rural India. Artificial Intelligence or AI in short, is the future of the modern world and accordingly it has a lot for the development of rural India. This paper deals with the potential of the Artificial Intelligence in the development of rural India.

the Indian population, rural India and development

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Adarsh Singh Punjeta, "Rural Development with the Help of Artificial Intelligence," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.779-780, 2018.

When adding capacity is not the option due to financial constraints or due to various other reasons, operating transportation systems efficiently is the only available option, in combating congestion. More and more transportation systems are concentrating on improving efficiency of these; and Traffic Archive Modelling and ITS –use of computer and communication technology is at fore-front to achieve the above said objective. For the last two decades, intelligent transportation systems (ITS) have emerged as an efficient way of improving the performance of transportation systems. A significant change in ITS in recent years is that much more data are collected from a variety of sources. The availability of a large amount of data can potentially lead to a revolution in ITS development, changing an ITS from a conventional technology-driven system into a more powerful multifunctional data-driven intelligent transportation system. In this paper, we provide a critical performance based survey on the development of intelligent transportation systems, discussing the functionality of its key components and some deployment issues associated with it. Future research directions and a roadmap to future is also presented.

Data Mining, data-driven intelligent transportation systems machine learning, Hierarchical clustering, GPS, mobility, Traffic Density

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Shailaja B. Jadhav, "A Critical Performance Based Survey of Tools, Research Techniques and Perspectives of Intelligent Traffic Archive models," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.781-788, 2018.