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The objective of this work is to explore the soil data analysis for crop yield prediction in KrishnagiriDistrict by comparing various data mining techniques which gives the maximum accuracy. Analyzing soil provides major contribution to support the farmers [2]. In this paper one of major parameter which is used to increase crop production is considered – soil, and also explores various proposed algorithms for analyzing soil using data mining techniques and different data mining algorithms are applied to soil data set to predict its soil fertility.

Crop Yield,Soil Data, Agricultural Yield Prediction, K-Means, Support Vector Machine (SVM), Multiple Linear Regression (MLR)

[1].N Hemageetha , G.M. Nasira,“Analysis of the Soil Data Using Classification Techniques for Agricultural Purpose”International Journal of Computer Sciences and Engineering,4(6)(2016).
[2].Huma Khan ,ShahistaNavaz, Dr. S. M. Ghosh3,” A Survey on Various Data Mining Techniques in Field of Agriculture for Prediction of Crop Yield”,International Journal of Science and Research (IJSR),6(5)(2017).
[3].E. Manjula,S. Djodiltachoumy,”A Model for Prediction of Crop Yield”,International Journal of Computational Intelligence and Informatics, 6(4)(2017).
[4].P. Kanjana Devi.S.Shenbagavadivu” Enhanced Crop Yield Prediction and Soil Data Analysis Using Data Mining”,International Journal of Modern Computer Science 4(6)(2016).
[5]. D Rames , B Vishnu Vardhan“Data Mining Techniques and Applications to Agricultural Yield Data” International Journal of Advanced Research in Computer and Communication 2(9)(2013).
[6].D Ramesh , B Vishnu Vardhan,” Analysis Of Crop Yield Prediction Using Data Mining Techniques”International Journal of Research in Engineering and Technology(IJRET),4(011)2015.
[7].Ramesh A.Medar, “A survey on Data Mining Techniques for Crop Yield Prediction” –A research Article in ijarcsms ,2(9) 2014.
[8].G Ruß, "Data Mining of Agricultural Yield Data : A Comparison of Regression Models", Conference Proceedings, Advances in Data Mining – Applications and Theoretical Aspects, P Perner (Ed.), Lecture Notes in Artificial Intelligence 6171, Berlin, Heidelberg, Springer, 2009, pages : 24-37.
[9].Sellam,V., Poovammal, E., “Prediction of Crop Yield using Regression Analysis”, Indian Journal of Science and Technology, Vol. 9(38), pp.1-5, 2016.
[10].Sujatha, R., Isakki, P., “A study on crop yield forecasting using classification techniques”, International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE), pp.1-4, 2016.
[11].S. Veenadhari, Dr. Bharat Misra, Dr. CD Singh, “Data mining Techniques for Predicting Crop Productivity – A review Article”, International Journal of Computer Science and Technology. (IJCST)2(1)(2011).
[12]. https://en.wikipedia.org/wiki/Krishnagiri_district
[13].https://krishnagiri.nic.in/about-district/history/

K. Samundeeswari, K. Srinivasan, "CROP YIELD PREDICTION AND SOIL DATA ANALYSIS USING DATA MINING TECHNIQUES IN KRISHNAGIRI DISTRICT", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.49-55, 2018.

Because of the approach of computer based innovation image processing strategies have turned out to be progressively vital in a wide assortment of utilizations. Segmentation is an exemplary subject in the field of image processing. Many works are existing in the area of segmentation and these systems regularly must be joined with area of learning new innovations techniques to achieve the end goal to adequately tackle the segmentation issue. This paper discuss the issue of segmenting yarn image with fuzzy and coherence techniques. The point of segmentation in the considered application is to remove yarn core from the yarn. The technique is guided and compelled by Coherence Enhancing Diffusion (CED) and FCM (Fuzzy C-Means) channel and furthermore the main problem of the yarn image segmentation is considered. For the process of segmentation Gaussian mixture model in enhanced with coherence and fuzzy to acquire a division limit esteem. The Results of segmentation by the CED, FCM and proposed strategy GMD are compared. The correlation demonstrates that the proposed method gives best outcomes. The yarn core and the hairiness segmentation from the proposed algorithm are adequate for assurance of yarn properties performed in the accompanying strides of the estimations of yarn hairiness measurements.

Coherence Enhancing Diffusion, Fuzzy C-Means,GMD, Yarn Segmentation, Yarn Hairiness

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R. Sudha Muthusamy, V. Chitraa, "Enhanced GMD Technique for Segmentation of Yarn Images based on Parametric Value and Intensity Gradient Analysis", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.56-63, 2018.

The main aim of image fusion (IF) is to integrate complementary multisensor, multitemporal and/or multiview information into one new image containing information the quality of which cannot be achieved otherwise. The need of image fusion for high resolution on panchromatic and multispectral images or real world images for better vision. There are various methods of image fusion and some techniques of image fusion such as IHS, PCA, DWT, Laplacian pyramids, Gradient Pyramids, DCT, SF. Several digital image fusion algorithms have been developed in a number of applications. Image fusion extracts the information from several images of a given scene to obtain a final image which has more information for human visual perception and become more useful for additional vision processing. Various performance matrices that used for the evolution of image fusion are Entropy, Standard Deviation, Peak Signal to Noise Ratio (PSNR), and etc.

Image fusion, Fused image, Discrete Wavelet Transform, Entropy, PSNR

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P. Suresh Babu, "A Significant Assessment of Image Fusion Techniques and its Performance Matrices", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.64-66, 2018.

Data mining is becoming strategically important area for many business organizations including banking sector. It is a process of analyzing the data from various perspectives and summarizing it into valuable information. Data mining assists the banks to look for hidden pattern in a group and discover unknown relationship in the data. Today, customers have so many opinions with regard to where they can choose to do their business. Early data analysis techniques were oriented toward extracting quantitative and statistical data characteristics. These techniques facilitate useful data interpretations for the banking sector to avoid customer attrition. Customer retention is the most important factor to be analyzed in today’s competitive business environment. Fraud is another significant problem in banking sector. Detecting and preventing fraud is difficult, because fraudsters develop new schemes all the time, and the schemes grow more and more sophisticated to elude easy detection. This paper analyzes the data mining techniques and its applications in banking sector like fraud prevention and detection, customer retention, marketing and risk management.

Banking Sector, Customer Retention, Credit Approval, Data mining, Fraud Detection

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M.V. Jisha, D. Vimal Kumar, "A CASE STUDY ON DATA MINING APPLICATIONS ON BANKING SECTOR", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.67-70, 2018.

The presence of high-end Internet-connected navigation and infotainment systems is becoming a reality that will easily lead to a dramatic growth in bandwidth demand by in-vehicle mobile users. This will induce vehicular users to resort to resource-intensive applications, to the same extent as today’s cellular customers .The research work considers a system where users aboard communication-enabled vehicles are interested in downloading different contents from Internet-based servers. This scenario captures many of the infotainment services that vehicular communication is envisioned to enable, including news reporting, navigation maps, and software updating, or multimedia file downloading. The project outlines the performance limits of such a vehicular content downloading system by modeling the downloading process as an optimization problem, and maximizing the overall system throughput. The research work investigates the impact of different factors, such as the roadside infrastructure deployment, the vehicle-to-vehicle relaying, and the penetration rate of the communication technology, even in presence of large instances of the problem. Results highlight the existence of two operational regimes at different penetration rates and the importance of an efficient, yet 2-hop constrained, vehicle-to-vehicle relaying.

Traffic Monitoring Control, Optimal Content Download, V-to-V Communication Model, Density Base Communication Model, Dynamic Network Monitoring system

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K. Gowthami, S. Vijaya kumar, "Density Base Road Accident Control Sensor Monitoring Using Dynamic Network Topology Graph Framework", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.71-76, 2018.

Cloud computing, delivers abundant services between Cloud Service Providers (CSP) and Cloud Users (CU) on a demand basis in metered service without having the underlying infrastructure with the help of Internet. This ease will increase the cloud users day by day to adopt cloud model. Technological advancements, specially Information Communication Technology (ICT) and cloud computing, transform traditional teaching and learning practices into blended learning. Due to the fabulous development of Massive Open Online Courses (MOOC) and Open Educational Resources (OER), more attention and efforts are crucial to the security procedures for massive open online courses. Authentication of the users to the cloud service is mandatory, because it eliminates the risks and attacks found in the cloud services. Password is widely used for user authentication because of its simplicity. Frequently changing password is a tedious work. Simple passwords are easily hacked, but complicated one is hard to memorize. To overcome this, we suggest Personally Identifiable Information (PII) for the purpose of Authentication. In this paper, we propose a security model using Dynamic Multi-Layer Authentication Mechanism, which is based on user’s personally identifiable information.

Authentication, Access Control, Massive Open Online Course, Open Educational Resource, Responsive Open Learning Environment, Self-Regulated Learning

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R. Anuratha, M. Ganaga Durga, "Data Privacy Using Dynamic Multi-Layer Authentication Mechanism in Open Learning Environment", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.77-80, 2018.

Symbolic execution techniques decrease the cost of path redundancy by choosing a separation of an existing test suite to use in retesting a customized program. Over the history, Eliminating Path Redundancy via Postconditioned Symbolic Execution techniques has been described in the literature. This paper aims to present a brief survey on symbolic executions in black-box and white-box regression testing under the Software testing and learning techniques that are in use in today`s software engineering of verification and validation tasks. Number of comparative study has been performed to evaluate the performance of predictive accuracy on the test cases and the outcome discloses that Bidirectional Symbolic Analysis for Effective Branch Testing method outperforms having better performance other predictive methods are not performing well.

Symbolic execution, testing and debugging, Parallel symbolic execution, AEG

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K.K. Nivethithaa, V. Krishnapriya, "A BRIEF SURVEY ON SYMBOLIC EXECUTION TEST-SELECTION TECHNIQUES", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.81-85, 2018.

An overview on the ruling technology “Artificial Intelligence” whose vision for High level-Perception has been done including its controversies. However, AI has reached its peak, the inventions like “Norman” done by MIT, which is a psychopathic robot has turned the vision or view of the entire community over AI. The AI Machines like “Cozmo” and “Moley”, who are being perfect in their purpose of creation has become an attention seeker in the views of the society. On the other hand “Deepmind” technologies explodes its perspectives and aspects towards every nook and corner of the people’s real time problems in daily life.”Alphago”, the master game being a Deepmind machine, has won the epic strong players of the game, taking AI to the top of the ladder. Notably, Deepmind technology with its amazing Neural Networks is ruling the medical society by completely changing the Lifestyle of patients. An Accurate and undoubted medicine system for everyone will be the future system which will be a dream come true for us. The future scope of AI would be a well-developed ‘AI Precision Farming’ and a strong Cyber security system which reduces the risk of Danger and a Well-developed Medicine system which will be a resolution of all the Social Problems.

Deepmind, Artificial Intelligence (AI), Precision medicine, Cyber security

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Sangeetha, "Artificial Intelligence-A Note on the Present Era Deepmind-Prospects and Aspects", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.86-90, 2018.

Server consolidation has recently become a major issue in cloud data centers. Energy efficiency is a key aspect in solving server consolidation issues. Virtual machine placement algorithms play an important role in maximizing the resource utilization may lead to energy efficiency. Constraint programming is an approach used to find the available servers and migrate these servers to the virtual machines by treating them as constraints to find optimal solution. The objective function of this work is to increase resource utilization by minimizing the number of active physical machines and decrease the search time of constraint solver for better energy efficiency. In this paper a Best Fit Resource Utilization ( BFRU) algorithm is proposed for virtual machine placement, it use best fit algorithm technique. However, virtual machine placement problem is formulated as a variant of multidimensional bin packing problem and then a constraint solver is used to solve the problem using the dataset collected from Amazon EC2.The proposed BFRU algorithm implemented through NetBeans IDE to evaluate the data collected. The simulation result shows that constraint programming based virtual machine placement algorithm BFRU can effectively reduce the energy consumption with respect to memory.

BFRU algorithm, Amazon EC2, Best Fit Resource Utilization ( BFRU) algorithm

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C. Pandi Selvi, S. Sivakumar, "Constraint Programming approach based Virtual Machine Placement Algorithm for Server Consolidation in Cloud data center", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.91-95, 2018.

Boolean expressions are major focus of specifications and they are very much prone to introduction of faults, this survey presents various fault based testing techniques.It recognizes that the methods differ in their fault detection capabilities and creation of test suite. The various techniques like Dealing with Constraints in Boolean Expression, Minimal Fault Detecting Test Suites, Reducing logic test set size, A logic mutation approach, SAT and SMT Solvers for Test Generation and Boolean Expressions by Cell Covering has been considered. This survey describes the fundamental algorithms and fault categories used by these strategies for evaluating their performance. Finally, it contains short summaries of the papers that use Boolean expressions used to specify the requirements for detecting faults. These techniques have been empirically evaluated by various researchers on a simplified safety related real time conditionals system.

Boolean Expression, BOR, Test suite, MBT

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[6] G. Kaminski and P. Ammann, “Reducing logic test set size while preserving fault detection,” Softw. Testing, Verification Rel., vol. 21, pp. 155–193, 2011.
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[11] Lian Yu and Wei-Tek Tsai, "Test Case Generation for Boolean Expressions by Cell Covering", IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, VOL. 44, NO. 1, JANUARY 2018.
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M. Sivaranjani, D. Gayathri Devi, "A Brief Survey Onboolean Expressions in Fault Based Techniques", International Journal of Computer Sciences and Engineering, Vol.06, Issue.08, pp.96-102, 2018.