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This paper presents an effective methodology for self scheduling of thermal generators to improve the profit of generation companies (GENCOs) in a day-ahead joint energy and reserve market. A recently projected Exchange Market Algorithm (EMA) is proposed to solve self scheduling problem. EMA is a powerful tool and having two dominant absorbing operators to pulling the solutions toward optimality and two smart searching operators for extract optimum point in optimization problem. Therefore, the proposed approach provides capability to determine global optimal solution for self scheduling problem. The problem modelled in the form of bi-objective optimization framework to simultaneously maximize the profit of GENCOs and reduce emission quantity taking into account reserve power generation.. The thermal generators emit the greenhouse gases into the atmosphere, which is answerable for change of climate and global warming in our environment. Sufficient spinning reserve is one of the major factors for reliable operation and profit maximization of power suppliers. So the problem is carefully coined with a view to maximize the profit of GENCOs by considering reserve power generation and added in the objective function. Also generated reserve power is sold in the reserve market. Numerical example with IEEE 39 bus (10 units with 24 hour) test system is considered to evaluate the performance of the proposed EMA. From the simulation results, it is found that the EMA based approach is able to afford the better solutions in terms of fuel cost, revenue, profit and emission with lesser computational effort.

Deregulation, Self scheduling of GENCOs, Energy and Reserve generation, Profit maximization, Reduction of Emission, Exchange market algorithm

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Senthilvadivu A, Gayathri K, Asokan K, "An Intelligent Computational Algorithm for Optimal Self Scheduling of GENCOs to Improve The Profit in a Day-ahead Energy and Reserve Market," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.251-265, 2018.

The financial market is very dynamic in nature and changing continuously. In addition of that due to it’s dynamicity prediction of stock price values are not much accurate. In order to predict the stock’s close values accurately machine learning technique is used in this proposed work. The proposed technique usages supervised learning technique because supervised learning techniques can predict values more accurately. In order to train and test the proposed machine learning prediction technique the YQL data in offline mode is used. The proposed stock market price prediction method is a hybrid data model. In this context two different algorithms are combined for obtaining the goodness of both the techniques. Here both the algorithms are analyze data according to their methodology and perform prediction. After that both algorithms’ approximated values are combined by computing the mean values as final prediction. Therefore the proposed technique optimizes the performance of the traditional back propagation based stock market price prediction. The implementation of the proposed technique is performed using the JAVA technology and the performance of the system is measured in term of accuracy, error rate, time complexity and memory usages. The performance of the system demonstrate the proposed technique enhance the prediction of the close values. In addition of that comparative performance study of proposed technique is performed with the traditional back propagation model using experimental outcomes. Results demonstrate proposed technique out perform with respect to the traditional approach of stock market price prediction.

Stock Market Price Prediction, Regression Analysis, Error Adjustment

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Prateek Purey, Anil Patidar, "Stock Market Close Price Prediction Using Neural Network and Regression Analysis," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.266-271, 2018.

In Virtual machine, Energy conservation is the major problem and it provides benefits such as reducing costs, increased reliability of the system and it also provides protection to the environment. Energy–aware scheduling is used to achieve these benefits. Existing energy-aware scheduling algorithms are not real time task oriented and also it lacks in system schedulability. Vacation queuing model is used for real-time, a periodic, independent task to solve this problem. The system which is proposed here can achieve energy optimization by combining the virtual machine resources with current exploitation. The eminence of hardware and nodes are well-organized with virtual network topologies. Vacation system is implemented with sojourn time to guarantee the schedulability of real-time tasks, efficiently. Simultaneously, energy consumption via dynamic VMs consolidation is concentrated. There are two strategies i.e. scale up and scale down to achieve a suitable trade-off sandwiched between task’s schedulability and energy preservation. Energy conservation is achieved by switching the active host to sleep mode when the system does not perform any action. The task should be completed within the deadline and each user must provide the deadline to avoid rejection. The deadline is analyzed and acknowledgement is provided to the scheduler for each task completion.

Virtualmachine, Scheduling, Deadline, Resources

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RV. Deepa, E. Ramaraj, "Energy Preserves Task Scheduling In Heterogeneous Virtual Machine Framework," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.272-277, 2018.

Now a days Diabetes mellitus is a major global public health problems. The machine learning techniques can be applied to help the people in detection of diabetes at an early stage and treatment, which may help in avoiding complications. In our work attempts to propose three kinds of techniques K- Nearest Neighbor (KNN), Naive Bayes (NB) and Artificial Neural Network (ANN) for classifying the individual user as diabetic or non diabetic.Providing diagnostic aid for diabetic by using a set of data that contains only medical information obtained without advanced medical equipments, can help number of people who want to discover the disease or the risk of disease at an initial stage. The experimental system achieves classification accuracy of KNN is 92.59%, NB is 85.71% and ANN is 94.64%. The aim of this study is to classify diabetes disease and deploy in to cloud for cost effective and easy to use.

Diabetes mellitus, K-Nearest Neighbor, Naïve Bayes, Artificial Neural Network, Cloud

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J. Seetha, T. Chakravarthy, "Diabetes Classification Using Machine Learning Techniques With The Help of Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.278-283, 2018.

K-means clustering approach is the most commonly used approach to reduce the sum of intra-cluster differences. But there is problem regarding the selection of centroid in k means clustering algorithm. Centroid can be poor or best depending upon the data. Therefore, there is a probablility of selecting good or bad centroid. So, in case of poor centroid selection, data does not get clustered in proper manners. To overcome this problem, we have used Min-max based K-means clustering algorithm along with ANN (Minimum- maximum based artificial neural network). The ANN algorithm overcomes the pitfalls of Min-max based K-means algorithm (Poor selection of centroid). In our research we have used Min-max K-means algorithm along with ANN to find out the exact category according to the labeled input data. Here, ANN is firstly trained with labeled input data. On the basis of training, testing phase is done to determine the accurate output for labeled input data. The enhancement in the accuracy of the proposed work from the existing work is approximately 16.47%.

Clustering, K-mean, Min-Max, ANN

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Gurpreet Virdi, Neena Madan, "Min-Max based K-means Clustering Algorithm using Artificial Neural Network Approach," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.284-288, 2018.

Internet of Things (IoT) refers to the latest technology which is changing the way of looking towards the world. The terminology Internet of Things (IoT) refers to a future where every day physical objects are connected by the Internet in one form or the other, but technology is quickly changing the way we interact with the world around us. It is the advancements in the networking with the help of which real world objects can be connected to communicate with one another without human intervention. IoT envisions a future in which both digital and physical world can be linked, by means of appropriate information and technologies. IoT is supported by the wide range of distributed devices with embedded identification, sensing and/or actuation capabilities. In this paper will discuss the applications and challenges of Internet of Things (IoT).

Internet of Things, IoT Components, IoT Applications, Challenges, Smart Home, Smart Environment, Smart Cities

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Deepanshu Mehta, "Internet of Things: Applications and Challenges," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.289-293, 2018.

A current popular trend of wallet security research is cryptography. For that Merkle tree is one of the solutions to enhance wallet security. It is basically used for cryptocurrencies, file system authentication, backup system, control system, database, etc. but it can be used for communication authentication and many more. And that is highlighted in this paper by stating the few future Merkle tree implementation possibility with its basic technical requirements. In this survey study also discuss about the Merkle tree concept with its advantages and disadvantages and its implementations such as Bitcoin, Ethereum, Hash-based Cryptography, Apache Cassandra, Btrfs, ZES, IPFS with their comparisons.

Merkle Tree, Bitcoin, Ethereum, Hash-based Cryptography, Apache Cassandra, Btrfs, ZES, IPFS

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Mansi Bosamia, Dharmendra Patel, "Current Trends and Future Implementation Possibilities of the Merkel Tree," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.294-301, 2018.

Classification of Gene expression data is one of the challenging tasks in the domain of Bio-medical recognition. Working on high dimensional data sets always poses complexity on accuracy and on the computational fronts. A Novel approach for classifying the gene expression data has been proposed which paves path for better efficiency and effectiveness measure using an enhanced algorithm for analyzing the sequential patterns by use of a novel algorithm which surpasses the existing methods. This approach provides a better heuristics for working with both supervised and the semi-supervised data. The proposed methodology increases the efficiency by making use of the threshold values which has been used for pruning the data sets which gives rise to a higher confidence on the data sets. The classification thus achieved could help us understand the patterns using the prediction algorithm and then grouping them based on the class labels. This work and the technique that is to be used could serve us in predicting interesting knowledge on the input gene data set. As the data set is of high dimension it throws open the corridors for various analysis on the acquired classes and considerably alleviate the computation cost.

Classification, Gene Expression, Supervised, Semi-supervised, pruning

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[11] T. Senthilselvi, R.Parimala, “Improving Clustering Accuracy using Feature Extraction Method “, IJSRCSE, Vol-6, Issue-2, pp 15-19, 2108.

A. Immaculate Mercy, M. Chidambaram, "A Novel Approach for Classifying Gene Expression Datasets," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.302-305, 2018.

The optical antenna transmits optical signals on nanometer scale. The nano-scale devices are expected to radiate in – THZ frequency range. The optical antenna has unique biological Application for communication networks to be analyzed. Its frequency response with high mode conductive antenna element for nano devices. The optical antenna has unique and key application for such types of area based configuration for optical communication devices. The optical antenna made-up nanoparticle like gold, particle because the calculation of three dimensions is possible in infrared band. In this research articles we have studied about antenna emission, distribution, characterization of terahertz (THZ) optical emission with high resonance of nanoantenna optical frequencies result. The wavelength optical antenna 400 nm nano-scale enable to study for far field radiation distribution.

Optical antenna, terahertz (THZ), DRA antenna, Gold-particle, nanoscale transmit, Dielectric Antenna, spontaneous emission, nanoparticle

[1]. Mohan, A., 2015. The advanced generation mobile broadband technology for wireless communication system and its applications. IJAR, 1(12), pp.383-385.
[2]. MOHAN, ANAND. "RADIATION CHARACTERISTIC OF METALLIC NANO- PARTICLE WITH APPLICATION TO NANO-ANTENNA." “An Experimental Study of Effect of Amalkirasayan and Amalkiswaras with Help of Electron Microscopy” 1-9 8, no. 5&6 (2014): 45.
[3].MOHAN,ANAND."SYNTHESIS OF BI-METALLIC NANOPARTICLES AND ANALYSIS OF THEIR PERFORMANCES." “An Experimental Study of Effect of Amalkirasayan and Amalkiswaras with Help of Electron Microscopy” 1-9 8, no. 5&6 (2014): 59.
[4]. Mohan, A. (2016). Study of Plasmonic Nano Antennas and Their Optimization., International Journal of Emerging Research in Management &Technology ISSN: 2278-9359 (Volume-5, Issue-5) Special Issue on International Conference on Advances in Engineering (ICAE) -2016 Conference Held at Hotel Magaji Orchid, Sheshadripuram, Bengaluru, India.
[5]. Mohan Anand “ROLE OF NANOANTENNA SYSTEM IN TRANSFORMING THERMAL ENERGY, Airo International Research Journal ISSN: 2320-3714 Volume: 7 June 2016
[6]. Mohan Anand “IOT: A BIG REVOLUTION FOR NANOSCIENCE” 7th virtual NanotechnologyPosterConference http://www.nanopaprika.eu/group/nanoposter/page/p17-21
[7]. Sachchida Nand Singh; Ashok Kumar: Anand Mohan: Study of nanoantennas for enhanced Optical emission, Proceedings of International Conference on Advances in Light Technologies and Spectroscopy of Materials (ICALTSM -2016), page. no. 256, January16-18, 2016.
[8].Akyildiz IF, Jornet JM, Han C. Terahertz band: Next frontier for wireless communications. Physics Communications. 2014; 12:16–32. DOI: 10.1016/j.phycom. 2014.01.006
[9].Anand Mohan,Cylindrical dielectric resonator antennas (CDRA) & its applications for human life, ISCA, Souvenir of 4th International Virtual Congress IVC-2017, ISBN: 978-93-84659-68-4, 2017
[10].Nagatsuma T, Ducournau G, Renaud CC. Advances in terahertz
communications accelerated by photonics. Nature Photonics.
2016;10(6):371–379
[11]. Anand Mohan, Ashok Kumar, Uses of Optical Nanoantenna in ICT and its Ability, Souvenir of 3rd International Virtual Congress, 3rd International Virtual Congress IVC-2016, ISBN: ISBN: 978-93-84648-78-7, 2016
[12].Anand Mohan, Study of Plasmonic Nano-Materials for Surface
enhanced Localized Surface Plasmon Resonance Spectroscopy (LSPR) &Their Applications for OpticalAntennas, Indian Journal of Agriculture and Allied Sciences, ISSN 2395-1109 Volume: 1, No.: 4, Year: 2015,
[13].Scholl, J. A., García-Etxarri, A., Koh, A. L. & Dionne, J. A. Observation of Quantum Tunneling between Two Plasmonic Nanoparticles. Nano Lett. 13, 564–569(2013).
[14]. K. O’Brien, H. Suchowski, J. Rho, A. Salandrino, B. Kante,X. Yin, X. Zhang, Predicting nonlinear properties of metamaterialsfrom the linear response, Nature Materials 14 (2015)379–383.

Anand Mohan, "Optical Antenna: A Key Enabling Arial For Device To Device Communication," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.306-309, 2018.

Transferring information over the network is widely used fast and reliable source for communication. Users with wide fidelity use this mechanism for transferring and accessing information. Portability and interoperability within the cloud system through offline and online mediums are continuously desirable but the problem of security arises during the transmission process. Security and reliability is the key issue during the transfer process which is considered in this research. Information security is provided using the public and private key RSA cryptography. The experiment is implied not only at offline data but also at online data such as Google Docs. Redundancy handling mechanism is used to ensure that space at data storage provider is least used since cost in DSP is accompanied by the amount of storage used. Overall space requirement in case of heavy files is reduced and security of online information accessing is enhanced by the use of RSA cryptography with redundancy handling mechanism.

Interoperability, Portability, Security, reliability, RSA, Redundancy, Cost

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Gagandeep Kaur, Kiranbir Kaur, "Enhancing Portability and Confidentiality of Data Migration Among Inter Clouds," International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.310-315, 2018.