-5171ffc0182b6af927f-7819 20220827033218947 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 07 30 2019 8 2 Research Associate, VIT Business School (VITBS), VIT Chennai Campus, Vandalur-Kelambakkam Road, Rajan Nagar, Chennai, India. Divya V Dr. Sharon Sophia Assistant Professor, VIT Business School (VITBS), VIT Chennai Campus, Vandalur-Kelambakkam Road, Rajan Nagar, Chennai, India. The study is to examine the volatility fluctuations based on investor sentiment as various studies has been carried out in the past concentrating mostly on the current reaction of investors sentiment depending on historical volatility estimations. Closing data of NYSE index is considered as independent variable in analyzing both the historical volatility and sentiment index as they are valuated from them. Observation of 807 trading days from the period of 2015-2018 from American Stock Exchange is considered for the study. The study also helps to determine the use of dependent (ARMS Index and Historical Volatility) and independent variable (NYSE Closing price data) among themselves and the reliability of the independent variable. The viability of the dependent variable in deriving the values of the independent variable is analyzed and it as found out that both the dependent variables can act as independent variable in examining the other dependent variable. 07 30 2019 5775 5780 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A1817.078219 https://www.ijrte.org/portfolio-item/A1817078219/ Computer Science and IT, AmritaVishwaVidyapeetham/ Amrita School of Arts and Scineces Kochi, Ernakulam, India Steena Gracious Geethu Nandanan Computer Science and IT, AmritaVishwaVidyapeetham/ Amrita School of Arts and Scineces Kochi, Ernakulam, India. Dagma K R Computer Science and IT, AmritaVishwaVidyapeetham/ Amrita School of Arts and Scineces Kochi, Ernakulam, India. Hari Narayanan A G Computer Science and IT, AmritaVishwaVidyapeetham/ Amrita School of Arts and Scineces Kochi, Ernakulam, India. With increasing apprehension and concerns of cloud computing and information security, awareness about the use of security algorithms in data systems and processes is indispensable. The objective of this paper is to examine a set of cryptographic algorithms for cloud platforms to secure clinical data. The main benefits of cloud storage are scalability, resilience, cost efficiency, high reliability and easy access to your knowledge anyplace, anytime. Because of these benefits every organization is moving its data to the cloud. So there is a necessity to protect that data against unauthorized access, modification or denial of access etc. we analyzed the use of cryptography in securing clinical data sets using evaluation parameters such as computing memory, encryption time and decryption time 07 30 2019 107 110 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A1819.078219 https://www.ijrte.org/portfolio-item/A1819058119/ Department of CSIT, DRCVRAMAN University Bilaspur, India. Sumati Pathak Rohit Raja Department of CSE, Sreyas Institute of Engineering and Technology, Nagole, Hyderabad, India Vaibhav Sharma Department of CSIT, DRCVRAMAN University Bilaspur, India. Sri nivas Ambala Department of CSE, Sreyas Institute of Engineering and Technology, Nagole, Hyderabad, India. Nowadays, higher education providing institutions depend upon Information and Communication Technologies (ICT) for all purposes like teaching, administration, learning and other research related works. ICT is found to be a major resource for bringing competitive growth for an organization. In general, the use of ICT in higher education institution plays a vital role in providing modern learning approaches. Further, the utilization of data mining in ICT can predict the performance of students and offer a way to improve it. This paper identifies the usage of ICTs among higher graduates and the impact of parameters such as gender, area of interest as well as name of the university. In addition, data mining based ranking algorithm is introduced in order to analyze the performance of students. The evaluation results show that the use of ICT in higher education provides technological improvements and these enhancements are associated with factors such as gender, area of interest as well as university. Moreover, the ranking algorithm can easily evaluate the ICT based performance of higher education institutions. 07 30 2019 5120 5124 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.B1825.078219 https://www.ijrte.org/portfolio-item/A1825058119/ Research Scholar, Department of ECE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science & Technology (Deemed to be University), Chennai, India. Narsaiah Domala Dr. G. Sasikala Associate Professor Department of ECE, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science & Technology (Deemed to be University), Chennai, India. The paper presents a sub-volt design of highly precise second-generation current conveyor (CCII  ) using Miller compensated Operational Transconductance Amplifier (OTA) designed using bulk driven quasi-floating gate (BDQFG) MOSFET. The bulk-driven approach help in working of proposed CCII  at low supply voltage. Moreover, followed BDQFG technique results in improves the transconductance and frequency response of the circuit over standalone bulk-driven technique. The proposed CCII  operates at  0.4V. Other performances which encourage its wide applicability are in terms of high current range and high bandwidth. The analysis of proposed current conveyor is carried in 0.18 m twin-well CMOS technology using HSpice. 07 30 2019 823 826 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A1861078219 https://www.ijrte.org/portfolio-item/A1861058119/ Department of Electrical and Electronics, PRIST University, Thanjavur, India. Ahalya R The Multilevel inverters are known for their high power capability and reliability. They produce the output in the form of staircase waveform. If the number of level increases then almost perfect sine wave can be attained at the output. The increase in number of levels improves the power quality but it also increases the complexity in control and cost, which will increase the switching losses also. Hence there is a need for research in the multilevel inverter topology to have reduced number of switches for increased levels than the conventional and pre-proposed topologies. The purpose of this paper is to design the new topology on multilevel inverter with reduced switching devices 07 30 2019 1230 1233 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A1868.078219 https://www.ijrte.org/portfolio-item/A1868058119/ Department of Electrical &Electronics Engg, M.Kumarasamy College of Engineering, Karur, India A.S.F. Subhamathi G. Sakthi Priya Department of Electrical &Electronics Engg, Velammal college of Engg & Tech, Madurai, India S. Banumathi Department of Electrical &Electronics Engg, M.Kumarasamy College of Engineering, Karur, India In power grid system power quality improvement plays an important role. Dual Voltage Source Inverter (DVSI) scheme is proposed to improve the aspects of Power and consistency of the micro grid system. Here we use Distributed Energy Resources (DER) for power exchange and unbalanced load compensation and nonlinear load in the system. Load sharing and power injections are done by grid interactive inverters in micro-grid. Based on Instantaneous Symmetrical Component Theory (ISCT), control algorithm is developed. For extraction of positive sequence voltage, dq0 transformation is done. An inverter connected to a 3- phase four- wire distribution combination is employed to test the managing strategy of the system. In this work we mainly focused on the assessment of overall performance of Proportional Integral (PI) controller and Fuzzy Logic Controller (FLC). Thus, the FLC provides increase in reliability, better performance of micro grid, less bandwidth requirements of inverters when compared to PI controller. The proposed system is validated by MATLAB simulation methods using PI controller and Fuzzy Logic Controller. 07 30 2019 827 832 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A1890.078219 https://www.ijrte.org/portfolio-item/A1890058119/ Assistant Professor, Department of Electronics and Communication Engineering, NSS College of Engineering, Palakkad. Kerala, India. (Research Scholar, University of Calicut) Anil Kumar K.R Dr. Meenakshy K Associate Professor, Department of Applied Electronics and Instrumentation Engineering, Government Engineering College, Kozhikode, Kerala, India Retinal vasculature extraction is an area of utmost interest in ophthalmology. It helps to diagnose various diseases and also play a crucial role in treatment planning and accomplishment.In this work, we suggest an algorithm to segment retinal vasculature from retinal Fundus Images(FI) using multi-structure element morphology after enhancing the image using Normal Inverse Gaussian (NIG) model in the fuzzified Non-Subsampled Contourlet Transform (NSCT) domain. Since both noises and weak edges produce low magnitude NSCT coefficients, image enhancement methods amplify weak edges as well as noises. Direct application of image boosting technique in the NSCT domain causes over enhancement. So a novel image enhancement method is employed by interpreting the term “contrast” as a qualitative instead of a quantitative measure of the image. Membership values of NSCT coefficients are modified using NIG model. Mathematical Morphology(MM) by Multi-structure Elements (MEs) is used to extract the edges of image. False vessel ridges are expunged, and the thin vessel edges are preserved using opening by reconstruction. Connected component analysis followed by length filtering is used to filter the still remaining false edges. In most of the available literature, low-resolution fundus image databases are used for evaluating the algorithm. In our work, we evaluate our algorithm not only utilizing the DRIVE database, a low-resolution retinal image (RI) database, but also using an openly available High-Resolution Fundus (HRF) image database. Our result illustrates that the proposed method outperforms the other techniques considered with average accuracy (ACC) of 96.71%. In addition to ACC, we also use F1-Score and Mathews Correlation Coefficient (MCC) to evaluate our method. The average values of the results obtained with the HRF image database for F1-Score and MCC are 0.8172 and 0.8031, respectively, which are very much encouraging. 07 30 2019 116 125 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.A1908.078219 https://www.ijrte.org/portfolio-item/A1908058119/ Assistant Prof (Sr.), SCSE, VIT University, Chennai. Nachiyappan S Justus S Associate Professor, SCSE, VIT University, Chennai. Big data is a new technology, which is defined by large amount of data, so it is possible to extract value from the capturing and analysis process. Large data faced many challenges due to various features such as volume, speed, variation, value, complexity and performance. Many organizations face challenges while facing test strategies for structured and unstructured data validation, establishing a proper testing environment, working with non relational databases and maintaining functional testing. These challenges have low quality data in production, delay in execution and increase in cost. Reduce the map for data intensive business and scientific applications Provides parallel and scalable programming model. To get the performance of big data applications, defined as response time, maximum online user data capacity size, and a certain maximum processing capacity. In proposed, to test the health care big data . In health care data contains text file, image file, audio file and video file. To test the big data document, by using two concepts such as big data preprocessing testing and post processing testing. To classify the data from unstructured format to structured format using SVM algorithm. In preprocessing testing test all the data, for the purpose data accuracy. In preprocessing testing such as file size testing, file extension testing and de-duplication testing. In Post Processing to implement the map reduce concept for the use of easily to fetch the data. 07 30 2019 2490 2494 CC-BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.B1912.078219 https://www.ijrte.org/portfolio-item/A1912058119/