S. Sujatha ¹, R. Anita ², P. Selvan ³, S. Selvakumar ⁴

Affiliations
1 TNEB, Karur, Tamilnadu, IN
2 Department of EEE, Institute of Road and Transport Technology, Erode, Tamilnadu, IN
3 Department of EEE, Erode Sengunthar Engineering College, Erode, Tamilnadu, IN
4 ABB Global Industries, Chennai, Tamilnadu, IN

Abstract

Main objective of the paper is to study the impact of SVC on stability and enhancing the power quality for a real time industrial system. Modified RK method is used for transient stability analysis and detailed frequency modeling is used for harmonic analysis. Real time system of 3.5 MTPA Steel plant at Raichur in Karnaraka, India with Electric Arc Furnace and Laddle Refining Furnace are considered for study. ETAP 12.6 software is used to simulate both transients and harmonic analysis. Harmonic study is performed with sinusoidal source non linear loads and Non sinusioidal source non linear loads. SVC performance when the non sinusoidal source is also verified to have the practical meaning. For Transient stability enhancement the controller tuning fault at 11V and 33KV bus is verified.

Keywords

Non-sinusoidal Source, Power Quality, SVC, Transient Stability Enhancement

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P. Parthiban ¹, S. Selvakumar ²

Affiliations
1 Computer Science and Engineering, Bharath University, Chennai - 600073,Tamil Nadu, IN
2 Computer Science and Engineering, GKM College of Engineering and Technology, Affiliated to Anna University, Chennai - 600063,Tamil Nadu, IN

Abstract

Objectives: The implementation of an Industry neutral architecture for an analysis on Big Data in the Internet of Things Platform. Methods/Statistical Analysis: The Outside temperature , Light and Humidity from weather station is monitered in dashboardand analyzed in ThingSpeak - Internet of Things Platform. The analysis on weather station data is performed using Matlab in ThingSpeak – Internet of Things Platform. Findings:To do a real time analysis of weather station data using ThingSpeak – Internet of Things Platform. Real time tracking of the attributes include dew point, temperature and humidity from the Arduino Sensor device which is installed on Weather Station. Application/Improvements: Internet of Things Platform broad network access allows investors/stakeholders to visualize the output of Data Presentation (Data Analytics, Data Visualization, BI reporting), easily from multiple locations and platforms, which can facilitate enterprise decision making and here we recommend solutions for the security and privacy issues in the Internet of Things Platform.

Keywords

Analyzing, Big Data, Internet of Things, Internet of Things Security,ThingSpeak.

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S. Selvakumar ¹, J. Vaideeswaran ¹

Affiliations
1 ECE Department, SCSVMV University, Kanchipuram - 631561, Tamil Nadu, IN

Abstract

Objectives: To develop an automatic modulation detection. Methods/Statistical Analysis: A single system having the antenna transmits and receives multiple signals. Autonomous modulation techniques avoid the multipath fading, delay and bandwidth limitation. Transmitter selects the modulation from group based on the receiver location and selected modulation gives maximum accuracy. Findings: This approach avoids the size limitation because of parallel relay terminal structure acceptance. This research work focuses on different set of modulation schemes in virtual logic channel implemented in low power consuming hardware and also be customized. Application/Improvements: Proposed work is a large number low power hardware used in more secured manner.

Keywords

FL2440, GNU, Modulation/Demodulation, Node/Network Security, WSN.

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P. Parthiban ¹, S. Selvakumar ²

Affiliations
1 Computer Science and Engineering, Bharath University, Chennai - 600073, Tamil Nadu, IN
2 Computer Science and Engineering, GKM College of Engineering and Technology, Anna University, Chennai - 600063, Tamil Nadu, IN

Abstract

Background/Objectives: To propose an Automated model to capture, store, analyze and visualize of Big Data. Methods/ Statistical Analysis: The web server logs are captured in real time and are stored into NoSQL database. The analysis on web server logs is performed using object-oriented language plus mongodb and finally the analyzed results are visualized in the R environment. Findings: To do a real time analysis of web server logs in data center using mongodb. Tracking of client location can be done using GeoIP. This GeoIP location information can be analyzed to find out the total number of visits from different country, real time information about server status of success, failure, warning and fatal errors. Real time updates of exact location of client who access sever and real time information of server status helpful to avoid repeating failure in a system. Application/Improvements: For the future work, we have planned to integrate our automated model with stream data processing system and to compare our proposed model with existing framework.

Keywords

Analyzing, Big Data, Capturing, Storing, Visualizing, Web Server Logs

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S. Selvakumar ¹, M. Mohanapriya ¹

Affiliations
1 Department of CSE, Karpagam University, Coimbatore - 641021, Tamil Nadu, IN

Abstract

Background/Objectives: The paper discusses about the data security issues in the cloud computing environment. It employs data masking to hide sensitive data from cloud services thereby ensuring reliability and trust in the cloud environment. Methods/Statistical Analysis: Data access in the cloud environment can be categorized into three such as at rest, at transit ,in use. The main aim of this paper is integrate security in data masking techniques. We employ the existing mechanisms to the cloud environment to secure the data with virtual machine masking and platform masking. Findings: The masked data is transmitted to the processing environment. The services in cloud utilize this masked data for processing. It is comparatively secured when compared to the conventional technique. This mechanism increases the trust worthiness and can be masked dynamically or statistically in application or database based service environments. Application/Improvements: The main application of this research is to serve people with secured cloud, thereby overcoming the data security issues.

Keywords

Cloud Environment, Cloud Service Provider, Data Masking.

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A. Sheik Abdullah ¹, S. Selvakumar ², P. Karthikeyan ¹, M. Venkatesh ³

Affiliations
1 Department of Information Technology, Thiagarajar College of Engineering, Madurai – 625015, Tamil Nadu, IN
2 Department of Computer Science and Engineering, G.K.M. College of Engineering and Technology, Chennai – 600063, Tamil Nadu, IN
3 Department of Medicine, Theni Government Medical College and Hospital, Theni – 625531, Tamil Nadu, IN

Abstract

The objective of this research work focus towards the identification of best variant between decision tree algorithm such as Weighted Decision Trees (WDT), C4.5 Decision Trees and C5.0. Methods: Decision tree has a number of variants such as ID3, Weight based decision tree, C4.5 and C5.0 algorithms. This research work focus towards the predictive performance analysis of weight based decision tree with information gain as the splitting criterion. The algorithm proceeds iteratively with the assignment of weights over the training instances to determine the best among the data attributes. Thereby, the attribute with best weight values can be significantly determined by an improvement over its accuracy. Results: The experimental results proves that among the variants of decision trees the algorithm corresponding to C4.5 provides the highest accuracy of about 71.42% and R2 value of about 0.265 respectively and for real world data the accuracy is about 48.69%. The effectiveness of the decision tree algorithm can be still improved by adopting certain feature selection techniques with the combination of decision tree algorithm. Conclusion: The determined results show that Decision tree algorithm suits well for medical data problems. The efficiency of the algorithm can still be improved by applying Decision Trees for various real world data problems such as Diabetes, Cancer classification with feature selection paradigms. But still a larger set of real world data has to be investigated.

Keywords

C4.5 Decision Tree Algorithm, Data Classification, Heart Disease, Predictive Analysis, Weighted Decision Tree,

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