Informatics Publishing Limited

R. Saranya ¹, K. Balamurugan ¹, M. Karuppasamy ²

Affiliations
1 School of Electrical & Electronics Engineering, SASTRA University, Thanjavur, IN
2 Department of Electrical Engineering, Anna University, Tiruchirapalli, IN

Abstract

Congestion Management is major issue in deregulated environment. The goal of congestion management is to alleviate overloads by generator rescheduling and/or load curtailments. Here, congestion is relieved by real power rescheduling employing Artificial Bee Colony algorithm. It comprises of two stages. First stage, Generator Sensitivity Factors (GSF) for the congested line is evaluated. Then, Artificial Bee Colony algorithm is used in the second stage for obtaining minimum values of generator power outputs after rescheduling. The efficacy of this algorithm has been tested on IEEE-30 bus system and four test cases are taken here and programming is developed using MATLAB software.

Keywords

Congestion Management, Contingency Analysis, Deregulation, Generator Sensitivity Factor.

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R. Saranya ¹, S. Muthumani ¹

Affiliations
1 Sathyabama University, Chennai, IN

Abstract

This empirical research paper deals with study of the cultural diversity in workplace of women employee working in the selected IT industries in Chennai city. Cultural diversity has a major impact on technical professionals since they have to interact more with people of different culture. This study aims to focus on the various cultures existing in selected IT industries in Chennai city and its impact on women employees. To measure the impact of cultural diversity on women employees working in IT sector a set of questionnaire were farmed. The data were collected by using convenience sampling from 90 women employees working in the different parts of the Chennai City. Using the SPSS, some of the relevant tests were carried out like reliability test, ANOVA and regression. Based on the analysis made, various findings were derived that will be useful, relevant and significant to find the impact of cultural diversity on women employees working in the selected IT companies in Chennai city.

Keywords

Cultural Diversity, It Companies, Organizational Culture, Women Employees.

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R. Saranya ¹, M. Jaikumar ²

Affiliations
1 Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore-641020, Tamilnadu, IN
2 Dept of Computer Applications (UG), Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore-641020, Tamilnadu, IN

Abstract

Determining road accident and provoke of the road occasion in every area is important for road safety enlargements. Earlier spatial immersion procedures did not concede the cause and asperity levels of road accidents. Applying Data-Driven Methods to ROAD Safety (DDMRS) can aid police departments designate resources more effectively. By lime-lighting on risky block, highly visible traffic law enforcement coincidently can diminish crashes. Most studies have focused on crunches after appealing new patrol paths, but few have archived how to progress or change police report time. To drastically reduce fatalities and serious cramps on roads, the ability need to review the appearance and cause of road accidents and classify the hidden information's behind the accidents using previous chronicles. For these analyses the raw data is not sufficient, so implementation of effective data excavating is obligatory.
With the use of data mining method such as decision trees will help to discover a best remedy for every scrutiny. The contemplated system familiarizes a road accident classification model. In the scheme, the system first mine associations rules of the crash data, and the detected rules will be build the decision tree named as "SDT" spatial Decision Tree, which is based on the consolidation of association rule and ID3 algorithms. Using these approaches the road accident data can be induced. And finally, the cause for the accident will be recognized for the desired effort.

Keywords

Road Accident Scrutiny, Methodology, SDT.

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M. Jaikumar ¹, R. Saranya ²

Affiliations
1 Dept. of Computer Applications (UG), Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore-641020, Tamilnadu, IN
2 Sri Ramakrishna Mission Vidyalaya College of Arts and Science, Coimbatore-641020, Tamilnadu, IN

Abstract

The cynosure of this paper is to fetch the important significance of Web Content Mining. The paper gives a vision into its functions, methods and its efforts in the current business environment as well in research extracting contents for day to day purpose. It also explicates how to use web content mining and how it plays an entity role by getting precious set of volumes and uses those contents in the judgment making in the cluster situation, literacy and scrutinize.

Keywords

Web Content Mining Techniques, Process of Mining.

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R. Saranya , R. Sathya , R. M. Umaiyal , P. Kanmani

Abstract

This paper will document the relationship between the consumer and their behaviors. Using this technique the consumers can use the web to find the information about the product and services. Ontologism can be constructed manually using ontology but the process can be tedious. The integration of knowledge acquisition with machine learning facilitates research toward automating the ontology generation process. Many approaches have been investigated for generating ontology. These include Natural Language Processing (NLP) techniques association rule mining hierarchical clustering translation from relational databases and Formal Concept Analysis. However these techniques focus mainly on constructing concept hierarchies from text documents or relational databases. They can also be used to find groups of people with similar interests. A major problem of traditional association rule mining techniques is that each item in a transaction is considered only to either exist or not. Thus, the user's preference and interest in each transaction item cannot be precisely represented. Since the concepts of preference and interest are fuzzy data fuzzy logic can be applied. For example combine fuzzy association rule mining and case-based reasoning (CBR) to improve the quality of web access pattern prediction. The fuzzy rule set was found to perform better in prediction accuracy and rule coverage than traditional rule set.

Keywords

Behavioral Tracking, Semantic Web, Knowledge Integration, Natural Language Processing.

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R. Saranya ¹, B. Arunkumar ¹

Affiliations
1 Karpagam University, IN

Abstract

Search queries on databases, and often it return a large number of results, only a small subset of result are relevant to the user. Ranking and categorization, which can also be combined, have been proposed to alleviate this information overload problem. Results categorization for databases is the focus of this work. In this paper, we present the system is a novel search interface that enables the user to navigate large number of query results by organizing them using the concept hierarchy. First, the query results are organized navigation tree. Inside the navigation tree edge cut operation is performed. The query results returns the two set of results that is relevant to the user and ignore results. At each node expansion step, this system of results reveals only a small subset of the concept nodes, selected such that the expected user navigation cost is minimized. In contrast, previous works expand the hierarchy in a predefined static manner, without navigation cost modelling. We show that the problem of selecting the best concepts to reveal at each node expansion and propose an efficient heuristic as well as a feasible optimal algorithm for relatively small trees.

Keywords

Information Retrieval, Navigation, Search Process.

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R. Saranya ¹, K. Tamilarasan ¹, N. Peatciyammal ¹, Rajamaniccam L. Sai ², M. Dharmendira Kumar ²

Affiliations
1 Department of Biotechnology, Madha Engineering College, Chennai 600069, IN
2 Department of Chemical Engineering, Alagappa College of Technology, Anna University, Chennai 600025, IN

Abstract

A Response Surface approach has been used to study the production of an extracellular lipase from Bacillus species. This research paper mainly focused on developing a media component and physical parameters for lipase production by Central Composite Design (CCD).Interaction were studied for four different factors are olive oil concentration, ammonium sulphate concentration, pH and Temperature. By using the statistical approach (Response Surface Methodology) the optimum enzyme activity of 8.69 IU/ml was predicted when olive oil concentration 1.5%, ammonium sulphate concentration 0.4%, pH 8, Temperature 40ºC.

Keywords

Central Composite Design, Lipase Activity, Maximum Yield, Response Surface Methodology, Statistical Approach.

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R. Saranya ¹, S. Gowri ¹, S. Monisha ¹, S. Vigneshwari ¹

Affiliations
1 Department of Information Technology, Sathyabama University, Chennai, IN

Abstract

Objective: The tremendous growth in volume of data is increasing the complexity of data handling. The existing content based search is not only complex and expensive, but also leads to poor processing and unacceptable latency for massive amount of data. Data accessed from large dataset using existing approach will slow down the query response rate. High resource cost is the severe performance bottleneck caused by query operations. The semantic based search can be carried out on the data, In order to reduce the complexity in data handling. The proposed method uses Resource Description Framework (RDF) with Ontology Web Language (OWL). Thus the RDF is used for non domain based search and OWL is used for domain based search. The non domain based search provides the composition of best data services from master RDF. The triplets from different RDF are combined to form master RDF. And the domain based search is one which provides recommendations for the user based on their search query. The main objective of this approach is to provide semantic search using RDF and recommendation using OWL. The search result will be the high similarity result sets as the method uses the combinational RDF to form large master RDF. Statistical Analysis/Methods: The user is provided with two methods of searching which is domain based search and non domain based search. The domain based search is one which provides recommendation for the user based on the search query. And the non domain based search originates the data services from master RDF. Agriculture data set is chosen as a sample data set for domain based search which can be extended further for any other domain. The web services which contain general information about the world and also related web services is chosen as a data set for non domain based search. Findings: The statistical analysis of ontology based semantic search with keyword based search produced the precision value of 0.8 out of 1.0 using the search results obtained from both semantic search and keyword based search. Applications/Improvements: The application can be further improved by adding realistic data sets and increasing the size of the database. The domain based approach is not restricted only to agriculture but it can also be extended to some other applications like Health care, pattern recognition and so on.

Keywords

Correlation, Data Services, Domain, Hazy Semantics, Ontology, Triplets.

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S. Monisha ¹, R. Saranya ¹, K. Vijay ¹

Affiliations
1 Department of Information Technology, Sathyabama University, Chennai – 600119, Tamil Nadu, IN

Abstract

Objective: The people all over the world are in need of gaining knowledge which is achieved by means of searching information through web services. Even though search results obtained from web services are relevant, the user is trying to obtain the best information providers. Methods: The existing approaches which is non-parametric generative model and infinite Hidden Markov Model (iHMM) of clustering technique does not yield better results for very large collections of web services. The iHMM model does not provide any security for datasets in a hierarchal structure. Thus to overcome such downsides of existing approach to a new technique can be used to help of Natural Language Processing (NLP). Findings: The new approach provides both tag recommendation and parental control. The tag recommendation is used to ping the best tags based on expert’s bookmarks, and parental control provided by group owner is used to resolve the privacy issues. The web filter denies the unauthorized access. Thus, using NLP technique in the conspiring environment enables the web user to achieve fine grained knowledge. Applications: The paper defines the efficient way to provide tag recommendation on the web for large dataset users.

Keywords

Bookmarks, NLP, Tag Recommendations, Tag Suppression, Text Mining, Web Services.

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P. Arumugam ¹, R. Saranya ¹

Affiliations
1 Department of Statistics, Manonmaniam Sundaranar University, IN

Abstract

Technical analysis is based on the assumption that the future price of a stock can be predicted from its history. Several technical trading systems exist for generating buy and sell signals in stock prices. Simple moving average crossovers are popular tools for trading. In this study, simple moving average crossovers with different periods are analyzed empirically on historical daily data of NIFTY 50 index. The profit and loss distribution in these trades are studied to identify profitable and stable crossover periods. The choppy price action known as whipsaws incur large number of small losses in the crossover based trading system. The phenomenon of rare trending price movements and its impact on the trading system are demonstrated.

Keywords

Stock Trading, Simple Moving Average, SMA Crossover, NIFTY 50, National Stock Exchange.

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R. Mahalakshmi ¹, R. Saranya ¹

Affiliations
1 VIT University, Vellore, IN

Abstract

Requirements management is a critical and essential phase for the delivery of the product to be successful. The requirements can be called as user needs or desired feature for a product. So, only with well defined requirements, the products can achieve success. To collect well defined requirements and to manage the specified requirements we make use of requirements management tools. The objective of this paper is to present the comparative study on different requirements tools that are available and to determine the most essential tool.

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R. Saranya ¹, R. Rajendra Kumar ¹

Affiliations
1 Department of Management Studies, Dr. N.G.P. Institute of Technology, Coimbatore, Tamil Nadu, IN

Abstract

The Budget is a financial statement of the country which describe the status of economy by considering twin factors of expenditure and Revenue. It occupies significant position in the minds of people as the budget either directly or indirectly affect the livelihood of them. In those lines, the Budget 2017 assumes importance as this document comes with the integration of railway budget that too in the post demonetization period and also at the time of Government is mulling over on implementation of GST. Some of the experts categorized this budget as an extraordinary and novel while others doesn't find any radical aspects with respect to growth of GDP and elimination of poverty etc. This document analyse the various aspects of budget in an nutshell form to make the people to understand its inherent concepts.

Keywords

Fiscal Deficit, GDP, Demonetization, Net Market Borrowing, Income Tax.

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V. Mareeswari ¹, R. Saranya ¹, R. Mahalakshmi ¹, E. Preethi ¹

Affiliations
1 Department of Software Engineering, School of Information Technology and Engineering, VIT University, Vellore, IN

Abstract

Diabetes mellitus is one of the world's major diseases. Millions of people are affected by the disease. The risk of diabetes is increasing day by day and is found mostly in women than men. The diagnosis of diabetes is a tedious process. So with improvement in science and technology it is made easy to predict the disease. The purpose is to diagnose whether the person is affected by diabetes or not using K Nearest Neighbor classification technique. The diabetes dataset is a taken as the training data and the details of the patient are taken as testing data. The training data are classified by using the KNN classifier and secondly the target data is predicted. KNN algorithm used here would be more efficient for both classification and prediction. The results are analyzed with different values for the parameter k.

Keywords

Data Mining Techniques, K Nearest Neighbor, Prediction of Diabetes, Classification, UCI Repository.

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R. Saranya ¹, S. Saravana Kumar ¹, R. Baskaran ¹, A. Vinidha Roc ¹, K. Sathiyasekar ¹

Affiliations
1 Department of EEE, S.A. Engineering College, Chennai, Tamilnadu, IN

Abstract

The Brushless Direct Current (BLDC) motors are one of the motor types that is gaining rapid popularity. Its major appliances include refrigerators, washing machines, vacuum cleaners, freezers, etc. As the name implies, BLDC motors do not use brushes for commutation; instead, they are electronically commutated. This paper proposes a new optimized technique for the Sensorless operation of permanent magnet brushless direct current (BLDC) motor, which is based on back Electro Motive Force (back EMF), Zero Crossing Detection (ZCD). This proposed commutation technique of BLDC motor significantly reduces sensing circuits and cost of motor drive.

Keywords

Back Electromotive Force (EMF), Brushless DC (BLDC) Motor, Sensorless Control, Zero Crossing Detection.

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P. Sadhasivam ¹, S. Kavitha ¹, R. Saranya ¹

Affiliations
1 Department of Management, PSGR Krishnammal College for Women, Coimbatore - 641004, Tamil Nadu, IN

Abstract

Objectives: Healthcare plays a vital role in every woman for their healthy long life. Government healthcare schemes are very essential to the people who are not availing the facilities offered by private hospitals. Therefore the purpose of the present study is to investigate the impact of promotional campaigns on utilization of government healthcare schemes among rural women in Coimbatore.

Research Methods: 125 women respondents are selected for this study using proportionate stratified random sampling method. Data were collected through questionnaires. The collected data were analyzed with simple percentage, multiple regression and chi-square tests.

Findings/Results: Results revealed that 41.6% of the variance of utilization was explained by the factors of promotional campaigns and demographic variables like type of family, education, occupation and income were significant relationship with utilization of government healthcare schemes.

Conclusion/Recommendations: The government should promote the healthcare schemes through Television for better reach and government should encourage the volunteers like NGO’s, lines club and many welfare associations to promote the government healthcare schemes for better reach and utilization. This study recommends that the government should concentrate more on the promotional campaigns for better utilization of government healthcare schemes by educated low-income women in rural Coimbatore.

Keywords

Coimbatore, Government Healthcare Schemes, Promotional Campaigns, Rural Women, and Utilization.

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G. R. Hemanth ¹, M. Jayasree ¹, S. Keerthi Venii ¹, P. Akshaya ¹, R. Saranya ¹

Affiliations
1 Department of Electrical and Electronics Engineering, PSG Institute of Technology and Applied Research, IN

Abstract

At present most of the scripts are handwritten due to the ease of using a pen tip in place of a keyboard, hence errors are common due to illegibility of the human handwriting. To avoid this problem handwriting recognition is essential. Offline handwritten Text recognition (OHTR) has become one of the major areas of research in recent times because of the need to eliminate errors due to misinterpretation of handwritten text and the need for automation to improve efficiency. The application of this system can be seen in fields like handwritten application interpretations, postal address recognition, signature verification, and various others. In this project, offline handwritten Text recognition is performed using Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) which uses the architecture of Recurrent Neural network (RNN) and Connectionist Temporal Classification (CTC). The neural network is trained and tested using the IAM database containing handwritten English text. The implementation of this work is done using image segmentation-based handwritten text recognition where OpenCV is used for performing image processing and TensorFlow is used for training and text recognition. This whole system is developed using python and the output is displayed in a word file.

Keywords

Offline Handwritten Text Recognition, Convolutional Neural Network, Recurrent Neural Network, Connectionist Temporal Classification, Long Short-Term Memory.

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