Informatics Publishing Limited

V. Shanthi ¹, N. Gajendran ²

Affiliations
1 University of Madras, 1Dept. of Economics, Chellammal Women’s College, Guindy, Chennai-600 005, IN
2 University of Madras, C.A.S. in Botany, University of Madras, Chennai-25, IN

Abstract

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Saranya Mohanbaba ¹, V. Shanthi ², Subhashini Mohanbaba ³

Affiliations
1 Ramco Systems, Adyar, Chennai-600 020, IN
2 Department of Economics, Chellammal women’s College, Guindy, Chennai-600032, IN
3 State key Laboratory of Reproductive Biology, institute of Zoology, Chinese Academy of Sciences, Beijing 100101, CN

Abstract

E-waste is the fastest growing source of municipal waste on earth. The 21st century witnesses novel environmental challenges due to the advent of electronic goods in our day-to-day life. The disposal of e-waste directly into landfill without prior treatment poses a threat for ground water contamination. The present investigation is to find out the best way of safe disposal of electronic wastes. For this purpose, we used the data in the existing literature on various soil properties and a decision tree algorithm, which was applied to the respective soil factors and bifurcated to find out suitable soil type/ conditions for dumping e-waste in landfill. In bifurcation with parameters viz. pH, specific gravity, electric conductivity, organic matter, clayey/ silt percent and permeability, it is found that clayey soil is much preferred to dump the e-waste chemicals because leaching is less besides its metal retention capacity. The study also suggests a pre-treatment prior to disposal in landfill area may further reduce the environmental threat caused by the heavy metal leachates from e-wastes.

Keywords

E-waste, Landfill, Decision Tree Algorithm, Soils, Safe Disposal

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C. R. Bharathi ¹, V. Shanthi ²

Affiliations
1 Research Scholar, Sathyabama University, Assistant Professor, Department of ECE,, Vel Tech University, Avadi, Chennai, IN
2 Professor, Department of MCA, St. Joseph’s College of Engineering, Chennai, IN

Abstract

A wide range of researches are carried out in this field for denoising, enhancement and more. Besides the other, stress management is important to identify the spot in which the stress has to be made in speech. In this paper, in order to provide proper speech practice for the abnormal child (mentally retarded (MR) child), their speech is analyzed. Initially, the normal and abnormal children speech is obtained with the same set of words. As an initial process, the Mel Frequency Cepstrum Coefficients (MFCC) is extracted from both words and the Principal Component Analysis (PCA) is applied to reduce the dimensionality of the words. From the dimensionality reduced words, the parameters are obtained and then these parameters are utilized to train using Support Vector Machines (SVM) for classification. After identifying the acute word (abnormal word), through the thresholding operation and then FFT is computed for the acute word and these parameters made use of the Fuzzy Inference system (FIS) for blemishing the acute spot in which the aberration is occurred in the world where the speech practice is required for the abnormal child which helps speech pathologist.

Keywords

Speech Signal, Stress, Mel Frequency Cepstrum Coefficients (MFCC), Principal Component Analysis (PCA), Support Vector Machines (SVM), Fuzzy Inference System (FIS).

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V. Shanthi ¹, D. Somasundareswari ²

Affiliations
1 Department in Park College of Engineering and Technology, Coimbatore, IN
2 Department of Electronics of Communication Engineering, Adithya Institute of Technology, Coimbatore, IN

Abstract

In mobile scenarios, location dependent data can be provided by an infrastructure, or, in case an infrastructure is not available or feasible, by opportunistic networking among mobile devices populating the region of interest. Caused by node mobility, data availability within the region of interest relies on replication and forwarding techniques. Our approach associates data with a geo-address describing the Point of Interest (POI) of the data and proposes a decentralized al-gorithm for data dissemination. Mobile devices replicate data to increase data availability within a circular area around the POI. To avoid unnecessary communication overhead, the distributed algorithm Sector Heads Aided Flooding Technique (SHAFT) restricts the number of mobile nodes that forward data by arranging data placement geometrically in the area. Hereby, each mobile node decides whether to become a forwarding node based on its geo-location and the known scheme for data arrangement. Additionally, the algorithm adapts to the locally measured density of mobile de-vices in range. By applying the approach to a cooperative parking lot management system based on the Manhattan mobility model we demonstrate its usefulness. Simulation results are provided show-ing that SHAFT reaches similar data availability as flooding by re-ducing the number of packets transferred by a factor of up to newly created data and by up to 81:1% for data updates in scenarios of high node density.

Keywords

MANETs, Mobile Data, Geo-based Data Dissemination, Replication.

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C. R. Bharathi ¹, V. Shanthi ²

Affiliations
1 Sathyabama University, Chennai, IN
2 St. Josephs' College of Engineering, IN

Abstract

In this work, mild level of mental retardation (MR) children speech samples were taken for consideration. In the existing system, there are many effective treatments for the problem of stammering. Most of these involve making changes in the manner of speaking. They are conducted by speech and language pathologists by giving fluency in speech practice in general. The proposed work is, the acute spot must be identified for affording speech training to the speech disordered children. In this paper, still classification of speech is found. Initially Feature Extraction is implemented using Mel Frequency Cepstrum Coefficients (MFCC) for both words of normal and pathological subjects' speech. Dimensionality reduction of features extracted is implemented using Principal Component Analysis (PCA). Finally the features are trained using Top of Form Support Vector Machines (SVM) for classification.

Keywords

Speech Signal, Stammering, Mel Frequency Cepstrum Coefficients (MFCC), Principal Component Analysis (PCA), Trained.

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Magesh Kasthuri ¹, V. Shanthi ²

Affiliations
1 SCSVMV University, Kanchipuram, IN
2 Department of MCA, St. Joseph College of Engineering, Chennai, IN

Abstract

This article discusses the concept of Brain Theory, Organization of brain, Techniques behind Artifical Neural Network Recognition and various popular techniques used in Neural network based Patter recognition. The aim of to give idea on Brain theory and its relation and mapping to Artificial Neural Network (ANN) which can guide a Research study on 'Neural networks and Character recognition' to study different techniques used for character recognition and to list the differences between them, the inter-relation between them. Also, I would like to bring out the advantage of each technique with their area of specialization (how easy to use the specified technique for a specific requirement). This will help in easily identify the best suited Handwritten character recognition technique for any requirement (digitizing cheques, palm scripts/manuscripts, extract data from old documents to name a few).

Keywords

ANN-Artificial Neural Networks, Neurons-Unit of Brain for Processing Any Operation, ADLINE-Adaptive Linear Elements, Training-Method for Practicing Neural Network, VTA-Ventral Tegmental Area, ART-Adaptive Resonance Theory, PET-Positron Emission Tomography, LVQ-Learning Vector Quantization.

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V. Shanthi ¹, S. Lalitha ²

Affiliations
1 St. Joseph's College of Engineering, Chennai, IN
2 Mother Teresa Univeristy, Kodaikanal, IN

Abstract

News article generation is very easy by using lexical chains. The news stories have to be prepared within a very short time. Time plays a prominent role in the production of news story. The information gathered from the places needed to be converted into news stories within a very short time. This preparation of news stories were so far done by the editors with lots of efforts. The artificial intelligence and natural language processing are the effective tools which is s successful in manipulating and creating text messages. JLexNews system generates the efficient and effective article with exact texts. It also identifies the statistical word association and gloss definitions for the creation of lexical chains. This system will be very useful for news article generations.

Keywords

Automatic Text Generation, Gloss Definition, Lexical Chains, Statistical Word Association.

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V. Shanthi ¹, S. Lalitha ²

Affiliations
1 St.Joseph's College of Engineering, Old Mahabalipuram Road, Chennai, Tamilnadu, IN
2 Sathyabama University, Old Mahabalipuram Road, Chennai, Tamilnadu, IN

Abstract

Lexical chains are defined as clusters of semantically related words. For the Text Generation the lexical chain are very important and the lexical chains are created using the WordNet database. The aim of this paper is to finds the new relation such as statistical word associations for the lexical chaining process. The statistical word associations represents an additional type of lexical cohesive relationship that is not found in WordNet. The architecture also recognizes the gloss definitions which identifies the relations between two concepts not directly related.

Keywords

Lexical Chaining, Extended Wordnet, Statistical Word Association, Gloss Definition.

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G. Malathi ¹, V. Shanthi ², V. R. Bhupathi Raju ¹

Affiliations
1 Department of Computer Applications, Velammal Engineering College, Affiliated to Anna University, Chennai, IN
2 Department of Computer Applications, St. Joseph College of Engineering, Affiliated to Anna University, Chennai, IN

Abstract

Gestational Diabetes Mellitus is a condition in pregnant women that affects the normal fetal growth and complicates the development of placenta. This study uses the ultrasound placenta images to calculate the volume of placenta. The large placentas are normally indications of gestational diabetes mellitus. Evaluation of the volume of placenta during the routine ultrasound scan can identify placenta complicated by diabetes mellitus. Placental volume is calculated using the linear measurements of placental thickness, height and width using the concave-convex Hull formula. Based on these measurements the placenta can be classified as normal or abnormal placenta. The abnormal placenta is further classified into placenta complicated by Gestational Diabetes Mellitus and the placenta complicated by other reasons. The estimation of placental volume can identify the fetal risk in conditions of gestational diabetes mellitus. This would help to diagnose the complications at the earliest which would minimize the fetal loss, birth defects and placenta abruption.

Keywords

Placenta, Ultrasound, Linear, Volume, Gestational Diabetes Mellitus, Thickness, Height, Width, Concave-Convex Hull, Haralick Features.

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Usha Chandrasekhar ¹, G. Geetha ¹, V. Shanthi ¹

Affiliations
1 Sri Avinashilingam Home Science College for Women, Coimbatore 641 043, IN

Abstract

Specialists from the world over agree that the basic cause of coronary heart disease is atherosclerosis, which results from a series of changes in the intima of arteries caused by total accumulation of fatty material and fibrous tissue, disrupting its normal architecture. The risk of developing coronary heart disease is positively correlated with the level of serum cholesterol, which can be successfully reduced or controlled by dietary modifications alone. Dietary protein has been recognised for its ability to alter plasma cholesterol levels. While few studies have been reported to evaluate the effect of pulses on serum cholesterol levels the effect of processed legumes need a great deal of exploration. The present study was undertaken to evaluate the effect of raw and roasted Bengal grahi in lowering the serum cholesterol and triglyceride level and histopathological alterations of the heart, aorta and liver on albino rats.

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E. Manigandan ¹, V. Shanthi ², Magesh Kasthuri ¹

Affiliations
1 SCSVMV University, Enathur, Kanchipuram-631561, Tamil Nadu, IN
2 Department of MCA, St. Joseph’s College of Engineering, Chennai – 600119, Tamil Nadu, IN

Abstract

Objectives: Clustering algorithm is broadly used as spectral algorithm in social media, where a reference of contact is used and mined further for various combinations of suggested friends and lookups. This paper Identifies key lead generation techniques to be used in customer relationship management for sales marketing to decide data gathering. Also to define key merits and demerits of these techniques and to prepare a Matrix of comparison of these techniques to justify the data source and data set. M-Cluster algorithm is used for lead qualification i.e. training set preparation and data evaluation. Methods: Todefine a training set based on various attributes/fields in the data given for classification. This training set is used to run the data process and to produce expected result. This is assessed and accepted for definite data set processing or additional run for interim training data set preparation. Findings: This study is taken to customize clustering algorithm for data mining process in a customer relationship management field as the space of data is more and variant. Also proving the usability of customized clustering algorithm in data mining and the efficiency in processing mechanism compared to other methods used in current situation of data mining in customer relationship management is the part of this study. The customized algorithm developed as part of this study considers the two major areas of data mining using clusters. Applications: The results produced tremendous trends that the clustered algorithm suits to any data mining process when scaling and data classification are diversified and less in control.

Keywords

Classification, Clustering Algorithm, Data Mining, K-Means, Lead Generation, M-Clustering Algorithm.

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L. Rajesh ¹, V. Shanthi ², V. Lakshmi Narasimhan ³

Affiliations
1 Department of CSA, SCSVMV University, Enathur, Tamil Nadu, IN
2 Department of MCA, St. Joseph’s College of Engineering, Chennai, IN
3 Department of Computer Science & Engineering, RGMCET, Andhra Pradesh, IN

Abstract

Objectives: To develop a suitable model to study the behavior of web crawled dataset and perform simulation on the modeled data for better understanding of the system Methods/Statistical Analysis: M/M/1 model is a variation of Single Birth Single Death (SBSD) model which is applied to study the behavior of web crawled dataset for the Classification Problem. KanchiCrawler, a stylized focused web crawler is implemented to collect the data for this application. The size of the corpora (Population) is 500k. Control corpus (sample) can be drawn from the corpora based on enforcing certain pre-determined conditions. Findings: A 20-state model starting with an initial test corpus of 25k and then by gradually increasing with an increment of 25k up to 500k is developed. This is achieved through the computation of Forward State Transition Probability and Reverse State Transition Probability for the respective states. This model provides fairly good results by testing the algorithmic efficiency of a KanchiCrawler and to model the web crawled dataset for the classification problem. Applications: M/M/1 models are tractable and often used to model various operations of nature. In most situations where large numbers are involved, M/M/1 model are statistically stable and reflective of reality.

Keywords

Dataset Modeling, KanchiCrawler, M/M/1 Model, State Transition Probability.

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R. Sonia ¹, V. Shanthi ²

Affiliations
1 Sathyabama University, Chennai - 600119, Tamil Nadu, IN
2 St Joseph’s College of Engineering, Chennai - 600119, Tamil Nadu, IN

Abstract

Objectives: Nuchal Translucency (NT) thickness measurement is a Down syndrome marker for chromosomal abnormalities which is detected by non-invasive test during first trimester. Methods: In this paper, a computerized method to measure NT thickness is proposed. It consists of region of interest extraction, NT segmentation using morphological operation with Otsu thresholding. The NT thickness is measured from the segmented area. The performance is analyzed on 80 ultrasound fetal images. Findings: Proposed approach for NT measurement is implemented in MATLAB software. Experimental results show that NT thickness for normal foetus is 1.99±.62 mm and abnormal foetus is 4.10±.90 mm during first trimester of pregnancy from 11 to 13+6 weeks of gestation. The proposed algorithm efficiently computes NT measurement and produces consistent result during first trimester in singleton pregnancies. Applications/Improvements: Proposed semi-automated technique helps the medical sonographer for accurate NT thickness measurement to detect Down syndrome marker during first trimester ultrasound scan.

Keywords

Down Syndrome, Morphological Operation, Nuchal Translucency, Trimester, Thresholding.

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V. Shanthi ¹, Jemima Florence Borgia ², S. Bhavani ², M. Sathya ²

Affiliations
1 P.G. Department of Zoology, Jayaraj Annapackiam College for Women (Autonomous), Periyakulam-625 601, Tamil Nadu, IN
2 P.G. Department of Zoology, Jayaraj Annapackiam College for Women (Autonomous), Periyakulam-625 601, Tamilnadu, IN

Abstract

The influence of Lactobacillus strains (L.fermentum, L.brevis, L.plantarum, L.curvatus, L.vulgaricus, L.casei, L.acidophilus and L.lactis) on the inactivation of human pathogens (Staphylococcus aerians, Salmonella typhi, S.paratyphi, Klebsiella oxytoca, Pseudomonas aeruginosa , Vibrio parahaemolyticus, Proteus mirabilis, Lactobacillus vulgaris, Vibrio cholerae and Shigella flexneri) were investigated. Strong antibacterial activities were exhibted on the plates inoculated in the Shigella flexneri by L.curvatus, L.plantarum and Proteus mirabilis and Pseudomonas aeruginosa by L.vulgaricus. L.plantarum showed broad spectrum of antibacterial activity against all tested pathogens. A weak inhibitory effect was detected in L.brevis on Vibrio parahaemolyticus and L.fermantum on L.vulgaris and S.typhi.

Keywords

Lactobacillus, Test Pathogens, Antibacterial.

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