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Shanthi, V.
- The Impact of Water Pollution on the Socio-economic Status of the Stakeholders of Ennore Creek, Bay of Bengal (India): Part I
Abstract Views :355 |
PDF Views:306
Authors
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
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
Source
Indian Journal of Science and Technology, Vol 2, No 3 (2009), Pagination: 66-79Abstract
No AbstractReferences
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- Jayaprakash M, Srinivasalu S, Jonathan MP and Mohan V (2005) A baseline study of physicochemical parameters and trace metals in water of Ennore Creek, Chennai, India. Marine Pollution Bullettin. 50 (5), 583-589.
- Kamala Kannan S, Lee KJ, Krishnamoorthy R, Purusothaman A, Shanthi K and Rajeshwara Rao (2007) Aerobic chromium reducing Bacillus cereus isolated ffrom the heavy metal contaminated Ennore Creek sediment, North of Chennai, Tamilnadu, South East India. Res.J.Microbiol. 2(2), 130-40.
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- Application of Decision Tree Algorithm in E-waste Land Filling
Abstract Views :566 |
PDF Views:0
Authors
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
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
Source
Indian Journal of Education and Information Management, Vol 1, No 1 (2012), Pagination: 40-48Abstract
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 DisposalReferences
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- Renewing E-waste, (2011). Accessed from: http://www.thehindu.com/opinion/editorial/article212950 5.ece. 30th June 2011.
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- TBC Recycler and Auctioneer, (2010). Accessed from: http://www.tbcrecycling.com/IT_Recycling_Overview.ht ml on 15 july 2011.
- Nokia launches e-waste management initiative, (2008). Accessed from: http://www.livemint.com/2008/12/311 73330/Nokia-launches-ewaste-managem. html on 1st july 2011.
- Texas Campaign for the Environment, (2011). Accessed from: http://www.texasenvironment.org/ewaste_dell.cfm on 16 july 2011.
- Samsung introduces Samsung Take back and Recycle (STAR) Program in India, (2010). Accessed from:http://www.knowyourmobile.in/news/814852/sams ung_introduces_samsung_takeback_and_recycle_star_pr ogram_in_india.html on 20 july 2011.
- Take-back and recycling, (2009). Accessed from : http://www.lg.com/global/sustainability/environment/tak e-back-recycling.jsp on 1st August 2009
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- Electronic Industries Alliance, (2000). The Evaluation of Materials used in Personal Computers accessed from: http://www.oecd.org/dataoecd/44/46/2741576.pdf
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- Arno Kaschl, Volker Romheld and Yona Chen. (2001). The influence of soluble organic matter from municipal solid waste compost on trace metal leaching in calcareous soils Isreal.
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- Ruiz-Labrador B, Coz A, Cifrián E, Galán B and Andrés A. (2011). Management of hazardous waste on sustainable landfills: Influence of the compaction of stabilised/solidified metallic waste on the leaching characteristics. Accessed from: http://www.iswa.org/ uploads/tx_iswaknowledgebase/20-259paper_long.pdf
- Spotting the Aberration Spot in a Speech with the Aid of Fuzzy Inference System
Abstract Views :401 |
PDF Views:65
Authors
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
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
Source
Indian Journal of Innovations and Developments, Vol 1, No 12 (2012), Pagination: 795-802Abstract
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).References
- Bharathi CR., Shanthi V, (2011). Classification of speech for Clinical Data using Artificial Neural Network. IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 6, No 1, November 2011 ISSN (Online): 1694-0814
- Bharathi CR., Shanthi V, (2012). Disorder Speech Clustering For Clinical Data Using Fuzzy C-Means Clustering and Comparison With SVM classification. Indian Journal of Computer Science and Engineering (IJCSE), Vol. 3, No.5
- Bharathi, CR., Shanthi V, (2012). Discriminant Analysis of Disorder Speech For Clinical Data. European Journal of Scientific Research, Volume 90.
- Bharathi CR., Shanthi V, (2012). Disorder Speech Classification for Clinical Data using SVM”, National Conference, IETE.
- Bharathi CR., Shanthi V, (2011). Finding acute Peaks and Amplitudes of Speech for Clinical Data using FFT. ICACM, International conference,
- Elseiver – 2011
- Bharathi CR., Shanthi, V, (2011). MFCC Feature Extraction Algorithm for Clinical Data. NCCCES’11, pp. 103-106.
- Bharathi CR., Shanthi V, (2011). Feature Extraction using MFCC and Survey on Classification Algorithms for Clinical Data. International Conference on Computer Science Engineering CSE – 2011
- Bharathi CR., Shanthi V, (2012). Survey on Objective Assessment of Stuttered Speech Signal for Disabled Children. International Conference on Cloud Computing and eGovernance.
- Bharathi CR., Shanthi V, (2012). An Effective System for Acute Spotting Aberration in the Speech of Abnormal Children Via Artificial Neural Network and Genetic Algorithm. American Journal of Applied Sciences 9 (10): 1561-1570.
- Sven Nordholm, Thushara Abhayapala, Simon Doclo, Sharon Gannot, Patrick Naylor and Ivan Tashev, (2010). Microphone Array Speech Processing. EURASIP Journal on Advances in Signal Processing. pp. 1-3, 2010
- Marius Crisan, (2007). Chaos and Natural Language Processing. Acta Polytechnica Hungarica, Vol. 4, No. 3, pp. 61-74.
- Rashad, Hazem M. El-Bakry and Islam R. Ismail (2010). Diphone Speech Synthesis System for Arabic Using MARY TTS. International journal of computer science & information Technology (IJCSIT), Vol. 2, No. 4, pp. 18-26.
- Stelzle, Ugrinovic, Knipfer, Bocklet, Noth, Schuster, Eitner, Seiss and Nkenke, (2010). Automatic, computer-based speech assessment on edentulous patients with and without complete dentures - preliminary results. Journal of Oral Rehabilitation, Vol.37, No. 3, pp. 209-216.
- A Metropolitan Geo Tracking based Opportunistic Data Dissemination for MANETS
Abstract Views :368 |
PDF Views:3
Authors
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
1 Department in Park College of Engineering and Technology, Coimbatore, IN
2 Department of Electronics of Communication Engineering, Adithya Institute of Technology, Coimbatore, IN
Source
Digital Signal Processing, Vol 3, No 2 (2011), Pagination: 69-76Abstract
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.- Disorder Speech Classification for Clinical Data Using SVM
Abstract Views :158 |
PDF Views:3
Authors
C. R. Bharathi
1,
V. Shanthi
2
Affiliations
1 Sathyabama University, Chennai, IN
2 St. Josephs' College of Engineering, IN
1 Sathyabama University, Chennai, IN
2 St. Josephs' College of Engineering, IN
Source
Data Mining and Knowledge Engineering, Vol 4, No 6 (2012), Pagination: 318-321Abstract
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.- Techniques in Neural Network Recognition and its Relation to Brain Theory
Abstract Views :156 |
PDF Views:4
Authors
Affiliations
1 SCSVMV University, Kanchipuram, IN
2 Department of MCA, St. Joseph College of Engineering, Chennai, IN
1 SCSVMV University, Kanchipuram, IN
2 Department of MCA, St. Joseph College of Engineering, Chennai, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 4, No 7 (2012), Pagination: 459-465Abstract
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.- An Empirical Study and Analysis of Automatic Text Generation Process
Abstract Views :211 |
PDF Views:3
Authors
V. Shanthi
1,
S. Lalitha
2
Affiliations
1 St. Joseph's College of Engineering, Chennai, IN
2 Mother Teresa Univeristy, Kodaikanal, IN
1 St. Joseph's College of Engineering, Chennai, IN
2 Mother Teresa Univeristy, Kodaikanal, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 4, No 4 (2012), Pagination: 198-201Abstract
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.- Automatic Text Generations Using Lexical Chaining
Abstract Views :193 |
PDF Views:5
Authors
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
1 St.Joseph's College of Engineering, Old Mahabalipuram Road, Chennai, Tamilnadu, IN
2 Sathyabama University, Old Mahabalipuram Road, Chennai, Tamilnadu, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 3, No 8 (2011), Pagination: 504-508Abstract
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.- Volume Estimation and Classification of Ultrasound Placenta Using Neural Network
Abstract Views :182 |
PDF Views:2
Authors
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
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
Source
Artificial Intelligent Systems and Machine Learning, Vol 3, No 2 (2011), Pagination: 90-95Abstract
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.- Effect of Raw and Roasted Bengal Gram on Some Physiological Parameters in Albino Rats
Abstract Views :179 |
PDF Views:2
Authors
Affiliations
1 Sri Avinashilingam Home Science College for Women, Coimbatore 641 043, IN
1 Sri Avinashilingam Home Science College for Women, Coimbatore 641 043, IN
Source
The Indian Journal of Nutrition and Dietetics, Vol 20, No 2 (1983), Pagination: 40-45Abstract
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.- Customized M-clustering Algorithm Comparison with Clustering Algorithms in Data Mining with the Case Study of Lead Generation Techniques
Abstract Views :178 |
PDF Views:0
Authors
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
1 SCSVMV University, Enathur, Kanchipuram-631561, Tamil Nadu, IN
2 Department of MCA, St. Joseph’s College of Engineering, Chennai – 600119, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 38 (2016), Pagination: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.- An M/M/1 Based Modeling Approach for the Web Crawled Data
Abstract Views :170 |
PDF Views:0
Authors
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
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
Source
Indian Journal of Science and Technology, Vol 9, No 35 (2016), Pagination: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.- Early Detection of Down Syndrome Marker by Measuring Fetal Nuchal Translucency Thickness from Ultrasound Images during First Trimester
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Authors
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
1 Sathyabama University, Chennai - 600119, Tamil Nadu, IN
2 St Joseph’s College of Engineering, Chennai - 600119, Tamil Nadu, IN
Source
Indian Journal of Science and Technology, Vol 9, No 21 (2016), Pagination: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.- Inhibitory Effects of Lactobacillus Species Against Human Pathogens
Abstract Views :167 |
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Authors
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
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