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Articles by S. Vijayalakshmi
Total Records ( 8 ) for S. Vijayalakshmi
  S. Vijayalakshmi and D. Manimegalai
  Text document clustering is the fundamental technique to mine massive amount of textual data. The problem is of high dimension and most of the machine learning algorithms does not perform well with all the terms in the corpus. In this study, researchers proposed an application of flocking algorithm for text document clustering using two document representation methods. They are Unigram and Noun. In this research, the problem of high dimensions has been dealt with representing documents as Bag of Nouns (BoN) and Bag of Unigrams (BoU). As there are thousands of words present in documents to find Unigram, user has to connect with WordNet and verified the selected features are Unigram. The same process is repeated for Noun. In clustering algorithm, boids follow four simple local rules like alignment, separation, cohesion and similarity to calculate the velocity for flocking. Experiments were conducted with documents of 20 Newsgroup, Reuter Real datasets and Specific Crime Judgment corpus to study the advantages of the system. Flocking algorithm for Text Document clustering is compared with Unigram based document representation and Noun based Document representation. It is observed that Flocking algorithm with Bag of Noun is working efficiently than Bag of Unigram and Bag of Words.
  S. Vijayalakshmi and G.R. Karpagam
  The concept of cloud is sprinkled on an excess of emerging products. Online voting is preferred by the elector by facing several major issues in traditional voting system including geographically dispersed, time constraint job, disabled and others. Online voting system is publically accessible so there are some issues one of the major issues is security. Our objective is to design and develop a frame work for a secure online voting system in cloud environment by using token based authentication, secure hash algorithm, RSA based blind Signature and encryption algorithms. This proposed system consists of three mangers such as User Administration Manager (UAM), Vote Administration Manager (VAM) and Vote Tallying Manager (VTM). In registration phase the elector interacts with UAM to acquire a certificate. VAM is responsible to authenticate the elector. VTM is in charge for verifying the identity of the elector, validity of his/her certificate and tally the votes. All the managers are implemented as agents because it is a capable of working autonomously and continuously in cloud environment. The assessment of the system is verified using properties called authenticity, verifiability, uniqueness, accuracy and non-coercibility.
  R. Karthikeyan , S. Karthigayan , M. Sri Balasubashini , S. Vijayalakshmi , S.T. Somasundaram and T. Balasubramanian
  The present study was carried out to assess the antitumor effect of venom from snake, Hydrophis spiralis on the Ehrlich Ascites Carcinoma (EAC). Four groups of albino Swiss mice were treated with three doses of the sub lethal dose of venom, viz., 0.418, 4.18 and 6.27 μg kg-1 body weight (intraperitoneal injection) along with the standard drug 5 flurouracil (20 mg kg-1 b.w.). The biochemical analysis and rest was left to calculate the mean survival time. In EAC bearing mice, mean life span tumor volume, hemoglobin, red blood cell and lymphocytes were significantly decreased when compared to the normal animals. Whereas, body weight, neutrophils and viable tumor cell count was increased in the EAC bearing mice. These changes were brought back to near normal levels in different treatment groups. The macromolecule concentration of peritoneal cells, such as, DNA, RNA and protein, were altered in the EAC bearing mice and observed to be near normal in the treatment groups. The caspase 3 activity was significantly increased in the peritoneal cells of the treatment groups when compared to the EAC bearing mice. The role of apoptotic cascade in EAC cell death was confirmed by the DNA fragmentation on agarose gel. Apart from the antitumor effect, snake venom reduced the tumor burden on the liver and altered the changes in the activities of alanine transaminase (ALT), aspartate transaminase (AST) and alkaline phosphatase (ALP). Hence the venom from H. spiralis has a potential antitumor effect on the EAC bearing mice.
  R. Karthikeyan , S. Karthigayan , M. Sri Balasubashini , S. Vijayalakshmi , S.T. Somasundaram and T. Balasubramanian
  The anti-tumor activity of the sea snake venom (Hydrophis spiralis) was evaluated against Ehrlich’s Ascites Carcinoma (EAC) in Swiss albino mice and HeLa and Hep2 tumor cell cultures. Among the different dose tested 4.18 μg mL-1 at 24 h was found to effectively inhibit cancer cell proliferation. The same dose on EAC-bearing mice by i.p. injection significantly reduced the tumor growth and was demonstrated by increased life span of the mice by 182.81%.
  S. Vijayalakshmi and V. Mohan
  Problem statement: To find frequently occurring Sequential patterns from web log file on the basis of minimum support provided. We introduced an efficient strategy for discovering Web usage mining is the application of sequential pattern mining techniques to discover usage patterns from Web data, in order to understand and better serve the needs of Web-based applications. Approach: The approaches adopt a divide-and conquer pattern-growth principle. Our proposed method combined tree projection and prefix growth features from pattern-growth category with position coded feature from early-pruning category, all of these features are key characteristics of their respective categories, so we consider our proposed method as a pattern growth, early-pruning hybrid algorithm. Results: Our proposed Hybrid algorithm eliminated the need to store numerous intermediate WAP trees during mining. Since only the original tree was stored, it drastically cuts off huge memory access costs, which may include disk I/O cost in a virtual memory environment, especially when mining very long sequences with millions of records. Conclusion: An attempt had been made to our approach for improving efficiency. Our proposed method totally eliminates reconstructions of intermediate WAP-trees during mining and considerably reduces execution time.
  R. Karthikeyan , S. Karthigayan , M. Sri Balasubashini , S. Vijayalakshmi and T. Balasubramanian
  The venom of the Lapemis curtus was tested for its ability to induce histopathological changes in mice intraperitoneal injection of the venom (LD50 of 0.65 mg kg-1), by light microscopic examination of some organs (liver, kidney and spleen). L. curtus venom induces changes including necrosis and edematous appearance with cellular infiltration and vacuolation. The injury of kidneys includes significant changes of the glomerular apparatus. Venom treated mice liver shows congestion, micro vesicular fatty changes and infiltration of inflammatory cells around the portal vein. Where as, spleen showed hemorrhage, congested and inflammation were observed. Areas of hemorrhage, vascular congestion and cloudy swelling in renal tubules were observed in the kidney. No myoglobinuria was noted in any group of animals. The crude venom was also administered intraperitoneally into the experimental animals and tissue samples were taken at several time intervals. The venom of the sea snake L. curtus, was tested for its ability to induce myonecrosis changes in albino mice. Induction of myonecrosis was demonstrated by their ability to release Creatine Kinase (CK) from damaged muscle fibers and direct histopathological examination of the injected muscles (i.m.). Crude venom exhibits intense myonecrosis characterized by the changes including, necrosis and edematous appearance with cellular infiltrate, vacuolation and degenerated muscle cells with delta lesions and heavy edema in between the cells.
  S. Vijayalakshmi and D. Manimegalai
  Increasingly large text datasets and the high dimensionality associated with natural language is a great challenge of text mining. Initially, researchers have been compared using three types of Document Representation (Bag of Word (BoW), Bag of Noun (BoN) and Bag of Phrase (BoP)) and researchers found that Bag of Noun and Bag of Phrase are performing better than BoW. BoP significantly improves the better F-measure than BoN and BoW when the corpus is smaller. If the corpus is larger, it increases the dimensionality. BoN document representation working efficiently and also used to reduce its dimensionality when the corpus is larger in text document clustering than BoP and BoN. Researchers have been used Bag of Noun document representation. Nouns are checked with ontology and extracted to construct term document matrix, although it reduces the dimension and gives semantics. The comparative study result shows that the performance of Bag of Noun document representation is better than Bag of Phrase. Exploration of learning algorithm gives promising results in recent years. In this study, researchers propose ontology based OHCLK-Means Clustering algorithm. It significantly improves the clustering quality than ontology based K-means and ontology based ONVK-means.
  P. Damotharan , N. Vengadesh Perumal , M. Arumugam , P. Perumal , S. Vijayalakshmi and T. Balasubramanian
  The spatial, temporal and tidal dynamics of the zooplankton community of the Kodiakkarai (also known as point calimere ) was studied from September 2006 to August 2007. The monthly sampling procedure included the measurement of hydrological parameters salinity, temperature, pH and the collection of zooplankton with plankton net (0.35 m mouth diameters), made up of bolting silk (Cloth No. 10; mesh size 158) for 20 min. The hydrographical parameters were found to very month-wise and station-wise. Air temperature showed summer peak and pre-monsoon, post-monsoon and monsoon decline and the variations were associated with the seasonal changes of meteorological events. Salinity was high during the post monsoon and summer seasons and low during the monsoon season at both stations and was mainly influenced by the rainfall pattern. pH was high during the monsoon and summer seasons and low during the monsoon and post-monsoon seasons at both stations and the rainfall mainly influenced the variation. Dissolved oxygen concentration was high during the monsoon season and low during the summer season at both stations. Distribution of dissolved nutrients also exhibited considerable seasonal due to the flooding and land runoff. The silicate concentration was especially found to be much higher than other nutrients. Among the 121 zooplanktonic forms recorded, the Copepoda formed the dominant group followed by larvae.
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