Kandasamy Premalatha

• PhD
• Professor (Full) at Bannari Amman Institute of Technology

Microarray technology has transformed the biotechnological research to next level in the recent years. It provides the expression levels of various genes involved in a particular disease. Prostate cancer disease turned into life threatening cancer. The genes causing this disease are identified through the classification methods. These gene expressi...

Aim: This study aims to investigate and apply effective machine learning techniques for the early detection and precise diagnosis of breast cancer. The analysis is conducted using various breast cancer datasets, including Breast Cancer Wisconsin, Breast Cancer Diagnosis, NKI Breast Cancer, and SEER Breast Cancer datasets. The primary focus is on id...

Even though various features have been investigated in the detection of figurative language, oxymoron features have not been considered in the classification of sarcastic content. The main objective of this work is to present a system that can automatically classify sarcastic phrases in multi-domain data. This multi-domain dataset consisting of 678...

Mountainous amounts of information are now available in hospitals, finance, counter-terrorism, education and many other sectors. Those information can offer a rich source for analysis and decision making. Such information contains user’s sensitive and personal data as well. This emanates direct conflict with the user’s privacy. Individual’s privacy...

In recent years, deep learning techniques have played an important role in the biological field. The present study proposes a convolutional neural network approach for identification of calanoid copepods Temora discaudata and Canthocalanus pauper. T. discaudata and C. pauper classifies with the image dataset to develop for classifying the species....

The influence of technology’s progress on the ability to read people's emotions has received increased attention in recent years. It is essential to identify the elderly's feelings because it indicates mental wellness. This study proposes a unique approach to micro-information extraction using a cross-model attention mechanism and a two-step hybrid...

Data sharing to the multiple organizations are essential for analysis in many situations. The shared data contains the individual’s private and sensitive information and results in privacy breach. To overcome the privacy challenges, privacy preserving data mining (PPDM) has progressed as a solution. This work addresses the problem of PPDM by propos...

Lung cancer is the uncontrolled growth of abnormal cells in one or both lungs. This is one of the dangerous diseases. A lot of feature extraction with classification methods were discussed previously regarding this disease, but none of the methods give sufficient results, not only that, those methods have high over fitting problem, as a result, the...

Mining high utility itemsets (HUIs) from transaction databases is one of the current research areas in the data mining field. HUI mining finds itemsets whose utility meets a predefined threshold. It enables users to quantify the usefulness or preferences of products by utilizing different values. Since utility mining approaches do not satisfy the d...

The Speech Emotion Recognition (SER) is a complex task because of the feature selections that reflect the emotion from the human speech. The SER plays a vital role and is very challenging in Human-Computer Interaction (HCI). Traditional methods provide inconsistent feature extraction for emotion recognition. The primary motive of this paper is to i...

Breast cancer is the most common invasive cancer in females worldwide. Breast cancer diagnosis and breast cancer prognosis are the two important challenges for the researchers in the medical field and also for the practitioners. If the cells in the breast start to grow without any control, it leads to cancer. Normally, the growth of the lump can be...

Breast cancer is the most common invasive cancer in females worldwide. Breast cancer diagnosis and breast cancer prognosis are the two important challenges for the researchers in the medical field and also for the practitioners. If the cells in the breast start to grow without any control, it leads to cancer. Normally, the growth of the lump can be...

The association rule mining approach produces uninteresting association rules. When the set of association rules become large, it becomes less interesting to the user. In order to pick interesting association rules among peak volumes of found association rules, it is critical to aid the decision-maker with an efficient post-processing phase. Theymo...

Although there have been various researches in the detection of different figurative language, there is no single work in the automatic classification of euphemisms. Our primary work is to present a system for the automatic classification of euphemistic phrases in a document. In this research, a large dataset consisting of 100,000 sentences is coll...

The semantic and XML in document classification are used to develop XML data based on tree-based document classification method. The document classification plays the main role in the information management and its retrieval of data, which is a learning problem. In a development context, document classification has a major role in many applications...

Alzheimer’s Disease (AD) is a neurological disorder that destroys memory and other significant mental functions. One of the most accurate methods to identify the disease-causing genes is to monitor gene expression values in various samples. Selecting significant genes for classification is important in gene expression studies. In this study, the ex...

Privacy is very important in shared data for the knowledge based applications. However it causes serious privacy concerns, when the sensitive data is stored and moved to other applications. It is vital to incorporate privacy in the sensitive data for the data mining process. While preserving privacy, certain protocols allow the knowledge extraction...

The study aims to analyze the haematological parameters of Cyprinus carpio with reference to the formulation of the probiotic fortified feeds using a machine learning approach. C. carpio fed with pelletized feed, probiotic pelletized feed (5% Lysinibacillus macroides), probiotic pearl beads (5% L. macroides) and probiotic rice puff (5% L. macroides...

Triclustering techniques are applied to analyze three-dimensional gene expression microarray data to retrieve group of genes under the tested samples over certain time points based on a similarity measure. The real-life three-dimensional dataset chosen is estrogen induced breast cancer dataset. In such datasets, identifying the variations in mining...

Recent advancements in data mining have given rise to a new channel of research, coined as privacy-preserving data mining (PPDM). PPDM technology allows us to derive useful information from vast amounts of data while protecting privacy of individual records. This paper proposed a methodology based on the machine learning algorithm called singular v...

This study aims to assess the physical and social vulnerability of floods, which occurred in the year 2015 in the Adyar Basin of Chennai, Tamil Nadu. Thematic layers, such as rainfall, land use land cover (LULC), drainage density, slope, soil, and roads per watershed, were prepared and assigned the ranks using the rank sum method. The knowledge-bas...

Privacy is an important factor that hospitals should preserve while publishing data that involve sensitive information of individuals. Research seeks to find solutions for releasing data to the public without infringing the confidentiality of personal information. Sanitizing data makes them safe for publishing while maintaining essential informatio...

Data mining is a method by which valuable information can be obtained from large databases. A supervised method of classification assigns data samples to target groups. In this system, it uses various classification algorithms namely decision trees, SVM, random forest and neural network. This system will classify and analyses the best suited algori...

Mobile adhoc network is a mixture of various mobile sensor nodes that are dispersed in the environment. The key idea of this system uses MANET environments to publicize the truths by increasing the data transmission rate. This influences to changed security problems such as collision, conflict et cetera. These problems would decrease the scattering...

The main purpose of this work is to exploit MANET environment in military environment to broadcast the data through efficient data transmission rate. This eventually results in different security issues like conflict and collision. These complexities could minimize the distribution of the packet ratio. Constant position node environment has been us...

In Outcome-Based Education (OBE), the assessment of the Course Outcomes (COs) is the most prominent aspect required to improve the quality of education. The COs for each course are based on the Program Outcomes (POs), Program Specific Outcomes (PSOs), and other requirements. There are various understandings toward the concept of OBE that resulted i...

Data Security makes the finest importance in the area of cloud computing. Cryptosystem will provide the greater security for the data in the cloud. Many encryption techniques are available for secured data storage with its own advantages and disadvantages. There is a problem of Key escrow and certificate revocation in the identity based encryption....

In today's modern world cardiovascular disease is the most lethal one. This disease attacks a person so instantly that it hardly gets any time to get treated with. So, diagnosing patients correctly on timely basis is the most challenging task for the medical fraternity. In order to reduce the risk of heart disease, effective feature selection and c...

Breast cancer is the most common invasive cancer in females worldwide. Breast cancer diagnosis and breast cancer prognosis are the two important challenges for the researchers in the medical field and also for the practitioners. If the cells in the breast start to grow without any control, it leads to cancer. Normally, the growth of the lump can be...

Biomedical literature is the primary repository of biomedical knowledge in which PubMed is the most absolute database for collecting, organizing and analyzing textual knowledge. The high dimensionality of the natural language text makes the text data quite noisy and sparse in the vector space. Hence, the data preprocessing and feature selection are...

This work is focused to improve the military communication by introducing Channel Load based Average Link Interference Estimation (CLAIE) which will assess the channel load level of every route path, thus the interference reduced communication can be guaranteed. Channel load metric is capable of identifying interference superior to the previous met...

Biclustering in gene-expression data is a subset of the genes demonstrating consistent patterns over a subset of the conditions. Recently, the most of research in biclustering involving statistical and graph-theoretic approaches by adding or deleting rows and/or columns in the data matrix based on some constraints. This is an exhaustive search of t...

Secured and trustable routing in military information system is a sophisticated task in which sharing of information with no distortion or collusion is important. Mobile ad hoc networking enables the military communication by forwarding the information to the corresponding nodes on the right time. In the available system, Neighborhood-based Interfe...

Analyzing time series microarray dataset is a challenging task due to its three dimensional characteristic. Clustering techniques are applied to analyze gene expression data to extract group of genes under the tested samples based on a similarity measure. Biclustering appears as an evolution of clustering due to its ability to mine subgroups of gen...

Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The classification of cancer is a foremost area of research in the field of bioinformatics. Microarray technology enables the researcher to investigate the expression levels of thousands of genes in a single experiment and gives the measurements o...

Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. It not only received the attention of the research community but also has a wide range of applications. The success of microarray technology depends on the precision of measurement, the usage of tools in data mining, analytical methods and statist...

In recent years, nature-inspired algorithms have been popular due to the fact that many real-world optimization problems are increasingly large, complex and dynamic. By reasons of the size and complexity of the problems, it is necessary to develop an optimization method whose efficiency is measured by finding the near optimal solution within a reas...

DNA microarrays have been applied successfully in diverse research fields such as gene discovery, disease diagnosis and drug discovery. The roles of the genes and the mechanisms of the underlying diseases can be identified using microarrays. Biclustering is a two dimensional clustering problem, where we group the genes and samples simultaneously. I...

Feature selection and classification of microarray data are the most important challenges in machine learning. The motivation behind the Feature selection techniques is in selecting discriminate feature subsets which plays a vital role in the process of classifying cancer/tumour microarray expression data. In the present work, a novel feature selec...

Worldwide heart disease forecast has been a major research over the past decade since the major reason of death is due to heart disease. Numerous researchers combined fuzzy technique with some other technique for proficient classification purpose in order to predict the heart disease, since the fuzzy is proficient only if proper fuzzy rules are spe...

With the real time data, results in increasing in size. Feature selection (FS) approach chooses the most informative features from the original features according to a selection method. Also current methods are inadequate. In particular, this has found successful application in tasks that involve datasets containing huge numbers of features (in the...

The biclustering of gene expression data is an important technology for biologists. Biclustering is used to discover groups of genes that are co-expressed over a subset of conditions in microarray gene expression data. There has been a lot of research in biclustering involving statistical and graph-theoretic approach. This entails that an exhaustiv...

Gene expression data analysis is used in several areas including drug discovery and clinical applications. Biclustering in gene expression data is a subset of the genes representing consistent patterns over a subset of the conditions. In this case the conditions can be related to the disease types, the biclustering method is much hopeful in this ap...

Privacy preservation becomes more stimulating task while publishing data which is maintained by any organization where there occurs isolated information about their customers. Data mining tasks are performed on published data for business intelligence or any of knowledge retrieval tasks. The task of sanitizing original data set should not loss the...

Microarray experiments generate vast amounts of data, leading to new requirements and challenges for bioinformatics. The crucial step in considering gene expression data is to discover a group of genes that have similar patterns. Biclustering is a two-dimensional clustering problem where the genes and samples are grouped simultaneously. Latest rese...

Document clustering is important for a variety of information needs and applications such as collection management, summary and analysis. Especially, mining biomedical texts for knowledge discovery and hypothesis generation has become a very active field due to the immense availability of large biomedical textual database. However, most of the prev...

With the real time data, results in increasing in size. Feature selection (FS) has been considered as the problem of selecting these input features that are most predictive of a given outcome. Also current methods are inadequate. By considering this scenario, this paper proposes the incremental techniques; in fact this has found unsuccessful applic...

The field of privacy pursues rapid advances in recent years because of the increases in the ability to store data. One of the most important topics in research community is Privacy preserving data mining (PPDM). Privacy preserving data mining has become increasingly popular because it allows sharing of privacy sensitive data for analysis purposes....

Biometrics is the science of identifying a person using physiological or behavioural characteristics. Hand vein pattern is a recent and unique biometric feature which is used for high secure authentication of individuals. The dorsal hand contains dorsal metacarpal veins, dorsal venous network, cephalic vein and basilic vein. This paper presents an...

DNA microarray gene expression data analysis has provided new insights into gene function, disease pathophysiology, disease classification, and drug development. Biclustering in gene expression data is a subset of the genes demonstrating consistent patterns over a subset of the conditions. The proposed work finds the significant biclusters in large...

In recent years, nature-inspired algorithms have been popular due to the fact that many real-world optimization problems are increasingly large, complex and dynamic. By reasons of the size and complexity of the problems, it is necessary to develop an optimization method whose efficiency is measured by finding the near optimal solution within a reas...

Traditionally, frequent pattern mining dealt in extracting frequency pattern from transaction databases by not considering utility factors. Utility-based data mining focuses on all aspects of economic utility in data mining and is aimed at incorporating utility in both predictive and descriptive data mining tasks. High utility itemset (HUI) mining...

The DNA microarray technology concurrently monitors the expression levels of thousands of genes during significant biological processes and across the related samples. The better understanding of functional genomics is obtained by extracting the patterns hidden in gene expression data. It is handled by clustering which reveals natural structures an...

Palmprint is the region between wrist and fingers. In this paper, a palmprint personal identification system is proposed based on the local and global information fusion. The local and global information is critical for the image observation based on the results of the relationship between physical stimuli and perceptions. The local features of the...

Feature selection in cancer classification is a central area of research in the field of bioinformatics and used to select the informative genes from thousands of genes of the microarray. The genes are ranked based on T-statistics, signal-to-noise ratio (SNR), and F-test values. The swarm intelligence (SI) technique finds the informative genes from...

Conventional Document clustering techniques aim to group the documents into different semantic classes based on the cluster hypothesis. Most of the existing techniques are based on either single term keyword with its frequency analysis or phrase based approach using n-gram techniques of the document. Accurate clustering is infeasible in document cl...

XML has been used as a universal format to design the documents on web, because Mark-up language created using XML for any application does not place any restriction on the number of tags that can be defined. The flexibility to create user-defined tags in XML enables smart searches in large data. The structure of XML provides sophisticated proximit...

In recent times, the mining of association rules from XML databases has received attention because of its wide applicability and flexibility. Many mining methods have been proposed. Because of the inherent flexibility of the structures and the semantics of the documents, however, these methods are challenging to use. In order to accomplish the mini...

Utility mining is the study of itemset mining from the consideration of utilities. It is the utility-based itemset mining approach to find itemsets conforming to user preferences. Modern research in mining high-utility itemsets (HUI) from the databases faces two major challenges: exponential search space and database-dependent minimum utility thres...

The hand vein pattern is a biometric feature in which the actual pattern is the shape of the vein network and its characteristics are the vein features. This paper investigates a new approach for dorsal hand vein pattern identification from grey level dorsal hand vein information. In this work Gabor filter quadrature pair is employed to compute loc...

Hand vein pattern is a biometric feature in which the actual pattern is the shape of vein network and its characteristics are the vein features. This paper proposes a new approach and uses local phase quantisation with Gaussian quadrature filter pair for hand dorsal vein identification. The proposed work extracts the phase information computed loca...

A Mobile Ad Hoc Network (MANET) is a collection of wireless mobile hosts forming a temporary network without the aid of any centralized administration or standard support services. Providing privacy and security is a critical problem when implementing MANET in an adversarial environment. A malicious node may pose a serious security threats for comm...

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Fourth-generation wireless networks may require an integration of mobile ad hoc networks (MANET) into external network to enhance the flexibility of the communication and roaming. This phenomenon is well-suited for commercial and military applications which yield additional benefit of roaming. However, integration of MANET with external network pos...

Abstract: Security plays a major role in implementing mobile ad hoc networks (MANET) for communication in an adverse environment. This study introduces the concept of anonymity for an informant who identifies and reports anonymously the misbehaviour of the users in the network. The trust-enhanced anonymous on-demand routing protocol (TEAP) is propo...

In recent years the amount of unstructured databases increased drastically. In lieu of continuous increasing of XML databases, it is mandatory to propose a method to retrieve useful information. Association Rule Mining places a major role to retrieve this useful information. XML data bases have more challenges because of its inherent flexibility in...

Conventional document clustering techniques are mainly based on the existence of keywords and the number of occurrences of it. Most of the term frequency based clustering techniques consider the documents as bag-of-words and ignore the important relationships between the words in the document. Phrase based clustering techniques also capture only th...

In this paper, we explore a Service Oriented Computing (SOC) paradigm which provides knowledge as a service that makes use of utility mining approach. The basic idea of providing knowledge is done via the web services in which we use a knowledge server to answer the queries of the consumers. A web service is a single entity which comprises of clust...

Security is a major concern while implementing Mobile Ad Hoc Networks (MANET) for communication in an adverse environment. The dynamism in network topology and the absence of centralized administration, MANET is susceptible to security attacks from malicious users. This paper introduces the concept of anonymity for an informant who identifies and d...

Bloom filter (BF) is a simple but powerful data structure that can check membership to a static set. The trade-off to use Bloom filter is a certain configurable risk of false positives. The odds of a false positive can be made very low if the hash bitmap is sufficiently large. Spam is an irrelevant or inappropriate message sent on the internet to a...

Bloom Filter (BF) is an extremely fast method for determining if an element is in a set. It may also show if an element is not in a set. The tradeoff to use Bloom filters is a certain configurable risk of false positives. The odds of a false positive can be made very low if the hash bitmap is sufficiently large. Spam is an irrelevant or inappropria...

The main goals of Association Rule Mining (ARM) are to find all frequent itemsets and to build rules based of frequent itemsets. But a frequent itemset only reproduces the statistical correlation between items, and it does not reflect the semantic importance of the items. To overcome this limitation we go for a utility based itemset mining approach...