K. Premalatha – författare

Scientific Essay from the year 2016 in the subject Communications - Multimedia, Internet, New Technologies, grade: 7.0, Bannari Amman Institute of Technology, course: Ph.D, language: English, abstract: Biometric methods for authenticating and identifying people are increasingly used in both the commercial and private sector. Today's commercially available biometric systems show good reliability. However, they generally lack user acceptance. Users showed an antipathy towards touching a possibly dirty fingerprint scanner, or looking into an iris scanner that might malfunction and eventually impair their vision. Whether those fears are well founded or not is less important. The fact is, they have considerable influence on user acceptance. And user consent is important for a good and successful application of a biometric system, as well as for good recognition rates. In response to the increasing demand for reliable as well as user friendly biometric systems, this work investigates the applicability of palmprint and FKP were the biometric features for authentication. Using palmprint or FKP as a biometric system avoids such problems as shown before, since it requires no subject interaction. The main objectives of the thesis are: to propose the transform based techniques that is used to achieve higher recognition accuracy and lower equal error rate; and to examine the performance of the proposed techniques with the existing methodologies.

Research Paper (undergraduate) from the year 2015 in the subject Computer Science - Bioinformatics, grade: 1, Bannari Amman Institute of Technology, language: English, abstract: Extracting meaningful information from gene expression data poses a great challenge to the community of researchers in the field of computation as well as to biologists. It is possible to determine the behavioral patterns of genes such as nature of their interaction, similarity of their behavior and so on, through the analysis of gene expression data. If two different genes show similar expression patterns across the samples, this suggests a common pattern of regulation or relationship between their functions. These patterns have huge significance and application in bioinformatics and clinical research such as drug discovery, treatment planning, accurate diagnosis, prognosis, protein network analysis and so on. In order to identify various patterns from gene expression data, data mining techniques are essential. Major data mining techniques which can be applied for the analysis of gene expression data include clustering, classification, association rule mining etc. Clustering is an important data mining technique for the analysis of gene expression data. However clustering has some disadvantages. To overcome the problems associated with clustering, biclustering is introduced. Clustering is a global model where as biclustering is a local model. Discovering such local expression patterns is essential for identifying many genetic pathways that are not apparent otherwise. It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data. Biclustering is a two dimensional clustering problem where we group the genes and samples simultaneously. It has a great potential in detecting marker genes that are associated with certain tissues or diseases. However, since the problem is NP-hard, there has been a lot of research in biclustering involving statistical and graph-theoretic. The proposed Cuckoo Search (CS) method finds the significant biclusters in large expression data. The experiment results are demonstrated on benchmark datasets. Also, this work determines the biological relevance of the biclusters with Gene Ontology in terms of function.

Biometrics refers to the authentication techniques that depend on measurable physical characteristics and behavioural characteristics to identify an individual. The biometric systems consist of different stages such as image acquisition, preprocessing, feature extraction and matching. Biometric techniques are widely used in the security world. The various types of biometric systems use different techniques for the preprocessing, feature extraction and classifiers.The dorsum of the hand is known as the finger back surface. It is highly used for personal authentication and has not yet attracted the attention of convenient researchers. It is mostly used due to contact free image acquisition. It is reported that the skin pattern on the finger-knuckle is extremely rich in texture due to skin folds and creases, and hence, can be considered as a biometric identifier. Furthermore, advantages of using Finger Knuckle Print (FKP) include rich in texture features, easily accessible, contact-less image acquisition, invariant to emotions and other behavioral aspects such as tiredness, stable features and acceptability in the society. As a result of that, there is less known use of finger knuckle pattern in commercial or civilian applications. The local features of an enhanced palmprint image are extracted using Fast Discrete Orthonormal Stockwell Transform (FDOST). The Fourier transform of an image is obtained by increasing the scale of FDOST to infinity. The Fourier transform coefficients extracted from the palmprint image and FKP image are considered as the global information. The local and global information are physically linked by means of the framework of time frequency analysis. The global feature is exploited to refine the arrangement of FKP images in matching. The proposed schemes make use of the local and global features to verify finger knuckle-print images. The weighted average of the local and global matching distances is taken as the final matching distance of two FKP images. The investigational results indicate that the proposed works outperform the existing works.

This book presents the select proceedings of the First Women Indian Geotechnical Conference (WIGC) 2024 showcasing the overarching theme of "Geotechnics for Sustainable and Resilient Infrastructure." The book presents cutting-edge contributions from distinguished women geotechnical engineers and esteemed professors across the field of geotechnical engineering. Encompassing a broad spectrum of topics, the contributions in this volume cover pivotal areas, such as geomaterial characterization, sustainable waste management, geoenvironmental engineering, foundation engineering, landslides and slope stability, ground improvement, soft clay engineering, AI/ML applications in geotechnical engineering, and illuminating case studies in the field. This book will prove useful to graduate students, researchers, academics, and professional engineers working in geotechnical engineering, civil engineering, and geological engineering.

This book presents the select proceedings of the First Women Indian Geotechnical Conference (WIGC) 2024 showcasing the overarching theme of "Geotechnics for Sustainable and Resilient Infrastructure." The book presents cutting-edge contributions from distinguished women geotechnical engineers and esteemed professors across the field of geotechnical engineering. Encompassing a broad spectrum of topics, the contributions in this volume cover pivotal areas, such as geomaterial characterization, sustainable waste management, geoenvironmental engineering, foundation engineering, landslides and slope stability, ground improvement, soft clay engineering, AI/ML applications in geotechnical engineering, and illuminating case studies in the field. This book will prove useful to graduate students, researchers, academics, and professional engineers working in geotechnical engineering, civil engineering, and geological engineering.

This book presents the select proceedings of the First Women Indian Geotechnical Conference (WIGC) 2024 showcasing the overarching theme of "Geotechnics for Sustainable and Resilient Infrastructure." The book presents cutting-edge contributions from distinguished women geotechnical engineers and esteemed professors across the field of geotechnical engineering. Encompassing a broad spectrum of topics, the contributions in this volume cover pivotal areas, such as geomaterial characterization, sustainable waste management, geoenvironmental engineering, foundation engineering, landslides and slope stability, ground improvement, soft clay engineering, AI/ML applications in geotechnical engineering, and illuminating case studies in the field. This book will prove useful to graduate students, researchers, academics, and professional engineers working in geotechnical engineering, civil engineering, and geological engineering.