Faculty Publications

Permanent URI for this communityhttps://idr.nitk.ac.in/handle/123456789/18736

Publications by NITK Faculty

Browse

Author: search.filters.author.Kamath, S.S.

Search Results

Now showing 1 - 10 of 23
  • No Thumbnail Available
    Item
    Relation between k-DRD and dominating set
    (Springer International Publishing, 2019) Kamath, S.S.; Senthil Thilak, A.; M, R.
    In this paper, a new parameter on domination is defined by imposing a restriction on the degrees of vertices in the dominating set. For a positive integer k, a dominating set D of a graph G is said to be a k-part degree restricted dominating set (k-DRD-set), if for all u ∈ D there exists a set C u ⊆ N(u) ∩ (V − D) such that |Cu|≤⌈d(u)k⌉ and ⋃ u ∈ D C u = V − D. The minimum cardinality of a k-part degree restricted dominating set of G is called the k-part degree restricted domination number of G and is denoted by γdk(G). Here, we determine the k-part degree restricted domination number of some well-known graphs, relation between dominating and k-DRD set, and an algorithm which verifies whether a given dominating set is a k-DRD set or not. © Springer Nature Switzerland AG 2019.
  • No Thumbnail Available
    Item
    An improved bound on weak independence number of a graph
    (2013) Bhat, R.S.; Kamath, S.S.; Surekha
    A vertex v in a graph G=(V,X) is said to be weak if d(v)≤d(u) for every u adjacent to v in G. A set S ⊆ V is said to be weak if every vertex in S is a weak vertex in G. A weak set which is independent is called a weak independent set (WIS). The weak independence number wβ0(G) is the maximum cardinality of a WIS. We proved that wβ0(G)≤ p-δ. This bound is further refined in this paper and we characterize the graphs for which the new bound is attained.
  • No Thumbnail Available
    Item
    Sample-based DC prediction strategy for HEVC lossless intra prediction mode
    (Institute of Electrical and Electronics Engineers Inc., 2017) Kamath, S.S.; Aparna., P.; Antony, A.
    High-Efficiency Video Coding (HEVC), the state-of-the-art video coding standard by the ITU-T Video Coding Experts Group and the ISO/IEC Moving Picture Experts Group, is presently being prepared to handle the next generation multi-media services. Lossless mode of HEVC is designed to support a variety of lossless compression applications like medical imaging, preservation of artwork, video analytics, etc. The accuracy of the intra prediction can be improved through the incorporation of sample-based prediction strategies which replace the block-based prediction within HEVC. In this work, we propose a sample-based DC intra prediction strategy to enhance the compression efficiency of the HEVC lossless mode. The detailed experimental analysis demonstrates that the proposed method outperforms the HEVC lossless mode of HM16.12 in terms of bit-rate savings by 1.43% and 0.46% on an average for AI-Main and AI-Main10 configurations respectively, without any increase in run-time. © 2017 IEEE.
  • No Thumbnail Available
    Item
    Graph Energy Based Centrality Measure to Identify Influential Nodes in Social Networks
    (Institute of Electrical and Electronics Engineers Inc., 2019) Kamath, S.S.; Mahadevi, S.
    One of the measures to analyze complex network is vertex centrality; it can reveal existing network patterns. It helps us in understanding networks. One of the measures to analyze complex network is vertex centrality, and it can reveal existing network patterns. It helps us in understanding networks and their components by analyzing their structural properties. The social network is one of the complex networks which is composed of nodes and relationships. It is growing very vastly due to the addition of new nodes every day. All nodes are not equally important in such a vast network hence, identifying influential nodes becomes a practical problem. Centrality measures were introduced to quantify the importance of nodes in networks. The various criterion is used to select critical nodes in the network. Therefore, different centrality measures like Betweenness Centrality, Degree Centrality, Closeness Centrality, and other well-known centrality measures are used to identify essential nodes. We have proposed an algorithm to compute a centrality using graph energy called Energy-Based-Centrality-Measure (EBCM) in this paper. It identifies the central nodes based on a graph invariant called graph energy. EBCM gives a better understanding of the current network by analyzing the impact of node deletion on graph connectivity and thereby helps us in achieving a better network understanding ability and maintenance. © 2019 IEEE.
  • No Thumbnail Available
    Item
    Graph energy ranking for scale-free networks using Barabasi-Albert model
    (Institute of Electrical and Electronics Engineers Inc., 2019) Mahadevi, S.; Kamath, S.S.
    A social network is a vast collection of actors and interactions. It forms one of the complex networks. There are various types of social networks such as acquaintance networks, online social networks, covert networks, citation networks, and collaboration networks, etc. Most of these real-world networks are scale-free, and they follow a power-law distribution. Each of these networks has nodes which have various roles to play, and all nodes are not equally important. Hence we need to rank them based on their importance. In this paper, we propose an algorithm named Graph Energy Ranking (GER) to rank the nodes of scale-free networks built using the Barabasi-Albert model. GER analyses the impact of node deletion on the underlying network and therefore gives a better understanding of the network features. Study of ranking done by existing centrality measures versus GER is performed to observe the similarity in the ranking process. ©2019 IEEE.
  • No Thumbnail Available
    Item
    Analysis of Kapferer Mine Network using Graph Energy Ranking
    (Institute of Electrical and Electronics Engineers Inc., 2019) Mahadevi, S.; Kamath, S.S.
    Vertex centrality is one of the procedures to evaluate complex networks, and it can disclose current patterns of networks. By evaluating their structural characteristics, it enables us to understand networks and their elements. One of the complex networks of nodes and interactions is the social network. It is increasing very greatly every day owing to the addition of fresh nodes. In such a vast network, therefore, not all nodes are equally essential, identifying influential nodes becomes a practical issue. To quantify the significance of nodes in networks, centrality measures were implemented. The multiple criteria are used to select critical nodes in the network. Various centrality measures such as Betweenness Centrality, Degree Centrality, Closeness Centrality, and some well-known centrality measures are therefore used to define vital nodes. In this article, we suggested a centrality to rank the nodes using a graph invariant called graph energy named as Graph-Energy-Ranking (GER). GER provides a better knowledge of the current network by evaluating the effect of node deletion on graph connectivity and thus enables us to better understand and maintain the network. In the current paper GER is applied on well-known social network called Kapferer mine network and results have been discussed. © 2019 IEEE.
  • No Thumbnail Available
    Item
    Enhancing QoS in a University Network by using Containerized Generic Cache
    (Institute of Electrical and Electronics Engineers Inc., 2020) Praveen Raj, H.L.; Tahiliani, M.P.; Mohanan, P.G.; Kamath, S.S.
    Ubiquitous access and enhanced Internet speeds have paved ways for online educational reforms at a large scale. There has been a widespread adoption of modern educational applications, ranging from interactive applets, video lessons and online quizzes to remotely conducting laboratory experiments. Consequently, there is a demand to provision more bandwidth to satisfy the users expectations. In this paper, we propose an approach to enhance the Quality of Service (QoS) in a University campus network and efficiently utilize the available bandwidth. Typically within a University, some requests are similar e.g., operating system updates, Linux package installs, Python pip packages and others. These are huge data transfer requests ranging from Megabytes to Gigabytes, and consume a large amount of bandwidth on external access links to the Internet. Redundant requests of this nature from a large user base lead to enormous wastage of bandwidth. The proposed approach overcomes this concern by setting up a containerized forward proxy with a generic cache for popular traffic in the University. Our experiments on a live network at National Institute of Technology Karnataka, Surathkal show that a large number of redundant requests can be successfully served from this Virtualized Network Function (VNF), thereby enhancing the QoS and efficiently utilizing the available bandwidth. The proposed system is able to reduce the latency by over 60% and saves 34GB of data per day on an average. Although the proposed approach is tested in a University environment in this work, it is applicable for other caching requirements with minor modifications. Moreover, since this cache is implemented as a VNF, it is portable and easy to deploy. © 2020 IEEE.
  • No Thumbnail Available
    Item
    Secure 4G SEPS-AKA Protocol for UMTS Networks
    (Institute of Electrical and Electronics Engineers Inc., 2020) Suvidha, K.S.; Kamath, S.S.
    User authentication is one of the crucial challenges that has to be addressed in UMTS (Universal Mobile Telecommunications Service) in order to grant the access to the services during handovers. Therefore, to provide the authentication the proposed protocol makes use of the existing Extensible Authentication Protocol (EAP). To provide the authentication in the LTE networks, an authentication framework EAP is used. EAPAKA is one of the methods of EAP framework. EAP-AKA, uses the mechanism Authentication and Key Agreement (AKA). EAPAKA is used in UMTS networks to secure the communication channel. In LTE, this mechanism is called as Evolved Packet System Authentication and Key Agreement (EPS-AKA). Mobile users in LTE networks access the packet data network through Evolved UMTS Terrestrial Radio Access Network (EUTRAN). However, with the thorough literature survey, it is proved that EPS-AKA mechanism is susceptible to the security vulnerabilities such as disclosure of the user identity, Man in the Middle attack and replay attacks. To overcome these security attacks, a new Secure Evolved Packet System (SEPS) protocol has been proposed. The formal security verification of the proposed SEPS protocol using widely accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool is presented in this paper. In addition to this, the proposed protocol is compared with the other protocols in terms of performance. The proposed SEPS protocol is efficient and robust. This makes the proposed protocol suitable for the practical implementation. © 2020 IEEE.
  • No Thumbnail Available
    Item
    Imbalanced Multi-Class Research Article Classification using Sentence Transformers and Machine Learning Algorithms
    (Association for Computing Machinery, Inc, 2025) Gowhar, S.; Kempaiah, P.; Kamath, S.S.; Sugumaran, V.
    Categorizing scientific articles into specific research fields is a challenging problem, considering the volume and variety of published literature. However, existing classification systems often suffer from limitations regarding taxonomy or the models used for classification. This article explores approaches built on Sentence Transformer embeddings combined with Machine Learning algorithms to classify articles into 123 predefined classes, with the dataset being heavily imbalanced in nature. The effectiveness of Large Language Models (LLMs) for generating synthetic data is also experimented with, along with synonym augmentation and SMOTE. The best-performing model, the One vs Rest classifier trained on MP-Net sentence embeddings with SMOTE, achieved an accuracy of 77%, and outperformed all the other models. © 2024 Copyright held by the owner/author(s).
  • No Thumbnail Available
    Item
    Generating Clinically Relevant Radiology Reports using Multimodal Deep Learning Models
    (Association for Computing Machinery, Inc, 2025) Mahajan, R.; Kamath, S.S.
    Generating radiology reports is an important component of the diagnostic process, facilitating the interpretation of medical images and subsequent clinical decision making. Recent advancements have opened new pathways to automate the generation of radiology reports, a task traditionally performed by radiologists through meticulous analysis of medical images. This study presents a framework that uses deep learning and NLP to automate the generation of radiology reports from chest X-ray images. Our approach utilizes a pre-trained RAD-DINO model to extract features from radio-graphic images and an encoder-decoder model to create coherent textual descriptions. The proposed models produced coherent reports outperforming several existing state-of-the-art methods when evaluated using standard metrics like BLEU. © 2024 Copyright held by the owner/author(s).