Browsing by Author "P, A."

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An integration of information communication technologies and entrepreneurial ventures: a bibliometric analysis and future research directions
(Emerald Publishing, 2025) P, A.; Mohan, B.C.
Purpose – This study outlines the key research areas, recent trends and future research directions in information communication technologies (ICTs) enabled entrepreneurship, as research activities on ICTs in entrepreneurship have gained significant momentum in recent decades, driven by technological advancements and business innovativeness. Design/methodology/approach – In this paper, we used a bibliometric systematic literature review, including citation, co-citation and keyword analysis of 182 documents published from 2005 to 2024 and exported from the Scopus and Web of Science (WoS) databases. We have also utilized bibliometric coupling analysis to determine emerging themes in this area. Findings – The most productive year was 2023, and the most productive journal, institute and country are the “Journal of Small Business and Enterprise Development, ” “Beijing University of Posts and Telecommunications” and the UK, respectively. The “Journal of Enterprise Information Management” is the most influential journal. A future research direction is proposed based on the six emerging clusters and identified gaps. Research limitations/implications – The study is based on the exclusive use of the Scopus and WoS databases, which could be expanded to other databases. Only articles were considered, excluding book chapters and conference papers. Originality/value – The study is distinctive as it recognizes the intellectual structure and advancement in ICT-enabled entrepreneurship. By comprehensively reviewing the existing literature, the study proposes a novel conceptual framework to serve as a foundation for future studies, offering significant insights for academics and practitioners to navigate the evolving landscape of this area. © 2025 Emerald Publishing Limited
Rapid single pot synthesis of hierarchical Bi2WO6 microspheres/RGO nanocomposite and its application in energy storage: A supercritical water approach
(Elsevier Ltd, 2023) Shetty, M.; Karnan, K.; Chetana, C.; Bekal, C.; Misnon, I.I.; P, A.; Roy, K.; Shivaramu, P.D.; Baloor, S.; Rangappa, D.
The application of novel three-dimensional (3D) architectures in energy storage has fascinated researchers for a long time. The fast-paced technological advancements require reliable rapid synthesis techniques for developing multi-metal oxide (MMO) nanostructures. For the first time, we disclose the supercritical water method's use to synthesize a single-phase hierarchical three-dimensional (3-D) Bi2WO6 microsphere/Reduced Graphene Oxide (BWS/RGO) nanocomposite (SCW). Through various nano-characterization technologies, it is possible to confirm the sample characteristics and determine the nanocomposites' morphological, physical, and thermal properties. Additionally, the constructed coin cells' electrochemical behavior analyses shed light on their well-known higher initial cycle capacity of about 700 mAh g−1, demonstrating BWS nanostructures' superior capacity for lithium-ion storage (Li-ion). In contrast, in supercapacitor studies, a half-cell configuration with a 6 M KOH electrolyte achieved its maximum specific capacity of 1158C g−1 at a current density of 3 A g−1. Similarly, Trasatti's analysis shows that the false nature of the BWS/RGO material results in 83 % over capacitive behavior of 17 %. When it comes to effectively developing a material process technique for multi-metal oxides and associated RGO nanocomposites, the reported quick single-pot SCW approach has shown encouraging results. © 2023
Strain induced structural transformation, mechanical and phonon stability in silicene derived 2D-SiB
(Korean Society of Industrial Engineering Chemistry A-803 Twin Bldg 275-3 Yangjae-Dong Seocho-Kul Seoul 137-130, 2020) M.s, M.; Thomas, S.; P, A.; Lee, S.U.; Ajith, A.K.
Two-dimensional monolayer SiB is a silicene derivative exhibiting buckling of atoms similar to that seen in silicene. This manuscript presents a systematic study of the strain-dependent variation of the structural, mechanical, and dynamical properties of SiB. Strain was applied in the uniaxial armchair, uniaxial zigzag, and biaxial directions within the range of ?0.2 to 0.3. The resultant strain energy plot indicates anisotropic behavior of SiB in these directions. The SiB showed a mechanical strength that was higher than its counterpart, silicene, by an order of 30%. The elastic constant data from the undeformed SiB indicated an anisotropic nature, which was also seen with all the strain directions. Charge density contours, along with Bader charge analysis, confirmed the ionic nature of SiB in its original form. This nature became covalent as the strain varied from the compressive to the tensile regime in the uniaxial zigzag and biaxial directions. The major finding described in this manuscript is a new flat conformation having orthorhombic symmetry in contrast to the buckled structure. In addition, this material was observed to attain stability with the application of uniaxial tensile armchair and zigzag directional strains. Ab-initio molecular dynamics simulation confirmed the thermal stability of SiB in its new conformation. © 2020 The Korean Society of Industrial and Engineering Chemistry
Survey: Neural Network Authentication and Tampering Detection
(Springer, 2023) Kumar, R.; P, A.; Naveen, B.; Chandavarkar, B.R.
Neural networks have become quite the buzzword in a decade, resulting in extensive research and extensive integration of neural networks in application development. From self-driving vehicles to IoT devices, each such area has seen some form of integration of a neural network(s). Image and video content have found application in medical, forensic, etc. Due to the excessive use of digital content, there has also been a rise in various advanced image editing applications such as Photoshop, making it easier for people to tamper with images. Therefore, coming up with techniques to validate or authenticate images has gained much interest in recent times. Current neural network-based methods can see all kinds of tampering because neural network capability extracts complex features from the images, making them more effective. Thus, in this study, we review some image forgery techniques and look over how neural networks find their application to detect forgery and authenticate images. Â© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.