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Applying Artificial Bee Colony Algorithm to Improve UWSNs Communication
The research in this study aims at implementing the ABC algorithm to enhance the communication within UWSNs. The ABC algorithm, motivated by the CPG approach being analogous to that of honey bees searching for food, specifies optimal values for critical parameters of the network such as energy consumption, reliability in data transfer, and scalability. From the analyses conducted in this exposition, it is apparent that the envisaged methodology outperforms other conventional routing parlances in the following ways: minimal energy usage, high data delivery ratios, low packet drops, and longest network lifetime. Therefore, from the above results it can be concluded that, the said ABC algorithm is helping in achieving a better result in terms of improved underwater communication as well as in mitigating with the difficulties of UWSNs. 2024 IEEE. -
Impact of Artificial Intelligence on Business Strategy and Decision-Making
Market analysis as knowledge-enhancement function, its use in internal politics, its abuse, and its ability to generate market understanding were recognised as the four key performance variables in market analysis. Profitability and bottom line may be increased, inefficiencies in corporate processes can be reduced, and other hidden insights can be uncovered by analyzing financial accounting transactions. The research focuses on the business strategy in decision-making using artificial intelligence. Reviewing existing research and providing recommendations. In this study, firstly collect the dataset finance data from Kaggle for the better-trained model. After that perform the pre-processing data for outlier removal. The implementation work is complete on the Python programming language. The results showed that the proposed KNN, the Decision tree model, achieved high accuracy. Businesses and organisations working in the field of artificial intelligence (AI) might greatly benefit from this research in terms of narrowing down the profiles that are certain to avoid in the future. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
A Intelligent Approach for Fault Detection in Solar Photovoltaic Systems based on BERT-BiGRU Network
Large-scale photovoltaic (PV) plant problem identification and diagnosis is expected to grow more difficult in the future as more and more plants of increasing capacity enter into existence. To keep large-scale PV installations safe, reliable, and productive, automatic identification and localization of any mal-operation among thousands of PV modules is necessary. In order to identify problems in PV plants, the suggested method compares the 'residuals' (fault indicator signals) generated by each string to a predetermined threshold. The suggested method relies on three distinct processes: data preparation, feature extraction, and model training. Preprocessing employs the method of Transform Invariant Low-rank Textures (TILT). The most useful and efficient measurements from feature extraction are kept while less important ones are discarded in favor of the Reduced Kernel PCA technique. Let's move on to model training with BERT-BiGRU. The proposed method is clearly superior compared to the two leading options, BERT and GRU. The proposed method had a 97.36% success rate. 2023 IEEE. -
Recent Research in Management, Accounting and Economics (RRMAE): A case study on Recent Research in Management, Accounting and Economics
The conference brought together innovative academics and industrial experts to present novel contributions related to real-world aspects of Economics, Management and Accounting. The primary goal of the conference was to promote research and developmental activities in these three fields. Another goal was to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. 2025 selection and editorial matter, Hafinaz, Hariharan R and R. Senthil Kumar. -
Digrich Chai Kashmirs Bygone Evenings
[No abstract available] -
Economic aspects of marine biopolymers
The usage of synthetic polymers such as plastic is a much-debated topic across the globe for a reason; it is not recyclable and harms the environment. However, todays consumers have shifted their preferences to eco-friendly products over harmful products. The biopolymers market globally accounted for about $13.7 billion in 2021, and by 2030, its projected to reach over $35.2 billion, growing at 11.07% [compound annual growth rate (CAGR)]. By 2026, the marine biotechnology sector will be worth $5 billion worldwide. Despite the manufacturing cost of marine biopolymers being higher than that of standard polymers, the market is growing faster because of its benefits across various industries and mainly for stakeholders. The biopolymer industry has evolved due to the depletion of petroleum reservoirs. Key players from countries such as the United States, Brazil, Germany, Netherlands, Italy, United Kingdom, Japan, Germany, and Australia are in the biopolymers market. Different classes of marine biopolymers and their industrial applications prove the precious value of ocean resources to society. 2025 Elsevier Ltd. All rights reserved. -
Recent Advances in Pedestrian Identification Using LiDAR and Deep Learning Methods in Autonomous Vehicles
The myriad benefits of autonomous vehicles (AVs) encompassing passenger convenience, heightened safety, fuel consumption reduction, traffic decongestion, accident mitigation, cost-efficiency and heightened dependability have underpinned their burgeoning popularity. Prior to their full-scale integration into primary road networks substantial functional impediments in AVs necessitate resolution. An indispensable feature for AVs is pedestrian detection crucial for collision avoidance. Advent of automated driving is swiftly materializing owing to consistent deployment of deep learning (DL) methodologies for obstacle identification coupled with expeditious evolution of sensor and communication technologies exemplified by LiDAR systems. This study undertakes exploration of DL-based pedestrian detection algorithms with particular focus on YOLO and R CNN for purpose of processing intricate imagery akin to LiDAR sensor outputs. Recent epochs have witnessed DL approaches emerge as potentially potent avenue for augmenting real-time obstacle recognition and avoidance capabilities of autonomous vehicles. Within this scholarly exposition we undertake exhaustive examination of latest breakthroughs in pedestrian detection leveraging synergy of LiDAR and DL systems. This discourse comprehensively catalogues most pressing unresolved issues within realm of LiDAR-DL solutions furnishing compass for prospective researchers embarking on journey to forge forthcoming generation of economically viable autonomous vehicles. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Segmentation of ancient and historical gilgit manuscripts
The Gilgit manuscripts belong to fifth century A.D. and are oeuvre of texts which deal with Buddhist work. It is one of the oldest manuscripts in the world and is considered to be a milestone in the history of Buddhist works in India. It is a collection of both official and unofficial Buddhist works which are believed to have helped in the evolution of many literatures including Chinese, Japanese, and Sanskrit. Since this manuscript is almost seventeen centuries old it has not been able to fully decipher the text yet. It has been laminated by the National Archives of India which proves it is one of the most important literatures concerning India. In this paper, we perform character- based image segmentation on Gilgit manuscript in order to simplify and to better identify character in the image of the manuscript. The employed method gives an accuracy of nearly 87%. Springer India 2016. -
Further results on induced graphoidal decomposition
Let G be a nontrivial, simple, finite, connected and undirected graph. A graphoidal decomposition (GD) of G is a collection ? of paths and cycles in G that are internally disjoint such that every edge of G lies in exactly one member of ?. As a variation of GD the notion of induced graphoidal decomposition (IGD) was introduced in [S. Arumugam, Path covers in graphs (2006)] which is a GD all of whose members are either induced paths or induced cycles. The minimum number of elements in such a decomposition of a graph G is called the IGD number, denoted by ?i(G). In this paper, we extend the study of the parameter ?i by establishing bounds for ?i(G) in terms of the diameter, girth and the maximum degree along with characterization of graphs achieving the bounds. 2013 World Scientific Publishing Company. -
Computational studies into the chemical nature, thermal behaviour, solvent role, reactivity and biological evaluation of Rigidin E A marine alkaloid with potent liver cancer inhibition
The current work includes theoretical studies of Rigidin E (marine alkaloid) molecule with the DFT technique and evaluation of its biological properties in silico. DFT calculations in different media were performed for the title molecule. Gradual changes were noticed in the properties of the title compound when subjected to solvation in polar solvents. Electron density distribution, interaction and excitation were demonstrated using topological studies (ELF, LOL, RDG, and charge transfer) done using Multiwfn software. From FMO analysis, methanol is the solvent in which the title compound has the highest band gap value (3.8972 eV) compared to other solvents, and in the gas phase it has a band gap value of 3.6886 eV. Theoretical UV studies show that n ->?* and n ->?* electronic transitions are significant in Rigidin E. In water, the title molecule has a first-order hyperpolarizability about 100 times that of the reference substance urea, indicating its powerful NLO potential in aqueous medium. ADMET profile was generated using online tools (ADMET lab 2.0, PreADMET, and SwissADME). For the title molecule, docking was done against select liver cancer targets using AutoDock Tools and the lowest binding affinity was obtained ?4.62 kcal/mol against 4H6J protein. 2023 Elsevier B.V. -
Changes in the dynamic profile of beneficial metabolites during Panax ginseng somatic embryogenesis
In this study, we characterized the dynamic changes in the metabolite profiles of Panax ginseng during somatic embryogenesis (SE) to explore their stage-specific functional potential. We quantified phenolic compounds and amino acids using high-performance liquid chromatography (HPLC), while bioactive metabolites were identified through LC-MS/MS analysis. During SE, the total phenolic content (TPC) and total flavonoid content (TFC) significantly increased at the globular-to-torpedo (GT) stage, exhibiting enhanced antioxidant activity. Anti-inflammatory activity and cytoprotective effects peaked during the young plantlet (Yp) stage, driven by the accumulation of terpenoid metabolites, such as ginsenosides Rd and sarcostin. Additionally, at the embryogenic stem cell (ESC) stage, stress-related amino acids such as GABA and proline, along with metabolites like venlafaxine, clebopride, and nemonapride, which possess neuromodulatory properties, were distinctively accumulated. These results reveal the stage-specific metabolites and associated biological characteristics of ginseng SE, demonstrating the potential of ginseng-derived metabolites for pharmacological and nutraceutical applications. 2025 The Authors -
Exploring the Relationship Between Leadership and Well-Being
Leadership and well-being are deeply intertwined, influencing individuals and organizational dynamics in profound ways. This study explores the bidirectional relationship between leadership styles, emotional intelligence, organizational culture, and well-being. By examining frameworks such as transformational, democratic, and ethical leadership, the research highlights the importance of adaptive, inclusive, and emotionally intelligent leadership in fostering employee satisfaction, mental health, and work-life balance. Additionally, the role of positive organizational culture and the evolving challenges of remote and hybrid leadership are analyzed. Findings suggest that leaders who emphasize empathy, ethics, and inclusivity create environments conducive to personal and collective growth. This comprehensive review provides actionable insights for leaders, policymakers, and organizations striving for effective leadership and enhanced employee well-being. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Quantum leap in quick commerce: Harnessing quantum computing for sustainable and efficient logistics
This chapter explores how quantum computing can revolutionise the quick commerce industry, focusing on logistics and supply chain management to boost efficiency and sustainability. Quick commerce, an emerging trend in e-commerce, promises incredibly fast delivery speeds to satisfy ever-growing consumer expectations. But this rapid expansion isnt without its hurdles, particularly when it comes to maintaining smooth operations and being eco-friendly. Quantum computing steps in as a potential game-changer, bringing its powerful processing abilities to the table. Integrating quantum computing into quick commerce could transform logistics operations, from planning delivery routes to managing warehouse resources. Its not just about speeding things up; its about rethinking the entire supply chain, including how we handle inventory and the final leg of delivery. Quantum algorithms, which are built on the principles of quantum mechanics, can help companies predict demand more accurately, restock shelves faster, cut down on waste, and enhance overall efficiency. These algorithms are especially good at optimising routes in real time, considering various factors to ensure quicker, more dependable deliveries. This study aims to bridge the gap between the theory and practice of quantum computing in logistics. It examines how quantum computing can be used, its possible benefits, and the challenges it might face in the quick commerce sector. The chapter argues that quantum computing could usher in a new era of logistics management characterised by unprecedented efficiency in routing deliveries, controlling inventory, and allocating resources. Highlighting the use of quantum algorithms for dynamic routing and demand forecasting underscores the potential for creating a more agile and eco-friendly delivery system. Ultimately, this research shines a light on how we can turn the conceptual promise of quantum computing into real-world improvements in quick commerce logistics, advocating for a future where quantum computing leads to a sustainable and efficient quick commerce ecosystem. 2026 selection and editorial matter, Pushan Kumar Dutta, Pronaya Bhattacharya, Jai Prakash Verma, Ashok Chopra, Neel Kanth Kundu and Khursheed Aurangzeb; individual chapters, the contributors. -
Does AI matter in marketing? Unveiling the role of AI-driven marketing in quick grocery
This study explores the impact of AI-driven marketing techniques on consumer attitudes and purchase intentions in the growing Q-grocery sector. The increasing use of AI in digital marketing presents opportunities to examine its influence on consumer decision-making, yet its specific impact within grocery shopping apps remains underexplored.Using theStimulus-Organism-Response (SOR) model, this study examines how AI-driven marketing techniques, namely personalisation, smart search, and dynamic pricing, influence consumer behaviour. Data were collected from 327 respondents through an online survey targeting users of Q-grocery shopping apps in India. Structural Equation Modelling (SEM) was used to test the relationships between AI marketing techniques and consumer purchase intentions.Findings reveal that personalisation and smart search have a significant positive impact on purchase intention, while dynamic pricing showed no significant effect. Additionally, consumer hedonic and utilitarian attitudes were found to mediate the relationship between AI marketing techniques and purchase intention. By connecting AI marketing strategies to purchase intention and consumer attitudes, this research adds a new perspective on how digital tools can influence consumer decision-making. These findings hold broader implications for omnichannel environments, where consistency in AI-enabled experiences across digital and physical touchpoints is critical for sustaining engagement. It also provides valuable insights for marketers seeking to enhance engagement and increase sales through targeted AI-driven strategies. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
From convenience to sustainability: Reimagining quick commerce in India
The concept of quick commerce, characterised by its promise of near-instant gratification through delivering goods and services within remarkably short time frames, has set new benchmarks for consumer expectations. However, this convenience often comes at an environmental cost, ranging from increased carbon emissions to excessive packaging waste. In this context, this paper aims to explore the sustainability of quick commerce in India, examining its business models and evaluating its impacts through the lens of the three pillars of sustainability: economic, social, and environmental. This research aims to provide a comprehensive overview of quick commerce, evaluate its viability and sustainability in India using case studies, and offer strategic suggestions to balance this sector's rapid growth with responsible business practices. Given the urgency of the sustainability issue in the quick commerce sector, this paper contributes to the ongoing discourse on how emerging business trends can align with sustainable development goals by providing a holistic view of quick commerce in India. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Enhancing Quick Commerce Service Experience Through AI Marketing: An Empirical Investigation
This study examines the impact of AI-driven marketing strategies on quick commerce service experience (QCSE). Specifically, it investigates how personalization, smart search, and dynamic pricing influence consumers' perceptions of service experience in ultra-fast delivery platforms. Using partial least squares structural equation modelling (PLS-SEM) on survey data from 427 quick commerce users in India, the study finds that personalization has the strongest positive effect on QCSE, followed by dynamic pricing, while smart search has a weaker yet significant impact. The research validates QCSE as a higher-order formative construct comprising app design, security, fulfilment, and service support dimensions. The findings contribute to signaling theory by demonstrating how AI-driven marketing features serve as signals of platform experience perceptions. For practitioners, the results highlight the importance of AI-powered personalization and pricing strategies in enhancing service experiences. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Robust Control of DFIG Based Wind Energy System Using an H? Controller
Wind Energy Conversion System (WECS) using a Doubly Fed Induction Generator (DFIG) is popular due to its control flexibility and higher conversion efficiency, but maintaining the operational stability and optimal efficiency under dynamic wind conditions is still a control challenge. In this paper, a nonlinear mathematical model for a DFIG based WECS was developed from fundamentals and its characteristics near the operating point were studied. A Proportional Integral (PI) controller and a Linear Quadratic Regulator (LQR) controller were designed to control the system and the behavior of the closed-loop system with these controllers was studied. While the designed PI controller failed to ensure stability, the LQR controller was giving stability but an LQR controller is vulnerable to loss of stability under uncertainties due to parameter variations or changes in operating points. A suboptimal H? controller was then synthesized to obtain robust control. The closed-loop system performance of the DFIG system with the proposed controller was found to be stable and superior to PI and LQR controllers in terms of performance. 2021, The Korean Institute of Electrical Engineers. -
Multi-Objective Reinforcement Learning With Physics-Aware Vehicle Dynamics for Safe and Efficient Adaptive Cruise Control
Adaptive Cruise Control (ACC) enhances safety and comfort in autonomous vehicles by maintaining appropriate inter-vehicular distance and speed regulation. Traditional ACC systems based on PID or Model Predictive Control (MPC) often struggle to handle complex, unforeseen traffic scenarios such as sudden braking, pedestrian crossings, or lane changes. Reinforcement Learning (RL) offers an adaptive alternative by enabling policy learning through environment interaction. However, existing RL-based ACC methods frequently suffer from poor smoothness and energy inefficiency under emergency conditions. This work proposes an enhanced RL-based ACC framework that integrates a physics-informed, multi-objective reward function to jointly optimize safety, ride comfort, and energy efficiency. The reward components are normalized and dynamically weighted based on the current driving context, allowing the agent to adaptively prioritize objectives. Vehicular dynamics are explicitly incorporated into the learning process to improve real-world applicability. The system is trained using the DDPG algorithm, which supports continuous control and stable policy convergence. Extensive MATLAB-based simulations were conducted across diverse urban driving scenarios including stopgo traffic, traffic signals, lane changes, and pedestrian interactions. Comparative analysis against PID and MPC-based ACC controllers demonstrates that the proposed framework achieves superior performance in maintaining safe inter-vehicular distance, reducing jerk, and improving energy efficiency. This study validates the feasibility of deploying a computationally efficient, model-free RL-based ACC for robust and safe autonomous driving in dynamic traffic environments. The Author(s), under exclusive licence to ITS Japan 2026. -
Mechanical Characterization of Cu-Al-based Shape Memory Alloys: Influence of Mn, Be and Fe on Tensile Strength, Yield Stress, Yield Strain, Ductility and Hardness
The pursuit of cost-effective and robust Shape Memory Alloys (SMAs) continues to expand, especially for applications in adaptive and smart structural systems, while Ni-Ti-based SMAs remain prevalent due to their superior pseudoelasticity and longevity. However, the limitations of NiTi alloys, including the high processing costs and fabrication difficulties, prompt the exploration of alternatives. This study investigates Cu-Al-based SMAs alloyed with Mn, Be, and Fe as cost-effective alternatives to NiTi systems. In the present work, Cu-Al-based alloy wires with Mn, Be, and Fe were betatized at 850 C and water-quenched to achieve martensitic structures, followed by evaluation of tensile strength, yield behavior, ductility, and hardness. Mn addition significantly enhanced tensile strength (up to 425 MPa), while Be and Fe improved ductility through grain refinement. Hardness increased with Mn due to solid solution strengthening. Thus, the current work provides a comparative analysis of Cu-Al-Mn, Cu-Al-Be-Mn, and Cu-Al-Fe-Mn alloys, linking alloying strategies to microstructural evolution and mechanical performance, demonstrating their potential for advanced engineering applications. 2025 King Mongkuts University of Technology North Bangkok. All Rights Reserved. -
An ethnographic expose of Mithun-human interrelationship among the Kuki community of Northeast India
Unrestrained consumption and a lack of a proper breeding ecosystem have depleted the variety and species count of mithun (Bos frontalis). Indigenous Kuki tribes have a unique relationship with mithun, reared in the semi-domestic countryside. For the Kuki community, a mithun is used during community festivals, as a bride price in marriages, to settle disputes, in land-deed covenants, and at death ceremonies. Mithun-human interrelationship lessens poverty, empowers community survival, guarantees the completion of critical cultural obligations, and maintains marital bonds in the Kuki community. The head of a mithun signifies solemnity and celebration in many cultural underpinnings. A white cock, a dog, a goat, a pig, and a mithun were sacrificial elements to appease the unseen spirits for good health and prosperity. While some Indigenous practices have faded with the arrival of Christianity, the cultural involvement of mithun persists to this date. 2023 Informa UK Limited, trading as Taylor & Francis Group.