International Journal of Innovations in Science, Engineering And Management
IJISEM International Journal of Innovations in Science, Engineering And Management A Peer-reviewed Scholarly Indexed Quarterly Journal International Journal of Innovations in Science, Engineering, and Management (IJISEM) is an open-access publication overseen by IJISEM Journals. It is dedicated to fostering the interests of emerging and promising writers. IJISEM endeavors to transcend geographical boundaries by welcoming contributions from professionals and academics worldwide, not limited to India. We thus adopted the term International as our motto and used it in the title of our journal. We are dedicated to fostering innovation and excellence across scientific, engineering, and management disciplines through our commitment to sharing knowledge. The publication focuses on research and intellectual viewpoints in order to achieve this goal. Realistic analysis, interdisciplinary/applied/methodological, empirical evidence production and utilization, critical viewpoint development and policy building work are all welcome in achieving this goal. IJISEM aims to provide a platform for doctoral researchers to showcase their investigations and disseminate their research findings and knowledge to a wider audience. IJISEM International Journal of Innovations in Science, Engineering and Management Title IJISEM International Journal of Innovations in Science, Engineering And Management Frequency Quarterly (July, October, January and April) ISSN 2583 – 7117 Publication Format Online Chief Editor Dr. Rajesh Gupta Publisher Yogesh Sharma, M.Tech (Industrial Design) Subject Multidisciplinary Published by IJISEM Journals Starting Year 2022 E-Mail editor@ijisem.com Mobile No (+91) 70893666889 Mobile No (+91) 9981622288 Publishing Body AG Publishing House Language Multiple Languages Copyright AG Publishing House Website http://www.ijisem.com/ Address IJISEM Journals 57-First Floor, Susheela Bhawan, Priyadarshini Phase-3, near Meenakshi Planet City, Bagmugaliya, Bhopal, Madhya Pradesh 462043
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Mathematical Modelling And Simulation-Based Evaluation Of Electric Powertrain Performance
This study presents a mathematical modeling and simulation-based framework for evaluating the electric powertrain performance of mini passenger electric vehicles under standardized driving conditions. The framework integrates vehicle longitudinal dynamics, electric motor characteristics, transmission behavior, and battery performance using MATLAB/Simulink. The New European Driving Cycle (NEDC) and Modified Indian Driving Cycle (MIDC) are used for detailed simulation and graphical analysis, while FTP-75 results are included in the comparative performance tables. The model considers kerb weight, gross vehicle weight, rolling resistance coefficient, aerodynamic drag coefficient, wheel radius, gear ratio, drivetrain efficiencies, and battery capacity. The simulations compare tractive-force demand, motor speed and torque, battery power and current, state of charge, and energy consumption. The results show that the selected driving profile significantly influences aerodynamic loading, battery demand, and energy performance. NEDC produces comparatively higher high-speed loading, whereas MIDC represents repeated acceleration and deceleration conditions relevant to Indian driving environments. The developed framework provides a repeatable basis for evaluating powertrain behavior and comparing vehicle configurations under different standardized cycles.
Copyright (c) 2026 Ramkrishna Mohan Kambli, Prof. Sagar S. Navale https://creativecommons.org/licenses/by-sa/4.0
Nature’s Fury: The Role of Environmental Elements in N.K. Jemisin’s The Fifth Season
N.K. Jemisin’s The Fifth Season reimagines environmental catastrophe as a powerful medium for examining systemic oppression, identity, and resilience within speculative fiction. While existing scholarship has primarily focused on the novel’s Afrofuturist dimensions, racial politics, and world-building, comparatively less attention has been devoted to the symbolic function of environmental forces as interconnected representations of power, existential threat, and transformative agency. Employing a qualitative textual analysis informed by ecocritical theory and close reading, this study investigates how geological instability, seismic activity, and the sentient Earth shape both the narrative structure and the lived experiences of the Orogenes. The analysis demonstrates that environmental elements operate beyond mere setting; they function as metaphors for institutional violence, ecological imbalance, and the persistent marginalization of vulnerable communities. Simultaneously, these same forces become instruments of resistance and renewal, enabling the Orogenes to reclaim agency and challenge oppressive social systems. By examining the interconnected relationship between environmental catastrophe and social injustice, this paper argues that Jemisin redefines ecological disruption as a political and ethical discourse on survival, transformation, and collective resilience. The study contributes to contemporary scholarship on ecocriticism, climate fiction, and speculative literature by highlighting how The Fifth Season employs environmental symbolism to interrogate structures of domination while envisioning possibilities for social and ecological renewal.
Copyright (c) 2026 Hensi Chelani https://creativecommons.org/licenses/by-sa/4.0
Goods and Services Tax (GST), implemented in India on July 1, 2017, replaced multiple indirect taxes such as VAT, Excise Duty, and Service Tax with a unified dual-tax structure comprising CGST, SGST, UTGST, and IGST. This paper examines the impact of GST on the Indian economy through exploratory research based on secondary data drawn from journals, articles, and government sources. The study outlines the basic features, benefits, and challenges of GST, and evaluates its sector-wise impact across electronics, FMCG, automobiles, textiles, real estate, banking, and logistics. Findings indicate that GST has simplified tax compliance, reduced cascading taxation through Input Tax Credit, improved transparency, widened the taxpayer base, and boosted government revenue and GDP growth. However, small businesses continue to face challenges related to compliance costs, technical difficulties, and frequent regulatory changes. The paper concludes that despite transitional hurdles, GST has emerged as a transformative reform strengthening India's economic structure and ease of doing business.
Copyright (c) 2026 Gomati Prasad Rai https://creativecommons.org/licenses/by-sa/4.0
Income tax, as a direct tax levied by the Central Government, plays a crucial role in shaping India's economic development by generating revenue, reducing income inequality, and financing public welfare programmes. This paper examines the concept, importance, trends, and patterns of income tax in India, along with its broader economic impact on consumption, savings, investment, and fiscal stability. The study also introduces the newly enacted Income-tax Act, 2025, which replaces the Income-tax Act, 1961, and represents a shift towards a simplified, technology-driven, and taxpayer-friendly direct-tax framework effective from 1 April 2026. Based on secondary data drawn from RBI publications, government reports, and Economic Survey 2025-26, the analysis shows substantial growth in personal income tax and non-corporate tax collections between FY 2022 and FY 2025, outpacing overall GDP growth. The findings highlight income tax's growing significance in strengthening India's fiscal framework and supporting sustainable economic growth.
Beyond Single-Modality Detection: A Systematic Review of Multimodal AI for Social Media Cybercrime
Social media platforms have emerged as a key battleground for cy-bercriminals, which leverages the speed, scale and interconnectedness of social media to orchestrate financial crimes such as phishing and OTP Fraud, identity-based crime such as deep-fake and account takeover, and social harms such as cyberbullying and coordinated influence campaigns. The threats are increasingly multifaceted and cross-platform, making it difficult for traditional detection solutions to stay ahead of the curve, as they are typically limited to a specific data type or a single platform. We review recent publications on detecting cybercrime in social networks ranging from misinformation detection, to machine learning and deep learning based classifiers, fraud and intrusion detection pipelines, to novel multimodal architectures for AI. The reviewed literature can be divided into three the-matic groups: (1) detection methods based on content and propagation patterns, (2) methods based on user behaviour and network structure, and (3) multimodal fusion models coupled with explainable AI mechanisms. We evaluate the data sets used, algorithm selection, reported performance, and inherent limitations of the underlying studies for each cluster. The analysis shows that there is a gap. Although there has been significant progress in the detection of individual tasks, existing systems are still highly specialised and platform-dependent, or type-dependent, or modal-ity dependent. Very few integrate text, image and behaviour into a single model. It also identifies a lack of attention to interpretability and cross-platform real time operation. To address these gaps, we suggest the necessity of developing a multimodal detection system that is uniform, adaptive and explainable, which can work in heterogeneous environments on social media platforms, and we propose some research directions for achieving this goal.
Copyright (c) 2026 Ekta R. Kaneriya, Disha M. Ganatra https://creativecommons.org/licenses/by-sa/4.0
Digitalisation impact on Retail Sector in Comparison with Pre and Post Pandemic Periods - Consumers Perspective
The rapid expansion of digital technologies has significantly influenced the retail sector and transformed the way consumers search, evaluate, purchase, and pay for products. The present study examines the impact of digitalization on consumers’ retail behaviour by comparing the pre pandemic and post pandemic periods. The study adopted a descriptive and analytical research design and collected primary data from 500 consumers across ten selected districts of Madhya Pradesh through a structured questionnaire. Consumer responses were measured using a five-point Likert scale across 15 statements covering online shopping, digital payments, mobile applications, online information, price comparison, home delivery, digital promotions, convenience, and satisfaction. Descriptive statistics and a paired samples t test were employed for data analysis. The findings reveal a clear shift towards greater adoption and acceptance of digital retail practices in the post pandemic period. The overall mean score declined from 45.61 to 33.51, while the paired samples t test showed a statistically significant difference (t = 33.910, p = 0.000). The study concludes that digitalization has substantially influenced consumers’ retail behaviour, preferences, perceptions, and shopping experience.
Copyright (c) 2026 Amreen Khan, Punnam Veeraiah, Santosh Shrivastav https://creativecommons.org/licenses/by-sa/4.0
Role of RBI in Development of India Economy
The Reserve Bank of India (RBI), established in 1935 and nationalized in 1949, serves as the central banking authority responsible for maintaining monetary and financial stability in India. This review paper is exploratory in nature, based on secondary data drawn from RBI publications, government reports, research papers, and academic journals. It examines the organizational structure of RBI, its major functions—including currency issuance, banking regulation, credit control, foreign exchange management, and acting as banker to the government—and its broader role in India's economic development. The study also reviews key initiatives undertaken by RBI, such as promoting financial inclusion, digital payments, priority sector lending, MSME finance, and banking sector reforms. Findings indicate that RBI has been instrumental in maintaining price stability, strengthening the banking system, supporting international trade, and fostering inclusive and sustainable economic growth across India, particularly through its adaptive and responsive regulatory approach in recent years.
Farm-Scale Production Performance of An Integrated Poultry–Fish Farming System Using Murrel (Channa Striatus) And Sonali Poultry: A Six-Month Case Study from Kothapally (V), Mupkal (M), Nizamabad District, Telangana, India
Integrated farming systems provide opportunities to combine multiple agricultural enterprises within a single production unit to improve resource utilization, diversify income sources, and enhance farm sustainability. This study describes the operational performance of a farm-scale integrated poultry–fish farming system involving murrel (Channa striatus) culture and Sonali poultry production at Kothapally Village, Mupkal Mandal, Nizamabad District, Telangana, India. The study evaluated farm configuration, fish production performance, poultry management practices, infrastructure development, water quality management, and economic outcomes during a six-month production cycle. The integrated farm was established on approximately 2 acres of leased land and consisted of one fish culture pond and two poultry sheds. The fish pond measured approximately 15 ft width × 50 ft length and was divided into four separate blocks for size-based management. The first two blocks consisted of fish with an average body weight of approximately 250 g, while the remaining two blocks consisted of larger fish weighing approximately 800 g to 1 kg. A total of 4000 murrel (Channa striatus) fish were stocked and managed using block-wise feeding practices. Fish were supplied with Stella commercial feed containing approximately 40% crude protein, with 4 mm pellets provided to 250 g fish and 6 mm pellets supplied to larger fish groups. During the six-month culture period, 3650 fish survived, while 350 fish were lost, resulting in a survival rate of 91.25%. The harvested fish achieved an average body weight of approximately 1 kg per fish, producing approximately 3650 kg of fish biomass. Water quality parameters including temperature, pH, dissolved oxygen, and ammonia were maintained within suitable operational ranges for murrel culture. The poultry component consisted of two sheds, each with a capacity of approximately 5000 Sonali breed chicks. Ten-day-old chicks were purchased at approximately ₹28 per bird and reared using Bhavani commercial poultry feed. The birds achieved an average final body weight of approximately 1–1.2 kg per bird under farm management conditions. The poultry sheds were equipped with essential facilities including water supply, overhead tanks, lighting, feeders, drinkers, rice bran flooring, mats, side walls, and green shade materials. The integrated farming system generated an estimated net return of ₹320,000, considering combined production outputs and operational expenses. The results indicate that integrated murrel–poultry farming can serve as a practical approach for improving resource utilization, reducing production risks, and generating diversified income opportunities for small and medium-scale farmers under Telangana farming conditions.
Copyright (c) 2026 Rama.K, Pavan Kumar K., P. Padmavathi, Malsoor Thirumala https://creativecommons.org/licenses/by-sa/4.0
“Examining English Speaking Anxiety Among Hindi-Medium Female Students in Dehradun”
This study explores English-speaking anxiety among Hindi-medium female students in secondary and senior secondary schools in Dehradun, Uttarakhand, an area which is relatively under-researched when it comes to English language teaching research in India. Using a mixed-method approach, quantitative data were gathered using a 31-item survey based on the Foreign Language Classroom Anxiety Scale from 93 participants, while qualitative data came through open-ended questions and interviews. Results showed a high level of English-speaking anxiety, with the shame from making mistakes in English the most prominent feature. It was found that the Ridicule Cycle was the main driving force behind English-speaking anxiety, where public ridicule creates ongoing fear of speaking English. Despite a positive attitude towards English language, it is also seen that there is widespread behavior of avoiding to speak English, thus resulting in a contradiction, which can be accounted to structural shortcomings in oral classroom practice.
Copyright (c) 2026 Shivangi Kapoor https://creativecommons.org/licenses/by-sa/4.0
A Comprehensive Review Of Neomarica Gracilis: Phytochemistry, Antidiabetic Activity, And Therapeutic Prospects
A chronic metabolic disorder called diabetes mellitus is characterised by persistent hyperglycemia brought on by decreased insulin production, insulin resistance, or both. The global prevalence of diabetes continues to increase, necessitating the development of safer and more effective therapeutic agents. Medicinal plants have gained significant attention due to their diverse bioactive compounds and minimal adverse effects compared to synthetic drugs. Neomarica gracilis, an ornamental perennial herb belonging to the Iridaceae family, has recently emerged as a promising medicinal plant because of its “rich phytochemical composition, including flavonoids, phenolic acids, alkaloids, tannins, saponins, and terpenoids”. These secondary metabolites have anti-inflammatory, glucose-lowering, and antioxidant properties that may be useful for managing diabetes. Streptozotocin (STZ)-induced diabetic rats represent one of the most widely accepted experimental models for evaluating antidiabetic agents because STZ selectively destroys pancreatic β-cells, mimicking diabetic pathology. This review discusses the pharmacological significance of Neomarica gracilis, the pathophysiology of diabetes mellitus, the mechanism of STZ-induced diabetes, phytochemical constituents responsible for antidiabetic activity, experimental approaches for evaluating antidiabetic efficacy, and possible molecular mechanisms underlying glucose regulation. The review also highlights current research gaps, future perspectives, and the potential of Neomarica gracilis as a natural source for developing novel antidiabetic therapeutics.
Copyright (c) 2026 Yashvant, Priyanka more, Satkar Prasad https://creativecommons.org/licenses/by-sa/4.0
Farm-scale production performance of striped murrel (Channa striata) in a recirculating aquaculture system: A one-year case study from Maggi (V), Nizamsagar (M), Telangana, India
We documented a one-year farm-scale production cycle of striped murrel (Channa striata) in a recirculating aquaculture system (RAS) at Maggi Village, Nizamsagar Mandal, Telangana, India. The culture cycle extended from March 2025 to February 2026. A total of 2,200 fingerlings with an initial mean weight of approximately 20 g were stocked in a 50 m³ culture tank, corresponding to 44 fish m⁻³ and an initial biomass density of 0.88 kg m⁻³. The system incorporated mechanical solids removal, a UV chamber, a 3 hp recirculation pump, and one 2 hp blower distributing air through multiple diffusers; partial water replacement was conducted weekly. Fish received Growel floating pellets containing approximately 42% crude protein three times daily, with pellet size adjusted to fish size. Marketable biomass at the end of the cycle was approximately 1,800 kg, giving a final biomass density of 36 kg m⁻³ and a net biomass gain of 1,756 kg. At the reported apparent feed conversion ratio of 1.30, estimated feed input was 2,282.8 kg. No overt clinical disease outbreak was observed during routine monitoring. At a farm-gate price of ₹320 kg⁻¹, gross sales were approximately ₹576,000 (₹5.76 lakh). The case demonstrates the practical production potential of striped murrel in a compact RAS, while also showing that complete sustainability and profitability claims require verified water-use, energy, survival, feed-ledger, and cost data.
Copyright (c) 2026 S. Saiteja, Malsoor Thirumala, Pavan Kumar K., P. Padmavathi https://creativecommons.org/licenses/by-sa/4.0
Artificial Intelligence (AI)-Based Digital Payment Systems in India:Opportunities, Challenges, and Future Prospects
Artificial Intelligence (AI) is rapidly transforming India's digital payment ecosystem by improving trans­action security, operational efficiency, customer experience, and financial inclusion. The increasing adoption of AI-enabled technologies in digital payment platforms has enhanced fraud detection, risk management, personalized services, and decision-making. This study examines the opportunities, challenges, and future prospects of AI-based digital payment systems in India through a descriptive and analytical review of secondary data collected from peer-reviewed journals, RBI and NPCI reports, government publications, and other reliable sources. The findings indicate that AI has significantly improved the efficiency and security of digital payment systems. However, issues such as data privacy, cybersecurity, regulatory compliance, ethical concerns, and digital literacy continue to challenge its widespread adoption. The study concludes that AI can play a vital role in the future of India's digital payment ecosystem, provided its implementation is supported by effective governance, responsible AI practices, and a strong regulatory framework.
Copyright (c) 2026 Sachin Awasthi, Prity Deshbhrtar https://creativecommons.org/licenses/by-sa/4.0
This study presents a sector-specific macroeconomic analysis of globalization’s impact on India, focusing on Defense, Primary, Secondary & Tertiary, Energy, and Finance/FDI sectors. While globalization fosters foreign investment, market access, and technological growth, it also brings risks like over-dependence, trade imbalances, and strategic vulnerabilities. Existing studies largely emphasize GDP growth, FDI inflows, and employment trends but often overlook sector-level structural changes, policy shifts, and long-term implications. This research contributes to filling that gap by examining sector-specific transformations and broader patterns, especially amid rising deglobalization trends. Using a mixed-methods approach—combining descriptive and empirical tools like correlation and regression—the study highlights the need for nuanced policymaking. Key recommendations include strengthening regulatory frameworks, fostering self-reliance in critical sectors, and diversifying global partnerships. By offering sectoral insights and strategic directions, this paper supports more inclusive and sustainable economic development, addressing both the benefits and vulnerabilities globalization presents in India’s evolving macroeconomic landscape.
Copyright (c) 2026 Mahi Vyas, Radha P Tiwari https://creativecommons.org/licenses/by-sa/4.0
State-of-the-Art Developments in Luminescent Nanophosphors for Solid-State Technologies
The luminescent nanophosphors are advanced functional materials with excellent optical performance, tunable emission characteristics, high quantum efficiency, and good thermal and chemical stability, suitable for next-generation solid-state technologies. This review summarizes the recent advances in luminescent nanophosphors by highlighting the Principles of photoluminescence, host materials, luminescence mechanisms, enhancement methods, characterization methods, and technological applications of these phosphors. The effects of rare-earth and transition-metal doping, energy transfer phenomena, core–shell structures, quantum confinement, and plasmonic effects on the enhancement of the photoluminescence properties are critically analyzed. Advanced characterization techniques which permit the correlation of structural, optical, compositional, and thermal properties with luminescence behavior are also reviewed. Moreover, the paper emphasizes the growing possibilities of using nanophosphors in phosphor converted white light emitting diodes, optical thermometry, high resolution display techniques, and anti-counterfeiting and forensic devices. Although marked advances have been made, there are still problems of concentration quenching, thermal degradation, scale production, and long-term stability. Future studies that combine defect engineering, computational materials design, and sustainable synthesis will likely help to speed the advancement of the highly efficient nanophosphors necessary for new photonic and optoelectronic technologies.
Copyright (c) 2026 Vinod Kumar, Rakesh Kumar https://creativecommons.org/licenses/by-sa/4.0
A Faculty-Centered AI-Based Personalized Learning Framework for Undergraduate and Postgraduate Students in Higher Education
Personalized learning is increasingly relevant in higher education because students entering the same course can differ in prior knowledge, topic-wise performance, learning pace, engagement, and preferred learning resources. A common instructional sequence may therefore provide insufficient support for some learners while offering unnecessary repetition to others. Artificial Intelligence (AI), Machine Learning (ML), and learning analytics can support a more responsive approach by identifying learner patterns and recommending resources or activities according to observed needs. This paper proposes a faculty-centered AI-based personalized learning framework for undergraduate (UG) and postgraduate (PG) students. The framework combines academic performance, assessment results, learning behaviour, resource preferences, and learner level to construct an evolving learner profile. A personalization engine uses this profile to recommend suitable learning resources, topic difficulty, practice activities, and learning sequences. A feedback loop updates recommendations after subsequent learning interactions and assessments. In addition, a faculty-support layer presents summarized information about weak topics, progress, and assessment trends so that instructors can provide targeted academic intervention. The paper defines the research gap, framework architecture, methodology, data requirements, evaluation plan, and ethical safeguards. No experimental results are claimed because implementation and empirical validation are proposed as subsequent research stages.
Copyright (c) 2026 Vaijanti Soni https://creativecommons.org/licenses/by-sa/4.0
A Case Study on Channa striata Farming Practices for Sustainable Aquaculture Development in Dharpally Village, Nizamabad District, Telangana, India
Striped murrel (Channa striata) is a high-value freshwater fish with growing interest among farmers seeking alternatives to conventional carp-based aquaculture. This paper evaluates an eight-month grow-out cycle carried out in Dharpally Village, Nizamabad District, Telangana, using farm production and cost records. The earthen pond measured 120 ft × 100 ft with an average water depth of 5 ft, giving a surface area of 12,000 ft² (1,114.84 m²) and an estimated water volume of 1,699 m³. A total of 3,500 fingerlings measuring 2–3 inches were stocked. Mortality during the cycle was reported as 500 fish, corresponding to an estimated survival rate of 85.71%. Commercial Stella and Phai feeds were used, with pellet size increased from 1.2 to 8 mm as the fish grew. Eighty 40-kg bags were consumed, equivalent to 3,200 kg of feed. Against a harvested biomass of 2,500 kg, the calculated feed conversion ratio was 1.28, closely matching the farm-reported value of 1.3. Water was exchanged weekly and pH, dissolved oxygen, ammonia, nitrite, nitrate and temperature were monitored. Recorded values included pH 8.6, dissolved oxygen 6 mg/L, nitrate 0.25 mg/L and ammonia below 0.25 mg/L. Gross revenue from 2,500 kg sold at ₹270/kg was ₹675,000. Using the farm ledger total of ₹546,645, net operating return was ₹128,355 and return on investment was 23.48%. Feed accounted for 79.65% of recorded expenditure. The production cycle shows that pond-based C. striata culture can provide a viable high-value enterprise under local conditions, but profitability depends strongly on feed efficiency, survival, water management and accurate farm records.
Copyright (c) 2026 Meghalatha.Y, Pavan Kumar K., Malsoor Thirumala https://creativecommons.org/licenses/by-sa/4.0
A Study on Demat Account Sales and Capital Market Awareness.
Over the past decade, retail investor participation in India's capital markets has grown exponentially, driven by regulatory changes, technological advancements, and the rise of smartphone usage. Despite this, market participation remains low in comparison to the number of demat accounts opened. This research explores retail investor awareness of demat accounts, the impact of Bajaj Broking's digital EKYC 3.0 onboarding process, and the drivers behind platform choice among retail investors in Navi Mumbai. Using primary survey data of 50 respondents (out of 120 leads interacted in a two-month internship) and secondary sources on digital KYC uptake and competition in the brokerage industry, the study shows that perceived risk and security, and lack of financial literacy, remain the largest participation barriers. Brand trust, more than price, drives platform choice. The Electronic Know Your Customer 3.0 (EKYC 3.0) process enabled 64 percent of respondents to open an account in less than 15 minutes. The findings suggest that sustainable retail investor engagement requires a hybrid model combining digital efficiency with personalised, education-led advisory support.
Copyright (c) 2026 Bindal Totlani, Sandesh Suresh Suvarna https://creativecommons.org/licenses/by-sa/4.0
A Critical Analysis of the Finance MIS at Concerto Software & Systems
The paper assesses the usefulness and necessity of an Accounting Information System (AIS), or Internal Departmental Management Information System (MIS) in the finance department of Concerto Software System Pvt. Ltd. which deals in electronic payment solutions. The study evaluates system impact using qualitative and secondary research based on internal records, industry standards and published sources. The results indicate that structured Finance AIS enhances operational and strategic performance due to the strict control of direct, indirect and overhead costs which are classified systematically. It improves the accuracy of the reconciliation process, minimizes the duration of audit, reinforces revenue analysis, and aids in budgeting and predicting. The AIS, though facing challenges, such as user resistance and overloading of data, converts the transactional data into actionable intelligence, which will guarantee financial discipline and competitive advantage.
Copyright (c) 2026 Bindal Totlani, Soniya Shaji Palamattam https://creativecommons.org/licenses/by-sa/4.0
Generative Adversarial Networks for Anomaly and Malware Detection
Generative Adversarial Networks or GANs, have become a significant approach in deep learning along with Con-volutional and Recurrent Neural Networks, due to improvements in computing technology and more advanced ways to train these frameworks or models. Since GANs were first introduced in 2014, their application has expanded beyond image generation to include critical security tasks like anomaly detection and malware analysis. This paper offers a comprehensive survey of how GAN-based methods are utilized for identifying unusual and harmful activities in cyber settings. It examines key variants of GANs relevant to this field, explains their fundamental architectures and training methods, and explains their integration into systems to detect anomalies and malware. Additionally, the paper catalogs publicly accessible datasets and evaluation metrics frequently used in the reviewed studies to illustrate common experimental methodologies and research directions. Finally, it addresses ongoing challenges and potential future avenues for employing GANs to counteract emerging cybersecurity threats, highlighting their importance in developing more proactive and robust security measures.
Copyright (c) 2026 Amit Kumar Thakore, Neha Gupta, Akash Saxena, Amar Singh Verma https://creativecommons.org/licenses/by-sa/4.0
To Compare Various Frameworks that Integrate XAI, GANs and LLMs for Dynamic Malware Behavior Analysis
Modern malware frameworks use advanced evasion techniques that bypass traditional detection methods; thus entail advanced analytical frameworks for comprehensive and robust analysis. This study provides a comparative analysis of several frameworks that utilize Explainable Artificial Intelligence (XAI), Generative Adversarial Networks (GANs), and Large Language Models (LLMs) to provide a dynamic approach to malware behaviour. The review consisted of five key metrics to assess these three frameworks: detection performance, explainability, robustness against adversarial attacks, behavioral interpretation, and automated reporting capabilities. The results indicate that Deep Learning models have attained high accuracy in detect-ing and identifying malicious code, but are not interpretable. The GAN-based frameworks are highly effective in generating adversarial samples for robustness testing. Conversely, LLM-based approaches are highly effective for generating automated forensic reports, but are not yet fully integrated into malware detection workflows. The analysis highlights a research gap pertaining to the lack of integrated frameworks for adversarial analysis, explainability and automated forensic reporting. This study proposes a unified approach of malware analysis incorpo-rating XAI, GAN and LLM to enable the development of more effective malware detection tools with more transparency, deeper analytical insight and advanced forensic decision-making.
Copyright (c) 2026 Amar Singh Verma, Neha Gupta, Akash Saxena, Amit Kumar Thakore https://creativecommons.org/licenses/by-sa/4.0
Technology-Driven Entrepreneurship and Skill Development in India: A Conceptual Framework for MSME Growth
India’s Micro, Small and Medium Enterprise (MSME) sector is undergoing rapid technology-enabled transformation through digital payments, open digital commerce, artificial intelligence (AI), and government-supported skill-development initiatives. However, technology access alone does not ensure improved entrepreneurial performance; complementary digital, financial and managerial capabilities are required to convert digital infrastructure into productive use. This paper examines the convergence of technology adoption and skill development in Indian entrepreneurship using an integrative review of government publications, industry evidence and peer-reviewed research published or updated primarily during 2020–2026. The review synthesises evidence on four technology enablers—digital payments, open digital commerce, AI-enabled tools, and digital public infrastructure—and two complementary skill pathways: digital/financial literacy and managerial/entrepreneurial capability. Current evidence shows substantial scale: UPI processed 24,161.69 crore transactions worth ₹314.23 lakh crore in FY2025–26, while more than 1.16 lakh retail sellers were live on ONDC across 630+ cities and towns by December 2025. PMKVY had trained or oriented 1.64 crore candidates by March 2026. Building on these findings, the paper proposes a conceptual framework linking technology enablers and skill pathways to five entrepreneurial outcomes: operational efficiency, productivity, cost reduction, market reach and profitability. The framework is explicitly presented as a set of research propositions for future empirical testing rather than as an empirically validated causal model. The paper concludes with implications for entrepreneurs, training providers and policymakers.
Copyright (c) 2026 Ramkrishna Mohan Kambli, Vinayak M. Kambli https://creativecommons.org/licenses/by-sa/4.0
Effectiveness of POSHAN Abhiyaan in Improving Nutritional Outcomes Among Children Under Five, Pregnant Women and Lactating Mothers in In­dia
POSHAN Abhiyaan, India’s National Nutrition Mission, represents a comprehensive multi-sectoral initiative aimed at addressing malnutrition and improving nutritional outcomes among vulnerable population groups. The mission focuses particularly on children aged 0–5 years, pregnant women, lactating mothers, adolescent girls, and women of reproductive age. This research examines the development, objectives, implementation framework, and significance of POSHAN Abhiyaan in addressing nutritional challenges in India. A mixed-methods approach incorporating quantitative and qualitative perspectives is considered to assess nutritional indicators, programme implementation, stakeholder experiences, and regional variations. The study emphasizes the roles of government institutions, Anganwadi Centres, frontline workers, NGOs, and communities in delivering nutrition-related interventions. Technology-enabled monitoring, inter-sectoral convergence, behavioural change, and community participation through the Jan Andolan approach are identified as important components of the mission. The study highlights POSHAN Abhiyaan as an integrated framework for strengthening nutrition services, improving maternal and child health, reducing malnutrition, and supporting sustainable human and national development.
Copyright (c) 2026 Sanjeev Kumar, Shweta Mehra, Amol Ohol, Priyamvada https://creativecommons.org/licenses/by-sa/4.0
FOX NUT (MAKHANA): Bihar’s Superfood with Global Potential - A Multidimensional Analysis of Nutritional Value, Economic Prospects and Sustainable Commercialization
Makhana the popped kernel of Euryale ferox Salisb. Makhana has transformed from a local wetland crop of Bihar into an strategic and important functional food, export commodity and asset for rural development. This study shall build a multi-faceted empirical understanding of makhana through combining nutritional biochemistry, agricultural economics and export competitiveness, value-chain efficiency and sustainability. The paper creates an analytical dataset from secondary sources, including Government of Bihar production estimates tied to various government policies, evidence from ICAR-RCER value chains, PMFME/NIFTEM technical documentation and peer-reviewed food-science research as well as policy announcements in 2025, and uses descriptive statistics, CAGR estimation, correlation analysis, multiple regression, time-series projections and SWOT analysis. The nutrition comparison indicates that makhana is not a traditional high fat nut – rather it is a low fat, carbohydrate rich, low glycemic snack with significant protein and mineral content. The economic analysis shows robust growth in area, production, and market visibility, with the area expanding from the APEDA dashboard midpoint estimate of 2020 (7.3 Lakhs Ha) to 2025 expectation (14.5 Lakhs Ha), and the production rising from 2020 midpoint (0.5 Lakhs Ha) to 2025 expectation (1.5 Lakhs Ha) and the export volume steeply rising from 2020 (6.7 Killed MT) to 2024 (25.1 Killed MT) before narrowing down slightly in 2025 (Jan-Oct) estimate. The positive effects of production volume and processing capacity and market expansion on the export performance index constructed here are the strongest, evidence pointing toward regression that GI branding embraces quality signalling and origin differentiation to strengthen commercialization. The study posits that addressing the constraints of productivity growth along with institutional/policy interventions like mechanised processing, export grade quality system, FPO aggregation, gender inclusive interventions and product innovations like healthy snacks, nutraceuticals and functional foods will be crucial for Bihar's potential to rise as a global hub for makhana.
Copyright (c) 2026 Vikash Kumar Singh https://creativecommons.org/licenses/by-sa/4.0
ESG Practices and SME Performance: A PLS-SEM Analysis of Financial Forecasting and Sustainable Practices
SMEs are quickly adopting ESG practices to boost organisational performance, deepen their sustainability commitment and increase their capacity to make wise financial decisions. The aim of this research is to analyse the impact of environmental, social and governance practices on financial projections, standards of sustainability, and SMEs. Partial Least Squares Structural Equation Modelling (PLS-SEM) was conducted using ADANCO using data from 230 SME owners in Odisha. People were given the questionnaire. The model has seven components: SMEs’ performance, environmental, social, governance, financial predictions and sustainable methods . The measurement model was shown to be accurate and valid with adequate Average Variance Extracted (AVE) values and significant explanatory power (R2 values over 0.88 for all endogenous constructs). The structural model illustrates that ESG activities are substantially beneficial for environmental, social and governance practices. The structural model also revealed that ESG practices might enhance financial predictions and sustainability. Financial projections and sustainable methods boost the performance of SMEs, which demonstrates the strategic value of incorporating environmental, social and governance principles into the operations of a firm. The results demonstrate that ESG-led financial planning and sustainability initiatives are important to long-term competitiveness, resilience and company development. This study offers practical recommendations for SMEs and policymakers.
Copyright (c) 2026 Subrat Kumar Rout, Suresh Kumar Sahoo, Vishal Sood https://creativecommons.org/licenses/by-sa/4.0
ग्रामीण विकास में महिला सरपंचों के नेतृत्व एवं योगदान का समाजशास्त्रीय अध्ययन: अशोकनगर जनपद पंचायत, मध्य प्रदेश के विशेष संदर्भ में”
भारत में 73वें संविधान संशोधन अधिनियम, 1992 के लागू होने के पश्चात पंचायती राज संस्थाओं में महिलाओं की सहभागिता को संवैधानिक आधार प्राप्त हुआ, जिससे ग्रामीण स्थानीय स्वशासन में महिलाओं की भागीदारी और नेतृत्व को नई दिशा मिली। प्रस्तुत अध्ययन में मध्य प्रदेश के अशोकनगर तहसील के जनपद पंचायत अशोकनगर के संदर्भ में पंचायती राज व्यवस्था में निर्वाचित महिला प्रतिनिधियों की भूमिका, उत्तरदायित्व, निर्णय-निर्माण की क्षमता, नेतृत्व शैली तथा ग्रामीण विकास में उनके योगदान का समाजशास्त्रीय विश्लेषण किया गया है। इस अध्ययन में महिलाओं की राजनीतिक सहभागिता को प्रभावित करने वाले सामाजिक, आर्थिक, शैक्षिक एवं सांस्कृतिक कारकों का परीक्षण किया गया है। साथ ही यह भी विश्लेषण किया गया है कि आरक्षण व्यवस्था ने महिलाओं के सशक्तिकरण, आत्मविश्वास, सामाजिक प्रतिष्ठा तथा स्थानीय शासन में उनकी प्रभावशीलता को किस सीमा तक बढ़ाया है। अध्ययन में महिला प्रतिनिधियों के समक्ष आने वाली प्रमुख चुनौतियों का भी विवेचन किया गया है। प्रस्तुत शोध में प्राथमिक एवं द्वितीयक दोनों प्रकार के तथ्यों का उपयोग किया गया है। प्राथमिक तथ्यों के संकलन हेतु संरचित साक्षात्कार अनुसूची तथा प्रत्यक्ष अवलोकन का उपयोग किया गया है, जबकि द्वितीयक तथ्यों के लिए पुस्तकों, शोध-पत्रों, सरकारी प्रतिवेदनों तथा अन्य प्रासंगिक स्रोतों का उपयोग किया गया है। अध्ययन के माध्यम से पंचायती राज संस्थाओं में महिला प्रतिनिधियों की वास्तविक भूमिका, नेतृत्व क्षमता, निर्णयात्मक सहभागिता तथा ग्रामीण विकास में उनके योगदान का मूल्यांकन किया गया है।
Copyright (c) 2026 गंगीता शर्मा, सुनीता बाणकर https://creativecommons.org/licenses/by-sa/4.0
Adoption and Use of Generative AI Tools among College Students in Kashmir: Implications for Academic Libraries and Information Services
Higher education has seen a significant shift towards using Generative Artificial Intelligence (GenAI), which has revolutionized student learning and behavior by significantly improving their ability to engage with information. The effects of Generative AI tools on academic libraries are investigated in a study conducted among undergraduate college students in Kashmir. Google Forms was employed to implement a questionnaire that provided measurable research findings. In the study, undergraduate students from degree colleges in Kashmir were observed to adopt and use Generative AI tools. The analysis of 172 valid responses was carried out using descriptive statistics, with the data being analysed using frequencies and percentages, and then presented in tables and figures. The results show that many students are familiar with Generative AI tools and ChatGPT is the most popular plateform. Most of the students use Generative AI mainly for learning new concepts, studying to clear exams and doing homework. Additionally, students indicate that Generative AI can be beneficial in terms of improving learning efficiency and reducing time-wasting. Also, most respondents believed that academic libraries should be a key factor in improving literacy on AI by providing instruction and knowledge about the responsible and ethical use of Generative AI technologies. The study suggests that academic libraries should enhance their AI literacy programmes and user education programmes to address the growing presence of Generative AI in student academic activities. The outcomes provide valuable information for librarians, teachers, and policy makers on how to make the use of Generative AI more responsibly in higher education.
Copyright (c) 2026 Shakir Ahmad Dar, Fajar ul Islam Malla https://creativecommons.org/licenses/by-sa/4.0
Corporate Governance and Post-M&A Performance in the Banking Industry: A Study
Corporate governance in the banking sector is essential for the success of mergers and acquisitions (M&A) since it significantly influences post-M&A performance. This research analysed the impact of corporate governance rules on post-merger and acquisition (M&A) performance, along with the key governance domains influencing financial stability and operational success. The research used quantitative methods and regression analysis to investigate governance frameworks and performance metrics after mergers and acquisitions. The results were gathered from 385 respondents of the questionnaire. The study identified a significant positive correlation between governance quality and performance after mergers and acquisitions. The research revealed that leadership, decision-making, risk management, compliance, and transparency were essential. The research demonstrated that exemplary governance enhances financial performance, operational efficiency, and stakeholder confidence. The research emphasized the need of systematic governance during integration. This research aims to enhance theoretical and practical understanding of the impact of corporate governance frameworks on banking mergers and acquisitions. It synthesizes many governance theories, including Agency Theory and Stakeholder Theory, together with their practical implications to enhance the understanding of governance methodologies. The suggestions of the study will enhance governance in mergers and acquisitions for banking executives and practitioners. The study's authors advocate for enhancing governance procedures and examining the long-term impacts of governance on integration success. The study demonstrated that effective corporate governance maintains performance after mergers and acquisitions.
Copyright (c) 2026 Pratibha Jena, Vishal Sood https://creativecommons.org/licenses/by-sa/4.0
Evolution of Algorithmic Trading Research: A Systematic Literature Review and Identification of Future Research Directions
Algorithmic trading has transformed modern financial markets through the integration of advanced computational techniques, quantitative models, and automated execution systems. The rapid growth of electronic trading platforms, increasing market data availability, and significant advancements in artificial intelligence (AI), machine learning (ML), deep learning (DL), and high-frequency trading (HFT) have stimulated extensive academic and industry research over the past two decades. Despite this expanding body of literature, existing studies remain fragmented across diverse research themes, methodologies, financial markets, and asset classes, creating a need for a comprehensive synthesis of current knowledge and identification of future research opportunities. This paper presents a comprehensive literature review of algorithmic trading research published with a special emphasize between 2000 and 2026. The review systematically examines the evolution of algorithmic trading, major algorithmic trading strategies, theoretical foundations, data sources, research methodologies, and performance evaluation metrics employed in prior studies. The review further categorizes existing research into key thematic areas, including trend-following strategies, statistical arbitrage, market making, portfolio optimization, high-frequency trading, sentiment-based trading, and cryptocurrency algorithmic trading. The analysis identifies several significant research gaps that continue to limit the practical implementation and academic advancement of algorithmic trading. Based on these findings, the paper proposes a comprehensive future research agenda emphasizing hybrid AI-driven trading frameworks. By synthesizing existing knowledge and identifying critical research gaps, this review provides a valuable reference for researchers, practitioners, financial institutions, and policymakers seeking to advance the theory and practice of algorithmic trading.
Copyright (c) 2026 Tuhin Mukherjee, Anirban Sarkar https://creativecommons.org/licenses/by-sa/4.0
Light weight Intelligence-TinyML based Energy Usage Prediction for Resource-Constrained IoT Edges Nodes
The extensive deployment of battery-powered and resource-constrained edge devices makes energy efficiency a major challenge in Internet of Things (IoT) systems. Accurate energy prediction is important to enable intelligent energy management. However, traditional machine learning models are usually computationally expensive and unsuitable for micro-controller based platforms. In this paper, we present a TinyML-based energy prediction framework for low-power IoT edge devices. The proposed approach employs lightweight machine learning models which are optimized for ultra-low memory and computation footprints, but still retain acceptable prediction accuracy. We collect energy consumption data from a real IoT testbed, and train and evaluate several TinyML compatible models. The experimental results show that the proposed TinyML-based predictor can provide reliable energy estimation with low inference latency and low memory overhead, and thus can be deployed on resource-constrained IoT devices. This work lays a fundamental foundation for intelligent and adaptive energy management in future IoT systems.
Copyright (c) 2026 Sandeep Kumar Rawat, Neha Tuli https://creativecommons.org/licenses/by-sa/4.0
Experimental Investigation of Adhesion Mechanisms and Curing Behaviour of Coated Polymer Substrates in Hybrid Printing Systems
The adhesion and curing behaviour of coated plastic substrates in hybrid printing processes are crucial for ensuring high-quality, durable prints specially for flexible packaging applications. This paper aims to optimize substrate performance by investigating ink adhesion and curing efficiency under controlled printing conditions in hybrid printing presses with the combination of Flexo and Gravure Printing processes. The research systematically evaluates the influence of coating formulations, curing parameters and substrate surface characteristics on overall print quality. To achieve this, biaxially oriented polyethylene terephthalate (BOPET) films (both coated and uncoated) are subjected to experimental trials assessing ink-substrate interactions. Key measurement methods included surface energy evaluations using ARCOTEST dyne solutions and adhesion strength assessments through Scotch Tape tests. Additionally, UV and electron beam (EB) curing techniques are employed to study polymerization dynamics, ink anchoring behaviour and overall stability of cured prints. By analysing these parameters, the study provides insights into optimizing hybrid printing technologies, advancing substrate engineering and enhancing durability for packaging applications.
Copyright (c) 2026 Shubham, Arohit Goyat, Satish https://creativecommons.org/licenses/by-sa/4.0