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Framing and Unframing the Divide: Analyzing the Representation and Softening of the India-Pakistan Mental Border in Popular Narratives
The paper attempts to address how popular narratives challenge the rigid notions of national borders by foregrounding shared histories and emotional solidarities. In this context, the paper critically analyzes Kabir Khan-directed Bajrangi Bhaijaan (2015, film), the rap song Humsaye Maa Jaye (2019, song) by Bushra sisters and Akhil Katyals The Border Speaks (2019, poem). In contrast to the general understanding of geographical borders as lines of division, the paper argues that art becomes the medium to transcend the physical borders by creating a sense of togetherness between the socially and culturally interrelated people of India and Pakistan. The subsequent narratives give voice to the concerns of common people through their characters, dialogues and song lyrics. The paper argues that such cultural productions offer powerful counter-narratives to state-sponsored discourses, thereby reframing the border not as a site of enmity but as a space of human connection. 2025 IUP. All Rights Reserved. -
Framing Conflict And Development: Media Narratives, Security Planning, And Regional Recovery In Post-Article 370 Jammu And Kashmir
The repeal of Article 370 in 2019 has brought about a drastic change in the political, security, and media situation in Jammu and Kashmir, changing the way the events related to the conflict are framed and perceived. This paper will analyze the reporting of the 2025 Pahalgam terror attack and the following Operation Sindoor in two of the most popular regional dailies, Greater Kashmir and Daily Excelsior. The study is based on the qualitative comparative methodology that is supported by the framing theory to compare the tone, stress, and editorial strategy through the purposive analysis of the front-page coverage of April 23-May 8, 2025. The results are contrasting: Daily Excelsior adopts nationalist and security-centered frame that highlights military heroism and state intervention whereas Greater Kashmir adopts humanitarian frame that highlights civilian victimization, emotional appeal and community healing. Such competing frames not only affect the perception of the population, but also the discourses of security planning, tourism recovery, and regional development. The study suggests the significance of the media discourses as a dynamic element of the process of defining policy directions and planning outcomes in conflict-sensitive environments. 2025, Green Publication. All rights reserved. -
Fraud Detection in Credit Card Transaction Using ANN and SVM
Digital Payment fraudulent cases have increased with the rapid growth of e-commerce. Masses use credit card payments for both online and day-to-day purchasing. Hence, payment fraud utilizes a billion-dollar business, and it is growing fast. The frauds use different patterns to make the transactions from the cardholders account, making it difficult for the organization or the users to detect fraudulent transactions. The studys principal purpose is to develop an efficient supervised learning technique to detect credit card fraudulent transactions to minimize the customers and organizations losses. The respective classification accuracy compares supervised learning techniques such as deep learning-based ANN and machine learning-based SVM models. This studys significant outcome is to find an efficient supervised learning technique with minimum computational time and maximum accuracy to identify the fraudulent act in credit card transactions to minimize the losses incurred by the consumers and banks. 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. -
Fraud detection in the era of AI: Harnessing technology for a safer digital economy
Fraudulent activities have increased along with the new prospects of the digital economy's quick growth for both consumers and enterprises. Conventional techniques of fraud detection are insufficient to keep up with these ever-evolving fraudulent strategies. In this sense, machine learning (ML) and artificial intelligence (AI) have become potent instruments to prevent and detect fraud and guarantee the safety of online transactions. This study examines the function of AI and ML and shows how these technologies can spot irregularities and intricate patterns that would be challenging to find with conventional methods. The study includes various methods of AI-based fraud detection and analyses important ethical issues related to these practices. Furthermore, the study looks at developing technology and trends that will probably influence fraud detection in the future. In conclusion, the revolutionary potential of AI and ML in building a safer digital economy is analysed. 2024, IGI Global. All rights reserved. -
Fraud Prevention in Banking: Innovative Techniques for Detecting Payment Fraud
Fraud detection in banking remains one of the most critical challenges, as fraudulent patterns continue changing to avoid detection. Classic rule-based methods provide a basis approach but often lead to high rates of false positives and negatives, which limiting their efficiency. Due to the rapid growth of fraud particularly in Banking Payments, tackling this challenge has become imperative. To this end, we employ the Banksim dataset-a synthetic tool that replicates the various payment behavior of customers- to assess a number of machine learning models, Support Vector Machines, Random Forest, Logistic Regression, AdaBoost and Decision trees. Our model evaluation, using confusion matrices and classification reports, demonstrates the ability of these approaches to provide precision and reliability in detecting fraudulent transactions. This research contributes to enhancing the reliability and integrity of banking services through fraud payment detection improvements. 2025 IEEE. -
Fraud Prevention in Banking: Machine Learning-driven Approaches for Detecting Payment Anomalies
The fast-paced development of digital banking has brought with it new convenience but also tremendous challenges in maintaining transaction security. Banks are confronted with mounting threats from malicious activities like identity theft, account takeover, and unauthorized access, which can lead to huge financial losses and loss of customer confidence. This study investigates the formulation of a cybersecurity framework for fraud prevention in banking through machine learning algorithms. A transactional real-world dataset of 200,000 instances from LOL Bank Pvt. Ltd. was used to construct and evaluate predictive models. Preprocessing included categorical encoding, temporal feature engineering, and synthetic minority oversampling (SMOTE) for class imbalance handling. Three machine learning classifiers - Logistic Regression, Random Forest, and XGBoost - have been compared using measures of accuracy, precision, recall, F1-score, and ROC-AUC. Results show that ensemble models significantly outperformed logistic regression by a wide margin, with Random Forest and XGBoost both achieving over 91% accuracy and very good discrimination power. The study emphasizes how well machine learning-based systems detect theft in real time and outlines avenues for future research to enhance detection using adaptive and interpretable AI models. 2025 IEEE. -
Free COOH-tethered layered Co(ii) framework and flexible composite as a size-reliant, tandem and robust catalyst for mild and scalable synthesis of bioactive molecules
Pore-functionalization in metalorganic frameworks (MOFs) through the immobilization of free carboxylic sites offers a promising strategy for designing high-performance materials with potential applications, including selective and benign chemical transformations. However, this feat is tricky because of their extreme tendency to coordinate with the concerned metal ions. Herein, we developed a layer-stacked and thermo-chemically stable two-dimensional MOF, encompassing flanked carboxylic acid and [Co2(COO)4] unit-decked porous channel, using a mixed-ligand approach. The guest-free structure serves as a one-of-a-kind superior heterogeneous catalyst for tricomponent KnoevenagelMichael condensation, yielding a multitude of 2-amino-3-cyano-4H-pyrans with low catalyst loading, short duration and mild temperature compared to the majority of reported materials. The role of Lewis and Brsted acidic sites in the MOF catalyst is comprehensively supported by control experiments, analyte-induced emission articulation, inferior activity of a task-specific site-truncated iso-skeletal framework, and density-functional theory results. Importantly, the MOF demonstrated the first-ever deacetalization multi-component reaction (MCR) with admirable and recyclable conversion under relatively green conditions. Besides covering twenty-two electronically diverse substrates, the MOF can synthesize nine bioactive pyrans with excellent yield and gram scale. Notably, fifteen 4H-pyrans are first-time characterized in their purest forms via X-ray crystallography besides other spectro-analytical studies. Larger-sized substrates failed to diffuse inside MOF's micropores and illustrate unprecedented molecular-dimension-mediated MCR. The in situ-grafted MOF inside melamine-foam (MF) yielded a reconfigurable composite that promotes this one-pot reaction with similar activity and reusability to that of the sole MOF and demarcates a paradigm shift toward cutting-edge sustainable catalysis over a practical platform. This journal is The Royal Society of Chemistry, 2025 -
Free Speech in the Age of Algorithms: Regulating Online Hate in India, Canada, and the United Kingdom
Online hate has increased while public conversation has expanded due to digital connectivity. This contrasts the laws governing hate speech online in the UK, Canada, and India. Canada strikes a compromise between equality and expression, India permits modest limits but issues with uneven enforcement, and the UK makes threatening or nasty online behavior illegal. Uncertain definitions, inconsistent enforcement, algorithmic dissemination, and the possibility of excessive censoring are some of the main obstacles. A harm- reduction model based on rights is put forth. 2026 by IGI Global Scientific Publishing. All rights reserved. -
Free vibration studies of box type laterite masonry structures
Vol.39, N0.3, /august -September 2012 pp 332-346 -
Friction and wear behaviour of copper reinforced acrylonitrile butadiene styrene based polymer composite developed by fused deposition modelling process
This paper focuses on the development of copper filled Acrylonitrile Butadiene Styrene (ABS) composites by fused deposition modelling (FDM) and to characterize its friction and wear behaviour. Twin screw extrusion technique was employed to extract copper-ABS composite filament. Three different materials were tested, i.e. pure ABS, ABS+2.5wt% Cu and ABS+5wt% Cu. Friction and wear characteristics of pure ABS and copper filled ABS composites were tested under various loads and sliding velocities. Addition of Copper powder has significantly improved the friction and wear properties of the developed composites. Further, it is also observed that friction and wear behaviour increased with increase in copper content in ABS. Worn out surfaces were subjected to scanning electron microscopy studies to analyse and identify the possible wear mechanisms involved. Faculty of Mechanical Engineering, Belgrade. -
Friction and wear behaviour of HVOF sprayed Cr2O3-TiO2 coatings on aluminium alloy
This study investigates the tribological behaviour of Cr2O3-TiO2 composite coatings deposited on aluminium 6061 alloy. Cr2O3-TiO2 composite coatings were deposited by high velocity oxyfuel (HVOF) technique. Developed coatings were subjected to microstructure studies, microhardness test (ASTM E92), friction and wear test (ASTM G99). Pin-on-disc machine was used to evaluate friction and wear characteristics of Cr2O3-TiO2 coatings. Effect of sliding velocity (0.314 m/s-1.26 m/s) and load (20 N-100 N) on friction and wear characteristics of Cr2O3-TiO2 coatings were studied and compared with uncoated aluminium alloy. Results showed 54% improvement in hardness of Cr2O3-TiO2 coatings in comparison with aluminium alloy. Coefficient of friction and wear rate decreases by 12% and 48% respectively when evaluated with uncoated aluminium alloy. Coefficient of friction (COF) and wear rate increases with increase in load and sliding velocity for both coatings and substrate. However, Cr2O3-TiO2 coatings showed lower wear rate and COF at all the loads and sliding velocities studied when compared with uncoated aluminium alloy. Worn out surfaces of uncoated and Cr2O3-TiO2 coated surfaces were subjected to SEM analysis to understand the wear mechanisms in composite coatings. 2021 Inderscience Enterprises Ltd.. All rights reserved. -
Friction stir welding of aluminum alloy 1100 and titanium-al alloy
A intercalating joint between Al and Ti alloy is friction stir welded using a high speed steel tool. The material mixing occurs mainly in the shoulder region while the pin region shows nominal mixing. Microscopy and hardness experiments indicate sporadic formation of intermetallic compounds. The joint region near the shoulder and to some extent below it shows increase in hardness compared to the base Ti alloy. Copyright 2016 by ASME. -
Friction Stir Welding of Dissimilar Aluminium Alloys for Vehicle Structures
Welding process in vehicle structures has gained importance, especially for better strength and mechanical properties. Hence, there is vast research going on in the domain of newer welding techniques. Friction Stir Welding (FSW) is one of them. FSW is used in this research to join two different grades of aluminium alloys by varying the process parameters. The process parameters are optimized based on the Design of Experiments (DoE) and the Taguchi techniques. From the experimental findings for different process parameters, the optimized set of conditions involving the normal, transverse forces and the torque are determined. Further, the process methodology is validated. 2022, MechAero Found. for Techn. Res. and Educ. Excellence. All rights reserved. -
Friction Stir Welding Process Parameters Optimization By Taguchi Analysis and Validating The Mathematical Model Using RSM For AA6101-C11000 Alloy Joints
Friction Stir Welding (FSW) is a well-established joining method that offers newlinesignificant advantages over traditional methods, including improved mechanical newlinecharacteristics, less distortion, and environmental friendliness. Due to its solid-state nature, the heat produced through the welding mainly influences the features of joints in FSW. In this investigation, 2D and 3D models of the base metals and welding tool newlinewith different pin profiles were designed using SOLIDWORKS. Fixture was designed and manufactured in accordance with the specifications of the welding machine. ANSYS software was used to investigate the temperature distributions near the weld newlinezones. The base metals AA6101 and C11000 of each 5 mm thickness with butt weld newlinepositioned, were joined by FSW mechanism with the help of OHNS steel tool with circular pin profile. Taguchi analysis was employed to optimize the FSW welding input process parameters, including tool rotational speed (rpm), feed rate (mm/min), and tool offset (mm), to determine their respective contribution (%) to the output response, namely ultimate tensile strength (UTS), hardness, impact load, and electrical newlineconductivity to achieve the high joint strength. During experimental work using the newlineTaguchi s design matrix, the maximum output response values were obtained when the input parameters were set to 1000 rpm, 50 mm/min and -1 mm. Taguchi analysis revealed that the tool rotational speed encounters high significance effects, followed by feed rate and least tool offset upon output response. The X-ray diffractometer (XRD) test was employed to specifically determine the existence of Al-Cu intermetallic compounds (IMCs) generated within the FSW of Al (AA6101) and Cu (C11000) joints. At medium 40 mm/min, 1000 rpm, and -1.68 mm, the IMCs newlinedeveloped were Al4Cu9 and Al1Cu3 giving a high UTS value of about 142.69 MPa. newlineMathematical model was developed utilizing the Response Surface Method (RSM) to newlinepredict the output response. -
Frictionless shopping in the digital era: A comprehensive analysis of instant gratification, ethical considerations, and future prospects
This research chapter investigates the dynamic interplay between instant gratification and smart retailing, focussing on the transformative impact of frictionless shopping experiences. This chapter examines various channels, including omnichannel shopping, personalized recommendations, gamification, and rewards, highlighting their roles in bridging the gap between physical and digital realms. Additionally, it delves into the immersive world of virtual try-ons, analyzing their influence on immediate decision-making and customer satisfaction. This chapter also explores the intersection of instant gratification and smart retailing, emphasizing frictionless shopping's transformative impact. It examines ethical implications, envisions future frameworks, and anticipates enhanced consumer empowerment in evolving retail landscapes. This chapter employs a comprehensive literature review approach to analyze the existing body of knowledge on frictionless shopping, instant gratification, and smart retail technologies. This chapter highlights the transformative potential of smart retail, emphasizing ethical considerations. Anticipating enhanced consumer empowerment, it envisions a moral evolution in retail practices for immediate satisfaction. Informing retailers on ethical considerations, influencing policy development, and guiding the industry towards transparent, consumer-centric smart retail practices for sustainable growth and customer satisfaction. This chapter contains updated work from Frictionless shopping, Smart retailing, Instant gratification, and Ethical considerations. A comprehensive exploration of instant gratification's interplay with smart retailing, emphasizing ethical considerations and forecasting future frameworks to guide the evolving landscape towards responsible and transparent consumer-centric practices. 2025 Talasila Harshitha, Prathiba S., Narasimha Murthy H. and Joel Jebadurai Devapictahi. Published under exclusive licence by Emerald Publishing Limited. All rights reserved. -
From a recession to the COVID-19 pandemic: Inflation-unemployment comparison between the UK and India
The recession in India and the UK peaked in 2017 due to the implications of new policy initiatives. The outbreak of the COVID-19 pandemic at the beginning of 2020 intensified the crisis, causing a drastic decline in aggregate demand and output. India and the UK have resorted to monetary and fiscal stimulus packages to face the economic crisis. This study investigated the inflation-unemployment dynamics during the recession and COVID-19 times in India and the UK. Using a generalized additive model (GAM), the results of this study revealed that the recession had given way to stagflation in India. In contrast, in the UK, it has led to a more severe recession in the short-run. During the downturn, policy initiatives aggravate the recession and eventually turn to stagflation in India due to inflation caused by the weak supply side. However, in the UK, the policy initiatives during this downturn pushed the economy into a deeper recession due to reduced demand. The outbreak of the COVID-19 pandemic has had a similar recessionary impact on both economies. A time horizon based recovery plan is suggested to help the economies recover from stagflation and even deeper recession. This framework could enable policymakers to choose the right path of recovery within the shortest possible time. 2021 by the author. Licensee MDPI, Basel, Switzerland. -
From Advisory to Authentic Co-Creation: Rethinking Employer-University Partnerships for Future-Ready Graduates
As the future of work becomes increasingly dynamic, higher education faces pressure better to align academic programs with the evolving demands of industry. Traditional employer engagement approaches, such as advisory boards or guest lectures, often remain surface-level, failing to bridge the persistent disconnect between academic curricula and workplace expectations. This chapter introduces the COACT Model as a transformative framework that redefines employeruniversity collaboration through authentic co-creation. Grounded in stakeholder theory, participatory curriculum design, and experiential learning, COACT comprises five iterative phases: Collaborate, Orchestrate, Apply, Co-Evaluate, and Transform. Each phase outlines actionable strategies for embedding employers into curriculum development, delivery, and evaluation at the program level. The model emphasizes mutual accountability, shared pedagogical ownership, and contextual adaptability, enabling institutions to reform curricula without overburdening faculty or marginalizing employer contributions incrementally. By positioning employers as co-educators and co-evaluators, COACT facilitates meaningful integration of real-world insights into academic learning, thus enhancing graduate employability, confidence, and readiness. The chapter also provides practical guidelines, implementation structures, and evaluative feedback loops that support continuous improvement and institutional learning. Ultimately, the COACT Model reframes curriculum not as a fixed academic product, but as a dynamic, co-authored space where diverse knowledge sources converge. In doing so, it offers a scalable pathway for universities to develop future-ready graduates through enduring, responsive, and equitable partnerships with industry. 2026 by IGI Global Scientific Publishing. -
From automation to optimization: Exploring the effects of al on supply chain management
Automation and the integration of artificial intelligence (AI) are reshaping modern business operations. This evolution has historical roots, with a growing emphasis on efficiency and cost reduction. AI's transformative role in supply chain optimization is evident through key technologies and applications, which empower businesses to make data-driven decisions, enhance customer experiences, and reduce costs. Real-world examples illustrate how companies leverage AI to streamline operations and deliver products and services with precision. 2024, IGI Global. -
From bean to brain: Coffee, gray matter, and neuroprotection in neurological disorders spectrum
Coffee is a popular drink enjoyed around the world, and scientists are very interested in studying how it affects the human brain. This chapter looks at lots of different studies to understand how drinking coffee might change the brain and help protect it from neurodegenerative disorders especially like schizophrenia. With the help of available literature a link between the coffee mechanism and neurodegenerative disorders is established in this chapter. Researchers have found that drinking coffee can change the size of certain parts of the brain that control things like thinking and mood. Scientists also study how coffee's ingredients, especially caffeine, can change how the brain works. They think these changes could help protect the brain from diseases. This chapter focuses on how coffee might affect people with schizophrenia as hallucination is caused during and after excess consumption of caffeine. There's still a lot we don't know, but researchers are learning more by studying how different people's brains respond to coffee over time. Overall, this chapter shows that studying coffee and the brain could lead to new ways to help people with brain disorders. This study also draws ideas for future research and ways to help people stay healthy. 2024 Elsevier B.V. -
From Beans to Business: A Rise of Coffee Preneurs in Kodagu, Karnataka
Coffee is the world's third most consumed beverage after water and tea. India stands at the 7th position as the largest coffee exporter globally, with a significant contribution of 72.5% from Karnataka and 33% from Kodagu alone. This region plays a crucial role in the country's coffee industry, making it a vital component of India's economy, and 80% of the residents of Kodagu rely on coffee cultivation for their livelihood. Coffee farming is considered an annual crop that requires the generated income to be cycled to the subsequent year's coffee cultivation. Planters face numerous challenges during their production, which forces them to sell or convert their agricultural lands into concrete lands (buildings) or convert them into resorts, thereby changing their occupation, which makes coffee sustainability questionable. Therefore, coffee farmers have recently adopted an entrepreneurial approach to augment their income sources and support their livelihoods and occupations. This study aims to assess the key drivers of coffee farmers opting for entrepreneurial activities to assist coffee farming in Kodagu, Karnataka. This study has revealed that additional income, passion for farming, business skills, available resources, opportunity, satisfaction, innovation, creativity, unfair market prices, education, and socialising platforms are the key determining factors for coffee farmers to choose entrepreneurship. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.