Research Paper Research Articles

Addressing the Abuse of Dominance in India Under the Competition Act, 2002

The regulation of abuse of dominance within India's competition law framework is pivotal for ensuring equitable competition, market efficacy, and consumer well-being. This research paper delves into the intricate dimensions of addressing abuse of dominance within the Indian context, shedding light on the legal framework, enforcement mechanisms, case precedents, and emerging hurdles. Commencing with an exhaustive overview, the paper meticulously examines the legal framework dictating abuse of dominance, elucidating the provisions enshrined in the Competition Act, 2002, and pertinent regulations. Through a thorough analysis of statutory clauses and judicial interpretations, it delineates the criteria and benchmarks utilized for discerning and adjudicating instances of abuse of dominance, thereby providing insights into the evolving jurisprudence in this sphere. Drawing from a diverse array of case laws and precedents, the paper traverses through seminal judgments and enforcement actions undertaken by the Competition Commission of India (CCI) to address abuse of dominance. Through meticulous case analyses, readers are furnished with a deeper comprehension of the enforcement mechanisms deployed by the CCI, encompassing investigative processes, adjudicatory proceedings, and the imposition of remedies and sanctions. Moreover, the paper delves into emerging challenges and discourse surrounding abuse of dominance, encompassing its intersection with digital markets, burgeoning technologies, and the phenomenon of globalization. By scrutinizing contemporary issues such as platform hegemony, apprehensions regarding data privacy, and ramifications of cross-border transactions, the paper furnishes insights into the intricate facets of regulating abuse of dominance within India's dynamic market milieu. In conclusion, this research paper furnishes a comprehensive exploration of the strategies, mechanisms, and impediments entailed in addressing abuse of dominance under competition law in India. By amalgamating legal tenets, case dissections, and contemporary developments, the paper seeks to enrich the scholarly dialogue on competition law enforcement and proffer pragmatic insights for policymakers, practitioners, and stakeholders navigating the convolutions of India's competitive landscape.

Enhanced Accessibility for Visually Impaired & Blind Artists (EAVIBA) using Machine Learning

This research paper introduces EAVIBA, an innovative voice-driven interface aimed at empowering individuals with visual impairments and blindness in the domain of art and creativity. Rooted in principles of accessible design, EAVIBA integrates advanced features including voice commands, text-to-speech functionality, and a customizable graphical user interface, exemplifying a commitment to inclusive technology. The paper delves into the intricacies of EAVIBA's development, elucidating its architectural framework, seamless integration of assistive technologies, and adherence to recognized accessibility standards such as the Web Content Accessibility Guidelines (WCAG). Employing a comprehensive approach, the research paper outlines the iterative process of user testing, providing both qualitative and quantitative insights into critical aspects such as interface clarity, voice command recognition accuracy, and the efficacy of customization options. The results of these evaluations affirm EAVIBA's remarkable success in delivering an inclusive, accessible, and empowering environment for individuals with visual impairments to engage in artistic expression, thereby contributing significantly to the broader landscape of assistive technologies and accessible interfaces. Keywords: Visually impaired, blind artists, voice-driven interface, assistive technologies, voice recognition, machine learning.

The role of influencer marketing in the rapid rise of Nusr-et: the cognitive response theory

PurposeThis research examines the factors that affect business owner influencers' success in growing their businesses and making them a brand in line with the principles of the cognitive response theory (CRT).Design/methodology/approachThis research examined the perceived uniqueness and originality of the posts on Nusr-et’s Instagram account as external information; information credibility was examined as a cognitive response, and desire was taken as a cognitive response and intention. Partial least squares structural equation modeling (PLS-SEM) was used in the analysis of the data.FindingsAccording to the research findings, perceived uniqueness and originality were found to have positively affected information credibility and cognitive response, while cognitive response factors were also found to have positively affected desire. In addition, cognitive response factors were found to have mediated the effect of external information factors on desire. All these results reveal the significant accuracy of the model developed based on the CRT. In addition, age and gender variables were found to have had moderating roles. Based on the research findings, original suggestions for restaurant enterprises have been presented to help them gain a competitive advantage.Practical implicationsThis study has found that the posts shared by business owner influencers have affected their followers in their desire to eat in the promoted restaurants and therefore, entrepreneurs and owners of the food and beverage industry should give importance to the preparation of social media content that could directly affect customers for visit to their restaurants and regularly post such contents in their social media accounts.Originality/valueThis research has been one of the first research papers using a model to reveal the reasons for behavioral intention in the field of hospitality based on the CRT.

To Get a Power Generation Using a Waste Heat Recovery from IC Engine

This Research paper aims to develop and design a low-temperature organic Rankine cycle (ORC) system, focusing on enhancing the performance of the expander and selecting optimal refrigerants and heat sources. The study begins with a comprehensive analysis of available expanders and refrigerants suitable for ORC applications. The research then progresses to the development and improvement of an expander utilizing a reverse scroll compressor configuration, a novel approach aimed at enhancing efficiency and performance. Dynamic tests are conducted to assess the performance of the scroll compressor in this new configuration, providing valuable data for further optimization. The same expander is then integrated into an ORC system to evaluate its performance within the overall setup. Various performance parameters of the scroll compressor and the ORC system are meticulously analyzed to gauge efficiency and identify areas for improvement. Furthermore, the research paper includes a detailed process of selecting the most appropriate refrigerant and heat source from the available options. This selection is critical in optimizing the ORC system's effectiveness and sustainability. Overall, this research contributes to advancing low-temperature ORC technology by improving expander design, optimizing component performance, and selecting suitable operating parameters for enhanced energy conversion efficiency.

Understanding the Roles of Family, Community in Visually Impaired & Low Vision Student’s Life

The objective of this paper is to acquire an efficient understanding of the roles of family,how family support to attain their goals towards life . Family plays an important role in contribution in promoting enrichment,support of the overall quality of lives of the visually impaired student. In the personal and professional lives of the visually impaired student, there are number of functions and daily living activities, which they are required to carry out smoothly. These activities carried out may be on one’s own or perform with help and assistance from family or dear ones. For example, in the pursuance of educational coursers or programs within institutions of all levels, the student are required to deal with special educators, supervisors, visually impaired or sighted classmates and other staff members. Hence, development of consensus with them is regarded to be of sheer significance. On the other hand, within home environment , family members need to work in co-ordination with each other to promote each other’s well-being ,mental health and goodwill. The visually impaired students implement a range of work functions and responsibilities in compliance with protocols and guidelines. The family and community members, particularly special educator and service providers need to be provided with adequate information in terms of methods and procedures of initial phase of learning . Consequently, duties and responsibilities should be carried out in a well-ordered and disciplined manner among family ,community and special educator. Therefore, it is well-understood, roles of family ,community members and special educator are acknowledged to a major extent. The main concepts that are taken into account in this research paper are, roles of family ,roles of community members and roles of special educator in visually impaired student life.

Operational Procedures of Forensic Science Laboratories and Protocols for Sample Collection

This research paper delves into the operational procedures employed within forensic science laboratories, with a specific focus on the protocols governing sample collection. Forensic science plays a crucial role in the criminal justice system, providing evidence and expert analysis to aid investigations and legal proceedings. Effective operational procedures and rigorous protocols for sample collection are essential to maintain the integrity and reliability of forensic evidence. Through an in-depth examination of existing literature, case studies, and expert insights, this paper aims to provide a comprehensive understanding of the methodologies and guidelines employed in forensic laboratories worldwide. Additionally, it explores the challenges faced by forensic scientists in sample collection and processing, along with recommendations for improving practices and enhancing the quality of forensic evidence.

Effective Strategies for Developing Online Courses in the University of Botswana

Online learning has become an essential component of higher education, and its effectiveness has been demonstrated by several studies (Al-Harbi et al., 2019; Li et al., 2020). In Botswana, the need for online learning has become more significant due to the COVID-19 pandemic (Keya et al., 2020). This research paper explores the effective strategies for developing online courses in the University of Botswana. The study is based on a qualitative research method, and data was collected through in-depth interviews with 15 university professors (Cohen et al., 2017). The results of the study show that effective strategies for developing online courses include early planning, developing effective course content, use of multimedia tools in course delivery, providing adequate support to students, developing assessments that align with course objectives, and promoting collaboration and engagement among students. These strategies are crucial in ensuring that online courses are effective and meet the needs of the students (Davis & Mansour, 2019). The study recommends that universities in Botswana should adopt these effective strategies to ensure that online courses are of high quality and provide a valuable learning experience for their students.

Utilization of Waste Heat Emitted by the Kiln

Kiln is where dolomite, iron ore and coal are used as intake product for the formation of sponge iron. At high temperature raw materials are molded to get the desired product. Due to this high temperature lots of heat is emitted from the kiln. The temperature in the kiln is about 800-1100°c, and it emits heat, this emitted heat storage is the cause for the emergence of this research paper. In this paper simple way is used for the utilization of heat. A panel which will work as a heat exchanger is used. This panel consists of tubes attached parallel to each other. Working fluid flows from the tube. The working fluid temperature increases as the heat from the kiln flows through it. It works just as the working of flat plate collectors. The main intension is to do maximum utilization of the kiln and heat released from it. This helps to do maximum use of kiln. This will further help in the increase of efficiency with the help of heat recovery technology. This will further lead to the reduction of pollution.

ARTIFICIAL INTELLIGENCE IN NUTRITION: REVOLUTIONARY DIETARY RESEARCH

Artificial intelligence has emerged as a transformative technology with the potential to revolutionize various aspects of society, including the field of nutrition. This research paper aims to explore the impact of artificial intelligence on nutrition and how it can revolutionize dietary research. With the rapid advancements in AI technology, it holds great promise for improving our understanding of nutrition and enhancing personalized dietary recommendations. By utilizing machine learning algorithms and big data analysis, AI can analyse vast amounts of nutritional information, including food composition, dietary patterns, and individual health data, to identify patterns and associations that can help inform dietary recommendations. Furthermore, AI can also assist in the development of novel food products and formulations that cater to individual dietary needs and preferences. By leveraging AI capabilities, researchers can gain deeper insights into the complex interactions between diet, genes, and health outcomes. This research paper aims to provide an overview of the current applications of AI in the field of nutrition, including its use in dietary assessment, personalized nutrition recommendations, and food product development. Keywords—Nutrition, Artificial Intelligence, Diet.

Evaluation of disaster preparedness in educational infrastructure of remote geographies using Analytical Hierarchy process

This research paper assesses the disaster preparedness of educational infrastructure in Central Kashmir, employing the Analytic Hierarchy Process (AHP) methodology. Its primary objective is to gauge the preparedness level of educational institutions and identify crucial factors influencing their capacity to effectively mitigate and respond to disasters. The study utilized a sample of 620 institutions, comprising 340 government and 280 private institutions, with 1240 respondents selected via stratified random sampling across Budgam, Srinagar, and Ganderbal areas of Central Kashmir. Results reveal that 73 % of the surveyed institutions in the region lack preparedness, while only 27 % demonstrate >50 < 100 % preparedness for handling multiple disaster scenarios. Notably, private institutions exhibit significantly higher individual disaster preparedness compared to their counterparts in government institutions. Additionally, the study identifies earthquakes as the primary concern, with fires, floods, and landslides perceived to have a comparatively lesser impact on individuals’ perception and awareness. These findings offer critical insights into the gaps and challenges within disaster preparedness in remote areas such as the Valley of Kashmir. This paper serves as a foundation for crafting targeted strategies aimed at bolstering the resilience of educational infrastructure throughout the region.

Enhancing Fashion Recommendations with Facial Recognition: A Gender and Age Prediction Perspective

This research paper presents a real-time system for age and gender estimation integrated into a fashion recommendation context. Leveraging deep learning models for facial detection and classification, alongside a Random Forest-based recommender system for fashion items, the system provides personalized recommendations based on user age, gender, and preferences. The methodology involves detecting faces in video streams, extracting facial regions, and preprocessing them for age and gender estimation using pre-trained CNN models. Fashion recommendations are then generated by assigning weighted scores to items based on various attributes and training a Random Forest regressor. Implementation details, including the use of Python, OpenCV, and machine learning libraries, are discussed. Evaluation metrics for age and gender detection models, as well as recommendation system performance, are outlined. The paper concludes with future directions and challenges, emphasizing enhancements in age and gender estimation accuracy, integration with e-commerce platforms, and the importance of data privacy and computational resources. Keywords — Age and gender estimation, Facial detection, Deep learning, Fashion recommendation, Random Forest.

Behavioral Involvement, Technology Acceptance, and Failure in Mobile Learning: A Systematic Review

As we move further into the digital age, machine learning algorithms have become increasingly popular in E-learning for their ability to predict learner failure and assess behavioral engagement, particularly in mobile learning environments. This paper reports on the systematic review conducted by the most relevant research in the literature that uses machine learning algorithms to predict failure, verify acceptance of mobile technology, and analyze behavioral engagement in mobile learning platforms. The search was performed using research papers extracted from four commonly used databases and published between 2010 and 2023; the last database access was on 15/05/2023. Guided by the PRISMA checklist, the review followed a structured approach to select, analyze, and report relevant studies. Studies were selected based on strict inclusion and exclusion criteria, focusing on peer-reviewed articles that empirically test the application of machine learning in mobile learning contexts. Of the initial 332 screened articles, 20 were eligible for inclusion. The results highlight the transformative role that machine learning is playing in revolutionizing online mobile learning experiences.

Video Object Search: A Semantic Approach with OpenAI's CLIP Technology

A research paper titled "Video Object Search: A Semantic Approach with OpenAI's CLIP Technology" examines the possibilities of semantic search in the identification of video objects. The technique that is proposed in this paper integrates textual and visual data to enhance the precision of video identification of objects. The conventional approach in video object detection utilizes only visual data, which might result in limited or incorrect item identification. By integrating certainty estimation, adaptability to handle a variety of questions, and semantic comprehension, the recommended approach gets over these limitations. The system evaluates textual and visual data using OpenAI's CLIP Technology, enabling more precise identification of objects in videos. The study's findings show that the suggested approach works more precisely than the conventional approach.

Active Chat Monitoring and Suspicious Chat Detection Over Internet

In the digital age, the proliferation of online communication platforms has facilitated unprecedented levels of connectivity and interaction. However, this interconnectedness has also introduced new challenges, particularly in ensuring the safety and security of users in online environments. One critical area of concern is the monitoring and detection of suspicious activities within chat platforms, where malicious actors may engage in harmful behaviors such as cyberbullying, harassment, or illicit activities. This research paper focuses on the development and implementation of active chat monitoring techniques for the detection of suspicious behavior over the internet. By leveraging advancements in natural language processing (NLP), machine learning, and data analytics, this study aims to explore effective methodologies for real-time monitoring and analysis of chat conversations to identify potentially harmful content. The paper will delve into various approaches for detecting suspicious patterns, including keyword analysis, sentiment analysis, and anomaly detection algorithms. Additionally, considerations for privacy, ethics, and legal implications surrounding chat monitoring will be discussed. Ultimately, this research endeavors to contribute to the enhancement of online safety measures by providing insights into the design and implementation of proactive monitoring systems capable of identifying and mitigating risks in virtual communication spaces. Keywords— Active Chat Monitoring, cybersecurity, user experience, digital era, security, user-controlled, effectiveness, evolving threat, Chat content analysis, Threat intelligence.

The Performance Assessment of Chinese Students in College and the Role of English Language

This research paper addresses the importance of investigating local students’ perceptions on the effectiveness of English as a medium of communication in and out of the classroom. Interviews with semi-structured questions of intrinsic and extrinsic nature through five-Likert scale were conducted in 140 undergraduate students who have been pursuing a bachelor’s degree at Zhengzhou Normal University in China. Descriptive analysis and factor component analysis (FCA) used for obtaining the results. The intrinsic and extrinsic nature of findings demonstrate that English considerably impacts their academic progress and performance. Furthermore, the findings show that students are eager to accept, support, and encourage their friends to adapt English to generate new knowledge and information. The findings also imply that local English instructors should be paid well and have a strong social position as teaching faculty. The findings suggest that curriculum improvement, content adjustment, and frequent use of English in exploration approaches to instruction, with the ultimate objective of opening up new avenues of knowledge, may significantly improve English effectiveness in student performance and career development.

Secure Text Transfer Using Cloud Environment

Cloud computing has become an integral part of the digital world, offering cost effective and flexible features for data storage, processing, and transfer. However, security concerns have become a major challenge with the increased reliance on cloud computing. In particular, secure text transfer in the cloud is a crucial aspect of cloud computing, as it involves the transmission of sensitive information. This research paper proposes a cloud-based secure text transfer mechanism that addresses the security challenges of text transfer in the cloud environment. The suggested technique guarantees the confidentiality, integrity, and availability of data during transmission, and provides a high level of security for cloud users. We present a comprehensive analysis of the proposed mechanism and evaluate its performance against various security metrics. The results of our research demonstrate the effectiveness of the proposed mechanism in providing secure text transfer in the cloud environment. Keywords: Cloud Computing, Secure Text Transfer, Confidentiality, Integrity, Availability, Security, Data Transmission, Cloud Users, Security Metrics.

Unravelling the origin of isoprene in the human body—a forty year Odyssey

In the breath research community’s search for volatile organic compounds that can act as non-invasive biomarkers for various diseases, hundreds of endogenous volatiles have been discovered. Whilst these systemic chemicals result from normal and abnormal metabolic activities or pathological disorders, to date very few are of any use for the development of clinical breath tests that could be used for disease diagnosis or to monitor therapeutic treatments. The reasons for this lack of application are manifold and complex, and these complications either limit or ultimately inhibit the analytical application of endogenous volatiles for use in the medical sciences. One such complication is a lack of knowledge on the biological origins of the endogenous volatiles. A major exception to this is isoprene. Since 1984, i.e. for 40 years, it has been generally accepted that the pathway to the production of human isoprene, and hence the origin of isoprene in exhaled breath, is through cholesterol biosynthesis via the mevalonate (MVA) pathway within the liver. However, various studies between 2001 and 2012 provide compelling evidence that human isoprene is produced in skeletal muscle tissue. A recent multi-omic investigation of genes and metabolites has revealed that this proposal is correct by showing that human isoprene predominantly results from muscular lipolytic cholesterol metabolism. Despite the overwhelming proof for a muscular pathway to isoprene production in the human body, breath research papers still reference the hepatic MVA pathway. The major aim of this perspective is to review the evidence that leads to a correct interpretation for the origins of human isoprene, so that the major pathway to human isoprene production is understood and appropriately disseminated. This is important, because an accurate attribution to the endogenous origins of isoprene is needed if exhaled isoprene levels are to be correctly interpreted and for assessing isoprene as a clinical biomarker.

Digital Finance-Fintech and it’s Impact on Financial Inclusion in India

Financial inclusion stands as a critical driver of economic empowerment and social development, ensuring that individuals across diverse socio-economic strata have access to and can effectively utilize formal financial services. In the context of India, where millions have historically been excluded from traditional banking systems, the emergence of digital finance presents a promising avenue for bridging this gap and fostering greater financial inclusion. This research paper delves into the transformative role of digital finance in driving financial inclusion in India, with a particular focus on understanding its impact on key aspects of financial access and empowerment. Central to our exploration is the definition of financial inclusion as the ability to access and effectively utilize a spectrum of formal financial services. In this context, we examine how digital tools such as credit/debit cards, internet banking, mobile banking, and the Unified Payments Interface (UPI) can empower individuals, particularly those who have been previously excluded from traditional banking systems. By investigating the impact of these digital instruments across ten key aspects of financial inclusion, including convenience, success rate of transactions, affordability, security, user-friendliness, timeliness, customer care support, internet connectivity, and overall usability, we aim to discern their strengths and weaknesses in promoting financial inclusion. Through a systematic analysis of each dimension, we seek to uncover the transformative potential of digital finance in bridging the financial gap in India. Our research will contribute valuable insights into the effectiveness of digital finance initiatives in fostering financial inclusion, providing evidence-based recommendations for policymakers, financial institutions, and fintech companies seeking to create a more inclusive financial landscape for all segments of Indian society. This research is not merely theoretical but grounded in empirical evidence and real-world observations. By synthesizing findings from existing literature and complementing it with primary data analysis, we aim to provide a comprehensive understanding of the dynamics shaping digital finance and financial inclusion in India. Our findings will be particularly relevant for policymakers, financial regulators, and industry stakeholders, informing strategic decision-making and shaping the future direction of digital finance initiatives in India.

Examining the Influence of AI Chatbots on Semantic Web-Based Global Information Management in Various Industries

This article presents a comprehensive analysis of the application and effect of ChatGPT, an advanced AI chatbot model, on global information management across various industries such as healthcare, industry, education, and more. Leveraging a dataset obtained from the Scopus database encompassing research papers from 2022 to 2023, this study investigates the influence of ChatGPT by examining publisher impact, authorship patterns based on Lotka's Law, country-specific scientific production, and keyword distribution. The analysis sheds light on prominent publishers, prolific authors, geographic distribution of research contributions, and prevailing research themes. By understanding the impact of ChatGPT in these sectors, this research contributes to the advancement of knowledge and facilitates informed decision-making regarding the responsible and effective utilization of artificial intelligence (AI) chatbot technologies in global information management.

Optimizing the fatigue‐resistant actuation performance of gel‐based bionic artificial muscles (GBAMs): A comparative study on crosslinking agents

AbstractThe study examined the impact of various calcium salts crosslinking agents on the fatigue‐resistant actuation performance of gel‐based bionic artificial muscles (GBAMs) that exhibited directional bending deflection and generated actuation force when electrically stimulated, thereby converting electrical energy into mechanical energy. Furthermore, a comparative investigation was carried out to examine the mechanical properties, electrochemical characteristics, microstructure, material composition, and actuation lifespan of GBAMs doped with various calcium salts, which were commonly found in biological muscles. Moreover, this research paper offered a comprehensive analysis of the mechanoelectric coupling's contribution towards optimizing the fatigue‐resistant actuation performance of the GBAM. The findings indicated that the GBAM, synthesized through the cross‐linking of calcium iodide doped with a 25% volume fraction of ethanol absolute, exhibited superior mechanical properties, electrochemical characteristics, microstructure, and actuation lifespan when compared to various other calcium salts. Hence, following a comprehensive comparison, it could be deduced that the fatigue‐resistant actuation performance of the GBAM, synthesized using calcium iodide doped with a 25% volume fraction of ethanol absolute as a crosslinking agent, exhibited the highest level of effectiveness when compared to the other four calcium salts.