International Journal of Supportive Research, ISSN: 3079-4692
About Us The International Journal of Supportive Research (IJSR), ISSN: 3079-4692 is a peer-reviewed, open-access journal dedicated to advancing interdisciplinary research that supports innovation, problem-solving, and informed decision-making across diverse domains. Published by Research Radicals Publication, Hong Kong, IJSR serves as a platform for scholars, professionals, and researchers to share groundbreaking ideas and practical applications that address real-world challenges. Our mission is to foster collaboration and knowledge-sharing by publishing high-quality research that contributes to the development and betterment of various fields. The journal covers a wide spectrum of topics, including but not limited to: Applied research in healthcare, education, and technology Interdisciplinary approaches to global challenges Evidence-based practices and methodologies Emerging trends in social, behavioral, and environmental studies Impact-driven studies that inform policy and practice At IJSR, we are committed to ensuring the dissemination of impactful and accessible research that supports growth, innovation, and sustainable progress. With a focus on inclusivity and international collaboration, we aim to inspire meaningful change and empower researchers worldwide. Here are the Key details of the Journal : International Journal of Supportive Research (IJSR) ISSN: 3079-4692 Impact Factor: 5.698 Chief Editor: Dr. Lian Chan, Senior Research Officer, City University of Hongkong Publisher: Research Radicals, Hong Kong Starting Year: 2023 Frequency: Semi-Annually [2 issues per year] Languages: English Accessibility: Open Access Crossref DOI Prefix: doi.org/10.64180/oct.ijsr Peer Review Process: Double Blind Peer Review Process Subject: English Plagiarism Checker: Turnitin Publication Format: Online Contact No.: +852-23591001 Email: researchradicals@gmail.com Website: https://www.researchradicals.com Address: 28/P, 1063 King's Road, Quarry Bay, Hong Kong S.A.R. Key Features of JIERS Journal listed in Google Scholar Indexed with CrossRef DOI Journal Publishes online on continuous basis Online article submission Standard peer review process We look forward to your valuable contributions and to fostering meaningful dialogue and collaboration in the field of research studies.
Effect of Regular Physical Activity on Physical Fitness and Academic Performance among College Students
Physical education promotes students' overall development by enhancing physical fitness, mental health, and academic achievement. The current study is to investigate the impact of regular physical activity on certain physical fitness components and academic performance in college students. A total of 60 college students (ages 18-22) were chosen as subjects and separated into two categories: physically active and physically inactive. Physical fitness characteristics such as cardiovascular endurance, muscular strength, flexibility, and body mass index (BMI) were measured.
Physical Education, Physical Activity, Physical Fitness, Academic Performance, College Students
Role of Physical Education in Women Empowerment
Women's empowerment is an essential component of social progress and gender equality. Physical Education (PE) empowers women by increasing physical fitness, mental strength, self-confidence, leadership abilities, and social participation. Participation in physical education and sports allows women to break down old boundaries, combat gender stereotypes, and gain independence. This research article emphasises the importance of physical education in empowering women through health, education, social inclusion, and economic opportunity.
Physical Education, Women Empowerment, Sports, Gender Equality, Health, Confidence
Development of typical-element-doped functional π systems consisting of naphthalene monoimide units
The function of these compounds is closely related tontheir delocalized π-electrons, which can be precisely modulated by introducing functional groups on the periphery of the compound. The characteristics of such designed molecules strongly rely on the inherent electronic nature of the parent skeleton, highlighting the importance of selecting an appropriate motif molecule. Such π-conjugated molecules should satisfy two criteria: (1) they intrinsically exhibit desirable electronic properties and (2) their structures are readily transformable via well-established organic transformations. π-Conjugated molecules are intrinsically electrondonors because the π-electrons are loosely bound to the core.
Naphthalene monoimide, Typical element, Functionalized π-system, n-Type semiconductor
Key Activities in Managing Software Project Effort
Accurate effort estimation is a crucial task for software business progression: for customers, acquiring software products or making project contracts for software implementation, accurate effort estimation enables adherence to schedule and budget without delay in deployment and introduction (Conte, et al., 1986; Sommer- ville, 2001).
project management, software development effort management
In this paper we practically deal with the problem of factorizing large integers. The various algorithms that have been proposed are not efficient that is they do not run in polynomial time. We use the algebraic approach proposed by Wanambisi et al [1]. We define a large integer based on the number of digits and seek to decompose these numbers based on place values.
Integer factorization, Composite integer, Algebraic approach, Primes, Algorithms, Prime differences
Advancing Cybersecurity in Industrial Control Systems: Frameworks, Threat Modeling, and Resilience Strategies
Industrial Control Systems (ICS) form the backbone of critical infrastructure sectors such as energy, manufacturing, water, and transportation. However, their increasing convergence with digital technologies, cloud platforms, and the Industrial Internet of Things
Industrial Control Systems (ICS), Cybersecurity Frameworks, Threat Modeling, Resilience Strategies, Critical Infrastructure Protection.
Technology-Enhanced Learning Methods – Current Trends and Practices
Every area of life is changing at a breakneck pace in the contemporary digital age. The digital world reduced in size because of technical advancements. Even in the classroom, we cannot avoid the urge.
E learning, student-centric learning, ICT, Podcasts, LSRW, New Technologies
Dr. G. Kiran Kumar Reddy, Dr. A.Kiran Mayee
Present Scenario of Library and Information Facility (Source and Service) in Support of Legal Education and Legal Research: A Study of DSNLU Library, Visakhapatnam, Andhra Pradesh
The quality of legal education holds the key to achieving the avowed ambitions and the dreams of the makers of the Indian constitution.
education, human resources, information, legal, library, research, scenario
Role of Maulana Azad in Modernizing Education System in India
This paper will critically examine the role of Azad’s contribution towards modernizing the education system in India. This paper would also study how Azad was distinct from other intellectuals to promote the notion of education in India. Azad has a remarkable place in the history of modern India because he challenged the earlier assumptions of political thought of Aligarh school in early twenties. He played a major role in keeping the movement of education alive in the country and insisted the students and all Muslims of India to learn Devangri and Hindi scripts.
development, economically, education, modern, nation, system, vision
Dr. T.Sharon Raju, Dr. P. Ramesh, Dr. Annusha Bonila, S. Uma Maheswara Rao, Sanjeevi Rao Boddepalli
A Study on "Emotion Regulation and Psychological Well-being in Faculty Work Engagement"
In the last few years, there has been an upsurge in interest in positive psychology and its applicability in educational contexts (Stiglbauer et al., 2013; Carmona-Halty et al., 2021). A special focus has been placed on how pleasant emotions influence academic engagement and performance (Pekrun and Linnenbrink-Garcia, 2012; Zhang et al., 2022). Psychological capital is a positive psychological growth condition characterized by efficacy, optimism, hope, and resilience (Luthans et al., 2015). Efficacy relates to having a trusting willingness to embrace and give the required effort to complete difficult jobs.
achievement, emotion regulation, psychological well-being, relationship
Dr. V.Vasudevan, Dr. D. Venkata Ramana Moorthy, Dr. K.Dasaradhi, Dr. Annusha Bonila, Dr. Manukonda Pushpa Rajyam
Money laundering is the process of making dirty money look clean. It erodes financial institutions and weakens the financial sectors role in economic growth. It has the habit of facilitating corruption, crime and other illegal activities at the expense of countries development and can increase the risk of macroeconomic instability. The negative economic effects of money laundering on economic development are difficult to quantify. Real estate has been the preferred choice of criminals for masking illegally gained funds and manipulations, also when unaccounted funds (black money) are funneled into real estate by individuals and institutions, then it becomes impossible for an ordinary individual to buy a piece of land.
This bestowal emphasizes the use of mobile robotics for conducting inspections and Non-Destructive Testing (NDT) in various sectors, including pipeline inspection. It underscores the crucial role of regular inspections in maintaining infrastructure integrity and explains the process of creating robot prototypes for industrial applications. These robots are fully equipped to deploy NDT systems and are designed to minimize downtime or, when feasible, perform NDT in real-time to avoid costly shutdowns. Flexible automation with non-destructive imaging significantly reduces costs, minimizes dosage, integrates advanced imaging techniques, and delivers higher quality results in less time. The automated welding industry is experiencing rapid growth, driven by the technological demands of Industry 4.0, which has intensified the focus on smart sensor-equipped robotic systems. This document introduces a cutting-edge multi-robot system specifically designed for automated welding and real-time Non-Destructive Evaluation (NDE), effectively replacing outdated manual inspection methods.
Kuldeep Sharma, Ashok Kumar, Vineet Yadav, Dipak K. Banerjee
Predictive Analytics with Deep Learning for It Resource Optimization
This paper aims to discuss the impact of using predictive analytics and deep learning for IT resource management. It also helps to optimize the needs and utility of systems and diminish costs in the operations of an organization. It improves on these facets by using complex algorithms to sort through large data amounts for better forecasting. Nonetheless, some of the barriers include; high computational costs, too many input attributes and the model's interpretability.
Edge Computing vs. Cloud Computing: Where to Deploy Your Applications
This study looks at some of the most exciting and difficult IoT scenarios and demonstrates why many of the applications anticipated for those scenarios will not be able to be met by the computing and storage models now in use in data centres. Cloud computing and edge computing are two quickly developing technologies that might have a big influence on how information technology and other sectors develop in the future. An overview of edge and cloud computing's current status, a discussion of industry stakeholders' viewpoints, and projections for these complementary technologies' future are the objectives of this survey report. We provide important insights into the possible advantages, difficulties, and ramifications of edge and cloud computing by reviewing the most recent scholarly and commercial literature, speaking with experts in-person and via surveys, and evaluating the information gathered. Over the last ten years, cloud computing has emerged as the de facto option for the processing and storage of massive amounts of data
Transdermal Drug Delivery Systems: Formulation and Evaluation
Transdermal drug delivery systems (TDDS) have garnered significant interest in the pharmaceutical industry due to their potential to offer numerous advantages over conventional oral or parenteral routes of drug administration. This abstract provides an overview of the formulation and evaluation aspects of transdermal drug delivery systems. The formulation of TDDS involves the careful selection of suitable drug candidates, excipients, and delivery technologies to ensure optimal drug permeation through the skin barrier. Various formulation strategies, including patches, gels, creams, and ointments, are explored to enhance drug solubility, stability, and skin permeability. Evaluation of TDDS is critical to ensure their safety, efficacy, and patient compliance. In vitro methods such as Franz diffusion cells are commonly employed to assess drug release kinetics and permeation profiles across synthetic or animal skin membranes. Additionally, in vivo studies involving human subjects provide valuable insights into TDDS performance under physiological conditions. Furthermore, various physicochemical characterization techniques, including differential scanning calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM), are utilized to investigate the structural integrity and stability of TDDS formulations. In conclusion, the development of transdermal drug delivery systems requires a comprehensive understanding of formulation principles and rigorous evaluation methods to achieve desired therapeutic outcomes. Continued research and innovation in this field hold promise for the advancement of novel TDDS formulations with improved efficacy, safety, and patient acceptability.
Transdermal drug delivery systems, Formulation, Evaluation, Permeation, Physicochemical characterization.
Soft Power vs. Hard Power: Analyzing the Effectiveness of Different Strategies in International Influence
In the complex landscape of international relations, the interplay between soft power and hard power significantly shapes global influence and diplomacy. This paper explores the comparative effectiveness of these two distinct strategies in exerting influence on the global stage. Hard power, characterized by military and economic coercion, offers direct and tangible means of influence but often at the cost of long-term relationships and stability. In contrast, soft power relies on cultural appeal, diplomatic engagement, and the attraction of values and policies, aiming for a more sustainable and consensual form of influence.
Soft Power, Hard Power, International Influence, Geopolitical Strategy, Diplomatic Engagement
Distributed CDN Models for Improved Fault Tolerance and Resiliency
With the growing demand for reliable and scalable content delivery, Distributed Content Delivery Network (CDN) models have emerged as a vital solution for enhancing network performance, fault tolerance, and resiliency. Traditional centralized CDNs often suffer from single points of failure, limited scalability, and vulnerabilities in the face of large-scale disruptions. In contrast, distributed CDN architectures leverage decentralized infrastructure to improve content availability, minimize latency, and optimize resource utilization across geographically dispersed edge servers. This paper investigates various distributed CDN models that focus on improving fault tolerance and resiliency, addressing challenges such as network congestion, hardware failures, and traffic surges.
Distributed CDN, Fault Tolerance, Resiliency, Content Delivery, Network Scalability
Next-Generation CDN Architectures: Leveraging 5G for Ultra-Low Latency
The rapid evolution of digital services and applications, such as real-time gaming, virtual reality, and autonomous systems, has amplified the demand for ultra-low latency content delivery networks (CDNs). Traditional CDN architectures face challenges in meeting these demands due to limitations in proximity to end users and network capabilities. This paper explores next-generation CDN architectures designed to leverage the transformative potential of 5G technology. By integrating edge computing, network slicing, and massive connectivity, 5G-enabled CDNs can achieve unprecedented levels of latency reduction, throughput, and reliability.
Next-Generation CDN, 5G Technology, Ultra-Low Latency, Edge Computing, Network Slicing
Personalization and Performance Optimization in AI-Augmented Content Delivery Networks
The advent of artificial intelligence (AI) has significantly transformed the landscape of Content Delivery Networks (CDNs), enabling more personalized, efficient, and performance-driven content distribution. This paper explores the integration of AI in CDNs to enhance both personalization and performance optimization. We examine the application of machine learning algorithms for real-time content recommendation, traffic prediction, and adaptive caching strategies, which enable CDNs to tailor content to individual user preferences and optimize resource utilization. Additionally, AI-driven analytics allow for proactive anomaly detection and network optimization, reducing latency and ensuring seamless user experiences across diverse devices and geographic locations
AI-Augmented CDNs, Personalization, Performance Optimization, Machine Learning, Content Delivery Networks
Drug-Device Combination Products: Design, Development and Regulatory Considerations
Drug-device combination products represent a significant and evolving segment within the healthcare industry, offering novel therapeutic approaches and enhanced patient care. This abstract delves into the multifaceted landscape of designing, developing, and regulating such products. The design phase of drug-device combination products demands a comprehensive understanding of both pharmaceutical and engineering principles. It necessitates seamless integration of drug substances with medical devices, ensuring compatibility, stability, and efficacy. Moreover, considerations such as patient usability, ergonomic design, and manufacturing feasibility play pivotal roles in product development. Development of drug-device combination products involves intricate processes, spanning from concept ideation to commercialization.
Drug-device combination products, Design, Development, Regulatory considerations, Healthcare industry.
The Role of Information Technology in Firm Performance
The role of information technology (IT) in enhancing firm performance has become increasingly critical in the modern business environment. This paper explores the impact of IT on organizational outcomes, focusing on productivity, efficiency, innovation, and competitive advantage. It examines how IT facilitates decision-making processes, streamlines operations, and fosters collaboration across departments, ultimately leading to improved financial performance and customer satisfaction. Furthermore, the paper delves into various IT frameworks and tools, such as enterprise resource planning (ERP) systems, data analytics, and cloud computing, assessing their effectiveness in optimizing business strategies. Through a combination of case studies and empirical analysis, the paper highlights the positive correlation between IT adoption and firm performance, while also addressing potential challenges and barriers to successful implementation. The findings suggest that, when leveraged strategically, information technology can act as a key enabler of sustainable growth and long-term success in a highly competitive marketplace.
Information Technology, Firm Performance, Productivity, Competitive Advantage, Innovation
Combining Reinforcement Learning and Human Feedback for AI System Optimization
The optimization of artificial intelligence (AI) systems has become increasingly complex due to the dynamic nature of real-world environments. This paper presents a novel approach that combines reinforcement learning (RL) with human feedback to enhance AI system performance. By integrating human insights into the RL process, we aim to address the limitations of traditional RL methods, which often struggle to learn efficiently in sparse reward environments. Our proposed framework utilizes human feedback to guide the exploration of the action space, improving the efficiency of learning and accelerating convergence to optimal solutions. We demonstrate the effectiveness of this hybrid approach through a series of experiments across various domains, including robotics and game playing. The results indicate a significant improvement in learning speed and overall performance compared to standard RL algorithms. This study highlights the potential of leveraging human expertise in the training of AI systems, paving the way for more robust and adaptive AI solutions in complex applications.
Reinforcement Learning, Human Feedback, AI System Optimization, Hybrid Approach, Learning Efficiency
Biosensors and Their Applications in Point of Care Diagnostics
Biosensors have emerged as powerful tools in the field of point-of-care diagnostics, offering rapid, sensitive, and specific detection of biomolecules with applications ranging from healthcare to environmental monitoring. This abstract provides an overview of biosensors and their pivotal role in revolutionizing diagnostic techniques. It begins by elucidating the fundamental principles underlying biosensor design, encompassing the interaction between biological recognition elements and transducing elements to convert biological signals into measurable outputs. Various types of biosensors, including electrochemical, optical, and piezoelectric biosensors, are discussed, highlighting their distinct advantages and applications. Furthermore, this abstract explores recent advancements in biosensor technology, such as the integration of nanomaterials, microfluidics, and smartphone-based platforms, which have enabled enhanced sensitivity, selectivity, and portability of biosensing devices. Moreover, the utility of biosensors in point-of-care diagnostics is emphasized, showcasing their ability to facilitate rapid and accurate detection of various analytes, including biomarkers for infectious diseases, cancer, and metabolic disorders. Finally, challenges and future perspectives in the field of biosensors are outlined, underscoring the importance of addressing issues related to assay complexity, reproducibility, and scalability to further enhance the efficacy and accessibility of point-of-care diagnostics. Overall, biosensors represent a promising avenue for advancing healthcare delivery by enabling timely and personalized disease diagnosis at the point of need.
Biosensors, Point-of-care diagnostics, Biomolecules, Transduction, Nanomaterials.
The Future of Nuclear Proliferation: Trends, Challenges, and Policy Responses
The evolving landscape of nuclear proliferation presents a complex array of trends, challenges, and policy responses that demand comprehensive analysis and strategic foresight. This paper explores the future trajectories of nuclear proliferation, emphasizing the increasing sophistication of nuclear technologies and the proliferation risks associated with non-state actors and emerging states. It examines current challenges, including the potential for regional arms races, the impact of technological advancements on nuclear security, and the effectiveness of existing non-proliferation regimes. The paper further assesses policy responses from major international actors and institutions, evaluating their effectiveness and proposing new strategies to enhance global nuclear security. By analyzing historical patterns, current trends, and future projections, this study aims to provide a nuanced understanding of nuclear proliferation dynamics and offer actionable recommendations for policymakers to address emerging threats and ensure a stable and secure nuclear order.
Nuclear Proliferation, Non-State Actors, Technological Advancements, Non-Proliferation Regimes, Policy Responses
AI-Based Disaster Response: Predictive Models for Emergency Management
In recent years, the increasing frequency and intensity of natural disasters have highlighted the urgent need for effective emergency management strategies. This paper presents an innovative approach to disaster response through the application of artificial intelligence (AI) and predictive modeling. By leveraging vast datasets, including historical disaster records, real-time environmental data, and social media analytics, we developed predictive models that enhance situational awareness and facilitate timely decision-making during emergencies. Our research showcases the potential of machine learning algorithms to forecast disaster occurrences and assess their impacts on communities. Furthermore, we discuss the integration of these predictive models into existing emergency management frameworks, emphasizing their role in resource allocation, evacuation planning, and post-disaster recovery efforts. The findings indicate that AI-driven predictive analytics can significantly improve response times and outcomes, ultimately reducing the loss of life and property. This paper contributes to the growing body of knowledge on AI applications in disaster management and underscores the importance of proactive strategies in mitigating the effects of future disasters.
Artificial Intelligence, Disaster Response, Predictive Modeling, Emergency Management, Machine Learning
Analyzing the Impact of Regulatory Changes
This paper examines the impact of regulatory changes on various sectors, focusing on their economic, social, and operational implications. Regulatory frameworks are dynamic, often evolving to address emerging challenges, promote innovation, or mitigate risks. These changes can significantly influence business strategies, market behavior, and compliance costs, while also shaping consumer protections and societal outcomes. By employing a multi-method approach that includes case studies, econometric analysis, and stakeholder interviews, this study evaluates the effects of recent regulatory reforms across industries such as finance, healthcare, and technology. The findings highlight both intended and unintended consequences, ranging from enhanced transparency and stability to increased compliance burdens and market inefficiencies.
Regulatory Changes, Economic Impact, Compliance Strategies, Policy Analysis, Market Dynamics
Innovative Techniques for Mineral Extraction in Underground Mines
This paper explores innovative techniques for mineral extraction in underground mining operations, addressing the growing demand for efficient and sustainable resource recovery. Traditional methods often face challenges such as safety hazards, environmental impact, and declining ore grades, necessitating the development of advanced extraction technologies. The study highlights several cutting-edge approaches, including automation, remote sensing, and the use of biodegradable solvents, which enhance operational efficiency while minimizing ecological footprints. Furthermore, it examines the integration of real-time data analytics and machine learning to optimize extraction processes and reduce operational costs. By evaluating case studies and recent advancements in technology, this paper aims to provide insights into best practices for future underground mining endeavors, promoting a balance between economic viability and environmental stewardship.
Mineral Extraction, Underground Mining, Innovative Techniques, Automation, Sustainability
Design of Slope Stabilization Systems in Surface Mines for Improved Safety
Slope stabilization in surface mines is crucial for ensuring safety and operational efficiency. This paper presents a comprehensive analysis of various slope stabilization systems designed to mitigate risks associated with landslides and soil erosion in mining environments. The study examines current stabilization techniques, including mechanical, vegetative, and geosynthetic methods, evaluating their effectiveness based on site-specific conditions and geological characteristics. Additionally, the paper highlights innovative technologies, such as real-time monitoring systems and advanced computational modeling, that enhances slope stability assessments and predict potential failures. Through case studies and empirical data, the research underscores the importance of a multidisciplinary approach in the design of slope stabilization systems, integrating engineering principles with environmental considerations. The findings aim to provide guidelines for mining operators to adopt best practices in slope management, ultimately improving safety standards and reducing operational disruptions in surface mining activities.
Slope stabilization, Surface mines, Safety, Landslide mitigation, Geotechnical engineering
Balancing Education and Cybersecurity: Addressing Data Privacy Challenges in Schools and Higher Education
As educational institutions increasingly integrate technology into their curricula and administrative processes, the necessity for robust cybersecurity measures becomes paramount. This paper explores the delicate balance between fostering an innovative educational environment and ensuring the protection of sensitive data within schools and higher education institutions. The rapid digital transformation in education has led to heightened vulnerabilities, exposing students, faculty, and administrative staff to potential data breaches and privacy violations. Through a comprehensive analysis of current data privacy challenges, this study identifies key vulnerabilities in existing educational frameworks and evaluates the implications of these challenges on student safety and institutional integrity. By examining case studies and best practices from various educational settings, the paper proposes actionable strategies for enhancing cybersecurity protocols while maintaining an enriching educational experience. Ultimately, this research aims to inform policymakers, educators, and cybersecurity professionals about the critical need for a collaborative approach to safeguarding data privacy in the evolving landscape of education.
Cybersecurity, Data Privacy, Education Technology, Vulnerabilities, Institutional Integrity
Exploring the Role of Cybersecurity in Integrated Programs for protecting and Improving Digital Platforms
This paper explores the critical role of cybersecurity in integrated programs designed to protect and enhance digital platforms. In the rapidly evolving digital landscape, where platforms are central to communication, commerce, and data management, robust cybersecurity measures have become essential to safeguarding these infrastructures from sophisticated threats. The study focuses on the integration of cybersecurity frameworks within broader digital strategies, examining how they can be leveraged to not only protect but also improve the resilience, performance, and trustworthiness of digital platforms. By analyzing various case studies and contemporary practices, the paper highlights key cybersecurity tools, techniques, and policies that enable the proactive identification and mitigation of vulnerabilities. It also addresses the challenges of balancing security with usability and innovation, providing insights into how organizations can align their cybersecurity efforts with strategic objectives for sustainable digital growth. Ultimately, this research emphasizes the necessity of a cohesive approach to cybersecurity within integrated programs to foster a safer and more reliable digital ecosystem
Cybersecurity, Digital Platforms, Integrated Programs, Vulnerability Mitigation, Digital Ecosystem Protection