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611 articles for “practice efficiency”
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Resolving International Sports Disputes: An Exploration of Mediation and Conciliation
Abstract: The globalization of sports has led to an increase in cross-border disputes, necessitating effective and efficient dispute resolution mechanisms. Traditional litigation and arbitration methods often prove time-consuming, costly, and ineffective in preserving relationships. This research explores the role of Alternative Dispute Resolution (ADR) methods, specifically mediation and conciliation, in resolving international sports disputes. Through a comparative analysis of international sports organizations and dispute resolution mechanisms, this study examines the benefits …
Published in Recent Trends in Sports · Vol. 1, Issue 2, 2024 · pp. 14–27 Read article
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Lignin-modified bitumen: Exploring characteristics and performance
Abstract: The surge in crude oil prices has sparked interest in finding efficient and cost-effective alternatives to bitumen, a binder used in road pavement. Bitumen, derived from crude oil distillation or natural deposits, is primarily utilized in pavement grade bitumen, accounting for 83% of its usage. However, traditional hot mix asphalt, which relies heavily on bitumen, emits significant amounts of CO2, CH4, and N2O, contributing to environmental concerns. To address these …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 24–30 Read article
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Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
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Automatic Car Controller Based on Sign Board using Deep Learning and IOT
Abstract: The rapid growth of intelligent transportation systems has increased the demand for safer and more efficient driving solutions. Conventional vehicles often rely heavily on human intervention, which can lead to accidents due to negligence, fatigue, or poor visibility of traffic signs. This project proposes an automated car control system that utilizes deep learning and Internet of Things (IoT) technologies to recognize traffic signboards and respond accordingly. The primary objective is …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article
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Algebraic Foundations of AES (Advanced Encryption Standard): Group Theory and Finite Field Applications in Symmetric Cryptography
Abstract: This paper presents a mathematical study of symmetric cryptographic algorithms, with a particular emphasis on the Advanced Encryption Standard (AES), which is one of the most widely used encryption schemes in modern security applications. The study highlights how abstract mathematical frameworks such as group theory, finite fields, and vector space concepts provide the foundation for the design, implementation, and analysis of AES. By approaching the algorithm from a mathematical perspective, …
Published in Recent Trends in Mathematics · Vol. 2, Issue 1, 2025 · pp. 12–16 Read article
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Rethinking Type-1 Diabetes Treatment: Emerging Medicines Based on AAT Therapy and C-peptide Preservation Therapy
Abstract: The increasing number of cases, especially in the younger age group, along with the lack of accessible clinical solutions, make Type-1 Diabetes (T1D) a growing global health concern. While gene therapy and transplantation approaches are promising avenues, their excessively high costs and logistical difficulties make them inaccessible to the majority and can impose a financial burden on those suffering from it, adding to the challenges already faced by these advanced …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 19–29 Read article
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Forecasting Commodity Prices Using Deep Learning Techniques: An Empirical Evidence from India
Abstract: Commodity price forecasting is instrumental in financial markets, providing framework for investment choices and risk management practices. Traditional models, including statistical and machine learning approaches, have limitations in capturing the nonlinear and volatile nature of commodity prices. Deep learning (DL) techniques have emerged as promising alternatives, leveraging advanced neural networks to enhance predictive accuracy. This study presents a thorough and comprehensive examination of deep learning applications in commodity price prediction, …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 08–12 Read article
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Enhancing Safety Protocols in Industrial Operations
Abstract: Industrial safety is a crucial aspect of maintaining both operational efficiency and protecting the workforce in hazardous environments. Despite significant advancements in safety technologies and regulatory frameworks, industrial accidents remain a persistent problem, often leading to severe injuries, fatalities, and financial losses. Such incidents typically arise from a combination of factors, including human error, equipment malfunctions, and insufficient safety protocols. In response to these challenges, this paper examines key strategies …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 3, 2024 · pp. 1–5 Read article
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Adaptive Traffic Control Systems: Enhancing Urban Mobility through Real-Time Traffic Management
Abstract: Traffic congestion is a ubiquitous challenge in urban areas, necessitating innovative solutions to improve transportation efficiency and alleviate gridlock. Traditional traffic signal control methods often prove inadequate in dynamically adapting to fluctuating traffic conditions, leading to increased travel times, fuel consumption, and emissions. In response, adaptive traffic control systems have emerged as a promising approach to mitigate congestion and enhance traffic flow in urban environments. These devices dynamically modify signal …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 37–45 Read article
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Bimetallic Catalysis in Renewable Energy Applications: A Review
Abstract: The transition to renewable energy sources necessitates innovative catalytic solutions to improve efficiency and sustainability. Bimetallic catalysis, leveraging the synergistic effects of two distinct metals, has emerged as a promising strategy in various renewable energy applications. This review explores the unique properties and mechanisms of bimetallic catalysts, highlighting their roles in biomass conversion, hydrogen production, and CO2 reduction. We delve into the interplay of electronic and geometric effects in these …
Published in Journal of Catalyst & Catalysis · Vol. 11, Issue 2, 2024 · pp. 25–29 Read article
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Development and Evaluation of a Cost-Effective UV-Protective Cream Containing Para-Aminobenzoic Acid and Aloe Vera for Indian Climatic Conditions.
Abstract: The increasing incidence of ultraviolet (UV) radiation-induced skin disorders has heightened the demand for effective, affordable photoprotective agents, especially in countries with high sun exposure such as India. This study aimed to develop a cost-effective and efficient UV-B protective cream formulation suitable for populations in Indian latitudes. Para-aminobenzoic acid (PABA) was selected as the primary sunscreening agent due to its high UV-B absorption efficiency, low toxicity, and affordability compared with …
Published in Recent Trends in Cosmetics · Vol. 2, Issue 2, 2025 · pp. 7–18 Read article
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Phytopharmacognostical Study and Development & Assessment of Topical Herbal Ointment from Leaves of Calotropis gigantea
Abstract: Joint pain is a common problem that affects people all over the world and calls for efficient treatment solutions. The present study investigated the creation of a topical formulation for the treatment of joint pain that uses an extract from the leaves of Calotropis gigantea. C. gigantea is sometimes referred to as huge milk weed and aak leaves. It is a member of the Apocynaceae family. This versatile plant has …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 114–120 Read article
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AI-Driven Robotics for Sustainable Solutions in Disaster Management
Abstract: Disasters, whether natural or man-made, present significant challenges to societies worldwide. Efficient response, recovery, and mitigation strategies are crucial to minimizing human suffering, loss of life, and economic damage. Traditional disaster management strategies, while effective to some degree, often face limitations related to human resources, response time, accessibility, and safety. The integration of artificial intelligence (AI) and robotics into disaster management offers transformative potential for overcoming these challenges. This paper …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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Electromagnetic and Dielectric Performance of Polymer–Ceramic Composite Substrates for Fractal-Based IoT-Antenna Fabrication
Abstract: Polymer–ceramic composite substrates play a crucial role in determining the electromagnetic performance, mechanical stability, and thermal reliability of radio-frequency devices. In this work, a polymer-based composite substrate is systematically investigated for its suitability in compact IoT and RFID antenna applications. A fractal-structured antenna is employed as a functional test platform to evaluate the dielectric behavior, impedance characteristics, and radiation efficiency of the composite substrate. Novelty of the proposed reader antenna …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1518–1534 Read article
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Traversal Speed Comparison of BFS and DFS in Balanced and Skewed Binary Trees
Abstract: In this paper, we provide an analysis of how well both breadth-first search (BFS) and depth-first search (DFS) algorithms perform while wandering through two kinds of binary trees: balanced and skewed. The research was motivated by the practical application of storing files and directories in a certain type of parent-child relationship through the use of hierarchical file systems (e.g., windows explorer). The result of measuring how fast and versatilely these …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 2, 2026 Read article
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Synthesizing Policy Gaps, Sector-Specific Challenges, and Emerging Opportunities to Develop Novel Research Themes in India’s Circular Economy
Abstract: The concept of the Circular Economy represents an important shift away from the linear & take-make-dispose" model toward a regenerative system, with quite a number of aspects in which circularity is needed in India, due to recent decades of rapid industrialization and rising consumption. Despite supportive policy initiatives such as the National Resource Efficiency Policy and Extended Producer Responsibility frameworks, India's transition to CE remains fragmented. This synthesis aims to …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 32–39 Read article
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article
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AI-Enabled Recycling of Thermoplastic Polymer Waste in Hospitals: A Circular Economy Pathway Toward Green Hospital Certification
Abstract: This review research explores the latest role of AI in improving thermoplastic waste management for hospitals in terms of segregation accuracy, operational efficiency, and circular economy outcomes. Seventy-five relevant studies were analysed, and it was reported that AI-based systems, especially CNNs, YOLO models, and sensor-fusion approaches, achieved high accuracy in the identification and sorting of medical plastics, often above 90%. Early evidence also reveals improvements in the reduction of contaminants, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 170–182 Read article
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Harnessing Biomass for Sustainable Insect Farming and Biotechnology: Ecological Roles, Industrial Applications, and Future Opportunities
Abstract: Biomass, derived from biological materials, such as plant residues, animal waste, and agricultural by-products, plays a pivotal role in ecological systems, including those involving insects. Insects interact with biomass at multiple levels, serving as decomposers, pollinators, and converters of organic matter into valuable resources. The integration of biomass into insect ecology and farming has garnered significant attention for its potential in sustainable agriculture, waste management, and biotechnology. This review highlights …
Published in International Journal of Insects · Vol. 2, Issue 1, 2025 · pp. 17–21 Read article
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A Systematic Review on The Role of Artificial Intelligence in Assisted Reproductive Technology
Abstract: Artificial Intelligence (AI) has significantly transformed Assisted Reproductive Technology (ART) over the past five years, enhancing diagnostic accuracy, treatment personalization, and overall success rates. AI-driven algorithms and machine learning models have been integrated into various aspects of ART, including sperm selection, embryo grading, and predicting implantation success. Deep learning techniques have improved image-based embryo assessment, reduced human subjectivity and increased efficiency. Additionally, AI-powered predictive analytics have helped optimize ovarian stimulation …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article