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193 articles for “advanced data structures”
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 Read article
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QSAR Modeling Techniques: A Comprehensive Review of Tools and Best Practices
Abstract: Quantitative Structure–Activity Relationship (QSAR) modeling has become an essential tool in drug discovery, toxicity assessment, and environmental chemistry. By correlating chemical structure with biological activity or toxicity, QSAR enables the prediction of compound behavior without extensive experimental testing. This approach not only saves time and resources but also supports ethical practices by reducing reliance on animal studies. The evolution of QSAR from basic linear models to advanced machine learning and …
Published in International Journal of Cheminformatics · Vol. 3, Issue 1, 2025 · pp. 56–63 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Applications of Machine Learning Algorithms in Health Data Science (HDS) for Next Research Directions: A Survey Report
Abstract: At present time, data science is the big trend in computer science. The functioning of this technology is purely based on other advanced technology known as machine learning (ML). Data science and ML are subsets of artificial intelligence (AI). When a process of data science is used in healthcare systems, the new system is known as health data science (HDS). HDS is a branch of data science used to handle …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 16–21 Read article
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Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 Read article
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A Pre-experimental Evaluation of a Structured Educational Program on Awareness of Mosquito-borne Diseases in Senior Secondary School Students in Punjab
Abstract: Introduction: Mosquitoes constitute the most important single family of insects from the standpoint of human health. They are found all over the world. The four important groups of mosquitoes in India that are related to disease transmission are the Anopheles, Culex, Aedes, and Mansonia. Aims: The aims of the study are to assess the effectiveness of structured teaching program on knowledge regarding mosquito-borne diseases among students of senior secondary schools …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 2, Issue 1, 2024 · pp. 7–14 Read article
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Integration of 5G and Low Earth Orbit (LEO) Satellite Communication for Global Connectivity
Abstract: This integration revolutionizes global connectivity by merging 5G's urban capabilities with LEO's wilderness coverage. This research examines how LEO satellite constellations can complement terrestrial 5G networks to extend high-speed, low-latency connectivity to underserved regions including rural areas, oceans, and airspace. Recent breakthroughs in LEO satellite technology and successful demonstrations of 5G-satellite integration point to a rapidly evolving ecosystem with significant market growth potential. To fully realize the potential of advanced …
Published in Journal of Thermal Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 15–32 Read article
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Optimizing Airline Efficiency Using Big Data and Predictive Analytics
Abstract: Recent technological advancements have resulted in the generation of vast volumes of data across industries, including the airline sector, supporting operational control and service quality. Big Data Analytics (BDA) enables organizations to analyze large and complex datasets to derive actionable insights that support informed decision – making and superior operational performance. This review paper systematically analyzes twenty relevant research studies to explore the application of Big Data Analytics (BDA) within …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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Optimization of Automatic Energy Management System Using Renewable Resources
Abstract: With the increasing demand for energy efficiency and sustainability, smart home energy management systems (SHEMS) have emerged as promising solutions to optimize residential energy consumption. This paper presents a comprehensive review of SHEMS technologies, focusing on their design, implementation, and impact. SHEMS integrates advanced sensors, real-time data analytics, and intelligent algorithms to monitor, control, and optimize energy usage within the home environment. By leveraging machine learning and predictive modelling techniques, …
Published in Journal of Thermal Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
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Optimization of Lightweight Polymer Composites Using Finite Element Analysis Machine Learning and Topology Optimization Techniques for Aerospace Applications
Abstract: The advancement of aerospace engineering depends on lightweight polymer matrix composites (PMCs) because they help decrease weight while improving fuel efficiency and payload capacity together with increased structural integrity. Research developed a computer program comprising FEA with ANN and TO optimize high-performance PMCs through integrated design approaches. The combination of Python-controlled LS-DYNA simulations measured hybrid composite laminate resistance to impact while an ANN model obtained data from simulations to forecast …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 693–709 Read article
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Investigations of Mechanical Testing and its Effects on Lithium Ion Battery and Battery Pack for Electric Vehicle Application
Abstract: This research delves into the comprehensive study of mechanical testing methodologies and their consequential impact on the structural integrity, safety, and performance of Lithium-Ion batteries (Li-ion) and battery packs designed for electric vehicle (EV) applications. The investigation aims to enhance the understanding of mechanical stressors' influence on the reliability and safety of energy storage systems crucial for the sustainable advancement of electric mobility. The paper opens with mechanical testing protocols …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 2, 2024 · pp. 35–49 Read article
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Ecomotion Cityglide Commuter E-Bike
Abstract: The transition from conventional gasoline motorcycles to electric bikes represents a pivotal step in addressing the increasing demand for sustainable transportation solutions in urban environments. This paper meticulously explores the multifaceted aspects of this transition, focusing on the technological advancements, design innovations, and societal implications associated with the adoption of electric bikes. Electric bikes, powered by Brushless DC (BLDC) motors and rechargeable battery packs, offer a suite of benefits over …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 2, Issue 1, 2024 · pp. 43–49 Read article
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Strategies for Flood Mitigation
Abstract: The world has always experienced change. Water-too much or too little is the most common cause of migration and a city's downfall. The notable and significant distinction right now is that we are seeing it in real-time for the first time in human history. We contributed to the dangers that were produced, and we contributed to the remedies that will influence the pace and scope of change and disruption. We …
Published in International Journal of Rural and Regional Development · Vol. 1, Issue 1, 2023 · pp. 1–9 Read article
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Process Optimization of Spot Welding for Galvanized Automotive Steel Sheets
Abstract: Resistance Spot Welding (RSW) is a pillar of the modern automotive industry with the usage of lightweight and high-strength products at the highest point of demand. The optimum weld quality of galvanized steel sheets which is a material of choice because of its additional corrosion protective property is however not achieved easily. This study is a well-developed data-based solution to designing the RSW process in the most efficient way, providing …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 32–42 Read article
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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A Review of Computational Methods for Image Restoration and Noise Reduction Using Reference Images
Abstract: Digital imaging systems play a vital role in numerous application domains, including consumer photography, biomedical imaging, remote sensing, aerial surveillance, and astronomical observation. Despite continuous advancements in imaging hardware and software, the visual data acquired by these systems often suffer from degradation caused by spatially non-uniform blur. This blur may arise due to several factors, such as lens imperfections, atmospheric turbulence, sensor limitations, motion between the camera and the scene, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 23–30 Read article
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Identification and Evaluation of Safety Factors in Construction Industry Using Fuzzy Reasoning Technique
Abstract: Modern construction projects, characterized by their complexity and uniqueness, are inherently susceptible to various risks. These risks represent uncertain events that may arise during the project's life cycle, potentially influencing its objectives either positively or negatively. Positive risks are referred to as opportunities, while negative risks are identified as threats. To effectively harness these opportunities and mitigate threats, the implementation of Risk Management is essential. A novel theoretical framework known …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 3, 2025 · pp. 7–12 Read article
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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A Study on Breast-feeding Self-Efficacy and Its Associated Factors Among Mothers
Abstract: Introduction: The process through which a kid is fed human breast milk is known as breastfeeding. Breastfeeding has a significant impact on disease prevention and health promotion. It helps to increase bonding with baby and mother. Oestrogen, progesterone, prolactin, and oxytocin are the four primary hormones that contribute to the production of breastmilk. A modifiable element that can improve breastfeeding success and duration is breastfeeding self-efficacy. Aim: To evaluate mothers' …
Published in International Journal of Midwifery Nursing And Practices · Vol. 1, Issue 1, 2023 · pp. 31–36 Read article
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The Emerging Golden Age of Astrophysics: Progress, Discoveries, and Future Directions
Abstract: The period between 2024 and 2026 has marked a transformative era in astrophysics, fundamentally reshaping our understanding of the universe and its underlying physical mechanisms. Significant advancements in observational astronomy, computational modeling, and space exploration technologies have enabled scientists to investigate cosmic phenomena with unprecedented precision. Among the most groundbreaking achievements, the James Webb Space Telescope (JWST) has provided high-resolution infrared observations that revealed the large-scale distribution of dark matter, …
Published in International Journal of Universe · Vol. 2, Issue 1, 2026 · pp. 6–9 Read article