Search
44 articles for “algorithms”
-
Optimization of Robotic Path Planning Algorithms for Autonomous Material Handling Systems
Abstract: For autonomous systems for handling materials (AMHS) to operate as efficiently as possible in industrial and logistical settings, robotic route planning is essential. This study examines many robotic route planning algorithms, emphasizing their use, ways of optimization, and difficulties in material handling systems. To improve the effectiveness, precision, and computational viability of these algorithms, the study also examines a number of optimization strategies, including machine learning, parallelization, heuristic search, and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 15–20 Read article
-
Algorithmic Ecology: A Framework for Achieving Carbon-Neutrality in Global Data Infrastructure
Abstract: The exponential growth of digital infrastructure has positioned data centers as critical enablers of the global digital economy, yet their environmental impact has become a paramount concern. Data centers consumed approximately 205 TWh globally in 2018, representing about 1% of global power usage with a steady 6% growth trend. This review synthesizes current literature on green algorithms and sustainable data center technologies, examining the intersection of artificial intelligence, machine learning …
Published in International Journal of Sustainability · Vol. 3, Issue 1, 2026 · pp. 33–48 Read article
-
Mitigation of Peak to Average Power Ratio in Orthogonal Frequency Division Multiplexing through SOP-PTS
Abstract: Orthogonal Frequency Division Multiplexing (OFDM) is a popular multicarrier modulation technology extensively employed in 4G wireless communication systems to transmit data over a dispersive channel. To address the Peak-to-Average Power Ratio (PAPR) issue in OFDM, a technique called Partial Transmit Sequence (PTS) is commonly utilized. The PTS method involves dividing the data block into non-overlapping sub-blocks and then combining them using phase factors to mitigate PAPR. However, the conventional PTS …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2024 · pp. 32–39 Read article
-
A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
-
Diet Mate: A Personal Nutrition and Health Tracking App
Abstract: The rising prevalence of chronic health conditions, including obesity, diabetes, and hypertension, has become a significant global health challenge. These conditions are often linked to poor dietary habits, which makes diet management a critical component of disease prevention and management. Traditional dietary approaches, such as generic meal plans or standard consultations with nutritionists, often fail to address the unique and evolving needs of individuals, especially those with specific health concerns. …
Published in International Journal of Nutritions · Vol. 2, Issue 2, 2025 Read article
-
Path and Trajectory Planning of Unmanned Ground Vehicles with Vehicle Dynamic Characters
Abstract: Given partial knowledge about its environment (obstacle, road…) and goal position, optimal path and trajectory planning is a key problem for the control of unmanned vehicles. In path planning problem, it is very important to consider the dynamic limits of the vehicle with optimization function. The path planning was implemented by applying optimization methods based on the given obstacle information(virtual or measured by sensor system) and numerical map without considering …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 7–14 Read article
-
Diet(Nutrition) Recommender using Machine Learning
Abstract: In an era where maintaining a healthy lifestyle has become a priority, personalized dietary recommendations play a crucial role in guiding individuals towards achieving their nutritional goals. The Diet Recommendation System is an inno- vative application that combines user-specific data with machine learning algorithms to provide tailored dietary suggestions. This system is designed to simplify the process of meal planning and promote healthier eating habits. The Diet Recommendation System is …
Published in International Journal of Nutritions · Vol. 2, Issue 2, 2025 Read article
-
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
-
Revolutionizing Petrology and Mineralogy: The Study of AI and Advanced Sensor Technologies
Abstract: Petrology and mineralogy are fundamental to understanding Earth's intricate processes, from crustal evolution to economic resource formation. However, traditional methods, while precise, are often laborious, time-consuming, and occasionally subject to interpretive bias. This abstract explores the transformative potential of integrating cutting-edge Artificial Intelligence (AI) and advanced sensor technologies to revolutionize data acquisition, analysis, and interpretation in these critical geosciences. Advanced sensor technologies, including high-resolution spectral imaging (hyperspectral, Raman), automated X-ray …
Published in International Journal of Minerals · Vol. 2, Issue 2, 2025 · pp. 1–11 Read article
-
A Study on Leveraging Sensors and AI in Insect-Inspired Robotics for Unstructured Environments: Bio-Inspired Autonomy
Abstract: Insects, with their unparalleled agility, resilience, and highly efficient sensory-motor control in complex, unstructured environments, offer a rich blueprint for the next generation of autonomous robots. This study explores the design, implementation, and potential of insect-inspired robots, focusing on the synergistic integration of miniaturized sensor arrays and advanced Artificial Intelligence (AI) algorithms. We delve into bio-mimetic sensing, drawing inspiration from compound eyes, olfactory systems, and tactile hairs, to equip robots …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 7–21 Read article
-
Evaluating AI-Driven Adaptive Learning Models in Mathematics: A Contemporary Perspective
Abstract: Artificial Intelligence (AI) continues to transform mathematics education through data-driven personalization and adaptive learning technologies. This study investigates how AI-enabled adaptive platforms influence student performance and engagement in mathematics classrooms. Using a quantitative approach across two institutions, pre- and post-assessment results were compared between students using AI-assisted adaptive learning tools and those receiving conventional instruction. The findings reveal that AI-driven learners demonstrated significantly higher gains in conceptual understanding and engagement …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 8–12 Read article
-
An Analytical Review of Machine Learning Methodologies
Abstract: Machine Learning (ML) is a dynamic and rapidly developing area of computer science that enables the system to learn from data and improve its performance without clear programs. Rooted in statistical theory and computer algorithms, ML has become a major technology that progresses in artificial intelligence. It strengthens the detection of the recommendations and speech for extensive applications from autonomous vehicles and medical diagnoses. This paper has reviewed the basics …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 13–21 Read article
-
Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
-
Innovative Approaches to Fake Product Detection: Blockchain and QR Code Synergy
Abstract: For consumers, corporations, and regulatory agencies, the worldwide market's rise of counterfeit goods presents serious issues. Maintaining consumer confidence, guaranteeing product safety, and preserving brand reputation all depend on the ability to identify counterfeit goods. An overview of the different approaches and difficulties associated with spotting counterfeit goods is given in this abstract. First off, the ability to identify sophisticated counterfeit goods is limited by the use of conventional techniques …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 21–27 Read article
-
The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments
Abstract: The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 9–24 Read article
-
Striking A Balance: Ethical Guidelines for A.I. Integration in Mental Health Services
Abstract: Introduction: Artificial Intelligence (AI) integration in mental health services presents opportunities and challenges. This study examines ethical considerations and proposes guidelines for responsible AI implementation in mental healthcare. The rapid advancement of AI technologies has sparked both excitement and concern within the mental health community, necessitating a thorough examination of their potential benefits and risks. By addressing these ethical considerations, this research aims to contribute to the development of a …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 1, 2025 · pp. 8–15 Read article
-
Data-driven Approaches to Mineral Resource Management Using AI: A Brief Review
Abstract: The role of Artificial Intelligence (AI) in the mineral resource sector has become increasingly significant over the past few years, as industries seek to optimize and modernize their operations. AI encompasses a variety of technologies and techniques, such as machine learning, deep learning, and expert systems, that are now widely used in mineral exploration, resource estimation, and mine management. These AI-driven approaches have brought about a transformative shift, enhancing efficiency, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 25–29 Read article
-
Atmospheric Remote Sensing: Bridging Technology and Environmental Challenges
Abstract: The rapid advancements in remote sensing technologies have revolutionized the field of atmospheric studies, offering unprecedented capabilities for detailed observation, analysis, and understanding of the Earth's atmosphere. These technological innovations have proven to be instrumental in tackling critical environmental challenges, providing scientists and researchers with the tools needed to monitor and analyze atmospheric phenomena with greater precision and depth.This article delves into the historical development, current state, and diverse applications …
Published in International Journal of Atmosphere · Vol. 2, Issue 1, 2025 · pp. 14–19 Read article
-
English Literature in the Digital Era: Transformations and Trends
Abstract: English literature context has been changed significantly with modernisation of the digital age that is creating a massive impact on creation, dissemination, and interpretation of literature. When one considers the relationship between literature and digital innovation, one may summarize these disruptive forces as both a challenge to and opportunity for literature — a hybridization of past forms. It explores how digital technologies have transformed reading practices, textual analysis, and the …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 27–32 Read article
-
Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article