Search
394 articles for “and Data Analytics”
-
A Pragmatic Analysis of Rapport Orientation in Selected Rehabilitated Schools in Syria
Abstract: Rapport orientations are not frequently explored in educational discourse, despite their significant role in enhancing or maintaining relationships between students and teachers, and in avoiding or mitigating embarrassing situations. This paper aims to investigate the rapport orientations of students and teachers based on Spencer-Oatey’s (2008) theory. A descriptive-analytical method was adopted to analyze and interpret the questionnaires from students and teachers in selected rehabilitated schools in Syria. The software MAXQDA …
Published in International Journal of Education Sciences · Vol. 2, Issue 1, 2025 · pp. 46–61 Read article
-
Analysis of Health Benefits Associated with Exclusive Breastfeeding Among Lactating Mothers in Maiduguri Metropolis, Borno State, Nigeria for Sustainable National Development
Abstract: Exclusive breastfeeding, which involves feeding an infant only breast milk for the first 6 months of life, offers numerous health benefits for both the baby and the breastfeeding mother. Despite the well-established advantages, global rates of exclusive breastfeeding remain lower than ideal, and this is also the case in Maiduguri Metropolis, Borno State, Nigeria. This study aims to explore the health benefits of exclusive breastfeeding for lactating mothers in Maiduguri …
Published in International Journal of Women's Health Nursing And Practices · Vol. 3, Issue 1, 2025 · pp. 1–8 Read article
-
Quantitative Approaches to Legal Decision-Making: The Mathematics of Justice
Abstract: The research paper examines the application of quantitative approaches to decision-making in legal systems, presenting the concept of "mathematical justice." As legal systems grow increasingly complex, the adoption of statistical and data-driven methods can provide valuable insights, offering clarity and consistency to judicial processes. By leveraging these methods, courts and policymakers can make more informed, evidence-based decisions, enhancing both fairness and accountability within the justice system. The paper is divided …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 27–31 Read article
-
The Symbiosis Between Spherical Refractive Error Cylindrical Refractive Error
Abstract: This study aimed to acknowledge the link between spherical refractive error and cylindrical refractive error, which is crucial for diagnosing and managing visual abnormalities productively. This research employed a multi-center, cross-sectional, analytical, and retrospective approach to investigate refractive errors. The objective results were refined subjectively to the best visual acuity with conventional clinical representations of refraction using the sphere, cylinder, and axis. The gathered data underwent analysis utilizing statistical software …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 1, 2024 · pp. 67–76 Read article
-
Photochemically Assisted LC–MS Method Development and Validation for Stability-Indicating Determination of Glasdegib in Rat Plasma
Abstract: A simple, precise, and cost-effective LC–MS method was successfully developed for the determination of Glasdegib in rat plasma. The method optimization was carried out by systematically varying key chromatographic parameters, including flow rate, injection volume, analyte concentration, and mobile phase composition, to achieve optimal sensitivity and resolution. A C18 Hypersil BDS column (150 mm × 4.6 mm, 3.5 µm particle size) was used for chromatographic separation, offering effective peak shape …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
-
A Web Application for Predicting Diabetes Using Machine Learning Methods
Abstract: Diabetes is a long-term disease caused by high glucose quantity in the blood. It has the potential to result in serious health complications like heart disease, hypertension, and ocular damage. It is good to identify any health issues as early as possible to get the right medical treatment and make necessary lifestyle adjustments. One makes use of machine learning techniques to predict diabetes and develop treatment options using actual cases. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 92–102 Read article
-
IoT Integration in Sustainable Agriculture
Abstract: The increasing demand for food production, environmental concerns, and resource limitations have necessitated the adoption of Internet of Things (IoT)-based innovative farming solutions. The current paper introduces an IoT-based system that integrates hydroponics, aquaponics, and poultry to promote sustainability, resource utilization, and agricultural productivity. Conventional farming practices are riddled with ineffective use of resources, uncertain environmental effects, and expensive operations. The new system facilitates real-time monitoring, automated decision support, and …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 69–84 Read article
-
Fundamental Principles of Fluid Behavior and Emerging Trends in Modern Fluid Mechanics Research
Abstract: Fluid behavior forms the foundation of numerous engineering technology and scientific applications, including aerospace flows, energy systems, and environmental processes. This paper presents a comprehensive overview of the fundamental principles governing fluid behavior, with a strong emphasis on their relevance to recent trends in fluid mechanic’s research. Core concepts such as fluid statics, fluid dynamics, and conservation laws are discussed to establish a solid theoretical framework. The study further examines …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 14–21 Read article
-
ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
-
A Threshold-Weighted Mathematical Fusion Model for Epidemic Outbreak Prediction Using SEIR Residual Dynamics and Cloud-Based Machine Learning
Abstract: Accurate prediction of epidemic outbreaks is critical for effective public health management, resource planning, early warning generation, and timely intervention by municipal authorities. Traditional compartmental models such as Susceptible–Exposed–Infectious–Recovered (SEIR) offer valuable epidemiological insights and mathematical interpretability; however, they may not adequately capture the complex nonlinear relationships present in real-world urban health systems. Conversely, data-driven machine learning techniques can identify hidden patterns in large datasets but often lack epidemiological structure …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 2, 2026 · pp. 12–19 Read article
-
Hyper Personalization Using AI: Elevate Fitness
Abstract: In the modern era, many individuals find it challenging to prioritize their health and well-being due to busy lifestyles filled with work, academic, and personal obligations. Conventional fitness and nutrition programs often apply uniform strategies that overlook individual differences in body type, preferences, and goals. This lack of real-time feedback and contextual customization often leads to poor user engagement and unsatisfactory results over time. Elevate is a comprehensive, AI-powered fitness …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 10–21 Read article
-
Diabetes Risk & Al Nutrition Assistant
Abstract: The rising prevalence of diabetes mellitus has emerged as a major global health challenge. Early identification of individuals at risk, combined with personalized lifestyle-based interventions, can significantly reduce future complications. This study presents an AI-driven Nutrition Assistant integrated with a Diabetes Risk Prediction model. The system uses a machine learning classification approach to estimate the likelihood of diabetes based on clinical and nutritional factors, including body mass index, glucose levels, …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 1, 2026 · pp. 31–38 Read article
-
ArcGIS Applications in COVID-19 Spatial Epidemiology: A Comprehensive Systematic Review
Abstract: Addressing complicated community health concerns frequently necessitates the establishment of health practices. Professionals who study community health using information technology require a thorough framework. Health care professionals and authorities have had the ability to comprehend health-related geographical data and make timely judgments in different situations. In the field of epidemic disease prevention, including a viral spread model into a GIS is a popular issue. As a result, a GIS as …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 17–25 Read article
-
Intelligent Farming: Integrating AI and IoT for Sustainable Agriculture
Abstract: Artificial Intelligence (AI) and the Internet of Things (IoT) are transforming modern agriculture by enabling data-driven, resource-efficient, and climate-resilient farming practices. This review critically examines recent advances in AI-IoT integration across crop production, irrigation management, pest and disease surveillance, and supply chain optimization through an analysis of published literature and documented case studies. The review indicates that AI-assisted predictive analytics combined with IoT-based real-time sensing significantly improves decision-making in precision …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 Read article
-
Enhancing Remote Patient Monitoring with Ai-Powered Virtual Assistants
Abstract: Artificial Intelligence (AI) is transforming personalized education by tailoring learning materials to meet the distinct needs, preferences, and progress of individual students. This paper explores how AI technologies—such as machine learning, natural language processing, and adaptive learning systems are improving the effectiveness of personalized learning experiences. Through AI, students benefit from timely feedback, access to intelligent tutoring systems, and data-driven insights that enable educators to enhance their teaching strategies. Additionally, …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
-
Smart City Solutions for Waste Management and Pollution Control
Abstract: Recent trends in the role of artificial intelligence, IoT, and other smart technologies have a critical role toward addressing urban environmental challenges related to air quality and waste management in the context of a smart city. This changes the scope of managing air quality as, with the integration of IoT sensors, big data, and AI, they are able to predict pollution levels through real time monitoring and analysis. These technologies …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
-
Leveraging Deep Learning and Cloud Computing for Water Usage Optimization in Agriculture: A Study
Abstract: Water scarcity and inefficient irrigation practices are significant challenges in modern agriculture. This research investigates how deep learning and cloud computing can be combined to enhance water efficiency in agricultural practices. Leveraging advancements in deep learning and cloud computing, researchers have developed innovative solutions for optimizing water usage. This review examines the state-of-the-art methodologies, technologies, and applications in smart irrigation systems. It explores how deep learning models and cloud platforms …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 83–91 Read article
-
Role of Beowulf Clusters in Next-Generation Military Applications: A Comprehensive Study
Abstract: Beowulf clusters, which utilize cost-effective commodity hardware combined with open-source software for parallel computing, have emerged as a viable and efficient solution for high-performance computing needs. This paper explores their growing relevance and practical applications in modern and future military technologies. Contemporary military operations increasingly rely on rapid data processing, real-time intelligence, high-fidelity simulations, and autonomous decision-making systems. Beowulf clusters offer scalable and adaptable computational power that supports these demands …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
-
Analytical Study on DNA-based Modern Cryptographic Techniques
Abstract: Today, as the amount of information being stored and shared continues to grow rapidly, ensuring the security of that information has become more important than ever.To ensure information security, a variety of techniques are employed, including traditional cryptographic methods such as substitution and transposition techniques, hashing functions, and encryption algorithms like DES, RSA, AES, IDEA, and ECC. DNA cryptography is also new emerging technique for providing security to data and …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
-
Comparative Study of Machine Learning Algorithms for Detection of Breast Cancer
Abstract: Breast cancer continues to be the most commonly diagnosed cancer among women, with more than 2.3 million new cases diagnosed yearly worldwide. It is stated as the leading cause of cancer-related deaths. Therefore, this emphasizes the dire necessity for early diagnosis with a view to improving survival. Early diagnosis elevates the effectiveness of prediction and treatment. This research carries out a structured and analytical evaluation of various machine learning algorithms, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 113–129 Read article