Search
110 articles for “Public model”
-
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
-
Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
-
Rethinking Consumer Preferences for Broiler Meat: Addressing Public Concerns for Sustainable Development
Abstract: Broiler meat is a crucial component of global protein consumption, yet its acceptance is often hindered by concerns related to health, animal welfare, environmental sustainability, and consumer perception. This study examines the factors influencing consumer preferences for broiler meat and explores strategies to address public concerns while promoting sustainable development. Misinformation regarding antibiotic residues, growth promoters, and broiler welfare has contributed to negative consumer sentiment, leading to a preference for …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
-
Funding Water and Sanitation Initiatives to Foster Economic Growth and Sustainable Development: A Case Study of Lagos State
Abstract: Sufficient funding, effective sanitation strategies, and the deployment of relevant technologies are essential for fostering economic growth, protecting public health, and promoting sustainable development. This study explores the crucial financing mechanisms needed to achieve sustainable water and sanitation goals, considering the diverse community needs, infrastructure complexities, and environmental responsibilities. It examines the challenges and opportunities in financing water and sanitation initiatives, emphasizing the importance of increased investments, improved governance, and …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 1, 2024 · pp. 1–17 Read article
-
Transforming Digital Health Card Healthcare in India: An Integrated IT Solution
Abstract: India's healthcare sector faces critical challenges, including fragmented medical records, limited access to quality care in rural areas, and inefficiencies in patient engagement and insurance processes. This study proposes an innovative IT-driven healthcare model integrating a digital health card, web application, and NFC-enabled mobile platform. The system aims to streamline medical record management, enable telemedicine consultations, and provide seamless prescription and insurance integration. Advanced digital capabilities ranging from AI-driven recommendations …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 11–15 Read article
-
Adversarial Attacks on Machine Learning Models in Cybersecurity: A Systematic Literature Review
Abstract: Adversarial machine learning (AML) is a field that is growing swiftly, especially as machine learning models are employed more and more in places where security is critical. This review goes into great depth over 746 publications from the Scopus database, with an emphasis on the connection between AML and network security. Using Biblioshiny and Scopus tools, we looked at trends in publications, study fields, productive authors, collaboration networks, and theme …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 23–38 Read article
-
Artificial Intelligence and IoT Integration for Real-Time Violence Monitoring
Abstract: The peace and tranquility of any place can be affected greatly by the insurgence of violence and violent attacks that are perpetrated by individuals with malicious and nefarious intentions. These individuals terrorize the areas and can cause a lot of harm and damage to people and public property. The incidences of violence are undesirable and can be problematic to handle by the law enforcement agencies, as these acts are committed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 39–45 Read article
-
Secure Forge: Deepfake Image Detection Using Vision Transformers
Abstract: Deepfake technologies have become a major risk to the credibility and trustworthiness of digital visual information. Using powerful generative models like GANs and autoencoders, deepfakes can generate highly realistic fake videos and images, resulting in misinformation, identity theft, and public loss of trust in digital media. Classic Convolutional Neural Networks (CNNs) while being highly effective in initial-stage, deepfake detection tend to be limited by their local receptive fields and dependency …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 32–45 Read article
-
Quality Dimensions of Open Access E-Journals in Library and Information Science: An Analytical Study
Abstract: The rapid growth of open access e-journals in Library and Information Science marks a significant transformation today. Open access journals provide unrestricted access to peer-reviewed research, enabling LIS professionals, researchers, and students worldwide to access required knowledge without subscription barriers. This study focuses on evaluating open access (OA) e-journals in Library and Information Science (LIS), with particular attention to their accessibility, quality, and scholarly impact. The main objectives of the …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 52–68 Read article
-
An Analysis of Open-Access E-Journals in Library and Information Science
Abstract: The growth of open-access e-journals in the field of Library and Information Science represents a transformative shift today. Open-access journals provide unrestricted access to peer-reviewed research, enabling Library and Information Science (LIS) professionals, researchers, and students worldwide to access required knowledge without subscription barriers. This study evaluates open-access (OA) e-journals in the field of LIS, assessing their accessibility, quality, and impact. Objectives: The main objectives of the study are to …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 39–56 Read article
-
Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article
-
Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
-
Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains
Abstract: This comparative analysis investigates the ethical challenges associated with natural language processing (NLP) by reviewing and synthesizing insights from ten influential and widely cited publications in the field. As NLP technologies are increasingly integrated into domains such as healthcare, finance, education, and governance, ethical concerns related to algorithmic bias, data privacy, fairness, accountability, and system transparency have become more prominent. This paper systematically examines how different researchers conceptualize and address …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article
-
Comparative Analysis of Personal Rapid Transit System with Thermoplastic Material for Interconnecting Metro Station with Airport
Abstract: Personal rapid transit (PRT) systems open a slew of new possibilities for solving airport-related transportation issues, both on the ground and in the air. For use in airport applications, the advantages and disadvantages of this mode of transportation are contrasted. An implementation of the ULTra Personal Rapid Transit system to assist passenger and staff vehicle squares at Heathrow is used to showcase the work. The ULTra infrastructure's compact size and …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 97–108 Read article
-
Vaccines Through Time: Conventional Foundations and Next-Gen Innovations–Part 1
Abstract: Vaccination serves as a critical pillar of global public health, markedly decreasing infection rates and associated mortality. Traditional vaccine platforms such as live attenuated, inactivated, toxoid, and subunit vaccines have demonstrated effectiveness against pathogens like Mycobacterium tuberculosis and Plasmodium spp., yet they are constrained by antigenic variability, limited immune persistence, and complex production processes. Breakthroughs in synthetic biology, structural antigen design, and computational vaccinology have driven the development of advanced …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 1, 2026 · pp. 53–70 Read article
-
Integrating Biotechnology, Physiology, and Agroecological Practices for Sustainable Crop Production and Protection
Abstract: Global agriculture is currently confronting a wide range of complex challenges, including a rapidly growing population, climate change, increasing pest and disease pressures, soil degradation, water scarcity, and the urgent need for sustainable intensification of crop production. Addressing these issues requires integrated strategies that combine crop improvement (through modern breeding and biotechnology), precision agronomic practices related to soil, irrigation, and nutrition, as well as advancements in plant physiology, molecular biology, …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
-
Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems. Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
-
A Study on “Clean" in Beauty: A Machine LearningApproach to Ingredient Transparency and ConsumerTrust
Abstract: The burgeoning "clean beauty" market, while driven by consumer demand for safer and more sustainable products, is plagued by ambiguous definitions and the pervasive challenge of "greenwashing". This ambiguity hinders informed consumer choices and complicates brand authenticity. This study addresses these complexities by developing a novel machine learning (ML) framework designed to objectively analyze cosmetic ingredient lists, classify products based on their "cleanliness" profile, and identify key ingredient attributes that …
Published in Recent Trends in Cosmetics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
-
The Tapper Approach: An Integrated Framework for Land Degradation, Restoration, and Climate-Conflict Dynamics
Abstract: Land systems across the globe are increasingly exposed to multiple and interacting pressures, including land degradation, climate change, biodiversity loss, unsustainable land-use practices, rapid population growth, and socio-economic conflicts. These challenges not only reduce ecosystem productivity and resilience but also threaten food security, water availability, rural livelihoods, and long-term environmental sustainability. Despite the growing recognition of these interconnected issues, most existing conceptual and analytical frameworks continue to address them in …
Published in Research & Reviews : Journal of Ecology · Vol. 15, Issue 2, 2026 Read article
-
Leveraging AI and Machine Learning for Early Prediction and Prevention of Non- Communicable Diseases in Resource-Limited Settings
Abstract: Populations in these regions face persistent structural barriers, such as underdeveloped healthcare infrastructure, shortages of trained health professionals, and fragmented or incomplete health information systems. These limitations delay timely diagnosis, restrict access to preventive care, and compromise effective disease management. In recent years, rapid progress in artificial intelligence (AI) and machine learning (ML) has opened promising avenues to mitigate these challenges. Practical applications already emerging include mobile health platforms for …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 9–15 Read article