Search
368 articles for “Transformer models”
-
Microalgae Based Wastewater Treatment: A Sustainable Approach
Abstract: The global water crisis and strict environmental policies demand advanced wastewater treatment techniques that combine pollution control with resource recovery. Microalgae-based wastewater treatment has emerged as a sustainable biotechnological solution that aligns with circular economy principles by simultaneously eliminating contaminants and producing valuable biomass that can be converted into useful products. This review paper provides an in- depth assessment of the application of microalgae in treating municipal, industrial, and agricultural …
Published in International Journal of Sustainability · Vol. 3, Issue 2, 2026 · pp. 1–15 Read article
-
Enhancing Sustainability in Building Design: Optimizing Energy Efficiency and Reducing Carbon Footprint Using BIM Tools and Polymer Matrix Composites
Abstract: Sustainable construction is an imperative that transcends the immediate and future horizons of the construction industry, propelled by the escalating recognition of the sector's ecological impact. Building Information Modelling (BIM) has firmly established itself as a pivotal instrument within the industry due to its unique capacity to seamlessly merge the physical and analytical dimensions of construction, thereby ushering in transformative practices. This research paper offers an all-encompassing exploration of the …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 181–189 Read article
-
AI in Mental Health: New Developments and Prospects
Abstract: Artificial intelligence (AI) has revolutionised numerous industries, including the mental health care sector.In order to clarify present trends, ethical issues, and future prospects in this ever-evolving subject, this paper examines the integration of AI into mental healthcare. Recent research, AI application examples, and ethical issues influencing the area were all included in this study. Research and development trends and regulatory frameworks were also examined.With applications including the early detection of …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 Read article
-
Developing Design Sense in First-Year Architecture Students: A Pedagogical Approach to Basic Design
Abstract: This study explores the pedagogical significance of Basic Design Studios in shaping the foundational competencies of first-year architecture students. Serving as the foundation of architectural education, these studios cultivate essential skills in spatial awareness, creative thinking, and problem-solving. The research underscores how structured studio exercises, material explorations, and conceptual modeling collectively nurture an understanding of the interrelationship between space, form, and function. By emphasizing experiential and hands-on learning, students are …
Published in International Journal of Architectural Design and Planning · Vol. 4, Issue 1, 2026 · pp. 1–6 Read article
-
Designing an AI-Based Platform for Stock Market Prediction
Abstract: The AI-Based Platform for Stock Market Prediction is an advanced tool designed to forecast stock prices and market trends using artificial intelligence. This platform combines machine learning algorithms, real-time financial data, and sentiment analysis to provide investors with actionable insights. The platform uses advanced predictive techniques like Long Short-Term Memory (LSTM) networks and Gradient Boosting Machines to generate precise and reliable forecasts. Additionally, it incorporates interactive visualizations and portfolio optimization …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 3, 2025 · pp. 14–19 Read article
-
Analyzing Barriers to Digital Procurement in Polymer Composites Supply Chain Using ISM for Sustainable Transformation
Abstract: The adoption of e-procurement in the polymer and composites industry presents a transformative opportunity to enhance supply chain efficiency, reduce material waste, and support sustainable engineering practices. However, industries face significant barriers in transitioning from traditional procurement to digital systems, particularly in sourcing specialized materials such as epoxy resins, bio-based polymers, and hybrid composites. This study employs Interpretive Structural Modeling (ISM) to identify, analyze, and prioritize eleven critical barriers affecting …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 512–521 Read article
-
Significant Advances in Cloud Computing in Information and Communications Technology
Abstract: The critical advances in information and communications technology (ICT) over the last half-century have led to the increasingly common vision that computing will one day become the 5th utility. This computing utility will provide the essential level of computing service considered basic to meet the everyday needs of the general public. To convey this vision, a number of computing models have been proposed, with the most recent being cloud computing. …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 33–38 Read article
-
Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article
-
Explainable Sentiment Mining Model in Mental Health Forums for Emotion Classification and Justification
Abstract: Understanding and interpreting emotions expressed in online mental health discussions plays a crucial role in enabling early detection of psychological distress and facilitating timely interventions. As individuals increasingly turn to digital platforms to share personal experiences and seek support, automated systems capable of accurately identifying emotional states can significantly assist clinicians, moderators, and support communities. This paper presents a deep learning–based sentiment mining and emotion classification framework specifically designed to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 22–32 Read article
-
E-Empire: Brake & Acceleration In E-Cycle
Abstract: As e-cycles continue to gain momentum as an eco-friendly and efficient mode of transportation, understanding their key mechanical and electronic systems becomes even more vital. The report delves deeply into the nuances of braking mechanisms and acceleration technologies, emphasizing their roles in enhancing both safety and performance. By comparing mechanical disc brakes with hydraulic systems, it highlights the distinct advantages of each. For instance, hydraulic brakes, known for their superior …
Published in Journal of Automobile Engineering and Applications · Vol. 11, Issue 3, 2024 Read article
-
Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
-
Real-time DDoS Attack Prediction in SDN Environments Using Machine Learning
Abstract: The ever-growing reliance on sdn-based services necessitates robust security measures against Distributed Denial-of-Service (DDoS) attacks that threaten service availability. This project investigates the development of a real-time prediction system for DDoS attacks in sdn environments, leveraging the power of machine learning. The proposed system employs a Decision Tree classification algorithm implemented in Python. To ensure accurate attack identification, the system meticulously addresses data preprocessing challenges inherent in network traffic datasets. …
Published in Journal Of Network security · Vol. 13, Issue 1, 2025 · pp. 16–27 Read article
-
Genetic Variability and Statistical Methods: Key Insights for Computational Genetics Research
Abstract: Genetic variability, defined as the differences in DNA sequences among individuals, serves as the foundation of evolutionary biology and plays a pivotal role in species’ adaptability, resilience, and overall survival. Advances in genomic technologies, particularly high-throughput sequencing, have enabled unprecedented exploration of genetic diversity, fostering the growth of computational genetics. This interdisciplinary field combines statistical methods and computational tools to analyze genetic data, identify patterns, and link phenotypes to genotypes. …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 19–23 Read article
-
Renewable Solar Energy Prediction in India : 2025-2030
Abstract: As India endeavors to realize its objective of achieving 500 GW of renewable energy capacity by the year 2030, the precise forecasting of solar power generation is rendered increasingly essential. This scholarly article conducts a comprehensive review of the utilization of machine learning (ML) methodologies in the prediction of solar energy across diverse Indian states, underscoring their potential to address the complexities associated with the variability of solar irradiance. Conventional …
Published in Journal of Power Electronics and Power Systems · Vol. 14, Issue 3, 2024 · pp. 41–46 Read article
-
Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
-
Impact of Partially Observable Markov Decision Process in Next Generation Satellite for Remote Sensing
Abstract: The integration of Partially Observable Markov Decision Processes (POMDPs) in next- generation satellite systems represents a transformative advancement in remote sensing technology. This article explores how POMDP frameworks address the inherent uncertainties and incomplete observability challenges in satellite operations, including dynamic task scheduling, resource allocation, and adaptive sensing strategies. By modeling satellite decision-making under uncertainty, POMDPs enable autonomous systems to optimize mission objectives while managing constraints such as limited power, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 20–28 Read article
-
From Rural to Urban: Understanding Taobao Villages to Redress Planetary Urbanisation
Abstract: This study examines Taobao Villages as an innovative model of urbanisation under China’s planetary urbanisation framework. These rural communities, driven by the rise of e-commerce and digital infrastructure, have successfully integrated into the broader urban ecosystem by reconfiguring their historical socio-spatial legacies. Through Lefebvre’s spatial triad framework, the research identifies three key historical legacies that underpin this transformation: (1) Collective Production Practices: Rooted in socialist collectivisation, these legacies include organisational …
Published in International Journal of Urban Design and Development · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
-
Future-proofing the Mind: Fostering Robust Innovation in Soft Computing and Computational Intelligence
Abstract: This study examines the impact of Computer Science (CS) and Soft Computing (SC) on a few scholarly disciplines and way of life. The study considers points to improve calculation execution by utilizing computational intelligence (CI) techniques, progressing the steadiness of statistical classification (SC) models, and optimizing them through algorithmic upgrades. These adjustments encourage the method of altering, selecting, and creating oneself, indeed in challenging circumstances. The effect on work, protection, …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 1–6 Read article
-
A Study on AI-Driven Multi-Layered Defense in 6G Ecosystems
Abstract: The 6G networks bring about new degrees of possible functions related to connectivity, latency, data throughput, and integration with artificial intelligence (AI). This enables advances within healthcare, autonomous systems, and smart cities. The positive impact of rapid advancements must also be balanced with heightened risks due to the sheer volume of gaps that can be exploited, and the complex nature of the alignments and breaches. This results in the breaches …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
-
Enhancing Robot Autonomy: Integrating AI for Advanced Decision-making in Autonomous Robotic Systems
Abstract: The capabilities of autonomous robotic systems have been drastically changed by the rapid progress in artificial intelligence (AI) technologies. In this work, we investigate the integration of AI approaches to improve robot autonomy by presenting even more advanced mechanisms for decision-making. Almost all traditional robotic systems involve predefined algorithms, making them unable to cope with dynamic environments. They can also help with learning based on machine learning and deep learning …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 28–37 Read article