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99 articles for “Deep Generative Models”
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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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
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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
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The Role of Optimization and Probability in Shaping Artificial Intelligence
Abstract: This study discusses the basic roles of optimization algorithms and the theory of probability in the process of evolution and development of Artificial intelligence (AI). First, we introduce the role played by the next generation of leading-edge optimization algorithms developed since gradient descent to evolutionary strategies with respect to the learning of high-level AI models and how to enable them to learn to effectively explore high-dimensional parameter spaces. At the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 123–128 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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Geo AI-Powered Urban Footprints
Abstract: In the contemporary era, building footprints are of paramount importance for accurate and current inventories in the development of infrastructure and geospatial analysis. Traditional methods, relying on manual digitization, were largely unsustainable as the urban regions were growing rapidly. Manual digitization was expensive and lacked geometric precision. This paper introduces an automated, end-to-end GEO AI-powered framework for high-end fidelity building footprint extraction from Google Satellite Data. Our approach for this …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Unravelling Modern News Classification Methods: A Systematic Review
Abstract: Nowadays, the news is being generated each second from every corner of the world, with millions of news articles generated every day. Some assume that at least 1.8 million articles are published yearly, in about 28,000 journals. It has become difficult to recognize what's fake and what's genuine due to the overflow of millions of articles every day. Not every person reads every news, so the classification of news according …
Published in Journal of Computer Technology & Applications Read article
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Comprehensive Study of Least Squares Estimation in Fast Fading MIMO-OFDM Systems
Abstract: MIMO-OFDM technology is now the foundation for modern wireless communication systems, allowing dramatic improvements in spectral efficiency, power efficiency, and transmission rate. On the other hand, the least accurate channel estimation is still a critical task, especially when they are in fast-fading environments. This study gives a comprehensive survey of LSE-based approaches and their applications on different fast-fading channel models for MIMO-OFDM systems. Techniques like Pilot Assisted Channel Estimation (PACE), …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 13–21 Read article
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Modeling and Simulation of Radiative MHD Casson-Type Polymer Composite Flow over a Porous Wedge with Variable Thermal Source and Sink
Abstract: This study presents a numerical investigation of the radiative magnetohydrodynamic (MHD) flow and heat transfer characteristics of a Casson-type polymer fluid over a moving and extending porous wedge under the influence of a spatially varying heat source and sink. The Casson fluid model, representing a class of viscoplastic polymeric materials, is analyzed within the MHD framework to explore the combined effects of magnetic field intensity, rheological behavior, and porous medium …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 837–850 Read article
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The Integration of Machine Learning in VLSI IC Design
Abstract: It represents the first use of AI in the domain of integrating circuits, which has been impacted by it. The conventional VLSI design process that is now in use is replaced by this technology. The laborious manual concepts created by people have been replaced with automated design innovations. This development would trigger a profound change in the fields of AI education and hardware computation. With the introduction of contemporary chips, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Cancer as one of the major diseases rank in the World is still very challenging to diagnose and treat hence need for the technological advancements. Chemotherapy, radiation, as well as surgery therapies have several drawbacks including non-selective action, damage to healthy tissues, and multi-drug resistance. Smart nano-theranostics, an advanced integration of nanotechnology with diagnostic and therapeutic modalities, offers a next-generation approach for precision oncology. Thus, the development of multifunctional nanoparticles …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Reimagining Plastic Waste: The Impact of Eco-Bricking on Student Engagement and Community Sustainability
Abstract: Plastic pollution poses a severe threat to the environment, impacting ecosystems, wildlife, and human health. With millions of tons of plastic waste generated globally each year, innovative solutions for waste management are essential. This paper explores the eco-bricking initiative at Sovanagar High School, which transforms plastic waste into eco-bricks—sustainable building materials used for constructing green walls, benches, and other structures on the school campus. By effectively reducing plastic waste, this …
Published in International Journal of Atmosphere · Vol. 1, Issue 1, 2024 · pp. 23–25 Read article
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Revolutionizing Motorcycle Safety: A Deep Learning Approach for Helmet and Triple Riding Detection using Computer Vision Technology and Machine Learning Model
Abstract: Introducing a revolutionary paradigm in road safety, our project unveils the Intelligent Traffic Surveillance System (ITSS), a groundbreaking initiative poised to transform urban traffic management. In an era where road safety is paramount, ITSS emerges as a beacon of innovation, harnessing the prowess of computer vision and machine learning to tackle two of the most pressing concerns plaguing our roads: helmet non-compliance and triple riding among motorcyclists. At its core, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 28–36 Read article
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Recent Trends in Fluid Mechanics with Emphasis on Aeroacoustics and Flow-Induced Noise Control
Abstract: Fluid mechanics continues to evolve rapidly due to increasing demands in aerospace, automotive, energy, and environmental engineering applications. Recent trends in this field highlight significant advancements in both theoretical understanding and practical implementations, particularly in complex flow phenomena. Among these, aeroacoustics and flow-induced noise control have emerged as critical research areas due to their direct impact on system performance, efficiency, and environmental sustainability. Aeroacoustics deals with the generation, propagation, and …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 32–38 Read article
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The Role of Artificial Intelligence in Automating Incident Response in Cloud-Based Cybersecurity
Abstract: As cloud computing continues to gain traction across industries, the complexity and scale of cloud environments present significant challenges to traditional cybersecurity practices. The dynamic and distributed nature of cloud infrastructures necessitates agile and effective incident response mechanisms to detect, analyze, and mitigate threats in real-time. However, conventional incident response methods often fall short due to the growing sophistication of cyber threats and the vast amounts of data generated in …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 15–24 Read article
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Exploring AI-Driven Student Performance Analysis as a Dimension of an AI-Powered Assessment and Feedback System: A Comprehensive Review
Abstract: The rapid proliferation of artificial intelligence (AI) in educational technology has heralded a paradigmatic transformation in assessment methodologies, transitioning from static, summative evaluations to dynamic, data-driven systems that emphasize continuous formative feedback. This comprehensive review interrogates AI-driven student performance analysis as a cardinal dimension of AI-powered assessment and feedback systems (AI-PAFS), synthesizing findings from forty-five rigorously curated open-access empirical studies published between 2015 and 2024. Employing a methodological lens, the …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 24–31 Read article
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Integrated Frameworks for Artifical Intelligence in Radioactive Waste Characterization and Nuclear Lifecycle Safety
Abstract: The management and characterization of radioactive waste represent a pivotal challenge for the global energy sector, requiring the convergence of advanced physics, material science, and computational intelligence. As the nuclear industry undergoes a paradigm shift toward decommissioning legacy facilities and establishing deep geological repositories, the limitations of traditional, manually-intensive waste management processes have become increasingly apparent. Rigid separation from the biosphere is required for radioactive waste, which is defined by …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 2, 2026 Read article