Search
168 articles for “Multi-Scale”
-
Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 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
-
Data Integration and Visualization in Bioinformatics: Techniques and Challenges
Abstract: Data integration and visualization play essential roles in bioinformatics, facilitating the thorough analysis, and interpretation of intricate biological datasets. In the field of bioinformatics, vast amounts of data are generated from various experimental platforms, such as genomic sequencing, proteomics, transcriptomics, and metabolomics. However, the heterogeneity of these datasets, coupled with their large scale and complexity, presents significant challenges in terms of integration, analysis, and visualization. Data integration techniques aim to …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
-
Cloud-based Application Development and Optimization
Abstract: As cloud computing powers today’s applications, optimizing cloud-based development is crucial to achieve performance, cost effectiveness, and scalability. This research focuses on enhancing the design, deployment, and maintenance of cloud applications, tackling challenges in resource management, scalability, and resilience. We specifically explore dynamic resource allocation algorithms that use predictive analytics for auto-scaling based on workload variations, aiming to cut costs while preserving high performance. The study also investigates cross-cloud optimization …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 37–42 Read article
-
A Comprehensive Review: Emerging Nanotechnology in Cancer Drug Delivery
Abstract: Nanotechnology has become a groundbreaking strategy in cancer therapy, especially in drug delivery systems, offering improved treatment effectiveness while minimizing the adverse effects associated with traditional methods. This review presents an in-depth analysis of recent progress in nanotechnology for cancer drug delivery, emphasizing the design, mechanisms, and practical applications of nanoparticle-based systems. Nanoparticles, such as liposomes, dendrimers, and gold nanoparticles, offer unique advantages, including improved drug solubility, targeted delivery to …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 1, 2025 · pp. 24–33 Read article
-
Optimized Machine Learning Framework for Battery State Prediction in Smart Charging Systems
Abstract: Good estimation of battery states, including State-of-Charge (SoC), State-of-Health (SoH), and Remaining Useful Life (RUL), are important in managing energy wisely and controlling the adaptive charging. This work introduces a streamlined machine learning model based on the ability to use multi-dimensional sensor measurements in terms of voltage, current, temperature, and cycle number to forecast battery conditions with high accuracy. Decent preprocessing, such as noise elimination, feature scaling, and calculated features, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 11–23 Read article
-
Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
-
Cardiovascular Illness Detection and Categorization with Innovative Neural Networks
Abstract: Health-related problems are increasingly prevalent in modern-day societies and are significantly shaped by a multitude of factors encountered in everyday life. Among these, cardiovascular diseases have emerged as one of the primary causes of death on a global scale, posing serious challenges to public health systems. In response to this growing concern, the present study proposes a machine learning-based framework that is not only highly effective but also reliable and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 21–30 Read article
-
Multi-Layered AI-Driven Paradigm Shift in IoT Ecosystem Security
Abstract: As the Internet of Things (IoT) continues to weave itself into the fabric of modern life – from smart homes and industrial automation to healthcare and urban infrastructure – the associated security vulnerabilities have become increasingly apparent. Traditional security mechanisms, often built on static rules and perimeter-based defenses, struggle to keep pace with the scale, heterogeneity, and dynamic nature of IoT ecosystems. In response, artificial intelligence (AI) has emerged as …
Published in Journal of Communication Engineering & Systems · Vol. 16, Issue 1, 2026 · pp. 13–21 Read article
-
Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures
Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and GPU-based architectures without centralizing sensitive data. This work proposes a parallel Adaptive Federated Learning (AFL) framework that integrates Differential Privacy and Secure Aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, and aggregation weights …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
-
Neuroinformatics and Its Impact on the Future of Brain-Computer Interface Technology
Abstract: Neuroinformatics, a multidisciplinary field combining neuroscience, information technology, and data science, plays a crucial role in advancing brain-computer interface (BCI) technology. By leveraging large-scale neural data, machine learning algorithms, and computational models, neuroinformatics enhances our understanding of brain function and improves the design and development of BCIs. The integration of neuroinformatics into BCI systems offers new possibilities for interpreting complex brain signals, facilitating real-time communication between the brain and external …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 9–18 Read article
-
Swarm-Enabled AI for Smart Mobility and Sustainable Transport
Abstract: The significant issues facing the modern urban infrastructure are the management of road traffic problems, such as severe traffic congestion, the detection of unsafe driving behavior, and road safety. The traditional ground-based surveillance systems will be helpful, but they will reach their limits in large and dynamic environments. It is because of predetermined perspectives, blindness, and the inability to scale. To designate these problems, the present study proposes a traffic …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 1, 2026 · pp. 33–38 Read article
-
An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
-
Approximation-Aware Computation for Graceful QoS Degradation in Modern Multiprocessor Operating Systems
Abstract: Modern multiprocessor operating systems face unprecedented challenges in maintaining Quality of Service (QoS) guarantees under dynamic workload conditions and resource constraints. Traditional approaches to resource management often result in abrupt service degradation or complete task failure when system resources become scarce. This study presents a comprehensive framework for approximation-aware computation that enables graceful QoS degradation in multiprocessor environments. We explore the integration of approximate computing paradigms with operating system schedulers, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article
-
Privacy-preserving Multi-keyword Search in Multi-owner Setting Using Blockchain
Abstract: Searchable encryption (SE) has become an essential cryptographic technique, allowing users to securely search through encrypted data. However, most existing SE schemes rely on a single intermediary, such as a cloud server, leading to potential single-point failures, privacy breaches, and untrustworthy results. Many blockchain-based SE schemes have been proposed to address these issues. However, they frequently encounter difficulties such as supporting a multi-keyword, multi-owner model, ensuring query privacy, and maintaining …
Published in Journal of Advances in Shell Programming · Vol. 11, Issue 2, 2024 · pp. 12–18 Read article
-
Exploring the Dynamics of Memristors: Mechanisms, Models, and Multifaceted Applications
Abstract: Memristors, a fundamental electronic component first proposed by Leon Chua in 1971, have garnered significant attention due to their unique electrical behavior and promising applications in various fields. This paper provides a comprehensive overview of memristors, covering their basic principles, characteristics, fabrication methods, and applications of Memristor and it’s significance with flux charge linkage. The paper also shows study of a grounded memristor emulator and it’s working as a memristor …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 1–7 Read article
-
Next-Generation Satellite Remote Sensing: Innovations, Applications, and Future Prospects
Abstract: Advances in satellite remote sensing have revolutionized our ability to monitor, analyze, and understand the Earth's environment across various scales. Over the past few decades, the field has seen remarkable progress in sensor technology, data processing techniques, and analytical methodologies. Modern satellites now provide high-resolution imagery and multi-spectral data, enabling enhanced monitoring of land cover, atmospheric conditions, oceanic dynamics, and natural disasters. These advancements have facilitated improvements in climate change …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 37–62 Read article
-
Bacteriophages- A New Frontier in Medicine
Abstract: Bacteriophages, or phages, are viruses that specifically target and infect bacteria, offering an innovative alternative to traditional antibiotic treatments, especially in the face of rising antibiotic resistance. The resurgence of phage therapy has been driven by the increasing prevalence of multidrug-resistant bacterial strains and the slowdown in the development of new antibiotics. Phages, unlike antibiotics, target specific bacterial strains, reducing the impact on the natural microbiota and potentially offering a …
Published in International Journal of Virus Studies · Vol. 1, Issue 2, 2024 · pp. 31–35 Read article
-
Investigation of Robotic Transverse Twin-Wire GMAW for Large-Scale Wire-Arc Additive Manufacturing Applications
Abstract: Bulk metal additive manufacturing using wire-arc processes has gained significant attention for fabricating large-scale engineering components due to their high deposition rate and material efficiency. In this study, the feasibility and performance of robotic transverse twin-wire gas metal arc welding (GMAW) for bulk wire-arc additive manufacturing (WAAM) is systematically assessed. The research focuses on understanding arc stability, weld bead characteristics, and process–product relationships under high-deposition conditions. Welding current signals from …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 4, Issue 1, 2026 · pp. 36–50 Read article
-
A Study on Clinical Evaluation of Multi Intervention Therapy for Enhancing Quality of Life in Maintenance Hemodialysis Patients
Abstract: Patients with Chronic Kidney Disease (CKD) receiving maintenance hemodialysis often report a markedly impaired health-related quality of life, largely resulting from factors such as psychological distress, chronic inflammation, and poor nutritional status. Despite its importance as a clinical outcome, HRQOL assessment in dialysis patients has received limited attention. Strengthening comprehensive patient care and optimizing treatment strategies may help reduce complications and promote improved physical, mental, and social well-being. The present …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 15, Issue 3, 2025 · pp. 69–81 Read article