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53 articles for “heterogeneous architecture”
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Framework-Based Optimization of Catalysis Efficiency through Reaction Pathway Engineering
Abstract: The rational design of heterogeneous catalysts through framework-based approaches has emerged as a transformative strategy for controlling reaction pathways and enhancing catalytic efficiency. This paper examines recent advances in the optimization of catalytic performance through engineered frameworks, including metal-organic frameworks (MOFs), zeolites, and related porous materials. By integrating computational methods with experimental validation, researchers have achieved unprecedented control overactive site architecture, reactant confinement, and elementary reaction steps. This work reviews …
Published in Emerging Trends in Chemical Engineering · Vol. 13, Issue 2, 2026 · pp. 88–99 Read article
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Internet of Things Data Semantics
Abstract: AbstractInternet of Things (IoT) is the latest phenomenon and this revolution in technology may exceed the industrial revolution. Merging internet and things, making them work together, we have developed a powerful technology, called The Internet of Things (IoT). Apart from smart phones and computers, today we have many other devices which are able to communicate through internet like door opener, automated sprinklers, automatic water quality sensors, ATM machines, robotic cars …
Published in Journal of Web Engineering & Technology · Vol. 4, Issue 2, 2017 · pp. 15–21 Read article
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Federated Learning for Energy Management in Next Generation Smart Cities
Abstract: Federated learning has emerged as a promising approach for addressing the challenges of energy management in next-generation smart cities. This decentralized approach to machine learning allows collaborative model training among distributed data sources, while safeguarding data privacy and security. In this study, we explore the application of federated learning techniques to optimize energy consumption, enhance grid stability, and promote sustainability in smart city environments. By aggregating data from diverse sources …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 1, 2024 · pp. 19–27 Read article
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Deep Learning for Earth Observation Using Satellite Imagery: A Comprehensive Review
Abstract: Earth observation (EO) satellites provide continuous, large-scale information about the Earth's land, oceans, atmosphere, vegetation, infrastructure, and environmental conditions. The rapid growth of multispectral, hyperspectral, synthetic aperture radar (SAR), thermal, and high- resolution satellite missions has generated large volumes of heterogeneous spatial and temporal data. Conventional image-processing and machine-learning techniques often require manually designed features and may have difficulty representing the complex spatial, spectral, temporal, and multimodal characteristics of satellite …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Comprehensive Analysis of Modern IoT Security Challenges and Solutions
Abstract: The Internet of Things (IoT) is rapidly transforming various industries by enhancing the human quality of life (QoL) through its wide-ranging applications. From healthcare to automotive, agriculture, education, and numerous other sectors, IoT has become essential for enabling smarter, more efficient systems. However, with its heterogeneous nature, IoT introduces a multitude of security challenges, as different IoT applications often function under varying frameworks and protocols. Consequently, addressing and studying IoT …
Published in Journal Of Network security · Vol. 12, Issue 3, 2024 · pp. 34–39 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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An Overview of Intelligent Operating Systems (iOS)
Abstract: The rapid convergence of artificial-intelligence techniques with core operating system services is ushering in a new class of platforms—intelligent operating systems (iOS)—that can anticipate, adapt, and optimize on behalf of both applications and users. This paper surveys the architectural shifts required to embed learning, reasoning, and self-healing capabilities into the kernel, scheduler, memory manager, and I/O subsystems. We present a prototype framework, NeuroKernel, that augments traditional OS primitives with three …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 · pp. 21–28 Read article
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Machine Learning-Based Task Scheduling and Resource Optimization in Edge-IoT Systems
Abstract: The rapid expansion of Internet of Things (IoT) applications has introduced significant challenges in managing computational workloads across distributed edge environments. Edge- IoT systems are characterized by limited computational capacity, dynamic task arrivals, and strict latency constraints. Traditional heuristic-based scheduling techniques often fail to adapt to fluctuating workloads and heterogeneous resource availability. This study proposes a machine learning-based task scheduling and resource optimization framework for Edge-IoT systems. The proposed model …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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AI-Driven Inverse Design of Functionally Graded Bio-Nanocomposites for Sustainable High-Barrier Packaging
Abstract: Multilayer plastic packaging realizes high barrier performance through laminated heterogeneous structures, but the heterogeneous structure has severe end-of-life challenges caused by the interfacial incompatibility of materials and the poor recyclability. This study proposes the inverse design of functionally graded PLA-nanoclay composite films by reinforcement learning as a monolithic alternative to traditional multilayer systems. Twin-screw extrusion is designed as a continuous control Markov decision process, and proximal policy optimization (PPO) is …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1547–1564 Read article
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Survey of System-on-Chip Modular Test Approach
Abstract: The advancement in semiconductor technology over the past few decades has enabled the industry to develop new design and reuse methodologies referred as System-on-chip (SoC) design. These typically integrate heterogeneous mix of various complex analog and digital cores, with all their necessary electronic circuitry. The recent advancements have led to the use of the 3D structures (3D-SOCs) that brought along the benefits of higher performance, minimum average interconnect length, reduced …
Published in Journal of VLSI Design Tools and Technology · Vol. 6, Issue 3, 2016 · pp. 56–70 Read article
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Adaptive Task Scheduling and Resource Optimization Using AI Middleware
Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, specialized schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that can learn, forecast, and react to the actual real-world conditions in the system. Artificial intelligence middleware is also an attractive solution to this …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 · pp. 23–31 Read article
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Intelligent Network Slicing and Adaptive Switching for Ultra-Low-Latency 6G Communications
Abstract: The rapid evolution of sixth-generation (6G) wireless communication networks demands intelligent and adaptive network management mechanisms capable of supporting ultra-low-latency, massive connectivity, high reliability, and heterogeneous service requirements. This study proposes an Intelligent Network Slicing and Adaptive Switching (INS-AS) framework for optimizing communication resources and minimizing end-to-end latency in 6G environments. The proposed framework dynamically creates and manages logical network slices according to application-specific requirements, including enhanced mobile broadband, ultra-reliable …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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A Comparative Study of the Structure–Property Relationships in CAD/CAM Milled vs. 3D-Printed High-Performance Polymers: Impact of Molecular Orientation on Abrasive-Wear Resistance
Abstract: Background: The transition from subtractive to additive manufacturing in prosthetic dentistry has introduced significant variations in the macromolecular architecture of high-performance polymers. While CAD/CAM milling utilizes high-density, industrially polymerized blocks, 3D printing (Additive Manufacturing) relies on layer-by-layer deposition, which may induce anisotropic molecular orientation. This retrospective study investigates how these distinct manufacturing “thermal histories” influence the long-term abrasive-wear resistance of PEEK and PEKK restorations. Materials and Methods: Data were retrospectively …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 133–140 Read article