Search
68 articles for “memory efficiency”
-
Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
-
Resilient Shell-Based Frameworks for Edge and IoT Systems: A Comprehensive Analysis of Lightweight Automation in Distributed Environments
Abstract: Edge computing and Internet of Things (IoT) deployments require automation solutions that minimize resource use while supporting real-time processing and intermittent connectivity. This study investigates shell-based frameworks for managing distributed edge and IoT systems, with emphasis on sensor integration, live monitoring, and fault recovery. Drawing from 200 real-world deployment cases across smart city, healthcare, and industrial domains, the analysis compares shell scripting directly against containerized approaches (e.g., Docker with lightweight …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article
-
An Overview on 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 (Intelligent OS)—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 …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
-
AI Adoption in Medical Libraries: A Study on SDMH’s Use of Ovid Discovery AI and Its Impact on Evidence-Based Medicine
Abstract: The role of Artificial Intelligence (AI) in transforming medical libraries is increasingly significant as these libraries evolve to become intelligent, responsive hubs for knowledge dissemination. This paper explores the adoption of AI tools at Santokba Durlabhji Memorial Hospital (SDMH) Medical Library, focusing on the integration of Ovid Discovery AI, a cutting-edge tool designed to enhance literature search accuracy, summarize content, and provide context-aware recommendations. Using a mixed-methods approach, the study …
Published in Journal of Advancements in Library Sciences · Vol. 13, Issue 2, 2026 · pp. 1–9 Read article
-
Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
-
Efficient Clustering Techniques for Data Stream Mining
Abstract: Data mining mainly works on a massive database for storing heavy amount of data. It is generally essential for extracting the meaning insights from the massive, continuously growing database. The traditional method often struggles with sheer volume and the dynamic nature of the modern data. Data stream mining allows for the real-time analysis, means insights are generated as the data arrives, and not after the long batch process. This continuous …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 26–32 Read article
-
Carbon-Aware Autonomous AI Systems: Reinforcement Learning for Sustainable Cloud and Edge Computing
Abstract: The field of communication and information technology is expanding quickly. Because of this, a significant amount of carbon emissions are produced by cloud data centres and edge computing nodes. In fact they are now responsible for 3 to 4 percent of the worlds total greenhouse gas emissions. Most of the time people who manage these resources focus on how they are working and how quickly they can get things done.. …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 2, 2026 Read article
-
Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article