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35 articles for “scheduling algorithms”
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Advanced Collaboration and Project Management Platform
Abstract: The growing dependence of employees on remote and hybrid working modes worldwide has driven a demand for modern collaborative platforms to optimize project management. All organizations are keen on solutions that enhance workflow efficiency, facilitate seamless communications, and boost overall productivity. The study presents an advancement in project management collaboration and aims at finding solutions to meet those demands, using API integration. The study explores the extent to which API …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 2, 2025 · pp. 11–18 Read article
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A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
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Artificial Intelligence and Personalized Learning
Abstract: Artificial Intelligence is transforming education by delivering customized learning pathways that align with each learner’s unique abilities and areas for improvement. Traditional teaching often struggles to meet individual needs; however, AI-powered systems analyse learning patterns in real time, ensuring customized lessons. Virtual tutors and AI chatbots provide instant feedback and 24/7 support, improving comprehension. Gamified learning, combined with augmented and virtual reality, transforms education into a more engaging and enjoyable …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 11–18 Read article
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Artificial Intelligence Enhanced Waste Sorting and Classification System for Urban Recycling
Abstract: This study explores the potential of Artificial Intelligence (AI) and Machine Learning (ML) to enhance waste management efficiency within urban environments. Rapid urbanization has resulted in a surge of municipal waste, which current systems often struggle to manage effectively. The proposed AI-enhanced waste sorting and classification system aims to optimize waste collection routes and accurately forecast waste generation trends, thereby reducing operational costs, fuel consumption, and traffic congestion. Additionally, AI-driven …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 23–32 Read article
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Swarm Intelligence: Nature-Inspired Problem Solving
Abstract: Swarm Intelligence (SI) is a computational paradigm inspired by the collective behavior of natural systems, such as flocks of birds, schools of fish, and colonies of ants. It involves decentralized, self- organized systems where simple agents follow simple rules, yet their interactions lead to complex global behaviors. SI has gained significant attention in recent years due to its potential applications in solving optimization problems, routing, scheduling, and artificial intelligence tasks. …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 Read article
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Artificial Intelligence for Real-time Water Management
Abstract: Effective water management is vital for sustainable development, requiring the strategic allocation and utilization of water resources to satisfy the diverse demands of agriculture, industry, and households. Traditional methods are increasingly inadequate due to escalating challenges from climate change and population growth, which amplify water scarcity and distribution issues. To overcome these challenges, we need innovative solutions. Artificial intelligence offers significant potential in revolutionizing realtime water management through advanced techniques …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 13–20 Read article
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Intelligent Automated Guided Vehicle (AGV) System for Optimized Material Handling
Abstract: This project is the development of an Automated Guided Vehicle (AGV) system that has been developed to handle materials in the high-accuracy, reliability, and efficiency in industrial settings. The AGV is a combination of a blend of advanced technologies including sensor fusion, real-time path planning, and AI-based navigation to allow smooth and intelligent operation with minimal human intervention. The vehicle is able to efficiently identify, and evade obstacles by using …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 2, 2026 Read article
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Personalized Therapy Using Drug Delivery Devices
Abstract: The persistent challenge in modern medicine lies in inter-patient heterogeneity, rendering standardized drug dosing protocols suboptimal for many chronic conditions. Traditional pharmacokinetics fail to account for real-time biological fluctuations, leading to cycles of ineffective treatment or dose-limiting toxicity. This paper explores the critical intersection of advanced drug delivery devices (DDDs) and personalized medicine, positioning these technologies as the vital link translating genomic and biological data into tangible, patient- specific interventions. …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 53–62 Read article
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Green and Edge-Aware Computing: Rethinking Cloud Infrastructure for Sustainability
Abstract: Cloud computing has transformed the way organizations access and manage information technology resources, providing flexible, scalable, and cost-efficient services that support today’s data-driven world. Despite these advantages, the rapid expansion of large-scale cloud infrastructures has resulted in rising energy consumption, significant heat generation, and a growing environmental footprint. This research focuses on advancing green cloud computing by examining methods that reduce power usage while maintaining high performance. Key strategies include …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 17–24 Read article
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Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems
Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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A Comprehensive Review of DiagnoTech: Your Healthcare Companion
Abstract: The review paper “A comprehensive review of DiagnoTech: Your Healthcare Companion” brings forth a transformative solution in the advancements of healthcare technology which aims to be an all-in-one Healthcare Companion. It explores the four key elements of DiagnoTech: Lab Tests, Body Mass Index (BMI) Calculation, Yoga and Diet Recommendations, and disease prediction. It brings to light each of these features’ functionalities, integration, and their collective impact on the healthcare industry. …
Published in International Journal of Mobile Computing Technology · Vol. 2, Issue 2, 2024 · pp. 24–32 Read article
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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
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Exploring Artificial Intelligence in Operating Systems for Consumer Enhanced Experience: Knowledge-Based Interfaces for Intelligent User Experience and System Optimization
Abstract: The convergence of knowledge-based systems, machine learning algorithms, and natural language interfaces that provide dynamic and context-sensitive behavior is another foundation for this change. AI-based operating systems are important because they can enhance user experiences via automation, self-optimization, and customization. AI signifies a new era of cognitive computing, from adaptive power management for desktops and embedded systems to predictive text and voice recognition on mobile devices. Furthermore, this ability to …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 26–30 Read article
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Smart Dustbin for Household Using Internet of Things (IoT)
Abstract: This article, titled “Smart Dustbin for Household Using Internet of Things (IoT)”, introduces an innovative solution to manage household waste effectively. In today's fast-paced world, many individuals find it challenging to dispose of garbage regularly due to busy schedules. This IoT-based system aims to address this issue by employing sensors and connectivity to monitor the fill-level of dustbins in real time. By utilizing ultrasonic sensors and microcontrollers like the ESP32, …
Published in Journal of Geotechnical Engineering · Vol. 11, Issue 2, 2024 · pp. 38–48 Read article
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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