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169 articles for “time-critical applications”
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Real-time Operating Systems in the Era of IoT: Challenges and Solutions for Time-Critical Applications
Abstract: Real-time operating systems (RTOS) are essential in the Internet of Things (IoT), as they ensure timely responses to events, which is critical for the performance and reliability of connected devices. This paper delves into the unique challenges faced by RTOS in IoT environments, highlighting issues such as limited computational resources, strict latency requirements, and the increasing need for robust security mechanisms. The resource constraints inherent in many IoT devices, which …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 13–24 Read article
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Time Series Sales Forecasting Using ARIMA Model
Abstract: Sales forecasting is a critical application in various industries and presents one of the most challenging problems worldwide. One method of prediction involves identifying patterns in historical data, where the outcome is known in advance and can be validated using more recent data. If a pattern consistently leads to the same outcome, it can be considered a genuine relationship. This method is highly flexible and can be utilized with diverse …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 17–27 Read article
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The Significance and Applications of Parallel Computing in the Modern Era
Abstract: This article explores the advancements in parallel computing, focusing on its applications in various domains such as scientific simulations, big data analytics, artificial intelligence, and real-time processing. We discuss the architectural shifts from traditional single-core processors to multi-core and many-core systems, along with the role of graphics processing unit (GPU)-based computing and specialized hardware like tensor processing units (TPUs) and field programmable gate arrays (FPGAs). Furthermore, the article examines contemporary …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 24–38 Read article
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Analysis of Project Management Optimization Using CPM and PERT in a Dynamic Business Environment
Abstract: In the current fast-changing business environment, organizations must remain agile and strategically responsive to unpredictable challenges such as supply chain disruptions, shifting consumer demands, and evolving market trends. Project management techniques like the Critical Path Method (CPM) and the Program Evaluation and Review Technique (PERT) serve as valuable tools in helping businesses manage these complexities effectively. CPM is a time-focused method that identifies the longest sequence of dependent tasks in …
Published in Journal of Construction Engineering, Technology & Management · Vol. 15, Issue 3, 2025 Read article
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64 Bit ALU DESIGN USING VEDIC MATHEMATHICS
Abstract: High-speed arithmetic operations are crucial for better performance in contemporary digital systems. Particularly for high bit-width operations, conventional arithmetic logic units (ALUs) frequently experience increased latency and complexity. This work presents the design and implementation of a 64-bit Arithmetic Logic Unit (ALU) using notions from Vedic mathematics. The suggested design makes use of a Kogge-Stone Adder for effective addition and the Urdhva Tiryagbhyam sutra for quick multiplication. Among other mathematical …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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Exploring Additive Manufacturing Technologies in Engineering: A Comprehensive Study
Abstract: The objective of this research was to systematically elucidate various pathways in casting, focusing on the utilization of Additive Manufacturing (AM) technology and its transformative impact on investment casting. The purpose of this systematic review is to ascertain whether AM may be a practical solution for investment casting production. Diverse databases, including Google Scholar, Research Gate, Mendeley, and Science Direct, were utilized for comprehensive research. When compared to creative techniques …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 2, Issue 1, 2024 · pp. 16–19 Read article
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Design and Validation of an Artificial Intelligence-Driven Digital Twin for Real-Time Monitoring and Control in Polymer Composite Manufacturing
Abstract: Polymer Matrix Composites (PMCs) have become indispensable in high-performance sectors such as aerospace and automotive engineering, offering exceptional strength-to-weight ratios that outperform traditional metals in many demanding applications. However, the reliability of manufacturing PMCs via Vacuum-Assisted Resin Transfer Molding (VARTM) is frequently undermined by stochastic process variabilities. Unpredictable fluctuations in thermal history, preform permeability, resin rheology, and ambient conditions often lead to some defects; namely voids, dry spots, and incomplete …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 224–233 Read article
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Innovative Biosensor Applications in Petroleum Industry for Enhanced Monitoring and Safety Measures
Abstract: The petroleum industry is fundamental to the global economy, providing the energy and raw materials that drive modern society. However, this industry faces a myriad of challenges, including ensuring the safety of operations, monitoring critical processes effectively, and minimizing environmental impacts. Traditional monitoring techniques, while valuable, often fall short in delivering real-time data and comprehensive insights into operational parameters. These limitations can result in delayed responses to potential hazards and …
Published in Journal of Petroleum Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 1–13 Read article
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Integration of AI and Machine Learning in Smart Environment Monitoring Systems
Abstract: The Internet of Things (IoT) plays an important role in our lives. Many real-time changes in logistics environment monitoring and location tracking can be measured using IoT. It uses a wireless sensor network to monitor important changes in the environment. In this article a comparative review study has been performed in which one side wireless sensor network is integrated with IoT only while on the other side wireless sensor network …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 15, Issue 2, 2024 · pp. 13–19 Read article
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Educating Compilers to Learn: Utilizing Machine Learning for More Brilliant Code Optimization
Abstract: This study explores the use of machine learning (ML) approaches to compiler optimization. The now-traditional static compilation techniques are transformed into adaptive, dynamic systems capable of making context-specific advancements. Traditional compilers rely mostly on heuristic or rule-based optimization techniques. While these techniques work well in general cases, they consistently fail to adapt well within the limits of code structures that modern machines display. This limitation is especially acute in today's …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 50–54 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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GeoPrompt: A Mobile Applications Reminder System Based on Location
Abstract: In today’s fast-paced environment, maintaining organization and order is more critical than ever. Traditional paper reminders, though useful, often fall short of meeting the efficiency demands of modern life. While mobile phone reminders are commonly used, they are typically time-based and cannot address tasks that require attention at specific locations. To address this gap, we present “GeoPrompt-A Mobile Application Reminder System Based on Location,” a cutting-edge Android app that improves …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 3, 2024 · pp. 21–27 Read article
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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Parametric Optimization of Aluminum Alloy 6061 Using Wire-EDM for Automotive Applications: A Taguchi-Based Approach
Abstract: Machining hard materials with complex geometries presents numerous challenges, often requiring the use of non-traditional methods such as wire Electric Discharge Machining (EDM). However, wire EDM machines operate at slow speeds, and increasing the speed can negatively impact surface finish, making it a difficult task. The ongoing research investigates the machinability study of Aluminum Alloy 6061 using wire EDM, emphasizing the optimization of process parameters to enhance machining performance and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 293–302 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
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Kinetic Analysis of Structural Acrylic Curing by DSC: Polymerization and Phase Transition Optimization
Abstract: Differential Scanning Calorimetry (DSC) was used to analyse the thermal properties and curing behaviour of a structural acrylic adhesive at heating rates of 5, 10, and 15 °C/min. The study focused on the curing kinetics, glass transition temperature (Tg), specific rate (k), and activation energy (Ea) of the polymerization reaction. The material is tested according to ASTM 3418 standards. Results showed that increasing the heating rate shifted the endothermic curing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 726–733 Read article