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43 articles for “memory utilization”
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Algorithmic Strategies for Complex Data Handling: Optimizing Data Structures for Enhanced Computational Performance
Abstract: We live in an age of big data and processing very large often complicated datasets can be crucial to efficient algorithmic performance. This paper discusses different algorithmic techniques when working with difficult data and how to arrange your information structures correctly for better functionality in large-scale methods. It checks the impact of different algorithms like sorting, searching, and hashing in boosting its processing speed as well as memory use. This …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 1–10 Read article
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Advanced Anomaly Detection in Cloud Infrastructures Using Deep Learning Algorithms
Abstract: It is critical to guarantee the stability and security of cloud environments as cloud computing is becoming the backbone of contemporary IT infrastructures. Neglecting to quickly identify and resolve anomalies, which might point to security breaches, performance problems, or system breakdowns, can lead to disastrous outcomes. The increasing size and complexity of cloud infrastructures are challenging the effectiveness of traditional anomaly detection methods. These approaches often depend on rule-based systems …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 1–11 Read article
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Violent Event Recognition and Monitoring Using Deep Learning for Surveillance Videos
Abstract: The significance of real-time capabilities in human detection and tracking is discussed in the abstract of the paper. We talk about tracking, eye detection, and face detection. A thorough motion detection program for use in video monitoring and other applications is suggested by the study. The goal of the study is to further human tracking technology. Optical flow features and appearance-invariant features from a Darknet CNN model are integrated. Acquiring …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 2, 2023 · pp. 39–44 Read article
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Traversal Speed Comparison of BFS and DFS in Balanced and Skewed Binary Trees
Abstract: In this paper, we provide an analysis of how well both breadth-first search (BFS) and depth-first search (DFS) algorithms perform while wandering through two kinds of binary trees: balanced and skewed. The research was motivated by the practical application of storing files and directories in a certain type of parent-child relationship through the use of hierarchical file systems (e.g., windows explorer). The result of measuring how fast and versatilely these …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 2, 2026 Read article
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AI-Enabled Feedback Management for Enhancing Education
Abstract: Institutions are becoming more aware of the importance of student input in improving learning experiences in the current educational environment. However, the intricate and complex patterns found in this feedback are frequently missed by conventional techniques like manual reviews and simple statistics. Our proposal suggests a novel method for analyzing student input and more accurately predicting sentiment by utilizing Long Short-Term Memory (LSTM) algorithms. We can learn more about student …
Published in International Journal of Electronics Automation · Vol. 3, Issue 2, 2025 · pp. 21–27 Read article
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Application of an Online Chromium Reduction System for D/H Analysis of Water Samples with Large Isotopic Variations Using Conventional Mass Spectrometer
Abstract: We present an online chromium (Cr) reduction system for measuring the D/H ratio of water samples exhibiting significant isotopic contrast, where the memory effect cannot be overlooked. Memory compensation is incorporated into the analysis procedure to mitigate this effect, allowing the utilization of injection results that would otherwise be discarded due to the memory effect. This approach enables a faster analysis and an increased sample throughput. Additionally, crucial aspects of …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 1, 2025 · pp. 7–12 Read article
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CMOS-Based Process-Scalable Analog Circuits for Machine Learning: A Comprehensive Review and Future Directions.
Abstract: Analog computing techniques are gaining attention for machine learning (ML) applications due to their ability to reduce computational complexity. Continuous operations such as addition and subtraction offer a simpler and more efficient approach compared to probabilistic product decoding, which can be sensitive to noise and inconsistent measurements. This paper presents a simulated VLSI implementation of a broadcast edge connection, independent of the MOS component model, along with experimental results. The …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 8–17 Read article
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Application of B-trees for Design of Optimal Page Replacement Technique in Modern Operating Systems
Abstract: Algorithms related to replacing the memory pages in operating systems are critical components of modern operating systems that manage virtual memory efficiently. Current algorithms such as LRU (Least Recently Used), Clock algorithms as well as FIFO (First-In-First-Out), often struggle with the increasing demands of contemporary applications and larger memory hierarchies. This research work proposes a novel approach utilizing B-tree data structures to design an optimal page replacement technique. The proposed …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 23–30 Read article
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Elderly Healthcare Using Federated Learning Approach
Abstract: The healthcare system for elderly people faces several challenges, which can be addressed using advanced machine learning models. These models can help monitor chronic diseases, detect falls, and provide personalized health recommendations. The study uses comprehensive datasets like MIMIC-III/IV, WESAD, and UCIHAR to explore human movements, device limitations, and the differences in fall occurrences. A detailed review of existing literature discusses current technologies for activity monitoring and fall detection, focusing …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 13–23 Read article
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Intelligent Polymer-Integrated Wearable Platforms for Sustainable IoT and Predictive Health Monitoring for Migraine Detection
Abstract: Migraine is a neurological disorder, and its effect on the global workforce is resultantly significant. However, the fact of the matter is the absence of notable technological breakthroughs and the fact that the technology presently available is reactive, meaning it tackles the symptoms of the attack after the attack has occurred. The requirement for this paper is, therefore, the provision of an innovative approach, and this paper will describe the …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 946–960 Read article
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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A Review on Medicinal Properties of Chickpea and Its Profile
Abstract: Cicer arietinum is the most well-known vegetable and seen everywhere in the world, particularly in Afro-Asian nations. It has a place with family Fabaceae and appropriated in tropical, sub-tropical and calm districts. It is an annual crop with 20–100 cm tallness and the stems are spread, erect while root framework is vigorous and leaves are made of 11–15 individual handouts which are oval fit as a fiddle. The blossoms are …
Published in Research and Reviews : Journal of Crop science and Technology Read article
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Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
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Decoding Big Data: A Practical Comparison Between Hadoop and Spark
Abstract: This paper conducts a comprehensive comparison of Apache Hadoop and Apache Spark, two essential frameworks in the big data era. The rapid expansion of data possesses challenges in terms of volume, variety, and velocity, which necessitate advanced processing solutions. Hadoop, utilizing its MapReduce paradigm, provides scalable and fault-tolerant storage, whereas Spark, built upon Hadoop, introduces in-memory processing to increase speed and flexibility. This study includes a detailed examination of their …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 15–23 Read article
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Hardware Synchronization for Embedded Multi-core Processors
Abstract: The focus is not on whether multi-core systems are becoming prevalent, but on how microcontroller architectures should be designed to comply with stringent field requirements. This paper illustrates the transition from single to multiple cores, ensuring coherence and consistency in shared memory through hardware mechanisms. Hardware barriers are implemented to allow for point-to-point synchronization between processor cores. Practical experiments center on the initial stages of transforming single-core systems into dual-core …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 33–42 Read article
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Enhancing IoT Network Security with Hybrid Deep Learning Classifiers for DDoS Attack Detection
Abstract: The security and operational dependability of Internet of Things (IoT) networks are seriously threatened by the growing susceptibility to Distributed Denial of Service (DDoS) assaults brought about by their rapid expansion. The intricacy and dynamic character of these advanced attacks can provide a challenge to conventional intrusion detection systems. This study presents a novel method for strengthening IoT network security by combining Convolutional Neural Networks (CNNs) and Long Short-Term Memory …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Deep Learning Approach to Produce Artificial Speech (Text-To-Audio)
Abstract: This program utilizes key features of the .NET framework to facilitate smooth text-to-speech conversion and audio playback. Upon execution, users are prompted to input text via a graphical user interface (GUI), which the program converts into speech using the ‘SpeechSynthesizer’ class from the ‘System. Speech.Synthesis’ namespace. The audio that has been synthesized is handled and stored as a WAV file called ‘output.wav’ by utilizing the ‘FileStream’ class, allowing for future …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 28–33 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 Read article
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Short Review: The Expanding Role of Shape Memory Alloys in Technology and Medicine
Abstract: Shape Memory Alloys (SMAs) are a unique class of smart materials that can recover their original shape when exposed to specific stimuli, such as temperature or magnetic fields. This exceptional property, attributed to the martensitic phase transformation, has garnered significant interest in various industries. SMAs exhibit remarkable characteristics such as pseudoelasticity, high corrosion resistance, excellent biocompatibility, and superior fatigue strength, making them ideal for applications in biomedical, aerospace, automotive, and …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 3, 2025 · pp. 35–44 Read article
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AI Powered Fault Detection in DC Motor using STM32
Abstract: This work presents the design and implementation of an embedded artificial intelligence system for real-time fault detection in a direct current (DC) motor using the STM32 Nucleo- F411RE microcontroller. The objective of the study is to develop a low-cost and efficient predictive maintenance solution capable of identifying abnormal motor behavior at an early stage. Vibration and temperature signals are acquired using an MPU6050 sensor and processed directly on the microcontroller …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 39–49 Read article