Search
160 articles for “scalable algorithms”
-
Data-Driven Design Framework for Biofunctional Polymer Composite Materials
Abstract: This paper introduces a knowledge-based design platform of biofunctional polymer composite substances through the combination of machine learning, materials informatics, and digital twins applications. The framework allows the effortless forecasting and maximization of mechanical, biological and degradation characteristics based on supervised, unsupervised and deep learning models. A materials database is accompanied by the AI algorithms to find the best material compositions and microstructure-property relationships. Experimental validation proves to be more …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article
-
Artificial Intelligence in Entomology: Global Advances, Applications, and Future Directions in Insect Research and Pest Management
Abstract: Artificial Intelligence (AI) is transforming entomology by enabling scalable, data-driven approaches to insect identification, ecological monitoring, and sustainable pest management. This review synthesizes recent global advances in AI applications across taxonomy, behavioral ecology, predictive modeling, and precision agriculture. Machine learning and deep learning techniques—including convolutional neural networks, acoustic classification models, and ensemble predictive algorithms—have demonstrated high classification accuracies (often exceeding 90% under controlled conditions) and improved early detection of pest …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 29–40 Read article
-
TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
-
Maintain Attendance Using Image Processing Technique
Abstract: Attendance tracking stands as a pivotal pillar in organizational management, bearing significant implications for operational efficiency, resource allocation, and fostering accountability. Traditional methodologies for attendance maintenance frequently exhibit deficiencies in terms of precision, security, and scalability, thus necessitating the exploration of avant-garde solutions. This research endeavors to introduce a pioneering approach to attendance upkeep, harnessing the prowess of image processing techniques synergized with artificial intelligence (AI) algorithms to surmount prevailing …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 29–34 Read article
-
An Experimental Analysis on Enhancement of Electric Vehicle Safety using ADAS Technology and Forward Collision Avoidance with an Automatic Braking System
Abstract: The rapid expansion of the automobile sector in developing nations has intensified road safety concerns, particularly in congested urban environments where human error accounts for approximately 90% of all accidents. This paper presents and experimentally validates an integrated Advanced Driver Assistance System (ADAS) for electric vehicles comprising three complementary safety modules: a Forward Collision Avoidance System (FCAS) employing an HC-SR04 ultrasonic sensor interfaced with an Arduino Uno R3 to detect …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 20–30 Read article
-
Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
-
Literature Review and Research Gaps in Power Quality Enhancement: From Conventional Methods to Intelligent Solutions
Abstract: Power quality (PQ) has become a critical concern in modern electrical power systems due to the rapid integration of renewable energy sources, proliferation of power electronic devices, and increasing sensitivity of loads. This paper presents a comprehensive literature review and research gap analysis of power quality enhancement techniques, ranging from conventional approaches to emerging intelligent solutions. Traditional methods, including passive filters, capacitor banks, and synchronous condensers, have been widely employed …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 38–80 Read article
-
Topology and Geometry in Data Science: Persistent Homology and Beyond
Abstract: In recent years, the interplay between topology, geometry, and data science has gained substantial momentum, offering powerful frameworks to analyze and interpret complex datasets. Traditional statistical and machine learning methods often rely on linear or metric- based assumptions, which may fail to capture the intrinsic structure of high-dimensional or nonlinear data. In contrast, topological and geometric methods provide shape-oriented, scale- invariant tools that focus on the continuity, connectivity, and global …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 21–27 Read article
-
Raspberry Pi-Based Real-Time Object Recognition for Smart Item Recovery
Abstract: In today’s fast-paced world, individuals often lose valuable time searching for misplaced items such as keys, phones, and remote controls—an estimated 2.5 days per year. This paper introduces a cost-effective, computer vision-based system that helps users efficiently locate everyday objects. The system utilizes a 1080p camera and the YOLO (You Only Look Once) object detection algorithm to enable accurate, real-time object recognition. Designed for practical usability, it stores detected object …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 28–36 Read article
-
A Comprehensive Survey on IoT-Enabled and Hand Gesture Controlled Robotic Arm Using Blynk IoT and OpenCV
Abstract: This venture presents an IoT-enabled and hand gesture-managed robot arm that operates in three distinct modes: automated control, IoT-based control via the Blynk app, and gesture-based control using OpenCV. The gadget integrates a NodeMCU microcontroller for wireless verbal exchange and management, with MQTT protocol enabling real-time messaging among the devices. In automated mode, the robotic arm plays predefined tasks autonomously. In IoT mode, users can remotely manage the arm using …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 35–40 Read article
-
Record Linkage in Knowledge Discovery Process Using Angle Based Machine Learning
Abstract: Record linkage is a critical data cleansing step in the knowledge discovery process, aimed at identifying and resolving inconsistencies across datasets. This study proposes an enhanced record linkage framework tailored for uncertain and large-scale data using a combination of distance measurement, probabilistic modeling, and semantic reasoning. A novel angle-based distance measurement technique is introduced to optimize matching between candidate records. To further boost match accuracy, a Finite Mixture Model (FMM) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1157–1170 Read article
-
Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
-
Transforming Cancer Care Through AI-Driven Machine Learning: Real-Time Patient Monitoring and Personalized Intervention Strategies
Abstract: Modern healthcare systems are being improved by artificial intelligence (AI) and machine learning (ML), particularly in the treatment of cancer. An AI-driven machine learning system for monitoring cancer patients in real time and offering tailored therapeutic methods is presented in this research. In order to track health issues in real time, the suggested system gathers ongoing health data from wearable sensors and integrates it with patient medical records. This data …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 31–38 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
-
Optimizing Urban Mobility with AI-Based Traffic Management
Abstract: Urban mobility is a pressing concern in modern cities, plagued by issues like traffic congestion and pollution. This research involves, "Optimising Urban Mobility with AI-based Traffic Management", delves into the potential of Artificial Intelligence (AI) to revolutionize traffic management. Focusing on AI algorithms, data analytics, and sensor technologies, the research aims to enhance traffic flow, reduce congestion, and improve overall efficiency. Through statistical analysis and simulations, the research evaluates the …
Published in Trends in Transport Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 34–43 Read article
-
Farmer’s Eye: A Sustainable Crop-Field Monitoring System
Abstract: This paper outlines the creation and implementation of an Internet of Things (IoT)-driven smart agriculture monitoring system. It aims to tackle major issues in agriculture, such as inefficient irrigation, excessive resource use, and a lack of real-time data. The system focuses on the Arduino Uno, which connects to a variety of sensors: soil moisture for measuring substrate conditions, DHT11 for monitoring ambient temperature and humidity, MQ135 for checking air quality, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 19–27 Read article
-
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
-
Task Scheduling in Cloud Computing using Hippopotamus Optimization Algorithm
Abstract: Cloud computing, which provides remote clients with on-demand services, has emerged as a crucial component of contemporary technology. It is still difficult to schedule tasks effectively in such diverse and dynamic situations. Motivated by the hippopotamus's balanced exploration and exploitation behavior, this research suggests a unique work scheduling method utilizing the hippopotamus optimization algorithm (HOA). In order to maximize resource usage and throughput while minimizing makespan and execution cost, the …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 22–29 Read article
-
Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article