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567 articles for “computational efficiency”
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Blockchain Technology: Comprehensive Review and Future Directions
Abstract: Blockchain technology has emerged as a transformative power, restructuring sectors by offering increased security, transparency, and decentralization. This research paper serves as a comprehensive examination of blockchain, aiming to dissect its intricate structure, explore its myriad applications, confront existing challenges, and envision future advancements. At its core, the problem addressed herein is the imperative to comprehend the present landscape of blockchain technology, discern its limitations, and chart a course toward …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 33–38 Read article
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Automated Math Solver Assist with LLM RAG
Abstract: The challenges of solving complex mathematical problems often hinder efficiency in various scientific and engineering domains. This project proposes an innovative solution to these challenges by integrating automated math solvers with large language model (LLM) retrieval-augmented generation (RAG). The proposed system aims to streamline mathematical problem-solving processes, offering a robust and precise tool for real-time recognition, classification, and solution generation. This work provides a novel method of automating the solution …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 25–30 Read article
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Deep Learning -Based Dental Issue Detection
Abstract: Dentistry is vital for preserving oral health, a key component of overall wellness. Early identification of dental issues is crucial for effective treatment and avoiding further complications. Conventional approaches to diagnosing dental problems typically depend on physical examinations and visual assessments by skilled professionals, which can be both time-intensive and influenced by individual judgment.In recent years, the application of deep learning algorithms has demonstrated significant potential in automating and enhancing …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 1, 2025 · pp. 18–23 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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ECO Report Analys Achieving SDG 15
Abstract: This project creates automated data processing tool Eco Data Analyser for ecological data analysis for SDG 15: Life on Land conservation and biodiversity. File_picker, Excel, and CSV are used in the Flutter and Dart based cross-platform solution to assist environmental organizations in handling ecological data. Uploading ecological datasets, verifying data, classifying biodiversity indicators, and producing summary reports helps Eco Data Analyser to make conservation data accessible and valuable. User-defined parameters …
Published in International Journal of Land · Vol. 2, Issue 2, 2025 · pp. 1–10 Read article
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Influence of Epoxy-Based Thermally Conductive Polymer Composites on the Thermo-Hydraulic Performance of Finned Helical Coil Heat Exchangers Across Flow Regimes
Abstract: The use of polymer composites in heat exchanger applications has gained increasing attention due to their advantages in weight reduction, corrosion resistance, and design flexibility. However, their relatively low thermal conductivity compared to conventional metallic materials remains a key limitation for efficient heat transfer. In this study, the thermo-hydraulic performance of a finned helical coil heat exchanger is investigated with particular focus on epoxy-based polymer composites reinforced with thermally conductive …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 586–602 Read article
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Optimizing Routing and Placement of VLSI Circuits with Differential Algorithms and Neural Networks
Abstract: The performance of modern VLSI systems is heavily influenced by power constraints, necessitating precise power estimation and effective optimization techniques. Traditional methods, such as gate-level simulations, are often slow and computationally intensive. This paper introduces DRPENN (Differential Algorithm for Routing and Placement Optimization using Neural Networks), an innovative solution that combines a Switching Activity Estimator (SAE) with a neural network-assisted differential algorithm. By leveraging toggle rates from simulations to train …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article
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DOCSNAP: Integrating NLP and Computer Vision for Comprehensive Document Summarization
Abstract: Because of the exponential growth of digital content, sophisticated tools are required for effective data interpretation and administration.. This project harnesses the capabilities of the Gemini AI model developed by Google DeepMind to address the challenges of PDF summarization and image captioning. Gemini AI integrates cutting-edge algorithms, including transformer architectures, to process textual and visual data seamlessly. The project's system architecture involves modules for text and image extraction, with a …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 Read article
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A Review on AI and Machine Learning for Predictive Maintenance and FDD in RAC Systems
Abstract: The paper reviews the existing AI/ML methods first in the general context of predictive maintenance and FDD of RAC systems, then specifically focusing on granular cooling appliances. Perspectives and insights are provided on the reasons why potentially valuable models do not make it into practice more often, and where future research and development should be headed. New emerging topics for decision support systems to include domain knowledge and physics-based modeling …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 · pp. 15–25 Read article
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Study of Lipid Profile and Its Correlation with Coronary Angiogram Finding in a Tertiary Care Hospital in an Urban Setting
Abstract: Coronary artery disease (CAD) is a major global health concern caused by the constriction or blockage of the coronary arteries, which can result in serious cardiovascular events. This study looks at the relationship between lipid profiles and the severity of CAD as measured by coronary angiography in patients in a tertiary care hospital. The study focuses on dyslipidemia as a major risk factor for CAD, emphasizing the importance of efficient …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 106–118 Read article
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Machine Learning for Finding Materials for Membranes
Abstract: Traditionally, finding and improving membrane materials has depended on trial-and-error experiments, which can take a long time, cost a lot of money, and only cover a small area. Recent improvements in machine learning (ML) have the potential to change the way membrane materials are designed by making it possible to make predictions about performance, selectivity, and stability based on data. ML algorithms can find hidden links between the structure, composition, …
Published in International Journal of Membranes · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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Application of Convolutional Neural Networks in Design of Efficient Pipe Flow System
Abstract: Convolutional Neural Networks exhibit remarkable capabilities in flow pattern recognition, pressure drop prediction, leak detection, and system optimization through their ability to process complex spatial and temporal data patterns. The study examines CNN architectures specifically adapted for fluid dynamics applications, including data preprocessing techniques, feature extraction methods, and performance optimization strategies. Key applications include real-time flow monitoring, predictive maintenance, design parameter optimization, and anomaly detection in pipe networks. Comparative analysis …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 3, 2025 · pp. 1–9 Read article
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Optimizing Vehicle Structures Using Functionally Graded Materials of Aluminum and Carbon Fiber Reinforced Polymer Composites
Abstract: This article investigates the optimization of vehicle structures through application of functionally graded materials (FGMs), specifically aluminium and carbon fibre reinforced polymer (CFRP) composites. Such materials, known as FGMs, are characterized by spatial variations in composition and structure designed to improve so-called performance attributes. For the purposes of this research, the material properties of aluminium and CFRP composites are taken to be randomly distributed in thickness direction of a FGM …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 478–489 Read article
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AI and IoT in Sustainable Agriculture: A Review
Abstract: Artificial Intelligence (AI) and Internet of Things (IoT) integration have transformed the world of sustainable agriculture, presenting new ways of resource optimization, increasing crop yields, and making environmental sustainability more accessible. The current literature review analyzes the applications of AI and IoT in three significant agricultural systems: aquaponics, hydroponics, and poultry farming. By critically analyzing recent studies, this paper emphasizes how deep learning- enabled computer vision techniques allow for the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 32–45 Read article
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Advancements in Smart Manufacturing: A Review of Industry 4.0 Technologies and Integration Strategies
Abstract: A new era of production known as “Smart Manufacturing,” which is primarily motivated by the ideas of Industry 4.0, has been brought about by the quick development of digital technologies. The goal of this technology revolution is to develop intelligent, adaptive, and networked production systems that react instantly to shifting supply, demand, and operating circumstances. The Internet of Things (IoT), artificial intelligence (AI), machine learning (ML), cyber-physical systems (CPS), big …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 1, 2025 · pp. 31–36 Read article
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Design and Performance Analysis of Microwave Filters and Resonators for High-Frequency Systems
Abstract: Microwave filters and resonators are fundamental components in high-frequency systems, playing a crucial role in signal selection, interference suppression, and frequency stabilization. This review presents a detailed analysis of design methodologies and performance characteristics of microwave filters and resonators used in modern communication and radar applications. Various filter topologies, including low-pass, high- pass, band-pass, and band-stop configurations, are examined with respect to their frequency response, insertion loss, selectivity, and bandwidth. …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 1, 2026 · pp. 8–16 Read article
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Optimizing Power Generation from Building Ventilation Systems: A Study on Exhaust Fan Efficiency
Abstract: Due to population growth, the world's energy consumption has increased dramatically in both wealthy and developing nations in recent years, and by 2042, it is predicted to have doubled or more. Since a few years ago, the use of innovative sustainable power sources to meet energy demands has been gradually increasing. We've chipped away at a different idea because of this. As an alternative energy source, renewable energy (RE) resources …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 2, 2023 · pp. 22–27 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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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article