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821 articles for “process modelling”
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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
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Investigating The Feasibility of Basalt Fiber as A Carbon Fiber Substitute in Composites for Automotive Applications
Abstract: The escalating carbon footprint, a consequence of dwindling natural resources and surging energy demand, necessitates immediate measures to mitigate environmental impact. This prompted the current study: to look at alternative manufacturing materials that could be utilized as a carbon-free substitute without compromising on mechanical properties. Basalt fiber was identified as a potential eco-friendly replacement to carbon fiber which has several advantages over carbon fiber and is entirely natural and biodegradable. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 275–285 Read article
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Real Time Automobile - Caused Air Pollution Monitoring System
Abstract: The system proposed in this paper aims to be a novel approach for real-time detection and quantification of vehicular emissions, integrated into smart city infrastructures. The structured workflow enhances accuracy and efficiency. The license plate is captured by OCR, while the ground clearance is simultaneously measured, allowing the thermal camera to dynamically adjust its position to align with the tailpipe level. The emission data is collected and transmitted to a …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 1, 2025 · pp. 49–55 Read article
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An Overview on Harnessing Microwave Frequencies for Next-Generation Satellite Communication and Earth Observation
Abstract: In the vacuum of space, where traditional cables cannot reach, humanity has woven an invisible, high-speed infrastructure made of oscillating electromagnetic waves. At the heart of this architecture lies the microwave spectrum—the unsung hero that enables everything from global GPS navigation to real-time climate monitoring. The evolution of global connectivity and environmental monitoring is intrinsically linked to the mastery of the microwave spectrum. As satellite constellations transition from traditional Geostationary …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 1–6 Read article
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Ethical Challenges in Natural Language Processing: A Comparative Study of Solutions Across Multiple Domains
Abstract: This comparative analysis investigates the ethical challenges associated with natural language processing (NLP) by reviewing and synthesizing insights from ten influential and widely cited publications in the field. As NLP technologies are increasingly integrated into domains such as healthcare, finance, education, and governance, ethical concerns related to algorithmic bias, data privacy, fairness, accountability, and system transparency have become more prominent. This paper systematically examines how different researchers conceptualize and address …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 13, Issue 1, 2026 · pp. 01–07 Read article
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Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
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Revolution of Artificial Intelligence and Machine Learning
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are profoundly transforming various industries by introducing groundbreaking technologies such as deep learning, federated learning, reinforcement learning, and natural language processing. These innovations are not only reshaping the way organizations operate but are also opening new avenues for solving complex problems across diverse sectors, including healthcare, finance, transportation, and more. This study provides a comprehensive exploration of these emerging technologies, emphasizing their practical …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 38–44 Read article
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Using AIML to Enhance Demand Forecasting in Business
Abstract: Artificial intelligence machine learning (AIML) can play a significant role in enhancing demand forecasting in business. AIML is a programming language designed for creating chatbots and conversational agents, but its application extends beyond simple interactions. In the context of demand forecasting, AIML can be utilized to analyze historical data, customer interactions, and market trends. By implementing AIML algorithms, businesses can create intelligent models that learn from past demand patterns, customer …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 35–40 Read article
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Money Laundering Transaction with Machine Learning
Abstract: This study discusses the use of machine learning algorithms to discover firms that are prone to money laundering. The purpose of this research is to develop, describe, and test a machine learning model for determining which bank transactions should be physically scrutinized for money laundering activities. To train a supervised machine learning model, three categories of historical data are required: legitimate "normal" transactions, transactions flagged as suspicious by the bank's …
Published in Current Trends in Information Technology · Vol. 14, Issue 2, 2024 · pp. 1–15 Read article
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Face Aging Using Generative Adversarial Network
Abstract: This project addresses the challenge of predicting how a person may look in the future or how they appeared in the past using a single photograph. While existing methods mainly focus on altering texture, they often neglect changes in head shape that naturally occur during the aging process, limiting their effectiveness, especially when applied to images of children. To tackle this issue, a novel approach is introduced that employs a …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 41–52 Read article
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article
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A Comprehensive Study of various Multi-Area Hybrid Power Systems for Generation Control
Abstract: This paper is a detailed examination of multi-area hybrid power systems in the control of the generation taking into consideration the two area up to five area connected networks. As renewable energy sources are more and more integrated, and modern grids become more and more complex, the stability of the system itself and the frequency regulation have risen to a major issue. The study highlights the significance of Automatic Generation …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 28–42 Read article
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Harnessing Marine Byproducts and Optimization of Biopolymer Extraction Quality Using Response Surface Methodology and Study of Its Physicochemical Properties
Abstract: Chitosan, a versatile biopolymer derived from chitin, holds immense potential across various industries owing to its antimicrobial, antioxidant, and biocompatible properties. This study aims to optimize the deacetylation process of chitin, sourced from shrimp shells, using Response Surface Methodology (RSM) to produce high-quality chitosan. The Box-Behnken Design (BBD) was employed to evaluate the effects of temperature, time, and alkali concentration on the degree of deacetylation (DD%), a key determinant of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 125–139 Read article
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SkinSight: Design and Implementation of an Intelligent Skin Type Detection System
Abstract: Identifying an individual’s skin type accurately is essential for creating personalized dermatological treatments and formulating skincare products that genuinely meet user needs. In this project, a real- time skin type classification system is developed using a combination of convolutional neural networks (CNNs) and modern computer vision techniques. The system processes live video streams, isolates the facial region through Haar cascade–based detection, and applies a series of preprocessing steps to enhance …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 35–45 Read article
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Collaborative Robotics and Smart Automation: Enhancing Human–Robot Synergy in Industry 5.0
Abstract: Industry 5.0 marks a paradigm shift from efficiency-centric automation to a human-centred, sustainable, and collaborative production environment . In this context, collaborative robots, commonly referred to as cobots, play a central role by enabling direct and safe interaction between humans and machines within shared workspaces. These systems are designed to support human operators by undertaking repetitive, precision-intensive, and physically demanding tasks, thereby allowing humans to focus on supervisory control, problem-solving, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 22–29 Read article
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Effect of Drilling Process Parameters on Surface Roughness of LM6/B4C/Fly Ash Hybrid Composites
Abstract: This research seeks to assess the effect of process variables such as feed rate (FR), spindle speed (SS), drill material (DM) and reinforcement (R%) on surface roughness (SR) when drilling LM6/B4C/Fly ash hybrid composites. The stir casting process was used to fabricate the LM6/B4C/Flyash hybrid composites utilizing LM6 aluminum alloy as the matrix material and B4C/Fly ash as strengthening materials. Experiments were carried out using an L18 orthogonal array (OA) …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 898–906 Read article
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Study on the Method of Calculation of the Additional Mass of Parachute
Abstract: As is well known, the air drag experienced by a parachute when it is open is one of the important parameters that must be taken into account in studying the parachute opening process. If this term is not calculated correctly, it can have a negative effect on the parachute canopy, and may lead to errors in the number of parachute strings, the nominal diameter of the parachute, and the material …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 3, Issue 2, 2025 · pp. 22–31 Read article
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Sign Language to Speech Translation and Emergency Alert System for Dumb persons using Ml and IOT
Abstract: This project proposes a novel approach for gesture recognition using key point extraction and neural networks. Our proposed system leverages key point extraction techniques to capture fine-grained spatial information from input gestures. These key points are then fed into a neural network model, allowing for automatic feature learning and robust gesture classification. The goal of this project is to integrate OpenCV's computer vision capabilities to build a flexible and effective …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 17–21 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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Parametric Investigations of Melt Flow Index for Nylon6-Mica Composite Based Hybrid FDM Filament
Abstract: The development of new hybrid filaments with improved mechanical and thermal properties has been driven by the increasing need for high-performance materials in additive manufacturing. This study explores the parametric investigations of the Melt Flow Index (MFI) for Nylon6-Mica composite-based hybrid Fused Deposition Modeling (FDM) filament. The investigation uses the Taguchi technique to examine how different extrusion temperatures, loads and the percentage of Mica filler affect the MFI, a critical …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 165–173 Read article