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78 articles for “data augmentation”
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Innovative Eyewear for the Visually Impaired
Abstract: Object detection systems are essential tools for identifying and locating objects within images or videos. When integrated into spectacles or wearable devices, these systems provide users with real-time information about objects present in their surroundings. This functionality serves diverse purposes, such as assisting visually impaired individuals in navigating their environment or offering augmented reality data to workers during tasks. Region-based Convolutional Neural Networks (RCNN) represent a prominent machine learning model …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article
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Academia to Industry: The Impact of AI on Information Retrieval Technologies
Abstract: Artificial intelligence (AI) has significantly reshaped the field of information retrieval (IR), bridging theoretical advancements from academia with practical applications across various industries. This article explores the transformative impact of AI on IR technologies, highlighting key contributions from academic research and how they have been adapted for industry-scale implementations. Academic innovations, such as neural ranking models and semantic search techniques, have improved the accuracy and relevance of search results by …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Transcript Summarizer of YouTube Videos Using Deep Learning
Abstract: Transcriber Sum is a deep learning-based YouTube transcript summarization tool. It employs advanced machine learning techniques to automatically generate concise summaries of YouTube video transcripts, enabling users to quickly grasp the key content and insights of videos without the need to watch or read the entire transcript. This Transcriber Sum addresses the challenge of providing users with concise and informative summaries of video content by harnessing the power of deep …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 119–126 Read article
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AI-Assisted Design and Theoretical Aerodynamic Evaluation of a Multistage Conical Diffuser Micro Wind Turbine Fabricated from Polymeric Composites
Abstract: The rising demand for compact, lightweight, and high-efficiency renewable energy systems has accelerated the development of micro wind turbines capable of delivering stable performance under low wind conditions. Traditional bare-rotor micro turbines suffer from limited aerodynamic efficiency, motivating the adoption of diffuser-augmented architectures and advanced polymer-based composite materials. This study presents the AI-assisted conceptual design and theoretical aerodynamic evaluation of a multistage conical diffuser micro wind turbine fabricated using a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1111–1118 Read article
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Smart Service Solutions AI: AI-driven Multimodal Search for Home Appliance Support
Abstract: The global home appliance services market is projected to reach USD 1,203.11 billion by 2032, driven by smart household appliances. Essential services like installations, maintenance, and repairs ensure optimal performance and longevity, leading to higher customer satisfaction and loyalty. The service station partner ecosystem is crucial for ongoing support and profitability. However, challenges such as identifying the right manuals, finding relevant parts, and providing accurate instructions must be addressed to …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 27–43 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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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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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Farmer’s Pal
Abstract: Precision agriculture, characterized by data-driven decision-making, has transformed contemporary farming practices. To increase agricultural sustainability and efficiency, this abstract investigates the combination of sensor monitoring, machine learning, and picture processing. A network of sensors continuously collects vital environmental data, including temperature, humidity, rainfall, sunshine, soil moisture, and conductivity, for precision agriculture. By providing real-time insights, these sensors enable farmers to make informed choices about pest control, fertilization, and irrigation. This …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 2, 2025 · pp. 19–31 Read article
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Smart Bio-Polymer Composite Systems for Sustainable Bio-Polymer Composite Media for Enhanced Pollutant Removal in Constructed Wetland Systems Using Machine Learning
Abstract: Constructed wetlands are widely used for wastewater treatment due to their low cost and ecological compatibility; however, their efficiency in removing emerging contaminants remains limited. This study presents the development of biodegradable polymer-based composite materials integrated into wetland filtration systems to enhance pollutant removal efficiency. Bio-polymers combined with natural fillers such as biochar and clay were synthesized and evaluated under simulated wetland conditions. The results demonstrate improved adsorption capacity, increased …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 190–200 Read article
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Evolving Face of Quality in The World Robotics Process Automation (RPA)
Abstract: Robotics Process Automation (RPA) is a technology that automates repetitive and rule-based tasks using software robots or "bots." These bots mimic human interactions with digital systems and perform tasks like data entry, validation, report generation, and system integration. RPA leverages AI and ML to improve operational efficiency and can be applied across industries and functions. Implementing RPA offers benefits such as error reduction, productivity enhancement, and cost savings. RPA is …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 1, 2023 · pp. 1–9 Read article
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Data to Diagnosis: A Systematic Review of AI/ML in Healthcare
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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Predictive Maintenance Strategies for Safety-critical Mechanical Systems
Abstract: Ensuring the reliability and safety of industrial systems is essential, especially in high-risk sectors such as aerospace, manufacturing, and energy. Predictive maintenance (PdM) has become a crucial approach for minimizing operational failures and improving maintenance efficiency. This research introduces an advanced PdM framework that enhances industrial safety by integrating Internet of Things (IoT) technology, machine learning (ML), and big data analytics. By enabling real-time monitoring and predictive fault detection, this …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 12–17 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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The Rise of AI in E-Commerce: Transforming Shopping Experiences
Abstract: The field of e-commerce is transforming due to the integration of artificial intelligence, offering businesses fresh possibilities to enhance customer experiences, streamline operations, and foster expansion. This article explores the transformative impact of artificial intelligence (AI) on various aspects of e-commerce, including personalized shopping experiences, intelligent chatbots and virtual assistants, predictive analytics for inventory management, dynamic pricing strategies, visual search and image recognition, fraud detection, and security measures, augmented reality …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 22–26 Read article
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Human-Centered AI in Museums: Enhancing Accessibility and Visitor Engagement
Abstract: Artificial intelligence (AI) is being used extensively in museums, which are cultural and learning spaces, to improve accessibility, optimize environmental conditions, and improve visitor experiences. Traditional museum designs are evolving to accommodate the demands of contemporary visitors, as they frequently fall short in properly engaging various audiences. AI-powered tools like augmented reality, machine learning, and smart sensors allow museums to design customized, adaptable spaces. Based on real-time visitor data, these …
Published in Journal of Structural Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 27–33 Read article
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5G and up to 6G
Abstract: The 5th generation of mobile networks is called 5G, and the next generation, 6G is expected to arrive soon. With the promise of faster speeds, less latency, and increased connectivity, 5G technology has revolutionized mobile communications. However, the 6G vision is already taking shape as the need for high-performance networks keeps increasing. By offering ultra-high-speed communication, smooth artificial intelligence (AI) integration, extensive Internet of Things (IoT) connectivity, and support for …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 01–06 Read article
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Unmasking Hallucinations in Large Language Models Using Analysis of the LLAMA 2 Model and RAG Intervention
Abstract: The study describes the creation of a chatbot for financial trading called "TradeBot" and how it uses Retrieval Augmented Generation (RAG) to overcome the problem of producing false or unverifiable information, sometimes known as hallucinations. RAG allows the chatbot to refer to an external data source in addition to its taught knowledge, which increases the accuracy of its responses. The NCFM (NSE's Certification in Financial Markets) book was integrated as …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 76–86 Read article
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A Review on Tailor Craft E-Commerce: Design, Implementation and Evaluation
Abstract: The rapid growth of e-commerce has transformed how consumers purchase products and interact with businesses. In particular, the clothing and fashion industry has embraced digital platforms to extend its reach, improve accessibility, and offer convenience to customers. However, challenges such as unclear product information, insecure payment methods, poor user experience, and inefficient order tracking still limit customer satisfaction in many platforms. The Tailor Craft E-Commerce project aims to bridge these …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 1, 2026 Read article
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ANN-Based Adaptive Rotor Current Control for DFIG Wind Systems: A Comparative Dynamic Analysis
Abstract: The variability of rotor current management in Doubly Fed Induction Generator (DFIG)-based wind energy conversion systems is crucial for maintaining stability in power extraction under fluctuating wind and grid circumstances. Traditional proportional-integral (PI) controllers, despite their ease of use, frequently exhibit diminished performance when faced with parameter uncertainty, nonlinear behaviors, and rapid wind fluctuations.This paper presents an adaptive rotor current control strategy, which is an Artificial Neural Network (ANN)-based approach …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 1, 2026 · pp. 41–53 Read article