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137 articles for “Data Pre-processing”
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Steps involved in EEG Signal Analysis for Arm Movement
Abstract: This study delves into the intricacies of analyzing EEG signals associated with arm movement motor imagery. We explore established techniques across three key stages: data pre-processing, feature extraction, and classification for movement identification. By critically evaluating the strengths and weaknesses of each approach, we optimize the analysis pipeline for robust decoding of arm movement intent. This work empowers researchers and practitioners to transform raw EEG data into actionable insights, opening …
Published in International Journal of Microwave Engineering and Technology · Vol. 10, Issue 1, 2024 · pp. 43–55 Read article
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Smart Wastewater Treatment Plant Modeling Using ANN And ASM1 MATLAB Simulation
Abstract: Wastewater Treatment Plants (WWTPs) are necessary infrastructure for protecting the environment and public health, but modeling and predicting performance has been an ongoing challenge for engineers working within a WWTP and regulators of the environment. For many years the Activated Sludge Model No. 1 (ASM1) has been the standard for simulating biological treatment processes, but the conventional implementations in MATLAB do not provide the user-friendly interface, the predictive intelligence, or …
Published in International Journal of Chemical Engineering and Processing · Vol. 12, Issue 2, 2026 · pp. 44–62 Read article
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Detailed survey on detection of Dirtiness of PV panels using different approaches
Abstract: The accumulation of dust, dirt, bird droppings, pollen, and other environmental contaminants on photovoltaic (PV) panels significantly reduces their power generation efficiency and increases operational and maintenance costs. Therefore, timely and accurate detection of the cleanliness condition of solar panels is essential for maintaining optimal energy production, improving system reliability, and extending the operational lifespan of PV installations. In recent years, considerable research interest has been directed toward automated soiling …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article
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Comparison Analysis of Lumpy Skin Disease Detection System Using X-Ray Images of Animals with the Help of Deep Learning
Abstract: Lumpy Skin Disease (LSD), caused by the Capripoxvirus, is a highly contagious viral infection impacting cattle and other livestock, resulting in significant economic losses due to decreased productivity and mortality. Early detection is critical to mitigate its spread and reduce its impact on agriculture and dairy sectors. This study investigates the efficacy of deep learning methodologies for detecting LSD through X-ray images, offering a non-invasive diagnostic approach to identify internal …
Published in International Journal of Animal Biotechnology and Applications · Vol. 11, Issue 2, 2025 · pp. 1–5 Read article
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Design, Development, and Testing of 2-Phase Separator
Abstract: As the pressure vessel operates under high internal pressure, the choice of material and accuracy indesign play a vital role in ensuring its safety and reliability. Proper design is essential because anyfailure in a pressure vessel can lead to serious hazards, financial losses, and operational shutdowns.In compliance with the ASME Code (Section VIII, Division 1) and the process data sheet, this articledescribes how to design a pressure vessel. To guarantee …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 12, Issue 1, 2026 · pp. 29–37 Read article
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Design, development and Testing of 2-Phase Separator
Abstract: AB S T R A C T As the pressure vessel operates under high internal pressure, the choice of material and accuracy in design play a vital role in ensuring its safety and reliability. Proper design is essential because any failure in a pressure vessel can lead to serious hazards, financial losses, and operational shutdowns. In compliance with the ASME Code (Section VIII, Division 1) and the process data sheet, …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 12, Issue 1, 2026 · pp. 1–6 Read article
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CNN-Based Traffic Sign Recognition with Voice Alerts
Abstract: Traffic sign recognition is a crucial component of intelligent transportation systems, significantly enhancing road safety by aiding both autonomous and human drivers. This paper presents a convolutional neural network-based traffic sign recognition system integrated with voice alerts. Our approach utilizes a deep learning model trained on a comprehensive dataset of traffic signs to accurately identify various road signs in realtime. Upon recognition, the system issues corresponding voice alerts to inform …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–9 Read article
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Gourmet Sage Using Deep Learning With Calories Chart
Abstract: Gourmet Sage via Deep Learning with Calories Chart is an innovative system that merges advanced deep learning technology with nutrition science to help users make healthier dietary choices. By leveraging YOLOv8, a cutting-edge object detection model, the system allows real-time identification of food items, estimating their calorie content and ingredient composition with remarkable accuracy. It goes beyond detection by providing a comprehensive nutritional breakdown, including macronutrients (proteins, fats, carbs) and …
Published in International Journal of Image Processing and Pattern Recognition Read article
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Intrusion Detection System Using Gated Recurrent Neural Network
Abstract: In the realm of cybersecurity, the constant evolution of threats demands sophisticated intrusion detection systems (IDSs) capable of discerning intricate patterns in network traffic. This study proposes an IDS leveraging the capabilities of gated recurrent neural networks (GRNNs) to enhance the detection of anomalies and potential security breaches. The GRNN architecture, employing mechanisms like long short-term memory (LSTM) and gated recurrent unit (GRU), demonstrates efficacy in capturing long-range dependencies within …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 1, 2024 · pp. 1–8 Read article
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Forecasting Trends in the Stock Market by Using Deep Learning Approaches
Abstract: Accurately predicting stock market trends remains a significant challenge in the field of finance. Deep learning, a subset of machine learning, has emerged as a powerful tool for capturing complex relationships within data. What sets deep learning apart is its ability to handle vast amounts of data, recognize intricate features, and adapt to evolving patterns, all while uncovering hidden insights. At its core, deep learning uses artificial neural networks that …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 2, 2024 · pp. 22–30 Read article
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A study AI-Driven IoT in Self-Healing Grid Power Systems
Abstract: Modern electricity infrastructure is undergoing a transformation thanks to the combination of artificial intelligence (AI) and the Internet of Things (IoT), especially in the development of self- healing grid systems. In the context of smart grid automation and resilience, this article provides a thorough review of AI-driven IoT infrastructures. By leveraging distributed sensor networks, real-time data acquisition, and advanced KSK Approach, and machine learning algorithms—includes ANN, DT and K-NN—the proposed …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 · pp. 15–24 Read article
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A Review on Surface Error Compensation in Thin-Walled Component Machining
Abstract: *Author for CorrespondenceManikandan HareendranE-mail: [email protected] 1,4,5,6Associate Professor, Department of Mechanical Engineering, Mangalam College of Engineering (APJAKTU), Kottayam, Kerala, India2,3Assistant Professor, Department of Mechanical Engineering, Mangalam College of Engineering (APJAKTU), Kottayam, Kerala, India7Professor, Department of Mechanical Engineering, Mangalam College of Engineering (APJAKTU), Kottayam, Kerala, India Received Date: November 12, 2024Accepted Date: November 14, 2024Published Date: November 22, 2024 Citation: Rajeeve K. Mohana, Santhu Varghese Thomas, Rahul Krishnan, Johan George Cherian, Navish …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 10, Issue 2, 2024 · pp. 1–11 Read article
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Next-Generation IoT-Based Air & Noise Pollution Monitoring System Using ESP32-S3
Abstract: Air and noise pollution have become serious environmental problems in modern urban areas due to rapid industrialization, increasing traffic, and population growth. Continuous monitoring of pollution levels is important to protect public health and maintain environmental safety. Traditional pollution monitoring systems are expensive and limited in coverage, which makes real- time monitoring difficult in many locations. To address this issue, this project proposes a low-cost Internet of Things (IoT) based …
Published in International Journal of Environmental Chemistry · Vol. 12, Issue 1, 2026 · pp. 69–75 Read article
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A Study on Sensors in Metallurgy Applications
Abstract: The relentless pursuit of efficiency, quality, and sustainability within the metallurgical industry hinges on unprecedented control over its often extreme and dynamic processes. This control is progressively realized through the strategic deployment of advanced sensor technologies. This paper explores the pivotal role of sensors in modern metallurgy, spanning from the raw material stage to the final product. It highlights how sensors, by providing real-time, accurate, and often non-intrusive data, are …
Published in International Journal of Metallurgy and Alloys · Vol. 11, Issue 2, 2025 · pp. 14–26 Read article
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An Overview on Metal Processing using Machine Learning
Abstract: Metalworking, which is an important part of modern industry, includes a wide range of steps, such as shaping and casting the metal, machining it, and riveting it. The industry has always relied on trial and error and other empirical methods, but machine learning (ML) is now causing a big change. It is expected that this change will lead to higher production, better product quality, and better use of resources. The …
Published in International Journal of Manufacturing and Materials Processing · Vol. 12, Issue 1, 2026 · pp. 43–53 Read article
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A Comprehensive Review of Convolutional Neural Network Architectures and Evolution
Abstract: Convolutional Neural Networks (CNNs) have become a foundational deep learning framework in computer vision because they can automatically extract layered, increasingly complex features directly from raw image data. CNNs use convolutional, pooling, and activation layers to extract spatial patterns from basic edges to intricate object components, drawing inspiration from the human visual cortex. An overview of CNNs’ basic architecture is given in this study, along with an explanation of important …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 32–40 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Customer preferences in adopting AI in their building designs: A Perspective case study from Saudi Arabian architects
Abstract: Recent AI advances have improved Saudi building design inventiveness, efficiency, and cultural sensitivity. Automating tedious activities like image resizing and layout optimization with AI helps designers focus on novel concepts. AI may assess client preferences and society conventions to assist designers adapt their ideas to local cultural values, making architectural development projects more appealing. Even though it has many advantages, artificial intelligence in architecture is confronted with several challenges. The …
Published in International Journal of Architecture and Infrastructure Planning · Vol. 10, Issue 2, 2024 · pp. 25–40 Read article
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Evaluation of the Effectiveness of a Structured Teaching Program on Mothers’ Knowledge Regarding the Prevention of Dengue Fever in Children: A Study in Pediatric Medical Wards at Shridevi Institute of Medical Sciences and Research Hospital
Abstract: Background and objectives: Dengue, commonly referred to as break-bone fever, is a viral infection spread to humans by mosquitoes, especially in tropical and subtropical areas. Although many people infected with dengue may show no symptoms, those who do typically exhibit symptoms such as high fever, headaches, body aches, nausea, and a rash. In most cases, individuals recover within 1–2 weeks. However, severe cases may necessitate hospital care. Home treatment is …
Published in International Journal of Pediatric Nursing · Vol. 10, Issue 1, 2024 · pp. 54–63 Read article