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372 articles for “Extraction process”
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Log Identification and Monitoring System Using Generative AI
Abstract: In contemporary software ecosystems, application and infrastructure logs play a vital role in ensuring system reliability, performance optimization, fault diagnosis, and security compliance. As applications become increasingly distributed and cloud native, the volume, velocity, and variety of generated log data have grown dramatically. This rapid expansion makes traditional manual log inspection inefficient, error-prone, and largely impractical. To address these challenges, this paper proposes an artificial intelligence (AI) driven log monitoring …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 08–16 Read article
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Integrated Polarimetric-Interferometric Fusion for Heterogeneous Urban Signature Extraction
Abstract: Mapping heterogeneous urban environments using conventional Synthetic Aperture Radar (SAR) backscatter intensity frequently produces classification errors due to spectral similarity between sparse built-up features, bare soil, and dry vegetation a challenge especially acute in semi-arid Deccan Plateau settings. This research presents a dual-path Pol- InSAR fusion framework that integrates polarimetric scattering decomposition and interferometric coherence stability to extract heterogeneous urban signatures over Beed Taluka, Maharashtra (area: 1,561.31 km²). A temporal …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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Identification of English Dialects and Emotions using Spectral and Prosodic Features of Speech Signal Processing
Abstract: AbstractIn this paper, the authors have explored speech features to identify English dialects and emotions. A dialect is any distinguishable variety of a language spoken by a group of people. Emotions provide naturalness to speech. Speech database considered for dialect identification task consists of spontaneous speech spoken by male and female speakers. The emotions considered in this study are anger, disgust, fear, happy, neutral and sad. Prosodic and spectral features …
Published in Journal of Computer Technology & Applications · Vol. 4, Issue 2, 2013 · pp. 10–17 Read article
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Plants Disease Detection Using TensorFlow and OpenCV
Abstract: Growing healthy and productive crops is crucial in the global battle for food security. To minimize crop losses and apply timely control measures, early and precise diagnosis of plant diseases is essential. Conventional illness detection techniques are subjective, labor-intensive, and complicated; they frequently rely on eye inspection. The TensorFlow and OpenCV libraries are used in this study to explore the use of Convolutional Neural Networks (CNNs) for plant disease discovery. …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 1, 2024 · pp. 31–38 Read article
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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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Boron Nitride Unleashed: Revolutionary Insights into Its Superhard Phases and Machining Aptitude
Abstract: Exploration from the prehistoric era has proven steel to be a hard substance. According to research, the four main crystalline forms of boron nitride are graphitic, cubic, rhombohedral, and wurtzitic. Better hard materials for industrial processes have been provided by diamond, hard ceramic, and cermet in the process of developing the front of the script, which is descriptive. Turning, cutting, drilling, boring, and grinding of hard materials have been linked …
Published in Journal of Catalyst & Catalysis · Vol. 11, Issue 2, 2024 · pp. 17–24 Read article
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EMOTION RECOGNITION FROM ELECTROENCEPHALOGRAM SIGNAL AND EYE MOVEMENT BASED ON DEEP LEARNING
Abstract: Emotion recognition from electroencephalogram (EEG) signals has gained significant attention due to its potential in human- computer interaction (HCI), mental health monitoring, and personalized content delivery. This paper presents the use of Convolutional neural networks (CNNs) to classify emotions such as happiness, sadness, fear, neutral, and disgust by leveraging a fusion of EEG signals and eye movements data. Compared to conventional methods of emotion detection, such as those that rely …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 8–15 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Some Plant Extracts Potential in Cleaning Soil Environment Contaminated with Petroleum Hydrocarbon
Abstract: This research considered the trend of some agro-based plant extracts obtained from paw paw, mango and aloe-vera leaves for the purpose of treatment of a contaminated soil environment. The potential of each agro-based plant extract was tested with respect to its ability in the area of petroleum hydrocarbon clean-up in soil environment. The impact of the variation on the pH on each of the bioreactor set-up was monitored and the …
Published in Journal of Petroleum Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 27–39 Read article
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IOT in Supply Chain and Logistics: A Critical Review
Abstract: Abstract Internet of Things (IoT) is a major component now-a-days in the industrial scenario. From procurement to supply chain, logistics every process can be made more organized and less time consuming as well as increasing the efficiency of the processes. This paper critically reviews the till date research on IoT in Logistics and supply chain and tries to obtain a logical conclusion of any research gap if any. In this …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 2, 2018 · pp. 11–16 Read article
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An Efficient Recursive Least Square (ERLS) Algorithm for Spectral Estimation with the Aid of Wavelet and Artificial Intelligence
Abstract: The spectral estimation technique is used for time frequency signal analysis, speech processing, and other signal processing applications. Some drawbacks of RLS algorithm are that it requires high computational power and the output obtained is numerically instability. So, the spectral efficiency of the signal is affected and a power error occurs in the estimator. In this paper, an efficient recursive least square (ERLS) algorithm is proposed for improving the power …
Published in Current Trends in Signal Processing · Vol. 2, Issue 1-3, 2012 · pp. 1–10 Read article
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POTENTIAL BIOPRESERVATIVE EFFECT OF ANTIMICROBIAL PEPTIDES OF SEEDS OF Vigna unguiculata (Cow Pea) ON Hibiscus sabdariffa L. (Roselle) Calyces (Zobo) DRINK
Abstract: Natural and efficient food preservatives are in greater demand because of growing concerns about the safety and quality of processed beverages. Antimicrobial peptides have emerged as promising natural substitutes for synthetic preservatives, boasting advantages like wide-ranging activity and reduced toxicity. In this research, we investigate the inhibitory effects of these peptides against common spoilage microorganisms in 'Zobo' drink. Peptides were extracted and purified from germinated Vigna unguiculata) seeds harvested on …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 14, Issue 1, 2025 · pp. 26–41 Read article
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Machine Learning-Based Structure–Property Quantification of Advanced Polymer Composites
Abstract: Advanced polymer composites are widely used in high-performance engineering due to their superior mechanical and multifunctional properties. Accurate structure–property quantification is essential for efficient material design and reducing experimental costs. Existing Machine Learning (ML) approaches often exhibit limited predictive generalization due to inadequate feature discrimination and suboptimal hyperparameter tuning. To address these limitations, the proposed method enhances the ability to capture the complex nonlinear interactions among composite structural descriptors. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Detection of Brain Tumors from MRI Images Based On Development of Thinking Computer Systems Techniques
Abstract: Brain tumors are one of the common diseases of the nervous system and have great harm to human health, and even lead to death. The detection, segmentation, and extraction of contaminated tumour regions from Magnetic Resonance Imaging (MRI) pictures are major problems; yet, a repetitive and time-consuming task performed by radiologists or clinical experts relies on their experience. The many anatomical structures of the human organ can be imagined using …
Published in Current Trends in Signal Processing Read article
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Detection of Brain Tumors from MRI Images based On Development of Thinking Computer systems Techniques
Abstract: Brain tumors are one of the common diseases of the nervous system and have great harm to human health, and even lead to death. The detection, segmentation, and extraction of contaminated tumour regions from Magnetic Resonance Imaging (MRI) pictures are major problems; yet, a repetitive and time-consuming task performed by radiologists or clinical experts relies on their experience. The many anatomical structures of the human organ can be imagined using …
Published in Current Trends in Signal Processing · Vol. 11, Issue 3, 2021 · pp. 28–34 Read article
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Alzheimer disorders diagnosis system design using machine learning for EEG signal
Abstract: The diagnosis of Alzheimer's disorders (AD), a prevalent neurological disorder, can created by utilising a range of therapeutic methods, including the electroencephalogram (EEG), which has been especially successful in the past. The objective for this study is to develop a computer-aided diagnosis tool which may recognize AD from EEG data. The EEG information was cleaned up with a band-pass elliptic digital filter to remove any interference or disruptions. The filtered …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 1, 2023 · pp. 9–22 Read article
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Spatial variations of land surface temperature and its relationship with the type of land use/cover
Abstract: Environmental parameters are intricately interdependent and affect nearby and sometimes distant components. Environmental parameters become more important when dealing directly with humans. Land surface temperature (LST) is one of the environmental parameters that when it is related to the city as the main center of human gathering, it is referred to as urban heat island (UHI). Land use/ Land cover (LU/LC) is one of the important environmental parameters that affect …
Published in Journal of Geotechnical Engineering · Vol. 11, Issue 1, 2024 · pp. 1–16 Read article
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Design of EMG based Control System for Prosthetic Arm
Abstract: Prosthesis, field of bio-mechatronics, is an artificial extension used to replace the function or appearance of a missing limb or lost body part due to injury (traumatic), to correct congenital deficiencies or to supplement defective body parts. A myoelectrically controlled prosthesis detects muscle contractions using electrodes and this electrical activity acts as a signal to activate the prosthesis. In the presented work, the EMG signal is acquired using surface electrodes …
Published in Journal of Electronic Design Technology · Vol. 4, Issue 2, 2013 · pp. 1–6 Read article