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112 articles for “signal extraction”
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Comparative Study of Bayes Net and Multilayer Perceptron Model using ECG Signals
Abstract: In recent days, heart abnormalities are common among people regardless of their age. Heart abnormalities must be detected and treated in very initial stage which protects people from major heart abnormalities. Sometimes, physician feels difficulty in classifying heart abnormalities from extracted features. This problem can be solved with an excellent data mining technique called classification. Classification is a data mining technique which is used to label tuples. In this paper …
Published in Recent Trends in Parallel Computing · Vol. 2, Issue 2, 2015 · pp. 14–17 Read article
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Text Data Hiding and Extraction of Image using Discrete Wavelet Transform
Abstract: Now a days with the wide use of multimedia is increasing to a large extent, the visual information that contains the high quality and low complexity digital images plays a very vital role in daily life applications such as satellite television, magnetic resonance imaging, computed tomography, geographical information systems and astronomy and many other areas. Main purpose of this paper is to investigate or develop new concepts to design digital …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 2, Issue 3, 2015 · pp. 1–5 Read article
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Power Quality Monitoring in Wind Solar Hybrid System
Abstract: With the development of new functionalities, solar and wind energy based hybrid systems are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting, is one of the most promising sources. Due to the development of modern power electronic devices, the power quality of wind solar hybrid system gets affected. Hence, due to the increasing usage of sensitive electronic equipments in wind solar …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 1, 2018 · pp. 16–23 Read article
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Pattern Recognition of Finger Movements of Two Channel based Surface EMG Signals
Abstract: Surface EMG signal is widely used as a control signal for prosthetic device for the amputees or paralyzed able-bodied person with added advantage of being noninvasive and not painful. An ample amount of research on the prosthetic control of movements of forearm and hand is available in the literatures but few researches has been carried out for control of more dexterous individual and combined finger movements. The ability to precisely …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 1, 2016 · pp. 7–14 Read article
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Bearing Fault Analysis using Variational Mode Decomposition
Abstract: Bearing health analysis plays a significant role in industry to improve reliability and performance of critical processes by alarming the faults at early stages. Conventional techniques do not guarantee to detect the faults at early stages because the low energy bearing frequencies get suppressed by stern noise and higher vibrations. The fast Fourier transform (FFT) fails to analyze the transient and nonstationary signals directly. This paper performs the signal analysis …
Published in Journal of Instrumentation Technology & Innovations · Vol. 4, Issue 2, 2014 · pp. 20–27 Read article
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Implementation of Base Line Interferometry Algorithm for Direction Finding
Abstract: The Electronic Warfare (EW) receiver aims to intercept the Radar signal and analyze its characteristics like Frequency, Pulse Width (PW), Pulse Repetition Interval (PRI), Amplitude and also its Direction of Arrival (DOA). The Radar signal is in the range of 0.5 to 40 GHZ this will be down converted using super-heterodyne receiver as front end. The Intermediate Frequency (IF) from front end in the range of 750 to 1250 MHZ …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 2, Issue 2, 2015 · pp. 21–24 Read article
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OBD-II Big Data–Driven ML and AI-Based Virtual Sensing for Fuel Economy, Component Health, and Carbon Intelligence
Abstract: The rapid growth of connected vehicles has led to the large-scale availability of high-frequency On-Board Diagnostics II (OBD-II) data; however, much of this data remains underutilised, as existing studies and commercial systems typically address fuel economy, maintenance, or emissions in isolation or rely on additional physical sensors. Such fragmented and sensor-dependent approaches limit scalability and increase system cost, particularly in high-volume and resource-constrained vehicle markets. To address this gap, this …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 41–52 Read article
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Emotion Recognition based on Human voice tones
Abstract: In this period of technology and automation, human interaction with machines has become an unavoidable occurrence. Machines are making our lives much easier, stretching their hands wherever it is possible for smoother operation of various tasks. Emotion recognition system is one of the system that can help humans for a much easier and meaningful interaction with machines. It can be used in various branches such as artificial intelligence, health care, …
Published in Current Trends in Information Technology · Vol. 10, Issue 2, 2020 · pp. 1–5 Read article
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A Real-time Automated Drowsiness Detection of Driver Using the Visual Behaviour and Machine Learning Technique Through WebCam
Abstract: In our day-to-day life, many accidents can occur due to the drowsiness of the driver. It is one of the causes of road accidents. To prevent accidents, we proposed a system to detect the drowsiness of driver by measuring the eye aspect ratio, mouth yawning and alert the driver. It will save the life of a person. In this, the driver fatigue is continuously captured by webcam. Image processing methods …
Published in Journal of Web Engineering & Technology · Vol. 10, Issue 2, 2023 · pp. 10–19 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Modeling and Acoustic Analysis of Noise Vibration in Automotive Gearbox by Non-destructive Testing
Abstract: A gearbox is used for transferring power from the engine to the wheels. Predicting the vibration and noise radiation from a dynamic system like a gearbox gives designers an insight early in the design process. It was conducted experimental and modeling of vibration and noise for magnitude and pressure level variations in a Peugeot 206 automotive 5-speed gearbox. It was extract vibration data related to different periodic processing and then …
Published in Journal of Experimental & Applied Mechanics · Vol. 11, Issue 3, 2020 · pp. 54–63 Read article
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A Mini-Review on Spectral (UV Visible, FT-IR, 1H NMR, GC-MS) Analysis of Various Shaded Dried Leaves Extracts
Abstract: To collect the different types of leaves in various places, wash collected leaves with distilled water and dried these leaves in various processes like under shade dry for 15 days, place oven (45 oC) for 1 hour. Grind well using the above-dried leaves, so these leaves are changed to powder form. Utilize these shaded dried leaves powder, to prepare extract with solvents like methanol, ethanol, hexane, carbon tetrachloride, petroleum ether, …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 13, Issue 1, 2022 · pp. 1–8 Read article
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Lip Reading: Transforming Speech to Text
Abstract: Lip reading, the ability to interpret spoken language by observing lip movements, is a valuable skill that can aid in various applications, particularly in enhancing speech recognition systems. This project explores the implementation of a deep learning-based lip-reading model to improve the accuracy and robustness of speech recognition in challenging environments, such as noisy or audio-limited settings. The proposed lip-reading system leverages Convolutional Neural Networks (CNNs) and Recurrent Neural Networks …
Published in Current Trends in Signal Processing · Vol. 14, Issue 1, 2024 · pp. 23–33 Read article
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Vibration Monitoring of Diesel Engine Using Bioethanol from Water Hyacinth as Fuel
Abstract: For the current study, water hyacinth plants (Eichhornia crassipes) are used as raw materials for fermentation with native yeast isolated from the water hyacinth plants. Acid hydrolysis followed by fermentation with the yeasts resulted in the yield of bioethanol. Bioethanol is mixed with diesel fuel in different ratios and used in IC engines. Vibrations have direct effects on engine components therefore; analysis of vibration resulting from combustion in IC engines …
Published in Journal of Automobile Engineering and Applications · Vol. 3, Issue 1, 2016 · pp. 21–33 Read article
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Embedding and Extraction of Watermark in Digital Audio
Abstract: AbstractDigital Watermarking, a discipline of steganography, is used to hide within an image or audio file some data specifically relating to that file. An enormous amount of work has been carried out in the field of Image Watermarking. Due to the increasing incidents of audio piracy and illegal retrieval of audio files over the internet, the field of audio watermarking has widespread attention from industry and researchers. In this paper, …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 2, 2014 · pp. 8–12 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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Comprehensive Evaluation of Quercetin from Bauhinia purpurea for Its Anti-Acne and Anti-Inflammatory Potential, Including Advances in Quercetin-Loaded Nanogel Formulation
Abstract: Acne vulgaris is among the most prevalent chronic inflammatory dermatoses in clinical dermatology, afflicting a substantial proportion of the global adolescent and adult population. Conventional pharmacotherapies — including topical retinoids, benzoyl peroxide, and systemic antibiotics — remain the therapeutic mainstay; however, their long-term utility is progressively undermined by adverse cutaneous reactions, systemic toxicity, and the rising prevalence of antibiotic-resistant Cutibacterium acnes strains. These limitations have intensified scientific interest in plant-derived …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 13, Issue 2, 2026 · pp. 34–46 Read article
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Detect the Edges in Satellite Image Using CED Algorithm
Abstract: Edge detection is that the name for a collection of mathematical strategies that aim at distinguishing points in a very digital image at that the image brightness changes sharply or, a lot of formally, has discontinuities. The points at that image brightness changes sharply square measure generally organized into a collection of flexuous line segments termed edges. Constant drawback of finding discontinuities in 1D signal is understood as step and …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 2, Issue 3, 2015 · pp. 30–35 Read article
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Bearing Fault Diagnosis Using ANN and SVM with the Help of Wavelet Transform Based Features
Abstract: Many researchers use vibration signals as fault characteristics of any rotating bearing for fault detection and use various optimization techniques available for fault of bearing classification. The method of fault classification uses few neural network (NN) geometry and parameters necessary for the formulation. There is no derived formulation which can be used to select the optimal values for the network parameters. The parameters which are required to be calculated, impacts …
Published in Recent Trends in Electronics Communication Systems · Vol. 4, Issue 2, 2017 · pp. 26–34 Read article
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Pharmaceutical Activity of Mirabilis Jalapa and its Biogenesis of Nanocrystals
Abstract: Bio friendly green modest synthesis of nanoparticles are the present research in nanotechnology. This study has been undertaken to explore the determinants of copper nanoparticles from 1 mM CuSO4 solution through profuse concentration of aqueous flower extract of Mirabilis jalapa reducing besides immobilizing agent. The attribute of copper nanoparticles was studied by using UV-VIS spectroscopy SEM and XRD. The XRD spectrum of the copper nanoparticles established the presence of elemental …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 12, Issue 3, 2025 · pp. 56–65 Read article