Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the application of 2-D FFT, Radon transform, the 1-D IFFT,and 1-D discrete wavelet transforms were used in the first proposed model, while discrete multicircularlet transform was used in the second proposed model. The final stage of the proposed models includes the use of the dynamic time warping algorithm for recognition tasks. The performance of the proposed systems was evaluated using forty different isolated Arabic words that are recorded fifteen times in a studio for speaker dependant. The result shows recognition accuracy of (91% and 89%) using discrete wavelet transform type Daubechies (Db1) and (Db4) respectively, and the accuracy score between (87%-93%) was achieved using
discrete multicircularlet transform for 9 sub bands.
One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca
... Show MoreOlfactory impairment and abnormal frontal EEG oscillations are recognized as early markers of Alzheimer’s disease (AD). Using a publicly available olfactory EEG dataset of 35 subjects spanning normal cognition, amnestic mild cognitive impairment (aMCI), and AD, each with MMSE scores and demographics, stimulus-locked epochs from four electrodes (Fp1, Fz, Cz, Pz) were processed with wavelet-based time–frequency analysis. Band-limited power ratios (delta, theta, alpha, beta) were computed as log-transformed post-odor/baseline values and aggregated to subject-level features. Statistical analyses revealed graded attenuation of odor-evoked frontal (Fp1) band-power ratios across groups, with significant differences in several band–od
... Show MoreA novel robust finite time disturbance observer (RFTDO) based on an independent output-finite time composite control (FTCC) scheme is proposed for an air conditioning-system temperature and humidity regulation. The variable air volume (VAV) of the system is represented by two first-order mathematical models for the temperature and humidity dynamics. In the temperature loop dynamics, a RFTDO temperature (RFTDO-T) and an FTCC temperature (FTCC-T) are designed to estimate and reject the lumped disturbances of the temperature subsystem. In the humidity loop, a robust output of the FTCC humidity (FTCC-H) and RFTDO humidity (RFTDO-H) are also designed to estimate and reject the lumped disturbances of the humidity subsystem. Based on Lyapunov theo
... Show MoreThree complexes of copper(II) and iron(II) with mixed ligands acetylacetonebis(thio-semicarbazone)- ABTSH2 and benzaldazine- BA have been prepared and characterized using different physico-chemical techniques including the determination of metal contents, mole-cular weight, measurement of molar conductivity, magnetic moment, molar refraction, infrared and electronic spectra. Accordingly, octahedral complexes having general formulaes [Cu2(ABTSH2)2(BA)2Cl2]Cl2 and [M2(ABTSH2)2(BA)2(SO4)2] {M= Cu(II) or (Fe(II)} have been proposed. The resulted complexes screened for antifungal activity in vitro against the citrus pathogen Aspergillus niger and Fusarium sp. which caused root rot of sugar and the beans pathogen Alternaria sp. All the complex
... Show MoreIn this paper, precision agriculture system is introduced based on Wireless Sensor Network (WSN). Soil moisture considered one of environment factors that effect on crop. The period of irrigation must be monitored. Neural network capable of learning the behavior of the agricultural soil in absence of mathematical model. This paper introduced modified type of neural network that is known as Spiking Neural Network (SNN). In this work, the precision agriculture system is modeled, contains two SNNs which have been identified off-line based on logged data, one of these SNNs represents the monitor that located at sink where the period of irrigation is calculated and the other represents the soil. In addition, to reduce p
... Show MoreNew complexes of the some trivalent transition metal ions of the uracil such as [M(Ura)3Cl3] and mixed ligand metal complexes with uracil and oxalic acid [M(Ura)2(OA)(OH2)Cl].H2O type, where (Ura)=Uracil, (OA= Oxalic acid dihydrate, (M= Cr+3 and Fe+3) were synthesized and characterized by the elemental analysis, FT.IR, electronic spectra, mass spectra and magnetic susceptibility as well as the conductivity measurements. Six–coordinated metal complexes were suggested for the isolated complexes of Cr+3 and Fe+3 with molecular formulas dependent on the nature of uracil and oxalic acid present. The proposed molecular structure for all complexes with their ions is octahedral geometries. The antibacterial efficiency was tested of metal salts, l
... Show MoreNowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of
... Show MoreCoaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artifi
... Show MoreWith the increasing reliance on microgrids as flexible and sustainable solutions for energy distribution, securing decentralized electricity grids requires robust cybersecurity strategies tailored to microgrid-specific vulnerabilities. The research paper focuses on enhancing detection capabilities and response times in the face of coordinated cyber threats in microgrid systems by implementing advanced technologies, thereby supporting decentralized operations while maintaining robust system performance in the presence of attacks. It utilizes advanced power engineering techniques to strengthen cybersecurity in modern power grids. A real-world CPS testbed was utilized to simulate the smart grid environment and analyze the impact of cyberattack
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