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Dual Stages of Speech Enhancement Algorithm Based on Super Gaussian Speech Models
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Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression algorithms. In this research, the design of SEA based on different speech models (Laplacian model or Gaussian model) has been implemented using two types of discrete transforms, which are Discrete Tchebichef Transform and Discrete Tchebichef-Krawtchouk Transforms. The proposed estimator consists of dual stages of a wiener filter that can effectively estimate the clean speech signal. The evaluation measures' results show the proposed SEA's ability to enhance the noisy speech signal based on a comparison with other types of speech models and a self-comparison based on different types and levels of noise. The presented algorithm's improvements ratio regarding the average SNRseq are 1.96, 2.12, and 2.03 for Buccaneer, White, and Pink noise, respectively.

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Publication Date
Mon Mar 10 2025
Journal Name
Proceedings On Engineering Sciences
WAREHOUSE IN INDUSTRY 4.0 BASED DRONE, COMPUTER VISION, AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES: A LITERATURE REVIEW
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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
The Determination of Critical-Sampling Scheme of Preprocessing for Multiwavelets Decomposition as 1st and 2nd Orders of Approximations.
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One of the important differences between multiwavelets and scalar wavelets is that each channel in the filter bank has a vector-valued input and a vector-valued output. A scalar-valued input signal must somehow be converted into a suitable vector-valued signal. This conversion is called preprocessing. Preprocessing is a mapping process which is done by a prefilter. A postfilter just does the opposite.

The most obvious way to get two input rows from a given signal is to repeat the signal. Two rows go into the multifilter bank. This procedure is called “Repeated Row” which introduces oversampling of the data by a factor of 2.

 For data compression, where one is trying to find compact transform representations for a

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Publication Date
Tue Sep 02 2025
Journal Name
Chemistry & Biodiversity
Synthesis, In Silico, and Biological Evaluation of Non‐Hydroxamate Benzoic Acid–Based Derivatives as Potential Histone Deacetylase Inhibitors (HDACi)
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ABSTRACT<p>Unregulated epigenetic modifications, including histone acetylation/deacetylation mediated by histone acetyltransferases (HATs) and histone deacetylases (HDACs), contribute to cancer progression. HDACs, often overexpressed in cancer, downregulate tumor suppressor genes, making them crucial targets for treatment. This work aimed to develop non‐hydroxamate benzoic acid–based HDAC inhibitors (HDACi) with comparable effect to the currently four FDA‐approved HDACi, which are known for their poor solubility, poor distribution, and significant side effects. All compounds were structurally verified using FTIR, <sup>1</sup>HNMR, <sup>13</sup>CNMR, and mass spectrometry. In silico ana</p> ... Show More
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Publication Date
Thu Feb 29 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Design and Development of Powerful Neuroevolution Based Optimized GNNBiLSTM Model for Consumer Behaviour and Effective Recommendation in Social Networks
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Publication Date
Wed Nov 23 2022
Journal Name
Dental Hypotheses
Remineralization of Dentine Caries Using Moringa Oleifera Based Nano-Silver Fluoride: A Single-Blinded, Randomized, Active-Controlled Clinical Trial
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Publication Date
Fri May 12 2023
Journal Name
Bulletin Of The Chemical Society Of Ethiopia
SYNTHESIS, CHARACTERIZATION, ANTIMICROBIAL STUDIES, AND MOLECULAR DOCKING STUDIES OF TRANSITION METAL COMPLEXES FORMED FROM A BENZOTHIAZOLE-BASED AZO LIGAND
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The azo ligand obtained from the diazotization reaction of 2-aminobenzothiazole and 4- nitroaniline yielded a novel series of complexes with Co(II), Ni(II), Cu(II), and Zn(II) ions. The complexes were investigated using spectral techniques such as UV-Vis, FT-IR, 1H and 13C NMR spectroscopic analyses, LC-MS and atomic absorption spectrometry, electrical conductivity, and magnetic susceptibility. The molar ratio of the synthesized compounds was determined using the ligand exchange ratio, which revealed the metal-ligand ratios in the isolated complexes were 1:2. The synthesized complexes were tested for antimicrobial activity against S. aureus, E. coli, C. albicans, and C. tropicalis bacterial species. Additionally, their binding affinities we

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Sensing Performance of Modified Single Mode Optical Fiber Coated With Nanomaterials-Based Ammonia Sensors Operated in the C-Band
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Tue Mar 21 2023
Journal Name
Biomedical And Pharmacology Journal
Development and Validation of HPLC Method For the Detection of Fusidic Acid Loaded in Non-ionic and Cationic Nanoemulsion-Based Gels
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Fusidic acid (FA) is a well-known pharmaceutical antibiotic used to treat dermal infections. This experiment aimed for developing a standardized HPLC protocol to determine the accurate concentration of fusidic acid in both non-ionic and cationic nano-emulsion based gels. For this purpose, a simple, precise, accurate approach was developed. A column with reversed-phase C18 (250 mm x 4.6 mm ID x 5 m) was utilized for the separation process. The main constituents of the HPLC mobile phase were composed of water: acetonitrile (1: 4); adjusted at pH 3.3. The flow rate was 1.0 mL/minute. The optimized wavelength was selected at 235 nm. This approach achieved strong linearity for alcoholic solutions of FA when loaded at a serial concentrati

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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Application of Box-Behnken Method Based ANN-GA to Prediction of wt.% of Doping Elements for Incoloy 800H Coated by Aluminizing-Chromizing
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In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg

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