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Automatic voice activity detection using fuzzy-neuro classifier
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Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, autocorrelation, and log energy. A modified version of fuzzy C-Means is then used to cluster speech segments into three clusters; two clusters for voice and one for unvoiced. After that, three feed forward neural networks are trained to adjust their weights, in which each network represents one cluster. To make the final decision regarding the class type of a given speech segment, the membership degrees of this segment in all clusters along with neural networks' decisions are given to a defuzzification step which finally gives the class type of that segment. The proposed FN-AVAD is tested on the public multimodal emotion database, Surrey AudioVisual Expressed Emotion (SAVEE), and the error rate was 2.08%. The achieved results are comparable to the results achieved by the current published works in the literature.

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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 Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Molecular detection by some virulence genes of Salmonella enterica subsp. enterica isolated from the stool of children with diarrhea
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Diarrhea is a real disease in childhood which could cause death. Therefore, this study was conducted to isolate Salmonella from 350 stool samples taken from children under five years in age, suffering from diarrhea during the period from March 2019 to March 2020 in Tikrit city / Iraq. The results showed the possibility to isolate ten isolates of Salmonella enterica subsp. Enterica, an infection rate, represents 2.875% of the total rate of patients who suffer from diarrhea. The virulence genes were investigated for ten isolates of S. enterica subsp. enterica, the result is that all isolates possessed the genes stn, invA, lpfA with an appearance percentage of 100%, whi

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Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Comparison between Quantitative Computed Tomography and Dual-Energy X-Ray Absorptiometry in the Detection of Osteoporosis in Postmenopausal Women
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Background: Osteoporosis is denoted by low bone mass and microarchitectural breakdown of bone tissue, directing to increased fracture risk and bone fragility. Fractures may lead to a decreased quality of life and increased medical costs. Thus, osteoporosis is widely considered a significant health concern.

Objective. This study aimed to compare quantitative computed tomography (QCT) and dual-energy X-Ray absorptiometry (DXA) to detect osteoporosis in postmenopausal women.

Subjects and Methods. We measured spinal volumetric bone mineral density (BMD) with QCT and areal spinal and hip BMD with DXA in 164 postmenopausal women. We calculated the osteo

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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Publication Date
Sun Jun 04 2017
Journal Name
Baghdad Science Journal
Synthesis, Characterization and Biological Activity of Schiff Bases Chelates with Mn(II),Co(II),Ni (II),Cu(II) and Hg(II)
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In this paper, some series of new complexes of Mn(II), Co(II), Ni (II) Cu(II) and Hg(II) are prepared from the Schiff bases (L1,L2). (L1) derived from 4-aminoantipyrine and O-phenylene dia mine then (L2) derived from (L1) and 2-benzoyl benzoic acid. Structural features are obtained from their elemental microanalyses, molar conductance, IR, UV–Vis, 1H, 13CNMR spectra and magnetic susceptibility. The magnetic susceptibility and UV–Vis, IR spectral data of the ligand (L1) complexes get square–planar and tetrahedral geometries and the complexes oflig and (L2) get an octahedral geometry. Antimicrobial examinations show good results in the sharing complexes.

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Publication Date
Wed Aug 10 2022
Journal Name
Biochemical And Celluler Archives
Synthesis, Characterization and evaluation the biological activity of some new Schiff bases and 1,3-oxazepin derivatives derived from secondary cyclic amine
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In this research a new compounds were synthesized started from compound 1 which was synthesized from two moll of piperidine (secondary cyclic amine) with dichloro acetic acid, compound 1 reacted by condensation reaction with methanol and H 2 SO 4 as a catalyst to give the ester compound 2. Compound 2 was reacted with hydrazine hydrate 80 % to give compound 3 , then the compounds 4-13 were synthesized from refluxing of compound 3 with the selected aldehydes and ketones via using few drops of glacial acetic acid, finely step the compounds 4-13 were reacted with phtalic anhydride to give compounds 14-23.. All these compounds were characterized by using of melting point, FTIR, 1 HNMR and mass spectroscopy. Scheme 1 and Scheme 2 shown the all re

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Publication Date
Wed Aug 18 2010
Journal Name
Journal Of Kerbala University
Synthesis of New Type of Sugar Ligands Starting from D-Glucose And Screening Their Biological Activity
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Publication Date
Sun Sep 25 2022
Journal Name
International Journal Of Drug Delivery Technology
Synthesis, Characterization and Evaluation of Antimicrobial Activity of Few New Heterocyclic Compounds Derived from Nicotinic Acid
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New schiff bases series (VIII) a-e and 1,3-thiazolidin-4-one derivatives (IX) a-e containing the 1,2,4-triazole and 1,3,4-thiazazole rings were synthesized and screening their biological activities. These compounds were identified via Fourier transform infrared (FT-IR) spectra, some via Proton nuclear magnetic resonance (1H-NMR) and mass spectra. The biological results indicated that all of these compounds did not reveal antibacterial effectiveness against (Escherichia coli and Klebsiella species) (G-). Some of these compounds showed moderate antibacterial activity against (Staphylococcus aureus, and Staphylococcus epidermidis) (G+), and all compounds exhibited moderate activity against Candida albicans.

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Publication Date
Sat Sep 30 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Performance Auditing Of Hotels Sector Under (Covid-19) And It’s Reflection On The Outcome Of Activity
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Abstract:

              The hotel sector is one of the most vital sectors exposed to risks, and the authorities concerned with control must take their active and influential role in putting the hotel sector on the right track and compatible with the internationally approved approaches, and the importance of auditing the performance of the hotel sector in light of the (Covid-19) pandemic is embodied in the fact that it gives a clear and realistic picture to the management and regulatory bodies about the performance and activities of this sector and the shortcomings and deviations that must be addressed, and also helps government decision makers to ob

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