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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 Jan 01 2022
Journal Name
Food Science And Technology
Study on herbicide residues in soybean processing based on UPLC-MS/MS detection
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Publication Date
Sun Nov 01 2020
Journal Name
2020 2nd Annual International Conference On Information And Sciences (aicis)
An Enhanced Multi-Objective Evolutionary Algorithm with Decomposition for Signed Community Detection Problem
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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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Publication Date
Sat Mar 21 2020
Journal Name
Journal Of Engineering
Development of Iraqi license plate recognition system based on Canny edge detection method
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny Edge detection algo

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Publication Date
Sat Nov 02 2013
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Images Segmentation Based on Fast Otsu Method Implementing on Various Edge Detection Operators
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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Wed Aug 28 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
A Novel Anomaly Intrusion Detection Method based on RNA Encoding and ResNet50 Model
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Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

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Publication Date
Sat Dec 29 2018
Journal Name
Journal Of Global Pharma Technology
Synthesis, Characterization and Study Biological Activity of Some New Compounds Derived From Phthalic Anhydride
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In this research , phthallic anhydride ring is opened with 4-methyl aniline and acetone as a solvent to results the compound [I] that reacted with dimethyl sulphate and anhydrous sodium carbonate formation to phathalate ester [II], while the acid hydrazide compound [III], was obtained from mixed the compound [II]with hydrazine hydrate, Synthesis four type of shiff bases[IV]a-d was synthesized from the reaction of acid hydrazide [III] with aromatic aldehyde or ketone , when reacted Shiff bases with phthalic anhydride or naphthalicanhydride,I get eight derivatives of oxazepine [V]a-d , [VI]a-d. The bacterial activity of the new compounds studied by four species of bacteria: Esherichia Coli, Enterobactecloacae (Gram negative) and staphylococcu

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Using the international standard for Training (ISO-10015) to Improve the Quality of the Control Activity – A Survey Study at the Federal Board of Supreme Audit.
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The great  importance of training made it as an investment for the organization, and assert the Quality of performance which support it by prepare the employee to the Current and future Jobs . The Research problem a rounded about How to measure the impact of training based on (ISO 10015) and its effect on the Quality of performance , How to evaluation the results of training to attained the training goals . The Research aims to find out the effects of application of international standard guidelines (ISO 10015) to attained the quality of audit work achieved in the Federal Board of Supreme Audit. The Research sought to achieve a number of objectives cognitive and applied on the basis of four key assumptions, and other su

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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Synthesis of New Heterocyclic Compounds Derived from Anthrone and Evaluation of Their Biological Activity
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In this research, Schiff bases derived from the reaction of anthrone with different heterocyclic amines have been described. The resulted Schiff base compounds were reacted with various nucleophiles in order to obtain new heterocyclic derivatives. Chemical structures of all products were confirmed by IR, 1H-, 13C-NMR spectral data and elemental analysis. All synthesized compounds were in vitro tested against a standard strain of pathogenic microorganism including Gram +ve bacteria (Staphylococcus aureus), Gram –ve bacteria (Escherichia coli), and fungi (Candida albicans).

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