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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
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Data Mining Techniques for Iraqi Biochemical Dataset Analysis
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This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Modeling The Power Grid Network Of Iraq
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Recently, the theory of Complex Networks gives a modern insight into a variety of applications in our life. Complex Networks are used to form complex phenomena into graph-based models that include nodes and edges connecting them. This representation can be analyzed by using network metrics such as node degree, clustering coefficient, path length, closeness, betweenness, density, and diameter, to mention a few. The topology of the complex interconnections of power grids is considered one of the challenges that can be faced in terms of understanding and analyzing them. Therefore, some countries use Complex Networks concepts to model their power grid networks. In this work, the Iraqi Power Grid network (IPG) has been modeled, visua

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Economic Benefits for the Application of Standards of Sustainability in Construction Projects
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In this research, that been focused on the most important economic benefits expected when applying the three standards of sustainability in construction projects (economic, environmental and social). Fuzzy AHP, a multi-decision decision-making technique for evaluating construction projects. Which when used we get the speed and accuracy in the results. Using this technique will reduce uncertainties decisions significantly (fuzzy environment), that found in most projects .The results of the data analysis showed  that the economic standards take the greatest relative importance (60%) among the three sustainability standards. Therefore, the implementation of any standards need a cost so the economic benefit of any proje

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Publication Date
Thu Apr 25 2019
Journal Name
Engineering And Technology Journal
Improvement of Harris Algorithm Based on Gaussian Scale Space
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Features is the description of the image contents which could be corner, blob or edge. Corners are one of the most important feature to describe image, therefore there are many algorithms to detect corners such as Harris, FAST, SUSAN, etc. Harris is a method for corner detection and it is an efficient and accurate feature detection method. Harris corner detection is rotation invariant but it isn’t scale invariant. This paper presents an efficient harris corner detector invariant to scale, this improvement done by using gaussian function with different scales. The experimental results illustrate that it is very useful to use Gaussian linear equation to deal with harris weakness.

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Publication Date
Sat Apr 01 2017
Journal Name
Iraqi National Journal Of Chemistry
Synthesis, anti-bacterial and anti-cancer activities of Some Antipyrine Diazenyl Benzaldehyde Derivatives and AntipyrineBased Heterocycles
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The present study envisaged utilizing 4-aminoantipyrine as key intermediate for the synthesis of some new derivatives bearing anti-bacterial and anti-cancer activities moieties viz., antipyrine diazenyl benzaldehydes 2(ad) which were obtained by coupling of diazotized 4-aminoantipyrine (1) with substituted benzaldehydes at 0◦C (iced) temperature. The other antipyrine derivatives where containing bis heterocycles like bis thiazolidinone-antipyrine (4), bis imidazolidinone -antipyrine (5) and bis azetidinone -antipyrine (6).These compounds were prepared through the reaction between 4- aminoantipyrine and terephthaldicarboxaldehyde to get (3) which were reacted with mercaptoacetic acid , glycine or chloroacetyl chloride separately to get com

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Publication Date
Fri Dec 15 2023
Journal Name
Al-academy
The role of the theatrical technical supervisor in developing the skills of preparatory stage learners
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The current study aimed to identify the role of the theatrical technical supervisor in developing and enhancing the skills of middle school students in Baghdad. The sample consisted of 73% of the original community of theatrical technical supervisors, randomly selected from those working in the first, second, and third educational directorates in the Rassafa and Karkh areas. The sample size was 32 theatrical technical supervisors. The study used a questionnaire to collect data on three axes: the cognitive skills developed by the theatrical technical supervisor, the voice and speech skills developed by the supervisor, and the body movement skills developed by the supervisor. The results showed that the theatrical technical supervisor play

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Publication Date
Sun Jul 13 2025
Journal Name
Al–bahith Al–a'alami
Propaganda speech in the Gulf press articles about the Qatari crisis An analytical study in the political articles published in the newspapers (Riyadh) Saudi Arabia and (Al-Ittihad) UAE from 5/6/2017 to 5/9/2017
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Propaganda speech in the Gulf press articles about the Qatari crisis, an analytical study in the political articles published in the newspapers (Riyadh) Saudi Arabia and (Al-Ittihad) UAE from 5/6/2017 to 5/9/2017, University of Baghdad, College of Media, Press Department, 2019. The problem of the research was to monitor the contents of propaganda messages to Saudi Arabia and the UAE regarding the Qatari crisis, especially with the escalation of propaganda media campaigns between the four boycotting countries on the one hand and Qatar on the other hand, in light of crises and conflicts in the Gulf region and the Arab region in general. The researcher used the survey method to answer the research questions and achieve its results. This res

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Publication Date
Thu Jun 20 2024
Journal Name
Fizjoterapia Polska
Development Artificial Neural Network (ANN) computing model to analyses men's 100¬meter sprint performance trends
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Coaches 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

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Publication Date
Thu Apr 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Polypropylene/Pt Nanocomposite: Synthesis, Characterization and Study the Cytotoxic Effects
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     This paper presents the synthesis of a polypropylene nanocomposite. The  nanocomposites were characterized using different techniques: atomic electron microscopy (AFM), surface shape was evaluated by (SEM),(EDS),(XRD) and (FTIR). The study showed that the platinum nanocomposite had a fatal effect on both strains of bacteria used, as well as on the growth of fungi. The compound tested showed antioxidant properties moderate activity was found. The mentioned material were evaluated in normal cell line HdFn (Human Dermal Fibroblasts, neonatal)  and breast cancer MCF-7 cancer cell line , by MTT assay for study cytotoxic effects, morphological changes, all experiments were conducted on cell lines by using the

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Agricultural And Statistical Sciences
A COMPARISON BETWEEN SOME HIERARCHICAL CLUSTERING TECHNIQUES
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In this paper, some commonly used hierarchical cluster techniques have been compared. A comparison was made between the agglomerative hierarchical clustering technique and the k-means technique, which includes the k-mean technique, the variant K-means technique, and the bisecting K-means, although the hierarchical cluster technique is considered to be one of the best clustering methods. It has a limited usage due to the time complexity. The results, which are calculated based on the analysis of the characteristics of the cluster algorithms and the nature of the data, showed that the bisecting K-means technique is the best compared to the rest of the other methods used.

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