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Speech Emotion Recognition Using Minimum Extracted Features
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Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF), k-Nearest Neighbor (k-NN), Sequential Minimal Optimization (SMO), Naïve Bayes (NB), and Decision Tree (DT). The performance of the system validated over Surrey Audio-Visual Expressed Emotion (SAVEE) dataset for seven emotions. The results of the experiments showed given good accuracy compared with the previous studies using a fusion of a few numbers of features with the RF classifier.

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Securing Text Messages Using Graph Theory and Steganography
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      Data security is an important component of data communication and transmission systems. Its main role is to keep sensitive information safe and integrated from the sender to the receiver. The proposed system aims to secure text messages through two security principles encryption and steganography. The system produced a novel method for encryption using graph theory properties; it formed a graph from a password to generate an encryption key as a weight matrix of that graph and invested the Least Significant Bit (LSB) method for hiding the encrypted message in a colored image within a green component. Practical experiments of (perceptibility, capacity, and robustness) were calculated using similarity measures like PSNR, MSE, and

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Image Compression Using 3-D Two-Level Technique
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In this paper three techniques for image compression are implemented. The proposed techniques consist of three dimension (3-D) two level discrete wavelet transform (DWT), 3-D two level discrete multi-wavelet transform (DMWT) and 3-D two level hybrid (wavelet-multiwavelet transform) technique. Daubechies and Haar are used in discrete wavelet transform and Critically Sampled preprocessing is used in discrete multi-wavelet transform. The aim is to maintain to increase the compression ratio (CR) with respect to increase the level of the transformation in case of 3-D transformation, so, the compression ratio is measured for each level. To get a good compression, the image data properties, were measured, such as, image entropy (He), percent r

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
Improving the Properties of Gypsum By Using Additives
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Gypsum Plaster is an important building materials, and because of the availabilty of its raw materials. In this research the effect of various additives on the properties of plaster was studied , like Polyvinyl Acetate, Furfural, Fumed Silica at different rate of addition and two types of fibers, Carbon Fiber and Polypropylene Fiber to the plaster at a different volumetric rate. It was found that after analysis of the results the use of Furfural as an additive to plaster by 2.5% is the optimum ratio of addition to that it improved the flexural Strength by 3.18%.
When using Polyvinyl Acetate it was found that the ratio of the additive 2% is the optimum ratio of addition to the plaster, because it improved the value of the flexural stre

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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of Models (NAGARCH & APGARCH) by Using Simulations
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Simulation experiments are a means of solving in many fields, and it is the process of designing a model of the real system in order to follow it and identify its behavior through certain models and formulas written according to a repeating software style with a number of iterations. The aim of this study is to build a model  that deals with the behavior suffering from the state of (heteroskedasticity) by studying the models (APGARCH & NAGARCH) using (Gaussian) and (Non-Gaussian) distributions for different sample sizes (500,1000,1500,2000) through the stage of time series analysis (identification , estimation, diagnostic checking and prediction). The data was generated using the estimations of the parameters resulting f

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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
Removal of Oil From Wastewater Using Walnut-Shell
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The ability of pulverized walnut-shell to remove oil from aqueous solutions has been studied. It involves two-phase process which consists of using walnut-shell as a filtering bed for the accumulation and adsorption of oil onto its surface. Up to 96% oil removal from synthetic wastewater samples was achieved while tests results showed that 75% of oil can be removed from the actual wastewater discharged from Al- Duara refinery in the south of Baghdad.

 

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Publication Date
Thu Jan 21 2021
Journal Name
Recent Innovations In Chemical Engineering (formerly Recent Patents On Chemical Engineering)
Soap Production Using Vacuum Reactive Distillation: Batch Model
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Introduction: Although soap industry is known from hundreds of years, the development accompanied with this industry was little. The development implied the mechanical equipment and the additive materials necessary to produce soap with the best specifications of shape, physical and chemical properties. Objectives: This research studies the use of vacuum reactive distillation VRD technique for soap production. Methods: Olein and Palmitin in the ratio of 3 to 1 were mixed in a flask with NaOH solution in stoichiometric amount under different vacuum pressures from -0.35 to -0.5 bar. Total conversion was reached by using the VRD technique. The soap produced by the VRD method was compared with soap prepared by the reaction - only method which

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Publication Date
Fri Dec 22 2006
Journal Name
Journal Of Planner And Development
Optimizing the location of banks using the Gis
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the banks are one of the public services that must be available in the city to ensure easy financial dealings between citizens and state departments and between the state departments with each other and between the citizens themselves and to ensure easy access to it, so it is very important to choose the best location for the bank, which can serve the largest number of The population achieves easy access. Due to the difficulty of obtaining accurate information dealing with the exact coordinates and according to the country's specific projection, the researcher will resort to the default work using some of the files available in the arcview program

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Publication Date
Fri Jan 01 2016
Journal Name
Engineering And Technology Journal
Face Retrieval Using Image Moments and Genetic Algorithm
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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Engineering
Reducing Lost Circulation Problem by Using Rice Material
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Drilling fluid loss during drilling operation is undesirable, expensive and potentially hazardous problem.

    Nasiriyah oil field is one of the Iraqi oil field that suffer from lost circulation problem. It is known that Dammam, um-Radoma, Tayarat, Shiranish and Hartha are the detecting layers of loss circulation problem. Different type of loss circulation materials (LCMs) ranging from granular, flakes and fibrous were used previously to treat this problem.  

    This study presents the application of rice as a lost circulation material that used to mitigate and stop the loss problem when partial or total losses occurred.

     The experim

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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