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),

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo

Background: The posterior slope of the articular eminence of completely edentulous patients compared to patients with maintained occlusion shows significant flattening. This study aimed to correlate between the flattening of the posterior slope of the articular eminence, with dental status, age, genders, on both sides using computed tomography. Materials and Methods: The sample of the present study was a total of 117 Iraqi subjects, who admitted to the maxillofacial department at Al-Sadr Teaching Hospital in Al-Najaf city. The examination was performed on CT scanner; the eminence inclination was measured in two methods using sagittal section. Results: Clinically, the inclination of articular eminence was higher in edentulous subjects than i

Objectives: Dickkopf-1 (DKK-1) is WNT/b-catenin pathway antagonist which plays a detrimental role in the development of diabetic retinopathy (DR). This research aimed to assess serum DKK-1 levels in diabetic patients who have and have not developed DR and, compare them with the control subjects finding out whether we can use it as an indicator for DR early diagnosis and to find out which one of the widely used two groups of antidiabetic treatments had the greater effect on this biomarker and hence on the progression of DR. Methods: The study participants were divided into two subgroups: First, 70 patients (36 male, 34 female) with type 2 diabetes mellitus, among them 35 patients diagnosed with DR and 35 with no evidence of DR, and s

A new method, simple and sensitive was utilized in determining mebeverine – HCl (MB-HCl) (3, 4-Dimethoxy benzoic acid ethyl 2, 4 methoxy4-phenyl-1-methyl ethyl amino-butyl ester) in pure and pharmaceutical formulations via utilization this multiple continuous flow cell. The method is dependent on genesis for complex of ion pair(4-((3, 4-dimethoxybenzoyl) oxy)-N-ethyl-N-(1-(4-methoxyphenyl) propan-2-yl) butan-1-aminium-2-hydroxy-3,5- dinitrobenzoate) among mebeverine–HCl (MB-HCl) and 3,5-Dinitrosalicylic acid (3,5-DNSA) in ammonium acetate middle to configure a whiteish yellow precipitate compound via utilizing multiple continuous flow cell that works as a solo flow cell with 4S×3 – 3D analyzer. Optimum parameters were studied to rai

The use of foam electrodes as a cathode has proven its efficiency in wastewater treatment. In this study, methyl orange (MO) was treated by Electro-Fenton technology (EFT) using a copper foam (Cf) as a cathode. EFT was an advanced strategy for MO degradation, which accomplished excellent degradation efficiency (%ReMO) exceeded 98% over 35 min treatment period at prime conditions using 0.124 mM of iron salts (FeSO4.7H2O), 0.3 LPM of air flow, 0.2 mA/cm2 of current density (CD), and initial pH of 3.0. The outcomes showed that the air flow rate had the main impact on the %ReMO. Furthermore, the contribution of anodic oxidation (AO) to dye removal was investigated to distinguish its role relative to the EFT mechanism, revealing that the MO degr

The crude enzyme Nattokinase produced by Bacillus subtilis was used in ripening cheddar cheese by adding three concentration of enzyme 80, 160 and 320mg/Kg beside the control treatment without enzyme, the product was checked for three months to determine humidity, protein, fat, non-protein nitrogen, soluble nitrogen and pH, sensory evaluation was conducted, it was noticed that the variety in protein percentages and the soluble nitrogen percentage during second month of ripening for T2, T3 and T4 treatments were (11.2, 15.54 and 18.48) respectively, in comparison with control which was 7.6%, while in the third month it was (17.37, 20.67 and 22.26) respectively, in comparison with control which was only 10%, on the other hand, non-protein

Artificial neural networks usage, as a developed technique, increased in many fields such as Auditing business. Contemporary auditor should cope with the challenges of the technology evolution in the business environment by using computerized techniques such as Artificial neural networks, This research is the first work made in the field of modern techniques of the artificial neural networks in the field of auditing; it is made by using thesample of neural networks as a sample of the artificial multi-layer Back Propagation neural networks in the field of detecting fundamental mistakes of the financial statements when making auditing. The research objectives at offering a methodology for the application of theartificial neural networks wi