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.
To understand what the arts in general, and plastic arts in particular, have to do, it is necessary to know how they perform, not only that, but also to know their history, which we should understand at least in general terms. Which in turn gives an image of the standards of taste prevailing in each age, and some of the social and historical relationship of each era, and the cultural expression of that era, which is shown in the arts. We need to understand that the arts of each stage, although different from each other, yet remain interrelated in what we see through the effects that appear through the succession of times, which creates certain artistic traditions, inherited by one generation after the other. The research in this field de
... Show MorePowder extracts hot water from local ground beef and studied inhibitory effectiveness of powder and extracts to the concentration of the aqueous extract hot Gulf students
The study aimed to evaluating the inhibitory activity of apigenin extracted from Salvia officinalis leaves on the growth of L20B cancer cell in vitro, and through two incubation periods; 48 and 72 hours. Accordingly, eight concentrations (1.56, 3.13, 6.25, 12.5, 25.0, 50.0, 100.0 and 200.0 micromol) of apigenin and similar concentrations of vitamin C and carbon tetrachloride (CCl4) were tested. The apigenin revealed its significant inhibitory potentials against the growth of L20B cell line, especially at the low concentrations (1.56, 3.13 and 6.25 micromol) and at 72 incubation period in comparison with vitamin C and CCl4.
The research problem revolves around the Iraqi public's use of digital television and cinematic websites، and their importance to the academic study and society، as it examines the public's relationship with these websites، usage habits، and the reasons for their interaction with them. And for the prevalence of this phenomenon of use، it was necessary to address the intensity، intentionality، and timing of use to theoretically root the subject of the study، which is one of the modern studies in Iraq and the Arab world. The survey approach، where the research was based on the theory of uses and gratifications that confer positivity and activity on the mass media audience.
The researchers designed
... Show MoreThe alfalfa plant, after harvesting, was washed, dried, and grinded to get fine powder used in water treatment. We used the alfalfa plant with ethanol to make the alcoholic extract characterized by using (GC-Mass, FTIR, and UV) spectroscopy to determine active compounds. Alcoholic extract was used to prepare zinc nanoparticles. We characterized Zinc nanoparticles using (FTIR, UV, SEM, EDX Zeta potential, XRD, AFM). Zinc nanoparticle with Alfalfa extract and alfalfa powder were used in the treatment of water polluted with inorganic elements such as Cr, Mn, Fe, Cu, Cd, Ag by (Batch processing). The batch process with using alfalfa powder gets treated with Pb (51.45%), which is the highest percentage of treatment. Mn (13.18%), which is the
... Show MoreThis research asks what are negative social behaviours in the Kurdistan Region of Iraq (KRI) raised by the talk shows on the (NRT) channel? Furthermore, it aims to identify the most significant themes addressed by talk shows on the (NRT) channel regarding negative social behaviours in the KRI by using the content analysis approach through non-random purposive sampling to understand the dialogue contents that dealt with this subject. This study has reached a set of results: through its talk shows, the (NRT) channel attempts to create a media vision about the spread of negative social behaviours in the KRI and stand up to the dangers associated with these behaviours. At the same time, those programs tried to marginalize the behaviours that
... Show MoreThis experiment presented essential oils by GC/MS, pigment content, and their antioxidant activities as well as sensory evaluation of delight samples. Limonene (66.88%) was the most prevalent yield. The peels of clementine had DPPH and ABT Scavenging activity. All levels of pigment extract had better scores for all sensory values and recorded acceptable scores in terms of appearance, color, aroma, and overall acceptability compared to control delight. Besides, delight samples containing 15 mg astaxanthin pigment extract showed maximum sensory scores compared to other samples and control delight. On the other hand, the product was less acceptable to the panelists compared to control in the case of the addition of 3.75 mg astaxanthin pigme
... Show MoreUpper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin
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