The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm has been developed for clustering purpose. Mainly, the purpose of using modified K-means clustering technique is to group the similar features into (K) templates in order to simulate the differences in the ways that human express each emotion. To evaluate the proposed system, a subset from Cohen-Kanade (CK) dataset have been used, it consists of 870 facial images samples for the seven basic emotions (angry, disgust, fear, happy, normal, sad, and surprise). The conducted test results indicated that SVM classifier can lead to higher performance in comparison with the results of other proposed methods due to its desirable characteristics (such as large-margin separation, good generalization performance, etc.).
<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreBig data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a
... Show MoreNigella sativa seeds (NSS) are reputed traditionally and scientifically as a potent agent that promote milk secretion (galactagogue), but their mechanism of action is studied trivially. One suggestion was that these seeds are bio-transformed to sex hormones within the ovaries. Therefore, this investigation was designated to throw light on the action of these seeds in the absence of ovaries i.e. in male rats. Thirty Norway male albino rats were used in this investigation. They were divided into experimental (n=20,fed NSS 2g/ Kg body weight /day for 14 days) and control (n=10, fed placebo for 14 days). After sacrifice mammary gland and blood samples were obtained. Experimental rats revealed a significant increase (p (0.01>in
... Show MoreWith the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect
... Show Moren-Hexane conversion enhancement was studied by adding TCE (Trichloro-ethylene) on feed stream using 0.3%Pt/HY zeolite catalyst. All experiments were achieved at atmospheric pressure and on a continuous laboratory unit with a fixed bed reactor at a temperature range 240-270◦C, LHSV 1-3h-1, H2/nC6 mole ratio 1-4.
By adding 435 ppm of TCE, 49.5 mole% conversion was achieved at LHSV 1h-1, temperature of 270ºC and H2/nC6 mole ratio of 4, while the conversion was 18.3 mol% on the same catalyst without adding TCE at the same conditions. The activation energy decreased from 98.18 for pure Pt/HY zeolite to 82.83 kJ/mole by adding TCE. Beside enhancement the activity, selectivity and product distribution enhanced by providing DMB (Dimethyl b
The CdSe pure films and doping with Cu (0.5, 1.5, 2.5, 4.0wt%) of thickness 0.9μm have been prepared by thermal evaporation technique on glass substrate. Annealing for all the prepared films have been achieved at 523K in vacuum to get good properties of the films. The effect of Cu concentration on some of the electrical properties such as D.C conductivity and Hall effect has been studied.
It has been found that the increase in Cu concentration caused increase in d.c conductivity for pure CdSe 3.75×10-4(Ω.cm)-1 at room temperatures to maximum value of 0.769(Ω.cm)-1 for 4wt%Cu.All films have shown two activation energies, where these value decreases with increasing doping ratio. The maximum value of activation energy was (0.319)eV f
Cold atmospheric plasma (CAP) is used widely in medical and biological fields because of non-thermal effected. Direct application of plasma is preferred in medical functions, so, direct application of cold plasma has obtained by the floating electrode dielectric barrier discharge (FE-DBD) system. The purpose of this paper to review the effect of (CAP) on the reproductive hormones (testosterone, LH, E2, progesterone, for male rats. The study appeared that no significant effect on E2 and progesterone hormone for all time of exposure, besides this significant difference in LH hormone (P<0.05) at 15 sec, (P<0.0001) at 30, 90 sec and (P<0.001) at 60 sec of exposure to plasma. Added to that significant difference (P<0.01) at 15, 30, 60 sec and no
... Show MoreFilms of CdSe have been prepared by evaporation technique with thickness 1µm. Doping with Cu was achieved using annealing under argon atmosphere . The Structure properties of these films are investigated by X-ray diffraction analysis. The effect of Cu doping on the orientation , relative intensity, grain size and the lattice constant has been studied. The pure CdSe films have been found consist of amorphous structure with very small peak at (002) plane. The films were polycrystalline for doped CdSe with (1&2wt%) Cu contents and with lattice constant (a=3.741,c=7.096)A°, and it has better crystallinty as the Cu contents increased to (3&5wt%) Cu. The reflections from [(002), (102). (110), (112), and (201)]planes are more prominen
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