Recognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on using a deep neural network that is generally divided into two critical issues. These are a variation of expression and overfitting. Expression variations such as identity bias, head pose, illumination, and overfitting formed as a result of a lack of training data. This paper firstly discussed the general background and terminology utilized in facial expression recognition in field of computer vision and image processing. Secondly, we discussed general pipeline of deep learning. After that, for facial expression recognition to classify emotion there should be datasets in order to compare the image with the datasets for classifying the emotion. Besides that we summarized, discussed, and compared illustrated various recent approaches of researchers that have used deep techniques as a base for facial expression recognition, then we briefly presented and highlighted the classification of the deep feature. Finally, we summarized the most critical challenges and issues that are widely present for overcoming, improving, and designing an efficient deep facial expression recognition system.
Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems. Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic. Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance. In this study, two different sets of select
... Show MoreElectrochemical Grinding (ECG) process is a mechanically assisted electrochemical process for material processing. The process is able to successfully machine electrically conducting harder materials at faster rate with improved surface finish and dimensional control. This research studies the effect of applied current, electrolyte concentration, spindle speed and the gap between workpiece and tool on hardness and material removal rate during electrochemical grinding for stainless steel 316. The characteristic features of the electrochemical grinding process are explored through Taguchi-design-based experimental studies. The better hardness can be obtained at 10 A of the current, 150 g/l of the electrolyte concentration, 0.3 mm of gap an
... Show MoreThe Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
... Show MoreSmishing is the delivery of phishing content to mobile users via a short message service (SMS). SMS allows cybercriminals to reach out to mobile end users in a new way, attempting to deliver phishing messages, mobile malware, and online scams that appear to be from a trusted brand. This paper proposes a new method for detecting smishing by combining two detection methods. The first method is uniform resource locators (URL) analysis, which employs a novel combination of the Google engine and VirusTotal. The second method involves examining SMS content to extract efficient features and classify messages as ham or smishing based on keywords contained within them using four well-known classifiers: support vector machine (SVM), random
... Show MoreTax state institution regards as one of the largest state institutions implementing the tax rules issuing be legislative body and achieving the goals of tax (financial, economic, social and political). So, the tax management should pay attention to the procedures enabling it to achieve those rules starting from the procedures of tax restrict and ending by tax allocation where the process of assessment the taxation must relaxing on modern methods. The problem of the study raising from that in spite of there is a low obliging the taxable person (registered or not) to submit a declaration about his income and the achieved profit to be the base of taxation˒ where the other ways are secondary ways helping in rejection of t
... Show MoreBackground: This study aimed to determine whether there is a relationship among the bite force with facial dimensions and dental arches in a sample of Iraqi adults with Class I skeletal and dental relations. Materials and methods: Forty dental students (20 males and 20 females) were selected under certain criteria. For those individuals, dental impressions, frontal facial photographs and maximum bite force at molar and incisor regions were taken. The dental arches widths and facial dimensions were measured using the AutoCAD program 2007, while the bite force was determined using special device. Descriptive statistics for the measured variables were performed and gender difference was determined using independent sample t-test, while the rel
... Show MoreThe current research focuses on the extent to which the strategic orientation(entrepreneurial orientation, customer orientation, technology orientation, learning orientation, and investment orientation) affects the learning organization (building common vision, systemic thinking, personal dominance, mental models, team learning)The first hypothesis to test the connection relation between research variables and The second hypothesis was to test the relationship between these variables. In order to ascertain the validity of the hypotheses, the research was based on a questionnaire questionnaire prepared according to a number of In addition to building a fifth sub-variable for the strategic orientation (investment orientation) based
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