Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Background: Complete removal of filling material from the root canal is an essential requirement for endodontic retreatment. The purpose of the present study is to evaluate and compare the dissolving capabilities of various solvents (Xylene, Eugenate Desobturator, Eucalyptol, EDTA and Distilled water (as a control)) on four different types of sealer (Endofill, Apexit Plus, AH Plus and EndoSequence bioceramic sealer). Materials and method: Eighty samples of each sealer were prepared according to the manufacturers' instructions and then divided into ten groups (of 8 samples) for immersion in the respective solvents for 2 and 5 min immersion periods. Each sealer specimen was weighed to obtain its initial mass. The specimens were immersed in

A variety of single-engine driven files and inematics have been introduced to improve the clinical performance of NiTi rotary files. The purpose of this in vitro study was to measure and compare the incidence of dentinal defects after root canal preparation with different single file systems.

This work is concerned with a two stages four beds adsorption chiller utilizing activated carbon-methanol adsorption pair that operates on six separated processes. The four beds that act as thermal compressors are powered by a low grade thermal energy in the form of hot water at a temperature range of 65 to 83 °C.  As well as, the water pumps and control cycle consume insignificant electrical power. This adsorption chiller consists of three water cycles. The first water cycle is the driven hot water cycle. The second cycle is the cold water cycle to cool the carbon, which adsorbs the methanol. Finally, the chilled water cycle that is used to overcome the building load. The theoretical results showed that average cycle cooling power

Among many problems that reduced the performance of the network, especially Wide Area Network, congestion is one of these, which is caused when traffic request reaches or exceeds the available capacity of a route, resulting in blocking and less throughput per unit time. Congestion management attributes try to manage such cases. The work presented in this paper deals with an important issue that is the Quality of Service (QoS) techniques. QoS is the combination effect on service level, which locates the user's degree of contentment of the service. In this paper, packet schedulers (FIFO, WFQ, CQ and PQ) were implemented and evaluated under different applications with different priorities. The results show that WFQ scheduler gives acceptable r

In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc