Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression alg

The present search aims to develop a test for selective attention, cognitive load and thinking mistakes and measuring these concepts among Baghdad university students. To make a comparison between the selective attention, cognitive load, and the mistakes of thinking among students in term of gender. To identify the relationship among the selective attention, cognitive load and the mistakes of thinking of university students. To achieve these purposes, the searcher has developed a test for selective attention, cognitive load, and the mistakes of thinking. Then, these tools were applied to a sample of (200) university students were selected from (21) college. The researcher used t-test of one sample, t-test of two independent

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

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

Objective: to assess the Nursing College students' health-protective behaviors (HPBs) and their
association with some sociodemograghic characteristics.
Methodology: A sample of 100 Students (males and females) was selected through a systematic
random sample that were at the third and fourth year of Nursing College in Baghdad University for the
period of April 1st through April 30th 2007. Data were collected through the use of a self-report
instrument that used for Americans as HPBs assessment that contains 23 items. Reliability and validity
of the tool were determined through a pilot study. A descriptive statistical approach (frequencies and
percentages) and inferential statistical approach (chi-square) were used for

In this paper, RBF-based multistage auto-encoders are used to detect IDS attacks. RBF has numerous applications in various actual life settings. The planned technique involves a two-part multistage auto-encoder and RBF. The multistage auto-encoder is applied to select top and sensitive features from input data. The selected features from the multistage auto-encoder is wired as input to the RBF and the RBF is trained to categorize the input data into two labels: attack or no attack. The experiment was realized using MATLAB2018 on a dataset comprising 175,341 case, each of which involves 42 features and is authenticated using 82,332 case. The developed approach here has been applied for the first time, to the knowledge of the authors, to dete

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

Leap Motion Controller (LMC) is a gesture sensor consists of three infrared light emitters and two infrared stereo cameras as tracking sensors. LMC translates hand movements into graphical data that are used in a variety of applications such as virtual/augmented reality and object movements control. In this work, we intend to control the movements of a prosthetic hand via (LMC) in which fingers are flexed or extended in response to hand movements. This will be carried out by passing in the data from the Leap Motion to a processing unit that processes the raw data by an open-source package (Processing i3) in order to control five servo motors using a micro-controller board. In addition, haptic setup is proposed using force sensors (F

The research aims to identify the effect of teaching according to the augmented reality on the technique of the visual thinking skills among scientific fifth-grade students in a biology course. In order to achieve the goal of the research, the researcher adopted the experimental approach with the partial set of the two equal groups with the dimensional test of visual thinking skills, The research population represented all the scientific students of the fifth grade for morning government schools affiliated to the General Directorate of Education of Baghdad / Karkh II, alshakerin preparatory for boys was chosen intentionally, in which two groups were chosen for this study, one group is chosen randomly as the control group via lottery, whe