A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was

Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage

This paper describes a newly modified wind turbine ventilator that can achieve highly efficient ventilation. The new modification on the conventional wind turbine ventilator system may be achieved by adding a Savonius wind turbine above the conventional turbine to make it work more efficiently and help spinning faster. Three models of the Savonius wind turbine with 2, 3, and 4 blades' semicircular arcs are proposed to be placed above the conventional turbine of wind ventilator to build a hybrid ventilation turbine. A prototype of room model has been constructed and the hybrid turbine is placed on the head of the room roof. Performance's tests for the hybrid turbine with a different number of blades and different values o

The automatic estimation of speaker characteristics, such as height, age, and gender, has various applications in forensics, surveillance, customer service, and many human-robot interaction applications. These applications are often required to produce a response promptly. This work proposes a novel approach to speaker profiling by combining filter bank initializations, such as continuous wavelets and gammatone filter banks, with one-dimensional (1D) convolutional neural networks (CNN) and residual blocks. The proposed end-to-end model goes from the raw waveform to an estimated height, age, and gender of the speaker by learning speaker representation directly from the audio signal without relying on handcrafted and pre-computed acou

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Background: Ruptured uterus is a catastrophic event to both
mother and her fetus. Apart from maternal and fetal mortality
rates, the incidence of rupture of uterus is often taken as an
index of the standard of obstetric care.
Objective: To determine the frequency, causes, management
outcome of ruptured uterus at Al Batool maternity hospital.
Method: The study was conducted in the department of
obstetrics and gynecology at Al Batool maternity hospital
Mosul-Iraq over a period of three years from October 1st 2002
to August 30th 2005. All the cases of uterine rupture presented
during the study period were recorded and managed in the
department. Data was recorded on designed forms.
Results: Thirty nine cas

Objective: The present study aimed to evaluate the occupational health hazards that face health care providers in Sulaimani City.

Methods: A cross-sectional study conducted utilizing quantitative data collection methods. It involved 159 respondents including Physicians, Pharmacists, Medical assistants, Laboratory Instructors and Nurses who worked in 8 major health facilities in Sulaimani city, Kurdistan region, Iraq.

Results: Nurses were the most susceptible group to sharp related injuries 13.84%, cuts and wounds 10.69% than the others and they were more experiencing verbal abuse in the workplace 15%. Laboratory instructors represent the most exposed group

The current study aims to assess the effectiveness of the cognitive-behavioral programs in reducing stuttering and social anxiety among high-school students. The researchers used the experimental design. The sample consists of (20) male students who reported the highest score on the stuttering severity scale and social anxiety scale. The sample was divided into experimental and control groups (each group consists of 10 participants). The researcher used the type and severity of stuttering scale developed by Onslow et al (2003), translated by Mahmoud Ismail and the social anxiety scale was prepared by the authors. The results showed that there are statistically significant differences in pre-post and follow-up tests amongst the experiment