Item Difficulty and Item Discrimination Coefficient for School and College Ability Tests (SCAT) Advanced Form in Classical Test Theory (CTT) and Item Response Theory (IRT) and the Correlation among Them Mohammad moqasqas Haifa T. Albokai Assistant Professor of Measurement and Evaluation Associate Professor of Measurement and Evaluation College of Education, Taibah University The aim of this study was to study the item difficulty and item discrimination of the SCAT (advance form) with CTT, and IRT, and to study the correlation among them. To do this, the researchers used the data of their previous study, which conducted in (2011). It consisted of (3943) subject. Then, they used two-statistical programs (TAP, Bilog-MG-3) to obtain the item

The morphometric parameters of Acinopus (Acinopus) laevigatus Ménétriés, 1832 (Coleoptera, Carabidae) were studied and their altitudinal variability was assessed. The length of head is the most variable, and the smallest value of the coefficient of variation is observed for the width of elytra. The length of body parts (head, pronotum, elytra) were more variable compared to their width. The correlation relationship between the morphometric parameters of different parts of the body was analyzed. A high correlation was found between the elytra length (EL) and the total body length (BL) (r=0.93), and the lowest correlation was found between the elytra width (EW) and the pronotum length (PL) (r=0.57). According to all measurement indicato

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

We have investigated twenty five patients with type-2 diabetes mellitus aged (35-60) years and fifteen healthy persons as control group to detect Anti-Helicobacter pylori IgG antibody. All studied groups were carried out to measure fasting blood sugar, anti- Glutamic acid decarboxylase (GAD), anti-? islets cells antibody by IFAT, Anti-H. pylori IgG antibody by ELISA technique. There was significant elevation in the concentration of fasting blood sugar than in control group (P < 0.05), the patients had negative results for anti-GAD antibody and anti- ? islets cells antibody, there were significant differences (P < 0.05) of anti-H. pylori IgG antibody in 28 % of patients had type-2 diabetes than control group. This lead to suggestion that typ

Abstract

The study aimed: To assess the level of trainers' knowledge about the application of strategies and to find out the relationship between Trainer's knowledge and their socio-demographic characteristics.

Methodology: Using the pre-experimental design of the current study, for one group of 47 trainers working at the private Autism Centers in Baghdad, data was collected from 8/January / 2022 to 13 /February /2022. Using non-probability samples (convenient samples), self-management technology in which trainers fill out the questionnaire form themselves was used in the data collection process; it was analyzed through descriptive and inference statistics.

Abstract

The current research aims to examine the effectiveness of a training program for children with autism and their mothers based on the Picture Exchange Communication System to confront some basic disorders in a sample of children with autism. The study sample was (16) children with autism and their mothers in the different centers in Taif city and Tabuk city. The researcher used the quasi-experimental approach, in which two groups were employed: an experimental group and a control group. Children aged ranged from (6-9) years old. In addition, it was used the following tools: a list of estimation of basic disorders for a child with autism between (6-9) years, and a training program for children with autism

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

The research aims to test the effect of the behavioral factors (intangible) represented by an explanatory variable represented by organizational silence and a responsive variable of quality of Function life. The problem was the negative effects of the organizational silence on the morale of the employees and consequently their performance and the quality of function life. To collect the data and information needed to measure the two variables of research conducted in the health center / Sulaikh by taking a sample of (40) employees to test the hypotheses of research through the survey of their views, using statistical tools non parametric using the program. The most important recommendations were the establishment of training workshops fo

The electron correlation effect for inter-shell have been analysed in terms of Fermi hole and partial Fermi hole for Li-atom in the excited states (1s² 3p) and (1s² 3d) using Hartree-Fock approximation (HF). Fermi hole Δf(r₁₂) and partial Fermi hole Δg(r₁₂ ,r₁) were determined in position space. Each plot of the physical properties in this work is normalized to unity. The calculation was performed using Mathcad 14 program.

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation