While many educators are highly focused on state test, it is important to consider that
over the course of a year, instructors can build in many opportunities to assess how learners
are learning. Therefore, assessment techniques are considered a good method to get benefit
for both instructors and learners in the process of teaching and learning. The sample consists
of 27 learners who participated in TOEFL training course in the Development and Continuous
Education Centre. Validity and reliability were verified.
To fulfill the aims and verify the hypothesis which reads as follows” It is hypothesized
that the TOEFL learners' scores will not be increased after TOEFL course training.” T-test
for two dependent samp

The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t

Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

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

Background: Various fluids in the oral environment can affect the surface roughness of resin composites. This in vitro study was conducted to determine the influence of the mouth rinses on surface roughness of two methacrylate-based resin (nanofilled and packable composite) and siloraine-based resin composites.

Materials and methods: Disc-shaped specimens (12 mm in diameter and 2mm in height) were prepared from three types of composi

To achieve optimal plant growth and production under salt stress, some products were added in adequate quantities to give a good yield, especially bean plants which are sensitive to salinity. For this purpose, this experiment was carried out during the spring growing season in 2022 in Baghdad, to study the effects of humic acid, cytokinin, arginine and their interaction with 9 parameters that reflect the overall traits of vegetative growth and yield of common bean plants Phaseolus vulgaris L. var. Astraid (from MONARCH seeds, China). The factorial design with 3 replicates was used, each with 7 plants treated via foliar spraying or by addition to the soil. The first factor included three groups; H0, H1 and H2 (0, 6, 12 Kg.h^-1 H