The paper aims to identify the impact of discrete realization strategy in the development of reflective thinking among students: (males/females) of Qur'an and Islamic education departments for the course of Islamic jurisprudence according to the variability of sex. The researcher used the experimental approach and adopted an experimental determination with a set part of the two groups (experimental and controlled). He selected the sample deliberately which consists of (147) students spread over four classes (experimental males/ experimental females/ controlled males/ controlled females), and it took last for an academic year of (2010-2011). He, then, prepared a post test to measure the reflective thinking with his five skills (skill of optical vision, skill of detecting fallacies, skill of reaching conclusions, skill of convincing explanations, and skill of proposed solutions) in the course of (Islamic jurisprudence) which consists of (25) items of multiple choice, each one has (5) options. The validity of the items was verified with sincerity of the content, certified arbitrators, internal consistency, as well as applied to the external exploratory sample to measure the level of difficulty, strength of the discriminatory, and effective of the alternatives, were all items acceptable according to the dependable standards. Then, the researcher comes out with the stability coefficient by the retail midterm, in which level of stability reached (0.79) according to Pearson equation, and it reached (0.88) after correction according to Spearman - Brown equation, and this is a good stability coefficient for the test. Moreover, after processing data for the test of the post reflective thinking of the sample concerned in the paper by using (t-test) for two independent samples, the study showed a statistically significant difference between the two groups, and in a favour for the experimental group that studied according to the strategy of (discrete realization) in all groups of (males/ females).
In this paper, the class of semi
In this paper, the process of comparison between the tree regression model and the negative binomial regression. As these models included two types of statistical methods represented by the first type "non parameter statistic" which is the tree regression that aims to divide the data set into subgroups, and the second type is the "parameter statistic" of negative binomial regression, which is usually used when dealing with medical data, especially when dealing with large sample sizes. Comparison of these methods according to the average mean squares error (MSE) and using the simulation of the experiment and taking different sample
... Show MoreThe present study aims at scrutinizing the impoliteness types, causes, and purposes utilized by Iraqi English language learners when refusing marriage proposals. Thus, it attempts to answer the questions: (1) what are the impoliteness formulas used by the Iraqi learners of English in refusing marriage proposals?, and (2) What are their impoliteness triggers/causes and the purposes? The study is significant in bridging the gap that few linguistic types of research concentrate on studying intentionality and emotions allied with impoliteness. Data were collected from 35 Iraqi learners of English responding to 6 situations of marriage. The data were analyzed using Culpeper’s (2011) formulas of impoliteness and Bousfield’s (2007) impolite
... Show MoreModern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the
... Show MoreThis work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.
The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20
... Show MoreThe present study aims at scrutinizing the impoliteness types, causes, and purposes utilized by Iraqi English language learners when refusing marriage proposals. Thus, it attempts to answer the questions: (1) what are the impoliteness formulas used by the Iraqi learners of English in refusing marriage proposals?, and (2) What are their impoliteness triggers/causes and the purposes? The study is significant in bridging the gap that few linguistic types of research concentrate on studying intentionality and emotions allied with impoliteness. Data were collected from 35 Iraqi learners of English responding to 6 situations of marriage. The data were analyzed using Culpeper’s (2011) formulas of impoliteness and Bousfield’s (2007) imp
... Show MoreThe 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
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