The present study aimed to identify the extent to which the content of social and national studies courses was included in interactive thinking maps in the educational stages in the Kingdom of Saudi Arabia, and to achieve the goal of the study, the researcher used the descriptive and analytical approach, and the study tool used consisted of a content analysis card; Where it included a list of the types of thinking maps, where the study sample consisted of all social and national studies courses at the elementary and intermediate levels, and it is (12) books for the student in its first and second parts, and after verifying the validity and reliability of the tool, it was applied to the study sample, and the study reached conclusions, including: The percentage of inclusion focused Thinking maps at the school level, each of the intermediate stage in the first and second semesters (54.9%), followed by the elementary stage (45.1%). The percentage of inclusion of thinking maps at the level of classroom arrangement in the first semester of elementary school ranked first with a percentage (30.6%), and with a high degree of availability, followed by the first and second semester of intermediate school in second place with a percentage (28.9%), (26.0) %), With medium availability, then the rest of the chapters with low availability. The order of thinking maps came in first place: the tree map was ranked first, with a total inclusion percentage in the primary and middle stages (37.0%), with a high degree of availability, then the flow chart came in second place with a percentage (19.7%), with a medium degree of availability, followed by the rest of the thinking maps with a degree Low availability. The study recommended that thinking maps should be included in a balanced and in-depth manner in all social and national studies courses at the different educational stages and more broadly, to conduct similar studies on different educational stages and other decisions.
In this paper, we apply the notion of a bipolar fuzzy n-fold KU-ideal of KU- algebras. We introduce the concept of a bipolar fuzzy n-fold KU-ideal and investigate several properties. Also, we give relations between a bipolar fuzzy n- fold KU-ideal and n-fold KU-ideal. The image and the pre-image of bipolar fuzzy n-fold KU-ideals in KU-algebras are defined and how the image and the pre- image of bipolar fuzzy n-fold KU-ideals in KU-algebras become bipolar fuzzy n- fold KU-ideals are studied. Moreover, the product of bipolar fuzzy n-fold KU- ideals in Cartesian product KU-algebras is given.
In this paper we present the first ever measured experimental electron momentum density of Cu2Sb at an intermediate resolution (0.6 a.u.) using 59.54 keV 241Am Compton spectrometer. The measurements are compared with the theoretical Compton profiles using density function theory (DFT) within a linear combination of an atomic orbitals (LCAO) method. In DFT calculation, Perdew-Burke-Ernzerhof (PBE) scheme is employed to treat correlation whereas exchange is included by following the Becke scheme. It is seen that various approximations within LCAO-DFT show relatively better agreement with the experimental Compton data. Ionic model calculations for a number of configurations (Cu+x/2)2(Sb-x) (0.0≤x≤2.0) are also performed utilizing free a
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Changing oil-wet surfaces toward higher water wettability is of key importance in subsurface engineering applications. This includes petroleum recovery from fractured limestone reservoirs, which are typically mixed or oil-wet, resulting in poor productivity as conventional waterflooding techniques are inefficient. A wettability change toward more water-wet would significantly improve oil displacement efficiency, and thus productivity. Another area where such a wettability shift would be highly beneficial is carbon geo-sequestration, where compressed CO2 is pumped underground for storage. It has recently been identified that more water-wet formations can store more CO2. We thus examined how silica based nanofluids can induce such a wettabil
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This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3
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The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T
The main objective of this research is to use the methods of calculus ???????? solving integral equations Altbataah When McCann slowdown is a function of time as the integral equation used in this research is a kind of Volterra