The Level of Having Supra-Cognitive Thinking for Law Students at Prince Mohammad Bin Fahd University Based on Some Variables from Their Own Perspective

The objective of this study is to know the level of possessing supra-cognitive thinking skills for the students of the Faculty of Law at Prince Mohammed Bin Fahd University from their own point of view according to some demographic variables. The study followed the descriptive approach, and applied the study tool to a randomly selected sample of (500) students (102) male students, and (398) female students. The results of the study showed that: the study sample members sometimes agree that the law students possess three of the supra-cognitive thinking skills. The study also revealed that there are no statistically significant differences at the level of statistical index of (0.05) or less in the study sample selections about (supra-cognitive thinking skills) based on gender variable. While there are statistically significant differences at the level of statistical index of (0.05) or less, in the replies of the study sample about (supra -cognitive thinking skills) based on the difference of the variable of the study level.

Quantitative Analysis of Phase Separation Using the Lattice Boltzmann Method

Phase separation is widely observed in multiphase systems. In this study, it has been investigated using Shan–Chen lattice Boltzmann method. The adhesion parameter in SC model leads to the desired fluid–fluid phenomenon, which was varied to specify the strength of separation between two phases to present emulsified performance in oil production. In order to describe such behaviors quantitatively, graphical distributions were described with time and were corresponded with a statistical index–Fourier structure factor that is able to predict complex phase separation behaviors, thereby providing a measurement for calculating such random distribution during the process of separation as well as evaluating heterogeneous degrees of the entire domain. The repulsive interactions are specified as low, intermediate, and high values. Phase separations with clear boundaries have been observed and each stage of separation evolvement has been discussed in this study. Magnitudes of structure factors are increased with higher degrees of fluctuations.

A spatial analysis for geothermal energy exploration using bivariate predictive modelling

The development of predictive maps for geothermal resources is fundamental for its exploration across Nigeria. In this study, spatial exploration data consisting of geology, geophysics and remote sensing was initially analysed using the Shannon entropy method to ascertain a correlation to known geothermal manifestation. The application of statistical index, frequency ratio and weight of evidence modelling was then used for integrating every predictive data for the generation of geothermal favourability maps. The receiver operating/area under curve (ROC/AUC) analysis was then employed to ascertain the prediction accuracy for all models. Basically, all spatial data displayed a significant statistical correlation with geothermal occurrence. The integration of these data suggests a high probability for geothermal manifestation within the central part of the study location. Accuracy assessment for all models using the ROC/AUC analysis suggests a high prediction capability (above 75%) for all models. Highest prediction accuracy was obtained from the frequency ratio (83.3%) followed by the statistical index model (81.3%) then the weight of evidence model (79.6%). Evidence from spatial and predictive analysis suggests geological data integration is highly efficient for geothermal exploration across the middle Benue trough.

GIS-Based Flood Susceptibility Mapping Using Statistical Index and Weighting Factor Models

Floods are one of the most devastating natural hazards, causing deaths, economic losses, and destruction of property. Flood susceptibility maps are an essential tool for flood mitigation and preparedness planning. This study mapped flood susceptibility using statistical index (SI) and weighting factor (WF) models in San Pa Tong District, Chiang Mai Province, Thailand. The conditioning factors used to perform flood susceptibility mapping were elevation, slope, aspect, curvature, topographic wetness index, stream power index, rainfall, distance from rivers, stream density, soil drainage, land use, and road density. The flood data were randomly classified as training data for mapping (70% of data) and testing data for model validation (30% of data). The results revealed that the SI and WF models classified 49.49% and 51.74% of the study area, respectively, as very highly susceptible to flooding. In the WF model, the factors with the greatest influence were land use, soil drainage, and elevation. The validation of the models using the area under the curve revealed that the success rates of the SI and WF models were 91.80% and 93.06%, while the prediction rates were 92.05% and 93.52%, respectively. The results from this study can be useful for local authorities in San Pa Tong District for flood preparedness and mitigation.

Providing a framework for knowledge sharing in knowledge-based organizations according to social capital indicators

Purpose: This study aimed to provide a framework for examining knowledge sharing from the perspective of social capital in knowledge-based organizations. For this purpose, the social capital and knowledge sharing literature has been reviewed and appropriate dimensions and components have been selected for use in the proposed framework. Research methodology: The number of experts participating in this study was 12. Kendall’s W Ranks is a statistical index for assessing the degree of agreement in a group. This statistical index, which is related to non-parametric statistics, is used to assess the degree to which a number of evaluators agree on the ranking of several factors. Result: This research's proposed framework shows that the main bottleneck in the knowledge sharing process is the sender. Numerous factors affect the motivation, quantity and quality of knowledge shared by him. The proposed conceptual model shows the factors in the field of social capital well. This means that the organization's managers should pay special attention to people with knowledge to activate the process of knowledge sharing in the organization as a driving force. Limitations: This research only described knowledge-based organizations. Contribution: The proposed conceptual framework makes a good distinction between formal and informal knowledge-sharing channels in a knowledge-based organization. Formal channels are controlled and manageable channels. Although the main burden of knowledge sharing in organizations lies with informal channels, the more managers can shift the organization's knowledge to formal channels, the more they can manage the process. This is a part of the job that social capital, in particular, helps to achieve. The proposed framework discusses the acceptance of the use of formal frameworks. Keywords: Social capital, Knowledge management, Knowledge sharing, Expertise method