• International Journal of Computer Science & Network Security
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• 제24권9호
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• pp.63-76
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• 2024

Weather forecasting has become a very popular topic nowadays among researchers because of its various effects on global lives. It is a technique to predict the future, what is going to happen in the atmosphere by analyzing various available datasets such as rain, snow, cloud cover, temperature, moisture in the air, and wind speed with the help of our gained scientific knowledge i.e., several approaches and set of rules or we can say them as algorithms that are being used to analyze and predict the weather. Weather analysis and prediction are required to prevent nature from natural losses before it happens by using a Deep Learning Approach. This analysis and prediction are the most challenging task because of having multidimensional and nonlinear data. Several Deep Learning Approaches are available: Numerical Weather Prediction (NWP), needs a highly calculative mathematical equation to gain the present condition of the weather. Quantitative precipitation nowcasting (QPN), is also used for weather prediction. In this article, we have implemented and analyzed the various distinct techniques that are being used in data mining for weather prediction.

• The Plant Pathology Journal
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• 제30권4호
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• pp.355-366
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• 2014

In this study, resistance responses were investigated during the interaction of Botrytis fabae with two faba bean cultivars expressing different levels of resistance against this pathogen, Nubaria (resistant) and Giza 40 (susceptible). Disease severity was assessed on leaves using a rating scale from 1 to 9. Accumulation levels of reactive oxygen species (ROS), lipid peroxidation and antioxidant enzymes (superoxide dismutase, catalase and ascorbate peroxidase) were measured in leaf tissues at different times of infection. The expression profiles of two pathogenesis-related proteins (PRPs) encoded by the genes PR-1 and ${\beta}$-1,3-glucanase were also investigated using reverse transcription RT-PCR analysis. The accumulation of these defense responses was induced significantly in both cultivars upon infection with B. fabae compared with un-inoculated controls. The resistant cultivar showed weaker necrotic symptom expression, less ROS accumulation, a lower rate of lipid peroxidation and higher activity of the enzymatic ROS scavenging system compared with susceptible cultivar. Interestingly, ROS accumulated rapidly in the resistant leaf tissues and peaked during the early stages of infection, whereas accumulation was stronger and more intense in the susceptible tissues in later stages. Moreover, the response of the resistant cultivar to infection was earlier and stronger, exhibiting high transcript accumulation of the PR genes. These results indicated that the induction of oxidant/antioxidant responses and the accumulation of PRPs are part of the faba bean defense mechanism against the necrotrophic fungus B. fabae with a different intensity and timing of induction, depending on the resistance levels.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.17-34
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• 2021

This study aimed to examine the Factor Structure of the teacher satisfaction scale (TSS) with distance education during the Covid-19 pandemic, as well as affirming the (Factorial Invariance) according to gender variable. It also aimed at identifying the degree of satisfaction according to some demographic variables of the sample. The study population consisted of all teachers in public education and faculty members in higher education in the Kingdom of Saudi Arabia. The (TSS) was applied to a random sample representing the study population consisting of (2399) respondents. The results of the study showed that the scale consists of five main factors, with a reliability value of (0.94). The scale also showed a high degree of construct validity through fit indices of the confirmatory factor analysis. The results have shown a gradual consistency of the measure's invariance that reaches the third level (Scalar-invariance) of the Measurement Invariance across the gender variable. The results also showed that the average response of the study sample on the scale reached (3.74) with a degree of satisfaction, as there are no statistically significant differences between the averages of the study sample responses with respect to the gender variable. While there were statistically significant differences in the averages with respect to the variable of the educational level in favor of the middle school and statistically significant differences in the averages attributed to the years of experience variable in favor of those whose experience is less than (5) years.