Overcoming the liability of renewal at the Saudi Railway Sector

関西学院大

Overcoming the Liability of Renewal at the Saudi Railway Sector

関西学院大

Learning Chemistry in English: Challenges Faced by Non-Native English Speakers

Every year many international students come to study in the United States. In addition to all the challenges associated with coming to a new country, non-native English speakers (NNES) face the additional challenge of having to learn their content in English. Therefore, in this project, I recruited NNES participants from general chemistry courses since preliminary inquiries indicated that they have the largest enrollments. Because there were relatively few students at MSU who are non-native English speakers studying chemistry, I used a case study design to be able to extract generalizations from an in-depth study of a few individuals. The aim of this qualitative study was to identify the key factors that contributed to language-based difficulties these students faced while taking general chemistry courses. Data were collected in two interviews throughout one semester for each participant. Based on a cross-case analysis, the most significant challenges common to all five participants were: the lack of self-confidence in using English language, avoidance of communication, the speed of discourse, and difficulty in laboratory courses. The utility of this study should be relevant to current and future NNES, their Universities and governments and organizations who sponsor these students

Respiratory Therapy Students\u27 Perception on Online Learning During COVID-19 in the Kingdom of Saudi Arabia

Background: In response to the COVID-19 pandemic, electronic learning (E-learning) has emerged as the primary method for delivering educational materials, particularly within the scope of Saudi Arabian (SA) Respiratory Therapy (RT) education. PURPOSE: To evaluate the perception of E-learning among RT students in the Kingdom of Saudi Arabia (KSA) by comparing face-to-face learning to E-learning during the COVID-19 pandemic. METHODS: A cross-sectional survey to investigate the perception of E-learning was conducted and distributed using a convenience sample of RT students through an online platform (Google Forms) between September and November 2023. RESULTS: Overall, 221 RT students, with females accounting for 119 (53.8%), replied to the online survey. The study revealed several advantages of E-learning, including the ability to study at home (67.9%), access to online materials (64.7%), and learning at own pace (62.4%). The main disadvantages as indicated by most respondents were the lack of interactions with patients (70.1%), technical problems (56.6%), and reduced interaction with teachers (50.7%). No significant difference in the perceptions of knowledge enhancement between face-to-face and E-learning methods (P = .32). However, E-learning was considered a lower effective method than face-to-face learning for both clinical skill development (P \u3c .001), and social competencies (P \u3c .001). Additionally, respondents reported that they were less actively engaged during E-learning classes compared to face-to-face classes (P \u3c .001). Nonetheless, a significant percentage of respondents (71.9%) claimed that E-learning was an enjoyable experience. CONCLUSION: This research emphasizes the potency of E-learning in terms of increasing knowledge as a valuable tool for educating Saudi RT students. Nevertheless, it highlights the need for a meticulously planned strategy and a proactive implementation approach to effectively implement clinical and social skills E-learning into the educational framework of RT students

Anticancer activity of methanolic extarct of Momordica charantia against human colon, liver and breast cancer cell lines- In vitro

Natural products are the best source for various medicinal drugs. Regardless investigate the toxic effect of these plant extracts, the results will still unsafe and unacceptable. This study aimed to identify anti-cancer activity and cytotoxicity effect of Momordica charantia extract on different cancer cell line. Materials and Methods:to archive the aim of this study 3 different cancer cell lines (HCT116, MCF-7, and HepG2) were treated with different Momordicacharantiaextract doses (from 0-100µg) for each cell line. IC50, cell viability,apoptosis, were evaluated. Results:The effect of Momordicacharantiaextract was highly significant in HepG2 cells than HCT116 cell as well as MCF-7 which showing the IC50 of Momordicacharantia extract in HepG2 was 0.77 µg/ml while in HCT116 was 0.81µg/mland was 1.35µg/ml in MCF-7 cells respectively. Also, the effect of the Momordicacharantia extract was more potent in HCT116 compared to MCF-7 cells.Conclusions: in the light of these resultsMomordicacharantiaextract may use as anticancer pro-drugat a specific type of cancer (Liver HepG2 cell line) but still need further studies to explore the mechanism of action that led to observe different results from different cell lines despite the same extract. Keywords: Momordicacharantia, Apoptosis, MCF-7, HepG2, HCT116

Evaluating Opportunities for Improved Processes and Flow Rates in Royal Saudi Air Force F-15 Reparable Items Supply Chain

This research focuses on improving the F-15 reparable parts supply chain process in the Royal Saudi Air Force. The F-15 reparable parts supply chain process currently requires too much time to repair and return parts which affect the capability of aircraft operational missions. Because the F-15 is the first line of Saudi Arabia s defense, it is essential that they be fully mission ready in the shortest time possible. That can be done by improving relationships, communication, reducing batching before shipments and by efficient use of the available qualified workforces, tools and equipment. Consideration is given to applying an existing management technique to the Royal Saudi Air Force s F-15 supply chain. The selected techniques are supply chain mapping, Lean management approach and gap analysis. The research suggests that those techniques can improve the F-15 supply chain process in the Royal Saudi Air Force

A dynamical sampling scheme for solving a generalized heat equation

We study an initial value problem for a generalized version of the heat equation, involving time/space variant coefficients, and fairly unknown initial conditions. t is known that solving the classical heat equation, under appropriate assumptions is possible even when the initial conditions are unknown; one can compensate for the lack of knowledge of the initial conditions by adding scarce measurements made at later time instances. This problem of compensation via a time-space trade off between the initial measurements and the later time measurements has been recently observed in applications of sampling theory, and referred to as the dynamical sampling problem. We give a general formulation of the initial value problem for a generalized version of the heat equation, and aim at producing a sequence of approximate solutions via a time-space trade off, which converges to the exact solution under appropriate assumptions. We study the correlation between the number of measurements that are needed to recover the initial profile to a prescribed accuracy, give precise estimates for the time instances when these measurements need to occur, and provide an optimal reconstruction algorithm under the assumption that the initial profile is in a Sobolev class.Thesis (M.S.)Department of Mathematical SciencesPreliminaries -- Determining a single sampling location x₀ -- Bounds on optimal performance -- Time selection for near optimal recover

UWB imaging for breast cancer detection using neural network.

This paper presents a simple feed-forward back-propagation Neural Network (NN) model to detect and locate early breast cancer/tumor efficiently through the investigation of Electromagnetic (EM) waves. A spherical tumor of radius 0.25 cm was created and placed at arbitrary locations in a breast model using an EM simulator. Directional antennas were used to transmit and receive Ultra-Wide Band (UWB) signals in 4 to 8 GHz frequency range. Small training and validation sets were constructed to train and test the NN. The received signals were fed into the trained NN model to find the presence and location of tumor. Very optimistic results (about 100% and 94.4% presence and location detection rate of tumor respectively) have been observed for early received signal components with the NN model. Hence, the proposed model is very potential for early tumor detection to save human lives in the future