Purpose: In 2020, the emergence of Corona Virus Disease (COVID-19) has led Malaysia to an unprecedented public health crisis. Due to this, all universities in Malaysia are forced to shut down any ...physical activities by the Government. Hence, Universiti Teknologi MARA (UiTM) had conducted an Online Distance Learning (ODL) starting on 13th April 2020 due to the spread of the Covid-19 virus. As a result, the government had to implement the Movement Control Order (MCO) to control the spread of the disease among the community. In attending online classes, a lot of challenges are faced by the students. Therefore, this study reveals out a few challenges: time management, family support and financial crisis during online learning.
Methodology: The sample of the study is 100 of UiTM students throughout Malaysia and the researchers set a form of questionnaires, distributed via google form to the respondents using convenience sampling.
Findings: SPSS is used in analyzing the data and the result shows that all independent variables (time management, family support, financial crisis) are challenges towards online learning. Implications: Thus, this study will benefit the Ministry of Education, universities and students in managing and controlling their challenges while attending online classes during Pandemic Covid 19.
Purpose: Teachers’ roles in delivering classroom instructions and executing lessons in this 21st century is much bigger than assumed by many who are not in the teaching field. Some people perceived ...teaching is a stressful job and those who do not have the passion would give up after a certain number of years. Many have opted for early retirement and this number has increased year by year. Thus, this study aims to analyze the factors (health, school management and workload) that influence teachers’ intention towards early retirement.
Design/Methodology/Approach: 152 teachers were chosen from four cluster schools in Dungun, Terengganu and online questionnaires were distributed among them using Stratified Random Sampling Method. The data was analyzed using SPSS. Findings: The results show only teachers’ health influence them towards early retirement intention. Meanwhile, the other factors are viewed as a challenge in the teaching world and would not influence them to opt for early retirement.
Implications/Originality/Value: This finding will assist the Ministry of Education in taking actions, to circumvent teachers from leaving their profession before reaching the compulsory retirement age. As a result, the school’s management will focus on improved alternatives in managing the teachers’ welfare and controlling the factors of early retirement among teachers.
Collecting data from students within classrooms or schools, and collecting data from students on multiple occasions over time, are two common sampling methods used in educational research that often ...require multilevel modeling (MLM) data analysis techniques to avoid Type-1 errors. The purpose of this article is to clarify the seven major steps involved in a multilevel analysis: (1) clarifying the research question, (2) choosing the appropriate parameter estimator, (3) assessing the need for MLM, (4) building the level-1 model, (5) building the level-2 model, (6) multilevel effect size reporting, and (7) likelihood ratio model testing. The seven steps are illustrated with both a cross-sectional and a longitudinal MLM example from the National Educational Longitudinal Study (NELS) dataset. The goal of this article is to assist applied researchers in conducting and interpreting multilevel analyses and to offer recommendations to guide the reporting of MLM analysis results.
•A substantial percentage of residential water—about 90%—was desalinated sea water.•Tabuk is a focal point of The NEOM City and Red Sea developments projects.•The four principal components (PC1 – ...PC4) indicate a total variance of 90.4%.•Most exposed geology (67%) exhibited strong permeability and good infiltration.•Five drainage basins show high priority degree for adding new groundwater wells.
The Tabuk province of Saudi Arabia (SA) has an arid zone, few aquifers, high groundwater salinity (seawater intrusion), and accelerated population, industrial, and agricultural development. The development of Tabuk Basin is essential for the addition of new freshwater resources and the enhancement of aquifer recharge potential. The hydrological characteristics of the drainage basin aid in the identification of watersheds, enabling the protection and management of land erosion and ground/surface water resources. This study analyzed hydro-morphometric data from the eighteen sub-basins of the Tabuk Basin using multivariate statistical approaches and coupled remote sensing (RS) and geographic information systems (GIS) for water priority determination. The results show that the four principal components(PC1-4) have a variance of90.4% concerningbifurcation ratio (Rb), ruggedness number (Rn), elongation ratio (Re), drainage density (Dd), basin relief (Bh), circularity ratio (Rc), and relief ratio (Rh). The Al Ula, Thaibah, Hamd, Dama, Al Wajh, Al Ghamra, and Azlam sub-basins showed the highest priority, indicating soil erosion and the necessity for mitigating measures to reduce infrastructure damage. Mostexposed geology (67%) exhibited strong permeability and good infiltration (sedimentary cover and Quaternary sediments). The rest(23%) showed low to medium permeability(igneous, metamorphic, and carbonate rocks). The bestpromisingsitesfor building new wells can reduce surface runoff and soil erosion through aquifer infiltration and abstraction. The aquifer potentiality map was accomplished for Al Ula, Thaibah, Hamd, and Dama drainage basins. The most prospective groundwater investigation regions were identified, coincidingwith the drilled wells that confirmed and validated the results. The estimated zones of high to very high aquifer potentiality were used to add additional wells for investment reduce soil erosion, mitigate alternatives, agriculture,urbanization, etc. The other sub-basins have a medium to low priority, with less soil erosion and aquifer recharge.
In this work, the sliding mode control (SMC) problem is addressed for the discrete‐time interval type‐2 fuzzy singularly perturbed systems. A component‐based dynamic event‐triggering scheme is first ...proposed to determine the transmission of each measurement component according to the prespecified triggering condition, under which each sensor node will transmit independently its signal to the controller. Meanwhile, the SMC approach is used to design an effective interval‐type‐2 fuzzy controller by only utilizing the transmitted component signals, and the ε‐independent conditions are developed to attain the stability of the closed‐loop system and the reachability of the sliding domain. In addition, a framework of the optimization control design is established, where the learning‐based iterative optimization algorithm is proposed via reducing the convergence domain around the sliding surface. Finally, the proposed SMC scheme is verified via the simulation results.
The primary investor for global warming and climate change is carbon dioxide (CO2), which accounts for the largest portion of greenhouse gases in and around firms. Artificial intelligence (AI) can ...have a big impact on reducing the carbon costs of firms. With AI, companies can monitor energy usage across different processes, identify inefficiencies and suggest ways to reduce them. This helps companies improve resource efficiency and costs while minimizing carbon emissions. The study aims to explore the impact of artificial intelligence (AI) on the carbon cost reduction of firms. This study investigates how businesses can leverage Artificial Intelligence (AI) for the reduction of carbon costs. Specifically, the research explores the impact of AI-based predictions, decision-making, recommendations, and renewable energy optimization on firms' carbon cost reduction. This research employs a quantitative research design and demonstrates that AI use in decision-making and optimizing renewable energy is highly correlated with carbon cost reduction. The outcomes of the research have significant practical implications for policymakers, and industry professionals in their development of sustainable business practices. Additionally, the research contributes to the literature surrounding AI and sustainability by offering an empirical perspective on how AI can be used to support environmental sustainability efforts, enhance corporate social responsibility, and promote long-term economic gains for firms. The statistical analysis shows that there is a significant impact of AI-based predictions on the reduction of carbon costs in firms. Furthermore, it demonstrates that AI-based decision-making impacts reducing carbon costs for firms. These results highlight the importance of incorporating AI technology into business practices to effectively address sustainability concerns and reduce carbon costs, ultimately promoting long-term economic sustainability and corporate social responsibility.
Pulsed power load (PPL) consumes a huge amount of energy within a very short period of time. Directly connecting a PPL to a shipboard power system (SPS) will cause large disturbance even instability ...during PPL deployment. As an important category of energy storage system (ESS), the flywheel ESS (FESS) is an ideal source for PPL accommodation. By powering the PPL separately with a sufficiently charged FESS, the negative impacts of PPL on SPS can be avoided. The paper presents an adaptive output-constrained control design that can realize fast charging of the FESS and simultaneously minimize the disturbance to system frequency. Major benefit of the algorithm is that transient response can be guaranteed to stay within user-defined, time-varying bounds. This property makes the algorithm different from typical adaptive control algorithms and very appealing for high-performance applications. By applying the standard Lyapunov synthesis, all closed-loop signals are proved to be bounded. Finally, the proposed control design is tested through simulations using SPS models with different details. Simulation results demonstrate the effectiveness of the proposed control design.
The paper starts with the research on the early discovery of college students' psychological problems. Besides, it analyzes the data of the general survey of college students' mental health in a ...certain university, the existing data of students with psychological problems, and the questionnaire data of students' basic information in school. By comprehensively using the decision tree model and Kendall correlation analysis and other methods, using Python and SPSS software to preprocess the data and realize the model, it can obtain a psychological problem prediction model based on the objective behavior data of college students. The model is actually analyzed, and it gets good results.
Comme pour tout logiciel, l'utilisation de SPSS nécessite un certain apprentissage et, pour apprivoiser ses fonctionnalités, rien ne vaut un bon accompagnement. Le présent ouvrage, conçu comme un ...outil d'autoformation, guide l'utilisateur en démystifiant SPSS. Il ne vise pas à remplacer le manuel de référence du logiciel, mais cherche plutôt accompagner le lecteur dans sa première exploration de ce dernier et l'aider à franchir le seuil, soit celui des manipulations de base.
