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The Effect Of Language Learning Strategy Instruction On The Academic Achievement Of Below Average Vocational College Efl Learners In China
(2024-08)
Jiao, Chen
Language learning strategy has been acknowledged as a significant technique for English learning. Some effective strategies can make learners accomplish the questions by themselves and feel powerful to regulate their English language learning process. However, there are few studies related to the LLS instruction of below-average EFL learners, and there are more problems that need to be explored. Several problems are reported: 1) learners lack of knowledge on how to learn English effectively; 2) the numbers of EFL below-average college learners are increasing. Consequently, the purpose of this study was to 1) investigate the frequency and preference of LLS used by below-average learners; 2) determine whether LLS instruction is effective in increasing below-average EFL learners’ LSU and EAA; 3) explore the efficient LLS instruction model for below-average EFL learners. Specifically, the study distributed SILL questionnaires to 442 Chinese EFL college learners to investigate the frequency and preference of LLS use. Intervention programme also conducted for 40 Chinese EFL learners to explore the effect of LLS instruction on the LSU and EAA of below-average learners. The study employed three instruments: (1) Strategy Inventory for Language Learning (SILL); Tests of English academic achievement (EAA), namely, (2) Test-4 (CET-4) and (3) College English Final Exam (CEFE), which were conducted for pre-test and post-test of the intervention program. From a qualitative perspective, the study applied outline of semi-structured interviews (OSIs). Overall, the study made analysis and triangulation of the data from SILL, CET-4, CEFE, and SOIs common themes referring to the LLS instruction, LSU, and EAA, and finally developed the efficient LLS instruction model based on 20 interviewees’ report on LLS instruction.
The Impact Of Digital Nudging On Online Health Information Sharing Behaviors: The Moderating Roles Of Social Capital And Personality
(2024-09)
Jia, Chenjin
Health information sharing is an important pro-social behavior to encourage greater dissemination of health-related information in the society. Sharing health information with others helps to increase public awareness and understanding of health issues. It also enables networking and support with people who have had similar experiences, enabling individuals to share experiences, encourage each other and obtain advice. However, due to their limited cognitive capacity, human beings tend to use heuristic or simplifying strategies when processing information rather than performing thorough analysis and evaluation, which leads to the possibility of cognitive biases in the processing of health information and hence the inability of individuals to make decisions about sharing health information. To address this situation, digital choice architecture is a potential approach where digital nudging intervenes in users’ behaviors when processing health information by designing and adapting choices and information presentation in digital environments in order to motivate them to share health information more actively. Although some studies have investigated users’ motivations for sharing health information and factors for avoiding health information, and explorations have begun for nudge to guide consumers to choose healthy lifestyles in digital environments, there is a dearth of knowledge on how nudge can effectively promote users’ health information sharing behavior. To fill this gap, this study tested the effect of digital nudges on users’ health information sharing behavior using nudge theory.
Analysis of shadowing losses in the rear side of bifacial photovoltaics with direct and diffuse radiation
(2023-08)
Muhamad Firdaus bin Zakaria
The bifacial solar panel is one of the latest technology solar panels that attract a lot of interest from PV industries since it has greater output power compared with conventional solar panels for similar size module. This is due to the bifacial solar panel can capture greater light spectrum from the front side and rear side of the solar panels. However, there are constraints toward the PV solar panel such as shadowing effect that will reduce the output power from solar panel and create hotspot effect. In this research, the shadowing effect toward bifacial solar panel will be analyzed especially at rear side of solar panel that rarely been investigated. The percentage of shadow area at the front side and rear side of bifacial solar panel will be controlled variable in this study. For the rear side of solar panel, the research will be repeated on the white surface, diffuse metallic reflector and mirror reflector. The result shadowing effect on front side of bifacial solar panel show shadowing effect give huge impact toward output power produced from bifacial solar panel even the 5% of shadow covering the area of the solar panel affected on the Isc reduction for 35.9%. The result shadowing effect at rear side of bifacial solar panel show shadowing effect does not give huge impact toward output power produced from bifacial solar panel even 80% of the areas for the rear side of solar panel been covered shadow only affect less than 5% for Isc reduction observed with difference types of surface reflector. Observation in this research show the highest average values for irradiance reflected on the ground is the mirror reflector (641.1W/m2) followed by metallic reflector (457.8W/m2), white reflector (352.9W/m2), concrete surface (170.8W/m2).
Analysis of electric field and thermal profile distribution of various dry band length on contaminted sir under ac application
(2023-08)
Muhammad Rafiqhilmi bin Mohd Zaini
The high voltage outdoor insulator is an important component in ensuring the safe and reliable operation of transmission system to deliver uninterrupted electric power to the consumers. However, due to its widespread application through the globe, sometimes it may experience some serious damage due to various environment factor which include pollution flashover. In this particular event the insulator often sustain severe dry band arcs and surface tracking on its surface, leaving a carbonized conductive path on its surface which might induce another pollution flashover event. Generally, through the course of history, there were several types of outdoor insulator available in the market which include porcelain, glass as well as polymer insulator. However, porcelain and glass insulator was known to sustain the most damage once dry band arcings occur on its surface, leading to diversion of researcher’s attention towards the advantage offers by polymer insulator including light weight, hydrophobic and low cost. Although it offers many advantage to sustain various environmental stresses, polymer insulator still need some improvement especially when it comes to its tracking performance thus leading to several past researches was done to use filler in the insulator. This researchers only focuses on the effects or tracking performance of the insulator without any clarification done to prove the factor which causes it to occur. Thus this knowledge gap was exploited in this project by simulating the IPT standardized in IEC 60587 standards. The dry band lengths and angle of applied voltage were varied to further observe its effect towards electric field distribution along the simulation model. The nominal voltage used was 4.5 kVrms as its angle was varied with 45 degree difference.
An optimization approach for the state of charge (SOC) estimation battery based on artificial neural network
(2023-07)
Ng, Zi Jun
For every battery there is an important factor which contributes to the battery life span which is known as the State of Charge (SOC) it is used to determine the how much energy is left in the battery and usually express in percentage. It is an important factor to optimize the battery performance and lifespan. researchers are required to know how much charge will be remaining in a battery and how quickly it is being used up. Accurately measuring and managing the battery’s SOC is essential for ensuring that the electric vehicle can travel to certain amount of distance for a single full charged. Therefore, the purpose of this research is to gather data from various battery types to study the performance on each type of them. Three batteries were used in this research which are the lithium-ion, nickel-metal hydride, and lithium polymer. To calculate the SOC, some parameters such as the voltage, capacity and temperature are considered. In this research the feedforward neural network (FFNN) was used to estimate the SOC for each of the battery type. The train model was built in MATLAB and after successfully constructing the FFNN using the Levenberg-Marquardt algorithm for estimating the SOC, analysis of variance (ANOVA) is used to find out the consistency of the accuracy performance. The performance of the FFNN produces a root mean squared error (RMSE) of 0.0124, mean squared error (MSE) of micro 0.21 and accuracy percentage of 99.23% in average.