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Multi-modalities in mobile technology for assisted learning performance in higher education in China
Get PDFMobile technology, especially mobile learning, has long been an emerging and thriving field, and remains a main theme in mobile learning applications and systems. The extensive utilization of mobile learning has prompted the invention of many mobile applications. As a result of rapid advances in application technologies, various learning applications can combine different media or multi-modalities, such as video, audio, images, animated graphics, and text, to create multimedia learning resources that engage learners. However, the most favorable modalities in different learning applications that assist performance are worth exploring. This study employed mixed methods to investigate the current multi-modality situation in learning application utilization among 300 university students in China, where a rapid educational technology revolution is occurring. The findings revealed that the verbal modality (M = 3.99, S*D = 0.79) and the writing modality (M = 3.99, S*D = 0.75) in the learning applications were less enjoyable and less effective at enhancing learning performance. In exam-based or function-based apps, all five modalities in this research were considered important, especially the visual and aural modes. The results of this study also revealed that a majority of university learners were satisfied with the multi-modalities in different types of applications, except for game-based apps, that assist their learning performance (56.7%, M = 3.87, S*D = 0.79), which contrasts with the results of several related studies. Overall, college users perceived that multi-modalities were effective in helping them to complete tasks, and all modalities in current applications satisfied most of the users’ needs to assist their learning performance. In the end, the findings indicated a positive and strong linear relationship [r = 0.766, p < 0.05] between multi-modalities and assisted learning performance with the help of more capable (knowledgeable) others with the use of mobile applications
Symh index prediction with Neural Basis Expansion Analysis for Time Series (N-BEATS)
No full textThe Geomagnetic SYMH index is commonly used to measure disturbances in geomagnetic activity, such as the impact on ground-based technological systems resulting from Sun-Earth interactions. This measure can help mitigate potential damage and disruptions caused by space weather events. Recently, artificial intelligence (AI) has garnered increasing attention for its capabilities in predicting tasks, particularly due to its advantages in analyzing large datasets.
Significant advancements in various model architectures for predicting the SYMH index have emerged, including empirical methods, machine learning, and deep learning techniques. However, challenges persist in this research area, as accurately predicting the SYM-H index remains difficult due to the dynamic nature of geomagnetic data. In this work, a new deep learning model of Neural Basis Expansion Analysis for Time Series (N-BEATS), which utilizes high temporal resolution data of one-minute SYMH index readings from the peak of most recent solar cycles (specifically, solar cycle 25). Our findings indicate that this new model has significant potential in capturing the temporal patterns of the SYMH index, achieving prediction accuracy of approximately 99%
A study of Chinese enterprises’ business models to determine the impact of dynamic capabilities on innovation and performance
No full textSmall and medium-sized enterprises (SMEs) can gain a competitive advantage by implementing business model innovation (BMI), which is characterized as irreversible changes to a company’s business model. However, BMI is often associated with high risk, uncertainty, and ambiguity. In this study, the effectiveness of BMI on improving SME performance is examined using structural equation modeling (SEM) based on data collected from 330 Chinese SMEs. The purpose of this paper is to examine how enterprise risk management (ERM), organizational agility (OA), and entrepreneurial orientation (EO) affect SME performance. The results reveal that ERM, OA, and EO all have a positive impact on efficiency-centered BMI and SME performance; efficiency-centered BMI mediates this pathway. Building on dynamic capabilities theory, this paper combines ERM, OA, and EO into one framework to assess their impact on SME performance. Additionally, a case study is presented to provide suggestions for making decisions about BMI implementation
Understanding dengue mortality factors and nursing roles: insights from two Malaysian Government Hospitals
No full textIntroduction: Dengue, a mosquito-borne viral infection, imposes significant socio-economic and disease burdens on tropical and subtropical regions worldwide. Data provided by Malaysia’s Health Ministry indicate that the number of dengue cases in 2024 is exhibiting a steeper increase compared to the corresponding period last year. This study aims to identify factors contributing to dengue mortality in Malaysian government hospitals and assess nursing involvement in mortality prevention. Method: A retrospective study was conducted using a proforma. Electronic data and documented nursing care in the nursing report before the patient’s death were extracted and analysed for all dengue mortality cases. Results: Thirty-seven dengue mortality cases were identified, 28 from Hospital 1 and 9 from Hospital 2, respectively. Most patients were admitted during the critical phase (day 4 or 5), with rates of 67.8% and 88.9% in Hospitals 1 and 2, respectively. Mean hospital stays were 3.39 days (SD±1.62) in Hospital 1 and 4.56 days (SD±1.88) in Hospital 2. Among cases with comorbidities (53.6%), diabetes mellitus was most common in Hospital 1. Common clinical signs included myalgia, arthralgia, severe vomiting, and fever (78.6%). Dehydration and headache were documented in approximately 75.0% of cases in Hospital 1 and 66.7% and 77.8%, respectively, in Hospital 2. Nursing interventions primarily focused on hyperthermia reduction, with dehydration management being less common. Conclusion: Major factors contributing to dengue-related deaths in both hospitals include illness stage at admission, dengue severity/classification, and delayed hospital admission. Future efforts should prioritise assessing patients’ hydration status upon admission and continuous nursing assessment for early signs of dehydration
True or false? the impact of health-oriented leadership on work engagement in the hotel industry
No full textThe rebound of the global tourism industry highlights the importance of hotel employees’ work engagement, given their pivotal roles in service performance. While previous research has demonstrated the positive impact of health-oriented leadership (HOL) on employee engagement, few studies have examined the underlying mechanism and boundary conditions. An empirical analysis was conducted on four- and five star hotels in China, and 520 frontline employees were randomly selected from different hotels. Data were collected via online questionnaire, and the proposed model was tested using partial least squares structural equation modeling (PLS-SEM) with SmartPLS 4. The findings underscore that HOL has a positive impact on work engagement. Recovery experiences emerges as a pivotal mechanism mediating the relationship between HOL and work engagement. Furthermore, trust moderates the relationship between HOL and recovery experiences. High trust strengthens the relationship, while HOL and recovery experiences even have slightly negative relationship when the level of trust is low. This study contributes to the underlying and boundary mechanisms of the relationship from a recovery perspective
Preliminary study: data analytics for predicting medication adherence in Malaysian arthritis patients
No full textObjective: In multi-ethnic Malaysian populations, understanding and improving medication adherence in arthritis patients is crucial for enhancing treatment outcomes. Non-adherence, whether intentional or due to complex factors, can lead to severe long-term consequences such as increased disability and disease progression. This study analysed and predicted Malaysian arthritis medication adherence using 13 machine learning models. Methods: A majority of 151 responders (82.1%) were female and 58.3% had comorbid illnesses. Notably, 90.07% of respondents were non-adherence to their prescription, with significant differences by occupation and aids in medication. This study's machine learning models perform better with recursive feature elimination for feature selection. Key variables included occupation, presence of other diseases, religion, income, medication aid, marital status, and number of medications taken per day. These variables were used to build predictive models for medication adherence. Results: Results from machine learning algorithms showed varied performance. Support vector machine, gradient boosting, and random forest models performed best with AUC values of 0.907, 0.775, and 0.632 utilizing all variables. When using selected variables, random forest (AUC = 0.883), gradient boosting (AUC = 0.872), and Bagging (AUC = 0.860) performed best. Model interpretation using SHapley Additive exPlanations analysis identified occupation as the most important variable affecting medication adherence. The study also found that unemployment, concomitant disease, income, medication aid type, marital status, and daily medication count are connected with non-adherence. Conclusion: The findings underscore the multifaceted nature of medication adherence in arthritis, highlighting the need for personalized approaches to improve adherence rates
Kereta elektrik: masa depan mobiliti hijau dan teknologi canggih
Get PDFDi era pemodenan ini, kereta elektrik kini semakin dilihat sebagai masa depan mobiliti dengan kemajuan teknologi yang canggih. Kereta elektrik (EV) adalah jenis kenderaan yang menggunakan tenaga elektrik bagi menggantikan enjin pembakaran dalaman (ICE) yang biasa ditemui dalam kereta konvensional
Improving quality and consumer acceptance of rabbit meat: prospects and challenges
No full textRabbit meat is an excellent source of high-quality proteins, essential fatty acids, vitamins, and minerals, which can be further improved through various management, preslaughter, and post-slaughter interventions. Rabbit meat consumption is popular in certain regions of the world. The multidimensional role of rabbits as pet, pest, and laboratory animals, lack of proper knowledge among consumers towards the nutritive value of rabbit meat, animal welfare, and ethical issues, sustainable potential, undeveloped marketing, and processing chain, and price parity with available cheap meat and non-meat alternatives, are some constraints in the rabbit meat production. Increasing awareness of the nutritive value, positive health effects of rabbit meat consumption and production chain, development of processed meat products, and proper animal welfare compliance in rabbit production could improve consumer acceptance. The present manuscript reviewed various factors that affect the meat quality and consumer acceptance of rabbit meat for a more sustainable and viable source for global meat supply
Challenges and solutions of deep learning-based automated liver segmentation: a systematic review
No full textThe liver is one of the vital organs in the body. Precise liver segmentation in medical images is essential for liver disease treatment. The deep learning-based liver segmentation process faces several challenges. This research aims to analyze the challenges of liver segmentation in prior studies and identify the modifications made to network models and other enhancements implemented by researchers to tackle each challenge. In total, 88 articles from Scopus and ScienceDirect databases published between January 2016 and January 2022 have been studied. The liver segmentation challenges are classified into five main categories, each containing some subcategories. For each challenge, the proposed technique to overcome the challenge is investigated. The provided report details the authors, publication years, dataset types, imaging technologies, and evaluation metrics of all references for comparison. Additionally, a summary table outlines the challenges and solutions
UPM, Fakulti Pengajian Pendidikan (FPP) anjur Sambutan Jubli Emas Fakulti Pengajian Pendidikan yang ke-50
Get PDFSERDANG, 20 Januari- Fakulti Pengajian Pendidikan (FPP), Universiti Putra Malaysia (UPM) telah mengadakan Majlis Peluncuran Sambutan Jubli Emas Fakulti Pengajian Pendidikan yang ke-50, menandakan perjalanan FPP yang telah mencapai usia 50 tahun