Patients' considerations when choosing an orthodontist are influenced by many factors, including background, ethnicity, and location. Accordingly, this study aimed to identify factors influencing ...patients’ considerations when selecting an orthodontist in both Malaysia and Taiwan.
In total, 248 dental students from Taipei Medical University and 110 dental students from Manipal University College Malaysia were selected for this study. Participants' considerations when selecting an orthodontist were assessed using a questionnaire survey. The questionnaire collected data regarding participants’ demographic characteristics and their preferences regarding clinical settings, orthodontist attributes, administrative systems, and the influence of social media. The gathered data were analyzed and compared using independent t-test, ANOVA, and chi-squared for both cohorts.
The present results revealed significant differences between the Malaysian and Taiwanese participants with several variables, including orthodontist experience, recommendations, pain-free treatment procedures, treatment duration, friendly reception, sources of information about orthodontists, and preferred social media platforms. Notably, among the Taiwanese participants, “person responsible for treatment costs,” was significantly correlated with the orthodontist's age, the orthodontist's work experience, information sources, travel distance, and content posted by orthodontists on social media. By contrast, among the Malaysian participants, this variable was correlated with the work experience of orthodontists.
Significant differences were observed between the Malaysian and Taiwanese participants in terms of their considerations when choosing an orthodontist. Participant's gender significantly influenced orthodontist preferences among the Malaysian participants, whereas the individual responsible for treatment costs was identified to be the most crucial factor influencing the Taiwanese participants.
Decorative plaited mat is one of the many examples of rich plait work often seen on Borneo handicraft products. The plaited mats are decorated with simple and complex motif designs; each has its own ...special meaning and taboos. The motif designs are used as a reflection of environment and the traditional beliefs in the Iban community. In line with efforts from UNESCO’s and Sarawak Government’s, digitization, and the use of IR4.0 technologies to preserve and promote this cultural heritage is encouraged. Towards this end goal, we present a novel image dataset containing 10 Iban plaited mat motif classes. The plaited mat motifs are made of diagonal and symmetrical shapes, as well as geometric and non-geometric patterns. Classification’s accuracy using scale-invariant feature transform (SIFT) features was evaluated against 6 common image deformations: zoom+rotation, viewpoint, image blur, JPEG compression, scale and illumination, across multiple threshold values. Varying degrees of each deformation were applied to a digitally cleaned (and cropped) image of each mat motif class. We used RANSAC to remove outliers from the noisy SIFT matching result. The optimal threshold value is 2.0e-2 with a reported 100.0% matching accuracy for the scale change and zoom+rotation set.
Speaker diarization plays a vital role in speech transcription involving conversations as it improves the transcribed content's accuracy, comprehension, and usability. By having a speech ...transcription diarized, the conversation data has a more structured presentation, allowing for a variety of applications that rely on accurate speaker attribution. Even so, speaker diarization is a field that has been less explored for low-resourced languages, as current resources that have been optimized and applied in speaker diarization are mostly for more developed and well-resourced languages, such as English, Spanish or French. In this paper, we propose an approach to using pseudo-labelled speech data to perform self-training on the x-vector models to improve diarization accuracy. The proposed method uses almost 13 hours Sarawak Malay unlabeled conversational speech corpus obtained from the Kalaka: Language Map of Malaysia website for training, as well as 1 hour and 26 minutes of manually labeled Sarawak Malay speech data for testing and evaluation. We demonstrate how speaker diarization models can be fine-tuned with the pseudo-labeled data.
Facial features deformed according to the intended facial expression. Specific facial features are associated with specific facial expression, i.e. happy means the deformation of mouth. This paper ...presents the study of facial feature deformation for each facial expression by using an optical flow algorithm and segmented into three different regions of interest. The deformation of facial features shows the relation between facial the and facial expression. Based on the experiments, the deformations of eye and mouth are significant in all expressions except happy. For happy expression, cheeks and mouths are the significant regions. This work also suggests that different facial features' intensity varies in the way that they contribute to the recognition of the different facial expression intensity. The maximum magnitude across all expressions is shown by the mouth for surprise expression which is 9x10-4. While the minimum magnitude is shown by the mouth for angry expression which is 0.4x10-4.
Miriek and Kenyah-Badeng are native minority languages in Sarawak with a dwindling number of speakers and are spoken particularly in the state's northern region 4. Miriek and Kenyah-Badeng are ...categorized as under-resourced languages and the resources for these languages are scarce and limited. Due to its scarcity, not a lot of information about the relationship between both languages is known although both languages supposedly belong to the same language family. In this study, rule-based morphological analyzers were built for Miriek and Kenyah-Badeng. The study aimed to create a written corpus for the targeted languages, morphological analyzers for the targeted languages, and findings on possible relationships between targeted languages in terms of morphology. The accuracy result of the rule-based morphological analyzers was high and the findings on the relationships between Miriek and Kenyah-Badeng show a high degree of similarities. The future work suggestion includes the inclusion of more languages especially the ones that are located in the same area of both languages were spoken to gain more insight into the relationship between these languages.
The impact of generative artificial intelligence-based Chatbots on medical education, particularly in Southeast Asia, is understudied regarding healthcare students' perceptions of its academic ...utility. Sociodemographic profiles and educational strategies influence prospective healthcare practitioners' attitudes toward AI tools.
This study aimed to assess healthcare university students' knowledge, attitude, and practice regarding ChatGPT for academic purposes. It explored chatbot usage frequency, purposes, satisfaction levels, and associations between age, gender, and ChatGPT variables.
Four hundred forty-three undergraduate students at a Malaysian tertiary healthcare institute participated, revealing varying awareness levels of ChatGPT's academic utility. Despite concerns about accuracy, ethics, and dependency, participants generally held positive attitudes toward ChatGPT in academics.
Multiple logistic regression highlighted associations between demographics, knowledge, attitude, and academic ChatGPT use. MBBS students were significantly more likely to use ChatGPT for academics than BDS and FIS students. Final-year students exhibited the highest likelihood of academic ChatGPT use. Higher knowledge and positive attitudes correlated with increased academic usage. Most users (45.8%) employed ChatGPT to aid specific assignment sections while completing most work independently. Some did not use it (41.1%), while others heavily relied on it (9.3%). Users also employed it for various purposes, from generating questions to understanding concepts. Thematic analysis of responses showed students' concerns about data accuracy, plagiarism, ethical issues, and dependency on ChatGPT for academic tasks.
This study aids in creating guidelines for implementing GAI chatbots in healthcare education, emphasizing benefits, and risks, and informing AI developers and educators about ChatGPT's potential in academia.
Facial features deformed according to the intended facial expression. Specific facial features are associated with specific facial expression, i.e. happy means the deformation of mouth. This paper ...presents the study of facial feature deformation for each facial expression by using an optical flow algorithm and segmented into three different regions of interest. The deformation of facial features shows the relation between facial the and facial expression. Based on the experiments, the deformations of eye and mouth are significant in all expressions except happy. For happy expression, cheeks and mouths are the significant regions. This work also suggests that different facial features' intensity varies in the way that they contribute to the recognition of the different facial expression intensity. The maximum magnitude across all expressions is shown by the mouth for surprise expression which is 9x10-4. While the minimum magnitude is shown by the mouth for angry expression which is 0.4x10-4.
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