Research on Factors Affecting the Choice of Vegetarian Restaurants in Vietnam

The purpose of this paper is to identify the factors affecting customers' choice of vegetarian restaurants in Da Nang, Vietnam by surveying 118 people. We modified appropriately through evaluation by Cronbach’s Alpha tool, correlation, regression analysis, EFA exploratory factor analysis, qualitative research, and quantitative research. The results show that four factors of the analysis model affect the intention and behaviour of customers to choose a vegetarian restaurant: (1) Quality of food, (2) Service, (3) Location and (4) Ambience of the restaurant. Since then, the study proposes some implications for restaurant owners to understand their customers' behavioural needs, to successfully market and achieve customers loyalty.

As Uncanny As a Body

‘As uncanny as a body’ is a video work which documents the constant transition of a dancing body from an abled human state into a glitched, injured, nonhuman one. Based on the development and use of a GAN model, the visual data of a dancer are processed, and figures that manifest this in-between state are produced. What happens when AI is not used in order to optimise the performance of the dancer but rather to generate body types and movements lying beyond fixed standards and classifications? How does a poorly trained AI model affect our perception of the body and the body itself? Does it remain human in all its smudges, cracks and distortions?Dance, as a practice that entails the act of change, offers the ground to study a body's possible becomings while undergoing the application of machine learning. 'As uncanny as a body' speculates upon AI-induced injuries in order to discuss trauma, to connect familiarity to uncanniness, and to raise questions about the witnessing and acknowledgment of our gaze.

How Different Text-Preprocessing Techniques using the Bert Model Affect the Gender Profiling of Authors

Forensic author profiling plays an important role in indicating possible profiles for suspects. Among the many automated solutions recently proposed for author profiling, transfer learning outperforms many other state-of-the-art techniques in natural language processing. Nevertheless, the sophisticated technique has yet to be fully exploited for author profiling. At the same time, whereas current methods of author profiling, all largely based on features engineering, have spawned significant variation in each model used, transfer learning usually requires a preprocessed text to be fed into the model. We reviewed multiple references in the literature and determined the most common preprocessing techniques associated with authors' genders profiling. Considering the variations in potential preprocessing techniques, we conducted an experimental study that involved applying five such techniques to measure each technique’s effect while using the BERT model, chosen for being one of the most-used stock pretrained models. We used the Hugging face transformer library to implement the code for each preprocessing case. In our five experiments, we found that BERT achieves the best accuracy in predicting the gender of the author when no preprocessing technique is applied. Our best case achieved 86.67% accuracy in predicting the gender of authors.

The Implementation of Numbered Head Together Learning Model on Student Integrated Science Learning Outcomes in SMP Negeri 1 Panei

The prevailing inquiry was performed aiming to know how Numbered Head Together Method was implemented and affect the students learning outcomes of 7th grade in SMP Negeri 1 Panei during Integrated Science Learning process. Cluster random sampling was employed to choose the samples, obtaining 64 students (two classes), in which one class (32 students) acted as experimental class receiving Numbered Head Together learning model, while another class (32 students) acted as control class received by conventional model. Data retrieved were then analyzed using SPSS 21. The analysis resulted that students who received Numbered Head Together learning model had better learning outcomes (80.62) than students’ who received conventional model (72.19). Hypothesis was further tested using t-test at significance level of α = 0.05 obtaining tcount (3.30) > ttable (2.00), thus Ha is accepted, indicating that Numbered Head Together learning model affect the Learning Outcomes of 7th grade students of SMP Negeri 1 Panei during Integrated Science learning process. It is concluded that Numbered Head Together has an impact on students learning outcomes of 7th grade of SMP Negeri 1 Panei during Integrated Science learning process at academic year of 2019/2020. The learning by using Numbered Head Together model can improve students’ learning outcomes during the Integrated Science subject, therefore such method can be selected as one of the alternatives to plan a better Integrated Science learning.

Comparative evaluation of Kalman filters and motion models in vehicular state estimation and path prediction

Vehicle state estimation and path prediction, which usually involve Kalman filter and motion model, are critical tasks for intelligent driving. In vehicle state estimation, the comparative performance assessment, regarding accuracy and efficiency, of the unscented Kalman filter (UKF) and the extended Kalman filter (EKF) is rarely discussed. This paper is devoted to empirically evaluating the performance of UKF and EKF incorporating different motion models and investigating the models’ properties and the affecting factors in path prediction. Extensive real world experiments have been carried out and the results show that EKF and UKF have roughly identical accuracy in state estimation; however, EKF is faster than UKF generally; the fastest filter is about 2⋅6 times faster than the slowest. The path prediction experiments reveal that the velocity estimate and the used motion model affect path prediction; the more realistically the model reflects the vehicle's driving status, the more reliable its predictions.

Does the choice of the reference model affect the results of 3D-3D superimposition procedure? A comparison of different protocols for personal identification

In literature, 3D-3D superimposition has been widely recognized as a valid method for personal identification. However, very little information is available about possible variability due to differences in protocols of registration of 3D models and calculation of RMS (root mean square) point-to-point distance. Frontal sinuses from 50 CT scans were segmented twice through the ITK-SNAP software and grouped in two samples (1 and 2). Maximum breadth, height and volume were measured. 3D models belonging to the same subject were then superimposed one on each other in 50 matches. In addition, superimposition of 50 random mismatches was performed. For each superimposition, the procedure was repeated four times choosing different reference models both for registration and calculation of RMS. Differences in RMS value among protocols of registration and RMS calculation were assessed through paired Student’s t-test (p < 0.05). Possible correlations between differences in RMS among groups and differences in frontal sinus size between the superimposed models were analysed through calculation of Pearson’s correlation coefficient (p < 0.05). Results showed that RMS calculation did not yield significant differences according to which 3D model is used as reference; on the other hand, RMS values from registration procedure significantly differ according to which model is chosen as reference, but only in the mismatch group (p < 0.001). Differences in RMS value according to RMS calculation are dependent upon all the three measurements, whereas differences according to registration protocols were significantly related only with the breadth of frontal sinuses but only in mismatches (p < 0.001). In no case, superimpositions of RMS values were found between matches and mismatches. This article for the first time proves that the protocol of registration and calculation of RMS significantly influences the results of 3D-3D superimposition only in case of mismatches.

Do Job Demands-Resources Model Affect Burnout among Penang Preschool Teachers

The vulnerability to burnout among teachers from Penang preschool has become an intense issue to be addressed. Moreover, preschool teachers struggle with more burnout when there are greater levels of job demands and insufficient levels of job resources. Therefore, this paper aimed to inspect the predictors of burnout among preschool teachers. Besides, this paper examines also work engagement as the promising mediator. There was a total of 102 participations by Penang preschool teachers in the research. The study discovered that work engagement was in a significant negative relationship with burnout. Meanwhile, job demands were in a significant negative relationship with work engagement whereas job resources were in a significant positive relationship with work engagement. Furthermore, it is determined that job demands and job resources possessed a significant indirect relationship with burnout respectively, through work engagement as a mediator. The outcomes of this study are advantageous to both scholars and practitioners who wish to safeguard and minimize the burnout level among preschool teachers.

Climate Change Risk Perceptions of Audiences in the Climate Change Blogosphere

The Climate Change Risk Perception Model (CCRPM, Van der Linden, 2015) has been used to characterize public risk perceptions; however, little is known about the model’s explanatory power in other (online) contexts. In this study, we extend the model and investigate the risk perceptions of a unique audience: The polarized climate change blogosphere. In total, our model explained 84% of the variance in risk perceptions by integrating socio-demographic characteristics, cognitive factors, experiential processes, socio-cultural influences, and an additional dimension: Trust in scientists and blogs. Although trust and the scientific consensus are useful additions to the model, affect remains the most important predictor of climate change risk perceptions. Surprisingly, the relative importance of social norms and value orientations is minimal. Implications for risk and science communication are discussed.