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The objective is to assess whether the extent to which employee resilience and organizational culture would be significantly related to and statistically predict the three facets of employee work engagement. Resilience was measured by four facets (Determination, Endurance, Adaptability, and Recuperability); and Organization Culture was measured for three types (Bureaucratic, Innovative, and Supportive). The dependent measures were the three facets of Work Engagement (Cognitive, Emotional, and Physical). This research by questionnaire was conducted in 2023. The questionnaires completed by 316 full-time workers revealed that all four facets of employee resilience had significant positive correlations with all three types of work engagement. Also, all three facets of work engagement were significantly higher in Innovative and Supportive cultures compared to Bureaucratic cultures. The regression analyses performed showed that the resilience factors of Determination and Adaptability were strong positive predictors of all three facets of work engagement. Furthermore, Innovative culture had additional positive effects on all three facets of work engagement; while Supportive culture had an additional positive effect on Emotional Work Engagement. The implications of the results for management are also discussed in this paper.

The design thinking methodology is a problem-solving approach that involves empathising with end-users, (re)defining problems, brainstorming solutions creatively, and experimenting with prototypes and testing. It has been widely adopted in education to help students develop critical thinking, creativity, and problem-solving skills in design. On the other hand, text-to-image artificial intelligence is a method used to generate images from natural language descriptors (usually referred to as prompts). Design thinking methodology can teach students to think creatively and critically about real-world problems when applied in the classroom. In the context of design teaching at the University of Saint Joseph, Macao, students use the design thinking methodology to develop innovative proposals for furniture design solutions. Combining design thinking methodologies with text-to-image artificial intelligence can further enhance the learning experience by allowing students to generate visual representations of their ideas during the ideation phase. The authors developed a systematic approach to generate images for ideation on furniture design based on prompting text-to-image (PTI). The analysis related students’ results who applied the design thinking methodology without using AI tools and the results generated using a standard text-to-image programme. By combining both methods, teachers can help students develop critical thinking, creativity, and problem-solving skills, while also allowing them to generate visual representations in a different paradigm and, by so, being able to communicate their ideas with the most appropriate support for them.

Design for Classroom Units: A Collaborative Multicultural Studio Development with Chinese Students

Various materials, objects, and sensors have been explored earlier for creating tangible user interfaces (TUIs). However, there is little work on 3D-printed TUIs based on visual markers for smartphone-based extended reality (XR) experiences. The combination of visual markers and smartphones results in cheap, accessible XR systems within reach of many people. Combined with 3D printing, it could foster do-it-yourself (DIY) projects for XR experiences, which may further expand and open-up possibilities for accessible and tangible interaction. This work explores the design space of modular 3D-printed tangibles for smartphone-based XR. The authors report the design exploration process, provide several interactive 3D-printed markers, and reflect on the resulting possibilities.

This review article is among the first to examine the new junket regulations in the Macau gaming industry. Particular emphasis is on the legal and regulatory framework governing the junket activity of gaming promoters and their associates. The recent changes to Macau gaming laws have resulted in stronger licensing requirements for local junket participants and precipitated the collapse of the VIP room system in casinos. Furthermore, this article highlights the policy and managerial implications of the current junket environment for the gaming industry in Macau and possibly other regional gaming jurisdictions. The effects of the new legal environment for Macau junkets could also provide insights into the implementation of similar legislation in other jurisdictions.

Classification of electroencephalogram (EEG) is a key approach to measure the rhythmic oscillations of neural activity, which is one of the core technologies of brain-computer interface systems (BCIs). However, extraction of the features from non-linear and non-stationary EEG signals is still a challenging task in current algorithms. With the development of artificial intelligence, various advanced algorithms have been proposed for signal classification in recent years. Among them, deep neural networks (DNNs) have become the most attractive type of method due to their end-to-end structure and powerful ability of automatic feature extraction. However, it is difficult to collect large-scale datasets in practical applications of BCIs, which may lead to overfitting or weak generalizability of the classifier. To address these issues, a promising technique has been proposed to improve the performance of the decoding model based on data augmentation (DA). In this article, we investigate recent studies and development of various DA strategies for EEG classification based on DNNs. The review consists of three parts: what kind of paradigms of EEG-based on BCIs are used, what types of DA methods are adopted to improve the DNN models, and what kind of accuracy can be obtained. Our survey summarizes the current practices and performance outcomes that aim to promote or guide the deployment of DA to EEG classification in future research and development.

Vertical housing is essential for modern cities because of its efficiency in using space (Wang, J. Murakami, A. 2019). The architecture of vertical housing is often determined by developers and designers. Therefore, the architecture of the building is fixed, and the end users are not involved nor can they influence its final appearance. For residential buildings, the unit sizes are based on market demand at a given point in time, which does not reflect the dynamic needs of the population as they evolve and may result in a mismatch between the supply and the demand for housing. The design of housing towers that have demographic characteristics and family size is dependent on housing size and can be very uncharacteristic and repetitive. The research question identified and addressed in this study is: How can residential buildings meet the evolving demand for housing units? Based on this question, this research paper develops a prototype for residential to resolve the dilemma between the supply and the demand in terms of the apartment size and layout. This research is a project-oriented project that focuses on residential that reflects the different family sizes required to be housed in the building and is combined with the open building method to maximize building performance. Ultimately, this research represents a meaningful innovation for market-driven architecture and defines architectural design based on the changing needs of the population using the open construction method. It also provides an opportunity to improve the design efficiency and develop a method for future growth, upgrades, and user needs. It may also be able to reflect the current housing ratio of the residential building. This work can be further explored to verify its effectiveness for other housing types and community living spaces

Crowdsensing exploits the sensing abilities offered by smart phones and users' mobility. Users can mutually help each other as a community with the aid of crowdsensing. The potential of crowdsensing has yet to be fully realized for improving public health. A protocol based on gamification to encoura...

Objective: As a world tourist destination, Macao is inevitably under the impact of the COVID-19 pandemic. However, the market of integrated resorts in Macao are shared by only a few casino concessionaries, together forming an oligopoly. While the firms attempted to adjust price, quantity and quality of their hotel services in response to the pandemic, they could not overlook the strategic interactions with other players in the market. Hence, this paper aims to investigate the possible impact of the pandemic on the oligopolistic strategies in the integrated resort market in Macao. Methodology: Application of a theoretical model of differentiated oligopoly to this six-firm case shows that price differences across firms depend on their quality differentiation. In order to analyze these price differences empirically, this paper collects data of hotel room rates of the integrated resorts from November, 2019 to mid-August, 2020, covering the periods before and after the outbreak of COVID-19. Originality: In the existing literature, there is a lack of studies of the oligopoly in the hospitality industry of Macao. Furthermore, the effect of COVID-19 is still ongoing, so this present paper is one of the first to perform such analysis. Results: The regression of each of the hotel price differentials on the COVID-19 dummy variable shows that COVID-19 has statistically significant impacts on almost all the price differentials. Intuitively, MGM and Wynn were in the high-price segment before and after the outbreak, while other firms switched positions in the low-price segment during the pandemic. One obvious downstream movement was by Conrad. According to the proposition derived from the theory, these imply that COVID-19 should have significant impact on the quality differentiation of the firms. Practical implications: The results are in line with the observations that the integrated resorts have rolled out staycation packages according to preferences of local residents. These quality adjustments observed in Macao’s hospitality industry currently only involved variable inputs rather than fixed inputs of production; therefore, the impact of COVID-19 should be seen as short-term effects. Keywords: Covid-19; Differentiated oligopoly; Hospitality industry; Hotel room rate; Oligopolistic market structure; Pricing strategy.

Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool for the accurate detection of COVID-19. The found papers showed high accuracy rate results, ranging between 85.70% and 100%, and F1-Scores from 89.52% to 100%. With this state-of-the-art, we concluded that the models proposed for the detection of COVID-19 already have significant results, but the area still has room for improvement, given the vast symptomatology and the better comprehension of individuals’ evolution of the disease.