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Poor medication adherence leads to high hospital admission rate and heavy amount of health-care cost. To cope with this problem, various electronic pillboxes have been proposed to improve the medication adherence rate. However, most of the existing electronic pillboxes use time-based reminders which may often lead to ineffective reminding if the reminders are triggered at inopportune moments, e.g. user is sleeping or eating.

In this paper, the authors propose an AI-empowered context-aware smart pillbox system. The pillbox system collects real-time sensor data from a smart home environment and analyzes the user’s contextual information through a computational abstract argumentation-based activity classifier.

Based on user’s different contextual states, the smart pillbox will generate reminders at appropriate time and on appropriate devices.

This paper presents a novel context-aware smart pillbox system that uses argumentation-based activity recognition and reminder generation.

This paper aims to adapt and computerize the Trail Making Test (TMT) to support long-term self-assessment of cognitive abilities.

The authors propose a divide-and-combine (DAC) approach for generating different instances of TMT that can be used in repeated assessments with nearly no discernible practice effects. In the DAC approach, partial trails are generated separately in different layers and then combined to form a complete TMT trail.

The proposed approach was implemented in a computerized test application called iTMT. A pilot study was conducted to evaluate iTMT. The results show that the instances of TMT generated by the DAC approach had an adequate level of difficulty. iTMT also achieved a stronger construct validity, higher test–retest reliability and significantly reduced practice effects than existing computerized tests.

The preliminary results suggest that iTMT is suitable for long-term monitoring of cognitive abilities. By supporting self-assessment, iTMT also can help to crowdsource the assessment processes, which need to be administered by healthcare professionals conventionally, to the patients themselves.

The safety and reliability of high-speed trains rely on the structural integrity of their components and the dynamic performance of the entire vehicle system. This paper aims to define and substantiate the assessment of the structural integrity and dynamical integrity of high-speed trains in both theory and practice. The key principles and approaches will be proposed, and their applications to high-speed trains in China will be presented.

First, the structural integrity and dynamical integrity of high-speed trains are defined, and their relationship is introduced. Then, the principles for assessing the structural integrity of structural and dynamical components are presented and practical examples of gearboxes and dampers are provided. Finally, the principles and approaches for assessing the dynamical integrity of high-speed trains are presented and a novel operational assessment method is further presented.

Vehicle system dynamics is the core of the proposed framework that provides the loads and vibrations on train components and the dynamic performance of the entire vehicle system. For assessing the structural integrity of structural components, an open-loop analysis considering both normal and abnormal vehicle conditions is needed. For assessing the structural integrity of dynamical components, a closed-loop analysis involving the influence of wear and degradation on vehicle system dynamics is needed. The analysis of vehicle system dynamics should follow the principles of complete objects, conditions and indices. Numerical, experimental and operational approaches should be combined to achieve effective assessments.

The practical applications demonstrate that assessing the structural integrity and dynamical integrity of high-speed trains can support better control of critical defects, better lifespan management of train components and better maintenance decision-making for high-speed trains.

Have you been to a smart restaurant, and how were its services? A common limitation of hospitality studies stems from the lack of research on how service quality is shaped within smart technology. This study aims to fill this literature void not merely to reiterate the importance of technology but also to recast service quality through the lens of information technology. It synthesizes the 5-S model of smart service quality (AKA SSQ) as a new conceptualization of service quality application in smart hospitality contexts such as smart restaurants.

This study undertook a qualitative research design based on theoretical synthesis from service quality, information technology and attention restoration. Drawing from online review comments and semistructured interviews from smart restaurants, the authors improvised the SSQ model to identify the essence of smart service in smart dining establishments.

“5-S” reflects an extension of the literature to denote a new SSQ abstraction pertinent to s-servicescape, s-assurance, s-responsiveness, s-reliability and s-empathy. A nomological network was posited to better understand the importance of smart design and consequence of SSQ.

The emergence of smart dining gives rise to smart restaurants, which puts technology at center stage. As consumers are becoming increasingly comfortable with self-service technology, auto-payment and ordering systems and robotic services, technology in foodservice will continue to play an essential role to better serve diners. Geared with advanced innovations and intelligent devices, smart restaurants are now more than mere eateries. It is a trend and a lifestyle.

This novel SSQ concept adds new nuances to the literature by acknowledging the technological essence in today’s hospitality industry. By integrating smart technology into the service quality paradigm, the authors are able to observe several interesting behaviors exhibited during smart dining, including tech-induced restoration, which opens a new avenue to understand how attention restoration could be attained through immersion in a technologically advanced setting. By synthesizing theoretical essence from service quality, attention restoration and information technology, the authors are able to create a new dialog that should warrant a forum of discussion in future studies.

A radial offset jet has the flow characteristics of a radial jet and an offset jet, which are encountered in many engineering applications. The purpose of this paper is to study the dynamics and mass transfer characteristics of the radial offset jet with an offset ratio 6, 8 and 12.

Three turbulence models, namely the SST k-? model, detached eddy simulation model, and improved delayed detached eddy simulation (IDDES), were applied to the radial offset jet with an offset ratio eight and their results were compared with experimental results. The contrasting results, such as the distributions of mean and turbulent velocity and pressure, show that the IDDES model was the best model in simulating the radial offset jet. The results of the IDDES were analyzed, including the Reynolds stress, turbulent kinetic energy, triple-velocity correlations, vertical structure and the tracer concentration distribution.

In the axisymmetric plane, Reynolds stresses increase to reach a maximum at the location where the jet central line starts to be bent rapidly, and then decrease with increasing distance in the radial direction. The shear layer vortices, which arise from the Kelvin-Helmholtz instability near the jet exit, become larger scale results in the entrainment and vortex pairing, and breakdown when the jet approaches the wall. Near the wall, the vortex swirling direction is different at both front and back of attachment point. In the wall-jet region, the concentration distributions present self-similarity while it keeps constant below the jet in the recirculation region.

The radial offset jet with other offset ratio and exit angle is not considered in this paper and should be investigated.

The results obtained in this paper will provide guidance for studying similar flow and a better understanding of the radial offset jet.

The purpose of this paper is to seek a surfactant or template-free, simple and green method to fabricate NiO nanobelts and to find an effective technique to detect the ethanol vapor at room temperature.

NiO nanobelts with high aspect ratio and dispersive distribution have been synthesized by a template-free hydrothermal reaction at 160°C for 12 h. The products are studied by X-ray diffraction (XRD), energy dispersive spectroscopY, scanning electron microscopy, atomic force microscopy, high-resolution transmission electron microscopy, selective area electron diffractio and X-ray photoelectron spectroscopy. In particular, the room-temperature ethanol sensitivity of NiO nanobelts is investigated by the surface photo voltage (SPV) technique.

The prepared NiO nanobelts is single crystalline bunsenite structure with the length of approximately 10 μm and the diameter of approximately 30 nm. The atomic ratio of “Ni” to “O” is 0.92:1. When the concentration of ethanol vapor reaches 100 ppm, the sensitivity of NiO nanobelts is 7, which can meet the commercial demanding of ethanol gas sensor.

The NiO nanobelts can be obtained by a template-free, simple and green hydrothermal reaction at 160°C for 12 h. The NiO nanobelts-based gas sensor is a promising candidate for the application in ethanol monitoring at room temperature by SPV technique.

This paper aims to investigate an identification strategy for the nonlinear state-space model (SSM) in the presence of an unknown output time-delay. The equations to estimate the unknown model parameters and output time-delay are derived simultaneously in the proposed strategy.

The unknown integer-valued time-delay is processed as a latent variable which is uniformly distributed in a priori known range. The estimations of the unknown time-delay and model parameters are both realized using the Expectation-Maximization (EM) algorithm, which has a good performance in dealing with latent variable issues. Moreover, the particle filter (PF) with an unknown time-delay is introduced to calculated the Q-function of the EM algorithm.

Although amounts of effective approaches for nonlinear SSM identification have been developed in the literature, the problem of time-delay is not considered in most of them. The time-delay is commonly existed in industrial scenario and it could cause extra difficulties for industrial process modeling. The problem of unknown output time-delay is considered in this paper, and the validity of the proposed approach is demonstrated through the numerical example and a two-link manipulator system.

The novel approach to identify the nonlinear SSM in the presence of an unknown output time-delay with EM algorithm is put forward in this work.

While the importance of social media will continue to grow, the purpose of this study is to provide a retrospective systematic literature review of the social media research published in major hospitality and tourism journals over a specific time period.

The study conducted a bibliometric analysis to review the literature of 439 social media articles published in 51 hospitality and tourism journals over a 15-year time span (2002-2016).

Ulrike Gretzel authored the highest fractional citations. The results indicated that social media-related research was mostly published in top-tier journals. The International Journal of Contemporary Hospitality Management was amongst the four leading journals in terms of the percentage of published social media articles. While inter-country social media research collaborations were relatively modest, interestingly, inter-country collaborations have been steadily increasing in the past five years. Another finding indicated that social media research in hospitality and tourism journals has been predominantly quantitative. The results revealed six new areas within the consumer behaviour research theme, namely, eWOM, service recovery, customer satisfaction, brand/destination image and service quality. Finally, it is important to note that four new trends in social media research appeared between 2011 and 2016, namely, big data, netnography, Travel 2.0 and Web 2.0.

While this study made significant contributions to the social media literature, some limitations do exist. For example, the current research excluded publications from major conferences, books, book chapters and dissertations. Additionally, it is not within the scope of this paper to take into account issues related to self-citations.

The results obtained from analysis contribute to a comprehensive understanding of social media research progress in hospitality and tourism. For example, evaluating the performance of individual scholars helps educational institutions to compete in the global university ranking system. Additionally, to compete for funding opportunities on the topic of social media, institutions can use citation counts to demonstrate their competitiveness. Furthermore, due to the expected future growth in the number of social media platforms, practitioners need to understand motivating factors and tourists’ needs in different countries, target market segments, age groups and cultures to create highly engaging communities around their brands.

To the best of the authors’ knowledge, the sample of this study synthesized the largest selection of social media articles published in hospitality and tourism journals. This is the first study to apply the fractional score at the author level, the adjusted appearance score at the university level and the average citation score at the journal and inter-country levels in the analysis. In addition, prevalent research orientations and research trends in social media made significant contributions to existing literature.