Qiong Wu, Zhiwei Zeng, Jun Lin and Yiqiang Chen
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
Based on user’s different contextual states, the smart pillbox will generate reminders at appropriate time and on appropriate devices.
Originality/value
This paper presents a novel context-aware smart pillbox system that uses argumentation-based activity recognition and reminder generation.
Details
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Zhiwei Zeng, Chunyan Miao, Cyril Leung and Zhiqi Shen
This paper aims to adapt and computerize the Trail Making Test (TMT) to support long-term self-assessment of cognitive abilities.
Abstract
Purpose
This paper aims to adapt and computerize the Trail Making Test (TMT) to support long-term self-assessment of cognitive abilities.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Weihua Zhang, Yuanchen Zeng, Dongli Song and Zhiwei Wang
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
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Zhiwei Zhang, Saasha Nair, Zhe Liu, Yanzi Miao and Xiaoping Ma
This paper aims to facilitate the research and development of resilient navigation approaches, explore the robustness of adversarial training to different interferences and…
Abstract
Purpose
This paper aims to facilitate the research and development of resilient navigation approaches, explore the robustness of adversarial training to different interferences and promote their practical applications in real complex environments.
Design/methodology/approach
In this paper, the authors first summarize the real accidents of self-driving cars and develop a set of methods to simulate challenging scenarios by introducing simulated disturbances and attacks into the input sensor data. Then a robust and transferable adversarial training approach is proposed to improve the performance and resilience of current navigation models, followed by a multi-modality fusion-based end-to-end navigation network to demonstrate real-world performance of the methods. In addition, an augmented self-driving simulator with designed evaluation metrics is built to evaluate navigation models.
Findings
Synthetical experiments in simulator demonstrate the robustness and transferability of the proposed adversarial training strategy. The simulation function flow can also be used for promoting any robust perception or navigation researches. Then a multi-modality fusion-based navigation framework is proposed as a light-weight model to evaluate the adversarial training method in real-world.
Originality/value
The adversarial training approach provides a transferable and robust enhancement for navigation models both in simulation and real-world.
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Keywords
IpKin Anthony Wong, Jingwen Huang, Zhiwei (CJ) Lin and Haoyue Jiao
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
“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.
Research limitations/implications
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.
Originality/value
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.
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Zhiwei Li, Wenxin Huai, Zhonghua Yang, Zhongdong Qian and Yuhong Zeng
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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Research limitations/implications
The radial offset jet with other offset ratio and exit angle is not considered in this paper and should be investigated.
Originality/value
The results obtained in this paper will provide guidance for studying similar flow and a better understanding of the radial offset jet.
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Zhiwei Li, Dingding Li, Yulong Zhou, Haoping Peng, Aijun Xie and Jianhua Wang
This paper aims to contribute to the performance improvement and the broader application of hot-dip galvanized coating.
Abstract
Purpose
This paper aims to contribute to the performance improvement and the broader application of hot-dip galvanized coating.
Design/methodology/approach
First, the ability to provide barrier protection, galvanic protection, and corrosion product protection provided by hot-dip galvanized coating is introduced. Then, according to the varying Fe content, the growth process of each sublayer within the hot-dip galvanized coating, as well as their respective microstructures and physical properties, is presented. Finally, the electrochemical corrosion behaviors of the different sublayers are analyzed.
Findings
The hot-dip galvanized coating is composed of η-Zn sublayer, ζ-FeZn13 sublayer, δ-FeZn10 sublayer, and Γ-Fe3Zn10 sublayer. Among these sublayers, with the increase in Fe content, the corrosion potential moves in a noble direction.
Research limitations/implications
There is a lack of research on the corrosion behavior of each sublayer of hot-dip galvanized coating in different electrolytes.
Practical implications
It provides theoretical guidance for the microstructure control and performance improvement of hot-dip galvanized coatings.
Originality/value
The formation mechanism, coating properties, and corrosion behavior of different sublayers in hot-dip galvanized coating are expounded, which offers novel insights and directions for future research.
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Zhiwei Zhang, Zhe Liu, Yanzi Miao and Xiaoping Ma
This paper aims to develop a robust navigation enhancement framework to handle one of the most urgent needs for real applications of autonomous vehicles nowadays, as these corner…
Abstract
Purpose
This paper aims to develop a robust navigation enhancement framework to handle one of the most urgent needs for real applications of autonomous vehicles nowadays, as these corner cases act as the most commonly occurred risks in potential self-driving accidents.
Design/methodology/approach
In this paper, the main idea is to fully exploit the consistent features among spatio-temporal data and thus detect the anomalies and build residual channels to reconstruct the abnormal information. The authors first develop an anomaly detection algorithm, then followed by a corresponding disturbed information reconstruction network which has strong robustness to address both the nature disturbances and external attacks. Finally, the authors introduce a fully end-to-end resilient navigation performance enhancement framework to improve the driving performance of existing self-driving models under attacks and disturbances.
Findings
Comparison results on CARLA platform and real experiments demonstrate strong resilience of the authors’ approach which enhances the navigation performance under disturbances and attacks.
Originality/value
Reliable and resilient navigation performance under various nature disturbances and even external attacks is one of the most urgent needs for real applications of autonomous vehicles nowadays, as these corner cases act as the most commonly occurred risks in potential self-driving accidents. The information reconstruction approach provides a resilient navigation performance enhancement method for existing self-driving models.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.
Details
Keywords
Chenxia Zhou, Zhikun Jia, Shaobo Song, Shigang Luo, Xiaole Zhang, Xingfang Zhang, Xiaoyuan Pei and Zhiwei Xu
The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their…
Abstract
Purpose
The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their outstanding reusability, compact form factor, lightweight construction, heightened sensitivity, immunity to electromagnetic interference and exceptional precision, are increasingly being adopted for structural health monitoring in engineering buildings. This research paper aims to evaluate the current challenges faced by FBG sensors in the engineering building industry. It also anticipates future advancements and trends in their development within this field.
Design/methodology/approach
This study centers on five pivotal sectors within the field of structural engineering: bridges, tunnels, pipelines, highways and housing construction. The research delves into the challenges encountered and synthesizes the prospective advancements in each of these areas.
Findings
The exceptional performance of FBG sensors provides an ideal solution for comprehensive monitoring of potential structural damages, deformations and settlements in engineering buildings. However, FBG sensors are challenged by issues such as limited monitoring accuracy, underdeveloped packaging techniques, intricate and time-intensive embedding processes, low survival rates and an indeterminate lifespan.
Originality/value
This introduces an entirely novel perspective. Addressing the current limitations of FBG sensors, this paper envisions their future evolution. FBG sensors are anticipated to advance into sophisticated multi-layer fiber optic sensing networks, each layer encompassing numerous channels. Data integration technologies will consolidate the acquired information, while big data analytics will identify intricate correlations within the datasets. Concurrently, the combination of finite element modeling and neural networks will enable a comprehensive simulation of the adaptability and longevity of FBG sensors in their operational environments.