Search results

The impact of image is widely investigated in various research fields. However, its effect in online health communities is rarely studied. In this research, the authors develop a theoretical model to assess the impact of physicians' image on patients' choices in online health communities.

The authors developed a web crawler based on R language program to collect more than 40,000 physicians' images and other related information from their homepages in Haodf.com–a leading online health community in China. The features of physicians' images are computed by Face++ Application Programming Interface (API) through the following variables: beauty, smile and skin status.

The empirical results derive the following findings: (1) physician's beauty or physical attractiveness has no significant effect on patients’ choice; (2) Smile has a positive effect on patients’ choices; (3) Physician's skin status also positively affects patients' choices; (4) Physician's professional capital strengthens the effect of beauty, smile and skin status on patients' choices; (5) Beauty and skin status are the substitutes for each other, and smile and skin status are the substitutes for each other too.

Also, this study provides implications for both physicians and online health community platform managers.

This study provides new evidence in understanding the impact of physician's online image and contributes to the literature on signaling theory, impression management theory and patients' choices.

Gamification has been widely implemented to improve user engagement in the online health community (OHC). While its effect on the physicians' engagement has recently been documented, whether and how gamification influences the patients' engagement in the OHC remains an untapped research area. The purpose of this study is to fill this dearth by encompassing the gamification strategy of Haodf.com, which awards the “Annual Physician” badges to the physicians, to analyze how this gamification approach motivates patients’ engagement in the OHC.

Real-world data are leveraged from the OHC. The Tobit model is employed for modeling the gamification-patient's engagement nexus in an OHC. Robust findings are obtained by incorporating different measures of a dependent variable, a set of control variables about the physician's characteristics and hospital's features, and alternative estimation techniques.

The results reveal that a patient's engagement in the OHC in the form of appointments and review-posting behavior is enhanced by the gamification strategy. Besides, the positive influence of gamification on the patient's engagement is further strengthened by the physician's professional capital. It is basically obtained that the gamification is an efficacious tool to accelerate not only the physicians' engagement but also of the patients in the OHC platform.

The study provides both theoretical and empirical discussion to enrich the understanding on how OHCs enhance patients' engagement by developing gamification techniques. The findings guide the practitioners of OHC to better understand the implications of their gamification design to optimize user engagement.

This paper aims to research the influence of pressure, friction factors, roughness and actuating speed to the mixed lubrication models of outstroke and instroke.

Mixed lubrication model is solved by finite volume method, which consists of coupled fluid mechanics, deformation mechanics and contact mechanics analyses. The influence of friction factor on the finite element model is also considered. Then, contact pressure, film thickness, friction and leakage have been studied.

It was found that the amount of leakage is sensitive to the film thickness. The larger the film thickness is, the greater the influence received from the friction factor, however, the effect of oil film on the friction is negligible. The friction is determined mainly by the contact pressure. The trend of friction and leakage influenced by actuating velocity and roughness is also obtained.

The influence of friction factor on the finite element model is considered. This can make the calculation more accurate.

Based on the summary and analysis of the particle dynamics, developed in the past 300 years, and of fundamental properties of unevenness of natural materials, we propose the opinion of the second stir. We analyze the gains and loses of employing the non‐dimensionalization method developed in the quantitative analysis system of the first push. Combined with some theoretical models, we also consider the epistemological failures of pure quantification, linearization, and formal logic analysis.

After many years’ practice and experiments, it was found that quantitative analysis systems with unequal quantitative effect cannot be extended into that with equal quantitative effect. While it is related to such epistemological viewpoints as irregularity and continuity systems, an infrastructural form comparison has shown universally scientific and methodological characteristics. In combination with evolution of weather systems, our infrastructural analysis involves applications of super low temperatures, reversed information order, rolling currents infrastructure in reversal weather change and long‐term weather forecasting.

In operational tropical cyclone (TC) forecasting practice, there are usually many TC track guidances available from various official sources. When they do not converge, the guidances need to be ensembled by systematic approaches to formulate the best possible track as an official local TC track forecasting.

The main approach of the research is focused on finding an atmospheric environment favourable for TC survival (genesis) with the help of commonly accepted knowledge in atmospheric physics that reveals mechanism driving evolution and change of synoptic patterns in the atmosphere, using routinely available observational data, i.e. identification of TCF/TCR areas. The techniques developed are then applied to ensemble the TC track guidances available operationally to formulate an official TC track forecasting.

The results show that TC movement is very dependent on the atmospheric environment surrounding a TC. Whether the environment is favourable (TCF) or resistant (TCR) to survival of a TC system is a vital factor to determine where the TC moving. A systematic approach to the identification of the TCR/TCF areas is a key technique to ensemble available TC track guidances to formulate an official TC track forecasting.

In operational TC forecasting, TC track forecasting is the most important and difficult issue. The results indicate that the systematic approach to TC track forecasting has philosophical justification, solid scientific ground, sound logic and practical viability, and thus, make TC track forecasting easy and effective.

The purpose of this paper is to describe an integer linear programming model to schedule the maintenance crew and the maintenance tasks in a bus operating company.

The proposed methodology relies on an integer linear programming model that finds feasible maintenance schedules. It minimizes the costs associated with maintenance crew and the costs associated with unavailability. The model is applied in a real-world case study of a Portuguese bus operating company. A constructive heuristic approach is put forward, based on solving the maintenance scheduling problem for each bus separately.

The heuristic finds better solutions than the exact methods (based on branch-and-bound techniques) in a much lower computational time.

The results suggest the relevance of such heuristic approaches for maintenance scheduling in practice.

This proposed model is an effective decision-making support method that provides feasible maintenance schedules for the maintenance technicians and for the maintenance tasks in a fleet of buses. It also complies with several operational, technical and labour constraints.

To forecast the path of tropic cyclones by using a non‐linear statistical forecasting technique – the method of successive analogy.

Non‐linear statistical forecasting models can describe the non‐linear relationship between the factors and the forecasting objects and the real atmospheric movement more accurately, so they usually have stronger forecasting capability. In practice, however, it is shown that the relationships between predictors and predictands sometimes are so complex that it is very difficult or even impossible to establish the kind of non‐linear mathematical model. Therefore, it is an important topic for atmospheric science to solve non‐linear prediction problem of atmospheric systems by using the non‐function model approach.

The objective and quantitative prediction of tropical cyclone moving path can be given by using the method of successive analogy, a non‐linear forecasting technique, and calculating the similarity parameters between the grayscale field and the height field.

Further experiments are needed to verify this technique.

A very useful technique for solving non‐linear problem.

Illustrates the new technique of solving non‐linear statistic problem and its application.

The purpose of this paper is to present a method to accurately forecast the tendency of the gross amount of energy sources consumption of the country and construct a new kind of algorithm for forecasting that synthesizes the advantages of the grey model, Markov chains, and least square method.

With the application of this new algorithm, this paper have forecasted the trend of the gross amount of energy sources consumption of the country and come to the conclusions that the new algorithm is more precise than the grey model. It is proved that the improved grey‐Markov chain algorithm is effective and can be used by authorities to make decision.

It was found that combining the grey model, Markov chains, and least square method, can be a new algorithm for forecasting the trendency of the gross amount of energy sources consumption.

The new algorithm is only suitable for the short‐term forecast.

The grey forecasting method reflects the overall tendency of primitive data sequence of the gross amount of energy source, and the Markov chain forecasting method reflects the effect of the random fluctuation. The least square method reflects the tendency of increase. The new algorithm is more precise than the grey model.

In order to improve performance robustness of control systems, the discrete variable structure control (VSC) design for uncertain systems and its application to a ship autopilot are to be discussed in this paper.

Discrete‐time variable structure control (DVSC) becomes worth investigating and various DVSC methods have been suggested by many papers. The approach that used the reaching law for controller design can describe how the switching function decreases toward zero and easier to obtain the control law, but this conventional method has some defects not to be ignored. First, due to the influence of the conventional discrete reaching law itself, the system trajectory oscillates in a neighborhood of the origin rather than converges to the origin. Second, this method requires that the uncertainty bound is known as a premise to assure robustness, so creates an over‐conservative controller and enlarges chattering.

It can be shown that the estimation error dynamics can be decoupled from sliding surface dynamics using the proposed scheme. Robust stability of the closed‐loop system can be ensured in the presence of uncertainties with bounded changing rate. No chattering occurs.

To supply useful references to controller design.

A new approach in the design of discrete VSC based on the reaching law approach is presented, a new discrete reaching law, which is stable at the origin, is proposed, and an algorithm for uncertainty estimation is developed in this paper. The proposed algorithm is applied to the control of a ship autopilot servo system. Simulation results show that the controller designed here can track a desired course well and exhibits very good performance robustness.