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The purpose of this research is to develop a time-cost optimization model to schedule repetitive projects while considering limited resource availability.

The model is based on the constraint programming (CP) framework; it integrates multiple scheduling characteristics of repetitive activities such as continuous or fragmented execution, atypical activities and coexistence of different modes in an activity. To improve project performance while avoiding inefficient hiring and firing conditions, the strategy of bidirectional acceleration is presented and implemented, which requires keeping regular changes in the execution modes between successive subactivities in the same activity.

Two case studies involving a real residential building construction project and a hotel refurbishing project are used to demonstrate the application of the proposed model based on four different scenarios. The results show that (1) the CP model has great advantages in terms of solving speed and solution quality than its equivalent mathematical model, (2) higher project performance can be obtained compared to using previously developed models and (3) the model can be easily replicated or even modified to enable multicrew implementation.

The original contribution of this research is presenting a novel CP-based repetitive scheduling optimization model to solve the multimode resource-constrained time-cost tradeoff problem of repetitive projects. The model has the capability of minimizing the project total cost that is composed of direct costs, indirect costs, early completion incentives and late completion penalties.

Interrupting work continuity provides a way to improve some project performance, but unexpected and harmful interruptions may impede the implementation. This paper aims to mitigate the negative impact caused by work continuity uncertainty based on the notion of robustness.

This paper develops a float-based robustness measurement method for the work continuity uncertainty in repetitive projects. A multi-objective optimization model is formulated to generate a schedule that achieves a balance between crew numbers and robustness. This model is solved using two modules: optimization module and decision-making module. The Monte Carlo simulation is designed to validate the effectiveness of the generated schedule.

The results confirmed that it is necessary to consider the robustness as an essential factor when scheduling a repetitive project with uncertainty. Project managers may develop a schedule that is subject to delays if they only make decisions according to the results of the deadline satisfaction problem. The Monte Carlo simulation validated that an appropriate way to measure robustness is conducive to generating a schedule that can avoid unnecessary delay, compared to the schedule generated by the traditional model.

Available studies assume that the work continuity is constant, but it cannot always be maintained when affected by uncertainty. This paper regards the work continuity as a new type of uncertainty factor and investigates how to mitigate its negative effects. The proposed float-based robustness measurement can measure the ability of a schedule to absorb unpredictable and harmful interruptions, and the proposed multi-objective scheduling model provides a way to incorporate the uncertainty into a schedule.

To reduce the effect of parameter uncertainties and input saturation on path tracking control for autonomous combine harvester, a path tracking controller is proposed, which integrates an adaptive neural network estimator and a saturation-aided system.

First, to analyze and compensate the influence of external factors, the vehicle model is established combining a dynamic model and a kinematic model. Meanwhile, to make the model simple, a comprehensive error is used, weighting heading error and position error simultaneously. Second, an adaptive neural network estimator is presented to calculate uncertain parameters which eventually improve the dynamic model. Then, the path tracking controller based on the improved dynamic model is designed by using the backstepping method, and its stability is proved by the Lyapunov theorem. Third, to mitigate round-trip operation of the actuator due to input saturation, a saturation-aided variable is presented during the control design process.

To verify the tracking accuracy and environmental adaptability of the proposed controller, numerical simulations are carried out under three different cases, and field experiments are performed in harvesting wheat and paddy. The experimental results demonstrate the tracking errors of the proposed controller that are reduced by more than 28% with contrast to the conventional controllers.

An adaptive neural network-based path tracking control is proposed, which considers both parameter uncertainties and input saturation. As far as we know, this is the first time a path tracking controller is specifically designed for the combine harvester with full consideration of working characteristics.

Despite the widespread expectation that additive manufacturing (AM) will become a disruptive technology to transform the spare parts supply chain, very limited research has been devoted to the quantitative modeling and analysis on how AM could fulfill the on-demand spare parts supply. On the other hand, the choice of using AM as a spare parts supply strategy over traditional inventory is a rising decision faced by manufacturers and requires quantitative analysis for their AM-or-stock decisions. The purpose of this paper is to develop a quantitative performance model for a generic powder bed fusion AM system in a spare parts supply chain, thus providing insights into this less-explored area in the literature.

In this study, analysis based on a discrete event simulation was carried out for the use of AM in replacement of traditional warehouse inventory for an on-demand spare parts supply system. Generic powder bed fusion AM system was used in the model, and the same modeling approach could be applied to other types of AM processes. Using this model, the impact of both spare parts demand characteristics (e.g. part size attributes, demand rates) and the AM operations characteristics (e.g. machine size and postpone strategy) on the performance of using AM to supply spare parts was studied.

The simulation results show that in many cases the AM operation is not as cost competitive compared to the traditional warehouse-based spare parts supply operation, and that the spare parts size characteristics could significantly affect the overall performance of the AM operations. For some scenarios of the arrival process of spare parts demand, the use of the batched AM production could potentially result in significant delay in parts delivery, which necessitates further investigations of production optimization strategies.

The findings demonstrate that the proposed simulation tool can not only provide insights on the performance characteristics of using AM in the spare parts supply chain, especially in comparison to the traditional warehousing system, but also can be used toward decision making for both the AM manufacturers and the spare parts service providers.

This paper aims to discuss major influencing factors causing users’ mobile social media fatigue and divides them into three hierarchies, including causal factors, intermediary factors and outcome factors. The study also sorts out connections between different levels of factors, thus providing effective guidance for the sustained development of social media.

Based on the grounded theory and by collecting data through in-depth interviews, the authors use open coding, axial coding and selective coding to analyze major influencing factors of users’ mobile social media fatigue, build a model using the software NVivo 11, organize and analyze mobile social media fatigue behavior and identify the relationships by combining the interpretive structural model and explore connections among the factors.

The influencing factors of mobile social media fatigue behavior conform with the stressors-strains-outcomes (SSO) theoretical framework, where stressors (S) include the five factors of fear of missing out, perceived overload, compulsive use, time cost and privacy concerns; strains (S) include the five factors of a low sense of achievement, emotional anxiety, reduced interest, social concerns and emotional exhaustion; outcomes (O) include the six factors of neglect behavior, diving behavior, avoidance behavior, tolerance behavior, withdrawal behavior and substitution behavior.

It focuses on the discussion of the interactions between users’ stressors, strains and outcomes without fully considering the impact of social environment and educational background on social media fatigue behavior. This study only focuses on one social media platform in the Chinese context, namely, WeChat. We reply on the qualitative research method to construct the relationships between social media fatigue factors because we were mainly interested in how users would respond psychologically and emotionally to social media fatigue behavior.

The study has extended the application of the SSO theory. Additionally, the research method and model used in this paper may serve as guidelines to other interested scholars who intend to explore relevant variables and conduct further research on the influencing factors of social media fatigue. In analyzing the causality of social media fatigue, the study has integrated the intermediary factor strain to display users’ strains from social media stress with a more detailed path discussion on the causality of social media fatigue, which has not received broad attention in previous research literature on social networking services users’ use.

In this study, text data are collected in a diversity of forms combined, allowing respondents to answer questions without being limited by the questions in the questionnaire, which helped us to identify new variables of social media fatigue. As a result, we were able to dig out the fundamental causes of social media fatigue and potential connections between the factors. Relevant scholars, users and businesses may analyze, manage and forecast users’ social media fatigue behavior by analyzing the type of social media stress and users’ state, providing guidance for the proposal of corresponding management strategies.

Most relevant studies focus on the sustained use of social media, and there is a scarcity of studies on social media fatigue in China. There is very limited research that conducts model analysis of social media fatigue through the integration of stressors, strains and outcomes.

This study aims to investigate the effect of vapor phase corrosion inhibitor (VCI) imidazoline, quinoline and urea on E36 ship steel in simulated marine atmospheric environment.

The inhibitive effect was investigated by weight loss, potentiodynamic polarization, electrochemical impedance and Raman spectroscopy.

The corrosion process was inhibited by adsorption of the three VCIs on the surface of ship steel. The corrosion inhibition mechanism is the adsorption film type. The corrosion inhibitor adsorbs on the metal surface to prevent Cl^- from reaching the surface of the substrate, so as to achieve the corrosion inhibition effect.

To the best of the authors’ knowledge, the work described was original research that has not been published previously and not under consideration for publication elsewhere, in whole or in part.

The purpose of this paper is to introduce the structure design process of the cantilever spindle with limited installation space and wishing to increase its critical speed.

In this paper, the finite element method was used to analyze the influence of the supporting stiffness and the structure of the spindle on the critical speed, and then the structure of the spindle was designed; moreover, the experiment was accomplished and the experiment results show that the spindle can work stably.

Through analyzing the influence of the supporting stiffness and the structure of the spindle on the critical speed, the following conclusions could be obtained: the shape of the first-mode is the bend vibration of the cantilever of the spindle; the first-order critical speed of the spindle gradually decreases with the diameter and length of the cantilever increasing; the first-order critical speed of the spindle increases with the depth and diameter of the blind hole increasing; and the experiment was accomplished and the experiment results show that the spindle can work stably.

In this paper, the finite element method was used to design the spindle of the testing machine, and satisfactory results were obtained. It can provide a theoretical reference for the design of a similar spindle.

This study developed two presentation modes of scientific articles and evaluated their usability with user experiments.

Two presentation modes of scientific articles, simply referred to as “genre presentation mode” and “argument presentation mode”, were constructed based on their genre structure and argument structure respectively. Their usability was evaluated by being compared against the existing RichHTML presentation mode in the experiments using eye-tracking and questionnaire methods.

The participants who were going to find the specific information of scientific articles rated the genre presentation mode higher than they did with either the argument or the RichHTML presentation mode for effectiveness. In contrast, those who were going to understand the general idea of scientific articles rated both the genre and argument presentation mode higher than they did with the RichHTML mode. In terms of efficiency, the participants took less reading time when the articles of non-native language were presented with the genre mode than they did when the articles were presented with the argument mode. When reading the articles in native language to understand the general idea, the participants took less reading time for the articles presented with the argument mode than they did for the articles presented with the genre mode. In comparison, they took less reading time when the articles were presented with the argument mode if they were going to find specific information. For satisfaction, the genre presentation mode was more popular than the argument mode and the RichHTML mode. However, the participants were less satisfied with the argument presentation mode than the other two when reading in native language and intending to find specific information.

The two presentation modes of scientific articles are found to improve the accuracy of information acquisition, shorten the total reading time and be more acceptable by readers.

The purpose of this paper is to propose an identification algorithm to obtain generalized attitude model (GAM) of satellites in on‐orbit environment, which includes missing attitude data and multi‐noise. The identified GAM and noise model are the basis of attitude control and state estimation on‐orbit.

To cope with noises contaminating both input and output of attitude model, the errors‐in‐variables model is transformed into a traditional Box‐Jenkins model according to the attitude control loop. The wavelet denoising (WD) technique is helpful to predict the missing output data using the identified GAM.

By the numerical simulation, it is verified that the proposal accompanied with WD has a faster prediction capability than that of the algorithm without WD. As a result, the proposed approach is suitable to attitude model identification of on‐orbit satellites.

This identification algorithm can deal with two kinds of on‐orbit conditions and has a fast parameter convergent rate. Therefore, it has a practical application value in on‐orbit environment.

The main purpose of this paper is to explore the influence mechanism of corporate social responsibility (CSR) for smart cities on consumers' purchase intention. The authors aim to identify the key components of CSR for smart cities based on the perspective of consumers, namely responsibility toward consumers, environment and community and validate their relationship.

The authors exploit data collected by questionnaire surveys to estimate the effects of CSR for smart cities on consumers' purchase intentions and to investigate the statistical causality between them. The multilinear regression model is used to figure out the different impact levels of the three dimensions of CSR for smart cities on consumers' purchase intention.

The results illustrate that CSR for smart cities and its three dimensions all have significant positive impacts on consumers' purchase intentions. Besides, consumer–corporate identity (CCI) exerts a partial mediation effect on this influence mechanism.

This research is based on a rather small sample size. Besides, due to the time limitation and other factors, some other control variables are neglected in the regression model. Therefore, the impact level could be distorted.

The authors put forward management implications according to research conclusions. Corporates should actively fulfill the CSR in the field of consumer responsibility to boost consumers' purchase intention. Corporate should strengthen the interaction with consumers to improve their corporate identity.

The main contribution of this paper is to provide convincing evidence of the impacts of CSR for smart cities on consumer purchase intention (CPI), thus proposing effective measures for corporates to win more consumers by taking on social responsibility for smart cities. This paper takes CCI as mediating variable to deepen the understanding of the impacts of CSR for smart cities on CPI, which is innovative and beneficial to enriching literature in related fields.