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This paper aims to study the oxidation kinetics of the nanocrystalline Al ultrathin films. The influence of structure and composition evolution during thermal oxidation will be observed. The reason for the change in the oxidation activation energy on increasing the oxidation temperature will be discussed.

Al thin films are deposited on the silicon wafers as substrates by vacuumed thermal evaporation under the base pressure of 2 × 10⁻⁴ Pa, where the substrates are not heated. A crystalline quartz sensor is used to monitor the film thickness. The film thickness varies in the range from 30 to 100 nm. To keep the silicon substrate from oxidation during thermal oxidation of the Al film, a 50-nm gold film was deposited on the back side of silicon substrate. Isothermal oxidation studies of the Al film were carried out in air to assess the oxidation kinetics at 400-600°C.

The activation energy is positive and low for the low temperature oxidation, but it becomes apparently negative at higher temperatures. The oxide grains are nano-sized, and γ-Al₂O₃ crystals are formed at above 500°C. In light of the model by Davies, the grain boundary diffusion is believed to be the reason for the logarithmic oxidation rate rule. The negative activation energy at higher temperatures is apparent, which comes from the decline of diffusion paths due to the formation of the γ-Al₂O₃ crystals.

It is found that the oxidation kinetics of nanocrystalline Al thin films in air at 400-600°C follows the logarithmic law, and this logarithmic oxidation rate law is related to the grain boundary diffusion. The negative activation energies in the higher temperature range can be attributed to the formation of γ-Al₂O₃ crystal.

This paper aims to improve the adaptability and control performance of the controller, a proposed seeker optimization algorithm (SOA) is introduced to optimize the controller parameters of a robot manipulator.

In this paper, a traditional proportional integral derivative (PID) controller and a fuzzy logic controller are integrated to form a fuzzy PID (FPID) controller. The SOA, as a novel algorithm, is used for optimizing the controller parameters offline. There is a performance comparison in terms of FPID optimization about the SOA, the genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). The DC motor model and the experimental platform are used to test the performance of the optimized controller.

Compared with GA, PSO and ACO, this novel optimization algorithm can enhance the control accuracy of the system. The optimized parameters ensure a system with faster response speed and better robustness.

A simplified FPID controller structure is constructed and a novel SOA method for FPID controller is presented. In this paper, the SOA is applied on the controller of 5-DOF manipulator, and the validation of controllers is tested by experiments.

This study aims to investigate the noise-inducing characteristics during the start-up process of a mixed-flow pump and the impact of different start-up schemes on pump noise.

This study conducted numerical simulations on the mixed-flow pump under different start-up schemes and investigated the flow characteristics and noise distribution under these schemes.

The results reveal that the dipole noise is mainly caused by pressure fluctuations, while the quadrupole noise is mainly generated by the generation, development and breakdown of vortices. Additionally, the noise evolution characteristics during the start-up process of the mixed-flow pump can be divided into the initial stage, stable growth stage, impulse stage and stable operation stage.

The findings of this study can provide a theoretical basis for the selection of start-up schemes for mixed-flow pumps, reducing flow noise and improving the operational stability of mixed-flow pumps.

Since its inception in 2009, the growth of real-time bidding (RTB) advertising has been dramatic. Yet, there is a dearth of research in the information system (IS) literature despite the potential for negative e-commerce outcomes. The purpose of this paper is to identify salient antecedents of users’ attitude toward RTB advertisements.

A research model was constructed and tested with data from 437 respondents. SmartPLS 3.0, a partial least square (PLS) structural equation modeling (SEM) tool, was used to evaluate the research model and test the hypotheses.

The findings indicate that user attitude is determined by opposing influences from the cognitive and affective attributes of an RTB advertisement. A surprise is found to elicit greater perception of advertisement personalization, timeliness and relevance, as well as privacy and intrusiveness concerns. While RTB advertisement relevance appears to lessen the effect of advertisement intrusiveness, privacy concern is exacerbated when the advertisement is more personalized. The authors discuss the implications of this study for click-through intentions and e-commerce.

At this point in the evolution of RTB advertising, the findings indicate that the surprise generated by the appearance of an RTB advertisement is not currently a “bad” surprise. In addition, the formation of positive user attitude toward RTB is complex because cognitive factors interact with users' concerns to strengthen or weaken the negative effects. The authors also demonstrate that attitude and stimulus–organism–response (S–O–R) theories are useful theoretical bases for the development of causal models to predict RTB attitude and click-through intentions.

Previous research has generally assumed that a homogeneous cultural value exists within a given country. This research aims to identify the regional differences in cultural value based on an urbanization dimension in China, which generate diversity with regard to perceived value and consumer decision‐making styles.

A large‐scale questionnaire was administered to freshmen from major colleges and universities across China to measure cultural value, perceived value, and consumer decision‐making style. The data were analyzed with a multi‐group structural equation model and a stepwise discrimination test.

Results demonstrated significant differences in cultural value, perceived value and consumer decision‐making style among regions with different degrees of urbanization and revealed antecedents and formation of the mechanism of decision‐making style.

Future research should explore more antecedents that influence consumer decision‐making styles and other market dimensions other than urbanization.

The research might provide prominent guidelines for marketers to understand Chinese consumers. Specifically, in regions with different degrees of urbanization, marketers should develop differential strategies to exploit the market given the distinctions in cultural value, perceived value and consumer decision‐making styles.

This study is the first to build a theoretical relational model of cultural value, perceived value and consumer decision‐making styles. And this model revealed the antecedents and formation of the mechanism of decision‐making style.

Automatic guided vehicles (AGVs) are widely used in industrial fields. But most control strategies merely take the lateral force into consideration. This will reduce the accuracy, stability and robustness and will pay additional costs. Therefore, this paper aims to design a control strategy that initially considers lateral force. Thereby, it will improve the accuracy, stability and robustness and reduce the overall cost of AGV.

To achieve the goal of comprehensively improving AGV operating performance, this paper presents a new scheme, combining the dual-wheeled chassis model (DCM) using proportional–integral–differential (PID) control and a supporting quick response (QR) code navigation technology. DCM is the core, which analyzes the deviation caused by lateral force. Then, DCM with PID control by the control law is combined to suppress the errors. Meanwhile, QR code navigation technology provides effective data support for the control strategy.

Most AGV experiments are carried out in a standard environment. However, this study prepares unfavorable scenarios and operating conditions for the experiments that generate detailed data to demonstrate this study’s strategy, which can make an accurate, stable and robust operation process of AGV under various adverse environmental and mechanical factors.

This study proposed DCM, fully considering lateral force and converting the force into velocity. Subsequently, PID controls the speed of two wheels to reduce the error. QR code provides an efficient and low – cost way to obtain information. The three are cleverly combined as a novel industrial AGV control strategy, which can comprehensively improve the operating performance while reducing overall costs.