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To realize stable and precise localization in the dynamic environments, the authors propose a fast and robust visual odometry (VO) approach with a low-cost Inertial Measurement Unit (IMU) in this study.

The proposed VO incorporates the direct method with the indirect method to track the features and to optimize the camera pose. It initializes the positions of tracked pixels with the IMU information. Besides, the tracked pixels are refined by minimizing the photometric errors. Due to the small convergence radius of the indirect method, the dynamic pixels are rejected. Subsequently, the camera pose is optimized by minimizing the reprojection errors. The frames with little dynamic information are selected to create keyframes. Finally, the local bundle adjustment is performed to refine the poses of the keyframes and the positions of 3-D points.

The proposed VO approach is evaluated experimentally in dynamic environments with various motion types, suggesting that the proposed approach achieves more accurate and stable location than the conventional approach. Moreover, the proposed VO approach works well in the environments with the motion blur.

The proposed approach fuses the indirect method and the direct method with the IMU information, which improves the localization in dynamic environments significantly.

Considering the industrial site environment and installation requirements, the straight-beam ultrasound probe with easy installation and good coupling agent adaptability is adopted to replace the traditional water immersion focusing probe for film thickness measurement in cylindrical roller bearings. The straight-beam probe has a large echo receiving range, which will result in measurement regions overlapping and bring about large measurement errors. In this paper, an improved measurement method for film thickness of cylindrical roller bearing with the straight-beam probe is developed.

An improved method is proposed to enhance the spatial resolution of the straight-beam probe. By introducing a correction coefficient based on the percentage of the effective measurement area, the method improves the measuring accuracy successfully.

The experimental results demonstrate that the lubricant-film thickness can be measured to reasonable accuracy by this method and have a better agreement with the theoretical film thickness solutions.

This paper used analytical method and model that is helpful for the improvement of the spatial resolution, which has great influence on the measuring accuracy, is mainly determined by the echo reflection area size of the ultrasound transducer.

Chinese consumers’ cross-border internet shopping, so called “haitao” is an emerging popular trend in China. Haitao can be understood as service innovation process because it creates new market spaces and provides differentiated values for Chinese customers.

This study aims to explore the service innovation strategies and success factors of haitao business in the Chinese market. The authors selected two successful haitao sites of Amazon.cn and Gmarket.co.kr, as representatives of a global player and a niche player, and conducted a comparative case study to analyze their service innovation strategies and key success factors.

This comparative case analysis based on value chain framework revealed some common success factors such as trust, advanced system and alliances as well as their service innovation efforts. Amazon has advantages such as efficient logistics system and global sourcing, whereas Gmarket has advantages such as product category, sales promotions, and payment system.

This study provides some implications for managers with localization, alliances and platform strategies.

This paper aims to analyze the research highlights, evolutionary process and future research directions in the field of tourism forecasting.

This study used CiteSpace to conduct a bibliometric analysis of 1,213 tourism forecasting articles.

The results show that tourism forecasting research has experienced three stages. The institutional collaboration includes transnational collaboration and domestic institutional collaboration. Collaboration between countries still needs to be strengthened. The authors’ collaboration is mainly based on on-campus collaboration. Articles with high co-citation are primarily published in core tourism journals and other relevant publications. The research content mainly pertains to tourism demand, revenue management, hotel demand and tourist volumes. Ex ante forecasting during the COVID-19 pandemic has broadened existing tourism forecasting research. The future forecasting research focuses on the rational use of big data, improving the accuracy of models and enhancing the credibility of forecasting results.

This paper uses CiteSpace to analyze tourism forecasting articles to obtain future research trends, which supplements existing research and provides directions for future research.

本文旨在分析旅游预测领域的研究重点、演化过程和未来的研究方向。

本研究使用 CiteSpace 软件对 1213 篇旅游预测文章进行了文 献计量学分析。

结果表明, 旅游预测研究经历三个阶段。机构合作包含国际机构合作和 国内机构合作, 需要持续加强国家之间的合作, 作者之间的合作多以校内合作为 主。高引用文章不仅发表在旅游领域的核心期刊还发表在其他专业的核心期刊上。 旅游预测研究的主要内容为旅游需求、收入管理、酒店需求和游客量。新冠疫情 期间的事前预测拓宽了现有的旅游预测研究。未来预测的研究重点在于合理利用 大数据, 提高模型的准确定以及提高预测结果的可信度。

本文使用 CiteSpace 分析旅游预测文章得到未来研究趋势, 既是对 现有研究的补充, 又为今后的研究提供方向。

Este artículo pretende analizar los aspectos más destacados de la investigación, el proceso evolutivo y las futuras orientaciones de la investigación en el campo de la previsión turística.

Este estudio utilizó CiteSpace para realizar un análisis bibliométrico de 1213 artículos sobre previsión turística.

Los resultados muestran que la investigación sobre previsión turística ha experimentado tres etapas. La colaboración institucional incluye la colaboración transnacional y la colaboración institucional nacional. La colaboración entre países aún debe reforzarse. La colaboración entre autores se basa principalmente en la colaboración dentro del campus. Los artículos con una alta cocitación se publican principalmente en las principales revistas de turismo y en otras publicaciones relevantes. El contenido de la investigación se refiere principalmente a la demanda turística, el revenue management, la demanda hotelera y los volúmenes turísticos. La previsión previa y durante la pandemia de la COVID-19 ha ampliado la investigación existente sobre previsión turística. La futura investigación sobre previsiones se centra en el uso racional de los big data, la mejora de la precisión de los modelos y el aumento de la credibilidad de los resultados de las previsiones.

Este artículo utiliza CiteSpace para analizar artículos de previsión turística con el fin de obtener futuras tendencias de investigación, lo que complementa la investigación existente y proporciona orientaciones para futuras investigaciones.

This paper aims to investigate the thermal oxidation characteristics of the unsaturated bonds (C=C) of trimethylolpropane trioleate (TMPTO) and to reveal the high temperature oxidation decay mechanism of unsaturated esters and the nature of the anti-oxidation properties of the additives.

Using a DXR laser microscopic Raman spectrometer and Linkam FTIR600 temperature control platform, the isothermal oxidation experiments of TMPTO with or without 1.0 wt. % of different antioxidants were performed.

The results indicated that the Raman peaks of =C-H, C=C and -CH₂- weaken gradually with prolonged oxidation time, and the corresponding Raman intensities drop rapidly at higher temperatures. The aromatic amine antioxidant can decrease the attenuation of peak intensity, as it significantly reduces the rate constant of C=C thermal oxidation. The hindered phenolic antioxidant has a protective effect during the early stages of oxidation (induction period), but it may accelerate the oxidation of C=C afterwards.

Research on the structure changes of synthetic esters during oxidation by Raman spectroscopy will be of great importance in promoting the use of Raman spectroscopy to analyze the oxidation of lubricants.

This paper aims to investigate the tribological behavior and online infrared spectra of three types of lubricating oils containing dinonyl diphenylamine (DNDA) antioxidant, which are mineral oil (MO), poly alpha olefin (PAO) and trimethylolpropane trioleate (TMPTO), during the friction process at high temperature (temperature rising at first and isothermal holding afterwards).

A platform of low speed four-ball tribometer equipped with a temperature controller combined with infrared spectrometer was established. MO, PAO and TMPTO base oils were mixed with 1.0 Wt.% DNDA antioxidant, coded as MO_a, PAO_a and TMPTO_a in sequence. The friction coefficient and online infrared spectra of the oils were tested during the friction process of temperature rising at first and isothermal holding afterwards, and the wear tracks of the upper balls were measured using a confocal scanning optical microscope.

The results indicated that the DNDA antioxidant was depleted to reduce the generation of alcohols and carbonyl products, and the depletion rate of DNDA followed the sequence of MO_a > PAO_a > TMPTO_a. In the temperature rising friction process, the critical transition of friction coefficient was confirmed. The addition of DNDA antioxidant reduced the temperature of the oils at the critical transition of friction coefficient, and the temperature followed the sequence of TMPTO_a > PAO_a > MO_a. After the critical transition, the friction coefficient was first increased and then declined to a steady value; the friction coefficient of MO_a increased and declined first, followed by PAO_a and TMPTO_a. In the steady stage of friction, there was no obvious effect of DNDA on the friction coefficient of the oils. Moreover, DNDA enhanced the wear properties of MO_a and PAO_a; no obvious improvement was revealed for the wear property of TMPTO_a.

The established platform of low speed four-ball tribometer combined with infrared spectrometer successfully realized online testing of the structure changes of lubricating oil during high temperature friction, which can give some reference on the oxidation and friction researches of lubricating oil.

Using typical structure of asphalt pavement in Harbin area of China, and the formula of generalized friction coefficient between base and surface layers of asphalt pavement in cold area is established.

Through structural characteristics analysis of asphalt pavement in cold area, the generalized formula of friction coefficient between base and surface layers of asphalt pavement in cold area is derived. The formula can quickly calculate the friction coefficient between layers of asphalt pavement.

Based on quantitative analysis to the contacting state between layers of asphalt pavement in cold area, the relationships between generalized friction coefficient and resilient modulus of asphalt mixtures, temperature shrinkage coefficient and temperature have been established.

The findings can enrich the description methods about the contacting state between layers of asphalt pavement, and have a certain theoretical and practical value. Through the application of the formula of generalized friction coefficient between layers, it can provide a technical basis for the asphalt pavement design, construction and maintenance in cold area.

The symmetrical valve is usually used in the hydraulic servo control system to control the asymmetrical cylinder, but this system’s structure involves asymmetry, and so its dynamic characteristics are asymmetrical, which causes issues in the control system of symmetric response. The purpose of this paper is to achieve the aim of symmetric control.

In this paper, the authors proposed a method that combined wavelet neural network (WNN) and model reference adaptive control. The reference model determined the dynamic response that the system was expected to achieve, and the WNN adaptive control made the system follow the reference model to achieve the purpose of symmetric control.

The experimental results show that the method can achieve a more accurate symmetric control and position control compared with the solutions via the classical PID control.

The proposed combination of the WNN and the reference model can effectively compensate for the asymmetry of dynamic response of the asymmetric cylinder in forward and return directions, which can be extended to deal with other classes of applications.

Additive manufacturing (AM) has shown its capability in producing complex geometries. Due to the additive nature, the in situ layer-wise inspection of geometric accuracy is essential to making AM reach its full potential. This paper aims to propose a novel automated in-plane alignment and error quantification framework to distinguish the fabrication, measurement and alignment errors in AM.

In this work, a multi-resolution framework based on wavelet decomposition is proposed to automatically align two-dimensional point clouds via a polar coordinate representation and then to differentiate errors from different sources based on a randomized complete block design approach. In addition, a two-stage optimization model is proposed to find the best configuration of the multi-resolution framework.

The proposed framework can not only distinguish errors attributed to different sources but also evaluate the performance and consistency of alignment results under different levels of details.

A sample part with different featured layers, including a simple free-form layer, a defective layer and a layer with internal features, is used to illustrate the effectiveness and efficiency of the proposed framework. The proposed alignment method outperforms the widely used iterative closest point algorithm.

This work fills a research gap of state-of-the-art studies by automatically quantifying different types of error inherent in manufacturing, measuring and part alignment.

To contribute to achieving the Sustainable Development Goals, this study aims to explore how to encourage innovative green behaviors among college students and the mechanisms behind the formation of green innovation behavior. Specifically, this study examines the influences of schools, mentors and college students themselves.

A multilevel, multisource study involving 261 students from 51 groups generally supported this study’s predictions.

Proenvironmental and responsible mentors significantly predicted innovative green behavior among college students. In addition, creative motivation mediated the logical chain among green intellectual capital, emotional intelligence and green innovation behavior.

The study findings offer new insights into the conditions required for college students to engage in green innovation. In addition, they provide practical implications for cultivating green innovation among college students.

The authors proposed and tested a multilevel theory based on the ability–motivation–opportunity framework. In this model, proenvironmental and responsible mentors, green intellectual capital and emotional intelligence triggered innovative green behavior among college students through creative motivation.