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The purpose of this paper is to provide a safe control strategy for aloft hot-line assembly of connection fittings in 110kV intelligent substations, which is significant to research on hot-line working robots.

This paper addresses challenges of the task and establish the contact models of connection fittings. By using this control strategy, neither high precision vision positioning nor preset global reference coordinate system is required. Visual computing only needs to provide an approximately position for the manipulator end-effector, after which the connection fittings assembly task could be completed with the posture of the manipulator adjusted following the guidance by force-position control. The authors also analyze the influence of the intervention of manipulators on the very non-uniform electric field during the operation.

This strategy will be particularly useful for the hot-line assembly of connection fittings in 110kV intelligent substations as well as some assembly tasks where uncertain target position and complex contact surface such as cylindrical hole is involved.

This assembly strategy is tested in energized simulated experimental system. The experiment results show that the robot can replace the manual operation to complete the assembly task safely and efficiently.

This assembly strategy is able to achieve the assembly task of connection fittings. Unlike other peg-in-hole assembly strategy, it does not require high stability of manipulator or plane contact surface around the hole.

This paper examines the problem of lack of historical data and inadequate consideration of factors influencing demand in the forecasting of demand for fast fashion clothing and proposes an improved Bass model for the forecasting of such a demand and the demand for new clothing products.

From the perspective of how to solve the lack of data and improve the precision of the clothing demand forecast, this paper studies the measurement of clothing similarity and the addition of demand impact factors. Using the fuzzy clustering–rough set method, the degree of resemblance of clothing is determined, which provides a basis for the scientific utilisation of historical data of similar clothing to forecast the demand for new clothing. Besides, combining the influence of consumer preferences and seasonality on demand forecasting, an improved Bass model for a fast fashion clothing demand forecast is proposed. Finally, with a forecasting example of demand for clothing, this study also tests the validity of the method.

The objective measurement method of clothing similarity in this paper solves the problem of the difficult forecasting of demand for fast fashion clothing due to a lack of sales data at the preliminary stage of the clothing launch. The improved Bass model combines, comprehensively, consumer preferences and seasonality and enhances the forecast precision of demand for fast fashion clothing.

The paper puts forward a scientific, quantitative method for the forecasting of new clothing products using historical sales data of similar clothing, thus solving the problem of lack of sales data of the fashion.

To explore how the blockchain affects the pricing and financing decisions in a low-carbon platform supply chain.

Considering the dual roles of the e-commerce platform as a seller and an initiator, a typical game-theoretical method is applied to analyze the behavior of supply chain decision-makers and the impact of key variables on equilibriums.

When loan interest rates are symmetric, whether blockchain is used or not, the e-commerce platform financing mode will always produce higher wholesale price and unit carbon emission reduction, while the retail price is the opposite. Higher unit additional income brought by the blockchain can bring higher economic and environmental performances, and the e-commerce platform financing mode is superior to bank financing mode. The application of blockchain may cause the manufacturer to change his/her financing choice. For bank financing, with the increase of loan interest rates, the advantages brought by blockchain will gradually disappear, but this situation will not occur under e-commerce platform financing.

Blockchain is known for its information transparency properties and its ability to enhance user trust. However, the impacts of applying blockchain in a low-carbon platform supply chain with different financing options are not clear. The authors examine the manufacturer's strategic choices for platform financing and bank financing, whether to adopt blockchain, and the impact of these decisions on carbon emissions reduction, consumer surplus and social welfare. The research conclusion can provide reference for the operation and financing decisions of platform supply chain under the carbon reduction target in the digital economy era.

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.

To examine how shareholding affects optimal profits, R&D innovation, NEV market scale and social welfare in two supply chain models with partial and cross ownership patterns.

The gradual retreat of government subsidies has directly weakened the financial support available to the stakeholders of new energy vehicles (NEVs). In this context, upstream and downstream enterprises of NEV are constantly seeking new business models of cooperation to achieve possible win-wins. NEV supply chain shareholding is an emerging new practice for such explorations. However, its performance in the NEV supply chain is seldom investigated. In this paper, we employ a Stackelberg game model to investigate how partial and cross-ownership affect the optimal decisions in a NEV supply chain.

Results showed that: (1) Compared with the unilateral shareholding model, the battery supplier will benefit from cross-ownership in the supply chain, while the NEV manufacturer will not necessarily benefit from it. At the same time, cross-ownership will bring the greatest incentive for battery R&D (2) Supply chain downstream competition will not necessarily lead to the improvement of the total consumption of NEVs or the level of battery design. Pareto improvement can be brought only when one of the manufacturers holds less than a certain equity threshold. In addition, downstream competition will also not necessarily bring more benefits to the battery supplier.

At present, NEV supply chain management has attracted widespread attention from scholars from all walks of life. Previous studies have been carried out that covers topics such as pricing strategies and optimal profits and the role of NEV in the sustainable development of the automotive industry supply chain, or disparate impacts of government subsidies and carbon emission regulation on supply chain members. However, as far as the authors know, compared with the new emerging NEV corporate practice, the shareholding phenomenon between upstream and downstream in the supply chain of NEV has not been studied in the existing studies.

Today clothing has become the largest category in online shopping in China, and even in Asia-Pacific. The satisfaction degree of apparel online shopping can be improved by effective personalized recommendation. The purpose of this paper is to propose a personalized recommendation model and algorithm based on Kansei engineering, traditional filtering algorithm and the knowledge relating to apparel.

Users’ perceptual image and the design elements of apparel based on Kansei engineering are discussed to build the mapping relation between the design elements and user ratings employing verbal protocol, semantic differential and partial least squares. The implicit knowledge and emotional needs pertaining to users are accessed using analytic hierarchy process. A personalized recommendation model for apparel online shopping is established and the algorithm for the personalized recommendation process is proposed. To present the personalized recommendation model, men’s plaid shirts are taken as the example, and the recommendations of apparel for online shopping were implemented and ranked in the context of differing users’ emotional needs. A comparison between the traditional model and this model is made to verify the effectiveness.

The recommendation model is capable of analyzing data and information effectively, and providing fast, personalized apparel recommendation services in accordance with users’ emotional needs. The experimental results suggest that the model is effective.

Similar researches of recommendation mainly focus on the field of computer science, the basic idea of which is using users’ history accessing records or the preferences of other similar users for determination of users’ preferences. Since the attributes of apparel products are not factored in the approach referred above, the issue of personalized recommendation cannot be solved in a really effective way. Combining Kansei engineering and recommendation algorithm, a framework for apparel product recommendation is presented and it is a new way for improvement of recommendations for apparel products on shopping sites.

This paper aims to compare the electronic properties of perylene diimide derivatives (DFPDI) and its anion radical (DFPDI.^-k.⁺) thin film by drop-coating of organic molecules on the interdigitated electrodes.

The authors compared the electronic properties of perylene diimide derivatives and its anion radical by drop-coating of organic molecules on interdigitated electrodes. Significantly, the current of perylene diimide derivatives anion radical increased by 2∼3 orders of magnitude compared to perylene diimide derivatives under a bias of 5 V, and the maximal current of anion radical that from tetrahydrofuran solution can reach 3.6 mA. Furthermore, DFPDI.^-k.⁺ thin film showed time-resistance sensitivity for acetic acid. When DFPDI.^-k.⁺ thin film was placed in acetic acid of 3.1 × 105 ppm, the current was decreased 46 times under a bias of 6 V after 8 min.

We developed the new method to prepare ambient stable perylene diimide derivatives anion radical, which shows sensitivity of absorption spectra to acid.

Perylene diimide derivatives anion radical thin film showed time-resistance sensitivity for acetic acid, suggesting potential application of perylene diimide derivatives anion radical as acid sensor.

Except the physiological comfort, the design aesthetic of plaid shirts is the decisive factor affecting the purchase decision making of consumers. However, as there is subjectivity and indeterminacy in evaluation of the aesthetic, current research in the literature has little information about the appearance design of checks. The purpose of this paper is to extract the check design features, which influence consumer evaluation, and determine the preferences of men of different ages for the check designs, and the preference differences between them.

Through cluster and preference experiments, the perception and evaluation of the subjects were gained. By cluster analysis, typical classifications of check designs were fixed. With Multidimensional Scaling (MDS) algorithm, users’ perceptual space was revealed as to the plaid samples. In the PREFMAP analysis, results of the ideal vectors of men of different ages were drawn.

The study results revealed four typical classifications of check designs, identified three design dimensions that had effects on users’ evaluation, and built the relationship between design features of checks and consumer evaluation. Besides, in the study, the differences in preference for check designs between men of different ages were also explored. It was found that young men liked modern check designs, but disliked “small and complex” check patterns. Middle aged men preferred dark and cool colors, with dislike for “youthful vigor style.” While they cared more about check colors, young men attached more importance to the design style.

Currently, there is little information in the literature about the evaluation of pattern design. In this study, the use of MDS and PREFMAP analysis reveals visualized complex statistical results. The visualization approach is also applicable to design and positioning of other apparel, and can help designers better understand and position design styles and effects, given their consumer groups and design samples.

The purpose of this paper is to study the influence of the porous structure on the maximum stress and modulus of elasticity of the specimens which are fabricated by rapid prototypes. According to the experimental results, modify the theoretical formula of elastic modulus.

The Objet Eden 250 was used to prepare the Vero White photosensitive resin samples with different porosity (ranges from 25 to 65 per cent) and different pore structures. The mechanical properties of different samples were numerically simulated and the formulas of the modulus of elasticity were established. Through the compression test, the performance of the specimen is compared and analyzed, and the theoretical elastic modulus formula is optimized.

With the increase of porosity, the maximum stress of honeycomb structure specimens decreases. The maximum stress of the honeycomb structure specimen with circular pore shape is higher than the hexagon cross-section while the hexahedron and octahedron structure are the arms (wall thickness between pores) with a square cross-section. The error comparison between the modulus of elasticity before and after the structure models regression analysis shows that after the regression analysis, the error of theoretical value and the actual value is between 0 and 14 per cent which is lower than the value before the regression analysis which was between 5 and 27 per cent.

The paper obtains rules of the influence of different porous structures which were fabricated by the Vero White photosensitive resin material on mechanical properties and higher prediction accuracy formula of elastic modulus. The conclusions provide a theoretical basis for Northeastern University, China, to reduce mass and mechanical properties prediction of load-bearing parts.

This paper aims to identify the relationship between users' perception image, clothing design features and users' preference and propose a clothing design scheme based on users perception image and users' preference.

In this paper, men's suit is composed into multiple design features under the design elements. Using the orthogonal experiment method, 16 schemes of the representative suit are designed. Through perception evaluation experiment, users' perception images and preference degree of the samples are obtained. By partial least squares (PLS) analysis method, the models between users' perception image, suit design features and users' preference are built.

The interrelationship between the three is identified by establishing PLS models between users' perception image, suit design features and users' preference. According to the coefficients of the models, the optimization schemes of men's suits considering users' perception image and preference are proposed. Verification results show that the optimization schemes are significantly better than other schemes.

The results of this paper can be used for consumer demand-oriented clothing design and provide references and methods for converting consumer's perceived needs into clothing design features.