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Accurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.

Physics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.

The results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.

The main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

The paper aims to clarify the effects of brand differentiation on the platform's formulation of channel strategy and help the online platform formulate the optimal channel strategy, which involves selecting a proper selling mode for each brand.

The paper develops a multistage game model consisting of one online platform and two competing manufacturers with differentiated brands and examines the effects of brand differentiation on these three channel members' profits under each candidate channel strategy.

The results show that the platform prefers to offer the reselling mode for both brands when the brand differentiation is low, and this preference will be enhanced by the decrease in order fulfilment cost. By contrast, when the brand differentiation is high, it will offer the reselling mode for the premium brand but the marketplace service for the economy brand if the order fulfilment cost is not high; or the marketplace mode will be offered to both brands if this cost is high.

This study assumes that the order fulfilment costs of platform and manufacturer are fixed and symmetric. Therefore, researchers are encouraged to consider asymmetric costs of order fulfilment.

The paper guides the online platform to formulate the optimal channel strategy for differentiated brands and provides managerial insights for differentiated brands entering online markets.

This paper explores platforms' optimal channel strategy by jointly considering the effects of brand differentiation and investigates the impacts of brand differentiation on the optimal decision making under four candidate options. Moreover, this paper has been extended to examine the case when the manufacturers' production costs cannot be neglected.

This paper aims to develop a robotic mirror therapy system for lower limb rehabilitation, which is applicable for different patients with individual movement disability levels.

This paper puts forward a novel system that includes a four-degree-of-freedom sitting/lying lower limb rehabilitation robot and a wireless motion data acquisition system based on mirror therapy principle. The magnetorheological (MR) actuators are designed and manufactured, whose characteristics are detected theoretically and experimentally. The passive training control strategy is proposed, and the trajectory tracking experiments verify its feasibility. Also, the active training controller that is adapt to the human motor ability is designed and evaluated by the comparison experiments.

The MR actuators produce continuously variable and compliant torque for robotic joints by adjusting excitation current. The reference limb joint position data collected by the wireless motion data acquisition system can be used as the motion trajectory of the robot to drive the affected limb. The passive training strategy based on proportional-integral control proves to have great trajectory tracking performance through experiments. In the active training mode, by comparing the real-time parameters adjustment in two phases, it is certified that the proposed fuzzy-based regulated impedance controller can adjust assistance torque according to the motor ability of the affected limb.

The system developed in this paper fulfills the needs of robot-assisted mirror therapy for hemiplegic patients.

Smog seriously affects the ecological environment and poses a threat to public health. Therefore, smog control has become a key task in China, which requires reliable prediction.

This paper establishes a novel time-lag GM(1,N) model based on interval grey number sequences. Firstly, calculating kernel and degree of greyness of the interval grey number sequence respectively. Then, establishing the time-lag GM(1,N) model of kernel and degree of greyness sequences respectively to obtain their values after determining the time-lag parameters of two models. Finally, the upper and lower bounds of interval grey number sequences are obtained by restoring the values of kernel and degree of greyness.

In order to verify the validity and practicability of the model, the monthly concentrations of PM2.5, SO2 and NO2 in Beijing during August 2017 to September 2018 are selected to establish the time-lag GM(1,3) model for kernel and degree of greyness sequences respectively. Compared with three existing models, the proposed model in this paper has better simulation accuracy. Therefore, the novel model is applied to forecast monthly PM2.5 concentration for October to December 2018 in Beijing and provides a reference basis for the government to formulate smog control policies.

The proposed model can simulate and forecast system characteristic data with the time-lag effect more accurately, which shows that the time-lag GM(1,N) model proposed in this paper is practical and effective.

Based on interval grey number sequences, the traditional GM(1,N) model neglects the time-lag effect of driving terms, hence this paper introduces the time-lag parameters into driving terms of the traditional GM(1,N) model and proposes a novel time-lag GM(1,N) model.

The selection of purchasing channels by wine consumers indirectly affects buying experience and satisfaction, therefore, it is of great practical significance to study consumers' preference on channel selection. The purpose of this study is to investigate the current state of consumer selection for purchasing channel and the corresponding influencing factors.

A total of 2,976 valid questionnaires were collected by convenience sampling from 34 provinces, municipalities and autonomous regions of China in 2020 via the Internet, yielding a response rate of 82.2%. A categorical statistical approach was used to understand consumer's selection for each channel. Besides, binary logistic regression model was used to analyze the factors affecting consumers' channel selection.

The results show that Chinese wine consumers' main purchasing channels are as follows: supermarket/mall, wine specialty stores, comprehensive e-business flagship stores, comprehensive e-business individual stores, restaurants and short video and live streaming platforms. Estimation results showed that among the 12 influencing factors in 4 categories, consumers' education and some other factors significantly influenced consumers' decision on wine purchasing channels.

Limited by time and experimental conditions, this study did not analyze the trend of wine consumers' purchasing channel selection. Future work would concentrate on multi-year data and conduct longitudinal comparative analysis.

This study innovatively subdivides the currently popular wine sales channels in Chinese market and conducts research related to consumer channel selection. The results of the study can provide reference for wine producers and distributors to update their strategic layout and also help various channels to understand the characteristics of their customer groups for targeted marketing.

This paper aims to propose a bilateral robotic system for lower extremity hemiparesis rehabilitation. The hemiplegic patients can complete rehabilitation exercise voluntarily with the assistance of the robot. The reinforcement learning is included in the robot control system, enhancing the muscle activation of the impaired limbs (ILs) efficiently with ensuring the patients’ safety.

A bilateral leader–follower robotic system is constructed for lower extremity hemiparesis rehabilitation, where the leader robot interacts with the healthy limb (HL) and the follow robot is worn by the IL. The therapeutic training is transferred from the HL to the IL with the assistance of the robot, and the IL follows the motion trajectory prescribed by the HL, which is called the mirror therapy. The model reference adaptive impedance control is used for the leader robot, and the reinforcement learning controller is designed for the follower robot. The reinforcement learning aims to increase the muscle activation of the IL and ensure that its motion can be mastered by the HL for safety. An asynchronous algorithm is designed by improving experience relay to run in parallel on multiple robotic platforms to reduce learning time.

Through clinical tests, the lower extremity hemiplegic patients can rehabilitate with high efficiency using the robotic system. Also, the proposed scheme outperforms other state-of-the-art methods in tracking performance, muscle activation, learning efficiency and rehabilitation efficacy.

Using the aimed robotic system, the lower extremity hemiplegic patients with different movement abilities can obtain better rehabilitation efficacy.

Over recent decades, talent agglomeration has emerged as a critical topic for scholars, businesses and government officers. Innovative ability is a core competition for high-tech talents. In China, low innovation is the bottleneck, as the high-tech industry usually cannot provide sufficient support for the continuous needs of innovative talents. To enhance the continuous support of talents, it is important to obtain the mechanisms of talent evaluation and flow in high-tech industry. Exploring the incentive factors influencing the scientific and technological personnel, adjust the layout of talents and promote the rational agglomeration. It’s significant to realize the regional economic development.

This study proposes an assessment model using the multi-criteria decision-making method of analytical hierarchy process (AHP) to determine the weights of incentive factors and a nonlinear programing model, from micro, meso and macro perspectives of individual, organizational and social incentives by adopting Maslow’s hierarchy of needs theory, Kurt Lewin’s field theory and Lee’s push-pull theory. After the literature review and interviews with 14 experts, this study produced a research framework and a pairwise comparison questionnaire. In addition, the relative quantitative weights of 3 main categories and 15 indicators are identified and ranked based on the AHP method.

The results demonstrate that the most important dimension is the individual, and the top three highest weighted factors are job satisfaction, sense of working accomplishment and interpersonal relationships. The discussion in this study showed that the proposed model is rational and acceptable to motivate high-tech innovation talent (HTIT) agglomeration for high-tech enterprises, universities, government and start-ups.

The pairwise comparison using the AHP method is limited to expert opinions, which are considered comparatively subjective. The number of incentive factors should be increased, as some indicators may have been omitted from the AHP model.

According to the results, some suggestions can be recommended to corporate executives, HR managers and government officers to attract and retain high-tech talents and further to improve industrial clusters and economic development.

This paper derives a relative ranking of importance based on the opinions of experienced HR specialists, high-tech talent, scholars and government official, and assesses the consistency of results. The ordering represents the importance of indicators and sub-indicators of two levels from respondents’ perspectives in an industry cluster background. The study, focusing on the high-tech industry in China (which is a developing country), offers a unique view, as earlier studies mainly collect data from developed countries.

We argue that the influence of public stakeholders (the state) and private stakeholders (nonstate social or economic stakeholders) on corporate philanthropy is interdependent, in that satisfying the state may increase the degree of scrutiny and pressure exerted by private stakeholders on the firm, particularly in institutional environments that place few checks and balances on the power of the state – thus creating suspicion that political patronage shelters firms’ social and moral wrongdoing. To test this theory, we examine the circumstances under which politically patronized firms engage more (or less) in corporate philanthropy. Utilizing a dataset that encompasses both publically traded and unlisted private firms in China, we find that corporate philanthropy is negatively associated with political patronage among unlisted firms but positively associated with political patronage among listed firms. These results are consistent with the predictions made based on our theoretical arguments. This chapter aims to foster further discussion regarding the interdependence of the influences exerted by different stakeholders on firms.

This study aims to develop a holistic and dynamic model that governs the various relationships among the critical factors of crisis management from a stakeholder perspective in the context of China’s COVID-19 epidemic outbreak.

Data were collected from 731 textual sources, and the text mining technique identified the themes of a holistic crisis management model. Then, content analysis was applied to reveal in-depth insights into the themes.

From a stakeholder perspective, the model comprises six elements: political environment, economic environment, technology, social environment, health and science and international relationships, which relate significantly to four procedural actions: prevention, response, recovery and adaptation. The overlapping stages and situational dynamic mechanisms of the process are another two new major findings of this study; learning and preparing are threaded throughout the whole dynamic process.

Hospitality stakeholders are advised to collaborate under the guidance of the dynamic crisis management model and adopt high-technology tools for the industry’s recovery management. Developing a new business model and marketing strategy is a useful approach to face similar crisis management challenges in the future.

This paper fills an existing research gap by presenting a health-related crisis management model that can be used to evaluate the dynamic process of collaborations among stakeholders in coping with external challenges forced upon the hospitality industry.

利益相关者视角下的危机管理动态模型：以covid-19在中国的发展为例

本研究以中国新冠肺炎疫情为背景, 从利益相关者的角度构建危机管理关键因素之间各种关系的整体动态模型。

本研究从731个文本来源收集定量数据, 并通过文本挖掘技术识别危机管理模型的构成要素,并运用内容分析对构成要素进行深入剖析。

从利益相关者的角度来看, 该模型包括六个要素:政治环境、经济环境、技术、社会环境, 健康科学和国际关系。这些要素与预防、反馈、恢复和适应这四项运行程序密切相关。本研究的两大发现是防疫机制的动态机制和重叠特性, 学习和预备贯穿于疫情防控的整个动态过程。

酒店利益相关者应在动态危机管理模型的指导下进行合作, 并运用高科技进行行业复苏管理。此外, 开发新的商业模式和营销策略也是面对新的外部环境的有效途径。

本文通过提出一个健康相关的危机管理模型来填补现有研究的空白, 该模型可用于评估酒店行业外部环境中利益相关者之间的动态合作过程。

En este estudio se recogieron datos cuantitativos de 731 fuentes textuales, se identificaron los elementos constitutivos del modelo de gestión de crisis a través de la minería textual y se analizaron en profundidad los elementos constitutivos mediante el análisis de contenido.

este estudio utiliza una combinación de minería de texto y análisis de contenido para explorar el manejo de crisis del brote de covid-19 en el sector turístico y hotelero de China. En primer lugar, se recogieron datos cuantitativos de 731 fuentes textuales y se identificaron los elementos constitutivos del modelo de gestión de crisis a través de la minería textual. En segundo lugar, se utiliza el análisis de contenido para analizar en profundidad los elementos constitutivos y, sobre la base de UN análisis de datos exhaustivo y una revisión de la literatura, se llega a UN marco teórico para el manejo de crisis.

Desde el punto de vista de las partes interesadas, el modelo consta de seis elementos: el entorno político, el entorno económico, el entorno tecnológico, el entorno social, la ciencia de la salud y las relaciones internacionales. Estos elementos están estrechamente relacionados con los cuatro procedimientos operativos: prevención, retroalimentación, recuperación y adaptación. Los dos principales hallazgos de este estudio son los mecanismos dinámicos y las características de superposición de los mecanismos de prevención de epidemias, y el aprendizaje y la preparación a lo largo de todo el proceso dinámico de prevención y control de brotes.

las partes interesadas del sector hotelero deben colaborar bajo la guía de UN modelo dinámico de gestión de crisis y utilizar la alta tecnología para la gestión de la recuperación del sector. Además, el desarrollo de nuevos modelos de negocio y estrategias de marketing es también una forma eficaz de afrontar el nuevo entorno externo.

este artículo colma las lagunas de la investigación existente proponiendo UN modelo de gestión de crisis relacionadas con la salud que pueda ser utilizado para evaluar procesos dinámicos de colaboración entre los interesados en el entorno externo del sector hotelero.