Search results

The purpose of this paper is to develop a modeling and interactive operating method for virtual assembly (VA) to support assembly process generation based on interactive operation.

This paper puts forward an assembly semantic modeling method for interactive assembly and process generation after the analysis on requirements of operation process generation. Based on this semantic model, methods for semantic generation, semantic processing and assembly motion extraction from interactive operation are presented. Partial process generation of auto engine is proposed to verify the approaches in this paper.

The application shows that assembly semantic modeling and operating methods can support process generation based on VA operations.

The approaches presented in this paper improve the efficiency of assembly process, making assembly process intuitive and natural.

The defect detection problem of color-patterned fabric is still a huge challenge due to the lack of manual defect labeling samples. Recently, many fabric defect detection algorithms based on feature engineering and deep learning have been proposed, but these methods have overdetection or miss-detection problems because they cannot adapt to the complex patterns of color-patterned fabrics. The purpose of this paper is to propose a defect detection framework based on unsupervised adversarial learning for image reconstruction to solve the above problems.

The proposed framework consists of three parts: a generator, a discriminator and an image postprocessing module. The generator is able to extract the features of the image and then reconstruct the image. The discriminator can supervise the generator to repair defects in the samples to improve the quality of image reconstruction. The multidifference image postprocessing module is used to obtain the final detection results of color-patterned fabric defects.

The proposed framework is compared with state-of-the-art methods on the public dataset YDFID-1(Yarn-Dyed Fabric Image Dataset-version1). The proposed framework is also validated on several classes in the MvTec AD dataset. The experimental results of various patterns/classes on YDFID-1 and MvTecAD demonstrate the effectiveness and superiority of this method in fabric defect detection.

It provides an automatic defect detection solution that is convenient for engineering applications for the inspection process of the color-patterned fabric manufacturing industry. A public dataset is provided for academia.

Body type classification has a great influence on plate making and garment sizing system, and the accuracy of body type classification method will greatly affect the fit of garment production. The purpose of this paper is to use the decision tree algorithm to study body classification rules, develop a decision tree body recognition model and judge the body shape of middle-aged women in Xinjiang.

First, perform dimensionless processing on the collected data of 256 middle-aged women in Xinjiang, and the dimensionless data were used for K-means body clustering; Then, quantitatively analyze the effectiveness of different classification clusters based on the silhouette coefficients. Second, the decision tree algorithm is used to divide the classified sample data into a training set and a test set at a ratio of 70/30, and select the best node and the best branch based on the Gini coefficient to construct a classification tree. Last, the overall optimal decision tree is generated by means of hyperparameter pruning.

The body shape of middle-aged women in Xinjiang can be divided into three types: standard body, plump body and obese body. The decision tree model has an excellent effect on body classification of middle-aged women in Xinjiang (precision (macro), 95.46%; precision (micro), 95.95%; recall (macro), 95.46%; recall (micro), 95.95%; F1 (macro), 95.46%; F1 (micro), 95.95%).

For scientific research, this paper is conducive to increasing the regional body type theory and stimulating the establishment of a garment sizing subdivision system in Xinjiang. In terms of production practice, this paper not only establishes a model for judging the shape of middle-aged women in Xinjiang, but also provides reference data for intermediates of various sizes. In addition, to facilitate pattern-making and the establishment of a subdivision system for the size of middle-aged women's garments in Xinjiang, this paper provides the grading values of various body control parts of middle-aged women in Xinjiang.

Tactile sensation is an important sensory function for robots in contact with the external environment. To better acquire tactile information about objects, this paper aims to propose a three-layer structure of the interdigital flexible tactile sensor.

The sensor consists of a bottom electrode layer, a middle pressure-sensitive layer and a top indenter layer. First, the pressure sensitive material, structure design, fabrication process and circuit design of the sensor are introduced. Then, the calibration and performance test of the designed sensor is carried out. Four functions are used to fit and calibrate the relationship between the output voltage of the sensor and the contact force. Finally, the contact force sensing test of different weight objects and the flexible test of the sensor are carried out.

The performance test results show that the sensitivity of the sensor is 0.93 V/N when it is loaded with 0–3 N and 0.23 V/N when it is loaded with 3–5 N. It shows good repeatability, and the cross-interference between the sensing units is generally low. The contact force sensing test results of different weight objects show that the proposed sensor performs well in contact force. Each part of the sensor is a flexible material, allowing the sensor to achieve bending deformation, so that the sensor can better perceive the contact signs of the grasped object.

The sensor can paste the surface of the paper robot’s gripper to measure the contact force of the grasping object and estimate the contour of the object.

In this paper, a three-layer interdigital flexible tactile sensor is proposed, and the structural parameters of the interdigital electrode are designed to improve the sensitivity and response speed of the sensor. The indenter with three shapes of the prism, square cylinder and hemisphere is preliminarily designed and the prism indenter with better conduction force is selected through finite element analysis, which can concentrate the external force in the sensing area to improve the sensitivity. The sensor designed in this paper can realize the measurement of contact force, which provides a certain reference for the field of robot tactile.

The purpose of this paper is to examine the efficiencies of China's foreign and domestic life insurance providers and to explore the relationship between ownership structure and the efficiencies of insurers while taking into consideration other firm attributes.

The data envelopment analysis (DEA) method is used to estimate the efficiencies of the insurers based on a panel data between 1999 and 2004.

The results indicate that the average efficiency scores for all the insurers are cyclical. Both technical and scale efficiency reached their peaks in 1999 and 2000 and gradually reduced for the rest of the period under examination until 2004 when average efficiency were improved again. The Tobit regression results show that the insurers' market power, the distribution channels used and the ownership structures may be attributed to the variation in the efficiencies.

Based on the research findings and the discussion, the study provides several recommendations for policy makers, regulators and senior executives of insurers.

The research results highlight the importance of deregulating the sector to allow a further expansion of each individual insurer or encourage mergers and acquisitions of insurers so more efficient resource utilization can be achieved through economies of scale. It also suggests that it is imperative for insurers to recruit motivated insurance agents and offer them on‐the‐job training as a part of the management strategies for gaining technical efficiency.

The paper reports the development within China's insurance industry and is one of the few studies analyzing the efficiencies of China's insurers.

The explosion of data due to the sophistication of information and communication technology makes it simple for prospective tourists to learn about previous hotel guests' experiences. They prioritize the rating score when selecting a hotel. However, rating scores are less reliable for suggesting a personalized preference for each aspect, especially when they are in a limited number. This study aims to recommend ratings and personalized preference hotels using cross-domain and aspect-based features.

We propose an aspect-based cross-domain personalized recommendation (AsCDPR), a novel framework for rating prediction and personalized customer preference recommendations. We incorporate a cross-domain personalized approach and aspect-based features of items from the review text. We extracted aspect-based feature vectors from two domains using bidirectional long short-term memory and then mapped them by a multilayer perceptron (MLP). The cross-domain recommendation module trains MLP to analyze sentiment and predict item ratings and the polarities of the aspect based on user preferences.

Expanded by its synonyms, aspect-based features significantly improve the performance of sentiment analysis on accuracy and the F1-score matrix. With relatively low mean absolute error and root mean square error values, AsCDPR outperforms matrix factorization, collaborative matrix factorization, EMCDPR and Personalized transfer of user preferences for cross-domain recommendation. These values are 1.3657 and 1.6682, respectively.

This study assists users in recommending hotels based on their priority preferences. Users do not need to read other people's reviews to capture the key aspects of items. This model could enhance system reliability in the hospitality industry by providing personalized recommendations.

This study introduces a new approach that embeds aspect-based features of items in a cross-domain personalized recommendation. AsCDPR predicts ratings and provides recommendations based on priority aspects of each user's preferences.

The study aims to analyze factors impacting firms’ success and persistence in a digital platform competition using the structure-conduct-performance (SCP) framework. The study also includes real-life cases that are beneficial to academicians and practitioners to understand and develop strategies for success and persistence during uncertainty.

A literature review to identify the factors that impact success and persistence in a digital platform competition was conducted following Webster and Watson (2002). Findings were integrated into a SCP framework to examine and understand the identified factors’ relational impact.

While analyzing factors under the SCP framework, all factors were divided into three categories: those impacting positively, those impacting negatively and those with ambiguous impact on the success and persistence in digital platform competition. Digital platform firms can exploit the positively impacting factors to increase market share by being distinctive from other digital platform firms and becoming dominant by withstanding competition. On the other hand, negatively impacting factors increase barriers to entry, intensify competition and reduce the distinctiveness of digital platform firms. Lastly, a few factors may have either a positive or a negative impact depending upon the particular characteristics of the firm/industry.

The study opens the scope for future research on empirically testing the developed conceptual framework and relationships by developing propositions to posit the possible impact of these factors on digital platforms’ success and persistence.

The study contributed to the existing literature by using SCP framework to analyze the factors affecting firm’s success and persistence in a digital platform competition. Also, the study has discussed the relational impact of factors rather than their impact in isolation.

This paper aims to introduce a high-temperature grease design method assisted by back propagation neural network (BPNN) and verify its application value.

First, the grease data sets were built by sorting out the base data of greases in a large number of literatures and textbooks. Second, the BPNN model was built, trained and tested. Then, the optimized BPNN model was used to search the unknown data space and find the composition of greases with excellent high-temperature performance. Finally, a grease was prepared according to the selected composition predicted by the model and the high-temperature physicochemical performance, high-temperature stability and tribological properties under different friction conditions were investigated.

Through high temperature tribology experiments, thermal gravimetric analysis and differential scanning calorimetry experiments, it is proved that the high temperature grease prepared based on BPNN has good high-temperature performance.

To the best of the authors’ knowledge, a new method of designing and exploring high-temperature greases is successfully proposed, which is useful and important for the industrial applications.

This article aims to investigate the differences and similarities among cross-cultural, values and ethics between the USA and Asian countries. This article analyzes the degree of cultural distance between USA and Asian countries and the impact it has in companies. It examines the comparison between the USA and China’s value system. It also assesses how idealism and relativism impact individual ethical decision-making. In addition, this article examines the impact that globalization, foreign direct investment (FDI) and trade have in the Chinese culture and other countries.

The data for this research paper were collected from the following models: Ethics Position Questionnaire of Forsyth, Rokeach Values Survey, Hofstede model, GLOBE model and Wilcoxon test. The main sources used for this research were the Journal of Technology Management in China and the EBSCO database.

The research found that Western cultures tend to be more individualistic, while Asian countries tend to be very collective. This study also found that the type of value system that each culture holds depends on the type of government. This research also found that researchers have discovered that American managers are more loyal to their ethical beliefs, rather than to their superior’s or company’s ethical beliefs. While eastern Asian cultures focus more on the importance of acting in the best interests of the company’s superior. The study also found that it is extremely important for foreigners to build a relationship with Chinese business professionals before they do business negotiations. In addition, the study found that globalization, FDI and trade do make a significant cultural difference in some cultural dimensions.

It contributes to the literature by analyzing the different measurements in value, ethics and cultural differentiation. This research wants to demonstrate the importance of cultural differences, ethics and values across different countries and cultures. It also provides factual evidence that it’s important to understand these differences to be a successful global manager. In addition, it contributes to this literature by analyzing the effect that globalization, FDI and trade have in national cultures.

The purpose of this paper is to examine the relation between chief executive officer (CEO) compensation and firm performance proxied by efficiency estimated from data envelopment analysis (DEA) of the US property‐liability (P&L) insurance industry.

This study was conducted in two stages. First the authors applied DEA model to calculate efficiency scores. In the second stage, a translog model was used to correlate the level and structure of CEO compensation and the efficiency for the sample P&L insurers over the period of 2000‐2006.

Firm efficiency is positively and significantly associated with total CEO compensation. While revenue efficiency is associated with CEO cash compensation, cost efficiency is associated with incentive compensation.

These findings suggest that while CEO compensation is tied to both revenue and cost efficiency, revenue efficiency is more important in determining cash compensation, and cost efficiency is more prevalent in influencing incentive compensation.

This is the first paper to use efficiency scores as proxies for firm performance to explore the relation between CEO compensation and firm performance in the P&L insurance industry. Due to the nature of insurance business, using efficiency as a performance measurement is more appropriate than accounting and financial ratios since it enables us to net out the effects of differences in exogenous firm‐specific conditions that are beyond management's control.