Search results

For many pattern recognition problems, the relation between the sample vectors and the class labels are known during the data acquisition procedure. However, how to find the useful rules or knowledge hidden in the data is very important and challengeable. Rule extraction methods are very useful in mining the important and heuristic knowledge hidden in the original high-dimensional data. It can help us to construct predictive models with few attributes of the data so as to provide valuable model interpretability and less training times.

In this paper, a novel rule extraction method with the application of biclustering algorithm is proposed.

To choose the most significant biclusters from the huge number of detected biclusters, a specially modified information entropy calculation method is also provided. It will be shown that all of the important knowledge is in practice hidden in these biclusters.

The novelty of the new method lies in the detected biclusters can be conveniently translated into if-then rules. It provides an intuitively explainable and comprehensive approach to extract rules from high-dimensional data while keeping high classification accuracy.

Given the fact that the income disparity has become extremely severe in rural China, the purpose of this paper is to examine heterogeneity in food consumption among various income classes and to investigate the impact of changes in income distribution patterns on food demand in rural China.

In this study, the authors partition the households into five income classes according to the distribution of household per capita net income. Using household data drawn from the China Health and Nutrition Survey in 2011, a two-stage demand model is applied to estimate a food demand system for each of the income classes. After obtaining the estimated income elasticities of eight studied food groups for each income class, the authors then examine the responsiveness of food demand to the changes in income distribution by means of four scenarios with varying income distribution.

The empirical results indicate that substantial differences in food consumption exist across various income classes. Specifically, the lowest-income households are more sensitive to price and income changes for most studied food groups than the highest-income households are. In general, income responsiveness is higher for meats, aquatic products and dairy products. Based on estimated income elasticities, the projected food consumption under different income distribution patterns shows that changes in income distribution have significant influences on food consumption. In addition, the authors conclude that a more equal distribution of income would be associated with a higher demand for food in rural China.

This paper employs a two-stage demand model to estimate food demand in rural China by income classes. The results imply substantial differences in food demand for various income classes. Therefore, income distribution should be taken into account instead of an average estimation for the population as a whole when investigating food demand in rural China. Given the significant changes in income distribution in rural China, this study provides several important policy implications to alleviate income inequality and poverty, as well as to improve nutrition for lower-income classes.

The purpose of this paper is to use the wavelet neural network and genetic algorithm to study the effects of polyalphaolefin, TMP108 and OCP0016 on the kinematic viscosity, viscosity index and pour point of lubricating oil.

Wavelet neural network is used to train the known samples, test the unknown samples and compare the obtained results with those obtained with a traditional empirical formula.

It is found that the wavelet neural network prediction value is closer to the experimental value than the traditional empirical formula calculation value.

The results show that the wavelet neural network can be used to study the physical and chemical indexes of lubricating oil.

This study aims to present a type of metamorphic mechanism-based quadruped crawling robot. The trunk design of the robot has a metamorphic mechanism, which endows it with excellent crawling capability and adaptability in challenging environments.

The robot consists of a metamorphic trunk and four series-connected three-joint legs. First, the walking and steering strategy is planned through the stability and mechanics analysis. Then, the walking and steering performance is examined using virtual prototype technology, as well as the efficacy of the walking and turning strategy.

The metamorphic quadruped crawling robot has wider application due to its variable trunk configuration and excellent leg motion space. The robot can move in two modes (constant trunk and trunk configuration transformation, respectively, while walking and rotating), which exhibits outstanding stability and adaptability in the examination and verification of prototypes.

The design can enhance the capacity of the quadruped crawling robot to move across a complex environment. The virtual prototype technology verifies that the proposed walking and steering strategy has good maneuverability and stability, which considerably expands the application opportunity in the fields of complicated scene identification and investigation.

This paper aims to clarify the effects of metallic nanoparticles (NPs) additives and room temperature ionic liquids (ILs) on the tribological performance of electric contacts.

Tribological properties of copper (Cu) and silver (Ag) NPs as lubricant additives in different lubricants of ILs or polyalphaolefin (PAO) oils under applied electric currents were investigated. After tribological tests, morphologies of worn surfaces were observed; meanwhile, lubrication and anti-wear properties were analyzed.

The mixture solution of the IL and Cu NPs showed desirable lubrication and anti-wear properties due to the reduction of electrocorrosion and the enhancement of rolling effects of particles in the contact region. The anti-wear performance of Cu NPs is better than that of Ag NPs due to the difference in the particle size. The PAO oil with the Cu NPs additives showed poor lubrication properties due to the low solubility of the particles in the oil. When the direction of applied current was changed, the friction of the lubricant with better conductivity was more stable in the variation trend.

This paper begins with a study of tribological properties of Cu and Ag NPs as lubricant additives in different lubricants of IL or PAO oils under applied electric currents. The authors then propose several methods and possible solutions which could be implemented to improve the tribological performance of electric contacts.

This paper aims to present a novel wireless passive pressure sensor based on an aperture coupled microstrip patch antenna embedded with an air cavity for pressure measurement.

In this paper, the sensitive membrane deformed when pressure was applied on the surface of the sensor and the relative permittivity of the mixed substrate changed, resulting in a change in the center frequency of the microstrip antenna. The size of the pressure sensor is determined by theoretical calculation and software simulation. Then, the sensor is fabricated separately as three layers using printed circuit board technology and glued together at last. The pressure test of the sensor is carried out in a sealed metal tank.

The extracted resonant frequency was found to monotonically shift from 2.219 to 1.974 GHz when the pressure varied from 0 to 300 kPa, leading to an average absolute sensitivity of 0.817 MHz/kPa.

This pressure sensor proposed here is mainly to verify the feasibility of this wireless passive maneuvering structure, and when the base material of this structure is replaced with some high-temperature-resistant material, the sensor can be used to measure the pressure inside the aircraft engine.

The sensor structure proposed here can be used to test the pressure in a high-temperature environment when the base material is replaced with some high-temperature-resistant material.

This paper aims to find optimal emission reduction investment strategies for the manufacturer and examine the effects of carbon cap-and-trade policy and uncertain low-carbon preferences on emission reduction investment strategies.

This paper studied a supply chain consisting of one manufacturer and one retailer, in which the manufacturer is responsible for emission reduction investment. The manufacturer has two emission reduction investment strategies: (1) invest in traditional emission reduction technologies only in the production process and (2) increase investment in smart supply chain technologies in the use process. Then, three different Stackelberg game models are developed to explore the benefits of the manufacturer in different cases. Finally, this paper coordinates between the manufacturer and the retailer by developing a revenue-sharing contract.

The manufacturer's optimal emission reduction strategy is dynamic. When consumers' low-carbon preferences are low and the government implements a carbon cap-and-trade policy, the manufacturer can obtain the highest profit by increasing the emission reduction investment in the use process. The carbon cap-and-trade policy can encourage the manufacturer to reduce emissions only when the initial carbon emission is low. The emission reduction, order quantity and the manufacturer's profit increase with the consumers' low-carbon preferences. And the manufacturer can adjust the emission reduction investment according to the emission reduction cost coefficient in two processes.

This paper considers the investment of emission reduction technologies in different processes and provides theoretical guidance for manufacturers to make a low-carbon transformation. Furthermore, the paper provides suggestions for governments to effectively implement carbon cap-and-trade policy.

This study explores the influencing factors of smart logistics ecological chain's (SLEC's) organizational collaboration and designs a corresponding conceptual framework.

The multi-case study is applied to this paper. Specifically, this study is a combination of exploratory and explanatory case studies.

The findings are threefold. First, empowerment capability and the information-sharing level are unique factors that affect SLEC's organizational collaboration. Second, greater empowerment capability stimulates the increase of information-sharing level. Third, emerging digital technology, personalized demand and peer competition affect the degree of SLEC's organizational collaboration through an intermediary variable – empowerment capability. Specifically, the emerging digital technology application and peer competition degrees have positive effects on empowerment capability, while the demand personalization degree negatively (positively) affects empowerment capability in the short (long) term.

As an important part of supply chain performance, organizational collaboration is receiving more attention. However, in the smart economy context, no theoretical framework exists for analyzing factors that affect the organizational collaboration degree of SLEC. This study fills this gap.

The purpose of this study is to examine the impact of corporate social capital and local embeddedness on perceived business performance of Chinese enterprises operating overseas, whose recent growth resulted from the Belt and Road Initiative.

This study reports the results of a sample of 83 Shaanxi outward foreign direct investment (FDI) firms operating in Africa, Asia, Australia, Europe and North America. In-depth interviews with a few sampled firms are used to develop the survey questionnaire and help interpret the results of statistical analysis.

This study proposes two hypotheses and both are supported by the data. First, corporate social capital is a three-dimensional concept, covering governmental, market and personal sources with each source making an equal, positive effect on perceived overseas performance of the surveyed firms. Second, these firms do better when having developed a higher degree of local embeddedness, a measure on local channels used to obtain information and mobilize resources. While local embeddedness indeed mediates some effect of corporate social capital, both variables have shown direct impact on performance.

Reported findings are from a small sample of 83 firms in an inland Chinese province, and business performance is measured by subjective evaluation rather than economic output.

The practical implication is that a Chinese FDI firm is expected to maintain all three relational channels – governmental, market and interpersonal – because the firm can gain different kinds of information and resources from these sources and each channel is necessary and equally important for the firm’s development. Importantly, it needs a different strategy to maintain and best use each channel. For the Belt and Road Initiative to be effective, China must establish platforms through which enterprises can strengthen and reconfigure their corporate social capital, as well as to cultivate and sustain their local networks in foreign destinations.

The purpose of this study is to explore organizational factors that act as antecedents of open innovation search. The authors aim to empirically examine whether the extent to which the organizational slack is absorbed determines its influence on firms’ openness in innovation search. In addition, the authors also examine the moderating effect of absorptive capacity on the relationship between slack and open innovation search.

This study adopted secondary data from multiple sources (NBER, Compustat and US census) and then constructed a ten-year balanced panel dataset of 298 manufacturers. The generalized least square method was used to explore the determinants of open innovation search among manufacturing firms.

The results of this study reveal that the absorption level of organizational slack indeed determines the openness in innovation search. Specifically, absorbed slack negatively affects a firm’s openness in innovation search, whereas unabsorbed slack promotes open innovation search. Additionally, the relationship between absorbed slack and open innovation search will be less negative with the increase of absorptive capacity.

Different from most previous studies that have examined the performance effect of open search among high-tech and large enterprises, this study focuses on the antecedents of open search strategy in both high- and low-tech, large and small firms. The findings reveal that different forms of organizational slack divergently influence a firm’s open search strategy, contributing to the understanding of the relationship between organizational slack and knowledge search behavior in a broader context, as well as the understanding of the moderating effect of absorptive capacity.