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This paper aims to study the yarn cross-section shape which is a very important yarn physical parameter and has a dominant effect on the physical structure of the yarn. Four factors affecting the yarn cross section, i.e. twist multiplier, Roving hank, spinning system and doubling technique, were investigated.

In past researches, the yarn cross-sectional area was calculated by considering any one yarn radius giving the approximate yarn cross-sectional area by assuming the yarn as a circular one.

In this study, a testing instrument is fabricated as shown in Plates 1 and 2 for yarn cross-section measurement and a novel method for calculating the correct yarn cross-sectional area of the yarn was developed.

In the past, no such studies have been conducted on the yarn cross-section studies because of the various limitations of the yarn cross-section measuring or testing instruments.

To address three issues of survey-based methods (i.e. the absence of behaviors, the reference inequivalence, and the lack of cross-cultural interaction), the purpose of this paper is to explore the potential of using the behavioral experiment method to collect cross-cultural data as well as the possibility of measuring culture with the experimental data. Moreover, challenges to this method and possible solutions are elaborated for intriguing further discussion on the use of behavioral experiments in international business/international management (IB/IM) research.

This paper illustrates the merits and downside of the proposed method with an ultimate-game experiment conducted in a behavioral laboratory. The procedure of designing, implementing, and analyzing the behavioral experiment is delineated in detail.

The exploratory findings show that the ultimate-game experiment may observe participants’ behaviors with comparable references and allow for cross-cultural interaction. The findings also suggest that the fairness-related cultural value may be calibrated with the horizontal and vertical convergence of cross-cultural behaviors (i.e. people’s deed), and this calibration may be strengthened by incorporating complementary methods such as a background survey to include people’s words.

The behavioral experiment method illustrated and discussed in this study contributes to the IB/IM literature by addressing three methodological issues that are not widely recognized in the IB/IM literature.

The purpose of this paper is to assess the performance of competing methods and model selection, which are non‐trivial issues given the financial implications. Researchers have adopted various methods including statistical models and machine learning methods such as neural networks to assist decision making in direct marketing. However, due to the different performance criteria and validation techniques currently in practice, comparing different methods is often not straightforward.

This study compares the performance of neural networks with that of classification and regression tree, latent class models and logistic regression using three criteria – simple error rate, area under the receiver operating characteristic curve (AUROC), and cumulative lift – and two validation methods, i.e. bootstrap and stratified k‐fold cross‐validation. Systematic experiments are conducted to compare their performance.

The results suggest that these methods vary in performance across different criteria and validation methods. Overall, neural networks outperform the others in AUROC value and cumulative lifts, and the stratified ten‐fold cross‐validation produces more accurate results than bootstrap validation.

To select predictive models to support direct marketing decisions, researchers need to adopt appropriate performance criteria and validation procedures.

The study addresses the key issues in model selection, i.e. performance criteria and validation methods, and conducts systematic analyses to generate the findings and practical implications.

The purpose of this paper is to discuss motion planning about crossing obstacles and welding trajectory for a new-model mobile obstacle-crossing welding robot system. The robot can cross the obstacle in this way that one of the three adhesion mobile parts is pulled off the ground in turn. An optimal obstacle-crossing approach needs to be studied to improve the welding efficiency.

According to the characteristics of this mobile welding robot, two methods for crossing obstacles are compared. A special method is used for obstacle-crossing and welding. The kinematic model is established. By the optimization method, the optimum parameters for crossing obstacles are calculated. The welding speed when the robot is crossing the obstacle is very important, so its value must be in a certain range. Finally, the tracks of the wheels when the robot is crossing the obstacle are analyzed in order to observe the obstacle-crossing process.

According to the analysis, the maximum speed of the vehicle in the obstacle-crossing is determined. When crossing the obstacle, the robot can do welding simultaneously. The welding speed cannot exceed a certain value. In the obstacle-crossing process, the tracks of the wheels can reflect the process. According to the obtained conclusion, the obstacle-crossing experiments are successfully completed, and the welding effect is good. The results can prove that the proposed method is feasible.

The speed of obstacle-crossing is not very large. It has some relationships with the lifting speed of the wheels, which is determined by the quality of drive motor. More efficient robot must be developed to meet the needs of industrial robot.

Based on the excellent obstacle-crossing and welding capabilities, the robot with the new mechanism has a widely applying prospect in the field of welding and inspecting large equipment.

The obstacle-crossing approach has certain innovation. The way that the robot can maintain continuous welding when crossing the obstacle is of a great significance.

Safety efficiency is the key to balance safety and production in construction industry; but the existing safety efficiency evaluation methods have the limitations of overestimating efficiency and ignoring undesirable outputs; therefore, according to the characteristics of safety production in construction industry, this paper innovatively develops a new cross-efficiency data envelopment analysis method to analyze safety efficiency, which can solve the limitations of traditional methods; and then the safety efficiency and its influencing factors of China's construction industry are analyzed, and some useful conclusions are obtained to improve its safety efficiency.

A new cross-efficiency data envelopment analysis method with undesirable outputs is proposed; and the two-stage efficiency analysis framework is designed.

First, the construction industries in different areas have different reasons for affecting their safety efficiency; second, the evaluation results of global safety priority tend to be more acceptable; third, frequent safety accidents and low resource utilization lead to a slow downward trend of the safety efficiency of China's construction industry in the long run; fourth, construction engineering supervision, construction industrial scale, and construction industrial structure have the significant impact on safety efficiency.

Theoretically, a new cross-efficiency data envelopment analysis method with undesirable outputs is proposed for evaluating safety efficiency; practically, the safety efficiency and its influencing factors of China's construction industry are analyzed.

The purpose of this paper is to get the topology shape and material distribution of composite rotor beam under the requirement of cross-sectional characteristics.

A new multi-material topology optimization method is given. Designated shear center (SC) position and stiffness terms are combined as the objective function. Multi-material model including isotropic and anisotropic materials are employed. Sensitivity analysis is given based on gradient-based algorithm, and density filtering scheme is adopted to avoid checkerboard problem.

The topology design method of composite rotor beam provides innovative cross-sectional shape and material distribution method. The final topology shape like “ > ” is given for different material types and cross-sectional shape under SC position requirement. The coefficient of stiffness components has great influence on the cross-sectional final topology shape.

The proposed method is just to give cross-sectional topology shape. To obtain final actual composite rotor beam structure, shape and size optimization should be conducted if the topology shape is given.

This method is suitable for the preliminary design of helicopter rotor beam to get designated SC position and stiffness terms.

The proposed method provides a new gradient-based algorithm for multi-material topology optimization design of composite rotor beam.

The purpose of this paper is to focus on the case where – by design – one needs to impute cross-country cross-survey (CCCS) data (situation typical for example among multinational firms who are confronted with the need to carry out comparative marketing surveys with respondents located in several countries). Importantly, while some work demonstrates approaches for single-item direct measures, no prior research has examined the common situation in international marketing where the researcher needs to use multi-item scales of latent constructs. The paper presents problem areas related to the choices international marketers have to make when doing cross-country/cross-survey research and provides guidance for future research.

Multi-country sample of real data is used as an example of cross-sample imputation (292 New Zealand exporters and 302 Finnish ones) the international entrepreneurial orientation (IEO) data. Three variations of the input data are tested: first, imputation based on all the data available for the measurement model; second, imputation based on the set of items based on the invariance structure of the joint items shared across the two groups; and third, imputation based both on examination of the invariance structures of the joint items and the performance of the measurement model in the group where the full data was originally available.

Based on distribution comparisons imputation for New Zealand after completing the measurement model with Finnish data (Model C) gave the most promising results. Consequently, using knowledge on between country measurement qualities may improve the imputation results, but this benefit comes with a downside since it simultaneously reduces the amount of data used for imputation. None of the imputation models leads to the same statistical inferences about covariances between latent constructs than as the original full data, however.

Considering multiple imputation, the present exploratory study suggests that there are several concerns and issues that should be taken into account when planning CCCSs (or split questionnaire or sub-sampling designs). Even if there are several advantages available for well-implemented CCCS designs such as shorter questionnaires and improved response rates, these concerns lead us to question the appropriateness of the CCCS approach in general, due to the need to impute across the samples.

The combination of cross-country and cross-survey approaches is novel to international marketing, and it is not known how the different procedures utilized in imputation affect the results and their validity and reliability. The authors demonstrate the consequences of the various imputation strategy choices taken by using a real example of a two-country sample. The exploration may have significant implications to international marketing researchers and the paper offers stimulus for further research in the area.

For robots to more actively interact with the surrounding environment in object manipulation tasks or walking, they must understand the physical attributes of objects and surface materials they encounter. Dynamic tactile sensing can effectively capture rich information about material properties. Hence, methods that convey and interpret this tactile information to the user can improve the quality of human–machine interaction. This paper aims to propose a visual-tactile cross-modal retrieval framework to convey tactile information of surface material for perceptual estimation.

The tactile information of a new unknown surface material can be used to retrieve perceptually similar surface from an available surface visual sample set by associating tactile information to visual information of material surfaces. For the proposed framework, the authors propose an online low-rank similarity learning method, which can effectively and efficiently capture the cross-modal relative similarity between visual and tactile modalities.

Experimental results conducted on the Technischen Universität München Haptic Texture Database demonstrate the effectiveness of the proposed framework and the method.

This paper provides a visual-tactile cross-modal perception method for recognizing material surface. By the method, a robot can communicate and interpret the conveyed information about the surface material properties to the user; it will further improve the quality of robot interaction.

Cross‐cultural research in marketing has been dominated by survey‐based quantitative approaches; however, the assumption of prior validity required for the adoption of the survey approach to values in cross‐cultural research has yet to be established. This paper aims to review the literature and outlines the problems of the survey‐based approach to cross‐cultural values research. These criticisms relate both to the choice of the method and its execution. The paper outlines the multiplicative effects of these problems, that threaten the validity of the survey methodology in this context, and suggests a methodological alternative.

This paper reviews and synthesises the relevant literature on conceptual and methodological issues pertinent to the survey approach to values research in a cross‐cultural context.

A review of the literature suggests numerous methodological problems that threaten the validity and reliability of the survey approach to cross‐cultural values research. This review exposes a methodological gap that can be filled by a qualitative approach to the study of values in cross‐cultural research. In particular, the paper advocates means‐end methodology as offering significant strengths and addressing several of the weaknesses of the survey‐based approach to cross‐cultural values research.

The paper synthesises the literature on methodological issues in cross‐cultural values research, bringing together disparate criticisms which reveal the range of unresolved problems with the empirical, survey‐based approach to cross‐cultural values research; the paper also offers a suggestion for an alternative methodological approach. The means‐end approach is increasingly being used in various research areas; this paper highlights its appropriateness in a cross‐cultural context, as an alternative to predefined and culturally determined measures that limit our understanding of cross‐cultural values. Means‐end addresses many of the specific weaknesses of the survey method identified in the literature review. This discussion of methodological issues has implications for the field of cross‐cultural research more generally and suggests a critical re‐assessment of cross‐cultural methods is needed.

Due to the paucity of research on web-based job applicant screening (i.e. cybervetting), the purpose of the current study was to examine the psychometric properties of cybervetting, including an examination of the impact of adding structure to the rating process.

Using a mixed-factorial design, 122 supervisors conducted cybervetting evaluations of applicant personality, cognitive ability, written communication skills, professionalism, and overall suitability. Cross-method agreement (i.e. the degree of similarity between cybervetting ratings and other assessment methods), as well as interrater reliability and agreement were examined, and unstructured versus structured cybervetting rating formats were compared.

Cybervetting assessments demonstrated high interrater reliability and interrater agreement, but only limited evidence of cross-method agreement was provided. In addition, adding structure to the cybervetting process did not enhance the psychometric properties of this assessment technique.

This study highlighted that whereas cybervetting raters demonstrated a high degree of consensus in cybervetting-based attributions, there may be concerns regarding assessment accuracy, as cybervetting-based ratings generally differed from applicant test scores and self-assessment ratings. Thus, employers should use caution when utilizing this pre-employment screening technique.

Whereas previous research has suggested that cybervetting ratings demonstrate convergence with other traditional assessments (albeit with relatively small effects), these correlational links do not provide information regarding cross-method agreement or method interchangeability. Thus, this study bridges a crucial gap in the literature by examining cross-method agreement for a variety of job-relevant constructs, as well as empirically testing the impact of adding structure to the cybervetting rating process.