Improving VDT workplaces in offices by use of a physiologically optimized screen with black symbols on a light background: basic considerations

Due to the increased importance and usage of self-managed virtual teams, many recent studies have examined factors that affect their success. One such factor that merits examination is the configuration or composition of virtual teams. This article tackles this point by (1) empirically testing trait-configuration effects on virtual team performance, which are based on supplementary, complementary and interaction person-team fit perspectives and (2) extending the suggested trait-configuration model to include virtual team configuration in terms of the perceived problem-solving demands of the task as a predictor of team performance. To this end, median regression techniques were applied to data from 62 self-managed virtual teams that used an asynchronous bulletin board for working on a case study analysis. The findings suggest a plausible negative main effect of within-team conscientiousness heterogeneity on team performance, operationalised as standardised team grade. This effect depends on the level of the within-team extroversion heterogeneity which helps to mitigate the negative effect of within-team conscientiousness heterogeneity on team performance. Furthermore, within-team heterogeneity of the perceived problem-solving demands of the task reduces team performance. Overall, this study proves that virtual team configuration matters, and demonstrates that the joint utilisation of multiple person-team fit perspectives for improving virtual team performance has merit. Implications for research and practice are further discussed.     

Knowledge management systems and organizational knowledge processing challenges: A field experiment

This paper investigates the appropriateness of knowledge management system (KMS) designs for different organizational knowledge processing challenges. Building on the theory of task-technology fit (TTF), we argue that different KMS designs are more effective for different knowledge tasks. An exploratory field experiment was conducted in the context of Internet-based knowledge sharing services to provide empirical support for our hypotheses. The results of our experiment show that a KMS designed to support the goal GENERATE is more appropriate for divergent type knowledge problems because of its affordances for iterative brainstorming processes. Conversely, for convergent type knowledge processing challenges, a KMS with the goal CHOOSE that supports the ability to clarify and to analyze is more effective.     

轮轴压装过程的有限元分析

由于轮轴压装质量直接影响轨道列车的安全运行,针对轮轴压装不当产生轮轴内表面严重机械损伤的问题,应用有限元法对其进行研究.用Abaqus建立过盈配合下轮轴的有限元模型,仿真分析压装过程中压装力和等效应力的变化及分布规律,发现应力集中位置位于车轴轮座与轮毂孔的结合处及注油孔的外沿,因此应对应力集中位置做重点探伤;压装过程中压装力和最大等效接触应力都不断变化,其中压装力随着压装位移的增大而逐渐增大,而最大等效接触应力随着压装位移的增大呈先增大后减小的趋势;通过对比不同压入位移时轮轴的等效应力发现,压入位移超过190 mm时,车轴左端卸荷槽处开始发生形变,出现应力集中现象,因此压入位移应控制在190 mm以内.     

Does culture influence m-banking use and individual performance?

We show evidence on the influence of culture on m-banking use and individual performance, by using a combination of the task-technology fit (TTF) model and two of Hofstede’s cross-cultural dimension scales: uncertainty avoidance and individualism. On the basis of a sample of 204 m-banking users, we show that individualism moderates the relationship between TTF and use, and uncertainty avoidance moderates the relationship between TTF and individual performance. The remaining constructs, which represent the core of the TTF model, can still empirically explain TTF, use, and individual performance of m-banking. Strategies grounded in these factors are suggested for m-banking service providers to better attract and retain users.     

大直径超声测井仪数据处理技术的研究

针对大直径钻井超声测井仪存在检测数据精确度不高的问题,提出了一套完整的数据处理方案,并通过大量的实验测试数据,建立了超声测距方程,提出了一种改进的曲线拟合算法。实验证明该算法对数据量较大的采样点进行曲线拟合具有明显效果。     

Integrating TTF and IDT to evaluate user intention of big data analytics in mobile cloud healthcare system

ABSTRACT

With the rapid development of mobile technology and cloud computing, observers have recognised the vast potential for mobile cloud healthcare systems in individualised preventive healthcare. Using a mobile cloud healthcare system and big data analysis, this study aids young users in preventive healthcare against diabetes. It also integrates the Task-Technology Fit (TTF) and Innovation Diffusion Theory (IDT) models to evaluate user intentions to use the system, and tests this model using data collected from 423 young people. Results show that task-technology fit is significantly affected by task characteristics and technology characteristics, and also user intention of using the mobile cloud healthcare system is affected by task-technology fit, complexity, and relative benefits. However, observability has no significant effect on user intentions of using the mobile cloud healthcare system. These findings provide some interesting theoretical insights into the usage of the mobile cloud healthcare system. The direct effects of TTF and IDT on young users′ intention of using the mobile cloud healthcare system are shown. This study thus makes an important contribution by highlighting the role that TTF and IDT may have in affecting use of the mobile cloud healthcare system.     

How students and instructors using a virtual learning environment perceive the fit between technology and task

Abstract   Virtual learning environments (VLEs) are widespread in higher education today, typically used to deliver instructional materials and facilitate communication within a course. This study aimed to investigate the task–technology fit of VLEs for their two main groups of users: instructors and students, using the VLE WebCT. Task–technology fit, user satisfaction, attitude towards use and anticipated consequences of use were found to be significantly higher for students than for instructors. Instructors were found to have higher perceptions of social norms and higher perceptions of facilitating conditions than students. However, there was no difference between the instructors and students in level of utilization of the VLE. Students perceived that the VLE had higher impacts on their learning compared with instructors' perceptions regarding their teaching. These results suggest that despite high levels of support acknowledged by instructors, they may still be unsure about the contribution of VLEs to their teaching.     

Comparison of Algorithmic and Machine Learning Approaches for the Automatic Fitting of Gaussian Peaks

Fitting Gaussian peaks to experimental data is important in many disciplines, including nuclear spectroscopy. Nonlinear least squares fitting methods have been in use for a long time, but these are iterative, computationally intensive, and require user intervention. Machine learning approaches automate and speed up the fitting procedure. However, for a single pure Gaussian, there exists a simple and automatic analytical approach based on linearisation followed by a weighted linear Least Squares (LS) fit. This paper compares this algorithmic method with an abductive machine learning approach based on AIM ¹ (Abductory Induction Mechanism). Both techniques are briefly described and their performance compared for analysing simulated and actual spectral peaks. Evaluated on 500 peaks with statistical uncertainties corresponding to a peak count of 100, average absolute errors for the peak height, position and width are 4.9%, 2.9% and 4.2% for AIM, versus 3.3%, 0.5% and 7.7% for the LS. AIM is better for the width, while LS is more accurate for the position. LS errors are more biased, under-estimating the peak position and over-estimating the peak width. Tentative CPU time comparison indicates a five-fold speed advantage for AIM, which also has a constant execution time, while LS time depends upon the peak width.     

How do we fit underground coal mining work boots?

Abstract

Acceptable footwear fit, particularly width, is subjective and vaguely quantified. Proper shoe fit is important because it affects both comfort and the potential to prevent injury. Although mismatches between the feet of underground coal miners and their internal boot dimensions are known, no research has been undertaken to determine the impact of these mismatches on worker perceptions of fit, comfort and pain. This study aimed to quantitatively assess mining work boot fit relative to underground coal miners’ subjectively rated work boot fit and comfort, reported foot problems, lower limb pain and lower back pain in order to develop evidence-based work boot fit recommendations. Traditional footwear fitting methods based predominantly on foot length are insufficient for underground coal mining-specific footwear. Instead, fit at the heel, instep and forefoot must be considered when fitting underground coal mining work boots, in conjunction with the traditional length measurement.Practitioner summary: Underground coal miners report their work boots fit but are uncomfortable. This study assessed actual fit relative to perceived fit, comfort, foot problems, lower limb pain and lower back pain of 197 miners. Fit at the heel, instep and forefoot must be considered when fitting mining work boots.     

Improving physicians' performance with a stroke CDSS: A cognitive fit design approach

A large body of evidence over many years suggests that clinical decision support systems (CDSSs) can be helpful in improving both clinical outcomes and adherence to evidence-based guidelines. CDSSs have however failed to show their effectiveness due to poor ease of use and integration within clinical workflows. This research therefore emphasizes a cognitive fit design approach to developing an effective CDSS to solve those issues. According to the cognitive fit theory CDSS should align with the problem and task representation in order to match the physician's mental model to reduce cognitive effort. Several guidelines based on the cognitive fit design are proposed. A stroke CDSS prototype following the design guidelines is developed to demonstrate its feasibility. The system usability test results showed that the developed stroke CDSS was acceptably accurate, able to lessen the cognitive effort as desired, and preferable for use due to the significant reduction in cognitive load. The developed artifact has shown the potential to benefit physicians. Finally, implications and conclusions are discussed.