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Straightness measurement of rail weld joint is of essential importance to railway maintenance. Due to the lack of efficient measurement equipment, there has been limited in-depth research on rail weld joint with a 5-m wavelength range, leaving a significant knowledge gap in this field.

In this study, the authors used the well-established inertial reference method (IR-method), and the state-of-the-art multi-point chord reference method (MCR-method). Two methods have been applied in different types of rail straightness measurement trollies, respectively. These instruments were tested in a high-speed rail section within a certain region of China. The test results were ultimately validated through using traditional straightedge and feeler gauge methods as reference data to evaluate the rail weld joint straightness within the 5-m wavelength range.

The research reveals that IR-method and MCR-method produce reasonably similar measurement results for wavelengths below 1 m. However, MCR-method outperforms IR-method in terms of accuracy for wavelengths exceeding 3 m. Furthermore, it was observed that IR-method, while operating at a slower speed, carries the risk of derailing and is incapable of detecting rail weld joints and low joints within the track.

The research compare two methods’ measurement effects in a longer wavelength range and demonstrate the superiority of MCR-method.

Research on employee non-/compliance to information security policies suffers from inconsistent results and there is an ongoing discussion about the dominating survey research methodology and its potential effect on these results. This study aims to add to this discussion by investigating discrepancies between what the authors claim to measure (theoretical properties of variables) and what they actually measure (respondents’ interpretations of the operationalized variables). This study asks: How well do respondents’ interpretations of variables correspond to their theoretical definitions? What are the characteristics of any discrepancies between variable definitions and respondent interpretations?

This study is based on in-depth interviews with 17 respondents from the Swedish public sector to understand how they interpret questionnaire measurement items operationalizing the variables Perceived Severity from Protection Motivation Theory and Attitude from Theory of Planned Behavior.

The authors found that respondents’ interpretations in many cases differ substantially from the theoretical definitions. Overall, the authors found four principal ways in which respondents interpreted measurement items – referred to as property contextualization, extension, alteration and oscillation – each implying more or less (dis)alignment with the intended theoretical properties of the two variables examined.

The qualitative method used proved vital to better understand respondents’ interpretations which, in turn, is key for improving self-reporting measurement instruments. To the best of the authors’ knowledge, this study is a first step toward understanding how precise and uniform definitions of variables’ theoretical properties can be operationalized into effective measurement items.

This paper aims to improve our understanding of performance measurement systems in the health and care sector, by focussing on employee reactions to core performance measurement practices. Targets and monitoring are hypothesised to be associated with employee perceptions of job control, supportive management and job demands, which in turn, are expected to be linked to employee-wellbeing and organisational commitment.

Matched employee workplace data are extracted from a nationally representative and publicly available survey. Structural equation models are estimated.

Performance measurement systems are neither perceived as resources nor additional demands. Setting many targets and a focus on productivity can lead to negative employee outcomes, since these positively correlate with perceptions of job demands, which negatively correlate with employee wellbeing. However, monitoring financial performance and monitoring employee performance may be helpful to managers, as these are positively associated with employee perceptions of job control and supportive management, which positively correlate with job satisfaction and organisational commitment and, negatively, with anxiety. Overall, common criticisms of performance measurement systems in healthcare are questioned.

Given the lack of consensus on how performance measurement systems can influence employee experiences and outcomes, this study combines theories that argue for performance measurement systems in managing operations with models developed by psychologists to describe how perceptions of the work conditions can affect employee attitude and wellbeing. A conceptual model is therefore developed and tested, and potential direct and indirect effects of performance measurement systems in the health sector are inferred.

Amidst the scarcity of resources, it is undisputable that an effective public procurement performance measurement system (PMS) is required particularly in county governments, especially for Kenya to realize its ambitions in devolved governance system. County governments cannot be effectively evaluated on their performance if the long-term, strategic impact of public procurement processes and projects is not captured. Arising from this backdrop, this study aims to determine the predictors of strategic procurement performance metrics (SPPM) adoption in public procurement PMS of county governments.

Anchored on institutional theory and public sector scorecard model, a survey research design was adopted where data were collected through census from 115 respondents working in procurement, finance and stores department of Kakamega county government. Data were collected using questionnaire (75.56% response rate) and key informant interviews, and analyzed by using multiple regression model and ordinal logistic regression models.

Multiple regression model and ordinal logistics regression revealed that national government support negatively and significantly, and regulatory framework positively and significantly affects the adoption of SPPM.

There is need for formal mechanism that will enable the national government in partnership with the council of governors to be proactively involved in developing procurement performance measurement capacity of county governments. This study’s findings also provide suggestions for a working regulatory framework required for the adoption of SPPM by county governments.

This work adds value to the prevailing body of knowledge on public procurement PMS in the public sector.

The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.

Intelligent and connected vehicle technology is in the ascendant. High-level autonomous driving places more stringent requirements on the accuracy and reliability of environmental perception. Existing research works on multitarget tracking based on multisensor fusion mostly focuses on the vehicle perspective, but limited by the principal defects of the vehicle sensor platform, it is difficult to comprehensively and accurately describe the surrounding environment information.

In this paper, a multitarget tracking method based on roadside multisensor fusion is proposed, including a multisensor fusion method based on measurement noise adaptive Kalman filtering, a global nearest neighbor data association method based on adaptive tracking gate, and a Track life cycle management method based on M/N logic rules.

Compared with fixed-size tracking gates, the adaptive tracking gates proposed in this paper can comprehensively improve the data association performance in the multitarget tracking process. Compared with single sensor measurement, the proposed method improves the position estimation accuracy by 13.5% and the velocity estimation accuracy by 22.2%. Compared with the control method, the proposed method improves the position estimation accuracy by 23.8% and the velocity estimation accuracy by 8.9%.

A multisensor fusion method with adaptive Kalman filtering of measurement noise is proposed to realize the adaptive adjustment of measurement noise. A global nearest neighbor data association method based on adaptive tracking gate is proposed to realize the adaptive adjustment of the tracking gate.

This paper aims to introduce a novel method for the analysis of open cell porous components fabricated by laser-based powder bed metal additive manufacturing (AM) for the purpose of quality control. This method uses photogrammetric analysis, the extraction of geometric information from an image through the use of algorithms. By applying this technique to porous AM components, a rapid, low-cost inspection of geometric properties such as material thickness and pore size is achieved. Such measurements take on greater importance, as the production of porous additive manufactured orthopaedic devices increases in number, causing other, slower and more expensive methods of analysis to become impractical.

Here the development of the photogrammetric method is discussed and compared to standard techniques including scanning electron microscopy, micro computed tomography scanning and the recently developed focus variation (FV) imaging. The system is also validated against test graticules and simple wire geometries of known size, prior to the more complex orthopaedic structures.

The photogrammetric method shows an ability to analyse the variability in build fidelity of AM porous structures for use in inspection purposes to compare component properties. While measured values for material thickness and pore size differed from those of other techniques, the new photogrammetric technique demonstrated a low deviation when repeating measurements, and was able to analyse components at a much faster rate and lower cost than the competing systems, with less requirement for specific expertise or training.

The advantages demonstrated by the image-based technique described indicate the system to be suitable for implementation as a means of in-line process control for quality and inspection applications, particularly for high-volume production where existing methods would be impractical.

The multiple factors of intelligence measurement are critical in intelligent science. The intelligence measurement is typically built as a model based on multiple factors. The different agent is generally difficult to measure because of the uncertainty between multiple factors. The purpose of this paper is to solve the problem of uncertainty between multiple factors and propose an effective method for universal intelligence measurement for the different agents.

In this paper, the authors propose a universal intelligence measurement method based on meta-analysis for crowd network. First, the authors get study data through keywords in the database and delete the low-quality data. Second, they compute the effect value by odds ratio, relative risk and risk difference. Then, they test the homogeneity by Q-test and analyze the bias by funnel plots. Third, they select the fixed effect and random effect as a statistical model. Finally, through the meta-analysis of time, complexity and reward, the weight of each factor in the intelligence measurement is obtained and then the meta measurement model is constructed.

This paper studies the relationship among time, complexity and reward through meta-analysis and effectively combines the measurement of heterogeneous agents such as human, machine, enterprise, government and institution.

This paper provides a universal intelligence measurement model for crowd network. And it can provide a theoretical basis for the research of crowd science.

Psychometric analyses of self-administered questionnaire data tend to focus on items and instruments as a whole. The purpose of this paper is to investigate the functioning of the response scale and its impact on measurement precision. In terms of the response scale direction, existing evidence is mixed and inconclusive.

Three experiments are conducted to examine the functioning of response scales of different direction, ranging from agree to disagree versus from disagree to agree. The response scale direction effect is exemplified by two different latent constructs by applying the Rasch model for measurement.

The agree-to-disagree format generally performs better than the disagree-to-agree variant with spatial proximity between the statement and the agree-pole of the scale appearing to drive the effect. The difference is essentially related to the unit of measurement.

A careful investigation of the functioning of the response scale should be part of every psychometric assessment. The framework of Rasch measurement theory offers unique opportunities in this regard.

Besides content, validity and reliability, academics and practitioners utilising published measurement instruments are advised to consider any evidence on the response scale functioning that is available.

The study exemplifies the application of the Rasch model to assess measurement precision as a function of the design of the response scale. The methodology raises the awareness for the unit of measurement, which typically remains hidden.

The literature highlights the relevance of performance measurement and management system in small and medium enterprises (SMEs) to face the current competitive environment. However, a number of studies investigate how performance measurement and management system is effective for evolving and how contingency factors could influence this change. Newer experiences are sporadic and rarely investigated by researchers and practitioners. The purpose of this study is to identify the feasible evolutionary path of performance measurement and management system in leading SMEs to respond to current business challenges. Furthermore, it aims to contribute to the understanding of the role of key contingency factors influencing this evolution.

A longitudinal case study, based on retrospective and real-time investigations, is performed to investigate the primary evolutions of the performance measurement and management system and its key determinants.

The findings highlight two evolution paths, increasing the maturity of performance measurement. The first path highlights a strong command and control of performance management; the second path shows a democratic and participative of performance management. Moreover, management information system, organizational culture and management style are highlighted as key contingency factors in the change of performance management.

The authors contribute to knowledge in performance measurement field, showing how the efforts for developing performance measurement and management system in a leading SME could determine two different evolutionary paths. Furthermore, the paper describes the increasing role of organizational culture, management style and management information system in performance management evolution, as well as the relevance of online chats and social media in performance management activities.