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This study aims to explore the relationship between speed behavior of participants and driving styles on interchange ramps. A spiral interchange in Chongqing was selected as an experimental road to carry out field driving experiment.

The continuous operating speed during experiment was selected by Mobile Eye, and the driving style was selected via two inventories.

Different driving behaviors showed great differences in age, driving mileage and driving experience. During driving process, male pursued driving stimulation more, whereas female pursued driving steadiness more. Therefore, driving characteristics of male were more disadvantageous to driving safety than that of female. Except for the large speed difference at the entrance and exit of the ramps, the differences at other positions were small. And the operating speed of male was slightly higher than that of female. The difference between different genders at the ascending end position achieved 4–5 kph, and the difference at other feature points were mostly 1–2 kph. During driving process, risky participants were more likely to pursue driving stimulation, and the poor speed control behavior was reflected in wide range of desired operating speed. Based on the results of analyzing at feature points, melancholy and sanguine participants more tended to take a high operating speed, and the poor speed control behavior was reflected in the most widely desired speed range. The speed control behavior of mixed participants was more cautious.

Advanced driving assistance system combined with two inventories was used to explore difference of speed behavior.

The purpose of this paper is to present a review of the implications building information modelling (BIM) is having on the building energy modelling (BEM) and design of buildings. It addresses the issues surrounding exchange of information throughout the design process, and where BIM may be useful in contributing to effective design progression and information availability.

Through review of current design procedures and examination of the concurrency between architectural and thermophysical design modelling, a procedure for information generation relevant to design stakeholders is created, and applied to a high-performance building project currently under development.

The extents of information key to the successful design of a buildings energy performance in relation to its architectural objectives are given, with indication of the level of development required at each stage of the design process.

BIM offers an extensible medium for parametric information storage, and its implementation in design development offers the capability to include BEM parameter-integrated construction information. The extent of information required for accurate BEM at stages of a building’s design is key to understanding how best to record performance information in a BIM environment.

This paper contributes to the discussion around the integration of concurrent design procedures and a common data environment. It presents a framework for the creation and dissemination of information during design, exemplifies this on a real building project and evaluates the barriers experienced in successful implementation.

SPACs are reshaping the world of digital entrepreneurial finance. Firms in the digital sector often need access to public markets for long-term competitiveness. SPACs offer a viable solution for these entities to collect capital and transition to public ownership quicker than IPOs. In this context, the paper aims to analyse and compare the performance of SPACs with those of IPOs in the post-business combination phase. The objective is to provide novel insights into the determinants of SPAC operating and market performance by considering firm-specific and deal-specific characteristics and the broader implications of market uncertainty.

The analysis applies univariate and multivariate OLS regressions to a sample of 96 SPACs to investigate the drivers affecting SPACs' performance vis-a-vis IPOs.

The study finds that SPACs underperform the matched group of IPOs on both operating and stock market performance (buy-and-hold strategy). The time to execute a business combination negatively correlates with SPAC performance, and proximity to the 80% deal threshold negatively affects share price performance and EBITDA margin.

The objective is to offer insights for institutional investors to effectively select prime targets within the SPAC framework.

This study strengthens the findings related to the drivers influencing the long-term performance of SPACs that were previously identified in prior research.

The article aims to investigate the effects of ownership and capital structure on postacquisition operating performance.

The article extends the ongoing literature from an operating loss perspective and provides empirical evidence on the probability of acquirers’ operating loss in relation to ownership and capital structure. The operating performance of publicly listed manufacturing firms in China was tracked up to five years since the completion of the mergers and acquisitions (M&A) during 2003–2014.

The empirical results show that, in a five-year postacquisition period, state-owned enterprises (SOEs) are more likely to experience operating loss than non-SOEs. The likelihood of the operating loss is negatively associated with ownership concentration, implying that concentrated ownership may serve as an effective corporate governance mechanism in the emerging economy and improve postacquisition performance. The rise in leverage increases the likelihood of postacquisition operating loss, indicating that the costs of debt may outweigh the benefits.

The findings contribute to the literature on ownership, debt governance and post-M&A performance from an emerging economy perspective.

Using the theoretical framework of the substantive economy, this study aims to point out the main aspects of the substantive mode of operation that help the integration of disadvantaged people while at the same time shedding light on the barriers that hinder economically efficient functioning in a market economy.

Research focuses on Hungarian rural work integration social cooperatives, which are engaged in producing activity by the employment of disadvantaged people. In the research, mixed methods were applied: results of a questionnaire survey covering 102 cooperatives, as well as 20 semi-structured interviews and experiences from the field. A total of 17 indicators were used to explore the substantive operational features, promoting mechanisms and problems in the following areas: organisational goals and outcomes; integrating roles and functions; productive functions; and the embeddedness of cooperatives.

As for results, substantive operational mechanisms and tools that support the integration of disadvantaged people have been identified such as mentoring, social incentives, the ability to create local value or the expansion of local community services. At the same time, several barriers have been detected that make it difficult to operate economically, such as cooperatives being a stepping stone for workers, excessive product heterogeneity or the lack of vertically structured bridging relationships.

The value of the study is to counterpoint the mechanisms promoting social purposes of work-integration social cooperatives and the obstacles to their long-term sustainability within the framework of the substantive economy, to better understand their functioning and the less quantifiable factors of their performance.

This study sheds light on the prediction of success using cutoff scores for student grades adopted for a required Physics pathway course for study in a health professions program at King Saud University in Saudi Arabia. Data on course grade and GPA for approximately 10,000 students enrolled in this course between 2008–2014, were analyzed. Receiver Operating Characteristic (ROC) curve analysis was used to determine cutoffs for course grades using ranges of GPA. This procedure has promise as a new method for quantitatively arriving at cutoff scores using an external criterion requiring less human judgment than most existing standard setting methods. The cutoff scores produced show that GPAs of students who complete the Physics course yield successive performance tiers that are lower than expected. In addition, the correlation between GPA and course grade for Physics is only 0.63 and therefore only 39% of the variation in GPA explains course grade. As a result of the findings of the study, the decision was made to maintain the existing standards thereby requiring higher grades in the Physics course for students seeking to enter a health professions course of study.

ﻧﺗﻟا ﺎﮭﺗردﻗو ﺔﯾدﺣﻟا تﺎﺟردﻟا ﻰﻠﻋ ءوﺿﻟا ﺔﯾﻟﺎﺣﻟا ﺔﺳاردﻟا طﻠﺳﺗ ﻲﻓ ﺔﺑﻠطﻟا حﺎﺟﻧ ﻰﻠﻋ ﺔﯾؤﺑﻲﻟوﻻا ءﺎﯾزﯾﻔﻟا ررﻘﻣ زﯾﻓ)145( ، دﻌﯾ يذﻟاوﻠﻋ ﺎﯾﺳﺎﺳا ﺎﺑﻠطﺗﻣكﻠﻣﻟا ﺔﻌﻣﺎﺟ ﻲﻓ ﺔﯾﺣﺻﻟا تﺎﺻﺻﺧﺗﻟا ﺔﺑﻠط ﻰ ﺔﻘﻠﻌﺗﻣﻟا تﺎﻧﺎﯾﺑﻟا ﻊﻣﺟ مﺗ دﻘﻓ ﺔﯾﻠﻋو ،ﺔﯾدوﻌﺳﻟا ﺔﯾﺑرﻌﻟا ﺔﻛﻠﻣﻣﻟﺎﺑ دوﻌﺳ نﻣ برﺎﻘﯾ ﺎﻣﻟ ررﻘﻣﻟا اذھ تﺎﺟردﺑ10000 ماوﻋﻻا نﯾﺑ ررﻘﻣﻟا اذﮭﺑ اوﻘﺣﺗﻟا نﯾذﻠﻟا ﺔﺑﻠطﻟا نﻣ2008 - 2014 .ﺔﯾﻣﻛارﺗﻟا مﮭﺗﻻدﻌﻣو ،م ﺗﻟو مادﺧﺗﺳا مﺗ دﻘﻓ ،تﺎﻧﺎﯾﺑﻟا هذھ لﯾﻠﺣ تﺎﯾﻠﻣﻌﻟا لﯾﻐﺷﺗ ﺔﯾﺻﺎﺧ ﻰﻧﺣﻧﻣReceiver Operating Characteristic (ROC) تﺎﺟردﻟا دﯾدﺣﺗﻟ نﻣ دﺣﻟاو ﺔﯾدﺣﻟا تﺎﺟردﻟا ﻰﻟا لوﺻوﻠﻟ ﺔﺛﯾدﺣﻟا ﺔﯾﻣﻛﻟا قرطﻟا نﻣ ﺔﻘﯾرطﻟا هذھ دﻌﺗ ثﯾﺣ ،ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نﻣ ﺔﻔﻠﺗﺧﻣ تﺎﻗﺎطﻧﻟ ﺔﯾدﺣﻟارﯾﺛﺄﺗﻟا .يرﺷﺑﻟا نﻣﺿ نﺎﻛ ررﻘﻣﻟا اذھ زﺎﺗﺟا نﻣﻟ ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نا ﻰﻟا ترﺎﺷا دﻗ ﺎﮭﯾﻠﻋ لوﺻﺣﻟا مﺗ ﻲﺗﻟا ﮫﯾدﺣﻟا تﺎﺟردﻟا نﺎﻓ ﺔﯾﻠﻋو تﻐﻠﺑ ﺔﺑﻠطﻟا تﺎﺟردو ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نﯾﺑ ﺔﯾطﺎﺑﺗرﻻا ﺔﻗﻼﻌﻟا نا ﺎﻣﻛ ،ﻊﻗوﺗﻣﻟا نﻣ لﻗا تﺎﻗﺎطﻧ0.63 ﻲﻧﻌﯾ ﺎﻣﻣ ، نا 39% نﻣتﺎﻧﯾﺎﺑﺗﻟا ﺔﯾﻣھا نﯾﺑﺗﯾ ﺞﺋﺎﺗﻧ نﻣ ﺔﯾﻠﻋ لوﺻﺣﻟا مﺗ ﺎﻣﻟ ﺎﻘﻓوو .رﻘﻣﻟا كﻟذ ﻲﻓ مﮭﺗﺎﺟرد رﯾﺳﻔﺗ ﻲﻓ مﮭﺳﺗ نا نﻛﻣﯾ ﺔﺑﻠطﻠﻟ ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا ﻲﻓﺔظﻓﺎﺣﻣﻟا ﻰﻠﻋ ررﻘﻣﻟا رﯾﯾﺎﻌﻣﺔﯾﻟﺎﺣﻟا ﻊﻣدﯾﻛﺄﺗ لوﺻﺣﺔﺑﻠطﻟا تﺎﺻﺻﺧﺗﻟﺎﺑ قﺎﺣﺗﻟﻼﻟ نﯾﺑﻏارﻟاﺔﯾﺣﺻﻟا تﺎﺟرد ﻰﻠﻋﺔﻌﻔﺗرﻣ .ءﺎﯾزﯾﻔﻟا ررﻘﻣ ﻲﻓ

This study aims to propose an adaptive fractional-order sliding mode controller to solve the problem of train speed tracking control and position interval control under disturbance environment in moving block system, so as to improve the tracking efficiency and collision avoidance performance.

The mathematical model of information interaction between trains is established based on algebraic graph theory, so that the train can obtain the state information of adjacent trains, and then realize the distributed cooperative control of each train. In the controller design, the sliding mode control and fractional calculus are combined to avoid the discontinuous switching phenomenon, so as to suppress the chattering of sliding mode control, and a parameter adaptive law is constructed to approximate the time-varying operating resistance coefficient.

The simulation results show that compared with proportional integral derivative (PID) control and ordinary sliding mode control, the control accuracy of the proposed algorithm in terms of speed is, respectively, improved by 25% and 75%. The error frequency and fluctuation range of the proposed algorithm are reduced in the position error control, the error value tends to 0, and the operation trend tends to be consistent. Therefore, the control method can improve the control accuracy of the system and prove that it has strong immunity.

The algorithm can reduce the influence of external interference in the actual operating environment, realize efficient and stable tracking of trains, and ensure the safety of train control.

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

Classification techniques have been applied to many applications in various fields of sciences. There are several ways of evaluating classification algorithms. The analysis of such metrics and its significance must be interpreted correctly for evaluating different learning algorithms. Most of these measures are scalar metrics and some of them are graphical methods. This paper introduces a detailed overview of the classification assessment measures with the aim of providing the basics of these measures and to show how it works to serve as a comprehensive source for researchers who are interested in this field. This overview starts by highlighting the definition of the confusion matrix in binary and multi-class classification problems. Many classification measures are also explained in details, and the influence of balanced and imbalanced data on each metric is presented. An illustrative example is introduced to show (1) how to calculate these measures in binary and multi-class classification problems, and (2) the robustness of some measures against balanced and imbalanced data. Moreover, some graphical measures such as Receiver operating characteristics (ROC), Precision-Recall, and Detection error trade-off (DET) curves are presented with details. Additionally, in a step-by-step approach, different numerical examples are demonstrated to explain the preprocessing steps of plotting ROC, PR, and DET curves.