高职计算机网络技术专业课程体系改革探析

通过分析鄂东职业技术学院计算机网络技术专业课程体系,提出了基于工作过程课程体系的构建方法,指出了未来专业课程体系改革的一个方向。     

基于无线USB技术组建无线办公网络

随着无线个域网(WPAN)开始进入实用阶段,对无线USB(WUSB)技术的研究也逐渐深入。WUSB技术在继承传统有线USB优势的同时,充分利用无线传输技术的灵活性,为互连设备提供了更大的便利性与可移动性。论述了无线USB的关键技术及利用WUSB技术组建无线办公网络的特点。     

Participants matter: Effectiveness of VR-based training on the knowledge,trust in the robot,and self-efficacy of construction workers and university students

Virtual Reality (VR)-based training has gained attention from the scientific community in the Architecture, Engineering, and Construction (AEC) industry as a cost-effective and safe method that eliminates the safety risks that may impose on workers during the training compared to traditional training methods (e.g., in-person hands-on training, apprenticeship). Although researchers have developed VR-based training for construction workers, some have recruited students rather than workers to understand the effect of their VR-based training. However, students are different from construction workers in many ways, which can threaten the validity of such studies. Hence, research is needed to investigate the extent to which the findings of a VR-based training study are contingent on whether students or construction workers were used as the study sample. This paper strives to compare the effectiveness of VR-based training on university students’ and construction workers’ knowledge acquisition, trust in the robot, and robot operation self-efficacy in remote operation of a construction robot. Twenty-five construction workers and twenty-five graduate construction engineering students were recruited to complete a VR-based training for remote operating a demolition robot. We used quantitative analyses to answer our research questions. Our study shows that the results are dependent on the target sample in that students gained more knowledge, whereas construction workers gained more trust in the robot and more self-efficacy in robot operation. These findings suggest that the effectiveness of VR-based training on students may not necessarily associate with its effectiveness on construction workers.     

Excavator 3D pose estimation using deep learning and hybrid datasets

Earthwork operations are crucial parts of most construction projects. Heavy construction equipment and workers are often required to work in limited workspaces simultaneously. Struck-by accidents resulting from poor worker and equipment interactions account for a large proportion of accidents and fatalities on construction sites. The emerging technologies based on computer vision and artificial intelligence offer an opportunity to enhance construction safety through advanced monitoring utilizing site cameras. A crucial pre-requisite to the development of safety monitoring applications is the ability to identify accurately and localize the position of the equipment and its critical components in 3D space. This study proposes a workflow for excavator 3D pose estimation based on deep learning using RGB images. In the proposed workflow, an articulated 3D digital twin of an excavator is used to generate the necessary data for training a 3D pose estimation model. In addition, a method for generating hybrid datasets (simulation and laboratory) for adapting the 3D pose estimation model for various scenarios with different camera parameters is proposed. Evaluations prove the capability of the workflow in estimating the 3D pose of excavators. The study concludes by discussing the limitations and future research opportunities.     

Spatial-temporal analysis of safety risks in trajectories of construction workers based on complex network theory

Understanding the traffic patterns of construction workers on high-risk construction sites is important for implementing behaviour-based safety management. However, safety risks in worker trajectories are a complex system with high uncertainty. This resulted in few studies focusing on analysing the spatial–temporal risk in workers' trajectories from a systematic perspective. This study designs a new framework to explore the spatial–temporal patterns of safety risks in the trajectories of construction workers based on complex network theory. First, an integrated site safety risk classification method by combining hazard sources and group trajectory distribution is developed to accurately describe the spatial distribution of site risks. Second, a new complex network chronnet is used to construct complex networks containing risk information for spatial–temporal analysis. Finally, key risk areas and risk transition patterns are identified through the analysis of network measures. The study also developed a computational program that allows the network to be constructed and analysed in real-time. The feasibility and effectiveness of the method are verified through a case study. The results show that the method can reveal the risk distribution at the micro level, and explore the risk clustering and transition features in worker trajectories at the macro level. The study allows for an accurate analysis of dynamic risk patterns in construction workers' trajectories from a systematic perspective. It can also provide theoretical and practical support for personalized and adaptive behaviour-based safety management for construction workers.     

编码协作系统准循环重复累积码的联合设计与性能分析

重复累积(RA)码是一种特殊结构的低密度奇偶校验(LDPC)码,不仅具有LDPC码的优点,还能实现差分编码。针对LDPC编码协作系统编码复杂度高、时延长的问题,该文引入准循环RA(QC-RA)码,推导出信源节点和中继节点采用的QC-RA码对应的联合校验矩阵,基于公差构造方法设计该联合校验矩阵,并证明该方法设计的联合校验矩阵不存在围长为girth-4, girth-6的短环。理论分析和仿真结果表明,同等条件下该系统比相应点对点系统具有更优异的误码率性能。仿真结果同时表明,与采用一般构造QC-RA码或基于Z型构造QC-RA码相比,采用基于公差构造的联合设计QC-RA码的多信源多中继协作均可获得更高的编码增益。     

Measuring Project Management Performance: Case of Construction Industry

This study develops construction-specific determinants and indicators of project management performance based on the 14 knowledge areas of the project management body of knowledge guide. Interrelations among the knowledge areas and influence of these factors on performance are investigated. Data collected from 121 construction projects are analyzed using structural equation modeling. Research findings suggest that project integration, communications, safety, risk, human resources, financial, and cost management have a direct impact, whereas scope and time management have an indirect effect on performance. The findings reported in this study are expected to help construction project managers devise and implement strategies and develop actions to improve project success. An engineering manager can use the framework developed in this research to define the underlying factors of efficient project management practices.     

Critical factors and paths influencing construction workers’ safety risk tolerances

While workers’ safety risk tolerances have been regarded as a main reason for their unsafe behaviors, little is known about why different people have different risk tolerances even when confronting the same situation. The aim of this research is to identify the critical factors and paths that influence workers’ safety risk tolerance and to explore how they contribute to accident causal model from a system thinking perceptive. A number of methods were carried out to analyze the data collected through interviews and questionnaire surveys. In the first and second steps of the research, factor identification, factor ranking and factor analysis were carried out, and the results show that workers’ safety risk tolerance can be influenced by four groups of factors, namely: (1) personal subjective perception; (2) work knowledge and experiences; (3) work characteristics; and (4) safety management. In the third step of the research, hypothetical influencing path model was developed and tested by using structural equation modeling (SEM). It is found that the effects of external factors (safety management and work characteristics) on risk tolerance are larger than that of internal factors (personal subjective perception and work knowledge & experiences). Specifically, safety management contributes the most to workers’ safety risk tolerance through its direct effect and indirect effect; while personal subjective perception comes the second and can act as an intermedia for work characteristics. This research provides an in-depth insight of workers’ unsafe behaviors by depicting the contributing factors as shown in the accident causal model developed in this research.     

Estimating Construction Material Indices with ARIMA and Optimized NARNETs

Construction Industry operates relying on various key economic indicators. One of these indicators is material prices. On the other hand, cost is a key concern in all operations of the construction industry. In the uncertain conditions, reliable cost forecasts become an important source of information. Material cost is one of the key components of the overall cost of construction. In addition, cost overrun is a common problem in the construction industry, where nine out of ten construction projects face cost overrun. In order to carry out a successful cost management strategy and prevent cost overruns, it is very important to find reliable methods for the estimation of construction material prices. Material prices have a time dependent nature. In order to increase the foreseeability of the costs of construction materials, this study focuses on estimation of construction material indices through time series analysis. Two different types of analysis are implemented for estimation of the future values of construction material indices. The first method implemented was Autoregressive Integrated Moving Average (ARIMA), which is known to be successful in estimation of time series having a linear nature. The second method implemented was Non-Linear Autoregressive Neural Network (NARNET) which is known to be successful in modeling and estimating of series with non-linear components. The results have shown that depending on the nature of the series, both these methods can successfully and accurately estimate the future values of the indices. In addition, we found out that Optimal NARNET architectures which provide better accuracy in estimation of the series can be identified/discovered as result of grid search on NARNET hyperparameters.     

建筑工程施工成本监测预警及协调控制

通过对施工成本影响因素的识别,建立了施工成本监测与预警信号模型,以及施工成本协调控制模型等。