校园网安全解决方案的分析与设计

校园网在运行过程中面临各种安全威胁,针对校园网的现状,提出了基于校园网安全运行的相关解决方案。对网络管理等多方面提出了相应的措施。     

浅谈计算机网络安全及相关安全对策

随着信息产业的高速发展,计算机网络也迅速普及,各部门都利用互联网建立自己的信息系统渗透到我们生活的各个角落。以充分利用各类信息资源。但在连接信息能力、流通能力提高的同时,基于网络连接的安全问题也日益突出。然而,网络自身固有其脆弱性,并且中国的网络信息技术起步较晚,给网络安全带来诸多潜在的威胁。本文针对影响计算机网络系统安全的主要因素,结合实际工作进行分析,并提出相应的对策进行探讨。     

油气系统工程从系统工程角度看油气业的安全和环境保护

本文从系统工程的角度对石油天然气工业的整体作系统分析,并从资源和环境的挑战和机遇进行讨论,强调其中资源是关键的,它是客观存在的,条件是困难的,需要不断投入,加强研究,努力创新。强调建立健康安全环境HSE体系的重要性和必要性,同时给出墨西哥湾BP深水地平线平台事故造成严重后果的案例。最后给出了简单结论-如何面对和适宜采取的措施,如面对一个油气工程系统必须作好系统分析,用系统工程的办法去解决,要以人为本,从上层至基层,注意人为因素,严格完整地采用和发展HSE体系的作用无疑是极为有效的方法。     

Theory and implementation of path planning by negotiation for decentralized agents

This paper presents a cooperative decentralized path-planning algorithm for a group of autonomous agents that provides guaranteed collision-free trajectories in real-time. The algorithm is robust with respect to arbitrary delays in the wireless traffic, possible sources being transmission time and error correction. Agents move on reserved areas which are guaranteed not to intersect, therefore ensuring safety. A handshaking procedure guarantees recent information states for the agents. Conflicts between agents are resolved by a cost-based negotiation process. The basic algorithm is augmented by the introduction of waypoints, which increase performance at the cost of additional wireless traffic. An implementation of the algorithm is tested in simulation and successfully applied to a real system of autonomous robots. The results are presented and discussed.     

轨道交通站台安全门控制系统

轨道交通站台安全门作为公共安全防护设备,广泛应用在地铁、轻轨等轨道交通中的高架和地面站台上,具有节能、环保和安全功能。因此它在设计、制造、安装过程中需要充分考虑其自身的可靠性及乘客安全、行车安全。本文将对安全门系统的网络、控制及软件三方面进行详细论述。     

集成安全分析的模型驱动软件开发方法研究

提出了一种集成安全分析的软件设计与开发新方法,该方法以MDA为基础框架,使用VMLsec建立软件安全属性的平台无关模型,使得在软件设计的早期就能够囊括更多的安全需求,从而降低后期开发的风险与成本,提高软件的复用性.     

Establishment-level occupational safety analytics: Challenges and opportunities

In occupational safety and health, big data and analytics show promise for the prediction and prevention of workplace injuries. Advances in computing power and analytical methods have allowed companies to reveal insights from the “big” data that previously would have gone undetected. Despite the promise, occupational safety has lagged behind other industries, such as supply chain management and healthcare, in terms of exploiting the potential of analytics and much of the data collected by organizations goes unanalyzed. The purpose of the present paper is to argue for the broader application of establishment-level safety analytics. This is accomplished by defining the terms, describing previous research, outlining the necessary components required, and describing knowledge gaps and future directions. The knowledge gaps and future directions for research in establishment-level analytics are categorized into readiness for analytics, analytics methods, technology integration, data culture, and impact of analytics.     

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.     

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.