基于GPU的大规模海浪实时绘制

海浪建模与绘制是近二十年来计算机图形学领域的一个经典问题,同时,随着硬件的发展,尤其是图形处理器(GPU)以大大超过摩尔定律的速度高速发展和其高速计算能力、并行性、其可编程功能,使得基于GPU的通用计算成为一个新研究热点.利用GPU的高速计算能力和可编程功能,解决海浪模拟中的复杂计算问题,提出一种基于图形硬件的大规模海浪实时绘制方法.首先,对图形处理器进行了概述.然后,基于Gerstner-Rankine模型生成海洋高度场,采用屏幕细分自适应算法对数字地球上的可视海洋表面进行采样,利用图形处理单元的可编程特性进行顶点和颜色计算,模拟实时球面海浪效果.实验结果表明,基于GPU的方法可以在普通PC图形硬件上实现大规模海浪的交互漫游.     

基于联锁分块的大规模地形建模方法研究

针对已有MRLoD算法生成的地形=三角形网不稳定等缺点,提出了一种新的基于联锁分块的大规模地形建模方法,在对地形进行分块调度的基础上通过预先建立分块模板和分块联锁模板,渲染时动态匹配各模板建立平滑完整的分块模型,在分块调度及附加计算策略下,拼接各分块以完成整块地形的多分辨率建模,并以高效的方式将模型数据传人渲染硬件.实验表明,在满足了精度要求的同时提高了模型的稳定性,有效减少了实时计算量,在渲染效率上取得了令人满意的结果,能够满足用户对大规模地形的实时漫游的要求.     

自动称重系统中PLC与上位机串口通信的实现

利用西门子CP340自带的串口通讯协议394R,并根据自动称重系统中重量数据格式的要求自定义应用层协议,用VC＋＋60编写应用程序,实现自动称重系统中计算机实时从PLC中读取重量数据。     

UAV imagery based potential safety hazard evaluation for high-speed railroad using Real-time instance segmentation

Potential safety hazards (PSHs) along the track needs to be inspected and evaluated regularly to ensure a safe environment for high-speed railroad operations. Other than track inspection, evaluating potential safety hazards in the nearby areas often requires inspectors to patrol along the track and visually identify potential threads to the train operation. The current visual inspection approach is very time-consuming and may raise safety concerns for the inspectors, especially in remote areas. Using the unmanned aerial vehicle (UAV) has great potential to complement the visual inspection by providing a better view from the top and ease the safety concerns in many cases. This study develops an automatic PSH detection framework named YOLARC (You Only Look at Railroad Coefficients) using UAV imagery for high-speed railroad monitoring. First, YOLARC is equipped with a new backbone having multiple available receptive fields to strengthen the multi-scale representation capability at a granular level and enrich the semantic information in the feature space. Then, the system integrates the abundant semantic features at different high-level layers by a light weighted feature pyramid network (FPN) with multi-scale pyramidal architecture and a Protonet with residual structure to precisely predict the track areas and PSHs. A hazard level evaluation (HLE) method, which calculates the distance between identified PSH and the track, is also developed and integrated for quantifying the hazard level. Experiments conducted on the UAV imagery of high-speed railroad dataset show the proposed system can quickly and effectively turn UAV images into useful information with a high detection rate and processing speed.     

A digital twin in transportation: Real-time synergy of traffic data streams and simulation for virtualizing motorway dynamics

The introduction of digital twins is expected to fundamentally change the technology in transportation systems, as they appear to be a compelling concept for monitoring the entire life cycle of the transport system. The advent of widespread information technology, particularly the availability of real-time traffic data, provides the foundation for supplementing predominated (offline) microscopic simulation approaches with actual data to create a detailed real-time digital representation of the physical traffic. However, the use of actual traffic data in real-time motorway analysis has not yet been explored. The reason is that there are no supporting models and the applicability of real-time data in the context of microscopic simulations has yet to be recognized. Thus, this article focuses on microscopic motorway simulation with real-time data integration during system run-time. As a result, we propose a novel paradigm in motorway traffic modeling and demonstrate it using the continuously synchronized digital twin model of the Geneva motorway (DT-GM). We analyze the application of the microscopic simulator SUMO in modeling and simulating on-the-fly synchronized digital replicas of real traffic by leveraging fine-grained actual traffic data streams from motorway traffic counters as input to DT-GM. Thus, the detailed methodological process of developing DT-GM is presented, highlighting the calibration features of SUMO that enable (dynamic) continuous calibration of running simulation scenarios. By doing so, the actual traffic data are directly fused into the running DT-GM every minute so that DT-GM is continuously calibrated as the physical equivalent changes. Accordingly, DT-GM raises a technology dimension in motorway traffic simulation to the next level by enabling simulation-based control optimization during system run-time that was previously unattainable. It, thus, forms the foundation for further evolution of real-time predictive analytics as support for safety–critical decisions in traffic management. Simulation results provide a solid basis for the future real-time analysis of an extended Swiss motorway network.     

Digital twinning for smart hospital operations: Framework and proof of concept

Analyzable data capturing physical entity activities is a prerequisite for complex hospital operational decision-makings. However, there is a lack of effective strategies to integrate real-time data from multiple sources for efficient clinical and non-clinical operations in healthcare settings. Drawing on previous explorations of digital twins that facilitate real-time feedback of physical entities, we propose a conceptual framework of digital twinning for smart hospitals, with identified information needs and enabling technologies. A pilot platform is developed and tested in a Shanghai municipal hospital. The results indicate that the digital twinning method enables continuous real-time control of related operational tasks, and further promotes the development of digitization, automation, and intelligence in hospital operations.     

基于Windows的开放式数控系统实时任务调度研究

对以Windows操作系统为平台的开放式数控系统实时多任务处理方案进行了研究。在探讨了基于Windows的多任务和多线程的实现方法、Windows的任务调度模式和实时性的实现形式的基础上,应用VC++6.0编程,给出了基于Windows XP开发的开放式数控系统的模块框架、多任务调度实现方案,并提出了一种新的处理实时性任务的方法;实现了数控总控软件的实时任务调度和多线程的应用。     

Dynamic hinting: Collaborative real-time resource management for reactive embedded systems

The increasing complexity of today’s reactive embedded applications can rapidly result in reduced real-time capabilities of the underlying hard and software. As an example for this paper we’ll refer to the specific and growing demands on the severely resource constrained sensor nodes in sensor/actuator networks (SANet). While preemptive operating systems are one way to retain acceptable reactivity within highly dynamic environments, their concurrency paradigm commonly leads to severe resource management problems, caused by the coexistence of tasks with interfering and even varying requirements. To counteract these problems, we present the novel Dynamic Hinting approach for maintaining good reactivity in typically resource constrained sensor/actuator systems by efficient combination of preemptive task scheduling and collaborative resource allocation. With respect to task priorities, our technique significantly improves classical methods for handling priority inversions (and deadlocks where required) under both short- and long-term resource allocations. Furthermore, we facilitate compositional software design by providing independently developed tasks with runtime information for yet collaborative and reflective resource sharing – e.g. by means of time-utility-functions. In many cases this even allows to reduce blocking delays as otherwise imposed by bounded priority inversion.     

Improving responsiveness of soft aperiodic tasks using proportional slack time

In a real-time system with both hard real-time periodic jobs and soft real-time aperiodic jobs, it is important to guarantee that the deadline of each periodic job is met, as well as to provide a fast response time for each aperiodic job. We propose an algorithm, called Proportional Slack Reserve (PSR), that produces an efficient schedule for such an environment. For every execution unit of a periodic job, the PSR algorithm reserves time which can be used for execution of aperiodic jobs. If reserved time is not available, the algorithm assigns a deadline to an aperiodic job for achieving better responsiveness of aperiodic jobs. The proposed algorithm can fully utilize processing power while meeting all deadlines of periodic jobs. It can also easily reclaim the time unused by the periodic job. We analytically show that for each aperiodic job, the response time in a PSR schedule is no longer than that in a TBS schedule, which is known to be efficient for servicing aperiodic jobs. We also present simulation results in which the response time of PSR is significantly improved over that of TBS, and moreover the performance of PSR compares favorably with TB(N) considering scheduling overhead.