冷拌冷铺乳化沥青混合料压实时机确定方法室内模拟研究

冷拌冷铺乳化沥青混合料的强度形成受多种因素的影响,导致其压实时机难以把握,而现行规范中缺少冷拌冷铺乳化沥青混合料压实时机的判定标准,制约了该材料的推广应用。为此,对冷拌冷铺乳化沥青混合料压实时机的确定方法和判据开展室内模拟研究。首先,通过室内试验建立了乳化沥青混合料劈裂强度、高温稳定性、低温抗裂性及水稳定性与试件成型时机的关系方程,相关性分析表明,劈裂强度与高温稳定性、低温抗裂性及水稳定性之间的相关性极显著,可以用劈裂强度作为代表性指标来确定压实时机。在此基础上,以路用性能满足热拌改性沥青混合料的规范要求为判据,确定了乳化沥青混合料压实时机的判定指标和标准,即判定指标为劈裂强度,判定标准为劈裂强度Q≥0.69 MPa。该成果对乳化沥青混合料压实时机的确定具有参考价值。

高含水率疏浚淤泥材料化土击实时机选择研究

研究2种初始含水率疏浚淤泥添加不同比例生石灰改性的材料化土、经不同时长的闷料期,其击实试样的无侧限抗压强度变化规律,通过比较强度的变化来选择淤泥材料化土的合理击实时机。试验结果表明:击实时机的选择对击实材料化土养护后的强度有显著的影响,闷料期越长,其无侧限抗压强度越大。但是从工程成本及施工效率的角度看,掺灰比大的材料化土适宜缩短闷料期,因为缩短闷料期对击实材料化土养护之后的强度影响不大;对于掺灰比小的材料化土则适宜延长闷料期,增长闷料期不仅可以改善土性,利于击实施工,且击实材料化土相同养护龄期的强度也有明显增大。

基于贯入阻力测试系统的聚氨酯混凝土压实时机确定方法

为了解决实际工程中聚氨酯混凝土因强度形成影响因素多而导致压实时机难以确定的问题,提出一种便捷直观的压实时机确定方法。首先针对自主研发的聚氨酯混凝土设计了一种贯入阻力测试系统,将容许空隙率(1.5%~4.0%)作为压实效果评价标准,通过重复性试验确定可压实贯入阻力范围值,提出以聚氨酯混凝土贯入阻力量化其固化反应程度的方法,进一步建立以催化剂用量为唯一可控因素的施工可压实时间预测模型。试验结果表明:在温度、湿度及催化剂用量代表性组合的试验条件下,当聚氨酯混凝土的贯入阻力在可压实贯入阻力值范围(0.20 kN±0.03 kN)内时,其马歇尔试件空隙率可满足容许空隙率(1.5%~4.0%)范围要求,相应的可压实时间预测模型相关系数高(R2=0.89)且差异性极显著。工程实例验证了该方法的可行性及可靠性。

实时计算机系统结构综述

在时间敏感的嵌入式系统中,任务需要满足其最后截止期限,错失任务期限会显著影响服务质量或带来灾难性后果.与通用系统相比,实时系统研究进展缓慢,甚至很多基本概念都未达成共识.精确计时(precision timed,PRET)机和实时处理单元(real-time processing unit,RPU)是2套现有的实时系统解决方案,以它们为例介绍实时系统相关的概念,阐述实时系统发展中遇到的问题,比较异同,并分析实时系统各个层次遇到的问题和现有的解决方法.在应用层,用户需要定时操作的接口;在指令集架构(instruction set architecture,ISA)层,应充分利用硬件提供的资源,向上层提供足够的时间语义抽象和计时精度;硬件层需要支持ISA的时间属性和时间语义,并在保证实时性的基础上尽可能地提高性能.对实时系统的研究面临许多挑战.在现有的实时系统设计研究的过程中,关键问题在于上层应用的时间语义难以与底层实现保持一致.

一种具有时间语义的实时处理器模型

实时嵌入式系统是安全关键设备的计算与控制核心.为了保证系统的时间行为正确,要求其软硬件具有时序确定性和可预测性.而现代计算机系统的各个抽象层次均缺乏时间语义,无法满足硬实时安全性设计要求.针对指令集体系结构层次的基础设施缺乏时间语义的问题,尝试重新定义实时嵌入式系统的指令集和微体系结构.首先,提出一种具有时间语义的实时计算机体系结构模型——实时机(real-time machine,RTM).接着,参考时间触发自动机理论,构建具有时间语义的指令集——TTI(time-triggered instruction set)作为RTM的软硬件接口,并讨论TTI的时间语义完备性问题.最后,设计并实现了实时处理单元(real-time processing unit,RPU),通过理论分析与实验结果的对照得出RPU的时序确定性.逻辑执行时间(logical execution time,LET)编程模型是学术界广泛认可的实时编程范式,通过给出在RPU上运行LET任务集的示例,说明RTM和TTI的有效性.

REAL-TIME TRACKING FOR FAST MOVING OBJECT ON COMPLEX BACKGROUND

A real-time tracking system for the fast moving object on the complex background is proposed.The Markov random filed（MRF）model based background subtraction algorithm is used to detect the changing pixels and track the moving object.The prior probability of the segmentation mask is modeled by using MRF,and the object tracking task is translated into the maximum a-posterior（MAP）problem.Experimental results show that the method is efficient at both offline and online moving objects on simple and complex background.

Single Point Positioning with Sequential Least-Squares Filter and Estimated Real-Time Stochastic Model

To obtain higher accurate position estimates, the stochastic model is estimated by using residual of observations, hence, the stochastic model describes the noise and bias in measurements more realistically. By using GPS data and broadcast ephemeris, the numerical results indicating the accurate position estimates at sub-meter level are obtainable.

A new approach for real time object detection and tracking on high resolution and multi-camera surveillance videos using GPU

High resolution cameras and multi camera systems are being used in areas of video surveillance like security of public places, traffic monitoring, and military and satellite imaging. This leads to a demand for computational algorithms for real time processing of high resolution videos. Motion detection and background separation play a vital role in capturing the object of interest in surveillance videos, but as we move towards high resolution cameras, the time-complexity of the algorithm increases and thus fails to be a part of real time systems. Parallel architecture provides a surpass platform to work efficiently with complex algorithmic solutions. In this work, a method was proposed for identifying the moving objects perfectly in the videos using adaptive background making, motion detection and object estimation. The pre-processing part includes an adaptive block background making model and a dynamically adaptive thresholding technique to estimate the moving objects. The post processing includes a competent parallel connected component labelling algorithm to estimate perfectly the objects of interest. New parallel processing strategies are developed on each stage of the algorithm to reduce the time-complexity of the system. This algorithm has achieved a average speedup of 12.26 times for lower resolution video frames(320×240, 720×480, 1024×768) and 7.30 times for higher resolution video frames(1360×768, 1920×1080, 2560×1440) on GPU, which is superior to CPU processing. Also, this algorithm was tested by changing the number of threads in a thread block and the minimum execution time has been achieved for 16×16 thread block. And this algorithm was tested on a night sequence where the amount of light in the scene is very less and still the algorithm has given a significant speedup and accuracy in determining the object.

DIV： Dynamic Integrity Validation Framework for Detecting Compromises on Virtual Machine Based Cloud Services in Real Time

with the increasing popularity of cloud services,attacks on the cloud infrastructure also increase dramatically.Especially,how to monitor the integrity of cloud execution environments is still a difficult task.In this paper,a real-time dynamic integrity validation(DIV) framework is proposed to monitor the integrity of virtual machine based execution environments in the cloud.DIV can detect the integrity of the whole architecture stack from the cloud servers up to the VM OS by extending the current trusted chain into virtual machine's architecture stack.DIV introduces a trusted third party(TTP) to collect the integrity information and detect remotely the integrity violations on VMs periodically to avoid the heavy involvement of cloud tenants and unnecessary information leakage of the cloud providers.To evaluate the effectiveness and efficiency of DIV framework,a prototype on KVM/QEMU is implemented,and extensive analysis and experimental evaluation are performed.Experimental results show that the DIV can efficiently validate the integrity of files and loaded programs in real-time,with minor performance overhead.

Open Architecture of Single-processor Real-time Robot Control System Based on Windows NT

This paper introduces the architecture and implementation of an industrial robot control system based on Windows NT. This robot control system, which is based on a single-processor structure, can run on general industrial computers. Owing to using Windows NT's real-time extension RTX, the control system can achieve good realtime performance and friendly user interface in one general-purpose operating system. A three layer hierarchical architecture of control software is proposed to make the system more scalable and flexible. Furthermore a communication and configuration system is implemented to enable modules to communicate with each other, which make the control system scalable and flexible.

Processing of 8-Channel Synchronous Electro-Cardiograph

A real time algorithm is presented here to recognize and analyze 8 channel simultaneous electro cardiograph(ECG). The algorithm transforms 8 channel simultaneous ECG into three orthogonal vectors and spatial velocity first, then forms the spatial velocity sample, and uses this spatial velocity sample to recognize each beat. The algorithm computes the averaged parameters by using averaged spatial velocity and the averaged ECG and the current parameters by using the current beat period and current width of QRS. The algorithm can recognize P, QRS and T onsets and ends of simultaneous 12 lead ECG precisely, and some arrhythmias such as premature ventricular beat, ventricular escape beat, R on T, bigeminy, trigeminy. The algorithm software works well on a real 8 channel ECG system and meets the demands of designing.

Real-Time, Automatic and Wireless Bridge Monitoring System Based on MEMS Technology

Currently, the monitoring of bridges in China heavily relies on manual operation, which has several major problems. It generally takes a very long time to complete an inspection process on bridges. The manual data is sometimes unreliable or even wrong in the case of careless operation. The inspection activity itself is dangerous for inspectors, e.g., bridges are located in the sea or river. Some semi-automatic monitoring methods are recently employed, but they are either very expensive or do not work properly. Therefore, the traditional bridge monitoring process becomes an increasing challenge for bridge operators. In this paper, a real-time and automatic bridge monitoring system is presented to meet the bridge monitoring needs, and MEMS （Micro Electro Mechanical Systems） are the key building block in this system. By using the MEMS-based sensors, it is much more efficient and accurate in monitoring bridges with the measurement of inclination, acceleration, displacement, moisture, temperature, stress and other data.

Real-time continuous-wave imaging with a 1.63THz OPTL and a pyroelectric camera

Real-time continuous-wave terahertz imaging is demonstrated with a 1.63 THz （184.31 lam） optically-pumped terahertz laser （OPTL） and a 124 × 124 element room-temperature pyroelectric camera. Transmission-mode THz imaging is presented for the samples hidden in various wrapping materials. These experimental results reveal the possibility to construct a simple real-time THz imaging system applied to nondestructive inspection.

Modeling and software implementation of flight system for simulator of a new fighter

Real-time modeling and simulation of flight system are the key parts of simulator. After describing the architecture of simulator for a newer fighter, author presents the composition of flight system and its mathematic models. In this paper, aircraft is regarded as an elastic flight body. And a new integrated algorithm which can remedy the shortcoming of Euler method and four-element method is used to calculate the Eulerian angles of aircraft. Finally, the software implementation of the flight system is given in the paper.

Real-time Business Network Selection Based on Auction Mechanism

In the framework of heterogeneous wireless networks,it is difficult for every user to obtain QoS-based services anywhere at any time.Due to heterogeneous networks,the dynamic network selection scheme needs to achieve seamless mobility,and also supports the optimization of service quality and load balancing.According to different business characteristics,this paper describes different real-time businesses in utility functions,and solves network selection problems for real-time businesses.Based on auction mechanism,it introduces the upset price in order to maximize online profits.Meanwhile,the network selection scheme is also helpful to control network congestion.The study of real-time business network selection based on auction mechanism can not only meet the demands of service quality of multiple realtime applications,but also achieves load balancing between different networks.

Irrigation Management in Real Time for Arugula Crop in Sergipe

The management of the irrigation is fundamental for success of leaves vegetables production. The work was carried out aiming to evaluate the production response of the arugula （Eruca sativa Mill.） under different irrigation levels at 25, 31, 37 and 43 days after sowing. The treatments were distributed in randomized blocks design with four replication, and evaluated in split-plot scheme of 4 × 4, with the plots constituted by four irrigation levels equivalent to reference evapotranspiration （ET0） at 50%, 75%, 100% and 125% estimated by Penman-Monteith equation; and the split-plot constituted by days after sowing. The arugula planting was established in November of 2008 with direct sowing in nursery with 0.1 m × 0.2 m per plant, using the cv. ＂Folha Larga＂. After the germination phase was carried out crop management necessary to the crop production. It was analyzed： plant height （cm）, leaf number, fresh weight （g m2） and dry weight （g m2）. The results showed the significant differences at level of 5% of probability for the Scott-Knott test for all variables analyzed after 37 days of planting. The results permit to infer that the irrigation levels exert influence under the studied variables with the higher efficiency of water use found for levels of 75% and 100% of the reference evapotranspiration.

Real-Time Animation of Cloth Based on Rigid Rods Model

A rigid rods model for real-time simulation of cloth is presented, which can be used in e-commerce applications, games or Wirtual Reality environment. The proposed algorithm simplifies the basic mass-spring model by replacing the springs of masses with the rigid rods, and using the Verlet Integration method to calculate the position and velocity of the masses. Compared the efficiency and the effect of sinmulation with other similar systems, this algorithm is faster and realistic for some real-time applications.

UML statechart based rigorous modeling of real-time system

Rigorous modeling could ensure correctness and could verify a reduced cost in embedded real-time system development for models. Software methods are needed for rigorous modeling of embedded real-time systems. PVS is a formal method with precise syntax and semantics defined. System modeled by PVS specification could be verified by tools. Combining the widely used UML with PVS, this paper provides a novel modeling and verification approach for embedded real-time systems. In this approach, we provide 1) a time-extended UML statechart for modeling dynamic behavior of an embedded real-time system; 2) an approach to capture timed automata based semantics from a timed statechart; and 3) an algorithm to generate a finite state model expressed in PVS specification for model checking. The benefits of our approach include flexibility and user friendliness in modeling, extendability in formalization and verification content, and better performance. Time constraints are modeled and verified and is a highlight of this paper.

Development of PC Worker’s Management System in PC Training Room and Office by Using IoT Technology

At present time, there has been a demand for management systems that can survey and monitor a PC （personal computer） practice room, movement of people in an office, situation of utilization of facilities and so on in real time without causing psychological stress. For example, PC administrators in Japanese national educational institutions must report operation status of PC practice rooms once a year. But, there is currently no system for automatically recording PC operating situations. Therefore, the burden on the PC administrators is big. In this study, we aimed at systems for accurately managing the sitting and work time without psychologically stressing PC users. This time, we propose uniform management systems of sitting and work time using smart tap node and mat sensor node by IoT （Internet of Things） technology. The smart tap was connected to PCs to acquire the operating status of the PCs. In parallel with this smart tap, the mat sensor was used to acquire human presence state. By calculating binary data representing the PC operating status and human presence state from the two sensing data （smart tap and mat sensor） by the proposed technique, we can exactly calculate wasteful power consumption etc. The use of IoT technology makes it unnecessary to use large installation services when introducing our system. Therefore, this our proposal system can be easily installed even by unskilled workers.

HYBRID INTERNET TRAFFIC CLASSIFICATION TECHNIQUE

Accurate and real-time classification of network traffic is significant to network operation and management such as QoS differentiation, traffic shaping and security surveillance. However, with many newly emerged P2P applications using dynamic port numbers, masquerading techniques, and payload encryption to avoid detection, traditional classification approaches turn to be ineffective. In this paper, we present a layered hybrid system to classify current Internet traffic, motivated by variety of network activities and their requirements of traffic classification. The proposed method could achieve fast and accurate traffic classification with low overheads and robustness to accommodate both known and unknown/encrypted applications. Furthermore, it is feasible to be used in the context of real-time traffic classification. Our experimental results show the distinct advantages of the proposed classifi- cation system, compared with the one-step Machine Learning (ML) approach.