Real Time Systems with Nonpreemptive Priorities and Ample Maintenance Facilities

We consider a real time data acquisition and processing multiserver system with identical servers (such as unmanned aerial vehicles, machine controllers, overhearing devices, medical monitoring devices, etc.) which can be maintained/programmed for different kinds of activities (e.g. passive or active). This system provides a service for real time tasks arriving via several channels (such as surveillance regions, assembly lines, communication channels, etc.) and involves maintenance. We focus on the worst case analysis of the system with ample maintenance facilities exponentially distributed time to failure and maintenance times. We consider two kinds of models (with and without nonpreemptive priorities) and provide balance equations for steady state probabilities and various performance measures, when both operation and maintenance times are exponentially distributed.

A Comparative Study between Landmark Based and Real Time Ultrasound Guided Sub Arachnoid Block

Background: Sub arachnoid block (SAB) performed by traditional landmark palpation technique can be inaccurate. This problem is exacerbated by altered patient anatomy due to obesity and age-related changes. A pre-procedural ultrasound scan of the lumbar spine has been shown to be of benefit in guiding lumbar epidural insertion in obstetric patients. Information on the use of real-time ultrasound (RUS) guided SAB, to date, been limited. This study compared RUS guided SAB to traditional landmark guided technique in patients undergoing spinal anesthesia for different surgical procedures. Methods: This was a prospective, single center, comparative observational study conducted in the department of anesthesiology at our center. 560 patients who underwent spinal anesthesia either by landmark based technique or real-time ultrasound-guided methods. The primary outcome was the first attempt success rate of dural puncture when employing the two methods. Results: Baseline characteristics were similar in the two study groups. The first attempt success rate of dural puncture in landmark guided group was 64.3% compared to 72.6% in the ultrasound guided group. This difference was not statistically significant. The procedure performance time was significantly shorter with landmark palpation compared to use of real-time ultrasound guided method. Conclusion: Use of RUS-guided technique does not significantly improve the first attempt success rate of SAB dural puncture during spinal anesthesia compared to the traditional landmark-guided technique.

基于Simulink Real-Time的汽车空调半实物仿真试验系统研发

针对多样化汽车空调电子零部件的高效、低成本总成级测试需求,研究基于一汽大众速腾1.6 L车型原型,设计了基于Simulink Real-Time的汽车空调半实物仿真试验系统。该系统集成了真实的汽车空调总成、制冷循环以及包含宿主机和目标机的双机实时仿真系统,用于开发和运行台架监控和空调控制模型,为汽车空调电子零部件提供半实物仿真测试环境。通过系统集成及功能验证,结果表明,汽车空调半实物仿真试验系统能够实现汽车空调基本控制功能,同时在不同工况下实现乘员舱温度控制的稳定性,稳态误差控制在±1℃以内。此外,该系统还具备灵活调整空调运行工况和状态的能力,为汽车空调电子零部件提供了高效、低成本的半实物仿真测试环境。

Intrusion Detection System for PS-Poll DoS Attack in 802.11 Networks Using Real Time Discrete Event System

Wi-Fi devices have limited battery life because of which conserving battery life is imperative. The 802.11 Wi-Fi standard provides power management feature that allows stations(STAs) to enter into sleep state to preserve energy without any frame losses. After the STA wakes up, it sends a null data or PS-Poll frame to retrieve frame(s) buffered by the access point(AP), if any during its sleep period. An attacker can launch a power save denial of service(PS-DoS) attack on the sleeping STA(s) by transmitting a spoofed null data or PS-Poll frame(s) to retrieve the buffered frame(s) of the sleeping STA(s) from the AP causing frame losses for the targeted STA(s). Current approaches to prevent or detect the PS-DoS attack require encryption,change in protocol or installation of proprietary hardware. These solutions suffer from expensive setup, maintenance, scalability and deployment issues. The PS-DoS attack does not differ in semantics or statistics under normal and attack circumstances.So signature and anomaly based intrusion detection system(IDS) are unfit to detect the PS-DoS attack. In this paper we propose a timed IDS based on real time discrete event system(RTDES) for detecting PS-DoS attack. The proposed DES based IDS overcomes the drawbacks of existing systems and detects the PS-DoS attack with high accuracy and detection rate. The correctness of the RTDES based IDS is proved by experimenting all possible attack scenarios.

Specifying Requirements of Real-Time System with Rules and Templates

This paper presents a model specifying requirements of real-time systems. Dif ferent from existing researches, this model mainly uses rules and templa tes to represent hierarchical FSMs (Finite State Machine). In this model, one ru le corresponds to one state transition of FSM and one template corresponds to on e FSM. Rules and information with respect to a FSM can be written in a template. So templates include not only state diagrams, but also information that can not be described by FSM, such as performance requirements. The specification using this model consists of a collection of templates and it is easy for users to und erstand and to review. After introduced the related researches and principles of the model, this paper specifies requirements of a real-time system with this m odel, and discusses characters of this model in the end.

Performance of real‑time neutron/gamma discrimination methods

Nuclear security usually requires the simultaneous detection of neutrons and gamma rays.With the development of crystalline materials in recent years,Cs2LiLaBr6(CLLB)dual-readout detectors have attracted extensive attention from researchers,where real-time neutron/gamma pulse discrimination is the critical factor among detector performance parameters.This study investigated the discrimination performance of the charge comparison,amplitude comparison,time comparison,and pulse gradient_(m)ethods and the effects of a Sallen–Key filter on their performance.Experimental results show that the figure of merit(FOM)of all four methods is improved by proper filtering.Among them,the charge comparison method exhibits excellent noise resistance;moreover,it is the most_(s)uitable method of real-time discrimination for CLLB detectors.However,its discrimination performance depends on the parameters t_(s),t_(m),and t_(e).When t_(s)corresponds to the moment at which the pulse is at 10%of its peak value,t_(e)requires a delay of only 640–740 ns compared to t_(s),at which time the potentially optimal FOM of the charge comparison method at 3.1–3.3 MeV is greater than 1.46.The FOM obtained using the t_(m)value calculated by a proposed maximized discrimination difference model(MDDM)and the potentially optimal FOM differ by less than 3.9%,indicating that the model can provide good guidance for parameter selection in the charge comparison method.

Pulse-shaping method for real-time neutron/gamma discrimination at low sampling rates

The Na I:Tl scintillator is an innovative material for dual-gamma-ray and neutron detection with a low ^(6)Li concentration.To achieve real-time n/γ discrimination,a zero-crossing time comparison algorithm based on trapezoidal pulse shaping was developed.The algorithm can operate efficiently at low sampling rates and was implemented on a single-probe portable digital n/γ discriminator based on a field-programmable gate array.The discriminator and Na I:Tl,^(6)Li detector were tested in a neutron-gamma mixed field produced by an ^(241)Am-Be neutron source to evaluate the performance of the algorithm.The figure of merits was measured as 2.88 at a sampling rate of 50 MHz,indicating that the discriminator with its embedded algorithm has a promising n/γ discrimination capability.Efficient discrimination at sampling rates of 40 and 25 MHz demonstrates that the capability of this method is not limited by low sampling rates.

Metaheuristics Based Node Localization Approach for Real-Time Clustered Wireless Networks

In recent times,real time wireless networks have found their applicability in several practical applications such as smart city,healthcare,surveillance,environmental monitoring,etc.At the same time,proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks.This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization(IM-EECNL)approach for real-time wireless networks.The proposed IM-EECNL technique involves two major processes namely node localization and clustering.Firstly,Chaotic Water Strider Algorithm based Node Localization(CWSANL)technique to determine the unknown position of the nodes.Secondly,an Oppositional Archimedes Optimization Algorithm based Clustering(OAOAC)technique is applied to accomplish energy efficiency in the network.Besides,the OAOAC technique derives afitness function comprising residual energy,distance to cluster heads(CHs),distance to base station(BS),and load.The performance validation of the IM-EECNL technique is carried out under several aspects such as localization and energy efficiency.A wide ranging comparative outcomes analysis highlighted the improved performance of the IM-EECNL approach on the recent approaches with the maximum packet delivery ratio(PDR)of 0.985.

Sentiment Drift Detection and Analysis in Real Time Twitter Data Streams

Handling sentiment drifts in real time twitter data streams are a challen-ging task while performing sentiment classifications,because of the changes that occur in the sentiments of twitter users,with respect to time.The growing volume of tweets with sentiment drifts has led to the need for devising an adaptive approach to detect and handle this drift in real time.This work proposes an adap-tive learning algorithm-based framework,Twitter Sentiment Drift Analysis-Bidir-ectional Encoder Representations from Transformers(TSDA-BERT),which introduces a sentiment drift measure to detect drifts and a domain impact score to adaptively retrain the classification model with domain relevant data in real time.The framework also works on static data by converting them to data streams using the Kafka tool.The experiments conducted on real time and simulated tweets of sports,health care andfinancial topics show that the proposed system is able to detect sentiment drifts and maintain the performance of the classification model,with accuracies of 91%,87%and 90%,respectively.Though the results have been provided only for a few topics,as a proof of concept,this framework can be applied to detect sentiment drifts and perform sentiment classification on real time data streams of any topic.

Internet of Things Enabled Energy Aware Metaheuristic Clustering for Real Time Disaster Management

Wireless Sensor Networks(WSNs)are a major element of Internet of Things(IoT)networks which offer seamless sensing and wireless connectivity.Disaster management in smart cities can be considered as a safety critical application.Therefore,it becomes essential in ensuring network accessibility by improving the lifetime of IoT assisted WSN.Clustering and multihop routing are considered beneficial solutions to accomplish energy efficiency in IoT networks.This article designs an IoT enabled energy aware metaheuristic clustering with routing protocol for real time disaster management(EAMCR-RTDM).The proposed EAMCR-RTDM technique mainly intends to manage the energy utilization of nodes with the consideration of the features of the disaster region.To achieve this,EAMCR-RTDM technique primarily designs a yellow saddle goatfish based clustering(YSGF-C)technique to elect cluster heads(CHs)and organize clusters.In addition,enhanced cockroach swarm optimization(ECSO)based multihop routing(ECSO-MHR)approach was derived for optimal route selection.The YSGF-C and ECSO-MHR techniques compute fitness functions using different input variables for achieving improved energy efficiency and network lifetime.The design of YSGF-C and ECSO-MHR techniques for disaster management in IoT networks shows the novelty of the work.For examining the improved outcomes of the EAMCR-RTDM system,a wide range of simulations were performed and the extensive results are assessed in terms of different measures.The comparative outcomes highlighted the enhanced outcomes of the EAMCRRTDM algorithm over the existing approaches.

Real-time Synchronization Method Based on Dual Ring Fieldbus in CNC System

As the popularization of dual ring fieldbus,the optimized dual ring synchronization methods are still in short.The current synchronization methods are generally established in traditional industrial fieldbus,in which transmission is commonly considered in single track,the two-way transmitting cannot take full effect,and would result in unwanted idle load on equipment lines.In stamp-transferring part,the synchronizing algorithm is not properly processed to diminish the latency,so the real-time performance of entire system cannot be ensured.To support the synchronization control of stations in the CNC system,a real-time time synchronization method for dual ring fieldbus in the CNC system is designed in this paper.In this method a synchronizing message transmission scheme based on dual ring architecture and the synchronization algorithm between master and secondary stations are integrated.In the scheme,the clock models of both master and secondary stations are optimized with corresponding modules and the stamp data transmission based on the dual ring fieldbus is devised exclusively,so the transmitting efficiency improves with less idle work.In the algorithm,all the secondary stations can accomplish the consistent state with master station by updating clock discrepancy information in one communication cycle,and it takes the advantage of two-way transmitting and makes the best use of dual ring structure,so the real-time performance of the system can be promoted while retaining the precision of synchronization.To evaluate the performance,the costs of the method and errors during synchronizing are noted and analyzed based on the actual running environment in the industrial fieldbus.The results show that it reduces communication cost and ensures the smoothness of the system with low lag effects under heavy load.The proposed time synchronization method optimizes the architecture of sync message transmission in dual ring fieldbus,and improves the efficiency of time synchronization in the stations of CNC system.

Real-time lane departure warning system based on principal component analysis of grayscale distribution and risk evaluation model

A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.

A Concept of Dynamically Reconfigurable Real-time Vision System for Autonomous Mobile Robotics

这篇论文描述被奉献在移动式机器人被嵌入的视觉系统的特定的限制。如果因为它的通用性，灵活性，性能，和费用，基于 PC 的硬件体系结构在这域里是方便的，当前的实时操作系统完全没被改编渴望与改变持续时间处理，并且它对经常必要太大保证设有自动保险装置的工作的系统。另外，和有更多的优先级的另外的机器的任务的相互作用是困难的处理。回答这个问题，我们发展了一动态地交换子可计算的视觉处理系统，基于有关安排和容错的 Cl é opatre 即时可适用的层的创新特征。这个框架允许定义紧急情况和可选的任务为机器人的另外的分系统保证最小的服务质量，当允许动态地改编处理链到的视觉时一在持续视觉过程或处理器超载上非凡。因此，它在单个硬件允许几个分系统的更好的同居，并且他们将为常规盒子并且不被设计开发不太昂贵却安全的系统，，稀罕的非凡的。最后，认为并且发展视觉系统带一个新方法，与一些求反运算符。

Multi-Threat Real-Time Separating System

This paper describes a multi-threat real-time separating system for broadband anti-radiation missile seeker. It presents a method, with a dual-port memory as comparer, to perform PF and PW hardware real-time separation and to determine the time-of-arrival (TOA) by use of sequential difference histogram (SDIF). The method has been applied to practice, which has achieved good results.

Improvement Design for Distributed Real-Time Stream Processing Systems

In the era of Big Data, typical architecture of distributed real-time stream processing systems is the combination of Flume, Kafka, and Storm. As a kind of distributed message system, Kafka has the characteristics of horizontal scalability and high throughput, which is manly deployed in many areas in order to address the problem of speed mismatch between message producers and consumers. When using Kafka, we need to quickly receive data sent by producers. In addition, we need to send data to consumers quickly. Therefore, the performance of Kafka is of critical importance to the performance of the whole stream processing system. In this paper, we propose the improved design of real-time stream processing systems, and focus on improving the Kafka's data loading process.We use Kafka cat to transfer data from the source to Kafka topic directly, which can reduce the network transmission. We also utilize the memory file system to accelerate the process of data loading, which can address the bottleneck and performance problems caused by disk I/O. Extensive experiments are conducted to evaluate the performance, which show the superiority of our improved design.

Modeling and Design of Real-Time Pricing Systems Based on Markov Decision Processes

A real-time pricing system of electricity is a system that charges different electricity prices for different hours of the day and for different days, and is effective for reducing the peak and flattening the load curve. In this paper, using a Markov decision process (MDP), we propose a modeling method and an optimal control method for real-time pricing systems. First, the outline of real-time pricing systems is explained. Next, a model of a set of customers is derived as a multi-agent MDP. Furthermore, the optimal control problem is formulated, and is reduced to a quadratic programming problem. Finally, a numerical simulation is presented.

A Text Categorization System with Soft Real-Time Guarantee

In order to provide predictable runtime performance for text categorization (TC) systems, an innovative system design method is proposed for soft real-time TC systems. An analyzable mathematical model is established to approximately describe the nonlinear and time-varying TC systems. According to this mathematical model, the feedback control theory is adopted to prove the system’s stableness and zero steady state error. The experiments result shows that the error of deadline satisfied ratio in the system is kept within 4% of the desired value. And the number of classifiers can be dynamically adjusted by the system itself to save the computation resources. The proposed methodology enables the theoretical analysis and evaluation to the TC systems, leading to a high-quality and low-cost implementation approach.

Theory and Application of System Integration for Real-Time Monitoring of Core Rock-Fill Dam Filling Construction Quality

The theory and method of system integration for the real-time monitoring of core rock-fill dam filling con- struction quality are studied in this paper. First, the importance analysis of system integration factors is carried out with the analytic hierarchy process. Then, according to the analysis result of integration factors, the conceptual model of system integration is built based on function integration, index integration, technology integration and information integration, the index structure of core rock-fill dam filling construction quality control is constructed and the method of function integration and technology integration is studied. The mathematical model of process monitoring is built according to monitoring objective, process and indexes. Research results have been applied in Nuozhadu core rock-fill dam construction management, realizing system integration through building appropriate monitoring work flow and comprehensive information platform of digital dam.

A Remote Real-Time Monitoring System for Power Quality

An introduction is made to the composition, design method and engineering application of a remote real time monitoring system of power quality in substations based on internet. With virtual instrument and network technique adopted, this system is characterized by good real time property, high reliability, plentiful functions, and so on. It also can be used to monitor the load of a substation, such as electric locomotives.

A Class of Parallel Algorithms of Real-TimeNumerical Simulation for Stiff Dynamic System

In this paper a class of real-time parallel modified Rosenbrock methods of numerical simulation is constructed for stiff dynamic systems on a multiprocessor system, and convergence and numerical stability of these methods are discussed. A-stable real-time parallel formula of two-stage third-order and A(α)-stable real-time parallel formula with o ≈ 89.96° of three-stage fourth-order are particularly given. The numerical simulation experiments in parallel environment show that the class of algorithms is efficient and applicable, with greater speedup.