Direct Detection Φ-OTDR System Based on the Different Pulse Width Method

In this paper, a data-driven conflict-aware safe reinforcement learning (CAS-RL) algorithm is presented for control of autonomous systems. Existing safe RL results with predefined performance functions and safe sets can only provide safety and performance guarantees for a single environment or circumstance. By contrast, the presented CAS-RL algorithm provides safety and performance guarantees across a variety of circumstances that the system might encounter. This is achieved by utilizing a bilevel learning control architecture: A higher meta-cognitive layer leverages a data-driven receding-horizon attentional controller (RHAC) to adapt relative attention to different system's safety and performance requirements, and, a lower-layer RL controller designs control actuation signals for the system. The presented RHAC makes its meta decisions based on the reaction curve of the lower-layer RL controller using a meta-model or knowledge. More specifically, it leverages a prediction meta-model (PMM) which spans the space of all future meta trajectories using a given finite number of past meta trajectories. RHAC will adapt the system's aspiration towards performance metrics (e.g., performance weights) as well as safety boundaries to resolve conflicts that arise as mission scenarios develop. This will guarantee safety and feasibility (i.e., performance boundness) of the lower-layer RL-based control solution. It is shown that the interplay between the RHAC and the lower-layer RL controller is a bilevel optimization problem for which the leader (RHAC) operates at a lower rate than the follower (RL-based controller) and its solution guarantees feasibility and safety of the control solution. The effectiveness of the proposed framework is verified through a simulation example.

The Advanced Photon Source third generation synchrotron light source needs a stabilized particle beam position to produce high brightness and low emittance of the beam. Global orbit correction control is introduced which is utilized to achieve the demanding needs of the accelerator. This paper describes the procedure to determine an effective and optimal performing controller to meet the global orbit correction requirements. These conditions include frequency domain and time domain requirements consisting of vibrational noise attenuation, limiting of controller gains for stability, and improving the system time response. Theoretical analysis is discussed with different control schemes compared graphically to reveal the best control design. A range or set of control parameters are selected as acceptable to achieve the system's performance requirements.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

In modern taxi networks, large amounts of taxi occupancy status and location data are collected from networked in-vehicle sensors in real- time. They provide knowledge of system models on passenger demand and mobility patterns for efficient taxi dispatch and coordination strategies. Such approaches face a new challenge: how to deal with uncertainties of predicted customer demand while fulfilling the system's performance requirements, including minimizing taxis' total idle mileage and maintaining service fairness across the whole city. To address this problem, we develop a data- driven robust taxi dispatch framework to consider spatial-temporally correlated demand uncertainties. The robust optimization problem has an objective function that is concave in the uncertain demand and convex in the decision variables, and constraints that are convex in the decision variables according to the practical requirements. We design a data-driven algorithm for constructing uncertainty sets of random demand vectors that provide a probabilistic guarantee for the performance of robust taxi dispatch solutions. It guarantees that the probability that the actual dispatch cost under the true demand vector being smaller than the optimal cost of the robust dispatch solutions with the uncertainty sets is greater than a desired probability value. We prove equivalent computationally tractable forms of the robust dispatch problem with the constructed closed convex polytope and second order cone types of uncertainty sets, using the minimax theorem and strong duality. Evaluations on four years of taxi trip data for New York City show that the probabilistic guarantee is satisfied. By selecting a probabilistic guarantee level that does not sacrifice the average cost much, the average demand- supply ratio error is reduced by 31.7%, and the average total idle driving distance is reduced by 10.13% compared with non-robust dispatch solutions.

Various wireless manufacturing sensors facilitate the monitoring and control process in industrial internet of things (IIoT) systems. Control and image data generated by control and vision-based monitoring systems are transmitted over shared wireless network to edge computing devices for further decisions. Due to limited spectrum resources and sensor transmit power, it is challenging to design efficient quality of service (QoS) aware transmission mechanism for heterogeneous data with diverse real-time and system performance requirements. In this paper, in order to guarantee control system performance and image clarity, the time slot allocation and transmission power for heterogeneous sensors are jointly optimized by formulating a mixed integer nonlinear programming (MINLP) problem. The MINLP problem is decomposed into multiple subproblems which are proved to have strong duality and can be solved in dual domain. Then, according to acknowledge (ACK) signals, we propose a priority-aware heuristic algorithm to solve each subproblem. Finally, the simulation results prove that our proposed mechanism can reduce the number of slots and energy consumption for transmission while guaranteeing performance requirements of heterogeneous data.

In this chapter, we will examine requirements determination and analysis that may be useful for defining the nonfunctional and domain requirements for an IDCM solution, including system sizing, architecture, and performance requirements. We also include a discussion on domain requirements, such as those for information technology and system administration. Our objectives are to do the following: • Document the requirements for system sizing and mass storage. • Consider the types of requirements analysis that enterprises apply to help suppliers of IDCM solutions offer an architecture solution that may meet enterprise requirements. • Define system performance requirements with known caveats and assumptions. • Define the requirements for the IDCM system to integrate with enterprise desktop, server, and network operating environments. • Define the requirements for the system development environment. • Document the system administration requirements for the system.

This article is aimed at studying the design and implementation of a football player training management system based on smart images. Based on the analysis of the importance of informatization for scientific football training, system performance requirements and intelligent image detection technology, the football player training management is designed. The overall architecture of the system, and the detailed design of each functional module of the system. It mainly includes football player information management module, football player training plan viewing module, training goal formulation module and training information feedback module. The realization of the training management system relies on intelligent image technology to detect and track athletes. Finally, the performance of the system was tested. The test results show that the expected response time of each module of the system when different numbers of users are accessed is within 3 seconds. The longest actual time is 2.64 s, and the actual shortest time is 1.18 s. It can be seen that the response time of the system meets the demand. At the same time, the system throughput rate meets the requirements of this article, and the user pass rate is also above 95%, indicating that the performance of the football player training management system designed in this article is better.

Demodulation techniques are of central importance for achieving intelligent receiving. Improvement in demodulation performance enhances the overall performance of a communication system correspondingly. However, conventional demodulators require dedicated hardware platforms leading to high implementation costs and time-consuming development. This work proposes a unified architecture for end-to-end automatic demodulated modulated signals. The proposed demodulator utilizes the residual unit and fully convolutional network (R-FCN) to extract the time-domain feature of the modulated signal and determine the transmitted symbols to realize the demodulation of a received signal. Simulations show that the proposed method has better demodulation performance compared to existing methods. It is further demonstrated that when the signal-to-noise ratios (SNR) exceed 2dB, the proposed demodulator exhibits similar demodulation performance to symbol-unsynchronized data compared to conventional demodulators.

Laser-activated irrigation (LAI) using erbium lasers is an irrigant agitation technique with great potential for improved cleaning of the root canal system, as shown in many in vitro studies. However, lasing parameters for LAI vary considerably and their influence remains unclear. Therefore, this study sought to investigate the influence of pulse energy, pulse frequency, pulse length, irradiation time and fibre tip shape, position and diameter on the cleaning efficacy of LAI. Transparent resin blocks containing standardized root canals (apical diameter of 0.4 mm, 6% taper, 15 mm long, with a coronal reservoir) were used as the test model. A standardized groove in the apical part of each canal wall was packed with stained dentin debris. The canals were filled with irrigant, which was activated by an erbium: yttrium aluminium garnet (Er:YAG) laser (2940 nm, AT Fidelis, Fotona, Ljubljana, Slovenia). In each experiment, one laser parameter was varied, while the others remained constant. In this way, the influence of pulse energy (10-40 mJ), pulse length (50-1000 μs), frequency (5-30 Hz), irradiation time (5-40 s) and fibre tip shape (flat or conical), position (pulp chamber, canal entrance, next to groove) and diameter (300-600 μm) was determined by treating 20 canals per parameter. The amount of debris remaining in the groove after each LAI procedure was scored and compared among the different treatments. The parameters significantly (P < 0.05, Kruskal-Wallis) affecting debris removal from the groove were fibre tip position, pulse length, pulse energy, irradiation time and frequency. Fibre tip shape and diameter had no significant influence on the cleaning efficacy.

This paper describes the application of system identification techniques and robust control strategies to a pneumatic muscle actuator system. Due to the inherent nonlinear and time-varying characteristics of this system, it is difficult to achieve excellent performance using conventional control methods. Therefore, we apply identification techniques to model the system as linear transfer functions and regard the un-modeled dynamics as system uncertainties. Because robust control is well-known for its capability in dealing with system uncertainties, we then apply robust control strategies to guarantee system stability and performance for the system. This work is carried out in three parts. First, the pneumatic muscle actuator system was modeled as linear transfer functions. Second, robust control theorem were utilized to design a Hinf robust controller to deal with system uncertainties and performance requirements. Finally, the designed controller was implemented for experimental verifications and compared with a conventional PID controller. From the experimental results, the proposed Hinf robust controller is deemed effective.

The deficient performance of existing downtown transit distribution systems may significantly affect the overall performance of the urban transportation system in many metropolitan areas. This paper has two principal objectives. First, it describes an approach entitled Performance Requirements Analysis for developing a set of requirements or standards that a downtown transit system should satisfy and structuring these requirements so as to generate a small set of alternative generic systems for detailed evaluation. Second, it provides a preliminary assessment of performance requirements for distribution systems in 19 of the largest cities in the United States.

OA24 Magnetic resonance imaging of the trabecular bone microarchitecture at 3 Tesla - comparison with 1.5 Tesla

Flash memory is hugely been using for small handheld to large enterprise applications due to its attractive characteristics like fast access speed, shock resistance and others. Performance oriented applications like multimedia, robotics, OLTP and further require fault tolerant more reliable high throughput. Therefore, flash memory with its remarkable features is an outstanding choice to meet their business needs. In this paper, we propose a firmware/driver based data storage framework to implement RAID 0 on flash memory platform to support the increasing requirements of data reliability and system performance. In our knowledge, this is the first research presented in concerned area. The real time experimental results prove the effectiveness of our technique.

Scaling presently available excimer laser systems to lasers designed to operate at high average power and high pulse repetition rates for long periods of time requires advances in many areas of engineering technology. For economical application to industrial processes, the efficiency must be increased. This leads to more stringent requirements on preionization techniques, energy delivery systems, and system chemistry. Long life operation (>109 to 1010 pulses) requires development of new pulse power components, optical ele-ments, and flow system components. A broad-based program underway at the Los Alamos National Laboratory is addressing these key technology issues, with the help of advanced component and systems development programs in industry. A prototype XeCI laser meeting all requirements for efficiency, system performance, and life is scheduled for completion in 1985.

Fault coverage modeling in nonlinear dynamical systems

A primary mission of air assets is to detect and destroy enemy ground targets. In order to accomplish this mission, it is essential to detect, track, and classify contacts to determine which are valid targets. Traditional combat identification has been performed using all-weather sensors and processing algorithms designed specifically for such sensor data. Electro- optical (EO) sensors produce a very different type of data that does not lend itself to traditional combat identification algorithms. This paper will detail how we analyzed the visual and physical characteristics of a large number of potential targets. The results of this analysis were used to drive the requirements of a demonstration system. We will detail the test data we collected from the military and CAD models for likely targets, as well as overall requirements for system performance.