No-reference quality assessment of dynamic sports videos based on a spatiotemporal motion model

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.     

Adaptive finite-time tracking control for parameterized nonlinear systems with full state constraints

In this article, the issue of adaptive finite-time dynamic surface control (DSC) is discussed for a class of parameterized nonlinear systems with full state constraints. Using the property of logarithmic function, a one-to-one nonlinear mapping is constructed to transform a constrained system into an unconstrained system with the same structure. The nonlinear filter is constructed to replace the first-order linear filter in the traditional DSC, and the demand on the filter time constant is reduced. Based on finite-time stable theory and using modified DSC, the finite-time controller is designed via DSC. Theoretical analysis shows that all the signals in the closed-loop system are semiglobal practical finite-time stable. Furthermore, none of the states are outside the defined open set. In the end, simulation results are presented to demonstrate the effectiveness of the proposed control schemes with both linear filters and nonlinear filters.     

Strategic environmental assessment in Romania: between benefits and constraints

This paper offers an overall picture of the importance of Strategic Environmental Assessment (SEA) in Romania and its opportunities and constraints. The role, scope and effectiveness of SEA in Romania are presented in two good practice examples and examined in order to highlight the strengths and weaknesses of the procedure at national and local scale. In practice, the number of SEA procedures is very high due to the legislation in force, and it is increasingly effective in decision-making about programmes and plans. SEA can be viewed as a great opportunity for the implementation of sustainable development in practice. It also continues to be an important procedural and decisional instrument for management and monitoring of socioeconomic development, spatial planning and environmental protection in Romania.     

Adaptive fuzzy control for nontriangular form systems with time-varying full-state constraints

This article investigates an adaptive fuzzy tracking control problem for a class of nontriangular form systems with asymmetric time-varying full state constraints. Unknown functions are approximated by the fuzzy logic systems. A domination approach is employed to tackle the nontriangular form structure. Time-varying asymmetric barrier Lyapunov functions (ABLFs) are adopted to ensure full-state constraints satisfaction. Based on the backstepping technique and time-varying ABLFs, an adaptive controller is proposed and guarantees that all the signals in the closed-loop system are ultimately bounded and the time-varying full state constraints are met. Simulation examples are presented to further demonstrate the effectiveness of the proposed approach.     

Analysis of the effect of voltage level requirements on an electricity market equilibrium model

This paper presents a conjectural-variation-based equilibrium model of a single-price electricity market. The main characteristic of the model is that the market equilibrium equations incorporate the effect of the voltage constraints on the companies’ strategic behavior. A two-stage optimization model is used to solve the market equilibrium. In the first stage, an equivalent optimization problem is used to compute the day-ahead market clearing process. In the second stage, some generation units have to modify their active and reactive power in order to meet the technical constraints of the transmission network. These generation changes are determined by computing an AC optimal power flow.     

Integral barrier Lyapunov function-based adaptive fuzzy output feedback control for nonlinear delayed systems with time-varying full-state constraints

In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time-delay systems with time-varying full state constraints and input saturation. To overcome the problem of time-varying constraints, the integral barrier Lyapunov functions (IBLFs) integrating with dynamic surface control (DSC) are applied for the first time to keep the state from violating constraints. The effects of unknown time delays can be removed by using designed Lyapunov-Krasovskii functions (LKFs). An auxiliary design system is introduced to solve the problem of input saturation. The unknown nonlinear functions are approximated by the fuzzy logic systems (FLS), and the unmeasured states are estimated by a designed fuzzy observer. The novel controller can guarantee that all signals remain semiglobally uniformly ultimately bounded and satisfactory tracking performance is achieved. Finally, two simulation examples illustrate the effectiveness of the presented control methods.     

Void region restriction for additive manufacturing via a diffusion physics approach

A longstanding challenge in additive manufacturing (AM), the presence of void regions in additively manufactured components, causes two main issues: the enclosing of build material powder in powder bed fusion techniques and limiting tool access in critical post-processing operations to remove sacrificial support structures. As topology optimization has embraced and overcome many of the obstacles of incorporating AM constraints into the underlying numerical optimization statement, there exist few solutions that directly address this fundamental void region issue. By developing computationally efficient and effective solutions to this problem, the integration of these two advanced technologies can be fully realized. Drawing on inspiration from the principles of diffusion physics, a particle diffusion void restriction (PDVR) method is presented in this work that is capable of encouraging the optimization scheme to generate final designs that are fully accessible. Additionally, this method empowers the user to choose the type of post-processing method to clear support material (eg, three-axis or five-axis milling operations, number and orientation of part set-ups) and, therefore, quantify the level of costs associated with the post-processing operation. The PDVR optimization framework is demonstrated on multiple two- and three-dimensional test problems, with physically manufactured examples depicting the real-world benefits this method admits.     

小尺度交通信号灯的检测与状态识别

交通信号灯识别包括检测和状态识别，在智能交通系统中发挥重要作用。基于YOLOv3算法提出了一种交通信号灯检测与状态识别模型。针对交通信号灯相较于交通场景中其他目标具有尺度小的特性进行了算法的设计：降低骨干网络的下采样倍率以增加小尺度目标的特征描述能力；通过增大特征图的尺度来改进多尺度特征融合；引入广义交并比作为检测任务的损失函数来改进目标边界框的回归效果。同时，根据交通信号灯本身的特性，使用颜色和形状约束的方法对信号灯进行状态识别和类别验证。最后在公开的Bosch交通信号灯数据集上和实际的城区道路进行了实验验证。实验结果表明，所提出的算法能够提升交通信号灯识别的精度和召回率，识别准确率可以达到90%左右。     

Risk-involved stochastic performance of hydrogen storage based intelligent parking lots of electric vehicles using downside risk constraints method

Today, the utilizations of hydrogen storage systems (HSS), renewable generation units (PV and wind generation) and distributed energy units are increased in the intelligent parking lots (IPL) in order to charge the electric vehicles (EVs) with clean energy sources. In this work, the uncertainties of upstream grid price, the demand of IPL, wind speed, solar irradiation and temperature are modeled via scenario approach based on stochastic programing. Furthermore, the downside risk constraints method (DRCM) is applied to consider risk related to uncertainties to get risk-involved stochastic performance of hydrogen storage based intelligent parking lots of electric vehicles. The proposed risk-based formulation is modeled using mixed-integer linear programming (MIP) which is implemented under GAMS software and solved via CPLEX solver. Two cases namely risk-averse and risk-neutral strategies are studied and compared to show the effects of DRCM implementation. The obtained results demonstrate the expected performance cost (EPC) of IPL is slowly raised while risk-in-cost (RIC) is significantly reduced due to model of risk related to uncertainties.