Lift-and-project MVEE based convex hull for robust SCED with wind power integration using historical data-driven modeling approach

This paper presents an adjustable robust security constrained economic dispatch (SCED) model with wind power uncertainties. First, the scenario based adjustable robust SCED model is presented. It considers multiple scenarios from historical data as well as the spatial correlation among wind farms. Then, the proposed SCED model becomes an optimization problem with a large amount of constraints which is skillfully solved using a lift-and-project minimum volume enclosing ellipsoid (MVEE) based convex hull. Furthermore, the proposed model is transformed into a second order cone programming (SOCP) model by the use of participation factors to generate adjustable generation outputs and thus guarantee the energy balance. In order to further reduce the computational complexity, the inactive constraints reduction strategy is proposed to quickly eliminate inactive SOC security constraints before solving the model. Numerical results of IEEE 14-bus and 118-bus test systems as well as the practical Polish power systems with several wind farms show that the proposed model can achieve better economies. Moreover, more than 82% of security constraints are identified as inactive in various cases of the simulation, and the proposed inactive constraints reduction strategy is promising for improving the computational performance.     

A comparison between optimization algorithms applied to synchronization of bilateral teleoperation systems against time delay and modeling uncertainties

The goal of this paper is to achieve optimal performance for synchronization of bilateral teleoperation systems against time delay and modeling uncertainties, in both free and contact motions. Time delay in bilateral teleoperation systems imposes a delicate tradeoff between the conflicting requirements of stability and transparency. To this reason, in this paper, population-based optimization algorithms are employed to tuning the proposed controller parameters. The performance of tuned controllers is compared with the gains obtained by Cuckoo Optimization Algorithm (COA), Biogeography-Based Optimization (BBO), Imperialist Competitive Algorithm (ICA), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization with continuous domain (ACOR), Self-adaptive Differential Evolution with Neighborhood Search (SaNSDE), Adaptive Differential Evolution with Optional External Archive (JADE), Differential Evolution with Ensemble of Parameters and mutation strategies (EPSDE) and Cuckoo Search (CS). Through numerical simulations, the validity of the proposed method is illustrated. It is also shown that the COA algorithm is able to solve synchronization problem with high performance in stable transparent bilateral teleoperation systems.     

Balance control during lateral load transfers over a slippery surface

Few studies have measured balance control during manual material handling, and even fewer with environmental cofactors. This study examined the effect of different surface frictions during a stationary manual material handling task. Thirty-six healthy participants completed 180° lateral transfer tasks of a load over high- and low-friction surfaces (μ = 0.86 and μ = 0.16, respectively). Balance measures, stance kinematics and lower extremity muscle activities were measured. Success during the novel slippery surface dichotomised our population, allowing us to investigate beneficial techniques to lateral load transfers over the slippery surface. Stance width reduction by 8 cm and 15° of additional external foot rotation towards the load were used to counter the imbalance created by the slippery surface. There was no clear alteration to lower extremity muscular control to adapt to a slippery surface. Changes in stance seemed to be used successfully to counter a slippery surface during lateral load transfers.

Statement of Relevance: Industries requiring manual material handling where slippery conditions are potentially present have a noticeable increase in injuries. This study suggests stance configuration, more so than any other measure of balance control, differentiates vulnerability to imbalance during material handling over a slippery surface.     

基于改进关联规则的Web使用挖掘方法研究

本文提出了改进关联挖掘算法的数据挖掘方式.在自然连接产生候选集以前,先进行一个修剪过程,减少参加连接的项集数量,进而减小生成的候选项集规模,减少了循环迭代次数和运行时间,同时在连接判断步骤中减少多余的判断次数,避免传统方法的弊端.仿真实验证明,这种改进算法能够大幅提高数据的查询速度,取得很好的效果.     

A robust learning based evolutionary approach for thermal-economic optimization of compact heat exchangers

This paper presents a robust, efficient and parameter-setting-free evolutionary approach for the optimal design of compact heat exchangers. A learning automata based particle swarm optimization (LAPSO) is developed for optimization task. Seven design parameters, including discreet and continuous ones, are considered as optimization variables. To make the constraint handling straightforward, a self-adaptive penalty function method is employed. The efficiency and the accuracy of the proposed method are demonstrated through two illustrative examples that include three objectives, namely minimum total annual cost, minimum weight and minimum number of entropy generation units. Numerical results indicate that the presented approach generates the optimum configuration with higher accuracy and a higher success rate when compared with genetic algorithms (GAs) and particle swarm optimization (PSO).     

Foot motions in manual material handling transfer tasks: A taxonomy and data from an automotive assembly plant

Ergonomic job analysis commonly applies static postural and biomechanical analysis tools to particular postures observed during manual material handling (MMH) tasks, usually focusing on the most extreme postures or those involving the highest loads. When these analyses are conducted prospectively using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses. In automotive assembly jobs, workers frequently take several steps between task elements, for example, picking up a part at one location and moving to another location to place it on the vehicle. A detailed understanding of the influence of task type and task sequence on the stepping pattern is necessary to accurately predict the foot placements associated with MMH tasks. The current study examined the patterns of foot motions observed during automotive assembly tasks. Video data for 529 pickup and delivery tasks from 32 automotive assembly jobs were analysed. A minimum of five cycles was analysed for each task. The approach angle, departure angle, hand(s) used, manipulation height and patterns of footsteps were coded from the video. Object mass was identified from the job information sheet provided by the assembly plant. Three independent raters coded each video and demonstrated an intraclass correlation coefficient of 0.54 for identification of the configuration of the lower extremities during terminal stance. Based on an analysis of the distribution of stepping behaviours during object transitions (pickups or deliveries), a transition classification system (TRACS) was developed. TRACS uses a compact notation to quantify the sequence of steps associated with a MMH transition. Five TRACS behaviour groups accounted for over 90% of the transition stepping behaviours observed in the assembly plant. Approximately two-thirds (68.4%) of the object transfers observed were performed with only one foot in contact with the ground during the terminal posture. The results from this paper suggest that a predictive model for choosing a transition stepping behaviour, coupled with a model to scale the selected foot behaviours, is needed to facilitate accurate prospective ergonomic analyses. This study proposes a method for categorising the stepping patterns associated with MMH tasks. The influence of task type and task sequence on the stepping patterns observed during several automotive assembly tasks is discussed. For prospective postural analyses conducted using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses.     

Foot-ground forces on sloping ground when lifting∗

Slipping risk associated with manual material handling on inclined surfaces was investigated using a 2⁴ factorial experimental design under controlled laboratory conditions. The reaction force data at the shoe sole-sloping surface interface, the box trajectories, and the subjects’ assessment of the risk involved in carrying out the prescribed tasks were obtained and analysed both analytically and statistically. The results of these analyses are presented in this paper.     

Effect of residual stresses on crack behaviour in single edge bending specimens

Residual stresses due to manufacturing processes, such as welding, change the load bearing capacity of cracked components. The effects of residual stresses on crack behaviour in single edge bending specimens were investigated using Finite element analyses. Three parameters (J, Q and R) were used to study the crack behaviour. The J‐integral predicts the size scale over which large stresses and strains exist, the constraint parameter Q describes the crack‐tip constraint as a result of geometry, loading mode and crack depth and the constraint parameter R is used to describe the constraint resulting from residual stresses. To carry out a systematic investigation on the effect of residual stresses on the J‐integral and crack‐tip constraints, models under different combinations of residual stresses and external loads with different crack depths were analysed. It has been shown that the crack‐tip constraint R increased by tensile residual stresses around the crack‐tip. On the other hand, the constraint parameter R decreased and tended to zero at high external load levels.     

Food safety education for people with diabetes and pregnant women: A positive deviance approach

Few education programs target audiences at high-risk for foodborne illness, especially people with diabetes and pregnant women. The objective of this study is to develop a food safety education program for each using a positive deviance approach. The positive deviance focus group is a novel educational intervention that allows participants to discuss their food handling behaviors and decide to try recommended positive practices modeled by people like themselves. To fit within the educational programs offered by the collaborating institutions, three sessions were given, discussing safe handling topics: ‘Cook and Chill,’ ‘Clean and Separate,’ and ‘Choose Safe Food.’ People with diabetes (32) and pregnant women (29) participated in the study. Focus groups were audiotaped and transcribed. Participants became involved and inspired by vivid discussions and were inspired to change their behaviors to the recommended food handling practices modeled by their peers. Safe food handling practices were reinforced by take-home tasks focused on using refrigerator and cooking thermometers and using separate cutting boards. Participants were unaware of details associated with safe handling recommendations, such as the recommended temperature for cooking specific items or the temperature of the refrigerator. Results of this study indicate that positive deviance discussion module could be a promising alternative to traditional methods of food safety education.     

基于动态RBF网络的预测控制在中速磨煤机优化控制的应用

针对大型火电厂直吹式制粉系统的时滞和非线性特点,将基于动态RBF网络模型的预测控制应用于MPS中速磨煤机的优化控制中。通过对M-RAN算法的改进,加快了对非线性系统的辨识速度。建模仿真证明了改进M-RAN算法的有效性和实时性,并结合预测控制解决了系统的时滞问题;应用结果也表明该方法具有良好的动态响应和较强的鲁棒性。