Cyberbullying: Effect of emergency perception on the helping tendencies of bystanders

The effect of the emergency perception of bystanders of cyberbullying victims on helping behaviors is often neglected in research on cyberbullying. In this study, we explored the influence of this cognitive factor on cyber-bystanders’ helping tendencies as well as elucidated possible underlying processes. The results of two studies were reported. In Study 1, 150 undergraduates read a true case of a girl experiencing cyberbullying. The results indicated that when the participants perceived the victim’s situation to be more critical (i.e., higher emergency perception), their helping tendencies were stronger, partly through increased state empathy followed by feelings of responsibility to help. In Study 2, we randomly assigned 300 undergraduates to two groups. The low emergency group read the same cyberbullying case as Study 1, whereas the cyberbullying case read by the high emergency group contained additional emergency information of the victim. The results indicated that the high emergency group expressed stronger helping tendencies than did the low emergency group. This effect was caused by a stronger perception that the victim was in an emergency situation, which not only strengthened the participants’ helping tendencies directly but also indirectly through increasing their state empathy and feelings of responsibility to help.     

A design of a robust discrete-time controller

In this paper, we proposed a robust discrete-time controller. This control system, which is derived from the idea of the normalized plant, does not include plant parameters. Thus, we obtain a control system independent of plant parameters and that has the same structure as a conventional optimal servo control system. Simulation and experimental results show that the proposed method is fairly robust to plant parameter variations and external disturbances.     

A note on the value function for constrained control problems

We consider the Mayer optimal control problem with dynamics given by a nonconvex differential inclusion, whose trajectories are constrained to a given set and we obtain a relation between the costate function that appears in the maximum principle and the value function. This relation extends the known conditions existing in the literature for unconstrained problems to those for problems under state constraints.     

对素描教学现状的思考

要培养学生的创造力，教师主要起引导作用。应提倡感性的观察方法与理性的表现相结合。从构图阶段开始就应该贯穿创新意念，鼓励学生采用大胆新奇的构图，以独特的视觉去观察对象、设计函面，充分发挥学生的主观能动性。     

具有完整性的状态反馈控制

本文基于矩阵方程解，提出了一种开环稳定系统反馈的设计方法，所设计的系统对任意传感器失效具有完整性。     

DCS的现状与发展趋势

叙述ＤＣＳ的进展。目前的ＤＣＳ正面临来自用户需求的挑战，为保住全球市场竞争优势，制造加工行业用户需要建立集过程控制数据与商业信息于一体的ＣＩＭＳ。未来ＤＣＳ应具备服从国际标准的开放性和互换操作性。以ＩＳＰ现场总线为基础的系统结构可能成为未来的ＤＣＳ。提高应用水平有助于发展未来的ＤＣＳ     

用于机器人轨迹定位纠正系统的回声状态神经网络研究

循环神经网络(RecurrentNeuralNetworks)是人工神经网络(ArtificialNeuralNetworks)中重要的分支,与前馈神经网络(ForwardNeuralNetworks)相比具有更好的时间序列学习能力。但长期以来其学习法一直不能脱离前馈神经网络而自成一体,回声状态神经网络(EchoStateNetworks(ESN))是打破这一局面的全新学习方法。其独特的结构,良好的短期记忆能力,方便的学习方法,不俗的非线性特性是以前循环神经网络所不可比的。本文在介绍了回声状态神经网络之后将其用于四轮机器人的位置测量系统中,有良好的表现。     

Florida DOT Project-Level Bridge Management Models

The Florida Department of Transportation (FDOT) is in the process of implementing Pontis, a Bridge Management System, to provide decision support to engineers in the headquarters and district offices as they make routine policy, programming, and budgeting decisions regarding the preservation and improvement of the state’s bridges. As part of this effort, an ongoing research program is underway to adapt the system to FDOT needs as well as to advance the state of the art in several areas important to the Department. Most of the research results are organized around a new project-level decision support framework that complements and builds on Pontis’ existing network-level analysis. Specific new models include accident risk and user cost due to roadway width and alignment deficiencies; user cost of load capacity and vertical clearance restrictions, and moveable bridge openings; project-level prediction models for bridge element condition and costs; and prediction of economics of scale and scoping possibilities. The new models are built into a highly graphical spreadsheet model for decision support use.     

DESIGN AND IMPLEMENTATION OF STATE OBSERVERS IN REACTIVE DISTILLATION

This study demonstrates that state observers can be developed and applied to infer the composition profiles of reactive distillation columns from noise-contaminated temperature measurements. The design and implementation of a Kalman filter (KF) and a Luenberger observer (LO) are carried out, and their performances are quantitatively assessed. The reliability, accuracy, and robustness of the two designs method are examined and compared quantitatively. The design and implementation of a Luenberger observer are simpler and easier to carry out than those of a Kalman filter. On the other hand, a Kalman filter is found to be more robust to a noisy measurements, erroneous initial estimates, and model uncertainties. A Luenberger observer could be used for composition estimation of reactive distillation when an ideal model of the system can reasonably approximate the real system; otherwise, a Kalman filter is recommended to be applied in more practical situations.