基于交流比例积分控制器的单相逆变器

提出一种电感电流、输出电压瞬时值反馈控制和负载电流前馈控制相结合的复合控制策略。在此基础上,研制了一台800W的单相逆变器。实验结果表明,提出的控制策略改善了逆变器输出电压的波形,提高了系统的暂态特性。     

Deterministic secure quantum communication without unitary operation based on high-dimensional entanglement swapping

By analysis of the basic properties of entanglement swapping of high-dimensional Bell states,a universal and general deterministic secure quantum communication(DSQC)protocol is proposed,in which unitary operation is not required.By making use of the results of high-dimensional Bell measurement,the sender and the receiver can encode and decode the message respectively by performing the modular addition and subtraction.Two mutually complementary bases are constructed;and according to the property of mutual complement,a method for checking security of the high-dimensional quantum channel is put forward.Some common attack strategies are analyzed,and the corresponding error rates are calculated.Then the upper bound of the threshold of error rate is deduced.     

支持状态机建模的工作流引擎研究

为了能清晰地描述存在较多审批环节和步骤跳转的业务流程,提出利用状态机为流程建模的方法。通过改进传统的关系结构工作流引擎,给出一个支持状态机建模的关系结构工作流引擎的设计方案,详细介绍该引擎的设计原理和实现柔性方法。最后通过一个示例,演示支持状态机建模的工作流引擎的工作机制和实例迁移的过程。原型已经应用到高校学费管理系统中。实践证明,该引擎可以有效地支持状态机建模,并缩短关键业务的开发周期。     

电位滴定法研究~(99)Tc-HMDP和~(99)Tc-HEDP中Tc的氧化态

~(99)Tc-HMDP和~(99)Tc-HEDP溶液是在相应的螫合剂存在下,用过量SnCl_2还原~(99)TcO_4-制得。用标准I_2液对SnCl_2进行了剩余量电位滴定,确定了在pH～3的介质中,~(99)Tc-HMDP和~(99)Tc-HE-DP中~(99)Tc的氧化态均为+4。全部实验在N_2气流中进行。~(99)Tc-HMDP和~(99)Tc-HEDP的紫外光谱表明:在用I_2滴定的过程中,~(99)Tc只处于一种氧化态+4;将它们放置在空气中,一小时后仍较稳定。     

Interpreting the negative mood-helping literature via "mega"-analysis: A contrary view.

"Mega"-analysis was developed by M. Carlson and N. Miller (see record 1987-31249-001) as an extension of traditional meta-analytic procedures for conducting integrative reviews of existing research literatures. One such mega-analysis was conducted by Carlson and Miller to synthesize the literature on the relation between negative mood states and helping. That analysis found no support for a theoretical account (negative state relief) that had been confirmed previously by using various experimental approaches. In an attempt to reconcile the discrepancy, the logic and methods used in Carlson and Miller's mega-analysis of the negative mood-helping literature were examined, and several serious problems were found. These problems are discussed, and data are presented to show that the results of that mega-analysis, and perhaps all mega-analyses, should not be viewed with confidence. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Stock Price Forecasting: An Echo State Network Approach

Forecasting stock prices using deep learning models suffers from problems such as low accuracy, slow convergence, and complex network structures. This study developed an echo state network (ESN) model to mitigate such problems. We compared our ESN with a long short-term memory (LSTM) network by forecasting the stock data of Kweichow Moutai, a leading enterprise in China’s liquor industry. By analyzing data for 120, 240, and 300 days, we generated forecast data for the next 40, 80, and 100 days, respectively, using both ESN and LSTM. In terms of accuracy, ESN had the unique advantage of capturing nonlinear data. Mean absolute error (MAE) was used to present the accuracy results. The MAEs of the data forecast by ESN were 0.024, 0.024, and 0.025, which were, respectively, 0.065, 0.007, and 0.009 less than those of LSTM. In terms of convergence, ESN has a reservoir state-space structure, which makes it perform faster than other models. Root-mean-square error (RMSE) was used to present the convergence time. In our experiment, the RMSEs of ESN were 0.22, 0.27, and 0.26, which were, respectively, 0.08, 0.01, and 0.12 less than those of LSTM. In terms of network structure, ESN consists only of input, reservoir, and output spaces, making it a much simpler model than the others. The proposed ESN was found to be an effective model that, compared to others, converges faster, forecasts more accurately, and builds time-series analyses more easily.     

Safe and intuitive manual guidance of a robot manipulator using adaptive admittance control towards robot agility

Key areas of robot agility include methods that increase capability and flexibility of industrial robots and facilitate robot re-tasking. Manual guidance can achieve robot agility effectively, provided that a safe and smooth interaction is guaranteed when the user exerts an external force on the end effector. We approach this by designing an adaptive admittance law that can adjust its parameters to modify the robot compliance in critical areas of the workspace, such as near and on configuration singularities, joint limits, and workspace limits, for a smooth and safe operation. Experimental validation was done with two tests: a constraint activation test and a 3D shape tracing task. In the first one, we validate the proper response to constraints and in the second one, we compare the proposed approach with different admittance parameter tuning strategies using a drawing task where the user is asked to guide the robot to trace a 3D profile with an accuracy or speed directive and evaluate performance considering path length error and execution time as metrics, and a questionnaire for user perception. Results show that appropriate response to individual and simultaneous activation of the aforementioned constraints for a safe and intuitive manual guidance interaction is achieved and that the proposed parameter tuning strategy has better performance in terms of accuracy, execution time, and subjective evaluation of users.     

引入关联分析的用户行为信任评估在云计算平台中的研究

关联规则是数据挖掘的重要方法。随着国内外云计算应用及研究的不断推进,云计算的安全性成为云计算的核心问题之一。通过进行用户的状态行为关联分析,提取信任信息,结合可信云的思想,提出一个云计算下基于信任的防御系统模型。     

液压支架工作状态模糊识别系统研究

针对目前综采工作面液压支架压力监测系统只能监测综采工作面压力,不能对液压支架工作状态进行识别的问题,设计了一种液压支架工作状态模糊识别系统。该系统可对现有的综采工作面液压支架压力监测系统监测到的压力数据进行模糊识别,根据模糊识别输出值即可判断液压支架的5种工作状态,即降架、移架、升架、增阻、卸压保持;当液压支架处于增阻工作状态且增阻时间过长时,该系统可及时通知液压支架操作工增大液压支架压力,辅助实现顶煤破碎。测试结果验证了该系统的可行性。