Study on the Interactivity of Controlled and Automatic Information Processing in L2 Reading

L2 reading is not only an important channel for people to obtain information and knowledge,but also the main way for people to learn a foreign language.Reading information processing can be divided into controlled processing and automatic processing.Controlled information processing is a conscious and resource-intensive processing model,while automatic information processing is an unconscious and automatic processing model.This study investigates the characteristics and interactivity of controlled and automatic information processing in L2 reading,and explores the roles of controlled and automatic information processing strategies in improving L2 reading ability.The findings are as follows:(a)controlled and automatic information processing is interactive in L2 reading;and(b)the uses of controlled and automatic information processing strategies are beneficial to the improvement of the reading ability of L2 learners.This study has important theoretical and practical value in improving the efficiency of L2 reading teaching and learning.

Modeling of Microstructure Evolution and Mechanical Properties of Steel Plates Produced by Thermo-Mechanical Control Process and Its On-line Application

An integrated metallurgical model was developed to predict microstructure evolution and mechanical properties of low-carbon steel plates produced by TMCP. The metallurgical phenomena occurring during TMCP and mechanical properties were predicted for different process parameters. In the later passes full recrystallization becomes difficult to occur and higher residual strain remains in austenite after rolling. For the reasonable temperature and cooling schedule, yield strength of 30 mm plain carbon steel plate can reach 310 MPa. The first on-line application of prediction and control of microstructure and properties (PCMP) in the medium plate production was achieved. The predictions of the system are in good agreement with measurements.

IMPROVING THE MECHANICAL PROPERTIES OF COPPER ALLOYS BY THERMO-MECHANICAL PROCESSING

Systematic physical simulation of thermo-mechanical processing routes has been ap-plied on a Gleeble 1500 simulator to four copper alloys (mass %) Cu-0.57Co-0.32Si,Cu-0.55Cr-0.065P, Cu-0.22Zr-0.035Si and Cu-1.01Ni-0.43Si aimed at clarifying theinfluences of processing conditions on their final properties, strength and electricalconductivity. Flow curves were determined over wide temperature and strain rateranges. Hardness was used as a measure of the strength level achieved. High hard-ness was obtained as using equal amounts (strains 0.5) of cold deformation beforeand after the precipitation annealing stage. The maximum values achieved for theCu-Co-Si, Cu-Cr-P, Cu-Zr-Si and Cu-Ni-Si alloys were 190, 165, 178 and 193 HV5,respectively. A thermo-mechanical schedule involving the hot deformation-ageing-colddeformation stages showed even better results for the Cu-Zr-Si alloy. Consequently,the processing routes were designed based on simulation test results and wires of 5 and2mm in diameters have been successfully processed in the industrial scale.

Effect of thermo-mechanical processing on microstructure and electrochemical behavior of Ti-Nb-Zr-V new metastable β titanium biomedical alloy

The influence of thermo-mechanical processing (TMP) on the microstructure and the electrochemical behavior of new metastableβ alloy Ti?20.6Nb?13.6Zr?0.5V (TNZV) was investigated. The TMP included hot working in belowβ transus, solution heat treatments at the same temperature and different cooling rates in addition to aging. Depending upon the TMP conditions, a wide range of microstructures with varying spatial distributions and morphologies of equiaxed/elongatedα andβ phases were attained, allowing for a wide range of electrochemical properties to be achieved. The corrosion behavior of the studied alloy was evaluated in a Ringer’s solution at 37 °C via open circuit potential?time and potentiodynamic polarization measurements.

EVOLUTION OF MICROSTRUCTURES AND HARDNESS DURING CONTINUOUS THERMO-MECHANICAL PROCESSING OF 6201 ALUMINUM ALLOY

Continuous thermo-mechanical processing (CTMP) of 6201 aluminum alloy was simulated on Gleeble-1500. The deformed specimens were analyzed by the observation of TEM and the measurement of hardness. It was shown that rapid solid solution and aging treatment can be effectively combined in one procedure by the strain induced during CTMP. The deformation temperature is ranging from 540* C to 300* C, the hardness increases directly before the 6th pass followed by a slight drop, the amount of precipitates increases with the holding time after deformation. Uniformly distributed and stabilized Mg2Si precipitates, as well as dislocation substructure can be observed on deformed specimens which have been subsequently held at 300℃ for 60 seconds.

Evolution of Microstructure in a Cu-Cr in situ Composite Produced by Thermo-Mechanical Processing

This paper studied the microstructure evolution of a deformation-processed Cu-7Cr in situ composite prepared by thermo-mechanical processing. The longitudinal and transverse sectional microstructures were analyzed using an optical microscope and a scanning electronic microscope. In the longitudinal section, the initially randomly distributed Cr dendrites in the as-cast Cu-7Cr alloy were transformed into the fibres aligned parallel to the drawing axis;the Cr dendrites experienced breaking, flattening and rotating, lapping and merging, and homogenizing and refinement during thermo-mechanical processing. In the transverse section, the initially randomly distributed Cr dendrites in the as-cast Cu-7Cr alloy were changed into the curvy ribbon like fibres;the Cr dendrites underwent breaking, flattening and rotating, folding and twisting, and irregularizing and refinement during thermo-mechanical processing.

NUMERICAL SIMULATION OF THE THERMO-MECHANICAL PROCESS FOR BEAM BLANK CONTINUOUS CASTING

The aim of this study was to simulate the solidification process of beam blank continuous casting, and then find the reasons for the typical defects of the beam blank. A two-dimensional transient coupled finite element model has been developed to compute the temperature and stress profile in beam blank continuous casting. The enthalpy method was used in the heat conduction equation. The thermo-mechanical property in the mushy zone was taken into consideration in this calculation. It is shown that at the mold exit the thickness of the shell had its maximum value at the flange tip and its minimum value at the fillet. The temperature had a great fluctuation on the surface of the beam blank in the secondary cooling zone. At the unbending point, the surface temperature of the web was in the brittleness temperature range under the present condition. To ensure the quality, it is necessary to weaken the intensity of secondary cooling. At the mold exit the equivalent stress and strain have higher values at the flange tip and at the web. From the spray 1 to the unbending point, the maximum values of stress and strain gradually moved to the internal section of the flange tip and the web. However, whenever, there were bigger stress and strain values near the flange tip and the web than in the other parts, it must be very easy to generate cracks at those positions. Now, online verification of this simulation has been developed, which has proved to be very useful and efficient to instruct the practical production of beam blank continuous casting.

Optimization study of station track utilization in high-speed railroad based on constraints of control in random origin and process

Purpose-The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times.These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals.The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.Design/methodologylapproach-To achieve this objective,the paper simulates actual train operations,incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station.The Monte Carlo simulation method is adopted to solve this problem.This approach transforms a nonlinear model,which includes constraints from probability distribution functions and is difficult to solve directly,into a linear programming model that is easier to handle.The method then linearly weights two objectives to optimize the solution.Findings-Through the application of Monte Carlo simulation,the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model.By continuously adjusting the weighting coefficients of the linear objectives,the method is able to optimize the Pareto solution.Notably,this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.Originality/value-The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times.The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement.Furthermore,the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.

A Compensation Controller Based on a Nonlinear Wavelet Neural Network for Continuous Material Processing Operations

Continuous material processing operations like printing and textiles manufacturing are conducted under highly variable conditions due to changes in the environment and/or in the materials being processed.As such,the processing parameters require robust real-time adjustment appropriate to the conditions of a nonlinear system.This paper addresses this issue by presenting a hybrid feedforward-feedback nonlinear model predictive controller for continuous material processing operations.The adaptive feedback control strategy of the controller augments the standard feedforward control to ensure improved robustness and compensation for environmental disturbances and/or parameter uncertainties.Thus,the controller can reduce the need for manual adjustments.The controller applies nonlinear generalized predictive control to generate an adaptive control signal for attaining robust performance.A wavelet-based neural network model is adopted as the prediction model with high prediction precision and time-frequency localization characteristics.Online training is utilized to predict uncertain system dynamics by tuning the wavelet neural network parameters and the controller parameters adaptively.The performance of the controller algorithm is verified by both simulation,and in a real-time practical application involving a single-input single-output double-zone sliver drafting system used in textiles manufacturing.Both the simulation and practical results demonstrate an excellent control performance in terms of the mean thickness and coefficient of variation of output slivers,which verifies the effectiveness of this approach in improving the long-term uniformity of slivers.

Formation Mechanism in Alloy Steel Rolling Process Using Thermo-mechanical Coupling Method

Based on the theory of elastic-plastic finite element method, the high-speed hot continuous rolling process of a billet is simulated and analyzed in vertical and horizontal passes. The billet is dragged into the passes by contact friction force between the billet and rollers. The rollers and billet are represented by respectively rigid and deformable bodies, and three-dimensional models are developed for the billet and rollers. The distribution of deformation field, effective strain, rolling force and temperature field are accurately calculated for the whole rolling process （including unstable and stable stages）. In addition, the rolling pressure on the width symmetry center is compared with that in the in-situ experimental measurements. It is revealed that various heat exchange phenomena among the billet, rollers and surroundings can result in unbalanced temperature distribution on the cross section. Rolling force and strain can change significantly when the billet is moved towards or away from the roller gap, and keep almost invariable in the stable stage. It is expected that the simulation results would be useful for practical manufacture and provide the theoretical foundation for improvement of process planning and optimization of process parameters.

Feeding Control System of Conveyor-belt Based on Image Processing

Based on the real time measurement of the width of coal flow, the method for measuring the width and the relative position of coal flow on a conveyor-belt by image processing was presented. A feeding control system of conveyor-belt was proposed using a fuzzy controller. This control system consists of CCD camera, universal image sampling system, control network and executor. The result shows that the algorithm used in the image processing is simple and efficient, and the measuring error of width is less than 4%.

Real-Time Discrete Adaptive Control of Robot Arm Based on Digital Signal Processing

A discrete model reference adaptive controller of robot arm is obtained by integrating the reduced dynamic model of robot, model reference adaptive control （MRAC） and digital signal processing （DSP） computer system into an electromechanical system. With the DSP computer system, the control signal of each joint of the robot arm can be processed in real time and independently. The simulation and experiment results show that with the control strategy, the robot achieved a good trajectory following precision, a good decoupling performance and a high real-time adaptivity.

Effect of Level of Processing Prior to Response on Cognitive Control:Evidence from ERP

Based on the idea that intentions have different penetrability to perception and thought, four Stroop-like tasks, AA, AW, WA, and WW are used. Event-related brain potentials are recorded as participants completed these tasks, and standardized low resolution brain electromagnetic tomography （sLORETA） is used to localize the sources at specific time points. These results show that there is an interference effect in the AA and WA tasks, but not in the AW or WW tasks. The activated brain areas related to the interference effect in the AA task are the PFC （prefrontal cortex） and ACC （anterior cingulated cortex）, and PFC aetivation takes place prior to ACC activation, but only in WA task. Combined with previous results, a new neural mechanism of cognitive control is proposed.

SINGLE MACHINE SCHEDULING WITH CONTROLLABLE PROCESSING TIMES AND COMPRESSION COSTS （PART I：EQUAL TIMES AND COSTS）

Abstract Most papers in scheduling research have treated individual job processing times as fixed parameters. However, in many practical situations, a manager may control processing time by reallocating resources. In this paper, authors consider a machine scheduling problem with controllable processing times. In the first part of this paper, a special case where the processing times and compression costs are uniform among jobs is discussed. Theoretical results are derived that aid in developing an O(n 2) algorithm to slove the problem optimally. In the second part of this paper, authors generalize the discussion to general case. An effective heuristic to the general problem will be presented.

SINGLE MACHINE SCHEDULING WITH CONTROLLABLE PROCESSING TIMES AND COMPRESSION COSTS ： PROOF OF THEOREMS

Abstract This report is virtually the appendix part of the author's previous paper which includes the proofs for the theorems and lemmas.

Application of single neuron adaptive PID controller during the process of timber drying

The paper presents a method of using single neuron adaptive PID control for adjusting system or servo system to implement timber drying process control, which combines the thought of parameter adaptive PID control and the character of neural network on exactly describing nonlinear and uncertainty dynamic process organically. The method implements functions of adaptive and self-learning by adjusting weighting parameters. Adaptive neural network can make some output trail given hoping value to decouple in static state. The simulation result indicates the validity, veracity and robustness of the method used in the timber drying process

IMPROVED PROCESSING FOR MICROSTRUCTURES AND MECHANICAL PROPERTIES OF A COMMERCIAL PIPELINE STEEL

The transformation productions of hot-deformation simulation experiments were investigated using a Gleeble-1500 hot simulator for a commercial pipeline steel. Based on the investigation results, the improved thermo-mechanical control processing (TMCP) schedules containing a two stage multi-pass controlled rolling coupled with moderate cooling rates were applied to hot rolling experiments and acicular ferrite dominated microstructure was obtained. Microstructures and mechanical properties of hot rolled plates were related to TMCP processing, and regression equations describing the relation between processing parameters and mechanical properties in the current TMCP were developed, which could be used to predict mechanical properties of the experimental steel during commercially processing. It was found that with an increase in cooling rate after hot rolling, grain size in the microstructure became smaller, the amount of polygonal ferrite decreased and acicular ferrite increased, and accordingly mechanical properties increased.

基于Statistical Process Control风险等级判定及神经网络模型构建珠海市传染病指数

目的建立珠海市传染病指数预报模型,为传染病风险预测预报提供思路。方法利用统计过程控制(SPC)的控制下限、中线和控制上限划分全市2014—2017年以周次为时间计量单位的流感样病例比例、手足口病及其他感染性腹泻发病率的风险等级(布雷图指数采用5、10、20判定)。运用长短时记忆神经网络模型(LSTM)和自回归移动平均模型(ARIMA)对2018年15~19周数据进行预测。计算传染病指数并将预测值与实际值对比进而评估预测一致性。结果珠海市手足口病发病率LSTM模型中,测试集MSE为9.0441,RMSE为3.0073,训练集MSE为1.1812,RMSE为1.0868。其余模型在训练集和测试集均表现良好,没有出现过拟合现象。风险指数等级预测与实际值对比,预测一致率为96.0%。结论利用SPC划分风险等级,运用LSTM等构建传染病指数预测模型可行。

Whole-Process Pollution Control for Cost-Effective and Cleaner Chemical Production A Case Study of the Tungsten Industry in China

In this research,a methodology named whole-process pollution control(WPPC)is demonstrated that improves the effectiveness of process optimization.This methodology considers waste/emission treatment as a step of the whole production process with respect to the minimization of cost and environmental impact for the whole process.The following procedures are introduced in a WPPC process optimization:①a material and energy flow investigation and optimization based on a systematic understanding of the distribution and physiochemical properties of potential pollutants;②a process optimization to increase the utilization efficiency of different elements and minimize pollutant emissions;and③an evaluation to reveal the effectiveness of the optimization strategies.The production of ammonium paratungstate was chosen for the case study.Two factors of the different optimization schemes-namely the cost-effectiveness factor and the environmental impact indicator-were evaluated and compared.This research demonstrates that by considering the nature of potential pollutants,technological innovations,economic viability,environmental impacts,and regulation requirements,WPPC can efficiently optimize a metal production process.

Multivariable Decoupling Predictive Control with Input Constraints and Its Application on Chemical Process

A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy.