3-Turns教学法在实践共同体促进深度学习中的应用

在电气工程专业实践教学过程中凝练出由Turn up、Turn away、Turn back等环节组成的3-Turns教学法。经过多轮的实践应用,3-Turns教学法在实践共同体中提供了一个兼具解释性与可操作性的教学样例。研究发现,3-Turns教学法对实践共同体促进工科生深度学习起到了提质增效的作用;3-Turns教学法为工程实践学习情境的强化设计提供了理论依据与经验支持。该研究验证了基于3-Turns教学法的实践共同体促进工科生深度学习的有效性,为助力工科人才培养质量的持续提升做出了积极的探索与实践。

Case Retrieval Strategy of Turning Process Based on Grey Relational Analysis

To solve the problem of long response time when users obtain suitable cutting parameters through the Internet based platform,a case-based reasoning framework is proposed.Specifically,a Hamming distance and Euclidean distance combined method is designed to measure the similarity of case features which have both numeric and category properties.In addition,AHP(Analytic Hierarchy Process)and entropy weight method are integrated to provide features weight,where both user preferences and comprehensive impact of the index have been concerned.Grey relation analysis is used to obtain the similarity of a new problem and alternative cases.Finally,a platform is also developed on Visual Studio 2015,and a case study is demonstrated to verify the practicality and efficiency of the proposed method.This method can obtain cutting parameters which is suitable without iterative calculation.Compared with the traditional PSO(Particle swarm optimization algorithm)and GA(Genetic algorithm),it can obtain faster response speed.This method can provide ideas for selecting processing parameters in industrial production.While guaranteeing the characteristic information is similar,this approach can select processing parameters which is the most appropriate for the production process and a lot of time can be saved.

High-sensitive state perception method for inverter-fed machine turn insulation based on FrFT-Mel

Amidst the swift advancement of new power systems and electric vehicles,inverter-fed machines have progressively materialized as a pivotal apparatus for efficient energy conversion.Stator winding turn insulation failure is the root cause of inverter-fed machine breakdown.The online monitoring of turn insulation health can detect potential safety risks promptly,but faces the challenge of weak characteristics of turn insulation degradation.This study proposes an innovative method to evaluate the turn insulation state of inverter-fed machines by utilizing the fractional Fourier transform with a Mel filter(FrFT-Mel).First,the sensitivity of the high-frequency(HF)switching oscillation current to variations in turn insulation was analyzed within the fractional domain.Subsequently,an improved Mel filter is introduced,and its structure and parameters are specifically designed based on the features intrinsic to the common-mode impedance resonance point of the electrical machine.Finally,an evaluation index was proposed for the turn insulation state of inverter-fed machines.Experimental results on a 3kW permanent magnet synchronous machine(PMSM)demonstrate that the proposed FrFT-Mel method significantly enhances the sensitivity of turn insulation state perception by approximately five times,compared to the traditional Fourier transform method.

Analysis on the turning point of dynamic in-plane compressive strength for a plain weave composite

Experimental investigations on dynamic in-plane compressive behavior of a plain weave composite were performed using the split Hopkinson pressure bar. A quantitative criterion for calculating the constant strain rate of composites was established. Then the upper limit of strain rate, restricted by stress equilibrium and constant loading rate, was rationally estimated and confirmed by tests. Within the achievable range of 0.001/s-895/s, it was found that the strength increased first and subsequently decreased as the strain rate increased. This feature was also reflected by the turning point(579/s) of the bilinear model for strength prediction. The transition in failure mechanism, from local opening damage to completely splitting destruction, was mainly responsible for such strain rate effects. And three major failure modes were summarized under microscopic observations: fiber fracture, inter-fiber fracture, and interface delamination. Finally, by introducing a nonlinear damage variable, a simplified ZWT model was developed to characterize the dynamic mechanical response. Excellent agreement was shown between the experimental and simulated results.

DER SPATIAL TURN IN DEN KLASSISCHEN ALTERTUMSWISSENSCHAFTEN(UND SPEZIELL IN DER EPIGRAPHIK)

Since the 1990s the so-called spatial turn has brought back space and topography into the discussion within historical studies,particular ancient studies.This survey reviews current trends and developments within the field and offers some perspectives on possible future developments related to space,material,objects,their agency,and frames.

HCB-turn热风干燥器在纸机改造中的应用

由于市场、成本、车速、纸张品质等原因,需要对背面涂布段进行优化改造,这时候加装HCB-turn热风干燥器则是最佳的选择之一,因为它比常规纸幅运行节省1/3的安装空间,且适用于所有纸种,对纸张和涂层能够有高效的干燥和无污染的转向。

Numerical Study of a Three-Dimensional Laminar Flow in a Rectangular Channel with a 180-Degree Sharp Turn

This study presents a numerical analysis of three-dimensional steady laminar flow in a rectangular channel with a 180-degree sharp turn. The Navier-Stokes equations are solved by using finite difference method for Re = 900. Three-dimensional streamlines and limiting streamlines on wall surface are used to analyze the three-dimensional flow characteristics. Topological theory is applied to limiting streamlines on inner walls of the channel and two-dimensional streamlines at several cross sections. It is also shown that the flow impinges on the end wall of turn and the secondary flow is induced by the curvature in the sharp turn.

TURNING LIGNIN INTO VALUABLE PRODUCTS

In a study published in Nature Catalysis on May 28,Chinese scientists unveiled a nove l approach to transforming lignin,a major component of woody biomass,into valuable chemical products(doi:10.1038/s41929-024-01165-w).This discovery could pave the way for more sustainable and efficient use of renewable resources.

A Study on the Effectiveness of Process-oriented Approach in ESL English Writing Teaching in YAU

This study sets out to conduct the effectiveness of process-oriented approach on the ESL writing teaching for non-Eng-lish majors in Yunnan Agricultural University(YAU),with the aim of enhancing the students' English writing proficiency andscores.120 non-English major sophomores and 10 English teachers from YAU are involved in it.With the results of questionnaire,interview and the composition scores of the target students,the findings indicate that the students have a positive attitude towardsprocess-oriented writing approach and it can help them write better and make the writing class more interesting.

Efficacy of Peer Revision in Process-oriented Writing

Peer revision is a collaborative activity during which student writers can exchange drafts and make suggestions for improvement. It has been widely used at present in process-oriented writing instruction. In this paper, the researcher carried out an empirical study about the effects and efficacy of peer revision on a group of Chinese Juniors majoring in English. It was found that student writers focused specially on grammar and vocabulary in PE session and organization was the least attended to. PE was quite effective in improving the overall writing quality, as the participants did incorporate most of the revisions suggested by their peers. However, the influences of students'writing proficiencies and of the rhetorical modes of the writing tasks on the effects of PE were proved to be not very significant.

Process-oriented Approach to Motivating Learners:Its Implications and Applications

Drawn upon Dornyei' s motivational study,this paper aims to explore the implications that process-oriented approach may bring and tries to shed light on some applications in Chinese EFL teaching context.

利用车载GNSS轨迹大数据的U-Turn道路结构信息获取方法

随着智慧交通和精细化导航技术的迅速发展,人们对道路地图要素的覆盖度、精准度、丰富度与新鲜度需求越来越高,而U-Turn作为城市路网连通关系的重要因素,成为道路地图更新的重要内容之一。现有专业道路测绘模式对U-Turn数据存在采集成本高、更新周期长、数据处理繁等问题,导致U-Turn数据无法满足智慧交通导航需求。本文采用车载GNSS轨迹大数据,提出了一种U-Turn道路结构信息获取方法。首先通过轨迹跟踪提取车辆掉头点对与行为;然后利用DBSCAN聚类算法提取U-Turn掉头类簇;再依据U-Turn流量占比等特征构建支持向量机二分模型,自适应剔除违规掉头类簇,并区分出U-Turn结构有无通行时间限制;最后根据掉头类簇在道路结构中的分布特征,识别U-Turn位置与空间结构。试验以武汉市滴滴网约车GNSS轨迹,对江汉区183个路段采用本文方法进行探测,U-Turn结构信息识别召回率为88.3%,精确率为87.6%,位置识别的横向和纵向精度分别为3.40 m和5.90 m,试验结果表明本文方法可以有效地从车载GNSS轨迹数据中获取U-Turn的位置与结构类型,为U-Turn数据获取提供了周期短、成本低的有效解决方案。

A theoretical and deep learning hybrid model for predicting surface roughness of diamond-turned polycrystalline materials

Polycrystalline materials are extensively employed in industry.Its surface roughness significantly affects the working performance.Material defects,particularly grain boundaries,have a great impact on the achieved surface roughness of polycrystalline materials.However,it is difficult to establish a purely theoretical model for surface roughness with consideration of the grain boundary effect using conventional analytical methods.In this work,a theoretical and deep learning hybrid model for predicting the surface roughness of diamond-turned polycrystalline materials is proposed.The kinematic–dynamic roughness component in relation to the tool profile duplication effect,work material plastic side flow,relative vibration between the diamond tool and workpiece,etc,is theoretically calculated.The material-defect roughness component is modeled with a cascade forward neural network.In the neural network,the ratio of maximum undeformed chip thickness to cutting edge radius RT S,work material properties(misorientation angle θ_(g) and grain size d_(g)),and spindle rotation speed n s are configured as input variables.The material-defect roughness component is set as the output variable.To validate the developed model,polycrystalline copper with a gradient distribution of grains prepared by friction stir processing is machined with various processing parameters and different diamond tools.Compared with the previously developed model,obvious improvement in the prediction accuracy is observed with this hybrid prediction model.Based on this model,the influences of different factors on the surface roughness of polycrystalline materials are discussed.The influencing mechanism of the misorientation angle and grain size is quantitatively analyzed.Two fracture modes,including transcrystalline and intercrystalline fractures at different RTS values,are observed.Meanwhile,optimal processing parameters are obtained with a simulated annealing algorithm.Cutting experiments are performed with the optimal parameters,and a flat surface finish with Sa 1.314 nm is finally achieved.The developed model and corresponding new findings in this work are beneficial for accurately predicting the surface roughness of polycrystalline materials and understanding the impacting mechanism of material defects in diamond turning.

Process-oriented knowledge-sharing platform for chemical engineering design projects

A process-oriented knowledge-sharing platform is studied to improve knowledge sharing and project management of chemical engineering design enterprises. First, problems and characteristics of knowledge sharing in multi-projects of chemical engineering design are analyzed. Then based on theories of project management, process management, and knowledge management, a process-oriented knowledge-sharing platform is proposed. The platform has three characteristics: knowledge is divided into professional knowledge and project management knowledge; knowledge sharing is integrated with the project process, which makes knowledge sharing a necessary part of the project process and ensures the quantity of knowledge shared; the platform provides quantitative measurements of incentive mechanisms for knowledge providers and users which ensures the quality of knowledge shared. This knowledge-sharing platform uses two knowledge management tools, a knowledge map and a knowledge base, to support the platform.

Integral Event-Triggered Attack-Resilient Control of Aircraft-on-Ground Synergistic Turning System With Uncertain Tire Cornering Stiffness

This article proposes an integral-based event-triggered attack-resilient control method for the aircraft-on-ground(AoG) synergistic turning system with uncertain tire cornering stiffness under stochastic deception attacks. First, a novel AoG synergistic turning model is established with synergistic reverse steering of the front and main wheels to decrease the steering angle of the AoG fuselage, thus reducing the steady-state error when it follows a path with some large curvature. Considering that the tire cornering stiffness of the front and main wheels vary during steering, a dynamical observer is designed to adaptively identify them and estimate the system state at the same time.Then, an integral-based event-triggered mechanism(I-ETM) is synthesized to reduce the transmission frequency at the observerto-controller end, where stochastic deception attacks may occur at any time with a stochastic probability. Moreover, an attackresilient controller is designed to guarantee that the closed-loop system is robust L2-stable under stochastic attacks and external disturbances. A co-design method is provided to get feasible solutions for the observer, controller, and I-ETM simultaneously. An optimization program is further presented to make a tradeoff between the robustness of the control scheme and the saving of communication resources. Finally, the low-and high-probability stochastic deception attacks are considered in the simulations. The results have illustrated that the AoG synergistic turning system with the proposed control method follows a path with some large curvature well under stochastic deception attacks. Furthermore,compared with the static event-triggered mechanisms, the proposed I-ETM has demonstrated its superiority in saving communication resources.

Nurses’ Experiences of Process-Oriented Supervision—Acquiring New Approaches to Demanding Situations

Background: Providing nursing care for patients and relatives requires a great effort from a nurse. It is therefore important for the nurse to have the opportunity to reflect on the caring acts included in process-oriented nursing supervision (PRONS). The overall objective of the nursing supervision is to support the professional development identity, competences, skills and ethics in different situations in nursing care. Aim: To investigate nurses’ experiences of the model of purging, playing and learning (PPL) according to Eriksson theory in a (PRONS) related to strengthen safe care, quality and professional development. Method: A qualitative study with individual interviews and the data was analyzed using qualitative interpretive content analysis. Participants: All eleven registered participated nurses were from southwestern Sweden and worked in different hospital units. Ethical Considerations: The study carried out in accordance with the ethical guidelines laid down in the Helsinki Declaration and according to the recommendations of the regional ethics committee. Findings: Three categories were identified, valuable purging in the process, responsive playing and awareness of learning. The study found that by participating in PRONS the nurses had developed new approaches with different “tools” when difficult situations occurred in daily nursing practice. Conclusion: PRONS with the model PPL has an important role to support nurses in daily nursing practice. The study highlights that there are residual successful effects after PRONS for the nurses in managing care situations that experienced strengthen quality in care and professional development.

The summer solstice is the turning point when light and temperature affect the growth of trees

The interaction between light and temperature is known to influence the seasonal growth of trees.Traditional studies on"light"primarily focus on day length,specifically short day(SD)or long day(LD)conditions.However,little research has been conducted on the process of transitioning between SD and LD conditions.

Technique for Multi-Pass Turning Optimization Based on Gaussian Quantum-Behaved Bat Algorithm

The multi-pass turning operation is one of the most commonly used machining methods in manufacturing field.The main objective of this operation is to minimize the unit production cost.This paper proposes a Gaussian quantum-behaved bat algorithm(GQBA)to solve the problem of multi-pass turning operation.The proposed algorithm mainly includes the following two improvements.The first improvement is to incorporate the current optimal positions of quantum bats and the global best position into the stochastic attractor to facilitate population diversification.The second improvement is to use a Gaussian distribution instead of the uniform distribution to update the positions of the quantum-behaved bats,thus performing a more accurate search and avoiding premature convergence.The performance of the presented GQBA is demonstrated through numerical benchmark functions and amulti-pass turning operation problem.Thirteen classical benchmark functions are utilized in the comparison experiments,and the experimental results for accuracy and convergence speed demonstrate that,in most cases,the GQBA can provide a better search capability than other algorithms.Furthermore,GQBA is applied to an optimization problem formulti-pass turning,which is designed tominimize the production cost while considering many practical machining constraints in the machining process.The experimental results indicate that the GQBA outperforms other comparison algorithms in terms of cost reduction,which proves the effectiveness of the GQBA.

Status of research on non-conventional technology assisted single-point diamond turning

With the increasing use of difficult-to-machine materials in aerospace applications,machining requirements are becoming ever more rigorous.However,traditional single-point diamond turning(SPDT)can cause surface damage and tool wear.Thus,it is difficult for SPDT to meet the processing requirements,and it has significant limitations.Research indicates that supplementing SPDT with unconventional techniques can,importantly,solve problems due to the high cutting forces and poor surface quality for difficult-to-machine materials.This paper first introduces SPDT and reviews research into unconventional techniques for use with SPDT.The machining mechanism is discussed,and the main advantages and disadvantages of various methods are investigated.Second,hybrid SPDT is briefly described,which encompasses ultrasonic-vibration magnetic-field SPDT,ultrasonic-vibration laser SPDT,and ultrasonic-vibration cold-plasma SPDT.Compared with the traditional SPDT method,hybrid SPDT produces a better optical surface quality.The current status of research into unconventional techniques to supplement SPDT is then summarized.Finally,future development trends and the application prospects of unconventional assisted SPDT are discussed.

Development and Evaluation of Intersection-Based Turning Movement Counts Framework Using Two Channel LiDAR Sensors

This paper presents vehicle localization and tracking methodology to utilize two-channel LiDAR data for turning movement counts. The proposed methodology uniquely integrates a K-means clustering technique, an inverse sensor model, and a Kalman filter to obtain the final trajectories of an individual vehicle. The objective of applying K-means clustering is to robustly differentiate LiDAR data generated by pedestrians and multiple vehicles to identify their presence in the LiDAR’s field of view (FOV). To localize the detected vehicle, an inverse sensor model was used to calculate the accurate location of the vehicles in the LiDAR’s FOV with a known LiDAR position. A constant velocity model based Kalman filter is defined to utilize the localized vehicle information to construct its trajectory by combining LiDAR data from the consecutive scanning cycles. To test the accuracy of the proposed methodology, the turning movement data was collected from busy intersections located in Newark, NJ. The results show that the proposed method can effectively develop the trajectories of the turning vehicles at the intersections and has an average accuracy of 83.8%. Obtained R-squared value for localizing the vehicles ranges from 0.87 to 0.89. To measure the accuracy of the proposed method, it is compared with previously developed methods that focused on the application of multiple-channel LiDARs. The comparison shows that the proposed methodology utilizes two-channel LiDAR data effectively which has a low resolution of data cluster and can achieve acceptable accuracy compared to multiple-channel LiDARs and therefore can be used as a cost-effective measure for large-scale data collection of smart cities.