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Fabric has complicated anisotropic mechanical behavior because of the woven pattern and complex physical properties. However, most current fabric simulation models are not satisfied because the models are usually geometrical models with stiffness parameters.

In this paper, the authors present a modeling technique to simulate fabric with Riemann manifold. The proposed nonlinear model is formed with ridge wave-curved surface based on the Riemann zero curvature, and the authors develop a solution to conserve the surface area. It decomposes the m × n matrix constituting the fabric into several batches and processes the fabric dots in batches. In this model, the distance between any two adjacent particles of the fabric's is assumed to be equal, and the area of the curved surface is always constant, and the inclination and decay of the ridge wave-curved surface are also considered.

As the result, the simulated shape is lifelike. In time cost performance, the model improves the efficiency of the fabric styling and meets the requirements of real-time simulation.

The proposed nonlinear model is formed with ridge wave-curved surface based on the Riemann zero curvature, and the authors develop a solution to conserve the surface area.

This paper aims to reveal the tribochemical reaction mechanism on the nano-cutting interface between HMX crystal and diamond tool.

Molecular dynamics simulation of HMX crystal nano-cutting by the reactive force field is carried out in this paper. The affinity of activated atoms and friction damage at the different interface have been well identified by comparing two cutting systems with diamond tool or indenter. The analyses of reaction kinetics, decomposition products and reaction pathways are performed to reveal the underlying atomistic origins of tribocatalytic reaction on the nano-cutting interface.

The HMX crystals only undergo damage and removal in the indenter cutting, while they appear to accelerate thermal decomposition in the diamond cutting. the C-O affinity is proved to be the intrinsic reason of the tribocatalytic reaction of the HMX-diamond cutting system. The reaction activation energy of the HMX crystals in the diamond cutting system is lower, resulting in a rapid increase in the decomposition degree. The free O atoms can induce the asymmetric ring-opening mode and change the decomposition pathways, which is the underlying atomistic origins of the thermal stability of the HMX-diamond cutting system.

This paper describes a method for analyzing the tribochemical behavior of HMX and diamond, which is beneficial to study the thermal stability in the nano-cutting of HMX.

This paper aims to use active fine lane management methods to solve the problem of congestion in a weaving area and provide theoretical and technical support for traffic control under the environment of intelligent connected vehicles (ICVs) in the future.

By analyzing the traffic capacities and traffic behaviors of domestic and foreign weaving areas and combining them with field investigation, the paper proposes the active and fine lane management methods for ICVs to optimal driving behavior in a weaving area. The VISSIM simulation of traffic flow vehicle driving behavior in weaving areas of urban expressways was performed using research data. The influence of lane-changing in advance on the weaving area was evaluated and a conflict avoidance area was established in the weaving area. The active fine lane management methods applied to a weaving area were verified for different scenarios.

The results of the study indicate that ICVs complete their lane changes before they reach a weaving area, their time in the weaving area does not exceed the specified time and the delay of vehicles that pass through the weaving area decreases.

Based on the vehicle group behavior, this paper conducts a simulation study on the active traffic management control-oriented to ICVs. The research results can optimize the management of lanes, improve the traffic capacity of a weaving area and mitigate traffic congestion on expressways.

This paper aims to reveal the mechanism for improving ductile machinability of 3C-silicon carbide (SiC) and associated cutting mechanism in stress-assisted nanometric cutting.

Molecular dynamics simulation of nano-cutting 3C-SiC is carried out in this paper. The following two scenarios are considered: normal nanometric cutting of 3C-SiC; and stress-assisted nanometric cutting of 3C-SiC for comparison. Chip formation, phase transformation, dislocation activities and shear strain during nanometric cutting are analyzed.

Negative rake angle can produce necessary hydrostatic stress to achieve ductile removal by the extrusion in ductile regime machining. In ductile-brittle transition, deformation mechanism of 3C-SiC is combination of plastic deformation dominated by dislocation activities and localization of shear deformation. When cutting depth is greater than 10 nm, material removal is mainly achieved by shear. Stress-assisted machining can lead to better quality of machined surface. However, there is a threshold for the applied stress to fully gain advantages offered by stress-assisted machining. Stress-assisted machining further enhances plastic deformation ability through the active dislocations’ movements.

This work describes a stress-assisted machining method for improving the surface quality, which could improve 3C-SiC ductile machining ability.

This paper aims to investigate an efficient approach to model the electromagnetic behaviors and predict stray-field loss inside the magnetic steel plate under 3D harmonic magnetization conditions so as to effectively prevent the structural components from local overheating and insulation damage in electromagnetic devices.

An experimental setup is applied to measure all the magnetic properties of magnetic steel plate under harmonic excitations with different frequencies and phase angles. The measurement and numerical simulation are carried out based on the updated TEAM Problem 21 Model B+ (P210-B+), under the 3D harmonic magnetization conditions. An improved method to evaluate the stray-field loss is proposed, and harmonic flux distribution in the structural components is analyzed.

The influence of the harmonic order and phase angle on the stray-field loss in magnetic steel components are noteworthy. Based on the engineering-oriented benchmark models, the variations of stray-field losses and magnetic field distribution inside the magnetic components under harmonic magnetization conditions are presented and analyzed in detail.

The capacity of the multi-function harmonic source, used in this work, was not large enough, which limits the magnetization level. Up to now, further improvements to increase the harmonic source capacity and investigations of the electromagnetic behaviors of magnetic steel components under multi-harmonic and DC-AC hybrid excitations are in progress.

To accurately predict the stray-field loss in magnetic steel plate, the improved method based on the combination of magnetic measurement and numerical simulation is proposed. The effects of the frequency and phase angle on the stray-field loss are analyzed.

Attention is one of the most important factors to affect the academic performance of students. Effectively analyzing students' attention in class can promote teachers' precise teaching and students' personalized learning. To intelligently analyze the students' attention in classroom from the first-person perspective, this paper proposes a fusion model based on gaze tracking and object detection. In particular, the proposed attention analysis model does not depend on any smart equipment.

Given a first-person view video of students' learning, the authors first estimate the gazing point by using the deep space–time neural network. Second, single shot multi-box detector and fast segmentation convolutional neural network are comparatively adopted to accurately detect the objects in the video. Third, they predict the gazing objects by combining the results of gazing point estimation and object detection. Finally, the personalized attention of students is analyzed based on the predicted gazing objects and the measurable eye movement criteria.

A large number of experiments are carried out on a public database and a new dataset that is built in a real classroom. The experimental results show that the proposed model not only can accurately track the students' gazing trajectory and effectively analyze the fluctuation of attention of the individual student and all students but also provide a valuable reference to evaluate the process of learning of students.

The contributions of this paper can be summarized as follows. The analysis of students' attention plays an important role in improving teaching quality and student achievement. However, there is little research on how to automatically and intelligently analyze students' attention. To alleviate this problem, this paper focuses on analyzing students' attention by gaze tracking and object detection in classroom teaching, which is significant for practical application in the field of education. The authors proposed an effectively intelligent fusion model based on the deep neural network, which mainly includes the gazing point module and the object detection module, to analyze students' attention in classroom teaching instead of relying on any smart wearable device. They introduce the attention mechanism into the gazing point module to improve the performance of gazing point detection and perform some comparison experiments on the public dataset to prove that the gazing point module can achieve better performance. They associate the eye movement criteria with visual gaze to get quantifiable objective data for students' attention analysis, which can provide a valuable basis to evaluate the learning process of students, provide useful learning information of students for both parents and teachers and support the development of individualized teaching. They built a new database that contains the first-person view videos of 11 subjects in a real classroom and employ it to evaluate the effectiveness and feasibility of the proposed model.

The purpose of this paper is to propose a relatively simple and rapid method to create a digital human model (DHM) to serve clothing industry.

Human body’s point cloud is divided into hands, foots, head and torso. Then forward modeling method is used to model hands and foots, photo modeling method is used to model head and reverse modeling method is used to model torso. After that, hands, foots, head and torso are integrated together to get a static avatar. Next, virtual skeleton is bound to the avatar. Finally, a lifelike digital human body model is created by the mixed modeling method (MMM).

In allusion to the defect of the three-dimension original data of human body, this paper presented an MMM, with which we can get a realistic digital human body model with accurate body dimensions. The DHM can well meet the needs of fashion industry.

The DHM, which is got by the MMM, can be well applied in the field of virtual try on, virtual fashion design, virtual fashion show and so on.

The originality of the paper lies in the integration of forward modeling, reverse modeling and photo modeling to present a novel method of human body modeling.

The purpose of this paper is to set up a women’s jeans knowledge base between consumer profile and jeans profile. The result of study could be applied to jeans recommendation system for a special consumer.

Women’s jeans are chosen as research objects. The sensory evaluation technology and intelligent data fusion methods are applied in this research.

Eight pairs of words were selected to set up normalized sensory evaluation criteria in the study for describing both consumers’ expectations and products. The relation between consumer profile and jeans profile could be quantified according to the principle of sensory evaluation technology.

Four experiments are designed for setting up this knowledge base by sensory evaluation technology, and set up the women’s jeans knowledge base by intelligent data fusion methods.

The theory of sensory evaluation technology is applied for building women’s jeans knowledge base that can be used for consumer-oriented intelligent garment recommendation system.

The purpose of the paper is to give a review of TEAM Problem 21, focus on its extended progress in engineering-oriented developments, and report the new benchmarking activity undertaken by the authors.

Testing electromagnetic analysis methods; verify computation models; detail the field behavior of typical magnetic structure; benefit to large-scale numerical modeling.

The calculated results of power loss and magnetic flux for all the member models agree well with the measured ones. The updated Problem 21 Family can now be used to model the saturation effect in the magnetic plate or the lamination by increasing the exciting currents. The new member model P21d-M allows further detailed examination of the electromagnetic behavior inside laminated sheets. The variation of both the iron loss and the magnetic flux with the excitation patterns and magnetic property data can be investigated inside the laminated sheets and the magnetic plate.

In order to model the possible saturation level of magnetic steel using Ar-V-Ar or T-Ω solvers, the exciting currents are increased from 10 to 50 A. In order to model the iron loss and magnetic flux densities inside the laminated sheets, a very simplified model, P21d-M of Problem 21 Family as shown in Figure 2, has been proposed.

Established on the detailed exploration of Chinese ancient management philosophies (CAMPs), the purpose of this paper is to extract enlightenments from CAMPs to see whether there exist some similarities between CAMPs and contemporary human resources management thoughts (CHRMTs) and pinpoint CAMPs' implications on human resource management practices nowadays.

Inspired by Lao Tzu's “When we can lay hold of the Dao of old to direct the things of the present day, and are able to know it as it was of old in the beginning, this is called (unwinding) the clue of Dao”, the paper explores, categorizes and integrates wisdom stemmed from CAMPs to evaluate whether there exist some commonly accepted arguments between CAMPs and CHRMTs.

CAMPs which have been passed on by generations for the past 2,500 years in China provide firm ground for human resources management thoughts and practices development; CAMPs' emphasis on people's well cultured morality and highly developed virtues has kindled a light to illuminate human resources management practices, not only in the past but also in the future. CHRMTs' principles concerning “people‐centered strategies”, employee recruitment and selection strategies, employee training and education strategies, staffing as well as employee retention strategies, can all trace their sources from CAMPs.

The research on CAMPs is not only significant to complement and extend CHRMTs but also useful to direct current human resource management practices.