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Identifying Brand Consistency by Product Differentiation Using CNN

Computer Modeling in Engineering & Sciences 2024年第7期140卷 685-709页

作者： Hung-Hsiang Wang Chih-Ping Chen department of industrial design National Taipei University of TechnologyTaipeiTaiwan department of Product design Ming Chuan UniversityTaoyuanTaiwan

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance *** Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and *** show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various *** investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late *** show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real *** relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style *** addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred *** study provides insights into practical problems for designers,manufacturers,and marketers in product *** not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand *** can use these techniques to find features that influence brand ***,capture these features as innovative design elements and maintain core brand values.

关键词： Machine learning product differentiation brand consistency principal component analysis convolutional neural network computer mouse

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A study of the effect of local scour on the flow field near the spur dike

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Theoretical & Applied Mechanics Letters 2024年第2期14卷 98-105页

作者： Yu-Tian Li Jie-Min Zhan Wing-Hong Onyx Wai department of industrial design School of Industrial Design and Ceramic ArtFoshan UniversityFoshan 528000China department of Applied Mechanics and Engineering Shenzhen Campus of Sun Yat-sen UniversityShenzhen 518107China department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityHong Kong 999077China

The flow field near a spur dike such as down flow and horseshoe vortex system(HVS)are susceptible to the topographic changes in the local scouring process,resulting in variation of the sediment transport with *** this study,large eddy simulations with fixed-bed at different scouring stages were conducted to investigate the changes in flow *** results imply that the bed deformation leads to an increase in flow rate per unit area,which represent the capability of sediment transportation by water,in the scour ***,the intensity of turbulent kinetic energy and bimodal motion near the sand bed induced by the HVS were also ***,the peak moments between the two sediment transport mechanisms were ***,understanding the complex feedback mechanism between topography and flow field is essential for the local scour problem.

关键词： Spur dike Local scour Large eddy simulation Down flow Horseshoe vortex system

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An Interactive Collaborative Creation System for Shadow Puppets Based on Smooth Generative Adversarial Networks

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Computers, Materials & Continua 2024年第6期79卷 4107-4126页

作者： Cheng Yang Miaojia Lou Xiaoyu Chen Zixuan Ren department of industrial design Hangzhou City UniversityHangzhou310000China College of Computer Science and Technology Zhejiang UniversityHangzhou310000China

Chinese shadow puppetry has been recognized as a world intangible cultural ***,it faces substantial challenges in its preservation and advancement due to the intricate and labor-intensive nature of crafting shadow *** ensure the inheritance and development of this cultural heritage,it is imperative to enable traditional art to flourish in the digital *** paper presents an Interactive Collaborative Creation System for shadow puppets,designed to facilitate the creation of high-quality shadow puppet images with greater *** system comprises four key functions:Image contour extraction,intelligent reference recommendation,generation network,and color adjustment,all aimed at assisting users in various aspects of the creative process,including drawing,inspiration,and content ***,we propose an enhanced algorithm called Smooth Generative Adversarial Networks(SmoothGAN),which exhibits more stable gradient training and a greater capacity for generating high-resolution shadow puppet ***,we have built a new dataset comprising high-quality shadow puppet images to train the shadow puppet generation *** qualitative and quantitative experimental results demonstrate that SmoothGAN significantly improves the quality of image generation,while our system efficiently assists users in creating high-quality shadow puppet images,with a SUS scale score of *** study provides a valuable theoretical and practical reference for the digital creation of shadow puppet art.

关键词： Shadow puppets deep learning image generation co-create

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DEM investigation of strength and critical state behaviours of granular materials under true triaxial loadings

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Particuology 2024年第2期85卷 198-212页

作者： Minyi Zhu Guobin Gong Jun Xia Stephen Wilkinson department of Civil Engineering Xi'an Jiaotong-Liverpool UniversityChina department of Civil Engineering and industrial design University of LiverpoolLiverpoolUK Faculty of Engineering and Information Sciences University of Wollongong in DubaiUnited Arab Emirates

This paper investigates the strength and critical state(CS)behaviours of granular materials via DEM simulations of true triaxial drained tests under three different loading modes including constant b(in-termediate stress ratio)tests with constantσ'1(major principal stress),constant p(mean pressure)and constantσ'3(minor principal stress)*** this end,a series of samples are generated with the same particle size distribution,and with the confining stresses ranging from 100 kPa to 900 *** CS is achieved for all *** the macroscopic behaviours and the microscopic behaviours are examined and compared considering different loading modes,confining stresses and intermediate stress ratios(b).The critical state lines(CSLs)are found to be unique and independent of the loading modes,but dependent on the b *** CSLs with b=0 and b=1 form the two boundaries of CSLs respectively beyond which CSLs under all other b tests cannot go *** different strength criteria are examined and compared in terms of both peak and CS *** Mohr-Coulomb strength criterion is found to be only suitable for axisymmetric loading *** Lade-Duncan criterion is only suitable for describing peak strengths,which is dependent on the loading modes and confining *** Satake criterion and Matsuoka-Nakai criterion are the more appropriate strength criteria for describing CS failures,indicating that the CS values of both the Satake parameter and the Matsuoka-Nakai parameter describe an inherent property that characterizes the CS failure for a given type of *** CS mechanical coordination number is fitted by a curved line for a given b value,which is unique regardless of the loading *** peak and CS values of both major and minor principal fabric tensors decrease with increasing b values,while they increase with increasing b values for the intermediate principal fabric tensor.

关键词： Discrete element method Intermediate stress ratio Dilation Critical state Failure criterion

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Combining Deep Learning with Knowledge Graph for design Knowledge Acquisition in Conceptual Product design

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工程与科学中的计算机建模(英文) 2024年第1期138卷 167-200页

作者： Yuexin Huang Suihuai Yu Jianjie Chu Zhaojing Su Yangfan Cong Hanyu Wang Hao Fan Key Laboratory of industrial design and Ergonomics Ministry of Industry and Information TechnologyNorthwestern Polytechnical UniversityXi’an710072China School of industrial design Engineering Delft University of TechnologyDelft2628 CEThe Netherlands department of industrial design College of ArtsShandong University of Science and TechnologyTsingtao266590China College of Computer Science and Technology Zhejiang UniversityHangzhou310027China

The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product *** study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge ***,the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data,and further constructs the knowledge graph to support design knowledge acquisition for conceptual product ***,the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module,and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction *** comparison verified the effectiveness and accuracy of the proposed knowledge extraction *** case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge.

关键词： Conceptual product design design knowledge acquisition knowledge graph entity extraction relation extraction

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Predicting grain size-dependent superplastic properties in friction stir processed ZK30 magnesium alloy with machine learning methods

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Journal of Magnesium and Alloys 2024年第5期12卷 1931-1943页

作者： Farid Bahari-Sambran Fernando Carreno C.M.Cepeda-Jiménez Alberto Orozco-Caballero Physical Metallurgy department CENIM-CSICAv.Gregorio del Amo 828040 MadridSpain department of Mechanical Engineering Chemistry and Industrial DesignPolytechnic University of MadridRonda de Valencia 328012MadridSpain

The aim of this work is to predict,for the first time,the high temperature flow stress dependency with the grain size and the underlaid deformation mechanism using two machine learning models,random forest(RF)and artificial neural network(ANN).With that purpose,a ZK30 magnesium alloy was friction stir processed(FSP)using three different severe conditions to obtain fine grain microstructures(with average grain sizes between 2 and 3μm)prone to extensive superplastic *** three friction stir processed samples clearly deformed by grain boundary sliding(GBS)deformation mechanism at high *** maximum elongations to failure,well over 400% at high strain rate of 10^(-2)s^(-1),were reached at 400℃ in the material with coarsest grain size of 2.8μm,and at 300℃ for the finest grain size of 2μ***,the superplastic response decreased at 350℃ and 400℃ due to thermal instabilities and grain coarsening,which makes it difficult to assess the operative deformation mechanism at such *** work highlights that the machine learning models considered,especially the ANN model with higher accuracy in predicting flow stress values,allow determining adequately the superplastic creep behavior including other possible grain size scenarios.

关键词： Machine learning Artificial intelligence Magnesium alloys Superplasticity Friction stir processing Grain coarsening

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Experimental study of 3D printed carbon fibre sandwich structures for lightweight applications

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Defence Technology（防务技术） 2024年第6期36卷 71-77页

作者： Solaiprakash Vellaisamy Raguraman Munusamy department of Mechanical Engineering Indian Institute of Information Technology Design and ManufacturingKancheepuramChennai600127India School of Interdisciplinary design and Innovation Indian Institute of Information Technology Design and ManufacturingKancheepuramChennai600127India

Honeycomb sandwich structures are widely used in lightweight ***,these structures are subjected to extreme loading conditions,leading to potential failures due to delamination and debonding between the face sheet and the honeycomb ***,the present study is focused on the mechanical characterisation of honeycomb sandwich structures fabricated using advanced 3D printing *** continuous carbon fibres and ONYX-FR matrix materials have been used as raw materials for 3D printing of the specimens needed for various mechanical characterization testing;ONYX-FR is a commercial trade name for flame retardant short carbon fibre filled nylon filaments,used as a reinforcing material in Morkforged 3D *** and flatwise compression tests have been conducted for different configurations of honeycomb sandwich structures,fabricated by varying the face sheet thickness and core cell size,while keeping the core cell thickness and core height *** on these tests,the proposed structure with face sheet thickness of 3.2 mm and a core cell size of 12.7 mm exhibited the highest energy absorption and prevented delamination and debonding ***,3D printing technology can also be considered as an alternative method for sandwich structure ***,detailed parametric studies still need to be conducted to meet various other structural integrity criteria related to the lightweight applications.

关键词： 3D printed composite Honeycomb sandwich Edgewise compression Flatwise compression Lightweight

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Restimate:Recovery Estimation Tool for Resilience Planning

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Journal of Safety Science and Resilience 2024年第1期5卷 47-63页

作者： Scott Miles Megan Ly Nick Terry Youngjun Choe department of Human Centered design&Engineering Campus Box 352315University of WashingtonSeattleWA 98195United States of America department of industrial&Systems Engineering Box 352650University of WashingtonSeattleWA 98195United States of America

The *** Institute of Standards and Technology(NIST)published the Community Resilience Planning Guide in *** NIST Guide advocates for a participatory process for developing a performance measurement framework for the jurisdiction’s resilience against a scenario *** framework centers around tables of expected and desired recovery times for selected community assets,such as electricity,water,and natural gas *** NIST Guide does not provide a method for estimating the expected recovery ***,building high-fidelity computer models for such estimations requires substantial resources that even larger ju-risdictions cannot *** most promising approach to recovery time estimation is to systematically use data elicited from people to tap into the wisdom of the(knowledgeable)*** paper describes a novel research-through-design project to enable the computer-supported elicitation of recovery time series *** work is the first in the literature to examine people’s ability to estimate recovery curves and how design in-fluences such *** main contribution to resilience planning is three-fold:development of a new elicitation tool called Restimate,understanding its potential user base,and providing insights into how it can facilitate resilience *** is the first tool to enable evidence-based expert elicitation in any community with limited resources for resilience *** resilience planning,those who facilitate high-stakes planning activities under large uncertainties(e.g.,mission-critical system design and planning)will benefit from a similar research-through-design process.

关键词： expert elicitation disaster natural hazard infrastructure community resilience restoration user-centered design computer-supported cooperative work

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A stable implicit nodal integration-based particle finite element method(N-PFEM)for modelling saturated soil dynamics

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2172-2183页

作者： Liang Wang Xue Zhang Jingjing Meng Qinghua Lei department of Earth Sciences ETH ZürichZürich8092Switzerland department of Civil Engineering and industrial design University of LiverpoolLiverpoolL693BXUK department of Civil Environmental and Natural Resources EngineeringLuleåUniversity of TechnologyLuleå97187Sweden department of Earth Sciences Uppsala UniversityUppsala75105Sweden

In this study,we present a novel nodal integration-based particle finite element method(N-PFEM)designed for the dynamic analysis of saturated *** approach incorporates the nodal integration technique into a generalised Hellinger-Reissner(HR)variational principle,creating an implicit PFEM *** mitigate the volumetric locking issue in low-order elements,we employ a node-based strain smoothing *** discretising field variables at the centre of smoothing cells,we achieve nodal integration over cells,eliminating the need for sophisticated mapping operations after re-meshing in the *** express the discretised governing equations as a min-max optimisation problem,which is further reformulated as a standard second-order cone programming(SOCP)***,pore water pressure,and displacements are simultaneously determined using the advanced primal-dual interior point ***,our numerical model offers improved accuracy for stresses and pore water pressure compared to the displacement-based PFEM *** experiments demonstrate that the N-PFEM efficiently captures both transient and long-term hydro-mechanical behaviour of saturated soils with high accuracy,obviating the need for stabilisation or regularisation techniques commonly employed in other nodal integration-based PFEM *** work holds significant implications for the development of robust and accurate numerical tools for studying saturated soil dynamics.

关键词： Particle finite element method Nodal integration Dynamic saturated media Second-order cone programming(SOCP)

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Stimulated Raman scattering tomography for rapid three-dimensional chemical imaging of cells and tissue

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Advanced Photonics 2024年第2期6卷 20-31页

作者： Weiqi Wang Zhiwei Huang National University of Singapore College of Design and EngineeringOptical Bioimaging LaboratoryDepartment of Biomedical EngineeringSingapore

Three-dimensional(3D)imaging is essential for understanding intricate biological and biomedical systems,yet live cell and tissue imaging applications still face challenges due to constrained imaging speed and strong scattering in turbid ***,we present a unique phase-modulated stimulated Raman scattering tomography(PM-SRST)technique to achieve rapid label-free 3D chemical imaging in cells and *** accomplish PM-SRST,we utilize a spatial light modulator to electronically manipulate the focused Stokes beam along the needle Bessel pump beam for SRS tomography without the need for mechanical z *** demonstrate the rapid 3D imaging capability of PM-SRST by real-time monitoring of 3D Brownian motion of polystyrene beads in water with 8.5 Hz volume rate,as well as the instant biochemical responses to acetic acid stimulants in MCF-7 ***,combining the Bessel pump beam with a longer wavelength Stokes beam(NIR-II window)provides a superior scattering resilient ability in PM-SRST,enabling rapid tomography in deeper tissue *** PM-SRST technique providestwofold enhancement in imaging depth in highly scattering media(e.g.,polymer beads phantom and biotissue like porcine skin and brain tissue)compared with conventional point-scan *** also demonstrate the rapid 3D imaging ability of PM-SRST by observing the dynamic diffusion and uptake processes of deuterium oxide molecules into plant *** rapid PM-SRST developed can be used to facilitate label-free 3D chemical imaging of metabolic activities and functional dynamic processes of drug delivery and therapeutics in live cells and tissue.

关键词： stimulated Raman scattering tomography deep tissue Raman imaging spatial light modulation

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