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检索条件"任意字段=11th International Conference on Computer-Aided Design and Computer Graphics"

共 8468 条记录，以下是491-500 订阅

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Can Electromyography and Subjective Metrics Work Better Together? Exploring Dynamic Muscle Fatigue to Promote the design of Health and Fitness Technology 11th

Can Electromyography and Subjective Metrics Work Better Toge...

引用

11th international conference on design, User Experience, and Usability (DUXU) Held as Part of the 24th international conference on Human-computer Interaction (HCII)

作者： Zhang, Lanyun He, Yan Zhu, Haiou Nanjing Univ Aeronaut & Astronaut 29 Yudao St Nanjing 210016 Peoples R China Loughborough Univ Epinal Way Loughborough L11 3TU Leics England

ISBN: (纸本)9783031059001;9783031058998

the assessment of local muscle fatigue during dynamic exercises is viewed as essential, since people tend to maximise effective muscle training and minimise harmful muscle injuries. this study aims to investigate how surface electromyography (sEMG) and subjective metrics together can play a role in dynamic muscle fatigue prediction during exercises to promote the design of health and fitness technology. 20 healthy male participants were recruited in the experiment, and sEMG and self-reported data were collected. Features in temporal and spatial domain were extracted from sEMG data, such as RMS (root mean square) and FInsm5 (spectral parameter proposed by Dimitrov). Our results showed that some sEMG features indicated directional changes with the increase of dynamic muscle fatigue. Spearman correlation analysis indicated that Borg ratings had strong correlations with RMS and FInsm5 (spectral parameter proposed by Dimitrov) slopes. then this paper discusses how to use sEMG and Borg data to evaluate muscle fatigue during exercises. A framework is proposed based on the joint analysis of spectra and amplitudes across RMS and FInsm5 slopes. this paper further discusses how to design health and fitness technology for the benefits and the limitations of the study.

关键词： Subjective metrics Electromyography Muscle fatigue design Fitness technology

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***: A Deep Learning System for Digital Smile design 11

***: A Deep Learning System for Digital Smile Design

引用

11th IEEE international conference on Intelligent Computing and Information Systems, ICICIS 2023

作者： Khaled Ali, Ganna Allah Abdelbadei, Khloud Aboelhasan Essam, Mohammad Gamal, Riham Essam Mohamed, Taghreed Samir Al-Berry, Maryam Nabil Nabil, Sarah Hatem Said, Amr Mohamed Ain Shams University Bioinformatics Department Computer and Information Science Cairo Egypt Ain Shams University Scientific Computing Department Computer and Information Science Cairo Egypt

ISBN: (纸本)9798350322101

Digital Smile design (DSD) is an advanced technique that enables dentists to create customized treatment plans for each patient by creating a digital representation of their desired smile. this approach promotes collaboration between dentists and patients to meet individual needs and goals. Special software like DSD allows dentists to plan treatments more precisely and achieve the patient's desired outcome. *** is an application inspired by DSD, which utilizes machine learning, deep learning, and image processing to simulate a desired *** helps patients participate in the smile creation process and allows for more predictable outcomes, improving patient acceptance of suggested treatment plans. *** also helps dentists to simplify the connection with their patients, educate them about the benefits of treatment, and trying to reduce patient reluctance. the first approach is based on image segmentation using a segmentation model. Unet++, MAnet, DeepLabv3+, FPN, while the second approach is based on ControlNet, ControlNet is a type of neural network architecture that controls diffusion models by introducing additional constraints. this innovation represents a major advance in the field of AI imaging as it allows excellent control over stable diffusion ControlNet is growing in popularity for several reasons. First, it produces high-quality output with better control compared to other methods like depth-to-image. Second, it is highly efficient and requires significantly less training time than traditional approaches. Finally, ControlNet prevents overfitting. Overall, *** is a revolutionary tool that can improve the quality of dental treatments and patient satisfaction. © 2023 IEEE.

关键词： Image segmentation

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Analysis and design Optimization of Surface Permanent Magnet Motor to Improve Torque Density and Ripple 11

Analysis and Design Optimization of Surface Permanent Magnet...

引用

11th international conference on Power Electronics - ECCE Asia, ICPE 2023-ECCE Asia

作者： Shakhin, Yussuf Talapiden, Kulash Minh thao, Nguyen Gia Bagheri, Mehdi Duc Do, Ton Department of Robotics and Mechatronics AstanaZ05H0P9 Kazakhstan Toyota Technological Institute Graduate School of Engineering Japan Department of Electrical and Computer Engineering AstanaZ05H0P9 Kazakhstan

ISBN: (纸本)9788957083505

Small-scale permanent magnet motor to reach high torque density and low torque ripple is discussed in this research. To increase the torque density, meanwhile making the motor size smaller and lighter, the motor axial length within a constrained diameter is optimized in view of various pole-slot configurations. Different slot-poles are selected and various combinations are studied, and the stator windings are optimized. To compare the torque density and ripple of new designs, precise models are created and simulated through ANSYS Maxwell 2D FEA under constant operational conditions, such as rated speed, torque, and power. Over the new designs, the influence of loss and temperature distribution variations in motor elements are analyzed. the simulation results show that the proposed 20-pole 18-slot motor design will obtain superior torque density and lower torque ripple compared to the baseline design. the final design provides a 30.7 % improvement of the torque density within the same rated torque condition. © 2023 the Korean Institute of Power Electronics.

关键词： Finite element method

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NEUROMECHANICAL AUTOENCODERS: LEARNING TO COUPLE ELASTIC AND NEURAL NETWORK NONLINEARITY 11

NEUROMECHANICAL AUTOENCODERS: LEARNING TO COUPLE ELASTIC AND...

引用

11th international conference on Learning Representations, ICLR 2023

作者： Oktay, Deniz Mirramezani, Mehran Medina, Eder Adams, Ryan P. Department of Computer Science Princeton University United States

Intelligent biological systems are characterized by their embodiment in a complex environment and the intimate interplay between their nervous systems and the nonlinear mechanical properties of their bodies. this coordination, in which the dynamics of the motor system co-evolved to reduce the computational burden on the brain, is referred to as "mechanical intelligence" or "morphological computation". In this work, we seek to develop machine learning analogs of this process, in which we jointly learn the morphology of complex nonlinear elastic solids along with a deep neural network to control it. By using a specialized differentiable simulator of elastic mechanics coupled to conventional deep learning architectures-which we refer to as neuromechanical autoencoders-we are able to learn to perform morphological computation via gradient descent. Key to our approach is the use of mechanical metamaterials-cellular solids, in particular-as the morphological substrate. Just as deep neural networks provide flexible and massively-parametric function approximators for perceptual and control tasks, cellular solid metamaterials are promising as a rich and learnable space for approximating a variety of actuation tasks. In this work we take advantage of these complementary computational concepts to co-design materials and neural network controls to achieve nonintuitive mechanical behavior. We demonstrate in simulation how it is possible to achieve translation, rotation, and shape matching, as well as a "digital MNIST" task. We additionally manufacture and evaluate one of the designs to verify its real-world behavior. © 2023 11th international conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Deep neural networks

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A design Ranking Method for Many-Objective Evolutionary Optimization 20th

A Design Ranking Method for Many-Objective Evolutionary Opti...

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20th international conference on computer-aided Architectural design Futures, CAAD Futures 2023

作者： Wang, Likai Tung, Do Phuong Bui Janssen, Patrick Xi’an Jiaotong – Liverpool University Suzhou China National University of Singapore 21 Lower Kent Ridge Road Singapore Singapore Packhunt Amsterdam Netherlands

ISBN: (纸本)9783031371882

this study presents a design ranking method for evolutionary optimization that is aimed to address design optimization problems with many performance-related evaluation metrics. the application of the method consists of three strategies. First, all evaluation scores are expressed as percentages that indicate the proportion of the design achieving acceptable performance. Second, related evaluation scores are grouped, and for each group, a combined score is calculated using a weighted product approach. third, design populations are evolved using the Pareto optimization of the combined evaluation scores. the combination of the three steps helps designers to define and organize the design evaluation metrics and can also produce optimization results revealing meaningful information. A case study is presented to demonstrate the efficacy of the proposed design ranking method. the relevance of the proposed method to performance-based evolutionary optimization research is also discussed. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Pareto principle

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WHY (AND WHEN) DOES LOCAL SGD GENERALIZE BETTER thAN SGD? 11

WHY (AND WHEN) DOES LOCAL SGD GENERALIZE BETTER THAN SGD?

引用

11th international conference on Learning Representations, ICLR 2023

作者： Gu, Xinran Lyu, Kaifeng Huang, Longbo Arora, Sanjeev Institute for Interdisciplinary Information Sciences Tsinghua University China Department of Computer Science Princeton University United States

Local SGD is a communication-efficient variant of SGD for large-scale training, where multiple GPUs perform SGD independently and average the model parameters periodically. It has been recently observed that Local SGD can not only achieve the design goal of reducing the communication overhead but also lead to higher test accuracy than the corresponding SGD baseline (Lin et al., 2020b), though the training regimes for this to happen are still in debate (Ortiz et al., 2021). this paper aims to understand why (and when) Local SGD generalizes better based on Stochastic Differential Equation (SDE) approximation. the main contributions of this paper include (i) the derivation of an SDE that captures the long-term behavior of Local SGD in the small learning rate regime, showing how noise drives the iterate to drift and diffuse after it has reached close to the manifold of local minima, (ii) a comparison between the SDEs of Local SGD and SGD, showing that Local SGD induces a stronger drift term that can result in a stronger effect of regularization, e.g., a faster reduction of sharpness, and (iii) empirical evidence validating that having a small learning rate and long enough training time enables the generalization improvement over SGD but removing either of the two conditions leads to no improvement. © 2023 11th international conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Stochastic systems

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A PSO and Random Forest-based Hybrid Model for Effective Intrusion Detection 11

A PSO and Random Forest-based Hybrid Model for Effective Int...

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11th international conference on Intelligent Systems and Embedded design, ISED 2023

作者： Murari, Krishan Singh, Sunil Kumar Mahatma Gandhi Central University Dept. of Computer Science and Information Bihar Motihari India

ISBN: (纸本)9798350318159

Recent technological advances have led to the need to store information electronically, which is why information security has become an increasingly important issue in recent years. Traditional intrusion detection takes care of unusual activity. It is crucial to improve the true positive while reducing false positives to having a trustworthy IDS in a network. We present a methodology intrusion detection system (IDS) that relies on machine learning classifiers and multi-objective PSO in our proposed model. the KDDCUP99 dataset is picked up as an input for evaluating the outcome of the proposed model. Based on the performance analysis and the comparative study, it can be concluded that the model is valid. PSO-RF proposed model gives better classification accuracy compared with DT, KNN, SVM, and Naïve Bayes and the highest Gbest value with maximum TPR and minimum FPR. © 2023 IEEE.

关键词： Nonlinear programming

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MULTI-LEVEL PROTEIN STRUCTURE PRE-TRAINING WIth PROMPT LEARNING 11

MULTI-LEVEL PROTEIN STRUCTURE PRE-TRAINING WITH PROMPT LEARN...

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11th international conference on Learning Representations, ICLR 2023

作者： Wang, Zeyuan Zhang, Qiang Yu, Haoran Hu, Shuangwei Jin, Xurui Gong, Zhichen Chen, Huajun College of Computer Science and Technology Zhejiang University China ZJU-Hangzhou Global Scientific and Technological Innovation Center China College of Chemical and Biological Engineering Zhejiang University China Vecx Biomedicines Inc. MindRank AI Ltd. University College London United Kingdom AZFT Joint Lab for Knowledge Engine China East China Sea Laboratory China

A protein can focus on different structure levels to implement its functions. Each structure has its own merit and driving forces in describing specific characteristics, and they cannot replace each other. Most existing function prediction methods take either the primary or the tertiary structure as input, unintentionally ignoring the other levels of protein structures. Considering protein sequences can determine multi-level structures, in this paper, we aim to realize the comprehensive potential of protein sequences for function prediction. Specifically, we propose a new prompt-guided multi-task pre-training and fine-tuning framework. through the prompt-guided multi-task pre-training, we learn multiple prompt signals to steer the model, called PromptProtein, to focus on different levels of structures. We also design a prompt fine-tuning module to provide downstream tasks the on-demand flexibility of utilizing respective levels of structural information. Extensive experiments on function prediction and protein engineering show that PromptProtein outperforms state-of-the-art methods by large margins. To the best of our knowledge, this is the first prompt-based pre-trained protein model. © 2023 11th international conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Proteins

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Expedited Machine-Learning-Based Global design Optimization of Antenna Systems Using Response Features and Multi-fidelity EM Analysis 24th

Expedited Machine-Learning-Based Global Design Optimization ...

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24th international conference on Computational Science (ICCS)

作者： Pietrenko-Dabrowska, Anna Koziel, Slawomir Leifsson, Leifur Gdansk Univ Technol Fac Elect Telecommun & Informat Narutowicza 11-12 PL-80233 Gdansk Poland Reykjavik Univ Engn Optimizat & Modeling Ctr Dept Engn Menntavegur 1 IS-102 Reykjavik Iceland Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47907 USA

ISBN: (纸本)9783031637742;9783031637759

the design of antenna systems poses a significant challenge due to stringent performance requirements dictated by contemporary applications and the high computational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. the latter stage is especially critical as rigorous numerical optimization becomes essential for achieving optimal performance. In an increasing number of instances, global parameter tuning is necessary. Unfortunately, the use of nature-inspired algorithms, the prevalent choice for global design, is hindered by their poor computational efficiency. this article presents an innovative approach to cost-efficient global optimization of antenna input characteristics. Our methodology leverages response feature technology, ensuring inherent regularization of the optimization task by exploring the nearly-linear dependence between the coordinates of feature points and the antenna's dimensions. the optimization process is structured as a machine learning (ML) procedure, utilizing a kriging surrogate model rendering response features to generate promising candidate designs (infill points). this model is iteratively refined using accumulated EM simulation data. Further acceleration is achieved by incorporating multi-fidelity EM analysis, where initial sampling and surrogate model construction use low-fidelity EM simulations, and the ML optimization loop employs high-fidelity EM analysis. the multi-fidelity EM simulation data is blended into a single surrogate using co-kriging. Extensive verification of the presented algorithm demonstrates its remarkable computational efficiency, with an average running cost not exceeding ninety EM simulations per run and up to a seventy percent relative speedup over the single-fidelity procedure.

关键词： Antenna design global optimization computer-aided design response features bio-inspired algorithms variable-fidelity EM analysis

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design and Implementation of Power Supply and Distribution System for Mars Landing Mission 1

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11th EAI international conference on MOBILe Wireless MiddleWARE, Operating Systems and Applications, MOBILWARE 2022

作者： Chen, Yan Yang, Dong Shi, Hai Ping Tang, Cheng Xiong Beijing Institute of Spacecraft System Engineering Beijing China

ISBN: (数字)9783031344978

ISBN: (纸本)9783031344961

Combined with the characteristics of Mars exploration mission, the functions, main indicators and system schemes of the power supply and distribution subsystem of China’s first Mars landing and rover mission are briefly introduced, and the design of high-specific energy lithium fluorocarbon batteries, the design of Mars solar spectrum-matched solar cells, the design of dust-proof coating, the design of MPPT, the estimation and management of on-orbit capacity, etc. are briefly introduced, and the design problems of power supply and distribution systems in the extreme environment of Mars landing and rover mission are proposed. the results of the on-orbit flight test show that the power supply and distribution system has normal function, reliable work and excellent performance, and the design scheme of the power supply and distribution system proposed for the landing and rover mission has successfully supported China’s first interplanetary exploration mission. through the design and implementation of this project, a large amount of valuable experience and data have been accumulated, which provides a high scientific and engineering reference value for the design and verification of power supply and distribution systems for subsequent Mars sampling and return missions. © 2023, ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Solar cells

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