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检索条件"任意字段=9th International Conference on Computer Aided Design and Computer Graphics"

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design and Analysis of a Novel Hybrid Grasping Mode Microgripper for High Precision Tasks 9

Design and Analysis of a Novel Hybrid Grasping Mode Microgri...

引用

9th IEEE international Women in Engineering (WIE) conference on Electrical and computer Engineering, WIECON-ECE 2023

作者： Das, Tilok Kumar Shahrear, Rifat Das, Arpita Shirinzadeh, Bijan Dept. of Mechanical Engineering Chattogram Bangladesh Temple University Dept. of Electrical and Computer Engineering PhiladelphiaPA United States Monash University Robotics and Mechatronics Research Laboratory Dept. of Mechanical and Aerospace Engineering MelbourneVIC Australia

ISBN: (纸本)9798350319651

this paper represents a novel piezoelectric actuated flexure-based compliant microgripper which can perform both parallel and angular grasping regardless of the geometric surface of the objects. Two compliant bridge-type mechanisms along with two symmetrical microgripper jaws at the end of the two side arms are accommodated to construct the microgripper. the two side arms of the microgripper act as lever-type amplification mechanisms. Simultaneous actuation of two bridge-type mechanisms is needed to perform linearized parallel grasping. the symmetric design is adopted to maintain better stability. the Finite Element Analysis (FEA) has been performed to evaluate the performance of the microgripper. FEA shows that each jaw of the microgripper can achieve a displacement of 141.72 μm resulting in a total displacement of 283.44 μm with an amplification ratio of 10.7 and 0.715% parasitic motion in y-direction of the X -axis displacement during parallel grasping. Also, each jaw can achieve a displacement of 283.88 μm which results in a total displacement of 567.76 μm with an amplification ratio of 21.5 and 5.17 mrad angular rotation about the Z-axis during angular grasping. the FEA suggests that the microgripper is capable of both parallel and angular grasping/releasing tasks. © 2023 IEEE.

关键词： Piezoelectric actuators

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2024 IEEE Integrated STEM Education conference, ISEC 2024

2024 IEEE Integrated STEM Education Conference, ISEC 2024

引用

14th IEEE Integrated STEM Education conference, ISEC 2024

ISBN: (纸本)9798350352801

the proceedings contain 132 papers. the topics discussed include: healthy longevity: smart home in a smart city;beware the hype around information technology!;exploring EFL learners’ pausing and revision behaviors in a timed argumentative writing task;toward a framework for providing equitable opportunities to activate STEM talent;the mathematics of Kolam;reimagining the insulin pump user experience;the development and implementation of a cost-effective educational robotic arm using ROS-MoveIT;advancing bacterial mitigation on hospital floors: a stem-centric exploration;spiking neural network implementation for real-time DNA classification;designing ethical hacking training through game-based design for high school students (9th -12th grade);and design and implementation of a STEAM robotics lesson on the spotted lanternfly: engineering a computer science solution.

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Development Based on Mobile Application for Learning Mandarin Language 9

Development Based on Mobile Application for Learning Mandari...

引用

9th IEEE international conference on Computing, Engineering and design, ICCED 2023

作者： Sukmandhani, Arief Agus Suryadi Ohliati, Jenny Prabowo, Yulius Denny Bina Nusantara University Binus Online Learning Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350370126

Mandarin is being learned more and more over the years due to globalization. this has led some people to develop learning media to learn this language. One of the learning media that we usually see is YouTube, courses, and learning apps. Many Chinese learning apps are found only learning vocabulary, writing, and grammar. Learning Chinese requires an understanding of intonation and pronunciation as mistakes in pronunciation can lead to misunderstanding and meaning. therefore, this research aims to help someone in learning Chinese vocabulary, writing, grammar, intonation, and pronunciation. the system is developed on mobile to provide convenience and flexibility. this application is called WilChinese. this application is evaluated using blackbox and UAT (User Acceptance Test). this application has been tested with a series of blackbox tests have passed while for UAT 92% of respondents are satisfied using this application to learn mandarin. these results make the application can be a solution to solve problems and challenges that are often faced when learning Mandarin. © 2023 IEEE.

关键词： Acceptance tests

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Development Health Machine of Heavy Equipment Condition Monitoring System 9

Development Health Machine of Heavy Equipment Condition Moni...

引用

9th IEEE international conference on Computing, Engineering and design, ICCED 2023

作者： Arwoko, Deddy Suryo Baniara, Yordan Raharjo, Teguh Yossy, Emny Harna Bina Nusantara University BINUS Online Learning Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350370126

Monitoring the performance of machines is crucial because any damages that occur within the machines can result in losses and additional costs for the company. Currently, there are performance monitoring systems available for specific types of machines, such as excavators and dump trucks, provided by Komatsu under the names VHMS and Komtrax. However, these systems are not available for the GD825A-2 motor grader model. this research aims to implement an loT system to monitor the real-time condition of heavy equipment, facilitating and improving the analysis of the equipment's data. the research utilizes an experimental method by testing the loT system on heavy equipment in a real industrial environment. the system consists of sensors installed on the machines and a gateway connected to the internet. the sensor data is transmitted to the gateway and stored on a server, then analyzed and processed using machine learning algorithms to detect potential machine damage. the analysis results are displayed on a user dashboard that can be accessed online. the test results demonstrate that the loT system can accurately monitor machine conditions, help enhance operational efficiency, and reduce maintenance costs. © 2023 IEEE.

关键词： Condition monitoring

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Big Data Resource Allocation of Animation design Intelligent Education System Based on Ant Colony Algorithm 9th

Big Data Resource Allocation of Animation Design Intelligent...

引用

9th EAI international conference on e-Learning, e-Education, and Online Training, eLEOT 2023

作者： Wang, Nan Cui, Meng School of Information Engineering and Big Data Zhengzhou Technical College Zhengzhou450121 China

ISBN: (纸本)9783031514708

In order to solve the problems of low utilization rate of Big data resources and high cost of resource allocation in animation design intelligent education system, a method of Big data resource allocation in animation design intelligent education system based on Ant colony optimization algorithms was proposed. In this study, the big data resource allocation is formally described. the goal of maximizing resource utilization and the goal of minimizing the cost of big data resource allocation are combined to form a multi-objective allocation model of big data resources. Using genetic algorithm to improve ant colony algorithm and solve the multi-objective allocation model of big data resources, the optimal solution of big data resource allocation of animation design intelligent education system is obtained. the results show that the big data resource utilization rate of the allocation method studied is relatively higher and the allocation cost is relatively lower, which indicates that the allocation method studied by the Institute has better allocation capability. © ICST Institute for computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Big data

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DSNet: A Superior Real-Time Semantic Segmentation Model for Road Scenes 9

DSNet: A Superior Real-Time Semantic Segmentation Model for ...

引用

9th international conference on computer and Communications, ICCC 2023

作者： Yin, Zhenyu Shi, Xiaoqiang Zhang, Feiqing Xu, Guangyuan Qin, Li Li, Shurui Chinese Academy of Sciences Shenyang Institute of Computing Technology Shenyang China University of Chinese Academy of Sciences Shenyang China Liaoning Key Lab. of Domestic Industrial Control Platform Technology on Basic Hardware Software Shenyang China Shenyang Aerospace University School of Computer Science Shenyang China

ISBN: (纸本)9798350317251

A series of semantic segmentation models have achieved remarkable accuracy, but their high computational cost limits their practical applications in areas such as autonomous driving and robotics. Recently, some multi-branch real-time semantic segmentation models have been proposed to improve segmentation accuracy by introducing detail branches. However, there is a lack of auxiliary guidance in the design of detail branches, and there is a high computational cost problem in designing multi-branch information fusion modules. therefore, to address these issues, in this paper, we propose a real-time semantic segmentation model called DSNet, which achieves a good balance between speed and accuracy. DSNet consists of two branches: the detail branch and the semantic branch. the detail branch effectively extracts detail information by introducing edge loss as auxiliary supervision, while the semantic branch extracts deeper-level semantic information by increasing network depth and channel count. Finally, the fusion of detail and semantic information serves as the feature for predicting the segmentation map. To fuse the detail and semantic information, we design a novel feature fusion module called LSAF, which efficiently integrates features from different branches with low computational costs. Our method achieves a speed of 152.3 FPS with an accuracy of 72.8% on the CityScapes test dataset. © 2023 IEEE.

关键词： Semantic Segmentation

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3D Human Pose Estimation via Graph Extended Spatio-Temporal Convolutional Network 9

3D Human Pose Estimation via Graph Extended Spatio-Temporal ...

引用

9th international conference on Virtual Reality, ICVR 2023

作者： Jia, Yanhui Fan, Wanshu Zhou, Dongsheng Zhang, Qiang Dalian University National and Local Joint Engineering Laboratory of Computer Aided Design School of Software Engineering Dalian China

ISBN: (纸本)9798350345810

3D human pose estimation is an important premise for human behavior analysis and understanding, which has a wide range of applications in intelligent transportation, human-computer interaction, and animation production. Most existing works focus on extracting the feature relationship between frames by combining spatio-temporal information to reduce the error of attitude reconstruction. However, the majority of them often suffer from insufficient joint correlation characteristics. To address this problem, we propose a Graph Expand Spatiotemporal Convolutional Network, named GESC-Net, to improve the limitation of extracting human spatial structure features. To better enrich the feature of extracting local information, we develop a learnable symmetric connection (LSC) block in the spatial structure. Moreover, a CbAttantion block is also designed to obtain a larger view of the acquisition of global structure and get more effective features. We evaluate our approach on two standard benchmark datasets: Human3.6M and HumanEva-I. the quantitative and qualitative evaluation results demonstrate that the GESC-Net can achieve better 3D human posture estimation than existing state-of-the-art methods. © 2023 IEEE.

关键词： Convolution

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PSA-CLNet: Pedestrian Search Method Based on Polarized Self-Attention and COIM Loss 9

PSA-CLNet: Pedestrian Search Method Based on Polarized Self-...

引用

9th international conference on Virtual Reality, ICVR 2023

作者： Fu, Junjie Liu, Rui Yi, Pengfei Dong, Jing Zhou, Dongsheng Wei, Xiaopeng Dalian University National and Local Joint Engineering Laboratory of Computer Aided Design School of Software Engineering Dalian China Dalian University of Technology School of Computer Science and Technology Dalian China

ISBN: (纸本)9798350345810

Pedestrian search is a combined task of pedestrian detection and pedestrian re-identification, i.e., how to find a specific pedestrian in a panoramic picture. However, due to the impact of different imaging conditions and environments, the accuracy of pedestrian search is still low at present, which is difficult to meet the needs of practical applications. To improve the accuracy of pedestrian search, this paper proposes PSA-CLNet pedestrian search method, which integrates polarized self-attention mechanism (PSA) and cosine online instance matching (COIM) loss. Firstly, the channel attention is added to enhance the pedestrian feature information and improve the expression ability of the feature information. Secondly, spatial attention is added to enhance the areas that have more contribution to the pedestrian search task to increase the correlation between the pictures and improve the recognition ability. Meanwhile, this paper proposes a COIM loss based on the online instance matching (OIM) loss. the loss function can enlarge the class distance between pedestrians and background, and reduce the class distance between pedestrians. this could improve the accuracy of pedestrian search algorithm effectively. Finally, this paper uses ResNet as the main backbone network to verify the proposed method. the pedestrian search method proposed in this paper could achieve 96.60% of mAP index and 96.83% of top-1 index in CUHK-SYSU dataset, and achieve 48.78% of mAP index and 88.38% of top-1 index in PRW dataset. © 2023 IEEE.

关键词： COIM loss pedestrian search PSA

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Fine-tuning Specialized NER Model for Symptom Extraction from Slovenian Medical Texts 9

Fine-tuning Specialized NER Model for Symptom Extraction fro...

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9th international conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Sallauka, Rigon Arioz, Umut Mlakar, Izidor University of Maribor Faculty of Electrical Engineering and Computer Science Laboratory of Digital Signal Processing Maribor Slovenia

ISBN: (纸本)9798350377224

In this study, we aim to develop a robust model capable of accurately extracting symptoms from clinical texts written in the Slovenian language. Our methodology involves several steps to achieve this objective. Initially, we identify datasets containing clinical texts in English and select a specialized model designed for symptom extraction from these texts. then, we annotate the datasets and undertake the translation process into Slovenian, ensuring the preservation of annotations to maintain data integrity. Utilizing the translated dataset, we proceed to fine-tune the selected model specifically for Slovenian texts. Despite our efforts, optimal performance has not yet been attained. Challenges encountered include the translation methodology employed and the architectural limitations of the chosen model, which is primarily optimized for English texts. However, ongoing efforts are underway to address these challenges and enhance the model's performance. Our study represents a step towards improving automated symptom extraction in Slovenian clinical texts, with ongoing work focused on mitigating identified issues to achieve better outcomes. © 2024 IEEE.

关键词： Machine translation

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Exploring Feature Uncertainty in Occluded Person Re-Identification via Entropy-Guided Fusion 9

Exploring Feature Uncertainty in Occluded Person Re-Identifi...

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9th IEEE international conference on Computational Intelligence and Applications, ICCIA 2024

作者： Li, Yanping Miao, Duoqian Yu, Feng Tongji University Department of Computer Science and Technology Shanghai China Guotai Junan Securities Department of Information Technology Shanghai China

ISBN: (纸本)9798350352214

Occlusion poses a considerable challenge in person re-identification. the Transformer architrecutre, with its longrange dependency capabilities, has an advantage in addressing occlusion issues. In this paper, we build on the Transformer back-bone, and propose a novel network termed EFusion. Specifically, to extract diverse pedestrian features, a multi-head attention module is utilized to map the input data into multiple subspaces. Given that attention patterns learned by different heads vary, with some focusing on visible parts and others capturing occluded areas, we propose an entropy-guided head fusion module, which dynamically adjusts the weights in accordance with the attention distribution of each head to obtain more distinctive pedestrian features. Meanwhile, to enlarge the variance among the heads, we design a diversity loss, using KL divergence to encourage the model to learn more diverse attention patterns, thereby making the class token learn the most salient pedestrian features. Additionally, we propose an auxiliary feature extraction module to learn fine-grained pedestrian features. Experimental results on occluded person re-identification datasets demonstrate the effectiveness of our method. © 2024 IEEE.

关键词： Feature extraction

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