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2nd International Conference on Applied Intelligence, ICAI 2024

作者： Huang, Lei Cai, Hongguo Peng, Yuzhong Liao, Jianping Guangxi Key Laboratory of Human-Computer Interaction and Intelligent Decision-Making School of Computer and Information Engineering Nanning Normal University Guangxi Nanning530100 China Guangxi Academy of Sciences Guangxi Nanning530007 China

ISBN: (纸本)9789819619030

This paper addresses the challenges of mobile traffic sign detection in dynamic environments by proposing a lightweight model, RePCMA-YOLOv8n, to enhance feature extraction efficiency and detection performance. The RePCMA module integrates Partial Convolution (PConv), re-parameterization strategies, and multi-scale attention mechanisms (EMA), effectively reducing redundancy in feature extraction to lower the number of parameters and floating-point operations, thereby improving overall model performance. Specifically, to tackle the common issue of varying target sizes in traffic sign detection, this study introduces the Normalized Wasserstein Distance (NWD) as an optimization loss function, significantly enhancing the model’s detection accuracy for targets of different sizes. The model demonstrates exceptional adaptability across various scenarios. Experimental results show that on the LISA dataset, the algorithm achieved an mAP50 of 97.9%, and its outstanding performance was further validated on seven other public datasets using mAP50 and mAP50-90 metrics. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolution

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VAction: A Lightweight and Integrated VR Training System for Authentic Film-Shooting Experience 25

VAction: A Lightweight and Integrated VR Training System for...

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Proceedings of the 2025 CHI Conference on human Factors in Computing Systems

作者： Shaocong Wang Che Qu Minjing Yu Chao Zhou Yuntao Wang Yu-Hui Wen Yuanchun Shi Yong-Jin Liu Department of Computer Science and Technology Tsinghua University Beijing China Film & TV Technology Department Beijing Film Academy Beijing Beijing China College of Intelligence and Computing Tianjin University Tianjin China Human Computer Interaction Technology and Intelligent Information Processing Laboratory Institute of Software Chinese Acadamy of Sciences Beijing China School of Computer Science and Technology Beijing Jiaotong University Beijing China Department of Computer science and Technology Tsinghua University Beijing China Computer Science and Technology Tsinghua University Beijing Beijing China

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Mem Brain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction

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Nano-Micro Letters 2018年第1期10卷 12-19页

作者： Xi Yin Jing Yang Feng Xiao Yang Yang Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Computer Science Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering

Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels,transporters, receptors. Because it is difficult to determinate the membrane protein's structure by wet-lab experiments,accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called Mem Brain, whose input is the amino acid sequence. Mem Brain consists of specialized modules for predicting transmembrane helices, residue–residue contacts and relative accessible surface area of a-helical membrane proteins. Mem Brain achieves aprediction accuracy of 97.9% of ATMH, 87.1% of AP,3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. Mem BrainContact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction,respectively. And Mem Brain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of13.593. These prediction results provide valuable hints for revealing the structure and function of membrane *** Brain web server is free for academic use and available at ***/bioinf/Mem Brain/.

关键词： Transmembrane a-helices Structure prediction Machine learning Contact map prediction Relative accessible surface area

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Experimental Study on Motion Controller based on NN-ARX and ARMAX Actuator Identification for 3-DoF Delta Parallel Robot 11

Experimental Study on Motion Controller based on NN-ARX and ...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Jalali, Hasan Damavandi, Hossein Kalhor, Ahmad Masouleh, Mehdi Tale University of Tehran Human and Robot Interaction Laboratory School of Electrical and Computer Engineering Tehran Iran Sadjad University Faculty of Computer Engineering and Information Technology Mashhad Iran University of Tehran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Tehran Iran

ISBN: (纸本)9798350308105

Today, system identification plays a pivotal role in control science and offering a myriad of applications. This paper places its focus on the identification of actuator models within real-world delta robots for informing controller design. Two identification methods, namely NN-ARX and ARMAX, have been employed to extract the dynamic characteristics of the robot actuators, resulting in dynamic models of these integral components being derived. These dynamic models have been utilized in simulations for controller design, and due to the disparities in the identification models, distinct controllers have been realized. Subsequently, these controllers have been practically implemented on delta robots, and their performances have been subjected to a comprehensive comparative analysis. The results demonstrate that controllers integrating the identified actuator models outperformed those designed without the incorporation of the identification models. In practice, the implementation of controllers based on NN-ARX yielded the most favorable results among all the tested controllers. This research not only underscores the importance of accurate actuator models in control system design but also highlights the superior performance of neural network-based controllers in real-world robotic applications. In particular, the practical results of NN-ARX-based controllers were able to achieve significantly lower RMSE of 2.3562, 1.9531, and 2.1185 for the three motors, respectively, as opposed to the 4.1369, 3.0125, and 3.0363 achieved by the ARMAX-based controllers. © 2023 IEEE.

关键词： Controllers

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Capturing Invisible Design: Modeling Multi-modal interaction in Pervasive Computing

Capturing Invisible Design: Modeling Multi-modal Interaction...

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International Conference on Pervasive Computing and Applications (ICPCA)

作者： Cuixia Ma Guozhong Dai Hongan Wang Human-computer Interaction and Intelligent information Processing Laboratory Institute of Software Chinese Academy and Sciences Beijing China

As technologies are rapidly evolving in the area of storage, recognition and displays, the vision of multi-modal interaction is positioning the human needs central to pervasive access to services. Users expect better looking interfaces that are also easy to use to improve high efficiency and productivity and to focus on task itself instead of tools as providing the invisibility in pervasive computing. However, it is hard to obtain the right service at the right time naturally in the multimedia environment based on current interaction approaches. In this paper, we propose a framework for multi-modal interaction which offers the sketch and speech interactive models without limitation of the diversity and richness of the provided services in the pervasive computing environment. Furthermore, it is applied to describe sample application and shows how it is used to create a new interface with high performance

关键词： Pervasive computing Application software Speech Real time systems Embedded system Logic Embedded computing humans Process design Keyboards

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Evaluating tagging behavior in social bookmarking systems: Metrics and design heuristics 07

Evaluating tagging behavior in social bookmarking systems: M...

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2007 International ACM Conference on Supporting Group Work, GROUP'07

作者： Farooq, Umer Kannampallil, Thomas G. Song, Yang Ganoe, Craig H. Carroll, John M. Giles, Lee Computer-Supported Collaboration and Learning Laboratory Center for Human-Computer Interaction United States Intelligent Systems Research Laboratory College of Information Sciences and Technology Pennsylvania State University University Park PA 16802 United States

ISBN: (纸本)9781595938459

To improve existing social bookmarking systems and to design new ones, researchers and practitioners need to understand how to evaluate tagging behavior. In this paper, we analyze over two years of data from CiteULike, a social bookmarking system for tagging academic papers. We propose six tag metrics-tag growth, tag reuse, tag non-obviousness, tag discrimination, tag frequency, and tag patterns-to understand the characteristics of a social bookmarking system. Using these metrics, we suggest possible design heuristics to implement a social bookmarking system for CiteSeer, a popular online scholarly digital library for computer science. We believe that these metrics and design heuristics can be applied to social bookmarking systems in other domains. © 2007 ACM.

关键词： Digital libraries

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Research on Differential Power Analysis of Lightweight Block Cipher LED 10th

Research on Differential Power Analysis of Lightweight Block...

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10th International Conference on computer Engineering and Networks, CENet 2020

作者： Zou, Yi Li, Lang Zhao, Hui-huang Jiao, Ge College of Computer Science and Technology Hengyang Normal University Hengyang421002 China Human Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002 China

ISBN: (纸本)9789811584619

LED algorithm is a new lightweight encryption algorithm proposed in CHES 2011, which is used for IOT to protect the communication security of RFID tags and smart cards. It has been found that it is possible to retrieve secret key of algorithm by appropriate analysis of the devicess power consumption, and the differential power analysis is the most powerful attack. This paper proposed a method of differential power analysis on LED algorithm. Combined with hardware circuit, it designed and implemented differential power analysis of the LED encryption system. The experimental results show that method which is proposed in this paper was cracked the 64 bits key of LED. Thus, without protection, the cipher LED would be difficult to resist differential power analysis. and according this, We provide a general analysis method of differential power analysis on other lightweight cryptographic algorithms. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Light emitting diodes

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Tangible augmented user interface for interactive simulation of the jaw motion

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Journal of information and Computational Science 2008年第5期5卷 2071-2076页

作者： Ji, Lianen Lu, You Zhang, Fengjun Department of Computer Science and Technology China University of Petroleum Beijing 102249 China Laboratory of Human-Computer Interaction and Intelligent Information Processing Institute of Software Chinese Academy of Sciences Beijing 100080 China

This paper presents a novel 3D interactive system for simulation and visualization of the human jaw motion. Based on the visual tracking technique, teeth plaster cast and marker cards is used for manipulating virtual teeth model and controlling the simulation of jaw motion. Through introducing their interactive semantic attributes, these physical interface elements are classified into various interaction types. Furthermore, various interaction tasks and techniques are seamlessly merged into a uniform interface framework, which integrates physical space with virtual space together. This innovative 3D interface can effectively exploit the dentist's existing skills and provide more intuitive and natural 3D interaction techniques than traditional ones. 1548-7741/Copyright © 2008 Binary information Press October 2008.

关键词： Augmented reality

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Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus

Generating high-coverage semantic orientation lexicons from ...

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2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Mohammad, Saif Dunne, Cody Dorr, Bonnie Laboratory for Computational Linguistics and Information Processing University of Maryland United States Human-Computer Interaction Lab. University of Maryland United States Institute for Advanced Computer Studies University of Maryland United States Department of Computer Science University of Maryland United States Human Language Technology Center of Excellence United States

Sentiment analysis often relies on a semantic orientation lexicon of positive and negative words. A number of approaches have been proposed for creating such lexicons, but they tend to be computationally expensive, and usually rely on significant manual annotation and large corpora. Most of these methods use WordNet. In contrast, we propose a simple approach to generate a high-coverage semantic orientation lexicon, which includes both individual words and multi-word expressions, using only a Roget-like thesaurus and a handful of affixes. Further, the lexicon has properties that support the Polyanna Hypothesis. Using the General Inquirer as gold standard, we show that our lexicon has 14 percentage points more correct entries than the leading WordNet-based high-coverage lexicon (SentiWordNet). In an extrinsic evaluation, we obtain significantly higher performance in determining phrase polarity using our thesaurus-based lexicon than with any other. Additionally, we explore the use of visualization techniques to gain insight into the our algorithm beyond the evaluations mentioned above. © 2009 ACL and AFNLP.

关键词： Thesauri

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FasterPlateNet: A Faster Deep Neural Network for License Plate Detection and Recognition 1st

FasterPlateNet: A Faster Deep Neural Network for License Pla...

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1st International Conference on Applied Intelligence, ICAI 2023

作者： Huang, Lei Huang, De Shuang Chen, Yuan Yuan Peng, Yu Zhong Wang, Chao Liao, Jianping Guangxi Key Laboratory of Human-Computer Interaction and Intelligent Decision-Making School of Computer and Information Engineering Nanning Normal University Guangxi Nanning530100 China Guangxi Academy of Sciences Guangxi Nanning530007 China School of Electronic and Information Engineering Tongji University Shanghai201804 China

ISBN: (纸本)9789819709021

License plate recognition is an important technology for vehicle management. However, the existing methods based on traditional image processing or deep learning have limitations in accuracy and efficiency. In this paper, we propose a novel method for license plate detection and recognition, called FasterPlateNet. FasterPlateNet consists of two stages: detection localization and character recognition. In the detection localization stage, it employs a backbone network with stacked C3_Faster modules and a one-stage object detection algorithm with a multi-scale feature fusion pyramid to extract multi-scale features of the license plate, and enhances the resolution and global feature dependency of the feature map by using the content-aware feature reassembly (CARAFE) algorithm and the exposed visual center (EVC) module. In the character recognition stage, it adopts a character recognition network with a convolutional neural network and a connectionist temporal classification loss function, which can directly output the character sequence from the license plate image without character segmentation. The experimental results on the CPPD dataset and its subsets demonstrate that our method achieves 98.8% and 98.5% accuracy in detection localization and recognition respectively. This method has great potential and value in practical applications. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep neural networks

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