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检索条件"任意字段=25th Conference on Innovation and Technology in Computer Science Education"

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A DMA Interruption Mechanism for Multi-Robot Communication and Location 4

A DMA Interruption Mechanism for Multi-Robot Communication a...

引用

2019 4th Annual International conference on Information System and Artificial Intelligence, ISAI 2019

作者： Zeng, Xiangjin Huang, Le Jin, Zilong Zhang, Like School of Computer Science and Engineering Wuhan Institute of Technology Hubei province Wuhan city430205 China

For multi-robot communication and positioning in lunar environment, we put forward an improved MOBUS-RTU communication networking protocol. the protocol adopts the cooperation mechanism, whichuses the sending and receiving of Direct Memory Access (DMA) and idle interruption of DMA. the data length is not limited for communication. Besides, the message is automatically stored in the cache and processed after receiving. this method greatly improves the utilization efficiency of the CPU. Finally, the corresponding communication and positioning test platform is developed based on STM32f103, which the system communication, positioning accuracy, packet loss rate and other experimental tests are carried out. the results show that the design meets the application requirements. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Multipurpose robots

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Detection of liver tumor candidates from CT images using deep convolutional neural networks 5th

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5th KES International conference on innovation in Medicine and Healthcare, InMed-17 2017

作者： Todoroki, Yoshihiro Han, Xian-Hua Iwamoto, Yutaro Lin, Lanfen Hu, Hongjie Chen, Yen-Wei Information Science and Engineering Ritsumeikan University Shiga Japan Faculty of Science Yamaguchi University Yamaguchi Japan College of Computer Science and Technology Zhejiang University Hangzhou China Radiology Department Sir Run Run Shaw Hospital Medical School Zhejiang University Hangzhou China

ISBN: (纸本)9783319593968

there are multiple types of tumors occurring in the liver. Different tumors have different visual appearance and their visual appearance changes after injection of the contrast medium. So detection of liver tumors is considered as a challenging task. In this paper, we propose a method for detection of liver tumor candidates from CT images using a deep convolutional neural network. Experimental results show that we can significantly improve the detection accuracy by using our proposed method compared with the previous researches. © Springer International Publishing AG 2018.

关键词： Tumors

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An Evaluation of the UIT-VSFC Dataset Using Modern Machine Learning Techniques and Word Embeddings

An Evaluation of the UIT-VSFC Dataset Using Modern Machine L...

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International computer science and Engineering conference (ICSEC)

作者： Quýnh Dương Vũ Xuân Kanjana Laosen Nasith Laosen School of Industrial Engineering and Management International University - Vietnam National University Ho Chi Minh City Ho Chi Minh City Vietnam AI-TaSI Center College of Computing Prince of Songkla University Phuket Campus Phuket Thailand Faculty of Science and Technology Phuket Rajabhat University Phuket Thailand

ISBN: (纸本)9781665411981

Feedback from students during the course and upon course completion has become a powerful resource to improve teaching quality and enhance student's learning experience. However, the available data for free use is limited, especially for a low-resource language like Vietnamese. Currently, there is only one dataset in the education domain, called the Vietnamese Students’ Feedback Corpus (UIT-VSFC), that has been published for free use. this study therefore aims at evaluating the available corpus to use as a benchmarking dataset for conducting future researches as well as developing real-world applications. In this paper, deep neural network (DNN) and recurrent neural network (RNN) models are developed employing a word embedding method for two different tasks, i.e., topic and polarity classification. the experimental results show that DNN models outperform RNN models with 85.22% (>84.30%) and 88.56% (>86.32%) of accuracy for topic and polarity classification, respectively. Error analysis is conducted to explore the confusion of labeling and imbalance of data in the dataset. Workarounds for solving the problems are presented together with their results.

关键词： Deep learning computer science Sentiment analysis Analytical models Recurrent neural networks Error analysis education

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Characteristic extraction, classification and identification algorithm based on two kinds of eaglewood micrographs 2

Characteristic extraction, classification and identification...

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2nd International conference on Image, Vision and Computing, ICIVC 2017

作者： Haifeng, Wang Kun, Zhang Li, Zhuang College of Ocean Information Engineering/Sanya Key Laboratory of Computer Vision Hainan Tropical Ocean University China College of Information Science and Technology Hainan University Haikou China College of Ocean Information Engineering/Division of Development and Planning Hainan Tropical Ocean University Sanya China

ISBN: (纸本)9781509062379

In order to classify the eaglewood, the work proposed a method of wood fiber segmentation and characteristic extraction based on the eaglewood micrographs. the active contour model was used to extract the contours of the eaglewood micrographs. After screening of wood fiber, the geometric features and shape factors were extracted to form characteristic vectors. After that, SVM was used to achieve the classification of the two kinds of eaglewood micrographs. Results show that the extracted characteristics can be used to express eaglewood fiber. With good classification performance, classification algorithm is easy to achieve. © 2017 IEEE.

关键词： Extraction

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FL-GNN: Efficient Fusion of Fuzzy Neural Network and Graph Neural Network 27

FL-GNN: Efficient Fusion of Fuzzy Neural Network and Graph N...

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27th European conference on Artificial Intelligence, ECAI 2024

作者： Du, Boyu Zhou, Jingya Liu, Ling She, Xiaolong School of Computer Science and Technology Soochow University China Engineering Lab.of Big Data and Intelligence of Jiangsu Province Soochow University China State Key Lab.for Novel Software Technology Nanjing University China School of Computer Science Georgia Institute of Technology United States

ISBN: (纸本)9781643685489

Graph Neural Networks (GNNs) have become an important graph feature learning paradigm that is extensively applied to graph inference ***, GNNs still have limitations in some aspects such as representation capability, interpretability, *** this end, this paper introduces a novel hybrid Fuzzy-Logic Graph Neural Network (FL-GNN) that synergistically combines Fuzzy Neural Network (FNN) and GNN to effectively capture and aggregate local information flows within the ***-GNN exhibits three distinctive ***, we incorporate a specialized structure fuzzy rule to enhance FL-GNN's graph inference capability, surpassing representative GNN ***, we augment the interpretability of FL-GNN by integrating analytical exploration methods from two perspectives: Fuzzy Inference System and Message Passing Algorithm (MPA).Lastly, we refine the structure of FL-GNN based on MPA to optimize its calculation complexity and consequently improve learning *** results show that FL-GNN outperforms existing representative graph neural networks for graph inference tasks. © 2024 the Authors.

关键词： Graph neural networks

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Age of Information for Slotted ALOHA with Synchronization Frames at Multiple Access Points 100

Age of Information for Slotted ALOHA with Synchronization Fr...

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100th IEEE Vehicular technology conference, VTC 2024-Fall

作者： Song, Changhao Xie, Mangang An, Baozhen Wang, Qianqian Wang, Yue Northwest Normal University School of Computer Science and Engineering Lanzhou730070 China

ISBN: (纸本)9798331517786

the traditional large-scale and low-power Internet of things systems cannot meet the requirement of freshness of information. In this paper, a frame-slotted Aloha (FSA) based synchronization strategy is proposed to update information for multi-node access, which makes the information at the receiver side as fresh as possible. Firstly, a multi-point access model of the system from the perspective of FSA is studied, and the corresponding data flow and framework analysis are presented. Secondly, the age of information (AoI) analysis of FSA is conducted, and the expression of the average AoI and the optimal frame size under frame synchronization are derived. Finally, numerical simulation results show that the proposed strategy achieves the lower AoI in FSA based multi-node wireless sensor networks. © 2024 IEEE.

关键词： age of information frame slotted Aloha Internet of things random access wireless sensor network

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AH-TDMA: An Adaptive Heterogeneous Tridiagonal Matrix Algorithm on the New Sunway Supercomputer 29

AH-TDMA: An Adaptive Heterogeneous Tridiagonal Matrix Algori...

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29th IEEE International conference on Parallel and Distributed Systems, ICPADS 2023

作者： Tian, Min Liu, Qi Li, Yanlong Du, Wei Ren, Zenghui Liu, Yue Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center National Supercomputer Center in Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks China Jinan Institute of Supercomputing Technology Jinan Key Laboratory of High Performance Computing China

ISBN: (纸本)9798350330717

the solution of tridiagonal linear systems is used in in various fields and plays a crucial role in numerical simulations. However, there is few efficient solver for tridiagonal linear systems on the new Sunway supercomputer. Based on a three-dimensional heat conduction problem, we propose an adaptive heterogeneous tridiagonal matrix algorithm (AH-TDMA). Our major innovations include: (1) To address computational hotspots within AH-TDMA, a multi-level parallel approach involving MPI+Athread has been adopted. (2) An adaptive data partitioning scheme has been set up to achieve load balance. (3) Employing direct memory access and establishing shared space between registers and main memory, instead of employing discrete memory access, is done to enhance memory access efficiency. (4) the optimization of the loop structure has been made in adjusting the sequencing of the dual-layered loops to reduce communication overhead. the experimental results show that, with one core group, the AH-TDMA achieves a speedup of 99.6 times for hotspot and total time speedup up to 59.4 times compared to the Parallel and Scalable Library for Tridiagonal Matrix Algorithm (PaScal TDMA). the AH-TDMA is scalable up to 2048 core groups, with a parallel efficiency of 69.2%. © 2023 IEEE.

关键词： adaptive heterogeneous algorithm MPI+Athread Sunway supercomputer three-dimensional heat conduction problem tridiagonal linear systems

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Dimensions of diversity in engineering: What we can learn from STS 125

Dimensions of diversity in engineering: What we can learn fr...

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125th ASEE Annual conference and Exposition

作者： Odumosu, Toluwalogo Ferguson, Sean Foley, Rider W. Neeley, Kathryn A. Wylie, Caitlin Donahue Ku, Sharon Tsai-Hsuan Berne, Rosalyn W. Department of Electrical and Computer Engineering School of Engineering and Applied Science University of Virginia United States

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Hybrid particle swarm optimization algorithm for traveling salesman problem based on ternary optical computer 4

Hybrid particle swarm optimization algorithm for traveling s...

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4th International conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT 2023

作者： Sun, Shaojiang Tong, Yihui Qi, Baofeng Wang, Zhehe Wang, Xianchao School of Computer and Information Engineering Fuyang Normal University Fuyang236600 China School of Computer Science and Technology Hainan Tropical Ocean University Sanya572000 China

In recent years, as a novel computer, the ternary optical computer (TOC) has attracted many attentions because of its own mega-parallelism. And with the development of optical computing technology, the exploration of applications based on TOC is also advancing. Travel Salesman problem (TSP) is a classical combinatorial optimization problem, which is also a NP problem. How to solve this problem quickly and efficiently is the major research direction. Particle swarm optimization algorithm (PSO) are prone to premature convergence and insufficient local search capability. To deal with the shortcomings of the problem, we promoted a hybrid algorithm that the hybrid particle swarm optimization algorithm (HPSO) to solve the problem. By introducing greedy strategy, the algorithm generates excellent populations. And the improved Metropolis criterion is added to individual learning and population learning to accept inferior solutions with certain probability, which can effectively increase the population diversity and the mutation adopts the 2-opt optimization strategy, which can solve the path crossing problem effectively, enhance the local optimization capability of the algorithm, and find higher quality solutions. At last, the results show that HPSO solves the TSP with fast convergence speed and high quality of the optimal solution. © 2024 the Authors.

关键词： Particle swarm optimization (PSO)

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Profit allocation mechanism of supply chain with bilateral asymmetric costs information 8

Profit allocation mechanism of supply chain with bilateral a...

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8th International conference on Management science and Engineering Management, ICMSEM 2014

作者： Wang, Xinhui Guo, Hongmei Wang, Xianyu Zhong, Jie School of Computer Science and Technology Southwest University for Nationalities Chengdu610041 China Business School Sichuan University Chengdu China School of Tourism and Historical Culture Southwest University for Nationalities Chengdu610041 China

ISBN: (纸本)9783642551819

this paper investigates the problem of profit allocation under bilateral asymmetric information *** specifically, we consider a supply chain consisting of one risk-neural manufacturer and one risk-neural retailer for an innovation product. In order to facilitate the cooperation, the manufacturer and the retailer commit to share their private information under a commitment contract based on the AGV (d’Aspremont and Gerard-Varet) mechanism. We analyze the relationship between the expected information rents and the realized supply chain profit, and discuss the allocation rule implementation under three different cases by introducing the R-S-K negotiation. We show that the commitment contract can achieve truthful information revealing and allocate the ex post profit reasonably. Finally, one numerical example is presented to explain the main results. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Profitability

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