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30th International Conference on Nuclear engineering, ICONE 2023

作者： Hidaka, Shinjiro Shoji, Gaku Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Ibaraki Japan Division of Engineering Mechanics and Energy Institute of Systems and Information Engineering University of Tsukuba Ibaraki Japan

ISBN: (纸本)9784888982566

Clarifying the dynamic buckling behavior of PWR steel reactor containment vessels (PWR-CVs) subject to seismic excitation is critical for improving a numerical seismic design scheme for PWR-CVs. In evaluating the static elastic-plastic buckling strength for PWR-CVs by a finite element (FE) analysis, first we compute the moments and axial forces acting onto the multiple lumped mass beam model of a targeted PWR-CV from the linear dynamic analysis, second using the buckling evaluation formula on JEAG 4601 addenda-1984 we calculate the equivalent static load distributions in terms of shear and axial forces as input loads to the FE model. This static FE buckling analysis for a PWR-CV idealizes dynamic buckling phenomena as be static phenomena, so we cannot basically consider the effects of dynamic behavior on the buckling strength of a PWR-CV. To tackle more realistic buckling assessment of a PWR-CV, we carried out the linear dynamic analysis for a PWR-CV FE numerical model and discussed the features of the response considering the oval vibration modes. It was revealed that the response accompanying the oval vibration modes showed the lower value compared with that from the static FE buckling analysis. In contrast, in a previous study by Hidaka et al., 2022, it was discussed that the buckling load of static FE buckling analysis for a PWR-CV is higher than the buckling load of buckling evaluation formula on JEAG4601. As a result, the ratio of buckling load to response in the linear dynamic FE analysis was within 3% of that in the static FE buckling analysis. © 2023 by JSME.

关键词： Elastoplasticity

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A Note on Even-Sized Spectral Clustering 13

A Note on Even-Sized Spectral Clustering

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Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Miyakawa, Hiroki Endo, Yasunori Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Master's Program in Risk and Resilience Engineering University of Tsukuba Ibaraki Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Ibaraki Tsukuba Japan

ISBN: (纸本)9798350373332

Clustering is a typical unsupervised learning method for classifying unsupervised data. One of the clustering meth-ods, even-sized clustering based on optimization (ECBO), is a clustering algorithm that imposes a constraint to equalize the size of each cluster. ECBO has been suggested to be effective in delivery and other problems. However, it is limited to Euclidean space. On the other hand, spectral clustering with a wide range of applicability for partitioning graph data has been proposed. In this paper, we propose even-sized spectral clustering, which imposes a size-equal constraint on spectral clustering, and show that it is an extension of the graph partitioning problem. We also verify the validity of the results through numerical examples. © 2024 IEEE.

关键词： Unsupervised learning

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Implementation and Performance Evaluation of Memory System Using Addressable Cache for HPC Applications on HBM2 Equipped FPGAs 28th

Implementation and Performance Evaluation of Memory System...

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28th International European Conference on Parallel and Distributed Computing , Euro-Par 2022

作者： Fujita, Norihisa Kobayashi, Ryohei Yamaguchi, Yoshiki Boku, Taisuke Center for Computational Sciences University of Tsukuba Tsukuba Japan Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Japan

ISBN: (纸本)9783031312083

When we apply field programmable gate arrays (FPGAs) as HPC accelerators, their memory bandwidth presents a significant challenge because it is not comparable to those of other HPC accelerators. In this paper, we propose a memory system for HBM2-equipped FPGAs and HPC applications that uses block RAMs as an addressable cache implemented between HBM2 and an application. This architecture enables data transfer between HBM2 and the cache bulk and allows an application to utilize fast random access on BRAMs. This study demonstrates the implementation and performance evaluation of our new memory system for HPC and HBM2 on an FPGA. Furthermore, we describe the API that can be used to control this system from the host. We implement RISC-V cores in an FPGA as controllers to realize fine-grain data transfer control and to prevent overheads derived from the PCI Express bus. The proposed system is implemented on eight memory channels and achieves 102.7 GB/s of the bandwidth. It overcomes the memory bandwidth of conventional FPGA boards with four channels of DDR4 memory despite using only 8 of 32 channels of the HBM2. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data transfer

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Evaluating a How-to Tip Machine Comprehension Model with QA Examples collected from a Community QA Site 35

Evaluating a How-to Tip Machine Comprehension Model with QA ...

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35th Pacific Asia Conference on Language, information and Computation, PACLIC 2021

作者： Li, Tingxuan Bai, Shuting Zhu, Fuzhu Utsuro, Takehito Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8573 Japan

In the field of factoid question answering (QA), it is known that the state-of-the-art technology has achieved an accuracy comparable to human. However, in the area of non-factoid QA, there are only limited numbers of datasets for training QA models. So within the field of the non-factoid QA, Chen et al. (2020) developed a dataset for training Japanese tip QA models. Although it can be shown that the trained Japanese tip QA model outperforms the factoid QA model, this paper further aims at answering tip questions more closely related to daily lives. Specifically, we collect community QA examples from a community QA site and then apply the trained Japanese tip QA model to those community QA examples. Evaluation results show that the trained tip QA model outperforms the factoid QA model when testing against those community QA examples. © Proceedings of the 35th Pacific Asia Conference on Language, information and Computation, PACLIC 2021.

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3D point cloud reconstruction based on stereo camera and rtk-gps with high accuracy under sequential correction 9

3D point cloud reconstruction based on stereo camera and rtk...

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9th IEEE Global Conference on Consumer Electronics, GCCE 2020

作者： Liu, Shuyi Zhang, Heming Kawai, Shin Nobuhara, Hajime University of Tsukuba Intelligent and Mechanical Interaction Systems Graduate School of Science and Technology Degree Programs in Systems and Information Engineering Tsukuba 1-1-1 Tennoudai Ibaraki305-8573 Japan

ISBN: (纸本)9781728198026

In the field of three-dimensional (3D) point cloud reconstruction, a commonly used algorithm is called Real-Time-Appearance-Based-Mapping. Although this algorithm performs well in outputting a point cloud with high accuracy in real time, its processing efficiency is expected to decline when Jetson Nano is installed on drones, as additional memory is required to calculate loop closures. To increase the processing speed and accuracy of 3D point cloud reconstruction based on Jetson Nano, we propose a new algorithm for drone flight, that does not rely on overlap. The proposed method combines the point cloud and real-time kinematic Global Positioning System, and its effectiveness is demonstrated by experiments in a real environment. © 2020 IEEE.

关键词： Drones

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Source Data-less Efficient Transfer Learning Based on Layer Importance Index Using Activated Feature Map

Source Data-less Efficient Transfer Learning Based on Layer ...

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2022 IEEE International Conference on systems, Man, and Cybernetics, SMC 2022

作者： Kanda, Daigo Nobuhara, Hajime University of Tsukuba Degree Programs in Systems and Information Engineering Graduate School of Science and Technology Tsukuba Japan University of Tsukuba Department of Intelligent Interaction Technologies Tsukuba Japan

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Transfer learning performance in convolutional neural networks (CNNs) depends on the selection of retraining and fixation layers. The conventional method requires source data, which increases the cost proportionally to the data's size. To solve this problem, this study proposed a source-data-less layer importance index that indicates the layers that should be retrained. Consequently, using the maximum activated feature maps generated by the model itself instead of the activated feature maps, the proposed method eliminates the need for any source data. Further, the experimental results on the five image classification datasets demonstrated a strong positive correlation of the proposed layer importance index compared with the conventional method. In addition, the transfer learning method using the layer importance index significantly improved the average classification accuracy compared with fine-tuning. CNNs have become indispensable owing to various applications, and thus, this study aimed at further enhancing its capabilities is relevant to the present and coming times. © 2022 IEEE.

关键词： Convolutional neural networks

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The Effect of Agenda-Setting on Occurrence of Echo Chamber on Social Media

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Transactions of the Japanese Society for Artificial Intelligence 2024年第6期39卷

作者： Nagura, Takuya Akiyama, Eizo Degree Programs in System and Information Engineering University of Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Japan

Echo chamber refers to a state in which individuals with similar preferences on social media construct closed networks and consume similar information reflectively. This is one of the causes to prevalent fake news and conspiracy on social media. Previous research has shown that echo chamber is prevented in communication where there are multiple topics. However, even though communication across multiple topics is common in daily social media use, echo chamber is still occurring on various topics. In this paper, we suggest the presence of agenda-setting as a potential background factor for occurrence of echo chamber from communication on multiple topics. Agenda-setting is the concept that topics frequently present to users are regarded as significant agendas. In this study, we experimented with multi-agent simulations to investigate the communication among agents who assess the significance of specific topics based on the frequency of encountering them. Our result shows that if a specific topic is recognized as significant by many users, users construct closed networks as echo chamber on the opinion of significant topic. We also conducted another experiment to verify the effect of agenda setting by mass media coverage. In this experiment, a specific topic came to be perceived as significant by many users, but echo chambers did not occur regarding significant topic. © 2024, Japanese Society for Artificial Intelligence. All rights reserved.

关键词： Social networking (online)

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The effect of increasing number of topics to polarization and echo chambers on SNS

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Transactions of the Japanese Society for Artificial Intelligence 2023年第4期38卷

作者： Nagura, Takuya Akiyama, Eizo Degree Programs in System and Information Engineering University of Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Japan

Communication through SNS (Social Networking Services) and function of SNS platform can cause two phenomena polarization and echo chambers. In previous study [sasahara 21] about the communication on SNSs regarding a single topic, it has been shown that there is a correlation between these two phenomena and also that SNS functions facilitate the occurrence of these phenomena. In this study, focusing on the fact that real SNS users often deal with multiple topics on a daily basis, we analyzed an agent-based model of SNS communication regarding multiple topics. The analysis revealed that polarization of opinions occurs even when the number of topics increases but that echo chambers are less likely to occur as the number of topics increases. We have also found that there is little correlation between polarization and echo chamber under the condition with more than certain number of topics. Additionally, some functions of SNS such as user recommendations and reposts was found to facilitate echo chambers regardless of the number of topics. This result implies that the findings of previous research are robust even in multiple topics environment. These results suggest that topic diversity and function of SNS platform amendment may be a means of reducing the occurrence of echo chambers. In this model, we cannot take into account the impact of an individual’s interest in a specific topic on such as unfollowing behavior. In future research, we should expand our model to implement these user’s real behavior. © 2023, Japanese Society for Artificial Intelligence. All rights reserved.

关键词： Polarization

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New Solutions Based on the Generalized Eigenvalue Problem for the Data Collaboration Analysis

arXiv

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arXiv 2024年

作者： Kawakami, Yuta Takano, Yuichi Imakura, Akira Degree Programs in Systems and Information Engineering University of Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Japan

In recent years, the accumulation of data across various institutions has garnered attention for the technology of confidential data analysis, which improves analytical accuracy by sharing data between multiple institutions while protecting sensitive information. Among these methods, Data Collaboration Analysis (DCA) is noted for its efficiency in terms of computational cost and communication load, facilitating data sharing and analysis across different institutions while safeguarding confidential information. However, existing optimization problems for determining the necessary collaborative functions have faced challenges, such as the optimal solution for the collaborative representation often being a zero matrix and the difficulty in understanding the process of deriving solutions. This research addresses these issues by formulating the optimization problem through the segmentation of matrices into column vectors and proposing a solution method based on the generalized eigenvalue problem. Additionally, we demonstrate methods for constructing collaborative functions more effectively through weighting and the selection of efficient algorithms suited to specific situations. Experiments using real-world datasets have shown that our proposed formulation and solution for the collaborative function optimization problem achieve superior predictive accuracy compared to existing *** Codes 15A18 Copyright © 2024, The Authors. All rights reserved.

关键词： Machine learning

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Human Pain Relief by Using Augmented Reality of Noxious Stimulation

Human Pain Relief by Using Augmented Reality of Noxious Stim...

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IEEE International Conference on systems, Man and Cybernetics

作者： Kotaro Toratori Fumihide Tanaka Degree Programs in Systems and Information Engineering University of Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Japan

It is estimated that 3.5-10 percent of the population are afraid of injections. These people are at risk of vasovagal syncope, a condition in which the patient faints during the injection. To help overcome this response to the perceived pain of injections, this paper proposes a diffuse noxious inhibitory control effect that can be applied through Augmented Reality (AR) smartphone applications. Furthermore, we confirm that presenting ARs that evoke noxious stimulation in participants can influence pain perception. We investigate the pain perception and negative affect when presented with noxious ARs and a distraction AR. The results show that pain thresholds are significantly increased in each AR condition when a painful stimulation is presented to participants. However, no difference in pain reduction between the noxious and distraction ARs is observed. One reason for this result may come from a manipulation problem: exposure to ARs does not make all participants feel pain. For the group of participants who felt pain when exposed to the ARs, the magnitude of pain tended to be smaller in a noxious AR (fire) condition than in the distraction condition. There was no significant increase in negative affect in the fire AR condition compared with the other conditions. These results may imply that the proposed method could reduce pain through diffuse noxious inhibitory control without producing any extra discomfort.

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