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arXiv 2022年

作者： Xu, Jiayi Yoshimoto, Shunsuke Ienaga, Naoto Kuroda, Yoshihiro The Graduate School of Science and Technology Degree Programs in Systems and Information Engineering University of Tsukuba Japan The Department of Human & Engineered Environmental Studies The University of Tokyo Japan The Faculty of Engineering Information and Systems University of Tsukuba Japan

Cold sensations of varying intensities are perceived when human skin is subject to diverse environments. The accurate presentation of temperature changes is important to elicit immersive sensations in applications such as virtual reality. We developed a method to elicit intensity-adjustable non-contact cold sensations based on the vortex effect. We applied this effect to generate cold air at approximately 0 ◦C and varied the skin temperature over a wide range. The perception of different temperatures can be elicited by adjusting the volume flow rate of the cold air. Additionally, we introduced a cooling model to relate the changes in skin temperature to various parameters such as the cold air volume flow rate and distance from the cold air outlet to the skin. For validation, we conducted measurement experiments and found that our model can estimate the change in skin temperature with a root mean-square error of 0.16 ◦C. Furthermore, we evaluated the performance of a prototype in psychophysical cold discrimination experiments based on the discrimination threshold. Thus, cold sensations of varying intensities can be generated by varying the parameters. These cold sensations can be combined with images, sounds, and other stimuli to create an immersive and realistic artificial environment. Copyright © 2022, The Authors. All rights reserved.

关键词： Vortex flow

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2D Slice-driven Physics-based 3D Motion Estimation Framework for Pancreatic Radiotherapy

arXiv

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arXiv 2023年

作者： Hara, Yuki Kadoya, Noriyuki Mitsume, Naoto Ienaga, Naoto Umezawa, Rei Jingu, Keiichi Kuroda, Yoshihiro The Degree Programs in Systems and Information Engineering University of Tsukuba Tsukuba Japan The Department of Radiation Oncology Tohoku University Graduate School of Medicine Sendai Japan The Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan

Pancreatic diseases are difficult to treat with high doses of radiation, as they often present both periodic and aperiodic deformations. Nevertheless, we expect that these difficulties can be overcome, and treatment results may be improved with the practical use of a device that can capture 2D slices of organs during irradiation. However, since only a few 2D slices can be taken, the 3D motion needs to be estimated from partially observed information. In this study, we propose a physics-based framework for estimating the 3D motion of organs, regardless of periodicity, from motion information obtained by 2D slices in one or more directions and a regression model that estimates the accuracy of the proposed framework to select the optimal slice. Using information obtained by slice-to-slice registration and setting the surrounding organs as boundaries, the framework drives the physical models for estimating 3D motion. The R2 score of the proposed regression model was greater than 0.9, and the RMSE was 0.357 mm. The mean errors were 5.11 ± 1.09 mm using an axial slice and 2.13 ± 0.598 mm using concurrent axial, sagittal, and coronal slices. Our results suggest that the proposed framework is comparable to volume-to-volume registration, and is feasible. Copyright © 2023, The Authors. All rights reserved.

关键词： Radiotherapy

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A Note on Even-Sized Spectral Clustering

A Note on Even-Sized Spectral Clustering

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International Symposium on Soft Computing and Intelligent systems (SCIS)

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

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

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.

关键词： Clustering algorithms Partitioning algorithms Classification algorithms Optimization Unsupervised learning

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3D Point Cloud Reconstruction Based on Stereo Camera and RTK-GPS with High Accuracy under Sequential Correction

3D Point Cloud Reconstruction Based on Stereo Camera and RTK...

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IEEE Global Conference on Consumer Electronics (GCCE)

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

ISBN: (数字)9781728198026

ISBN: (纸本)9781728198033

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.

关键词： Three-dimensional displays Memory management Measurement uncertainty Kinematics Real-time systems Drones Global Positioning System

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Preliminary Evaluation of Kyokko for Inter-FPGA Communication Framework CIRCUS

Preliminary Evaluation of Kyokko for Inter-FPGA Communicatio...

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IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Kaito Kitazume Norihisa Fujita Ryohei Kobayashi Taisuke Boku Master's Program in Computer Science Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Center for Computational Sciences University of Tsukuba

In recent years, Field-Programmable Gate Arrays (FPGAs) are gaining attention as computational acceleration devices in the field of high-performance computing. By implementing specialized circuits that can be customiz... 详细信息

ISBN: (数字)9798350383454

ISBN: (纸本)9798350383461

关键词： Conferences High performance computing Circuits Cluster computing Low latency communication Field programmable gate arrays

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Affinity-Weighted RandAugment for Problem-Oriented Augmentation

Affinity-Weighted RandAugment for Problem-Oriented Augmentat...

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International Joint Conference on Neural Networks (IJCNN)

作者： Yuna Park Tomoumi Takase Keisuke Kameyama Masaki Onishi Degree Programs in Systems and Information Engineering and Graduate School of Science and Technology University of Tsukuba Tsukuba Japan Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology (AIST) Japan Institute of Systems and Information Engineering University of Tsukuba

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Data augmentation is a technique with the potential to improve model generalization performance. Automatic Augmentation, which autonomously designs suitable data augmentation strategies, has significantly improved performance. One of the effective Automatic Augmentation is RandAugment (RA), which randomly selects methods to apply from the set of available augmentations. However, its selection with equal probabilities for all available augmentations is not ideal. In this study, we propose Affinity-Weighted RandAugment which assigns weights to the selection probabilities for the available augmentations in RA. The weights are calculated based on the value of Affinity, which represents the distributional similarity between original and augmented data. Affinity provides the prediction of the effect of each augmentation according to both the model and the dataset in advance. This enables the assignment of weights to the selection probabilities with low computational cost. As an additional effort, whether Affinity could be obtained at a much lower computational cost was considered. Based on these insights we implemented Single-Pass Affinity-Weighted RA, which can achieve effective weighting for RA without additional or separate learning. Experiments in image classification using CIFAR-10/100 and Describable Textures Dataset (DTD) demonstrated that Affinity-Weighted RandAugment achieves better test accuracy in comparison with the other known RA methods.

关键词： Accuracy Computational modeling Neural networks Probability Predictive models Data augmentation Data models

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Imitation Learning for Variable Speed Contact Motion for Operation up to Control Bandwidth

arXiv

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arXiv 2021年

作者： Sakaino, Sho Fujimoto, Kazuki Saigusa, Yuki Tsuji, Toshiaki Faculty of Engineering Information and Systems Department of Intelligent Interaction Technologies University of Tsukuba Japan Electrical and Electronic Systems Saitama University Saitama Japan Graduate School of Science and Technology Degree Programs in Intelligent and Mechanical Interaction Systems University of Tsukuba Japan

The generation of robot motions in the real world is difficult by using conventional controllers alone and requires highly intelligent processing. In this regard, learning-based motion generations are currently being investigated. However, the main issue has been improvements of the adaptability to spatially varying environments, but a variation of the operating speed has not been investigated in detail. In contact-rich tasks, it is especially important to be able to adjust the operating speed because a nonlinear relationship occurs between the operating speed and force (e.g., inertial and frictional forces), and it affects the results of the tasks. Therefore, in this study, we propose a method for generating variable operating speeds while adapting to spatial perturbations in the environment. The proposed method can be adapted to nonlinearities by utilizing a small amount of motion data. We experimentally evaluated the proposed method by erasing a line using an eraser fixed to the tip of the robot as an example of a contact-rich task. Furthermore, the proposed method enables a robot to perform a task faster than a human operator and is capable of operating close to the control bandwidth. Copyright © 2021, The Authors. All rights reserved.

关键词： Motion planning

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Single-cell transcriptomics uncovers EGFR signaling-mediated gastric progenitor cell differentiation in stomach homeostasis (vol 14, 3750, 2023)

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NATURE COMMUNICATIONS 2023年第1期14卷 1-16页

作者： Takada, Hitomi Sasagawa, Yohei Yoshimura, Mika Tanaka, Kaori Iwayama, Yoshimi Hayashi, Tetsutaro Isomura-Matoba, Ayako Nikaido, Itoshi Kurisaki, Akira Laboratory of Stem Cell Technologies Graduate School of Science and Technology Nara Institute of Science and Technology Takayama-cho Ikoma Nara Japan Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research Wako Saitama Japan Department of Functional Genome Informatics Biological Data Science Medical Research Institute Tokyo Medical and Dental University Bunkyo Tokyo Japan Master’s/Doctoral Program in Life Science Innovation (Bioinformatics) Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Ibaraki Japan

Defects in gastric progenitor cell differentiation are associated with various gastric disorders, including atrophic gastritis, intestinal metaplasia, and gastric cancer. However, the mechanisms underlying the multilineage differentiation of gastric progenitor cells during healthy homeostasis remain poorly understood. Here, using a single-cell RNA sequencing method, Quartz-Seq2, we analyzed the gene expression dynamics of progenitor cell differentiation toward pit cell, neck cell, and parietal cell lineages in healthy adult mouse corpus tissues. Enrichment analysis of pseudotime-dependent genes and a gastric organoid assay revealed that EGFR-ERK signaling promotes pit cell differentiation, whereas NF-κB signaling maintains gastric progenitor cells in an undifferentiated state. In addition, pharmacological inhibition of EGFR in vivo resulted in a decreased number of pit cells. Although activation of EGFR signaling in gastric progenitor cells has been suggested as one of the major inducers of gastric cancers, our findings unexpectedly identified that EGFR signaling exerts a differentiation-promoting function, not a mitogenic function, in normal gastric homeostasis.

关键词： Adult stem cells Stem-cell differentiation Stem-cell niche

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Higher-continuity s-version of finite element method with B-spline functions

arXiv

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arXiv 2023年

作者： Magome, Nozomi Morita, Naoki Kaneko, Shigeki Mitsume, Naoto University of Tsukuba Degree Programs in Systems and Information Engineering Tennodai 1-1-1 Ibaraki Tsukuba3058573 Japan University of Tsukuba Institute of Systems and Information Engineering Tennodai 1-1-1 Ibaraki Tsukuba3058573 Japan The University of Tokyo Department of Systems Innovation School of Engineering Hongo 7-3-1 Bunkyo-ku Tokyo1138656 Japan

This paper proposes a strategy to solve the problems of the conventional s-version of finite element method (SFEM) fundamentally. Because SFEM can reasonably model an analytical domain by superimposing meshes with different spatial resolutions, it has intrinsic advantages of local high accuracy, low computation time, and simple meshing procedure. However, it has disadvantages such as accuracy of numerical integration and matrix singularity. Although several additional techniques have been proposed to mitigate these limitations, they are computationally expensive or ad-hoc, and detract from the method’s strengths. To solve these issues, we propose a novel strategy called B-spline based SFEM. To improve the accuracy of numerical integration, we employed cubic B-spline basis functions with C2-continuity across element boundaries as the global basis functions. To avoid matrix singularity, we applied different basis functions to different meshes. Specifically, we employed the Lagrange basis functions as local basis functions. The numerical results indicate that using the proposed method, numerical integration can be calculated with sufficient accuracy without any additional techniques used in conventional SFEM. Furthermore, the proposed method avoids matrix singularity and is superior to conventional methods in terms of convergence forMSC Codes 65N30 Copyright © 2023, The Authors. All rights reserved.

关键词： Finite element method

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Performance improvement by enhancing spatial parallelism on FPGA for HPC applications

Performance improvement by enhancing spatial parallelism on ...

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IEEE International Conference on Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)

作者： Yuka Sano Taisuke Boku Mitsuhisa Sato Miwako Tsuji Norihisa Fujita Ryohei Kobayashi Degree Programs in Systems and Information Engineering University of Tsukuba Japan Center for Computational Sciences University of Tsukuba Japan Faculty of Health Data Science Juntendo University Japan Center for Computational Science RIKEN Japan

In today’s HPC systems, GPUs with high computational performance and memory bandwidth under relatively low power consumption are the leading players. However, GPU-based acceleration is designed to excel when utilizing many computation cores and performing SIMD/STMD manner of synchronized computation over a large number of uniform data array elements. Therefore, it may not fully exploit its computational performance in calculations with low parallelism, complex operations involving conditional branching, or parallel applications with frequent inter-node communication to interrupt continuous computing on GPU devices. One of the alternative solutions for accelerated computing is FPGA (Field Programmable Gate Array), especially with recent advancements in devices containing a large number of logic elements, high memory bandwidth, and even multiple channels of high-speed optical interconnection interfaces, reaching up to 100 Gbps for each. The performance of an FPGA is based on pipeline parallelism, enabling the computation stream to continue even with conditional branches.

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