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2023 International Conference on High Performance Computing in Asia-Pacific Region Workshops, HPC Asia 2023

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

ISBN: (纸本)9781450399890

In the high-performance computing domain, Field Programmable Gate Array (FPGA) is a novel accelerator that exhibits high flexibility and performance characteristics distinct from other accelerators such as the Graphics Processing Unit (GPU). Recent advanced high-end FPGA is equipped with multiple channels of high speed optical link up to 100Gbps performance for each. This is a crucial feature when we construct PC clusters with FPGAs as accelerators, however it is not easy to utilize from user kernels because this feature is implemented in low level and simple direct communication between neighboring FPGAs. In order to provide the communication feature between FPGAs for accelerated PC clusters, we developed a communication system named CIRCUS which implies a user-friendly API from OpenCL and is equipped with routing function over multi-hop communication on multi-dimensional torus network of FPGAs. However, current CIRCUS only provides a point-to-point communication between source and destination FPGAs. In ordinary parallel processing environment such as MPI, the user program the message passing with various collective communication functions for parallel algorithm, for instance Allreduce, Allgather, etc. In this paper, we implement the collective communication function over CIRCUS for user-friendly programming of ordinary parallel algorithms on FPGAs. As the first target, we implement Allreduce function which is the most essential and important function. The paper describes the CIRCUS system briefly followed by the design, implementation and preliminary performance evaluation on Intel Stratix10 FPGAs. © 2023 ACM.

关键词： Field programmable gate arrays (FPGA)

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Haptic Interface for Proximity Object Recognition Considering Hand Structure

Haptic Interface for Proximity Object Recognition Considerin...

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International Conference on Intelligent Transportation

作者： Takuma Yabe Hiroaki Yano Degree Programs in Systems and Information Engineering University of Tsukuba Tsukuba Japan tFaculty of Engineering Information and Systems University of Tsukuba Tsukuba Japan

The drivers who drive in spaces such as SharedSpace must pay attention in all directions given that there are chances of accidents in any direction. In this paper, we introduce a haptic interface that alerts about obstacles surrounding the vehicle by haptic pressure to the dorsal side of the hand. Because the hand shape is not symmetrical at the tip and wrist sides, both should be considered when presenting force perception around the hand. We proposed two approaches for pressure stimulation and two approaches for holding the joystick lever as a means of increasing the amount of information that could be presented to the front side. We show that static pressure could achieve a higher-resolution stimulation than periodic pressure. In addition, by detaching the finger and lever, the deep sensation can be used to sense pressure. Regarding the rear side, we proposed a method for mounting manipulators to present obstacles in the rearward region. We conducted an experiment and proved that shearing force from -180° can present obstacles in the rearward region.

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A FPGA-based Learning Accelerator for Self-Organizing Map and Its Application to Trend-Visualization

A FPGA-based Learning Accelerator for Self-Organizing Map an...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Yusuke Yamagiwa Kenji Kanazawa Moritoshi Yasunaga Degree Programs in Systems and Information Engineering University of Tsukuba Tsukuba Japan Institute of Systems and Information and Engineering University of Tsukuba Tsukuba Japan

Self-Organizing Map (SOM) is one of the neural networks employed, particularly in data mining and related fields. Like Deep Learning, SOM requires iterative calculations of a vast number of high-dimensional vectors. Consequently, dedicated hardware is essential for accelerating SOM computations. We propose a dedicated SOM accelerator utilizing FPGA. In this accelerator, all reference vectors of SOM neurons are implemented in the internal memory (UltraRAM) embedded in the FPGA, and those vectors are calculated in parallel based on the internal parallelism within SOM. Furthermore, we propose a SOM application that visualizes similarities among trends in vast numbers of tweets in X (Twitter), which requires on-line learning that keeps up the rapid changes of tweets. The proposed accelerator is applied to this application, demonstrating approximately 5 times faster performance compared to an Intel Core i7 (multithreaded) processor.

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Whole Time-Series Clustering by Embedding Relational Graphs into Vector Spaces Using DeepWalk

Whole Time-Series Clustering by Embedding Relational Graphs ...

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International Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Koh Kumamoto Yasunori Endo Degree Programs in Systems and Information Engineering University of Tsukuba Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Japan

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

Clustering is a type of unsupervised learning, which can be broadly classified into static and dynamic methods. Whole time-series clustering, one of the dynamic methods, is performed on multiple time-series data and classifies them. However, few whole time-series clustering methods take into account the fact that the clusters belonging to each time-series data change with time. Therefore, the purpose of this study is to propose a method to adapt static clustering methods to whole time-series clustering that takes into account the time variation of cluster classification. Specifically, we propose a method to perform static clustering for each time point of time-series data, embed a relationship graph consisting of clusters at each time point into a vector space, and perform time-series clustering by analyzing relationships among clusters at different time points. For embedding the graph into the vector space, we use DeepWalk, a method based on random walk. Numerical experiments are then conducted to verify the behavior of the proposed method.

关键词： Clustering methods Vectors Unsupervised learning

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On a New Rough Clustering Based on Optimization 13

On a New Rough Clustering Based on Optimization

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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： Furuta, Sakuya Endo, Yasunori Master's Program in Risk and Resilience Engineering Degree Programs in Systems and Information Engineering Graduate School of Science Annd Technology University of Tsukuba 1-1-1 Tennodai Tsukuba Ibaraki305-8573 Japan Institute of Systems and Information Engineering University of Tsukuba 1-1-1 Tennodai Tsukuba Ibaraki305-8573 Japan

ISBN: (纸本)9798350373332

The purpose of this study is to develop and investigate a new rough clustering based on optimization. We propose a restructured algorithm using only one variable, instead of the algorithm described using two variables in existing methods. We also perform numerical examples using artificial data and the Iris and Wine datasets. This research has the potential to be used as a method for determining false negatives and false positives in cancer diagnosis. © 2024 IEEE.

关键词： Clustering algorithms

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Embedded Topic Models Enhanced by Wikification

arXiv

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arXiv 2024年

作者： Shibuya, Takashi Utsuro, Takehito Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Japan

Topic modeling analyzes a collection of documents to learn meaningful patterns of words. However, previous topic models consider only the spelling of words and do not take into consideration the homography of words. In this study, we incorporate the Wikipedia knowledge into a neural topic model to make it aware of named entities. We evaluate our method on two datasets, 1) news articles of New York Times and 2) the AIDA-CoNLL dataset. Our experiments show that our method improves the performance of neural topic models in generalizability. Moreover, we analyze frequent terms in each topic and the temporal dependencies between topics to demonstrate that our entity-aware topic models can capture the time-series development of topics well. © 2024, CC BY.

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Analysis of Hesitation Behavior by Human Receiver toward Facing Motion of Robot during Handover

Analysis of Hesitation Behavior by Human Receiver toward Fac...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Ryoya Goto Modar Hassan Kenji Suzuki Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Japan Institute of Systems and Information Engineering University of Tsukuba Japan

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

This paper examines whether the robot’s face-turning behavior toward humans during handover can be a behavior cue that supports the human action plan in accomplishing a task. A series of behavior cues observed in interactions, such as Joint action, are understood as social signals, which can be used as cues to help each other make decisions about their own action plans. We hope that constructing a inference model of empathetic behavior will enable humans and robots to share the intention of their behavioral goals in joint action. We conducted temporal analysis and subjective evaluation of the receiver’s behavior in an object handover experiment. The results showed that the subjective experience did not significantly change when the robot turned its head toward the receiver, but the time to receive the participant significantly increased. This suggests that the robot’s face-turning behavior may have altered the receiver’s human prediction and action plan, causing the receiver to hesitate to respond. This shows the potential for the robot face-turning to a human which could change the human inference and response behavior plan.

关键词： Receivers Handover Turning Behavioral sciences Robots Faces

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Optimal Control of Battery System by Reinforcement Learning Considering Profitability

Optimal Control of Battery System by Reinforcement Learning ...

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Power and Renewable Energy engineering (PREE), International Conference on

作者： Takuya Goto Daisuke Kodaira Degree programs in Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki Japan Institute of Systems and Information Engineering University of Tsukuba Tsukuba Ibaraki Japan

Government-led pilot experiments for Virtual Power Plants (VPPs) are being conducted in Japan. However, these experiments have faced challenges such as deviations between predicted and actual values of photovoltaic (PV) generation, as well as insufficient battery capacity, leading to imbalances and associated penalties that reduce the revenue of VPP aggregators. In this study, we propose a method that combines probabilistic PV forecasting and deep reinforcement learning to determine the charging and discharging schedules of batteries within the VPP. Our approach considers the risks associated with deviations between forecasted and actual values, enabling the generation of operational plans while considering these uncertainties.

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CoT based Few-Shot Learning of Negative Comments Filtering

CoT based Few-Shot Learning of Negative Comments Filtering

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IEEE International Conference on Big Data

作者： Takashi Mitadera Takehito Utsuro Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Japan

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

In this paper, we filter negative comments on videos using large language models (LLMs). In comment filtering using LLMs such as GPT-4 (zero-shot learning), over filtering occurs frequently. This over filtering can be improved by using few-shot learning based on chain-of-thought reasoning. Few-shot learning is a strategy to improve the performance of LLMs by presenting a small number of examples to LLMs. Chain-of-thought (CoT) [18] is one of the reasoning strategy which allows LLMs to engage in more logical reasoning by generating the process of inference. In this paper, we propose and evaluate an effective method of few-shot learning based on CoT in the task of negative comment filtering. The results showed that over filtering can be effectively reduced by selecting appropriate few-shot comments from the clusters created by GPT-4, and providing them for the prompt as demonstrations of CoT.

关键词： Analytical models Accuracy Filtering Large language models Zero shot learning Big Data Cognition Data models Few shot learning Videos

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Passive Elimination of Nonlinearity in Autoparametric Vibration Absorber by Magnetic Force

Passive Elimination of Nonlinearity in Autoparametric Vibrat...

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SICE Annual Conference

作者： Chao Zhang Hiroshi Yabuno Degree Programs in Systems and Information Engineering University of Tsukuba Tsukuba Japan University of Tsukuba Tsukuba Japan

ISBN: (数字)9784907764838

ISBN: (纸本)9798331544461

This study presents a passive control strategy that improves autoparametric vibration absorbers' performance. The cubic nonlinear stiffness of the absorber is eliminated by using the nonlinear characteristic of the magnetic force. Then, the performance of the autoparametric vibration absorber is kept even if the amplitude of absorber is large under the large amplitude excitation to the main system. In contrast, traditional active control methods require external energy sources and complex feedback mechanisms to adjust the absorber's natural frequency to match external frequencies. The proposed approach involves the strategic placement of permanent magnets around a pendulum-type vibration absorber, configuring its nonlinear characteristics. Theoretical and experimental analyzes demonstrate the varigity of the proposed method to enhance vibration suppression in dynamic systems.

关键词： Vibrations Force Magnetic forces Permanent magnets Iron Frequency response Dynamical systems Tuning

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