13197 research outputs found
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Enriching Non-parametric Components of Semi-parametric Control Policies for Robotics
Full text link奈良先端科学技術大学院大学博士（工学）doctoral thesi
Design and Optimization of Energy-Efficient Neural Network Accelerators Using Emerging Computing Paradigms
Full text link奈良先端科学技術大学院大学博士（工学）doctoral thesi
コウリツテキ ペプチド コウゾウ サイテキカ シュホウ ノ カイハツ ト シンキ TrkA ソガイザイ ノ カイハツ
Full text link奈良先端科学技術大学院大学博士（理学）doctoral thesi
Crash-Tolerant Perpetual Exploration with Myopic Luminous Robots on Rings
No full textWe investigate crash-tolerant perpetual exploration algorithms by myopic luminous robots on ring networks. Myopic robots mean that they can observe nodes only within a certain fixed distance ϕ, and luminous robots mean that they have light devices that can emit a color from a set of colors. The goal of perpetual exploration is to ensure that robots, starting from specific initial positions and colors, move in such a way that every node is visited by at least one robot infinitely often. As a main contribution, we clarify the tight necessary and sufficient number of robots to realize perpetual exploration when at most f robots crash. In the fully synchronous model, we prove that f+2 robots are necessary and sufficient for any ϕ ≥ 1. In the semi-synchronous and asynchronous models, we prove that 3f+3 (resp., 2f+2) robots are necessary and sufficient if ϕ = 1 (resp., ϕ ≥ 2).conference pape
Ternary amorphous oxide semiconductor of In–Ga–O system for three-dimensional integrated device application
No full textIn2O3-based oxide semiconductors are potential materials for supporting the development of next-generation integrated devices with low power consumption, such as back-end-of-line-compatible transistors and ferroelectric memories. Currently, these are standard semiconductor materials used in display research and industrial fields; however, their physical properties and functions must be optimized and reviewed to accelerate integrated device applications. This study proposed a concept for developing thermally stable amorphous oxide semiconductor materials for three-dimensional ferroelectric memory applications. We focused on ternary amorphous oxide semiconductors in terms of the atomic layer deposition process, thermal stability of the amorphous phase, and electrical properties. The electrical properties of ternary In–X–O (X = Al, Ga, Zn, or Sn) in a thin-film transistor fabricated using a high-temperature process were evaluated and compared. A ternary In–Ga–O system satisfied the stability of mobility over 20 cm2/Vs and threshold voltage close to 0 V under high temperature annealing up to 600 °C, which implies compatibility with HfO2-based ferroelectric device applications. The designed amorphous In–Ga–O induced a ferroelectric phase of Zr-doped HfO2 and exhibited sufficient semiconducting properties even after annealing at 500 °C in an N2 atmosphere. In addition, we developed an atomic layer deposition process for fabricating In–Ga–O. The atomic-layer-deposited In–Ga–O channel exhibited thermal stability, field-effect mobility over 20 cm2/Vs, and a subthreshold swing below 80 mV/decade, which was nearly identical to that of the sputter-deposited channel. The ternary In–Ga–O can be considered a potential material for future memory applications. This study provides a unique perspective on the design of oxide semiconductor materials for integrated devices.journal articl
Comprehensive evaluation of pipelines for classification of psychiatric disorders using multi-site resting-state fMRI datasets
No full textObjective classification biomarkers that are developed using resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for psychiatric disorders. Unfortunately, no widely accepted biomarkers are available at present, partially because of the large variety of analysis pipelines for their development. In this study, we comprehensively evaluated analysis pipelines using a large-scale, multi-site fMRI dataset for major depressive disorder (MDD). We explored combinations of options in four sub-processes of the analysis pipelines: six types of brain parcellation, four types of functional connectivity (FC) estimations, three types of site-difference harmonization, and five types of machine-learning methods. A total of 360 different MDD classification biomarkers were constructed using the SRPBS dataset acquired with unified protocols (713 participants from four sites) as the discovery dataset, and datasets from other projects acquired with heterogeneous protocols (449 participants from four sites) were used for independent validation. We repeated the procedure after swapping the roles of the two datasets to identify superior pipelines, regardless of the discovery dataset. The classification results of the top 10 biomarkers showed high similarity, and weight similarity was observed between eight of the biomarkers, except for two that used both data-driven parcellation and FC computation. We applied the top 10 pipelines to the datasets of other psychiatric disorders (autism spectrum disorder and schizophrenia), and eight of the biomarkers exhibited sufficient classification performance for both disorders. Our results will be useful for establishing a standardized pipeline for classification biomarkers.journal articl
シナリオ オ カツヨウシタ タヨウ ナ プログラミング エンシュウ モンダイ ジドウ セイセイ シュホウ ノ テイアン
Full text linkプログラミング演習では，学生が学習すべき内容に応じた演習問題を教員が大量に作成する必要がある．我々の研究グループでは，演習問題作成時に教員にかかる負荷の低減を目的として，自然な文章やテキストの自動生成を可能とする生成AIを用いた演習問題自動生成手法を提案している．本研究では，シナリオというプログラムの流れを説明する短い文章を演習問題生成時に与えることで，標準入力の有無や複数クラス構成といった問題パターン，アルゴリズムやデータ構造といった実装，問題難易度の3種類の観点に基づく多様性を持った演習問題を自動生成する手法を提案する．この手法を実装した演習問題自動生成システムでは，演習問題ごとに学習内容を教員が入力すると，解答例コード，仕様，実行例およびテストコードが自動的に生成される．実際にシナリオを用いて演習問題を生成した結果，生成時に意図したとおりの問題パターン，実装や難易度が異なる多様な演習問題の生成がある程度可能であることが分かった．特に実装や難易度の多様性については，演習問題生成時に与えるシナリオの内容の影響を強く受けることが確認された．journal articl
タイシャブツ ノ ジカン ヘンドウ データ オ モチイタ アロステリック セイギョ ネットワーク ノ システム ドウテイ
Full text link奈良先端科学技術大学院大学博士（理学）doctoral thesi
Computational Mechanisms of Neuroimaging Biomarkers Uncovered by Multicenter Resting-State fMRI Connectivity Variation Profile
Full text linkResting-state functional connectivity (rsFC) is increasingly used to develop biomarkers for psychiatric disorders. Despite progress, development of the reliable and practical FC biomarker remains an unmet goal, particularly one that is clinically predictive at the individual level with generalizability, robustness, and accuracy. In this study, we propose a new approach to profile each connectivity from diverse perspective, encompassing not only disorder-related differences but also disorder-unrelated variations attributed to individual difference, within-subject across-runs, imaging protocol, and scanner factors. By leveraging over 1500 runs of 10-minute resting-state data from 84 traveling-subjects across 29 sites and 900 participants of the case-control study with three psychiatric disorders, the disorder-related and disorder-unrelated FC variations were estimated for each individual FC. Using the FC profile information, we evaluated the effects of the disorder-related and disorder-unrelated variations on the output of the multi-connectivity biomarker trained with ensemble sparse classifiers and generalizable to the multicenter data. Our analysis revealed hierarchical variations in individual functional connectivity, ranging from within-subject across-run variations, individual differences, disease effects, inter-scanner discrepancies, and protocol differences, which were drastically inverted by the sparse machine-learning algorithm. We found this inversion mainly attributed to suppression of both individual difference and within-subject across-runs variations relative to the disorder-related difference by weighted-averaging of the selected FCs and ensemble computing. This comprehensive approach will provide an analytical tool to delineate future directions for developing reliable individual-level biomarkers.journal articl