13197 research outputs found
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TV ゲーム オ トモ ニ プレイ スル コミュニケーション ロボット ノ ケントウ
No full text本研究では，ロボットとの日常的な楽しいコミュニケーションを演出するために，ユーザと一緒に TV ゲームをプレイするコミュニケーションロボットを提案する．提案手法は，ロボットの発話を制御するだけでなく，ゲームキャラクタを操作することでゲーム展開も制御する．また，提案ロボットの設計にあたって，人同士の TV ゲームの対戦を分析する予備実験を行った．その結果，ゲームプレイに発話が組み合わさることで，より楽しくコミュニケーションできることがわかった．人同士の対戦におけるこの知見をもとに，人とロボットの対戦における発話とゲームプレイを設計していく．technical repor
Selection framework of visualization methods in designing AR industrial task-support systems
No full textAn Augmented reality (AR) task-support system incorporates head-mounted displays (HMDs) to improve human performance in maintenance, assembly, and disassembly tasks by intuitively showing the working procedure to the operator. To achieve the intended AR capability and to enable the operator to work efficiently, a system designer must understand the characteristics of AR and design the information to be shown operators for each subtask, taking into account the working situation represented by the procedure, operator performance skills, workspace, devices, and operating objects (i.e., AR information design). Especially, in the AR information design, the designer needs AR expertize to select the suitable visualization method among the many extant methods. This is difficult for designers (manual writers) to perform AR information design in factories in the future. However, at present, only a few studies have been conducted to select the suitable visualization method for each subtask. This study proposes to define 31 subtask types as criteria for decomposing tasks in AR information design. Furthermore, we classify and define 42 visualization methods in terms of AR information design. Finally, to select the suitable visualization method for each subtask, we construct a selection framework consisting of three selection categories representing the working status and 17 selection conditions. The evaluation experiments of the proposed framework could output an average of 4.3 suitable visualization method candidates, including at least one suitable visualization method selected by AR experts in the subtask working situation. By incorporating the proposed framework into a website and combining it with existing HMDs and services for AR application development, it is expected that designers will be able to develop appropriate AR task-support systems.journal articl
Topic ツウシン ショリ キジュツ ノ カイセキ ニ ヨル ROS アプリケーション ノ データ フロー ノ カシカ
Get PDF組込みソフトウェアの信頼性を向上するためには，第三者によるコードレビューが重要である．コードレビューを支援する技術の 1 つとして，ソフトウェア内部のデータフローの可視化が用いられている．組み込みソフトウェアの一種である ROS アプリケーションでは Topic 通信というモデルでデータフローが扱われており，これを可視化するための既存ツールは動的解析を使用している．そのため，コードレビューだけを行う担当者も，アプリケーションのテスト実行環境を準備する必要がある．本研究では，テスト実行環境なしでもコードレビューを容易に実施できる環境を実現するため，ROS アプリケーションのソースコードおよび設定ファイルに書かれた Topic 通信処理の記述を静的に解析し，データフローの可視化を行うツールを開発した．プロトタイプの出力結果を ROS アプリケーションの開発者およびコードレビューの実務者に提供した結果，好意的な意見を得た．technical repor
CaMV35S プロモーター カイヘン ニ ヨル テンシャ カイシテン ノ シュウソク : ホンヤク エンハンサー ノ ノウリョク ニ チャクモクシテ
Get PDF奈良先端科学技術大学院大学修士(工学)master thesi
Symbolic regression for the interpretation of quantitative structure-property relationships
No full textThe interpretation of quantitative structure2013property relationships is important in the field of chemoinformatics. Although multivariate linear regression models are typically interpretable, they do not generally have high predictive abilities. Symbolic regression (SR) combined with genetic programming (GP) is a well-established technique for generating the mathematical expressions that describe the relationships within a dataset. However, SR sometimes produces complicated expressions that are hard for humans to interpret. This paper proposes a method for generating simpler expressions by incorporating three filters into GP-based SR. The filters are further combined with nonlinear least-squares optimization to give filter-introduced GP (FIGP), which improves the predictive ability of SR models while retaining simple expressions. As a proof-of-concept, the quantitative estimate of drug-likeness and the synthetic accessibility score are predicted based on the chemical structures of compounds. Overall, FIGP generates less-complicated expressions than previous SR methods. In terms of predictive ability, FIGP is better than GP, but is outperformed by a support vector machine with a radial basis function kernel. Furthermore, quantitative structure$2013activity relationship models are constructed for three matching molecular series with biological targets. In the case of one target, the activity prediction models given by FIGP exhibit better predictive ability than multivariate linear regression and support vector regression with the radial basis function kernel, whereas for the remaining cases, FIGP is slightly less accurate than multivariate linear regression.journal articl
Tailor-Made Poly(vinylamine) via Purple LED-Activated RAFT Polymerization of N-vinylformamide
No full textPhoto-iniferter reversible addition-fragmentation chain transfer (PI-RAFT) polymerization of N-vinylformamide (NVF) is demonstrated by using purple light. PNVFs with predetermined molar masses and narrow molar mass distributions are obtained. High RAFT chain-end fidelity is confirmed by matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) and electrospray-ionization time-of-flight mass spectrometry (ESI-TOF-MS), and chain extension experiment. To demonstrate the potential of this approach, an original poly(N-vinylpyrrolidone)-b-poly(N-vinylformamide) (PVP-b-PNVF) diblock copolymer is synthesized and characterized by aqueous size-exclusion chromatography (SEC), asymmetric flow field-flow fractionation (A4F), and 1H diffusion-ordered spectroscopy nuclear magnetic resonance (1H DOSY NMR). Finally, selective hydrolysis of PNVF block to corresponding pH-responsive poly(N-vinylpyrrolidone)-b-poly(N-vinylformamide) (PVP-b-PVAm) is performed.journal articl
Unsupervised learning with a physics-based autoencoder for estimating the thickness and mixing ratio of pigments
No full textLayered surface objects represented by decorated tomb murals and watercolors are in danger of deterioration and damage. To address these dangers, it is necessary to analyze the pigments’ thickness and mixing ratio and record the current status. This paper proposes an unsupervised autoencoder model for thickness and mixing ratio estimation. The input of our autoencoder is spectral data of layered surface objects. Our autoencoder is unique, to our knowledge, in that the decoder part uses a physical model, the Kubelka2013Munk model for the decoder, latent variables in the middle layer can be interpretable as the pigment thickness and mixing ratio. We conducted a quantitative evaluation using synthetic data and confirmed that our autoencoder provides a highly accurate estimation. We measured an object with layered surface pigments for qualitative evaluation and confirmed that our method is valid in an actual environment. We also present the superiority of our unsupervised autoencoder over supervised learning.journal articl
ニュウインチュウ ノ ニンチショウ コウレイシャ ニ タイスル ノウサギョウ オ フクメタ シュウダン リョウホウ ノ コウカ ノ タヘンリョウ トウケイテキ コウサツ
Get PDF奈良先端科学技術大学院大学博士(工学)doctoral thesi