• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 추계학술대회 논문집 학회본부 B
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• pp.543-545
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• 1998

Robotic soccer is multi-agent system playing soccer game under given rule. This system consists of three mobile robots, vision sensor, action decision module, action execution module and communication module. This paper presents new action decision method using multi-layer neural networks.

• 한국압력기기공학회 논문집
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• 제5권2호
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• pp.40-44
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• 2009

In this study, Event Corrective Action Supporting System (ECAS) is developed for the accident evaluation in nuclear power plant. The ECAS system can be used in supporting regulator and/or operator under event situation in nuclear power plants. The ECAS system consists of 5 modules including failure location module, failure analysis module, failure integrity evaluation module, system vulnerability evaluation module, and reporting and operating experience feedback module. The ECAS system will be used as sub module of Knowledge-Based Event Evaluation Network (K-EvENT) which is developing for the against the accident in nuclear power plants.

• Korean Journal of Mathematics
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• 제7권1호
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• pp.71-77
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• 1999

We show that if the stable rank of $B^{\alpha}$ is one, then the stable rank of B is less than or equal to the order of G for any action of a finite group G. Also we give a short proof to the known fact that if the action of a finite group on a $C^*$-algebra B is saturated then the canonical conditional expectation from B to $B^{\alpha}$ is of index-finite type and the crossed product $C^*$-algebra is isomorphic to the algebra of compact operators on the Hilbert $B^{\alpha}$-module B.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.89-94
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• 1998

In this paper the authors propose a model about interaction of inner modules of autonomous robot which is possible to team walking action without external and explicit supervisor signal. A main feature of the model is that completed and fixed module for estimating robot's motion parameter by utilizing binocular parallax can be a supervisor for the module to team the walking action.

• 한국정보과학회논문지:소프트웨어및응용
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• 제27권8호
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• pp.902-911
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• 2000

언어의 의미정의모듈은 서로 밀접하게 관련 있는 개념과 연산의 의미구조를 모아 놓은 집합이다. 이 논문은 액션 의미표기법으로 의미정의모듈을 구성하고 확장하는 방법을 제시한다. 표현중심언어 핵심 모듈을 먼저 정의하고, 바인딩, 블록구조, 파라미터, 고차 표현식(함수)에 대한 확장 모듈을 정의한다. 그리고 의미의 획일성과 직교성이 보장되도록 의미정의 모듈들을 합성하면 더 복잡한 언어를 구축할 수 있음을 보인다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2017년도 전력전자학술대회
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• pp.596-597
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• 2017

For General Purpose Inverter dedicated in Motor drive, this market is blood market due to low market price. So, developing engineer must consider the cost reduction plan and do action. This inverter always needs to measure current and shunt solution can be one of cost reduction solution.

• 대한수학회논문집
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• 제9권2호
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• pp.415-418
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• 1994

Let G be a compact Lie group and let $S^1$ denote the unit circle in $R^2$ with the standard metric. Since every smooth compact Lie group action on $S^1$ is smoothly equivalent to a linear action (cf. [3J TH 2.0), we may think of $S^1$ with a smooth G-action as S(V) the unit circle of a real 2-dimensional orthogonal G-module V.(omitted)

• 호남수학학술지
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• 제41권2호
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• pp.357-368
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• 2019

We define the concepts of the first and the second module dual of a Banach space X. And also bring a new concept of module amenability for a Banach algebra ${\mathcal{A}}$. For inverse semigroup S, we will give a new action for ${\ell}^1(S)$ as a Banach ${\ell}^1(E_S)$-module and show that if S is amenable then ${\ell}^1(S)$ is ${\ell}^1(E_S)$-module amenable.

• 한국정보전자통신기술학회논문지
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• 제14권4호
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• pp.314-322
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• 2021

Skeleton-based action recognition has attracted considerable attention in human action recognition. Recent methods for skeleton-based action recognition employ spatiotemporal graph convolutional networks (GCNs) and have remarkable performance. However, most of them have heavy computational complexity for robust action recognition. To solve this problem, we propose a shuffle graph convolutional network (SGCN) which is a lightweight graph convolutional network using pointwise group convolution rather than pointwise convolution to reduce computational cost. Our SGCN is composed of spatial and temporal GCN. The spatial shuffle GCN contains pointwise group convolution and part shuffle module which enhances local and global information between correlated joints. In addition, the temporal shuffle GCN contains depthwise convolution to maintain a large receptive field. Our model achieves comparable performance with lowest computational cost and exceeds the performance of baseline at 0.3% and 1.2% on NTU RGB+D and NTU RGB+D 120 datasets, respectively.

• BMB Reports
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• 제52권4호
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• pp.227-238
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• 2019

GROWTH-REGULATING FACTORs (GRFs) are sequence-specific DNA-binding transcription factors that regulate various aspects of plant growth and development. GRF proteins interact with a transcription cofactor, GRF-INTERACTING FACTOR (GIF), to form a functional transcriptional complex. For its activities, the GRF-GIF duo requires the SWITCH2/SUCROSE NONFERMENTING2 chromatin remodeling complex. One of the most conspicuous roles of the duo is conferring the meristematic potential on the proliferative and formative cells during organogenesis. GRF expression is post-transcriptionally down-regulated by microRNA396 (miR396), thus constructing the GRF-GIF-miR396 module and fine-tuning the duo's action. Since the last comprehensive review articles were published over three years ago, many studies have added further insight into its action and elucidated new biological roles. The current review highlights recent advances in our understanding of how the GRF-GIF-miR396 module regulates plant growth and development. In addition, I revise the previous view on the evolutionary origin of the GRF gene family.