• The monthly packaging world
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• s.268
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• pp.86-90
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• 2015

• The monthly packaging world
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• s.281
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• pp.74-78
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• 2016

• The monthly packaging world
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• s.276
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• pp.82-85
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• 2016

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.149-158
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• 1996

In this paper we describe designing and implementing a digital neural chip and a parallel neural machine for simulating large scale neural netsorks. The chip is a single-chip multiprocessor which has four digiral neural processors (DNP-II) of the same architecture. Each DNP-II has program memory and data memory, and the chip operates in MIMD (multi-instruction, multi-data) parallel processor. The DNP-II has the instruction set tailored to neural computation. Which can be sed to effectively simulate various neural network models including on-chip learning. The DNP-II facilitates four-way data-driven communication supporting the extensibility of parallel systems. The parallel neural machine consists of a host computer, processor boards, a buffer board and an interface board. Each processor board consists of 8*8 array of DNP-II(equivalently 2*2 neural chips). Each processor board acn be built including linear array, 2-D mesh and 2-D torus. This flexibility supports efficiency of mapping from neural network models into parallel strucgure. The neural system accomplishes the performance of maximum 40 GCPS(giga connection per second) with 16 processor boards.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.533-536
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• 1998

The intent of this paper is to describe a neural network structure called dynamic neural processor(DNP), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. Computer simulations are provided to demonstrate the effectiveness of the proposed learning using the DNP.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.890-893
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• 1999

The intent of this paper is to describe a neural network structure called dynamic neural processor(DNP), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. Computer simulations are demonstrate the effectiveness of the Proposed learning using the DNP.

• YAKHAK HOEJI
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• v.41 no.2
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• pp.268-272
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• 1997

We studied the action of methyleugenol on immediate hypersensitivity. Methyleugenol completely inhibited systemic anaphylaxis induced by compound 48/80 in mice. Methyleugenol al so inhibited local anaphylaxis induced by anti-dinitrophenyl (DNP) IgE. Moreover, methyleugenol dose-dependently inhibited histamine release in peritoneal mast cells activated by compound 48/80 or anti-DNP IgE. These results suggest that the inhibitory effect of methyleugenol on anaphylaxis induced by compound 48/80 or anti-DNP IgE is due to, in part at least, the membrane stabilization of mast cells.

• Review of KIISC
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• v.24 no.3
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• pp.44-53
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• 2014

최근 전력 제어시스템의 자동화 효율(Automation Efficiency)과 상호운용성(Interoperability)을 높이기 위해 공개된 표준 프로토콜과 상용 시스템을 사용하게 되었고 외부망과의 연결 필요성이 증가됨에 따라 SCADA 시스템에 대한 공격 위협성이 증가하고 있다. 그러나 전력 제어시스템의 중앙제어장치(Master)와 현장 운영장치(Outstation) 간 데이터를 교환하기 위한 통신 규격인 DNP(Distributed Network Protocol) 프로토콜은 보안을 고려하지 않고 개발되어 통신규격 자체에 보안 취약점을 가지고 있었고, 제어시스템에 대한 사이버 위협 요소도 크게 증가하고 있다. 정보통신 기술의 발전과 개방형 망이 갖는 장점을 취하기 위하여 DNP3 프로토콜은 TCP/IP 네트워크를 지원하게 되었고, TCP/IP 네트워크가 가지고 있는 기존의 보안 취약점(Vulnerability)이 전력 제어시스템 및 통신망에 그대로 이전되고 있어 중앙제어장치와 현장운영장치 간에 DNP3 표준에서 제시한 사항 외에 추가적인 보안 메커니즘이 요구된다. 본 논문에서는 SCADA 시스템이 보안성을 갖고 안전하게 운용되기 위한 IEEE DNP3 표준과 ISO/IEC TC57 WG15에서 권고하고 있는 IEC 62351 표준의 인증 및 암호화 메커니즘을 소개한다.

• Journal of the Korean Magnetic Resonance Society
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• v.23 no.3
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• pp.81-86
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• 2019

Overhauser dynamic nuclear polarization (O-DNP) has been an efficient method to boost the thermal nuclear polarization in liquids at room temperature. However, O-DNP for a benchtop NMR using a permanent magnet has remained unexplored yet. In this work, we report the development of an O-DNP system adopting a permanent magnet of 1.6 T. Q-band (~43 GHz) high-power amplifier produced 6 W microwave for saturation. Instead of resonator, we used an open-type antenna for the microwave irradiation. For several representative small molecules, we measured the concentration and frequency dependences of the enhancement factor. This work paves the way for the development of a benchtop DNP-NMR system overcoming its disadvantage of low quality signal when using a permanent magnet.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.931-934
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• 2008

SCADA 시스템과 관련된 많은 표준 프로토콜이 등장하고 있으며, 이들 프로토콜들이 공존하는 형태로 발전할 것으로 예상된다. 본 논문은 범용 SCADA 게이트웨이 개발을 위해 DNP 3.0 응용 계층을 분석한 결과를 소개하고 있다. 여기에는 게이트웨이 설계 시 반드시 고려되어야 하는, DNP3.0 응용 계층의 객체 모델링과 객체 의미, 그리고 통신 기능이 포함된다.