• 한국진공학회:학술대회논문집
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• 한국진공학회 2011년도 제40회 동계학술대회 초록집
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• pp.32-32
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• 2011

Plasma etching is used in microelectronic processing for patterning of micro- and nano-scale devices. Commonly, optical emission spectroscopy (OES) is widely used for real-time endpoint detection for plasma etching. However, if the viewport for optical-emission monitoring becomes blurred by polymer film due to prolonged use of the etching system, optical-emission monitoring becomes impossible. In addition, when the exposed area ratio on the wafer is small, changes in the optical emission are so slight that it is almost impossible to detect the endpoint of etching. For this reason, as a simple method of detecting variations in plasma without contamination of the reaction chamber at low cost, a method of measuring plasma impedance is being examined. The object in this research is to investigate the suitability of using plasma impedance monitoring (PIM) with statistical approach for real-time endpoint detection of $SiO_2$ etching. The endpoint was determined by impedance signal variation from I-V monitor (VI probe). However, the signal variation at the endpoint is too weak to determine endpoint when $SiO_2$ film on Si wafer is etched by fluorocarbon plasma on inductive coupled plasma (ICP) etcher. Therefore, modified principal component analysis (mPCA) is applied to them for increasing sensitivity. For verifying this method, detected endpoint from impedance analysis is compared with optical emission spectroscopy (OES). From impedance data, we tried to analyze physical properties of plasma, and real-time endpoint detection can be achieved.

• 정보화연구
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• 제11권2호
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• pp.143-155
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• 2014

최근 국내의 전자, 금융, 전기, 서비스, 제조, 제약 등 기업의 형태를 막론하고 악의적인 해커를 통해 기업 보안사고가 발생되고 있으며 이로 인한 기업정보 손실의 피해가 매년 꾸준히 늘어가고 있다. 이에 대응하기 위해 국내 대다수 기업들은 기업 활동과 관련된 중요 정보를 보호하기 위해 노트북, 스마트폰, 태블릿 내 다양한 Endpoint 보안솔루션을 도입하고 있다. 그러나 무분별하게 도입되고 있는 Endpoint 보안솔루션 간에는 과다 예산, 동일한 기능으로 인한 충돌이나 성능 저하 등의 문제들이 발생하고 있으며, 이로 인한 추가적인 유지비용, 충돌 문제를 해결하기 위한 노력은 보안부서의 IT운영상의 새로운 어려움이 되고 있다. 본고에서는 이러한 Endpoint 보안솔루션 도입 및 운영상의 문제를 해결하기 위해서 PC를 중심으로 정보보호 거버넌스에 기반한 Endpoint보안 솔루션 도입 결정을 위한 프로세스를 마련하여 해결 방안으로 제시하고자 한다.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제43회 하계 정기 학술대회 초록집
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• pp.153-153
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• 2012

Endpoint detection with plasma impedance monitoring and self-plasma optical emission spectroscopy is demonstrated for dielectric layers etching processes. For in-situ detecting endpoint, optical-emission spectroscopy (OES) is used for in-situ endpoint detection for plasma etching. However, the sensitivity of OES is decreased if polymer is deposited on viewport or the proportion of exposed area on the wafer is too small. To overcome these problems, the endpoint was determined by impedance signal variation from I-V monitoring (VI probe) and self-plasma optical emission spectroscopy. In addition, modified principal component analysis was applied to enhance sensitivity for small area etching. As a result, the sensitivity of this method is increased about twice better than that of OES. From plasma impedance monitoring and self-plasma optical emission spectroscopy, properties of plasma and chamber are analyzed, and real-time endpoint detection is achieved.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2012년도 제42회 동계 정기 학술대회 초록집
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• pp.182-182
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• 2012

Plasma etching is used in various semiconductor processing steps. In plasma etcher, optical- emission spectroscopy (OES) is widely used for in-situ endpoint detection. However, the sensitivity of OES is decreased if polymer is deposited on viewport or the proportion of exposed area on the wafer is too small. Because of these problems, the object is to investigate the suitability of using plasma impedance monitoring (PIM) and self plasma optical emission spectrocopy (SPOES) with statistical approach for in-situ endpoint detection. The endpoint was determined by impedance signal variation from I-V monitor (VI probe) and optical emission signal from SPOES. However, the signal variation at the endpoint is too weak to determine endpoint when $SiO_2$ and SiNx layers are etched by fluorocarbon on inductive coupled plasma (ICP) etcher, if the proportion of $SiO_2$ and SiNx area on Si wafer are small. Therefore, modified principal component analysis (mPCA) is applied to them for increasing sensitivity. For verifying this method, detected endpoint from impedance monitoring is compared with optical emission spectroscopy.

• 융합보안논문지
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• 제18권3호
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• pp.19-25
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• 2018

엔드포인트 보안은 네트워크에 연결된 여러 개별 장치를 철저하게 보호함으로써 네트워크 보안을 보장하는 방법입니다. 본 연구에서는 엔드포인트 보안의 다양한 상용제품의 기능과 특 장점을 살펴본다. 그리고 클라우드, 모바일, 인공지능, 그리고 사물인터넷 기반의 초연결시대를 대비하여 날로 지능화되고 고도화되는 보안위협에 대응하기 위한 엔드포인트 보안의 중요성을 강조하고, 그 개선방안으로서 선제적인 보안 정책 구현, 실시간 탐지 및 필터링, 탐지 및 수정 등의 정보보안의 생명주기의 개선방안을 제시한다.

• 한국전기전자재료학회논문지
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• 제24권9호
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• pp.701-709
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• 2011

In semiconductor wafer fabrication, etching is one of the most critical processes, by which a material layer is selectively removed. Because of difficulty to correct a mistake caused by over etching, it is critical that etch should be performed correctly. This paper proposes a new approach for etch endpoint detection of small open area wafers. The traditional endpoint detection technique uses a few manually selected wavelengths, which are adequate for large open areas. As the integrated circuit devices continue to shrink in geometry and increase in device density, detecting the endpoint for small open areas presents a serious challenge to process engineers. In this work, a high-resolution optical emission spectroscopy (OES) sensor is used to provide the necessary sensitivity for detecting subtle endpoint signal. Partial Least Squares (PLS) method is used to analyze the OES data which reduces dimension of the data and increases gap between classes. Support Vector Machine (SVM) is employed to detect endpoint using the data after PLS. SVM classifies normal etching state and after endpoint state. Two data sets from OES are used in training PLS and SVM. The other data sets are used to test the performance of the model. The results show that the trained PLS and SVM hybrid algorithm model detects endpoint accurately.

• 한국환경독성학회:학술대회논문집
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• 한국환경독성학회 2001년도 춘계심포지움 및 학술발표회
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• pp.118-118
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• 2001

Lemna gibba에 대한 성장저해시험은 OECD Lemna Growth Inhibition Test(1998)와 EPA Auqatic Toxicity Test Using Lemna sp, (OPPTS 850.4400)에 제시된 시험 방법으로, 시험물질에 대한 수중식물의 독성값을 알기 위하여 광범위하게 사용되고 있다. 본 실험은 각각의 Guideline에서 제시된 endpoint를 서로 비교하여, 가장 효과적으로 시험의 결과를 표현 할 수 있는 endpoint를 찾고자 하였으며, 이때 사용된 endpoint로는 잎의 수, 잎 면적, 습중량, 건중량을 이용하였다. (중략)

• 음성과학
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• 제5권1호
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• pp.81-88
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• 1999

This paper provides a method for speech detection. After first order FIR filtering on the speech signals, we applied the conventional method of endpoint detection which utilizes the energy as the criterion in separating signals from background noise. By FIR filtering, only the Fourier components with large values of [amplitude x frequency] become significant in energy profile. By applying this procedure to the 445-words database constructed from ETRI, we confirmed that the low-amplitude noise and/or the low-frequency noise are separated clearly from the speech signals, thereby enhancing the feasibility of ideal endpoint detections.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2001년도 추계학술발표회 논문집
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• pp.75-76
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• 2001

An endpoint detection method for speech signals utilizing hidden Markov model(HMM) is proposed. It turns out that the proposed algorithm is quite satisfactory to apply isolated word speech recognition.

• ETRI Journal
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• 제36권5호
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• pp.714-720
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• 2014

In this paper, we propose the use of data-driven probabilistic utterance-level decision logic to improve Weighted Finite State Transducer (WFST)-based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame-level speech/non-speech classification based on statistical hypothesis testing, and the second process is a heuristic-knowledge-based utterance-level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST-based approach. However, a WFST-based approach has the same limitations as conventional approaches in that the utterance-level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data-driven probabilistic utterance-level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy-speech corpora collected for an endpoint detection evaluation.