• 한국통신학회논문지
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• 제35권9B호
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• pp.1322-1329
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• 2010

As body sensor network (BSN) research becomes mature, the need for managing power consumption of sensor nodes has become evident since most of the applications are designed for continuous monitoring. Real time Electrocardiograph (ECG) analysis on sensor nodes is proposed as an optimal choice for saving power consumption by reducing data transmission overhead. Smart sensor nodes with the ability to categorize lately detected ECG cycles communicate with base station only when ECG cycles are classified as abnormal. In this paper, ECG classification algorithms are described, which categorize detected ECG cycles as normal or abnormal, or even more specific cardiac diseases. Our Euclidean distance (ED) based classification method is validated to be most power efficient and very accurate in determining normal or abnormal ECG cycles. A close comparison of power efficiency and classification accuracy between our ED classification algorithm and generalized linear model (GLM) based classification algorithm is provided. Through experiments we show that, CPU cycle power consumption of ED based classification algorithm can be reduced by 31.21% and overall power consumption can be reduced by 13.63% at most when compared with GLM based method. The accuracy of detecting NSR, APC, PVC, SVT, VT, and VF using GLM based method range from 55% to 99% meanwhile, we show that the accuracy of detecting normal and abnormal ECG cycles using our ED based method is higher than 86%.

• 대한안전경영과학회지
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• 제19권1호
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• pp.157-167
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• 2017

The two-way quality theory has been widely used as a method for classifying quality attributes for several decades. In particular, the Kano model that classifies attributes into not just conventional one-dimensional but must-be and attractive has gained popularity due to its applicability and ease of use. However, the wordings of the five alternatives in the Kano's questionnaire has been criticised for unclear meanings. This study proposes a new two-way model to classify attributes using 5-point Likert scale alternatives. For this, the current paper investigated a case of TV sets to examine how the proposed model works in comparison with the Kano model. The application results of the proposed model are different from the original one. The two-way model classifies quality attributes in more detail such as the "one-dimensional with an attractive tendency" attribute, which has a greater influence on satisfaction than dissatisfaction, the opposite "one-dimensional with a must-be tendency" attribute, and "highly one-dimensional" and "less one-dimensional" attributes. In this study, a potential satisfaction coefficient (PSC), a potential dissatisfaction coefficient (PDC), and an average potential coefficient (APC) to manage quality attributes are proposed and discussed for their utilization.

• 한국문헌정보학회지
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• 제44권3호
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• pp.137-154
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• 2010

본 연구는 오픈액세스 출판을 위한 수입원들이 국내의 무료 오픈액세스 학술지와 유료 원문 학술지에서 어떻게 도입되고 있는지를 분석하고자 하였다. 그 결과 무료 오픈액세스 학술지와 유료 원문 학술지 간에 분명한 차이는 없었으며, 오히려 유료 원문서비스 학술지에서 오픈액세스 학술지 모델의 특성이 많이 나타나고 있음을 알 수 있었다. 즉, 논문처리비용을 저자측에 요구하고 있었으며, 연구비 수혜논문에 대한 추가 게재료를 부과하고, 외부기관으로부터 지원금을 받는 경우도 무료 오픈액세스 학술지보다 더 많았다. 이것은 국내의 유료 원문 학술지가 무료 오픈액세스로 전환될 가능성이 상당히 높다는 것을 의미한다.

• Transactions on Electrical and Electronic Materials
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• 제14권2호
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• pp.71-77
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• 2013

Advanced semiconductor manufacturing technology requires methods to maximize tool efficiency and improve product quality by reducing process variability. Real-time plasma process monitoring and diagnosis have become crucial for fault detection and classification (FDC) and advanced process control (APC). Additional sensors may increase the accuracy of detection of process anomalies, and optical monitoring methods are non-invasive. In this paper, we propose the use of a chromatic data acquisition system for real-time in-situ plasma process monitoring called the Plasma Eyes Chromatic System (PECS). The proposed system was initially tested in a six-inch research tool, and it was then further evaluated for its potential to detect process anomalies in an eight-inch production tool for etching blanket oxide films. Chromatic representation of the PECS output shows a clear correlation with small changes in process parameters, such as RF power, pressure, and gas flow. We also present how the PECS may be adapted as an in-situ plasma arc detector. The proposed system can provide useful indications of a faulty process in a timely and non-invasive manner for successful run-to-run (R2R) control and FDC.

• 반도체디스플레이기술학회지
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• 제18권2호
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• pp.48-52
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• 2019

Virtual metrology, which is one of APC techniques, is a method to predict characteristics of manufactured films using machine learning with saving time and resources. As the photoresist is no longer a mask material for use in high aspect ratios as the CD is reduced, hard mask is introduced to solve such problems. Among many types of hard mask materials, amorphous carbon layer(ACL) is widely investigated due to its advantages of high etch selectivity than conventional photoresist, high optical transmittance, easy deposition process, and removability by oxygen plasma. In this study, VM using different machine learning algorithms is applied to predict the thickness of ACL and trained models are evaluated which model shows best prediction performance. ACL specimens are deposited by plasma enhanced chemical vapor deposition(PECVD) with four different process parameters(Pressure, RF power, $C_3H_6$ gas flow, $N_2$ gas flow). Gradient boosting regression(GBR) algorithm, random forest regression(RFR) algorithm, and neural network(NN) are selected for modeling. The model using gradient boosting algorithm shows most proper performance with higher R-squared value. A model for predicting the thickness of the ACL film within the abovementioned conditions has been successfully constructed.

• International Journal of Control, Automation, and Systems
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• 제3권4호
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• pp.571-579
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• 2005

In this paper, we proposed an algorithm for arrhythmia classification, which is associated with the reduction of feature dimensions by linear discriminant analysis (LDA) and a support vector machine (SVM) based classifier. Seventeen original input features were extracted from preprocessed signals by wavelet transform, and attempts were then made to reduce these to 4 features, the linear combination of original features, by LDA. The performance of the SVM classifier with reduced features by LDA showed higher than with that by principal component analysis (PCA) and even with original features. For a cross-validation procedure, this SVM classifier was compared with Multilayer Perceptrons (MLP) and Fuzzy Inference System (FIS) classifiers. When all classifiers used the same reduced features, the overall performance of the SVM classifier was comprehensively superior to all others. Especially, the accuracy of discrimination of normal sinus rhythm (NSR), arterial premature contraction (APC), supraventricular tachycardia (SVT), premature ventricular contraction (PVC), ventricular tachycardia (VT) and ventricular fibrillation (VF) were $99.307\%,\;99.274\%,\;99.854\%,\;98.344\%,\;99.441\%\;and\;99.883\%$, respectively. And, even with smaller learning data, the SVM classifier offered better performance than the MLP classifier.

• 한국통신학회논문지
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• 제32권9C호
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• pp.826-833
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• 2007

본 논문에서는 CR (Cognitive Radio) 시스템의 무선 적응전송에 대한 연구 기반을 마련하기 위해 CR 시스템 환경 및 시나리오 모델을 제시하고, 제시된 시스템 환경 모델에서 CR 시스템을 위한 간섭온도 인지 기반의 적응 전송 기법을 제안한다. 제안된 CR 적응전송 기법은 CR-APC (CR-Adaptive Power Control)를 사용하여 주 사용자에게 간섭 영향을 미치지 않는 범위 내에서 CR 사용자에게 최대 전송전력을 제공하고, CR-AMC (CR-Adaptive Modulation and Coding)를 적용하여 주어진 채널 상태에서 CR 사용자에게 최적의 전송률을 보장할 수 있는 방식이다. 모의실험 결과, 제안된 CR 적응전송 기법을 사용한 경우 주 사용자에게는 간섭 영향을 거의 미치지 않아 비트오율 성능 열화가 거의 없었으며, CR 사용자에게는 주어진 채널 상태에서 최적의 전송률을 보장할 수 있음을 확인할 수 있다.

• JSTS:Journal of Semiconductor Technology and Science
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• 제11권3호
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• pp.135-145
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• 2011

Accurate process characterization and optimization are the first step for a successful advanced process control (APC), and they should be followed by continuous monitoring and control in order to run manufacturing processes most efficiently. In this paper, process characterization and recipe optimization methods with multiple outputs are presented in high density plasma-chemical vapor deposition (HDP-CVD) silicon dioxide deposition process. Five controllable process variables of Top $SiH_4$, Bottom $SiH_4$, $O_2$, Top RF Power, and Bottom RF Power, and two responses of interest, such as deposition rate and uniformity, are simultaneously considered employing both statistical response surface methodology (RSM) and neural networks (NNs) based genetic algorithm (GA). Statistically, two phases of experimental design was performed, and the established statistical models were optimized using performance index (PI). Artificial intelligently, NN process model with two outputs were established, and recipe synthesis was performed employing GA. Statistical RSM offers minimum numbers of experiment to build regression models and response surface models, but the analysis of the data need to satisfy underlying assumption and statistical data analysis capability. NN based-GA does not require any underlying assumption for data modeling; however, the selection of the input data for the model establishment is important for accurate model construction. Both statistical and artificial intelligent methods suggest competitive characterization and optimization results in HDP-CVD $SiO_2$ deposition process, and the NN based-GA method showed 26% uniformity improvement with 36% less $SiH_4$ gas usage yielding 20.8 ${\AA}/sec$ deposition rate.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2009년도 추계학술대회 논문집
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• pp.83-83
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• 2009

우수한 압전성을 가지는 PZT는 인체에 유해한 다량의 PbO을 함유하여 심각한 환경문제를 야기함은 물론 제조 공정 중 PbO 휘발 억제 시설 구비에 따른 경제적 부담 등 문제점이 지적되었다. 따라서 환경오염 및 가격경쟁력을 갖추기 위해 현재 무연 조성 세라믹스에 대한 많은 연구가 진행되고 있다. 최근 비납계 압전 세라믹의 연구는 비스무스 레이어형과 페로브스카이트 형 비납계 세라믹스의 연구가 활발히 진행되고 있다. 특히 $(Na,K)NbO_3$ 계는 페로브스카이트 구조를 가지는 비납계 세라믹으로 현재 많은 연구가 진행되고 있다. 이 물질은 PZT계와 유사하게 상전이(morphotropic phase boundary:MPB)영역을 가지고 있 으며 이 영역에서 높은 압전 특성을 보여주고 있다. 최근 $Na_{0.5}K_{0.5}NbO_3$에 $LiTaO_3$를 치환하여 우수한 압전 특성을 지니는 조성이 개발되고 있지만, 보통 소성법으로 제조된 세라믹스는 PZT계 세라믹스와 비교하여 특성이 떨어진다. 본 연구에서는 압전성이 우수한 $(Na_{0.44}K_{0.52}Li_{0.44})(Nb_{0.90}Sb_{0.06}Ta_{0.04})O_3$ 조성에 도너 도핑과 억셉터 도핑을 한 다음 전기기계결합계수, 압전상수, 유전상수의 변화를 평가하고, hardener 와 softener 특성이 본조성에서 나타나는지를 관찰하였다. 실험방법은 보통 소성법을 사용하였으며, 분쇄와 혼합은 직경 3 mm zirconia ball을 사용하여 볼밀 하였다. $850^{\circ}C$ 에서 5h 하소 후 $1100{\sim}1200^{\circ}C$ 에서 소결하고, 두께 1 mm로 연마한 다음 silver paste를 $650^{\circ}C$ 에서 소부하여 전극을 형성하였다. 제작된 시편은 $90^{\circ}C$의 실리콘유에서 3~4 kV/mm의 전계를 가해 20분간 분극 처리를 수행하였다. 제작된 시편의 압전전하 상수 값은 d33-meter(APC-8000)를 이용하여 측정하였고, 유전율, 전기기계결합계수 및 기계적품질계수 등은 임피던스 분석기 (impedance/gain phase analyzer)를 이용하여 특성을 측정 하였다. 또한 전압-분극 특성의 평가에는 강유전특성 측정기(ferroelectric tester: Precision-LC, Radiant Technologies, USA)를 이용하였다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권16호
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• pp.7277-7284
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• 2015

Background: The Wnt/${\beta}$-catenin signaling pathway is an important regulator of cellular functions such as proliferation, survival and cell adhesion. Wnt/${\beta}$-catenin signaling is associated with tumor initiation and progression; ${\beta}$-catenin mutations explain only 30% of aberrant signaling found in breast cancer, indicating that other components and/or regulation of the Wnt/${\beta}$-catenin pathway may be involved. Objective: We evaluated AXIN2 rs2240308 and rs151279728 polymorphisms, and expression profiles of ${\beta}$-catenin destruction complex genes in breast cancer patients. Materials and Methods: We collected peripheral blood samples from 102 breast cancer and 102 healthy subjects. The identification of the genetic variation was performed using PCR-RFLPs and DNA sequencing. RT-qPCR was used to determine expression profiles. Results: We found significant association of AXIN2 rs151279728 and rs2240308 polymorphisms with breast cancer risk. Significant increase was observed in AXIN2 level expression in breast cancer patients. Further analyses showed APC, ${\beta}$-catenin, CK1${\alpha}$, GSK3${\beta}$ and PP2A gene expression to be associated to clinic-pathological characteristics. Conclusions: The present study demonstrated, for the first time, that AXIN2 genetic defects and disturbance of ${\beta}$-catenin destruction complex expression may be found in breast cancer patients, providing additional support for roles of Wnt/${\beta}$-catenin pathway dysfunction in breast cancer tumorigenesis. However, the functional consequences of the genetic alterations remain to be determined.