• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.237.1-237.1
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• 2014

Etching is one of the most important steps in semiconductor manufacturing. In etch process control a critical task is to stop the etch process when the layer to be etched has been removed. If the etch process is allowed to continue beyond this time, the material gets over-etched and the lower layer is partially removed. On the other hand if the etch process is stopped too early, part of the layer to be etched still remains, called under-etched. Endpoint detection (EPD) is used to detect the most accurate time to stop the etch process in order to avoid over or under etch. The goal of this research is to develop a hardware and software system for EPD. The hardware consists of an Optical Plasma Monitor (OPM) sensor which is used to continuously monitor the plasma optical emission intensity during the etch process. The OPM software was developed to acquire and analyze the data to perform EPD. Our EPD algorithm is based on the following theory. As the etch process starts the plasma generated in the vacuum is added with the by-products from the etch reactions on the layer being etched. As the endpoint reaches and the layer gets completely removed the plasma constituents change gradually changing the optical intensity of the plasma. Although the change in optical intensity is not apparent, the difference in the plasma constituents when the endpoint has reached leaves a unique signature in the data gathered. Though not detectable in time domain, this signature could be obscured in the frequency spectrum of the data. By filtering and analysis of the changes in the frequency spectrum before and after the endpoint we could extract this signature. In order to do that, first, the EPD algorithm converts the time series signal into frequency domain. Next the noise in the frequency spectrum is removed to look for the useful frequency constituents of the data. Once these useful frequencies have been selected, they are monitored continuously in time and using a sub-algorithm the endpoint is detected when significant changes are observed in those signals. The experiment consisted of three kinds of etch processes; ashing, SiO2 on Si etch and metal on Si etch to develop and evaluate the EPD system.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.32 no.2
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• pp.24-58
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• 2019

Objectives : The purpose of this study is to confirm the Efficacy and Safety of "Functional cosmetics containing Humulus japonicus Extract" on dry skin due to mild atopic dermatitis. Methods : A total of 48 patients who visited Semyung Oriental Medical Center from March 20th, 2018 to July 5th, 2018 were included in the study. In this study, the patients were treated with Functional cosmetics containing Humulus japonicus Extract and positive control group. For 6 weeks of gross examination, instrumental assessment were made before and after the study to evaluate how well the products for treatment group with positive control products for control group in recovering the dry skin barriers by mild atopic dermatitis. Results : 1. In the primary endpoint, Skin Hydration showed a statistically significant increase and Transepidermal Water Loss(TEWL) showed a statistically significant decrease in treatment group between Baseline and 6 weeks. 2. In the secondary endpoint, Skin Hydration showed a statistically significant increase in treatment group between Baseline and 3 weeks, but TEWL showed no statistical significance. 3. In the secondary endpoint, Skin Hydration showed a statistically significant increase in treatment group between 3 weeks and 6 weeks, but TEWL showed no statistical significance. 4. In the secondary endpoint, Change of Skin Hydration and TEWL between treatment and control group showed a statistical significance in 6 weeks. 5. In the secondary endpoint, Change of Skin Hydration of 1cm below the medial aspect of the elbow between treatment and control group showed a statistical significance in 3 weeks. 6. In the secondary endpoint, Change of Skin Hydration between treatment and control group showed a statistical significance in 3 weeks and 6 weeks except Center between the medial aspect of the elbow and the wrist in 3 weeks, and Change of TEWL between treatment and control group showed a statistical significance in 6 weeks. 7. To evaluate the safety of the products for the human body, Adverse events, EASI Score, Itching Symptoms Assessment, vital sign check were conducted; There were no severe adverse events during this study. And both experimental group and control group showed no abnormal level. Therefore, it is suggested that products, if used for certain period, should be safe for the human body. Conclusions : According to the above experiments, it is suggested that "Functional cosmetics containing Humulus japonicus Extract" should be effective for dry skin due to mild atopic dermatitis.

• Bulletin of the Korean Mathematical Society
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• v.45 no.3
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• pp.563-571
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• 2008

We deduce the necessary conditions for the optimality of endpoint constrained optimal control problem. These conditions comprise the adjoint equation, the maximum principle and the transversality condition. We assume that the cost function is merely differentiable. Therefore the technique under Lipschitz continuity hypothesis is not directly applicable. We introduce Fermat's rule and value function technique to obtain the results.

• Communications for Statistical Applications and Methods
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• v.13 no.1
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• pp.125-134
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• 2006

This study confirms that the regression model of endpoint of interval outputs is not identical with that of the other endpoint of interval outputs in interval regression models proposed by Tanaka et al. (1987) and constructs interval regression models using the best regression model given by variable selection. Also, this paper suggests a method to minimize the sum of lengths of a symmetric difference among observed and predicted interval outputs in order to estimate interval regression coefficients in the proposed model. Some examples show that the interval regression model proposed in this study is more accuracy than that introduced by Inuiguchi et al. (2001).

• Toxicological Research
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• v.19 no.2
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• pp.133-139
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• 2003

Allergic contact dermatitis may be caused by a wide variety of chemicals. A murine local lymph node assay (LLNA) has been developed as an alternative to guinea pig models for assessing the contact sensitization potential of chemical. However, there is a need to develop a nonradioisotopic endpoint for the LLNA, because of the radioisotopic method's requiring the use of special facilities. In this study, we investigated the development of a nonradioisotopic endpoint for LLNA using ELISA (enzyme-linked immunosorbent assay). Female Balb/c mice were treated by the topical application on the dorsum of both ears with four different strong sensitizers, 2,4-dinitrochlorobenzene (DNCB), oxazolone (OXZ), toluene diisocyanate (TDI), and trimellitic anhydride (TMA), and a strong irritant, sodium lauryl sulfate (SLS), once daily for three consecutive days. The proliferation of cells in the auricular Iymph node was analyzed by means of the labelling index (Ll) of bromodeoxyuridine (BrdU) incorporation into cells. The weights of the Iymph nodes in the mice treated with allergens, DNCB, OXZ, TDl and TMA were increased compared to the vehicle control. The stimulation index (Sl) of mice treated with DNCB, OXZ, TDl, and TMA was over three-fold increase compared to the vehicle control. However, the S1 of mice exposed to SLS was not significantly increased compared to the vehicle control, while the lymph node weight of SLS was significantly increased. These results suggest that the LLNA modified endpoint using ELISA based on BrdU incorporation could provide a useful method of screening for irritants and allergens.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1A
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• pp.58-65
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• 2002

This paper deals with a delay problem in the endpoint detection of double-talk detection algorithm using correlation coefficient in the acoustic echo canceller. In case that past power is much bigger than current power like at the end of double-talking period, the power, estimated using forgetting factor, decreases slowly to cause a delay problem in the endpoint detection. In this paper, two methods are proposed to solve this problem. One is that the current power is periodically replaced by a new average power and the other is that the past power in recursive equation is periodically removed or replaced by other values. The simulation results show that proposed methods outperform conventional method in the endpoint of double-talking periods without increasing the computational burden much more.

• Korean Journal of Metals and Materials
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• v.56 no.11
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• pp.813-821
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• 2018

The basic oxygen furnace (BOF) steelmaking process in the steel industry is highly complicated, and subject to variations in raw material composition. During the BOF steelmaking process, it is essential to maintain the carbon content and the endpoint temperature at their set points in the liquid steel. This paper presents intelligent models used to estimate the endpoint temperature in the basic oxygen furnace (BOF) steelmaking process. An artificial neural network (ANN) model and a least-squares support vector machine (LSSVM) model are proposed and their estimation performance compared. The classical partial least-squares (PLS) method was also compared with the others. Results of the estimations using the ANN, LSSVM and PLS models were compared with the operation data, and the root-mean square error (RMSE) for each model was calculated to evaluate estimation performance. The RMSE of the LSSVM model 15.91, which turned out to be the best estimation. RMSE values for the ANN and PLS models were 17.24 and 21.31, respectively, indicating their relative estimation performance. The essential input parameters used in the models can be selected by sensitivity analysis. The RMSE for each model was calculated again after a sequential input selection process was used to remove insignificant input parameters. The RMSE of the LSSVM was then 13.21, which is better than the previous RMSE with all 16 parameters. The results show that LSSVM model using 13 input parameters can be utilized to calculate the required values for oxygen volume and coolant needed to optimally adjust the steel target temperature.

• Korean Journal of Clinical Pharmacy
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• v.34 no.2
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• pp.134-139
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• 2024

Background: Increasing numbers of studies and research about artificial intelligence (AI) and machine learning (ML) have led to their application in clinical trials. The purpose of this study is to analyze computer-based new technologies (AI/ML) applied on clinical trials registered on ClinicalTrials.gov to elucidate current usage of these technologies. Methods: As of March 1st, 2023, protocols listed on ClinicalTrials.gov that claimed to use AI/ML and included at least one of the following interventions-Drug, Biological, Dietary Supplement, or Combination Product-were selected. The selected protocols were classified according to their context of use: 1) drug discovery; 2) toxicity prediction; 3) enrichment; 4) risk stratification/management; 5) dose selection/optimization; 6) adherence; 7) synthetic control; 8) endpoint assessment; 9) postmarketing surveillance; and 10) drug selection. Results: The applications of AI/ML were explored in 131 clinical trial protocols. The areas where AI/ML was most frequently utilized in clinical trials included endpoint assessment (n=80), followed by dose selection/optimization (n=15), risk stratification/management (n=13), drug discovery (n=4), adherence (n=4), drug selection (n=1) and enrichment (n=1). Conclusion: The most frequent application of AI/ML in clinical trials is in the fields of endpoint assessment, where the utilization is primarily focuses on the diagnosis of disease by imaging or video analyses. The number of clinical trials using artificial intelligence will increase as the technology continues to develop rapidly, making it necessary for regulatory associates to establish proper regulations for these clinical trials.

• Korean Circulation Journal
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• v.52 no.5
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• pp.354-364
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• 2022

Background and objectives: To compare the safety and efficacy of a new everolimus-eluting stent with an abluminal-coated biodegradable polymer (Osstem Cardiotec Centum) with those of the Xience Alpine stent (Xience). Methods: This randomized, prospective, multicenter, parallel-designed, single-blind trial was conducted among patients with myocardial ischemia undergoing percutaneous coronary intervention (PCI) from 21st September 2018 until 3rd July 2020. The primary efficacy endpoint was in-segment late lumen loss (LLL) at 270 days after the procedure and the primary safety endpoints were major adverse cardiac events (MACE), composite of cardiac death, myocardial infarction, and target lesion revascularization. Results: We enrolled 121 patients and analyzed 113 patients who finished 270 days of follow-up for the primary efficacy endpoint. The mean age of the participants was 66.8 years. As for the primary efficacy endpoint, LLL of the Osstem Cardiotec Centum group was 0.09±0.13 mm and that of the Xience group was 0.12±0.14 mm (upper limit of 1-sided 95% confidence interval, 0.02; p for non-inferiority, 0.0084). This result demonstrates the non-inferiority of the Osstem Cardiotec Centum. As for the primary safety endpoint, MACE occurred in one patient (1.59% of the Xience group). Meanwhile, no MACE occurred in the Osstem Cardiotec Centum group. Conclusions: The Osstem Cardiotec Centum is non-inferior to the Xience Alpine^® stent and is confirmed to be safe. It could be safely and effectively applied to patients with coronary artery disease undergoing PCI.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.37-39
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• 2009

In the research of speech recognition, locating the beginning and end of a speech utterance in a background of noise is of great importance. Since the background noise presenting to record will introduce disturbance while we just want to get the stationary parameters to represent the corresponding speech section, in particular, a major source of error in automatic recognition system of isolated words is the inaccurate detection of beginning and ending boundaries of test and reference templates, thus we must find potent method to remove the unnecessary regions of a speech signal. The conventional methods for speech endpoint detection are based on two simple time-domain measurements - short-time energy, and short-time zero-crossing rate, which couldn't guarantee the precise results if in the low signal-to-noise ratio environments. This paper proposes a novel approach that finds the Lyapunov exponent of time-domain waveform. This proposed method has no use for obtaining the frequency-domain parameters for endpoint detection process, e.g. Mel-Scale Features, which have been introduced in other paper. Comparing with the conventional methods based on short-time energy and short-time zero-crossing rate, the novel approach based on time-domain Lyapunov Exponents(LEs) is low complexity and suitable for Digital Isolated Word Recognition System.