• Korean Journal of Plant Resources
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• v.19 no.6
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• pp.660-664
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• 2006

The aerial part of Siegesbeckia pubescens (Compositae) has been used to treat rheumatoid arthritis and hypertension in the Oriental medicine. This crude drug has been used without process (SP-0) or with three times-process of steaming and drying (SP-3) or the nine times of that process (SP-9). To search for the antinociceptive anti-inflammatory components from this crude drug, activity-directed fractionation was performed on this crude drug. Since the $CHCl_3$ extract was shown to have a more potent effect than other extracts, it was subjected to silica gel & ODS column chromatography to yield two diterpene compounds (1). Compound 1 was structurally identified as ent-16 (H, 17-hydroxykauran-19-oic acid, which were tentatively named siegeskaurolic acid A. A main diterpene, siegeskaurolic acid A was tested for the antiiflammatory antinociceptive effects using both hot plate- and writhing anti-nociceptive assays and carrageenan-induced anti-inflammatory assays in mice and rats. Pretreatment with siegeskaurolic acid A (20 and 30mg/kg) significantly reduced the stretching episodes, action time of mice and carrageenan-induced edema. These results support that siegeskaurolic acid is a main diterpene responsible for antinociceptive and antiiflammatory action of S. pubescens. In addition, the assays on SP-0, SP-3 and SP-9 produced the experimental results that SP-9 had more significant effects than other two crude drugs. These results suggest that the processing on the original plant may lead to the higher pharmacological effect.

• Journal of the Korean Society of Systems Engineering
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• v.10 no.2
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• pp.89-95
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• 2014

In recent years, the United States have been several major failures of launch. As a result of these failures, activity of mission assurance valued. Mission assurance is defined as the application of systems engineering process towards the goal of achieving mission success. Therefore, mission assurance perform independent technical assessments throughout the concept and requirements definition, design, development, production, test, deployment, and operations phases. Space system program was emphasized the importance of the system engineering for that required huge cost and long term development. For this reason, independent review and verification of mission assurance is essential. Mission assurance gives us confidence to proceed with launch and best opportunity for mission success. In this study, framework of mission assurance is proposed by foreign case analysis.

• Journal of Microbiology and Biotechnology
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• v.19 no.5
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• pp.468-473
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• 2009

The antibiotic meroparamycin was produced in the free culture system of Streptomyces sp. strain MAR01. Five solid substrates (rice, wheat bran, Quaker, bread, and ground corn) were screened for their ability to support meroparamycin production in solid-state fermentation. In batch culture, wheat bran recorded the highest antibacterial activity with the lowest residual substrate values. The highest residual substrate values were recorded for both ground corn and Quaker. On the other hand, no antibacterial activity was detected for rice as a solid substrate. The use of the original strength of starch-nitrate medium in the solid-state fermentation gave a lower antibacterial activity compared with the free culture system. Doubling the strength of this medium resulted in the increase in the activity to be equivalent to the free culture. The initial pH (7.0) of the culture medium and 2 ml of spore suspension (1 ml contains $5{\times}10^{9}spores/ml$) were the optima for antibiotic production. The water was the best eluent for the extraction of the antibiotic from the solid-state culture. Ten min was enough time to extract the antibiotic using a mixer, whereas, 60 min was required when shaking was applied. Semicontinuous production of meroparamycin using a percolation method demonstrated a more or less constant antibacterial activity over 4 runs ($450-480{\mu}g/ml$). The semicontinuous production of the antibiotic was monitored in a fixed-bed bioreactor and the maximum activity was attained after the fourth run ($510{\mu}g/ml$) and the overall process continued for 85 days.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.89-103
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• 2023

Obstructive sleep apnea (OSA) is one of the most prevalent sleep disorders that can lead to serious consequences, including hypertension and/or cardiovascular diseases, if not treated promptly. Continuous positive airway pressure (CPAP) is widely recognized as the most effective treatment for OSA, which needs the proper titration of airway pressure to achieve the most effective treatment results. However, the process of CPAP titration can be time-consuming and cumbersome. There is a growing importance in predicting personalized CPAP pressure before CPAP treatment. The primary objective of this study was to optimize the CPAP titration process for obstructive sleep apnea patients through EEG feature engineering with machine learning techniques. We aimed to identify and utilize the most critical EEG features to forecast key OSA predictive indicators, ultimately facilitating more precise and personalized CPAP treatment strategies. Here, we analyzed 126 OSA patients' PSG datasets before and after the CPAP treatment. We extracted 29 EEG features to predict the features that have high importance on the OSA prediction index which are AHI and SpO2 by applying the Shapley Additive exPlanation (SHAP) method. Through extracted EEG features, we confirmed the six EEG features that had high importance in predicting AHI and SpO2 using XGBoost, Support Vector Machine regression, and Random Forest Regression. By utilizing the predictive capabilities of EEG-derived features for AHI and SpO2, we can better understand and evaluate the condition of patients undergoing CPAP treatment. The ability to predict these key indicators accurately provides more immediate insight into the patient's sleep quality and potential disturbances. This not only ensures the efficiency of the diagnostic process but also provides more tailored and effective treatment approach. Consequently, the integration of EEG analysis into the sleep study protocol has the potential to revolutionize sleep diagnostics, offering a time-saving, and ultimately more effective evaluation for patients with sleep-related disorders.

• Journal of the Korean Ceramic Society
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• v.43 no.2 s.285
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• pp.79-84
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• 2006

We studied the microstructure and magnetic property of the pulsed DC magnetron sputtered $Zn_{\0.8}Co_{0.2}O$ film as a function of substrate temperatures. The X-ray patterns of the $Zn_{\0.8}Co_{0.2}O$ film showed a strong (002) preferential orientation at $500^{\circ}C$. The films with a crystallite size of 23-35 nm were grown in the form of nano-sized structure and this tendency was remarkable with increasing substrate temperature. The UV-visible result showed that the $Zn_{\0.8}Co_{0.2}O$ film prepared above $300^{\circ}C$ has a high optical transmittance of over $80\%$ in the visible region. The absorption bands were observed due to sp-d interchange action by $Co^{2+}$ complex ion and dd transition in the region from 500 to 700nm. The resistivity of the film was below $10^{-1}\;\Omega-cm\;above\;300^{\circ}C$. The AGM analysis results for the all films showed the magnetic hysteresis curves of ferromagnetic nature. The low electrical resistivity and room temperature ferromagnetism of ZnCoO thin films 'deposited above $300^{\circ}C$ suggested the possibility for the application to Diluted Magnetic Semiconductors (DMSs).

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.43-49
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• 2004

The classification time required by conventional multi-class SVMs(Support Vector Machines) greatly increases as the number of pattern classes increases. This is due to the fact that the needed set of binary class SVMs gets quite large. In this paper, we propose a method to reduce the number of classes by using nearest neighbor rule (NNR) in the principle component analysis and linear discriminant analysis (PCA+LDA) feature subspace. The proposed method reduces the number of face classes by selecting a few classes closest to the test data projected in the PCA+LDA feature subspace. Results of experiment show that our proposed method has a lower error rate than nearest neighbor classification (NNC) method. Though our error rate is comparable to the conventional multi-class SVMs, the classification process of our method is much faster.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.137-145
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• 2010

Digital vessel have to accurate and efficient mange the digital data from various sensors in the digital vessel. But, In sensor network, it is difficult to transmit and analyze the entire stream data depending on limited networks, power and processor. Therefore it is suitable to use alternative stream data processing after classifying the continuous stream data. In this paper, We propose efficient processing method that arrange some sensors (temperature, humidity, lighting, voice) and process query based on sliding window for efficient input stream and pre-clustering using multiple Support Vector Machine(SVM) algorithm and manage hash table to summarized information. Processing performance improve as store and search and memory using hash table and usage reduced so maintain hash table in memory. We obtained to efficient result that accuracy rate and processing performance of proposal method using 35,912 data sets.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.54-60
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• 2010

The local appearance-based method is one of the face recognition methods that divides face image into small areas and extracts features from each area of face image using statistical analysis. It collects classification results of each area and decides identity of a face image using a voting scheme by integrating classification results of each area of a face image. The conventional local appearance-based method divides face images into small pieces and uses all the pieces in recognition process. In this paper, we propose a local appearance-based method that makes use of only the relatively important facial components. The proposed method detects the facial components such as eyes, nose and mouth that differs much from person to person. In doing so, the proposed method detects exact locations of facial components using support vector machines (SVM). Based on the detected facial components, a number of small images that contain the facial parts are constructed. Then it extracts features from each facial component image using principal components analysis (PCA). We compared the performance of the proposed method to those of the conventional methods. The results show that the proposed method outperforms the conventional local appearance-based method while preserving the advantages of the conventional local appearance-based method.

• Journal of the Korean Ceramic Society
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• v.42 no.7 s.278
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• pp.475-482
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• 2005

Zn$_{l-x}$Co$_{x}$O (x = 0.05 - 0.20) films were grown on Coming 7059 glass by sol-gel process. A homogeneous and stable Zn$_{l-x}$Co$_{x}$O sol was prepared by dissolving zinc acetate dihydrate (Zn(CH$_{3}$COO)$_{2}$$\cdot$2H$_{2}$O), cobalt acetate tetrahydrate ((CH$_{3}$)$_{2}$$\cdot$CHOH) and aluminium chloride hexahydrate (AlCl$_{3}$ $\cdot$ 6H$_{2}$O) as solute in solution of isopropanol ((CH$_{3}$)$_{2}$$\cdot$CHOH) and monoethanolamine (MEA:H$_{2}$NCH$_{2}$CH$_{2}$OH). The films grown by spin coating method were postheated in air at 650°C for 1 h and annealed in the condition of vacuum (5 $\times$ 10$^{-6}$ Torr) at 300$^{\circ}C$ for 30 min and investigated the nature of c-axis preferred orientation and physical properties with different Co concentrations. Znl_xCOxO thin films with different Co concentrations were well oriented along the c-axis, but especially a highly c-axis oriented Zn$_{l-x}$Co$_{x}$O thin film was grown at 10 at$\%$ Co concentration. The transmittance spectra showed that Zn$_{l-x}$Co$_{x}$O thin films occur typical d-d transitions and sp-d exchange interaction became activated with increasing Co concentration. The electrical resistivity of the films at 10 at$\%$ Co had the lowest value due to the highest c-axis orientation. X-ray photoelectron spectroscopy and alternating gradient magnetometer analyses indicated that no Co metal cluster was formed, and the ferromagnetic properties appeared, respectively. The characteristics of the electrical resistivity and room temperature ferromagnetism of Zn$_{l-x}$Co$_{x}$O thin films suggested the possibility for the application to dilute magnetic semiconductors.