• Herbal Formula Science
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• v.31 no.3
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• pp.171-182
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• 2023

Objectives : Saposhnikoviae Radix (SR) and Glehniae Radix (GR) have been frequently used in traditional medicine to treat diseases related to 'wind' syndrome, but there have been cases where it has been mixed in a state where the plant of origin is not clear. In this study, to select materials for conducting preclinical cerebral infarction research, the network pharmacology analysis method was used to select suitable medicinal materials for the study. Methods : In this study, a Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) based network pharmacology analysis method was used, and oral bioavailability (OB), drug likeness (DL), Caco-2 and BBB permeability were utilized to select compounds with potential activity. For the values of each variable used in this study, OB ≥ 20%, DL ≥ 0.18, Caco-2 ≥ 0, and BBB ≥ -0.3 were applied, then networks of bioactive compounds, target proteins, and target diseases was constructed. STRING database was used to construct a protein-protein interaction network. Results : It was confirmed that SR rather than GR has various target proteins and target diseases based on network pharmacological analysis using TCMSP database. And it was analyzed that the bioactive compounds only in SR act more on neurovascular diseases, and both drugs are expected to be effectively used for cardiovascular diseases. Conclusions : In our future study, SR will be used in an ischemic stroke mouse model, and the mechanism of action will be explored focusing on apoptosis and cell proliferation.

• Health Policy and Management
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• v.14 no.2
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• pp.1-16
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• 2004

The study purpose was to find which factors affect selection of hospital network types. This study used the 1998 American Hospital Association Annual Survey Database from Health Forum. Among these U.S. hospitals, the researcher selected hospitals located in Metropolitan Statistical Areas. Therefore the final observation cases for analysis are 1,971 Metropolitan Statistical Area hospitals in the United States. To identify significant variables influencing hospital network types, the study used proportional odds logistics regression model on population size, Health Maintenance Organization penetration rate, and market competition rate of area including a hospital, types of hospital ownership, hospital bed size, proportion of Medicare patients and Medicaid patients in total hospital patients, and occupancy rate. Contrary to conventional wisdom, selection of hospital network types was influenced by population size of area which a hospital located, types of ownership, hospital bed size, and proportion of medicare patients rather than Health Maintenance Organization penetration. Population size 1,000,000-2,499,999 had the highest probability of selecting type IV (clinical-vertical integration) from an independent hospital, and a religious group owned hospitals and for-profit owned hospitals had the highest probability of selecting Type IV (clinical-vertical integration) from an independent hospital. A bed size had positive relation on selecting Type IV (clinical-vertical integration) from an independent hospital. Unlikely general belief that the selecting types of hospital network was determined by the change of health insurance policy such as Health Maintenance Organizations and Preferred Provider Organizations, the types of hospital network were influenced by community characteristics such as population size, and hospital characteristics.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.5
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• pp.629-636
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• 2015

This study carried out in order to investigate the most basic elements of suitability selection methods for composition of artificial reef. Acquired data by in-situ measurements and satellite remote sensing analysed in applying GIS. To identify the characteristic of marine environment around the West Sea, the South Sea and the East Sea of Korea, physical conditions-seabed sediment and depth, biological conditions-chlorophyll-${\alpha}$, chemical conditions-Sea Surface Temperature(SST) and DO were used. Suitable sites for artificial reef are selected Taean Peninsula, Geoje, Wando, Pohang, Seocheon, etc. From now on, it will be helpful to effectively utilize artificial reef as well as construct synthetic database. It is also expected to use basic data for artificial reef facilities management.

• International Journal of Highway Engineering
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• v.12 no.1
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• pp.61-69
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• 2010

In this paper, we present the methodology about an optimal probability distribution selection as well as survival rate estimation with the national highway database from 1999 to 2008. Probability paper methods are adopted to estimate the parameters of each hazard model. The goodness-of-fit test, such as the Anderson-Darling statistics, was performed. As a result, we found that Lognormal distributionan is an appropriate distribution of newly constructed sections as well as overlayed sections. We also ascertained that the results of survival rate for pavement life between the proposed method and observed data are similar. Such a selection methodology and measures based on reliability theory can provide useful information for maintenance plans in pavement management systems as long as additional life data on pavement sections are accumulated.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.339-346
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• 2003

This paper proposes a multiple classifier system having massive micro classifiers. The micro classifiers are trained by using a local set of training patterns. The k nearest neighboring training patterns of one training pattern comprise the local region for training a micro classifier. Each training pattern is incorporated with one or more micro classifiers. Two types of micro classifiers are adapted in this paper. SVM with linear kernel and SVM with RBF kernel. Classification is done by selecting the best micro classifier among the micro classifiers in vicinity of incoming test pattern. To measure the goodness of each micro classifier, the weighted sum of correctly classified training patterns in vicinity of the test pattern is used. Experiments have been done on Elena database. Results show that the proposed method gives better classification accuracy than any conventional classifiers like SVM, k-NN and the conventional classifier combination/selection scheme.

• International Journal of Highway Engineering
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• v.4 no.1 s.11
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• pp.123-134
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• 2002

Special pavement test sections were selected to develop a distress prediction model on asphalt pavement of National Highway. Experimental design was conducted for the selection of LTPP sections on in-service pavement(new and overlaid pavement) using several variables affecting pavement performance. Preliminary sections that satisfied the design template were chosen from the national highway database, and final selection was fixed through field inspection. The number of monitoring section is 95 including 47 overlaid pavement. A pavement distress data such as crack and rutting were collected for two years. An interim pavement performance analysis was peformed to show feasibility of performance monitoring program. Data related pavement such as traffic, weather, material characteristic and crack etc. should be collected for next project years and distress prediction model will be developed through the statistical analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2B
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• pp.130-142
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• 2009

In this paper, we propose a self-adaptation framework that selects a TCP variant adapted to current end-to-end path among available TCP variants. There is no single version of TCP that is suitable to all network environments since the causes for performance degradation are different one another according to characteristics of network environments. Thus, determining that which TCP variants should be selected in order to get best performance is very important. To enable adaptation through such determination, we integrate the existing network estimation schemes and some TCP variants into our framework then make light-weight performance knowledge database for TCP selection. Through implementing and evaluating the proposed framework we show that our solution can help TCP get high and stable performance on the various types of network environments by pure end-to-end.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.6
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• pp.857-870
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• 2017

The use of shield TBM is gradually increasing due to the urbanization of social infrastructures. Reliable estimation of advance rate is very important for accurate construction period and cost. For this purpose, it is required to develop the prediction model of advance rate that can consider the ground properties reasonably. Based on the database collected from field, statistical prediction procedure for field penetration index (FPI) was modularized in this study to calculate penetration rate of shield TBM. As output parameter, FPI was selected and various systems were included in this module such as, procedure of eliminating abnormal dataset, preprocessing of dataset and ridge regression with best subset selection. And it was finally validated by using field dataset.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.4
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• pp.521-530
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• 2021

Objectives: This was to examine and explore the elements of Size Korea 6th 3D head anthropometric database and to provide basic information for the selection of respirators in Korea. Methods: This was a pilot study for the first year of work in a two-year-project initiated at KOSHA in 2021. 3D head dimensions data were obtained from the Size Korea Center managing the Size Korea 6th 3D national anthropometry survey databases. The 3D head dimensions data, including 45 dimensions, were used in line with ISO standards (e.g., ISO/TS 16976-2) for examinations, comparisons, statistical analyses, etc. Results: A total of 3,088 subjects were finally determined in this study. The main features were: Male subjects were 52.5%; the highest age group was 15-29 at 36.7%; unhealthy weight group based on BMI was 31.7%; and survey area was the capital region. For the 6th 3D head dimensions data with 45 items, the means and standard deviations for 'Face length' were 115.9±7.5 cm for males and 107.3±6.9 cm for females respectively while those for 'Face width' item were not available since there was no such item in the data. Numerous findings were discussed accordingly. Conclusions: This study showed that there were likely requirements for improvements in the 6th 3D head anthropometric data as follows: Standardization of Korean and English terms; addition of head dimensions items missed in the Size Korea survey; and reliability of generalizability for subjects, suggesting that the study results can be used for further studies or improvement of respirator selection in Korea.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.50-55
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• 2021

Multi-path system is a system in which utilizes various networks simultaneously. It is expected that multi-path system can enhance communication speed, reliability, security of network. In this paper, we focus on path selection in multi-path system. To select optimal path, we propose deep reinforcement learning algorithm which is rewarded by the round-trip-time (RTT) of each networks. Unlike multi-armed bandit model, deep Q learning is applied to consider rapidly changing situations. Due to the delay of RTT data, we also suggest compensation algorithm of the delayed reward. Moreover, we implement testbed learning server to evaluate the performance of proposed algorithm. The learning server contains distributed database and tensorflow module to efficiently operate deep learning algorithm. By means of simulation, we showed that the proposed algorithm has better performance than lowest RTT about 20%.