• Perspectives in Nursing Science
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• v.8 no.2
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• pp.113-120
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• 2011

Purpose: The aim of this study was to develop and validate Detailed Clinical Models (DCMs) for pain assessment in nursing. Methods: First, we identified the entities of pain assessment from ICNP. We identified the attributes and values of the attributes to describe the entities in more detail by reviewing the literature. Data types and optionalities of the attributes were defined. Second, we modeled the DCMs by linking an entity and its corresponding attributes with values and by specifying the data types and optionalities of the attributes. Finally, the DCMs were validated by a group of domain experts using a content validity index. Results: In total, 19 DCMs with 11 attributes for pain assessment were developed. The experts' evaluations showed that the DCMs were valid enough to represent pain related information of nursing assessment. Conclusion: The DCMs developed in this study can be used in electronic nursing records. The DCMs for pain can ensure the semantic interoperability of pain related information in electronic nursing records.

• Korean Journal of Agricultural and Forest Meteorology
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• v.6 no.1
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• pp.49-60
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• 2004

Northern Gyeonggi Province(NGP), consisting of 3 counties, is the northernmost region in South Korea adjacent to the de-militarized zone with North Korea. To supplement insufficient spatial coverage of official climate data and climate atlases based on those data, high-resolution digital climate models(DCM) were prepared to support weather- related activities of residents in NGP Monthly climate data from 51 synoptic stations across both North and South Korea were collected for 1981-2000. A digital elevation model(DEM) for this region with 30m cell spacing was used with the climate data for spatially interpolating daily maximum and minimum temperatures, solar irradiance, and precipitation based on relevant topoclimatological models. For daily minimum temperature, a spatial interpolation scheme accommodating the potential influences of cold air accumulation and the temperature inversion was used. For daily maximum temperature estimation, a spatial interpolation model loaded with the overheating index was used. Daily solar irradiances over sloping surfaces were estimated from nearby synoptic station data weighted by potential relative radiation, which is the hourly sum of relative solar intensity. Precipitation was assumed to increase with the difference between virtual terrain elevation and the DEM multiplied by an observed rate. Validations were carried out by installing an observation network specifically for making comparisons with the spatially estimated temperature pattern. Freezing risk in January was estimated for major fruit tree species based on the DCMs under the recurrence intervals of 10, 30, and 100 years, respectively. Frost risks at bud-burst and blossom of tree flowers were also estimated for the same resolution as the DCMs.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.1
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• pp.63-73
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• 2010

A comprehensive mapping project for agroclimatic zoning in South Korea will end by April 2010, which has required 4 years, a billion won (ca. 0.9 million US dollars) and 22 experts from 7 institutions to complete it. The map database from this project may be categorized into primary, secondary and analytical products. The primary products are called "high definition" digital climate maps (HD-DCMs) and available through the state of the art techniques in geospatial climatology. For example, daily minimum temperature surfaces were prepared by combining the climatic normals (1971-2000 and 1981-2008) of synoptic observations with the simulated thermodynamic nature of cold air by using the raster GIS and microwave temperature profiling which can quantify effects of cold air drainage on local temperature. The spatial resolution of the gridded climate data is 30m for temperature and solar irradiance, and 270m for precipitation. The secondary products are climatic indices produced by statistical analysis of the primary products and includes extremes, sums, and probabilities of climatic events relevant to farming activities at a given grid cell. The analytical products were prepared by driving agronomic models with the HD-DCMs and dates of full bloom, the risk of freezing damage, and the fruit quality are among the examples. Because the spatial resolution of local climate information for agronomic practices exceeds the current weather service scale, HD-DCMs and the value-added products are expected to supplement the insufficient spatial resolution of official climatology. In this lecture, state of the art techniques embedded in the products, how to combine the techniques with the existing geospatial information, and agroclimatic zoning for major crops and fruits in South Korea will be provided.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04a
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• pp.874-876
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• 2004

본 논문에서는 트랜스코딩가 미디어캐슁 기법을 적목한 프록시 시스템인 DCMS(Dual Caching proxy for adaptive Multimedia Streaming service)를 제안한다. 미디어 데이터 특성을 이용해서 DCMS는 전체 파일 중 파일의 시작 부분만을 미리 캐쉬에 저장하여 클라이언트가 미디어 서비스를 요청하면, 서버를 대신해 데이터를 클라이언트로 전송해주면서 데이터 블록의 뒷부분부터 미리 선반입(Pre-fetching)함으로써 미디어 재생에 끊김이 없도록 한다. 그리고 미디어 데이터를 네트워크 대역폭, 무선단말기 수용성과 사용자 선호도를 고려한 트랜스코딩을 통해 미디어 데이터의 질을 레벨화 하여 저장함으로써 각 클라이언트에 적합한 미디어 데이터를 바로 제공한다.

• Current Optics and Photonics
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• v.3 no.3
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• pp.193-198
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• 2019

We propose a novel method to design a dispersion map for a WDM (Wavelength Division Multiplexing) ring network with the capability of wavelength reconfiguration. The method is simple, but gives us an optimum set of DCMs (Dispersion Compensation Modules) which satisfies a given value of the tolerable residual dispersion. The proposed method does not depend on compensation method, fiber type, or modulation format. We also demonstrate numerically how it works with an example 10-node ring network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1243-1246
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• 2003

It is known that structure of Human's brain information system is controlled by cerebral cortex mainly. Cerebral cortex is divided by sensory area, motor area and associated area largely. Sensory area takes part in information from environment and motor area is actuation by decision as associated area determined. It is possible to copy brain information system by input-output pattern. but there is difficulty in modeling of memorizing new information. Such action is performed by Limbic Lobe and Papez circuit which is controlled by intrinsic emotion. So we need of definition of emotion's role in decision. In this paper, we define roles of emotion in intrinsic decision using Dynamic Cognitive Maps(DCMs). The emotion is evaluated by outside information then intrinsic decision performed as how much emotion variated. The dynamic cognitive maps take part in emotion evaluating process.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.508-517
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• 2007

본 사례연구는 한국정보사회진흥원에서 개발한 디지털콘텐츠의 표준식별체계인 UCI(Universal Content Identifier)를 (주)누리미디어 보유의 약33만 건 콘텐츠에 적용한 사례와 비즈니스 모델을 소개하고 있다. UCI란 '디지털콘텐츠의 유통활성화' 를 이룩하기 위한 목적으로 도입하는 기술로 개별 디지털콘텐츠에 식별기호를 부여하는 기술이다. 본 사업은 UCI코드 체계를 이용하여 콘텐츠 관리 시스템을 구축하는 것을 목표로 하고 있다. UCI-RA시스템 구축이후 기대효과로는 콘텐츠 제공과 관련된 업무에 인적, 물적 비용을 절감하고, 신규 콘텐츠 발굴 및 개발이 용이하도록 하였다. 또한 서비스 운영과정에서는 기 확보된 콘텐츠를 비즈니스화 하여 신규 수익창출의 모델로 육성할 수 있다. 한편 콘텐츠 소비과정에서는 콘텐츠 검색의 용이성 및 구매 용이성 증대를 통해 양질의 콘텐츠를 유통하는 것이다. 아울러 운영기업의 콘텐츠 등록 및 운영과정에서의 유료콘텐츠 정산주기율 단축, 콘텐츠 품질 고객만족도 제고 등의 효율성을 증가할 수 있다.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.256-256
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• 2013

기존에 사용되어 오던 DCMS (DC magnetron sputtering)과 HPPMS (high-power pulsed magnetron sputtering)에 비해 MPP를 이용한 magnetron sputtering은 높은 증착률을 가지고 있으며, 증착된 박막의 특성도 우수하다고 알려져 있다. 본 연구에서는 최대 출력 700 V, 12.5 A, 100 kHz)의 사양을 가지는 DC, pulse DC, modulated pulsed DC의 세 종류로 변환이 가능한 Power supply를 제작하여 Cr 박막을 증착하였다. 증착시 혼합기체 Ar/$N_2$를 사용하였으며, 박막의 특성을 sputtering power 종류별로 비교 평가하였다. 실험 결과얻어진 박막을 SEM과 XRD를 이용하여 분석하였다.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2017.05a
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• pp.69-69
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• 2017

For several decades, industrial processes consume a huge amount of raw water for various objects that consequently results in the generation of large amounts of wastewater. There effluents are mainly treated by conventional technologies such are aerobic, anaerobic treatment and chemical coagulation. But, there processes are not suitable for eliminating all hazardous chemical compounds form wastewater and generate a large amount of toxic sludge. Therefore, other processes have been studied and applied together with these techniques to enhance purification results. These techniques include photocatalysis, absorption, advanced oxidation processes, and ozonation, but also have their own drawbacks. In recent years, electrochemical techniques have received attention as wastewater treatment process that show higher purification results and low toxic sludge. There are many kinds of electrode materials for electrochemical process, among them, boron doped diamond (BDD) attracts attention due to good chemical and electrochemical stability, long lifetime and wide potential window that necessary properties for anode electrode. So, there are many researches about high quality BDD, among them, researches are focused BDD on Si substrate. But, Si substrate is hard to apply electrode application due to the brittleness and low life time. And other substrates are also not suitable for wastewater treatment electrode due to high cost. To solve these problems, Ti has been candidate as substrate in consideration of cost and properties. But there are critical issues about adhesion that must be overcome to apply Ti as substrate. In this study, to overcome this problem, TiN interlayer is introduced between BDD and Ti substrate. TiN has higher electrical and thermal conductivity, melting point, and similar crystalline structure with diamond. The TiN interlayer was deposited by reactive DC magnetron sputtering (DCMS) with thickness of 50 nm, $1{\mu}m$. The microstructure of BDD films with TiN interlayer were estimated by FE-SEM and XRD. There are no significant differences in surface grain size despite of various interlayer. In wastewater treatment results, the BDD electrode with TiN (50nm) showed the highest electrolysis speed at livestock wastewater treatment experiments. It is thought to be that TiN with thickness of 50 nm successfully suppressed formation of TiC that harmful to adhesion. And TiN with thickness of $1{\mu}m$ cannot suppress TiC formation.