• Journal of Conservation Science
• /
• v.5 no.1 s.5
• /
• pp.105-111
• /
• 1996

In order to maintain and evaluate the adequate humidity and temperature of a museum, the data of these should be periodically monitored and accumulated. For this purpose, We have designed the interpretation method of charts of the widely used thermo hydrorecorder at the museum, and developed the computer-based program (name of the program : HATH interpretation program). This method is as follows;The recording of thermo hydrorecorder(model ; Sato R-704) Input a through scanner (UMAX type), and was transformed into numerical value and was processed the statistics by HATH interpretation program. Output can be present the numerical value and the graph which are classified by a day, a month, and a year. By this method, the humidity and temperature data which were taken from 12points in the exhibition case, storage and outdoor of the Ho-Am art Museum in 1995 were processed. At the results, its ability for fast processing, management and analysis of the data was proved to be excellent.

• Journal of the Korean Society of Costume
• /
• v.60 no.10
• /
• pp.118-132
• /
• 2010

The purpose of the research is to develop a systematic model to interpret makeup signs through a case analysis of makeup shown in Alexander McQueen's ready-to-wear collections from 2001 to 2010 and to prove an importance of makeup as a communication medium to deliver social and cultural values. This research employed Panofsky's Iconology theory to analyze data. This theory consists of three steps to interpret the meaning of a work: (1) pre-iconographical description, (2) iconographical analysis, and (3) iconological interpretation. Alexander McQueen's makeup was analyzed with the three steps in order. As a result of the pre-iconographical description step, makeup styles (icons) in his collections are identified which are Egyptian style, Gothic style, Androgynous style, Victorian style, Fantasia style, and Futuristic variant style. The iconographical analysis step identified that the elements used in his makeup are inspired by his identity and life. In the final step of iconological interpretation, the researcher concluded that Alexander McQueen's makeup expresses social, cultural, and aesthetical value of the time period when the collection was created. His makeup shows postmodernism that accepts a diversity of views (the pluralism) and humanism, romantic narcissism that is his personality trait, and avant-garde that pursues a new, creative aesthetics.

• Communications for Statistical Applications and Methods
• /
• v.23 no.6
• /
• pp.467-478
• /
• 2016

The accelerated failure time model or accelerated life model relates the logarithm of the failure time linearly to the covariates. The parameters in the model provides a direct interpretation. In this paper, we review some newly developed practically useful estimation and inference methods for the model in the analysis of right censored data.

• Journal of the Korean Statistical Society
• /
• v.22 no.2
• /
• pp.201-208
• /
• 1993

Given the specific mean shift outlier model, the score test for multiple outliers in nonlinear regression is discussed as an alternative to the likelihood ratio test. The geometric interpretation of the score statistic is also presented.

• ETRI Journal
• /
• v.16 no.4
• /
• pp.27-47
• /
• 1995

This paper improves top-down execution models of logic programs based on a two-phase abstract interpretation which consists of a bottom-up analysis followed by a top-down one. The two-phase analysis provides an approximation of all (possibly non-ground) success patterns of clauses relevant to a query. It is specialized by considering Sato and Tamaki’s depth k abstraction as abstract function. By the ability of the analysis to approximate possibly non-ground success patterns of clauses relevant to a query, it can be statically determined whether some subgoals will fail during execution and some succeeding subgoals do not participate in success patterns of program clauses relevant to a given query. These properties are utilized to improve execution models. This approach can be easily applied to any top-down (parallel) execution models. As instances, it is shown to be applicable to linear execution model and AND/OR Process Model.

• Journal of Ocean Engineering and Technology
• /
• v.4 no.1
• /
• pp.35-42
• /
• 1990

The area where age dating of the seafloor and interpretation of geomagnetic basic structure are conducted is also important in the aspect of geophysics. Near the sea mount (water depth to the top is 3900m and 6500m to the bottom), there are Mesozoic magnetic lineations at the sea-side flank along the trench axis. A two dimensional model analysis of Talwani and Heirtzler(1964) and a three dimensional model analysis of Talwani are performed by using data obtained from the marine proton magnetometer. Distribution, direction of the lineation, amplitude and period of magnetic anomaly are correlated and analysed with speed of the plate movement and lineation of the sea mount. In the west and north-west Pacific there are lots of huge sea mounts retaining the history of oceanic crust. This indicates that geomagnetic basis subsided into the oceanic crust and has interest in the aspects of the isostasy theory of the gravity.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.9 no.6
• /
• pp.546-552
• /
• 2016

We present a quantitative evaluation of an algorithm for model-based face recognition. The algorithm actively learns how individual faces vary through video sequences, providing on-line suppression of confounding factors such as expression, lighting and pose. By actively decoupling sources of image variation, the algorithm provides a framework in which identity evidence can be integrated over a sequence. We demonstrate that face recognition can be considerably improved by the analysis of video sequences. The method presented is widely applicable in many multi-class interpretation problems.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
• /
• 1998.11a
• /
• pp.123-126
• /
• 1998

We have conducted surface electrical resistivity surveys along with the electrical logging at Bookil-Myun, Chungwon-Goon, Choongchungbuk-Do to determine the depths of basement and water table, and for the purpose of preparing the basic input data for hydrogeologic model combined with GIS. A twenty lines of dipole-dipole array survey and a twenty-five stations of resistivity sounding were performed and ten holes were employed for electrical logging to cross check the surface data. A combined interpretation gave the quantitative information of the shallow geologic structure over the area and we constructed layers using the grid analysis of Arc/info. The constructed layers were turned out to be similar to the geologic structure confirmed from the drilling data and we concluded that the methodology adopted in this study would be applicable to hydrogeologic model setup as a tool of providing the basic input data.

• The KIPS Transactions:PartD
• /
• v.9D no.2
• /
• pp.243-250
• /
• 2002

In order to properly interpret and process or operators in deductive databases including indefinite clauses, we propose to use Lasez′s Strong Model Semantics(LSMS) which is reasonably simple yet powerful enough to support both exclusive and inclusive interpretations. Conventional semantics either fail to support both interpretations or simply too complex. Therefore, in this paper we study advantages and difficulties of representing indefinite information, and as for the solution to difficulties, we show how LSMS can be used to support both inclusive or and exclusive or interpretations. We also investigate and analyze it′s properties and show how it semantically differs from others. We believe that LSMS is the only "reasonably simple" semantics that supports both inclusive and exclusive interpretations.

• Journal of Korean Society of Water and Wastewater
• /
• v.36 no.4
• /
• pp.239-248
• /
• 2022

The prediction of algal bloom is an important field of study in algal bloom management, and chlorophyll-a concentration(Chl-a) is commonly used to represent the status of algal bloom. In, recent years advanced machine learning algorithms are increasingly used for the prediction of algal bloom. In this study, XGBoost(XGB), an ensemble machine learning algorithm, was used to develop a model to predict Chl-a in a reservoir. The daily observation of water quality data and climate data was used for the training and testing of the model. In the first step of the study, the input variables were clustered into two groups(low and high value groups) based on the observed value of water temperature(TEMP), total organic carbon concentration(TOC), total nitrogen concentration(TN) and total phosphorus concentration(TP). For each of the four water quality items, two XGB models were developed using only the data in each clustered group(Model 1). The results were compared to the prediction of an XGB model developed by using the entire data before clustering(Model 2). The model performance was evaluated using three indices including root mean squared error-observation standard deviation ratio(RSR). The model performance was improved using Model 1 for TEMP, TN, TP as the RSR of each model was 0.503, 0.477 and 0.493, respectively, while the RSR of Model 2 was 0.521. On the other hand, Model 2 shows better performance than Model 1 for TOC, where the RSR was 0.532. Explainable artificial intelligence(XAI) is an ongoing field of research in machine learning study. Shapley value analysis, a novel XAI algorithm, was also used for the quantitative interpretation of the XGB model performance developed in this study.