• Korean Journal of Soil Science and Fertilizer
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• v.42 no.6
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• pp.522-528
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• 2009

This study focused on establishing prediction models using visible-near infrared spectrum to simultaneously detect multiple components of soils and enhancing the performance quality by suitably transformed input spectra and classification of soil spectral types for prediction model input. The continuum-removed spectra showed significant result for all cases in terms of soil properties and classified or bulk predictions. The prediction model using classified soil spectra at an absorption peak area around 500nm and 950nm efficiently indicating soil color showed slightly better performance. Especially, Ca and CEC were well estimated by the classified prediction model at $R^{2}$ > 0.8. For organic carbon, both classified and bulk prediction model had a good performance with $R^{2}$ > 0.8 and RPD> 2. This prediction model may be applied in global soil mapping, soil classification, and remote sensing data analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.552-557
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• 2020

The Radar Cross Section (RCS) is a virtual region indicating the strength of a wavelength at which a radar signal is reflected and received. As the ship's RCS represents its own stealth performance and survivability, efforts have been made in various areas from design to construction to reduce the RCS. The RCS can be predicted using design drawings and CAD models, but it is necessary to measure the RCS at sea since sea clutter and multipath reflections occur in the sea environment. However, such RCS predictions and measured values provide only a simple relative magnitude to the user, and there has not been much research on this topic. In this paper, a missile countermeasure technique was studied using 3D RCS measurement data in an operating environment. The elevation and azimuth angle of the ship viewed from the missile were estimated using the location information of the missile, and the RCS value was inverted by mapping it to previously measured 3D RCS measurement data. In addition, by using the movement information of the missile, the RCS observed by the missile could be predicted in advance, and this method can be used to propose a response plan based on the maneuvering and chaff system.

• The KIPS Transactions:PartD
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• v.16D no.3
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• pp.451-462
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• 2009

Collaborative Filtering (CF), one of the most successful technologies among recommender systems, is a system assisting users in easily finding the useful information. However, despite its success and popularity, CF encounters a serious limitation with quality evaluation, called cold start problems. To alleviate this limitation, in this paper, we propose a unique method of building models derived from explicit ratings and applying the models to CF recommender systems. The proposed method is divided into two phases, an offline phase and an online phase. First, the offline phase is a building pre-computed model phase in which most of tasks can be conducted. Second, the online phase is either a prediction or recommendation phase in which the models are used. In a model building phase, we first determine a priori predicted rating and subsequently identify prediction errors for each user. From this error information, an error-reflected model is constructed. The error-reflected model, which is reflected average prior prediction errors of user neighbors and item neighbors, can make accurate predictions in the situation where users or items have few opinions; this is known as the cold start problems. In addition, in order to reduce the re-building tasks, the error-reflected model is designed such that the model is updated effectively and users'new opinions are reflected incrementally, even when users present a new rating feedback.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1641-1645
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• 2006

수문순환과 수질오염과정의 제반 기작들이 완벽하게 규명되지 않은 상황에서 인위적 또는 자연적 조건에 따른 수질의 평가는 수질모형으로서 추정하는 것이 유일한 대안이며, 다양한 관리대안에 따른 수질환경변화를 예측함으로서 합리적인 관리방안을 도출하는데 유용한 수단이 되고 있다. 현재 시행 중인 수질오염총량관리제에서 또한 수질모형은 핵심적인 역할을 담당하고 있으며, 보다 구체적으로는 단위유역의 목표수질을 결정하는 것에서부터 기본계획 또는 시행계획에 따른 오염부하량 등 환경요인의 변화와 이에 따른 목표수질 설정지점의 수질 변화 등을 모의하는데 이용되고 있다. 그러나 모형에 사용되는 입력 매개변수의 불확실성과 이에 관련된 수질 모형 자체의 불확실성은 수질오염총량관리제와 같이 많은 이해당사자가 관여된 정책의 결정 시에는 공학적으로 많은 부담으로 작용하고 있는 것 또한 현실이다. 실제로 미국의 오염총량관리제의 경우를 살펴보면 모형의 불확실성 분석이 전체 과정의 진행에서 가장 핵심적인 지위를 차지하고 있다고 볼 수 있다. 많은 연구들이 수질모형에 있어서의 불확실성을 정량화하기 위하여 수행되어 왔으며, 특히 미국의 오염총량관리계획의 수립 시에는 이러한 불확실성 분석을 토대로 하여 안전율을 산정하도록 되어있다. 그러나 이러한 연구들의 대부분은 수질모형의 매개변수 중 수질기작에 관련된 매개변수들(예를 들어, DO, BOD, N, P 등에 대한 반응계수)에 대한 연구에 집중되어 있다. 하천의 수질을 적절하게 모델링하기 위해서는 이러한 수질에 직접적으로 관련한 매개변수들 이외에 하천의 수리특성에 관한 올바른 이해를 바탕으로 그와 관련된 수리학적 매개변수들에 대한 연구가 뒷받침되어야 한다. 그동안 수행되어온 수질 모델링의 적용 사례를 살펴본 바에 따르면 하천을 모델링하기 위해서는 현장 특성 자료의 중요성, 특히 하천수리특성에 관련된 기초 자료의 가용성 여부가 모형의 성패에 매우 중요한 역할을 함을 알 수 있다. 이는 유량, 유속 및 폭과 깊이로 대변되는 하천 지형은 물질 이송에 대한 주요 외력 함수이며, 다른 모든 예측치들은 이들에 의존적일 수밖에 없기 때문이다. 따라서 이들의 정확한 표현은 올바른 수질 예측에 있어서 필수적일 수밖에 없다. 많은 모형매개변수들이 유속과 깊이에 의존적이나, 이들에 관한 정보는 종종 현장관측에서 조차 무시되는 경우가 많다. 이에 본 연구에서는 수질모형의 매개변수 중 특히 수리특성에 관련된 매개변수들이 수질에 미치는 영향을 파악하는 것을 목적으로 하고 있다. 이를 위해 적용된 수질모형은 QualKo를 사용하였으며, 대상 하천은 낙동강 본류 경남구간 시점 부근인 회천 합류 전부터 낙동강 본류 경남구간 종점 부근인 밀양강 합류 전까지의 경남 오염총량관리 기본계획 시 구축된 모형 매개변수를 바탕으로 분석을 수행하였다. 일차오차분석을 이용하여 수리매개변수와 수질매개변수의 수질항목별 상대적 기여도를 파악해 본 결과, 수리매개변수는 DO, BOD, 유기질소, 유기인 모든 항목에 일정 정도의 상대적 기여도를 가지고 있는 것을 알 수 있었다. 이로부터 수질 모형의 적용 시 수리 매개변수 또한 수질 매개변수의 추정 시와 같이 보다 세심한 주의를 기울여 추정할 필요가 있을 것으로 판단된다.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.263-286
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• 2022

This study acquires NBA statistical information for a total of 32 years from 1990 to 2022 using web crawling, observes variables of interest through exploratory data analysis, and generates related derived variables. Unused variables were removed through a purification process on the input data, and correlation analysis, t-test, and ANOVA were performed on the remaining variables. For the variable of interest, the difference in the mean between the groups that advanced to the playoffs and did not advance to the playoffs was tested, and then to compensate for this, the average difference between the three groups (higher/middle/lower) based on ranking was reconfirmed. Of the input data, only this year's season data was used as a test set, and 5-fold cross-validation was performed by dividing the training set and the validation set for model training. The overfitting problem was solved by comparing the cross-validation result and the final analysis result using the test set to confirm that there was no difference in the performance matrix. Because the quality level of the raw data is high and the statistical assumptions are satisfied, most of the models showed good results despite the small data set. This study not only predicts NBA game results or classifies whether or not to advance to the playoffs using machine learning, but also examines whether the variables of interest are included in the major variables with high importance by understanding the importance of input attribute. Through the visualization of SHAP value, it was possible to overcome the limitation that could not be interpreted only with the result of feature importance, and to compensate for the lack of consistency in the importance calculation in the process of entering/removing variables. It was found that a number of variables related to three points and errors classified as subjects of interest in this study were included in the major variables affecting advancing to the playoffs in the NBA. Although this study is similar in that it includes topics such as match results, playoffs, and championship predictions, which have been dealt with in the existing sports data analysis field, and comparatively analyzed several machine learning models for analysis, there is a difference in that the interest features are set in advance and statistically verified, so that it is compared with the machine learning analysis result. Also, it was differentiated from existing studies by presenting explanatory visualization results using SHAP, one of the XAI models.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.351-360
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• 2018

The LWR (Locally Weighted Regression) model, which is traditionally a lazy learning model, is designed to obtain the solution of the prediction according to the input variable, the query point, and it is a kind of the regression equation in the short interval obtained as a result of the learning that gives a higher weight value closer to the query point. We study on an incremental ensemble learning approach for LWR, a form of lazy learning and memory-based learning. The proposed incremental ensemble learning method of LWR is to sequentially generate and integrate LWR models over time using a genetic algorithm to obtain a solution of a specific query point. The weaknesses of existing LWR models are that multiple LWR models can be generated based on the indicator function and data sample selection, and the quality of the predictions can also vary depending on this model. However, no research has been conducted to solve the problem of selection or combination of multiple LWR models. In this study, after generating the initial LWR model according to the indicator function and the sample data set, we iterate evolution learning process to obtain the proper indicator function and assess the LWR models applied to the other sample data sets to overcome the data set bias. We adopt Eager learning method to generate and store LWR model gradually when data is generated for all sections. In order to obtain a prediction solution at a specific point in time, an LWR model is generated based on newly generated data within a predetermined interval and then combined with existing LWR models in a section using a genetic algorithm. The proposed method shows better results than the method of selecting multiple LWR models using the simple average method. The results of this study are compared with the predicted results using multiple regression analysis by applying the real data such as the amount of traffic per hour in a specific area and hourly sales of a resting place of the highway, etc.

• Journal of the Korean Geographical Society
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• v.38 no.2
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• pp.312-323
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• 2003

This writer absolutely agrees with the government that regional disequilibrium is severe enough to consider moving the administrative capital. Pursuing this course solely to establish a balanced development, however, is not a convincing enough reason. The capital city is directly related to not only the social and economic situation but, much more importantly, to the domestic political situation as well. In the mid-1970s, the proposal by the Third Republic to move the capital city temporarily was based completely on security reasons. At e time, the then opposition leader Kim, Dae-jung said that establishing a safe distance from the demilitarized zone(DMZ) reflected a typically military decision. His view was that retaining the capital city close to the DMZ would show more consideration for the will of the people to defend their own country. In fact, independent Pakistan moved its capital city from Karachi to Islamabad, situated dose to Kashmir the subject of hot territorial dispute with India. It is regrettable that no consideration has been given to the urgent political situation in the Korean peninsula, which is presently enveloped in a dense nuclear fog. As a person requires health to pursue his/her dream, a country must have security to implement a balanced territorial development. According to current urban theories, the fate of a country depends on its major cities. A negligently guarded capital city runs the risk of becoming hostage and bringing ruin to the whole country. In this vein, North Koreas undoubted main target of attack in the armed communist reunification of Korea is Seoul. For the preservation of our state, therefore, it is only right that Seoul must be shielded to prevent becoming hostage to North Korea. The location of the US Armed Forces to the north of the capital city is based on the judgment that defense of Seoul is of absolute importance. At the same time, regardless of their different standpoints, South and North Korea agree that division of the Korean people into two separate countries is abnormal. Reunification, which so far has defied all predictions, may be realized earlier than anyone expects. The day of reunification seems to be the best day for the relocation of the capital city. Building a proper capital city would take at least twenty years, and a capital city cannot be dragged from one place to another. On the day of a free and democratic reunification, a national agreement will be reached naturally to find a nationally symbolic city as in Brazil or Australia. Even if security does not pose a problem, the governments way of thinking would not greatly contribute to the balanced development of the country. The Chungcheon region, which is earmarked as the new location of the capital city, has been the greatest beneficiary of its proximity to the capital region. Not being a disadvantaged region, locating the capital city there would not help alleviate regional disparity. If it is absolutely necessary to find a candidate region at present, considering security, balanced regional development and post-reunification scenario of the future, Cheolwon area located in the middle of the Korean peninsula may be a plausible choice. Even if the transfer of capital is delayed in consideration of the present political conflict between the South and the North Koreas, there is a definite shortcut to realizing a balanced regional development. It can be found not in the geographical dispersal of the central government, but in the decentralization of power to the provinces. If the government has surplus money to build a new symbolic capital city, it is only right that it should improve, for instance, the quality of drinking water which now everyone eschews, and to help the regional subway authority whose chronic deficit state resoled in a recent disastrous accident. And it is proper to time the transfer of capital city to coincide with that of the reunification of Korea whenever Providence intends.