• Molecules and Cells
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• 제44권11호
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• pp.843-850
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• 2021

The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http://qomics.sookmyung.ac.kr.

• The Journal of Asian Finance, Economics and Business
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• 제9권2호
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• pp.325-333
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• 2022

Foreign direct investment (FDI) and export are now often regarded as two of the most important drivers of economic growth on a worldwide scale. The impact of foreign direct investment on Vietnam's exports is investigated in this study. The data for the time period 1985-2020 was obtained from the World Bank and the Vietnam General Statistics Office. The years 1985 to 2020 were chosen to evaluate the evolution of macroeconomic parameters since 1986. The impact of the Covid-19 epidemic on renovation reform. The Johansen co-integration test proved that FDI and domestic investment (DI) had a long-term positive impact on Vietnam's export growth. The Granger causality test revealed that there is a one-way relationship between FDI and export in the near term, but no such relationship exists between DI and export. The result of the variance decomposition study demonstrates that the FDI sector has a bigger impact on Vietnam's export growth than the DI sector. Furthermore, export activities are vulnerable to FDI sector shocks. As a result, in recent years, FDI has been regarded as the most important factor of export growth in Vietnam.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.352-357
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• 2001

This study presents an analysis of healthcare quality indicators using data mining for developing quality improvement strategies. Specifically, important factors influencing the inpatient mortality were identified using a decision tree method for data mining based on 8,405 patients who were discharged from the study hospital during the period of December 1, 2000 and January 31, 2001. Important factors for the inpatient mortality were length of stay, disease classes, discharge departments, and age groups. The optimum range of target group in inpatient healthcare quality indicators were identified from the gains chart. In addition, a decision support system was developed to analyze and monitor trends of quality indicators using Visual Basic 6.0. Guidelines and tutorial for quality improvement activities were also included in the system. In the future, other quality indicators should be analyze to effectively support a hospital-wide continuous quality improvement (CQI) activity and the decision support system should be well integrated with the hospital OCS (Order Communication System) to support concurrent review.

• 문화기술의 융합
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• 제9권4호
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• pp.529-536
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• 2023

한국의 중고거래 시장은 꾸준한 성장을 보이고 있지만, 중고거래 사기의 발생 건수와 피해 금액도 함께 늘어나고 있다. 2021년 기준 중고거래 시장 규모는 24조원이지만 동시에 사기 피해 금액은 3,606억 원에 달한다. 중고거래 플랫폼은 개인 간 거래 사기를 방지하기 위해 안전거래 결제 시스템을 마련했다. 그러나 안전결제 시스템을 악용한 신종 사기 수법이 생겨나고 있어 중고거래 안전결제도 사기로부터 안전하다고 볼 수 없다. 이에 본 연구는 텍스트마이닝을 활용하여 중고거래 안전결제 서비스의 사기 방지를 위해 생긴 안전결제 시스템의 실태를 파악하고, 이를 텍스트마이닝과 네트워크 분석으로 분석하여 안전결제 시스템의 개선 방안을 제안한다.

• 디지털융복합연구
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• 제14권3호
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• pp.209-217
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• 2016

최근 경제성장과 더불어 삶의 질이 향상됨에 따라 야외활동이 증가되었으며, 야외활동의 진행여부 의사결정은 기상여건과 밀접한 관계를 갖고 있다. 현재 이러한 야외활동 의사결정은 기상청의 일기예보와 주관적인 경험에 의해 결정되어지고 있다. 따라서, 야외활동 의사결정을 위해 기상정보를 기반으로 객관적 근거를 제시할 수 있는 분석 방법이 필요하다. 논문에서는 데이터마이닝을 기반으로 기상정보를 분석하여 야외활동 의사결정을 지원할 수 있는 기상정보 분석 알고리즘을 제안한다. 또한, 프로야구 일정 히스토리와 자동기상관측장비의 관측 자료를 데이터마이닝의 분류 알고리즘을 적용하여 실험을 수행하고, 제안한 알고리즘의 향상된 성능을 검증하였다.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.109-116
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• 2022

The energy corporation of Kosovo continuously monitors and analyzes the impact of its own activities on the environment. Regarding the environmental situation, energy corporation of Kosovo- ECK regularly informs and reports objectively to the competent state institutions, local municipal institutions and interested parties. ECK, through numerous contacts with the competent authorities, firstly with different ministers, harmonizes the positions regarding environmental issues in the direction of achieving certain environmental standards or legal requirements in order to gradually be in accordance with them, based on the real possibilities, especially the financial ones. From this point of view, the environmental issue is very sensitive, quite complex and represents one of the biggest challenges of society currently and in the future. The researched variables show a continuous increase in the need for electricity production in Kosovo and this increase in production conditions a wide range of environmental impacts both at the local, regional and global levels. The aim of the work is to reduce the emission of pollutants through the main variables without inhibiting the economic development of the country, i.e. to bring the pollution as a result of the activities of the ECK operation into compliance with the permitted environmental norms. As a result of ECK's operational activities, the following follows: Air pollution mainly as a result of emissions from TCs in the air, transport, etc. Water pollution - as a result of technological water discharges, Land degradation - as a result of surface mining activities of the entire mining area. The purpose of the paper is to research and analyze the main water variables in the area of the Kosova B power plant, which is to determine the degree of their pollution from the activities of the power plants, as well as to assess the real state of surface water quality and control the degree of pollution of these waters. Methodology of the work: The analyzes of the water samples were done in the company Institute "INKOS" JSC by simultaneous methods using different reagents.

• 경영정보학연구
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• 제21권1호
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• pp.135-152
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• 2019

최근 ICT 기반 서비스 기업의 성공 사례로 다양한 창업 기업 육성 및 지원이 등장하고 있지만 정책 및 지원이 창업 초기에 몰려 있어 창업 후 안정적인 성장이 어려운 실정이다. 이는 창업 과업을 개별적인 활동으로 인식하기 때문이다. 하지만 창업 초기부터 성장 및 안정 단계에 이르기까지 창업성공에 영향을 미치는 일련의 프로세스가 존재하고 이를 파악하는 것은 창업자의 성공적인 창업 경험을 지원하는 기반이 될 수 있다. 따라서 본 연구에서는 실제 창업 경험자들을 대상으로 설문 조사를 실시하여 프로세스 마이닝 기법을 이용하여 창업 프로세스 모델을 구축하고 분석하고자 한다. 실제 ICT 서비스업 창업 사례를 기반으로 프로세스 분석한 결과, 창업자 분석, 아이디어 도출, 사업계획서 작성, 사업다각화가 전체 창업 과정에서 중요한 프로세스로 도출되었다. 반면에 마케팅 관련 활동 및 투자자금 활용 과업이 빈도는 높았지만 중요하게 나타나지 않았는데 이는 이러한 활동들이 일회성활동이 아니라 지속적으로 수행되어야 하는 과업임을 의미한다. 본 연구에서 제안하는 분석 방법을 통해 창업 과업 간의 순차적인 흐름을 도출하고 과업 수행 간 특징을 도출할 수 있을 뿐만 아니라 개별 과업 단위의 연구에서는 파악할 수 없었던 일시적 과업의 파악과 상호 보완적인 과업 활동의 파악이 가능할 것이라 기대된다. 본 연구에서 제안하는 프로세스 모델 및 분석 결과를 바탕으로 창업자 지원 시스템을 구축하게 되면 더 많은 실제 창업 사례 분석을 통하여, 예비 창업자 또는 신규 창업자의 창업 과정에서 개인별 맞춤형 지원이 가능할 뿐만 아니라, 창업 과정에서 발생되는, 또는 발생 가능한 여러 어려움을 극복하는데 도움이 될 것으로 기대된다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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• pp.109-120
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• 2006

본 연구에서는 RFM 분석을 통하여 전체 고객들을 점수화(scoring)하고 이를 다시 5개의 그룹 (최우수그룹, 우수그룹, 일반그룹, 하위그룹, 최하위그룹)으로 세분화하고, 세분그룹별 유의성을 검정한다. 이렇게 분류된 5개의 세분화그룹들은 연관분석과 의사결정나무 등을 통하여 고객들의 인구학적 변수와 자 그룹별 유의한 변수들의 패턴을 찾아냄으로써 우수 고객들을 유지하기 위해 서는 어떻게 해야 하며, 경쟁업체로 떠날 가능성이 높은 고객은 누구이며, 이러한 이유가 무엇인지에 대하여 효과적인 분석을 할 수 있는 기반이 조성된다. 본 연구의 목적은 통하여 연관규칙(association rules)과 의사결정나무(decision tree)를 비친 분석을 함으로써, 이론적으로 설명할 수 없는 복잡한 세분그룹의 특성들에 대해 효과적으로 파악하는 방법을 제시하는 것이다.

• Geomechanics and Engineering
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• 제24권6호
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• pp.519-529
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• 2021

In coal mining activities, the abutment stress of the coal has to undergo cyclic loading and unloading, affecting the strength and seepage characteristics of coal; additionally, it can cause dynamic disasters, posing a major challenge for the safety of coal mine production. To improve the understanding of the dynamic disaster mechanism of gas outburst and rock burst coupling, triaxial devices are applied to axial pressure cyclic loading-unloading tests under different axial stress peaks and different pore pressures. The existing empirical formula is use to perform a non-linear regression fitting on the relationship between stress and permeability, and the damage rate of permeability is introduced to analyze the change in permeability. The results show that the permeability curve obtained had "memory", and the peak stress was lower than the conventional loading path. The permeability curve and the volume strain curve show a clear symmetrical relationship, being the former in the form of a negative power function. Owing to the influence of irreversible deformation, the permeability difference and the damage of permeability mainly occur in the initial stage of loading-unloading, and both decrease as the number of cycles of loading-unloading increase. At the end of the first cycle and the second cycle, the permeability decreased in the range of 5.777 - 8.421 % and 4.311-8.713 %, respectively. The permeability decreases with an increase in the axial stress peak, and the damage rate shows the opposite trend. Under the same conditions, the permeability of methane is always lower than that of helium, and it shows a V-shape change trend with increasing methane pressures, and the permeability of the specimen was 3 MPa > 1 MPa > 2 MPa.

• Steel and Composite Structures
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• 제41권6호
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• pp.831-850
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• 2021

Surface subsidence caused by mining subsidence has an impact on neighboring structures and utilities. In other words, subsurface voids created by mining or tunneling activities induce soil movement, exposing buildings to physical and/or functional destruction. Soil-structure is evaluated employing probability distribution laws to account for their uncertainty and complexity to estimate structural vulnerability. In this study, to investigate the displacement field and surface settlement profile caused by mining subsidence, on the basis of a Winklersoil model, analytical equations for the moment-rotation response ofsoil during mining induced ground movements are developed. To define the full static moment-rotation response, an equation for the uplift-yield state is constructed and integrated with equations for the uplift- and yield-only conditions. The constructed model's findings reveal that the inverse of the factor of safety (x) has a considerable influence on the moment-rotation curve. The maximal moment-rotation response of the footing is defined by X = 0:6. Despite the use of Winkler model, the computed moment-rotation response results derived from the literature were analyzed through the ELM-SVM hybrid of Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Also, Monte Carlo simulations are used to apply continuous random parameters to assess the transmission of ground motions to structures. Following the findings of RMSE and R2, the results show that the choice of probabilistic laws of input parameters has a substantial impact on the outcome of analysis performed.