• International Commerce and Information Review
• /
• v.19 no.2
• /
• pp.237-258
• /
• 2017

This research thoroughly analyzes prior literature related to the flexibility of cargo airlines to switch the airport and discusses the driving factors of such footloose nature. The main purpose of the study is to identify the most deterrent factors leading to airport relocation decision which determines cargo industries role on the global trade. Qualitative research based on systematic process analysis was conducted as a main research method. As a result, 24 factors related to airport-airline relationship were chosen and categorized into four main groups; (1) Location issues, (2) Restrictions, (3) Poor quality, and (4) High costs. The findings derived from the analysis of selected studies suggest that restriction related issues (e.g. night-time flight restrictions, customs administration) followed by location issues (e.g. absence of origin destination demand) have created more constraint to airport-airline relationship.

• Proceedings of the Korean Information Science Society Conference
• /
• 2004.04b
• /
• pp.247-249
• /
• 2004

마이크로어레이 기술은 근래에 개발된 신기술로써 동시에 수천-수만 개의 유전자 발현을 측정할 수 있어 다양한 생물학적 연구에 이용되고 있다. 여러 단계의 실험 과정과 이를 통해 얻은 다량의 데이터를 처리하기 위해서는 이를 효율적으로 관리. 저장, 분석할 수 있는 통할 정보 관리 시스템을 필요로 한다. 현재 외국에서는 몇몇 관리시스템이 개발되어 있고. 국내에서도 WEMA 등이 있지만 아직 데이터 관리부분에 기능이 치우쳐 있다. 따라서 우리는 복잡한 자료구조를 가지는 마이크로어레이의 실험 정보와 각 단계별 처리 정보 등을 사용자의 관점에서 효과적이고 체계적으로 관리할 수 있고, 데이터 정규화 및 다양한 통계적 분석 기능을 갖춰 불필요한 시간과 비용을 줄임으로써 마이크로어레이 연구에 도움을 주고자 통합 분석관리 시스템 cMAMS (cDNA Microarray Analysis and Management System)를 개발하였다. 웹 기반으로 구현된 cMAMS는 데이터를 저장, 관리하는 부분과 데이터를 분석하는 부분, 그리고 모든 관련 점보가 저장되는 데이터베이스 부분으로 구성되어 있다 데이터관리부분에서는 WEMA의 계층적 데이터구조론 도입해 관리의 효율성을 높이고 시스템의 이용자를 시스템운영자, 프로젝트관리자, 일반사용자로 구분하여 데이터 접근을 제한함으로써 보안성을 높였다. 통계처리 언어 R로 구현된 데이터분석 부분은 7 단계의 다양한 분석(전처리 정규화, 가시화, 군집분석. 판별분석, 특이적 발현 유전자 선뿐, 마이크로어레이 간의 상판분석)이 가능하도록 구현하였고, 분석결과는 데이터베이스에 저장되어 추후에 검토 및 연구자간의 공유가 가능하도록 하였다. 데이터베이스는 실험정보가 저장된 데이터베이스, 분석결과가 저장된 데이터베이스, 그리고 유전자 정보 탐색을 위한 데이터베이스로 분류해 데이터를 효율적으로 관리할 수 있게 하였다. 본 시스템은 LiNUX를 운영체계로 하고 데이터베이스는 MYSQL로 하여 JSP, Perl. 통계처리 언어인 R로 구현되었다.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.135-135
• /
• 2015

2004년 개발된 다차원홍수피해산정법(MD-FDA)은 홍수에 따른 경제적 피해를 추정하기 위한 기법으로서 그 동안 하천설계기준, 댐설계기준, KDI 예비타당성조사 지침 등에 반영되어 실무에서 활발히 사용 중이다. 그러나 그 동안 많은 연구에서 MD-FDA의 인벤토리 체계, 가용자료의 정밀성, 손상함수, 손실유형 범위와 관련한 개선이 요구되었으며, 최근에는 재난위기 관리 능력강화를 위한 "한국형 재난피해 예측 시스템" 개발의 필요성이 제기되면서 현재 다양한 분야의 전문가들이 재난손실과 관련한 많은 연구를 진행 중이다. 이에 본 연구는 국외 주요 홍수손실 예측 모델과 현재 국가차원에서 서비스되는 상세자료를 검토하여 일반건물(general building)의 홍수손실 평가 체계를 제시하고, 이와 연관된 세부요소 기술을 정립하였다. 우선, 지역 내 건물현황 및 특성정보가 참조가능한 자료를 바탕으로 일반건물의 유형을 분류하였고, 이밖에 건물손실 평가에서 주요 참고자료로 활용되는 인구, 종사자수 등의 사회 경제적 정보를 연계한 인벤토리 DB 구조를 설계하였다. 이로부터 구축되는 인벤토리 DB는 위치정보를 포함하는 공간자료이며, 손상(damage)과 손실(loss)을 평가하기 위한 건물특성 정보를 포함한다. 한편, 본 연구에서의 건물손실은 자산의 총가치를 기준으로 한 상대적 손상률(%)을 설명하는 손상함수를 기반으로 하기 때문에 감가상각을 고려한 건물의 완전대체비용(건물자산가치)가 정의되어야 한다. 이를 위해 본 연구는 최근 한국감정원에서 발간한 "건물신축단가표"와 "유형고정자산 내용연수표"를 바탕으로 손실평가에 필요한 요소기술을 정립하였다. 제시한 일련의 과정은 동두천시 신천 범람사례를 대상으로 적용하였고, 그 결과를 기존의 MD-FDA 결과와 비교하였다.

• The Journal of Society for e-Business Studies
• /
• v.26 no.1
• /
• pp.79-91
• /
• 2021

The public records of universities shall be classified according to the Enforcement Decree of the Public Records Act and public records management activities shall be carried out accordingly. Among various kinds of public records of the university, the records of performance management are still managed as paper documents, such as attendance books, answer sheets, and assignments, and the management system and methods of each school are different, making it difficult for the management manager to manage them. In this paper, we propose a service model that can perform blockchain-based records management of records related to performance at universities currently kept in paper documents. The proposed service is expected to reduce resource consumption, such as the cost, time and effort spent on storing and managing paper documents.

• Korean Journal of Construction Engineering and Management
• /
• v.4 no.4 s.16
• /
• pp.192-200
• /
• 2003

The object of this research is to develop a computerized algorithm of cost estimation method to forecast the total construction cost in the bidding stage by the historical and elemental work cost data. Traditional cost models to prepare Bill of Quantities in the korea construction industry since 1970 are not helpful to forecast the project total cost in the bidding stage because the BOQ is always constant data according to the design factors of a particular project. On the contrary, statistical models can provide cost quicker and more reliable than traditional ones if the collected cost data are sufficient enough to analyze the trends of the variables. The estimation system considers non-deterministic methods which referred to as the 'Monte Carlo simulation. The method interprets cost data to generate a probabilistic distribution for total costs from the deficient elemental experience cost distribution.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.2
• /
• pp.36-54
• /
• 2017

The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.19 no.4
• /
• pp.13-29
• /
• 2020

Automobiles have long been an essential part of daily life, but the social costs of car traffic accidents exceed 9% of the national budget of Korea. Hence, it is necessary to establish prevention and response system for car traffic accidents. In order to present a model that can classify and predict the degree of injury in car traffic accidents, we used big data analysis techniques of K-nearest neighbor, logistic regression analysis, naive bayes classifier, decision tree, and ensemble algorithm. The performances of the models were analyzed by using the data on the nationwide traffic accidents over the past three years. In particular, considering the difference in the number of data among the respective injury severity levels, we used down-sampling methods for the group with a large number of samples to enhance the accuracy of the classification of the models and then verified the statistical significance of the models using ANOVA.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.406-409
• /
• 2001

This study refers to development of WBS(Work Breakdown Structure) and Activity sample for integrated cost and schedule control system of sample bridge work in the field. The conclusions from this study may be summarized as following 1. It showed that the level of detail to network's activities depend upon schedule's intended purpose. 2. It is more effective 'activity to cost package model' than 'activity to resource model', for integrated cost and schedule control reflect the characteristics of domestic construction industry.

• Journal of Digital Convergence
• /
• v.19 no.2
• /
• pp.523-529
• /
• 2021

Medical service robots are variously defined and classified by researchers and related government departments, but surgical robots and rehabilitation robots are commonly included in medical service robots, and except for these, the robots are classified as other medical service robots. In this study, domestic and foreign development trends and use cases were considered, focusing on logistics, guidance, and drug processing robots among other medical service robots. Logistics and guidance robots were developed quite a lot in Korea and completed a pilot project, or are being commercialized in hospitals, and exported. However, although the drug prcocessing robots was developed in Korea, the robot being use in the hospital was an imported. In order to expand and activate the robot market, systematic follow-up studies such as demand prediction studies are needed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.399-401
• /
• 2022

A definitive diagnosis to classify the breast malignancy status may be achieved by microscopic analysis using surgical open biopsy. However, this procedure requires experts in the specializing of histopathological image analysis directing to time-consuming and high cost. To overcome these issues, deep learning is considered practically efficient to categorize breast cancer into benign and malignant from histopathological images in order to assist pathologists. This study presents a pre-trained convolutional neural network model architecture with a 100% fine-tuning scheme and Adagrad optimizer to classify the breast cancer histopathological images into benign and malignant using a 40× magnification BreaKHis dataset. The pre-trained architecture was constructed using the InceptionResNetV2 model to generate a modified InceptionResNetV2 by substituting the last layer with dense and dropout layers. The results by demonstrating training loss of 0.25%, training accuracy of 99.96%, validation loss of 3.10%, validation accuracy of 99.41%, test loss of 8.46%, and test accuracy of 98.75% indicated that the modified InceptionResNetV2 model is reliable to predict the breast malignancy type from histopathological images. Future works are necessary to focus on k-fold cross-validation, optimizer, model, hyperparameter optimization, and classification on 100×, 200×, and 400× magnification.