• Title/Summary/Keyword: Research Field Classification

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Application and development of a machine learning based model for identification of apartment building types - Analysis of apartment site characteristics based on main building shape - (머신러닝 기반 아파트 주동형상 자동 판별 모형 개발 및 적용 - 주동형상에 따른 아파트 개발 특성분석을 중심으로 -)

  • Sanguk HAN;Jungseok SEO;Sri Utami Purwaningati;Sri Utami Purwaningati;Jeongseob KIM
    • Journal of the Korean Association of Geographic Information Studies
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    • v.26 no.2
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    • pp.55-67
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    • 2023
  • This study aims to develop a model that can automatically identify the rooftop shape of apartment buildings using GIS and machine learning algorithms, and apply it to analyze the relationship between rooftop shape and characteristics of apartment complexes. A database of rooftop data for each building in an apartment complex was constructed using geospatial data, and individual buildings within each complex were classified into flat type, tower type, and mixed types using the random forest algorithm. In addition, the relationship between the proportion of rooftop shapes, development density, height, and other characteristics of apartment complexes was analyzed to propose the potential application of geospatial information in the real estate field. This study is expected to serve as a basic research on AI-based building type classification and to be utilized in various spatial and real estate analyses.

A Study on the Status of Use and Value of 'Saemi' in Sacheon Alluvial Fan (사천 선상지 '새미'의 이용 실태 및 가치 고찰)

  • Kim, Dohyun;Jeong, Myeong Cheol;Seo, Ki Chun
    • Journal of the Korean Institute of Rural Architecture
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    • v.24 no.4
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    • pp.85-95
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    • 2022
  • This study is about the story of 'Saemi', existing in the Sacheon Alluvial fan area. Saemi is a local word for Dumbeong, which is the traditional water irrigation facilities in this area that could be formed according to the geographical characteristics of a Alluvial fan site. In the meantime, although Saemi has been an important source of water, related research has been mainly done from an ecological point of view. Accordingly, the researcher paid attention to the functional aspects of Saemi itself, grasped its location, distribution status, and usage including the construction method, and considered its intrinsic value through classification and characteristic analysis of Saemi. As a result of five field surveys from September 2021 to October 2022, 129 Saemies remained in the Sacheon alluvial fan area. According to the structure and shape, Saemi could be divided into basic type, complex type, and buried type. The basic type was subdivided into bucket-type and stairs-type along with the complex type, and the buried type was subdivided into all buried-type and some buried-type. Saemies were mainly distributed at the distal end of the Sacheon alluvial fan site, individual Saemies were built on farmland, and common Saemies were usually built along roadsides adjacent to villages. The reason why the Saemies are concentrated at the distal end is the geographical characteristics of the alluvial fan where the water underflows. Saemi was an important multifunctional water supply source equivalent to the main water source for people at the distal end of the pond who did not receive a stable supply of water from the reservoir. Saemi was at the center of the underground water irrigation network agricultural system in the Sacheon alluvial fan area according to the principles of 'bbaeim(drop out)' and 'gaepim(pooling)' It has provided a foundation for establishing itself as an appropriate technology in this area. Such Saemi contributed to the rural landscape and agricultural biodiversity through its own system and served as a public interest function. It is necessary to know, conserve, manage, and continuously utilize the value of this Saemi as an agricultural heritage.

What We Want for Virtual Humans: Classification of Consumer Expectation Value on Virtual Influencer by Age Based on Q-methodology (가상 인간에 대한 우리들이 원하는 모습: Q방법론을 기반으로 한 연령대에 따른 소비자 기대 가치 분류)

  • Ji-Chan Yun;Do-Hyung Park
    • Knowledge Management Research
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    • v.24 no.2
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    • pp.137-159
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    • 2023
  • This study focuses on consumers' perceptions of virtual influencers, which many companies recently used for marketing. This study uses the Q methodology to derive what kind of perception consumers have about virtual influencers who work with various appearances, background stories, and worldviews as components. In addition, we want to see how the expected value of virtual influencers differs by age group. To this end, 34 statements were produced through preliminary interviews and literature reviews. This study showed that some consumers preferred appearances similar to humans, despite recognizing that virtual influencers are fictional characters. Some other consumers preferred to feel like a fictional character by maintaining virtuality, confirming that there are both opposite consumers. In addition, consumers expect virtual influencers to have consistency and expertise in the content field covered, and some consumers do not prefer to show an overly commercial appearance. This study will likely provide implications for companies that want to utilize virtual influencers in considering which ones to use for target customers in marketing activities.

A Study on the Maritime Law According to the Occurrence of Marine Accidents of MASS(Maritime Autonomous Surface Ship) (자율운항선박의 해양사고 발생에 따른 해상법적 고찰)

  • Lee, Young-Ju
    • Maritime Security
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    • v.6 no.1
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    • pp.37-56
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    • 2023
  • Recently, with the rapid development of ICT(Information and Communication Technology) and AI(Artificial Intelligence) technology industries, the emergence of MASS(Maritime Autonomous Surface Ship), which were thought only in the distant future, is approaching a reality. Along with the development of these amazing technologies, changes in the private law sector, such as liability, compensation for damages, and maritime insurance, as well as in the public law sector, such as maritime safety, marine environment protection, and maintenance of maritime order, have become necessary in the field of maritime law. In particular, with the advent of a new type of ship called MASS that does not have a crew on board, the kind and type of liability, compensation for damages, and insurance contracts in the event of a marine accident will also change. In this paper, the general theory about concept, classification, effectiveness and future of MASS and the general theory about concept and various obligations and responsibilities under the maritime law for discussion of MASS are reviewed. Next, in addition, regarding the problems that may occur in the event of a marine accident from MASS, the status as a ship, the legal relationship of the chartering contract, obligation to exercise due diligence in making the vessel seaworthiness, subject of responsibility, and liability for damages and immunity are reviewed from the perspective of maritime law. In addition, in the degree four of MASS, the necessities of further research to clarify the attributable subjects and standards of responsibility in the event of a marine accident, as well as the necessities of institutional improvement such as technology development, enactment and amendment of law and funding are presented.

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Stock Price Direction Prediction Using Convolutional Neural Network: Emphasis on Correlation Feature Selection (합성곱 신경망을 이용한 주가방향 예측: 상관관계 속성선택 방법을 중심으로)

  • Kyun Sun Eo;Kun Chang Lee
    • Information Systems Review
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    • v.22 no.4
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    • pp.21-39
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    • 2020
  • Recently, deep learning has shown high performance in various applications such as pattern analysis and image classification. Especially known as a difficult task in the field of machine learning research, stock market forecasting is an area where the effectiveness of deep learning techniques is being verified by many researchers. This study proposed a deep learning Convolutional Neural Network (CNN) model to predict the direction of stock prices. We then used the feature selection method to improve the performance of the model. We compared the performance of machine learning classifiers against CNN. The classifiers used in this study are as follows: Logistic Regression, Decision Tree, Neural Network, Support Vector Machine, Adaboost, Bagging, and Random Forest. The results of this study confirmed that the CNN showed higher performancecompared with other classifiers in the case of feature selection. The results show that the CNN model effectively predicted the stock price direction by analyzing the embedded values of the financial data

A basic research for evaluation of a Home Care Nursing Delivery System (가정간호 서비스 질 평가를 위한 도구개발연구)

  • Kim, Mo-Im;Cho, Won-Jung;Kim, Eui-Sook;Kim, Sung-Kyu;Chang, Soon-Bok;Ryu, Ho-Sihn
    • Journal of Home Health Care Nursing
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    • v.6
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    • pp.33-45
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    • 1999
  • The purpose of this study was to develop a basic framework and criteria for evaluation of quality care provided to patients with the attributes of disease in the home care nursing field, and to provide measurement tools for home health care in the future. The study design was a developmental study for evaluation of hospital-based HCN(home care nursing) in Korea. The study process was as follows: a home care nursing study team of College of Nursing. Yonsei University reviewed the nursing records of 47 patients who were enrolled at Yonsei University Medical Center Home Care Center in March, 1995. Twenty-five patients were insured at that time, were selected from 47 patients receiving home care service for study feasibility with six disease groups; Caesarean Section (C/S), simple nephrectomy, Liver cirrhosis(LC), chronic obstructive pulmonary disease(COPD), Lung cancer or cerebrovascular accident(CVA). In this study, the following items were selected : First step : Preliminary study 1. Criteria and items were selected on the basis of related literature on each disease area. 2. Items were identified by home care nurses. 3. A physician in charge reviewed the criteria and content of selected items. 4. Items were revised through preliminary study offered to both HCN patients and discharged patients from the home care center. Second step : Pretest 1. To verify the content of the items, a pretest was conducted with 18 patients of which there were three patients in each of the six selected disease groups. Third step : Test of reliability and validity of tools 1. Using the collected data from 25 patients with either cis, Simple nephrectomy, LC, COPD, Lung cancer, or CVA. the final items were revised through a panel discussion among experts in medical care who were researchers, doctors, or nurses. 2. Reliability and validity of the completed tool were verified with both inpatients and HCN patients in each of field for researches. The study results are as follows: 1. Standard for discharge with HCN referral The referral standard for home care, which included criteria for discharge with HCN referral and criteria leaving the hospital were established. These were developed through content analysis from the results of an open-ended questionnaire to related doctors concerning characteristic for discharge with HCN referral for each of the disease groups. The final criteria was decided by discussion among the researchers. 2. Instrument for measurement of health statusPatient health status was measured pre and post home care by direct observation and interview with an open-ended questionnaire which consisted of 61 items based on Gorden's nursing diagnosis classification. These included seven items on health knowledge and health management, eight items on nutrition and metabolism, three items on elimination, five items on activity and exercise, seven items on perception and cognition, three items on sleep and rest, three items on self-perception, three items on role and interpersonal relations, five items on sexuality and reproduction, five items on coping and stress, four items on value and religion, three items on family. and three items on facilities and environment. 3. Instrument for measurement of self-care The instrument for self-care measurement was classified with scales according to the attributes of the disease. Each scale measured understanding level and practice level by a Yes or No scale. Understanding level was measured by interview but practice level was measured by both observation and interview. Items for self-care measurement included 14 for patients with a CVA, five for women who had a cis, ten for patients with lung cancer, 12 for patients with COPD, five for patients with a simple nephrectomy, and 11 for patients with LC. 4. Record for follow-up management This included (1) OPD visit sheet, (2) ER visit form, (3) complications problem form, (4) readmission sheet. and (5) visit note for others medical centers which included visit date, reason for visit, patient name, caregivers, sex, age, time and cost required for visit, and traffic expenses, that is, there were open-end items that investigated OPD visits, emergency room visits, the problem and solution of complications, readmissions and visits to other medical institution to measure health problems and expenditures during the follow up period. 5. Instrument to measure patients satisfaction The satisfaction measurement instrument by Reisseer(1975) was referred to for the development of a tool to measure patient home care satisfaction. The instrument was an open-ended questionnaire which consisted of 11 domains; treatment, nursing care, information, time consumption, accessibility, rapidity, treatment skill, service relevance, attitude, satisfaction factors, dissatisfaction factors, overall satisfaction about nursing care, and others. In conclusion, Five evaluation instruments were developed for home care nursing. These were (1)standard for discharge with HCN referral. (2)instrument for measurement of health status, (3)instrument for measurement of self-care. (4)record for follow-up management, and (5)instrument to measure patient satisfaction. Also, the five instruments can be used to evaluate the effectiveness of the service to assure quality. Further research is needed to increase the reliability and validity of instrument through a community-based HCN evaluation.

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The Social Influence of the Landscape Architecture Engineer Examination on the Establishment of Authenticity in Landscaping History Department (조경기사 '조경사' 과목이 조경역사학(造景歷史學) 분야의 진정성 확립에 미친 사회적 영향)

  • Lee, Chang-Hun;Shin, Hyun-Sil;Kim, Kyu-Seob;Lee, Won-Ho
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.36 no.3
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    • pp.128-136
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    • 2018
  • This study was centered on the protested data of the issue of "History of Landscape Architecture" in the handwritten course of landscaping articles of National Qualifications Test. The purpose of this study is to examine the types of social problems in the process of correcting erroneous historical facts. The purpose of this study was to find alternatives for the development of the field of landscape and culture history that can assist in the verification of the historical facts of the landscape sciences examination questions. The main results are as follows. First, as a result of analyzing the contents of the landscape architects' subject matter, the establishment of concept of landscape style and form and the confirmation of historical facts were investigated as important types to be established for development of landscape landscape history department. It seems that the social consensus of the expert group is needed to supplement the lack of data to refer to landscape architectural theory. Second, the analysis of the problematic narrative contents resulted in a total of five types of questionnaires. The appeared in the Undefined style and form(52.94%), Unproven historical facts(25.13%), Obscurity Era classification(11.77%), Lack of specificity(6.95%), Content scope of obscurity events(3.21%) Third, it is not only the lack of information to learn the theory by comparing and analyzing the contents of the statements in the landscape architect 's question items, but also the difference of contents between books was analyzed as the main cause of the problem. As a result of examining the characteristics and examples of the issues raised in landscape architectural problems, it was related to the social phenomenon, and it was classified into cultural factors and political factors. Fourth, the resolution of problematic issues in landscape architects' landscaping articles, which are national technical qualification tests, shows positive results. The information determined in the process of solving the perceived content can be used directly in landscaping field, and it helps the accuracy of the verification process by identifying the types and characteristics of the issues.

Development of a Failure Probability Model based on Operation Data of Thermal Piping Network in District Heating System (지역난방 열배관망 운영데이터 기반의 파손확률 모델 개발)

  • Kim, Hyoung Seok;Kim, Gye Beom;Kim, Lae Hyun
    • Korean Chemical Engineering Research
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    • v.55 no.3
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    • pp.322-331
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    • 2017
  • District heating was first introduced in Korea in 1985. As the service life of the underground thermal piping network has increased for more than 30 years, the maintenance of the underground thermal pipe has become an important issue. A variety of complex technologies are required for periodic inspection and operation management for the maintenance of the aged thermal piping network. Especially, it is required to develop a model that can be used for decision making in order to derive optimal maintenance and replacement point from the economic viewpoint in the field. In this study, the analysis was carried out based on the repair history and accident data at the operation of the thermal pipe network of five districts in the Korea District Heating Corporation. A failure probability model was developed by introducing statistical techniques of qualitative analysis and binomial logistic regression analysis. As a result of qualitative analysis of maintenance history and accident data, the most important cause of pipeline damage was construction erosion, corrosion of pipe and bad material accounted for about 82%. In the statistical model analysis, by setting the separation point of the classification to 0.25, the accuracy of the thermal pipe breakage and non-breakage classification improved to 73.5%. In order to establish the failure probability model, the fitness of the model was verified through the Hosmer and Lemeshow test, the independent test of the independent variables, and the Chi-Square test of the model. According to the results of analysis of the risk of thermal pipe network damage, the highest probability of failure was analyzed as the thermal pipeline constructed by the F construction company in the reducer pipe of less than 250mm, which is more than 10 years on the Seoul area motorway in winter. The results of this study can be used to prioritize maintenance, preventive inspection, and replacement of thermal piping systems. In addition, it will be possible to reduce the frequency of thermal pipeline damage and to use it more aggressively to manage thermal piping network by establishing and coping with accident prevention plan in advance such as inspection and maintenance.

A Study on the Health Insurance Management System; With Emphasis on the Management Operating Cost (의료보험 관리체계에 대한 연구 - 관리비용을 중심으로 -)

  • 남광성
    • Korean Journal of Health Education and Promotion
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    • v.6 no.2
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    • pp.23-39
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    • 1989
  • There have been a lot of considerable. discussion and debate surrounding the management model in the health insurance management system and opinions regarding the management operating cost. It is a well known fact that there have always been dissenting opinions and debates surrounding the issue. The management operating cost varies according to the scale of the management organization and component members characteristics of the insurance carrier. Therefore, it is necessary to examine and compare the management operating cost to the simulated management models developed to cover those eligible for the health insurance scheme in this country. Since the management operating cost can vary according to the different models of management, four alternative management models have been established based on the critical evaluation of existing theories concerned, as well as on the basis of the survey results and simulation attempts. The first alternative model is the Unique Insurance Carrier Model(Ⅰ) ; desigened to cover all of the people with no classification of insurance qualifications and finances from the source of contribution of the insured, nationwide. The second is the Management Model of Large-scale District Insurance Carrier(Ⅱ) ; this means the Korean society would be divided into 21 large districts; each having its own insurance carrier that would cover the people in that particular district with no classification of insurance qualifications arid finances as in Model I. The third is the Management Model of Insurance Carrier Divided by Area and Classified with Occupation if Largescale (Ⅲ) ; to serve the self-employed in the 21 districts divided as in Model Ⅱ. It would serve the employees and their dependents by separate insurance carriers in large-scale similar to the area of the district-scale for the self-employed, so that the insurance qualifications and finances would be classified with each of the insurance carriers: The last is the Management Model of the Multi - insurance Carrier (Ⅳ) based on the Si. Gun. Gu area which will cover their own self- employed people in the area with more than 150 additional insurance carriers covering the employees and their dependents. The manpower necessary to provide services to all of the people according to the four models is calculated through simulation trials. It indicates that the Management Model of Large-scale District Insurance Carrier requires the most manpower among the four alternative models. The unit management operating costs per the insured individuals and covered persons are leveled with several intervals based on the insurance recipients. in their characteristics. The interval levels derived from the regression analysis reveal that the larger the scale of the insurance carriers is in the number of those insured and covered. the more the unit management operating cost decreases. significantly. Moreover. the result of the quadratic functional formula also shows the U-shape significantly. The management operating costs derived from the simulated calculation. on the basis of the average salary and related cost per staff- member of the Health Insurance Societies for Occupational Labours and Korean Medical Insurance Corporation for the Official Servants and Private School Teachers in 1987 fiscal year. show that the Model of Multi-insurance Carrier warrants the highest management operating cost. Meanwhile the least expensive management operating cost is the Management Model of Unique Insurance Carrier. Insurance Carrier Divided by Area and Classified with Occupation in Large-scale. and Large-scale District Insurance Carrier. in order. Therefore. it is feasible to select the Unique Insurance Carrier Model among the four alternatives from the viewpoint of the management operating cost and in the sense of the flexibility in promoting the productivity of manpower in the human services field. However. the choice of the management model for health insurance systems and its application should be examined further utilizing the operation research analysis for such areas as the administrative efficiency and factors related to computer cost etc.

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Anomaly Detection for User Action with Generative Adversarial Networks (적대적 생성 모델을 활용한 사용자 행위 이상 탐지 방법)

  • Choi, Nam woong;Kim, Wooju
    • Journal of Intelligence and Information Systems
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    • v.25 no.3
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    • pp.43-62
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    • 2019
  • At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.