• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.193-206
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• 2008

Medical diagnosis can be considered a classification task which classifies disease types from patient's condition data represented by a set of pre-defined attributes. This study proposes a hybrid genetic algorithm based classification method to develop classifiers for multidimensional pattern classification problems related with medical decision making. The classification problem can be solved by identifying separation boundaries which distinguish the various classes in the data pattern. The proposed method fits a finite number of regional agents to the data pattern by combining genetic algorithms and local adaptive operations. The local adaptive operations of an agent include expansion, avoidance and relocation, one of which is performed according to the agent's fitness value. The classifier system has been tested with well-known medical data sets from the UCI machine learning database, showing superior performance to other methods such as the nearest neighbor, decision tree, and neural networks.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.3
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• pp.147-154
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• 2023

In the case of river facilities, the management of this information differs depending on national and regional rivers, therefore, there is no integrated management in place. There is concern about the loss of facility information owing to the insufficient accumulation of information during their design and construction stages. Additionally, as a result, the utilization level of facility information during the maintenance and operation stages is insufficient. To ensure effective maintenance and operation of river facilities, it is necessary to secure data consistency and increase efficiency by organizing facility information according to a standardized classification system. This study proposes a strategy for implementing the BIM standard classification system in the river sector, considering facility characteristics. The goal is to introduce a BIM information model for 3D-based river facilities, and enable efficient maintenance and operation conversion.

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.82-95
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• 2024

Analyzing the aftermath of events at domestic nuclear power plants brings in the question: "Why do workers not comply with the prescribed procedures?" The current investigation of nuclear power plant events identifies their reasons considering the factors affecting the workers' behaviors. However, there are some complications to it: in addition to confirming the action such as an error or a violation, there is a limit to identifying the intention of the actor. To overcome this limitation, the study analyzed and examined the reasons for non-compliance identified in nuclear power plant events by Reason's rule-related behavior classification. For behavior analysis, I selected unit behaviors for events that are related to human and organizational factors and occurred at domestic nuclear power plants since 2017, and then I applied the rule-related behavior classification introduced by Reason (2008). This allowed me to identify the intentions by classifying unit behaviors according to quality and compliance with the rules. I also identified the factors that influenced unit behaviors. The analysis showed that most often, non-compliance only pursued personal goals and was based on inadequate risk appraisal. On the other hand, the analysis identified cases where it was caused by such factors as poorly written procedures or human system interfaces. Therefore, the probability of non-compliance can be reduced if these factors are properly addressed. Unlike event investigation techniques that struggle to identify the reasons for employee behavior, this study provides a new interpretation of non-compliance in nuclear power plant events by examining workers' intentions based on the concept of rule-related behavior classification.

• Journal of the Korean Geographical Society
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• v.39 no.1
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• pp.132-152
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• 2004

The critical point in this research is that the research on the phenomenon "teaching geography" should include how various elements consisting of the phenomenon are interrelated with each other in diverse angles, not deal with only teaching methods. This research focused on the relationships of the three components of teaching geography : contents of geography subject matter; learner; and scaffolding. Firstly, the characteristics of contents of geography subject matter were analyzed. Geographical knowledge was classified into four categories based on the way of perception. And then the selected geographic contents for this study were done didactic transposition into materials for geography education. These can be presented in a specific classification system from a context of geography education. Secondly, four categories of learning styles were divided by the way learners perceive and process information : Diverger; Assimilator; Converger; Accommodator. Each was connected with learner′s preferred contents of geography subject matter. The correlation between divergers and typical CulturalㆍHistorical Geography and Environmental Geography was high. So was between assimilators and typical Physical Geography and UrbanㆍEconomic Geography. Learners of Converger style tend to prefer GIS and Cartography. Finally, Regional Development and Regional Environmental Problems were highly correlated with accommodators.

• Journal of the Korean association of regional geographers
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• v.9 no.3
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• pp.385-394
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• 2003

Authors tried to classify landforms of civilian-restricted trans-border coastal region of the East Sea by using both field survey and remote sensing data including IKONOS images and digital maps. As a result, authors can draw the boundaries of landform units on satellite images and classify landforms effectively. Typical landforms of undisturbed depositional coastal area such as coastal sand dune, sand bar, lagoons, and tombolo are found within the study area. Also, riverine wetlands and estuarine wetlands are readily discernable on both satellite image and field survey. Even though landforms within the study area are relatively small, they are so dynamically connected that their preservation value is very high.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.3
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• pp.35-46
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• 2013

In order to develop an accurate analytical model for domestic electricity demand forecasting, we propose a prediction method of the electric power demand pattern by combining SMO classification techniques and a dimension reduction conceptualized subspace clustering techniques suitable for high-dimensional data cluster analysis. In terms of electricity demand pattern prediction, hourly electricity load patterns and the demographic and geographic characteristics can be analyzed by integrating the wireless load monitoring data as well as sub-regional unit of census information. There are composed of a total of 18 characteristics clusters in the prediction result for the sub-regional demand pattern by using census information and power load of Seoul metropolitan area. The power demand pattern prediction accuracy was approximately 85%.

• Safety and Health at Work
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• v.6 no.4
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• pp.353-356
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• 2015

Background: In 2012, the Alaska Section of Epidemiology investigated personnel potentially exposed to a Brucella suis isolate as it transited through three laboratories. Methods: We summarize the first implementation of the United States Centers for Disease Control and Prevention 2013 revised recommendations for monitoring such exposures: (1) risk classification; (2) antimicrobial postexposure prophylaxis; (3) serologic monitoring; and (4) symptom surveillance. Results: Over 30 people were assessed for exposure and subsequently monitored for development of illness. No cases of laboratory-associated brucellosis occurred. Changes were made to gaps in laboratory biosafety practices that had been identified in the investigation. Conclusion: Achieving full compliance for the precise schedule of serologic monitoring was challenging and resource intensive for the laboratory performing testing. More refined exposure assessments could inform decision making for follow-up to maximize likelihood of detecting persons at risk while not overtaxing resources.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.28-32
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• 2021

The article discusses the theoretical and methodological part that characterizes and assessment of the current state of the theory of GR-activity, disclosed the essence and content of the concept of GR-technologies, as well as their classification. The analysis of the system of additional education for children in the social structure, as well as the analysis of the current state of the education system is carried out. The formulation of tasks for the construction of an effective model for the use of GR-technologies in the process of developing the education system using GR-technologies

• Journal of Korean Society of Rural Planning
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• v.30 no.2
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• pp.79-96
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• 2024

The purpose of this study is to analyze the factors affecting residential mobility between urban and rural. After classifying urban and rural region based on discriminatory attributes of the regions, we applied a multinomial logistic model, using the sample data of 2020 Korea Population and Housing Census. The major findings are as follows. The young highly educated in cities avoided rural. The young less educated in rural engaged in 2, 3th industries as well as agricultural industry, but remained in low-paying and unstable jobs. In addition, various classes moved to rural and rising house prices in cities pushed people to rural. Therefore, it is necessary to develop diversified regional industry models and provide opportunities for high quality and stable jobs in rural by linking industrial demand, education and jobs. Also, preserving the rural environment, settlement conditions and residential environment are needed for satisfying various needs of urban residents who migrate to rural areas. While regional policies so far have focused on maintaining the population size and promoting a population influx, rural development and population policies should be established in a way that responds to diverse population classes in an era of population decline.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.26-41
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• 2012

It is necessary to manage, forecast and prepare agricultural production based on accurate and up-to-date information in order to cope with the climate change and its impacts such as global warming, floods and droughts. This study examined the applicability as well as challenges of the object-based image analysis method for developing a land cover image classification algorithm, which can support the fast thematic mapping of wide agricultural areas on a regional scale. In order to test the applicability of RapidEye's multi-temporal spectral information for differentiating agricultural land cover types, the integration of other GIS data was minimized. Under this circumstance, the land cover classification accuracy at the study area of Kimje ($1300km^2$) was 80.3%. The geometric resolution of RapidEye, 6.5m showed the possibility to derive the spatial features of agricultural land use generally cultivated on a small scale in Korea. The object-based image analysis method can realize the expert knowledge in various ways during the classification process, so that the application of spectral image information can be optimized. An additional advantage is that the already developed classification algorithm can be stored, edited with variables in detail with regard to analytical purpose, and may be applied to other images as well as other regions. However, the segmentation process, which is fundamental for the object-based image classification, often cannot be explained quantitatively. Therefore, it is necessary to draw the best results based on expert's empirical and scientific knowledge.