• 경영과학
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• 제10권1호
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• pp.1-22
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• 1993

Systemetic classification of a technology is critical to the development of technology strategy. This paper suggests a new technology classification scheme for computer and communication : a two-level scheme. Technology is first classified by its role and function in the upper level which forms a 2 * 2 matrix. The technology is then further classified into the lower level of 3 classes by associations among technology elements. Thus, a new classification scheme of 2 * 2 * 3 matrix is proposed for the computer and communication technology.

• 대한원격탐사학회지
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• 제38권4호
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• pp.395-409
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• 2022

The purpose of this study is to evaluate the classification performance and applicability when land cover datasets constructed for AI training are cross validation to other areas. For study areas, Gyeongsang-do and Jeolla-do in South Korea were selected as cross validation areas, and training datasets were obtained from AI-Hub. The obtained datasets were applied to the U-Net algorithm, a semantic segmentation algorithm, for each region, and the accuracy was evaluated by applying them to the same and other test areas. There was a difference of about 13-15% in overall classification accuracy between the same and other areas. For rice field, fields and buildings, higher accuracy was shown in the Jeolla-do test areas. For roads, higher accuracy was shown in the Gyeongsang-do test areas. In terms of the difference in accuracy by weight, the result of applying the weights of Gyeongsang-do showed high accuracy for forests, while that of applying the weights of Jeolla-do showed high accuracy for dry fields. The result of land cover classification, it was found that there is a difference in classification performance of existing datasets depending on area. When constructing land cover map for AI training, it is expected that higher quality datasets can be constructed by reflecting the characteristics of various areas. This study is highly scalable from two perspectives. First, it is to apply satellite images to AI study and to the field of land cover. Second, it is expanded based on satellite images and it is possible to use a large scale area and difficult to access.

• Management Science and Financial Engineering
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• 제19권1호
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• pp.1-10
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• 2013

Hierarchical forecasting strategy does not always outperform direct forecasting strategy. The performance generally depends on demand features. This research guides the use of the alternative forecasting strategies according to demand features. This paper developed and evaluated various classification models such as logistic regression (LR), artificial neural networks (ANN), decision trees (DT), boosted trees (BT), and random forests (RF) for predicting the relative performance of the alternative forecasting strategies for the South Korean navy's spare parts demand which has non-normal characteristics. ANN minimized classification errors and inventory costs, whereas LR minimized the Brier scores and the sum of forecasting errors.

• 대한안전경영과학회지
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• 제26권1호
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• pp.63-74
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• 2024

The objectives of this study is to classify evacuation types, derive the characteristics of 4 types, develop and discover evacuation routes within the performance hall space, and present the statistical classification results of the evacuation classification model by classification type. To achieve this purpose, the characteristics of each evacuation type's four types are applied through a network reliability analysis method and utilized for institutional improvement and policy. This study applies for the building law, evacuation and relief safety standards when establishing a performance hall safety management plan, and reflects it in safety-related laws, safety standards, and policy systems. Statistical data by evacuation type were analyzed, and measurement characteristics were compared and analyzed by evacuation types. Evaluate the morphological similarity and reliability of evacuation types according to door width and passage length and propose the install position of evacuation guidance sign boards. The results of this study are expected to be used as basic data to provide operation strategies for safety facility evacuation information sign boards according to evacuation route classification types when taking a safety management plan. The operation strategy for the evacuation sign boards installation that integrates employee guidance and safety training is applied to the performance hall safety management plan. It will contribute to establishing an operational strategy for performance space safety when constructing performance facilities in the future.

• Journal of Information Technology Applications and Management
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• 제31권1호
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• pp.79-95
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• 2024

In modern society, as data plays a crucial role at the levels of businesses, industries, and nations, the utilization of data becomes increasingly important. Consequently, governments are prioritizing the development and implementation of plans to cultivate data workforce, viewing the data industry as a cornerstone of national strategy. To enhance domestic capabilities and nurture workforce in the data industry, it is deemed necessary to conduct an objective comparative analysis with major foreign countries. Therefore, this study aims to analyze cases of domestic and international data industries and explore methods for quantitatively comparing data industry workforce across nations. Initially, the study distinguishes between "data industry workforce" and "data job-related workforce," particularly focusing on professionals handling data-related tasks. Subsequently, it compares the workforce sizes of data job-related workforce across nations, utilizing standardized occupational classification codes based on the International Standard Classification of Occupations(ISCO). However, it should be noted that countries employing their own unique occupational classification systems often require matching job titles with similar meanings for accurate comparison. Through this study, it is anticipated that policymakers will be able to establish future directions for cultivating data workforce based on comparable status.

• Journal of Information Technology Applications and Management
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• 제15권4호
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• pp.21-36
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• 2008

As the great disturbance from abusing credit cards in Korea becomes stabilized, credit card companies need to interpret credit-card delinquents classification models from the viewpoint of profit. However, hit ratio which has been used as a measure of goodness of classification models just tells us how much correctly they classified rather than how much profits can be obtained as a result of using classification models. In this research, we tried to develop a new utility-based measure from the viewpoint of profit and then used this new measure to analyze two classification models(Neural Networks and Decision Tree models). We found that the hit ratio of neural model is higher than that of decision tree model, but the utility value of decision tree model is higher than that of neural model. This experiment shows the importance of utility based measure for credit-card delinquents classification models. We expect this new measure will contribute to increasing profits of credit card companies.

• Geomechanics and Engineering
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• 제37권3호
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• pp.263-277
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• 2024

Artificial Neural Networks (ANNs) are artificial learning algorithms that provide successful results in solving many machine learning problems such as classification, prediction, object detection, object segmentation, image and video classification. There is an increasing number of studies that use ANNs as a prediction tool in soil classification. The aim of this research was to understand the role of hyperparameter optimization in enhancing the accuracy of ANNs for soil type classification. The research results has shown that the hyperparameter optimization and hyperparamter optimized ANNs can be utilized as an efficient mechanism for increasing the estimation accuracy for this problem. It is observed that the developed hyperparameter tool (HyperNetExplorer) that is utilizing the Covariance Matrix Adaptation Evolution Strategy (CMAES), Genetic Algorithm (GA) and Jaya Algorithm (JA) optimization techniques can be successfully used for the discovery of hyperparameter optimized ANNs, which can accomplish soil classification with 100% accuracy.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.198-201
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• 2000

We propose a method for analyzing the document structure. This method consists of two processes, segmentation and classification. The segmentation first divides a low resolution image, and then finely splits the original document image using projection profiles. The classification deterimines each segmented region as text, line, table or image. An experiment with 238 documents images shows that the segmentation accuracy is 99.1% and the classification accuracy is 97.3%.

• International Journal of Knowledge Content Development & Technology
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• 제4권1호
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• pp.39-51
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• 2014

The paper proposes that the Basic Concepts Classification (BCC) could serve as the controlled vocabulary for the Semantic Web. The BCC uses a synthetic approach among classes of things, relators, and properties. These are precisely the sort of concepts required by RDF triples. The BCC also addresses some of the syntactic needs of the Semantic Web. Others could be added to the BCC in a bottom-up process that carefully evaluates the costs, benefits, and best format for each rule considered.

• 한국과학교육학회지
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• 제32권1호
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• pp.95-112
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• 2012

이 연구에서는 초등학생의 관찰과 분류를 중심으로 한 명시적이고 반성적인 교수 학습전략을 개발, 적용하여 학생들의 과학 탐구기능 향상에 미치는 효과를 알아보았다. 명시적이고 반성적인 교수 학습전략은 이론적 고찰 후에 초안을 개발하고 전문가 검토를 거쳐 수정, 보완하였다. 실제 수업 진행을 위해 실험집단은 명시적이고 반성적인 교수 학습전략을 적용하여 수업하였고, 통제집단은 교사용지도서에 따른 일반적인 수업을 하였다. 학생들은 수업시행 전 후 과학탐구능력검사와 수업시행 후 학업성취도 검사를 하였다. 그리고 수업전사자료, 심층면담, 교사의 반성적 저널을 통해서 수업 전 후 탐구기능의 변화를 살펴보았다. 연구의 결과로 첫째, 개발한 교수 학습전략의 단계를 (1) 동기유발하기, (2) 반성적으로 탐색하기, (3) 명시적으로 안내하기, (4) 명시적으로 탐구하기, (5) 반성적으로 검증하기의 5단계로 설정하였다. 둘째, 개발한 교수 학습전략의 수업 적용 결과, 정량분석에서는 관찰과 분류에 대한 탐구능력의 성취도 향상이 전체(관찰과 분류를 합한 탐구능력)와 관찰능력에는 효과적이었으나, 분류능력에는 효과가 나타나지 않았다. 또한 개발된 수업전략을 적용한 수업은 학업성취도 향상에 효과적인 것으로 나타났다. 특히 학업성취도와 탐구능력의 상관관계를 분석한 결과, 학업성취도를 높이기 위해서는 탐구능력의 향상이 중요하다는 사실을 알 수 있었다. 셋째, 정성분석결과, 개발한 교수 학습전략을 적용한 수업에서 교사의 명시적인 안내와 소집단 활동을 통하여 반성적인 학습활동이 이루어졌다. 이는 학생의 관찰과 분류의 탐구기능 향상에 효과적이었다. 그리고 정량분석과 정성분석 결과를 통해 과학탐구의 가장 기본적인 관찰기능이 형성된 후 이를 바탕으로 분류기능이 향상됨을 알 수 있었다.