• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.141-152
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• 2011

The Internet is changing old organizational schemes, including education. A growing number of universities are creating curriculums to reflect these changes. Economic market is being opened to the international world, and in order to overcome the difficulties are demanding continuous supply of men power from university to efficiently manage human resource and implement superior e-business model. Technology innovation plays an important role in the sustainable grows of the firm in the global economy. The objective of this study is to suggest an e-business curriculum for e-business department. We will analyze what kind of people is needed for e-business, and provide appropriate curriculum for educating suitable human resources, which could be for university program. This study may contribute to the much needed systematic analysis for e-business curriculum. We prioritize e-business curriculum selected and rank their importance through an exploratory study for suggesting the undergraduate curriculum.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.2
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• pp.199-207
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• 2010

Recently, large amount of information in IDS(Intrusion Detection System) can be un manageable and also be mixed with false prediction error. In this paper, we propose a data mining methodology for IDS, which contains uncertainty based on training process and post-processing analysis additionally. Our system is trained to classify the existing attack for misuse detection, to detect the new attack pattern for anomaly detection, and to define border patter between attack and normal pattern. In experimental results show that our approach improve the performance against existing attacks and new attacks, from 0.62 to 0.84 about 35%.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.205-206
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• 2019

National Competency Standard(NCS) is a national organization that organizes the knowledge, skills, and quality required to perform duties at industrial sites by industry sector and level. As NCS was developed and adopted as part of the government's implementation of capability-oriented society, the construction industry is also fully applying NCS to the curriculum and training. This study investigated and analyzed the problems of NCS development in construction work field through prior research analysis and experts interview and derived problems such as discrepancies in classification system, lack of connectivity with curriculum, and lack of effectiveness in revising NCS in construction work field. Further research is thought to be necessary for the establishment of the development system reflecting the construction characteristics in the future and for the presentation of practical improvement directions.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.5
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• pp.531-536
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• 2021

As artificial intelligence technology advances, it is being applied to various application fields. Artificial intelligence is performing well in the field of image recognition and classification. Chip design specialized in this field is also actively being studied. Artificial intelligence-specific chips are designed to provide optimal performance for the applications. At the design task, memory component optimization is becoming an important issue. In this study, the optimal algorithm for the memory size exploration is presented, and the optimal memory size is becoming as a important factor in providing a proper design that meets the requirements of performance, cost, and power consumption.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.2
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• pp.19-28
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• 2019

The purpose of this study is to examine the trends on machine learning and deep learning research in the published journals from the Web of Science Database. To achieve the study purpose, we used the abstracts of 20,664 articles published between 1990 and 2017, which include the word 'machine learning', 'deep learning', and 'artificial neural network' in their titles. Twenty major research topics were identified from topic modeling analysis and they were inclusive of classification accuracy, machine learning, optimization problem, time series model, temperature flow, engine variable, neuron layer, spectrum sample, image feature, strength property, extreme machine learning, control system, energy power, cancer patient, descriptor compound, fault diagnosis, soil map, concentration removal, protein gene, and job problem. The analysis of the time-series linear regression showed that all identified topics in machine learning research were 'hot' ones.

• Journal of Biomedical Engineering Research
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• v.39 no.6
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• pp.256-267
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• 2018

The number of items and the market size of the senior-friendly medical devices are rapidly increasing, and it is necessary to come up with a safety management plan for senior-friendly medical devices. We searched and analyzed the definition and policy of senior-friendly medical device, and classified medical device items of the Ministry of Food and Drug Safety, calculated market sizes and manufacturing export import results by classification, and investigated the current state of senior-friendly industry and the fields of its culture. In order to prepare a safety management plan, we reduce the number of items that need to be managed intensively by extracting 69 items for administration, that are substantially harmful to the elderly. As specific safety management plans of items for administration, we propose plans for introductions of readability-enhanced labeling, QR codes for cautions and manuals, universal design mandatory, UDI code system with considering a balanced viewpoint of the industry development.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.1
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• pp.37-45
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• 2022

It is well known that the Kano model measures customer satisfaction and classifies quality attributes into must-be, attractive as well as one-dimensional. The main purpose of this study is to investigate the dynamics of e-learning quality attributes by applying the proposed method using Kano's satisfaction index in the rapidly changing online learning environment. For this, the current study examined 27 e-learning quality attributes and conducted a comparative study using Kano's results obtained in 2013 and 2020. The result shows that the dynamics of quality attributes suggested by Kano(2001) is confirmed in the case of e-learning. The proposed approach shows better results in terms of Kano's direct classification method, and has potential application areas such as IPA(Importance-Performance Analysis) in the area of risk assemement. Some suggestions for better understanding of the proposed SI-DI diagram are also included in this study.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.349-354
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• 2020

This paper, firstly, propose a new Clustering scheme Based on Conceptual graphs (CBC) that can describe objects freely and can perform clustering efficiently. The conceptual clustering is one of machine learning technique. The similarity among the objects in conceptual clustering are decided on the bases of concept membership, unlike the general clustering scheme which decide the similarity without considering the context or environment of the objects. A new conceptual clustering scheme, CBC, which can perform efficient conceptual clustering by describing various objects freely with conceptual graphs is introduced in this paper.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1083-1090
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• 2022

Since renal cell carcinoma(RCC) has various examination and treatment methods according to clinical stage and histopathological characteristics, it is required to determine accurate and efficient treatment methods in the clinical field. However, the process of collecting and processing RCC medical data is difficult and complex, so there is currently no AI-based clinical decision support system for RCC treatments worldwide. In this study, we propose a clinical decision support system that helps clinicians decide on a precision treatment to each patient. RCC standard big database is built by collecting structured and unstructured data from the standard common data model and electronic medical information system. Based on this, various machine learning classification algorithms are applied to support a better clinical decision making.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_2
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• pp.687-697
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• 2022

An automated system is needed for the effectiveness of non-destructive testing. In order to utilize the radiographic testing data accumulated in the film, the types of welding defects were classified into 9 and the shape of defects were analyzed. Data was preprocessed to use deep learning with high performance in image classification, and a combination of one-stage/two-stage method and convolutional neural networks/Transformer backbone was compared to confirm a model suitable for welding defect detection. The combination of two-stage, which can learn step-by-step, and deep-layered CNN backbone, showed the best performance with mean average precision 0.868.