• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.225-230
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• 2018

Recently, there are various employment-related homepages such as Jobkorea and World Job. However, since these websites have the one-to-one communication with corporate users and users, the amount of information that can be obtained from the viewpoint of users is limited. The proposed system improves this limitation, where a user creates a blog through member registration, uploads and creates a document to a blog, and a company official can perform an annotation function. This enables users to easily manage the desired documents, share information with other users, and affix them to the users who want to add to the company, so that the corporate users and users can communicate with each other. Thus, we believe that the proposed model can solve problems in the current job market and provide a new level of portfolio system for new media environment.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.2
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• pp.51-73
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• 2022

Currently, an implementation plan of administrative information dataset record management has been prepared; however, analyzing the specificity of various administrative information systems and preparing a reasonable level of management reference table by applying about 1.3% (EA portal registration system: 16,199, consulting system: 214) has its limitations. This study started by recognizing the importance of the records management environment in administrative information datasets. Based on the described information, the current records management environment was analyzed by dividing the six areas of the management reference table of the picture archiving and communication system (PACS) into three groups. Thus, a systematic environmental improvement model was proposed, enhancing the effectiveness of dataset records management in the field. Although there is a limitation in analyzing one of the dataset records management environments of various institutions, it is intended to help broaden the horizons of records management research.

• Journal of radiological science and technology
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• v.46 no.5
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• pp.435-444
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• 2023

The purpose of this study was to analyze the factors that demographic factors, radiation knowledge level, and radiation awareness could be affecting the benefits of radiation. From July 2022 to July 2023, after receiving consent to participate by using the link of Naver through Social Network Service (SNS) for the general public, 312 people were surveyed by self-registration method without collecting personal information. The questionnaire consisted of a total of 25 questions following demographic factors (5 questions including age group by life cycle, sex, monthly household income, residence), radiation knowledge level (8 questions including basic physical, biological effects, radiation protection technology), radiation awareness (12 questions including risk, management, benefit). Independent sample T-test and ANOVA tests were performed for significant differences in the average radiation awareness between variables, and hierarchical regression was performed to identify influencing factors on radiation benefits. As a result, the benefit of radiation was significantly high among the radiation awareness, but the awareness of the danger of radiation was insufficient to the level of recognizing it as safe. Men had significantly higher awareness of radiation management and benefits than women, and the awareness of radiation management was significantly higher in the middle class with a monthly household income of 4.31 million won or more. The higher the knowledge level of radiation, the higher the awareness of the benefits of radiation. The factors that had a positive effect on radiation benefits were the high level of radiation knowledge and awareness of radiation management.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.31-40
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• 2024

In the realm of domestic online fashion platform industry the manual registration of product information by individual business owners leads to inconvenience and reliability issues, especially when dealing with simultaneous registrations of numerous product groups. Moreover, bias is significantly heightened due to the low quality of product images and an imbalance in data quantity. Therefore, this study proposes a ResNet50 model aimed at minimizing data bias through oversampling techniques and conducting multiple classifications for 13 fashion categories. Transfer learning is employed to optimize resource utilization and reduce prolonged learning times. The results indicate improved discrimination of up to 33.4% for data augmentation in classes with insufficient data compared to the basic convolution neural network (CNN) model. The reliability of all outcomes is underscored by precision and affirmed by the recall curve. This study is suggested to advance the development of the domestic online fashion platform industry to a higher echelon.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.435-441
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• 2024

In order for the large amount of collected data sets to be used as deep learning training data, sensitive personal information such as resident registration number and disease information must be changed or encrypted to prevent it from being exposed to hackers, and the data must be reconstructed to match the structure of the built deep learning model. Currently, these tasks are performed manually by experts, which takes a lot of time and money. To solve these problems, this paper proposes a technique that can automatically perform data processing tasks to protect personal information during the deep learning process. In the proposed technique, privacy protection tasks are performed based on data generalization and data reconstruction tasks are performed using circular queues. To verify the validity of the proposed technique, it was directly implemented using C language. As a result of the verification, it was confirmed that data generalization was performed normally and data reconstruction suitable for the deep learning model was performed properly.

• The Korean Journal of Pesticide Science
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• v.18 no.4
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• pp.236-246
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• 2014

Pesticide is used to protect the crops, but also become a cause of polluting the environment. Perform a risk assessment using physical and chemical properties, environmental fate and toxicity data in order to determine the pesticide registration. The aquatic model estimates pesticide concentrations in water bodies that result from pesticide applications to rice paddies and apple orchard. The used models are the PRZM, EXAMS and AGRO shell (PA5), Rice Water Quality Model (RICEWQ) and Screening Concentration In GROund Water (SCI-GROW). The residual concentration of water body was estimated using meteorological data, crop calendar and soil series of Korea. The chosen pesticides were butachlor, carbofuran, iprobenfos and tebuconazole. It has shown the potential that the RICEWQ is possible to predict residue level in water of butachlor and iprobenfos, because the maximum value in water monitoring data is lower than the peak concentration of the model, and the minimum value is lower than the average annual concentration of the model. But RICEWQ was insufficient to predict exposure concentrations in ground water. The estimated exposure concentrations of carbofuran in ground water is very higher than in surface water because of its low soil adsorption coefficient. Although tebuconazole were not detected in the water monitoring that means very low concentration, it is possible that the PA5 can be used to predict residue level in water.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7C
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• pp.997-1006
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• 2004

The rapid expansion of the Internet has provided users with a diverse range of services. Most Internet users create many different IDs and passwords to subscribe to various Internet services. Thus, the SSO system has been proposed to supplement vulnerable security that may arise from inefficient management system where administrators and users manage a number of ms. The SSO system can provide heightened efficiency and security to users and administrators. Recently commercialized SSO systems integrate a single agent with the broker authentication model. However, this hybrid authentication system cannot resolve problems such as those involving user pre-registration and anonymous users. It likewise cannot provide non-repudiation service between joining objects. Consequently, the hybrid system causes considerable security vulnerability. Since it cannot provide security service for the agent itself, the user's private information and SSO system may have significant security vulnerability. This paper proposed an authentication model that integrates a broker authentication model, out of various authentication models of the SSO system, with a multi-agent system. The proposed method adopts a secure multi-agent system that supplements the security vulnerability of an agent applied to the existing hybrid authentication system. The method proposes an SSO authentication model that satisfies various security requirements not provided by existing broker authentication models and hybrid authentication systems.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.159-173
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• 2017

In order to provide technical financial support to small and medium-sized venture companies based on technology, the government implemented the TCB evaluation, which is a kind of technology rating evaluation, from the Kibo and a qualified private TCB. In this paper, we briefly review the current state of TCB evaluation and available indicators related to technology evaluation accumulated in the Korea Credit Information Services (TDB), and then use indicators that have a significant effect on the technology rating score. Multiple regression techniques will be explored. And the relative importance and classification accuracy of the indicators were calculated by applying the key indicators as independent features applied to the generalized boosting model, which is a representative machine learning classifier, as the class influence and the fitness of each model. As a result of the analysis, it was analyzed that the relative importance between the two models was not significantly different. However, GBM model had more weight on the InnoBiz certification, R&D department, patent registration and venture confirmation indicators than regression model.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.191-197
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• 2019

As the shipbuilding and offshore plant industries grow larger and more complex, their maintenance and inspection systems become more important. Recently, maintenance and inspection systems based on augmented reality have been attracting much attention for improving worker's understanding of work and efficiency, but it is often difficult to work with because accurate matching between the augmented model and reality information is not. To solve this problem, marker based AR technology is used to attach a specific image to the model. However, the markers get damaged due to the characteristic of the shipbuilding and offshore plant industry, and the camera needs to be able to detect the entire marker clearly, and thus requires sufficient space to exist between the operator. In order to overcome the limitations of the existing AR system, in this study, a markerless AR was adopted to accurately recognize the actual model of the pipe system that occupies the most processes in the shipbuilding and offshore plant industries. The matching methodology. Through this system, it is expected that the twist phenomenon of the augmented model according to the attitude of the real worker and the limited environment can be improved.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.1025-1032
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• 2006

Sensor modeling of high-resolution satellites is a prerequisite procedure for mapping and GIS applications. Sensor models, describing the geometric relationship between scene and object, are divided into two main categories, which are rigorous and approximate sensor models. A rigorous model is based on the actual geometry of the image formation process, involving internal and external characteristics of the implemented sensor. However, approximate models require neither a comprehensive understanding of imaging geometry nor the internal and external characteristics of the imaging sensor, which has gathered a great interest within photogrammetric communities. This paper described a comparison between rigorous and various approximate sensor models that have been used to determine three-dimensional positions, and proposed the appropriate sensor model in terms of the satellite imagery usage. Through the case study of using IKONOS satellite scenes, rigorous and approximate sensor models have been compared and evaluated for the positional accuracy in terms of acquirable number of ground controls. Bias compensated RFM(Rational Function Model) turned out to be the best among compared approximate sensor models, both modified parallel projection and parallel-perspective model were able to be modelled with a small number of controls. Also affine transformation, one of the approximate sensor models, can be used to determine the planimetric position of high-resolution satellites and perform image registration between scenes.