• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.43-52
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• 2023

Rubber produced by rubber companies is subjected to quality suitability inspection through rheometer test, followed by secondary processing for automobile parts. However, rheometer test is being conducted by humans and has the disadvantage of being very dependent on experts. In order to solve this problem, this paper proposes a deep learning-based rheometer quality inspection system. The proposed system combines LSTM(Long Short-Term Memory) and CNN(Convolutional Neural Network) to take advantage of temporal and spatial characteristics from the rheometer. Next, combination materials of each rubber was used as an auxiliary input to enable quality conformity inspection of various rubber products in one model. The proposed method examined its performance with 30,000 validation datasets. As a result, an F1-score of 0.9940 was achieved on average, and its excellence was proved.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.153-167
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• 2024

DMAIC is the most familiar problem-solving methodology to battery manufacturing-related engineers, but continuous problems such as task delay, insufficient performance, and partial optimization are occurring due to indiscriminate application to various tasks of battery production system developers. In order to secure an "optimized model for DMAIC methodology" that can effectively respond to battery production system developers' tasks, a three-stage research model was used to derive the required characteristics of the production system developer task methodology, analyze the suitability of DMAIC, and conduct optimization modeling by supplementing the shortcomings. It was confirmed that the DMAIC methodology can be more suitable by applying the "system structural seven-step methodology", which is the result of this study, to developer tasks. It is expected that it will be applied to various industrial fields in the future by making it easier to learn and allowing differentiated operations according to the characteristics of various industries.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.383-393
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• 2024

Monopile foundations of offshore wind turbines embedded in soft clay are subjected to the long-term cyclic lateral loads induced by winds, currents, and waves, the vibration of monopile leads to the accumulation of pore pressure and cyclic strains in the soil in its vicinity, which poses a threat to the safety operation of monopile. The researchers mainly focused on the hysteretic stress-strain relationship of soft clay and kinds of stiffness degradation models have been adopted, which may consume considerable computing resources and is not applicable for the long-term bearing performance analysis of monopile. In this study, a modified cyclic stiffness degradation model considering the effect of plastic strain and pore pressure change has been proposed and validated by comparing with the triaxial test results. Subsequently, the effects of cyclic load ratio, pile aspect ratio, number of load cycles, and length to embedded depth ratio on the accumulated rotation angle and pore pressure are presented. The results indicate the number of load cycles can significantly affect the accumulated rotation angle of monopile, whereas the accumulated pore pressure distribution along the pile merely changes with pile diameter, embedded length, and the number of load cycles, the stiffness of monopile can be significantly weakened by decreasing the embedded depth ratio L/H of monopile. The stiffness degradation of soil is more significant in the passive earth pressure zone, in which soil liquefaction is likely to occur. Furthermore, the suitability of the "accumulated rotation angle" and "accumulated pore pressure" design criteria for determining the required cyclic load ratio are discussed.

• Research in Plant Disease
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• v.7 no.1
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• pp.20-24
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• 2001

As stand-missing rate (SMR) of ginseng plants in fields are directly related to the ginseng root rot, the forecasting model for the root rot progress in ginseng fields was developed, using the estimated SMRs by disease incidence (DI) of ginseng seedling in the soil-indexing bioassay and the estimate of DI derived from soil environmental factors or rhizoplane microflora. For fitness analysis of the forecasting model, simple correlation and linear regression between SMRs at different planting ages in fields and their estimates by 3 factors of the model were evaluated.The SMR estimated from the factor of DI in the bioassay had much higher fitness to the SMR observed in fields than that from the factors of soil environments and rhizoplane microflora. The estimated SMRs in young and aged ginseng fields by DI in the bioassay were significantly correlated with the observed SMRs in 3- and 5-year-old ginseng fields, respectively (p=0.01). this implicates that indexing preplanting field soils with the forecasting model using DI in the bioassay can provide an information to determine the suitability of the fields for ginseng cultivation, and that indexing cultivating field soils can be helpful to determine the time of harvesting to reduce further yield loss by root rot in continuous cultivation in the next year.

• Journal of the Korea Institute of Building Construction
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• v.18 no.5
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• pp.489-498
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• 2018

The purpose of this study was to propose a decision support model for selecting a lifting method of large spatial roof construction. First, we deducted influential factors consist of 6 factors and 19 sub-factors through literature reviews and expert's advices. Second, the relative importance of each factor was calculated by Analytic Hierarchy Process. As a result, 'site condition(0.237)' among 6 factors and 'available space of the site(0.118)' among 19 sub-factors were identified as the most important factor for selecting lifting method. In addition, methods and procedures were established for evaluating alternatives of lifting methods for each influential factor. A decision support model was completed by providing the Site Suitability Index(SSI) of each lifting method. Finally, we got advices form experts who were actually in charge of the works for large spatial construction project to validate the model. The model proposed in this study was analyzed to be useful in selecting the lifting method. The findings of this study are expected to support the decision making of on-site managers when they select the lifting method on the beginning of the project.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.6
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• pp.557-564
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• 2014

In this study, we present an algorithm that conducts an unique naming process for the bridge object through the solid object identification focused on 3D straight bridge model. For the recognition of 3D objects, the numerical algorithm utilizes centroid point, and solid object on the local coordination system. It classifies the object feature set by classifying the objects and members based on the bridge direction. By doing so, unique names, which contain the information about span, members and order of the object, were determined and the suitability of this naming algorithm was examined through a truss bridge model and a bridge model with different coordinate systems. Also, the naming process based on the object feature set was carried out for the real 3D bridge model and then was applied to the module on local server and mobile device for real bridge inspection work. From the comparison of the developed naming algorithm based on object identification and the conventional one based on field inspection, it was shown that the conventional field inspection work can be effectively improved.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.433-439
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• 2022

The purpose of the study was to determine the suitability of the research model on the intentions of university students to watch mega sports events for people with disabilities to which the theory of planned behavior was applied, and to examine the influence relationship between variables. Based on the items of sub-variables derived from the previous research, the questionnaire was optimally constructed through expert meetings, validity, and reliability verification. For data analysis, Cronbach's 𝛼 and exploratory factor analysis were performed using SPSS 21.0, and structural equation model analysis (SEM) and confirmatory factor analysis (CFA) were performed using AMOS 18.0. The results were as follows; first, as a result of verification of the research model of intentions of university students to watch mega sports events with people with disabilities to which the theory of planned behavior was applied, the evaluation indices of CFI, NFI, and IFI met the acceptance criteria, indicating that this research model was well suited. Second, as a result of examining the influence relationship of the research model on the intentions of university students to watch mega sports event for people with disabilities, it was found that the behavioral beliefs and normative beliefs of university students had a significantly positive (+) influence to intentions. However, it was found that there was a significantly negative (-) influence on the control beliefs to intentions.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.355-360
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• 2023

Recently, with the development of digital, children are exposed to a lot of media media. Reading activity decreases, making it difficult to acquire information from books or organize and remember acquired information. Since education with augmented reality increases children's participation and immersion in learning, we proposed a reading activity application with augmented reality technology to increase children's reading interest and creativity. In addition, based on the five nurturing processes, we designed a play-oriented reading activity for the application. In addition to the application suggestions, we designed a play-centered lesson model so that it can be used in actual lessons. In order to analyze the conceptual thinking framework according to the lesson model design, we visited an actual daycare center and conducted a class attended by an expert. Experts who participated were asked to fill out a pre-produced questionnaire to review the suitability of the reading activity class model and operation, and the feasibility was examined. Our lesson model design was based on limited book content, and due to ethical concerns, large-scale experiments with children could not be conducted, so the results of the study are not representative of the whole. However, it is significant that the possibility of running a new reading activity class based on the Nuri course has been examined and proposed.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.439-449
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• 2024

Recent rapid advancements in voice generation technology have enabled the natural synthesis of voices using text alone. However, this progress has led to an increase in malicious activities, such as voice phishing (voishing), where generated voices are exploited for criminal purposes. Numerous models have been developed to detect the presence of synthesized voices, typically by extracting features from the voice and using these features to determine the likelihood of voice generation.This paper proposes a new model for extracting voice features to address misuse cases arising from generated voices. It utilizes a deep learning-based audio codec model and the pre-trained natural language processing model BERT to extract novel voice features. To assess the suitability of the proposed voice feature extraction model for voice detection, four generated voice detection models were created using the extracted features, and performance evaluations were conducted. For performance comparison, three voice detection models based on Deepfeature proposed in previous studies were evaluated against other models in terms of accuracy and EER. The model proposed in this paper achieved an accuracy of 88.08%and a low EER of 11.79%, outperforming the existing models. These results confirm that the voice feature extraction method introduced in this paper can be an effective tool for distinguishing between generated and real voices.

• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.149-158
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• 2015

Programming education plays a very effective role in comprehensively learning problem analysis ability, logical thinking ability, procedural problem solving method, and imaginary problem solving method. Until recently, however, it is not applied to the elementary and the middle school in Korea, which is very different from the other IT centerd countries such as the U.S., etc., where coding class is actively implemented. Fortunately, Korean government recognized this reality and decided to implement programming education as a regular subject in the elementary school from 2017. In this situation, many researchers' programming education model research is urgently required for the students to learn in the elementary and the middle school. This research developed and suggested 17 sessions of programing education model connected with scratch language and sensor board, which is hardware, to be applied to the class of the 5th and 6th graders. As the result of implementing the joint class of 5th and 6th graders during the after-school class based on programming education process suggested to verify the suitability for elementary school programing education, satisfactory achievement was attained by the assessed students. The researcher plans to develop an optimum model proper for the elementary school students' intellectual capacity by more improving programming education model.