• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.118-129
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• 2022

The purpose of this report is to study a strategic model of promotion activities through various analysis and sales forecasting by selecting wearable products for domestic online companies and collecting sales data. For data analysis, various algorithms are used for analysis and the results are selected as the optimal model. The gradation boosting model, which is selected as the best result, will allow nine independent variables to be entered, including promotion type, price, amount, gender, model, company, grade, sales date, and region, when predicting dependent variables through supervised learning. In this study, the review values set as dependent variables for each type of sales promotion were studied in more detail through the ensemble analysis technique, and the main purpose is to analyze and predict them. The purpose of this study is to study the grades. As a result of the analysis, the evaluation result is 95% of AUC, and F1 is about 93%. In the end, it was confirmed that among the types of sales promotion activities, value-added benefits affected the number of reviews and review grades, and that major variables affected the review and review grades.

• Korean Journal of Construction Engineering and Management
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• v.24 no.5
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• pp.12-21
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• 2023

Green remodeling proposed in the Korean New Deal is a project to build or remodel eco-friendly and energy-efficient buildings using renewable energy facilities and high-performance insulation for public buildings. The government intends to achieve the carbon emission reduction target by conducting green remodeling. Major overseas cities that conduct green remodeling are actively promoting technology support and promotion along with energy performance evaluation according to building characteristics, subsidies for private revitalization, and tax benefits. With this background, the analysis of the current status and problems of the green remodeling project was performed and the Activation factors of Green Remodeling were derived from survey results. This study suggested strategic measures such as a participation of civil society, promotion, and priority selection of administration and policy measures such as a leading role of the public sector, expanding support for the socially underprivileged, and financial support and tax benefits. And this study results are expected to be utilized as basic data to promote the green remodeling project.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.257-268
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• 2023

Sea ice plays an important role in Earth's climate by regulating the amount of solar energy absorbed and controlling the exchange of heat and material across the air-sea interface. Its growth, drift, and melting are monitored on a regular basis by satellite observations. However, low-resolution products with passive microwave radiometer have reduced accuracy during summer to autumn when the ice surface changes rapidly. Synthetic aperture radar (SAR) observations are emerging as a powerful complementary, but previous researches have mainly focused on winter ice. In this study, sea ice drift tracking was evaluated and analyzed using SAR images and tracker with global positioning system (GPS) during late summer-early autumn period when ice surface condition changes a lot. The results showed that observational uncertainty increases compared to winter period, however, the correlation coefficient with GPS measurements was excellent at 0.98, and the performance of the ice tracking algorithm was proportional to the sea ice concentration with a correlation coefficient of 0.59 for ice concentrations above 50%.

• The Journal of Bigdata
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• v.7 no.2
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• pp.31-41
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• 2022

Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.31-49
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• 2023

With the growth of the food-catering industry, consumer preferences and the number of dine-in restaurants are gradually increasing. Thus, personalized recommendation services are required to select a restaurant suitable for consumer preferences. Previous studies have used questionnaires and star-rating approaches, which do not effectively depict consumer preferences. Online reviews are the most essential sources of information in this regard. However, previous studies have aggregated online reviews into long documents, and traditional machine-learning methods have been applied to these to extract semantic representations; however, such approaches fail to consider the surrounding word or context. Therefore, this study proposes a novel review textual-based restaurant recommendation model (RT-RRM) that uses deep learning to effectively extract consumer preferences from online reviews. The proposed model concatenates consumer-restaurant interactions with the extracted high-level semantic representations and predicts consumer preferences accurately and effectively. Experiments on real-world datasets show that the proposed model exhibits excellent recommendation performance compared with several baseline models.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.392-399
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• 2023

This paper proposes a deep learning model to determine the region and depth of cabbage cores for robotic automation of the cabbage core removal process during the kimchi manufacturing process. In addition, rather than predicting the depth of the measured cabbage, a model was presented that simultaneously detects and classifies the area by converting it into a discrete class. For deep learning model learning and verification, RGB images of the harvested cabbage 522 were obtained. The core region and depth labeling and data augmentation techniques from the acquired images was processed. MAP, IoU, acuity, sensitivity, specificity, and F1-score were selected to evaluate the performance of the proposed YOLO-v4 deep learning model-based cabbage core area detection and classification model. As a result, the mAP and IoU values were 0.97 and 0.91, respectively, and the acuity and F1-score values were 96.2% and 95.5% for depth classification, respectively. Through the results of this study, it was confirmed that the depth information of cabbage can be classified, and that it can be used in the development of a robot-automation system for the cabbage core removal process in the future.

• Tunnel and Underground Space
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• v.34 no.3
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• pp.185-195
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• 2024

The Incheon Metro Line 1 Geomdan Extension Phase 1 is the first project in South Korea where both a roadheader and TBM (Tunnel Boring Machine) are being used together. The shield TBM tunnel section is 1,057 m long, and is mostly composed of rock, including the section beneath the Airport Railroad and the Gyeongin Ara Waterway. A 7.8 m earth pressure balance shield TBM was used for tunnel excavation. The average monthly advance rate for both the North and South tracks is 239.1 m, with a maximum monthly advance rate of 334.5 m. This technical article comprehensively evaluates the productivity of the shield TBM, focusing on the TBM excavation performance. Above all, it aims to provide useful reference material for the successful execution of shield TBM tunnel construction.

• Journal of Radiation Protection and Research
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• v.40 no.3
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• pp.162-167
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• 2015

Although the perfomance indicators of the nuclear power plants in Korea show optimal, it requires detailed analysis and discussion centered on the radiation dose. As analysis methods, analysis on the radiation dose of nuclear power plants over the past five years was assessed by comparing the relevant radiation dose of radiation workers and per capita average annual radiation dose of the world's major nuclear power stations was also analyzed. The radiation workers over the annual radiation dose limit of 50 mSv were not. The contrast ratio of the radiation exposure according to the reactor type was the normal operation of PHWR was 6.2% higher than those of the PWR. This shows the radiation work of PHWR during normal driving operation is much more than those of PWR. According to the Performance Indicators of the World Association of Nuclear Operator, the annual radiation dose per unit in 2013 showed 527 man-mSv of Korea is the best country among the major nuclear power generating states, the world average was 725 man-mSv. The annual per capita radiation dose is about 80% less than 1 mSv of the public dose limit and also the average per capita dose showed a very low level as 0.82 mSv. Workers in related organizations showed 1.07 mSv, the non-destructive inspection agency workers showed 3.87 mSv. The remarkable results were due to radiation reduced program such as development of radiation shielding and radiation protection. In conclusion, the radiation exposured dose of nuclear power plants workers in Korea showed a trend which is ideally reduced. But more are expected to be difficul and the psychological insecurity against the operation of the nuclear power plants is existed to the residents near the nuclear power plants. So the radiation dose reduction policy and radiation dose follow up study of nuclear power plants will be continously excuted.

• Sleep Medicine and Psychophysiology
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• v.12 no.1
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• pp.27-31
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• 2005

Objectives: We attempted to compare the performance of 2 commercially available actigraphies with focus on sleep parameters, using polysomnography as standard comparison tool. Methods: Fourteen normal volunteers (5 males and 9 females, mean age of $28{\pm}4.6\;years$) participated in this study. All the participants went through one night of polysomnography, simultaneously wearing 2 different kinds of actigraphies on each wrist. Polysomnographic and actigraphic data were stored, downloaded, and processed according to standard protocols and then statistically compared. Results: Both $ActiWatch^{(R)}$ and $SleepWatch^{(R)}$ tended to overestimate the total sleep time, compared to the polysomnography. $SleepWatch^{(R)}$ tended to underestimate the sleep latency. The two actigraphs and the polysomnograph did not show significant difference of sleep efficiency, when compared with one another. In addition, all of the sleep parameters from the instruments showed linear correlations except in $SleepWatch^{(R)}'s$ sleep latency. The sleep parameters from the two actigraphs did not show much noteworthy difference, and linear relationships were found between the sleep parameters from the two actigraphs. There was no significant distinction in the results of the two different actigraphs. Conclusion: The results of two actigraphies can be used interchangeably since the sleep parameters of the two different actigraphies do not show significant differences statistically. Overall, it is not legitimate to use actigraphy as a substitute for polysomnography. However, since sleep parameters except sleep latency show linear correlations, actigraphy might possibly be used to follow up patients after polysomnography.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9B
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• pp.610-618
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• 2005

As developed Internet and Computer Capability, Many Users take the many information through the network. So requirement of User that use to network was rapidly increased and become various. But it spend much time to accept user requirement on current network, so studied such as Active network for solved it. This Active node on Active network have the capability that stored and processed execution code aside from capability of forwarding packet on current network. So required execution code for executed packet arrived in active node, if execution code should not be in active node, have to take by request previous Action node and Code Server to it. But if this execution code take from previous active node and Code Server, bring to time delay by transport execution code and increased traffic of network and execution time. So, As used execution code stored in cache on active node, it need to increase execution time and decreased number of request. So, our paper suggest ANC caching technique that able to decrease number of execution code request and time of execution code by efficiently store execution code to active node. ANC caching technique may decrease the network traffic and execution time of code, to decrease request of execution code from previous active node.