• Journal of the Korea Institute of Building Construction
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• v.21 no.5
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• pp.483-493
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• 2021

Urban overcrowding has created an explosive supply and demand for high-rise buildings. High-rise buildings are contributing to enhancing the image of the city by serving as focal points, but due to the stack effect, malfunction of elevator doors, difficulties in opening and closing the doors and windows of the outer wall, smoke and odors spreading to the upper floors, noise, energy loss, fire and pollutants have been causing various unexpected problems such as rapid spread of fire. This study classified high-rise buildings according to their vertical zoning, analyzed the causes of and solutions to the stack effect, and derived design and construction methods. Through the initial plan to block the outside air and securing airtightness through precise construction, we sought ways to secure the airtightness inside and outside the building by actively blocking the airflow from the lower floors. In addition, the facility solution can be a measure to reduce the specific phenomena caused by the stack effect, but it should only be applied to the minimum extent because the potential for secondary damage is high. This study emphasized the need for systematic stack effect management by suggesting design and construction measures for each vertical zoning of the causes and countermeasures of the stack effect. It is expected that this study will be helpful not only for design and construction, but also for building maintenance.

• The Korean Journal of Archival Studies
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• no.62
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• pp.225-258
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• 2019

Since the opening of Joseon in 1876, the photographic records of the late Joseon Dynasty and the period of the Korean Empire exist more than expected, considering the technological level and the social situations at that time. Photographs related to Korea can be distributed in various forms, such as illustrations of books printed to introduce Korea to Western society, plates of graphic journalism like newspapers or magazines, vintage prints, photo-postcards, stereo-photographs, card-type photographs, and lantern slides. There are still a great deal left in various archives of the Europe, America, Japan and Korea. According to related researchers, Korean-related photographs taken between 1863 and 1910, since Koreans were first photographed, were at least 3,000 to 4,000 cuts and the photo postcards issued was 25,000. It is said that most of them exist. This paper categorizes two ways of producing and distributing photographic records related to Korea, which were early modern times. The subjects of the photographs are clearly Korea or Koreans, but most of the producers of these photographs were Westerners and Japanese, who were imperial servants of imperialism. In the case of photography, there is a great possibility of distortion of the facts depending on the needs or perspectives of the producers. In order to correct the distortion, not only the contents of the photograph but also the intention of the producer, the production and the communication status should be grasped. This is because the problem of reading photograph records accurately and fairly in an age where there is no real experience is the cornerstone for understanding modern Korea correctly and broadly studying the Modern History of Korea.

• (The)Study of the Eastern Classic
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• no.72
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• pp.97-126
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• 2018

has many sexual elements among our literature. So is considered obscene. But if you take a closer look at , you can see that he is dealing with the real problem. Especially, the conflict between Gangsoe and Jangseung shows the contradiction of reality. However, it can not be questioned because it is hidden behind sexual elements. 's strategy of revealing is similar in Media Narrative. has been made into a film since the 1980s. However, these films stayed at the level of B-erotic movies. The real meaning of is gone, and the sexual image is more emphasized. Incidentally, this aspect is related to reality at the time. At that time, the military was in control of politics. So I wanted the people not to be interested in politics. For this reason, many erotic movies were created. Eventually, the strategy of revealing was even more maximized in Media Narrative. But recently there was a new attempt like . This was a new attempt to go beyond the standardized approach. Future interpretations of are expected more.

• Journal of the Korea Society for Simulation
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• v.30 no.2
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• pp.41-48
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• 2021

As the rural population continues to decline and aging, the improvement of agricultural productivity is becoming more important. Early prediction of crop quality can play an important role in improving agricultural productivity and profitability. Although many researches have been conducted recently to classify diseases and predict crop yield using CNN based deep learning and transfer learning technology, there are few studies which predict postharvest crop quality early in the planting stage. In this study, a early quality prediction model is proposed for sprout ginseng, which is drawing attention as a healthy functional foods. For this end, we took pictures of ginseng seedlings in the planting stage and cultivated them through hydroponic cultivation. After harvest, quality data were labeled by classifying the quality of ginseng sprout. With this data, we build early quality prediction models using several pre-trained CNN models through transfer learning technology. And we compare the prediction performance such as learning period and accuracy between each model. The results show more than 80% prediction accuracy in all proposed models, especially ResNet152V2 based model shows the highest accuracy. Through this study, it is expected that it will be able to contribute to production and profitability by automating the existing seedling screening works, which primarily rely on manpower.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.87-95
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• 2020

The Incheon airport is a gateway to and from the Republic of Korea and has a great influence on the image of the country. Therefore, it is necessary to predict the number of airport passengers in the long term in order to maintain the quality of service at the airport. In this study, we compared the predictive performance of various time series models to predict the air passenger demand at Incheon Airport. From 2002 to 2019, passenger data include trend and seasonality. We considered the naive method, decomposition method, exponential smoothing method, SARIMA, PROPHET. In order to compare the capacity and number of passengers at Incheon Airport in the future, the short-term, mid-term, and long-term was forecasted by time series models. For the short-term forecast, the exponential smoothing model, which weighted the recent data, was excellent, and the number of annual users in 2020 will be about 73.5 million. For the medium-term forecast, the SARIMA model considering stationarity was excellent, and the annual number of air passengers in 2022 will be around 79.8 million. The PROPHET model was excellent for long-term prediction and the annual number of passengers is expected to be about 99.0 million in 2024.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.473-479
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• 2021

The diagnostic criteria for diffuse thyroid disease are ambiguous and there are many errors due to the subjective diagnosis of experts. Also, studies on ultrasound imaging of thyroid nodules have been actively conducted, but studies on diffuse thyroid disease are insufficient. In this study, features were extracted by applying the GLCM algorithm to ultrasound images of normal and diffuse thyroid disease, and quantitative analysis was performed using the extracted feature values. Using the GLCM algorithm for thyroid ultrasound images of patients diagnosed at W hospital, 199 normal cases, 132 mild cases, and 99 moderate cases, a region of interest (50×50 pixel) was set for a total of 430 images, and Autocorrelation, Sum of squares, sum average, sum variance, cluster prominence, and energy were analyzed using six parameters. As a result, in autocorrelation, sum of squares, sum average, and sum variance four parameters, Normal, Mild, and Moderate were distinguished with a high recognition rate of over 90%. This study is valuable as a criterion for classifying the severity of diffuse thyroid disease in ultrasound images using the GLCM algorithm. By applying these parameters, it is expected that errors due to visual reading can be reduced in the diagnosis of thyroid disease and can be utilized as a secondary means of diagnosing diffuse thyroid disease.

• Journal of Broadcast Engineering
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• v.27 no.3
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• pp.318-331
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• 2022

With the recent development of hardware computing devices and software based frameworks, machine tasks using deep learning networks are expected to be utilized in various industrial fields and personal IoT devices. However, in order to overcome the limitations of high cost device for utilizing the deep learning network and that the user may not receive the results requested when only the machine task results are transmitted from the server, Collaborative Intelligence (CI) proposed the transmission of feature maps as a solution. In this paper, an efficient compression method for feature maps with vast data sizes to support the CI paradigm was analyzed and presented through experiments. This method increases redundancy by applying feature map reordering to improve compression efficiency in traditional video codecs, and proposes a feature map method that improves compression efficiency and maintains the performance of machine tasks by simultaneously utilizing image compression format and video compression format. As a result of the experiment, the proposed method shows 14.29% gain in BD-rate of BPP and mAP compared to the feature compression anchor of MPEG-VCM.

• Economic and Environmental Geology
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• v.55 no.3
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• pp.309-316
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• 2022

In order to minimize the human and time consumption required for rock classification, research on rock classification using artificial intelligence (AI) has recently developed. In this study, basic volcanic rocks were subdivided by using polarizing microscope thin section images. A convolutional neural network (CNN) model based on Tensorflow and Keras libraries was self-producted for rock classification. A total of 720 images of olivine basalt, basaltic andesite, olivine tholeiite, trachytic olivine basalt reference specimens were mounted with open nicol, cross nicol, and adding gypsum plates, and trained at the training : test = 7 : 3 ratio. As a result of machine learning, the classification accuracy was over 80-90%. When we confirmed the classification accuracy of each AI model, it is expected that the rock classification method of this model will not be much different from the rock classification process of a geologist. Furthermore, if not only this model but also models that subdivide more diverse rock types are produced and integrated, the AI model that satisfies both the speed of data classification and the accessibility of non-experts can be developed, thereby providing a new framework for basic petrology research.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.184-193
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• 2021

The system for managing spatial data updates the existing information by extracting only the information that is different from the existing information for the newly obtained spatial information file to update the stored information. In order to extract only objects that have changed from existing information, it is necessary to compare whether there is any difference from existing information for all objects included in the newly obtained spatial information file. This study was conducted to improve this total inspection method in a situation where the amount of spatial information that is frequently updated increases and data update is required at the national level. In this study, before inspecting individual objects in a new acquisition space information file, a method of determining whether individual space objects have been changed only by the information in the file was considered. Spatial data files have structured data characteristics different from general image or text document files, so it is possible to determine whether to change the file unit in a simpler way compared to the existing method of creating and managing file hash. By reducing the number of target files that require full inspection, it is expected to improve the use of resources in the system by saving the overall data quality inspection time and saving data extraction time.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.