• Journal of radiological science and technology
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• v.46 no.4
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• pp.315-323
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• 2023

Post-mortem computed tomography (PMCT) is commonly employed in the field of forensic pathology. PMCT was mainly performed using a whole-body scan with a wide field of view (FOV), which lead to a decrease in spatial resolution due to the increased pixel size. This study aims to evaluate the potential for developing a super-resolution model based on conditional generative adversarial networks (CGAN) to enhance the image quality of CT. 1761 low-resolution images were obtained using a whole-body scan with a wide FOV of the head phantom, and 341 high-resolution images were obtained using the appropriate FOV for the head phantom. Of the 150 paired images in the total dataset, which were divided into training set (96 paired images) and validation set (54 paired images). Data augmentation was perform to improve the effectiveness of training by implementing rotations and flips. To evaluate the performance of the proposed model, we used the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Deep Image Structure and Texture Similarity (DISTS). Obtained the PSNR, SSIM, and DISTS values of the entire image and the Medial orbital wall, the zygomatic arch, and the temporal bone, where fractures often occur during head trauma. The proposed method demonstrated improvements in values of PSNR by 13.14%, SSIM by 13.10% and DISTS by 45.45% when compared to low-resolution images. The image quality of the three areas where fractures commonly occur during head trauma has also improved compared to low-resolution images.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.2
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• pp.224-233
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• 2023

The purpose of this study is to investigate the effect of environmental classes using EBS program on the environmental sensitivity and environmentally responsible behavior of 6th grade elementary school students. To this end, the 2015 revised elementary school curriculum was reconstructed for 6th grade students, and subject-centered environmental classes were planned, and EBS educational broadcasting environmental contents suitable for each class were applied and utilized. The conclusion of this study is as follows. First, this study analyzed the 2015 revised curriculum and reorganized the 6th grade curriculum and creative experience activities to plan the 22nd environmental class, specifying environmental sensitivity and environmentally responsible behavior that can have a positive impact on learners in each class. EBS educational broadcasting environmental contents that can be utilized were selected and environmental classes were conducted using them. Second, it was found that environmental classes using EBS educational broadcasting had a significant effect on improving the environmental sensitivity of elementary school students. The fact that environmental classes using EBS educational broadcasting goes beyond the spatial limitations of schools and informs that global citizens are interested in environmental problems and are working to solve environmental problems. Third, it was found that environmental classes using EBS educational broadcasting had a significant effect on elementary school students' environmentally responsible behavior. This is because environmental classes using EBS educational broadcasting do not stop at imparting knowledge, but suggest learning that leads to civic behavior, educational behavior, economic behavior, physical behavior, and persuasive behavior related to the environment.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.211-231
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• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.24-35
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• 2023

Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.

• Journal of Cadastre & Land InformatiX
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• v.53 no.1
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• pp.5-20
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• 2023

The government is operating a course evaluation-type qualification system for the purpose of overcoming the limitations of the test-type qualification system and cultivating talents with practical skills applicable to related industries. However, there is a part that does not match the purpose of the course evaluation qualification system by educating competency units in the field of surveying rather than the field of cadastral field in the education and training course of the course evaluation qualification. Therefore, this study closely analyzed the course evaluation qualification system in the cadastral field and suggested improvement plans accordingly. First, NCS in the cadastral field has not been supplemented or developed since its development in 2014, and there are many parts that do not conform to the current laws, so supplementary development is necessary. Second, It was proposed to improve the optional competency unit in the field of surveying to the NCS competency unit in the cadastral field. In addition, if the 12 competency units of the current NCS in the cadastral field are designated as essential competency units and education and training are operated, it will be possible to foster working-level talents with sufficient competency at the cadastral engineer level. However, for practical system operation and application, supplementation and development of NCS in the cadastral field, which is used for education and training of the course evaluation qualification system, must be preceded.

• Smart Media Journal
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• v.12 no.1
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• pp.77-91
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• 2023

Interaction methods and technologies for mutual exploration based on user behavior are evolving variously. Especially, in recent years, with the development of a wide range of sensors, they have developed from contact to non-contact methods. However, developers' senseless definitions of the interaction methods have made the exploration process quite complicated, which rather creates the hassle of users needing to learn the interaction guide defined by the developers before experiencing the exhibition contents. In this context, in order to make visitors smoothly communicate with exhibition contents, a preliminary study on easy interaction for users of various ages is needed, and in particular, research on improving the usability of user interaction is also essential when developing non-contact exhibition contents. So, in this study, a method to reduce the confusion between developers and users was sought by researching non-contact interaction that could be universally interacted with in the field of exhibition contents and proposing behavior designs. First, based on the narrative structure of cultural resources, existing studies were reviewed and the points of interactions as cultural contents were derived. Then the most efficient search process was selected among non-contact behaviors based on hand gestures that allow users to naturally guess and learn interaction methods. Furthermore, on the basis of the meaning of non-linear narrative-based interaction and the analysis results of spatial behavior elements, affordance behavior with high learning effect and efficiency was derived. Through this research process, an action that helps users to understand non-contact interaction naturally in the process of exploring exhibition-type cultural contents and to utilize non-contact interaction in the process of immersion in exhibition contents is proposed as a final model.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.693-699
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• 2023

Ultrasound is widely used in the medical field for non-destructive and non-invasive disease diagnosis. In order to improve the disease diagnosis accuracy of diagnostic medical images, improving spatial resolution is a very important factor. In this study, we aim to model the super resolution convolutional neural network (SRCNN) algorithm in ultrasound images and analyze its applicability in the medical diagnostic field. The study was conducted as an experimental study using Field II simulation and open source clinical liver hemangioma ultrasound imaging. The proposed SRCNN algorithm was modeled so that end-to-end learning can be applied from low resolution (LR) to high resolution. As a result of the simulation, we confirmed that the full width at half maximum in the phantom image using a Field II program was improved by 41.01% compared to LR when SRCNN was used. In addition, the peak to signal to noise ratio (PSNR) and structural similarity index (SSIM) evaluation results showed that SRCNN had the excellent value in both simulated and real liver hemangioma ultrasound images. In conclusion, the applicability of SRCNN to ultrasound images has been proven, and we expected that proposed algorithm can be used in various diagnostic medical fields.

• Communications of Mathematical Education
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• v.37 no.3
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• pp.349-368
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• 2023

The revised 2022 educational curriculum highlighted the significance of mathematical literacy as a foundational competency that can be cultivated through the learning of various subjects, along with language proficiency and digital literacy. However, due to the lack of a precise definition for mathematical literacy, there exists a challenge in systematically implementing it across all subjects in the educational curriculum. The aim of this study is to clarify the definition of mathematical literacy in the curriculum through a literature review and to analyze the application patterns of mathematical literacy in other subjects so that mathematical literacy can be systematically applied as a basic literacy in Korea's curriculum. To achieve this, the study first clarifies and categorizes the meaning of mathematical literacy through a comparative analysis of terms such as numeracy and mathematical competence via a literature review. Subsequently, the study compares the categories of mathematical literacy identified in both domestic and international educational curricula and analyzes the application of mathematical literacy in the education curriculum of New South Wales (NSW), Australia, where mathematical literacy is reflected in the achievement standards across various subjects. It is expected that understanding each property by subdividing the meaning of mathematical literacy and examining the application modality to the curriculum will help construct a curriculum that reflects mathematical literacy in subjects other than mathematics.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.15-30
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• 2023

Recently, various services using artificial intelligence(AI) are emerging in the media field as well However, most of the video editing, which involves finding an editing point and attaching the video, is carried out in a passive manner, requiring a lot of time and human resources. Therefore, this study proposes a methodology that can detect the edit points of video according to whether person in video are spoken by using Video Swin Transformer. First, facial keypoints are detected through face alignment. To this end, the proposed structure first detects facial keypoints through face alignment. Through this process, the temporal and spatial changes of the face are reflected from the input video data. And, through the Video Swin Transformer-based model proposed in this study, the behavior of the person in the video is classified. Specifically, after combining the feature map generated through Video Swin Transformer from video data and the facial keypoints detected through Face Alignment, utterance is classified through convolution layers. In conclusion, the performance of the image editing point detection model using facial keypoints proposed in this paper improved from 87.46% to 89.17% compared to the model without facial keypoints.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.53-66
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• 2023

Recently, there has been a significant interest in the development of autonomous driving simulation environment based on digital twin. In the development of such digital twin-based simulation environment, many researches has been conducted not only performance and functionality validation of autonomous driving, but also generation of virtual training data for deep learning. However, such digital twin-based autonomous driving simulation system has the problem of requiring a significant amount of time and cost for the system development and the data construction. Therefore, in this research, we aim to propose a method for rapidly designing and implementing a digital twin-based autonomous driving simulation system, using only the existing 3D models and high-definition map. Specifically, we propose a method for integrating 3D model of FBX and NGII HD Map for the Busan EDC area into CARLA, and a method for adding and modifying CARLA functions. The results of this research show that it is possible to rapidly design and implement the simulation system at a low cost by using the existing 3D models and NGII HD map. Also, the results show that our system can support various functions such as simulation scenario configuration, user-defined driving, and real-time simulation of traffic light states. We expect that usability of the system will be significantly improved when it is applied to broader geographical area in the future.