• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.7-15
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• 2022

With the aim of an intelligent world in the age of individual customization through decentralization of information and technology, sharing/opening, and connection, we often see a tendency to cross expectations and concerns in the technological discourse and interest in artificial intelligence more than ever. Recently, it is easy to find claims by futurists that AI singularity will appear before and after 2045. Now, as part of preparations to create a paradigm of coexistence that coexists and prosper with AI in the coming age of artificial intelligence, a standard framework for setting up more correct AI ethics and regulations is required. This is because excluding the risk of omission of setting major guidelines and methods for evaluating reasonable and more reasonable guideline items and evaluation standards are increasingly becoming major research issues. In order to solve these research problems and at the same time to develop continuous experiences and learning effects on AI ethics and regulation setting, we collect guideline data on AI ethics and regulation of international organizations / countries / companies, and research and suggest ways to set up a standard framework (SF: Standard Framework) through a setting research model and text mining exploratory analysis. The results of this study can be contributed as basic prior research data for more advanced AI ethics and regulatory guidelines item setting and evaluation methods in the future.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.53-61
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• 2022

Recent years have drawn a great attention to generation MZ and Metaverse, due to 4th industrial revolution and the development of digital environment that blurs the boundary between reality and virtual reality. Generation MZ approaches the information very differently from the existing generations and uses distinguished communication methods. In terms of learning, they have different motivations, types, skills and build relationships differently. Meanwhile, Metaverse is drawing a great attention as a teaching method that fits traits of gen MZ. Thus, the current research aimed to investigate how to increase the use of Metaverse in Educational Technology. Specifically, this research examined the antecedents of popularity of Gather Town, a platform of Metaverse. Big data of news articles have been collected and analyzed using the Bigkinds system provided by Korea Press Foundation. The analysis revealed, first, a rapid increasing trend of media exposure of Gather Town since July 2021. This suggests a greater utilization of Gather Town in the field of education after the COVID-19 pandemic. Second, Word Association Analysis and Word Cloud Analysis showed high weights on education related words such as 'remote', 'university', and 'freshman', while words like 'Metaverse', 'Metaverse platform', 'Covid19', and 'Avatar' were also emphasized. Third, Network Analysis extracted 'COVID19', 'Avatar', 'University student', 'career', 'YouTube' as keywords. The findings also suggest potential value of Gather Town as an educational tool under COVID19 pandemic. Therefore, this research will contribute to the application and utilization of Gather Town in the field of education.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.103-108
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• 2022

Various studies have been conducted on cloud observation using all-sky images acquired with a wide-angle camera system since the early 21st century, but it is judged that an automatic observation system that can completely replace the eye observation has not been obtained. In this study, to verify the quantification of cloud observation, which is the final step of the algorithm proposed to automate the observation, the cloud distribution of the all-sky image and the corrected image were compared and analyzed. The reason is that clouds are formed at a certain height depending on the type, but like the retina image, the center of the lens is enlarged and the edges are reduced, but the effect of human learning ability and spatial awareness on cloud observation is unknown. As a result of this study, the average cloud observation error of the all-sky image and the corrected image was 1.23%. Therefore, when compared with the eye observation in the decile, the error due to correction is 1.23% of the observed amount, which is very less than the allowable error of the eye observation, and it does not include human error, so it is possible to collect accurately quantified data. Since the change in cloudiness due to the correction is insignificant, it was confirmed that accurate observations can be obtained even by omitting the unnecessary correction step and observing the cloudiness in the pre-correction image.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.109-117
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• 2021

Recently, the use of speech-based interfaces is increasing as a means for human-computer interaction (HCI). Accordingly, interest in post-processors for correcting errors in speech recognition results is also increasing. However, a lot of human-labor is required for data construction. in order to manufacture a sequence to sequence (S2S) based speech recognition post-processor. To this end, to alleviate the limitations of the existing construction methodology, a new data construction method called Back TranScription (BTS) was proposed. BTS refers to a technology that combines TTS and STT technology to create a pseudo parallel corpus. This methodology eliminates the role of a phonetic transcriptor and can automatically generate vast amounts of training data, saving the cost. This paper verified through experiments that data should be constructed in consideration of text style and domain rather than constructing data without any criteria by extending the existing BTS research.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.3-14
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• 2022

Autonomous equipment requires a large amount of data from various environments. However, it takes a lot of time and cost for an experiment in a real construction sites, which are difficulties in data collection and processing. Therefore, this study aims to develop a virtual environment for autonomous tower cranes technology development and validation. The authors defined automation functions and operation conditions of tower cranes with three performance criteria: operational design domain, object and event detection and response, and minimum functional conditions. Afterward, this study developed a virtual environment for learning and validation for autonomous functions such as recognition, decision making, and control using the Unity game engine. Validation was conducted by construction industry experts with a fidelity which is the representative matrix for virtual environment assessment. Through the virtual environment platform developed in this study, it will be possible to reduce the cost and time for data collection and technology development. Also, it is also expected to contribute to autonomous driving for not only tower cranes but also other construction equipment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.177-185
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• 2022

A method of restoring the occluded area was proposed by referring to images taken with the same types of sensors on high-resolution optical satellite images through deep learning. For the natural continuity of the simulated image with the occlusion region and the surrounding image while maintaining the pixel distribution of the original image as much as possible in the patch segmentation image, CycleGAN (Cycle Generative Adversarial Network) method with ConvNeXt block applied was used to analyze three experimental regions. In addition, We compared the experimental results of a training patch size of 512*512 pixels and a 1024*1024 pixel size that was doubled. As a result of experimenting with three regions with different characteristics,the ConvNeXt CycleGAN methodology showed an improved R² value compared to the existing CycleGAN-applied image and histogram matching image. For the experiment by patch size used for training, an R² value of about 0.98 was generated for a patch of 1024*1024 pixels. Furthermore, As a result of comparing the pixel distribution for each image band, the simulation result trained with a large patch size showed a more similar histogram distribution to the original image. Therefore, by using ConvNeXt CycleGAN, which is more advanced than the image applied with the existing CycleGAN method and the histogram-matching image, it is possible to derive simulation results similar to the original image and perform a successful simulation.

• Journal of the Korean Applied Science and Technology
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• v.39 no.4
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• pp.568-579
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• 2022

The purpose of this study was to investigate the relationship between physical activity participation habits, physical fitness level, and academic performance among the Reserve Military Training Corps (ROTC). Participants in the current study were 71 ROTCs from J University. Physical activity participation was investigated using the Global Physical Activity Questionnaire (GPAQ), and the level of physical fitness was measured by health-related physical fitness evaluation. For academic performance, university grade data (GPA) was approved by the head of the relevant school district, and the data were collected with the consent of the participants, and each data was analyzed. The correlation between physical activity participation habits, physical fitness level, and GPA was analyzed, and GPA by physical fitness level were compared. This study found that there was no statistically significant correlation between physical activity participation and academic performance. Otherwise, there was a statistically significant correlation between major subjects and total physical fitness score, cardiorespiratory fitness, muscular endurance, flexibility, and body composition. By the level of physical fitness, the ROTCs in the high-physical fitness group showed statistically significantly higher academic performance than the ROTCs in the low-physical fitness group. In addition, low level of physical fitness ROTC group was lower than the other. In conclusion, ROTCs with a high physical fitness level had a positive effect on improving learning ability compared to those who did not. By recommending an autonomous but systematic exercise training program, it is suggested to improve the physical strength of ROTCs and to cultivate excellent future military officers.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.274-282
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• 2022

In order to secure pedestrians' right to walk, we have up-cycled second hand mobile phones to overcome limitations of the existing survey methods, analysis methods, and diagnosis to reduce pedestrian traffic accidents. Second hand mobile phones were up-cycled to produce mobile CCTVs and installed in areas where pedestrian deaths rate is high to secure image data sets for the period of more than 24 hours. It was analyzed by applying image visualization technology and clouding reporting technology, and more precise and accurate results were derived through modeling based on artificial intelligence learning and GIS-based diagnostic guidance. As a result, it was possible to analyze the risk factors and number of pedestrian safety, and even factors that were not known in the existing method could be derived. In addition, the traffic accident risk index was derived by converting data into one year to verify whether second hand mobile phone up-cycling mobile CCTV will be an objective tool for finding pedestrian risk factors. Up-cycling mobile CCTV of second hand mobile phones newly applied through research can be used as a new tool to find pedestrian risk factors, and it can be used as a service to protect the safety of the traffic vulnerable other than pedestrians.

• Journal of the Korean Geotechnical Society
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• v.37 no.11
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• pp.119-129
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• 2021

The process of constructing the DB in the current geotechnical information DB system needs a lot of human and time resource consumption. In addition, it causes accuracy problems frequently because the current input method is a person viewing the PDF and directly inputting the results. Therefore, this study proposes building an automatic digital DB using AI (artificial intelligence) of boring logs. In order to automatically construct DB for various boring log formats without exception, the boring log forms were classified using the deep learning model ResNet 34 for a total of 6 boring log forms. As a result, the overall accuracy was 99.7, and the ROC_AUC score was 1.0, which separated the boring log forms with very high performance. After that, the text in the PDF is automatically read using the robotic processing automation technique fine-tuned for each form. Furthermore, the general information, strata information, and standard penetration test information were extracted, separated, and saved in the same format provided by the geotechnical information DB system. Finally, the information in the boring log was automatically converted into a DB at a speed of 140 pages per second.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.200-207
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• 2020

The purpose of the establishment of Fab Lab is to promote the sustainable development of local communities around the world. To this end, The Fab foundation are preparing a resource-circulating society that maintains a city's self-sufficiency rate of 50% or more by 2054. In developed countries, Fab Lab is not only a manufacturing space for startup support, but an open innovation space for learning and creation. In addition, in emerging countries, Fab Lab is playing a role as a digital production center to create and share appropriate new technologies by reflecting the needs of local communities. India has 70 Fab Labs, the largest emerging country, ahead of Russia's 48. India's Fab Lab is conducting a collaboration project through regular meetings held every six months. The subject of this study, Fab Lab Vigyan Ashram, is defined as a place to transfer the concept of digital lab to alternative schools in rural India. In this study, we looked at a case in which an alternative school for an agricultural community called Vigyan Ashram, the modern version of the Gurukula system, successfully combined with the digital fabrication called Fab Lab to become a new citizen-led making community of the 4th Industrial Revolution. Based on this, we explored the development model of the Indian Fab Lab that fits the local situation.