• Journal of Korean Society of Disaster and Security
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• v.14 no.1
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• pp.61-72
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• 2021

There is an increasing need for water supply plan using sustainable groundwater to resolve water shortage problem caused by drought due to climate change and artificial aquifer recharge has recently emerged as an alternative. This study deals with recharge potential assessment for artificial recharge system and quantitative assessment for securing stable water and efficient agricultural water supply adapt to drought finding optimal operating condition by numerical modeling to reflect recharge scenarios considering climate condition, target water intake, injection rate, and injection duration. In order to assess recharge potential of injection well, numerical simulation was performed to predict groundwater level changes in injection and observation well respect to injection scenarios (Case 1~4) for a given total injection rate (10,000 m³). The results indicate that groundwater levels for each case are maintained for 25~42 days and optimal injection rate is 50 m³/day for Case 3 resulted in groundwater level rise less than 1 m below surface. The results also show that influential area of groundwater level rise due to injection was estimated at 113.5 m and groundwater storage and elapsed time were respectively increased by 6 times and 4 times after installation of low permeable barrier. The proposed assessment method can be contributed to sustainable agricultural water supply and stable water security for drought adaptation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.133-139
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• 2022

Recently, livestock farms in Korea are introducing data-based technologies to improve productivity, such as livestock environment and breeding management, safe livestock production, and animal welfare. In addition, the government has been conducting a smart livestock distribution project since 2017 through the modernization of ICT-based livestock facilities in order to improve the productivity of livestock products and improve the livestock environment as a policy. However, the current smart livestock house has limitations in connection, diversity, and integration between monitoring and control. Therefore, in order to intelligently systemize all processes of livestock with intelligent algorithms and remote control in order to link and integrate various monitoring and control, the Internet of Things, big data, artificial intelligence, cloud computing, and mobile It is necessary to develop a smart livestock system. In this study, domestic and foreign research trends related to smart livestock based on intelligent information technology were introduced and the limitations of domestic application of advanced technologies were analyzed. Finally, future intelligent information technology applicable to the livestock field was examined.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.12
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• pp.357-362
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• 2023

Bridges are important transportation infrastructure, but they are subject to damage and cracking due to various environmental factors and constant traffic loads, which accelerate their aging. With many bridges now older than their original construction, there is a need for systems to ensure safety and diagnose deterioration. Bridges are already utilizing structural health monitoring (SHM) technology to monitor the condition of bridges in real time or periodically. Along with this technology, the development of intelligent bridge monitoring technology utilizing artificial intelligence and Internet of Things technology is underway. In this paper, we study an edge system technique for predicting bridge safety using fast Fourier transform and dimensionality reduction algorithm for maintenance of aging bridges. In particular, unlike previous studies, we investigate whether it is possible to form a dataset using sensor data collected from actual bridges and check the safety of bridges.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.1-7
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• 2023

An artificial intelligence (AI) method based on image deep learning is proposed to predict the entire displacement shape of a structure using the feature of partial displacements. The performance of the method was investigated through a structural test of a steel frame. An image-to-image regression (I2IR) training method was developed based on the U-Net layer for image recognition. In the I2IR method, the U-Net is modified to generate images of entire displacement shapes when images of partial displacement shapes of structures are input to the AI network. Furthermore, the training of displacements combined with the location feature was developed so that nodal displacement values with corresponding nodal coordinates could be used in AI training. The proposed training methods can consider correlations between nodal displacements in 3D space, and the accuracy of displacement predictions is improved compared with artificial neural network training methods. Displacements of the steel frame were predicted during the structural tests using the proposed methods and compared with 3D scanning data of displacement shapes. The results show that the proposed AI prediction properly follows the measured displacements using 3D scanning.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.87-96
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• 2017

This study was carried out to provide basic data for prevention of death from injuries and traumas by analyzing the characteristics of length of hospital stay of patients with injuries and traumas, utilizing in-depth investigation data of discharged injuries. The study subjects were 233 patients discharged from January 1 to December 31 in 2014 whom the final treatment result was 'death' and the main diagnosis were injuries and accidental external causes(S00-T98). According to the research findings, the length of hospital stay of females was longer than that of males. Based on the main diagnosis, the longest length of hospital stay had complication of other internal prosthetic devices, implants and grafts(T85). In conclusion, it is necessary to develop a policy to identify the factors affecting the length of hospital stays of patients and to manage them intensively.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.409-412
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• 2022

본 논문에서는 대입수시전형에서 생활기록부 입력은 대한민국 입시를 결정하는 매우 중요한 평가자료이다. 30명의 교사를 대상으로 실시한 설문조사를 통해서 교사들이 생활기록부를 작성하는데 가장 많이 참고하는 자료로는 수행평가 결과물, 발표내용, 보고서, 감상문 등의 학습 결과물(90%), 학생들이 작성한 자기평가서(73.3%), 관찰 평가지(50%)로 나타났으며, 80%(24명)의 교사들이 생활기록부를 작성하는데 고충을 겪고 있음을 확인할 수 있었다. 교사들이 느끼는 고충의 원인으로는 학생들의 개인별 특성 파악이 어려워 차별성있게 작성하는 것(76.7%)을 가장 힘들어 하였고, 작성해야 할 많은 수의 학생(60%), 문구를 만드는데 대해 부담(86.7%)을 느끼는 것으로 나타났다. 이 과정에서 교사의 전문성 뿐만 아니라 기계적이고 반복적인 작업도 많이 요구되고 있기 때문에, 생활기록부를 작성하는데에 도움을 줄 수 있는 프로그램 개발이 필요하다고 고안을 내었다. 교사들 역시 반복적이고 일률적인 생활기록부 작성에 도움을 줄 수 있는 프로그램이 있다면 유용하게 활용할 것이라는 응답이 90%였다. 따라서 본 연구에서 자연어 처리 인공지능 기술을 활용하여 교사들이 생활기록부를 작성하는데 있어 기계적이고 단순한 작업을 도와 주는 프로그램 개발에 대한 연구의 필요성을 제시하였다. 제안하는 프로그램은 학생들의 탐구보고서, 토론, 발표, 감상문 등의 생화기록부 작성 참고자료들을 텍스트로 변환하고 추상요약(Abstractive Summarization)을 통해 교사들이 효율적으로 작성하는데 활용될 수 있도록 설계하였다. 연구 결과 생활기록부 작성 참고자료를 텍스트로 변환하는 것과 추상요약을 할 수 있는 개방형 데이터셋까지는 확보하였다. 추상요약을 구현하는 방법에 대해서는 보다 심도 있는 추가연구가 필요하였다. 이를 통해 교사들이 교육 본질에 더욱 충실할 수 있는 환경을 마련하고, 내실 있는 생활기록부 작성이 공교육 신뢰 제고에 밑바탕이 되고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.415-418
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• 2024

본 논문에서는 텍스처 합성을 할 때 CNN을 사용하여 효율성을 높이고 방향을 고려하여 동적인 결과로 품질을 개선시킬 수 있는 방법을 제안한다. 자유로운 회전 각도로 방향성을 고려하여 동적인 결과물을 생성할 수 있도록 하였으며, 기존 접근법인 사각형 형태의 마스크 블록이 아닌 다양한 회전 각도를 고려하여 학습을 했기 때문에 텍스처 합성 과정에서 방향성 특징을 좀 더 잘 표현할 수 있다.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.1-12
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• 2019

In this study, TI(Toxic Index) of Daphnia toximeter corresponded to ecological toxicity standard 1 TU(Toxic Unit) was set up using Daphnia toximeter and when operating NOEC(water quality standards for drinking water) and $EC_{50}$ Daphnia toximeter alarm was issued appropriately, which enables real time ecological toxicity evaluation. I studied to get a good shot and the research was conducted by investigating domestic and international related data and conducting a preliminary study. 6 of 59 hazardous substances (As, Hg, Cr, Diazinon, Dioxane, and Phenol) recommended by the water quality monitoring items for artificial river water were selected and static, dynamic and quality management test, TI was shown to be good in other materials except Diazinon, and as a result of $EC_{50}$ spiking test, TI was matched to TU by distinguishing between 1 TU and 1 TU. in suggesting the complementary point of ecological toxicity management system and the future of research on water Daphnia toximeter.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.591-601
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• 2024

As generative AI-based educational content and services targeting child users rapidly increase, the need for research related to children's perception of generative AI is increasing. Accordingly, this study sought to determine the type of generative AI recognized by children and whether cognitive, behavioral, and emotional properties were assigned to it. To understand this, we collected responses through workshop activities to create storybooks with children, semi-structured interviews, and drawing. As a result, children viewed generative AI as an artifact with a high cognitive level, but it was not a type of existing artifact.

• Journal of the Korean Institute of Landscape Architecture
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• v.15 no.1
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• pp.39-67
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• 1987

The purpose of this thesis is to suggest objective basic data for the environmental design through the quantitative analysis of the visual quality included in the physical environment of forest landscape. For this, landscape values of forest landscape have been evaluated by using the Iverson method, the images structure of forest landscape's main utilizing space have been analysed by the factor analysis algorithm, degree of visual preferences have been pleasured mainly by questionnaries and SBE method, and finally these thesis can be summarized as fallow LCP with high values of Iverson factors I and IV yield high landscape value. Specifically, Iverson factor IV has been found to play the dominant. For all experimental points, significant seasonal variations in S.D. scale values have been observed. In natural parks, where artificial structures are complementary to the natural landscape, main factors of image are S.D. scales such as the visual sequence, the formal simplicity of structures, the emphasis, the unification of heterogeneous factors and the assimilation. Factors covering the spatial image of natural parks have been found to be the overall evaluation, the individual characteristics, the tidiness, the potentiality, the dignity, the intimacy and the space volume. For all seasons, factors such as the individual characteristics, the dignity, the tidiness, the potentiality, yield high factor scores. As for factors determining the degree of visual preference, variables such as the summit, the skyline, rocks, the water and the degree of natural destruction by artificial structures yield high values for all seasons.