• Title/Summary/Keyword: 시스템경계

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Policy Suggestions for Geological and Geotechnical Information Management in Earthquake Hazard Mitigation Measures by Local Governments (지자체 지진방재 대책을 위한 지질과 지반정보관리 정책 제언)

  • Lim, Hyunjee;Song, Cheol Woo;Ha, Sangmin;Kim, Min-Cheol;Son, Moon
    • Journal of the Korean earth science society
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    • v.43 no.1
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    • pp.176-187
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    • 2022
  • Due to recent mid-scale earthquakes in the Korean Peninsula, the Korean central and local governments are preparing new measures for earthquake hazard mitigation. Geological and geotechnical information is essential for earthquake hazard assessment. Thus, related data have been collected and assimilated as DBs by various national organizations. However, several problems arise when local governments intend to use this information to establish earthquake hazard mitigation measures. In the case of the geological information, small-scale geological maps make it difficult to acquire detailed information, whereas lithofacies and faults do not often match at the boundaries of large-scale geological maps. Significant geotechnical information is lost due to lack of digitalization. Present study proposes four policy plans for geological and geological information management. First, it is necessary to link industry-academictechnology fields to use the information that has already been or to be produced more efficiently and professionally. Second, local government regulations are required to be enacted and revised to accumulate a lot of geological and geotechnical information. Third an expert system should be prepared to improve the quality of the information. Fourth, it is necessary to establish a dedicated department and expand budget support for efficient information management.

A Study on Future Changes of Sea Surface Temperature and Ocean Currents in Northwest Pacific through CMIP6 Model Analysis (CMIP6 모형 결과 분석을 통한 북서태평양 해면수온과 해류의 미래변화에 대한 고찰)

  • JEONG, SUYEON;CHOI, SO HYEON;KIM, YOUNG HO
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.26 no.4
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    • pp.291-306
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    • 2021
  • From the climate change scenario experiments of 21 models participating in Coupled Climate Model Inter-comparison Project Phase 6, future changes of sea surface temperature (SST) and Kuroshio in the Northwest Pacific were analyzed. The spatial feature of SST change was found to be related to the change of the current speed and spatial distribution of Kuroshio. To investigate the relationship between the change in latitude of the Kuroshio extension region, which flows along the boundary between the subtropical gyre and the subarctic gyre in the North Pacific, and the large-scale atmospheric circulation due to global warming, the zero-windstress curl line for each climate change experiment from 9 out of 21 models were compared. As the atmospheric radiative forcing increases due to the increase of greenhouse gases, it was confirmed that the zero-windstress curl line moves northward, which is consistent with the observation. These results indicate that as the Hadley Circulation expands to the north due to global warming, the warming of the mid-latitudes to which the Korean Peninsula belongs may be accelerated. The volume transport and temperature of the Tsushima Warm Current flowing into the East Sea through the Korea Strait also increased as the atmospheric radiative forcing increased.

Analysis of Grounding Accidents in Small Fishing Vessels and Suggestions to Reduce Them (소형어선의 좌초사고 분석과 사고 저감을 위한 제언)

  • Chong, Dae-Yul
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.4
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    • pp.533-541
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    • 2022
  • An analysis of marine accidents that occurred in the last five years, revealed that 77.0 % of all grounding accidents and 66.1% of all marine casualties involved small vessels, which was a very high level relatively. The Mokpo Regional Maritime Safety Tribunal (Mokpo-KMST) inquired on 72 cases of marine accidents in 2021, of which 10 cases were grounding accidents. Furthermore, eight cases of grounding accidents occurred in small fishing vessels. This study analyzed eight cases of grounding accidents on small fishing vessels that inquired in the jurisdictional area of Mokpo-KMST in 2021. I found out that this grounding occurred in clear weather with good visibility (2-4 miles) and good sea conditions with a wave height of less than 1 meter. Furthermore, I found that the main causes of grounding were drowsy navigation due to fatigue, neglect of vigilance, neglect of checking ship's position, overconfidence in GPS plotter, and lack of understanding of chart symbols and tidal differences. To reduce grounding accidents of small fishing vessels, I suggested the following measures. First, crew members who have completed the able seafarer training course on bridge watchkeeping should assist to the master. Second, alarm systems to prevent drowsiness should be installed in the bridge. Third, the regulation should be prepared for the performance standards and updating GPS plotter. Finally, the skipper of small vessels should be trained periodically to be familiar with chart symbols and basic terrestrial navigation.

Analysis of Research Trends in Tax Compliance using Topic Modeling (토픽모델링을 활용한 조세순응 연구 동향 분석)

  • Kang, Min-Jo;Baek, Pyoung-Gu
    • The Journal of the Korea Contents Association
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    • v.22 no.1
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    • pp.99-115
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    • 2022
  • In this study, domestic academic journal papers on tax compliance, tax consciousness, and faithful tax payment (hereinafter referred to as "tax compliance") were comprehensively analyzed from an interdisciplinary perspective as a representative research topic in the field of tax science. To achieve the research purpose, topic modeling technique was applied as part of text mining. In the flow of data collection-keyword preprocessing-topic model analysis, potential research topics were presented from tax compliance related keywords registered by the researcher in a total of 347 papers. The results of this study can be summarized as follows. First, in the keyword analysis, keywords such as tax investigation, tax avoidance, and honest tax reporting system were included in the top 5 keywords based on simple term-frequency, and in the TF-IDF value considering the relative importance of keywords, they were also included in the top 5 keywords. On the other hand, the keyword, tax evasion, was included in the top keyword based on the TF-IDF value, whereas it was not highlighted in the simple term-frequency. Second, eight potential research topics were derived through topic modeling. The topics covered are (1) tax fairness and suppression of tax offenses, (2) the ideology of the tax law and the validity of tax policies, (3) the principle of substance over form and guarantee of tax receivables (4) tax compliance costs and tax administration services, (5) the tax returns self- assessment system and tax experts, (6) tax climate and strategic tax behavior, (7) multifaceted tax behavior and differential compliance intentions, (8) tax information system and tax resource management. The research comprehensively looked at the various perspectives on the tax compliance from an interdisciplinary perspective, thereby comprehensively grasping past research trends on tax compliance and suggesting the direction of future research.

Detection of Wildfire Smoke Plumes Using GEMS Images and Machine Learning (GEMS 영상과 기계학습을 이용한 산불 연기 탐지)

  • Jeong, Yemin;Kim, Seoyeon;Kim, Seung-Yeon;Yu, Jeong-Ah;Lee, Dong-Won;Lee, Yangwon
    • Korean Journal of Remote Sensing
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    • v.38 no.5_3
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    • pp.967-977
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    • 2022
  • The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO2), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

Improvement in Regional-Scale Seasonal Prediction of Agro-Climatic Indices Based on Surface Air Temperature over the United States Using Empirical Quantile Mapping (경험적 분위사상법을 이용한 미국 지표 기온 기반 농업기후지수의 지역 규모 계절 예측성 개선)

  • Chan-Yeong, Song;Joong-Bae, Ahn;Kyung-Do, Lee
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.4
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    • pp.201-217
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    • 2022
  • The United States is one of the largest producers of major crops such as wheat, maize, and soybeans, and is a major exporter of these crops. Therefore, it is important to estimate the crop production of the country in advance based on reliable long- term weather forecast information for stable crops supply and demand in Korea. The purpose of this study is to improve the seasonal predictability of the agro-climatic indices over the United States by using regional-scale daily temperature. For long-term numerical weather prediction, a dynamical downscaling is performed using Weather Research and Forecasting (WRF) model, a regional climate model. As the initial and lateral boundary conditions of WRF, the global hourly prediction data obtained from the Pusan National University Coupled General Circulation Model (PNU CGCM) are used. The integration of WRF is performed for 22 years (2000-2021) for period from June to December of each year. The empirical quantile mapping, one of the bias correction methods, is applied to the timeseries of downscaled daily mean, minimum, and maximum temperature to correct the model biases. The uncorrected and corrected datasets are referred WRF_UC and WRF_C, respectively in this study. The daily minimum (maximum) temperature obtained from WRF_UC presents warm (cold) biases over most of the United States, which can be attributed to the underestimated the low (high) temperature range. The results show that WRF_C simulates closer to the observed temperature than WRF_UC, which lead to improve the long- term predictability of the temperature- based agro-climatic indices.

Dynamic Behavior Characteristics of Group Piles with Relative Density in Sandy Soil (건조 모래지반의 상대밀도에 따른 무리말뚝의 동적거동특성)

  • Heungtae Kim;Hongsig Kang;Kusik Jeong;Kwangkuk Ahn
    • Journal of the Korean GEO-environmental Society
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    • v.24 no.9
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    • pp.33-40
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    • 2023
  • The lateral load which is applied to the pile foundation supporting the superstructure during an earthquake is divided into the inertia force of the upper structure and the kinematic force of the ground. The inertia force and the kinematic force could cause failure to the pile foundation through different complex mechanisms. So it is necessary to predict and evaluate interaction of the ground-pile-structure properly for the seismic design of the foundation. The interaction is affected by the lateral behavior of the structure, the length of the pile, the boundary conditions of the head, and the relative density of the ground. Confining pressure and ground stiffness change accordingly when the relative density changes, and it results that the coefficient of subgrade reaction varies depending on each system. Horizontal bearing behavior and capacity of the pile foundation vary depending on lateral load condition and relative density of the sandy soil. Therefore, the 1g shaking table tests were conducted to confirm the effect of the relative density of the dried sandy soil to dynamic behavior of the group pile supporting the superstructure. The result shows that, as the relative density increases, maximum acceleration of the superstructure and the pile cap increases and decreases respectively, and the slope of the p-y curve of the pile decreases.

Examination of Lateral Torsional Bucling Strength by Increasing the Warping Strength of I-Section Plate Girder with Concrete Filled Half Pipe Stiffener (콘크리트 충전 반원기둥보강재가 적용된 플레이트 거더의 뒤틀림 강도)

  • Cheon, Jinuk;Lee, Senghoo;Baek, Seungcheol;Kim, Sunhee
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.43 no.5
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    • pp.577-585
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    • 2023
  • Lateral torsional buckling causessafety accidentssuch as collapse accidents during erection. Therefore, anaccurate safety designshould be conducted. Lateral torsional buckling canbe prevented by reinforcing the end orreducing the unbraced length. The method ofreducing the unbraced length by installing a crossframe has high material and installation costs and low maintenance performance.In addition, structuralsafety may be deteriorated due to cracks. The end reinforcement method using Concrete Filled Half Pipe Stiffeneris a method ofreinforcing the end of a plate girder using a stiffenerin the form of a semi-circular column. This method increasesthewarping strength ofthe girder and increasesthe lateral torsional buckling strength.In thisstudy, the effect ofincreasing the warping strengthof plate girders with concrete filled half pipe stiffeners was confirmed. To verify the effect, the results ofthe designequationand the finite element analysis were compared and verified through a experiment. As a result, the plate girderwithCFHPS increased thewarping strengthand confirmed that the lateral torsional buckling strength was increased.

A Case Study on the Introduction and Use of Artificial Intelligence in the Financial Sector (금융권 인공지능 도입 및 활용 사례 연구)

  • Byung-Jun Kim;Sou-Bin Yun;Mi-Ok Kim;Sam-Hyun Chun
    • Industry Promotion Research
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    • v.8 no.2
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    • pp.21-27
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    • 2023
  • This study studies the policies and use cases of the government and the financial sector for artificial intelligence, and the future policy tasks of the financial sector. want to derive According to Gartner, noteworthy technologies leading the financial industry in 2022 include 'generative AI', 'autonomous system', 'Privacy Enhanced Computation (PEC) was selected. The financial sector is developing new technologies such as artificial intelligence, big data, and blockchain. Developments are spurring innovation in the financial sector. Data loss due to the spread of telecommuting after the corona pandemic As interests in sharing and personal information protection increase, companies are expected to change in new digital technologies. Global financial companies also utilize new digital technology to develop products or manage and operate existing businesses. I n order to promote process innovation, I T expenses are being expanded. The financial sector utilizes new digital technology to prevent money laundering, improve work efficiency, and strengthen personal information protection. are applying In the era of Big Blur, where the boundaries between industries are disappearing, the competitive edge in the challenge of new entrants In order to preoccupy the market, financial institutions must actively utilize new technologies in their work.

BIM Mesh Optimization Algorithm Using K-Nearest Neighbors for Augmented Reality Visualization (증강현실 시각화를 위해 K-최근접 이웃을 사용한 BIM 메쉬 경량화 알고리즘)

  • Pa, Pa Win Aung;Lee, Donghwan;Park, Jooyoung;Cho, Mingeon;Park, Seunghee
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.2
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    • pp.249-256
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    • 2022
  • Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.