• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.444-444
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• 2021

하천의 오염부하량 관리 계획은 지속적인 모니터링을 통한 자료 구축과 모형을 이용한 예측결과를 기반으로 수립된다. 하천의 모니터링과 예측 분석은 많은 예산과 인력 등이 필요하나, 정부의 담당 공무원 수는 극히 부족한 상황이 일반적이다. 이에 정부는 전문가에게 관련 용역을 의뢰하지만, 한국과 같이 지형이 복잡한 지역에서의 오염부하량 배출 특성은 각각 다르게 나타나기 때문에 많은 예산 소모가 발생 된다. 이를 개선하고자, 본 연구는 합성곱 신경망 (convolution neural network)과 수문학적 이미지 (hydrological image)를 이용하여 강우 발생시 BOD 및 총인의 부하량 예측 모형을 개발하였다. 합성곱 신경망의 입력자료는 일반적으로 RGB (red, green, bule) 사진을 이용하는데, 이를 그래도 오염부하량 예측에 활용하는 것은 경험적 모형의 전제(독립변수와 종속변수의 관계)를 무너뜨리는 결과를 초래할 수 있다. 이에, 본 연구에서는 오염부하량이 수문학적 조건과 토지이용 등의 변수에 의해 결정된다는 인과관계를 만족시키고자 수문학적 속성이 내재된 수문학적 이미지를 합성곱 신경망의 훈련자료로 사용하였다. 수문학적 이미지는 임의의 유역에 대해 2차원 공간에서 무차원의 수문학적 속성을 갖는 grid의 집합으로 정의되는데, 여기서 각 grid의 수문학적 속성은 SCS 토양보존국(soil conservation service, SCS)에서 발표한 수문학적 토양피복형수 (curve number, CN)를 이용하여 산출한다. 합성곱 신경망의 구조는 2개의 Convolution Layer와 1개의 Pulling Layer가 5회 반복하는 구조로 설정하고, 1개의 Flatten Layer, 3개의 Dense Layer, 1개의 Batch Normalization Layer를 배열하고, 마지막으로 1개의 Dense Layer가 연결되는 구조로 설계하였다. 이와 함께, 각 층의 활성화 함수는 정규화 선형함수 (ReLu)로, 마지막 Dense Layer의 활성화 함수는 연속변수가 도출될 수 있도록 회귀모형에서 자주 사용되는 Linear 함수로 설정하였다. 연구의 대상지역은 경기도 가평군 조종천 유역으로 선정하였고, 연구기간은 2010년 1월 1일부터 2019년 12월 31일까지로, 2010년부터 2016년까지의 자료는 모형의 학습에, 2017년부터 2019년까지의 자료는 모형의 성능평가에 활용하였다. 모형의 예측 성능은 모형효율계수 (NSE), 평균제곱근오차(RMSE) 및 평균절대백분율오차(MAPE)를 이용하여 평가하였다. 그 결과, BOD 부하량에 대한 NSE는 0.9, RMSE는 1031.1 kg/day, MAPE는 11.5%로 나타났으며, 총인 부하량에 대한 NSE는 0.9, RMSE는 53.6 kg/day, MAPE는 17.9%로 나타나 본 연구의 모형은 우수(good)한 것으로 판단하였다. 이에, 본 연구의 모형은 일반 ANN 모형을 이용한 선행연구와는 달리 2차원 공간정보를 반영하여 오염부하량 모의가 가능했으며, 제한적인 입력자료를 이용하여 간편한 모델링이 가능하다는 장점을 나타냈다. 이를 통해 정부의 물관리 정책을 위한 의사결정 및 부족한 물관리 분야의 행정력에 도움이 될 것으로 생각된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.551-560
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• 2009

This paper describes a newly developed pollutant transport model named ARPTM which was designed to simulate the transport and characteristics of pollutant materials after an accidental spill in upstream of river system up to a given position in the downstream. In particular, the ARPTM incorporated ADCP data to compute longitudinal dispersion coefficient and advection velocity which are necessary to apply one-dimensional advection-dispersion equation. ARPTM was built on top of the geographic information system platforms to take advantage of the technology's capabilities to track geo-referenced processes and visualize the simulated results in conjunction with associated geographic layers such as digital maps. The ARPTM computes travel distance, time, and concentration of the pollutant cloud in the given flow path from the river network, after quickly finding path between the spill of the pollutant material and any concerned points in the downstream. ARPTM is closely connected with a recently developed GIS-based Arc River database that stores inputs and outputs of ARPTM. ARPTM thereby assembles measurements, modeling, and cyberinfrastructure components to create a useful cyber-tool for determining and visualizing the dynamics of the clouds of pollutants while dispersing in space and time. ARPTM is expected to be potentially used for building warning system for the transport of pollutant materials in a large basin.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.1019-1023
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• 2006

The slope information based on DEM is very useful for urban planning, landscape, road design and water resource areas such as rainfall-runoff and soil erosion estimation. The resolution of slope, which is from DEM, can be variously decided by an application fields and the kinds of modeling method. In particular, the more decreased resolution makes the more decreased slope value because of the increased horizontal distance. This study presents slope evaluation method by aggregation method based on discharge and Manning's velocity equation to advance the loss of slope information in according to the resolution, and then applied it to calculate topographic factors of soil erosion model. As a result, conventional method shows 34.8% errors but aggregation method shows 12.6% errors. This study selected up-, middle-, and downstream region in watershed and analyzed the capability of aggregation method in order to estimate the influence of topographic characteristics. As a result of estimation, aggregation method shows more advanced results than conventional method. Therefore, the slope evaluation method by aggregation method can improve efficiently the loss of slope information in according to the variation of resolution in water resource area such as rainfall-runoff model.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.160-172
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• 2023

The metaverse, derived from the fusion of "meta" and "universe," encompasses a three-dimensional virtual realm where avatars actively participate in a range of political, economic, social, and cultural activities. With the recent development of the metaverse, the traditional way of experiencing services is changing. While existing studies have mainly focused on the technological advancements of metaverse services (e.g., scope of technological enablers, application areas of technologies), recent studies are focusing on evaluating the quality of experience (QoE) of metaverse services from a customer perspective. This is because understanding and analyzing service characteristics that determine QoE from a customer perspective is essential for designing successful metaverse services. However, relatively few studies have explored the customer-oriented approach for QoE evaluation thus far. This study conducted an online review analysis using text mining to overcome this limitation. In particular, this study analyzed 227,332 online reviews of the Roblox service, known as a representative metaverse service, and identified points for improving the Roblox service based on the analysis results. As a result of the study, nine service features that can be used for QoE evaluation of metaverse services were derived, and the importance of each feature was estimated through relationship analysis with service satisfaction. The importance estimation results identified the "co-experience" feature as the most important. These findings provide valuable insights and implications for service companies to identify their strengths and weaknesses, and provide useful insights to gain an advantage in the changing metaverse service environment.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.542-549
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• 2023

Since the growing interest in surrogate modeling, there has been continuous research aimed at simulating nonlinear chemical processes using data-driven machine learning. However, the opaque nature of machine learning models, which limits their interpretability, poses a challenge for their practical application in industry. Therefore, this study aims to analyze chemical processes using Explainable Artificial Intelligence (XAI), a concept that improves interpretability while ensuring model accuracy. While conventional sensitivity analysis of chemical processes has been limited to calculating and ranking the sensitivity indices of variables, we propose a methodology that utilizes XAI to not only perform global and local sensitivity analysis, but also examine the interactions among variables to gain physical insights from the data. For the ammonia synthesis process, which is the target process of the case study, we set the temperature of the preheater leading to the first reactor and the split ratio of the cold shot to the three reactors as process variables. By integrating Matlab and Aspen Plus, we obtained data on ammonia production and the maximum temperatures of the three reactors while systematically varying the process variables. We then trained tree-based models and performed sensitivity analysis using the SHAP technique, one of the XAI methods, on the most accurate model. The global sensitivity analysis showed that the preheater temperature had the greatest effect, and the local sensitivity analysis provided insights for defining the ranges of process variables to improve productivity and prevent overheating. By constructing alternative models for chemical processes and using XAI for sensitivity analysis, this work contributes to providing both quantitative and qualitative feedback for process optimization.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• Journal of the Korean Chemical Society
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• v.68 no.2
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• pp.107-116
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• 2024

The purpose of this study is to analyze changes in pre-service chemistry teachers' cognition of the nature of model in the evaluation and modification process of model using technology. Changes in cognition of the nature of model were analyzed focusing on the 'Abstraction' and 'Simplification' of the 'Representational aspect', 'Interpretation', 'Reasoning', 'Explanation' and 'Quantification' of the 'Explanatory aspect' that were deemed insufficient for pre-chemistry teachers in previous study. For this purpose, 19 third-year pre-service chemistry teachers at a teacher's college in Chungcheongbuk-do were asked to evaluate the model related to Boyle's law developed using technology, revise the model based on the evaluation results, and make a final evaluation. As a result of the study, it was confirmed that pre-service chemistry teachers' cognition of 'Simplification' of the 'Representational aspect' and 'Interpretation', 'Explanation', and 'Quantification' of the 'Explanatory aspect' changed positively through the evaluation and modification process of the model. Therefore, it was found that the evaluation and modification process of the model plays a key role in changing the cognition of the nature of model. However, there was little change in cognition of 'Abstraction' of the 'Representational aspect' and 'Reasoning' of the 'Explanatory aspect'. The cognition of these factors can be seen as more difficult to change than the cognition of other factors. To solve this problem, more sophisticated educational design for pre-service chemistry teachers is needed.

• Journal of the Korea Organic Resources Recycling Association
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• v.18 no.3
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• pp.77-86
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• 2010

In this study, the model of the indirect wind suction waste sorting machine for characteristics of the screening of waste was studied using computational fluid dynamics and the drag coefficient for the model and the suction wind speed were obtained. The wind separator are developing by installing a cyclone air outlet to the suction blower impeller waste is selective in a way that does not pass the features and characteristics of the inlet pipe of the pressure loss and separation efficiency can have a significant impact on. Using Wind separator for selection of waste in the waste prior research on the aerodynamic properties are essential. For plastic cases, it is reasonable to take the drag coefficient between 0.8 and 1.0, and for cans, compression depending on whether the cans, the drag coefficient is in the range from 0.2 to 0.7. The separation efficiency of waste as change suction speed was the highest efficiency when the suction speed was 25~26 m/s. Shape of the inlet, depending on how the transfer pipe of the duct pressure loss occurs because the inlet velocity changes through the appropriate design standards to allow for continued research is needed.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.259-265
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• 2024

Shape memory alloy (SMA)-textile actuators have attracted significant attention across various fields, including soft robotics and wearable technology. These smooth actuators are developed by combining SMA and simple textile fibers and then knitting them into two loop patterns known as the knit (K-loop) and plain (P-loop) patterns. Both loops are distinguished by opposite bending characteristics owing to loop head geometry. However, the knitting processes for these actuator sheets require expertise and time, resulting in high production costs for knitted loop actuation sheets. This study introduces a novel method by which to assess the strain in SMA textile-based actuators, which experience large deformations when subjected to voltage. Owing to the highly nonlinear constitutive equations of the SMA material, developing an analytical model for numerical analysis is challenging. Therefore, this study employs a novel approach that utilizes a linear constitutive equation to analyze large deformations in SMA material with nonlinear geometry considerations. The user-defined material (UMAT) subroutine integrates the linear constitutive equation into the ABAQUS software suite. This equivalent unit cell (EUC) model is validated by comparing the experimental bending actuation results of K-loops and P-loops.

• The Journal of Engineering Geology
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• v.34 no.3
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• pp.415-427
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• 2024

This study undertook a quantitative analysis of the distribution of fractures in deep drillcore from a Precambrian metamorphic complex on the north face of Hongcheon-gun, Gangwon-do, Korea. The fracture distribution with depth, inclination of fractures, and grain size in the fracture zone were measured and statistical techniques applied to derive probability distributions of fracture intervals. Analysis of the inclination angles of fracture planes showed that sub-horizontal fractures are dominant, and fracture spacing is mainly ≤0.5 m, with a median of 0.09 m, first quartile of 0.04 m, and third quartile of 0.18 m, indicating very dense fracture development. Statistical analysis of joint properties was undertaken with fitting using five probability density functions (double Weibull, exponential, generalized logistic, gamma, and lognormal). The lognormal distribution (sum of squared errors, SSE = 2.80) yielded the best fit based on the sum of residual squares. Quantitative characterization of the fracture characteristics of deep bedrock in the Hongcheon area is important for various geotechnical applications such as groundwater flow modeling, slope stability assessment, and underground structure design. In future studies, it will be necessary to combine in situ stress measurements and geophysical surveys to determine the relationship between fracture development and the local stress field.