• 한국농공학회논문집
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• 제63권5호
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• pp.63-71
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• 2021

Windbreak forests, which have a windproof effect against strong winds, are known to be effective in reducing the spread of odors and dust emitted from livestock farms. The effect of reducing the spread of odors and dust can be estimated through numerical models such as computational fluid dynamics, which require aerodynamic coefficients of the windbreaks for accurate prediction of their performance. In this study, we aimed to evaluate the aerodynamic coefficients, Co, C₁, C₂, and α, of two windbreaks, Thuja occidentalis and a mesh net, through wind tunnel experiments. The aerodynamic coefficients were derived by the relation between the incoming wind speed and the pressure loss due to the windbreaks which was measured by differential pressure sensors. In order to estimate the change in the aerodynamic coefficient concerning various leaf density, the experiments were conducted repeatedly by removing the leaves gradually in various stages. The results showed that the power law regression model more suitable for coefficient evaluation compared to the Darcy-Forchheimer model.

• Tribology and Lubricants
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• 제35권3호
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• pp.158-168
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• 2019

This paper presents the investigation of two types of rotordynamic modeling issues for 2.2 kW-class, rated speed of 1,800 rpm, squirrel-cage type induction motors. These issues include the lamination structure of rotor cores, and the radial clearance of ball bearings that support the shaft of the motor. Firstly, we focus on identifying the effects of rotor core lamination on the rotordynamic analysis via a 2D prediction model. The influence of lamination is considered as the change in the elastic modulus of the rotor core, which is determined by a modification factor ranging from 0 to 1.0. The analysis results show that the unbalanced response of the rotor-bearing system significantly varies depending on the value of the modification factor. Through modal testing of the system, the modification factor of 0.079 is proven to be appropriate to consider the effects of lamination. Next, we investigate the influence of ball bearing clearance on the rotordynamic analysis by establishing a bearing analysis model based on Hertz's contact theory. The analysis results indicate that negative clearance greatly changes the bearing static behavior. Rotordynamic analysis using predicted bearing stiffness with various clearances from -0.005 mm to 0.010 mm reveals that variations in clearance result in a slight difference in the displacement of the system up to 18.18. Thus, considering lamination in rotordynamic analysis is necessary as it can cause serious analysis errors in unbalanced response. However, considering the effect of the bearing clearance is optional because of its relatively weak impact.

• 한국가시화정보학회지
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• 제18권3호
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• pp.23-34
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• 2020

Two-phase flow and heat transfer characteristics during the reflood phase of a single heated rod in the KHU reflood experimental facility were examined. Two-phase flow behavior during the reflooding experiment was carefully visualized along with transient temperature measurement at a point inside the heated rod. By numerically solving one-dimensional inverse heat conduction equation using the measured temperature data, time-resolved wall heat flux and temperature histories at the interface of the heated rod and coolant were obtained. Once water coolant was injected into the test section from the bottom to reflood the heated rod of >700℃, vast vapor bubbles and droplets were generated near the reflood front and dispersed flow film boiling consisted of continuous vapor flow and tiny liquid droplets appeared in the upper part. Following the dispersed flow film boiling, inverted annular/slug/churn flow film boiling regimes were sequentially observed and the wall temperature gradually decreased. When so-called minimum film boiling temperature reached, the stable vapor film between the heated rod and coolant was suddenly collapsed, resulting in the quenching transition from film boiling into nucleate boiling. The moving speed of the quench front measured in the present study showed a good agreement with prediction by a correlation in literature. The obtained results revealed that typical two-phase flow and heat transfer behaviors during the reflood phase of overheated fuel rods in light water nuclear reactors are well reproduced in the KHU facility. Thus, the verified reflood experimental facility can be used to explore the effects of other affecting parameters, such as CRUD, on the reflood heat transfer behaviors in practical nuclear reactors.

• 한국안전학회지
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• 제36권1호
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• pp.72-79
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• 2021

This basic study introduces the concept of S-BRT and develops dwell time estimation models that consider road geometry and S-BRT characteristics for a signal operation strategy to meet the S-BRT's operational goal of high speed and punctuality. Field surveys of low-floor buses similar in shape to S-BRTs and data collection of passengers, station elements, vehicle elements, and other factors that can affect stop times were used in a regression analysis to establish statistically significant dwell time estimation models. These dwell time estimation models are developed by categorizing according to the locations of the signal or sidewalk that have the most impact on the dwell time. In this way, the number of people boarding and alighting the bus at the crowded door and the number of people boarding and alighting the bus at the front door considering the internal congestion was analyzed to affect the dwell time. The estimation dwell time models in this study can be used in the establishment of strategies that provide priority signals to S-BRTs.

• 한국전자통신학회논문지
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• 제16권3호
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• pp.471-476
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• 2021

분말 야금 기술에 의한 복합 연자성 재료는 전기기기에 일반적으로 사용되는 종래의 전기강판보다 많은 장점을 가지고 있으며, 그 관련 기술은 최근에 상당한 발전을 거듭하고 있다. 복합 연자성 재료는 일반적으로 분말의 형태로 인해 자기적 등방성 가지므로 3차원 자속 및 복잡한 구조의 전기기기 구성에 적합하다. 하지만 SMC와 같이 등방성 자기 특성을 가지는 재료는 복잡한 벡터 히스테리시스를 가지므로 정확한 손실 특성을 예측하는 것이 매우 어렵다. 따라서 본 논문에서는 전기강판 및 SMC의 링 타입 시편을 제작하고 시편 크기에 따라 자기적 특성을 측정한 후, 측정된 자기적 정보를 이용하여 800Hz 이상에서 구동하는 고속 영구자석 전동기의 전자계 해석을 수행하였다. 또한, 해당 모델의 시작품을 제작하고 효율 측정 및 비교를 통해 본 논문의 신뢰성을 입증하였다.

• 한국정보전자통신기술학회논문지
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• 제14권4호
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• pp.328-337
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• 2021

석면, 벤젠과 같이 발암물질 1급인 미세먼지는 각종 질병에 원인이 되고 있다. 초 미세먼지 확산은 코로나 바이러스 확산의 중요한 원인중 하나이다. 본 논문은 2015년부터 2019년까지 서울시 평균 기온, 강수량, 평균 풍속등의 기상 데이터와 SO2, NO2, O3,등의 대기 환경 데이터를 기반으로 미세먼지와 초 미세먼지를 분석하고 예측한다. 계절별과 월별로 미세먼지와 초미세먼지 현황을 파악·분석하며 미세먼지를 예측하기 위해 기계학습 모델 중 선형회귀, SVM, 앙상블 모델을 이용하여 비교 분석하였다. 또한 미세먼지와 초 미세먼지 발생에 영향을 미치는 중요한 피쳐(속성)를 파악한다. 본 논문이 파악한 결과 3월에 가장 (초)미세먼지가 높았고, 8월에서 9월까지 (초)미세먼지가 가장 낮았다. 기상 데이터일 경우 (초)미세먼지에 가장 영향을 미치는 데이터가 평균 기온이며, 기상 데이터와 대기 환경 데이터일 경우 NO2가 (초)미세먼지 발생에 가장 크게 작용하였다.

• 한국컴퓨터정보학회논문지
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• 제27권1호
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• pp.157-166
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• 2022

본 연구는 철로 복합화물 운송 시 환적 작업으로 인해 발생하는 소요 시간과 비용을 줄이고 운송속도 향상이 가능한 피기백시스템의 도입 타당성을 분석하는 것을 목표로 한다. 이를 위해 국내외 문헌검토를 통해 타당성 분석방법론을 검토한다. 타당성 분석 값을 정량적으로 도출하기 위해 교통 데이터베이스를 적용하여 운송거리가 200KM이상인 주요 화물 운송 O-D 노선에 화물 운송 시뮬레이션 모델과 운송 수단별 화물 수요 예측 모델을 개발하였다. 2025년 주요 화물 운송 O-D 노선에 피기백시스템이 도입된다는 전제로 분석기간을 15년으로 설정하여 경제적 타당성을 분석한 결과 NPV 값이 양수이고 B/C값이 1.18로 도출되어 피기백시스템이 경제성이 있는 것으로 나타났다. 제안된 연구 방법은 철도운송의 경쟁력을 향상할 수 있는 교통 정책 수립에 유의미한 자료가 될 수 있다.

• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.406-412
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• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• 대한의용생체공학회:의공학회지
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• 제43권1호
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• pp.27-34
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• 2022

Drunk driving defines a driver as unable to drive a vehicle safely due to drinking. To crack down on drunk driving, alcohol concentration evaluates through breathing and crack down on drinking using S-shaped courses. A method for assessing drunk driving without using BAC or BrAC is measurement via biosignal. Depending on the individual specificity of drinking, alcohol evaluation studies through various biosignals need to be conducted. In this study, we measure biosignals that are related to alcohol concentration, predict BrAC through SVM, and verify the effectiveness of the S-shaped course. Participants were 8 men who have a driving license. Subjects conducted a d2 test and a scenario evaluation of driving an S-shaped course when they attained BrAC's certain criteria. We utilized SVR to predict BrAC via biosignals. Statistical analysis used a one-way Anova test. Depending on the amount of drinking, there was a tendency to increase pupil size, HR, normLF, skin conductivity, body temperature, SE, and speed, while normHF tended to decrease. There was no apparent change in the respiratory rate and TN-E. The result of the D2 test tended to increase from 0.03% and decrease from 0.08%. Measured biosignals have enabled BrAC predictions using SVR models to obtain high Figs in primary and secondary cross-validations. In this study, we were able to predict BrAC through changes in biosignals and SVMs depending on alcohol concentration and verified the effectiveness of the S-shaped course drinking control method.

• 한국컴퓨터정보학회논문지
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• 제26권12호
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• pp.133-142
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• 2021

이동 패턴 인식은 사용자 궤적 질의, 사용자 행동 예측, 사용자 위치에 기초한 흥미요소 추천, 사용자 개인 정보 보호 및 지자체 교통 계획과 같은 여러 측면에서 널리 사용된다. 현재 인식 정확도는 응용 요건을 충족할 수 없기 때문에 이동 패턴 인식 연구는 궤적 데이터 연구의 초점이라 할 수 있다. GPS 내비게이션 기술과 지능형 모바일 기기의 대중화로 많은 사용자 모바일 데이터 정보를 얻을 수 있고, 이를 바탕으로 많은 의미 있는 연구가 이루어질 수 있다. 현재의 이동 패턴 연구 방법에서 궤적의 특징 추출은 궤도의 기본 속성(속도, 각도, 가속도 등)으로 제한된다. 본 논문에서 순열 엔트로피는 궤적 분류 연구에 참여하기 위한 궤적의 고유값으로 사용되었으며 시계열의 복잡성을 측정하기 위한 속성으로도 사용되었다. 속도 순열 엔트로피와 각도 순열 엔트로피가 이동 패턴 분류에 참여하기 위한 궤적의 특성으로 사용되었으며, 본 논문에서 사용된 순열 엔트로피를 기반으로 한 속성 분류의 정확도는 81.47%에 달했다.