2022년 국내에서 이태원 참사라는 대형 인파사고가 발생한 이래로 인파밀집 현상이 수시로 발생하고, 인파가 이동할 수 있는 방향이 한정되어 있는 도시철도 역사내 대기공간의 인파밀집 문제가 심각하게 대두됨에 따라 인파밀집에 대한 모니터링 및 관리에 대한 중요 성이 커졌다. 이러한 문제사항을 해결하기 위해 영상분석에서 개별 객체의 수를 파악하여 인파의 밀집도를 파악한 연구들은 많이 이 루어졌으나 객체 간의 중첩으로 인해 검지 정확도가 떨어진다는 단점이 존재한다. 따라서 본 연구는 개별 객체를 검지하는 방식이 아 닌 Semantic Segmentation 기법 중 사전에 라벨링이 된 이미지들을 활용하는 지도학습 방식을 사용하여 밀집된 인파의 영역과 그렇지 않은 영역을 구분하고, 관심영역(ROI) 전체 공간 대비 인파가 차지하고 있는 영역의 점유율을 산출하여 혼잡도를 파악하는 방법을 적 용하였다. 본 연구의 목적은 도시철도 역사 내 대기공간의 인파의 밀집도를 점유율을 이용하여 산출하는 방법론을 만들고, 이를 혼잡 도를 나타내는 지표(MOE)로 적용할 수 있도록 그 기준을 검토하는 것이다. 데이터수집의 경우, 첨두시간대에 지하철 2호선 교대역의 대기공간인 대합실을 촬영한 CCTV 영상 데이터를 확보하여 이를 10fps 단위로 분할한 이미지들을 사용하였다. 이후 각 서비스수준별 (LOS A~F)로 다양한 이미지들에 대하여 인파에 해당하는 부분과 그렇지 않은 부분을 라벨링하였다. 분석방법론의 경우, 지도학습 기 반의 Semantic Segmentation 기법을 적용하여 대상 이미지들 전체에 대해서 인파와 인파가 아닌 부분을 구분하도록 이미지를 가공하였 으며, 이미지에 ROI를 설정하여 “전체 ROI 대비 인파 점유 공간의 비율”에 해당하는 점유율을 계산하였다. 여기서 인파와 인파가 아 닌 부분의 원활한 구분을 위해 픽셀 단위로 학습을 하며, 사전에 라벨링이 된 이미지들을 학습하는 모델을 적용하는게 본 연구에 적 합하다고 판단하여 해당 분석 기법을 사용하였다. 모든 이미지들의 점유율을 도출한 후 전체 결과를 Classification 기법을 활용하여 인 파 혼잡도의 서비스수준을 나타내는 현행 지침과 동일하게 6단계로 구분하였으며, 각 단계를 구분하는 경계값에 해당하는 점유율 역 시 도출하였다. 최종적으로 분할된 이미지들을 합쳐 영상에서 연속적인 인파분석 기법을 적용할 수 있도록 하였다. 향후에는 test dataset을 할용하여 해당 인파분석 기법의 적정성을 검토할 예정이며, 객체 검지 방식을 사용하는 기존의 모델과 성능을 비교하여 해당 기법의 우수성을 검토할 예정이다. 본 연구가 새로운 방식의 인파 혼잡도의 서비스수준 기준을 제공하는 모델을 개발하는 것을 목적 으로 함에 따라 실제 현장에 이 방법론을 적용할 시 인파밀집사고 예방 및 관리에 기여할 수 있을 것이다.

Although many attempts have been made to solve the atmospheric diffusion equation, there are many limits that prevent both solving it and its application. The causes of these impediments are primarily due to both the partial differentiation term and the turbulence diffusion coefficient. In consideration of this dilemma, this study aims to discuss the methodology and cases of utilizing a passive air sampler to increase the applicability of atmospheric dispersion modeling. Passive air samplers do not require pumps or electric power, allowing us to achieve a high resolution of spatial distribution data at a low cost and with minimal effort. They are also used to validate and calibrate the results of dispersion modeling. Currently, passive air samplers are able to measure air pollutants, including SO2, NO2, O3, dust, asbestos, heavy metals, indoor HCHO, and CO2. Additionally, they can measure odorous substances such as NH3, H2S, and VOCs. In this paper, many cases for application were introduced for several purposes, such as classifying the VOCs’ emission characteristics, surveying spatial distribution, identifying sources of airborne or odorous pollutants, and so on. In conclusion, the validation and calibration cases for modeling results were discussed, which will be very beneficial for increasing the accuracy and reliability of modeling results.

In this study, we analyze a finite-buffer M/G/1 queueing model with randomized pushout space priority and nonpreemptive time priority. Space and time priority queueing models have been extensively studied to analyze the performance of communication systems serving different types of traffic simultaneously: one type is sensitive to packet delay, and the other is sensitive to packet loss. However, these models have limitations. Some models assume that packet transmission times follow exponential distributions, which is not always realistic. Other models use general distributions for packet transmission times, but their space priority rules are too rigid, making it difficult to fine-tune service performance for different types of traffic. Our proposed model addresses these limitations and is more suitable for analyzing communication systems that handle different types of traffic with general packet length distributions. For the proposed queueing model, we first derive the distribution of the number of packets in the system when the transmission of each packet is completed, and we then obtain packet loss probabilities and the expected number of packets for each type of traffic. We also present a numerical example to explore the effect of a system parameter, the pushout probability, on system performance for different packet transmission time distributions.

도로협곡에서의 수목식재에 따른 보도 내 교통유발 대기오염도 변화를 살펴보기 위해 오픈소스 전산유체역학 코드 FDS(Fire Dynamics Simulator)를 사용하여 수목 투과지수, 식재 위치 및 유형에 따른 영향을 조사하였다. 광범위한 시뮬레이션을 통해 1) 관목층 만으로만 구성된 사례, 2) 관목층과 아교목층으로 구성된 사례 및 3) 관목층과 교목층으로 구성된 사례를 포함하는 400개의 시나리오 사례 중 399개 사례에 대해 유효한 데이터를 생성하였다. 분석결과, 보도 위에서 관찰되는 평균화된 정상상태 대기오염 농도는 식재유 형과는 무관하게 수목식재 후 약 10% 이상 감소하는 것으로 나타났다. 가장 큰 대기오염 감소효과는 관목층만으로 구성된 사례에서 관찰되었는데 대략 45%까지 감소하는 것으로 나타났다. 이러한 감소효과는 차선에서 인도로 대기오염물질을 직접 수송하는 선회류가 관목층에 의해 유리한 방향으로 변형되는 물리적 과정에 기초한다.

To meet rapidly changing market demands, manufacturers strive to increase both of productivity and diversity at the same time. As a part of those effort, they are applying flexible manufacturing systems that produce multiple types and/or options of products at a single production line. This paper studies such flexible manufacturing system with multiple types of products, multiple Bernoulli reliability machines and dedicated buffers between them for each of product types. As one of the prevalent control policies, priority based policy is applied at each machines to select the product to be processed. To analyze such system and its performance measures exactly, Markov chain models are applied. Because it is too complex to define all relative transient and its probabilities for each state, an algorithm to update transient state probability are introduced. Based on the steady state probability, some performance measures such as production rate, WIP-based measures, blocking probability and starvation probability are derived. Some system properties are also addressed. There is a property of non-conservation of flow, which means the product ratio at the input flow is not conserved at the succeeding flows. In addition, it is also found that increased buffer capacity does not guarantee improved production rate in this system.

최근 백두산 화산분화의 전조현상 증가로 인해 백두산 분화의 가능성이 지속적으로 제기되고 있으며 주변국인 일본의 화산 활동 또한 활발한 추세이다. 일본 화산 및 백두산으로부터 500km 이상의 거리에 위치한 우리나라의 경우 화산 분화로부터 근접 재해의 직접적인 위험은 없으나 화산재 확산에 의한 영향을 받을 가능성이 있어 이에 대한 대책 및 대응 방안 마련이 요구되고 있는 실정 이며 이에 대한 대응 방안 중 하나로, 화산재 확산 모델을 이용하여 화산재 입자의 공간분포 예측 및 대기 중 화산재 농도와 지표면의 화산재 퇴적 두께를 예측하는 방법이 있다. 본 연구에서는 화산재 확산 예측 모형에 의해 도출된 대기 중의 화산재 농도와 낙하 화산재 퇴적 두께를 이용하여 한반도 근역에 대하여 화산재 공간 확산 확률 및 낙하 확률 분석 기법을 제시하고 우리나라 17개 광역지자체에 대한 분석을 수행하였다.

The spatial resolution of 3-Dimensional numerical model has a very important influence on the model result. The land-use and orographic effect is also influenced by the spatial resolution of the model. A large errors in model performance are produced depending on the terrain complexity. In this study we performed Air Quality Forecast model (AQF) simulation and analyzed the change in the ozone concentration depending on spatial resolution at small and medium-sized mixed areas with urban and rural area types. As the result, improving the spatial resolution improved the simulation of the downward trend of ozone at night. This was mainly due to improvement of local concentration contaminants at fragmented grid. In the case of wind speed, the model with high-resolution shows better agreement with observation at night.

Temporal and spatial characteristics of the frequency of several weather types and the change in air pollutant concentrations according to these weather types were analyzed over a decade (2007-2016) in seven major cities and a remote area in Korea. This analysis was performed using hourly (or daily) observed data of weather types (e.g., mist, haze, fog, precipitation, dust, and thunder and lighting) and air pollutant criteria (PM10, PM2.5, O3, NO2, CO, and SO2). Overall, the most frequent weather type across all areas during the study period was found to be mist (39%), followed by precipitation (35%), haze (17%), and the other types (≤ 4%). In terms of regional frequency distributions, the highest frequency of haze (26%) was in Seoul (especially during winter and May-June), possibly due to the high population and air pollutant emission sources, while that of precipitation (47%) was in Jeju (summer and winter), due to its geographic location with the sea on four sides and a very high mountain. PM10 concentrations for dust and haze were significantly higher in three cities (up to 250 μg/m3 for dust in Incheon), whereas those for the other four types were relatively lower. The concentrations of PM2.5 and its major precursor gases (NO2 and SO2) were higher (up to 69 μg/m3, 48 ppb, and 16 ppb, respectively, for haze in Incheon) for haze and/or dust than for the other weather types. On the other hand, there were no distinct differences in the concentrations of O3 and CO for the weather types. The overall results of this study confirm that the frequency of weather types and the related air quality depend on the geographic and environmental characteristics of the target areas.

The relationship between urban spatial structures and GHG-AP integrated emissions was investigated by statistically analyzing those from 25 administrative districts of Seoul. Urban spatial structures, of which data were obtained from Seoul statistics yearbook, were classified into five categories of city development, residence, environment, traffic and economy. They were further classified into 10 components of local area, population, number of households, residential area, forest area, park area, registered vehicles, road area, number of businesses and total local taxes. GHG-AP integrated emissions were estimated based on IPCC(intergovernmental panel on climate change) 2006 guidelines, guideline for government greenhouse inventories, EPA AP-42(compilation of air pollutant emission factors) and preliminary studies. The result of statistical analysis indicated that GHG-AP integrated emissions were significantly correlated with urban spatial structures. The correlation analysis results showed that registered vehicles for GHG (r=0.803, p<0.01), forest area for AP (r=0.996, p<0.01), and park area for AP (r=0.889, p<0.01) were highly significant. From the factor analysis, three groups such as city and traffic categories, economy category and environment category were identified to be the governing factors controlling GHG-AP emissions. The multiple regression analysis also represented that the most influencing factors on GHG-AP emissions were categories of traffic and environment. 25 administrative districts of Seoul were clustered into six groups, of which each has similar characteristics of urban spatial structures and GHG-AP integrated emissions.

For this research, they were monitored CO2 flux and environmental factors (CO2 concentration, soil temperature, soil moisture, soil organic carbon, soil pH, soil Eh) in foreshore, paddy field and woods sites at the winter season (January 2009) and the summer season (September 2009). Seasonal and spatial variations for monitored data were analyzed, and linear regression functions of CO2 flux as environmental factors were estimated. CO2 fluxes averaged between surface and atmosphere monitored in foreshore and paddy field at the winter season were shown -8 mgCO2m-2hr-1 and -25 mgCO2m-2hr-1, respectively. CO2 fluxes averaged between surface and atmosphere monitored in foreshore and paddy field at the summer season were shown 47 mgCO2m-2hr-1 and 117 mgCO2m-2hr-1, respectively. Thus, CO2 was sunk from atmosphere to surface at the winter season and it was emitted from surface to atmosphere at the summer season. CO2 fluxes in woods site were emitted 145 mgCO2m-2hr-1 at the winter season and 279 mgCO2m-2hr-1 at the summer season.

With increasing population densities in cities, underground facilities and entertainment locations are proliferating at a rapid pace in efforts to maximize the use of land. The purpose of this study is to evaluate CO concentration level of subway stations having underground platforms in Busan Metropolitan City, from September to November 2000, over seven times. The places of inquiry include Yonsan-dong station, Somyon station, Busan station, Nampo-dong station and Dusil station. The samplings were conducted at three points of each station, i.e. gates, ticket gates, and platforms. The component of CO concentration is the main elements of indoor air quality evaluation. The total concentrations and average concentrations of CO were the higher at the Somyon station. The distribution of CO concentrations at each station, generally was higher at gate than ticket gates and platforms. The I/O ratios(I-platforms, O-gates) were expressed highly than 1 at the Yonsan-dong station, Busan station, Nampo-dong station and were lower than 1 at the others.

The purpose of this study was to investigate spatial distributions of total deposition. A total number 79 samples were collected at 17 sampling sites from September 1999 to January 2000. Total (=wet+dry) atmospheric depositions were collected by filtered deposition sampler at sampling site (the Western Part of Kyongsangnam Province). In addition, the deposition of soluble and insoluble fraction was also investigated to find a suitable simplified collection method for a long-term monitoring of total deposition. The total depositions were measured soluble amount(mm/month), insoluble amount(kg/km2/month), pH, conductivity(E.C.) and eight ionic components. The spatial distribution of deposition flux was to estimated by using a kringing analysis. The 17 sites mean fluxes of water soluble ionic components; SO42-, Cl-, NO3-, Na+, NH4+, K+, Mg2+, Ca2+ were 100.7～315.6kg/km2/month, 30.1～234.3kg/km2/month, 64.4～139.4kg/km2/month, 7.5～68.3kg/km2/month, 10.7～48.7kg/km2/month, 5.6～27.9kg/km2/month, 4.5～17.5kg/km2/month, 27.6～81.7kg/km2/month, respectively.

The purpose of this study is designed to estimate the air quality of subway stations that have the underground platforms in Pusan Metropolitan City, from September to November 2000, over seventimes. The subjects include Yonsan-dong station, Somyon station, Pusan station, Nampo-dong station, and Tushil station. The samplings were conducted at three points of each station, i.e. gates, ticket gates, and platforms. The major materials for analysis were CO, NO, NO2, and O3. The experiment was conducted at 7:00 pm with KIMOTO HS-7 Handy sampler and Tedlar Bag of SKC INC(U.S.A). In order to more fully understand station environments, we also measured temperature at each point. The results showed that O3 average concentration at Yonsan-dong station was higher than others with 38～51 ppb. The average concentration of NO was high at ticket gate and platform at Somyon station(119 ppb, 122 ppb), Nampo-dong station(102 ppb, 100 ppb). These results show that the air pollution of stations with underground shopping malls was higher than others. At Somyon station having a junction station, NO and NO2 concentration level of platform-2(noncrowded) was higher than platform-1(crowded). This is most likely due to the accumulation of air pollutants and inadequate ventilation systems.