In this study, the risk of red water and turbid water occurrence was analyzed by classifying it into detachment risk and deposition risk. First, risk factors for red water and turbid water were determined, and hydraulic analysis was conducted considering seasonal water consumption. The applied area was Cheongju City, and the risk analysis was conducted across 13 areas, and the areas with high deposition risk and high detachment risk were selected. The high risk of both detachment and deposition can be judged as an area with a very high probability of causing water quality problems. The areas with the highest deposition risk and detachment risk are the old towns of Nae deok1-dong and Yul1yang-dong, which are the oldest areas in Cheongju City with an age of more than 30 service years of pipe installation. By analyzing the risk of deposition and detachment, it will be possible to strengthen the maintenance function of the water supply network to provide the safe water to citizens and increase their confidence for tap water.
Minhyuk Jung;Hyun-soo Lea;Moonseo Park;Bogyeong Lee
International conference on construction engineering and project management
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2013.01a
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pp.397-402
/
2013
In super-tall building construction projects, schedule risk factors which vertically change and are not found in the low and middle-rise building construction influence duration of a project by vertical attribute; and it makes hard to estimate activity or overall duration of a construction project. However, the existing duration estimating methods, that are based on quantity and productivity assuming activities of the same work item have the same risk and duration regardless of operation space, are not able to consider the schedule risk factors which change by the altitude of operation space. Therefore, in order to advance accuracy of duration estimation of super-tall building projects, the degree of changes of these risk factors according to altitude should be analyzed and incorporated into a duration estimating method. This research proposes a simulation model using Monte Carlo method for estimating activity duration incorporating schedule risk factors by weather conditions in a super-tall building. The research process is as follows. Firstly, the schedule risk factors in super-tall building are identified through literature and expert reviews, and occurrence of non-working days at high altitude by weather condition is identified as one of the critical schedule risk factors. Secondly, a calculating method of the vertical distributions of the weather factors such as temperature and wind speed is analyzed through literature reviews. Then, a probability distribution of the weather factors is developed using the weather database of the past decade. Thirdly, a simulation model and algorithms for estimating non-working days and duration of each activity is developed using Monte-Carlo method. Finally, sensitivity analysis and a case study are carried out for the validation of the proposed model.
Min-Jung Kim;Jun-Gi Lee;Youngwoo Nam ;Yonghwan Park
Korean journal of applied entomology
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v.62
no.3
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pp.215-220
/
2023
A recent discovery of drywood termites (Cryptotermes domesticus) in a residential facility in Seoul has raised significant concern. This exotic insect species, which can damage timber and wooden buildings, necessitates an immediate investigation of potential infestation. In this study, we assessed the climatic suitability for this termite species using a species distribution modeling approach. Global distribution data and bioclimatic variables were compiled from published sources, and predictive models for climatic suitability were developed using four modeling algorithms. An ensemble prediction was made based on the mean occurrence probability derived from the individual models. The final model suggested that this species could potentially establish itself in tropical coastal regions. While the climatic suitability in South Korea was generally found to be low, a careful investigation is still warranted due to the potential risk of colonization and establishment of this species.
In order to get basic information for establishing weed control methods, weed distribution was surveyed at 15 days interval in garlic and red pepper fields at 8 locations in Chungnam Province. In garlic fields, 68 weed species(27 families) were distributed. Portulaca oleracea, Chenopodium album and Digitana sanguinalis were most dominant and Equisetum arvense, Alopecurus aequalis, and Setaria viridis dominant among them. Highest number of weeds emerged in May and dry weight or weeds was more heavy in June and summer broadleaf weeds were most abundant throughout garlic growing period. In red pepper fields, 38 weed species(17 families) were distributed, D. sanguinalis, Cyperus amuricus and P. oleracea were most dominant and Echinochloa crus-galli, Eleusine indica, D. violascens, and Centipeda minima also dominant among them. The highest number of weeds were emerged in June and summer, grasses and summer broadleaf weeds were more abundant in June and July. Seasonal Shannon's diversity index(H'), maximum diversity(Hmax') and eveness(J') for the Shannon diversity index, and Simpson index were high in both red pepper and garlic fields. Interspecific competition(probability for interspecific encounter) was more severe than intraspecific competiton.
This study included the analysis of mushroom data collected from Mt. Chiak in Gangwon-do using various methods. Former studies of Korean mushrooms are limited by regional characters and there is less species diversity among the regions. This study tried to find a way for the forecast of mushroom distribution and appearance by indexes of species diversity. The indexes used in this study include the number of fungi (N), the number of species (S), similarity index (C), richness index (R1, R2), variety index (V1, V2), evenness index (E1, E2, E3, E4, E5), and dominance index (D1) to analyze variety of species diversity. Analyses of data of fungi using a multistage cluster sampling indicate that the average value of C for years was higher than the average value of C for areas. The mushrooms consisted of 208 species in 686 individuals in limited fungal collection from 2002 to 2003. One hundred thirty nine species in 393 individuals were collected in 2002, and 122 species 293 individuals were collected in 2003. The individuals collected in 2003 were smaller than 2002's individuals. Similarity, richness, and variety indexes' values of 2003 were reduced than 2002's values but dominance index of 2003 was increased than 2002's value. Generally the species diversity of the environment to evaluate the index of similarity, richness, and variety was a higher index; dominance index was lower than that of the surrounding environment, suggesting a good diversity. As a result, the occurrence of mushrooms in the surrounding environment and the various factors seem fell in 2002 compared to 2003. The majority genus of the limited fungal collection was Mycena genus in 63 individuals; the majority species was Laccaria laccata in 34 individuals. Ninety three species in 106 individuals were collected by the extended collection and the majority genus of the extended collection was Amanita genus in 17 individuals; the majority species was Amanita citrina (Schaeff.) Pers. which was found in 5 individuals. This demonstrates that periodical similarity's value was 0.159 is higher than special similarity's 0.119. This indicates that the probability of the appearance of same mushrooms in the same area in following year is higher than the probability of the appearance of same mushrooms in the surrounding area in same year. The value of coefficient of variation (CV), in which the amount of change is much or less by N is higher than the CV value by S. CV value of dominance index(D) was the highest r point among other indexes, and evenness index (E) was the lowest point among other indexes. The correlation matrix with 66 combinations between the indexes, the combinations with correlations was 46 combinations. These results revealed that indexes of R1, V2, and E1 were proper to represent species diversity of fungi based on the correlation matrix and the theory of statistical independence which means there is no or less mutual association. This research would contribute to the study about variable living creature by measuring method and in the future this would be used to figure out regulation about fungi with their correlation, values in ecosystem, develop improving new models about agricultural fungi species and numbers by investigating agricultural variable species.
Domestic PB products have emerged and been distributed by hypermarkets, department stores, convenience stores, as well as TV home shopping channels and Internet shopping malls. However, the fierce competition among the distributors due to the emergence of the PB products have caused the diversion of consumers' recognition to be reduced weight and volume as well as had the effect of misleading consumers about the prices. The width of the PB product price's up and down is larger than the width of the NB product. Thus, following consumers' purchases of PB products, there has been an increasing number of consumer complaints. In order to research consumers' recognition of PB products and to examine how consumers' recognition and information search comparative to PB products affect consumers' dissatisfaction, an online survey targeted consumers with experience purchasing PB products. This study was conducted and analyzed using SPSS 19 Statistics. The findings can be summarized as follows. Even though more consumers who frequently purchased and used the PB products, the more they compared with information search comparative to the NB product and then purchased the PB product. We investigated the result that the relevant variables of consumer complaints have some relative influence in the purchasing of PB products. There will be a higher probability o the group having high recognition about price and safety not making consumer complaints in comparison with the probability of other consumers making complaints after the purchase of a PB product. Therefore, based on the results of this study, companies need to build a system so that they can figure out consumers' needs in order to prevent the occurrence of consumer complaints related to the products of distribution companies' brands. By means of the system, it is also necessary for companies to collect consumer complaints and analyze them by category. Then they eventually should develop a consumer-centered management system which may contribute to quality improvement, product development and the reduction of consumer complaints.
In this study, we collected snake roadkill data from 2006 to 2017 and developed a species distribution model to identify the pattern of snake roadkill and predict the potential hotspot of snake roadkill in the Odaesan National Park of South Korea. During the study period, snake roadkills occurred most frequently on the road, which passes through between forest and stream at an altitude of about 600 m. The modeling result showed that the occurrence probability of snake roadkill was high on a road with a gentle slope at a distance of 25 m from the stream and an altitude of 600 m. The most susceptible regions for snake roadkill in the Odaesan National Park were located on National Route 6, about 2.2 km and 11.7 km away from the southern border of the park, and on Local Road 446, 3.44 km away from the southern border of the park. The results of this study suggest that providing alternative basking places and eco-corridors and installing protection fences that block the inflow of snakes into roads, preferentially around roads and streams at an altitude lower than 700 m would be an effective way of reducing snake roadkill in the Odaesan National Park.
Lee, Hee-Jin;Nam, Won-Ho;Jason A. Otkin;Yafang Zhong;Xiang Zhang;Mark D. Svoboda
Journal of Korea Water Resources Association
/
v.57
no.8
/
pp.509-518
/
2024
Flash drought is a rapid-onset drought that occurs rapidly over a short period due to abrupt changes in meteorological and environmental factors. In this study, we utilized satellite-based soil moisture product from the Advanced Microwave Scanning Radiometer-2(AMSR2) ascending X-band to calculate the weekly Flash Drought Intensity Index (FDII). We also analyzed the characteristics of flash droughts on the Korean Peninsula over a 10-year period from 2013 to 2022. The analysis of monthly spatial distribution patterns of the irrigation period across the Korean Peninsula revealed significant variations. In North Korea (NK), a substantial increase in the rate of intensification (FD_INT) was observed due to the rapid depletion of soil moisture, whereas South Korea (SK) experienced a significant increase in drought severity (DRO_SEV). Additionally, regional time series analysis revealed that both FD_INT and DRO_SEV were significantly high in the Gangwon province of both NK and SK. The estimation of probability density by region revealed a clear difference in FD_INT between NK and SK, with SK showing a higher probability of severe drought occurrence primarily due to the high values of DRO_SEV. As a result, it is inferred that the occurrence frequency and damage of flash droughts in NK are higher than those in SK, as indicated by the higher density of large FDII values in the NK region. We analyzed the correlation between DRO_SEV and the Evaporative Stress Index (ESI) across the Korean Peninsula and confirmed a positive correlation ranging from 0.4 to 0.6. It is concluded that analyzing overall drought conditions through the average drought severity holds high utility. These findings are expected to contribute to understanding the characteristics of flash droughts on the Korean Peninsula and formulating post-event response plans.
Journal of the Korean Association of Geographic Information Studies
/
v.20
no.4
/
pp.89-101
/
2017
Crime occurs differently based on not only place locations and building uses but also the characteristics of the people who use the place and the spatial structures of the buildings and locations. Therefore, if spatial big data, which contain spatial and regional properties, can be utilized, proper crime prevention measures can be enacted. Recently, with the advent of big data and the revolutionary intelligent information era, predictive policing has emerged as a new paradigm for police activities. Based on 7420 actual crime incidents occurring over three years in a typical provincial city, "J city," this study identified the areas in which crimes occurred and predicted risky areas. Spatial regression analysis was performed using spatial big data about only physical and environmental variables. Based on the results, using the street width, average number of building floors, building coverage ratio, the type of use of the first floor (Type II neighborhood living facility, commercial facility, pleasure use, or residential use), this study established a Crime Incident Prediction Model (CIPM) based on Bayesian probability theory. As a result, it was found that the model was suitable for crime prediction because the overlap analysis with the actual crime areas and the receiver operating characteristic curve (Roc curve), which evaluated the accuracy of the model, showed an area under the curve (AUC) value of 0.8. It was also found that a block where the commercial and entertainment facilities were concentrated, a block where the number of building floors is high, and a block where the commercial, entertainment, residential facilities are mixed are high-risk areas. This study provides a meaningful step forward to the development of a crime prediction model, unlike previous studies that explored the spatial distribution of crime and the factors influencing crime occurrence.
Journal of the Korean Association of Geographic Information Studies
/
v.20
no.4
/
pp.139-151
/
2017
The habitat preference of roe deers(Capreolus pygargus) in Jeju island, South Korea was analyzed by using their occurrence probability in MaxEnt model in this study. Totally 490 surveying data were gathered and 15 environmental variables were chosen for the model in which 6 variables out of 15 ones were filtered and finally removed because of there being higher correlation(over 0.7 in correlation coefficient). According to the modeling, roe deers were known to prefer the area ranging from 200 to 700 meter and over 1,500 meter in sea level, where there were not many dominant tree and/or dominant vegetation with low density so that understory vegetation can grow well with plentiful sunlight and can be used as a food of herbivore like roe deers. Otherwise, the region ranging from 700 to 1,500 meter was mostly covered with high density vegetation which cut off sunlight trying to penetrate through the dominant vegetation. It can cause a lower density of vegetation on surface, which can not attract to roe deers.
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