• Journal of Environmental Impact Assessment
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• v.29 no.1
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• pp.8-25
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• 2020

Industrialization has increased the production of road-deposited sediments (RDS) and the level of heavy metals in those RDS, which can have a significant impact on the surrounding aquatic environments through non-point pollution. Although the relationship between contamination characteristics and particle size of RDS is important for pollution control, there is very little information on this. In this study, we investigated the characteristics of grain size distribution and heavy metal concentrations in the road-deposited sediments (RDS) collected from 25 stations in Shihwa Industrial Complex. The environmental impact of RDS with particle size is also studied. I_geo, the contamination assessment index of each metal concentration, represents the RDS from Shihwa Industrial Complex are very highly polluted with Cu, Zn, Pb and Sb, and the levels of those metals were 633~3605, 130~1483, 120~1997, 5.5~50 mg/kg, respectively. The concentrations of heavy metals in RDS increased with the decrease in particle size. The particle size fraction below 250 ㎛ was very dominant with mass and contamination loads, 78.6 and 70.4%, respectively. Particles less than 125 ㎛ of RDS were highly contaminated and toxic to benthic organisms in rivers. RDS particles larger than 250 ㎛ and smaller than 250 ㎛ were contaminated by the surrounding industrial facility and vehicle activities, respectively. As a result of this study, the clean-up of fine particles of RDS, smaller than 125-250 ㎛, is very important for the control and reduction of non-point pollution to nearby water in Shihwa Industrial Complex.

• The Journal of Engineering Geology
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• v.3 no.2
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• pp.125-148
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• 1993

Groundwater flow in fractured rock masses is controlled by combined effects of fracture networks, state of geostafic stresses and crossflow between fractures and rock matrix. Furthermore the scaie dependent, anisotropic properties of hydraulic parameters results mainly from irregular paftems of fracture system, which can not be evaluated properly with the methods available at present. The basic assumpfion of discrete fracture network model is that groundwater flows only along discrete fractures and the flow paths in rock mass are determined by geometric paftems of interconnected fractures. The characteristics of fracture distribution in space and fracture hydraulic parameters are represented as the probability density functions by stochastic simulation. The discrete fracture network modelling was aftempted to characterize the groundwater flow in the vicinity of existing large cavems located in Wonjeong-ri, Poseung-myon, Pyeungtaek-kun. The fracture data of $1\textrm{km}^2$ area were analysed. The result indicates that the fracture sets evaluated from an equal area projection can be grouped into 6 sets and the fracture sizes are distributed in longnormal. The conductive fracture density of set 1 shows the highest density of 0.37. The groundwater inflow into a carvem was calculated as 29ton/day with the fracture transmissivity of $10^{-8}\textrm{m}^2/s$. When the fracture transmissivity increases in an order, the inflow amount estimated increases dramatically as much as fold, i.e 651 ton/day. One of the great advantages of this model is a forward modelling which can provide a thinking tool for site characterization and allow to handle the quantitative data as well as qualitative data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8B
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• pp.667-680
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• 2008

In this work, we present the results of our empirical study on 802.11 wireless LAN network traffic. We collect the packet trace from existing campus wireless LAN infra-structure. We analyzed four different data sets: aggregate traffic, upstream traffic, downstream traffic, tcp only packet trace from aggregate traffic. We analyze the time series aspect of underlying traffic (byte count process and packet count process), marginal distribution of time series, and packet size distribution. We found that in all four data sets there exist long-range dependent property in byte count and packet count process. Inter-arrival distribution is well fitted with Pareto distribution. Upstream traffic, i.e. from the user to Internet, exhibits significant difference in its packet size distribution from the rests. Average packet size of upstream traffic is 151.7 byte while average packet size of the rest of the data sets are all greater than 260 bytes. Packets with full data payloads constitutes 3% and 10% in upstream traffic and the downstream traffic, respectively. Despite the significant difference in packet size distribution, all four data sets have similar Hurst values. The Hurst alone does not properly explain the stochastic characteristics of the underlying traffic. We model the underlying traffic using fractional-ARIMA (FARIMA) and fractional Gaussian Noise (FGN). While the fractional Gaussian Noise based method is computationally more efficient, FARIMA exhibits superior performance in accurately modeling the underlying traffic.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.97-106
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• 2010

Various time series representation methods have been suggested in order to process time series data efficiently and effectively. SAX is the representative time series representation method combining segmentation and discretization techniques, which has been successfully applied to the time series classification task. But SAX requires a large number of segments in order to represent the meaningful dynamic patterns of time series accurately, since it loss the dynamic property of time series in the course of smoothing the movement of time series. Therefore, this paper suggests a new time series representation method that combines PIPs detection and Persist discretization techniques. The suggested method represents the dynamic movement of high-diemensional time series in a lower dimensional space by detecting PIPs indicating the important inflection points of time series. And it determines the optimal discretizaton ranges by applying self-transition and marginal probabilities distributions to KL divergence measure. It minimizes the information loss in process of the dimensionality reduction. The suggested method enhances the performance of time series classification task by minimizing the information loss in the course of dimensionality reduction.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.89-99
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• 2015

The World Economic Forum and the Korean Ministry of Knowledge Economy have selected big data as one of the top 10 in core information technology. The key of big data is to analyze effectively the properties that do have data. Clustering analysis method of big data techniques is a method of assigning a set of objects into the clusters so that the objects in the same cluster are more similar to each other clusters. Similarity measures being used in the cluster analysis may be classified into various types depending on the nature of the data. In this paper, we studied upper and lower bounds for binary similarity measures with negative matches such as Russel and Rao measure, simple matching measure by Sokal and Michener, Rogers and Tanimoto measure, Sokal and Sneath measure, Hamann measure, and Baroni-Urbani and Buser mesures I, II. And the comparative studies with these measures were shown by real data and simulated experiment.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.186-190
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• 2015

Intelligent vehicle plans motion and navigate itself based on the surrounding environment perception. Hence, the precise environment recognition is an essential part of self-driving vehicle. There exist many vulnerable road users (e.g. vehicle, pedestrians) on vehicular driving environment, the vehicle must percept all the dynamic obstacles accurately for safety. In this paper, we propose an multiple vehicle tracking algorithm using microwave radar. Our proposed system includes various special features. First, exceptional radar measurement model for vehicle, concentrated on the corner, is described by mixture density network (MDN), and applied to particle filter weighting. Also, to conquer the curse of dimensionality of particle filter and estimate the time-varying number of multi-target states, reversible jump markov chain monte carlo (RJMCMC) is used to sampling step of the proposed algorithm. The robustness of the proposed algorithm is demonstrated through several computer simulations.

• Journal of KIISE
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• v.43 no.7
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• pp.795-800
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• 2016

In image classification, recent CNNs compete with human performance. However, there are limitations in more general recognition. Herein we deal with indoor images that contain too much information to be directly processed and require information reduction before recognition. To reduce the amount of data processing, typically variational inference or variational Bayesian methods are suggested for object detection. However, these methods suffer from the difficulty of marginalizing over the given space. In this study, we propose an image-text integrated recognition system using active vision based on Spatial Transformer Networks. The system attempts to efficiently sample a partial region of a given image for a given language information. Our experimental results demonstrate a significant improvement over traditional approaches. We also discuss the results of qualitative analysis of sampled images, model characteristics, and its limitations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.9
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• pp.1119-1129
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• 2011

Shot-peening effects on the fatigue behavior of bearing steel were investigated under the high cyclic loading. Hourglass shape specimens were made of bearing steel(JIS-SUJ2) for rotary bending fatigue tests. Two kinds of treatments were performed : a heat treatment and a shot-peened surface treatment after the heat treatment. The fracture surfaces of specimens were classified into two types of fracture mode : the surface fracture mode induced by a surface defect and the internal fracture mode induced by a nonmetallic inclusion. Inclusion depth and shape affected considerably the fatigue life. Shot-peening treatment improved much the fatigue life of the bearing steel under low and high levels of cyclic loads. Probabilistic-stress-life (P-S-N) curves were suggested for the reliable fatigue life estimation of the improved bearing steel.

• Korean Journal of Environment and Ecology
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• v.36 no.5
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• pp.460-467
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• 2022

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.

• Korean Journal of Heritage: History & Science
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• v.56 no.3
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• pp.62-74
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• 2023

Much attention has been focused on the Baekpoman area due to the archaeological achievements of the past, but studies on prehistoric times when villages began to form is insufficient, and the Bronze Age village landscape was examined in order to supplement this. In the area of Baekpo Bay, the natural geographical limit connected to the inland was culturally confirmed by the distribution density of dolmens, and the generality of the Bronze Age settlement was confirmed with the Hwangsan-ri settlement. Bunto Village in Hwangsan-ri represents a farming-based village in the Baekpo Bay area, and the residential group and the tomb group are located on the same hill, and it is composed of three individual residential groups, and the village landscape had attached buildings used as warehouses and storage facilities. In the area of Baekpo Bay, it spread in the Tamjin River basin and the Yeongsan River basin where Songgukri culture and dolmen culture were integrated, and the density distribution of the villages was considered to correspond to the distribution density of dolmens. In order to examine the landscape of village distribution, the classification of Sochon-Jungchon-Daechon was applied, and it was classified as Sochon, a sub-unit constituting the village, in that the number of settlements constituting the village in the Bronze Age was mostly less than five. There are numerical differences between Jungchon and Daechon, and the distribution pattern does not necessarily coincide with the hierarchy. The three individual residential groups of Bunto Village in Hwangsan-ri are Jungchon composed of complex communities of blood relatives with each family community, and a stabilized village landscape was created in the Gusancheon area. In the area of Baekpo Bay, Bronze Age villages formed a landscape in which small villages were scattered around the rivers and formed a single-layered relationship. Dolmens (tombs) were formed between the villages and villages, and seem to have coexisted. Sochondeul is a family community based on agriculture, and it is believed that self-sufficient stabilized rural villages that live by acquiring various wild resources in rivers, mountains, and the sea formed a landscape.