• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.77-85
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• 2024

In this dissertation, a we designed and implemented a patrol robot that integrates a thermal imaging camera, speed dome camera, PTZ camera, radar, lidar sensor, and smartphone. This robot has the ability to monitor and respond efficiently even in complex environments, and is especially designed to demonstrate high performance even at night or in low visibility conditions. An orbital movement system was selected for the robot's mobility, and a smartphone-based control system was developed for real-time data processing and decision-making. The combination of various sensors allows the robot to comprehensively perceive the environment and quickly detect hazards. Thermal imaging cameras are used for night surveillance, speed domes and PTZ cameras are used for wide-area monitoring, and radar and LIDAR are used for obstacle detection and avoidance. The smartphone-based control system provides a user-friendly interface. The proposed robot system can be used in various fields such as security, surveillance, and disaster response. Future research should include improving the robot's autonomous patrol algorithm, developing a multi-robot collaboration system, and long-term testing in a real environment. This study is expected to contribute to the development of the field of intelligent surveillance robots.

• Smart Media Journal
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• v.13 no.8
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• pp.79-86
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• 2024

In design studies, there has been extensive prior research on accident and disaster prevention, but it mainly focuses on visualization methods to improve visibility. Most accidents and disasters are caused by human factors. However, there is little design research that considers human characteristics that manifest in dangerous situations. This study aims to identify the concepts and characteristics of safety information design that reflects human traits. It examines the concepts of risk and safety from a social science perspective and looks into human visual information processing from a cognitive neuroscience perspective. Additionally, it explores the relationship between human information processing and accident rates in dangerous situations from a psychological perspective. Based on these analyses, the study distinguishes between conventional information design and safety information design, ultimately identifying the features of safety information design that incorporates human traits. The key findings are as follows: First, information should be presented considering the human tendency to suspend rational judgment in dangerous situations. Second, appropriately dispersing or concentrating attention according to the level of risk can serve as an opportunity to minimize harm. Third, it was found that sensory and perceptual characteristics should be given top priority in the field of risk and safety information design. Through these findings, the study concludes that a design approach that reflects human traits in safety information design can ultimately be a key indicator for improving safety levels.

• Progress in Medical Physics
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• v.26 no.4
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• pp.215-222
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• 2015

In this work, we performed a proof-of-concept experiment for phase-contrast x-ray imaging (PCXI) based on a single antiscatter grid and a polychromatic x-ray source. We established a table-top setup which consists of a focused-linear grid having a strip density of 200 lines/inch, a microfocus x-ray tube having a focal-spot size of about $5{\mu}m$, and a CMOS-type flat-panel detector having a pixel size of $48{\mu}m$. By using our prototype PCXI system and the Fourier demodulation technique, we successfully obtained attenuation, scattering, and differential phase-contrast images of improved visibility from the raw images of several selected samples at x-ray tube conditions of $90kV_p$ and 0.1 mAs. Further, fusion image (e.g., the attenuation+the scattering) may have an advantage in displaying details of the sample's structures that are not clearly visible in the conventional attenuation image. Our experimental results indicate that single-grid-based approach seems a useful method for PCXI with great simplicity and minimal requirements on the setup alignment.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.451-463
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• 2018

The empirical/statistical models to estimate the ground Particulate Matter ($PM_{2.5}$) concentration from Geostationary Ocean Color Imager (GOCI) Aerosol Optical Depth (AOD) product were developed and analyzed for the period of 2015 in Seoul, South Korea. In the model construction of AOD-$PM_{2.5}$, two vertical correction methods using the planetary boundary layer height and the vertical ratio of aerosol, and humidity correction method using the hygroscopic growth factor were applied to respective models. The vertical correction for AOD and humidity correction for $PM_{2.5}$ concentration played an important role in improving accuracy of overall estimation. The multiple linear regression (MLR) models with additional meteorological factors (wind speed, visibility, and air temperature) affecting AOD and $PM_{2.5}$ relationships were constructed for the whole year and each season. As a result, determination coefficients of MLR models were significantly increased, compared to those of empirical models. In this study, we analyzed the seasonal, monthly and diurnal characteristics of AOD-$PM_{2.5}$model. when the MLR model is seasonally constructed, underestimation tendency in high $PM_{2.5}$ cases for the whole year were improved. The monthly and diurnal patterns of observed $PM_{2.5}$ and estimated $PM_{2.5}$ were similar. The results of this study, which estimates surface $PM_{2.5}$ concentration using geostationary satellite AOD, are expected to be applicable to the future GK-2A and GK-2B.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.423-433
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• 2018

Particulate matter air pollution is a serious problem affecting human health and visibility. The variations in $PM_{10}$ concentrations are influenced by not only local emission sources, but also atmospheric circulation conditions. In this study, we investigate the temporal features of $PM_{10}$ concentrations in South Korea and the atmospheric circulation patterns associated with high concentration episodes of $PM_{10}$ during winter (December-January-February) 2001-2016. Based on those analyses, a Korea Particulate matter Index (KPI) is developed to represent the large-scale atmospheric pattern associated with high concentration episodes of $PM_{10}$. The atmospheric patterns are characterized by persistent high-pressure anomalies, weakened lower-level north-westerly anomalies, and northward shift of the upper-level meridional wind anomalies near the Korean Peninsula. To evaluate the change in occurrence of high concentration episodes of $PM_{10}$ under a possible future warmer climate, we apply KPI analysis to CMIP5 climate simulations. Here, historical and two representative concentration pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) are used. It is found that the occurrence of atmospheric conditions favorable for high $PM_{10}$ concentration episodes tends to increase over South Korea in response to climate change. This suggests that large-scale atmospheric circulation changes under future warmer climate can contribute to increasing high $PM_{10}$ concentration episodes in South Korea.

• Korean Journal of Environment and Ecology
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• v.28 no.3
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• pp.365-373
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• 2014

This study is to analyze the physical environment and conduct spatial data for bicycle road system in changwon. Index for evaluation index was developed based on literatures. Then the level of importance and weight have been modified through experts review. Finally, index with eight categories such as greenness(40% over), bicycle road connectivity(1.8, 9.8%), road type bike(bicycle lane, 24.4%), pave type(asphalt 72.5%), illegal parking(none, 93.9%), bike road surface visibility(exist, 46.8%), vehicle speed limits(30km, under), vehicle traffic(500/hr under, 44.3%) have been applied to empirical investigation. Collected data has been hierarchically classification by ArcGIS Program. The Highest grades(score 31-35, level 1) occupied 35% of target destination. High level of greenness and load type has contributed to high score. In addition, average level of greenness of those destination was 35% and higher, which provide high degree of security and freshness for bicycle riding. Meanwhile, lowest level(level 5, which earned 15 point or less) occupied 24.5%. illegal parking, low level of greenness, and no surface sign caused low score.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of Korea Port Economic Association
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• v.31 no.4
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• pp.91-106
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• 2015

This study aims to analyze the effects of service quality offered by automotive Ro-Ro terminal operators on customer satisfaction and loyalty. The results of the research can be used to understand how to enhance the service level in order to manage competitiveness of the terminal operators, finally resulting in global competitiveness of the automobile industry of Korea in both exports and imports. We carried out a survey on two groups: shippers (customers) and providers (related terminal operators and stakeholders). To identify and classify the factors into groups, we conducted Exploratory Factors Analysis (EFA) and Confirmatory Factor Analysis (CFA), which showed construct validity and convergent validity. We also calculated Cronbach's alpha for reliability. Five factor groups were identified: tangibles, reliability, responsiveness, assurance, and empathy. We found that empathy is the most influential factor group among the five groups, and that the other groups too exhibited similar effects. Based on the results of the survey and analyses, we can conclude that empathy is most important in automotive Ro-Ro terminals. In particular, specialties, training, experiences, and loyalty of employees are crucial factors because automotive Ro-Ro terminals significantly rely on work forces, differently from other bulk terminals and container terminals. Flexible working hours and fringe benefits for work forces can increase empathy, finally resulting in productivity and efficiency. Next, well-designed work schedules are followed, based on visibility through logistics and SCM activities in automobile export and import processes with information and communication networks.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.549-556
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• 2012

Longitudinal tunnels are defined as tunnels with length of over 1km. Because of Korea's topographical conditions and as safety measures for linear design, many tunnels are inevitably being constructed in Korea. The number of longitudinal tunnels constructed on expressways amounted to 104 as of the end of 2010 with a total length of 192km. Given the increasing demand for tunnels and the increasing length of tunnels, a safety evaluation of longitudinal tunnels needs to be conducted. As such, this study selected design elements, transportation environment and delineation system as elements to check and tried to determine factors influencing road crashes. For this, tunnels have been classified based on history of crashes; ones with crashes and ones without crashes and statistically meaningful explanatory variables were selected. By using these variables, a logit model was development in order to better grasp the factors that directly and strongly influence crashes. The result, related to crashes as well as the analysis were utility tunnel interior materials of driving lane and passing lane, which are related to driver's visibility, lateral width widening to consolidate space in a tunnel, and annual average daily traffic (AADT) per lane. These results may be used in the future as analysis indicators when drawing up plans to prevent crashes in longitudinal tunnels.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.38 no.1
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• pp.43-57
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• 2002

This paper introduces an analysis method to predicting the flow characteristic of flow field around otter board In order to develope a high performance model. In this experiment, it is used a numerical analysis of flow field through CFD(Computational Fluid Dynamic), PIV method in which quantitative, qualitative evaluation is possible. In this experiment, it is used PIV method with flow filed image around otter board in order to analysis of flow characteristic. The result compared flow pattern with analysis result through CFD and also measurement result of lift and drag force coefficient carried out in CWC(Circulating Water Channel). The numerical analysis result is matched well with experiment result of PIV in the research and it is able to verify In the physical aspect. The result is as follows ; (1) It was carried out visibility experiment using laser light sheet, and picture analysis through PIV method in order to analysis fluid field of otter-board. As a result, the tendency of qualitative fluid movement only through the fluid particle's flow could be known. (2) Since PIV analysis result is quantitative, this can be seen in velocity vector distributions, instantaneous streamline contour, and average vorticity distributions through various post processing method. As a result, the change of flow field could be confirmed. (3) At angle of attack 24$^{\circ}$ where It Is shown maximum spreading force coefficient, the analysis result of CFD and PIV had very similar flow pattern. In both case, at the otter-board post edge a little boundary layer separation was seen, but, generally they had a good flow (4) As the result of post processing with velocity vector distributions, instantaneous streamline contour and average vorticity distributions by PIV, boundary layer separation phenomenon started to happen from angle of attack 24$^{\circ}$, and from over angle of attack 28$^{\circ}$, it happen at leading edge side with the width enlarged.