• Journal of Korean Society for Atmospheric Environment
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• v.16 no.1
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• pp.37-47
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• 2000

The Urban thermal environment is influenced and modified in many ways. One modification is brought by the anthropogenic heat generation emitted from the combustion processes and the use of energy such as industrial, domestic and traffic procedure. The anthropogenic heat generation affect an the increase of urban temperature, the well-known urban heat islands. The study on the urban thermal environment needs a great deal of the statistic data about the inner-structure of urban, the contribution of different constructions and the traffic amount on urban thermal environment in finite region. In order to overtake a quantitative analysis of effect of the anthropogenic heat, a distribution map of the urban anthropogenic heat was made using hte data of the energy consumption used at the several constructions and traffic amount of vehicles in Pusan Metropolitan. Annual mean heat flux over the 4$\textrm{km}^2$ urbanized area in Pusan is 41.5W/$m^2$, ranging from 31.4W/$m^2$ in summertime to 59.5W/$m^2$ in wintertime and maximum diurnal anthropogenic heat generation is corresponding to 10% of irradiance during summertime.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.45-50
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• 2022

The vehicle motion in urban environment is determined by surrounding traffic flow, which cause understanding the flow to be a factor that dominantly affects the motion planning of the vehicle. The traffic flow in this urban environment is accessed using various urban infrastructure information. This paper represents a color recognition algorithm for traffic lights to perceive traffic condition which is a main information among various urban infrastructure information. Deep learning based vision open source realizes positions of traffic lights around the host vehicle. The data are processed to input data based on whether it exists on the route of ego vehicle. The colors of traffic lights are estimated through pixel values from the camera image. The proposed algorithm is validated in intersection situations with traffic lights on the test track. The results show that the proposed algorithm guarantees precise recognition on traffic lights associated with the ego vehicle path in urban intersection scenarios.

• Journal of Environmental Health Sciences
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• v.40 no.3
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• pp.204-214
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• 2014

Objectives: Vehicular emissions are one of the main sources of air pollution in urban areas. Correlation analysis was conducted between air pollutants and traffic volume in order to identify causes of air pollution in Gwangju. Methods: Using traffic volumes and air quality monitoring data from 2002 to 2012 from nine stations (seven urban areas, two roadside areas), especially at three sites where traffic volumes were high, the correlation coefficients were obtained between air pollutants as PM-10 (particulate matter), $NO_2$, $SO_2$, CO and $O_3$ at the stations and traffic volumes near the air monitoring stations. Results: Due to traffic volume and distance between the station and the traffic road, concentrations of pollutants at roadside areas were higher than at urban areas, with the exception of $O_3$. The concentration of $O_3$ showed statistically significance with those of other gas materials as $NO_2$, $SO_2$, and CO in winter (p<0.001) and spring (p<0.05). During the period of October 7 to 20, 2012, excluding periods of yellow dust, smog and rainy season, the ratio of $NO/(NO+NO_2)$ showed the highest value 0.57 and 0.40 at Unam and Chipyeong of two roadside stations, followed by 0.35 at Nongseong with vehicular effects. The correlation coefficient between traffic volume and $O_3$, CO, $NO_2$ became higher when the data on mist and haze days were excluded, than when all hourly data were used in that period, at the three sites of Unam, Chipyeong, and Nongseong. Conclusions: Air quality showed a considerable effect from vehicles at roadside areas compared to in urban areas. Air pollutant diminishment strategies need to be aggressively adopted in order to protect atmospheric environment.

• Journal of the Korean Institute of Landscape Architecture
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• v.21 no.2
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• pp.34-49
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• 1993

This research aimed to analize the cognitive intensity of valuation(C.I.V) on urban environment as a first stage of the works on evaluative urban image under the hypothesis that it could be interpreted with a correlation analysis between the C.I.V and attitude(Satisfaction of unsatisfaction Intensity) toward urban environment. As a method of a study, 118 cognitive elements were selected representing an urban environment, and each of elements was suggested to citizens of Kyungju with 7 point Likert Scale. The analysis of C.I.V was operated under the three criteria: The first, three of urban space scale(urban scale, neighborhood scale, and housing scale), the second, four elements of urban living environment(safety, amenity, healthfulness, and effectiveness), and the last, thirteen urban unit environment(housing, traffic, education, tourism, medical/health, culture, etc.). The results were as follows: C.I.V to each of 118 elements was cleary defined, showing the possibilities of being applied to a method for subjective, or cognitive evaluation on urban environment: It was revealed that citizens'C.I.V was rather higher in non-physical, qualitative elements than in physical and quantitative ones. This shows well the limitation of the objective method of evaluation of urban environment: The results of the others' studies on the image of Kyungju based on the cognitive approach, being focused on the analysis of the visual aspects of urban structure, cultural assets, historic site and tourism, were almost same as this study but it was quite different for this research to reveal well the citizens' cognition on their living environment of traffic, education, medical, etc..

• Journal of Auto-vehicle Safety Association
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• v.14 no.4
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• pp.6-15
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• 2022

In this study, a traffic light recognition algorithm was implemented and validated for low-speed special purpose vehicles in an urban environment. Real-time image data using a camera and YOLO algorithm were applied. Two methods were presented to increase the accuracy of the traffic light recognition algorithm, and it was confirmed that the second method had the higher accuracy according to the traffic light type. In addition, it was confirmed that the optimal YOLO algorithm was YOLO v5m, which has over 98% mAP values and higher efficiency. In the future, it is thought that the traffic light recognition algorithm can be used as a dual system to secure the platform safety in the traffic information error of C-ITS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.582-585
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• 2018

As traffic volume increases and road networks become more complicated, identifying for accurate traffic flow and driving smooth traffic flow are a concern of many countries. There are various analytical techniques and studies which desire to study about effective traffic flow. However, the necessary activity is finding the traffic flow pattern through data visualization including location information. In this paper aim to study a real-world urban traffic trajectory and visualize a pattern of traffic flow with a simulation tool. Our experiment is installing the sensor module in 40 taxis and our dataset is generated along 24 hours and unscheduled routes. After pre-processing data, we improved an open source traffic visualize tools to suitable for our experiment. Then we simulate our vehicle trajectory data with a dots animation over a period of time, which allows clearly view a traffic flow simulation and a understand the direction of movement of the vehicle or route pattern. In addition we further propose some novel timelines to show spatial-temporal features to improve an urban environment due to the traffic flow.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.4
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• pp.97-110
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• 2020

This study conducted observations at 72 traffic lights and road signs in Sejong-si, Korea from March to June 2019 in order to analyze nest-site, nest-site characteristics and feeding behavior in Tree sparrow (Passeer montanus) in urban. Feeding behavior during breeding season in 2019 was investigated at 10 Town representing traffic facilities installed on the road located in the center of the city and 10 Riverside Geumgang river's riverside road. We fitted both general linear model and regression model to our field data and estimated the spatial variation of initial date of the first feeding (i.e., being date of breeding) and the total number of caterpillar fed by parents per hour. Our results showed that the frequency of nest building on artificial structures, such as traffic lights, was about 26% higher and about 8 days earlier in the riverside. In particular, the first feeding was significantly faster when the nearest distance between nest to green field as foraging site was shorter whereas there was no significant effect of the number of nest within 50 meters on the first feeding. Number of caterpillars fed by parents was higher in the Riverside than in the Urban, and especially the number in the second brood was sharply decreased in the Urban. As we estimated average amount of caterpillars per hour to 446 traffic safety facilities in Sejong-si, it was estimated that Tree sparrows fed 18,742.8 caterpillars per hour during the breeding season. In this study, we showed that characteristics of nests built in artificial structures and feeding behavior in order to analyze effects of environmental condition in urban on life-history traits during the breeding season. Finally, we discussed the conservation of birds in urban and pest control effects.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.2
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• pp.9-16
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• 2022

The nodes constituting the vehicle ad hoc network (VANET) are vehicles moving along the road and road side units (RSUs) installed around the road. The vehicle ad hoc network is used to collect the status, speed, and location information of vehicles driving on the road, and to communicate with vehicles, vehicles, and RSUs. Today, as the number of vehicles continues to increase, urban roads are suffering from traffic jams, which cause various problems such as time, fuel, and the environment. In this paper, we propose a method to solve traffic congestion problems on urban roads and demonstrate that the method can be applied to solve traffic congestion problems through performance evaluation using two typical protocols of vehicle ad hoc networks, AODV and GPSR. The performance evaluation used ns-2 simulator, and the average number of traffic jams and the waiting time due to the average traffic congestion were measured. Through this, we demonstrate that the vehicle ad hoc-based traffic congestion management technique proposed in this paper can be applied to urban roads in smart cities.

• KIEAE Journal
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• v.4 no.3
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• pp.95-101
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• 2004

As a part of acoustical design, it is often necessary to quantify aspects of an existing environment and to predict the result of adding an acoustical treatment. The most common sources of exterior noise, also termed as environmental noise,(or community noise) are traffic noise, air craft noise, industrial noise, etc. Transportation(air, road, and rail)noise is the dominant and most common source of noise exposure in residential neighborhoods, and the annoyance is its most consequential effect. The road traffic noise becomes aggravated due to the rapid increase of vehicles. It has a great effect on the dwelling environment. Therefore we investigate the characteristics and sources of the road traffic noise through grasping the status of the road traffic noise. In the present study, preceding studies investigated the noise level of urban areas in Seoul were reviewed and the noise level of urban areas in Seoul was measured at first, fifth, tenth, and nineteenth floor for two days of weekdays and two days of weekend.

• Advances in environmental research
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• v.6 no.2
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• pp.139-146
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• 2017

The purpose of this study was to determine the present air pollutant concentrations and predicted levels for next 30 years in urban environment of Karachi city. For that, a total of fifty measurements were made for each twenty selected locations of the city. The locations were selected on the basis of land use pattern such as residential, commercial, industrial settlements, open areas, congested traffic and low traffic areas for investigation of air pollutants variability and intensity. The measurements were taken continuously for six months period using PM Meter, Model AEROCET 531 and Ambient Air Quality Meter, Model AAQ 7545. The concentration of air pollutants were found higher at Al Asif Square and Maripur Road due to higher intensity of traffic and at Korangi Crossing because of industrial areas. The level of pollutants was lower at Sea View owing to lower traffic congestion and transportation of pollutants by sea breezes.