• Archives of Craniofacial Surgery
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• v.22 no.2
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• pp.110-114
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• 2021

Retrobulbar hemorrhage is a disastrous condition that can lead to permanent blindness. As such, rapid diagnosis and treatment are critical. Here, we report a patient who presented with retrobulbar hemorrhage following an orbital floor fracture. Restoration of inferior orbital wall with porous polyethylene implant was underwent. Four days after the orbital floor reconstruction, the patient smoked a cigarette outdoors in -3℃ weather. Cold temperature and smoking caused an increase in his systemic blood pressure. The elevated blood pressure increased intraorbital pressure to the extent of causing central retinal artery occlusion and exacerbated oozing. During exploratory surgery, 3 mL of hematoma and diffuse oozing without arterial bleeding were observed. Prompt diagnosis and treatment prevented vision impairment. Few studies have reported on the risk factors for retrobulbar hemorrhage. This case showed that daily activities, such as exposure to cold weather or tobacco smoking, could be risk factors for retrobulbar hemorrhage.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.76-80
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• 2018

In recent years, with the development of automobile technology, smart system technology that assists safe driving has been developed. A camera is installed on the front and rear of the vehicle as well as on the left and right sides to detect and warn of collision risks and hazards. Beyond the technology of simple black-box recording via cameras, we are developing intelligent systems that combine various computer vision technologies. However, most related studies have been developed to optimize performance in laboratory-like environments that do not take environmental factors such as weather into account. In this paper, we propose a method to detect object by restoring visibility in image with degraded image due to weather factors such as fog. First, the image quality degradation such as fog is detected in a single image, and the image quality is improved by restoring using an intermediate value filter. Then, we used an adaptive feature extraction method that removes unnecessary elements such as noise from the improved image and uses it to recognize objects with only the necessary features. In the proposed method, it is shown that more feature points are extracted than the feature points of the region of interest in the improved image.

• Journal of Environmental Science International
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• v.31 no.4
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• pp.311-318
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• 2022

In this study, we analyzed the relationships between weather factors and photosystem II activity (F_v/F_m), as a measure of photochemical efficiency, in three cool-season turfgrasses commonly planted on golf courses in Jeju, South Korea: perennial ryegrass (Lolium perenne L.), Kentucky bluegrass (Poa pratensis L.), and creeping bentgrass (Agrostis palustris Huds.). In all three turfgrasses, F_v/F_m was higher during late summer than during early summer. However, in late summer, F_v/F_m was significantly lower in perennial ryegrass than in the other two species. In early summer, F_v/F_m in perennial ryegrass and Kentucky bluegrass was positively correlated with mean low temperature and extreme minimum temperature, whereas, in late summer, this parameter in Kentucky bluegrass and creeping bentgrass was positively correlated with relative humidity, and in creeping bentgrass was negatively correlated with mean high temperature, mean low temperature, and extreme maximum temperature. These results indicate that raising low temperatures is favorable for perennial ryegrass and Kentucky bluegrass in early summer, whereas, in late summer, the lowering of high temperatures proves to be beneficial for creeping bentgrass, and raising relative humidity is conducive to the growth of Kentucky bluegrass and creeping bentgrass. These findings will contribute to improving the selection and management of turfgrasses on golf courses and sports fields.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.704-706
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• 2022

In this study, we analyzed the correlation between the amount of photovoltaic power generation and the factors of meteorological changes. A total of 52,561 data were used in the correlation analysis from January 2018 to January 2020, and the variables used in the correlation analysis were time, horizontal plane scattering solar radiation, direct solar radiation, wind velocity, and relative humidity. The temperature was used. Based on this data, we used the Google Colab platform to analyze the correlation, and the analysis revealed whether there was a correlation between solar power and meteorological change factors.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.116-126
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• 2013

Weather factor to affect driver's driving environment are due to changes in weather conditions is caused rainfall, snowfall, fog etc and the reducing of road capacity and because deteriorating weather could be affect the headway and vehicle speed and the decrease in lane caused by an accident occurs that was analyzed that bad weather occur congestion greater than on the clear day. Bad weather to reduce of the driver's visibility was analysed the sensitive to changes in travel speed and traffic accident to appears high characteristics according to weather conditions on the expressway(higher speed) than general road. As a result, visibility have been determined to be important factor in changes of the highway traffic flow characteristics. Therefore, in this study, we selected traffic volume and travle speed that have a major impact on high-speed expressway basic segments as importance effect factor and we selected to subject of analysis among the Metropolitan Expressway that it could be obtained certain level of traffic volume data and we studied the changing of expressway traffic flow due to change visibility after the collecting of meteorological and traffic data. In order to perform this study, data collection and analysis methods were established through the existing literature and we had selected level of visibility of the expressway and we had performed the statistical verification. Finally, we had calculated the rate of change of expressway traffic flow characteristics due to visibility and we had come up with a way to apply at capacity and service level analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.859-867
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• 2019

Severe weather conditions, such as heavy snowfall, rain, heatwave, etc., may affect travel behaviors of people and finally change traffic patterns in transportation networks. To deal with those changes and prevent any negative impacts on the transportation system, understanding those impacts of severe weather conditions on the travel patterns is one of the critical issues in the transportation fields. Hence, this study has focused on the impacts of a weather condition on travel patterns of public transportations, especially when a heavy snowfall which is one of the most critical weather conditions. First, this study has figured out the most significant weather condition affecting changes of public transport ridership using weather information, card data for public transportation, mobile phone data; and then, developed a decision-tree model to determine complex inter-relations between various factors such as socio-economic indicators, transportation-related information, etc. As a result, the trip generation of public transportations in Seoul during a heavy snowfall is mostly related to average access times to subway stations by walk and the number of available parking lots and spaces. Meanwhile, the trip attraction is more related to business and employment densities in that destination.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.6
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• pp.521-530
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• 2016

Weather radar is observation equipment that transmits electromagnetic waves and receives backscattered signals from the targets. The weather radar systems of the Korea Meteorological Administration have a doppler mode that can extract the target's radial velocity. However, the radial velocity over the maximum unambiguous velocity(${\nu}_m$) for which is in a trade-off relationship with the maximum unambiguous range is folded. Therefore, a dual PRF mode of which transmits and receives signals using two different PRFs(high and low) must be used to extend the vm while maintaining the maximum unambiguous range. Using a dual PRF mode, vm can be extended to the amount of lowest common denominator of two observed vm from high and low PRF. For this extension, we have developed a velocity unfolding algorithm of which uses several criteria for classification considering observed velocity differences between high and low PRF and their error boundary. Then, correction factors are calculated for each class and are applied to unfold radial velocity. The developed algorithm was applied to the Yong-In Testbed(YIT) radar and the generated better performance of radial velocity extraction than those of the previous system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.56-65
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• 2019

This study empirically analyzes the effect of weather on pedestrian volume in an urban space. We used data from the 2009 Seoul Flow Population Survey and constructed a model with the pedestrian volume as a dependent variable and the weather and physical environment as independent variables. We constructed 28 models and compared the results to determine the effects of weather on pedestrian volume by season, land use, and time zone. A negative binomial regression model was used because the dependent variable did not have a normal distribution. The results show that weather affects the volume of walking. Rain reduced walking volume in most models, and snow and thunderstorms reduced the volume in a small number of models. The effects of the weather depended on the season and land use, and the effects of environmental factors depended on the season. The results have various policy implications. First, it is necessary to provide semi-outdoor urban spaces that can cope with snow or rain. Second, it is necessary to have different policies to encourage walking for each season.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.320-323
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• 2014

Today is going with the advancement of intelligent transportation systems and traffic environment and helping to provide safe and convenient service through a mobile device work with the popularization of the vehicle black box. The traffic flow by a variety of causes is constantly changing, it is often unable to prepare the driver, depending on external factors can not be controlled by the power of the public, leading to a major accident. The system needs to pass the real-time weather data in the inter-operator to prevent this. The proposed detection algorithm weather information delivered real-time weather information for this paper. The weather condition is detected by using the contrast between the histogram of the motion of the wiper and the clear day algorithm. In general, the wiper is worked in extreme weather conditions that will have a value different contrast due to rain or snow. Situation was considered clear, snowy conditions, such as using it on a rainy situation. First, designated as ROI (Region Of Interest) of the minimum area that can be detected in order to reduce the amount of calculation for the wiper, the wiper, which was detected through the operation of the threshold Thresholding the brightness of the vehicle wiper. In addition, we distinguish the value of each meteorological situation by using contrast. Results was obtained to 80% for the snow conditions, a rainy situation.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.849-858
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• 2012

Today, local environmental factors has an influence on our society. Local environmental factors, as well as weather-related natural phenomena, social phenomena are also included. In this paper, numeric factors and categorical factors were analyzed, looking for a local environmental factors affecting the company's sales.Sales model by performing a regression analysis based on this was implemented.Sales model considering the local environment had an accuracy of 88.89%.