• Journal of Korean Port Research
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• v.14 no.1
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• pp.66-75
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• 2000

From the traffic analysis, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results were obtained : ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy. ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period showed 10mph decrease when compared with the 24hours'average speed, but the speed did not show a big difference in the afternoon peak period. ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge section. ⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.111-121
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• 1999

From the traffic analyses, and model constructions and verifications for speed prediction on the freeway ramp junctions with 70mph speed limit, the following results obtained: ⅰ) The traffic flow distribution showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy distribution was also shown to be varied by a big difference depending on the time periods. Especially, the occupancy in the morning peak period showed over 100% increase when compared with the 24hours average occupancy, and the occupancy in the afternoon peak period over 25% increase when compared with the same occupancy.ⅲ) The speed distribution was not shown to have a big difference depending on the time periods. Especially, the speed in the morning peak period shown 10mph decrease when compared with the 24hours' average speed, but the speed did not show a big difference in the afternoon peak period.ⅳ) The analyses of variance showed a high explanatory power between the speed predictive models(SPM) constructed and the variables used, especially the upstream speed. ⅴ) The analysis of correlation for verifying the speed predictive models(SPM) constructed on the ramp junctions were shown to have a high correlation between observed data and predicted data. Especially, the correlation coefficients showed over 0.95 excluding the unstable condition on the diverge sectionⅵ) Speed predictive models constructed were shown to have the better results than the HCM models, even if the speed limits on the freeway were different between the HCM models and speed predictive models constructed.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.131-140
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• 1999

Today freeway is experiencing a severe congestion with incoming or outgoing traffic through freeway ramps during the peak periods. Thus, the objectives of this study is to identify the traffic characteristics, analyze the relationships between the traffic characteristics and finally construct the delay predictive models on the ramp junctions of freeway with 70mph speed limit. From the traffic analyses, and model constructions and verifications for delay prediction on the ramp junctions of freeway, the following results were obtained: ⅰ) Traffic flow showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period when compared with the afternoon peak period. ⅱ) The occupancy also showed a big difference depending on the time periods, and the downstream occupancy(Od) was especially shown to have a higher explanatory power for the delay predictive model construction on the ramp junction of freeway. ⅲ) The speed-occupancy curve showed a remarkable shift based on the occupancies observed ; Od < 9% and Od$\geq$9%. Especially, volume and occupancy were shown to be highly explanatory for delay prediction on the ramp junctions of freeway under Od$\geq$9%, but lowly for delay predicion on the ramp junctions of freeway under Od<9%. Rather, the driver characteristics or transportation conditions around the freeway were through to be a little higher explanatory for the delay perdiction under Od<9%. ⅳ) Integrated delay predictive models showed a higher explanatory power in the morning peak period, but a lower explanatory power in the non-peak periods.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.20 no.6
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• pp.113-119
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• 2018

Occupancy-based heating control is effective in reducing heating energy by preventing unnecessary heating during unoccupied period. Various technologies on detecting human occupancy have been developed using complicated machine learning algorithm and stochastic methodologies. This study aims at deriving low-cost and simple algorithm of occupancy inference that can be implemented to residential buildings. The core concept of the algorithm is to combine the occupancy probabilities based on indoor CO2 concentration and PIR(passive infrared) signals. The probability was estimated by applying different levels of decrement ratio depending on CO2 concentration change rate and aggregated PIR signals. The developed algorithm was validated by comparing the inference results with the occupancy schedule in a real residential building. The results showed that the inference algorithm can achieve the accuracy of 75~99%, which would be successfully implemented to the control of residential heating systems.

• Journal of the Korean Solar Energy Society
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• v.37 no.2
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• pp.23-33
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• 2017

Accurate prediction of stochastic behavior of occupants is a well known problem for improving prediction performance of building energy use. Many researchers have been tried various sensors that have information on the status of occupant such as $CO_2$ sensor, infrared motion detector, RFID etc. to predict occupants, while others have been developed some algorithm to find occupancy probability with those sensors or some indirect monitoring data such as energy consumption in spaces. In this research, various sensor data and energy consumption data are utilized for decision tree algorithms (C4.5 & CART) for estimation of sub-hourly occupancy status. Although the experiment is limited by space (private room) and period (cooling season), the prediction result shows good agreement of above 95% accuracy when energy consumption data are used instead of measured $CO_2$ value. This result indicates potential of IoT data for awareness of indoor environmental status.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.4
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• pp.279-287
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• 1996

Frequency occupancy data can provide information on both the actual ratio of usage of individual frequency channels and the average ratio of usage of these frequency bands so that the reserved capacity of the spectrum can be estimated. Such an estimate can be used for the planning of additional spectrum allocations and as a means of assessing the impact of new technologies on spectrum usage. In this paper, we introduce about the frequency occu- pancy measurement system that is developed in Korea. And, we introduce Frequency Occupancy Ratio with a time period and with a area zone by using radio monitoing measurement datas.

• Journal of Korean Port Research
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• v.14 no.2
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• pp.175-185
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• 2000

Today freeway is experiencing a severe congestion with incoming or outgoing traffic through freeway ramps during the peak periods. Thus, the purpose of this study is to identify the traffic characteristics, analyze the relationships between the traffic characteristics and finally construct the delay predictive models on the rap junctions of freeway with 70mph speed limit. From the traffic analyses, and model construction and verification for delay prediction on the ramp junctions of freeway, the following results were obtained : ⅰ) Traffic flow showed a big difference depending on the time periods. Especially, more traffic flows were concentrated on the freeway junctions in the morning peak period. ⅱ) The occupancy also showed a big difference depending on the time periods, and the downstream occupancy(Od) was especially shown to have a higher explanatory power for the delay predictive model construction on the ramp junctions of freeway. ⅲ) The delay-occupancy curve showed a remarkable shift based on the occupancies observed : O$\_$d/〈9% and O$\_$d/$\geq$9%. Especially, volume and occupancy were shown to be highly explanatory for delay prediction on the ramp junctions of freeway under O$\_$d/$\geq$9%, but lowly for delay prediction on the ramp junctions of freeway under O$\_$d/〈9%. Rather, the driver characteristics or transportation conditions around the freeway were thought to be a little higher explanatory for the delay prediction under O$\_$d/〈9%. ⅳ) Integrated delay predictive models showed a higher explanatory power in the morning peak period, but a lower explanatory power in the non-peak periods.

• Korea Journal of Hospital Management
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• v.15 no.4
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• pp.43-62
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• 2010

This study provides an evidence on the determinants of the profitability of university hospital by analyzing university hospital-level data set of hospital performance during the year 2007 (32 university hospitals in total). For the study, a multiple regression model is employed in which profitability index obtained from the DEA computations, operating margin to total asset and gross revenue are used as the dependent variables, and a number of hospital operating characteristics are chosen as the independent variables such as ownership type, location, bed size, period of establishment, bed occupancy rate, admission ratio of outpatients, patients per medical specialist, personnel cost per patient, liabilities to total assets, current ratio, fixed ratio, total asset turnover, medical assistance rate and public indicator. First, the results indicate that the bed occupancy rate and liabilities to total assets are positively and significantly associated with operating margin to total asset. Second, number of beds, the bed occupancy rate and number of patients per medical specialist are positively and significantly associated with operating margin to gross revenue. Third, the bed occupancy rate, number of patients per medical specialist, liabilities to total assets, total asset turnover are positively and significantly associated with profitability index revealed from DEA.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1559-1563
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• 2009

Despite the serious lack of parking lots, studies on parking lot expansion are insufficient; research on users' satisfaction following parking lot expansion is practically nonexistent. Therefore, this study sought to provide basic data for the parking lot expansion of old apartments by comparatively analyzing users' satisfaction before and after the parking lot expansion through a questionnaire survey that targeted residents benefiting from the expanded parking lot. Results revealed a low post-occupancy satisfaction with the parking lot expansion despite the parking lot expansion and improvement of the parking lot environment. This was because the parking lot was not expanded up to the second basement floor due to the lack of appropriate parking space. Other factors included the construction cost burden and lack of connectivity of the basement parking lot with elevators. The results actually raise the need for the establishment of an optimally suitable expansion plan and development of method and technology requiring lower cost and shorter construction period in the design and construction processes for parking lot expansion. Through post-occupancy evaluation (POE) after parking lot expansion, this study quantitatively identified the problems associated with the parking lots of old apartments and ensuing expansion effects. The findings in this study can be used as basic data to seek a suitable diagnosis and evaluation method for the parking lots of old apartments.

• Journal of architectural history
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• v.8 no.1 s.18
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• pp.29-40
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• 1999

This paper discusses the change of land ownership in the urban historical core of Kyungju city in the Period of Japanese occupancy(1910-45) based on the analysis of land register records. Kyungju city was not designated for the cities controlled by urban planning law which was set up in 1912 and 1934. The major purpose of this paper is to clarify the urbanization process of a Korean local city where the formal urban planning projects were not carried out. The focus of the study is the increase of the Japanese landowners and Japanization of the landscape. In the very beginning of occupation, Japanese already owned about 8% of the total land of the city centre where the old Kyungju castle had been located. The ratio of the land owned by Japanese went up to more or less 70% at the end of World war II. The process which the urban core had been replaced for the Japanese is very clearly traced from the analysis of a land register records.