• 한국주거학회:학술대회논문집
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• 한국주거학회 2003년도 정기총회 및 추계학술대회
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• pp.159-164
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• 2003

Cohousing is communities balance the traditional advantages of home ownership with the benefits of shared common facilities and ongoing connections with your neighbors. It is characterized by private dwellings with their own kitchen living-dining room etc, but also extensive common facilities. These cooperative neighborhoods are one of the most promising solutions to many of today's most challenging social and environmental concerns. The purpose of this study is suggest planning direction to cohousing as alternative house. It focuses on the planning method through case study. The result of the study are summarized as follow ; Size of cohousing is 20${\sim}$50 family. Location of cohousing is urban. Type of house is detached house+row house. Size per family is 0${\sim}$15m$^2$. Common house makes up kitchen, dining-room living-room, guest room nursery room and so on.

• Wind and Structures
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• 제2권3호
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• pp.133-150
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• 1999

Significant costs to the public and private sectors due to recent extreme wind events have motivated the need for systematic post-hurricane damage data collection and analysis. Current post disaster data are collected by many different interested groups such as government agencies, voluntary disaster relief agencies, representatives of media companies, academicians and companies in the private sector. Each group has an interest in a particular type of data. However, members of each group collect data using different techniques. This disparity in data is not conducive to quantifying damage data and, therefore, inhibits the statistical and spatial description of damage and comparisons of damage among different extreme wind events. The data collection does not allow comparisons of data or results of analyses within a group and also prohibits comparison of damage data and information among different groups. Typically, analyses of data from a given event lead to different conclusion depending upon the definition of damage used by individual investigators and the type of data collected making it difficult for members of groups to compare the results of their analyses with a common language and basis. A formal method of data collection and analysis-within any single group-would allow comparisons to be made among different individuals, hazardous events and eventually among different groups, thus facilitating the management and reduction of damage due to future disaster. This research introduces a definition of damage to single family dwellings, and a common method of data collection and analysis suited for groups interested in regional characterization of damage. The current state-of-data is presented and a method for data collection is recommended based on these existing data collection methods. A fixed-scale damage index is proposed to consider the damage to a dwelling's feature. Finally, the damage index is applied to three dwellings damaged by Hurricane Iniki (1992). The damage index reflects the reduced functionality of a structure as a single family detached dwelling and provides a means to evaluate regional damage due to a single event or to compare damage due to events of different severity. Evaluation of the damage index and the data available support recommendation for future data collection efforts.

• Journal of Preventive Medicine and Public Health
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• 제21권1호
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• pp.132-151
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• 1988

This study was conducted to establish the control program for preventing unfavorable health effects of nitrogen dioxide($NO_2$) exposure in homes by preparing the fundamental data for evaluation of relation-ships between $NO_2$ levels and influencing factors through measurements of indoor-outdoor $NO_2$ levels and personal $NO_2$ exposures for housewives with questionnaire survey on 172 homes in Pusan area from April to June, 1987 $NO_2$ measurements were made by using diffusion tube samplers(Palmes tube $NO_2$ sampler) for one week at 4 sites in homes ; kitchen(KIT), bedroom(BED), living room(LIV), outdoor(OUT) and near the collar of housewives(personal exposure livel, PNO). The details of questionnaire were number of household members(FAM), number of regular smokers (SMOKER), daily number of meals eaten(MEAL), type of housing units(HOUSE), location of house with distance from the heavy traffic roads as walking time(DIST), and of kitchen(KAREA), kind of cooking fuels(FUEL), cooking time of each meal(CTIME), usage of kitchen fan for cooking(FAN), type of heating facilities(HEAT) and so on of subject homes. The Obtained results were as fellows : 1) The mean $NO_2$ level was significantly higher at indoors than outdoors(p<0.01) and the kitchen $NO_2$ level was the highest with $33.7{\pm}13.6ppb$(9.5-81.5ppb). The mean personal exposure level of $NO_2$ for housewives was $20.6{\pm}8.8ppb$(3.1-46.9ppb). 2) The mean indoor $NO_2$ level was significantly higher in the group of household members above 5 than below 4(p<0.05), in detached dwellings than apartments(p<0.001), within 5 minutes of distance than over 5 minutes(p<0.001), in the group of unusing fan(p<0.001), in the group of longer cooking time(p<0.001), and it was in order of coal briquette, gas, electricity and oil by kind of cooking fuels(p<0.05). 3) Variables showing significant correlation(p<0.001) with indoor $NO_2$ level were kitchen $NO_2$ level(r=0.8677), cooking time(r=0.5921), outdoor $NO_2$ level(r=0.5192), personal $NO_2$ exposure level(r=0.4615), usage of kitchen fan(r=0.3573) and location of house(r=-0.2988) 4) As a result of multiple regression analysis, the most significant influencing variable to the kitchen $NO_2$ level was cooking time[KIT=$-0.378{\pm}11.772$(CTIME)+0.298(OUT)+3.102(FAN)], it was kitchen $NO_2$ level to the indoor $NO_2$ level[IND=6.996+0.458(KIT)+0.230(OUT)-1.127(KAREA)], and it was indoor $NO_2$ level to the personal $NO_2$ exposure level[PNO=15.562+0.729(IND)-4.542(DIST)-0.200(KIT)] 5) It was recognized that aritificial ventilation in the kitchen, suppression of unnecessary combustion and replacement of cooking fuel, as much as possible, were effective means for decreasing indoor $NO_2$ levels in homes.