In metropolitan areas where an enormous number of evacuees are expected, residents of high-rise buildings will be requested to stay in their home even after an earthquake as much as possible. The residents are not familiar with such fire protection systems and are not likely to notice damage on them. It is expected that the residents would decide to stay home in the aftermath of the earthquake if the building has no structural problem even if the fire protection systems are damaged.
 If the residents continue to live in a high-rise building, it is necessary to check fire safety to avoid a disaster in case of a fire after checking that the building has no structural problem. However, there will be no easily accessible method of assessing fire protection feature of the damaged buildings by checking damage conditions after an earthquake. It is socially significant to construct simple methods for residents, management company and specialists to inspect fire protection features of a damaged building and judge if the building can be safely used against a fire after an earthquake. The purpose of this research is to develop a method of assessing fire safety of the buildings damaged by an earthquake. In this paper a survey was conducted on the action taken by residents and management company and the damage, inspection and restoration of fire protection systems after the great earthquake.
 The following three issues are studied based on the survey results; (1)who will be able to conduct the inspection, (2)time phases after an earthquake and (3)necessary conditions to continue living in a high-rise building.
 The study results are as follows;
 - People who inspect the buildings and fire prevention systems vary with the lapse of time. The residents need to conduct the inspection for a certain period of time after the earthquake.
 - Fire prevention features get lower immediately after the earthquake and gradually recover to normal as the surrounding situation improves (people returning home, lifeline restoration (electricity and water supply), and reunited fire brigade) and the fire prevention features are restored by inspection and repairs.
 - It may be difficult to encourage the residents to evacuate from the high-rise building after the earthquake even if the fire prevention features have some failures. Keeping safety against a fire by lowering a fire risk with fire usage restriction will be a practical method if the residents continue to live in the building with lower fire prevention features.
 It can be concluded the following is important to make the assessment method more efficient, considering the above.
 - Divide the period after the earthquake into several time phases based on the time elapsed (hereafter referred to as “phase”) and clarify the minimum fire prevention features required for each phase in order to assess safety of high-rise building against a fire after an earthquake in a viewpoint of “whether the residents can continue to live in the building.”
 - Check whether the building maintains required features by inspection of the fire prevention features and lower a fire risk properly. Impose more stringent limits or encourage evacuation if no features are maintained.
 This study divides the period from the earthquake occurrence to the normal condition (fire protection features) into four time phases and shows which restoration stage each phase indicates, approximate period of each phase, fire protection features required and a reduction of fire risk imposed per each phase.

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 A cardiac disease is the second most common cause of death and a cerebrovascular disease is the fourth, a major cause of which is hypertension. Hypertension is an asymptomatic disease, which is called “silent killer”, affecting one-third of the population. Therefore, it is essential not only “high risk approaches” which are measures for hypertensive individuals such as treatment with an antihypertensive drug but also “population approaches” which are measures to reduce blood pressure (BP) of entire nation toward prevention of Hypertension.
 Against this background, the effects of the indoor thermal environment on BP have attracted attention because it affects asymptomatic individuals. Now some studies on the relationship between BP and indoor thermal environment are accumulated. But most of the studies are cross-sectional studies, so there is a real need for follow-up studies and actual proof of causal correlation between BP and indoor thermal environment. This study aimed to demonstrate antihypertensive effects by moving to high thermal insulation performance houses.
 Follow-up studies on home BP and indoor temperature was conducted before and after moving in winter 2014 and 2015. Home BP was measured by participants twice daily: before getting into bed in the evening and after getting out of bed in the morning for two weeks. Indoor temperature at 1.1 m above the floor was measured in the living room, bedroom, bathroom, and dressing room at 10-min intervals. During the survey periods, participants recorded the wake time and bedtime each day in a diary. Questionnaire surveys on personal factors and housing were also carried out. Besides, questionnaire surveys on housing were distributed to building contractor to get a reliable answer.
 Thermal insulation performance of houses before moving was either “pre-1980 standards” or “1980 standards.” While thermal insulation performance of houses after moving satisfied “1999 standards”: heat loss coefficient (Q value) of houses after moving was 1.9 W/m²K, corresponding gap area (C value) was 0.4 cm²/m² on average. Average daily outdoor temperature of before moving survey periods (5.7 °C) was nearly equal to average daily outdoor temperature of after moving survey periods (5.1 °C). The living room temperature gap between before and after moving was the largest at a wake-up time. At 6 o'clock, living room temperature after moving was higher by 2.0 °C than living room temperature before moving. In addition, the lowest temperature had increased and the highest temperature had decreased in each room. So, stabilizing effects of indoor temperature by moving were recognized.
 Systolic BP (SBP) decreased by 1.5 mmHg per 1 °C increase in indoor air temperature and standard deviation (SD) of SBP improved by 2.3 mmHg per 1 °C improvement in SD of indoor air temperature in a group over 125 mmHg. Therefore, stabilization of indoor temperature has stabilizing effects on BP. However, there were several participants whose houses got colder and more unstable after moving. To examine factors related to indoor temperature changes, a comparison of indoor temperature between before and after moving by patterns of moving was carried out. As a result, moving from a single-family house to a single-family house and from a wooden house to a wooden house became warmer and improved SD of indoor temperature. On the other hand, moving from a condominium to a single-family house and from a reinforced concrete house to a wooden house became colder. Moreover, not heating a room after moving caused a sharp decrease in indoor temperature. So, it is not satisfied only by moving to high thermal insulation performance houses but paying attention to house form and structure and adequately heating a room to improve BP value and stability of BP.

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 The objective of this study is to report the passive thermal storage effects achieved by applying PCM (Phase Change Material) plastered wall. The PCM plastered wall is a novel finish material where PCM in the form of n-paraffin capsules are mixed with wall finishing materials, such as plaster. When applied on the wall, the PCM plastered wall can deliver excellent indoor environmental improvements and energy savings, because of thermal storage of solar heat gain on the wall. In this study, the effects of the PCM plastered wall are elucidated using an experimental module with triple glass window at Otaru, Hokkaido.
 First, the measuring method of the basic thermal performance test of thermal storage building materials was examined. The analysis of basic thermal performance using radiant heating, convection heating, and conduction heating, showed that convection heating had the highest reproducibility. In addition, when measuring the specific heat and latent heat of solid and liquid phases, it was found that the heating rate of ambient air had a minor effect on the measurement results (Fig. 8, Fig. 9, and Fig. 10). In contrast, the measurement results of specific heat in the solid liquid mixed phase region tended to depend on the heating rate. To measure the basic thermal performance of the PCM plastered wall, we had to examine the heating rate and the temperature rising width. It was found that a heating rate of 20[min. /K] was required and for more than 10 °C width, except for the phase change region at the thermo-hygrostat.
 Second, the effects of the PCM plastered wall on indoor environmental improvement and energy savings were elucidated using the experimental module. The glass surface temperature of the indoor side was approximately 60 °C during the day in winter (Fig. 17). The heat balance between direct gain and heat loss from the window was measured by installing a heat flow meter on the indoor side glass surface (Fig. 15, Photo3). According to the integrated measured value on the heat flow meter, the heat balance of the window glass during the measurement period was +16.2 [MJ/m²], where the heat gain was more than the heat loss. The experimental module consist of two rooms: the gPCM room (coated with granulated PCM plastered wall) and the PB room (plain). The room temperatures at both rooms were evaluated and compared. It was found that the gPCM room had a higher minimum ambient temperature than the PB room. (Fig. 20 and Fig. 24). When the maximum room temperature became higher than the melting point, the minimum room temperature at the gPCM room the next morning was observed to be 3 [K] higher than that at the PB room. Moreover, excess over heat due to direct gain from heating for 24h was suppressed and energy savings were achieved because of the delay in the heating start time (Fig. 21).
 Finally, the energy-saving effects of PCM plastered wall were established. The influx and efflux of the material measured using the heat flow sensor revealed the thermal behavior of the PCM layer. By observing the heat flow fluctuation in the PCM layer, we found that equivalent thermal conductivity showed a large amount of heat storage, and a small amount of heat loss (Fig. 29 and Fig. 30). In addition, the equivalent surface heat transfer was about the same as that of the gypsum board (Fig. 32). Energy saving effects of the PCM plastered wall was 17% (average of the measurement period) in the experimental module installed at Otaru, Hokkaido (Fig. 33). The use of PCM plastered wall is a novel passive thermal storage method that can be located closest to the interior of the heat storage material.

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 In recent years, natural ventilation system have attracted greater attention as an alternative to reduce building energy consumption. And natural ventilated buildings have been increasingly applied even in large office buildings. In Japan, summer is hot and humid climate, winter is low on both temperature and humidity. And hence, the quality of fresh air in the intermediate seasons varies in both temperature and humidity. Therefore, determining the criteria of outdoor air to introduce natural ventilation is an important factor to achieve energy saving and comfortable indoor thermal environment.
 In this paper, switching conditions to natural ventilation in 42 buildings with natural ventilation system were investigated and classified in six groups ([t-h type], [t-x type], [t-h-φ type], [t type], [h type], [Lt-h type]). Each type was evaluated with the reference weather data of 2000yr versions from three aspects : 1) total operating hours, 2) continuity, defined as the daily average hours of operating natural ventilation, 3) the quality of supply outdoor air. The total operating hours of the six types in basic setpoints ranged from 972h to 1, 278h. Continuity was between 6.2 and 8.3.
 Comparison of calculation results based on the reference weather data of 2000yr versions with those based on the Meteorological Agency from 2001 to 2013 showed no significant difference in the operating hours and continuity. For the setpoint, the changing of the lowest outdoor temperature setpoint from 18Co to 15Co in [t-x type] and the changing of the highest dew-point temperature setpoint from 19Co to 15Co in [t-h-φ type] exhibited significant effect. It has been confirmed that the setpoint of relative humidity affected total operating hours at the nights. In order to study the regional difference, futher analysis was conducted with the reference weather data of 20 cities in Japan. And it was founded that operating times of Sapporo and Okinawa in intermediate seasons tend to be shorter than other cities.

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 A leakage model can be used to predict the leakage characteristics of a room or a building from measurements. The models used for leakage prediction are shown in Table 1. The relationship between air flow rate and pressure difference is an exponential equation, commonly referred to as the power law for narrow openings, and is given by equation (1). The exponent n is dependent on the Reynolds number as well as opening geometry (see Fig. 1). The square law for large openings (e.g., purpose-provided openings such as air vents) is given by equation (2). The square law is based on the power law, and becomes the same as the power law when n = 2. Generally, there are various types of opening geometries, and they may be combined in parallel or in series (see Fig. 1). The parallel combination model is given by equation (3). The theoretical evidence for straight parallel openings with laminar flow favors the quadratic by equation (4) rather than the power law. The problem is to decide which flow equation is the most appropriate to adopt for combination. The parallel combination model can divide a specific effective leakage area (ELA, αA) into ELAs of narrow opening and large opening.
 Table 2 presents the overall content of the dataset and contains the year of construction, size of the buildings and several variables related to this information. From daily life, the leakage is usually measured at pressure differences of approximately 10 to 50 Pa. And in the case of high airtight dwellings, the leakage is measured at pressure differences of approximately 30 to 100 Pa. Normally, the flow equation for series or parallel combination is not a power law. Figure 3 shows how the flow equations were fitted to the measured data on leakage (Table 3) of dwelling unit F1 (Fig. 2). Table 4 presents the measured data of the apartment houses given in Table 2. The quadratic equation can provide good fits for the measured data of plots of Q and ΔP (see Fig. 4). The parallel combination model's ability to provide a good fit was equivalent to that of the power law.
 As shown in Table 5, the ELA at 9.8 Pa (ELA₁₀) of existing dwelling stocks (built in 1960-1970s) decreased by 30% or more by retrofitting. Retrofitted stocks and new constructions have leakage characteristics similar to narrow openings at low Reynolds number. In addition, differences in leakage characteristics are seen in the same building for different plans, as displayed in Fig. 5. A plan with many windows relative to floor area is reeky. The flow characteristics of cracks around doors and window frames are similar to those of purpose-provided openings (see Table 6). Although these cracks are often narrow, it is because length is short. On the other hand, background openings (e.g., cracks in walls and ceilings) are narrow, and their width (depth) is much less than their length.
 Figure 6 shows a low correlation linear fit between ELA₁₀ per the floor area (ELA_F10) and “power law” exponent n. The relationship between “αA_N / (αA_N+αA_L)” and exponent n is obtained by regression weighted by measurements (see Fig. 7), where “αA_N” means ELA₁₀ of the narrow opening at low Reynolds number, and “αA_L” means ELA₁₀ of the large opening. Therefore, “αA_N / (αA_N+αA_L)” refers to the crack opening ratio. The exponent n becomes small in the order of stocks (+), retrofitted stocks (▲), and new constructions between 2003 and 2007 (●), and the crack opening ratio becomes high in the same order. This method is effective in the evaluation of retrofitting and leakage characteristics of apartments.

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 Passive cooling systems, which control or utilize natural energy sources, can contribute to the cooling/heating of a building without the need for mechanical equipment. Underground air tunnel systems, which are a type of EAHE (Earth-to-Air Heat Exchanger), have been often adopted as a method of passive cooling in relatively large office buildings. However, to evaluate these effects precisely, reproducing the air velocity and temperature distributions in the system by applying a three-dimensional unsteady CFD (Computational Fluid Dynamics) analysis is desirable. Estimating the annual cooling/heating effects by CFD analysis is nontrivial, however, due to the large number of calculations required.
 The purpose of this study is to propose and validate the prediction method of the short/long period thermal performance for underground air tunnel systems by three-dimensional unsteady CFD analysis. In this paper, we proposed an annual prediction method for the pre-cooling and pre-heating performance of an EAHE by unsteady CFD analysis, which does not analyze flow fields to reduce calculation loads. Our method (uncoupled simulation) reduces the calculation load for CFD analysis by using flow fields simulated in advance, and linearizing the heat equation by loading these flow fields. The following effects are expected by the proposed uncoupled simulation: (1) The conventional method (full coupled simulation) calculates equations for continuity, momentum, heat, turbulence energy , and turbulence energy dissipation rate for every time step. However, uncoupled simulations need to solve the only heat equation by loading flow fields. (2) Velocity, turbulence energy, and the turbulence energy dissipation rate become constant in the uncoupled simulation. Thus, the flow fields and temperature fields are coupled indirectly, meaning that heat equation is linearized, and this linearization improves the convergence and expansion of time intervals comparison with the full coupled simulation.
 Moreover, we carried out case studies using the conventional method and proposed method with two types of outside air flow rate, and verified the validity of this proposed method comparing the conventional method. The target office building of this investigation was located in Kitakyushu, Fukuoka, Japan. In that case study, the initial temperature distribution of underground and air tunnel system elements were set temperature distributions that based on the results of the one-dimensional heat conduction analysis at 24:00 on December 31. Time intervals in uncoupled simulation were an hour. Flow fields in the uncoupled simulations were obtained at a representative date and time in the summer or winter. The following results were obtained from the case study: 1) It was suggested that using an EAHE which outside air flow rate were 10,350 m³/h and 2,070 m³/h, annual sensible heat loads of outdoor air-conditioning units were reduced by 20.6 % and 38.8 %, respectively. 2) In all cases by the proposed method, the relative errors of an annual integrated pre-cooling and pre-heating quantity based on the results for the conventional method were under 3 %. 3) The required time for the annual prediction by full coupled simulation were about 50 days, in contrast, uncoupled simulation were able to carry out in 6 hour in all cases. Comparing the conventional method with the proposed method, computing times for the annual prediction were reduced by about 0.5 %.
 Accordingly, it was assumed that the proposed method has a practical use in terms of calculation times and precisions for estimating the annual thermal performance of EAHE in design phase.

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 The number of single households consisting of elderly people is increasing in Japan. We are conducting series of research on the “Biofied Building” that can control the living spaces suitable for each resident's needs. This system utilizes the algorithm learnt from living organisms with the help of small sensor agent robots. In this system, every information in living space is collected by the robots for the space control. The information about the resident's activity is one of the most important data for the “Biofied Building”. When we acquire the information on activities, we have to add tags on the data such as meaning of these activities. For this purpose, we proposed an activity recognition method for residents in living spaces.
 An activity is defined as an action done aimed at some target, and consists of several movements. A movement is a motion defined by the unit body form. In this study, we defined two types of activities, activities consisting of single movement and activities consisting of multiple movements. For example, the activity of “eating” consisting of multiple movements, such as; “holding chopsticks” and “catching food” etc., is classified into “Multiple type”. On the other hand, the activity of “standing up” consisting of a single movement of “standing up”, is classified into “Single type”. The activities in living space are thus categorized into two.
 In this study, we used Kinect for Windows by Microsoft to acquire the depth data. After the noise rejection, R transformation or variance, PCA, LDA, and k-means classification were applied to recognize the activities. Our proposed method has two phases, the activity categorization phase, and the activity recognition phase.
 The ten activities including the six “Single type” activities (“standing up”, “sitting down”, “crunching”, “standing up from crunching”, “picking up something” and “standing up from picking up something”), and the four “Multiple type” activities (“handling a smart phone”, “reading a book”, ”writing” and “eating”) were performed by eleven subjects.
 We proved that it was effective to categorize the activities into each activity type for activity recognition, because each activity type has own features. We had 100% of mean recognition rate of activity categorization. And we had better mean recognition rates of activity classification with the activity categorization than without it.
 After the activity categorization phase, the activity classification using R transformation and variance was applied. These two methods were used for transforming two dimensional depth data into one dimensional parameters. R transformation is often used for image analysis in several conventional methods. However, the R transformation for “Multiple type” activities was rarely referred. We applied both methods to “Multiple type” activities and found that they worked well. In addition, we examined the effect of variance for the transformation of two dimensional matrix. As “Multiple type” activities consist of continuous movements in limited space, we hypothesized that variance of several consecutive depth data may be able to detect the features of “Multiple type” activities.
 As the results, we got 91.4% of mean recognition rate of “Single type” activities in case of using R transformation. And we also got 77.3% of mean recognition rate of “Multiple type” activities in case of using variance. Although some improvement is needed, the proposed method showed a certain level of feasibility for practical applications.

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