975 resultados para Real Building Fires


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Designing is a heterogeneous, fuzzily defined, floating field of various activities and chunks of ideas and knowledge. Available theories about the foundations of designing as presented in "the basic PARADOX" (Jonas and Meyer-Veden 2004) have evoked the impression of Babylonian confusion. We located the reasons for this "mess" in the "non-fit", which is the problematic relation of theories and subject field. There seems to be a comparable interface problem in theory-building as in designing itself. "Complexity" sounds promising, but turns out to be a problematic and not really helpful concept. I will argue for a more precise application of systemic and evolutionary concepts instead, which - in my view - are able to model the underlying generative structures and processes that produce the visible phenomenon of complexity. It does not make sense to introduce a new fashionable meta-concept and to hope for a panacea before having clarified the more basic and still equally problematic older meta-concepts. This paper will take one step away from "theories of what" towards practice and doing and try to have a closer look at existing process models or "theories of how" to design instead. Doing this from a systemic perspective leads to an evolutionary view of the process, which finally allows to specify more clearly the "knowledge gaps" inherent in the design process. This aspect has to be taken into account as constitutive of any attempt at theory-building in design, which can be characterized as a "practice of not-knowing". I conclude, that comprehensive "unified" theories, or methods, or process models run aground on the identified knowledge gaps, which allow neither reliable models of the present, nor reliable projections into the future. Consolation may be found in performing a shift from the effort of adaptation towards strategies of exaptation, which means the development of stocks of alternatives for coping with unpredictable situations in the future.

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Most Artificial Intelligence (AI) work can be characterized as either ``high-level'' (e.g., logical, symbolic) or ``low-level'' (e.g., connectionist networks, behavior-based robotics). Each approach suffers from particular drawbacks. High-level AI uses abstractions that often have no relation to the way real, biological brains work. Low-level AI, on the other hand, tends to lack the powerful abstractions that are needed to express complex structures and relationships. I have tried to combine the best features of both approaches, by building a set of programming abstractions defined in terms of simple, biologically plausible components. At the ``ground level'', I define a primitive, perceptron-like computational unit. I then show how more abstract computational units may be implemented in terms of the primitive units, and show the utility of the abstract units in sample networks. The new units make it possible to build networks using concepts such as long-term memories, short-term memories, and frames. As a demonstration of these abstractions, I have implemented a simulator for ``creatures'' controlled by a network of abstract units. The creatures exist in a simple 2D world, and exhibit behaviors such as catching mobile prey and sorting colored blocks into matching boxes. This program demonstrates that it is possible to build systems that can interact effectively with a dynamic physical environment, yet use symbolic representations to control aspects of their behavior.

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Fueled by ever-growing genomic information and rapid developments of proteomics–the large scale analysis of proteins and mapping its functional role has become one of the most important disciplines for characterizing complex cell function. For building functional linkages between the biomolecules, and for providing insight into the mechanisms of biological processes, last decade witnessed the exploration of combinatorial and chip technology for the detection of bimolecules in a high throughput and spatially addressable fashion. Among the various techniques developed, the protein chip technology has been rapid. Recently we demonstrated a new platform called “Spacially addressable protein array” (SAPA) to profile the ligand receptor interactions. To optimize the platform, the present study investigated various parameters such as the surface chemistry and role of additives for achieving high density and high-throughput detection with minimal nonspecific protein adsorption. In summary the present poster will address some of the critical challenges in protein micro array technology and the process of fine tuning to achieve the optimum system for solving real biological problems.

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Real-time geoparsing of social media streams (e.g. Twitter, YouTube, Instagram, Flickr, FourSquare) is providing a new 'virtual sensor' capability to end users such as emergency response agencies (e.g. Tsunami early warning centres, Civil protection authorities) and news agencies (e.g. Deutsche Welle, BBC News). Challenges in this area include scaling up natural language processing (NLP) and information retrieval (IR) approaches to handle real-time traffic volumes, reducing false positives, creating real-time infographic displays useful for effective decision support and providing support for trust and credibility analysis using geosemantics. I will present in this seminar on-going work by the IT Innovation Centre over the last 4 years (TRIDEC and REVEAL FP7 projects) in building such systems, and highlights our research towards improving trustworthy and credible of crisis map displays and real-time analytics for trending topics and influential social networks during major news worthy events.

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Salvage logging is a common practice carried out in burned forests worldwide, and intended to mitigate the economic losses caused by wildfires. Logging implies an additional disturbance occurring shortly after fire, although its ecological effects can be somewhat mitigated by leaving wood debris on site. The composition of the bird community and its capacity to provide ecosystem services such as seed dispersal of fleshy-fruited plants have been shown to be affected by postfire logging. We assessed the effects of the habitat structure resulting from different postfire management practices on the bird community, in three burned pine forests in Catalonia (western Mediterranean). For this purpose, we focused on the group of species that is responsible for seed dispersal, a process which takes place primarily during the winter in the Mediterranean basin. In addition, we assessed microhabitat selection by seed disperser birds in such environments in relation to management practices. Our results showed a significant, positive relationship between the density of wood debris piles and the abundance of seed disperser birds. Furthermore, such piles were the preferred microhabitat of these species. This reveals an important effect of forest management on seed disperser birds, which is likely to affect the dynamics of bird-dependent seed dispersal. Thus, building wood debris piles can be a useful practice for the conservation of both the species and their ecosystem services, while also being compatible with timber harvesting

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The classical computer vision methods can only weakly emulate some of the multi-level parallelisms in signal processing and information sharing that takes place in different parts of the primates’ visual system thus enabling it to accomplish many diverse functions of visual perception. One of the main functions of the primates’ vision is to detect and recognise objects in natural scenes despite all the linear and non-linear variations of the objects and their environment. The superior performance of the primates’ visual system compared to what machine vision systems have been able to achieve to date, motivates scientists and researchers to further explore this area in pursuit of more efficient vision systems inspired by natural models. In this paper building blocks for a hierarchical efficient object recognition model are proposed. Incorporating the attention-based processing would lead to a system that will process the visual data in a non-linear way focusing only on the regions of interest and hence reducing the time to achieve real-time performance. Further, it is suggested to modify the visual cortex model for recognizing objects by adding non-linearities in the ventral path consistent with earlier discoveries as reported by researchers in the neuro-physiology of vision.

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This paper presents a multicriteria decision-making model for lifespan energy efficiency assessment of intelligent buildings (IBs). The decision-making model called IBAssessor is developed using an analytic network process (ANP) method and a set of lifespan performance indicators for IBs selected by a new quantitative approach called energy-time consumption index (ETI). In order to improve the quality of decision-making, the authors of this paper make use of previous research achievements including a lifespan sustainable business model, the Asian IB Index, and a number of relevant publications. Practitioners can use the IBAssessor ANP model at different stages of an IB lifespan for either engineering or business oriented assessments. Finally, this paper presents an experimental case study to demonstrate how to use IBAssessor ANP model to solve real-world design tasks.

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While building provides shelter for human being, the previous models for assessing the intelligence of a building seldom consider the responses of occupants. In addition, the assessment is usually conducted by an authority organization on a yearly basis, thus can seldom provide timely assistance for facility manager to improve his daily facility maintenance performance. By the extending the law of entropy into the area of intelligent building, this paper demonstrate that both energy consumption and the response of occupants are important when partially assessing the intelligence of a building. This study then develops a sensor based real time building intelligence (BI) assessment model. An experimental case study demonstrates how the model can be implemented. The developed model can address the two demerits of the previous BI assessment model.

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A combined windcatcher and light pipe (SunCatcher) was installed in the seminar room at the University of Reading, UK. Monitoring of indoor environment in real weather conditions was conducted to evaluate the application of windcatchers for natural ventilation. In addition, a subjective occupancy survey was undertaken. External weather conditions and internal indoor air quality indicators were recorded. The “tracer-gas decay” method using SF6 was used to establish air change rate for various conditions. The results indicated that the ventilation rate achieved through the windcatcher depends on the difference between internal and external air temperatures, and on wind speed and direction, in agreement with other published work in the area. The indoor air quality parameters were found to be within acceptable levels when the windcatcher was in operation. The measured air change rate was between 1.5ac/h and 6.8ac/h. Occupants’ questionnaires showed 75 per cent satisfaction with the internal conditions and welcomed the installation of the systems in UK buildings.

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Mirror lightpipes are useful for providing healthy and energy-efficient daylight into buildings where windows and skylights are unsuitable, insufficient or generate too much heat gain. The lightpipes have been installed in dozens of buildings in the UK. Field monitoring has been carried out to assess their performance in four different buildings: the headquaters of a major insurance company, a health clinic, a residential building and a college dining hall In those cases where lighipipes with moderate aspect ratios were installed, good illuminance of up to 450 lux has been obtained with internal/external illuminance ratios around 1%. When long and narrow lightpipes with many bends are used, however, the ratio reduced to around 0.1%. These results showed that lightpipes can be effective daylighting devices provided that excessive aspect ratios and numbers of bends are avoided. Lightpipes with larger diameters should be used whenever possible. The lightpipes often improved signiScantly the visual quality af the interior environment, and high user satisfaction was found even in buildings where a relatively low level of daylight was admitted through the lightpipes

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This paper investigates the effect of voluntary eco-certification on the rental and sale prices of US commercial office properties. Hedonic and logistic regressions are used to test whether there are rental and sale price premiums for LEED and Energy Star certified buildings. The results of the hedonic analysis suggest that there is a rental premium of approximately 6% for LEED and Energy Star certification. A sale price premium of approximately 35% was found for 127 price observations involving LEED rated buildings and 31% for 662 buildings involving Energy Star rated buildings. When compared to samples of similar buildings identified by a binomial logistic regression for LEED-certified buildings, the existence of a rent and sales price premium is confirmed albeit with differences regarding the magnitude of the premium. Overall, the results of this study confirm that LEED and Energy Star buildings exhibit higher rental rates and sales prices per square foot controlling for a large number of location- and property-specific factors.

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This paper investigates whether obtaining sustainable building certification entails a rental premium for commercial office buildings and tracks its development over time. To this aim, both a difference-in-differences and a fixed-effects model approach are applied to a large panel dataset of office buildings in the United States in the 2000–2010 period. The results indicate a significant rental premium for both ENERGY STAR and LEED certified buildings. Controlling for confounding factors, this premium is shown to have increased steadily from 2006 to 2008, followed by a moderate decline in the subsequent periods. The results also show a significant positive relationship between ENERGY STAR labeling and building occupancy rates.

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The peak congestion of the European grid may create significant impacts on system costs because of the need for higher marginal cost generation, higher cost system balancing and increasing grid reinforcement investment. The use of time of use rates, incentives, real time pricing and other programmes, usually defined as Demand Side Management (DSM), could bring about significant reductions in prices, limit carbon emissions from dirty power plants, and improve the integration of renewable sources of energy. Unlike previous studies on elasticity of residential electricity demand under flat tariffs, the aim of this study is not to investigate the known relatively inelastic relationship between demand and prices. Rather, the aim is to assess how occupancy levels vary in different European countries. This reflects the reality of demand loads, which are predominantly determined by the timing of human activities (e.g. travelling to work, taking children to school) rather than prices. To this end, two types of occupancy elasticity are estimated: baseline occupancy elasticity and peak occupancy elasticity. These represent the intrinsic elasticity associated with human activities of single residential end-users in 15 European countries. This study makes use of occupancy time-series data from the Harmonised European Time Use Survey database to build European occupancy curves; identify peak occupancy periods; draw time use demand curves for video and TV watching activity; and estimate national occupancy elasticity levels of single-occupant households. Findings on occupancy elasticities provide an indication of possible DSM strategies based on occupancy levels and not prices.