829 resultados para Traditional building techniques


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Wood is a natural and traditional building material, as popular today as ever, and presents advantages. Physically, wood is strong and stiff, but compared with other materiais like steel is light and flexible. Wood material can absorb sound very effectively and it is a relatively good heat insulator. But dry wood does bum quite easily md produces a great deal ofheat energy. The main disadvantage is the high levei ofcombustion when exposed to fíre, where the point at which it catches fire is fi-om 200-400°C. After fu-e exposure, is need to determine if the charred wooden stmctures are safe for future use. Design methods require the use ofcomputer modelling to predict the fíre exposure and the capacity ofstructures to resist fhose action. Also, large or small scale experimental tests are necessary to calibrate and verify the numerical models. The thermal model is essential for wood stmctures exposed to fire, because predicts the charring rate as a fünction offire exposure. The charring rate calculation ofmost stmctural wood elements allows simple calculations, but is more complicated for situations where the fire exposure is non-standard and in wood elements protected with other materiais.

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Thesis (Ph.D.)--University of Washington, 2016-06

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Smallholder farmers in Africa practice traditional cropping techniques such as intercropping. Intercropping is thought to offer higher productivity and resource milisation than sole cropping. In this study, risk associated with maize-bean intercropping was evaluated by quantifying long-term yield in both intercropping and sole cropping in a semi-arid region of South Africa (Bloemfontein, Free State) with reference to rainfall variability. The crop simulation model was run with different cultural practices (planting date and plant density) for 52 summer crop growing seasons (1950/1951-2001/2002). Eighty-one scenarios, consisted of three levels of initial soil water, planting date, maize population, and bean population, were simulated. From the simulation outputs, the total land equivalent ratio (LER) was greater than one. The intercrop (equivalent to sole maize) had greater energy value (EV) than sole beans, and the intercrop (equivalent to sole beans) had greater monetary value (MV) than sole maize. From these results, it can be concluded that maize-bean intercropping is advantageous for this semi-arid region. Soil water at planting was the most important factor of all scenario factors, followed by planting date. Irrigation application at planting, November/December planting and high plant density of maize for EV and beans for MV can be one of the most effective cultural practices in the study region. With regard to rainfall variability, seasonal (October-April) rainfall positively affected EV and MV, but not LER. There was more intercrop production in La Nina years than in El Nino years. Thus, better cultural practices may be selected to maximize maize-bean intercrop yields for specific seasons in the semi-arid region based on the global seasonal outlook. (c) 2004 Elsevier B.V. All rights reserved.

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We present the first characterization of the mechanical properties of lysozyme films formed by self-assembly at the air-water interface using the Cambridge interfacial tensiometer (CIT), an apparatus capable of subjecting protein films to a much higher level of extensional strain than traditional dilatational techniques. CIT analysis, which is insensitive to surface pressure, provides a direct measure of the extensional stress-strain behavior of an interfacial film without the need to assume a mechanical model (e.g., viscoelastic), and without requiring difficult-to-test assumptions regarding low-strain material linearity. This testing method has revealed that the bulk solution pH from which assembly of an interfacial lysozyme film occurs influences the mechanical properties of the film more significantly than is suggested by the observed differences in elastic moduli or surface pressure. We have also identified a previously undescribed pH dependency in the effect of solution ionic strength on the mechanical strength of the lysozyme films formed at the air-water interface. Increasing solution ionic strength was found to increase lysozyme film strength when assembly occurred at pH 7, but it caused a decrease in film strength at pH 11, close to the pI of lysozyme. This result is discussed in terms of the significant contribution made to protein film strength by both electrostatic interactions and the hydrophobic effect. Washout experiments to remove protein from the bulk phase have shown that a small percentage of the interfacially adsorbed lysozyme molecules are reversibly adsorbed. Finally, the washout tests have probed the role played by additional adsorption to the fresh interface formed by the application of a large strain to the lysozyme film and have suggested the movement of reversibly bound lysozyme molecules from a subinterfacial layer to the interface.

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Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.

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Grid computing is an advanced technique for collaboratively solving complicated scientific problems using geographically and organisational dispersed computational, data storage and other recourses. Application of grid computing could provide significant benefits to all aspects of power system that involves using computers. Based on our previous research, this paper presents a novel grid computing approach for probabilistic small signal stability (PSSS) analysis in electric power systems with uncertainties. A prototype computing grid is successfully implemented in our research lab to carry out PSSS analysis on two benchmark systems. Comparing to traditional computing techniques, the gird computing has given better performances for PSSS analysis in terms of computing capacity, speed, accuracy and stability. In addition, a computing grid framework for power system analysis has been proposed based on the recent study.

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This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional costbased approach.

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This paper is based upon the findings of a CIMA research project into the way which corporate performance is affected by the performance measurement system adopted. It compares and contrasts the techniques in use in a sample of large companies that use a variety of techniques. We have classified these techniques into 3 types: • Value based management techniques • Stakeholder management techniquesTraditional accounting techniques. The analysis traces the interactions between corporate objectives, decision making criteria, performance measurement systems, and executive incentive schemes in order to develop an understanding of the effects of such techniques upon corporate performance. This paper seeks to provide some answers to the following two questions: • What approach leads to superior performance for a firm? • What is different between these approaches when they are used in practice, as distinct from theory? In doing so we have drawn upon both contingency theory and sociobiology theory to develop a framework for understanding the relationship between the choke of performance measurement system and the resulting performance.

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We discuss the application of beamforming techniques to the field of magnetoencephalography (MEG). We argue that beamformers have given us an insight into the dynamics of oscillatory changes across the cortex not explored previously with traditional analysis techniques that rely on averaged evoked responses. We review several experiments that have used beamformers, with special emphasis on those in which the results have been compared to those observed in functional magnetic resonance imaging (fMRI) and on those studying induced phenomena. We suggest that the success of the beamformer technique, despite the assumption that there are no linear interactions between the mesoscopic local field potentials across distinct cortical areas, may tell us something of the balance between functional integration and segregation in the human brain. What is more, MEG beamformer analysis facilitates the study of these complex interactions within cortical networks that are involved in both sensory-motor and cognitive processes. © 2005 Wiley-Liss, Inc.

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We develop a principal component approach to systematic liquidity measurement by introducing moving and expanding estimation windows. We evaluate these methods along with traditional estimation techniques (full sample PCA and market average) in terms of ability to explain (1) cross sectional stock liquidity and cross sectional stock returns. For several traditional liquidity measures our results suggest an expanding window specification for systematic liquidity estimation. The market average proxy of systematic liquidity produces the same degree of commonality, but does not have the same ability to explain stock returns as the PCA-estimates.

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This paper explores the use of the optimization procedures in SAS/OR software with application to the contemporary logistics distribution network design using an integrated multiple criteria decision making approach. Unlike the traditional optimization techniques, the proposed approach, combining analytic hierarchy process (AHP) and goal programming (GP), considers both quantitative and qualitative factors. In the integrated approach, AHP is used to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, a GP model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. To facilitate the use of integrated multiple criteria decision making approach by SAS users, an ORMCDM code was implemented in the SAS programming language. The SAS macro developed in this paper selects the chosen variables from a SAS data file and constructs sets of linear programming models based on the selected GP model. An example is given to illustrate how one could use the code to design the logistics distribution network.

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Short text messages a.k.a Microposts (e.g. Tweets) have proven to be an effective channel for revealing information about trends and events, ranging from those related to Disaster (e.g. hurricane Sandy) to those related to Violence (e.g. Egyptian revolution). Being informed about such events as they occur could be extremely important to authorities and emergency professionals by allowing such parties to immediately respond. In this work we study the problem of topic classification (TC) of Microposts, which aims to automatically classify short messages based on the subject(s) discussed in them. The accurate TC of Microposts however is a challenging task since the limited number of tokens in a post often implies a lack of sufficient contextual information. In order to provide contextual information to Microposts, we present and evaluate several graph structures surrounding concepts present in linked knowledge sources (KSs). Traditional TC techniques enrich the content of Microposts with features extracted only from the Microposts content. In contrast our approach relies on the generation of different weighted semantic meta-graphs extracted from linked KSs. We introduce a new semantic graph, called category meta-graph. This novel meta-graph provides a more fine grained categorisation of concepts providing a set of novel semantic features. Our findings show that such category meta-graph features effectively improve the performance of a topic classifier of Microposts. Furthermore our goal is also to understand which semantic feature contributes to the performance of a topic classifier. For this reason we propose an approach for automatic estimation of accuracy loss of a topic classifier on new, unseen Microposts. We introduce and evaluate novel topic similarity measures, which capture the similarity between the KS documents and Microposts at a conceptual level, considering the enriched representation of these documents. Extensive evaluation in the context of Emergency Response (ER) and Violence Detection (VD) revealed that our approach outperforms previous approaches using single KS without linked data and Twitter data only up to 31.4% in terms of F1 measure. Our main findings indicate that the new category graph contains useful information for TC and achieves comparable results to previously used semantic graphs. Furthermore our results also indicate that the accuracy of a topic classifier can be accurately predicted using the enhanced text representation, outperforming previous approaches considering content-based similarity measures. © 2014 Elsevier B.V. All rights reserved.

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A vállalatok jelentős része szembesül azzal, hogy termékei jelentős része iránt viszonylag kevés alkalommal jelentkezik kereslet. Ebből következik, hogy az ilyen termékekre a klasszikus előrejelzési módszerek, mint pl. a mozgó átlag számítása, vagy az exponenciális simítás nem alkalmazható. Azon termékeket, amelyek iránt viszonylag ritkán jelenik meg kereslet, sporadikus keresletű termékeknek nevezzük. A megkülönböztetés a sporadikus és nem sporadikus termékek között sokszor csak hüvelykujj szabály alapján állapítható meg, de erre vonatkozóan a szakirodalomban találunk iránymutatást. A nemzetközi szakirodalomban már megjelentek olyan új kereslet-előrejelzési módszerek, melyeket kimondottan az ilyen, sporadikus kereslettel rendelkező termékek estében javasoltak. Cikkünk célja, hogy ezeket a szakirodalmi ajánlásokat egy konkrét hazai vállalat valós adatain esettanulmány jelleggel tesztelje. A nemzetközi szakirodalomban is ritkán publikálnak tudományos dolgozatokat, amelyek ezt a témakört valós alkalmazási környezetben tárgyalják; ismereteink szerint magyar nyelven erről tudományos dolgozat pedig még nem született. Elméleti bevezetőnk után egy gyógyszer-nagykereskedelmi vállalatnál valós adatait használva vizsgáljuk a kérdéskört. Sor kerül a vállalat termékportfóliójának a kereslet-előrejelzés szempontjából történő tipizálására, majd sporadikus keresletű termékek keresletének előrejelzésére és ennek során a szakirodalomban az alkalmazandó módszerekre vonatkozó ajánlások vizsgálatára. _____ Significant numbers of companies have the problem that demand for their products are sporadic in nature. Demand of such products is not continual in time; its demand is diffused, is random with large proportion of zero values in the analyzed time series. The sporadic character of a demand pattern actually means that available information on the demand of previous selling periods is leaky resulting in lower quality of data available. In these cases traditional forecasting techniques do not result in reliable forecast. Special forecasting algorithms have been developed during the last decade dealing with this problem. The paper introduces these techniques and offers suggestions for application. It also presents the case study of a Hungarian pharmaceutical wholesaler company. Based on real data we develop a topology of the company's product portfolio, carry out forecasts using different techniques including those developed for products with sporadic demand and also analyze the quality of these forecasts.

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Wireless sensor networks are emerging as effective tools in the gathering and dissemination of data. They can be applied in many fields including health, environmental monitoring, home automation and the military. Like all other computing systems it is necessary to include security features, so that security sensitive data traversing the network is protected. However, traditional security techniques cannot be applied to wireless sensor networks. This is due to the constraints of battery power, memory, and the computational capacities of the miniature wireless sensor nodes. Therefore, to address this need, it becomes necessary to develop new lightweight security protocols. This dissertation focuses on designing a suite of lightweight trust-based security mechanisms and a cooperation enforcement protocol for wireless sensor networks. This dissertation presents a trust-based cluster head election mechanism used to elect new cluster heads. This solution prevents a major security breach against the routing protocol, namely, the election of malicious or compromised cluster heads. This dissertation also describes a location-aware, trust-based, compromise node detection, and isolation mechanism. Both of these mechanisms rely on the ability of a node to monitor its neighbors. Using neighbor monitoring techniques, the nodes are able to determine their neighbors’ reputation and trust level through probabilistic modeling. The mechanisms were designed to mitigate internal attacks within wireless sensor networks. The feasibility of the approach is demonstrated through extensive simulations. The dissertation also addresses non-cooperation problems in multi-user wireless sensor networks. A scalable lightweight enforcement algorithm using evolutionary game theory is also designed. The effectiveness of this cooperation enforcement algorithm is validated through mathematical analysis and simulation. This research has advanced the knowledge of wireless sensor network security and cooperation by developing new techniques based on mathematical models. By doing this, we have enabled others to build on our work towards the creation of highly trusted wireless sensor networks. This would facilitate its full utilization in many fields ranging from civilian to military applications.

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Interest in the health of marine mammals has increased due, in part, to the attention given to human impact on the marine environment. Recent mass strandings of the Atlantic bottlenose dolphin (Tursiops truncatus) and rising mortalities of the endangered Florida manatee (Trichechus manatus latirostris) have raised questions on the extent to which pollution, infectious disease, "stress," and captivity influence the immune system of these animals. This study has provided the first in-depth characterization of immunocytes in the peripheral blood of dolphins (n = 190) and manatees (n = 56). Immunocyte morphology and baseline values were determined in clinically normal animals under free-ranging, stranded and captive living conditions as well as by age and sex. Additionally, immunocyte population dynamics were characterized in sick animals. This was accomplished with traditional cytochemical techniques and new lymphocyte phenotyping methodology which was validated in this study. Traditional cytochemical techniques demonstrated that blood immunocyte morphology and cell numbers are similar to terrestrial mammals with some notable exceptions. The manatee heterophilic granulocyte is a morphologically unique cell and probably functions similarly to the typical mammalian neutrophil. Eosinophils were rarely found in manatees but were uncommonly high in healthy and sick dolphins. Basophils were not identified. Manatees had higher total lymphocyte numbers compared to dolphins and most terrestrial mammals. Lymphocyte subsets identified in healthy animals included T$\rm\sb{h}$, T$\rm\sb{c/s}$, B and NK cells. Dolphin and manatee T and B cell values were higher than those reported in man and most terrestrial mammals. The manatee has extraordinarily high absolute numbers of circulating T$\rm\sb{h}$ cells which suggests an enhanced immunological response capability. With few exceptions, immunocyte types and absolute numbers were not significantly different between free-ranging, stranded and captive categories or between sex and age categories. The evaluation of immunocyte dynamics in various disease states demonstrated a wide variation in cellular responses which provided new insights into innate, humoral and cell-mediated immunity in these species. Additionally, this study demonstrated that lymphocyte phenotyping has diagnostic significance and could be developed into a potential indicator of immunocompetence in both free-ranging and captive dolphin and manatee populations.