25 resultados para ADAPTIVE SUPPORT VENTILATION

em Universidade do Minho


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The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

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Nowadays natural ventilation has gained prominence because its correct use can reduce energy consumption for cooling systems and improve thermal comfort among users. In this paper, we report on the modelling initiative, based on the wind tunnel tests that were carried out for the determination of the influence of natural ventilation in buildings. Indeed, the renewal of air in a closed environment without using an air conditioning system with mechanical elements can lead to energy savings and, in addition, provide air quality.The wind tunnel tests were carried out by varying the positioning of six ventilation modules in the façade system configuration. The modules were positioned below the window-sill (ventilated window-sill) as well as separately above and below the façade. The wind speed measurements were taken inside and outside the model for the different façades configurations to evaluate the best performance in relation to natural ventilation. The results supported the positioning of the six ventilation modules below the window-sill, forming a â ventilated window-sillâ as the most effective natural ventilation solution.

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The data acquisition process in real-time is fundamental to provide appropriate services and improve health professionals decision. In this paper a pervasive adaptive data acquisition architecture of medical devices (e.g. vital signs, ventilators and sensors) is presented. The architecture was deployed in a real context in an Intensive Care Unit. It is providing clinical data in real-time to the INTCare system. The gateway is composed by several agents able to collect a set of patients’ variables (vital signs, ventilation) across the network. The paper shows as example the ventilation acquisition process. The clients are installed in a machine near the patient bed. Then they are connected to the ventilators and the data monitored is sent to a multithreading server which using Health Level Seven protocols records the data in the database. The agents associated to gateway are able to collect, analyse, interpret and store the data in the repository. This gateway is composed by a fault tolerant system that ensures a data store in the database even if the agents are disconnected. The gateway is pervasive, universal, and interoperable and it is able to adapt to any service using streaming data.

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The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.

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The assessment of concrete mechanical properties during construction of concrete structures is of paramount importance for many intrinsic operations. However many of the available non-destructive methods for mechanical properties have limitations for use in construction sites. One of such methodologies is EMM-ARM, which is a variant of classic resonant frequency methods. This paper aims to demonstrate the efforts towards in-situ applicability of EMMARM, as to provide real-time information about concrete mechanical properties such as E-modulus and compressive strength. To achieve the aforementioned objective, a set of adaptations to the method have been successfully implemented and tested: (i) the reduction of the beam span; (ii) the use of a different mould material and (iii) a new support system for the beams. Based on these adaptations, a reusable mould was designed to enable easier systematic use of EMMARM. A pilot test was successfully performed under in-situ conditions during a bridge construction.

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The selective collection of municipal solid waste for recycling is a very complex and expensive process, where a major issue is to perform cost-efficient waste collection routes. Despite the abundance of commercially available software for fleet management, they often lack the capability to deal properly with sequencing problems and dynamic revision of plans and schedules during process execution. Our approach to achieve better solutions for the waste collection process is to model it as a vehicle routing problem, more specifically as a team orienteering problem where capacity constraints on the vehicles are considered, as well as time windows for the waste collection points and for the vehicles. The final model is called capacitated team orienteering problem with double time windows (CTOPdTW).We developed a genetic algorithm to solve routing problems in waste collection modelled as a CTOPdTW. The results achieved suggest possible reductions of logistic costs in selective waste collection.

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It is a difficult task to avoid the “smart systems” topic when discussing smart prevention and, similarly, it is a difficult task to address smart systems without focusing their ability to learn. Following the same line of thought, in the current reality, it seems a Herculean task (or an irreparable omission) to approach the topic of certified occupational health and safety management systems (OHSMS) without discussing the integrated management systems (IMSs). The available data suggest that seldom are the OHSMS operating as the single management system (MS) in a company so, any statement concerning OHSMS should mainly be interpreted from an integrated perspective. A major distinction between generic systems can be drawn between those that learn, i.e., those systems that have “memory” and those that have not. These former systems are often depicted as adaptive since they take into account past events to deal with novel, similar and future events modifying their structure to enable success in its environment. Often, these systems, present a nonlinear behavior and a huge uncertainty related to the forecasting of some events. This paper seeks to portray, for the first time as we were able to find out, the IMSs as complex adaptive systems (CASs) by listing their properties and dissecting the features that enable them to evolve and self-organize in order to, holistically, fulfil the requirements from different stakeholders and thus thrive by assuring the successful sustainability of a company. Based on the revision of literature carried out, this is the first time that IMSs are pointed out as CASs which may develop fruitful synergies both for the MSs and for CASs communities. By performing a thorough revision of literature and based on some concepts embedded in the “DNA” of the subsystems implementation standards it is intended, specifically, to identify, determine and discuss the properties of a generic IMS that should be considered to classify it as a CAS.

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In order to create safer schools, the Chilean authorities published a Standard regarding school furniture dimensions. The aims of this study are twofold: to verify the existence of positive secular trend within the Chilean student population and to evaluate the potential mismatch between the anthropometric characteristics and the school furniture dimensions defined by the mentioned standard. The sample consists of 3078 subjects. Eight anthropometric measures were gathered, together with six furniture dimensions from the mentioned standard. There is an average increase for some dimensions within the Chilean student population over the past two decades. Accordingly, almost 18% of the students will find the seat height to be too high. Seat depth will be considered as being too shallow for 42.8% of the students. It can be concluded that the Chilean student population has increased in stature, which supports the need to revise and update the data from the mentioned Standard. Practitioner Summary: Positive secular trend resulted in high levels of mismatch if furniture is selected according to the current Chilean Standard which uses data collected more than 20 years ago. This study shows that school furniture standards need to be updated over time.

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"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

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Due to the increasing acceptance of BPM, nowadays BPM tools are extensively used in organizations. Core to BPM are the process modeling languages, of which BPMN is the one that has been receiving most attention these days. Once a business process is described using BPMN, one can use a process simulation approach in order to find its optimized form. In this context, the simulation of business processes, such as those defined in BPMN, appears as an obvious way of improving processes. This paper analyzes the business process modeling and simulation areas, identifying the elements that must be present in the BPMN language in order to allow processes described in BPMN to be simulated. During this analysis a set of existing BPM tools, which support BPMN, are compared regarding their limitations in terms of simulation support.

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Archeology and related areas have a special interest on cultural heritage sites since they provide valuable information about past civilizations. However, the ancient buildings present in these sites are commonly found in an advanced state of degradation which difficult the professional/expert analysis. Virtual reconstructions of such buildings aim to provide a digital insight of how these historical places could have been in ancient times. Moreover, the visualization of such models has been explored by some Augmented Reality (AR) systems capable of providing support to experts. Their compelling and appealing environments have also been applied to promote the social and cultural participation of general public. The existing AR solutions regarding this thematic rarely explore the potential of realism, due to the following lacks: the exploration of mixed environments is usually only supported for indoors or outdoors, not both in the same system; the adaptation of the illumination conditions to the reconstructed structures is rarely addressed causing a decrease of credibility. MixAR [1] is a system concerned with those challenges, aiming to provide the visualization of virtual buildings augmented upon real ruins, allowing soft transitions among its interiors and exteriors and using relighting techniques for a faithful interior illumination, while the user freely moves in a given cultural heritage site, carrying a mobile unit. Regarding the focus of this paper, we intend to report the current state of MixAR mobile unit prototype, which allows visualizing virtual buildings – properly aligned with real-world structures – based on user's location, during outdoor navigation. In order to evaluate the prototype performance, a set of tests were made using virtual models with different complexities.

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Barotrauma is identified as one of the leading diseases in Ventilated Patients. This type of problem is most common in the Intensive Care Units. In order to prevent this problem the use of Data Mining (DM) can be useful for predicting their occurrence. The main goal is to predict the occurence of Barotrauma in order to support the health professionals taking necessary precautions. In a first step intensivists identified the Plateau Pressure values as a possible cause of Barotrauma. Through this study DM models (classification) where induced for predicting the Plateau Pressure class (>=30 cm

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The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the “Bois de Peu” tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.

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Wind tunnel tests are a reliable tool to determine the effect of natural ventilation on buildings. This paper presents results of wind tunnel tests conducted to evaluate the influence of ventilation modules positioning on a façade system. Modules positioning was modified, resulting in different façade configurations. The tests were carried out with the use of a model, varying the position of the ventilation modules in the façade configuration. The cases tested were six ventilation modules positioned below the window-sill (ventilated window-sill), and three ventilation modules positioned above and below the façade. The façade system proposed was movable and interchangeable so that the same basic model could be used to test the possibilities for ventilation. Wind speed measurements were taken inside and outside the model for the different façades configurations to evaluate the best performance in relation to natural ventilation. Singleâ sided and Cross ventilation were considered for wind speed measurements. Results show the use of six ventilation modules positioned below the window-sill, forming "a ventilated window-sill" is the best solution in terms of natural ventilation.