848 resultados para NonDestructive Evaluation, Compressive Sensing, Lamb waves, Structural Health Monitoring


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Following a drop in estrogen in the period of menopause some women begin to lose bone mass more than 1% per year reaching the end of five years with loss greater than 25%. In this regard, factors such as older age, low calcium intake and premature menopause favor the onset of osteoporosis. Preventive methods such as nutritional counseling to a proper diet and the support of technology through applications that assess dietary intake are essential. Thus, this study aimed to develop an application for Android® platform focused on the evaluation of nutritional and organic conditions involved in bone health and risks for developing osteoporosis in postmenopausal women. To achieve this goal we proceeded to a study of 72 women aged 46-79 years, from the physical exercise for bone health of the Laboratory for Research in Biochemistry and Densitometry the Federal Technological University of Paraná program. Data were collected in the second half of 2014 through tests Bone Densitometry and Body Composition, Blood Tests, Anthropometric data and Nutrition Assessment. The study included women with a current diagnosis of osteopenia or osteoporosis primary, aged more than 45 years postmenopausal. For the assessment of bone mineral density and body composition used the device Absorptiometry Dual Energy X-ray (DXA) brand Hologic Discovery TM Model A. For anthropometric assessment was included to body mass, height, abdominal circumference, Waist circumference and hip circumference. The instrument for assessing food consumption was used Recall 24 hours a day (24HR). The estimated intake of energy and nutrients was carried from the tabulation of the food eaten in the Software Diet Pro 4®. In a sub sample of 30 women with osteopenia / osteoporosis serum calcium and alkaline phosphatase tests were performed. The results demonstrated a group of women (n = 30) average calcium intake of 570mg / day (± 340). The analysis showed a mean serum calcium within the normal range (10,20mg / dl ± 0.32) and average values and slightly increased alkaline phosphatase (105.40 U / L ± 23.70). Furthermore, there was a significant correlation between the consumption of protein and the optimal daily intake of calcium (0.375 p-value 0.05). Based on these findings, we developed an application early stage in Android® platform operating system Google®, being called OsteoNutri. We chose to use Java Eclipse® where it was executed Android® version of the project; choice of application icons and setting the visual editor for building the application layouts. The DroidDraw® was used for development of the three application GUIs. For practical tests we used a cell compatible with the version that was created (4.4 or higher). The prototype was developed in conjunction with the Group and Instrumentation Applications Development (GDAI) of the Federal Technological University of Paraná. So this application can be considered an important tool in dietary control, allowing closer control consumption of calcium and dietary proteins.

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Tese (doutorado)—Universidade de Brasília, Instituto de Ciências Biológicas, Programa de Pós-Graduação em Biologia Molecular, 2015.

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O presente relatório diz respeito às atividades realizadas no âmbito de um estágio no Health Club Virgin Active Oeiras (VAO), com incidência sobre a importância da avaliação da aptidão física aos utentes. Este estágio decorreu ao longo do 2º ano de Mestrado em Exercício e Saúde da Faculdade de Motricidade Humana. Para além de uma descrição e reflexão sobre os métodos e procedimentos adotados no decorrer do estágio, este relatório tem como objetivo principal explorar questões relacionadas com a metodologia de avaliação física aos utentes neste clube de saúde, com vista à sua otimização. Perante isto, foram estudados os meios disponíveis para a operacionalização de um protocolo de avaliação que englobasse todas as componentes da aptidão física segundo as recomendações atuais, incluindo a vertente cardiorrespiratória que não era usualmente avaliada no clube. De forma a atingir os objetivos pretendidos, o processo de sensibilização da direção do Clube foi realizado através da avaliação da aptidão cardiorrespiratória a 100 utentes iniciantes. Esta abordagem mostrou que 47% dos utentes iniciantes possuía uma aptidão cardiorrespiratória abaixo do razoável. Uma vez que esta análise era limitada, tendo em conta a elevada população que frequenta o clube, foram ainda abordados 150 utentes não iniciantes, através de uma campanha denominada “coração saudável”, na qual constou incluiu um “vale” para a realização de uma avaliação da aptidão cardiorrespiratória e um questionário. Este questionário refletiu que aproximadamente 70% dos utentes nunca tinha sido sujeito a uma prova de esforço já tendo frequentado outros clubes de saúde. Outras abordagens aos utentes foram realizadas durante este processo, nomeadamente, a promoção de atividades de cariz cardiorrespiratório e a disponibilização e instrução quanto ao uso do cardio-frequêncimetro. Este relatório refletiu a necessidade de um clube de saúde diferenciar-se não só pelas infraestruturas e atividades oferecidas, mas também pela informação e educação dos utentes relativamente à aptidão física relacionada com a saúde e ao impacto do exercício físico na qualidade de vida de quem o pratica.

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Hazardous materials are substances that, if not regulated, can pose a threat to human populations and their environmental health, safety or property when transported in commerce. About 1.5 million tons of hazardous material shipments are transported by truck in the US annually, with a steady increase of approximately 5% per year. The objective of this study was to develop a routing tool for hazardous material transport in order to facilitate reduced environmental impacts and less transportation difficulties, yet would also find paths that were still compelling for the shipping carriers as a matter of trucking cost. The study started with identification of inhalation hazard impact zones and explosion protective areas around the location of hypothetical hazardous material releases, considering different parameters (i.e., chemicals characteristics, release quantities, atmospheric condition, etc.). Results showed that depending on the quantity of release, chemical, and atmospheric stability (a function of wind speed, meteorology, sky cover, time and location of accidents, etc.) the consequence of these incidents can differ. The study was extended by selection of other evaluation criteria for further investigation because health risk as an evaluation criterion would not be the only concern in selection of routes. Transportation difficulties (i.e., road blockage and congestion) were incorporated as important factor due to their indirect impact/cost on the users of transportation networks. Trucking costs were also considered as one of the primary criteria in selection of hazardous material paths; otherwise the suggested routes would have not been convincing for the shipping companies. The last but not least criterion was proximity of public places to the routes. The approach evolved from a simple framework to a complicated and efficient GIS-based tool able to investigate transportation networks of any given study area, and capable of generating best routing options for cargos. The suggested tool uses a multi-criteria-decision-making method, which considers the priorities of the decision makers in choosing the cargo routes. Comparison of the routing options based on each criterion and also the overall suitableness of the path in regards to all the criteria (using a multi-criteria-decision-making method) showed that using similar tools as the one proposed by this study can provide decision makers insights in the area of hazardous material transport. This tool shows the probable consequences of considering each path in a very easily understandable way; in the formats of maps and tables, which makes the tradeoffs of costs and risks considerably simpler, as in some cases slightly compromising on trucking cost may drastically decrease the probable health risk and/or traffic difficulties. This will not only be rewarding to the community by making cities safer places to live, but also can be beneficial to shipping companies by allowing them to advertise as environmental friendly conveyors.

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The objectives of this study are to investigate the association between cardiorespiratory fitness and cardiovascular risk factors in schoolchildren and to evaluate the degree of association between overall and abdominal adiposity and cardiorespiratory fitness. A total of 1,875 children and adolescents attending public schools in Bogota, Colombia (56.2% girls; age range of 9–17.9 years). A cardiovascular risk score (Z-score) was calculated and participants were divided into tertiles according to low and high levels of overall (sum of the skinfold thicknesses) and abdominal adiposity. Schoolchildren with a high level of overall adiposity demonstrated significant differences in seven of the 10 variables analyzed (i.e. systolic and diastolic blood pressure, triglycerides, triglycerides/HDL-c ratio, total cholesterol, glucose and cardiovascular risk score). Schoolchildren with high levels of both overall and abdominal adiposity and low cardiorespiratory fitness had the least favorable cardiovascular risk factors score. These findings may be relevant to health promotion in Colombian youth.

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Wearable electronic textiles are an emerging research field playing a pivotal role among several different technological areas such as sensing, communication, clothing, health monitoring, information technology, and microsystems. The possibility to realise a fully-textile platform, endowed with various sensors directly realised with textile fibres and fabric, represents a new challenge for the entire research community. Among several high-performing materials, the intrinsically conductive poly(3,4-ethylenedioxythiophene) (PEDOT), doped with poly(styrenesulfonic acid) (PSS), or PEDOT:PSS, is one of the most representative and utilised, having an excellent chemical and thermal stability, as well as reversible doping state and high conductivity. This work relies on PEDOT:PSS combined with sensible materials to design, realise, and develop textile chemical and physical sensors. In particular, chloride concentration and pH level sensors in human sweat for continuous monitoring of the wearer's hydration status and stress level are reported. Additionally, a prototype smart bandage detecting the moisture level and pH value of a bed wound to allow the remote monitoring of the healing process of severe and chronic wounds is described. Physical sensors used to monitor the pressure distribution for rehabilitation, workplace safety, or sport tracking are also presented together with a novel fully-textile device able to measure the incident X-ray dose for medical or security applications where thin, comfortable, and flexible features are essential. Finally, a proof-of-concept for an organic-inorganic textile thermoelectric generator that harvests energy directly from body heat has been proposed. Though further efforts must be dedicated to overcome issues such as durability, washability, power consumption, and large-scale production, the novel, versatile, and widely encompassing area of electronic textiles is a promising protagonist in the upcoming technological revolution.

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Imaging technologies are widely used in application fields such as natural sciences, engineering, medicine, and life sciences. A broad class of imaging problems reduces to solve ill-posed inverse problems (IPs). Traditional strategies to solve these ill-posed IPs rely on variational regularization methods, which are based on minimization of suitable energies, and make use of knowledge about the image formation model (forward operator) and prior knowledge on the solution, but lack in incorporating knowledge directly from data. On the other hand, the more recent learned approaches can easily learn the intricate statistics of images depending on a large set of data, but do not have a systematic method for incorporating prior knowledge about the image formation model. The main purpose of this thesis is to discuss data-driven image reconstruction methods which combine the benefits of these two different reconstruction strategies for the solution of highly nonlinear ill-posed inverse problems. Mathematical formulation and numerical approaches for image IPs, including linear as well as strongly nonlinear problems are described. More specifically we address the Electrical impedance Tomography (EIT) reconstruction problem by unrolling the regularized Gauss-Newton method and integrating the regularization learned by a data-adaptive neural network. Furthermore we investigate the solution of non-linear ill-posed IPs introducing a deep-PnP framework that integrates the graph convolutional denoiser into the proximal Gauss-Newton method with a practical application to the EIT, a recently introduced promising imaging technique. Efficient algorithms are then applied to the solution of the limited electrods problem in EIT, combining compressive sensing techniques and deep learning strategies. Finally, a transformer-based neural network architecture is adapted to restore the noisy solution of the Computed Tomography problem recovered using the filtered back-projection method.

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The incidence of sudden unexpected death in epilepsy (SUDEP) has been estimated from 0.5-1.4/1,000 person-years in people with treated epilepsy, and 9/1,000 person-years in candidates for epilepsy surgery. Potential risk factors for SUDEP include: age, early onset of epilepsy, duration of epilepsy, uncontrolled seizures, seizure type and winter temperatures. The arrythmogenic side-effect of antiepileptic drugs and seizures may increase the risk of SUDEP. In this report, we describe a patient with prolonged post-ictal tachycardia in EEG video recordings with a typical case of SUDEP: a 16-year-old boy with medically intractable complex partial seizures. Magnetic resonance imaging revealed left mesial temporal sclerosis. During non-invasive video-EEG monitoring, the patient presented a post-ictal heart rate increased for five hours. Two months after video-EEG, he died from SUDEP during a tonic-clonic secondary generalized seizure. The possibility of cardiac involvement in the pathogenesis of SUDEP has been suggested by many studies. Evaluation of this patient with EEG-video monitoring, including measurement of heart rate, contributed to an identification of ictal tachycardia that may have played a role in the SUDEP. Premature mortality seems to be increased in patients with epilepsy, and cardiac abnormalities may be a possible cause of SUDEP. (Cardiol J 2011; 18, 2: 194-196)

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This paper presents experimental results of the communication performance evaluation of a prototype ZigBee-based patient monitoring system commissioned in an in-patient floor of a Portuguese hospital (HPG – Hospital Privado de Guimar~aes). Besides, it revisits relevant problems that affect the performance of nonbeacon-enabled ZigBee networks. Initially, the presence of hidden-nodes and the impact of sensor node mobility are discussed. It was observed, for instance, that the message delivery ratio in a star network consisting of six wireless electrocardiogram sensor devices may decrease from 100% when no hidden-nodes are present to 83.96% when half of the sensor devices are unable to detect the transmissions made by the other half. An additional aspect which affects the communication reliability is a deadlock condition that can occur if routers are unable to process incoming packets during the backoff part of the CSMA-CA mechanism. A simple approach to increase the message delivery ratio in this case is proposed and its effectiveness is verified. The discussion and results presented in this paper aim to contribute to the design of efficient networks,and are valid to other scenarios and environments rather than hospitals.

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Operational Modal Analysis is currently applied in structural dynamic monitoring studies using conventional wired based sensors and data acquisition platforms. This approach, however, becomes inadequate in cases where the tests are performed in ancient structures with esthetic concerns or in others, where the use of wires greatly impacts the monitoring system cost and creates difficulties in the maintenance and deployment of data acquisition platforms. In these cases, the use of sensor platforms based on wireless and MEMS would clearly benefit these applications. This work presents a first attempt to apply this wireless technology to the structural monitoring of historical masonry constructions in the context of operational modal analysis. Commercial WSN platforms were used to study one laboratory specimen and one of the structural elements of a XV century building in Portugal. Results showed that in comparison to the conventional wired sensors, wireless platforms have poor performance in respect to the acceleration time series recorded and the detection of modal shapes. However, for frequency detection issues, reliable results were obtained, especially when random excitation was used as noise source.

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Wireless sensor network (WSN) applications such as patients’ health monitoring in hospitals, location-aware ambient intelligence, industrial monitoring /maintenance or homeland security require the support of mobile nodes or node groups. In many of these applications, the lack of network connectivity is not admissible or should at least be time bounded, i.e. mobile nodes cannot be disconnected from the rest of the WSN for an undefined period of time. In this context, we aim at reliable and real-time mobility support in WSNs, for which appropriate handoff and rerouting decisions are mandatory. This paper1 drafts a mechanism and correspondent heuristics for taking reliable handoff decisions in WSNs. Fuzzy logic is used to incorporate the inherent imprecision and uncertainty of the physical quantities at stake.

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Wireless Body Area Network (WBAN) is the most convenient, cost-effective, accurate, and non-invasive technology for e-health monitoring. The performance of WBAN may be disturbed when coexisting with other wireless networks. Accordingly, this paper provides a comprehensive study and in-depth analysis of coexistence issues and interference mitigation solutions in WBAN technologies. A thorough survey of state-of-the art research in WBAN coexistence issues is conducted. The survey classified, discussed, and compared the studies according to the parameters used to analyze the coexistence problem. Solutions suggested by the studies are then classified according to the followed techniques and concomitant shortcomings are identified. Moreover, the coexistence problem in WBAN technologies is mathematically analyzed and formulas are derived for the probability of successful channel access for different wireless technologies with the coexistence of an interfering network. Finally, extensive simulations are conducted using OPNET with several real-life scenarios to evaluate the impact of coexistence interference on different WBAN technologies. In particular, three main WBAN wireless technologies are considered: IEEE 802.15.6, IEEE 802.15.4, and low-power WiFi. The mathematical analysis and the simulation results are discussed and the impact of interfering network on the different wireless technologies is compared and analyzed. The results show that an interfering network (e.g., standard WiFi) has an impact on the performance of WBAN and may disrupt its operation. In addition, using low-power WiFi for WBANs is investigated and proved to be a feasible option compared to other wireless technologies.

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Wireless Body Area Networks (WBANs) have emerged as a promising technology for medical and non-medical applications. WBANs consist of a number of miniaturized, portable, and autonomous sensor nodes that are used for long-term health monitoring of patients. These sensor nodes continuously collect information of patients, which are used for ubiquitous health monitoring. In addition, WBANs may be used for managing catastrophic events and increasing the effectiveness and performance of rescue forces. The huge amount of data collected by WBAN nodes demands scalable, on-demand, powerful, and secure storage and processing infrastructure. Cloud computing is expected to play a significant role in achieving the aforementioned objectives. The cloud computing environment links different devices ranging from miniaturized sensor nodes to high-performance supercomputers for delivering people-centric and context-centric services to the individuals and industries. The possible integration of WBANs with cloud computing (WBAN-cloud) will introduce viable and hybrid platform that must be able to process the huge amount of data collected from multiple WBANs. This WBAN-cloud will enable users (including physicians and nurses) to globally access the processing and storage infrastructure at competitive costs. Because WBANs forward useful and life-critical information to the cloud – which may operate in distributed and hostile environments, novel security mechanisms are required to prevent malicious interactions to the storage infrastructure. Both the cloud providers and the users must take strong security measures to protect the storage infrastructure.

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During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.