857 resultados para clustering and QoS-aware routing
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In the present paper we compare clustering solutions using indices of paired agreement. We propose a new method - IADJUST - to correct indices of paired agreement, excluding agreement by chance. This new method overcomes previous limitations known in the literature as it permits the correction of any index. We illustrate its use in external clustering validation, to measure the accordance between clusters and an a priori known structure. The adjusted indices are intended to provide a realistic measure of clustering performance that excludes agreement by chance with ground truth. We use simulated data sets, under a range of scenarios - considering diverse numbers of clusters, clusters overlaps and balances - to discuss the pertinence and the precision of our proposal. Precision is established based on comparisons with the analytical approach for correction specific indices that can be corrected in this way are used for this purpose. The pertinence of the proposed correction is discussed when making a detailed comparison between the performance of two classical clustering approaches, namely Expectation-Maximization (EM) and K-Means (KM) algorithms. Eight indices of paired agreement are studied and new corrected indices are obtained.
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The authors report the clinical, laboratorial and epidemiological aspects of a human case of jungle yellow fever. The patient suffered from fever, chills, sweating, headaches, backaches, myalgia, epigastric pains, nausea, vomiting, diarrhea and prostration. He was unvaccinated and had been working in areas where cases of jungle yellow fever had been confirmed. Investigations concerning the yellow fever virus were performed. Blood samples were collected on several days in the course of the illness. Three of these samples (those obtained on days 5,7 and 10) were inoculated into suckling mice in attempt to isolate virus and to titrate the viremia level. Serological surveys were carried out by using the IgM Antibodies Capture Enzyme Linked Immunosorbent Assay (MAC-ELISA), Complement Fixation (CF), Hemagglulinalion Inhibition (HI) and Neutralization (N) tests. The yellow fever virus, recovered from the two first samples and the virus titration, showed high level of viremia. After that, specific antibodies appeared in all samples. The interval between the end of the viremia and the appearance of the antibodies was associated with the worsening of clinical symptoms, including bleeding of the mucous membrane. One must be aware of the risk of having a urban epidemics in areas where Aedes aegypti is found in high infestation indexes.
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As the wireless cellular market reaches competitive levels never seen before, network operators need to focus on maintaining Quality of Service (QoS) a main priority if they wish to attract new subscribers while keeping existing customers satisfied. Speech Quality as perceived by the end user is one major example of a characteristic in constant need of maintenance and improvement. It is in this topic that this Master Thesis project fits in. Making use of an intrusive method of speech quality evaluation, as a means to further study and characterize the performance of speech codecs in second-generation (2G) and third-generation (3G) technologies. Trying to find further correlation between codecs with similar bit rates, along with the exploration of certain transmission parameters which may aid in the assessment of speech quality. Due to some limitations concerning the audio analyzer equipment that was to be employed, a different system for recording the test samples was sought out. Although the new designed system is not standard, after extensive testing and optimization of the system's parameters, final results were found reliable and satisfactory. Tests include a set of high and low bit rate codecs for both 2G and 3G, where values were compared and analysed, leading to the outcome that 3G speech codecs perform better, under the approximately same conditions, when compared with 2G. Reinforcing the idea that 3G is, with no doubt, the best choice if the costumer looks for the best possible listening speech quality. Regarding the transmission parameters chosen for the experiment, the Receiver Quality (RxQual) and Received Energy per Chip to the Power Density Ratio (Ec/N0), these were subject to speech quality correlation tests. Final results of RxQual were compared to those of prior studies from different researchers and, are considered to be of important relevance. Leading to the confirmation of RxQual as a reliable indicator of speech quality. As for Ec/N0, it is not possible to state it as a speech quality indicator however, it shows clear thresholds for which the MOS values decrease significantly. The studied transmission parameters show that they can be used not only for network management purposes but, at the same time, give an expected idea to the communications engineer (or technician) of the end-to-end speech quality consequences. With the conclusion of the work new ideas for future studies come to mind. Considering that the fourth-generation (4G) cellular technologies are now beginning to take an important place in the global market, as the first all-IP network structure, it seems of great relevance that 4G speech quality should be subject of evaluation. Comparing it to 3G, not only in narrowband but also adding wideband scenarios with the most recent standard objective method of speech quality assessment, POLQA. Also, new data found on Ec/N0 tests, justifies further research studies with the intention of validating the assumptions made in this work.
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Dissertação para obtenção do Grau de Mestre em Engenharia Informática
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Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering
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The implementation of competitive electricity markets has changed the consumers’ and distributed generation position power systems operation. The use of distributed generation and the participation in demand response programs, namely in smart grids, bring several advantages for consumers, aggregators, and system operators. The present paper proposes a remuneration structure for aggregated distributed generation and demand response resources. A virtual power player aggregates all the resources. The resources are aggregated in a certain number of clusters, each one corresponding to a distinct tariff group, according to the economic impact of the resulting remuneration tariff. The determined tariffs are intended to be used for several months. The aggregator can define the periodicity of the tariffs definition. The case study in this paper includes 218 consumers, and 66 distributed generation units.
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Epidemiologic studies have reported an inverse association between dairy product consumption and cardiometabolic risk factors in adults, but this relation is relatively unexplored in adolescents. We hypothesized that a higher dairy product intake is associated with lower cardiometabolic risk factor clustering in adolescents. To test this hypothesis, a cross-sectional study was conducted with 494 adolescents aged 15 to 18 years from the Azorean Archipelago, Portugal. We measured fasting glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, triglycerides, systolic blood pressure, body fat, and cardiorespiratory fitness. We also calculated homeostatic model assessment and total cholesterol/high-density lipoprotein cholesterol ratio. For each one of these variables, a z score was computed using age and sex. A cardiometabolic risk score (CMRS) was constructed by summing up the z scores of all individual risk factors. High risk was considered to exist when an individual had at least 1 SD from this score. Diet was evaluated using a food frequency questionnaire, and the intake of total dairy (included milk, yogurt, and cheese), milk, yogurt, and cheese was categorized as low (equal to or below the median of the total sample) or “appropriate” (above the median of the total sample).The association between dairy product intake and CMRS was evaluated using separate logistic regression, and the results were adjusted for confounders. Adolescents with high milk intake had lower CMRS, compared with those with low intake (10.6% vs 18.1%, P = .018). Adolescents with appropriate milk intake were less likely to have high CMRS than those with low milk intake (odds ratio, 0.531; 95% confidence interval, 0.302-0.931). No association was found between CMRS and total dairy, yogurt, and cheese intake. Only milk intake seems to be inversely related to CMRS in adolescents.
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It is well recognized that professional musicians are at risk of hearing damage due to the exposure to high sound pressure levels during music playing. However, it is important to recognize that the musicians’ exposure may start early in the course of their training as students in the classroom and at home. Studies regarding sound exposure of music students and their hearing disorders are scarce and do not take into account important influencing variables. Therefore, this study aimed to describe sound level exposures of music students at different music styles, classes, and according to the instrument played. Further, this investigation attempted to analyze the perceptions of students in relation to exposure to loud music and consequent health risks, as well as to characterize preventive behaviors. The results showed that music students are exposed to high sound levels in the course of their academic activity. This exposure is potentiated by practice outside the school and other external activities. Differences were found between music style, instruments, and classes. Tinnitus, hyperacusis, diplacusis, and sound distortion were reported by the students. However, students were not entirely aware of the health risks related to exposure to high sound pressure levels. These findings reflect the importance of starting intervention in relation to noise risk reduction at an early stage, when musicians are commencing their activity as students.
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In recent years, vehicular cloud computing (VCC) has emerged as a new technology which is being used in wide range of applications in the area of multimedia-based healthcare applications. In VCC, vehicles act as the intelligent machines which can be used to collect and transfer the healthcare data to the local, or global sites for storage, and computation purposes, as vehicles are having comparatively limited storage and computation power for handling the multimedia files. However, due to the dynamic changes in topology, and lack of centralized monitoring points, this information can be altered, or misused. These security breaches can result in disastrous consequences such as-loss of life or financial frauds. Therefore, to address these issues, a learning automata-assisted distributive intrusion detection system is designed based on clustering. Although there exist a number of applications where the proposed scheme can be applied but, we have taken multimedia-based healthcare application for illustration of the proposed scheme. In the proposed scheme, learning automata (LA) are assumed to be stationed on the vehicles which take clustering decisions intelligently and select one of the members of the group as a cluster-head. The cluster-heads then assist in efficient storage and dissemination of information through a cloud-based infrastructure. To secure the proposed scheme from malicious activities, standard cryptographic technique is used in which the auotmaton learns from the environment and takes adaptive decisions for identification of any malicious activity in the network. A reward and penalty is given by the stochastic environment where an automaton performs its actions so that it updates its action probability vector after getting the reinforcement signal from the environment. The proposed scheme was evaluated using extensive simulations on ns-2 with SUMO. The results obtained indicate that the proposed scheme yields an improvement of 10 % in detection rate of malicious nodes when compared with the existing schemes.
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Multi-standard mobile devices are allowing users to enjoy higher data rates with ubiquitous connectivity. However, the benefits gained from multiple interfaces come at an expense—that being higher energy consumption in an era where mobile devices need to be energy compliant. One promising solution is the usage of short-range cooperative communication as an overlay for infrastructure-based networks taking advantage of its context information. However, the node discovery mechanism, which is pivotal to the bearer establishment process, still represents a major burden in terms of the total energy budget. In this paper, we propose a technology agnostic approach towards enhancing the MAC energy ratings by presenting a context-aware node discovery (CANDi) algorithm, which provides a priori knowledge towards the node discovery mechanism by allowing it to search nodes in the near vicinity at the ‘right time and at the right place’. We describe the different beacons required for establishing the cooperation, as well as the context information required, including battery level, modes, location and so on. CANDi uses the long-range network (WiMAX and WiFi) to distribute the context information about cooperative clusters (Ultra-wideband-based) in the vicinity. The searching nodes can use this context in locating the cooperative clusters/nodes, which facilitates the establishing of short-range connections. Analytical and simulation results are obtained, and the energy saving gains are further demonstrated in the laboratory using a customised testbed. CANDi saves up to 50% energy during the node discovery process, while the demonstrative testbed shows up to 75% savings in the total energy budget, thus validating the algorithm, as well as providing viable evidence to support the usage of short-range cooperative communications for energy savings.
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This paper analyses forest fires in the perspective of dynamical systems. Forest fires exhibit complex correlations in size, space and time, revealing features often present in complex systems, such as the absence of a characteristic length-scale, or the emergence of long range correlations and persistent memory. This study addresses a public domain forest fires catalogue, containing information of events for Portugal, during the period from 1980 up to 2012. The data is analysed in an annual basis, modelling the occurrences as sequences of Dirac impulses with amplitude proportional to the burnt area. First, we consider mutual information to correlate annual patterns. We use visualization trees, generated by hierarchical clustering algorithms, in order to compare and to extract relationships among the data. Second, we adopt the Multidimensional Scaling (MDS) visualization tool. MDS generates maps where each object corresponds to a point. Objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to identify forest fire patterns.
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In this paper we analyze the behavior of tornado time-series in the U.S. from the perspective of dynamical systems. A tornado is a violently rotating column of air extending from a cumulonimbus cloud down to the ground. Such phenomena reveal features that are well described by power law functions and unveil characteristics found in systems with long range memory effects. Tornado time series are viewed as the output of a complex system and are interpreted as a manifestation of its dynamics. Tornadoes are modeled as sequences of Dirac impulses with amplitude proportional to the events size. First, a collection of time series involving 64 years is analyzed in the frequency domain by means of the Fourier transform. The amplitude spectra are approximated by power law functions and their parameters are read as an underlying signature of the system dynamics. Second, it is adopted the concept of circular time and the collective behavior of tornadoes analyzed. Clustering techniques are then adopted to identify and visualize the emerging patterns.
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During June 1997-June 1999 rotavirus infection was screened in infants aged up to 2 years and hospitalised with acute diarrhoea in São Luís, Northeastern Brazil. Altogether, 128 stool samples were collected from diarrhoeic patients and additional 122 faecal specimens from age- and- temporal matched inpatients without diarrhoea were obtained; rotavirus positivity rates for these groups were 32.0% (41/128) and 9.8% (12/122), respectively (p < 0.001). Both electropherotyping and serotyping could be performed in 42 (79.2%) of the 53 rotavirus-positive stool samples. Long and short electropherotypes were detected at similar rates - 38.1% and 40.5% of specimens, respectively. Overall, a G serotype could be assigned for 35 (83.3%) of specimens, the majority of them (66.7%) bearing G1-serotype specificity. Taking both electropherotypes and serotypes together, G1 rotavirus strains displaying long and short RNA patterns accounted for 30.9% and 19.0% of tested specimens, respectively; all G2 strains had short electropherotype. Rotavirus gastroenteritis was detected year-round and, in 1998, the incidence rates tended to be higher during the second semester than in the first semester: 45.2% and 26.1% (p = 0.13), respectively. Rotavirus infections peaked at the second semester of life with frequencies of 30.1% and 13.5% for diarrhoeic children and controls, respectively. While the six rotavirus strains bearing G2-type specificity were circulating throughout the whole study period, G1 serotypes (n = 27) emerged as from June 1998 onwards, 20 (74.1%) of which clustering in 1998. These data underscore the importance of rotaviruses in the aetiology of severe infantile gastroenteritis in Northeastern Brazil and sustain the concept that a future vaccine should confer protection against more than one serotype.
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Presented at IEEE 21st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2015). 19 to 21, Aug, 2015.
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Smart Cities are designed to be living systems and turn urban dwellers life more comfortable and interactive by keeping them aware of what surrounds them, while leaving a greener footprint. The Future Cities Project [1] aims to create infrastructures for research in smart cities including a vehicular network, the BusNet, and an environmental sensor platform, the Urban Sense. Vehicles within the BusNet are equipped with On Board Units (OBUs) that offer free Wi-Fi to passengers and devices near the street. The Urban Sense platform is composed by a set of Data Collection Units (DCUs) that include a set of sensors measuring environmental parameters such as air pollution, meteorology and noise. The Urban Sense platform is expanding and receptive to add new sensors to the platform. The parnership with companies like TNL were made and the need to monitor garbage street containers emerged as air pollution prevention. If refuse collection companies know prior to the refuse collection which route is the best to collect the maximum amount of garbage with the shortest path, they can reduce costs and pollution levels are lower, leaving behind a greener footprint. This dissertation work arises in the need to monitor the garbage street containers and integrate these sensors into an Urban Sense DCU. Due to the remote locations of the garbage street containers, a network extension to the vehicular network had to be created. This dissertation work also focus on the Multi-hop network designed to extend the vehicular network coverage area to the remote garbage street containers. In locations where garbage street containers have access to the vehicular network, Roadside Units (RSUs) or Access Points (APs), the Multi-hop network serves has a redundant path to send the data collected from DCUs to the Urban Sense cloud database. To plan this highly dynamic network, the Wi-Fi Planner Tool was developed. This tool allowed taking measurements on the field that led to an optimized location of the Multi-hop network nodes with the use of radio propagation models. This tool also allowed rendering a temperature-map style overlay for Google Earth [2] application. For the DCU for garbage street containers the parner company provided the access to a HUB (device that communicates with the sensor inside the garbage containers). The Future Cities use the Raspberry pi as a platform for the DCUs. To collect the data from the HUB a RS485 to RS232 converter was used at the physical level and the Modbus protocol at the application level. To determine the location and status of the vehicles whinin the vehicular network a TCP Server was developed. This application was developed for the OBUs providing the vehicle Global Positioning System (GPS) location as well as information of when the vehicle is stopped, moving, on idle or even its slope. To implement the Multi-hop network on the field some scripts were developed such as pingLED and “shark”. These scripts helped upon node deployment on the field as well as to perform all the tests on the network. Two setups were implemented on the field, an urban setup was implemented for a Multi-hop network coverage survey and a sub-urban setup was implemented to test the Multi-hop network routing protocols, Optimized Link State Routing Protocol (OLSR) and Babel.