996 resultados para Distributed monitoring


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Long-term monitoring of data of ambient mercury (Hg) on a global scale to assess its emission, transport, atmospheric chemistry, and deposition processes is vital to understanding the impact of Hg pollution on the environment. The Global Mercury Observation System (GMOS) project was funded by the European Commission (http://www.gmos.eu) and started in November 2010 with the overall goal to develop a coordinated global observing system to monitor Hg on a global scale, including a large network of ground-based monitoring stations, ad hoc periodic oceanographic cruises and measurement flights in the lower and upper troposphere as well as in the lower stratosphere. To date, more than 40 ground-based monitoring sites constitute the global network covering many regions where little to no observational data were available before GMOS. This work presents atmospheric Hg concentrations recorded worldwide in the framework of the GMOS project (2010–2015), analyzing Hg measurement results in terms of temporal trends, seasonality and comparability within the network. Major findings highlighted in this paper include a clear gradient of Hg concentrations between the Northern and Southern hemispheres, confirming that the gradient observed is mostly driven by local and regional sources, which can be anthropogenic, natural or a combination of both.

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Background Heart failure and diabetes often occur simultaneously in patients, but the prognostic value of glycemia in chronic heart failure is debatable. We evaluated the role of glycemia on prognosis of heart failure. Methods Outpatients with chronic heart failure from the Long-term Prospective Randomized Controlled Study Using Repetitive Education at Six-Month Intervals and Monitoring for Adherence in Heart Failure Outpatients (REMADHE) trial were grouped according to the presence of diabetes and level of glycemia. All-cause mortality/heart transplantation and unplanned hospital admission were evaluated. Results Four hundred fifty-six patients were included (135 [29.5%] female, 124 [27.2%] with diabetes mellitus, age of w50.2 +/- 11.4 years, and left-ventricle ejection fraction of 34.7% +/- 10.5%). During follow-up (3.6 +/- 2.2 years), 27 (5.9%) patients were submitted to heart transplantation and 202 (44.2%) died; survival was similar in patients with and without diabetes mellitus. When patients with and without diabetes were categorized according to glucose range (glycemia <= 100 mg/dL [5.5 mmol/L]), as well as when distributed in quintiles of glucose, the survival was significantly worse among patients with lower levels of glycemia. This finding persisted in Cox proportional hazards regression model that included gender, etiology, left ventricle ejection fraction, left ventricle diastolic diameter, creatinine level and beta-blocker therapy, and functional status (hazard ratio 1.45, 95% CI 1.09-1.69, P = .039). No difference regarding unplanned hospital admission was found. Conclusion We report on an inverse association between glycemia and mortality in outpatients with chronic heart failure. These results point to a new pathophysiologic understanding of the interactions between diabetes mellitus, hyperglycemia, and heart disease. (Am Heart J 2010; 159: 90-7.)

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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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Dissertação para obtenção do Grau de Doutor em Química Sustentável

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Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

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The “CMS Safety Closing Sensors System” (SCSS, or CSS for brevity) is a remote monitoring system design to control safety clearance and tight mechanical movements of parts of the CMS detector, especially during CMS assembly phases. We present the different systems that makes SCSS: its sensor technologies, the readout system, the data acquisition and control software. We also report on calibration and installation details, which determine the resolution and limits of the system. We present as well our experience from the operation of the system and the analysis of the data collected since 2008. Special emphasis is given to study positioning reproducibility during detector assembly and understanding how the magnetic fields influence the detector structure.

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In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

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The purpose of resource management is the efficient and effective use of network resources, for instance bandwidth. In this article, a connection oriented network scenario is considered, where a certain amount of bandwidth is reserved for each label switch path (LSP), which is a logical path, in a MPLS or GMPLS environment. Assuming there is also some kind of admission control (explicit or implicit), these environments typically provide quality of service (QoS) guarantees. It could happen that some LSPs become busy, thus rejecting connections, while other LSPs may be under-utilised. We propose a distributed lightweight monitoring technique, based on threshold values, the objective of which is to detect congestion when it occurs in an LSP and activate the corresponding alarm which will trigger a dynamic bandwidth reallocation mechanism

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Monitoring of posture allocations and activities enables accurate estimation of energy expenditure and may aid in obesity prevention and treatment. At present, accurate devices rely on multiple sensors distributed on the body and thus may be too obtrusive for everyday use. This paper presents a novel wearable sensor, which is capable of very accurate recognition of common postures and activities. The patterns of heel acceleration and plantar pressure uniquely characterize postures and typical activities while requiring minimal preprocessing and no feature extraction. The shoe sensor was tested in nine adults performing sitting and standing postures and while walking, running, stair ascent/descent and cycling. Support vector machines (SVMs) were used for classification. A fourfold validation of a six-class subject-independent group model showed 95.2% average accuracy of posture/activity classification on full sensor set and over 98% on optimized sensor set. Using a combination of acceleration/pressure also enabled a pronounced reduction of the sampling frequency (25 to 1 Hz) without significant loss of accuracy (98% versus 93%). Subjects had shoe sizes (US) M9.5-11 and W7-9 and body mass index from 18.1 to 39.4 kg/m2 and thus suggesting that the device can be used by individuals with varying anthropometric characteristics.

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Multiple motor function and strength assessment tools exist for the evaluation of neuromuscular diseases, but most do not directly assess functional ability in the patients' daily physical activity in their home environment. In this study our aim was to assess: 1) the feasibility and accuracy of physical activity monitoring during two days in a home environment of five DMD patients using a non-commercialized monitor containing a 3D accelerometer and a gyroscope, 2) if a difference in the physical activity parameters could be measured before and one month after starting prednisolone. We reliably quantified the time spend sitting, standing, lying, walking, the number of steps taken, the cadence, the number of walking episodes and their duration as well as how these were distributed over the day. Parameters possibly reflecting endurance, such as the duration of the walking episodes or the succession of two or three walking episodes lasting more than 30 s were the most improved after prednisolone treatment. This degree of detailed determination of physical activity in a home environment has not been previously reported in neuromuscular disorders to our knowledge and some of the reported parameters are potential new outcome measures in clinical trials.

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The research of power-line communications has been concentrated on home automation, broadband indoor communications and broadband data transfer in a low voltage distribution network between home andtransformer station. There has not been carried out much research work that is focused on the high frequency characteristics of industrial low voltage distribution networks. The industrial low voltage distribution network may be utilised as a communication channel to data transfer required by the on-line condition monitoring of electric motors. The advantage of using power-line data transfer is that it does not require the installing of new cables. In the first part of this work, the characteristics of industrial low voltage distribution network components and the pilot distribution network are measured and modelled with respect topower-line communications frequencies up to 30 MHz. The distributed inductances, capacitances and attenuation of MCMK type low voltage power cables are measured in the frequency band 100 kHz - 30 MHz and an attenuation formula for the cables is formed based on the measurements. The input impedances of electric motors (15-250 kW) are measured using several signal couplings and measurement based input impedance model for electric motor with a slotted stator is formed. The model is designed for the frequency band 10 kHz - 30 MHz. Next, the effect of DC (direct current) voltage link inverter on power line data transfer is briefly analysed. Finally, a pilot distribution network is formed and signal attenuation in communication channels in the pilot environment is measured. The results are compared with the simulations that are carried out utilising the developed models and measured parameters for cables and motors. In the second part of this work, a narrowband power-line data transfer system is developed for the data transfer ofon-line condition monitoring of electric motors. It is developed using standardintegrated circuits. The system is tested in the pilot environment and the applicability of the system for the data transfer required by the on-line condition monitoring of electric motors is analysed.

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OBJECTIVE: This study aimed to survey current practices in European epilepsy monitoring units (EMUs) with emphasis on safety issues. METHODS: A 37-item questionnaire investigating characteristics and organization of EMUs, including measures for prevention and management of seizure-related serious adverse events (SAEs), was distributed to all identified European EMUs plus one located in Israel (N=150). RESULTS: Forty-eight (32%) EMUs, located in 18 countries, completed the questionnaire. Epilepsy monitoring unit beds are 1-2 in 43%, 3-4 in 34%, and 5-6 in 19% of EMUs; staff physicians are 1-2 in 32%, 3-4 in 34%, and 5-6 in 19% of EMUs. Personnel operating in EMUs include epileptologists (in 69% of EMUs), clinical neurophysiologists trained in epilepsy (in 46% of EMUs), child neurologists (in 35% of EMUs), neurology and clinical neurophysiology residents (in 46% and in 8% of EMUs, respectively), and neurologists not trained in epilepsy (in 27% of EMUs). In 20% of EMUs, patients' observation is only intermittent or during the daytime and primarily carried out by neurophysiology technicians and/or nurses (in 71% of EMUs) or by patients' relatives (in 40% of EMUs). Automatic detection systems for seizures are used in 15%, for body movements in 8%, for oxygen desaturation in 33%, and for ECG abnormalities in 17% of EMUs. Protocols for management of acute seizures are lacking in 27%, of status epilepticus in 21%, and of postictal psychoses in 87% of EMUs. Injury prevention consists of bed protections in 96% of EMUs, whereas antisuffocation pillows are employed in 21%, and environmental protections in monitoring rooms and in bathrooms are implemented in 38% and in 25% of EMUs, respectively. The most common SAEs were status epilepticus reported by 79%, injuries by 73%, and postictal psychoses by 67% of EMUs. CONCLUSIONS: All EMUs have faced different types of SAEs. Wide variation in practice patterns and lack of protocols and of precautions to ensure patients' safety might promote the occurrence and severity of SAEs. Our findings highlight the need for standardized and shared protocols for an effective and safe management of patients in EMUs.

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Tarve tälle työlle on noussut sanomapalvelinsoveluksissa (servers) esiintyvistä ongelmista. Sanomapalvelinsovelluksia käytetään lähettämään ja vastaanottamaan sanomia paperiteollisuuden myynnin ja jakelun järjestelmässä maantieteellisesti erillään olevista paperiteollisuuden tehtaista. Sanomapalvelinsovelusten kunnollinen toimivuus on tärkeää koko järjestelmän toimivuuden kannalta, koska nämä palvelimet käsittelevät päivittäin tuhansia sanomia, jotka sisältävät merkityksellistä järjestelmätietoa. Tässä työssä on tutkittu mahdollisia toteutustekniikoita ja näihin tutkimuksiin pohjautuen toteutettu työkalut sanomapalvelinsovellusten testaukseen ja valvontaan. Sovellus-arkkituuritekniikoita tutkittaessa tutkimus rajattiin 3-tasoarkkitehtuuritekniikkaan, erityisesti TUXEDOTM -järjestelmätekniikkaan, koska toteutettavaa sovellusta käytetään hajautetussa sovellusympäristössä. Sovellusasiakkaan (client) toteutusta varten tutkittiin ja vertailtiin XML-tekniikkaa ja Microsoft Visual C++ -tekniikkaa käytettynä Tieto-Enatorin Phobos Interaktiivisen C++ -luokkakirjaston kanssa. XML-tekniikoita sekä Visual C++ ja Phobos-luokkakirjasto –tekniikkaa tutkittiin niiltä osin, mitä tarvittiin sanomamerkkijonojen katseluun. XML-tietokantatekniikoita tutkittiin mahdollisena vaihtoehtona tietokanta ja sovelluspalvelintekniikalle. Työn ensimmäisenä tavoitteena oli toteuttaa työkalu sanomapalvelinsovellusten testaamiseen. Toisena tavoitteena oli toteuttaa työkalu sanomien sisällön oikeellisuuden valvontaan. Kolmantena tavoitteena oli analysoida olemassaolevaa sanomavirheiden valvontasovellusta ja kehittää sitä eteenpäin. Diplomityön tuloksena toteutettiin sovellus sanomapalvelinsovellusten testaamiseen ja valvontaan. Tutkituista asiakassovelustekniikoista valittiin toteutus-tekniikaksi MS Visual C++ käytettynä Phobos Interaktiivisen C++ luokkakirjaston kanssa tekniikan tunnettavuuden vuoksi. 3-taso TUXEDOTM-tekniikka valittiin sovelluksen arkkitehtuuriksi. Lisäksi löydettiin parannuksia olemassa oleviin sanoma-virheiden valvontatoimintoihin. Tutkitut toteutustekniikat ovat yleisiä ja niitä voidaan käyttää, kun toteutetaan samanlaisia sovelluksia samanlaisiin sovellusympäristöihin.

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We presented a bird-monitoring database inMediterranean landscapes (Catalonia, NE Spain) affected by wildfires and we evaluated: 1) the spatial and temporal variability in the bird community composition and 2) the influence of pre-fire habitat configuration in the composition of bird communities. The DINDIS database results fromthemonitoring of bird communities occupying all areas affected by large wildfires in Catalonia since 2000.We used bird surveys conducted from 2006 to 2009 and performed a principal components analysis to describe two main gradients of variation in the composition of bird communities, which were used as descriptors of bird communities in subsequent analyses. We then analysed the relationships of these community descriptors with bioclimatic regions within Catalonia, time since fire and pre-fire vegetation (forest or shrubland).We have conducted 1,918 bird surveys in 567 transects distributed in 56 burnt areas. Eight out of the twenty most common detected species have an unfavourable conservation status, most of them being associated to open-habitats. Both bird communities’ descriptors had a strong regional component and were related to pre-fire vegetation, and to a lesser extent to the time since fire.We came to the conclusion that the responses of bird communities to wildfires are heterogeneous, complex and context dependent. Large-scale monitoring datasets, such as DINDIS, might allow identifying factors acting at different spatial and temporal scales that affect the dynamics of species and communities, giving additional information on the causes under general trends observed using other monitoring systems

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Thermal and air conditions inside animal facilities change during the day due to the influence of the external environment. For statistical and geostatistical analyses to be representative, a large number of points spatially distributed in the facility area must be monitored. This work suggests that the time variation of environmental variables of interest for animal production, monitored within animal facility, can be modeled accurately from discrete-time records. The aim of this study was to develop a numerical method to correct the temporal variations of these environmental variables, transforming the data so that such observations are independent of the time spent during the measurement. The proposed method approached values recorded with time delays to those expected at the exact moment of interest, if the data were measured simultaneously at the moment at all points distributed spatially. The correction model for numerical environmental variables was validated for environmental air temperature parameter, and the values corrected by the method did not differ by Tukey's test at 5% significance of real values recorded by data loggers.