958 resultados para Network air gap


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Recently, wireless network technology has grown at such a pace that scientific research has become a practical reality in a very short time span. One mobile system that features high data rates and open network architecture is 4G. Currently, the research community and industry, in the field of wireless networks, are working on possible choices for solutions in the 4G system. The researcher considers one of the most important characteristics of future 4G mobile systems the ability to guarantee reliable communications at high data rates, in addition to high efficiency in the spectrum usage. On mobile wireless communication networks, one important factor is the coverage of large geographical areas. In 4G systems, a hybrid satellite/terrestrial network is crucial to providing users with coverage wherever needed. Subscribers thus require a reliable satellite link to access their services when they are in remote locations where a terrestrial infrastructure is unavailable. The results show that good modulation and access technique are also required in order to transmit high data rates over satellite links to mobile users. The dissertation proposes the use of OFDM (Orthogonal Frequency Multiple Access) for the satellite link by increasing the time diversity. This technique will allow for an increase of the data rate, as primarily required by multimedia applications, and will also optimally use the available bandwidth. In addition, this dissertation approaches the use of Cooperative Satellite Communications for hybrid satellite/terrestrial networks. By using this technique, the satellite coverage can be extended to areas where there is no direct link to the satellite. The issue of Cooperative Satellite Communications is solved through a new algorithm that forwards the received data from the fixed node to the mobile node. This algorithm is very efficient because it does not allow unnecessary transmissions and is based on signal to noise ratio (SNR) measures.

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Oscillating Water Column (OWC) is one type of promising wave energy devices due to its obvious advantage over many other wave energy converters: no moving component in sea water. Two types of OWCs (bottom-fixed and floating) have been widely investigated, and the bottom-fixed OWCs have been very successful in several practical applications. Recently, the proposal of massive wave energy production and the availability of wave energy have pushed OWC applications from near-shore to deeper water regions where floating OWCs are a better choice. For an OWC under sea waves, the air flow driving air turbine to generate electricity is a random process. In such a working condition, single design/operation point is nonexistent. To improve energy extraction, and to optimise the performance of the device, a system capable of controlling the air turbine rotation speed is desirable. To achieve that, this paper presents a short-term prediction of the random, process by an artificial neural network (ANN), which can provide near-future information for the control system. In this research, ANN is explored and tuned for a better prediction of the airflow (as well as the device motions for a wide application). It is found that, by carefully constructing ANN platform and optimizing the relevant parameters, ANN is capable of predicting the random process a few steps ahead of the real, time with a good accuracy. More importantly, the tuned ANN works for a large range of different types of random, process.

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Gravity surveying is challenging in Antarctica because of its hostile environment and inaccessibility. Nevertheless, many ground-based, airborne and shipborne gravity campaigns have been completed by the geophysical and geodetic communities since the 1980s. We present the first modern Antarctic-wide gravity data compilation derived from 13 million data points covering an area of 10 million km**2, which corresponds to 73% coverage of the continent. The remove-compute-restore technique was applied for gridding, which facilitated levelling of the different gravity datasets with respect to an Earth Gravity Model derived from satellite data alone. The resulting free-air and Bouguer gravity anomaly grids of 10 km resolution are publicly available. These grids will enable new high-resolution combined Earth Gravity Models to be derived and represent a major step forward towards solving the geodetic polar data gap problem. They provide a new tool to investigate continental-scale lithospheric structure and geological evolution of Antarctica.

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Low pO2 values have been measured in the perivitelline fluids (PVF) of marine animal eggs on several occasions, especially towards the end of development, when embryonic oxygen consumption is at its peak and the egg case acts as a massive barrier to diffusion. Several authors have therefore suggested that oxygen availability is the key factor leading to hatching. However, there have been no measurements of PVF pCO2 so far. This is surprising, as elevated pCO2 could also constitute a major abiotic stressor for the developing embryo. As a first attempt to fill this gap in knowledge, we measured pO2, pCO2 and pH in the PVF of late cephalopod (Sepia officinalis) eggs. We found linear relationships between embryo wet mass and pO2, pCO2 and pH. pO2 declined from >12 kPa to less than 5 kPa, while pCO2 increased from 0.13 to 0.41 kPa. In the absence of active accumulation of bicarbonate in the PVF, pH decreased from 7.7 to 7.2. Our study supports the idea that oxygen becomes limiting in cephalopod eggs towards the end of development; however, pCO2 and pH shift to levels that have caused significant physiological disturbances in other marine ectothermic animals. Future research needs to address the physiological adaptations that enable the embryo to cope with the adverse abiotic conditions in their egg environment.

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Wireless sensor networks (WSNs) have shown wide applicability to many fields including monitoring of environmental, civil, and industrial settings. WSNs however are resource constrained by many competing factors that span their hardware, software, and networking. One of the central resource constrains is the charge consumption of WSN nodes. With finite energy supplies, low charge consumption is needed to ensure long lifetimes and success of WSNs. This thesis details the design of a power system to support long-term operation of WSNs. The power system’s development occurs in parallel with a custom WSN from the Queen’s MEMS Lab (QML-WSN), with the goal of supporting a 1+ year lifetime without sacrificing functionality. The final power system design utilizes a TPS62740 DC-DC converter with AA alkaline batteries to efficiently supply the nodes while providing battery monitoring functionality and an expansion slot for future development. Testing tools for measuring current draw and charge consumption were created along with analysis and processing software. Through their use charge consumption of the power system was drastically lowered and issues in QML-WSN were identified and resolved including the proper shutdown of accelerometers, and incorrect microcontroller unit (MCU) power pin connection. Controlled current profiling revealed unexpected behaviour of nodes and detailed current-voltage relationships. These relationships were utilized with a lifetime projection model to estimate a lifetime between 521-551 days, depending on the mode of operation. The power system and QML-WSN were tested over a long term trial lasting 272+ days in an industrial testbed to monitor an air compressor pump. Environmental factors were found to influence the behaviour of nodes leading to increased charge consumption, while a node in an office setting was still operating at the conclusion of the trail. This agrees with the lifetime projection and gives a strong indication that a 1+ year lifetime is achievable. Additionally, a light-weight charge consumption model was developed which allows charge consumption information of nodes in a distributed WSN to be monitored. This model was tested in a laboratory setting demonstrating +95% accuracy for high packet reception rate WSNs across varying data rates, battery supply capacities, and runtimes up to full battery depletion.

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Complexity science is the multidisciplinary study of complex systems. Its marked network orientation lends itself well to transport contexts. Key features of complexity science are introduced and defined, with a specific focus on the application to air traffic management. An overview of complex network theory is presented, with examples of its corresponding metrics and multiple scales. Complexity science is starting to make important contributions to performance assessment and system design: selected, applied air traffic management case studies are explored. The important contexts of uncertainty, resilience and emergent behaviour are discussed, with future research priorities summarised.

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The Canadian economy is largely dependent on the distribution of large volumes of oil to domestic and international markets by a long network of pipelines. Unfortunately, accidents occur, and oil can leak or spill from these pipelines before it reaches its destination. Of particular concern are the long-term consequences of oil spills in freshwater, which include sinking of oil in water and the contamination of sensitive areas, such as where fish (e.g., salmon) deposit their eggs in gravel-dominated river sediments. There is a knowledge gap regarding the fate and behaviour of oil in river sediment. To this end, this study aimed at finding the potential for diluted bitumen (dilbit) oil to become trapped in gravel and to transfer hydrocarbons into water by dissolution, which are harmful to aquatic life. Two sets of laboratory experiments were conducted to simulate conditions of an oil spill on an exposed bank or in shallow water. In the first set, by conducting capillary pressure-saturation (Pc-Sw) experiments it was found that dilbit can enter gravel pores without much resistance and approximately 14% of the pore volume can be occupied by discontinuous single or multipore blobs of dilbit following imbibition of water. Air-water Pc-Sw experiments done in laboratory 1-D columns required gravity correction and could be successfully scaled to predict dilbit-water Pc-Sw curves, except for the trapped amount of dilbit. Trapped dilbit constituents can be dissolved into the water flowing through gravel pores (hyporheic flow) at different velocities. In the second set, dissolution experiments suggested that for the duration of the test, hydrocarbons that cause acute toxicity dissolve rapidly, likely resulting in a decrease in their effective solubility. However, dilbit saturation changed only <2% within that time. Chronically toxic PAH compounds were also detected in the effluent water. The total concentration of all detected PAHs and alkylPAHs exceeded the threshold literature value to protect early-life stage fish. Observations of decreased concentrations with increased aqueous velocities as well as less than equilibrium concentrations indicated that the mass transfer was rate-limited. A correlation was developed for the mass transfer rate coefficient to understand the mass transfer behaviour beyond the conditions used in the experiments, which had a Reynolds number exponent similar to the studies of NAPL dissolution in groundwater.

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Complex network theory is a framework increasingly used in the study of air transport networks, thanks to its ability to describe the structures created by networks of flights, and their influence in dynamical processes such as delay propagation. While many works consider only a fraction of the network, created by major airports or airlines, for example, it is not clear if and how such sampling process bias the observed structures and processes. In this contribution, we tackle this problem by studying how some observed topological metrics depend on the way the network is reconstructed, i.e. on the rules used to sample nodes and connections. Both structural and simple dynamical properties are considered, for eight major air networks and different source datasets. Results indicate that using a subset of airports strongly distorts our perception of the network, even when just small ones are discarded; at the same time, considering a subset of airlines yields a better and more stable representation. This allows us to provide some general guidelines on the way airports and connections should be sampled.

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Multiphase flows, type oil–water-gas are very common among different industrial activities, such as chemical industries and petroleum extraction, and its measurements show some difficulties to be taken. Precisely determining the volume fraction of each one of the elements that composes a multiphase flow is very important in chemical plants and petroleum industries. This work presents a methodology able to determine volume fraction on Annular and Stratified multiphase flow system with the use of neutrons and artificial intelligence, using the principles of transmission/scattering of fast neutrons from a 241Am-Be source and measurements of point flow that are influenced by variations of volume fractions. The proposed geometries used on the mathematical model was used to obtain a data set where the thicknesses referred of each material had been changed in order to obtain volume fraction of each phase providing 119 compositions that were used in the simulation with MCNP-X –computer code based on Monte Carlo Method that simulates the radiation transport. An artificial neural network (ANN) was trained with data obtained using the MCNP-X, and used to correlate such measurements with the respective real fractions. The ANN was able to correlate the data obtained on the simulation with MCNP-X with the volume fractions of the multiphase flows (oil-water-gas), both in the pattern of annular flow as stratified, resulting in a average relative error (%) for each production set of: annular (air= 3.85; water = 4.31; oil=1.08); stratified (air=3.10, water 2.01, oil = 1.45). The method demonstrated good efficiency in the determination of each material that composes the phases, thus demonstrating the feasibility of the technique.

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Near-surface air temperature is an important determinant of the surface energy balance of glaciers and is often represented by a constant linear temperature gradients (TGs) in models. Spatiotemporal variability in 2 m air temperature was measured across the debris-covered Miage Glacier, Italy, over an 89 d period during the 2014 ablation season using a network of 19 stations. Air temperature was found to be strongly dependent upon elevation for most stations, even under varying meteorological conditions and at different times of day, and its spatial variability was well explained by a locally derived mean linear TG (MG–TG) of −0.0088°C m−1. However, local temperature depressions occurred over areas of very thin or patchy debris cover. The MG–TG, together with other air TGs, extrapolated from both on- and off-glacier sites, were applied in a distributed energy-balance model. Compared with piecewise air temperature extrapolation from all on-glacier stations, modelled ablation, using the MG–TG, increased by <1%, increasing to >4% using the environmental ‘lapse rate’. Ice melt under thick debris was relatively insensitive to air temperature, while the effects of different temperature extrapolation methods were strongest at high elevation sites of thin and patchy debris cover.

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An important aspect of sustainability is to maintain biodiversity and ecosystem functioning while improving human well-being. For this, the ecosystem service (ES) approach has the potential to bridge the still existing gap between ecological management and social development, especially by focusing on trade-offs and synergies between ES and between their beneficiaries. Several frameworks have been proposed to account for trade-offs and synergies between ES, and between ES and other components of social-ecological systems. However, to date, insufficient explicit attention has been paid to the three facets encompassed in the ES concept, namely potential supply, demand, and use, leading to incomplete descriptions of ES interactions. We expand on previous frameworks by proposing a new influence network framework (INF) based on an explicit consideration of influence relationships between these three ES facets, biodiversity, and external driving variables. We tested its ability to provide a comprehensive view of complex social-ecological interactions around ES through a consultative process focused on environmental management in the French Alps. We synthetized the interactions mentioned during this consultative process and grouped variables according to their overall propensity to influence or be influenced by the system. The resulting directed sequence of influences distinguished between: (1) mostly influential variables (dynamic social variables and ecological state variables), (2) target variables (provisioning and cultural services), and (3) mostly impacted variables (regulating services and biodiversity parameters). We discussed possible reasons for the discrepancies between actual and perceived influences and proposed options to overcome them. We demonstrated that the INF holds the potential to deliver collective assessments of ES relations by: (1) including ecological as well as social aspects, (2) providing opportunities for colearning processes between stakeholder groups, and (3) supporting communication about complex social-ecological systems and consequences for environmental management.

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The reluctance of ammonia to be ignited easily and the necessity to advance the spark for optimum performance in combustion engines led to this investigation. Ionization gap techniques showed that long induction times and slow flame speed were both contributors to the observed phenomena. The most important factor in determining combustion characteristics of ammonia was found to be the extent of predissociation prior to attempted ignition. There was evidence from combustion gas analysis that NO + was the probable most abundant ion contributing to succesful application of the ionization gap techniques, and that the NO + was probably produced in the pyrolysis of ammonia rather than by equilibrium reactions. © 1967 Combustion Institute.

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Travel demand models are important tools used in the analysis of transportation plans, projects, and policies. The modeling results are useful for transportation planners making transportation decisions and for policy makers developing transportation policies. Defining the level of detail (i.e., the number of roads) of the transport network in consistency with the travel demand model’s zone system is crucial to the accuracy of modeling results. However, travel demand modelers have not had tools to determine how much detail is needed in a transport network for a travel demand model. This dissertation seeks to fill this knowledge gap by (1) providing methodology to define an appropriate level of detail for a transport network in a given travel demand model; (2) implementing this methodology in a travel demand model in the Baltimore area; and (3) identifying how this methodology improves the modeling accuracy. All analyses identify the spatial resolution of the transport network has great impacts on the modeling results. For example, when compared to the observed traffic data, a very detailed network underestimates traffic congestion in the Baltimore area, while a network developed by this dissertation provides a more accurate modeling result of the traffic conditions. Through the evaluation of the impacts a new transportation project has on both networks, the differences in their analysis results point out the importance of having an appropriate level of network detail for making improved planning decisions. The results corroborate a suggested guideline concerning the development of a transport network in consistency with the travel demand model’s zone system. To conclude this dissertation, limitations are identified in data sources and methodology, based on which a plan of future studies is laid out.

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Still a big gap exists between clinical and genetic diagnosis of dyslipidemic disorders. Almost the 60% of the patients with a clinical diagnosis of Familial hypercholesterolemia (FH) still lack of a genetic diagnosis. Here we present the preliminary results of an integrative approach intended to identify new candidate genes and to dissect pathways that can be dysregulated in the disease. Interesting hits will be subsequently knocked down in vitro in order to evaluate their functional role in the uptake of fluorescently-labeled LDL and free cell cholesterol using automated microscopy.

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Resonant tunnelling diode (RTD) is known to be the fastest electronics device that can be fabricated in compact form and operate at room temperature with potential oscillation frequency up to 2.5 THz. The RTD device consists of a narrow band gap quantum well layer sandwiched between two thin wide band gap barriers layers. It exhibits negative differential resistance (NDR) region in its current-voltage (I-V) characteristics which is utilised in making oscillators. Up to date, the main challenge is producing high output power at high frequencies in particular. Although oscillation frequencies of ~ 2 THz have been already reported, the output power is in the range of micro-Watts. This thesis describes the systematic work on the design, fabrication, and characterisation of RTD-based oscillators in microwave/millimetre-wave monolithic integrated circuits (MMIC) form that can produce high output power and high oscillation frequency at the same time. Different MMIC RTD oscillator topologies were designed, fabricated, and characterised in this project which include: single RTD oscillator which employs one RTD device, double RTDs oscillator which employs two RTD devices connected in parallel, and coupled RTD oscillators which combine the powers of two oscillators over a single load, based on mutual coupling and which can employ up to four RTD devices. All oscillators employed relatively large size RTD devices for high power operation. The main challenge was to realise high oscillation frequency (~ 300 GHz) in MMIC form with the employed large sized RTD devices. To achieve this aim, proper designs of passive structures that can provide small values of resonating inductances were essential. These resonating inductance structures included shorted coplanar wave guide (CPW) and shorted microstrip transmission lines of low characteristics impedances Zo. Shorted transmission line of lower Zo has lower inductance per unit length. Thus, the geometrical dimensions would be relatively large and facilitate fabrication by low cost photolithography. A series of oscillators with oscillation frequencies in the J-band (220 – 325 GHz) range and output powers from 0.2 – 1.1 mW have been achieved in this project, and all were fabricated using photolithography. Theoretical estimation showed that higher oscillation frequencies (> 1 THz) can be achieved with the proposed MMIC RTD oscillators design in this project using photolithography with expected high power operation. Besides MMIC RTD oscillators, reported planar antennas for RTD-based oscillators were critically reviewed and the main challenges in designing high performance integrated antennas on large dielectric constant substrates are discussed in this thesis. A novel antenna was designed, simulated, fabricated, and characterised in this project. It was a bow-tie antenna with a tuning stub that has very wide bandwidth across the J-band. The antenna was diced and mounted on a reflector ground plane to alleviate the effect of the large dielectric constant substrate (InP) and radiates upwards to the air-side direction. The antenna was also investigated for integration with the all types of oscillators realised in this project. One port and two port antennas were designed, simulated, fabricated, and characterised and showed the suitability of integration with the single/double oscillator layout and the coupled oscillator layout, respectively.