900 resultados para biomass allocation
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The IEEE 802.15.4 standard provides appealing features to simultaneously support real-time and non realtime traffic, but it is only capable of supporting real-time communications from at most seven devices. Additionally, it cannot guarantee delay bounds lower than the superframe duration. Motivated by this problem, in this paper we propose an Explicit Guaranteed time slot Sharing and Allocation scheme (EGSA) for beacon-enabled IEEE 802.15.4 networks. This scheme is capable of providing tighter delay bounds for real-time communications by splitting the Contention Free access Period (CFP) into smaller mini time slots and by means of a new guaranteed bandwidth allocation scheme for a set of devices with periodic messages. At the same the novel bandwidth allocation scheme can maximize the duration of the CFP for non real-time communications. Performance analysis results show that the EGSA scheme works efficiently and outperforms competitor schemes both in terms of guaranteed delay and bandwidth utilization.
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We present an algorithm for bandwidth allocation for delay-sensitive traffic in multi-hop wireless sensor networks. Our solution considers both periodic as well as aperiodic real-time traffic in an unified manner. We also present a distributed MAC protocol that conforms to the bandwidth allocation and thus satisfies the latency requirements of realtime traffic. Additionally, the protocol provides best-effort service to non real-time traffic. We derive the utilization bounds of our MAC protocol.
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The IEEE 802.15.4 protocol proposes a flexible communication solution for Low-Rate Wireless Personal Area Networks including sensor networks. It presents the advantage to fit different requirements of potential applications by adequately setting its parameters. When enabling its beacon mode, the protocol makes possible real-time guarantees by using its Guaranteed Time Slot (GTS) mechanism. This paper analyzes the performance of the GTS allocation mechanism in IEEE 802.15.4. The analysis gives a full understanding of the behavior of the GTS mechanism with regards to delay and throughput metrics. First, we propose two accurate models of service curves for a GTS allocation as a function of the IEEE 802.15.4 parameters. We then evaluate the delay bounds guaranteed by an allocation of a GTS using Network Calculus formalism. Finally, based on the analytic results, we analyze the impact of the IEEE 802.15.4 parameters on the throughput and delay bound guaranteed by a GTS allocation. The results of this work pave the way for an efficient dimensioning of an IEEE 802.15.4 cluster.
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The IEEE 802.15.4 protocol proposes a flexible communication solution for Low-Rate Wireless Personal Area Networks (LR-WPAN) including wireless sensor networks (WSNs). It presents the advantage to fit different requirements of potential applications by adequately setting its parameters. When in beaconenabled mode, the protocol can provide timeliness guarantees by using its Guaranteed Time Slot (GTS) mechanism. However, power-efficiency and timeliness guarantees are often two antagonistic requirements in wireless sensor networks. The purpose of this paper is to analyze and propose a methodology for setting the relevant parameters of IEEE 802.15.4-compliant WSNs that takes into account a proper trade-off between power-efficiency and delay bound guarantees. First, we propose two accurate models of service curves for a GTS allocation as a function of the IEEE 802.15.4 parameters, using Network Calculus formalism. We then evaluate the delay bound guaranteed by a GTS allocation and express it as a function of the duty cycle. Based on the relation between the delay requirement and the duty cycle, we propose a power-efficient superframe selection method that simultaneously reduces power consumption and enables meeting the delay requirements of real-time flows allocating GTSs. The results of this work may pave the way for a powerefficient management of the GTS mechanism in an IEEE 802.15.4 cluster.
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The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.
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Dispersion of returns has gained a lot of attention as a measure to distinguish good and bad investment opportunities time. In the following dissertation, the cross-sectional returns volatility is analyzed over a fifteen year period across the S&P100 Index composition. The main inference drawn from the data sample is that the canonical measure of dispersion is highly macro-risk driven and therefore more biased towards returns volatility rather than its correlation component.
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QUESTION UNDER STUDY: To assess which high-risk acute coronary syndrome (ACS) patient characteristics played a role in prioritising access to intensive care unit (ICU), and whether introducing clinical practice guidelines (CPG) explicitly stating ICU admission criteria altered this practice. PATIENTS AND METHODS: All consecutive patients with ACS admitted to our medical emergency centre over 3 months before and after CPG implementation were prospectively assessed. The impact of demographic and clinical characteristics (age, gender, cardiovascular risk factors, and clinical parameters upon admission) on ICU hospitalisation of high-risk patients (defined as retrosternal pain of prolonged duration with ECG changes and/or positive troponin blood level) was studied by logistic regression. RESULTS: Before and after CPG implementation, 328 and 364 patients, respectively, were assessed for suspicion of ACS. Before CPG implementation, 36 of the 81 high-risk patients (44.4%) were admitted to ICU. After CPG implementation, 35 of the 90 high-risk patients (38.9%) were admitted to ICU. Male patients were more frequently admitted to ICU before CPG implementation (OR=7.45, 95% CI 2.10-26.44), but not after (OR=0.73, 95% CI 0.20-2.66). Age played a significant role in both periods (OR=1.57, 95% CI 1.24-1.99), both young and advanced ages significantly reducing ICU admission, but to a lesser extent after CPG implementation. CONCLUSION: Prioritisation of access to ICU for high-risk ACS patients was age-dependent, but focused on the cardiovascular risk factor profile. CPG implementation explicitly stating ICU admission criteria decreased discrimination against women, but other factors are likely to play a role in bed allocation.
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Estudio de las distribuciones horizontales y verticales del zooplancton a lo largo de una línea desde cerca de la costa hasta el borde de la plataforma.
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Cuscuta spp. are holoparasitic plants that can simultaneously parasitise several host plants. It has been suggested that Cuscuta has evolved a foraging strategy based on a positive relationship between preuptake investment and subsequent reward on different host species. Here we establish reliable parasite size measures and show that parasitism on individuals of different host species alters the biomass of C. campestris but that within host species size and age also contributes to the heterogeneous resource landscape. We then performed two additional experiments to test whether C. campestris achieves greater resource acquisition by parasitising two host species rather than one and whether C. campestris forages in communities of hosts offering different rewards (a choice experiment). There was no evidence in either experiment for direct benefits of a mixed host diet. Cuscuta campestris foraged by parasitising the most rewarding hosts the fastest and then investing the most on them. We conclude that our data present strong evidence for foraging in the parasitic plant C. campestris.
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Mountain regions worldwide are particularly sensitive to on-going climate change. Specifically in the Alps in Switzerland, the temperature has increased twice as fast than in the rest of the Northern hemisphere. Water temperature closely follows the annual air temperature cycle, severely impacting streams and freshwater ecosystems. In the last 20 years, brown trout (Salmo trutta L) catch has declined by approximately 40-50% in many rivers in Switzerland. Increasing water temperature has been suggested as one of the most likely cause of this decline. Temperature has a direct effect on trout population dynamics through developmental and disease control but can also indirectly impact dynamics via food-web interactions such as resource availability. We developed a spatially explicit modelling framework that allows spatial and temporal projections of trout biomass using the Aare river catchment as a model system, in order to assess the spatial and seasonal patterns of trout biomass variation. Given that biomass has a seasonal variation depending on trout life history stage, we developed seasonal biomass variation models for three periods of the year (Autumn-Winter, Spring and Summer). Because stream water temperature is a critical parameter for brown trout development, we first calibrated a model to predict water temperature as a function of air temperature to be able to further apply climate change scenarios. We then built a model of trout biomass variation by linking water temperature to trout biomass measurements collected by electro-fishing in 21 stations from 2009 to 2011. The different modelling components of our framework had overall a good predictive ability and we could show a seasonal effect of water temperature affecting trout biomass variation. Our statistical framework uses a minimum set of input variables that make it easily transferable to other study areas or fish species but could be improved by including effects of the biotic environment and the evolution of demographical parameters over time. However, our framework still remains informative to spatially highlight where potential changes of water temperature could affect trout biomass. (C) 2015 Elsevier B.V. All rights reserved.-
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Remote monitoring of a power boiler allows the supplying company to make sure that equipment is used as supposed to and gives a good chance for process optimization. This improves co-operation between the supplier and the customer and creates an aura of trust that helps securing future contracts. Remote monitoring is already in use with recovery boilers but the goal is to expand especially to biomass-fired BFB-boilers. To make remote monitoring possible, data has to be measured reliably on site and the link between the power plant and supplying company’s server has to work reliably. Data can be gathered either with the supplier’s sensors or with measurements originally installed in the power plant if the plant in question is not originally built by the supplying company. Main goal in remote monitoring is process optimization and avoiding unnecessary accidents. This can be achieved for instance by following the efficiency curves and fouling in different parts of the process and comparing them to past values. The final amount of calculations depends on the amount of data gathered. Sudden changes in efficiency or fouling require further notice and in such a case it’s important that dialogue toward the power plant in question also works.
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In marine benthic communities, herbivores consume a considerable proportion of primary producer biomass and, thus, generate selection for the evolution of resistance traits. According to the theory of plant defenses, resistance traits are costly to produce and, consequently, inducible resistance traits are adaptive in conditions of variable herbivory, while in conditions of constant/strong herbivory constitutive resistance traits are selected for. The evolution of resistance plasticity may be constrained by the costs of resistance or lack of genetic variation in resistance. Furthermore, resource allocation to induced resistance may be affected by higher trophic levels preying on herbivores. I studied the resistance to herbivory of a foundation species, the brown alga Fucus vesiculosus. By using factorial field experiments, I explored the effects of herbivores and fish predators on growth and resistance of the alga in two seasons. I explored genetic variation in and allocation costs of resistance traits as well as their chemical basis and their effects on herbivore performance. Using a field experiment I tested if induced resistance spreads via water-borne cues from one individual to another in relevant ecological conditions. I found that in the northern Baltic Sea F. vesiculosus communities, strength of three trophic interactions strongly vary among seasons. The highly synchronized summer reproduction of herbivores promoted their escape from the top-down control of fish predators in autumn. This resulted into large grazing losses in algal stands. In spring, herbivore densities were low and regulated by fish, which, thus,enhanced algal growth. The resistance of algae to herbivory increased with an increase in constitutive phlorotannin content. Furthermore, individuals adopted induced resistance when grazed and when exposed to water-borne cues originating from grazing of conspecific algae both in the laboratory and in field conditions. Induced resistance was adopted to a lesser extent in the presence of fish predators. The results in this thesis indicate that inducible resistance in F. vesiculosus is an adaptation to varying herbivory in the northern Baltic Sea. The costs of resistance and strong seasonality of herbivory have likely contributed to the evolution of this defense strategy. My findings also show that fish predators have positive cascading effects on F. vesiculosus which arise via reduced herbivory but possibly also through reduced resource allocation to resistance. I further found evidence that the spread of resistance via water-borne cues also occurs in ecologically realistic conditions in natural marine sublittoral. Thus, water-borne induction may enable macroalgae to cope with the strong grazing pressure characteristic of marine benthic communities. The results presented here show that seasonality can have pronounced effects on the biotic interactions in marine benthic communities and thereafter influence the evolution of resistance traits in primary producers.
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Hub location problem is an NP-hard problem that frequently arises in the design of transportation and distribution systems, postal delivery networks, and airline passenger flow. This work focuses on the Single Allocation Hub Location Problem (SAHLP). Genetic Algorithms (GAs) for the capacitated and uncapacitated variants of the SAHLP based on new chromosome representations and crossover operators are explored. The GAs is tested on two well-known sets of real-world problems with up to 200 nodes. The obtained results are very promising. For most of the test problems the GA obtains improved or best-known solutions and the computational time remains low. The proposed GAs can easily be extended to other variants of location problems arising in network design planning in transportation systems.
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Hub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.