870 resultados para Combination of short term inflation forecast models
Resumo:
Terrestrial gastropods are both herbivores and detritivores, but the ratio between these two modes of feeding can be highly variable over time. While previous studies have examined long-term seasonal patterns in the consumption of fresh material, mechanisms explaining short-term variation in dietary preferences have not been explored. We used faecal analysis to determine how short-term variation in weather affects the ratio of herbivory to detritivory in the land snail Cepaea nemoralis. Averaged across sampling dates, c. 9% of the faeces were composed of fresh plant material, with the remainder consisting of plant litter and soil. Temperature, relative humidity and soil moisture did not affect the proportional consumption of fresh material; however, snails consumed more soil with increasing temperature. If there had not been a recent precipitation event, the mean proportion of fresh material in the faeces more than doubled on average; however, this increase only occurred in areas of low herbaceous cover. Our results suggest that an increased proportion of snails consume fresh material during dry periods to compensate for water losses. Moreover, our study highlights that studies of dietary composition in the field need to account for short-term variation in feeding
preferences caused by weather.
Resumo:
The renewed concern in assessing risks and consequences from technological hazards in industrial and urban areas continues emphasizing the development of local-scale consequence analysis (CA) modelling tools able to predict shortterm pollution episodes and exposure effects on humans and the environment in case of accident with hazardous gases (hazmat). In this context, the main objective of this thesis is the development and validation of the EFfects of Released Hazardous gAses (EFRHA) model. This modelling tool is designed to simulate the outflow and atmospheric dispersion of heavy and passive hazmat gases in complex and build-up areas, and to estimate the exposure consequences of short-term pollution episodes in accordance to regulatory/safety threshold limits. Five main modules comprising up-to-date methods constitute the model: meteorological, terrain, source term, dispersion, and effects modules. Different initial physical states accident scenarios can be examined. Considered the main core of the developed tool, the dispersion module comprises a shallow layer modelling approach capable to account the main influence of obstacles during the hazmat gas dispersion phenomena. Model validation includes qualitative and quantitative analyses of main outputs by the comparison of modelled results against measurements and/or modelled databases. The preliminary analysis of meteorological and source term modules against modelled outputs from extensively validated models shows the consistent description of ambient conditions and the variation of the hazmat gas release. Dispersion is compared against measurements observations in obstructed and unobstructed areas for different release and dispersion scenarios. From the performance validation exercise, acceptable agreement was obtained, showing the reasonable numerical representation of measured features. In general, quality metrics are within or close to the acceptance limits recommended for ‘non-CFD models’, demonstrating its capability to reasonably predict hazmat gases accidental release and atmospheric dispersion in industrial and urban areas. EFRHA model was also applied to a particular case study, the Estarreja Chemical Complex (ECC), for a set of accidental release scenarios within a CA scope. The results show the magnitude of potential effects on the surrounding populated area and influence of the type of accident and the environment on the main outputs. Overall the present thesis shows that EFRHA model can be used as a straightforward tool to support CA studies in the scope of training and planning, but also, to support decision and emergency response in case of hazmat gases accidental release in industrial and built-up areas.
Resumo:
Climate changes are foreseen to produce a large impact in the morphology of estuaries and coastal systems. The morphology changes will subsequently drive changes in the biologic compartments of the systems and ultimately in their ecosystems. Sea level rise is one of the main factors controlling these changes. Morphologic changes can be better understood with the use of long term morphodynamic mathematical models.
Resumo:
In situ observations of clam dredging showed that the effects of the dredge on the benthic macrofauna may not be constant during a tow. A sand buffer forms in front of the gear approximately 10m after the beginning of a tow, and this pushes the sediment partially aside.In this study, we analyse differences in abundance, the number of taxa present, diversity, and evenness within sections of dredge-tracks in a disturbed, fished area and a non-fished area along the southern coast of Portugal. These areas were sampled by divers before and after dredge-fishing activity. At each site, three dredge-tracks were produced. These tracks were divided in three longitudinal sections 1start, middle and end) and two transverse sections 1track and edge). Six quadrats were used to sample macrofauna in each section of every track and edge. Our results show differences exist in macro- faunal distribution and abundance across sections of a dredge-track. These differences should be considered in any assessment of the short-term ecological impact of dredges on benthic macrofauna
Resumo:
The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.
Resumo:
The current regulatory framework for maintenance outage scheduling in distribution systems needs revision to face the challenges of future smart grids. In the smart grid context, generation units and the system operator perform new roles with different objectives, and an efficient coordination between them becomes necessary. In this paper, the distribution system operator (DSO) of a microgrid receives the proposals for shortterm (ST) planned outages from the generation and transmission side, and has to decide the final outage plans, which is mandatory for the members to follow. The framework is based on a coordination procedure between the DSO and other market players. This paper undertakes the challenge of optimization problem in a smart grid where the operator faces with uncertainty. The results show the effectiveness and applicability of the proposed regulatory framework in the modified IEEE 34- bus test system.
Resumo:
Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.
Resumo:
Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.
Resumo:
In the current context of serious climate changes, where the increase of the frequency of some extreme events occurrence can enhance the rate of periods prone to high intensity forest fires, the National Forest Authority often implements, in several Portuguese forest areas, a regular set of measures in order to control the amount of fuel mass availability (PNDFCI, 2008). In the present work we’ll present a preliminary analysis concerning the assessment of the consequences given by the implementation of prescribed fire measures to control the amount of fuel mass in soil recovery, in particular in terms of its water retention capacity, its organic matter content, pH and content of iron. This work is included in a larger study (Meira-Castro, 2009(a); Meira-Castro, 2009(b)). According to the established praxis on the data collection, embodied in multidimensional matrices of n columns (variables in analysis) by p lines (sampled areas at different depths), and also considering the quantitative data nature present in this study, we’ve chosen a methodological approach that considers the multivariate statistical analysis, in particular, the Principal Component Analysis (PCA ) (Góis, 2004). The experiments were carried out in a soil cover over a natural site of Andaluzitic schist, in Gramelas, Caminha, NW Portugal, who was able to maintain itself intact from prescribed burnings from four years and was submit to prescribed fire in March 2008. The soils samples were collected from five different plots at six different time periods. The methodological option that was adopted have allowed us to identify the most relevant relational structures inside the n variables, the p samples and in two sets at the same time (Garcia-Pereira, 1990). Consequently, and in addition to the traditional outputs produced from the PCA, we have analyzed the influence of both sampling depths and geomorphological environments in the behavior of all variables involved.
Resumo:
Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.
Resumo:
L’observation d’un modèle pratiquant une habileté motrice promeut l’apprentissage de l’habileté en question. Toutefois, peu de chercheurs se sont attardés à étudier les caractéristiques d’un bon modèle et à mettre en évidence les conditions d’observation pouvant optimiser l’apprentissage. Dans les trois études composant cette thèse, nous avons examiné les effets du niveau d’habileté du modèle, de la latéralité du modèle, du point de vue auquel l’observateur est placé, et du mode de présentation de l’information sur l’apprentissage d’une tâche de timing séquentielle composée de quatre segments. Dans la première expérience de la première étude, les participants observaient soit un novice, soit un expert, soit un novice et un expert. Les résultats des tests de rétention et de transfert ont révélé que l’observation d’un novice était moins bénéfique pour l’apprentissage que le fait d’observer un expert ou une combinaison des deux (condition mixte). Par ailleurs, il semblerait que l’observation combinée de modèles novice et expert induise un mouvement plus stable et une meilleure généralisation du timing relatif imposé comparativement aux deux autres conditions. Dans la seconde expérience, nous voulions déterminer si un certain type de performance chez un novice (très variable, avec ou sans amélioration de la performance) dans l’observation d’une condition mixte amenait un meilleur apprentissage de la tâche. Aucune différence significative n’a été observée entre les différents types de modèle novices employés dans l’observation de la condition mixte. Ces résultats suggèrent qu’une observation mixte fournit une représentation précise de ce qu’il faut faire (modèle expert) et que l’apprentissage est d’autant plus amélioré lorsque l’apprenant peut contraster cela avec la performance de modèles ayant moins de succès. Dans notre seconde étude, des participants droitiers devaient observer un modèle à la première ou à la troisième personne. L’observation d’un modèle utilisant la même main préférentielle que soi induit un meilleur apprentissage de la tâche que l’observation d’un modèle dont la dominance latérale est opposée à la sienne, et ce, quel que soit l’angle d’observation. Ce résultat suggère que le réseau d’observation de l’action (AON) est plus sensible à la latéralité du modèle qu’à l’angle de vue de l’observateur. Ainsi, le réseau d’observation de l’action semble lié à des régions sensorimotrices du cerveau qui simulent la programmation motrice comme si le mouvement observé était réalisé par sa propre main dominante. Pour finir, dans la troisième étude, nous nous sommes intéressés à déterminer si le mode de présentation (en direct ou en vidéo) influait sur l’apprentissage par observation et si cet effet est modulé par le point de vue de l’observateur (première ou troisième personne). Pour cela, les participants observaient soit un modèle en direct soit une présentation vidéo du modèle et ceci avec une vue soit à la première soit à la troisième personne. Nos résultats ont révélé que l’observation ne diffère pas significativement selon le type de présentation utilisée ou le point de vue auquel l’observateur est placé. Ces résultats sont contraires aux prédictions découlant des études d’imagerie cérébrale ayant montré une activation plus importante du cortex sensorimoteur lors d’une observation en direct comparée à une observation vidéo et de la première personne comparée à la troisième personne. Dans l’ensemble, nos résultats indiquent que le niveau d’habileté du modèle et sa latéralité sont des déterminants importants de l’apprentissage par observation alors que le point de vue de l’observateur et le moyen de présentation n’ont pas d’effets significatifs sur l’apprentissage d’une tâche motrice. De plus, nos résultats suggèrent que la plus grande activation du réseau d’observation de l’action révélée par les études en imagerie mentale durant l’observation d’une action n’induit pas nécessairement un meilleur apprentissage de la tâche.
Resumo:
The flammability of short Kevlar aramide fiber-thermoplastic polyurethane (TPU) has been investigated with respect to fiber loading and various flame retardant additives such as halogen containing polymers, antimony oxide/chlorine donor combination, zinc borate, and aluminum hydroxide. Smoke generation was reduced drastically, while the oxygen index was reduced marginally in the presence of short fibers. The best improvement in the oxygen index was obtained with antimony oxide/chlorinated paraffin wax combination, in the weight ratio 1:6. A 70 phr loading of aluminum hydroxide improved LOI and reduced smoke generation.
Resumo:
Applicaciò d'un model de hydrodinàmica i de qualitat de l'aigua als embassaments de Sau i Boadella
Resumo:
Aquesta tesi doctoral està basada en el desenvolupament de nous agents antimicrobians derivats del pèptid híbrid cecropina A-melitina WKLFKKILKVL-NH2 (Pep3) que siguin sostenibles i útils per al control de malalties de plantes. Es van dissenyar i sintetitzar més de 133 anàlegs de Pep3 mitjançant química combinatòria. Es van obtenir anàlegs de Pep3 amb una elevada activitat contra fitopatògens i que presentaven baixa toxicitat. Els millors anàlegs van presentar eficàcies comparables amb pesticides de referència en la prevenció d'infeccions causades per fitopatògens. Es va estudiar el mecanisme d'acció de KKLFKKILKYL-NH2 (BP100) investigant la seva interacció amb models de membrana mitjançant tècniques espectroscòpiques. Es va observar la capacitat de BP100 a induir la permeabilització, la neutralització, i l'agregació de vesícules lipídiques aniòniques a una determinada concentració llindar. Es va deduir una equació que relaciona la CMI d'un pèptid antimicrobià amb la constant de partició i la concentració llindar en la membrana.
Resumo:
This report provides a forecast of the potential direct and indirect influences of various kinds of technologies on the LTC milieu, answering the following question: from a technology-driven perspective: “Consider each technological solution. What could be its future usage in the LTC sector?” Future technological deployments will induce changes in the respective roles of the care recipient and of the formal and informal carers, with an impact on three major concerns: the transformation of the care recipient into a proactive subject, the augmented potentiality for home care and the new functions that informal carers could assume.