37 resultados para Short stories, Russian.


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O Short Sea Shipping (SSS) é um conceito de transporte marítimo de difícil definição. No entanto, considera-se neste trabalho, que corresponde ao movimento de carga e passageiros por mar entre portos situados geográficamente na Europa ou entre outros portos que não estejam situados na Europa, mas que partilham costa com mares que banham a Europa. Esta definição é sem dúvida aquela que melhor se adequa à inclusão do Short SSS como elo de uma cadeia multimodal de transporte de mercadorias no espaço Europeu, e como alternativa ao transporte de mercadorias apenas por estrada. Este trabalho aborda alguns conceitos importantes subjacentes ao transporte marítimo de forma a permitir uma contextualização que possibilite uma melhor compreensão da abordagem feita ao SSS. A sua promoção e implementação, como alternativa viável para o transporte de mercadorias dentro do espaço Europeu, são objetivos da política de transportes da União Europeia (UE). Este trabalho reflete sobre algumas das políticas estratégicas de promoção da UE para impulsionar o SSS como alternativa ao transporte rodoviário. O objetivo deste trabalho é analisar se o SSS é uma alternativa ao transporte terrestre, no contexto de uma distribuição no Reino Unido de produtos de uma Industria localizada nos arredores da cidade do Porto. Neste trabalho analisou-se as vantagens e desvantagens do SSS, foi efetuada uma descrição do Porto de Leixões como porto escolhido para as expedições, assim como uma análise descritiva dos serviços de Short Sea disponiveis neste porto para as zonas de distribuição desta empresa. Foram descritos os fatores chave da mudança de transporte terrestre para SSS, efectuada uma caracterização da distribuição desta empresa e da solução que esta adotou para distribuir os seus produtos no Reino Unido. A anállise económica da operação, dos tempos de trânsito são dois temas fundamentais para a viabilidade da solução como alternativa ao transporte terrestre.

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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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Data Mining (DM) methods are being increasingly used in prediction with time series data, in addition to traditional statistical approaches. This paper presents a literature review of the use of DM with time series data, focusing on short- time stocks prediction. This is an area that has been attracting a great deal of attention from researchers in the field. The main contribution of this paper is to provide an outline of the use of DM with time series data, using mainly examples related with short-term stocks prediction. This is important to a better understanding of the field. Some of the main trends and open issues will also be introduced.

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First IFAC Workshop on Fractional Differentiation and Its Application - 19-21 July 2004, Enseirb, Bordeaux, France - FDA'04

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This paper reports investigation on the estimation of the short circuit impedance of power transformers, using fractional order calculus to analytically study the influence of the diffusion phenomena in the windings. The aim is to better characterize the medium frequency range behavior of leakage inductances of power transformer models, which include terms to represent the magnetic field diffusion process in the windings. Comparisons between calculated and measured values are shown and discussed.

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In this paper, we formulate the electricity retailers’ short-term decision-making problem in a liberalized retail market as a multi-objective optimization model. Retailers with light physical assets, such as generation and storage units in the distribution network, are considered. Following advances in smart grid technologies, electricity retailers are becoming able to employ incentive-based demand response (DR) programs in addition to their physical assets to effectively manage the risks of market price and load variations. In this model, the DR scheduling is performed simultaneously with the dispatch of generation and storage units. The ultimate goal is to find the optimal values of the hourly financial incentives offered to the end-users. The proposed model considers the capacity obligations imposed on retailers by the grid operator. The profit seeking retailer also has the objective to minimize the peak demand to avoid the high capacity charges in form of grid tariffs or penalties. The non-dominated sorting genetic algorithm II (NSGA-II) is used to solve the multi-objective problem. It is a fast and elitist multi-objective evolutionary algorithm. A case study is solved to illustrate the efficient performance of the proposed methodology. Simulation results show the effectiveness of the model for designing the incentive-based DR programs and indicate the efficiency of NSGA-II in solving the retailers’ multi-objective problem.

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This work explores the use of fluorescent probes to evaluate the responses of the green alga Pseudokirchneriella subcapitata to the action of three nominal concentrations of Cd(II), Cr(VI), Cu(II) and Zn(II) for a short time (6 h). The toxic effect of the metals on algal cells was monitored using the fluorochromes SYTOX Green (SG, membrane integrity), fluorescein diacetate (FDA, esterase activity) and rhodamine 123 (Rh123, mitochondrial membrane potential). The impact of metals on chlorophyll a (Chl a) autofluorescence was also evaluated. Esterase activity was the most sensitive parameter. At the concentrations studied, all metals induced the loss of esterase activity. SG could be used to effectively detect the loss of membrane integrity in algal cells exposed to 0.32 or 1.3 μmol L−1 Cu(II). Rh123 revealed a decrease in the mitochondrial membrane potential of algal cells exposed to 0.32 and 1.3 μmol L−1 Cu(II), indicating that mitochondrial activity was compromised. Chl a autofluorescence was also affected by the presence of Cr(VI) and Cu(II), suggesting perturbation of photosynthesis. In conclusion, the fluorescence-based approach was useful for detecting the disturbance of specific cellular characteristics. Fluorescent probes are a useful diagnostic tool for the assessment of the impact of toxicants on specific targets of P. subcapitata algal cells.