932 resultados para Real electricity markets


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This thesis addresses the topic of real-time decision making by driverless (autonomous) city vehicles, i.e. their ability to make appropriate driving decisions in non-simplified urban traffic conditions. After addressing the state of research, and explaining the research question, the thesis presents solutions for the subcomponents which are relevant for decision making with respect to information input (World Model), information output (Driving Maneuvers), and the real-time decision making process. TheWorld Model is a software component developed to fulfill the purpose of collecting information from perception and communication subsystems, maintaining an up-to-date view of the vehicle’s environment, and providing the required input information to the Real-Time Decision Making subsystem in a well-defined, and structured way. The real-time decision making process consists of two consecutive stages. While the first decision making stage uses a Petri net to model the safetycritical selection of feasible driving maneuvers, the second stage uses Multiple Criteria Decision Making (MCDM) methods to select the most appropriate driving maneuver, focusing on fulfilling objectives related to efficiency and comfort. The complex task of autonomous driving is subdivided into subtasks, called driving maneuvers, which represent the output (i.e. decision alternatives) of the real-time decision making process. Driving maneuvers are considered as implementations of closed-loop control algorithms, each capable of maneuvering the autonomous vehicle in a specific traffic situation. Experimental tests in both a 3D simulation and real-world experiments attest that the developed approach is suitable to deal with the complexity of real-world urban traffic situations.

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Polymorphisms of glutathione transferases (GST) are important genetic determinants of susceptibility to environmental carcinogens (Rebbeck, 1997). The GSTs are a multigene family of dimeric enzymes involved in detoxification, and, in a few cases, the bioactivation of a variety of xenobiotics (Hayes et al., 1995). The cytosolic GST enzyme family consists of four major classes of enzymes, referred to as alpha, mu, pi and theta. Several members of this family (for example, GSTM1, GSTT1 and GSTP1) are polymorphic in human populations (Wormhoudt et al., 1999). Molecular epidemiology studies have examined the role of GST polymorphisms as susceptibility factors for environmentally and/or occupationally induced cancers (Wormhoudt et al., 1999). In particular, case-control studies showed a relationship between the GSTM1 null genotype and the development of cancer in association with smoking habits, which has been shown for cancers of the respiratory and gastrointestinal tracts as well as other cancer types (Miller et al., 1997). Only a few molecular epidemiological studies addressed the role of GSTT1 and GSTP1 polymorphisms in cancer susceptibility. Since GSTP1 is a key player in biotransformation/bioactivation of benzo(a)pyrene, GSTP1 may be even more important than GSTM1 in the prevention of tobacco-induced cancers (Harries et al., 1997; Harris et al., 1998). To date, this relationship has not been sufficiently addressed in humans. Comprehensive molecular epidemiological studies may add to the current knowledge of the role of GST polymorphisms in cancer susceptibility and extent of the knowledge gained from approaches that used phenotyping, such as GSTM1 activity as it relates to trans-stilbene oxide, or polymerase chain reaction (PCR) based genotyping of polymorphic isoenzymes (Bell et al., 1993; Pemble et al., 1994; Harries et al., 1997).

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Ascidians are marine invertebrates that have been a source of numerous cytotoxic compounds. Of the first six marine-derived drugs that made anticancer clinical trials, three originated from ascidian specimens. In order to identify new anti-neoplastic compounds, an ascidian extract library (143 samples) was generated and screened in MDA-MB-231 breast cancer cells using a real-time cell analyzer (RTCA). This resulted in 143 time-dependent cell response profiles (TCRP), which are read-outs of changes to the growth rate, morphology, and adhesive characteristics of the cell culture. Twenty-one extracts affected the TCRP of MDA-MB-231 cells and were further investigated regarding toxicity and specificity, as well as their effects on cell morphology and cell cycle. The results of these studies were used to prioritize extracts for bioassay-guided fractionation, which led to the isolation of the previously identified marine natural product, eusynstyelamide B (1). This bis-indole alkaloid was shown to display an IC50 of 5 μM in MDA-MB-231 cells. Moreover, 1 caused a strong cell cycle arrest in G2/M and induced apoptosis after 72 h treatment, making this molecule an attractive candidate for further mechanism of action studies.

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Economic competition between introduced and native aquaculture species is of interest for industry stakeholders since increased production can affect price formation if both aquaculture species are part of the same market or even substitutes. In this study, we focus on the Australian edible oyster industry, which is dominated by two major species—the native Sydney rock oyster (grown mainly in Queensland and New South Wales) and the non-native Pacific oyster (grown mainly in South Australia and Tasmania). We examine the integration of the Australian oyster market to determine if there exists a single or several markets. Short- and long-run own, cross-price and income flexibilities of demand are estimated for both species using an inverse demand system of equations. The results suggest that the markets for the two species are integrated. We found evidence that the development of the Pacific oyster industry has had an adverse impact on Sydney rock oyster prices. However, our results show that both species are not perfect substitutes. Demand for Sydney rock oysters is relatively inelastic in the long run, yet no long-run relationships can be identified for Pacific oysters, reflecting the developing nature of this sector.

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Due to the popularity of security cameras in public places, it is of interest to design an intelligent system that can efficiently detect events automatically. This paper proposes a novel algorithm for multi-person event detection. To ensure greater than real-time performance, features are extracted directly from compressed MPEG video. A novel histogram-based feature descriptor that captures the angles between extracted particle trajectories is proposed, which allows us to capture motion patterns of multi-person events in the video. To alleviate the need for fine-grained annotation, we propose the use of Labelled Latent Dirichlet Allocation, a “weakly supervised” method that allows the use of coarse temporal annotations which are much simpler to obtain. This novel system is able to run at approximately ten times real-time, while preserving state-of-theart detection performance for multi-person events on a 100-hour real-world surveillance dataset (TRECVid SED).

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Network Real-Time Kinematic (NRTK) is a technology that can provide centimeter-level accuracy positioning services in real time, and it is enabled by a network of Continuously Operating Reference Stations (CORS). The location-oriented CORS placement problem is an important problem in the design of a NRTK as it will directly affect not only the installation and operational cost of the NRTK, but also the quality of positioning services provided by the NRTK. This paper presents a Memetic Algorithm (MA) for the location-oriented CORS placement problem, which hybridizes the powerful explorative search capacity of a genetic algorithm and the efficient and effective exploitative search capacity of a local optimization. Experimental results have shown that the MA has better performance than existing approaches. In this paper we also conduct an empirical study about the scalability of the MA, effectiveness of the hybridization technique and selection of crossover operator in the MA.

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A systematic literature review and a comprehensive meta-analysis that combines the findings from existing studies, was conducted in this thesis to analyse the impact of traffic characteristics on crash occurrence. Sensitivity analyses were conducted to investigate the quality, publication bias and outlier bias of the various studies, and the time intervals used to measure traffic characteristics were considered. Based on this comprehensive and systematic review, and the results of the subsequent meta-analysis, major issues in study design, traffic and crash data, and model development and evaluation are discussed.

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The paper investigates whether Big-Four affiliated (B4A) firms earn audit premiums in an emerging economy context, using Bangladesh as a case. The joint determination of audit and non-audit service fees is also examined using a sample of 122 companies listed in the Dhaka Stock Exchange. Our findings reveal that although the B4A firms do not generally earn a fee premiumin Bangladesh, they charge higher audit fees for clients not purchasing non-audit services. This suggests that the B4A firms may actually lower audit fees to attract non-audit services, and cross subsidizes audit fees through non-audit-services fees. The lack of a B4A premium implies that there is lack of quality audit in emerging markets. We also document that audit and non-audit service fees are jointly determined in Bangladesh. Thus, we provide evidence of joint determination of audit and non-audit service fees in an emerging economy context.

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A new technique is presented for automatically identifying the phase connection of domestic customers. Voltage information from a reference three phase house is correlated with voltage information from other customer electricity meters on the same network to determine the highest probability phase connection. The techniques are purely based upon a time series of electrical voltage measurements taken by the household smart meters and no additional equipment is required. The method is demonstrated using real smart meter datasets to correctly identify the phase connections of 75 consumers on a low voltage distribution feeder.

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This research aims to understand what factors influence consumers' behaviour to subculture marketing and how companies can strategically overcome potential brand alienation. Findings validate cryptic marketing as a strategy for organizations to communicate effectively with their chosen market through the use of cryptic cues, symbols and messages while circumventing negative responses from non-target audiences. The thesis contributes to extending current understanding of marketing communication through the use of covert strategies, employing covert tactics on the non-target, wider market instead of the target, subculture market.

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Large-scale integration of non-inertial generators such as wind farms will create frequency stability issues due to reduced system inertia. Inertia based frequency stability study is important to predict the performance of power system with increased level of renewables. This paper focuses on the impact large-scale wind penetration on frequency stability of the Australian Power Network. MATLAB simulink is used to develop a frequency based dynamic model utilizing the network data from a simplified 14-generator Australian power system. The loss of generation is modeled as the active power disturbance and minimum inertia required to maintain the frequency stability is determined for five-area power system.