6,733 research outputs found

    Atomic-scale visualization of quasiparticle interference on a type-II Weyl semimetal surface

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    We combine quasiparticle interference simulation (theory) and atomic resolution scanning tunneling spectro-microscopy (experiment) to visualize the interference patterns on a type-II Weyl semimetal Mox_{x}W1x_{1-x}Te2_2 for the first time. Our simulation based on first-principles band topology theoretically reveals the surface electron scattering behavior. We identify the topological Fermi arc states and reveal the scattering properties of the surface states in Mo0.66_{0.66}W0.34_{0.34}Te2_2. In addition, our result reveals an experimental signature of the topology via the interconnectivity of bulk and surface states, which is essential for understanding the unusual nature of this material.Comment: To appear in Phys. Rev. Let

    Basic of Fault Tree (FT) method

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    A fault tree described the logical relationship between events and causes. This method shows significant success in analyzing the root cause of an accident. This paper will review the basics of the Fault Tree (FT) method including the structure, factors that contribute and FT application

    Evolutionary computation enabled game theory based modelling of electricity market behaviours and applications

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    The collapse of the Californian electricity market system in 2001 has highlighted urgency in research in intelligent electricity trading systems and strategies involving both suppliers and customs. In their trading systems, power generation companies under the new electricity trading arrangement (NETA) of the UK are now developing gaming strategies. However, modelling of such "intelligent" market behaviours is extremely challenging, because traditional mathematical and computer modelling techniques cannot cope with the involvement of game theory. In this paper, evolutionary computation enabled modelling of such system is presented. Both competitive and cooperative game theory strategies are taken into account in evolving the intelligent model. The model then leads to intelligent trading strategy development and decision support. Experimental tests, verification and validation are carried out with various strategies, using different model scales and data published by NETA. Results show that evolutionary computation enabled game theory involved modelling and decision making provides an effective tool for NETA trading analysis, prediction and support

    WSC-07: Evolving the Web Services Challenge

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    Service-oriented architecture (SOA) is an evolving architectural paradigm where businesses can expose their capabilities as modular, network-accessible software services. By decomposing capabilities into modular services, organizations can share their offerings at multiple levels of granularity while also creating unique access points for their peer organizations. The true impact of SOA will be realized when 3rd party organizations can obtain a variety of services, on-demand, and create higher-order composite business processes. The Web Services Challenge (WSC) is a forum where academic and industry researchers can share experiences of developing tools that automate the integration of web services. In the third year (i.e. WSC-07) of the Web Services Challenge, software platforms will address several new composition challenges. Requests and results will be transmitted within SOAP messages. In addition, semantic representations will be both represented in the eXtensible Markup Language (XML) and in the Web Ontology Language (OWL). Finally, composite processes will have both sequential and concurrent branches

    Green Trade Agreements: Comparison of Canada, US and WTO

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    Paper presented at the CAES/NAREA meeting, Quebec City, June 29 - July 1, 2008.trade, free trade agreements, environment, World Trade Organization, Environmental Economics and Policy, International Relations/Trade,

    The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms

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    open access articleWe present Stochastic Optimisation Software (SOS), a Java platform facilitating the algorithmic design process and the evaluation of metaheuristic optimisation algorithms. SOS reduces the burden of coding miscellaneous methods for dealing with several bothersome and time-demanding tasks such as parameter tuning, implementation of comparison algorithms and testbed problems, collecting and processing data to display results, measuring algorithmic overhead, etc. SOS provides numerous off-the-shelf methods including: (1) customised implementations of statistical tests, such as the Wilcoxon rank-sum test and the Holm–Bonferroni procedure, for comparing the performances of optimisation algorithms and automatically generating result tables in PDF and formats; (2) the implementation of an original advanced statistical routine for accurately comparing couples of stochastic optimisation algorithms; (3) the implementation of a novel testbed suite for continuous optimisation, derived from the IEEE CEC 2014 benchmark, allowing for controlled activation of the rotation on each testbed function. Moreover, we briefly comment on the current state of the literature in stochastic optimisation and highlight similarities shared by modern metaheuristics inspired by nature. We argue that the vast majority of these algorithms are simply a reformulation of the same methods and that metaheuristics for optimisation should be simply treated as stochastic processes with less emphasis on the inspiring metaphor behind them

    Indirect Pathways Into Practice: A Comparative Examination of Indian and Philippine Internationally Educated Nurses and Their Entry Into Ontario’s Nursing Profession

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    In Canada half of all internationally educated nurses (IENs) are employed in Ontario, and in 2010 the top three countries where new IENs had received their training were the Philippines, India and China. This presentation reports on preliminary results from an ongoing research project examining the experiences of IENs from the Philippines and India who intend to enter Ontario’s nursing profession indirectly via temporary migration streams. The preliminary survey results will be presented, including differences in the characteristics and experiences of the two groups as they follow migration and occupational pathways to enter Canada and the nursing profession in Ontario. The preliminary findings will highlight some of the issues the data reveal in terms of specific settlement experiences, issues of effective conversion of pre-migration training into professional practice post-migration, and how policy shifts toward temporary and two-step migration may be shaping the nature of IENs’ indirect pathways into practice

    Organic Trends 8

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    Newsletter on Organic agriculture and food development in China

    Differential evolution with an evolution path: a DEEP evolutionary algorithm

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    Utilizing cumulative correlation information already existing in an evolutionary process, this paper proposes a predictive approach to the reproduction mechanism of new individuals for differential evolution (DE) algorithms. DE uses a distributed model (DM) to generate new individuals, which is relatively explorative, whilst evolution strategy (ES) uses a centralized model (CM) to generate offspring, which through adaptation retains a convergence momentum. This paper adopts a key feature in the CM of a covariance matrix adaptation ES, the cumulatively learned evolution path (EP), to formulate a new evolutionary algorithm (EA) framework, termed DEEP, standing for DE with an EP. Without mechanistically combining two CM and DM based algorithms together, the DEEP framework offers advantages of both a DM and a CM and hence substantially enhances performance. Under this architecture, a self-adaptation mechanism can be built inherently in a DEEP algorithm, easing the task of predetermining algorithm control parameters. Two DEEP variants are developed and illustrated in the paper. Experiments on the CEC'13 test suites and two practical problems demonstrate that the DEEP algorithms offer promising results, compared with the original DEs and other relevant state-of-the-art EAs

    CPLD based controller for single phase inverters

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    The DC-AC converter, also known as inverter, converts DC power to AC power at desired output voltage and frequency. The DC power input to the inverter is obtained from an existing power supply. Nowadays inverters use high power switching transistors either IGBT's and/or MOSFETs. In addition, the voltage and frequency of the source can be adjustable. These single phase inverters and their operating principles are analyzed in detail. In this project, a full-bridge, single phase inverter that uses a digital Pulse Width Modulation (PWM) to control the power switches at 18 kHz was constructed. The concept of PWM with different strategies for inverters is described. A type of filter is used to improve the distortion in the output waveform. A design and implementation of PWM by using complex programmable logic device (CPLD) from Altera MaxPlus II is constructed and programmed. The involved software, hardware, and suitable algorithm to implement and generate the PWM are developed in details. To verify the significant of this single phase inverter, the output voltage will be tested with resistive load and inductive load
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