975 resultados para New Orleans, Louisiana.


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Longitudinal panel studies of large, random samples of business start-ups captured at the pre-operational stage allow researchers to address core issues for entrepreneurship research, namely, the processes of creation of new business ventures as well as their antecedents and outcomes. Here, we perform a methods-orientated review of all 83 journal articles that have used this type of data set, our purpose being to assist users of current data sets as well as designers of new projects in making the best use of this innovative research approach. Our review reveals a number of methods issues that are largely particular to this type of research. We conclude that amidst exemplary contributions, much of the reviewed research has not adequately managed these methods challenges, nor has it made use of the full potential of this new research approach. Specifically, we identify and suggest remedies for context-specific and interrelated methods challenges relating to sample definition, choice of level of analysis, operationalization and conceptualization, use of longitudinal data and dealing with various types of problematic heterogeneity. In addition, we note that future research can make further strides towards full utilization of the advantages of the research approach through better matching (from either direction) between theories and the phenomena captured in the data, and by addressing some under-explored research questions for which the approach may be particularly fruitful.

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Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance.

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Emergence and dissemination of community acquired methicillin resistant Staphylococcus aureus (CA-MRSA) strains are being reported with increasing frequency in Australia and worldwide. These strains of CA-MRSA are genetically diverse and distinct in Australia. Genotyping of CA-MRSA using eight highly-discriminatory single nucleotide polymorphisms (SNPs) is a rapid and robust method for monitoring the dissemination of these strains in the community. In this study, a SNP genotyping method was used to investigate the molecular epidemiology of 249 community acquired non-multiresistant MRSA (nm-MRSA) isolates over a 12-month period from routine diagnostic specimens. A real-time PCR for the presence of Panton-Valentine leukocidin (PVL) was also performed on these isolates. The CA-MRSA isolates were sourced from a large private laboratory in Brisbane, Australia that serves a wide geographic region encompassing Queensland and Northern New South Wales. This study identified 16 different STs and 98% of the CA-MRSA isolates were positive for the PVL gene. The most common ST was ST93 with 41% of isolates testing positive for this clone.

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Trust can be used for neighbor formation to generate automated recommendations. User assigned explicit rating data can be used for this purpose. However, the explicit rating data is not always available. In this paper we present a new method of generating trust network based on user’s interest similarity. To identify the interest similarity, we use user’s personalized tag information. This trust network can be used to find the neighbors to make automated recommendation. Our experiment result shows that the precision of the proposed method outperforms the traditional collaborative filtering approach.

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This paper presents a novel topology for the generation of high voltage pulses that uses both slow and fast solid-state power switches. This topology includes diode-capacitor units in parallel with commutation circuits connected to a positive buck-boost converter. This enables the generation of a range of high output voltages with a given number of capacitors. The advantages of this topology are the use of slow switches and a reduced number of diodes in comparison with conventional Marx generator. Simulations performed for single and repetitive pulse generation and experimental tests of a prototype hardware verify the proposed topology.

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This is the first article in a series of three that examines the legal role of medical professionals in decisions to withhold or withdraw life-sustaining treatment from adults who lack capacity. This article considers the position in New South Wales. A review of the law in this State reveals that medical professionals play significant legal roles in these decisions. However, the law is problematic in a number of respects and this is likely to impede medical professionals’ legal knowledge in this area. The article examines the level of training medical professionals receive on issues such as advance directives and substitute decision-making, and the available empirical evidence as to the state of medical professionals’ knowledge of the law at the end of life. It concludes that there are gaps in legal knowledge and that law reform is needed in New South Wales.

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Should new ventures stick to their knitting once they start commercialising or should they engage in frequent changes of their business idea? In this paper we argue that new ventures still need to learn their way in the early phases of commercialisation and that changes are good, but subject to two important contingencies. First is that changes should be aimed at enhancing uniqueness, which in turn enhances new venture performance. Second is that our results show that changes have limited affect on uniqueness and performance for entrepreneurs aiming at maximising opportunities, but that changing the business idea has a significant positive impact for entrepreneurs focusing on minimising losses. Our findings indicate that entrepreneurs aiming at minimising losses may offset their initial disadvantages by engaging in a series of adaptations of the business idea to gain higher performance and a more unique product offering.

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By integrating two theoretical foundations of entrepreneurship research, behaviour and process, this conceptual paper proposes a new model to examine the behaviour of the entrepreneur across the new venture development process. Existing macro level research on the new venture creation process recognises the entrepreneur as a central agent in the process yet generally avoids, at each stage of the process, an examination of the micro level psychological experiences of the individual entrepreneur. Similarly, behavioural research examining entrepreneur individual differences has failed to systematically explore the emotion and behaviour of the entrepreneur across the cycle of the new venture creation process. We propose a conceptual framework to integrate the new venture creation process of opportunity discovery, evaluation and exploitation, with the psychological capital (efficacy, hope, resilience and optimism) of the individual entrepreneur. Propositions for future research to facilitate deeper insight into the impact of entrepreneur behaviour on the new venture creation process and ultimately the success or failure of the new venture are provided.

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The emerging theory of ‘bricolage’ as a resource behaviour represents an attempt to address the central entrepreneurship research problem of making systematic sense of entrepreneurs that sometimes manage to create significant new economic activity under what appears to be severe resource constraints (Baker & Nelson 2005). However, despite growing interest in bricolage there is little large scale empirical evidence about the effectiveness and outcomes of using bricolage processes while developing innovative outcomes in nascent and young firms. In this research we test bricolage using different forms of innovation using data from the Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) project. Our results indicate overall positive results of bricolage with all forms of innovativeness. A discussion of the results and recommended future research is provided.

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Immigrant Entrepreneurs (IE) are often portrayed as being pushed into self-employment due to employment barriers in their adopted countries. But IE have human resources, like international experience, which can help them form international new ventures (INV). We question the role of IE in INV. We use randomly selected data from 561 young firms from the Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) project. We find that IE are overrepresented in INV and have many of the characteristics known to facilitate INV success. These findings have relevance to policy makers, IE and NE.

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Multilevel converters are used in high power and high voltage applications due to their attractive benefits in generating high quality output voltage. Increasing the number of voltage levels can lead to a reduction in lower order harmonics. Various modulation and control techniques are introduced for multilevel converters like Space Vector Modulation (SVM), Sinusoidal Pulse Width Modulation (SPWM) and Harmonic Elimination (HE) methods. Multilevel converters may have a DC link with equal or unequal DC voltages. In this paper a new modulation technique based on harmonic elimination method is proposed for those multilevel converters that have unequal DC link voltages. This new technique has better effect on output voltage quality and less Total Harmonic Distortion (THD) than other modulation techniques. In order to verify the proposed modulation technique, MATLAB simulations are carried out for a single-phase diode-clamped inverter.

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Teaching is emotional work. This is especially the case in the first years of teaching when new teachers are particularly vulnerable. By understanding changes in teacher emotions in the early years of teaching we hope to identify strategies that might ultimately reduce teacher attrition. As part of a larger study of the transition of new teachers to the profession, this ethnographic case study explores how a new science teacher produced and reproduced positive emotional interaction rituals with her students in her first year of teaching. We show how dialogical interactions were positive and satisfying experiences for the teacher, and how they were reproduced successfully in different contexts. We also illustrate how both teacher and students used humor to create a structure for dialogical interactions. During these successful interactions the students used shared resources to satisfy their teacher that they were engaging in the relevant science content. The implications of what we have learned for the professional development of new teachers are discussed in relation to an expanded understanding of teacher emotions.

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Modern technologies mean that the principles of quality arts education are the same (as they ever were) and different. Discussion in this paper is based on a small research project that used art as pedagogy, art as research method and, for the young children participants, celebrated art for art's sake. The project was designed with two aims. Firstly, the authors were interested in how young children engage with media as a strand of the arts. This also informed some of their thinking around the debates over Information and Communication Technology (ICT) as a process for the production of a media text. Secondly, they were interested in the extent to which digital media could enable young children to make their learning visible.

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Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.