244 resultados para Line: profiles


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Most advanced musicians are able to identify and label a heard pitch if given an opportunity to compare it to a known reference note. This is called ‘relative pitch’ (RP). A much rarer skill is the ability to identify and label a heard pitch without the need for a reference. This is colloquially referred to as ‘perfect pitch’, but appears in the academic literature as ‘absolute pitch’ (AP). AP is considered by many as a remarkable skill. As people do not seem able to develop it intentionally, it is generally regarded as innate. It is often seen as a unitary skill and that a set of identifiable criteria can distinguish those who possess the skill from those who do not. However, few studies have interrogated these notions. The present study developed and applied an interactive computer program to map pitch-labelling responses to various tonal stimuli without a known reference tone available to participants. This approach enabled the identification of the elements of sound that impacted on AP. Pitch-labelling responses of 14 participants with AP were recorded for their accuracy. Each participant’s response to the stimuli was unique. Their accuracy of labelling varied across dimensions such as timbre, range and tonality. The diversity of performance between individuals appeared to reflect their personal musical experience histories.

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Principal Topic The Comprehensive Australian Study of Entrepreneurial Emergence (CAUSEE) represents the first Australian study to employ and extend the longitudinal and large scale systematic research developed for the Panel Study of Entrepreneurial Dynamics (PSED) in the US (Gartner, Shaver, Carter and Reynolds, 2004; Reynolds, 2007). This research approach addresses several shortcomings of other data sets including under coverage; selection bias; memory decay and hindsight bias, and lack of time separation between the assessment of causes and their assumed effects (Johnson et al 2006; Davidsson 2006). However, a remaining problem is that any a random sample of start-ups will be dominated by low potential, imitative ventures. In recognition of this issue CAUSEE supplemented PSED-type random samples with theoretically representative samples of the 'high potential' emerging ventures employing a unique methodology using novel multiple screening criteria. We define new ''high-potential'' ventures as new entrepreneurial innovative ventures with high aspirations and potential for growth. This distinguishes them from those ''lifestyle'' imitative businesses that start small and remain intentionally small (Timmons, 1986). CAUSEE is providing the opportunity to explore, for the first time, if process and outcomes of high potentials differ from those of traditional lifestyle firms. This will allows us to compare process and outcome attributes of the random sample with the high potential over sample of new firms and young firms. The attributes in which we will examine potential differences will include source of funding, and internationalisation. This is interesting both in terms of helping to explain why different outcomes occur but also in terms of assistance to future policymaking, given that high growth potential firms are increasingly becoming the focus of government intervention in economic development policies around the world. The first wave of data of a four year longitudinal study has been collected using these samples, allowing us to also provide some initial analysis on which to continue further research. The aim of this paper therefore is to present some selected preliminary results from the first wave of the data collection, with comparisons of high potential with lifestyle firms. We expect to see owing to greater resource requirements and higher risk profiles, more use of venture capital and angel investment, and more internationalisation activity to assist in recouping investment and to overcome Australia's smaller economic markets Methodology/Key Propositions In order to develop the samples of 'high potential' in the NF and YF categories a set of qualification criteria were developed. Specifically, to qualify, firms as nascent or young high potentials, we used multiple, partly compensating screening criteria related to the human capital and aspirations of the founders as well as the novelty of the venture idea, and venture high technology. A variety of techniques were also employed to develop a multi level dataset of sources to develop leads and firm details. A dataset was generated from a variety of websites including major stakeholders including the Federal and State Governments, Australian Chamber of Commerce, University Commercialisation Offices, Patent and Trademark Attorneys, Government Awards and Industry Awards in Entrepreneurship and Innovation, Industry lead associations, Venture Capital Association, Innovation directories including Australian Technology Showcase, Business and Entrepreneurs Magazines including BRW and Anthill. In total, over 480 industry, association, government and award sources were generated in this process. Of these, 74 discrete sources generated high potentials that fufilled the criteria. 1116 firms were contacted as high potential cases. 331 cases agreed to participate in the screener, with 279 firms (134 nascents, and 140 young firms) successfully passing the high potential criteria. 222 Firms (108 Nascents and 113 Young firms) completed the full interview. For the general sample CAUSEE conducts screening phone interviews with a very large number of adult members of households randomly selected through random digit dialing using screening questions which determine whether respondents qualify as 'nascent entrepreneurs'. CAUSEE additionally targets 'young firms' those that commenced trading from 2004 or later. This process yielded 977 Nascent Firms (3.4%) and 1,011 Young Firms (3.6%). These were directed to the full length interview (40-60 minutes) either directly following the screener or later by appointment. The full length interviews were completed by 594 NF and 514 YF cases. These are the cases we will use in the comparative analysis in this report. Results and Implications The results for this paper are based on Wave one of the survey which has been completed and the data obtained. It is expected that the findings will assist in beginning to develop an understanding of high potential nascent and young firms in Australia, how they differ from the larger lifestyle entrepreneur group that makes up the vast majority of the new firms created each year, and the elements that may contribute to turning high potential growth status into high growth realities. The results have implications for Government in the design of better conditions for the creation of new business, firms who assist high potentials in developing better advice programs in line with a better understanding of their needs and requirements, individuals who may be considering becoming entrepreneurs in high potential arenas and existing entrepreneurs make better decisions.

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Manual calibration of large and dynamic networks of cameras is labour intensive and time consuming. This is a strong motivator for the development of automatic calibration methods. Automatic calibration relies on the ability to find correspondences between multiple views of the same scene. If the cameras are sparsely placed, this can be a very difficult task. This PhD project focuses on the further development of uncalibrated wide baseline matching techniques.