4 resultados para Rank Correlation
em Aston University Research Archive
Resumo:
Whole life costing (WLC) has become the best practice in construction procurement and it is likely to be a major issue in predicting whole life costs of a construction project accurately. However, different expectations from different organizations throughout a project's life and the lack of data, monitoring targets, and long-term interest for many key players are obstacles to be overcome if WLC is to be implemented. A questionnaire survey was undertaken to investigate a set of ten common factors and 188 individual factors. These were grouped into eight critical categories (project scope, time, cost, quality, contract/administration, human resource, risk, and health and safety) by project phase, as perceived by the clients, contractors and subcontractors in order to identify critical success factors for whole life performance assessment (WLPA). Using a relative importance index, the top ten critical factors for each category, from the perspective of project participants, were analyzed and ranked. Their agreement on those categories and factors were analyzed using Spearman's rank correlation. All participants identify “Type of Project” as the most common critical factor in the eight categories for WLPA. Using the relative index ranking technique and weighted average methods, it was found that the most critical individual factors in each category were: “clarity of contract” (scope); “fixed construction period” (time); “precise project budget estimate” (cost); “material quality” (quality); “mutual/trusting relationships” (contract/administration); “leadership/team management” (human resource); and “management of work safety on site” (health and safety). There was relatively a high agreement on these categories among all participants. Obviously, with 80 critical factors of WLPA, there is a stronger positive relationship between client and contactor rather than contractor and subcontractor, client and subcontractor. Putting these critical factors into a criteria matrix can facilitate an initial framework of WLPA in order to aid decision making in the public sector in South Korea for evaluation/selection process of a construction project at the bid stage.
Resumo:
This study was concerned with the structure, functions and development, especially the performance, of some rural small firms associated with the Council for Small Industries in Rural Areas (C?SIRA) of England. Forty firms were used as the main basis of analysis. For some aspects of the investigation, however, data from another 54 firms, obtained indirectly through nine CoSIRA Organisers, were also used. For performance-analysis, the 40 firms were firstly ranked according to their growth and profitability rates which were calculated from their financial data. Then each of the variables hypothesised to be related to performance was tested to ascertain its relationship with performance, using the Spearman's Rank Correlation technique. The analysis indicated that each of the four factors .. the principal, the firm itself, its management, and the environment - had a bearing upon the performance of the firm. Within the first factor, the owner-manager's background and attitudes were found to be most important; in the second, the firm's size, age and scope of activities were also found to be correlated with performance; with respect to the third, it was revealed that firms which practised some forms of systems in planning, control and costing performed better than those which did not and, finally with respect to the fourth factor, it was found that some of the services provided by CoSIRA, especially credit finance, were facilitative to the firm's performance. Another significant facet of the firms highlighted by the study was their multifarious roles. These, meeting economic, psychological, sociological and political needs, were considered to be most useful to man and his society. Finally, the study has added light to the structural characteristics of the sampled firms, including various aspects of their development, orientation and organisation, as well as their various structural strengths and weakness. ' .
Resumo:
Purpose: To investigate the correlation between tests of visual function and perceived visual ability recorded with a 'quality-of-life' questionnaire for patients with central field loss. Method: 12 females and 7 males (mean age = 53.1 years; Range = 23 - 80 years) with subfoveal neovascular membranes underwent a comprehensive assessment of visual function. Tests included unaided distance vision, high and low contrast distance logMAR visual acuity (VA), Pelli-Robson contrast senstivity (at 1m), near logMAR word VA and text reading speed. All tests were done both monocularly and binocularly. The patients also completed a 28 point questionnaire separated into a 'core' section consisting of general questions about perceived visual function and a 'module' section with specific questions on reading function. Results: Step-wise multiple regression analysis was used to determine which visual function tests were correlated with the patients's perceived visual function and to rank them in order of importance. The visual function test that explains most of the variance in both 'core' score (66%0 and the 'module' score (68%) of the questionnaire is low contrast VA in the better eye (P<0.001 in both cases). Further, the module score also accounts for a significant proportion of the variance (P<0.01) of the distance logMAR VA in both the better and worse eye, and the near logMAR in both the better eye and binocularly. Conclusions: The best predictor of both perceived reading ability and of general perceived visual ability in this study is low contrast logMAR VA. The results highlight that distance VA is not the only relevant measure of visual fucntion in relation to a patients's perceived visual performance and should not be considered a determinant of surgical or management success.
Resumo:
Social media influence analysis, sometimes also called authority detection, aims to rank users based on their influence scores in social media. Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users’ influence scores. They rarely consider a person’s expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally ”Sina microblogging”). We found that there is a strong correlation between expertise levels and social media influence scores. Our analysis gave a good explanation of the phenomenon of “top across-domain influencers”. In addition, different expertise levels showed influence variation patterns: e.g., (1) high-expertise celebrities have stronger influence on the “audience” in their expertise domains; (2) expertise seems to be more important than relevance and participation for social media influence; (3) the audiences of top expertise celebrities are more likely to forward tweets on topics outside the expertise domains from high-expertise celebrities.