83 resultados para cluster analysis


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A novel near-infrared spectroscopy (NIRS) method has been researched and developed for the simultaneous analyses of the chemical components and associated properties of mint (Mentha haplocalyx Briq.) tea samples. The common analytes were: total polysaccharide content, total flavonoid content, total phenolic content, and total antioxidant activity. To resolve the NIRS data matrix for such analyses, least squares support vector machines was found to be the best chemometrics method for prediction, although it was closely followed by the radial basis function/partial least squares model. Interestingly, the commonly used partial least squares was unsatisfactory in this case. Additionally, principal component analysis and hierarchical cluster analysis were able to distinguish the mint samples according to their four geographical provinces of origin, and this was further facilitated with the use of the chemometrics classification methods-K-nearest neighbors, linear discriminant analysis, and partial least squares discriminant analysis. In general, given the potential savings with sampling and analysis time as well as with the costs of special analytical reagents required for the standard individual methods, NIRS offered a very attractive alternative for the simultaneous analysis of mint samples.

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It has been proposed that body image disturbance is a form of cognitive bias wherein schemas for self-relevant information guide the selective processing of appearancerelated information in the environment. This threatening information receives disproportionately more attention and memory, as measured by an Emotional Stroop and incidental recall task. The aim of this thesis was to expand the literature on cognitive processing biases in non-clinical males and females by incorporating a number of significant methodological refinements. To achieve this aim, three phases of research were conducted. The initial two phases of research provided preliminary data to inform the development of the main study. Phase One was a qualitative exploration of body image concerns amongst males and females recruited through the general community and from a university. Seventeen participants (eight male; nine female) provided information on their body image and what factors they saw as positively and negatively impacting on their self evaluations. The importance of self esteem, mood, health and fitness, and recognition of the social ideal were identified as key themes. These themes were incorporated as psycho-social measures and Stroop word stimuli in subsequent phases of the research. Phase Two involved the selection and testing of stimuli to be used in the Emotional Stroop task. Six experimental categories of words were developed that reflected a broad range of health and body image concerns for males and females. These categories were high and low calorie food words, positive and negative appearance words, negative emotion words, and physical activity words. Phase Three addressed the central aim of the project by examining cognitive biases for body image information in empirically defined sub-groups. A National sample of males (N = 55) and females (N = 144), recruited from the general community and universities, completed an Emotional Stroop task, incidental memory test, and a collection of psycho-social questionnaires. Sub-groups of body image disturbance were sought using a cluster analysis, which identified three sub-groups in males (Normal, Dissatisfied, and Athletic) and four sub-groups in females (Normal, Health Conscious, Dissatisfied, and Symptomatic). No differences were noted between the groups in selective attention, although time taken to colour name the words was associated with some of the psycho-social variables. Memory biases found across the whole sample for negative emotion, low calorie food, and negative appearance words were interpreted as reflecting the current focus on health and stigma against being unattractive. Collectively these results have expanded our understanding of processing biases in the general community by demonstrating that the processing biases are found within non-clinical samples and that not all processing biases are associated with negative functionality

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One of the features of the sporting industry is the ritualized way in which it is consumed across the world. Fans of every sport have rituals and superstitions to help them enjoy the spectacle, socialize with other like-minded fans, and reduce some of the anxiety of watching their team play. These rituals include dress, barracking styles and pre and post match behaviors. What is not known are the factors that lead fans to engage in ritual behaviors and what relationship rituals have with desirable outcomes such as increased attendance, attitudinal loyalty or satisfaction. Given that some ritual behaviors are clearly undesirable, (e.g., hooliganism), understanding these relationships is important to managers who may be questioning whether rituals should be encouraged. Although ritualized behavior amongst fans is clearly visible, the symbolic and emotional nature of ritual poses challenges to researchers. Most previous ritual research is exploratory and qualitative in nature. This study, however, uses a behavior-based scale to measure fan ritual and relates it to desirable outcomes such as commitment and attendance. Over 2,000 season ticket holders of a football (soccer) team in Australia’s professional A-League competition were surveyed to investigate the antecedents and consequences of fan ritual behavior. Cluster analysis was used to explore the characteristics of respondents, and it revealed that those fans that engage in ritual behavior also differed on many other demographic and attitudinal dimensions. The associations between ritual and psychological commitment, and ritual and attendance are positive and significant. When used in conjunction with other constructs, fan ritual also improves the explanation of attendance behavior. The findings support previous research that found a significant and positive relationship between team identification, involvement and attendance, and extend previous research by finding a significant and positive relationship between rituals and attendance. For sports marketing practitioners, the results indicate the importance of developing and managing consumption rituals tied to game day attendance, with a view to generating uncommon loyalty.

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The identification of attractors is one of the key tasks in studies of neurobiological coordination from a dynamical systems perspective, with a considerable body of literature resulting from this task. However, with regards to typical movement models investigated, the overwhelming majority of actions studied previously belong to the class of continuous, rhythmical movements. In contrast, very few studies have investigated coordination of discrete movements, particularly multi-articular discrete movements. In the present study, we investigated phase transition behavior in a basketball throwing task where participants were instructed to shoot at the basket from different distances. Adopting the ubiquitous scaling paradigm, throwing distance was manipulated as a candidate control parameter. Using a cluster analysis approach, clear phase transitions between different movement patterns were observed in performance of only two of eight participants. The remaining participants used a single movement pattern and varied it according to throwing distance, thereby exhibiting hysteresis effects. Results suggested that, in movement models involving many biomechanical degrees of freedom in degenerate systems, greater movement variation across individuals is available for exploitation. This observation stands in contrast to movement variation typically observed in studies using more constrained bi-manual movement models. This degenerate system behavior provides new insights and poses fresh challenges to the dynamical systems theoretical approach, requiring further research beyond conventional movement models.

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Multivariate methods are required to assess the interrelationships among multiple, concurrent symptoms. We examined the conceptual and contextual appropriateness of commonly used multivariate methods for cancer symptom cluster identification. From 178 publications identified in an online database search of Medline, CINAHL, and PsycINFO, limited to articles published in English, 10 years prior to March 2007, 13 cross-sectional studies met the inclusion criteria. Conceptually, common factor analysis (FA) and hierarchical cluster analysis (HCA) are appropriate for symptom cluster identification, not principal component analysis. As a basis for new directions in symptom management, FA methods are more appropriate than HCA. Principal axis factoring or maximum likelihood factoring, the scree plot, oblique rotation, and clinical interpretation are recommended approaches to symptom cluster identification.

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Communication is one team process factor that has received considerable research attention in the team literature. This literature provides equivocal evidence regarding the role of communication in team performance and yet, does not provide any evidence for when communication becomes important for team performance. This research program sought to address this evidence gap by a) testing task complexity and team member diversity (race diversity, gender diversity and work value diversity) as moderators of the team communication — performance relationship; and b) testing a team communication — performance model using established teams across two different task types. The functional perspective was used as the theoretical framework for operationalizing team communication activity. The research program utilised a quasi-experimental research design with participants from a large multi-national information technology company whose Head Office was based in Sydney, Australia. Participants voluntarily completed two team building exercises (a decision making and production task), and completed two online questionnaires. In total, data were collected from 1039 individuals who constituted 203 work teams. Analysis of the data revealed a small number of significant moderation effects, not all in the expected direction. However, an interesting and unexpected finding also emerged from Study One. Large and significant correlations between communication activity ratings were found across tasks, but not within tasks. This finding suggested that teams were displaying very similar profiles of communication on each task, despite the tasks having different communication requirements. Given this finding, Study Two sought to a) determine the relative importance of task versus team effects in explaining variance in team communication measures for established teams; b) determine if established teams had reliable and discernable team communication profiles and if so, c) investigate whether team communication profiles related to task performance. Multi-level modeling and repeated measures analysis of variance (ANOVA) revealed that task type did not have an effect on team communication ratings. However, teams accounted for 24% of the total variance in communication measures. Through cluster analysis, five reliable and distinct team communication profiles were identified. Consistent with the findings of the multi-level analysis and repeated measures ANOVA, teams’ profiles were virtually identical across the decision making and production tasks. A relationship between communication profile and performance was identified for the production task, although not for the decision making task. This research responds to calls in the literature for a better understanding of when communication becomes important for team performance. The moderators tested in this research were not found to have a substantive or reliable effect on the relationship between communication and performance. However, the consistency in team communication activity suggests that established teams can be characterized by their communication profiles and further, that these communication profiles may have implications for team performance. The findings of this research provide theoretical support for the functional perspective in terms of the communication – performance relationship and further support the team development literature as an explanation for the stability in team communication profiles. This research can also assist organizations to better understand the specific types of communication activity and profiles of communication that could offer teams a performance advantage.

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OBJECTIVES: To develop and validate a wandering typology. ---------- DESIGN: Cross-sectional, correlational descriptive design. ---------- SETTING:: Twenty-two nursing homes and six assisted living facilities. ---------- PARTICIPANTS: One hundred forty-two residents with dementia who spoke English, met Diagnostic and Statistical Manual for Mental Disorders, Fourth Edition, criteria for dementia, scored less than 24 on the Mini-Mental State Examination (MMSE), were ambulatory (with or without assistive device), and maintained a stable regime of psychotropic medications were studied. ---------- MEASUREMENTS: Data on wandering were collected using direct observations, plotted serially according to rate and duration to yield 21 parameters, and reduced through factor analysis to four components: high rate, high duration, low to moderate rate and duration, and time of day. Other measures included the MMSE, Minimum Data Set 2.0 mobility items, Cumulative Illness Rating Scale—Geriatric, and tympanic body temperature readings. ---------- RESULTS: Three groups of wanderers were identified through cluster analysis: classic, moderate, and subclinical. MMSE, mobility, and cardiac and upper and lower gastrointestinal problems differed between groups of wanderers and in comparison with nonwanderers. ---------- CONCLUSION: Results have implications for improving identification of wanderers and treatment of possible contributing factors.

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Advances in symptom management strategies through a better understanding of cancer symptom clusters depend on the identification of symptom clusters that are valid and reliable. The purpose of this exploratory research was to investigate alternative analytical approaches to identify symptom clusters for patients with cancer, using readily accessible statistical methods, and to justify which methods of identification may be appropriate for this context. Three studies were undertaken: (1) a systematic review of the literature, to identify analytical methods commonly used for symptom cluster identification for cancer patients; (2) a secondary data analysis to identify symptom clusters and compare alternative methods, as a guide to best practice approaches in cross-sectional studies; and (3) a secondary data analysis to investigate the stability of symptom clusters over time. The systematic literature review identified, in 10 years prior to March 2007, 13 cross-sectional studies implementing multivariate methods to identify cancer related symptom clusters. The methods commonly used to group symptoms were exploratory factor analysis, hierarchical cluster analysis and principal components analysis. Common factor analysis methods were recommended as the best practice cross-sectional methods for cancer symptom cluster identification. A comparison of alternative common factor analysis methods was conducted, in a secondary analysis of a sample of 219 ambulatory cancer patients with mixed diagnoses, assessed within one month of commencing chemotherapy treatment. Principal axis factoring, unweighted least squares and image factor analysis identified five consistent symptom clusters, based on patient self-reported distress ratings of 42 physical symptoms. Extraction of an additional cluster was necessary when using alpha factor analysis to determine clinically relevant symptom clusters. The recommended approaches for symptom cluster identification using nonmultivariate normal data were: principal axis factoring or unweighted least squares for factor extraction, followed by oblique rotation; and use of the scree plot and Minimum Average Partial procedure to determine the number of factors. In contrast to other studies which typically interpret pattern coefficients alone, in these studies symptom clusters were determined on the basis of structure coefficients. This approach was adopted for the stability of the results as structure coefficients are correlations between factors and symptoms unaffected by the correlations between factors. Symptoms could be associated with multiple clusters as a foundation for investigating potential interventions. The stability of these five symptom clusters was investigated in separate common factor analyses, 6 and 12 months after chemotherapy commenced. Five qualitatively consistent symptom clusters were identified over time (Musculoskeletal-discomforts/lethargy, Oral-discomforts, Gastrointestinaldiscomforts, Vasomotor-symptoms, Gastrointestinal-toxicities), but at 12 months two additional clusters were determined (Lethargy and Gastrointestinal/digestive symptoms). Future studies should include physical, psychological, and cognitive symptoms. Further investigation of the identified symptom clusters is required for validation, to examine causality, and potentially to suggest interventions for symptom management. Future studies should use longitudinal analyses to investigate change in symptom clusters, the influence of patient related factors, and the impact on outcomes (e.g., daily functioning) over time.

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Transportation disadvantaged groups, in the previous studies, are defined as those who are low income earners, family dependent, limited access to private motor vehicles and public transport services, and also those who oblige to spend relatively more time and money on their trips. Additionally those disable, young and elderly are considered among the natural groups of transportation disadvantaged. Although in general terms this definition seems correct, it is not specific enough to become a common universal definition that could apply to all urban contexts. This paper investigates whether travel difficulty perceptions vary and so does the definition of transportation disadvantaged in socio-culturally different urban contexts. For this investigation the paper undertakes a series of statistical analysis in the case study of Yamaga, Japan, and compares the findings with a previous case study, where the same methodology, hypothesis, and assumptions were utilized in a culturally and demographically different settlement of Aydin, Turkey. After comparing the findings observed in Aydin with the statistical analysis results of Yamaga, this paper reveals that there can be no explicitly detailed universal definition of transportation disadvantaged. The paper concludes by stating characteristics of transportation disadvantage is not globally identical, and policies and solutions that work in a locality may not show the same results in another socio-cultural context.

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This paper presents a method for calculating the in-bucket payload volume on a dragline for the purpose of estimating the material’s bulk density in real-time. Knowledge of the bulk density can provide instant feedback to mine planning and scheduling to improve blasting and in turn provide a more uniform bulk density across the excavation site. Furthermore costs and emissions in dragline operation, maintenance and downstream material processing can be reduced. The main challenge is to determine an accurate position and orientation of the bucket with the constraint of real-time performance. The proposed solution uses a range bearing and tilt sensor to locate and scan the bucket between the lift and dump stages of the dragline cycle. Various scanning strategies are investigated for their benefits in this real-time application. The bucket is segmented from the scene using cluster analysis while the pose of the bucket is calculated using the iterative closest point (ICP) algorithm. Payload points are segmented from the bucket by a fixed distance neighbour clustering method to preserve boundary points and exclude low density clusters introduced by overhead chains and the spreader bar. A height grid is then used to represent the payload from which the volume can be calculated by summing over the grid cells. We show volume calculated on a scaled system with an accuracy of greater than 95 per cent.

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The current research aimed to profile off-road riders to identify specific sub-groups in relation to their risk-related behaviours and perceptions. A total of 235 adults from the Australian state of Queensland who had ridden a motorcycle or ATV off-road in the last 12 months were recruited. A cluster analysis was applied to the survey data. Two distinct clusters of riders were identified, which corresponded with the self-report of injury from an off-road riding crash in the prior 12 months. The injured cluster had a significantly higher mean risk propensity and use of safety equipment, though did not differ on self-reported risk taking. The injured cluster as a whole included a higher percentage of males, was younger, and rode more often for recreational or competitive purposes than the non-crash involved cluster. The results indicate that the crash cluster may be both more aware of the potential risks of riding and more willing to ride in a riskier manner.

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This paper presents a method for measuring the in-bucket payload volume on a dragline excavator for the purpose of estimating the material's bulk density in real-time. Knowledge of the payload's bulk density can provide feedback to mine planning and scheduling to improve blasting and therefore provide a more uniform bulk density across the excavation site. This allows a single optimal bucket size to be used for maximum overburden removal per dig and in turn reduce costs and emissions in dragline operation and maintenance. The proposed solution uses a range bearing laser to locate and scan full buckets between the lift and dump stages of the dragline cycle. The bucket is segmented from the scene using cluster analysis, and the pose of the bucket is calculated using the Iterative Closest Point (ICP) algorithm. Payload points are identified using a known model and subsequently converted into a height grid for volume estimation. Results from both scaled and full scale implementations show that this method can achieve an accuracy of above 95%.

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The most common human cancers are malignant neoplasms of the skin. Incidence of cutaneous melanoma is rising especially steeply, with minimal progress in non-surgical treatment of advanced disease. Despite significant effort to identify independent predictors of melanoma outcome, no accepted histopathological, molecular or immunohistochemical marker defines subsets of this neoplasm. Accordingly, though melanoma is thought to present with different 'taxonomic' forms, these are considered part of a continuous spectrum rather than discrete entities. Here we report the discovery of a subset of melanomas identified by mathematical analysis of gene expression in a series of samples. Remarkably, many genes underlying the classification of this subset are differentially regulated in invasive melanomas that form primitive tubular networks in vitro, a feature of some highly aggressive metastatic melanomas. Global transcript analysis can identify unrecognized subtypes of cutaneous melanoma and predict experimentally verifiable phenotypic characteristics that may be of importance to disease progression.

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Although germline mutations in CDKN2A are present in approximately 25% of large multicase melanoma families, germline mutations are much rarer in the smaller melanoma families that make up most individuals reporting a family history of this disease. In addition, only three families worldwide have been reported with germline mutations in a gene other than CDKN2A (i.e., CDK4). Accordingly, current genomewide scans underway at the National Human Genome Research Institute hope to reveal linkage to one or more chromosomal regions, and ultimately lead to the identification of novel genes involved in melanoma predisposition. Both CDKN2A and PTEN have been identified as genes involved in sporadic melanoma development; however, mutations are more common in cell lines than uncultured tumors. A combination of cytogenetic, molecular, and functional studies suggests that additional genes involved in melanoma development are located to chromosomal regions 1p, 6q, 7p, 11q, and possibly also 9p and 10q. With the near completion of the human genome sequencing effort, combined with the advent of high throughput mutation analyses and new techniques including cDNA and tissue microarrays, the identification and characterization of additional genes involved in melanoma pathogenesis seem likely in the near future.

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Grocery shopping is a routine activity widely considered the responsibility of the female spouse, yet modern social and demographic shifts are causing men to engage in this task. This study develops a retail shopping typology of male grocery shoppers, employing a cluster analysis technique. Five distinct cohorts emerge from the data of eight constructs, measured by seventy one items. One new shopper type emerges from this research. This shopper presented as a younger man, at the commencement of their family lifecycle, attracted by a strong value offer, focusing on price and promotional discounts. Our research offers a contribution to the marketing, consumer behaviour and supermarket retailing disciplines in three ways. By examining and identifying male shopping behaviour in the context of grocery shopping, the development of a retail shopping typology of male grocery shoppers and the extension and employment of a cluster analysis in identifying distinct groups. This research has implications for gender, segmentation studies and consumer behaviour disciplines in regard to grocery shopping. The identification of specific groups of male grocery shoppers will enable grocery retailers to effectively implement important, targeted marketing strategies.