Marketing Turistikog Odredista

Turisti danas imaju na raspolaganju pregršt mogućih odredišta za godišnji odmor. Na današnjem izrazito kompetitivnom turističkom tržištu, za konkurentnost odredišta nužna je učinkovita organizacija marketinga. Knjiga “Marketing turističkog odredišta” bavi se izazovima vezanim uz promociju odredišta na dinamičnim i heterogenim tržištima, te na razliku između onih koji se turizmom bave praktično i onih koji se njime bave akademski. Pisan od strane jednog “praktičara”, “Marketing turističkog odredišta” spaja turizam kao poslovni sektor i polje akademskog znanja, sintetizirajući mnoštvo akademske literature od izuzetnog praktičnog značaja za organizacije za upravljanje turističkim odredištima.

Destination brand positions of a competitive set of near-home destinations

Although the branding literature commenced during the 1940s, the first publications related to destination branding did not emerge until half a century later. A review of 74 destination branding publications by 102 authors from the first 10 years of destination branding literature (1998-2007) found at least nine potential research gaps warranting attention by researchers. In particular, there has been a lack of research examining the extent to which brand positioning campaigns have been successful in enhancing brand equity in the manner intended in the brand identity. The purpose of this paper is to report the results of an investigation of brand equity tracking for a competitive set of destinations in Queensland, Australia between 2003 and 2007. A hierarchy of consumer-based brand equity (CBBE) provided an effective means to monitor destination brand positions over time. A key implication of the results was the finding that there was no change in brand positions for any of the five destinations over the four year period. This leads to the proposition that destination position change within a competitive set will only occur slowly over a long period of time. The tabulation of 74 destination branding case studies, research papers, conceptual papers and web content analyses provides students and researchers with a useful resource on the current state of the field.

Destination brand equity among the host community : a potential source of comparative advantage for DMO's

Since the emergence of the destination branding literature in 1998, there have been few studies related to performance measurement of destination brand campaigns. There has also been little interest to date in researching the extent to which a destination brand represents the host community’s sense of place. Given that local residents represent a key stakeholder group for the destination marketing organisation (DMO), research is required to examine the extent to which marketing communications have been effective in enhancing engagement with the brand, and inducing a brand image that is congruent with the brand identity. Motivated by conceptual and practical aims, this paper reports the trial of a hierarchy of consumer-based brand equity (CBBE) for a destination, from the perspective of residents as active participants of local tourism. It is proposed that strong levels of CBBE among the host community representsa strong level of CBBE among the host community represents a source of comparative advantage for a destination, for which the DMO could proactively develop into a competitive advantage.

How can entrepreneurial musicians use electronic social networks to diffuse their music

Principal Topic: ''In less than ten years music labels will not exist anymore.'' Michael Smelli, former Global COO Sony/BMG MCA/QUT IMP Business Lab Digital Music Think Thanks 9 May 2009, Brisbane Big music labels such as EMI, Sony BMG and UMG have been responsible for promoting and producing a myriad of stars in the music industry over the last decades. However, the industry structure is under enormous threat with the emergence of a new innovative era of digital music. Recent years have seen a dramatic shift in industry power with the emergence of Napster and other file sharing sites, iTunes and other online stores, iPod and the MP3 revolution. Myspace.com and other social networking sites are connecting entrepreneurial artists with fans and creating online music communities independent of music labels. In 2008 the digital music business internationally grew by around 25% to 3.7 Billion US-Dollar. Digital platforms now account for around 20% of recorded music sales, up from 15 % in 2007 (IFPI Digital music report 2009). CD sales have fallen by 40% since their peak levels. Global digital music sales totalled an estimated US$ 3 Billion in 2007, an increase of 40% on 2006 figures. Digital sales account for an estimated 15% of global market, up from 11% in 2006 and zero in 2003. The music industry is more advanced in terms of digital revenues than any other creative or entertainment industry (except games). Its digital share is more than twice that of newspapers (7%), films (35) or books (2%). All these shifts present new possibilities for music entrepreneurs to act entrepreneurially and promote their music independently of the major music labels. Diffusion of innovations has a long tradition in both sociology (e.g. Rogers 1962, 2003) and marketing (Bass 1969, Mahajan et al., 1990). The context of the current project is theoretically interesting in two respects. First, the role of online social networks replaces traditional face-to-face word of mouth communications. Second, as music is a hedonistic product, this strongly influences the nature of interpersonal communications and their diffusion patterns. Both of these have received very little attention in the diffusion literature to date, and no studies have investigated the influence of both simultaneously. This research project is concerned with the role of social networks in this new music industry landscape, and how this may be leveraged by musicians willing to act entrepreneurially. Our key research question we intend to address is: How do online social network communities impact the nature, pattern and speed that music diffuses? Methodology/Key Propositions : We expect the nature/ character of diffusion of popular, generic music genres to be different from specialized, niche music. To date, only Moe & Fader (2002) and Lee et al. (2003) investigated diffusion patterns of music and these focus on forecast weekly sales of music CDs based on the advance purchase orders before the launch, rather than taking a detailed look at diffusion patterns. Consequently, our first research questions are concerned with understanding the nature of online communications within the context of diffusion of music and artists. Hence, we have the following research questions: RQ1: What is the nature of fan-to-fan ''word of mouth'' online communications for music? Do these vary by type of artist and genre of music? RQ2: What is the nature of artist-to-fan online communications for music? Do these vary by type of artist and genre of music? What types of communication are effective? Two outcomes from research social network theory are particularly relevant to understanding how music might diffuse through social networks. Weak tie theory (Granovetter, 1973), argues that casual or infrequent contacts within a social network (or weak ties) act as a link to unique information which is not normally contained within an entrepreneurs inner circle (or strong tie) social network. A related argument, structural hole theory (Burt, 1992), posits that it is the absence of direct links (or structural holes) between members of a social network which offers similar informational benefits. Although these two theories argue for the information benefits of casual linkages, and diversity within a social network, others acknowledge that a balanced network which consists of a mix of strong ties, weak ties is perhaps more important overall (Uzzi, 1996). It is anticipated that the network structure of the fan base for different types of artists and genres of music will vary considerably. This leads to our third research question: RQ3: How does the network structure of online social network communities impact the pattern and speed that music diffuses? The current paper is best described as theory elaboration. It will report the first exploratory phase designed to develop and elaborate relevant theory (the second phase will be a quantitative study of network structure and diffusion). We intend to develop specific research propositions or hypotheses from the above research questions. To do so we will conduct three focus group discussions of independent musicians and three focus group discussions of fans active in online music communication on social network sites. We will also conduct five case studies of bands that have successfully built fan bases through social networking sites (e.g. myspace.com, facebook.com). The idea is to identify which communication channels they employ and the characteristics of the fan interactions for different genres of music. We intend to conduct interviews with each of the artists and analyse their online interaction with their fans. Results and Implications : At the current stage, we have just begun to conduct focus group discussions. An analysis of the themes from these focus groups will enable us to further refine our research questions into testable hypotheses. Ultimately, our research will provide a better understanding of how social networks promote the diffusion of music, and how this varies for different genres of music. Hence, some music entrepreneurs will be able to promote their music more effectively. The results may be further generalised to other industries where online peer-to-peer communication is common, such as other forms of entertainment and consumer technologies.

The power of a single prototype : sustainable fashion textile design and the prevention of carcinogenic melanoma

Is there a role for prototyping (sketching, pattern making and sampling) in addressing real world problems of sustainability (People, Profit, and Planet), in this case social/healthcare issues, through fashion and textiles research? Skin cancer and related illnesses are a major cause of disfigurement and death in New Zealand and Australia where the rates of Melanoma, a serious form of skin cancer, are four times higher than in the Northern Hemisphere regions of USA, UK and Canada (IARC, 1992). In 2007, AUT University (Auckland University of Technology) Fashion Department and the Health Promotion Department of Cancer Society - Auckland Division (CSA) developed a prototype hat aimed at exploring a barrier type solution to prevent facial and neck skin damage. This is a paradigm shift from the usual medical research model. This paper provides an overview of the project and examines how a fashion prototype has been used to communicate emergent social, environmental, personal, physiological and technological concerns to the trans-disciplinary research team. The authors consider how the design of a product can enhance and support sustainable design practice while contributing a potential solution to an ongoing health issue. Analysis of this case study provides an insight into prototyping in fashion and textiles design, user engagement and the importance of requirements analysis in relation to sustainable development. The analysis and a successful outcome of the final prototype have provided a gateway to future collaborative research and product development.

What causes childhood leukaemia? Some beliefs of parents of affected children

The theories of parents about the cause of their children's leukaemia have been documented in the course of a case-control study. From a sample of 175 children who were diagnosed as having acute lymphoblastic leukaemia, 91.4% of their parents put forward their theories. Some of these theories were related clearly to material that had been published and therefore had some scientific validity. Other theories often had no apparent scientific basis. Persons who are involved in the care of children with leukaemia should be aware of the wide variety of theories that are held by their parents so that they may provide counselling which could be of help in the relief of feelings of anxiety or guilt among the parents. Parents should always be afforded the opportunity to put forward their own theories so that they may be discussed on a rational basis. It is conceivable that some parents might put forward new hypotheses about leukaemogenesis that could be tested scientifically.

The effectiveness of marketing communication within the immersive environment

Immersive environments are part of a recent media innovation that allow users to become so involved within a computer-based simulated environment that they feel part of that virtual world (Grigorovici, 2003). A specific example is Second Life, which is an internet-based, three-dimensional immersive virtual world in which users create an online representation of themselves (an avatar) to play games and interact socially with thousands of people simultaneously. This study focuses on Second Life as an example of an immersive environment, as it is the largest adult freeform virtual world, home to 12 million avatars (IOWA State University, 2008). Already in Second Life there are more than 100 real-life brands from a range of industries, including automotive, professional services, and consumer goods and travel, among others (KZero, 2007; New Business Horizons, 2009). Compared to traditional advertising media, this interactive media can immerse users in the environment. As a result of this interactivity, users can become more involved with a virtual environment, resulting in prolonged usage over weeks, months and even years. Also, it can facilitate presence. Despite these developments, little is known about the effectiveness of marketing messages in a virtual world context. Marketers are incorporating products into Second Life using a strategy of online product placement. This study, therefore, explores the perceived effectiveness of online product placement in Second Life in terms of effects on product/brand recall, purchase intentions and trial. This research examines the association between individuals’ involvement with Second Life and online product placement effectiveness, as well as the relationship between individuals’ Second Life involvement and the effectiveness of online product placement. In addition, it investigates the association of immersion and product placement involvement. It also examines the impact of product placement involvement on online product placement effectiveness and the role of presence in affecting this relationship. An exploratory study was conducted for this research using semi-structured in-depth interviews face-to-face, email-based and in-world. The sample comprised 24 active Second Life users. Results indicate that product placement effectiveness is not directly associated with Second Life involvement, but rather effectiveness is impacted through the effect of Second Life involvement on product placement involvement. A positive relationship was found between individuals’ product placement involvement and online product placement effectiveness. Findings also indicate that online product placement effectiveness is not directly associated with immersion. Rather, it appears that effectiveness is impacted through the effect of immersion on product placement involvement. Moreover, higher levels of presence appear to have a positive impact on the relationship between product placement involvement and product placement effectiveness. Finally, a model was developed from this qualitative study for future testing. In terms of theoretical contributions, this study provides a new model for testing the effectiveness of product placement within immersive environments. From a methodological perspective, in-world interviews as a new research method were undertaken. In terms of a practical contribution, findings identified useful information for marketers and advertising agencies that aim to promote their products in immersive virtual environments like Second Life.

Teachers’ understanding of school connectedness : implications for the development and implementation of school based injury prevention strategies

Aim: Worldwide, injury is the leading cause of death and disability for young people. Injuries among young people are commonly associated with risk taking behaviour, including violence and transport risks, which often occur in the context of alcohol use. The school environment has been identified as having a significant role in shaping adolescent behaviour. In particular, school connectedness, the degree to which adolescents feel that they belong and are accepted at school, has been shown to be an important protective factor. Strategies for increasing school connectedness may therefore be effective in reducing risk taking and associated injury. Prior to developing connectedness strategies, it is important to understand the perspectives of those in the school regarding the construct and how it is realised in the school context. The aim of this research was to understand teachers’ perspectives of school connectedness, the strategies they employ to connect with students, and their perceptions of school connectedness as a strategy for risk taking and injury prevention. Method: In depth interviews of approximately 45 minutes duration were conducted with 13 Health and PE teachers and support staff from 2 high schools in Southeast Queensland, Australia. Additionally, 6 focus group workshop discussions were held with 35 Education department employees (5-6 per group), including teachers from 15 Southeast Queensland high schools. Results: Participants were found to place strong importance on the development of connectedness among students, including those at risk for problem behaviour. Strategies used to promote connectedness included building trust, taking an interest in each student and being available to talk to, and finding something positive for students to succeed at. Teachers identified strategies as being related to decreased risk taking behavior. Teacher training on school connectedness was perceived as an important and useful inclusion in a school based injury prevention program. Conclusions: The established link between increased school connectedness and decreased problem behaviour has implications for school based strategies designed to decrease adolescent risk taking behaviour and associated injury. Targeting school connectedness as a point of intervention, in conjunction with individual attitude and behaviour change programs, may be an effective injury prevention strategy.

The effects of exercise-induced weight loss on appetite-related peptides and motivation to eat

Context: The magnitude of exercise-induced weight loss depends on the extent of compensatory responses. An increase in energy intake is likely to result from changes in the appetite control system toward an orexigenic environment; however, few studies have measured how exercise impacts on both orexigenic and anorexigenic peptides. ---------- Objective: The aim of the study was to investigate the effects of medium-term exercise on fasting/postprandial levels of appetite-related hormones and subjective appetite sensations in overweight/obese individuals. ---------- Design and Setting: We conducted a longitudinal study in a university research center. ---------- Participants and Intervention: Twenty-two sedentary overweight/obese individuals (age, 36.9 ± 8.3 yr; body mass index, 31.3 ± 3.3 kg/m2) took part in a 12-wk supervised exercise programme (five times per week, 75% maximal heart rate) and were requested not to change their food intake during the study. ---------- Main Outcome Measures: We measured changes in body weight and fasting/postprandial plasma levels of glucose, insulin, total ghrelin, acylated ghrelin (AG), peptide YY, and glucagon-like peptide-1 and feelings of appetite. ---------- Results: Exercise resulted in a significant reduction in body weight and fasting insulin and an increase in AG plasma levels and fasting hunger sensations. A significant reduction in postprandial insulin plasma levels and a tendency toward an increase in the delayed release of glucagon-like peptide-1 (90–180 min) were also observed after exercise, as well as a significant increase (127%) in the suppression of AG postprandially. ---------- Conclusions: Exercise-induced weight loss is associated with physiological and biopsychological changes toward an increased drive to eat in the fasting state. However, this seems to be balanced by an improved satiety response to a meal and improved sensitivity of the appetite control system.

Prandial subcutaneous injections of glucagon-like peptide-1 cause weight loss in obese human subjects

Recombinant glucagon-like peptide-1 (7–36)amide (rGLP-1) was recently shown to cause significant weight loss in type 2 diabetics when administered for 6 weeks as a continuous subcutaneous infusion. The mechanisms responsible for the weight loss are not clarified. In the present study, rGLP-1 was given for 5d by prandial subcutaneous injections (PSI) (76nmol 30min before meals, four times daily; a total of 302·4nmol/24h) or by continuous subcutaneous infusion (CSI) (12·7nmol/h; a total of 304·8nmol/24h). This was performed in nineteen healthy obese subjects (mean age 44·2 (sem 2·5) years; BMI 39·0 (sem 1·2)kg/m2) in a prospective randomised, double-blind, placebo-controlled, cross-over study. Compared with the placebo, rGLP-1 administered as PSI and by CSI generated a 15% reduction in mean food intake per meal (P=0·02) after 5d treatment. A weight loss of 0·55 (sem 0·2) kg (P<0·05) was registered after 5d with PSI of rGLP-1. Gastric emptying rate was reduced during both PSI (P<0·001) and CSI (P<0·05) treatment, but more rapidly and to a greater extent with PSI of rGLP-1. To conclude, a 5d treatment of rGLP-1 at high doses by PSI, but not CSI, promptly slowed gastric emptying as a probable mechanism of action of increased satiety, decreased hunger and, hence, reduced food intake with an ensuing weight loss.

The highs (B1H) and lows (B1L) of human heart B1-adrenoceptors (AR)

The 1AR has two binding sites which can be activated to cause cardiostimulation. The first, termed, 1HAR (high affinity site of 1AR) is activated by noradrenaline and adrenaline and is blocked by relatively low concentrations of β-blockers including carvedilol (Kaumann and Molenaar, 2008). The other, termed, 1LAR (low affinity site of 1AR) has lower affinity for noradrenaline and adrenaline and is activated by some β-blockers including CGP12177 and pindolol, at higher concentrations than those required to block the receptor (Kaumann and Molenaar, 2008). (-)-CGP12177 is a non-conventional partial agonist that causes modest and transient increases of contractile force in human atrial trabeculae (Kaumann and Molenaar, 2008). These effects are markedly increased and maintained by inhibition of phosphodiesterase PDE3. The stimulant effects of (-)-CGP12177 at human β1ARs was verified with recombinant receptors (Kaumann and Molenaar, 2008). However, in a recent report it was proposed that the positive inotropic effects of CGP12177 are mediated through 3ARs in human right atrium (Skeberdis et al 2008). This proposal was not consistent with the lack of blockade of (-)-CGP12177 inotropic effects or increases in L-type Ca2+ current (ICa-L ) by the β3AR blocker 1 μM LY748,337 (Christ et al, 2010). On the otherhand, (-)-CGP12177 increases in inotropic effects and ICa-L were blocked by (-)-bupranolol 1-10 μM (Christ et al, 2010). Chronic infusion of (-)-CGP 12177 (10 mg/Kg/24 hours) for four weeks in an aortic constriction mouse model of heart failure caused an increase in left ventricular wall thickness, fibrosis and inflammation-related left ventricular gene expression levels. Christ T et al (2010) Br J Pharmacol, In press Kaumann A and Molenaar P (2008) Pharmacol Ther 118, 303-336 Skeberdis VA et al (2008) J Clin Invest, 118, 3219-3227

The impact of psychosocial factors on adherence to compression therapy to prevent recurrence of venous leg ulcers

Aims To identify self-care activities undertaken and determine relationships between self-efficacy, depression, quality of life, social support and adherence to compression therapy in a sample of patients with chronic venous insufficiency. Background Up to 70% of venous leg ulcers recur after healing. Compression hosiery is a primary strategy to prevent recurrence, however, problems with adherence to this strategy are well documented and an improved understanding of how psychosocial factors influence patients with chronic venous insufficiency will help guide effective preventive strategies. Design Cross-sectional survey and retrospective medical record review. Method All patients previously diagnosed with a venous leg ulcer which healed between 12–36 months prior to the study were invited to participate. Data on health, psychosocial variables and self-care activities were obtained from a self-report survey and data on medical and previous ulcer history were obtained from medical records. Multiple linear regression modelling was used to determine the independent influences of psychosocial factors on adherence to compression therapy. Results In a sample of 122 participants, the most frequently identified self-care activities were application of topical skin treatments, wearing compression hosiery and covering legs to prevent trauma. Compression hosiery was worn for a median of 4 days/week (range 0–7). After adjustment for all variables and potential confounders in a multivariable regression model, wearing compression hosiery was found to be significantly positively associated with participants’ knowledge of the cause of their condition (p=0.002), higher self-efficacy scores (p=0.026) and lower depression scores (p=0.009). Conclusion In this sample, depression, self-efficacy and knowledge were found to be significantly related to adherence to compression therapy. Relevance to clinical practice These findings support the need to screen for and treat depression in this population. In addition, strategies to improve patient knowledge and self-efficacy may positively influence adherence to compression therapy.

Application of data mining techniques in the prediction of coronary artery disease : use of anaesthesia time-series and patient risk factor data

The high morbidity and mortality associated with atherosclerotic coronary vascular disease (CVD) and its complications are being lessened by the increased knowledge of risk factors, effective preventative measures and proven therapeutic interventions. However, significant CVD morbidity remains and sudden cardiac death continues to be a presenting feature for some subsequently diagnosed with CVD. Coronary vascular disease is also the leading cause of anaesthesia related complications. Stress electrocardiography/exercise testing is predictive of 10 year risk of CVD events and the cardiovascular variables used to score this test are monitored peri-operatively. Similar physiological time-series datasets are being subjected to data mining methods for the prediction of medical diagnoses and outcomes. This study aims to find predictors of CVD using anaesthesia time-series data and patient risk factor data. Several pre-processing and predictive data mining methods are applied to this data. Physiological time-series data related to anaesthetic procedures are subjected to pre-processing methods for removal of outliers, calculation of moving averages as well as data summarisation and data abstraction methods. Feature selection methods of both wrapper and filter types are applied to derived physiological time-series variable sets alone and to the same variables combined with risk factor variables. The ability of these methods to identify subsets of highly correlated but non-redundant variables is assessed. The major dataset is derived from the entire anaesthesia population and subsets of this population are considered to be at increased anaesthesia risk based on their need for more intensive monitoring (invasive haemodynamic monitoring and additional ECG leads). Because of the unbalanced class distribution in the data, majority class under-sampling and Kappa statistic together with misclassification rate and area under the ROC curve (AUC) are used for evaluation of models generated using different prediction algorithms. The performance based on models derived from feature reduced datasets reveal the filter method, Cfs subset evaluation, to be most consistently effective although Consistency derived subsets tended to slightly increased accuracy but markedly increased complexity. The use of misclassification rate (MR) for model performance evaluation is influenced by class distribution. This could be eliminated by consideration of the AUC or Kappa statistic as well by evaluation of subsets with under-sampled majority class. The noise and outlier removal pre-processing methods produced models with MR ranging from 10.69 to 12.62 with the lowest value being for data from which both outliers and noise were removed (MR 10.69). For the raw time-series dataset, MR is 12.34. Feature selection results in reduction in MR to 9.8 to 10.16 with time segmented summary data (dataset F) MR being 9.8 and raw time-series summary data (dataset A) being 9.92. However, for all time-series only based datasets, the complexity is high. For most pre-processing methods, Cfs could identify a subset of correlated and non-redundant variables from the time-series alone datasets but models derived from these subsets are of one leaf only. MR values are consistent with class distribution in the subset folds evaluated in the n-cross validation method. For models based on Cfs selected time-series derived and risk factor (RF) variables, the MR ranges from 8.83 to 10.36 with dataset RF_A (raw time-series data and RF) being 8.85 and dataset RF_F (time segmented time-series variables and RF) being 9.09. The models based on counts of outliers and counts of data points outside normal range (Dataset RF_E) and derived variables based on time series transformed using Symbolic Aggregate Approximation (SAX) with associated time-series pattern cluster membership (Dataset RF_ G) perform the least well with MR of 10.25 and 10.36 respectively. For coronary vascular disease prediction, nearest neighbour (NNge) and the support vector machine based method, SMO, have the highest MR of 10.1 and 10.28 while logistic regression (LR) and the decision tree (DT) method, J48, have MR of 8.85 and 9.0 respectively. DT rules are most comprehensible and clinically relevant. The predictive accuracy increase achieved by addition of risk factor variables to time-series variable based models is significant. The addition of time-series derived variables to models based on risk factor variables alone is associated with a trend to improved performance. Data mining of feature reduced, anaesthesia time-series variables together with risk factor variables can produce compact and moderately accurate models able to predict coronary vascular disease. Decision tree analysis of time-series data combined with risk factor variables yields rules which are more accurate than models based on time-series data alone. The limited additional value provided by electrocardiographic variables when compared to use of risk factors alone is similar to recent suggestions that exercise electrocardiography (exECG) under standardised conditions has limited additional diagnostic value over risk factor analysis and symptom pattern. The effect of the pre-processing used in this study had limited effect when time-series variables and risk factor variables are used as model input. In the absence of risk factor input, the use of time-series variables after outlier removal and time series variables based on physiological variable values’ being outside the accepted normal range is associated with some improvement in model performance.

Alternative analytical methods for the identification of cancer-related symptom clusters

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.

Analysis of distrubances in large interconnected power systems

World economies increasingly demand reliable and economical power supply and distribution. To achieve this aim the majority of power systems are becoming interconnected, with several power utilities supplying the one large network. One problem that occurs in a large interconnected power system is the regular occurrence of system disturbances which can result in the creation of intra-area oscillating modes. These modes can be regarded as the transient responses of the power system to excitation, which are generally characterised as decaying sinusoids. For a power system operating ideally these transient responses would ideally would have a “ring-down” time of 10-15 seconds. Sometimes equipment failures disturb the ideal operation of power systems and oscillating modes with ring-down times greater than 15 seconds arise. The larger settling times associated with such “poorly damped” modes cause substantial power flows between generation nodes, resulting in significant physical stresses on the power distribution system. If these modes are not just poorly damped but “negatively damped”, catastrophic failures of the system can occur. To ensure system stability and security of large power systems, the potentially dangerous oscillating modes generated from disturbances (such as equipment failure) must be quickly identified. The power utility must then apply appropriate damping control strategies. In power system monitoring there exist two facets of critical interest. The first is the estimation of modal parameters for a power system in normal, stable, operation. The second is the rapid detection of any substantial changes to this normal, stable operation (because of equipment breakdown for example). Most work to date has concentrated on the first of these two facets, i.e. on modal parameter estimation. Numerous modal parameter estimation techniques have been proposed and implemented, but all have limitations [1-13]. One of the key limitations of all existing parameter estimation methods is the fact that they require very long data records to provide accurate parameter estimates. This is a particularly significant problem after a sudden detrimental change in damping. One simply cannot afford to wait long enough to collect the large amounts of data required for existing parameter estimators. Motivated by this gap in the current body of knowledge and practice, the research reported in this thesis focuses heavily on rapid detection of changes (i.e. on the second facet mentioned above). This thesis reports on a number of new algorithms which can rapidly flag whether or not there has been a detrimental change to a stable operating system. It will be seen that the new algorithms enable sudden modal changes to be detected within quite short time frames (typically about 1 minute), using data from power systems in normal operation. The new methods reported in this thesis are summarised below. The Energy Based Detector (EBD): The rationale for this method is that the modal disturbance energy is greater for lightly damped modes than it is for heavily damped modes (because the latter decay more rapidly). Sudden changes in modal energy, then, imply sudden changes in modal damping. Because the method relies on data from power systems in normal operation, the modal disturbances are random. Accordingly, the disturbance energy is modelled as a random process (with the parameters of the model being determined from the power system under consideration). A threshold is then set based on the statistical model. The energy method is very simple to implement and is computationally efficient. It is, however, only able to determine whether or not a sudden modal deterioration has occurred; it cannot identify which mode has deteriorated. For this reason the method is particularly well suited to smaller interconnected power systems that involve only a single mode. Optimal Individual Mode Detector (OIMD): As discussed in the previous paragraph, the energy detector can only determine whether or not a change has occurred; it cannot flag which mode is responsible for the deterioration. The OIMD seeks to address this shortcoming. It uses optimal detection theory to test for sudden changes in individual modes. In practice, one can have an OIMD operating for all modes within a system, so that changes in any of the modes can be detected. Like the energy detector, the OIMD is based on a statistical model and a subsequently derived threshold test. The Kalman Innovation Detector (KID): This detector is an alternative to the OIMD. Unlike the OIMD, however, it does not explicitly monitor individual modes. Rather it relies on a key property of a Kalman filter, namely that the Kalman innovation (the difference between the estimated and observed outputs) is white as long as the Kalman filter model is valid. A Kalman filter model is set to represent a particular power system. If some event in the power system (such as equipment failure) causes a sudden change to the power system, the Kalman model will no longer be valid and the innovation will no longer be white. Furthermore, if there is a detrimental system change, the innovation spectrum will display strong peaks in the spectrum at frequency locations associated with changes. Hence the innovation spectrum can be monitored to both set-off an “alarm” when a change occurs and to identify which modal frequency has given rise to the change. The threshold for alarming is based on the simple Chi-Squared PDF for a normalised white noise spectrum [14, 15]. While the method can identify the mode which has deteriorated, it does not necessarily indicate whether there has been a frequency or damping change. The PPM discussed next can monitor frequency changes and so can provide some discrimination in this regard. The Polynomial Phase Method (PPM): In [16] the cubic phase (CP) function was introduced as a tool for revealing frequency related spectral changes. This thesis extends the cubic phase function to a generalised class of polynomial phase functions which can reveal frequency related spectral changes in power systems. A statistical analysis of the technique is performed. When applied to power system analysis, the PPM can provide knowledge of sudden shifts in frequency through both the new frequency estimate and the polynomial phase coefficient information. This knowledge can be then cross-referenced with other detection methods to provide improved detection benchmarks.