Due to Cable-TV by special permission with high restriction and monopolize that the customers forced to accept without choices. The result of customer satisfaction inquire unable to understand what¡¦s the enterprise real needed and expect of customer. Formerly scholar research of relationship and interaction between customer satisfaction and enterprise by using inquire tools and result for strategy. But, That¡¦s not only one condition to judge the customer satisfaction. Such as channel content, network quality, manner of customer service ¡K etc. The multi condition to judge of customer satisfaction for the enterprise. Because, Every condition has causality of an event or a situation. It¡¦s not easy to explain the complicated with time delay. The system thinking will be solved such as this case In my research. The purpose of research : 1. Using BSC(Balance Score Card) and strategy map for case analysis in my research and find out what¡¦s critical problem in this case. 2. Using SD(System Dynamic) to simulation what is causality between system and customer satisfaction. The simulation result will verify with real system and provide for decision.

Detection of coronary calcification from computed tomography scans is a noninvasive examination and has great potential for heart disease diagnosis. This study proposes new features to characterize calcium lesions. Different from the traditional calcium score features, these features are generated from the texture, shape, and gray level statistics of the calcium lesions. We study the correlation between these features and acute myocardial infarction and then compare the results with traditional calcium score features. According to the location of the lesions, patients are first divided into two groups. In one group, the myocardial infarction is located in segment of culprit lesion. For the second group, myocardial infarction is located in segment of non-culprit lesion. In comparing their means, the corresponding p-value of gray level statistics feature ¡§histogram relative smoothness¡¨ could reach 4.47E-07, which has fairly high significance. Furthermore, in studying the differences among patients, experiment on Hypercholesterolemia provide a good result. By comparing the means of patients which are classified into Hypercholesterolemia and non-Hypercholesterolemia groups, the corresponding p-value of texture feature ¡§inverse difference moment¡¨ could reach 3.74E-04. Initially, acute myocardial infarction do not have statistically significant result However, after adding the location weighting factor for the lesions, the corresponding p-value of texture feature ¡§average of information measures of correlation¡¨ could be reduced to 8.8921E-03, and p-value of gray level statistics feature ¡§Histogram relative Smoothness¡¨ could be improved to 2.4019E-02.

Research concerning covenants has at large not examined what quantifiable relationship covenants have with yield spreads. We shed light on this topic as we evaluate Swedish bond indentures. By examining the relationship between covenants and yield spread, our results indicate whether covenants effectively mitigate the bondholder-stockholder conflict. The results from our OLS-model indicate that the poison put option and covenants restricting dividends and mergers have a positive relationship with the yield spread, and that the negative pledge has a negative relationship with the yield spread. Furthermore, our results indicate that some covenants are too costly for companies issuing investment grade bonds. Those covenants are therefore only included in bonds with higher yield spreads, where a conflict between bondholders and stockholders could be greater. / Ett kvantifierbart förhållande mellan kovenanter och räntebasmarginalen har överlag i tidigare forskning inte undersökts. I denna uppsats åskådliggör vi detta förhållande genom att undersöka svenska företagsobligationer. Genom att studera relationen mellan kovenanter och räntebasmarginalen kan våra resultat visa på huruvida kovenanter motverkar konflikten mellan obligationsinnehavare och aktieägare. Resultaten från vår OLS-modell visar att poison put option och kovenanter som begränsar utdelningar och fusioner har ett positivt samband med räntebasmarginalen, medan negative pledge har ett negativt samband med räntebasmarginalen. Vidare visar våra resultat att vissa kovenanter är för dyra för företag som ger ut investment grade obligationer. Dessa kovenanter finns därför bara med i obligationer med högre räntebasmarginaler, där en konflikt mellan obligationsinnehavare och aktieägare kan vara större.

Since January 2006 Medicare beneficiaries have the option to purchase prescription drug benefits from Medicare under the Part D program. The addition of outpatient drugs to the Medicare programs reflects Congress’ recognition of the fundamental change in recent years in how medical care is delivered in the U.S. It recognizes the vital role of prescription drugs in the health care delivery system and the need to modernize Medicare to assure their availability to Medicare beneficiaries. The Medicare Prescription Drug Improvement and Modernization Act of 2003 (MMA) created the Medicare drug benefit and specified a standard plan. The law also enables plans to offer alternative benefit packages that are either actuarially equivalent or provide enhanced benefits above the basic benefits. A majority of these alternative plans offer multitiered formulary where different medications have different patient copayments. Different from traditional Medicare, Part D benefits are provided by private sector plans through a competitive bidding process. Firms submit a bid to the Center for Medicare and Medicaid Services (CMS) which represents the expected cost to the firm for providing basic benefits to an individual of average health. The competition between plans was expected to drive premiums down toward marginal cost, ensuring that the beneficiaries receive maximum benefits for a given public expenditure (Biles et al. 2004). This dissertation examines the stand-alone Medicare Prescription Drug Plans (PDPs) bid and premium from the following perspectives using the 2006-2008 PDP data. First, we examine the use of multiple-tier copayment structures. In particular, we tend to discover the relationship between enrollee cost sharing at each tier and prescription drug plan (PDP) bids. Bids are equivalent to the total premiums charged by an insurer. This includes the premium paid by the consumer and the portion paid by the federal government. Further, we decompose plan bid and premium changes between 2006 and 2008 into two components, the proportion due to changes in plan characteristics and the proportion due to changes in marginal price. By doing so, we estimate whether the actuarial methods used to price those characteristics play a role in explaining the plan bid and premium difference across years.  Finally, we measure the Medicare beneficiaries’ sensitivity to price in the PDP market, specifically the elasticity and semi-elasticity of enrollment with respect to PDP premium.

The Adequate Yearly Progress (AYP) Model has been used to make many high-stakes decisions concerning schools, though it does not provide a complete assessment of student academic achievement and school effectiveness. To provide a clearer perspective, many states have implemented various Growth and Value Added Models, in addition to AYP. The purpose of this study was to examine two Value Added Model specifications, the Gain Score Model and the Layered Effects Model, to understand similarities and differences in school effect results. Specifically, this study correlated value added school effect estimates, which were derived from two model specifications and two outcome measures (mathematics and reading test scores). Existing data were obtained from a moderately large and rural school district in Florida. The outcome measures of 7,899 unique students were examined using the Gain Score Model and the Layered Effects Model to estimate school effects. Those school effect estimates were then used to calculate and examine the relationship between school rankings. Overall, the findings in this study indicated that the school effect estimates and school rankings were more sensitive to outcome measures than they were to model specifications. The mathematics and reading correlations from the Gain Score Model for school effects and school rankings were low (indicating high sensitivity), when advancing from Grades 4 to 5, and were moderate in other grades. The mathematics and reading correlations from the Layered Effects Model were low at Grade 5 for school effects and school rankings, as were the correlations at Grade 7 for the school rankings. In the other grades, correlations were moderate to high (indicating lower sensitivity). Correlations between the Gain Score Model and the Layered Effects Model from mathematics were high in each grade for both school effects and school rankings. Reading correlations were also high for each of the grades. These results were similar to the findings of previous school effects research and added to the limited body of literature. Depending upon the outcome measure used, school effects and rankings can vary significantly when using Value Added Models. These models have become a popular component in educational accountability systems, yet there is no one perfect model. If used, these models should be used cautiously, in addition to other accountability approaches.

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Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(情報学) / 甲第19106号 / 情博第552号 / 新制||情||98 / 32057 / 京都大学大学院情報学研究科知能情報学専攻 / (主査)教授 河原 達也, 教授 田中 利幸, 講師 吉井 和佳 / 学位規則第4条第1項該当

Film musicology is growing at a heartening pace, but the discipline is still bereft of sustained contributions from music theory. The current study seizes the opportunity presented by the underanalyzed repertoire of film music, offering an argument for applying the techniques of transformational analysis, and neo-Riemannian analysis in particular, to the interpretation of music for the moving image. Film musical style and form respond strongly to a transformational approach, which adapts well to both the triadic chromaticism characteristic of Hollywood’s harmonic practice and the dynamic and contingent condition of musical design inherent to the medium. Concurrently, the analytic tools and conceptual structure of neo-Riemannian theory benefit from exposure to a fresh repertoire with different analytic needs than those of art music. In this dissertation, the author scrutinizes the capacity for tonality to act as a unifying and dramatically potent force in film. With parameters of effective cinematic tonal design established, the adapted transformational methodology responds faithfully to the expressive and temporal qualities of the soundtrack. The author develops a model for harmonic associativity and a general hermeneutics of transformation, extrapolated from analyses of scores from John Williams, James Horner, Jerry Goldsmith, and many others. The power of the transformational approach to capture tonal phenomena through spatial representations is marshaled to perform critical readings of scores for A Beautiful Mind and Star Trek. Not only can the neo-Riemannian stance illuminate the way film music works, but it can train the listener and analyst to perceive and enjoy film with more sensitive ears. / Music

Much health related research depends heavily on the analysis of a rapidly expanding universe of observational data. A challenge in analysis of such data is the lack of sound statistical methods and tools that can address multiple facets of estimating treatment or exposure effects in observational studies with a large number of covariates. We sought to advance methods to improve analysis of large observational datasets with an end goal of understanding the effect of treatments or exposures on health. First we compared existing methods for propensity score (PS) adjustment, specifically Bayesian propensity scores. This concept had previously been introduced (McCandless et al., 2009) but no rigorous evaluation had been done to evaluate the impact of feedback when fitting the joint likelihood for both the PS and outcome models. We determined that unless specific steps were taken to mitigate the impact of feedback, it has the potential to distort estimates of the treatment effect. Next, we developed a method for accounting for uncertainty in confounding adjustment in the context of multiple exposures. Our method allows us to select confounders based on their association with the joint exposure and the outcome while also accounting for the uncertainty in the confounding adjustment. Finally, we developed two methods to combine het- erogenous sources of data for effect estimation, specifically information coming from a primary data source that provides information for treatments, outcomes, and a limited set of measured confounders on a large number of people and smaller supplementary data sources containing a much richer set of covariates. Our methods avoid the need to specify the full joint distribution of all covariates.

BACKGROUND: Morbidity, defined as disease history, is an important and well-known confounder in epidemiologic studies. Numerous methods have been developed over the last 30 years to measure morbidity via valid and reliable processes. OBJECTIVE: The goal of the current study was to evaluate, via comparative predictive validity assessment, the Centers for Medicaid and Medicare Studies Hierarchical Condition Category (CMS-HCC) comorbidity model for its ability to improve the prediction of 12-month all-cause mortality among a Medicare population compared to previously published comorbidity index models. There were three specific aims: (1) challenge the current state of risk adjustment among aged populations via an evaluation of the comparative predictive validity of one novel and four existing models to predict all-cause mortality within 12 months among a heterogeneous population of Medicare beneficiaries; (2) Investigate the comparative predictive validity of the five models to predict all-cause mortality within 12 months among two homogenous populations diagnosed with ischemic heart disease and selected cancers, including prostate cancer, lung cancer, colorectal cancer, breast cancer, pancreas cancer, and endometrial cancer; and (3) measure each comorbidity model's ability to control for a known example of confounding by indication. METHODS: A retrospective cohort design was used for all specific aims. Study 1 included 257,641 Medicare beneficiaries enrolled in three Medicare Advantage prescription drug health plans in Alabama, Florida, or Ohio in 2010 and 2011. Study 2 limited analysis to 14,260 and 66,440 beneficiaries with administrative evidence of selected cancers or ischemic heart disease in 2010, respectively. Study 3 limited analysis to the beneficiaries with ischemic heart disease. For each participant, comorbidity risk scores for the following five models were generated using administrative data from 2010: an age/sex model, the Romano adaption of the Charlson Comorbidity Index (CCI) model, the Putnam adaptation of the Chronic Disease Score Model (CDS), the CMS version of the Hierarchical Condition Category (CMS-HCC) model, and the Agency for Healthcare Research and Quality (AHRQ) adaptation of the Elixhauser model. The prospective predictive validity of the models to predict all-cause mortality during 2011 was compared via the c statistic test. Participants with ischemic heart disease were randomly allocated retrospectively to either 1) a group that had "received" a hypothetical "Drug A" in 2010 or 2) a group that had "received" a hypothetical "Drug B" in 2010. In order to evaluate the impact of confounding by indication, a weighting factor was applied to the randomization process in order to force the 33,220 participants randomized to "Drug A" to have a 2.736 times higher likelihood of having at least one acute inpatient hospitalization in 2010. Each comorbidity model's ability to control for the contrived confounding by indication was evaluated via relative risk of death. RESULTS: The CMS-HCC model had statistically significant higher c-statistic values than all four existing comorbidity indices among the heterogeneous Medicare Advantage population (N=257,641) and the homogeneous populations with breast cancer (N=4,160) and prostate cancer (N=6,594). The CMS-HCC model displayed similar performance for lung cancer (N=1,384), colorectal cancer (N=1,738), endometrial cancer (N=232), and ischemic heart disease (N=66,640) and statistically significant lower performance for pancreas cancer (N=152). The log-transformed CMS-HCC model was the only model to generate a non-significant association between exposure to "Drug A" and subsequent mortality. CONCLUSION: In general, the CMS-HCC model is the preferred comorbidity measure due to its predictive performance. However, other comorbidity models may be optimal for diseases with low prevalence and/or high mortality. Researchers should carefully and thoughtfully select a comorbidity model to assess the existence and direction of confounding. The CMS-HCC model should be log-transformed when used as a dependent variable since the score is a ratio level measurement that displays a normal distribution when log transformed. The resulting score is less likely to violate the assumptions (i.e. violations of normality) of common statistical models due to extreme values. The national availability of CMS-HCC scores for all Medicare beneficiaries provides researchers with access to a new tool to measure co-morbidity among older Americans using an empirically weighted, single score. In terms of policy, it is recommended that CMS produce CMS-HCC scores for all Medicare beneficiaries on a rolling 12 month basis for each month during the year. The availability of monthly scores would increase the ease of use of the score, as well as help facilitate more rapid adoption of the tool.