An Empirical Evaluation of Preconditioning Data for Accelerating Convex Hull Computations

The convex hull describes the extent or shape of a set of data and is used ubiquitously in computational geometry. Common algorithms to construct the convex hull on a finite set of n points (x,y) range from O(nlogn) time to O(n) time. However, it is often the case that a heuristic procedure is applied to reduce the original set of n points to a set of s < n points which contains the hull and so accelerates the final hull finding procedure. We present an algorithm to precondition data before building a 2D convex hull with integer coordinates, with three distinct advantages. First, for all practical purposes, it is linear; second, no explicit sorting of data is required and third, the reduced set of s points is constructed such that it forms an ordered set that can be directly pipelined into an O(n) time convex hull algorithm. Under these criteria a fast (or O(n)) pre-conditioner in principle creates a fast convex hull (approximately O(n)) for an arbitrary set of points. The paper empirically evaluates and quantifies the acceleration generated by the method against the most common convex hull algorithms. An extra acceleration of at least four times when compared to previous existing preconditioning methods is found from experiments on a dataset.

Chloride ingress into marine exposed concrete: A comparison of empirical- and physically- based models

In establishing the reliability of performance-related design methods for concrete – which are relevant for resistance against chloride-induced corrosion - long-term experience of local materials and practices and detailed knowledge of the ambient and local micro-climate are critical. Furthermore, in the development of analytical models for performance-based design, calibration against test data representative of actual conditions in practice is required. To this end, the current study presents results from full-scale, concrete pier-stems under long-term exposure to a marine environment with work focussing on XS2 (below mid-tide level) in which the concrete is regarded as fully saturated and XS3 (tidal, splash and spray) in which the concrete is in an unsaturated condition. These exposures represent zones where concrete structures are most susceptible to ionic ingress and deterioration. Chloride profiles and chloride transport behaviour are studied using both an empirical model (erfc function) and a physical model (ClinConc). The time dependency of surface chloride concentration (Cs) and apparent diffusivity (Da) were established for the empirical model whereas, in the ClinConc model (originally based on saturated concrete), two new environmental factors were introduced for the XS3 environmental exposure zone. Although the XS3 is considered as one environmental exposure zone according to BS EN 206-1:2013, the work has highlighted that even within this zone, significant changes in chloride ingress are evident. This study aims to update the parameters of both models for predicting the long term transport behaviour of concrete subjected to environmental exposure classes XS2 and XS3.

Moral Emotions in Palliative Care: Empirical Insights from Austria and Canada

Research aims: Moral emotions as one specific group of emotions play a vital role in delivering palliative care as e.g. ethical issues and moral distress belong to daily routine.
Moral emotions are oriented to the welfare of other persons or the society as a whole. To better understand moral emotions in Palliative Care the aims of the presented study are to ana- lyze care situations from Austria and Canada in different care settings and identify families of moral emotions on one hand and describe influencing contextual factors on the other hand. Methods: Within a qualitative study design a reanalysis of Austrian narratives on ethical issues and Canadian narra- tives on moral distress were conducted. Data in Austria encompass 36 narratives that were generated through qual- itative questionnaires in nursing homes. Canadian data are based on qualitative interviews with home care palliative specialists and encompass 47 critical incidents. The reanal- ysis of data was conducted with narrative analysis. Results: Preliminary results show that moral emotions in palliative care can be found in families around “empathy and relatedness”, “sadness, isolation and bereavement”, “anger, frustration and powerlessness”, “guilt and shame” and “being touched and feel close”. Contextual factors influencing moral emotions can be summarized as “suffer- ing and decline of client”, “expectations and dynamics of family”, “structural conflicts and power issues” and “lack of resources and information”.
Conclusion: The diversity of moral emotions reflects the everyday experiences in palliative care. It became obvious that most of the moral emotions that have been expressed appear to be interconnected within a bundle of other emo- tions. Contextual factors influencing moral emotions in pal- liative care are relatively independent of care settings. In Palliative Care moral emotions and their contextual factors constitute an important source of insight for reflection in organizational ethics.

Target language use : An empirical study of the target language use in the Swedish 4-6 grade classroom

A consistent use of the target language during English lessons is beneficial for pupils’ linguistic development, but also challenging for both teachers and pupils. The main purpose for pupils to learn English is to be able to use it in communication, which requires that they develop the ability to comprehend input, produce output and use language strategies. Several researchers claim that a consistent use of the target language is necessary in order to develop these abilities. Therefore, the aim of this study is to examine the target language use during English lessons in Swedish grades 4-6, and what pupils’ opinions regarding target language use are. The methods used to collect data consisted of a pupil questionnaire with 42 respondents and an observation of two teachers’ English lessons during a week’s time. The results from the observations show that the teachers use plenty of target language during lessons, but the first language as well to explain things that pupils might experience difficult to understand otherwise. The results from the questionnaire mainly show that the pupils seem to enjoy English and like to both speak and hear the target language during lessons. The main input comes from listening to a CD with dialogues and exercises in the textbook and the workbook, and from the teacher speaking. The results also show that a majority of the pupils use the target language in their spare time. A conclusion that can be drawn from this study is that the TL should be used to a large extent in order to support pupils’ linguistic development. However, teachers may sometimes need to use L1 in order to facilitate understanding of the things that many pupils find difficult, for example grammar. Suggestions for further research in this area include similar studies conducted on a larger scale.

Internal Control application : Empirical evidence from Sweden

Aim The aim of this study is to explore based on internationally recognised frameworks: 1. how internal control structures are applied in Sweden among different sectors; 2. how organizational size and environment affect internal control structures; and 3. the impact of internal control structures on organizational performance. Methods A quantitative method was used in the data collection and analysis. The sample consisted of 1117 organizations operating in Sweden. A mean analysis was conducted to measure the level of internal control structures among different industries, organizational sizes, and different choices of listing in the stock exchange market. Person’s correlation analysis was then used to explore possible correlations between external environmental factors and internal control structures, and internal control structures and organizational performance. Lastly, a structural model was built to measure the impact of internal control structures on organizational performance. The measurements of internal control structures and organizational performance are based on COSO framework’s principles and objectives. Results This study gives an insight on how internal control structures are applied across industrial sectors in Sweden, with financial institutions and manufacturing organizations having notably higher levels of internal control structures. Additionally, it provides evidence of the impact external environmental factors have on internal control structures. Furthermore, it shows that organizations that are listed in the Swedish stock exchange market have an equivalent level of internal control structures to those registered in the American stock exchange market. In contrast, organisations that are not listed in the stock exchange market have a notably lower level of internal control structures. Lastly, it illustrates the positive impact the presence of internal control structures has on organizational performance. 3 | P a g e Conclusion The results highlight a crucial role the supervisory authority Finansinspektionen (FI) has in regulating the Swedish financial market. They also show that the stability of the Swedish business environment has had a positive impact on the level of internal control structures.

PROPOSAL OF AN EMPIRICAL MODEL FOR SUPPLIERS SELECTION

The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, trough the literature review, there were identified five broad suppliers selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. Thereafter, a survey was elaborated and companies were contacted in order to answer which factors have more relevance in their decisions to choose the suppliers. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Simple Multi-Attribute Rating Technique (SMART). The result of the research undertaken by the authors is a reference model that represents a decision making support for the suppliers/partners selection process.

Climbing Up the Leaderboard: An Empirical Study of Applying Gamification Techniques to a Computer Programming Class

Conventional taught learning practices often experience difficulties in keeping students motivated and engaged. Video games, however, are very successful at sustaining high levels of motivation and engagement through a set of tasks for hours without apparent loss of focus. In addition, gamers solve complex problems within a gaming environment without feeling fatigue or frustration, as they would typically do with a comparable learning task. Based on this notion, the academic community is keen on exploring methods that can deliver deep learner engagement and has shown increased interest in adopting gamification – the integration of gaming elements, mechanics, and frameworks into non-game situations and scenarios – as a means to increase student engagement and improve information retention. Its effectiveness when applied to education has been debatable though, as attempts have generally been restricted to one-dimensional approaches such as transposing a trivial reward system onto existing teaching materials and/or assessments. Nevertheless, a gamified, multi-dimensional, problem-based learning approach can yield improved results even when applied to a very complex and traditionally dry task like the teaching of computer programming, as shown in this paper. The presented quasi-experimental study used a combination of instructor feedback, real time sequence of scored quizzes, and live coding to deliver a fully interactive learning experience. More specifically, the “Kahoot!” Classroom Response System (CRS), the classroom version of the TV game show “Who Wants To Be A Millionaire?”, and Codecademy’s interactive platform formed the basis for a learning model which was applied to an entry-level Python programming course. Students were thus allowed to experience multiple interlocking methods similar to those commonly found in a top quality game experience. To assess gamification’s impact on learning, empirical data from the gamified group were compared to those from a control group who was taught through a traditional learning approach, similar to the one which had been used during previous cohorts. Despite this being a relatively small-scale study, the results and findings for a number of key metrics, including attendance, downloading of course material, and final grades, were encouraging and proved that the gamified approach was motivating and enriching for both students and instructors.

Exact Solution of Bayes and Minimax Change-Detection Problems

The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with discrete time and discrete observations. Change-detection problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case change-time distribution. Both types of problems are addressed. The most important result of the dissertation is the development of a polynomial-time algorithm for the solution of important classes of Markov Bayes change-detection problems. Existing techniques for epsilon-exact solution of partially observable Markov decision processes have complexity exponential in the number of observation symbols. A new algorithm, called constellation induction, exploits the concavity and Lipschitz continuity of the value function, and has complexity polynomial in the number of observation symbols. It is shown that change-detection problems with a geometric change-time distribution and identically- and independently-distributed observations before and after the change are solvable in polynomial time. Also, change-detection problems on hidden Markov models with a fixed number of recurrent states are solvable in polynomial time. A detailed implementation and analysis of the constellation-induction algorithm are provided. Exact solution methods are also established for several types of minimax change-detection problems. Finite-horizon problems with arbitrary observation distributions are modeled as extensive-form games and solved using linear programs. Infinite-horizon problems with linear penalty for detection delay and identically- and independently-distributed observations can be solved in polynomial time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and methods for finding minimally sized policy representations are described.

Empirical studies on share issuance and repurchase decisions

Financial constraints influence corporate policies of firms, including both investment decisions and external financing policies. The relevance of this phenomenon has become more pronounced during and after the recent financial crisis in 2007/2008. In addition to raising costs of external financing, the effects of financial crisis limited the availability of external financing which had implications for employment, investment, sale of assets, and tech spending. This thesis provides a comprehensive analysis of the effects of financial constraints on share issuance and repurchases decisions. Financial constraints comprise both internal constraints reflecting the demand for external financing and external financial constraints that relate to the supply of external financing. The study also examines both operating performance and stock market reactions associated with equity issuance methods. The first empirical chapter explores the simultaneous effects of financial constraints and market timing on share issuance decisions. Internal financing constraints limit firms’ ability to issue overvalued equity. On the other hand, financial crisis and low market liquidity (external financial constraints) restrict availability of equity financing and consequently increase the costs of external financing. Therefore, the study explores the extent to which internal and external financing constraints limit market timing of equity issues. This study finds that financial constraints play a significant role in whether firms time their equity issues when the shares are overvalued. The conclusion is that financially constrained firms issue overvalued equity when the external equity market or the general economic conditions are favourable. During recessionary periods, costs of external finance increase such that financially constrained firms are less likely to issue overvalued equity. Only unconstrained firms are more likely to issue overvalued equity even during crisis. Similarly, small firms that need cash flows to finance growth projects are less likely to access external equity financing during period of significant economic recessions. Moreover, constrained firms have low average stock returns compared to unconstrained firms, especially when they issue overvalued equity. The second chapter examines the operating performance and stock returns associated with equity issuance methods. Firms in the UK can issue equity through rights issues, open offers, and private placement. This study argues that alternative equity issuance methods are associated with a different level of operating performance and long-term stock returns. Firms using private placement are associated with poor operating performance. However, rights issues are found empirically to be associated with higher operating performance and less negative long-term stock returns after issuance in comparison to counterpart firms that issue private placements and open offers. Thus, rights issuing firms perform better than open offers and private placement because the favourable operating performance at the time of issuance generates subsequent positive long-run stock price response. Right issuing firms are of better quality and outperform firms that adopt open offers and private placement. In the third empirical chapter, the study explores the levered share repurchase of internally financially unconstrained firms. Unconstrained firms are expected to repurchase their shares using internal funds rather than through external borrowings. However, evidence shows that levered share repurchases are common among unconstrained firms. These firms display this repurchase behaviour when they have bond ratings or investment grade ratings that allow them to obtain cheap external debt financing. It is found that internally financially unconstrained firms borrow to finance their share repurchase when they invest more. Levered repurchase firms are associated with less positive abnormal returns than unlevered repurchase firms. For the levered repurchase sample, high investing firms are associated with more positive long-run abnormal stock returns than low investing firms. It appears the market underreact to the levered repurchase in the short-run regardless of the level of investments. These findings indicate that market reactions reflect both undervaluation and signaling hypotheses of positive information associated with share repurchase. As the firms undertake capital investments, they generate future cash flows, limit the effects of leverage on financial distress and ultimately reduce the risk of the equity capital.

Regional differences of outpatient physician supply as a theoretical economic and empirical generalized linear model

BACKGROUND: Regional differences in physician supply can be found in many health care systems, regardless of their organizational and financial structure. A theoretical model is developed for the physicians' decision on office allocation, covering demand-side factors and a consumption time function. METHODS: To test the propositions following the theoretical model, generalized linear models were estimated to explain differences in 412 German districts. Various factors found in the literature were included to control for physicians' regional preferences. RESULTS: Evidence in favor of the first three propositions of the theoretical model could be found. Specialists show a stronger association to higher populated districts than GPs. Although indicators for regional preferences are significantly correlated with physician density, their coefficients are not as high as population density. CONCLUSIONS: If regional disparities should be addressed by political actions, the focus should be to counteract those parameters representing physicians' preferences in over- and undersupplied regions.

Numerical methods for solar tomography in the STEREO era

In this thesis, we propose several advances in the numerical and computational algorithms that are used to determine tomographic estimates of physical parameters in the solar corona. We focus on methods for both global dynamic estimation of the coronal electron density and estimation of local transient phenomena, such as coronal mass ejections, from empirical observations acquired by instruments onboard the STEREO spacecraft. We present a first look at tomographic reconstructions of the solar corona from multiple points-of-view, which motivates the developments in this thesis. In particular, we propose a method for linear equality constrained state estimation that leads toward more physical global dynamic solar tomography estimates. We also present a formulation of the local static estimation problem, i.e., the tomographic estimation of local events and structures like coronal mass ejections, that couples the tomographic imaging problem to a phase field based level set method. This formulation will render feasible the 3D tomography of coronal mass ejections from limited observations. Finally, we develop a scalable algorithm for ray tracing dense meshes, which allows efficient computation of many of the tomographic projection matrices needed for the applications in this thesis.

Empirical evidence of bias in the design of experimental stroke studies: a metaepidemiologic approach

Background and Purpose: At least part of the failure in the transition from experimental to clinical studies in stroke has been attributed to the imprecision introduced by problems in the design of experimental stroke studies. Using a metaepidemiologic approach, we addressed the effect of randomization, blinding, and use of comorbid animals on the estimate of how effectively therapeutic interventions reduce infarct size. Methods: Electronic and manual searches were performed to identify meta-analyses that described interventions in experimental stroke. For each meta-analysis thus identified, a reanalysis was conducted to estimate the impact of various quality items on the estimate of efficacy, and these estimates were combined in a meta meta-analysis to obtain a summary measure of the impact of the various design characteristics. Results: Thirteen meta-analyses that described outcomes in 15 635 animals were included. Studies that included unblinded induction of ischemia reported effect sizes 13.1% (95% CI, 26.4% to 0.2%) greater than studies that included blinding, and studies that included healthy animals instead of animals with comorbidities overstated the effect size by 11.5% (95% CI, 21.2% to 1.8%). No significant effect was found for randomization, blinded outcome assessment, or high aggregate CAMARADES quality score. Conclusions: We provide empirical evidence of bias in the design of studies, with studies that included unblinded induction of ischemia or healthy animals overestimating the effectiveness of the intervention. This bias could account for the failure in the transition from bench to bedside of stroke therapies.

Identifying stationary series in panels: A Monte Carlo evaluation of sequential panel selection methods

Sequential panel selection methods (spsms — procedures that sequentially use conventional panel unit root tests to identify I(0)I(0) time series in panels) are increasingly used in the empirical literature. We check the reliability of spsms by using Monte Carlo simulations based on generating directly the individual asymptotic pp values to be combined into the panel unit root tests, in this way isolating the classification abilities of the procedures from the small sample properties of the underlying univariate unit root tests. The simulations consider both independent and cross-dependent individual test statistics. Results suggest that spsms may offer advantages over time series tests only under special conditions.

AN EMPIRICAL ASSESSMENT OF USER ONLINE SECURITY BEHAVIOR: EVIDENCE FROM A UNIVERSITY

The ever-increasing number and severity of cybersecurity breaches makes it vital to understand the factors that make organizations vulnerable. Since humans are considered the weakest link in the cybersecurity chain of an organization, this study evaluates users’ individual differences (demographic factors, risk-taking preferences, decision-making styles and personality traits) to understand online security behavior. This thesis studies four different yet tightly related online security behaviors that influence organizational cybersecurity: device securement, password generation, proactive awareness and updating. A survey (N=369) of students, faculty and staff in a large mid-Atlantic U.S. public university identifies individual characteristics that relate to online security behavior and characterizes the higher-risk individuals that pose threats to the university’s cybersecurity. Based on these findings and insights from interviews with phishing victims, the study concludes with recommendations to help similat organizations increase end-user cybersecurity compliance and mitigate the risks caused by humans in the organizational cybersecurity chain.