Fisher networks: A principled approach to retrieval-based classification

Due to the technological advances in the acquisition and processing of information, current data mining applications involve databases of sizes that would be unthinkable just two decades ago. However, real-word datasets are often riddled with irrelevant variables that not only do not generate any meaningful information about the process of interest, but may also obstruct the contribution of the truly informative data features. Taking into consideration the relevance of the different measures available can make the difference between reaching an accurate reflection of the underlying truth and obtaining misleading results that cause the drawing of erroneousconclusions. Another important consideration in data analysis is the interpretability of the models used to fit the data. It is clear that performance must be a key aspect in deciding which methodology to use, but it should not be the only one. Models with an obscure internal operation see their practical usefulness effectively diminished by the difficulty to understand the reasoning behind their inferences, which makes them less appealing to users that are not familiar with their theoretical basis. This thesis proposes a novel framework for the visualisation and categorisation of data in classification contexts that tackles the two issues discussed above and provides an informative output of intuitive interpretation. The system is based on a Fisher information metric that automatically filters the contribution of variables depending on their relevance with respect to the classification problem at hand, measured by their influence on the posterior class probabilities. Fisher distances can then be used to calculate rigorous problem-specific similarity measures, which can be grouped into a pairwise adjacency matrix, thus defining a network. Following this novel construction process results in a principled visualisation of the data organised in communities that highlights the structure of the underlying class membership probabilities. Furthermore, the relational nature of the network can be used to reproduce the probabilistic predictions of the original estimates in a case-based approach, making them explainable by means of known cases in the dataset. The potential applications and usefulness of the framework are illustrated using several real-world datasets, giving examples of the typical output that the end user receives and how they can use it to learn more about the cases of interest as well as about the dataset as a whole

Glosarium Matematika

273 p.; 24 cm

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Community College Transfer to Four-Year Institutions: A Latent Class Structural Equation Model

Drawing on data from the nationally representative 2004/09 Beginning Postsecondary Students Longitudinal Study (BPS 04/09), this study proposed and tested a latent class measurement model of public two-year community college student transfer subtypes, and examined the latent class conditional structural relationships among student background characteristics, Remediation, First-year college GPA, Student Engagement and transfer to four-year institutions. Perhaps, most importantly, this study examined whether latent class membership moderated the relationships between malleable factors and four-year transfer likelihood. This study employed latent class analysis (LCA) to identify potential latent transfer subtypes, confirmatory factor analysis (CFA) to account for the unreliability in the indicators of the hypothesized latent student Engagement factor, and structural equation modeling (SEM), using an unbiased 3-step approach to the analysis of both predictors of latent class and latent class prediction of distal outcomes (Asparouhov & Muthén, 2014a; Vermunt, 2010), to examine the associations among the above mentioned variables and four-year transfer likelihood. Based on a comprehensive review of information criteria and fit indices, a four class solution fit the data best and provided four substantively relevant transfer classes which I labeled as follows: Class 1:High Transfer Intentions, Few Barriers, Class 2: Low Transfer Intentions, Some Barriers, Class 3: Moderate Transfer Intentions, Low Academic Resources, Class 4: Moderate Transfer Intentions, Low Academic Momentum. Controlling for latent class membership, first generation college status and exposure to remediation were negatively associated with four-year transfer likelihood, while increases in both first-year GPA and student Engagement were positively associated with transfer outcomes. However, when latent class specific slopes were estimated, exposure to Remediation and first-year GPA were statistically significantly (p<.05) related to transfer only in Class 1:High Transfer Intentions, Few Barriers, while only First Generation Status was statistically significantly related to transfer in Class 3; Moderate Transfer Intentions, Low Academic Resources and Class 4: Moderate Transfer Intentions, Low Academic Momentum; student Engagement, at an inflated alpha of .10, was statistically significantly (p=.07) related to transfer in Class 4: Moderate Transfer Intentions, Low Academic Momentum.That latent class membership moderated the relationships between malleable factors and transfer likelihood provides underfunded community colleges with a more nuanced answer as to which variables are related to transfer. Using such information, community colleges could provide class-specific advice and interventions, rather than a one size fits all approach, which may or may not be right for each transfer subtype. In this way, community colleges may increase transfer rates in an efficient and strategic manner that meets the needs of its diverse student population

Advanced imaging techniques for cardiovascular research

According to the World Health Organization, cardiovascular diseases (CVDs) are the first cause of death globally. CVDs are a cluster of disorders that involve heart and blood vessels. Among them, coronary artery disease (CAD) is the most important disease in terms of mortality, causing more than 50% of the annual deaths. Over the last decades, many recognized international organisms, such as the World Health Organization and the American College of Cardiology have done great efforts to reduce the mortality and morbidity of CAD. In this line, accurate diagnosis and cost-effective management of CAD have revealed to be of utmost importance. Several imaging techniques are currently used in the clinical practice to provide a diagnosis and clinical assessment of the disease. Among them, Positron Emission Tomography (PET) is considered to be the “gold standard” for non invasive assessment of myocardial perfusion and viability, the two most relevant physiological parameters used to diagnose and manage patients with known or suspected CAD..

Study of the effects of corporate governance systems on the internationalisation of Iranian companies

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Advanced Imaging Techniques for Cardiovascular Research

Objectives: In this thesis we addressed some of those difficulties by exploring new applications of a 68Galabeled radiotracer (68Ga-DOTA). 68Ga can be obtained from a 68Ge/68Ga generator and has a half-life of 68 minutes, which makes it a convenient candidate for its widespread clinical use. We proposed and validated the use of 68Ga-DOTA as a radiotracer for assessment of myocardial blood flow (MBF), myocardial viability and pulmonary blood flow (PBF). Additionally, we introduced a new methodology to perform a PET scan in which this tracer could be coinjected simultaneously with some other radiotracers such as 18FDG (multi-tracer PET). Lastly, we developed an automatic detector able to perform blood spectroscopy analysis, which offered the possibility to perform multi-tracer PET with minimal human intervention. Methods To test the capability of 68Ga-DOTA to measure MBF, viability and PBF, different groups of Large White pigs underwent PET/CT scans using 68Ga-DOTA as the injected radiotracer. For PBF studies, a group of healthy pigs (n = 4) were scanned under rest conditions. For MBF studies, a group of 8 pigs were scanned under rest and pharmacologically-induced stress in order to perform rest/stress tests, as it is done for humans in clinical routine. Additionally, a group of 5 pigs were scanned 7 days after the induction of a myocardial infarction (MI) to assess viability and MBF in a MI model. MBF, extracellular volume fraction (ECV, for viability assessment) and PBF maps were obtained after fitting the dynamic PET images to the corresponding pharmacokinetic model followed by 68Ga-DOTA in each tissue under study. Global and regional perfusion maps for the myocardial tissue (MBF) and lungs (PBF) were obtained. For validation purposes, the “goldstandard” technique used in tissue perfusion quantification (fluorescent-labeled microspheres (MS)) was simultaneosly performed along with the PET/CT scans. The blood sampling spectroscopic methodology was evaluated and calibrated in vitro using different 68Ga/18F mixtures. Then, it was tested in pigs (n = 3) injected with 68Ga-DOTA and 18FDG in the same acquisition. The activity concentration of each radiotracer in myocardial tissue was subsequently measured ex vivo. The automatic blood sampling detector was built from scratch and characterized using a catheter filled with different 68Ga/18F mixtures. Finally, it was additionally evaluated in vivo in n = 3 pigs under conditions resembling to those encountered in clinical routine. Results Regarding MBF quantification and validation with 68Ga-DOTA-PET, a strong correlation (r = 0.91) between MBF measured with PET and MS was obtained (slope = 0.96 ± 0.10, y-intercept = 0.11 ± 0.19 ml·min−1·g−1). For the myocardial infarction model, MBF values obtained with 68Ga-DOTA-PET in the infarcted area (LAD, left anterior descendant) were significantly reduced in comparison to remote ones LCX (left circumflex artery, p < 0.0001) and RCA (right coronary artery, p < 0.0001). In addition, 68Ga-DOTA-PET detected a significant ECV increase in the infarcted area (p < 0.0001). The correlation evaluation between 68Ga-DOTA-PET and MS as a PBF radiotracer also showed a good and significant correlation (r = 0.74, p < 0.0001). The gamma spectroscopic analysis on blood samples proposed for multi-tracer PET imaging was also succesfully validated, showing a correlation of r = 0.95 (p < 0.0001) for 18FDG concentration in myocardium measured with multi-tracer PET and by ex vivo validation. The blood sampling detector was able to measure the arterial input function in pigs in an experimental setup under realistic conditions. Discussion and conclusions 68Ga-DOTA-PET allowed accurate non-invasive assessment of MBF and ECV in pigs with myocardial infarction and under rest-stress conditions. This technique could provide wide access to quantitative measurement of both MBF and ECV with PET imaging. 68Ga-DOTA-PET was also demonstrated to be a potential inexpensive method for measuring PBF in clinical settings. As for multi-tracer PET imaging, the proposed methodology allowed explicit measurement of separate arterial input functions, offering very similar results to those obtained as a reference from the ex vivo analysis of the tissue under evaluation. Finally, a novel blood sampling device was developed and characterized, showing performance parameters similar to other devices in the literature. Noteworthy, this detector has the additional and unique feature of allowing us to perform multi-tracer PET by means of a gamma spectroscopic analysis of the blood flowing between its detection blocks. All the results summarized in this abstract may contribute to spread the use of PET in clinical routine, either by the clinical use of 68Ga-DOTA as an inexpensive but accurate radiotracer for MBF, PBF or viability assessment, or by the implementation of multi-tracer PET, which could lead to cost reduction of PET examinations by shortening the scanning time and eliminating misalignment inaccuracies. This multi-tracer PET methodology could also be safely implemented using our proposed automated device that permits to perform the gamma spectroscopic analysis on blood samples with minimal human intervention