Mapping, Localization and Path Planning for Image-based Navigation using Visual Features and Map

Building on progress in feature representations for image retrieval, image-based localization has seen a surge of research interest. Image-based localization has the advantage of being inexpensive and efficient, often avoiding the use of 3D metric maps altogether. That said, the need to maintain a large number of reference images as an effective support of localization in a scene, nonetheless calls for them to be organized in a map structure of some kind. The problem of localization often arises as part of a navigation process. We are, therefore, interested in summarizing the reference images as a set of landmarks, which meet the requirements for image-based navigation. A contribution of this paper is to formulate such a set of requirements for the two sub-tasks involved: map construction and self-localization. These requirements are then exploited for compact map representation and accurate self-localization, using the framework of a network flow problem. During this process, we formulate the map construction and self-localization problems as convex quadratic and second-order cone programs, respectively. We evaluate our methods on publicly available indoor and outdoor datasets, where they outperform existing methods significantly.Comment: CVPR 2019, for implementation see https://github.com/janinethom

The characterisation of growth hormone-related cardiac disease with magnetic resonance imaging & The effects of growth hormone dysregulation on adenosine monophosphate-activated protein kinase in cardiac tissue

PhDChronic growth hormone (GH) excess, acromegaly, causes a specific cardiomyopathy, which remains poorly understood. The pattern of hypertrophy is distinct from other forms of cardiac disease and begins to appear before hypertension or diabetes. GH deficiency (GHD) also causes cardiovascular problems, with reduced ability to mount a cardiovascular response to exercise. Acromegaly and GHD patients have increased cardiac mortality. Cardiac magnetic resonance imaging (CMR) is the gold standard for assessment of cardiac mass and provides data on cardiac function, fibrosis, valve function and ischaemia. This study used CMR to assess 23 patients with acromegaly or GHD, before and after treatment of their GH disorder, and 23 healthy controls. Patients with acromegaly demonstrated increased left ventricular mass index (LVMi), end diastolic volume index, stroke volume index and cardiac index, which persisted at one year, despite treatment of underlying disease. Patients with GHD demonstrated LVMi at the bottom (males) or beneath (females) published normal references ranges, which increased with one year of GH replacement. The mechanisms by which GH influences cardiac tissue are poorly understood. Adenosine monophosphate-activated protein kinase (AMPK) is an energy-regulator enzyme, which interacts with several metabolic hormones. Mutations in AMPK cause arrhythmias and cardiac hypertrophy. AMPK activation may be a mechanism by which GH causes some of its cardiac effects. This study used primary cardiomyocytes and mouse and rat models of GH excess and deficiency to study the effects of GH on cardiac AMPK. Acute GH treatment increased AMPK activity in both in vivo and in vitro studies; acute IGF-I treatment had the opposite effect. In 2 and 8 month old bovine GH-overexpressing (bGH) and GH receptor knock out (GHRKO) mice, functional AMPK assay did not demonstrate any difference in cardiac AMPK activity between transgenics and controls. However, Western blotting for Threonine-172 phospho (p)AMPK levels, a marker of AMPK activity, demonstrated increased cardiac pAMPK in 2 month old bGH mice and a reduction in cardiac pAMPK levels in 8 month old animals. A trend towards the same findings was seen in GHRKO mice. This indicates that both GH and IGF-I interact with myocardial AMPK, apparently via different mechanisms

Relationship between eating pathology, body dissatisfaction and depressive symptoms among male and female adolescents in the United Arab Emirates

Research in the field of eating disorders remains limited in the Arab world. The cross-sectional study addressed this gap by examining eating disturbances and related problem behaviors among 361 (284 females, 77 males) undergraduates in the United Arab Emirates (UAE). Standardized measures were used to assess the relationship between symptoms of eating pathology, body dissatisfaction and depression. Three quarters (73%) of the sample indicated body dissatisfaction (78% of females, 58% of males) and 20% scored above the clinical cutoff on the eating pathology scale (20% of females, 22% of males). Depressive symptomatology predicted significantly higher levels of eating pathology in both genders. The findings highlight that eating disturbances and body dissatisfaction are of concern among adolescents in the UAE. Local eating disorders prevention strategies should address the needs of both females and males and consider potential depressive co-morbidity. © 2013 Elsevier Ltd

Linking Big Data and Business: Design Parameters of Data-Driven Organizations

Big data analytics is accepted to be an important driver of business value. However, this value does not come without a cost. Becoming a data-driven organization (DDO) necessitates a substantial transformation along the components structure, actors, task, and technology. Moreover, as successfully generating value from big data requires the utilization of data insights in business, attention needs to be assigned to the different actors from the data and business side, and their interrelation and collaboration. By taking a socio-technical systems perspective and utilizing a multi-case research approach, we developed a taxonomy to structure insights about different design parameters of a DDO. Thus, we contribute to the information systems literature by proposing a holistic design framework for DDOs paying tribute to its high collaboration requirements, and offer a compendium for managers with pathways how to design a DDO

The Making of Pieces of the Puzzle: Reflections on a Collaborative Ethnographic Filmmaking Process

This is a companion piece to the “Pieces of the Puzzle” film. &nbsp

Collaborative mechanisms for big data analytics projects: Building bridges over troubled waters

Big data analytics (BDA) is accepted to be an important driver of business value. Deriving value from big data to improve organizational decision-making requires the collaboration of data science experts and business users. However, recent literature has shown that their relationship is troubled. Tension arises from diverse relational difficulties and change-inherent challenges. The relationship has been theorized to lack social capital, which leads to inferior collaboration and diminishes project success. In this vein, scholars have begun to investigate relational governance mechanisms, but detailed insights on collaborative approaches to foster the relationship remain scarce. By applying multiple-case research, we shed light on collaborative mechanisms and reveal their impact on the relationship between data science and business employees, theorized by means of social capital. Thus, we build theoretical and practical bridges over the troubled waters in BDA collaboration and contribute to BDA success from a social perspective