An Algorithmic Framework for Labeling Road Maps

Given an unlabeled road map, we consider, from an algorithmic perspective, the cartographic problem to place non-overlapping road labels embedded in their roads. We first decompose the road network into logically coherent road sections, e.g., parts of roads between two junctions. Based on this decomposition, we present and implement a new and versatile framework for placing labels in road maps such that the number of labeled road sections is maximized. In an experimental evaluation with road maps of 11 major cities we show that our proposed labeling algorithm is both fast in practice and that it reaches near-optimal solution quality, where optimal solutions are obtained by mixed-integer linear programming. In comparison to the standard OpenStreetMap renderer Mapnik, our algorithm labels 31% more road sections in average.Comment: extended version of a paper to appear at GIScience 201

IMAGE QUALITY IMPROVEMENTS IN LOW-COST UNDERWATER PHOTOGRAMMETRY

This study presents an evaluation of a cheap consumer-grade camera used for modelling a coral reef section. We evaluate the quality of a reconstructed coral reef using GoPro cameras and a high-end camera with data from an actual coral reef dataset. We also investigate components of the processing pipeline (like image quality) separate from the final results. Because our GoPro images suffer from severe chromatic aberration, we apply different image pre-processing steps to improve their quality and show its effects on the reconstructed object points. Bundle adjustment is carried out as free networks in all cases, with a follow-up rigid 3D Helmert transformation onto a geodetic control network, carried out to define the common datum and to remove the bias from the free network results

COMPARISON of DIVER-OPERATED UNDERWATER PHOTOGRAMMETRIC SYSTEMS for CORAL REEF MONITORING

Underwater photogrammetry is a well-established technique for measuring and modelling the subaquatic environment in fields ranging from archaeology to marine ecology. While for simple tasks the acquisition and processing of images have become straightforward, applications requiring relative accuracy better then 1:1000 are still considered challenging. This study focuses on the metric evaluation of different off-the-shelf camera systems for making high resolution and high accuracy measurements of coral reefs monitoring through time, where the variations to be measured are in the range of a few centimeters per year. High quality and low-cost systems (reflex and mirrorless vs action cameras, i.e. GoPro) with multiple lenses (prime and zoom), different fields of views (from fisheye to moderate wide angle), pressure housing materials and lens ports (dome and flat) are compared. Tests are repeated at different camera to object distances to investigate distance dependent induced errors and assess the accuracy of the photogrammetrically derived models. An extensive statistical analysis of the different systems is performed and comparisons against reference control point measured through a high precision underwater geodetic network are reported

COMPARISON OF DIVER-OPERATED UNDERWATER PHOTOGRAMMETRIC SYSTEMS FOR CORAL REEF MONITORING

Underwater photogrammetry is a well-established technique for measuring and modelling the subaquatic environment in fields ranging from archaeology to marine ecology. While for simple tasks the acquisition and processing of images have become straightforward, applications requiring relative accuracy better then 1:1000 are still considered challenging. This study focuses on the metric evaluation of different off-the-shelf camera systems for making high resolution and high accuracy measurements of coral reefs monitoring through time, where the variations to be measured are in the range of a few centimeters per year. High quality and low-cost systems (reflex and mirrorless vs action cameras, i.e. GoPro) with multiple lenses (prime and zoom), different fields of views (from fisheye to moderate wide angle), pressure housing materials and lens ports (dome and flat) are compared. Tests are repeated at different camera to object distances to investigate distance dependent induced errors and assess the accuracy of the photogrammetrically derived models. An extensive statistical analysis of the different systems is performed and comparisons against reference control point measured through a high precision underwater geodetic network are reported

Quantifying the Loss of Coral from a Bleaching Event Using Underwater Photogrammetry and AI-Assisted Image Segmentation

Detecting the impacts of natural and anthropogenic disturbances that cause declines in organisms or changes in community composition has long been a focus of ecology. However, a tradeoff often exists between the spatial extent over which relevant data can be collected, and the resolution of those data. Recent advances in underwater photogrammetry, as well as computer vision and machine learning tools that employ artificial intelligence (AI), offer potential solutions with which to resolve this tradeoff. Here, we coupled a rigorous photogrammetric survey method with novel AI-assisted image segmentation software in order to quantify the impact of a coral bleaching event on a tropical reef, both at an ecologically meaningful spatial scale and with high spatial resolution. In addition to outlining our workflow, we highlight three key results: (1) dramatic changes in the three-dimensional surface areas of live and dead coral, as well as the ratio of live to dead colonies before and after bleaching; (2) a size-dependent pattern of mortality in bleached corals, where the largest corals were disproportionately affected, and (3) a significantly greater decline in the surface area of live coral, as revealed by our approximation of the 3D shape compared to the more standard planar area (2D) approach. The technique of photogrammetry allows us to turn 2D images into approximate 3D models in a flexible and efficient way. Increasing the resolution, accuracy, spatial extent, and efficiency with which we can quantify effects of disturbances will improve our ability to understand the ecological consequences that cascade from small to large scales, as well as allow more informed decisions to be made regarding the mitigation of undesired impacts

Apolipoprotein A-IV Serum Concentrations Are Elevated in Patients with Mild and Moderate Renal Failure

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Changes in Employment Uncertainty and the Fertility Intention-Realization Link: An Analysis Based on the Swiss Household Panel.

How do changes in employment uncertainty matter for fertility? Empirical studies on the impact of employment uncertainty on reproductive decision-making offer a variety of conclusions, ranging from gender and socio-economic differences in the effect of employment uncertainty on fertility intentions and behaviour, to the effect of employment on changes in fertility intentions. This article analyses the association between a change in subjective employment uncertainty and fertility intentions and behaviour by distinguishing male and female partners' employment uncertainty, and examines the variation in these associations by education. Using a sample of men and women living in a couple from the Swiss Household Panel (SHP 2002-2011), we examine through multinomial analysis how changes in employment uncertainty and selected socio-demographic factors are related to individual childbearing decisions. Our results show strong gendered effects of changes in employment uncertainty on the revision of reproductive decisions among the highly educated population

On the ability of virtual agents to decrease cognitive load: an experimental study

When attempting to solve a problem, humans call upon cognitive resources. These resources are limited, and the degree of their utilisation is described as cognitive load. While the number of parameters to be taken into account and to be processed by modern-day knowledge workers increases, their cognitive resources do not. Research shows that too high a load can increase stress and failure rates and decrease the work satisfaction and performance of employees. It is thus in the interest of organisations to reduce the cognitive load of their employees and keep it at a moderate level. One way to achieve this may be the application of virtual assistants (VAs), software programs, that can be addressed via voice or text commands and respond to the users’ input. This study uses a laboratory experiment with N = 91 participants comparing two groups in their ability to solve a task. One group was able to make use of a VA while the other could not. Besides task performance, the cognitive load of the participants was measured. Results show that (a) cognitive load is negatively related to task performance, (b) the group using the VA performed better at the task and (c) the group using the VA had a lower cognitive load. These findings show that VAs are a viable way to support employees and can increase their performance. It adds to the growing field of IS research on VAs by expanding the field for the concept of cognitive load