A compactness result for non-local unregularized gradient flow lines

We prove an abstract compactness result for gradient flow lines of a non-local unregularized gradient flow equation on a scale Hilbert space. This is the first step towards Floer theory on scale Hilbert spaces.Comment: 27 page

An iterated graph construction and periodic orbits of Hamiltonian delay equations

According to the Arnold conjectures and Floer's proofs, there are non-trivial lower bounds for the number of periodic solutions of Hamiltonian differential equations on a closed symplectic manifold whose symplectic form vanishes on spheres. We use an iterated graph construction and Lagrangian Floer homology to show that these lower bounds also hold for certain Hamiltonian delay equations.Comment: 25 pages, 3 figure

Modelling And Visualizing Knowledge On The Reference System And Varations Based On The Model Of PGE – Product Generation Engineering For Decision Support

In 2019, Dyson had to cancel its ambitious electric car project after having already 500 Million pounds spent. This example shows how difficult it is to assess the consequences of decisions on development targets as cost, risk, and innovation potential. Knowledge about references, variation types and their impact on development targets can help to increase the maturity of the decision basis. The model of PGE - product generation engineering describes these interrelations using the reference system. This contribution deals with the question of how knowledge about the impact of variation types and characteristics of reference system elements on new product generations can be made usable through modelling and visualization. Therefore, characteristics of reference system elements and their impacts on common development targets are collected through literature research. To process this knowledge base in technical information systems, an Entity-Relationship data model is developed. Through the implementation of a VR visualization, the data model is validated and a first visualisation approach is shown. The findings of this work can be used to systematise research on impact factors in PGE and to develop further digital methods

Identifying used methods and datasets in scientific publications

Although it has become common to assess publications and researchers by means of their citation count (e.g., using the h-index), measuring the impact of scientific methods and datasets (e.g., using an h-index for datasets) has been performed only to a limited extent. This is not surprising because the usage information of methods and datasets is typically not explicitly provided by the authors, but hidden in a publication’s text. In this paper, we propose an approach to identifying methods and datasets in texts that have actually been used by the authors. Our approach first recognizes datasets and methods in the text by means of a domain-specific named entity recognition method with minimal human interaction. It then classifies these mentions into used vs. non-used based on the textual contexts. The obtained labels are aggregated on the document level and integrated into the Microsoft Academic Knowledge Graph modeling publications’ metadata. In experiments based on the Microsoft Academic Graph, we show that both method and dataset mentions can be identified and correctly classified with respect to their usage to a high degree. Overall, our approach facilitates method and dataset recommendation, enhanced paper recommendation, and scientific impact quantification. It can be extended in such a way that it can identify mentions of any entity type (e.g., task)

Hamiltonian delay equations -- examples and a lower bound for the number of periodic solutions

We describe a variational approach to a notion of Hamiltonian delay equations. Our delay Hamiltonians are of product form. We consider several examples. For closed symplectically aspherical symplectic manifolds $(M,\omega)$ we prove that for generic delay Hamiltonians the number of 1-periodic solutions of the Hamiltonian delay equation is at least the sum of the Betti numbers of $M$, extending the proof of the Arnold conjecture to the case with delay.Comment: 13 page

Income Misperception and Populism

We propose that false beliefs about the own current economic status are an important factor for explaining populist attitudes. Along with the subjects' receptiveness to right-wing populism, we elicit their perceived relative income positions in a representative survey of German households. We find that people with pessimistic beliefs about their income position are more attuned to populist statements. Key to understanding the misperception-populism relationship are strong gender differences in the mechanism: Misperception triggers income dissatisfaction for both men and women, but the former are much more likely to channel their discontent into affection for populist ideas

EVOLUTIONARY PERSPECTIVE ON SYSTEM GENERATION ENGINEERING BY THE EXAMPLE OF THE IPHONE

Industrial practice shows that products are developed in generations. Innovation success with complex technical systems can only be achieved economically by using existing solutions as references. These references come from predecessors, competitors, and even industry-external sources. The model of SGE – System Generation Engineering describes these relationships. The iPhone is often used as an example of an innovative product developed in generations. Multiple studies have examined the iPhone. However, none of these studies systematically considers the influence of the product context on references and variations. In this contribution, an evolutionary descriptive model based on the model of SGE is applied to 15 iPhone product generations. The central result is an overview of the variation shares over the generations and the relationships between context factors, reference-based variation activities, and innovation success and hypotheses for causalities. This is one of a series of case studies to investigate these causalities. The study showed how the iPhone remained successful in its context: not through a high new development share, but through strategically placed variations and the use of references from various sources

Helmet use detection of tracked motorcycles using CNN-based multi-task learning.

Automated detection of motorcycle helmet use through video surveillance can facilitate efficient education and enforcement campaigns that increase road safety. However, existing detection approaches have a number of shortcomings, such as the inabilities to track individual motorcycles through multiple frames, or to distinguish drivers from passengers in helmet use. Furthermore, datasets used to develop approaches are limited in terms of traffic environments and traffic density variations. In this paper, we propose a CNN-based multi-task learning (MTL) method for identifying and tracking individual motorcycles, and register rider specific helmet use. We further release the HELMET dataset, which includes 91,000 annotated frames of 10,006 individual motorcycles from 12 observation sites in Myanmar. Along with the dataset, we introduce an evaluation metric for helmet use and rider detection accuracy, which can be used as a benchmark for evaluating future detection approaches. We show that the use of MTL for concurrent visual similarity learning and helmet use classification improves the efficiency of our approach compared to earlier studies, allowing a processing speed of more than 8 FPS on consumer hardware, and a weighted average F-measure of 67.3% for detecting the number of riders and helmet use of tracked motorcycles. Our work demonstrates the capability of deep learning as a highly accurate and resource efficient approach to collect critical road safety related data

Patterns of motorcycle helmet use – a naturalistic observation study in Myanmar

Developing countries are subject to increased motorization, particularly in the number of motorcycles. As helmet use is critical to the safety of motorcycle riders, the goal of this study was to identify observable patterns of helmet use, which allow a more accurate assessment of helmet use in developing countries. In a video based observation study, 124,784 motorcycle riders were observed at seven observation sites throughout Myanmar. Recorded videos were coded for helmet use, number of riders on the motorcycle, rider position, gender, and time of day. Generally, motorcycle helmet use in Myanmar was found to be low with only 51.5% percent of riders wearing a helmet. Helmet use was highest for drivers (68.1%) and decreased for every additional passenger. It was lowest for children standing on the floorboard of the motorcycle (11.3%). During the day, helmet use followed a unimodal distribution, with the highest use observed during the late morning and lowest use observed in the early morning and late afternoon. Helmet use varied significantly between observation sites, ranging from 74.8% in Mandalay to 26.9% in Pakokku. In Mandalay, female riders had a higher helmet use than male riders, and helmet use decreased drastically on a national holiday in the city. Helmet use of motorcycle riders in Myanmar follows distinct patterns. Knowledge of these patterns can be used to design more precise helmet use evaluations and guide traffic law policy and police enforcement measures. Video based observation proved to be an efficient tool to collect helmet use data