Peer reviewed Publikation in Master Journal List
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Rheumatoid arthritis is an autoimmune disease that causes chronic inflammation of synovial joints, often resulting in irreversible structural damage. The activity of the disease is evaluated by clinical examinations, laboratory tests, and patient self-assessment. The long-term course of the disease is assessed with radiographs of hands and feet. The evaluation of the X-ray images performed by trained medical staff requires several minutes per patient. We demonstrate that deep convolutional neural networks can be leveraged for a fully automated, fast, and reproducible scoring of X-ray images of patients with rheumatoid arthritis. A comparison of the predictions of different human experts and our deep learning system shows that there is no significant difference in the performance of human experts and our deep learning model.
When a country grants preferential tariffs to another, either reciprocally in a free trade agreement (FTA) or unilaterally, rules of origin (RoOs) are defined to determine whether a product is eligible for preferential treatment. RoOs exist to avoid that exports from third countries enter through the member with the lowest tariff (trade deflection). However, RoOs distort exporters' sourcing decisions and burden them with red tape. Using a global data set, we show that, for 86% of all bilateral product-level comparisons within FTAs, trade deflection is not profitable because external tariffs are rather similar and transportation costs are non-negligible; in the case of unilateral trade preferences extended by rich countries to poor ones that ratio is a striking 98%. The pervasive and unconditional use of RoOs is, therefore, hard to rationalize.
The aim of this paper is to portray the risks of climate change for low mountain range tourism and to develop sustainable business models as adaption strategy. A mixed-method-approach is applied combining secondary analysis, a quantitative survey, and qualitative in-depth-interviews in a transdisciplinary setting. Results show, that until now, climate change impacts on the snow situation in the Black Forest – at least above 1,000 m – have been mild and compensated by artificial snowmaking, and up to now have not had measurable effects on tourism demand. In general, the Black Forest appears to be an attractive destination for more reasons than just snow. The climate issue seems to be regarded as a rather incidental occurrence with little importance to current business decisions. However, the authors present adaption strategies as alternatives for snow tourism, e. g. the implementation of hiking hostels, since climate change will make winter tourism in the Black Forest impossible in the long run.
This paper presents a framework to assess the cultural sustainability of Aboriginal tourism in British Columbia, which meets must take into account the protection of human rights, good self-governance, identity, control of land, the tourism product’s authenticity, and a market-ready tourism product. These criteria are specified by two indicators each. The cultural sustainability framework was generated by triangulating qualitative research methods like experts’ interviews, secondary research, and participant and non-participant observations. This paper is thus conceptual in nature and inductive in its approach. It partly leverages a collaborative approach, as it includes interviewees in an iterative research loop. Furthermore, the paper shows why cultural sustainability is a determinant of the success of Aboriginal tourism.
Purpose – The purpose of this paper is to examine visitor management in the German-Swiss border area of the Lake Constance region. Taking a customer perspective, it determines the requirements for an application with the ability to optimize personal mobility.
Design/methodology/approach – A quantitative study and a survey of focus groups were conducted to identify movement patterns of different types of visitors and their requirements concerning the development of a visitor management application.
Findings – Visitors want an application that provides real-time forecasts of issues such as traffic, parking and queues and, at the same time, enables them to create a personal activity schedule based on this information.
Research limitations/implications – Not every subsample reached a sufficient number of cases to yield representative results.
Practical implications – The results may lead to an optimization and management separation of mobility flows in the research area and be helpful to municipal planners, destination marketing organizations and visitors.
Originality/value – The German border cities of Konstanz, Radolfzell and Singen in the Lake Constance region need improved visitor management, mainly because of a high level of shopping tourism by Swiss visitors to Germany. In the Summer months, Lake Constance is also a popular destination for leisure tourists, which causes overtourism. For the first time, the results of this research presented here offer possible solutions, in particular by showing how a mobile application for visitors could defuse the situation.
Thermochemical surface hardening is used to overcome the weak mechanical performance of austenitic and duplex stainless steels. Both low-temperature carburizing and nitrocarburizing can improve the hardness, wear, galling, and cavitation resistance, while maintaining their good corrosion resistance. Therefore, it is crucial to not form chromium-rich precipitates during hardening as these can deteriorate the passivity of the alloy. The hardening parameters, the chemical composition of the steel, and the manufacturing route of a component determine whether precipitates are formed. This article gives an overview of suitable alloys for low-temperature surface hardening and the performance under corrosive loading.
In this paper, multivariate polynomials in the Bernstein basis over a box (tensorial Bernstein representation) are considered. A new matrix method for the computation of the polynomial coefficients with respect to the Bernstein basis, the so-called Bernstein coefficients, is presented and compared with existing methods. Also matrix methods for the calculation of the Bernstein coefficients over subboxes generated by subdivision of the original box are proposed. All the methods solely use matrix operations such as multiplication, transposition and reshaping; some of them rely on the bidiagonal factorization of the lower triangular Pascal matrix or the factorization of this matrix by a Toeplitz matrix. In the case that the coefficients of the polynomial are due to uncertainties and can be represented in the form of intervals it is shown that the developed methods can be extended to compute the set of the Bernstein coefficients of all members of the polynomial family.
The Lempel–Ziv–Welch (LZW) algorithm is an important dictionary-based data compression approach that is used in many communication and storage systems. The parallel dictionary LZW (PDLZW) algorithm speeds up the LZW encoding by using multiple dictionaries. This simplifies the parallel search in the dictionaries. However, the compression gain of the PDLZW depends on the partitioning of the address space, i.e. on the sizes of the parallel dictionaries. This work proposes an address space partitioning technique that optimises the compression rate of the PDLZW. Numerical results for address spaces with 512, 1024, and 2048 entries demonstrate that the proposed address partitioning improves the performance of the PDLZW compared with the original proposal. These address space sizes are suitable for flash storage systems. Moreover, the PDLZW has relative high memory requirements which dominate the costs of a hardware implementation. This work proposes a recursive dictionary structure and a word partitioning technique that significantly reduce the memory size of the parallel dictionaries.
We have introduced in this paper new variants of two methods for projecting Supply and Use Tables that are based on a distance minimisation approach (SUT-RAS) and the Leontief model (SUT-EURO). We have also compared them under similar and comparable exogenous information, i.e.: with and without exogenous industry output, and with explicit consideration of taxes less subsidies on products. We have conducted an empirical assessment of all of these methods against a set of annual tables between 2000 and 2005 for Austria, Belgium, Spain and Italy. From the empirical assessment, we obtained three main conclusions: (a) the use of extra information (i.e. industry output) generally improves projected estimates in both methods; (b) whenever industry output is available, the SUT-RAS method should be used and otherwise the SUT-EURO should be used instead; and (c) the total industry output is best estimated by the SUT-EURO method when this is not available.