Refine
Year of publication
Document Type
- Article (unreviewed) (25) (remove)
Language
- English (25) (remove)
Has Fulltext
- no (25) (remove)
Is part of the Bibliography
- yes (25)
Keywords
- Export (4)
- Trade (3)
- COVID-19 (2)
- Deep Learning (2)
- Finance (2)
- Public Service Models (2)
- Ultraschall (2)
- Additive Manufacturing (1)
- Afrika (1)
- Außenhandel (1)
Institute
- Fakultät Wirtschaft (W) (25) (remove)
Open Access
- Open Access (13)
- Bronze (2)
- Closed Access (2)
- Diamond (2)
With economic weight shifting toward net zero, now is the time for ECAs, Exim-Banks, and PRIs to lead. Despite previous success, aligning global economic governance to climate goals requires additional activities across export finance and investment insurance institutions. The new research project initiated by Oxford University, ClimateWorks Foundation, and Mission 2020 including other practitioners and academics from institutions such as Atradius DSB, Columbia University, EDC, FMO and Offenburg University focuses on reshaping future trade and investment governance in light of climate action. The idea of a ‘Berne Union Net Zero Club’ is an important item in a potential package of reforms. This can include realigning mandates and corporate strategies, principles of intervention, as well as ECA, Exim-Bank and PRI operating models in order to accelerate net zero transformation. Full transparency regarding Berne Union members’ activities would be an excellent starting point. We invite all interested parties in the sector to come together to chart our own path to net zero
The COVID19 pandemic, a unique and devastating respiratory disease outbreak, has affected global populations as the disease spreads rapidly. Recent Deep Learning breakthroughs may improve COVID19 prediction and forecasting as a tool of precise and fast detection, however, current methods are still being examined to achieve higher accuracy and precision. This study analyzed the collection contained 8055 CT image samples, 5427 of which were COVID cases and 2628 non COVID. The 9544 Xray samples included 4044 COVID patients and 5500 non COVID cases. The most accurate models are MobileNet V3 (97.872 percent), DenseNet201 (97.567 percent), and GoogleNet Inception V1 (97.643 percent). High accuracy indicates that these models can make many accurate predictions, as well as others, are also high for MobileNetV3 and DenseNet201. An extensive evaluation using accuracy, precision, and recall allows a comprehensive comparison to improve predictive models by combining loss optimization with scalable batch normalization in this study. Our analysis shows that these tactics improve model performance and resilience for advancing COVID19 prediction and detection and shows how Deep Learning can improve disease handling. The methods we suggest would strengthen healthcare systems, policymakers, and researchers to make educated decisions to reduce COVID19 and other contagious diseases.
Additive manufacturing (AM) and in particular the application of 3D multi material printing offers completely new production technologies thanks to the degree of freedom in design and the simultaneous processing of several materials in one component. Today's CAD systems for product development are volume-based and therefore cannot adequately implement the multi-material approach. Voxel-based CAD systems offer the advantage that a component can be divided into many voxels and different materials and functions can be assigned to these voxels. In this contribution two voxel-based CAD systems will be analyzed in order to simplify the AM on voxel level with different materials. Thus, a number of suitable criteria for evaluating voxel-based CAD systems are being developed and applied. The results of a technical-economic comparison show the differences between the voxel-based systems and disclose their disadvantages compared to conventional CAD systems. In order to overcome these disadvantages, a new method is therefore presented as an approach that enables the voxelization of a component in a simple way based on a conventional CAD model. The process chain of this new method is demonstrated using a typical component from product design. The results of this implementation of the new method are illustrated and analyzed.
Financing trade and development sustainably will be crucial for Africa. Enhanced collaboration between multilateral development banks, development finance institutions and ECAs could greatly enhance intra-regional trade. Furthermore, setting up a ‘level playing field’ on the continent will allow governments to make strategic interventions for successful export credits and trade finance solutions, fostering growth through trade. African trade is already showing signs of rebounding from the coronavirus- induced recession. Through concerted, co-operative and continent-wide efforts, drawing on the knowledge and resources of all types of institutions and policy experts, Africa will continue to grow confidently and quickly into its increasingly important role as an engine of economic growth and global trade.
Creating growth through trade is an important part of the policy approach of many economies. For decades, many member countries of the Organisation for Economic Co-operation and Development (OECD) have cooperated in a fair competition for the benefit of their national exporters. The countries’ official export credit agencies (ECAs) have established and jointly improved rules and regulations for export credit and political risk insurance. However, new players such as China, Russia or other fast developing countries have now joined the list of top exporting nations. As these countries have established their own ECAs, there is a need to introduce rules and regulations on global standards for financial terms as well as truly international norms ensuring ‘ethical’ trading behaviour.
But how will government support for foreign trade look like in the future? Will global standards for export credit and political risk insurance become reality by 2020? And how will strict rules and regulations for officially supported export credits and FDI regarding ethics, human rights and the environment impact growth through trade in general, or exporters in particular? These are questions addressed by the thirty eight contributions to Global Policy’s third eBook entitled ‘The Future of Foreign Trade Support – Setting Global Standards for Export Credit and Political Risk Insurance’, guest edited by Andreas Klasen and Fiona Bannert.
Excellent organisations require targeted strategies to implement their vision and mission, deploying a stakeholder-focused approach. As part of evidence-based policy making, it is a common approach to measure government financing vehicles’ results. A state-of-the-art method in quantitative benchmarking to overcome the challenge of considering multiple inputs and outputs is Data Envelopment Analysis (DEA). Descriptive statistics and explorative-qualitative approaches are also applied in a modern ECA benchmarking model to substantiate DEA results and put them into perspective. This enabler-result model provides a holistic view and allows to identify top performing ECAs and Exim-Banks, providing the opportunity for inefficient institutions to learn from their most productive peers. This best practice approach for strategic benchmarking enables the senior management to develop and implement a cutting-edge strategy, and increase value for key stakeholders.
Risk aversion, financing and real servicThe Global CEO Survey was launched in 2015 by researchers from Offenburg University, the University of Westminster and the London School of Economics and Political Science (LSE) to better understand and discover what factors influence exporters’ demand for credit insurance. Although some scholars discussed aspects of corporate insurance demand with regard to exporters, there is limited research concerning the demand for export credit insurance associated with firm-specific factors. Only few empirical studies support existing theories on corporate insurance demand and export credits. This project investigates and fills the relevant gap of official export credit insurance demand.es
In an extensive research project, we have assessed the application of different service models by export credit agencies (ECAs) and export-import banks (EXIMs). We conducted interviews with 35 representatives of ECAs and EXIMs from 27 countries. The question guiding this study is: How do ECAs and EXIMs adopt public service models for supporting exporters? We conducted a holistic multiple case study, investigating if and how these organisations apply public service models developed by Schedler and Guenduez, and which roles of the state are relevant. We find that there is a variety of different service models used by ECAs and EXIMs, and that the service model approaches have great potential to learn from each other and innovate existing services.
The paper conceptualizes the systemic approach for enhancing innovative and competitive capacity of industrial companies (named as Advanced Innovation Design Approach – AIDA) including analysis, optimizations and further development of the innovation process and promoting the innovation climate in industrial companies. The innovation process is understood as a holistic stage-gate system comprising following typical phases with feedback loops and simultaneous auxiliary or follow-up processes: uncovering of solution-neutral customer needs, technology and market trends, identification of the needs and problems with high market potential and formulation of the innovation tasks and strategy, idea generation and problem solving, evaluation and enhancement of solution ideas, creation of innovation concepts based on solution ideas, evaluation of the innovation concepts as well as implementation, validation and market launch of chosen innovation concepts. The article presents the current state of innovation research and discusses the actual status of innovation process in the industrial environment. It defines the future research tasks for amplification of the innovation process with self-configuration, self-optimization, self-diagnostics and intelligent information processing and communication.
Silicon edges as one-dimensional waveguides for dispersion-free and supersonic leaky wedge waves
(2012)
Acoustic waves guided by the cleaved edge of a Si(111) crystal were studied using a laser-based angle-tunable transducer for selectively launching isolated wedge or surface modes. A supersonic leaky wedge wave and the fundamental wedge wave were observed experimentally and confirmed theoretically. Coupling of the supersonic wave to shear waves is discussed, and its leakage into the surface acoustic wave was observed directly. The velocity and penetration depth of the wedge waves were determined by contact-free optical probing. Thus, a detailed experimental and theoretical study of linear one-dimensional guided modes in silicon is presented.
Micro-cracks give rise to non-analytic behavior of the stress-strain relation. For the case of a homogeneous spatial distribution of aligned flat micro-cracks, the influence of this property of the stress-strain relation on harmonic generation is analyzed for Rayleigh waves and for acoustic wedge waves with the help of a simple micromechanical model adopted from the literature. For the efficiencies of harmonic generation of these guided waves, explicit expressions are derived in terms of the corresponding linear wave fields. The initial growth rates of the second harmonic, i.e., the acoustic nonlinearity parameter, has been evaluated numerically for steel as matrix material. The growth rate of the second harmonic of Rayleigh waves has also been determined for microcrack distributions with random orientation, using a model expression for the strain energy in terms of strain invariants known in a geophysical context.
CNN-based deep learning models for disease detection have become popular recently. We compared the binary classification performance of eight prominent deep learning models: DenseNet 121, DenseNet 169, DenseNet 201, EffecientNet b0, EffecientNet lite4, GoogleNet, MobileNet, and ResNet18 for their binary classification performance on combined Pulmonary Chest Xrays dataset. Despite the widespread application in different fields in medical images, there remains a knowledge gap in determining their relative performance when applied to the same dataset, a gap this study aimed to address. The dataset combined Shenzhen, China (CH) and Montgomery, USA (MC) data. We trained our model for binary classification, calculated different parameters of the mentioned models, and compared them. The models were trained to keep in mind all following the same training parameters to maintain a controlled comparison environment. End of the study, we found a distinct difference in performance among the other models when applied to the pulmonary chest Xray image dataset, where DenseNet169 performed with 89.38 percent and MobileNet with 92.2 percent precision.
Rotation of an elastic medium gives rise to a shift of frequency of its acoustic modes, i.e., the time-period vibrations that exist in it. This frequency shift is investigated by applying perturbation theory in the regime of small ratios of the rotation velocity and the frequency of the acoustic mode. In an expansion of the relative frequency shift in powers of this ratio, upper bounds are derived for the first-order and the second-order terms. The derivation of the theoretical upper bounds of the first-order term is presented for linear vibration modes as well as for stable nonlinear vibrations with periodic time dependence that can be represented by a Fourier series.