Amplifier enhances ring-down spectroscopy

In recent years, investigators have adapted the principles of ringdown spectroscopy (see sidebar, facing page) to fiber optic configurations by placing high reflectors on each end of a fiber and observing the ringdown time of an injected pulse. But a major drawback is the difficulty of creating a low-loss, high-Q resonator in an optical fiber

One-Component Regular Variation and Graphical Modeling of Extremes

The problem of inferring the distribution of a random vector given that its norm is large requires modeling a homogeneous limiting density. We suggest an approach based on graphical models which is suitable for high-dimensional vectors. We introduce the notion of one-component regular variation to describe a function that is regularly varying in its first component. We extend the representation and Karamata's theorem to one-component regularly varying functions, probability distributions and densities, and explain why these results are fundamental in multivariate extreme-value theory. We then generalize Hammersley-Clifford theorem to relate asymptotic conditional independence to a factorization of the limiting density, and use it to model multivariate tails

Payload crew interface design criteria and techniques. Task 1: Inflight operations and training for payloads

Guidelines are developed for use in control and display panel design for payload operations performed on the aft flight deck of the orbiter. Preliminary payload procedures are defined. Crew operational concepts are developed. Payloads selected for operational simulations were the shuttle UV optical telescope (SUOT), the deep sky UV survey telescope (DUST), and the shuttle UV stellar spectrograph (SUSS). The advanced technology laboratory payload consisting of 11 experiments was selected for a detailed evaluation because of the availability of operational data and its operational complexity

Business process management tools as a measure of customer-centric maturity

In application of business process management (BPM) tools in European commercial sectors, this paper examines current maturity of customer centricity construct (CC) as an emerging dimension of competition and as a potential strategic management direction for the future of business. Processes are one of the key components of transformation in the CC roadmap. Particular departments are more customer orientated than others, and processes, customer-centric expertise, and approach can be built and utilized starting from them. Positive items within a current business process that only involve minor modification could be the basis for that. The evidence of movement on the customer-centric roadmap is found. BPM in European telecommunications, banking, utility and retail sector supports roadmap towards customer-centricity in process view, process alignment and process optimization. However, the movement is partial and not flawless, as BPM hasn’t been inquired for supporting many of customer-centric dimensions

Comparison of macro- and microscopic solutions of the Riemann problem I. Supercritical shock tube and expansion into vacuum

The Riemann problem is a fundamental concept in the development of numerical methods for the macroscopic flow equations. It allows the resolution of discontinuities in the solution, such as shock waves, and provides a powerful tool for the construction of numerical flux functions. A natural extension of the Riemann problem involves two phases, a liquid and a vapour phase which undergo phase change at the material boundary. For this problem, we aim at a comparison with the macroscopic solution from molecular dynamics simulations. In this work, as a first step, the macroscopic solution of two important Riemann problem scenarios, the supercritical shock tube and the expansion into vacuum, were compared to microscopic solutions produced by molecular dynamics simulations. High fidelity equations of state were used to accurately approximate the material behaviour of the model fluid. The results of both scenarios compare almost perfect with each other. During the vacuum expansion, the fluid obtained a state of non-equilibrium, where the microscopic and macroscopic solutions start to diverge. A limiting case was shown, where liquid droplets appeared in the expansion fan, which was approximated by the macroscopic solution, assuming an undercooled vapour.DFG, 84292822, TRR 75: Tropfendynamische Prozesse unter extremen Umgebungsbedingunge

Intended and unintended consequences of mandatory IFRS adoption: A review of extant evidence and suggestions for future research

This paper discusses empirical evidence on the economic consequences of mandatory adoption of International Financial Reporting Standards (IFRS) in the European Union (EU) and provides suggestions on how future research can add to our understanding of these effects. Based on the explicitly stated objectives of the EU‟s so-called „IAS Regulation‟, we distinguish between intended and unintended consequences of mandatory IFRS adoption. Empirical research on the intended consequences generally fails to document an increase in the comparability or transparency of financial statements. In contrast, there is rich and almost unanimous evidence of positive effects on capital markets and at the macroeconomic level. We argue that certain research design issues are likely to contribute to this apparent mismatch in findings and we suggest areas for future research to address it. The literature investigating unintended consequences of mandatory IFRS adoption is still in its infancy. However, extant empirical evidence and insights from non-IFRS settings suggest that mandatory IFRS adoption has the potential to materially affect contractual outcomes. We conclude that both the intended and the unintended consequences deserve further scrutiny to assess the costs and benefits of mandatory IFRS adoption, which may help provide a basis for evaluating the effectiveness of the IAS Regulation. We provide specific guidance for future research in this field.International accounting, IFRS adoption, economic consequences, contracting, regulation, review

Online Informative Path Planning for Active Classification on UAVs

We propose an informative path planning (IPP) algorithm for active classification using an unmanned aerial vehicle (UAV), focusing on weed detection in precision agriculture. We model the presence of weeds on farmland using an occupancy grid and generate plans according to information-theoretic objectives, enabling the UAV to gather data efficiently. We use a combination of global viewpoint selection and evolutionary optimization to refine the UAV's trajectory in continuous space while satisfying dynamic constraints. We validate our approach in simulation by comparing against standard "lawnmower" coverage, and study the effects of varying objectives and optimization strategies. We plan to evaluate our algorithm on a real platform in the immediate future.Comment: 7 pages, 4 figures, submission to International Symposium on Experimental Robotics 201

Digital maturity variables and their impact on the enterprise architecture layers

This study examines the variables of digital maturity of companies. The framework for enterprise architectures Archimate 3.0 is used to compare the variables. The variables are assigned to the six layers of architecture: Strategy, Business Environment, Applications, Technology, Physical and Implementation and Migration. On the basis of a literature overview, 15 “digital maturity models” with a total of 147 variables are analyzed. The databases Scopus, EBSCO – Business Source Premier and ProQuest are used for this purpose

Structure Preserving Large Imagery Reconstruction

With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for various goals, such as image clustering, 3D scene reconstruction, and other big data applications. However, such tasks are not easy due to the fact the retrieved photos can have large variations in their view perspectives, resolutions, lighting, noises, and distortions. Fur-thermore, with the occlusion of unexpected objects like people, vehicles, it is even more challenging to find feature correspondences and reconstruct re-alistic scenes. In this paper, we propose a structure-based image completion algorithm for object removal that produces visually plausible content with consistent structure and scene texture. We use an edge matching technique to infer the potential structure of the unknown region. Driven by the estimated structure, texture synthesis is performed automatically along the estimated curves. We evaluate the proposed method on different types of images: from highly structured indoor environment to natural scenes. Our experimental results demonstrate satisfactory performance that can be potentially used for subsequent big data processing, such as image localization, object retrieval, and scene reconstruction. Our experiments show that this approach achieves favorable results that outperform existing state-of-the-art techniques