Evaluation of Sensors and Mapping Approaches for Disasters in Tunnels

Ground or aerial robots equipped with advanced sensing technologies, such as three‐dimensional laser scanners and advanced mapping algorithms, are deemed useful as a supporting technology for first responders. A great deal of excellent research in the field exists, but practical applications at real disaster sites are scarce. Many projects concentrate on equipping robots with advanced capabilities, such as autonomous exploration or object manipulation. In spite of this, realistic application areas for such robots are limited to teleoperated reconnaissance or search. In this paper, we investigate how well state‐of‐the‐art and off‐the‐shelf components and algorithms are suited for reconnaissance in current disaster‐relief scenarios. The basic idea is to make use of some of the most common sensors and deploy some widely used algorithms in a disaster situation, and to evaluate how well the components work for these scenarios. We acquired the sensor data from two field experiments, one from a disaster‐relief operation in a motorway tunnel, and one from a mapping experiment in a partly closed down motorway tunnel. Based on these data, which we make publicly available, we evaluate state‐of‐the‐art and off‐the‐shelf mapping approaches. In our analysis, we integrate opinions and replies from first responders as well as from some algorithm developers on the usefulness of the data and the limitations of the deployed approaches, respectively. We discuss the lessons we learned during the two missions. These lessons are interesting for the community working in similar areas of urban search and rescue, particularly reconnaissance and search.     

Online Bi-Objective Scheduling for IaaS Clouds Ensuring Quality of Service

This paper focuses on a bi-objective experimental evaluation of online scheduling in the Infrastructure as a Service model of Cloud computing regarding income and power consumption objectives. In this model, customers have the choice between different service levels. Each service level is associated with a price per unit of job execution time, and a slack factor that determines the maximal time span to deliver the requested amount of computing resources. The system, via the scheduling algorithms, is responsible to guarantee the corresponding quality of service for all accepted jobs. Since we do not consider any optimistic scheduling approach, a job cannot be accepted if its service guarantee will not be observed assuming that all accepted jobs receive the requested resources. In this article, we analyze several scheduling algorithms with different cloud configurations and workloads, considering the maximization of the provider income and minimization of the total power consumption of a schedule. We distinguish algorithms depending on the type and amount of information they require: knowledge free, energy-aware, and speed-aware. First, to provide effective guidance in choosing a good strategy, we present a joint analysis of two conflicting goals based on the degradation in performance. The study addresses the behavior of each strategy under each metric. We assess the performance of different scheduling algorithms by determining a set of non-dominated solutions that approximate the Pareto optimal set. We use a set coverage metric to compare the scheduling algorithms in terms of Pareto dominance. We claim that a rather simple scheduling approach can provide the best energy and income trade-offs. This scheduling algorithm performs well in different scenarios with a variety of workloads and cloud configurations.     

Designing a supply network artifact for data,process, and people integration

E-procurement and supplier-relationship management systems have helped to substantially advance process execution in supply management. However, current supply network systems still face challenges of high data integration efforts, as well as the decoupling of structured data and processes from the growing amount of digitalized unstructured interactions of supply management professionals. Inspired by the room for improvement posed by this challenges, our research proposes a design for a supply network artifact in supplier qualification that addresses these problems by enabling holistic integration of data, processes, and people. The artifact is developed following an action design research approach. Building on a set of meta-requirements derived from literature and practice explorations, we conceptualize two design principles and derive corresponding design decisions that have been implemented in an software artifact. Finally, we formulate testable hypotheses and evaluate the artifact and its design in the context of supplier qualification. Our results show that the proposed design reduces mental effort of supply management professionals and significantly increases efficiency when performing typical supply network tasks such as supplier qualification.     

Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.     

Using Discriminative Dimensionality Reduction to Visualize Classifiers

Neural Processing Letters - Albeit automated classifiers offer a standard tool in many application areas, there exists hardly a generic possibility to directly inspect their behavior, which goes...     

Mbius-invariant curve and surface energies and their applications

Curvature-based surface energies are frequently used in mathematics, physics, thin plate and shell engineering, and membrane chemistry and biology studies. Invariance under rotations and shifts makes curvature-based energies very attractive for modeling various phenomena. In computer-aided geometric design, the Willmore surfaces and the so-called minimum variation surfaces （MVS） are widely used for shape modeling purposes. The Willmore surfaces are invariant w.r.t conformal transformations （Mbius or conformal invariance）, and studied thoroughly in differential geometry and related disciplines. In contrast, the minimum variation surfaces are not conformal invariant. In this paper, we suggest a simple modification of the minimum variation energy and demonstrate that the resulting modified MVS enjoy Mbius invariance （so we call them conformal-invariant MVS or, shortly, CI-MVS）. We also study connections of CI-MVS with the cyclides of Dupin. In addition, we consider several other conformal-invariant curve and surface energies involving curvatures and curvature derivatives. In particular, we show how filtering with a conformal-invariant curve energy can be used for detecting salient subsets of the principal curvature extremum curves used by Hosaka and co-workers for shape quality inspection purposes.     

Note: Heated sample platform for in situ temperature-programmed XPS

We present the design, fabrication, and performance of the multi-specimen heated platform for linear in situ heating during the Temperature-Programmed XPS (TPXPS). The platform is versatile, compatible with high vacuum (HV) and bakeout. The heater platform is tested under in situ linear heating of typical high surface area sorbent∕catalyst support--nanoporous TiO(2). The platform allows the TPXPS of multiple samples located on specimen disk that can be transferred in and out of the TPXPS chamber. Electric characteristics, temperature and pressure curves are provided. Heating power supply, PID temperature controller, data-logging hardware and software are described.     

Determinants for Successful Agile Collaboration between UX Designers and Software Developers in a Complex Organisation

ABSTRACT

Agile and User-centered design processes have been reported to frequently putting contradictory demands on people working within these methodological frameworks. The current research addresses this point by focussing on the crucial relationship between software developer and designer. An online survey, a contextual inquiry, and a diary study were employed with 107 developers and designers in a large media organization to determine the factors for success in agile development cycles. The results from the survey show that while developers and designers have similar levels of satisfaction with agile processes, there are differences in the factors predicting those ratings. Developers are happier with the wider teamwork but want more access to and close collaboration with designers, while the latters’ concern was the quality of the wider teamwork. Additional contextual inquiries and a diary study with pairs of designers and developers reflected the survey findings that close cooperation (and proximity) was essential for improving communication, reducing inefficiencies, and avoiding suboptimal products being released. However, organizational processes, the setup of the work environment, and managerial traditions meant that this close collaboration and localized decision-making was found difficult to maintain. Results from the survey, the contextual inquiry, and the diary study found six factors for success from collaborations emerged.     

Open source: the Russian experience (legislation and practice)

The emergence of so-called free or open-source software and the growth of its economic importance in various industries make questions regarding the legal status of free/open-source licenses especially important. In December 2010, new draft amendments to the Civil Code were published, introducing new concepts in order to reflect the ideas pursued by these types of licenses. This article analyzes existing problems with the legal status of free/open-source licenses, whether proposed amendments may solve them, and what risks they may create. Since Russia is among the first countries trying to include provisions on free/open-source licenses in its legislation, such analysis may be of interest to foreign lawmakers since the concept of open source is universal all over the world.     

On the Complexity of Pareto-Optimal Nash and Strong Equilibria

We consider the computational complexity of coalitional solution concepts in scenarios related to load balancing such as anonymous and congestion games. In congestion games, Pareto-optimal Nash and strong equilibria, which are resilient to coalitional deviations, have recently been shown to yield significantly smaller inefficiency. Unfortunately, we show that several problems regarding existence, recognition, and computation of these concepts are hard, even in seemingly special classes of games. In anonymous games with constant number of strategies, we can efficiently recognize a state as Pareto-optimal Nash or strong equilibrium, but deciding existence for a game remains hard. In the case of player-specific singleton congestion games, we show that recognition and computation of both concepts can be done efficiently. In addition, in these games there are always short sequences of coalitional improvement moves to Pareto-optimal Nash and strong equilibria that can be computed efficiently.