Detecting unknown coal fires: synergy of automated coal fire risk area delineation and improved thermal anomaly extraction

This paper presents two complementing algorithms for remote sensing based coal fire research and the results derived thereof. Both are applicable on Landsat, ASTER and MODIS data. The first algorithm automatically delineates coal fire risk areas from multispectral satellite data. The second automatically extracts local coal fire related thermal anomalies from thermal data. The presented methods aim at the automated, unbiased retrieval of coal fire related information. The delineation of coal fire risk areas is based on land cover extraction through a knowledge based spectral test sequence. This sequence has been proven to extract coal fire risk areas not only in time series of the investigated study areas in China, but also in transfer regions of India and Australia. The algorithm for the extraction of thermal anomalies is based on a moving window approach analysing sub‐window histograms. It allows the extraction of thermally anomalous pixels with regard to their surrounding background and therefore supports the extraction of very subtle, local thermal anomalies of different temperature. It thus shows clear advantages to anomaly extraction via simple thresholding techniques. Since the thermal algorithm also does extract thermal anomalies, which are not related to coal fires, the derived risk areas can help to eliminate false alarms. Overall, 50% of anomalies derived from night‐time data can be rejected, while even 80% of all anomalies extracted from daytime data are likely to be false alarms. However, detection rates are very good. Over 80% of existing coal fires in our first study area were extracted correctly and all fires (100%) in study area two were extracted from Landsat data. In MODIS data extraction depends on coal fire types and reaches 80% of all fires in our study area with hot coal fires of large spatial extent, while in another region with smaller and ‘colder’ coal fires only the hottest ones (below 20%) can be extracted correctly. The success of the synergetic application of the two methods has been proven through our detection of so far unknown coal fires in Landsat 7 ETM+ remote sensing data. This is the first time in coal fire research that unknown coal fires were detected in satellite remote sensing data exclusively and were validated later subsequently during in situ field checks.     

Perci: Pervasive Service Interaction with the Internet of Things

The advancement of ubiquitous computing technologies has greatly improved the availability of digital resources in the real world. Here, the authors investigate mobile interaction with tagged, everyday objects and associated information that's based on the Internet of Things and its technologies. Their framework for integrating Web services and mobile interaction with physical objects relies on information typing to increase interoperability. Two prototypes for mobile interaction with smart posters build upon this framework to realize multi-tag interaction with physical user interfaces. The authors' evaluation identifies usability issues regarding the design of physical mobile interactions, interfaces, and applications.     

A Linear Time Algorithm for the Arc Disjoint Menger Problem in Planar Directed Graphs

Given a graph G=(V,E) and two vertices s,t ∈ V , s\neq t , the Menger problem is to find a maximum number of disjoint paths connecting s and t . Depending on whether the input graph is directed or not, and what kind of disjointness criterion is demanded, this general formulation is specialized to the directed or undirected vertex, and the edge or arc disjoint Menger problem, respectively. For planar graphs the edge disjoint Menger problem has been solved to optimality [W2], while the fastest algorithm for the arc disjoint version is Weihe's general maximum flow algorithm for planar networks [W1], which has running time \bf O (|V| log |V|) . Here we present a linear time, i.e., asymptotically optimal, algorithm for the arc disjoint version in planar directed graphs. Received August 1997; revised January 1999.     

Selection of knowledge acquisition techniques based upon the problem domain characteristics of production and operations management expert systems

The application of expert systems to various problem domains in business has grown steadily since their introduction. Regardless of the chosen method of development, the most commonly cited problems in developing these systems are the unavailability of both the experts and knowledge engineers and difficulties with the process of acquiring knowledge from domain experts. Within the field of artificial intelligence, this has been called the 'knowledge acquisition' problem and has been identified as the greatest bottleneck in the expert system development process. Simply stated, the problem is how to acquire the specific knowledge for a well-defined problem domain efficiently from one or more experts and represent it in the appropriate computer format. Given the 'paradox of expertise', the experts have often proceduralized their knowledge to the point that they have difficulty in explaining exactly what they know and how they know it. However, empirical research in the field of expert systems reveals that certain knowledge acquisition techniques are significantly more efficient than others in helping to extract certain types of knowledge within specific problem domains. In this paper we present a mapping between these empirical studies and a generic taxonomy of expert system problem domains. In so doing, certain knowledge acquisition techniques can be prescribed based on the problem domain characteristics. With the production and operations management (P/OM) field as the pilot area for the current study, we first examine the range of problem domains and suggest a mapping of P/OM tasks to a generic taxonomy of problem domains. We then describe the most prominent knowledge acquisition techniques. Based on the examination of the existing empirical knowledge acquisition research, we present how the empirical work can be used to provide guidance to developers of expert systems in the field of P/OM.     

Virtual Reality Interfaces for Visualization and Control of Remote Vehicles

The Autonomy and Robotics Area (ARA) at NASA Ames Research Center has investigated the use of various types of Virtual Reality-based operator interfaces to remotely control complex robotic mechanisms. In this paper, we describe the major accomplishments and technology applications of the ARA in this area, and highlight the advantages and issues related to this technology.     

Work Practices Surrounding PACS: The Politics of Space in Hospitals

This paper uses a case study of collaborative work practices within the radiology department of a hospital, for examining the usefulness of spatial approaches to collaboration. It takes a socio-political perspective on understanding the shaping effects of spatial arrangements on work practices, and seeks to identify some of the key CSCW issues that can be addressed in spatial terms. We analyse the spatial settings or layers (physical, digital and auditory) within which work takes place, and the qualities of connections between them, examining in how far they support (professional) boundaries or help maintain a sense of context. Guiding themes are the relationships between space and the visibility of work, and how to accommodate social world needs through spatial arrangements.     

Hepatoma with severe non-islet cell tumor hypoglycemia

We report a 22-yr-old male patient with chronic hepatitis B and a large, well differentiated hepatoma who developed episodes of symptomatic fasting hypoglycemia, which were caused by paraneoplastic secretion of unprocessed "big" insulin-like growth factor-II. Initially, the patient presented with normal liver function, which deteriorated during the clinical course. Therapeutic attempts to reduce tumor mass failed and the patient subsequently died because of metastases of the hepatoma. The pathophysiology of non-islet cell tumor hypoglycemia, differential diagnosis, and therapeutic options are discussed.     

An observation on probability versus randomness with applications to complexity classes

Every class C of languages satisfying a simple topological condition is shown to have probability one if and only if it contains some language that is algorithmically random in the sense of Martin-Löf. This result is used to derive separation properties of algorithmically random oracles and to give characterizations of the complexity classesP, BPP, AM, andPH in terms of reducibility to such oracles. These characterizations lead to results like:P =NP if and only if an algorithmically random set exists that is _btt ^P -hard forNP.The work of the first author was supported in part by the Alexander-von-Humboldt-Stiftung and by the National Science Foundation under Grant CCR-8913584 while he visited the Lehrstuhl für Theoretische Informatik, Institut für Informatik, Universität Würzburg, Germany. The work of the second author was supported in part by the National Science Foundation under Grant CCR-8809238 and in part by DIMACS, where he was a visitor while a portion of his work was done.     

Reduced mechanical efficiency in chronic obstructive pulmonary disease but normal peak VO2 with small muscle mass exercise

We studied six patients with chronic obstructive pulmonary disease (COPD) (FEV1 = 1.1 +/- 0.2 L, 32% of predicted) and six age- and activity level-matched control subjects while performing both maximal bicycle exercise and single leg knee-extensor exercise. Arterial and femoral venous blood sampling, thermodilution blood flow measurements, and needle biopsies allowed the assessment of muscle oxygen supply, utilization, and structure. Maximal work rates and single leg VO2max (control subjects = 0.63 +/- 0.1; patients with COPD = 0.37 +/- 0.1 L/minute) were significantly greater in the control group during bicycle exercise. During knee-extensor exercise this difference in VO2max disappeared, whereas maximal work capacity was reduced (flywheel resistance: control subjects = 923 +/- 198; patients with COPD = 612 +/- 81 g) revealing a significantly reduced mechanical efficiency (work per unit oxygen consumed) with COPD. The patients had an elevated number of less efficient type II muscle fibers, whereas muscle fiber cross-sectional areas, capillarity, and mitochondrial volume density were not different between the groups. Therefore, although metabolic capacity per se is unchanged, fiber type differences associated with COPD may account for the reduced muscular mechanical efficiency that becomes clearly apparent during knee-extensor exercise, when muscle function is no longer overshadowed by the decrement in lung function.