Smart video surveillance: exploring the concept of multiscale spatiotemporal tracking

Situation awareness is the key to security. Awareness requires information that spans multiple scales of space and time. Smart video surveillance systems are capable of enhancing situational awareness across multiple scales of space and time. However, at the present time, the component technologies are evolving in isolation. To provide comprehensive, nonintrusive situation awareness, it is imperative to address the challenge of multiscale, spatiotemporal tracking. This article explores the concepts of multiscale spatiotemporal tracking through the use of real-time video analysis, active cameras, multiple object models, and long-term pattern analysis to provide comprehensive situation awareness.     

Diagnostic value of MR arthrography in detection of intrinsic carpal ligament lesions: use of cine-MR arthrography as a new approach

Twenty-five patients with chronic wrist pain and a preliminary diagnosis of carpal instability were examined with conventional MR imaging and MR arthrography with single compartment intra-articular injection. A new cine-MR arthrography technique, with image acquisition at every 5 s during intra-articular injection, was performed in 17 subjects. The purpose of this study was to determine the diagnostic value of MR arthrography in ligamentous lesions of the wrist and to assess the value of cine-MR arthrography in comparison with arthroscopy and/or surgery. Magnetic resonance arthrography, a semi-invasive technique, increased the diagnostic accuracy of intrinsic carpal ligament injuries. Cine-MR arthrography can be considered as a promising technique especially for the evaluation of lunatotriquetral and scapholunate ligament injuries of the wrist.     

Pure cycles in flexible robotic cells

In this study, an m-machine flexible robotic manufacturing cell consisting of CNC machines is considered. The flexibility of the machines leads to a new class of robot move cycles called the pure cycles. We first model the problem of determining the best pure cycle in an m-machine cell as a special travelling salesman problem in which the distance matrix consists of decision variables as well as parameters. We focus on two specific cycles among the huge class of pure cycles. We prove that, in most of the regions, either one of these two cycles is optimal. For the remaining regions we derive worst case performances of these cycles. We also prove that the set of pure cycles dominates the flowshop-type robot move cycles considered in the literature. As a design problem, we consider the number of machines in a cell as a decision variable. We determine the optimal number of machines that minimizes the cycle time for given cell parameters such as the processing times, robot travel times and the loading/unloading times of the machines.     

Defining critical current

The critical current of a practical superconductor can be defined in a variety of ways such as a specific voltage level, an apparent resistivity, or even the point of the irreversible superconducting-to-normal transition. The resultant values may differ very little or be meaningless for one given condition, but when comparing superconductors under a variety of conditions, such as different magnetic fields or applied stresses, these various definitions can give apparently different behavior. This is illustrated using data on the effects of stress on the critical current behavior in wires. As part of an initial effort at the National Bureau of Standards to develop standard practices and definitions for practical superconductors, several critical current criteria are proposed and discussed.     

Using economic valuation techniques to inform water resources management: a survey and critical appraisal of available techniques and an application

The need for economic analysis for the design and implementation of efficient water resources management policies is well documented in the economics literature. This need is also emphasised in the European Union's recent Water Framework Directive (2000/60/EC), and is relevant to the objectives of Euro-limpacs, an EU funded project which inter alia, aims to provide a decision-support system for valuing the effects of future global change on Europe's freshwater ecosystems. The purpose of this paper is to define the role of economic valuation techniques in assisting in the design of efficient, equitable and sustainable policies for water resources management in the face of environmental problems such as pollution, intensive land use in agriculture and climate change. The paper begins with a discussion of the conceptual economic framework that can be used to inform water policy-making. An inventory of the available economic valuation methods is presented and the scope and suitability of each for studying various aspects of water resources are critically discussed. Recent studies that apply these methods to water resources are reviewed. Finally, an application of one of the economic valuation methods, namely the contingent valuation method, is presented using a case study of the Cheimaditida wetland in Greece.     

Automatic soccer video analysis and summarization

We propose a fully automatic and computationally efficient framework for analysis and summarization of soccer videos using cinematic and object-based features. The proposed framework includes some novel low-level processing algorithms, such as dominant color region detection, robust shot boundary detection, and shot classification, as well as some higher-level algorithms for goal detection, referee detection, and penalty-box detection. The system can output three types of summaries: i) all slow-motion segments in a game; ii) all goals in a game; iii) slow-motion segments classified according to object-based features. The first two types of summaries are based on cinematic features only for speedy processing, while the summaries of the last type contain higher-level semantics. The proposed framework is efficient, effective, and robust. It is efficient in the sense that there is no need to compute object-based features when cinematic features are sufficient for the detection of certain events, e.g., goals in soccer. It is effective in the sense that the framework can also employ object-based features when needed to increase accuracy (at the expense of more computation). The efficiency, effectiveness, and robustness of the proposed framework are demonstrated over a large data set, consisting of more than 13 hours of soccer video, captured in different countries and under different conditions.