PM10 remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region

The subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM₁₀ over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10 km and 2 measurements per day for MODIS, ∼ 25 km and observation intervals of 15 min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM₁₀ observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (r_SEV∼ 0.7, r_MOD∼ 0.6) with regard to daily averaged PM₁₀. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r∼ 0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM₁₀ assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas.     

Optimization problems in contracted tensor networks

We discuss the calculus of variations in tensor representations with a special focus on tensor networks and apply it to functionals of practical interest. The survey provides all necessary ingredients for applying minimization methods in a general setting. The important cases of target functionals which are linear and quadratic with respect to the tensor product are discussed, and combinations of these functionals are presented in detail. As an example, we consider the representation rank compression in tensor networks. For the numerical treatment, we use the nonlinear block Gauss?CSeidel method. We demonstrate the rate of convergence in numerical tests.     

Automatically performing weak mutation with the aid of symbolic execution,concolic testing and search-based testing

Automating software testing activities can increase the quality and drastically decrease the cost of software development. Toward this direction, various automated test data generation tools have been developed. The majority of existing tools aim at structural testing, while a quite limited number aim at a higher level of testing thoroughness such as mutation. In this paper, an attempt toward automating the generation of mutation-based test cases by utilizing existing automated tools is proposed. This is achieved by reducing the killing mutants’ problem into a covering branches one. To this extent, this paper is motivated by the use of state of the art techniques and tools suitable for covering program branches when performing mutation. Tools and techniques such as symbolic execution, concolic execution, and evolutionary testing can be easily adopted toward automating the test input generation activity for the weak mutation testing criterion by simply utilizing a special form of the mutant schemata technique. The propositions made in this paper integrate three automated tools in order to illustrate and examine the method’s feasibility and effectiveness. The obtained results, based on a set of Java program units, indicate the applicability and effectiveness of the suggested technique. The results advocate that the proposed approach is able to guide existing automating tools in producing test cases according to the weak mutation testing criterion. Additionally, experimental results with the proposed mutation testing regime show that weak mutation is able to speedup the mutant execution time by at least 4.79 times when compared with strong mutation.     

Understanding risk-taking behavior of groups: A “decision analysis” perspective

Past research has extensively investigated the effect of media, especially focusing on how anonymity increases risk-related behaviors of groups when using computer-mediated communication (CMC). This study extends prior research by examining the differences in group risk-taking behaviors between face-to-face groups and completely non-anonymous CMC groups (i.e., groups working in a fully identified, synchronous CMC environment similar to popular instant messaging systems utilized widely within organizations). Drawing on the “decision analysis” perspective, a key framework for understanding organizational decision-making, the study also examines the effects of the firm's risk preferences as well as the type of information distribution among group members (i.e., full information known to all group members versus partial information know by only some of the members) on the groups' risk-taking behaviors. Results from a laboratory experiment using student subjects found no differences in risk-taking behaviors between CMC and face-to-face groups; additionally, no differences were found related to how information was distributed among group members. A significant effect was found, however, for the risk preference of the firm, showing that risk-neutral firms influenced groups to make riskier decisions than groups from risk-averse firms. Finally, groups within risk-neutral firms receiving partial information made riskier decisions than groups receiving full information. The implications of these results for future research and practice are examined.     

A threshold insensitive method for locating the forest canopy top with waveform lidar

Lidars have the unique ability to make direct, physical measurements of forest height and vertical structure in much denser canopies than is possible with passive optical or short wavelength radars. However the literature reports a consistent underestimate of tree height when using physically based methods, necessitating empirical corrections. This bias is a result of overestimating the range to the canopy top due to background noise and failing to correctly identify the ground.This paper introduces a method, referred to as “noise tracking”, to avoid biases when determining the range to the canopy top. Simulated waveforms, created with Monte-Carlo ray tracing over geometrically explicit forest models, are used to test noise tracking against simple thresholding over a range of forest and system characteristics. It was found that noise tracking almost completely removed the bias in all situations except for very high noise levels and very low (< 10%) canopy covers. In all cases noise tracking gave lower errors than simple thresholding and had a lower sensitivity to the initial noise threshold.Finite laser pulses spread out the measured signal, potentially overriding the benefit of noise tracking. In the past laser pulse length has been corrected by adding half that length to the signal start range. This investigation suggests that this is not always appropriate for simple thresholding and that the results for noise tracking were more directly related to pulse length than for simple thresholding. That this effect has not been commented on before may be due to the possible confounding impacts of instrument and survey characteristics inherent in field data. This method should help improve the accuracy of waveform lidar measurements of forests, whether using airborne or spaceborne instruments.     

Generating Test Sets from Non-Deterministic Stream X-Machines

X-machines were proposed by Holcombe as a possible specification language and since then a number of further investigations have demonstrated that the model is intuitive and easy to use as well as general enough to cater for a wide range of applications. In particular (generalised) stream X-machines have been found to be extremely useful as a specification method and most of the theory developed so far has concentrated on this particular class of X-machines. Furthermore, a method for testing systems specified by stream X-machines exists and is proved to detect all faults of the implementation provided that the system meets certain initial requirements. However, this method can only be used to generate test sequences from deterministic X-machine specifications. In this paper we present the theoretical basis for a method for generating test sets from non-deterministic generalised stream X-machines. Received November 1999 / Accepted in revised form September 2000     

Performance evaluation for DRED discrete-time queueing network analytical model

Due to the rapid development in computer networks, congestion becomes a critical issue. Congestion usually occurs when the connection demands on network resources, i.e. buffer spaces, exceed the available ones. We propose in this paper a new discrete-time queueing network analytical model based on dynamic random early drop (DRED) algorithm to control the congestion in early stages. We apply our analytical model on two-queue nodes queueing network. Furthermore, we compare between the proposed analytical model and three known active queue management (AQM) algorithms, including DRED, random early detection (RED) and adaptive RED, in order to figure out which of them offers better quality of service (QoS). We also experimentally compare the queue nodes of the proposed analytical model and the three AQM methods in terms of different performance measures, including, average queue length, average queueing delay, throughput, packet loss probability, etc., aiming to determine the queue node that offers better performance.     

Christopher Strachey: Recollections of His Influence

My early research was inspired by the mathematical semantics of Scott and Strachey. Two such topics, recounted in this paper, were the fixed-point analysis of pointer loops and the expressibility of a style of functional programming introduced by Barron and Strachey.