Specifying and analyzing early requirements in Tropos

We present a framework that supports the formal verification of early requirements specifications. The framework is based on Formal Tropos, a specification language that adopts primitive concepts for modeling early requirements (such as actor, goal, and strategic dependency), along with a rich temporal specification language. We show how existing formal analysis techniques, and in particular model checking, can be adapted for the automatic verification of Formal Tropos specifications. These techniques have been implemented in a tool, called the T-Tool, that maps Formal Tropos specifications into a language that can be handled by the NuSMV model checker. Finally, we evaluate our methodology on a course-exam management case study. Our experiments show that formal analysis reveals gaps and inconsistencies in early requirements specifications that are by no means trivial to discover without the help of formal analysis tools.

Modelling of thermal cracking effects in a two-phase concrete-like solid — a parametric investigation

Incompatibility of the physical properties of concrete constituents — the aggregate and the cement paste — gives rise to microcracking when the material is cooled to very low temperatures. The phenomenon is complex and affected by a large number of factors. An analytical model of the cracking process could be instrumental in identifying parameters for experimental investigation. A preliminary study is presented, which models concrete as a two-phase medium consisting of the coarse aggregate as inclusions in the mortar matrix. A simplified finite element procedure is employed to evaluate the effects of four parameters on crack initiating temperature and on crack volume. The parameters include two physical properties — thermal expansion coefficient and elastic modulus — and two mix factors — inclusion/matrix volume fraction and inclusion particle size. Thermal coefficient and inclusion volume fraction emerge as the major parameters affecting the fracture process, but the relationship of the two mix factors is complex.     

Effect of roasting conditions on the antioxidant compounds of quinoa seeds

The effect of different roasting conditions on the antioxidant properties and the phenolic content of quinoa seeds was studied. Advanced and final products of the Maillard reaction were also quantified in order to evaluate the contribution to DPPH radical scavenging capacity and reducing power of samples. In general, response surface analysis showed significant increases in the phenolic content, the antioxidant activity and the level of Maillard reaction products (MRPs), mainly as processing temperature increased, while roasting time had a minor impact on these response variables. The highest antioxidant activity was achieved in extracts of quinoa seeds roasted at 190 °C for 30 min. Principal component analysis applied to the data suggested that MRPs had a greater contribution to antioxidant properties than phenolic compounds in the processed samples. These results demonstrated that roasted quinoa seeds/flour may be considered as a nontraditional ingredient with enhanced antioxidant capacity for the production of functional foods.     

Risk Information Seeking and Processing Model: A Meta‐Analysis

This study relies on state‐of‐the‐art meta‐analytical techniques to assess overall effects of the Risk Information Seeking and Processing (RISP) model. The results support the utility of the RISP model in predicting risk information seeking and systematic processing. However, the model demonstrated limited explanatory power for heuristic processing. A reduced model composed of only 2 variables—current knowledge and informational subjective norms—accounted for a substantial proportion of variance in the outcome variables. This more parsimonious explanation of information seeking and systematic processing might extend the utility of the RISP model to other communication settings not related to risk. Theoretical boundaries of the RISP model and implications for future research are discussed.     

Distributed shortest-path protocols for time-dependent networks

 This paper addresses algorithms for networks whose behavior changes with time according to known functions. Because the computation depends on the same functions it attempts to compute, its execution must obey strict timing constraints. When distributed versions of such algorithms are considered, a key difficulty is how to transfer local timing functions among the participating nodes. To that end it is necessary to characterize the parameterization of the functions and accommodate this parameterization in the computation. In particular, we consider the shortest-path problem in networks in which the delay of the edges changes with time according to continuous functions. We present distributed protocols for finding the shortest and minimum delay path under various waiting constraints. We investigate and analyze protocols that exchange local time-delay functions only within limited intervals yet allow every node to calculate its representation in the shortest path in time for it to be used. Received: November 1992 / Accepted: December 1995     

Practical quantum bit commitment protocol

A quantum protocol for bit commitment the security of which is based on technological limitations on non demolition measurements and long-term quantum memory is presented.     

Leontief Meets Markov: Sectoral Vulnerabilities Through Circular Connectivity

Economists have been aware of the mapping between an Input-Output (I-O, hereinafter) table and the adjacency matrix of a weighted digraph for several decades (Solow, Econometrica 20(1):29–46, 1952). An I-O table may be interpreted as a network in which edges measure money flows to purchase inputs that go into production, whilst vertices represent economic industries. However, only recently the language and concepts of complex networks (Newman 2010) have been more intensively applied to the study of interindustry relations (McNerney et al. Physica A Stat Mech Appl, 392(24):6427–6441, 2013). The aim of this paper is to study sectoral vulnerabilities in I-O networks, by connecting the formal structure of a closed I-O model (Leontief, Rev Econ Stat, 19(3):109–132, 1937) to the constituent elements of an ergodic, regular Markov chain (Kemeny and Snell 1976) and its chance process specification as a random walk on a graph. We provide an economic interpretation to a local, sector-specific vulnerability index based on mean first passage times, computed by means of the Moore-Penrose inverse of the asymmetric graph Laplacian (Boley et al. Linear Algebra Appl, 435(2):224–242, 2011). Traversing from the most central to the most peripheral sector of the economy in 60 countries between 2005 and 2015, we uncover cross-country salient roles for certain industries, pervasive features of structural change and (dis)similarities between national economies, in terms of their sectoral vulnerabilities.

     

Learning Explicit Smoothing Kernels for Joint Image Filtering

Smoothing noises while preserving strong edges in images is an important problem in image processing. Image smoothing filters can be either explicit (based on local weighted average) or implicit (based on global optimization). Implicit methods are usually time‐consuming and cannot be applied to joint image filtering tasks, i.e., leveraging the structural information of a guidance image to filter a target image. Previous deep learning based image smoothing filters are all implicit and unavailable for joint filtering. In this paper, we propose to learn explicit guidance feature maps as well as offset maps from the guidance image and smoothing parameter that can be utilized to smooth the input itself or to filter images in other target domains. We design a deep convolutional neural network consisting of a fully‐convolution block for guidance and offset maps extraction together with a stacked spatially varying deformable convolution block for joint image filtering. Our models can approximate several representative image smoothing filters with high accuracy comparable to state‐of‐the‐art methods, and serve as general tools for other joint image filtering tasks, such as color interpolation, depth map upsampling, saliency map upsampling, flash/non‐flash image denoising and RGB/NIR image denoising.     

Supporting users in finding successful matches in reciprocal recommender systems

User Modeling and User-Adapted Interaction - Online platforms which assist users in finding a suitable match, such as online-dating and job recruiting environments, have become increasingly popular...