Risk assessment for a video surveillance system based on Fuzzy Cognitive Maps

For various IT systems security is considered a key quality factor. In particular, it might be crucial for video surveillance systems, as their goal is to provide continuous protection of critical infrastructure and other facilities. Risk assessment is an important activity in security management; it aims at identifying assets, threats and vulnerabilities, analysis of implemented countermeasures and their effectiveness in mitigating risks. This paper discusses an application of a new risk assessment method, in which risk calculation is based on Fuzzy Cognitive Maps (FCMs) to a complex automated video surveillance system. FCMs are used to capture dependencies between assets and FCM based reasoning is applied to aggregate risks assigned to lower-level assets (e.g. cameras, hardware, software modules, communications, people) to such high level assets as services, maintained data and processes. Lessons learned indicate, that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on effectiveness of security system.     

Radiation- and Photo-Induced Oxidation Pathways of Methionine in Model Peptide Backbone under Anoxic Conditions

Within the reactive oxygen species (ROS) generated by cellular metabolisms, hydroxyl radicals (HO^•) play an important role, being the most aggressive towards biomolecules. The reactions of HO^• with methionine residues (Met) in peptides and proteins have been intensively studied, but some fundamental aspects remain unsolved. In the present study we examined the biomimetic model made of Ac-Met-OMe, as the simplest model peptide backbone, and of HO^• generated by ionizing radiation in aqueous solutions under anoxic conditions. We performed the identification and quantification of transient species by pulse radiolysis and of final products by LC-MS and high-resolution MS/MS after γ-radiolysis. By parallel photochemical experiments, using 3-carboxybenzophenone (CB) triplet with the model peptide, we compared the outcomes in terms of short-lived intermediates and stable product identification. The result is a detailed mechanistic scheme of Met oxidation by HO^•, and by CB triplets allowed for assigning transient species to the pathways of products formation.     

Influence of Unmodified and β-Glycerophosphate Cross-Linked Chitosan on Anti-Candida Activity of Clotrimazole in Semi-Solid Delivery Systems

The combination of an antifungal agent and drug carrier with adjunctive antimicrobial properties represents novel strategy of complex therapy in pharmaceutical technology. The goal of this study was to investigate the unmodified and ion cross-linked chitosan’s influence on anti-Candida activity of clotrimazole used as a model drug in hydrogels. It was particularly crucial to explore whether the chitosans’ structure modification by β-glycerophosphate altered its antifungal properties. Antifungal studies (performed by plate diffusion method according to CLSI reference protocol) revealed that hydrogels obtained with chitosan/β-glycerophosphate displayed lower anti-Candida effect, probably as a result of weakened polycationic properties of chitosan in the presence of ion cross-linker. Designed chitosan hydrogels with clotrimazole were found to be more efficient against tested Candida strains and showed more favorable drug release profile compared to commercially available product. These observations indicate that novel chitosan formulations may be considered as promising semi-solid delivery system of clotrimazole.     

Evaluation of quadratic cost functionals for neutral systems: the frequency-domain approach

As shown in Grabowski (1983), the problem of evaluation of the quadratic performance index for delay-differential systems of neutral type can be effectively solved by the use of Lyapunov functionals. In this paper another solution to that problem, based on the frequency-domain approach, is proposed. With the use of Plancherel's theorem and other tools of complex analysis, this task is reduced to a Riemann-Hilbert problem, an explicit solution to which is found by elementary methods. Our results can be regarded as a generalization of those due to Walton and Marshall (1984, 1987). Two simple examples of application are also provided.     

A two-pronged approach for springback variability assessment using sparse polynomial chaos expansion and multi-level simulations

In this study, we show that stochastic analysis of metal forming process requires both a high precision and low cost numerical models in order to take into account very small perturbations on inputs (physical as well as process parameters) and to allow for numerous repeated analysis in a reasonable time. To this end, an original semi-analytical model dedicated to plain strain deep drawing based on a Bending-Under-Tension numerical model (B-U-T model) is used to accurately predict the influence of small random perturbations around a nominal solution estimated with a full scale Finite Element Model (FEM). We introduce a custom sparse variant of the Polynomial Chaos Expansion (PCE) to model the propagation of uncertainties through this model at low computational cost. Next, we apply this methodology to the deep drawing process of U-shaped metal sheet considering up to 8 random variables.     

The Effect of Implanted Al and/or Y on the Scale Formation on Low-Al Fe20Cr2Al Alloy

The very early stages of the oxidation of an Fe20Cr2Al alloy, unmodified and ion-implanted by aluminium, yttrium and a combination of both elements, Al and Y, were studied at 1100 °C in oxygen using two-stage-oxidation exposures with ¹⁸O₂ as a tracer and subsequent characterisation of the scales using SIMS analyses of distribution of oxygen isotopes and oxide-related negative ion clusters, SEM observations of the surface morphology and photoluminescence spectroscopy analysis of the phase composition. The scales formed in all cases, except for the Al-implanted alloy, exhibited layered structures, with the outer part comprising Fe- and Cr-rich oxide, and the inner part being Al₂O₃, which grew due to a mixed outward–inward mechanism . The alumina sub-layers contained the transient oxides and α-Al₂O₃. Implanted Al significantly affected the mechanism of the scale growth, providing that the scale consisted essentially of α-Al₂O₃, and grew via a mixed inward-outward mechanism typical for scales on alumina formers.     

Decision trees for uplift modeling with single and multiple treatments

Most classification approaches aim at achieving high prediction accuracy on a given dataset. However, in most practical cases, some action such as mailing an offer or treating a patient is to be taken on the classified objects, and we should model not the class probabilities themselves, but instead, the change in class probabilities caused by the action. The action should then be performed on those objects for which it will be most profitable. This problem is known as uplift modeling, differential response analysis, or true lift modeling, but has received very little attention in machine learning literature. An important modification of the problem involves several possible actions, when for each object, the model must also decide which action should be used in order to maximize profit. In this paper, we present tree-based classifiers designed for uplift modeling in both single and multiple treatment cases. To this end, we design new splitting criteria and pruning methods. The experiments confirm the usefulness of the proposed approaches and show significant improvement over previous uplift modeling techniques.     

Optimization of reinforcement layout of scissor‐type bridge using differential evolution algorithm

Scissors mechanisms are commonly used in safety engineering during the construction of temporary structures, owing to their inherent advantages of foldability, transformability, and reusability. We effectively utilized these scissors mechanism features to develop a lightweight, deployable emergency Mobile Bridge (MB) based on optimization, and control of the folding structure. Here, we discuss the problems of optimal reinforcement layout for the MB by formulating and solving three optimization problems, namely: (a) the load capacity maximization problem, (b) the weight minimization problem, and (c) coupling the load capacity maximization problem and the weight minimization problem. The potential benefits resulting from the application of reinforcement were evaluated using a combination of finite element analysis and an optimization algorithm based on the differential evolution method. The results demonstrate the significant positive influence of the additional reinforcing members. In particular, the limit load was increased by over 10 times, while the weight was decreased to approximately half. The proposed methodology enabled the development of a substantially improved version of the MB characterized by a higher load capacity and lower weight in comparison to the initial bridge design.