N‐Oligo(3‐hydroxybutyrate)‐functionalized polypyrroles: towards bio‐erodible conducting copolymers

New copolymer materials have been prepared by chemical grafting of oligomeric 3‐hydroxybutyric acid (OHB) onto polypyrrole (PPy) derivatives. The influence of grafting density and molecular weight of OHB brushes on the physicochemical properties of prepared copolymers was investigated. PPy substrates were prepared by FeCl₃‐driven oxidative homopolymerization of N‐(2‐carboxyethyl)pyrrole or its copolymerization with pyrrole. The grafting method employed involved controlled anionic polymerization of β‐butyrolactone on pyrrole‐tethered potassium carboxylate active sites. Obtained PPy‐g‐OHB copolymers of varying grafting density and pendant polyester chain length were characterized and the observed structure–property relationships discussed. The impact of real time exposure to phosphate‐buffered saline environment was investigated and the residue products were characterized. Cross‐correlation of spectroscopic, thermal, electrical and elemental analysis data afforded comprehensive evaluation of the structure of prepared materials and their behaviour in hydrolytic medium. Erosion and degradation pathways have been identified, indicating ways to consciously tailor the physicochemical properties of these new biomimetic materials. © 2016 Society of Chemical Industry     

An approach to reduce energy consumption and performance losses on heterogeneous servers using power capping

Journal of Scheduling - Rapid growth of demand for remote computational power, along with high energy costs and infrastructure limits, has led to treating power usage as a primary constraint in...     

A strengthened analysis of a local algorithm for the minimum dominating set problem in planar graphs

In recent years growing interest in local distributed algorithms has widely been observed. This results from their high resistance to errors and damage, as well as from their good performance, which is independent of the size of the network. A local deterministic distributed algorithm finding an approximation of a Minimum Dominating Set in planar graphs has been presented by Lenzen et al., and they proved that the algorithm returns a 130-approximation of the Minimum Dominating Set. In this article we will show that the algorithm is two times more effective than was previously assumed, and we prove that the algorithm by Lenzen et al. outputs a 52-approximation to a Minimum Dominating Set. Therefore the gap between the lower bound and the approximation ratio of the best yet local deterministic distributed algorithm is reduced by half.     

An efficient algorithm for positive realizations

We observe that successive applications of known results from the theory of positive systems lead to an efficient general algorithm for positive realizations of transfer functions. We give two examples to illustrate the algorithm, one of which complements an earlier result of [L. Benvenuti, L. Farina, An example of how positivity may force realizations of ‘large’ dimensions, Systems Control Lett. 36 (1999) 261–266]. Finally, we improve a lower-bound of [B. Nagy, M. Matolcsi, A lower-bound on the dimension of positive realizations, IEEE Trans. Circuits Syst. I 50 (2003) 782–784] to indicate that the algorithm is indeed efficient in general.     

Grid-Controlled Lightpaths for High Performance Grid Applications

Grid applications call for high performance networking support. One attractive solution is to deploy Grids over optical networks. However, resource management in optical domains is traditionally very rigid and cannot successfully meet the requirements of Grid applications, such as flexible provisioning and configuration. In this paper, we present a customizable resource management solution for optical networks where users can create lightpaths on demand and manage their own network resources. Thanks to a Grid-centric system architecture, lightpath resources can be shared among users and easily integrated with data and computation Grids.     

Path‐space Motion Estimation and Decomposition for Robust Animation Filtering

Renderings of animation sequences with physics‐based Monte Carlo light transport simulations are exceedingly costly to generate frame‐by‐frame, yet much of this computation is highly redundant due to the strong coherence in space, time and among samples. A promising approach pursued in prior work entails subsampling the sequence in space, time, and number of samples, followed by image‐based spatio‐temporal upsampling and denoising. These methods can provide significant performance gains, though major issues remain: firstly, in a multiple scattering simulation, the final pixel color is the composite of many different light transport phenomena, and this conflicting information causes artifacts in image‐based methods. Secondly, motion vectors are needed to establish correspondence between the pixels in different frames, but it is unclear how to obtain them for most kinds of light paths (e.g. an object seen through a curved glass panel). To reduce these ambiguities, we propose a general decomposition framework, where the final pixel color is separated into components corresponding to disjoint subsets of the space of light paths. Each component is accompanied by motion vectors and other auxiliary features such as reflectance and surface normals. The motion vectors of specular paths are computed using a temporal extension of manifold exploration and the remaining components use a specialized variant of optical flow. Our experiments show that this decomposition leads to significant improvements in three image‐based applications: denoising, spatial upsampling, and temporal interpolation.     

Reduced Aggregate Scattering Operators for Path Tracing

Aggregate scattering operators (ASOs) describe the overall scattering behavior of an asset (i.e., an object or volume, or collection thereof) accounting for all orders of its internal scattering. We propose a practical way to precompute and compactly store ASOs and demonstrate their ability to accelerate path tracing. Our approach is modular avoiding costly and inflexible scene‐dependent precomputation. This is achieved by decoupling light transport within and outside of each asset, and precomputing on a per‐asset level. We store the internal transport in a reduced‐dimensional subspace tailored to the structure of the asset geometry, its scattering behavior, and typical illumination conditions, allowing the ASOs to maintain good accuracy with modest memory requirements. The precomputed ASO can be reused across all instances of the asset and across multiple scenes. We augment ASOs with functionality enabling multi‐bounce importance sampling, fast short‐circuiting of complex light paths, and compact caching, while retaining rapid progressive preview rendering. We demonstrate the benefits of our ASOs by efficiently path tracing scenes containing many instances of objects with complex inter‐reflections or multiple scattering.     

A Partial Order Approach to Branching Time Logic Model Checking

Partial order techniques enable reducing the size of the state space used for model checking, thus alleviating the “state space explosion” problem. These reductions are based on selecting a subset of the enabled operations from each program state. So far, these methods have been studied, implemented, and demonstrated for assertional languages that model the executions of a program as computation sequences, in particular the linear temporal logic. The present paper shows, for the first time, how this approach can be applied to languages that model the behavior of a program as a tree. We study here partial order reductions for branching temporal logics, e.g., the logics CTL and CTL* (with the next time operator removed) and process algebra logics such as Hennesy–Milner logic (withτactions). Conditions on the selection of subset of successors from each state during the state-space construction, which guarantee reduction that preserves CTL* properties, are given. The experimental results provided show that the reduction is substantial.     

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.     

A Geometric Approach to Solving Problems of Control Constraints: Theory and a DAE Framework

The paper deals with controlled mechanical systems in which the number of control inputs is equal to the number of desired system outputs, and is smaller than the number of degrees of freedom of the system. The determination of control input strategy that force the underactuated system to complete the partly specified motion is a challenging problem. In the present formulation, the outputs (performance goals), expressed in terms of system states, are treated as constraints on the system—called control or program constraints as distinct from contact constraints in the classical sense, and a mathematical resemblance of the inverse control problem to the constrained system dynamics is exploited. However, while the reactions of contact constraints act in the directions orthogonal to the respective constraint manifold, the available control reactions may have arbitrary directions with respect to the program constraint manifold, and in the extreme may be tangent. A specific methodology must then be developed to find the solution of such singular problems, related to a class of control tracking problems such as position control of elastic joint robots, control of cranes, and aircraft control in prescribed trajectory flight. The governing equations of the problem arise as a set of differential-algebraic equations (DAEs), and an effective method for solving the DAEs, based on backward Euler method, is proposed. The open-loop control formulation obtained this way is then extended by a closed-loop control law to provide stable tracking of the required reference trajectories in the presence of perturbations. Some examples of applications of the theory and results of numerical simulations are reported.