Energy-aware lazy scheduling algorithm for energy-harvesting sensor nodes

The main problem in dealing with energy-harvesting (EH) sensor nodes is represented by the scarcity and non-stationarity of powering, due to the nature of the renewable energy sources. In this work, the authors address the problem of task scheduling in processors located in sensor nodes powered by EH sources. Some interesting solutions have appeared in the literature in the recent past, as the lazy scheduling algorithm (LSA), which represents a performing mix of scheduling effectiveness and ease of implementation. With the aim of achieving a more efficient and conservative management of energy resources, a new improved LSA solution is here proposed. Indeed, the automatic ability of foreseeing at run-time the task energy starving (i.e. the impossibility of finalizing a task due to the lack of power) is integrated within the original LSA approach. Moreover, some modifications have been applied in order to reduce the LSA computational complexity and thus maximizing the amount of energy available for task execution. The resulting technique, namely energy-aware LSA, has then been tested in comparison with the original one, and a relevant performance improvement has been registered both in terms of number of executable tasks and in terms of required computational burden.     

Needs and desires: transcending the ‘bipolar tendency’

The paper connects two of the concerns of this special issue: the way to transcend the ‘bipolar tendency’ of the market culture and to ‘deal with the swings between prophesies of doom that serve only to paralyse us further, and the unbridled consumerism that makes things worse’, and how to remain human when being mediated by technology in contrast to how we are in the presence of others. Our contribution is based on an extensive conception of human beings (HBs). HBs cannot be considered only as cognitive subjects but also in their anthropological integrity. What we mean by this that they think and feel, they share concepts and emotions, they plan and desire. It implies that any attempt at reducing this complexity is a way to diminish human beings and their capabilities. HBs need meaningful course of actions to manage complexity and to tackle alternatives. Meanings come from purposeful activities, and people’s purposes are based not only on utilitarian or rational enquiries but also on what they consider right and good, according to their vision of the world. This is also the key to overcome the ‘bipolar tendency’.     

On the detection of card-sharing traffic through wavelet analysis and Support Vector Machines

In the last years, the interest in methods and techniques for circumventing the security of the available digital video broadcasting systems is continuously increasing. Digital TV providers are struggling to restrict access to their video contents only to authorized users, by deploying more and more sophisticated conditional access systems. At the state-of-the-art, the most significant menace is the card-sharing activity which exploits a known weakness allowing an authorized subscriber to provide access to digital contents to a potentially large group of unauthorized ones connected over a communication network. This is usually realized by using ad hoc customized devices. Detecting the presence of these illegal systems on a network, by recognizing their related traffic is an issue of primary importance. Unfortunately, to avoid the identification of such traffic, payload obfuscation strategies based on encryption are often used, hindering packet inspection techniques.This paper presents a strategy for the detection of card-sharing traffic, empowered by machine-learning-driven traffic classification techniques and based on the natural capability of wavelet analysis to decompose a traffic time series into several component series associated with particular time and frequency scales and hence allowing its observation at different frequency component levels and with different resolutions. These ideas have been used for the proof-of-concept implementation of an SVM-based binary classification scheme that relies only on time regularities of the traffic and not on the packet contents and hence is immune to payload obfuscation techniques.     

A 2D Full-Band Monte Carlo Study of HgCdTe-Based Avalanche Photodiodes

This work presents a numerical simulation study of HgCdTe-based avalanche photodetectors (APDs). The two-dimensional model used is based on a full-band Monte Carlo approach in which the electronic structure is computed using a nonlocal empirical pseudopotential model with spin–orbit corrections. The carrier–phonon scattering rates have been computed from first principles using a rigid pseudo-ion model. The most attractive feature of these devices is the potential for single-carrier ionization when electrons are used as the primary injection carrier. For this reason, this work focuses on two front-illuminated (electron-injection) device structures: a planar diffused PIN structure and a planar diffused PN photodiode with guard rings. To predict the performance of these APDs, the electron multiplication gain has been studied as a function of the position where photogenerated carriers are injected and as a function of the curvature of the p-type diffusion region. We find that, in the diffused PIN structure, the limited lateral spatial extent of the high-electric-field region leads to a reduction of the multiplication gain from the center of the device to the periphery. Furthermore, the higher the curvature, the more abruptly the gain decreases. For the simple PN structure, we find that the presence of the guard rings removes the high electric field from the surface and induces a more gradual roll-off of the gain from the center of the device to the periphery.     

Estimation of the mass of powder trapped at collision during ball milling from the kinetics of the mechanically activated decomposition of Ag oxalate

The present work aims at providing a direct experimental estimate of the amount of powder trapped at each collision during the mechanical processing by ball milling. Attention has been focused on the mechanochemical reactivity of anhydrous Ag oxalate powders, prepared by mixing Ag nitrate and Na oxalate aqueous solutions, and then filtering and drying the white precipitate formed. Suitable amounts of such powders were mechanically processed with a single milling ball. The mechanical processing induced the gradual decomposition of Ag oxalate into Ag and carbon dioxide. The process was followed by gravimetric analyses, and its kinetics related to individual collisions. It is shown that the decomposition process follows a simple exponential kinetics, which allows the identification and evaluation of an apparent rate constant. This can be regarded as a measure of the amount of powder trapped at each collision, which is roughly equal to 0.41 mg.     

Predicting mode-II delamination suppression in z-pinned laminates

A finite element model for predicting delamination resistance of z-pin reinforced laminates under the mode-II load condition is presented. End notched flexure specimen is simulated using a cohesive zone model. The main difference of this approach to previously published cohesive zone models is that the individual bridging force exerted by z-pin is governed by a specific traction-separation law derived from a unit-cell model of single pin failure process, which is independent of the fracture toughness of the unreinforced laminate. Therefore, two separate traction-separation laws are employed; one represents unreinforced laminate properties and the other for the enhanced delamination toughness owing to the pin bridging action. This approach can account for the so-called large scale bridging effect and avoid using concentrated pin forces in numerical models, thus removing the mesh-size dependency and permitting more accurate and reliable computational solutions.     

Parametric macromodeling based on amplitude and frequency scaled systems with guaranteed passivity

We propose a novel parametric macromodeling method for systems described by scattering parameters, which depend on multiple design variables such as geometrical layout or substrate features. It is able to build accurate multivariate macromodels that are stable and passive over the entire design space. Poles and residues are parameterized indirectly. The proposed method is based on an efficient and reliable combination of rational identification, a procedure to find amplitude and frequency scaling system coefficients and positive interpolation schemes. Pertinent numerical examples validate the proposed parametric macromodeling technique. Copyright © 2011 John Wiley & Sons, Ltd.     

金属W中辐照缺陷的产生、演化与热回复机制

金属W是核聚变反应堆中面向等离子体部件的主要候选材料。服役期间,钨部件需要承受高温、高通量聚变反应中子轰击带来的辐照级联损伤。这些损伤主要表现为高浓度的点缺陷及团簇。它们与氢氦等离子体、嬗变反应的多种产物相互作用,导致辐照硬化、韧脆转变温度升高、导热能力下降等问题。本文围绕金属W的辐照级联损伤,基于显微缺陷实验表征与材料多尺度模拟计算,系统总结了辐照缺陷的产生、演化与热回复行为及作用机制。这些信息反映了材料中辐照缺陷特征的统计规律,构成定量描述微观损伤组织随时间尺度与空间尺度变化的依据,有利于钨部件性能的预测、服役可靠性评价以及未来新型材料部件的研发。