Abstract
A transceiver for single-line communication among sensor nodes of a body-area network is presented. It is meant to operate on a mesh like network where nodes are interconnected by two conducting-textile lines, which provide both power and communication features. The textile conductors are sewn directly to the garment in order to enhance user's mobility and comfort. For the same reason, a single battery placed in a central processing module is used to supply all sensor nodes. A low-dropout voltage regulator supplied from the transmission-line via a low pass filter ensures in each node the respective 3 V DC power supply. Power-line-communication is performed using a binary phase shift keying modulation process over a non-zero direct current line voltage at a 10 Mbps rate. The transceiver includes also line-fault testing to detect hazards which are likely to occur due to the stress applied to the conductive yarns.

Abstract
We define the notion of a catalytic-space computation. This is a computation that has a small amount of clean space available and is equipped with additional auxiliary space, with the caveat that the additional space is initially in an arbitrary, possibly incompressible, state and must be returned to this state when the computation is finished. We show that the extra space can be used in a nontrivial way, to compute uniform TC1-circuits with just a logarithmic amount of clean space. The extra space thus works analogously to a catalyst in a chemical reaction. TC1-circuits can compute for example the determinant of a matrix, which is not known to be computable in logspace. In order to obtain our results we study an algebraic model of computation, a variant of straight-line programs. We employ register machines with input registers x1, : : :, xn and work registers r1, : : :, rm. The instructions available are of the form ri?ri±u×?, with u, ? registers (distinct from ri) or constants. We wish to compute a function f(x1, : : :, xn) through a sequence of such instructions. The working registers have some arbitrary initial value ri = ti, and they may be altered throughout the computation, but by the end all registers must be returned to their initial value ti, except for, say, r1 which must hold t1 + f(x 1, : : :, xn). We show that all of Valiant's class VP, and more, can be computed in this model. This significantly extends the framework and techniques of Ben-Or and Cleve [6]. © 2014 ACM.

Abstract

Abstract
This paper aims at contributing to new insights and ideas in the area of Supply Chain Management. Revisiting some theories and areas of knowledge is critical to generate different perspectives and ways of understanding supply chains. Accordingly, this paper reopens some areas of knowledge that have fed and are continuing to feed the area of SCM (Supply Chain Management) with new ideas and thoughts, in both theoretical and practical terms. SCM approaches and practices are cross functional, organizational and inter-organizational centred areas of knowledge and, for these reasons, the authors have also made an effort to dedicate some parts of the paper to discuss and register some competitive advantages arising essentially from a pre-paradigmatic body of knowledge like SCM.

Abstract
Automatic traffic sign recognition is a difficult task, as it is necessary to distinguish between a very high number of classes with low inter-class variability. The state-of-the-art methods report very high accuracy rates but just a few classes are covered and several training samples are required. For the sake of the development of an asset management system, these approaches are out of reach. Furthermore, in this context, minimizing user's effort is more important than achieving maximal classification accuracy. In this paper, we propose a catalogue-based traffic sign classifier which doesn't require real training samples for model building and promotes minimal user's workload involving the catalogue's semantic structure in the error propagation. Experimental results reveal that user's workload was reduced by 20% while accuracy was improved by 2%.

Abstract
This paper presents a comparative study of the influence of different aggregated electrical circuit battery models in the sizing process of a hybrid energy storage system (ESS), composed by Li-ion batteries and supercapacitors (SCs). The aim is to find the number of cells required to propel a certain vehicle over a predefined driving cycle. During this process, three battery models will be considered. The first consists in a linear static zeroeth order battery model over a restricted operating window. The second is a non-linear static model, while the third takes into account first-order dynamics of the battery. Simulation results demonstrate that the adoption of a more accurate battery model in the sizing of hybrid ESSs prevents over-sizing, leading to a reduction in the number of cells of up to 29%, and a cost decrease of up to 10%.