A viral system algorithm to optimize the car dispatching in elevator group control systems of tall buildings

Nowadays is very common the presence of tall buildings in the business centres of the main cities of the world. Such buildings require the installation of numerous lifts that are coordinated and managed under a unique control system. Population working in the buildings follows a similar traffic pattern generating situations of traffic congestion. The problem arises when a passenger makes a hall call wishing to travel to another floor of the building. The dispatching of the most suitable car is the optimization problem we are tackling in this paper. We develop a viral system algorithm which is based on a bio-inspired virus infection analogy to deal with it. The viral system algorithm is compared to genetic algorithms, and tabu search approaches that have proven efficiency in the vertical transportation literature. The experiments undertaken in tall buildings from 10 to 24 floors, and several car configurations from 2 to 6 cars, provide valuable results and show how viral system outperforms such soft computing algorithms.     

Synthesis and structure of cage-like mesoporous silica using different precursors

In this work the synthesis of cubic, FDU-1 type, ordered mesoporous silica (OMS) was developed from two types of silicon source, tetraethyl orthosilicate (TEOS) and a less expensive compound, sodium silicate (Na₂Si₃O₇), in the presence of a new triblock copolymer template Vorasurf 504 (EO₃₈BO₄₆EO₃₈). For both silicon precursors the synthesis temperature was evaluated. For TEOS the effect of polymer dissolution in methanol and the acid solution (HCl and HBr) on the material structure was analyzed. For Na₂Si₃O₇ the influence of the polymer mass and the hydrothermal treatment time were the explored experimental parameters. The samples were examined by Small Angle X-ray Scattering (SAXS) and Nitrogen Sorption. For both precursors the decrease on the synthesis temperature from ambient, ?25 °C, to ?15 °C improved the ordered porous structure. For TEOS, the SAXS results showed that there is an optimum amount of hydrophobic methanol that contributed to dissolve the polymer but did not provoke structural disorder. The less electronegative Br^? ions, when compared to Cl^?, induced a more ordered porous structure, higher surface areas and larger lattice parameters. For Na₂Si₃O₇ the increase on the hydrothermal treatment time as well as the use of an optimized amount of polymer promoted a better ordered porous structure.     

Measuring spatial dispersion: exact results on the variance of random spatial distributions

Measuring the spatial distribution of locations of many entities (trees, atoms, economic activities, etc.), and, more precisely, the deviations from purely random configurations, is a powerful method to unravel their underlying interactions. Several coefficients have been developed in the past to quantify the possible deviations. It is important to quantify the variances of the coefficients for random distributions, to ascertain the statistical significance of an empirical deviation. By lack of a proper analytical expression, the significance is usually obtained by simulating many random configurations by Monte Carlo simulations. In the present paper, we present an exact analytical expression for the variance of several spatial coefficients for random distributions, and we rigorously show that these distributions asymptotically follow a Normal law. These two results eliminate the need for cumbersome Monte Carlo simulations. They also allow to understand qualitatively the main factors that may change the variance: number of sites, spatial inhomogeneity, etc.     

Cost‐Efficient Virtual Optical Network Embedding for Manageable Inter‐Data‐Center Connectivity

Network virtualization opens the door to novel infrastructure services offering connectivity and node manageability. In this letter, we focus on the cost‐efficient embedding of on‐demand virtual optical network requests for interconnecting geographically distributed data centers. We present a mixed integer linear programming formulation that introduces flexibility in the virtual‐physical node mapping to optimize the usage of the underlying physical resources. Illustrative results show that flexibility in the node mapping can reduce the number of add‐drop ports required to serve the offered demands by 40%.     

Dual-band CMOS low-noise amplifier without switches and with continuously adjustable gain

A dual-band CMOS low-noise amplifier with inductor magnetic coupling and current steering is presented which avoids the use of switches in the signal path, and has the possibility of controlling the voltage gain in the two bands, without disturbing the input impedance matching.     

Image reconstruction using interval simulated annealing in electrical impedance tomography

Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.     

A Matrix Formulation of Discrete Chirp Fourier Transform Algorithms

This work presents a computational matrix framework in terms of tensor signal algebra for the formulation of discrete chirp Fourier transform algorithms.These algorithms are used in this work to estimate the point target functions(impulse response functions)of multiple-input multiple-output(MIMO)synthetic aperture radar(SAR)systems.This estimation technique is being studied as an alternative to the estimation of point target functions using the discrete cross-ambiguity function for certain types of environmental surveillance applications.The tensor signal algebra is presented as a mathematics environment composed of signal spaces,finite dimensional linear operators,and special matrices where algebraic methods are used to generate these signal transforms as computational estimators.Also,the tensor signal algebra contributes to analysis,design,and implementation of parallel algorithms.An instantiation of the framework was performed by using the MATLAB Parallel Computing Toolbox,where all the algorithms presented in this paper were implemented.     

Distributed cross-layer coordination of congestion control and resource allocation in S-TDMA wireless networks

We consider the problem of joint congestion control and resource allocation in spatial-TDMA wireless networks. The design problem is posed as a utility maximization problem subject to link rate constraints which involve both transmission scheduling and power allocation. Starting from the performance limitations of a centralized optimization based on global network information, we proceed systematically in our development of two distributed and transparent protocols that rely on local information only. In the process, we introduce a novel decomposition method for convex optimization, establish its convergence for the utility maximization problem, and demonstrate how it suggests a distributed solution based on TCP/AQM and incremental updates of the transmission schedule. We develop a two-step procedure for finding the schedule updates and suggest two schemes for distributed link scheduling and power control under realistic interference models. Although the final protocols are suboptimal, we isolate and quantify the performance losses incurred by each simplification and demonstrate strong performance in examples.

Emulation-based transient thermal modeling of 2D/3D systems-on-chip with active cooling

State-of-the-art devices in the consumer electronics market are relying more and more on Multi-Processor Systems-On-Chip (MPSoCs) as an efficient solution to meet their multiple design constrains, such as low cost, low power consumption, high performance and short time-to-market. In fact, as technology scales down, logic density and power density increase, generating hot spots that seriously affect the MPSoC performance and can physically damage the final system behavior. Moreover, forthcoming three-dimensional (3D) MPSoCs can achieve higher system integration density, but the aforementioned thermal problems are seriously aggravated. Thus, new thermal exploration tools are needed to study the temperature variation effects inside 3D MPSoCs. In this paper, we present a novel approach for fast transient thermal modeling and analysis of 3D MPSoCs with active (liquid) cooling solutions, while capturing the hardware-software interaction. In order to preserve both accuracy and speed, we propose a close-loop framework that combines the use of Field Programmable Gate Arrays (FPGAs) to emulate the hardware components of 2D/3D MPSoC platforms with a highly optimized thermal simulator, which uses an RC-based linear thermal model to analyze the liquid flow. The proposed framework offers speed-ups of more than three orders of magnitude when compared to cycle-accurate 3D MPSoC thermal simulators. Thus, this approach enables MPSoC designers to validate different hardware- and software-based 3D thermal management policies in real-time, and while running real-life applications, including liquid cooling injection control.     

Reducing channel change delay in IPTV by predictive pre-joining of TV channels

One of the major concerns of IPTV network deployment is channel change delay (also known as zapping delay). This delay can add up to 2 s or more, and its main culprits are synchronisation and buffering of the media streams. Proving the importance of the problem is the already significant amount of literature addressing it. We start this paper with a survey of techniques proposed to reduce IPTV channel change delay.Then, by analysing an extensive dataset from an operational IPTV provider - comprising 255 thousand users, 150 TV channels, and covering a 6-month period - we have observed that most channel switching events are relatively predictable: users very frequently switch linearly, up or down to the next TV channel. This fact motivated us to use this dataset to analyse in detail a specific type of solutions to this problem, namely, predictive pre-joining of TV channels. In these schemes each set top box (STB) simultaneously joins additional multicast groups (TV channels) along with the one that is requested by the user. If the user switches to any of these channels the switching latency is virtually eliminated, not affecting therefore user's experience.We start by evaluating a simple scheme, where the neighbouring channels (i.e., channels adjacent to the requested one) are pre-joined by the STB during zapping periods. Notwithstanding the simplicity of this scheme, trace-driven simulations show that the zapping delay can be virtually eliminated for a significant percentage of channel switching requests. For example, when sending the previous and the next channel concurrently with the requested one, for only 1 min after a zapping event, switching delay is eliminated for close to half of all channel switching requests. Importantly, this result is achieved with a negligible increase of bandwidth utilisation in the access link. Other more complex schemes where user behaviour is tracked were also evaluated, but the improvement over the simple scheme was insignificant.