Implementation of fractional-order electromagnetic potential through a genetic algorithm

Several phenomena present in electrical systems motivated the development of comprehensive models based on the theory of fractional calculus (FC). Bearing these ideas in mind, in this work are applied the FC concepts to define, and to evaluate, the electrical potential of fractional order, based in a genetic algorithm optimization scheme. The feasibility and the convergence of the proposed method are evaluated.

Demux devices based on A-SiC:H

In this paper we present results about the functioning of a multilayered a-SiC:H heterostructure as a device for wavelength-division demultiplexing of optical signals. The device is composed of two stacked p-i-n photodiodes, both optimized for the selective collection of photogenerated carriers. Band gap engineering was used to adjust the photogeneration and recombination rates profiles of the intrinsic absorber regions of each photodiode to short and long wavelength absorption and carrier collection in the visible spectrum. The photocurrent signal using different input optical channels was analyzed at reverse and forward bias and under steady state illumination. This photocurrent is used as an input for a demux algorithm based on the voltage controlled sensitivity of the device. The device functioning is explained with results obtained by numerical simulation of the device, which permit an insight to the internal electric configuration of the double heterojunction.These results address the explanation of the device functioning in the frequency domain to a wavelength tunable photocapacitance due to the accumulation of space charge localized at the internal junction. The existence of a direct relation between the experimentally observed capacitive effects of the double diode and the quality of the semiconductor materials used to form the internal junction is highlighted.

Hyperspectral unmixing based on mixtures of Dirichlet components

This paper introduces a new unsupervised hyperspectral unmixing method conceived to linear but highly mixed hyperspectral data sets, in which the simplex of minimum volume, usually estimated by the purely geometrically based algorithms, is far way from the true simplex associated with the endmembers. The proposed method, an extension of our previous studies, resorts to the statistical framework. The abundance fraction prior is a mixture of Dirichlet densities, thus automatically enforcing the constraints on the abundance fractions imposed by the acquisition process, namely, nonnegativity and sum-to-one. A cyclic minimization algorithm is developed where the following are observed: 1) The number of Dirichlet modes is inferred based on the minimum description length principle; 2) a generalized expectation maximization algorithm is derived to infer the model parameters; and 3) a sequence of augmented Lagrangian-based optimizations is used to compute the signatures of the endmembers. Experiments on simulated and real data are presented to show the effectiveness of the proposed algorithm in unmixing problems beyond the reach of the geometrically based state-of-the-art competitors.

People counting system using existing surveillance video camera

The Casa da Música Foundation, responsible for the management of Casa da Música do Porto building, has the need to obtain statistical data related to the number of building’s visitors. This information is a valuable tool for the elaboration of periodical reports concerning the success of this cultural institution. For this reason it was necessary to develop a system capable of returning the number of visitors for a requested period of time. This represents a complex task due to the building’s unique architectural design, characterized by very large doors and halls, and the sudden large number of people that pass through them in moments preceding and proceeding the different activities occurring in the building. To achieve the technical solution for this challenge, several image processing methods, for people detection with still cameras, were first studied. The next step was the development of a real time algorithm, using OpenCV libraries and computer vision concepts,to count individuals with the desired accuracy. This algorithm includes the scientific and technical knowledge acquired in the study of the previous methods. The themes developed in this thesis comprise the fields of background maintenance, shadow and highlight detection, and blob detection and tracking. A graphical interface was also built, to help on the development, test and tunning of the proposed system, as a complement to the work. Furthermore, tests to the system were also performed, to certify the proposed techniques against a set of limited circumstances. The results obtained revealed that the algorithm was successfully applied to count the number of people in complex environments with reliable accuracy.

Optimization of multi-stage amplifiers in deep-submicron CMOS using a distributed/parallel genetic algorithm

IEEE International Symposium on Circuits and Systems, pp. 724 – 727, Seattle, EUA

Including context in a routing algorithm for the internet of things

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

Improving Assumption based Distributed Belief Revision

Belief revision is a critical issue in real world DAI applications. A Multi-Agent System not only has to cope with the intrinsic incompleteness and the constant change of the available knowledge (as in the case of its stand alone counterparts), but also has to deal with possible conflicts between the agents’ perspectives. Each semi-autonomous agent, designed as a combination of a problem solver – assumption based truth maintenance system (ATMS), was enriched with improved capabilities: a distributed context management facility allowing the user to dynamically focus on the more pertinent contexts, and a distributed belief revision algorithm with two levels of consistency. This work contributions include: (i) a concise representation of the shared external facts; (ii) a simple and innovative methodology to achieve distributed context management; and (iii) a reduced inter-agent data exchange format. The different levels of consistency adopted were based on the relevance of the data under consideration: higher relevance data (detected inconsistencies) was granted global consistency while less relevant data (system facts) was assigned local consistency. These abilities are fully supported by the ATMS standard functionalities.

Algorithm-oriented design of efficient many-core architectures applied to dense matrix multiplication

Recent integrated circuit technologies have opened the possibility to design parallel architectures with hundreds of cores on a single chip. The design space of these parallel architectures is huge with many architectural options. Exploring the design space gets even more difficult if, beyond performance and area, we also consider extra metrics like performance and area efficiency, where the designer tries to design the architecture with the best performance per chip area and the best sustainable performance. In this paper we present an algorithm-oriented approach to design a many-core architecture. Instead of doing the design space exploration of the many core architecture based on the experimental execution results of a particular benchmark of algorithms, our approach is to make a formal analysis of the algorithms considering the main architectural aspects and to determine how each particular architectural aspect is related to the performance of the architecture when running an algorithm or set of algorithms. The architectural aspects considered include the number of cores, the local memory available in each core, the communication bandwidth between the many-core architecture and the external memory and the memory hierarchy. To exemplify the approach we did a theoretical analysis of a dense matrix multiplication algorithm and determined an equation that relates the number of execution cycles with the architectural parameters. Based on this equation a many-core architecture has been designed. The results obtained indicate that a 100 mm(2) integrated circuit design of the proposed architecture, using a 65 nm technology, is able to achieve 464 GFLOPs (double precision floating-point) for a memory bandwidth of 16 GB/s. This corresponds to a performance efficiency of 71 %. Considering a 45 nm technology, a 100 mm(2) chip attains 833 GFLOPs which corresponds to 84 % of peak performance These figures are better than those obtained by previous many-core architectures, except for the area efficiency which is limited by the lower memory bandwidth considered. The results achieved are also better than those of previous state-of-the-art many-cores architectures designed specifically to achieve high performance for matrix multiplication.

Detect and pointing algorithm's performance for a planar smart antenna array: a review

An adaptive antenna array combines the signal of each element, using some constraints to produce the radiation pattern of the antenna, while maximizing the performance of the system. Direction of arrival (DOA) algorithms are applied to determine the directions of impinging signals, whereas beamforming techniques are employed to determine the appropriate weights for the array elements, to create the desired pattern. In this paper, a detailed analysis of both categories of algorithms is made, when a planar antenna array is used. Several simulation results show that it is possible to point an antenna array in a desired direction based on the DOA estimation and on the beamforming algorithms. A comparison of the performance in terms of runtime and accuracy of the used algorithms is made. These characteristics are dependent on the SNR of the incoming signal.

A physical packing sequence algorithm for the container loading problem with static mechanical equilibrium conditions

The container loading problem (CLP) is a combinatorial optimization problem for the spatial arrangement of cargo inside containers so as to maximize the usage of space. The algorithms for this problem are of limited practical applicability if real-world constraints are not considered, one of the most important of which is deemed to be stability. This paper addresses static stability, as opposed to dynamic stability, looking at the stability of the cargo during container loading. This paper proposes two algorithms. The first is a static stability algorithm based on static mechanical equilibrium conditions that can be used as a stability evaluation function embedded in CLP algorithms (e.g. constructive heuristics, metaheuristics). The second proposed algorithm is a physical packing sequence algorithm that, given a container loading arrangement, generates the actual sequence by which each box is placed inside the container, considering static stability and loading operation efficiency constraints.

Building a person home behavior model based on data from smart house sensors 2015

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

NoC contention analysis using a branch-and-prune algorithm

“Many-core” systems based on a Network-on-Chip (NoC) architecture offer various opportunities in terms of performance and computing capabilities, but at the same time they pose many challenges for the deployment of real-time systems, which must fulfill specific timing requirements at runtime. It is therefore essential to identify, at design time, the parameters that have an impact on the execution time of the tasks deployed on these systems and the upper bounds on the other key parameters. The focus of this work is to determine an upper bound on the traversal time of a packet when it is transmitted over the NoC infrastructure. Towards this aim, we first identify and explore some limitations in the existing recursive-calculus-based approaches to compute the Worst-Case Traversal Time (WCTT) of a packet. Then, we extend the existing model by integrating the characteristics of the tasks that generate the packets. For this extended model, we propose an algorithm called “Branch and Prune” (BP). Our proposed method provides tighter and safe estimates than the existing recursive-calculus-based approaches. Finally, we introduce a more general approach, namely “Branch, Prune and Collapse” (BPC) which offers a configurable parameter that provides a flexible trade-off between the computational complexity and the tightness of the computed estimate. The recursive-calculus methods and BP present two special cases of BPC when a trade-off parameter is 1 or ∞, respectively. Through simulations, we analyze this trade-off, reason about the implications of certain choices, and also provide some case studies to observe the impact of task parameters on the WCTT estimates.

Time-domain optimization of amplifiers based on distributed genetic algorithms

Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering

Step count algorithm adapted to indoor localization

This paper presents a step count algorithm designed to work in real-time using low computational power. This proposal is our first step for the development of an indoor navigation system, based on Pedestrian Dead Reckoning (PDR). We present two approaches to solve this problem and compare them based in their error on step counting, as well as, the capability of their use in a real time system.

Traveled Distance Estimation Algorithm for Indoor Localization

This paper presents an ankle mounted Inertial Navigation System (INS) used to estimate the distance traveled by a pedestrian. This distance is estimated by the number of steps given by the user. The proposed method is based on force sensors to enhance the results obtained from an INS. Experimental results have shown that, depending on the step frequency, the traveled distance error varies between 2.7% and 5.6%.