Taufik Abrão

Cadmium mobility in sediments and soils from a coal mining area on Tibagi River watershed: environmental risk assessment.

The risk of cadmium contamination in the Tibagi River watershed (Parana State, Brazil) affected by past coal mining activities was assessed through sorption-desorption modeling for sediment and soil samples. The acidic character of the samples resulted in more competition between the cadmium ions and protons, thereby influencing the cadmium sorption-desorption. The sorption isotherms were fitted to the Langmuir and Freundlich single models and to the dual-site Langmuir-Freundlich (or Sips) model. The single-site models indicated a low-energy character of sorption sites on the sample sorption sites, whereas the dual-site model explained the availability of higher-affinity and lower-affinity non-specific sites. The correlation of the sorption and desorption constants with the physicochemical and mineralogical characteristics of the samples showed that the cadmium sorption behavior was significantly affected by the pH, point of zero charge, and also by the magnesium, aluminum, calcium and manganese amounts. Besides, the desorption rate and hysteresis index suggested a high risk of cadmium mobilization along the Tibagi River basin.

Particle Swarm and Quantum Particle Swarm Optimization Applied to DS/CDMA Multiuser Detection in Flat Rayleigh Channels

The particle swarm and quantum particle swarm optimization (PSO and QPSO) techniques applied to direct sequence/code division multiple access systems (DS/CDMA) with multiuser detection (MuD) are analyzed, evaluated and compared. The swarm techniques efficiency when applied to the DS-CDMA MuD (PSO-MuD and QPSO-MuD) in flat Rayleigh channels is compared through the trade-off between performance and computational complexity. With the same simulation scenario, the comparison is accomplished among the PSO-MuD, QPSO-MuD, genetic algorithm (GA) and evolutionary programming with cloning (EP-C) algorithms. The complexity of these four heuristics-MuD (heur-MuD) is compared, expressing it through the number of computational operations necessary in order to reach the performance obtained through the maximum likelihood detector (ML)

The effects of power control on the optical CDMA random access protocol

Abstract In this work, the performance of the hybrid system that combines the distributed power control algorithm (DPCA) with the random access protocol as a novel and simple scheme of achieving a high performance in decentralized optical code division multiple access (OCDMA) networks has been investigated. The multiple access interference (MAI) and the near–far problem effects have been considered. The DPCA’s advantage lies in its characteristics being effectively implemented to each node, since only local parameters are necessary. The principal results have shown that the network throughput and delay are strongly affected by the near–far problem and the DPCA works to solve this problem. Hence, the introduction of a certain level of the power control to the random access temporally coded (1D) or the time-wavelength coded (2D) OCDMA networks has demonstrated profitability of the throughput increase and the delay reduction. As a consequence, the proposed system configuration with the DPCA using a very low number of iterations has resulted in a better throughput and simultaneously in a delay decrease when compared to the system without power control mechanisms.

Fourier and wavelet spectral analysis of EMG signals in supramaximal constant load dynamic exercise

Frequency domain analyses of changes in electromyographic (EMG) signals over time are frequently used to assess muscle fatigue. Fourier based approaches are typically used in these analyses, yet Fourier analysis assumes signal stationarity, which is unlikely during dynamic contractions. Wavelet based methods of signal analysis do not assume stationarity and may be more appropriate for joint time-frequency domain analysis. The purpose of this study was to compare Short-Time Fourier Transform (STFT) and Continuous Wavelet Transform (CWT) in assessing muscle fatigue in maximal constant load dynamic exercise (100% Wmax). The results of this study indicate that CWT and STFT analyses give similar fatigue estimates (slope of median frequency) in maximal constant load dynamic exercise (P>0.05). However, the results of the variance was significantly lower for at least one of the muscles studied in CWT compared to STFT (P<0.05) indicating more variability in the EMG signal analysis using STFT. Thus, the stationarity assumption may not be the sole factor responsible for affecting the Fourier based estimates.

Energy-efficient power allocation for WDM/OCDM networks with particle swarm optimization

In this paper, an optical network optimization based on particle swarm intelligence is described. The particle swarm optimization (PSO) algorithm is evocated in order to solve the problem of resource allocation (RA) based on the signal-to-noise plus interference ratio optimization in a hybrid wavelength division multiplexing/optical code division multiplexing network with quality-of-service restrictions. The RA optimization based on the PSO strategy allows the regulation of the transmitted power in order to maximize the energy efficiency. For the network optimization context, a system model is described, figures of merit are presented, and a suitable model for the heuristic optimization approach is developed, with emphasis on the optimization of input parameters and network performance. Afterward, extensive numerical results for both optimization problems are discussed, taking into account realistic network operation scenarios.

Ant colony input parameters optimization for multiuser detection in DS/CDMA systems

In this work a simple and efficient methodology for tuning the input parameters applied to the ant colony optimi- zation multiuser detection (ACO-MUD) in direct sequence code division multiple access (DS-CDMA) is proposed. The motivation in using a heuristic approach is due to the nature of the NP complexity posed by the wireless multiuser detection optimization problem. The challenge is to obtain suitable data detection performance in solving the associated hard complexity problem in a polynomial time. Previous results indicated that the application of heuristic search algorithm in several wireless optimization problems have been achieved excellent performance-complexity tradeoffs. Regarding different system operation and channels scenarios, a complete input parameters optimization procedure for the ACO-MUD is provided herein, which represents the major contribution of this work. Furthermore, the performance of the PSO-MUD is analyzed via Monte-Carlo simulations. Simulation results show that, after convergence, the performance reached by the ACO-MUD is much better than the conventional detector, and somewhat close to the single user bound (SuB). Rayleigh flat channel is initially considered, but the results is straightforward extended to selective fading channels, as well as diversity (time and spatial) wireless channels.

S/MIMO MC-CDMA Heuristic Multiuser Detectors Based on Single-Objective Optimization

This paper analyzes the complexity-performance trade-off of several heuristic near-optimum multiuser detection (MuD) approaches applied to the uplink of synchronous single/multiple-input multiple-output multicarrier code division multiple access (S/MIMO MC-CDMA) systems. Genetic algorithm (GA), short term tabu search (STTS) and reactive tabu search (RTS), simulated annealing (SA), particle swarm optimization (PSO), and 1-opt local search (1-LS) heuristic multiuser detection algorithms (Heur-MuDs) are analyzed in details, using a single-objective antenna-diversity-aided optimization approach. Monte- Carlo simulations show that, after convergence, the performances reached by all near-optimum Heur-MuDs are similar. However, the computational complexities may differ substantially, depending on the system operation conditions. Their complexities are carefully analyzed in order to obtain a general complexity-performance framework comparison and to show that unitary Hamming distance search MuD (uH-ds) approaches (1-LS, SA, RTS and STTS) reach the best convergence rates, and among them, the 1-LS-MuD provides the best trade-off between implementation complexity and bit error rate (BER) performance.

Hybrid heuristic-waterfilling game theory approach in MC-CDMA resource allocation

Abstract: This paper discusses the power allocation with fixed rate constraint problem in multi-carrier code division multiple access (MC-CDMA) networks, that has been solved through game theoretic perspective by the use of an iterative water-filling algorithm (IWFA). The problem is analyzed under various interference density configurations, and its reliability is studied in terms of solution existence and uniqueness. Moreover, numerical results reveal the approach shortcoming, thus a new method combining swarm intelligence and IWFA is proposed to make practicable the use of game theoretic approaches in realistic MC-CDMA systems scenarios. The contribution of this paper is twofold: (i) provide a complete analysis for the existence and uniqueness of the game solution, from simple to more realist and complex interference scenarios; (ii) propose a hybrid power allocation optimization method combining swarm intelligence, game theory and IWFA. To corroborate the effectiveness of the proposed method, an outage probability analysis in realistic interference scenarios, and a complexity comparison with the classical IWFA are presented.

Evolutionary programming with cloning and adaptive cost function applied to multi-user DS-CDMA systems

A new utilization form for the evolutionary programming (EP) algorithm applied to multi-user DS-CDMA (direct sequence code division multiple access) systems in a synchronous AWGN (additive white Gaussian noise) channel is proposed. In order to find the maximum likelihood (ML) solution, the variance matrix for the generation of new candidates was expressed as a function of the following parameters: E/sub b//N/sub 0/; near-far ratio (NFR); cost function (fitness value). A cloning strategy procedure was introduced where the best vectors with the bit-candidates were cloned, reducing drastically the required time for the algorithm convergence to the single user bound (SuB) performance. An improvement in the convergence process was obtained using a parallel interference canceller with soft decision (SD-PIC) for initial vector generation.

Anomaly detection using DSNS and Firefly Harmonic Clustering Algorithm

The networks are becoming an essential part of society life and anomalies may represent a loss in network performance. Modeling the traffic behavior pattern is possible to predict the behavior expected and characterize an anomaly. We proposed a hybrid clustering algorithm, Firefly Harmonic Clustering Algorithm (FHCA), for network volume anomaly detection by the combined forces of the algorithms K-Harmonic means (KHM) and Firefly Algorithm (FA). Processing the Digital Signature of Network Segment (DSNS) data and real traffic data, it is possible to detect and point intervals considered anomalous with a trade-off between the 80% true-positive rate and 20% false-positive rate.