Optimization of the Topology of Electric Energy Distribution Networks by Using Algorithm Inspired on Ant Behaviors

An algorithm inspired on ant behavior is developed in order to find out the topology of an electric energy distribution network with minimum power loss. The algorithm performance is investigated in hypothetical and actual circuits. When applied in an actual distribution system of a region of the State of Sao Paulo (Brazil), the solution found by the algorithm presents loss lower than the topology built by the concessionary company.

Avoiding Divergence in the Shalvi-Weinstein Algorithm

The most popular algorithms for blind equalization are the constant-modulus algorithm (CMA) and the Shalvi-Weinstein algorithm (SWA). It is well-known that SWA presents a higher convergence rate than CMA. at the expense of higher computational complexity. If the forgetting factor is not sufficiently close to one, if the initialization is distant from the optimal solution, or if the signal-to-noise ratio is low, SWA can converge to undesirable local minima or even diverge. In this paper, we show that divergence can be caused by an inconsistency in the nonlinear estimate of the transmitted signal. or (when the algorithm is implemented in finite precision) by the loss of positiveness of the estimate of the autocorrelation matrix, or by a combination of both. In order to avoid the first cause of divergence, we propose a dual-mode SWA. In the first mode of operation. the new algorithm works as SWA; in the second mode, it rejects inconsistent estimates of the transmitted signal. Assuming the persistence of excitation condition, we present a deterministic stability analysis of the new algorithm. To avoid the second cause of divergence, we propose a dual-mode lattice SWA, which is stable even in finite-precision arithmetic, and has a computational complexity that increases linearly with the number of adjustable equalizer coefficients. The good performance of the proposed algorithms is confirmed through numerical simulations.

Jointly multi-user detection and channel estimation with genetic algorithm

This work aims at proposing the use of the evolutionary computation methodology in order to jointly solve the multiuser channel estimation (MuChE) and detection problems at its maximum-likelihood, both related to the direct sequence code division multiple access (DS/CDMA). The effectiveness of the proposed heuristic approach is proven by comparing performance and complexity merit figures with that obtained by traditional methods found in literature. Simulation results considering genetic algorithm (GA) applied to multipath, DS/CDMA and MuChE and multi-user detection (MuD) show that the proposed genetic algorithm multi-user channel estimation (GAMuChE) yields a normalized mean square error estimation (nMSE) inferior to 11%, under slowly varying multipath fading channels, large range of Doppler frequencies and medium system load, it exhibits lower complexity when compared to both maximum likelihood multi-user channel estimation (MLMuChE) and gradient descent method (GrdDsc). A near-optimum multi-user detector (MuD) based on the genetic algorithm (GAMuD), also proposed in this work, provides a significant reduction in the computational complexity when compared to the optimum multi-user detector (OMuD). In addition, the complexity of the GAMuChE and GAMuD algorithms were (jointly) analyzed in terms of number of operations necessary to reach the convergence, and compared to other jointly MuChE and MuD strategies. The joint GAMuChE-GAMuD scheme can be regarded as a promising alternative for implementing third-generation (3G) and fourth-generation (4G) wireless systems in the near future. Copyright (C) 2010 John Wiley & Sons, Ltd.

Hardware/firmware implementation of a soft sensor using an improved version of a fuzzy identification algorithm

This paper presents the design and implementation of an embedded soft sensor, i. e., a generic and autonomous hardware module, which can be applied to many complex plants, wherein a certain variable cannot be directly measured. It is implemented based on a fuzzy identification algorithm called ""Limited Rules"", employed to model continuous nonlinear processes. The fuzzy model has a Takagi-Sugeno-Kang structure and the premise parameters are defined based on the Fuzzy C-Means (FCM) clustering algorithm. The firmware contains the soft sensor and it runs online, estimating the target variable from other available variables. Tests have been performed using a simulated pH neutralization plant. The results of the embedded soft sensor have been considered satisfactory. A complete embedded inferential control system is also presented, including a soft sensor and a PID controller. (c) 2007, ISA. Published by Elsevier Ltd. All rights reserved.

The single machine earliness and tardiness scheduling problem: lower bounds and a branch-and-bound algorithm

This paper addresses the single machine scheduling problem with a common due date aiming to minimize earliness and tardiness penalties. Due to its complexity, most of the previous studies in the literature deal with this problem using heuristics and metaheuristics approaches. With the intention of contributing to the study of this problem, a branch-and-bound algorithm is proposed. Lower bounds and pruning rules that exploit properties of the problem are introduced. The proposed approach is examined through a computational comparative study with 280 problems involving different due date scenarios. In addition, the values of optimal solutions for small problems from a known benchmark are provided.

A split-pot experiment with sorghum to test a root water uptake partitioning model

Correct modeling of root water uptake partitioning over depth is an important issue in hydrological and crop growth models. Recently a physically based model to describe root water uptake was developed at single root scale and upscaled to the root system scale considering a homogeneous distribution of roots per soil layer. Root water uptake partitioning is calculated over soil layers or compartments as a function of respective soil hydraulic conditions, specifically the soil matric flux potential, root characteristics and a root system efficiency factor to compensate for within-layer root system heterogeneities. The performance of this model was tested in an experiment performed in two-compartment split-pot lysimeters with sorghum plants. The compartments were submitted to different irrigation cycles resulting in contrasting water contents over time. The root system efficiency factor was determined to be about 0.05. Release of water from roots to soil was predicted and observed on several occasions during the experiment; however, model predictions suggested root water release to occur more often and at a higher rate than observed. This may be due to not considering internal root system resistances, thus overestimating the ease with which roots can act as conductors of water. Excluding these erroneous predictions from the dataset, statistical indices show model performance to be of good quality.

Separation and partitioning of Green Fluorescent Protein from Escherichia coli homogenate in poly(ethylene glycol)/sodium-poly(acrylate) aqueous two-phase systems

The partitioning of Green Fluorescent Protein (GFP) in poly(ethylene glycol)/Na-poly(acrylate) aqueous two-phase systems (PEG/NaPA-ATPS) has been investigated. The aqueous two-phase systems are formed by mixing the polymers with a salt and a protein solution. The protein partitioning in the two-phase system was investigated at 25 degrees C. The concentration of the GFP was measured by fluorimetry. It was found that the partitioning of GFP depends on the salt type, pH and concentration of PEG. The data indicates that GFP partitions more strongly to the PEG phase in presence of Na2SO4 relative to NaCl. Furthermore, the GFP partitions more to the PEG phase at higher pH. The partition to the PEG phase is strongly favoured in systems with larger tie-line lengths (i.e. systems with higher polymer concentrations). The molecular weight of PEG is important since the partition coefficient (K) of GFP gradually decreases with increasing PEG size, from K ca. 300-400 for PEG 400 to K equal to 1.19 for PEG 8000. A separation process was developed where GFP was separated from a homogenate in two extraction steps: the GFP is first partitioned to the PEG phase in a PEG 3000/NaPA 8000 system containing 3 wt% Na2SO4, where the K value of GFP was 8. The GFP is then re-extracted to a salt phase formed by mixing the previous top-phase with a Na2SO4 solution. The K-value of GFP in this back-extraction was 0.22. The total recovery based on the start material was 74%. (c) 2008 Elsevier B.V. All rights reserved.

Protein partitioning in poly(ethylene glycol)/sodium polyacrylate aqueous two-phase systems

The partition of hemoglobin, lysozyme and glucose-6-phospate dehydrogenase (G6PDH) in a novel inexpensive aqueous two-phase system (ATPS) composed by poly(ethylene glycol) (PEG) and sodium polyacrylate (NaPA) has been studied. The effect of NaCl and Na2SO4, pH and PEG molecular size on the partitioning has been studied. At high pH (above 9), hemoglobin partitions strongly to the PEG-phase. Although some precipitation of hemoglobin occurs, high recovery values are obtained particularly for lysozyme and G6PDH. The partitioning forces are dominated by the hydrophobic and electrochemical (salt) effects, since the positively charged lysozyme and negatively charged G6PDH partitions to the non-charged PEG and the strongly negatively charged polyacrylate enriched phase, respectively. (c) 2007 Elsevier B.V. All rights reserved.

An improved seeded region growing algorithm

Recently Adams and Bischof (1994) proposed a novel region growing algorithm for segmenting intensity images. The inputs to the algorithm are the intensity image and a set of seeds - individual points or connected components - that identify the individual regions to be segmented. The algorithm grows these seed regions until all of the image pixels have been assimilated. Unfortunately the algorithm is inherently dependent on the order of pixel processing. This means, for example, that raster order processing and anti-raster order processing do not, in general, lead to the same tessellation. In this paper we propose an improved seeded region growing algorithm that retains the advantages of the Adams and Bischof algorithm fast execution, robust segmentation, and no tuning parameters - but is pixel order independent. (C) 1997 Elsevier Science B.V.

Data partitioning for parallel spatial join processing

The cost of spatial join processing can be very high because of the large sizes of spatial objects and the computation-intensive spatial operations. While parallel processing seems a natural solution to this problem, it is not clear how spatial data can be partitioned for this purpose. Various spatial data partitioning methods are examined in this paper. A framework combining the data-partitioning techniques used by most parallel join algorithms in relational databases and the filter-and-refine strategy for spatial operation processing is proposed for parallel spatial join processing. Object duplication caused by multi-assignment in spatial data partitioning can result in extra CPU cost as well as extra communication cost. We find that the key to overcome this problem is to preserve spatial locality in task decomposition. We show in this paper that a near-optimal speedup can be achieved for parallel spatial join processing using our new algorithms.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.

A consistent point-searching algorithm for solution interpolation in unstructured meshes consisting of 4-node bilinear quadrilateral elements

To translate and transfer solution data between two totally different meshes (i.e. mesh 1 and mesh 2), a consistent point-searching algorithm for solution interpolation in unstructured meshes consisting of 4-node bilinear quadrilateral elements is presented in this paper. The proposed algorithm has the following significant advantages: (1) The use of a point-searching strategy allows a point in one mesh to be accurately related to an element (containing this point) in another mesh. Thus, to translate/transfer the solution of any particular point from mesh 2 td mesh 1, only one element in mesh 2 needs to be inversely mapped. This certainly minimizes the number of elements, to which the inverse mapping is applied. In this regard, the present algorithm is very effective and efficient. (2) Analytical solutions to the local co ordinates of any point in a four-node quadrilateral element, which are derived in a rigorous mathematical manner in the context of this paper, make it possible to carry out an inverse mapping process very effectively and efficiently. (3) The use of consistent interpolation enables the interpolated solution to be compatible with an original solution and, therefore guarantees the interpolated solution of extremely high accuracy. After the mathematical formulations of the algorithm are presented, the algorithm is tested and validated through a challenging problem. The related results from the test problem have demonstrated the generality, accuracy, effectiveness, efficiency and robustness of the proposed consistent point-searching algorithm. Copyright (C) 1999 John Wiley & Sons, Ltd.

Trial-of-antibiotic algorithm for the diagnosis of tuberculosis in a district hospital in a developing country with high HIV prevalence

OBJECTIVE: To evaluate a diagnostic algorithm for pulmonary tuberculosis based on smear microscopy and objective response to trial of antibiotics. SETTING: Adult medical wards, Hlabisa Hospital, South Africa, 1996-1997. METHODS: Adults with chronic chest symptoms and abnormal chest X-ray had sputum examined for Ziehl-Neelsen stained acid-fast bacilli by light microscopy. Those with negative smears were treated with amoxycillin for 5 days and assessed. Those who had not improved were treated with erythromycin for 5 days and reassessed. Response was compared with mycobacterial culture. RESULTS: Of 280 suspects who completed the diagnostic pathway, 160 (57%) had a positive smear, 46 (17%) responded to amoxycillin, 34 (12%) responded to erythromycin and 40 (14%) were treated as smear-negative tuberculosis. The sensitivity (89%) and specificity (84%) of the full algorithm for culture-positive tuberculosis were high. However, 11 patients (positive predictive value [PPV] 95%) were incorrectly diagnosed with tuberculosis, and 24 cases of tuberculosis (negative predictive value [NPV] 70%) were not identified. NPV improved to 75% when anaemia was included as a predictor. Algorithm performance was independent of human immunodeficiency virus status. CONCLUSION: Sputum smear microscopy plus trial of antibiotic algorithm among a selected group of tuberculosis suspects may increase diagnostic accuracy in district hospitals in developing countries.

Partitioning of polycyclic aromatic hydrocarbons in the hair-air system

Partitioning behavior of PAHs including NAP, FLO, PHE, and PYR was investigated. A plot of experimental K-HA against log K-OW gives a good linear relationship. A somewhat similar slope and intercept it-as obtained for the hair-air system using PCB values from the literature. In comparison to K-VA values from the literature, lower values for K-VA were obtained. This may be attributed from differences in species and degradability across biota groups. K-HLA also exhibits good linear relationships with K-OA and other physical chemical properties such as W The lipid fraction has a strong influence on bioconcentration in hair from the air and water. However, hair treatments, hair length, growth dilution, photodegradation, biodegradation, temperature, seasonal variations, wet and dry depositions could alter the degree of bioconcentration of PAHs in the hair.

An equivalent algorithm for simulating thermal effects of magma intrusion problems in porous rocks

An equivalent algorithm is proposed to simulate thermal effects of the magma intrusion in geological systems, which are composed of porous rocks. Based on the physical and mathematical equivalence, the original magma solidification problem with a moving boundary between the rock and intruded magma is transformed into a new problem without the moving boundary but with a physically equivalent heat source. From the analysis of an ideal solidification model, the physically equivalent heat source has been determined in this paper. The major advantage in using the proposed equivalent algorithm is that the fixed finite element mesh with a variable integration time step can be employed to simulate the thermal effect of the intruded magma solidification using the conventional finite element method. The related numerical results have demonstrated the correctness and usefulness of the proposed equivalent algorithm for simulating the thermal effect of the intruded magma solidification in geological systems. (C) 2003 Elsevier B.V. All rights reserved.