Use of SVM Methods with Surface-Based Cortical and Volumetric Subcortical Measurements to Detect Alzheimer`s Disease

Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

Direct measurement of instantaneous source speed for a HDR brachytherapy unit using an optical fiber based detector

Purpose: Several attempts to determine the transit time of a high dose rate (HDR) brachytherapy unit have been reported in the literature with controversial results. The determination of the source speed is necessary to accurately calculate the transient dose in brachytherapy treatments. In these studies, only the average speed of the source was measured as a parameter for transit dose calculation, which does not account for the realistic movement of the source, and is therefore inaccurate for numerical simulations. The purpose of this work is to report the implementation and technical design of an optical fiber based detector to directly measure the instantaneous speed profile of a (192)Ir source in a Nucletron HDR brachytherapy unit. Methods: To accomplish this task, we have developed a setup that uses the Cerenkov light induced in optical fibers as a detection signal for the radiation source moving inside the HDR catheter. As the (192)Ir source travels between two optical fibers with known distance, the threshold of the induced signals are used to extract the transit time and thus the velocity. The high resolution of the detector enables the measurement of the transit time at short separation distance of the fibers, providing the instantaneous speed. Results: Accurate and high resolution speed profiles of the 192Ir radiation source traveling from the safe to the end of the catheter and between dwell positions are presented. The maximum and minimum velocities of the source were found to be 52.0 +/- 1.0 and 17.3 +/- 1:2 cm/s. The authors demonstrate that the radiation source follows a uniformly accelerated linear motion with acceleration of vertical bar a vertical bar = 113 cm/s(2). In addition, the authors compare the average speed measured using the optical fiber detector to those obtained in the literature, showing deviation up to 265%. Conclusions: To the best of the authors` knowledge, the authors directly measured for the first time the instantaneous speed profile of a radiation source in a HDR brachytherapy unit traveling from the unit safe to the end of the catheter and between interdwell distances. The method is feasible and accurate to implement on quality assurance tests and provides a unique database for efficient computational simulations of the transient dose. (C) 2010 American Association of Physicists in Medicine. [DOI: 10.1118/1.3483780]

Effects of bromazepam in frontal theta activity on the performance of a sensorimotor integration task: A quantitative electroencephalography study

Our objective is to verify the modulatory effects of bromazepam on EEG theta absolute power when subjects were submitted to a visuomotor task (i.e., car driver task). Sample was composed of 14 students (9 males and 5 females), right handed, with ages varying between 23 and 42 years (mean = 32.5 +/- 9.5), absence of mental or physical impairments, no psychoactive or psychotropic substance use and no neuromuscular disorders (screened by a clinical examination). The results showed an interaction between condition and electrodes (p=0.034) in favor of F8 electrode compared with F7 in both experimental conditions (t-test; p=0.001). Additionally, main effects were observed for condition (p=0.001), period (p=0.001) and electrodes (p=0.031) in favor of F4 electrode compared with F3. In conclusion, Br 6 mg of bromazepam may interfere in sensorimotor processes in the task performance in an unpredictable scenario allowing that certain visuospatial factors were predominant. Therefore, the results may reflect that bromazepam effects influence the performance of the involved areas because of the acquisition and integration of sensory stimuli processes until the development of a motor behavior based on the same stimuli. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Supporting content-based image retrieval and computer-aided diagnosis systems with association rule-based techniques

In this work, we take advantage of association rule mining to support two types of medical systems: the Content-based Image Retrieval (CBIR) systems and the Computer-Aided Diagnosis (CAD) systems. For content-based retrieval, association rules are employed to reduce the dimensionality of the feature vectors that represent the images and to improve the precision of the similarity queries. We refer to the association rule-based method to improve CBIR systems proposed here as Feature selection through Association Rules (FAR). To improve CAD systems, we propose the Image Diagnosis Enhancement through Association rules (IDEA) method. Association rules are employed to suggest a second opinion to the radiologist or a preliminary diagnosis of a new image. A second opinion automatically obtained can either accelerate the process of diagnosing or to strengthen a hypothesis, increasing the probability of a prescribed treatment be successful. Two new algorithms are proposed to support the IDEA method: to pre-process low-level features and to propose a preliminary diagnosis based on association rules. We performed several experiments to validate the proposed methods. The results indicate that association rules can be successfully applied to improve CBIR and CAD systems, empowering the arsenal of techniques to support medical image analysis in medical systems. (C) 2009 Elsevier B.V. All rights reserved.

Upper-mantle seismic anisotropy from SKS splitting in the South American stable platform: A test of asthenospheric flow models beneath the lithosphere

Upper-mantle seismic anisotropy has been extensively used to infer both present and past deformation processes at lithospheric and asthenospheric depths. Analysis of shear-wave splitting (mainly from core-refracted SKS phases) provides information regarding upper-mantle anisotropy. We present average measurements of fast-polarization directions at 21 new sites in poorly sampled regions of intra-plate South America, such as northern and northeastern Brazil. Despite sparse data coverage for the South American stable platform, consistent orientations are observed over hundreds of kilometers. Over most of the continent, the fast-polarization direction tends to be close to the absolute plate motion direction given by the hotspot reference model HS3-NUVEL-1A. A previous global comparison of the SKS fast-polarization directions with flow models of the upper mantle showed relatively poor correlation on the continents, which was interpreted as evidence for a large contribution of ""frozen"" anisotropy in the lithosphere. For the South American plate, our data indicate that one of the reasons for the poor correlation may have been the relatively coarse model of lithospheric thicknesses. We suggest that improved models of upper-mantle flow that are based on more detailed lithospheric thicknesses in South America may help to explain most of the observed anisotropy patterns.

Generic relationships and dating of lineages in Winteraceae based on nuclear (ITS) and plastid (rpS16 and psbA-trnH) sequence data

Phylogenetic analyses of representative species from the five genera of Winteraceae (Drimys, Pseudowintera, Takhtajania, Tasmannia, and Zygogynum s.l.) were performed using ITS nuclear sequences and a combined data-set of ITS + psbA-trnH + rpS16 sequences (sampling of 30 and 15 species, respectively). Indel informativity using simple gap coding or gaps as a fifth character was examined in both data-sets. Parsimony and Bayesian analyses support the monophyly of Drimys, Tasmannia, and Zygogynum s.l., but do not support the monophyly of Belliolum, Zygogynum s.s., and Bubbia. Within Drimys, the combined data-set recovers two subclades. Divergence time estimates suggest that the splitting between Drimys and its sister clade (Pseudowintera + Zygogynum s.l.) occurred around the end of the Cretaceous; in contrast, the divergence between the two subclades within Drimys is more recent (15.5-18.5 MY) and coincides in time with the Andean uplift. Estimates suggest that the earliest divergences within Winteraceae could have predated the first events of Gondwana fragmentation. (C) 2009 Elsevier Inc. All rights reserved.

Partitions selection strategy for set of clustering solutions

Clustering is a difficult task: there is no single cluster definition and the data can have more than one underlying structure. Pareto-based multi-objective genetic algorithms (e.g., MOCK Multi-Objective Clustering with automatic K-determination and MOCLE-Multi-Objective Clustering Ensemble) were proposed to tackle these problems. However, the output of such algorithms can often contains a high number of partitions, becoming difficult for an expert to manually analyze all of them. In order to deal with this problem, we present two selection strategies, which are based on the corrected Rand, to choose a subset of solutions. To test them, they are applied to the set of solutions produced by MOCK and MOCLE in the context of several datasets. The study was also extended to select a reduced set of partitions from the initial population of MOCLE. These analysis show that both versions of selection strategy proposed are very effective. They can significantly reduce the number of solutions and, at the same time, keep the quality and the diversity of the partitions in the original set of solutions. (C) 2010 Elsevier B.V. All rights reserved.

Investigation of a new GRASP-based clustering algorithm applied to biological data

A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

Alignment-based extraction of multiword expressions

Due to idiosyncrasies in their syntax, semantics or frequency, Multiword Expressions (MWEs) have received special attention from the NLP community, as the methods and techniques developed for the treatment of simplex words are not necessarily suitable for them. This is certainly the case for the automatic acquisition of MWEs from corpora. A lot of effort has been directed to the task of automatically identifying them, with considerable success. In this paper, we propose an approach for the identification of MWEs in a multilingual context, as a by-product of a word alignment process, that not only deals with the identification of possible MWE candidates, but also associates some multiword expressions with semantics. The results obtained indicate the feasibility and low costs in terms of tools and resources demanded by this approach, which could, for example, facilitate and speed up lexicographic work.

Towards improving cluster-based feature selection with a simplified silhouette filter

This paper proposes a filter-based algorithm for feature selection. The filter is based on the partitioning of the set of features into clusters. The number of clusters, and consequently the cardinality of the subset of selected features, is automatically estimated from data. The computational complexity of the proposed algorithm is also investigated. A variant of this filter that considers feature-class correlations is also proposed for classification problems. Empirical results involving ten datasets illustrate the performance of the developed algorithm, which in general has obtained competitive results in terms of classification accuracy when compared to state of the art algorithms that find clusters of features. We show that, if computational efficiency is an important issue, then the proposed filter May be preferred over their counterparts, thus becoming eligible to join a pool of feature selection algorithms to be used in practice. As an additional contribution of this work, a theoretical framework is used to formally analyze some properties of feature selection methods that rely on finding clusters of features. (C) 2011 Elsevier Inc. All rights reserved.

A hybrid case adaptation approach for case-based reasoning

Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.

Template-based quadrilateral meshing

Generating quadrilateral meshes is a highly non-trivial task, as design decisions are frequently driven by specific application demands. Automatic techniques can optimize objective quality metrics, such as mesh regularity, orthogonality, alignment and adaptivity; however, they cannot make subjective design decisions. There are a few quad meshing approaches that offer some mechanisms to include the user in the mesh generation process; however, these techniques either require a large amount of user interaction or do not provide necessary or easy to use inputs. Here, we propose a template-based approach for generating quad-only meshes from triangle surfaces. Our approach offers a flexible mechanism to allow external input, through the definition of alignment features that are respected during the mesh generation process. While allowing user inputs to support subjective design decisions, our approach also takes into account objective quality metrics to produce semi-regular, quad-only meshes that align well to desired surface features. Published by Elsevier Ltd.

Infeasibility handling in genetic algorithm using nested domains for production planning

In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.

Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms

J.A. Ferreira Neto, E.C. Santos Junior, U. Fra Paleo, D. Miranda Barros, and M.C.O. Moreira. 2011. Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms. Cien. Inv. Agr. 38(2): 169-178. The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productivity index. The sequence of tests in the study was carried out in two areas with eight different agricultural aptitude classes, including one area of 391.88 ha subdivided into 12 lots and another of 404.1763 ha subdivided into 14 lots. The effectiveness of the method was measured using the shunting line standard value of a parceled area lot`s productivity index. To evaluate each parameter, a sequence of 15 calculations was performed to record the best individual fitness average (MMI) found for each parameter variation. The best parameter combination found in testing and used to generate the new parceling with the GA was the following: 320 as the generation number, a population of 40 individuals, 0.8 mutation tax, and a 0.3 renewal tax. The solution generated rather homogeneous lots in terms of productive capacity.

Entropy-Based Approach to Analyze and Classify Mineral Aggregates

This paper presents an automatic method to detect and classify weathered aggregates by assessing changes of colors and textures. The method allows the extraction of aggregate features from images and the automatic classification of them based on surface characteristics. The concept of entropy is used to extract features from digital images. An analysis of the use of this concept is presented and two classification approaches, based on neural networks architectures, are proposed. The classification performance of the proposed approaches is compared to the results obtained by other algorithms (commonly considered for classification purposes). The obtained results confirm that the presented method strongly supports the detection of weathered aggregates.