930 resultados para Pattern classification
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In this work we focus on pattern recognition methods related to EMG upper-limb prosthetic control. After giving a detailed review of the most widely used classification methods, we propose a new classification approach. It comes as a result of comparison in the Fourier analysis between able-bodied and trans-radial amputee subjects. We thus suggest a different classification method which considers each surface electrodes contribute separately, together with five time domain features, obtaining an average classification accuracy equals to 75% on a sample of trans-radial amputees. We propose an automatic feature selection procedure as a minimization problem in order to improve the method and its robustness.
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Nowadays, World Heritage Sites (WHS) have been facing new challenges, partially due to a different tourism consumption patterns. As it is highlighted in a considerable amount of studies, visits to these sites are almost justified by this prestigious classification and motivations are closely associated with their cultural aspects and quality of the overall environment (among others, Marujo et al, 2012). However, a diversity of tourists’ profiles have been underlined in the literature. Starting from the results obtained in a previous study about cultural tourists’ profile, conducted during the year 2009 in the city of Évora, Portugal, it is our intend to compare the results with a recent survey applied to the visitors of the same city. Recognition of Évora by UNESCO in 1986 as “World Heritage” has fostered not only the preservation of heritage but also the tourist promotion of the town. This study compares and examined tourists’ profile, regarding from the tourists’ expenditure patterns in Évora. A total of 450 surveys were distributed in 2009, and recently, in 2015, the same numbers of surveys were collected. Chi-squared Automatic Interaction Detection (CHAID) was applied to model consumer patterns of domestic and international visitors, based on socio demographic, trip characteristics, length of stay and the degree of satisfaction of pull factors. CHAID allowed find a population classification in groups that able to describe the dependent variable, average daily tourist expenditure. Results revealed different patterns of daily average expenditure amongst the years, 2009 and 2015, even if primarily results not revealed significant variations in socio-demographic and trip characteristics among the visitors’ core profile. Local authorities should be aware of this changing expensive behavior of cultural visitors and should formulate strategies accordingly. Policy and managerial recommendations are discussed.
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In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD) and Latent Semantic Indexing (LSI) techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in.
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Hand gesture recognition based on surface electromyography (sEMG) signals is a promising approach for the development of intuitive human-machine interfaces (HMIs) in domains such as robotics and prosthetics. The sEMG signal arises from the muscles' electrical activity, and can thus be used to recognize hand gestures. The decoding from sEMG signals to actual control signals is non-trivial; typically, control systems map sEMG patterns into a set of gestures using machine learning, failing to incorporate any physiological insight. This master thesis aims at developing a bio-inspired hand gesture recognition system based on neuromuscular spike extraction rather than on simple pattern recognition. The system relies on a decomposition algorithm based on independent component analysis (ICA) that decomposes the sEMG signal into its constituent motor unit spike trains, which are then forwarded to a machine learning classifier. Since ICA does not guarantee a consistent motor unit ordering across different sessions, 3 approaches are proposed: 2 ordering criteria based on firing rate and negative entropy, and a re-calibration approach that allows the decomposition model to retain information about previous sessions. Using a multilayer perceptron (MLP), the latter approach results in an accuracy up to 99.4% in a 1-subject, 1-degree of freedom scenario. Afterwards, the decomposition and classification pipeline for inference is parallelized and profiled on the PULP platform, achieving a latency < 50 ms and an energy consumption < 1 mJ. Both the classification models tested (a support vector machine and a lightweight MLP) yielded an accuracy > 92% in a 1-subject, 5-classes (4 gestures and rest) scenario. These results prove that the proposed system is suitable for real-time execution on embedded platforms and also capable of matching the accuracy of state-of-the-art approaches, while also giving some physiological insight on the neuromuscular spikes underlying the sEMG.
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Hippocampal sclerosis (HS) is considered the most frequent neuropathological finding in patients with mesial temporal lobe epilepsy (MTLE). Hippocampal specimens of pharmacoresistant MTLE patients that underwent epilepsy surgery for seizure control reveal the characteristic pattern of segmental neuronal cell loss and concomitant astrogliosis. However, classification issues of hippocampal lesion patterns have been a matter of intense debate. International consensus classification has only recently provided significant progress for comparisons of neurosurgical and clinic-pathological series between different centers. The respective four-tiered classification system of the International League Against Epilepsy subdivides HS into three types and includes a term of gliosis only, no-HS. Future studies will be necessary to investigate whether each of these subtypes of HS may be related to different etiological factors or with postoperative memory and seizure outcome. Molecular studies have provided potential deeper insights into the pathogenesis of HS and MTLE on the basis of epilepsy-surgical hippocampal specimens and corresponding animal models. These include channelopathies, activation of NMDA receptors, and other conditions related to Ca(2+) influx into neurons, the imbalance of Ca(2+)-binding proteins, acquired channelopathies that increase neuronal excitability, paraneoplastic and non-paraneoplastic inflammatory events, and epigenetic regulation promoting or facilitating hippocampal epileptogenesis. Genetic predisposition for HS is clearly suggested by the high incidence of family history in patients with HS, and by familial MTLE with HS. So far, it is clear that HS is multifactorial and there is no individual pathogenic factor either necessary or sufficient to generate this intriguing histopathological condition. The obvious variety of pathogenetic combinations underlying HS may explain the multitude of clinical presentations, different responses to clinical and surgical treatment. We believe that the stratification of neuropathological patterns can help to characterize specific clinic-pathological entities and predict the postsurgical seizure control in an improved fashion.
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Ochnaceae s.str. (Malpighiales) are a pantropical family of about 500 species and 27 genera of almost exclusively woody plants. Infrafamilial classification and relationships have been controversial partially due to the lack of a robust phylogenetic framework. Including all genera except Indosinia and Perissocarpa and DNA sequence data for five DNA regions (ITS, matK, ndhF, rbcL, trnL-F), we provide for the first time a nearly complete molecular phylogenetic analysis of Ochnaceae s.l. resolving most of the phylogenetic backbone of the family. Based on this, we present a new classification of Ochnaceae s.l., with Medusagynoideae and Quiinoideae included as subfamilies and the former subfamilies Ochnoideae and Sauvagesioideae recognized at the rank of tribe. Our data support a monophyletic Ochneae, but Sauvagesieae in the traditional circumscription is paraphyletic because Testulea emerges as sister to the rest of Ochnoideae, and the next clade shows Luxemburgia+Philacra as sister group to the remaining Ochnoideae. To avoid paraphyly, we classify Luxemburgieae and Testuleeae as new tribes. The African genus Lophira, which has switched between subfamilies (here tribes) in past classifications, emerges as sister to all other Ochneae. Thus, endosperm-free seeds and ovules with partly to completely united integuments (resulting in an apparently single integument) are characters that unite all members of that tribe. The relationships within its largest clade, Ochnineae (former Ochneae), are poorly resolved, but former Ochninae (Brackenridgea, Ochna) are polyphyletic. Within Sauvagesieae, the genus Sauvagesia in its broad circumscription is polyphyletic as Sauvagesia serrata is sister to a clade of Adenarake, Sauvagesia spp., and three other genera. Within Quiinoideae, in contrast to former phylogenetic hypotheses, Lacunaria and Touroulia form a clade that is sister to Quiina. Bayesian ancestral state reconstructions showed that zygomorphic flowers with adaptations to buzz-pollination (poricidal anthers), a syncarpous gynoecium (a near-apocarpous gynoecium evolved independently in Quiinoideae and Ochninae), numerous ovules, septicidal capsules, and winged seeds with endosperm are the ancestral condition in Ochnoideae. Although in some lineages poricidal anthers were lost secondarily, the evolution of poricidal superstructures secured the maintenance of buzz-pollination in some of these genera, indicating a strong selective pressure on keeping that specialized pollination system.
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Diabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semi-soft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2 ± 2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors.
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Despite the remarkable improvements in breast cancer (BC) characterization, accurate prediction of BC clinical behavior is often still difficult to achieve. Some studies have investigated the association between the molecular subtype, namely the basal-like BC and the pattern of relapse, however only few investigated the association between relapse pattern and immunohistochemical defined triple-negative breast cancers (TNBCs). The aim of this study was to evaluate the pattern of relapse in patients with TNBC, namely the primary distant relapse site. One-hundred twenty nine (129) invasive breast carcinomas with follow-up information were classified according to the molecular subtype using immunohistochemistry for ER, PgR and Her2. The association between TNBC and distant relapse primary site was analyzed by logistic regression. Using multivariate logistic regression analysis patients with TNBC displayed only 0.09 (95% CI: 0.00-0.74; p=0.02) the odds of the non-TNBC patients of developing bone primary relapse. Regarding visceral and lymph-node relapse, no differences between in this cohort were found. Though classically regarded as aggressive tumors, TNBCs rarely development primary relapse in bone when compared to non-TNBC, a clinical relevant fact when investigating a metastasis of an occult or non-sampled primary BC.
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The aim of this cephalometric study was to evaluate the influence of the sagittal skeletal pattern on the 'Y-axis of growth' measurement in patients with different malocclusions. Lateral head films from 59 patients (mean age 16y 7m, ranging from 11 to 25 years) were selected after a subjective analysis of 1630 cases. Sample was grouped as follows: Group 1 - class I facial pattern; group 2 - class II facial pattern; and Group 3 - class III facial pattern. Two angular measurements, SNGoGn and SNGn, were taken in order to determine skeletal vertical facial pattern. A logistic regression with errors distributed according to a binomial distribution was used to test the influence of the sagittal relationship (Class I, II, III facial patterns) on vertical diagnostic measurement congruence (SNGoGn and SNGn). RESULTS show that the probability of congruence between the patterns SNGn and SNGoGn was relatively high (70%) for group 1, but for groups II (46%) and III (37%) this congruence was relatively low. The use of SNGn appears to be inappropriate to determine the vertical facial skeletal pattern of patients, due to Gn point shifting throughout sagittal discrepancies. Clinical Significance: Facial pattern determined by SNGn must be considered carefully, especially when severe sagittal discrepancies are present.
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Chronic telogen effluvium (CTE), a poorly understood condition, can be confused with or may be a prodrome to female pattern hair loss (FPHL). The pathogenesis of both is related to follicle cycle shortening and possibly to blood supply changes. To analyze a number of histomorphometric and immunohistochemical findings through vascular endothelial growth factor (VEGF), Ki-67, and CD31 immunostaining in scalp biopsies of 20 patients with CTE, 17 patients with mild FPHL and 9 controls. Ki-67 index and VEGF optical density were analyzed at the follicular outer sheath using ImageJ software. CD31 microvessel density was assessed by a Chalkley grid. Significant follicle miniaturization and higher density of nonanagen follicles were found in FPHL, compared with patients with CTE and controls. Ki-67+ index correlated positively with FPHL histological features. The FPHL group showed the highest VEGF optical density, followed by the CTE and control groups. No differences were found in CD31 microvessel density between the three groups. Histomorphometric results establish CTE as a distinct disorder, separate from FPHL from its outset. Its pathogenic mechanisms are also distinct. These findings support the proposed mechanism of 'immediate telogen release' for CTE, leading to cycle synchronization. For FPHL, accelerated anagen follicular mitotic rates and, thus, higher Ki-67 and VEGF values, would leave less time for differentiation, resulting in hair miniaturization.
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The Subaxial Injury Classification (SLIC) system and severity score has been developed to help surgeons in the decision-making process of treatment of subaxial cervical spine injuries. A detailed description of all potential scored injures of the SLIC is lacking. We performed a systematic review in the PubMed database from 2007 to 2014 to describe the relationship between the scored injuries in the SLIC and their eventual treatment according to the system score. Patients with an SLIC of 1-3 points (conservative treatment) are neurologically intact with the spinous process, laminar or small facet fractures. Patients with compression and burst fractures who are neurologically intact are also treated nonsurgically. Patients with an SLIC of 4 points may have an incomplete spinal cord injury such as a central cord syndrome, compression injuries with incomplete neurologic deficits and burst fractures with complete neurologic deficits. SLIC of 5-10 points includes distraction and rotational injuries, traumatic disc herniation in the setting of a neurological deficit and burst fractures with an incomplete neurologic deficit. The SLIC injury severity score can help surgeons guide fracture treatment. Knowledge of the potential scored injures and their relationships with the SLIC are of paramount importance for spine surgeons who treated subaxial cervical spine injuries.
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to assess the construct validity and reliability of the Pediatric Patient Classification Instrument. correlation study developed at a teaching hospital. The classification involved 227 patients, using the pediatric patient classification instrument. The construct validity was assessed through the factor analysis approach and reliability through internal consistency. the Exploratory Factor Analysis identified three constructs with 67.5% of variance explanation and, in the reliability assessment, the following Cronbach's alpha coefficients were found: 0.92 for the instrument as a whole; 0.88 for the Patient domain; 0.81 for the Family domain; 0.44 for the Therapeutic procedures domain. the instrument evidenced its construct validity and reliability, and these analyses indicate the feasibility of the instrument. The validation of the Pediatric Patient Classification Instrument still represents a challenge, due to its relevance for a closer look at pediatric nursing care and management. Further research should be considered to explore its dimensionality and content validity.
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Frankfurters are widely consumed all over the world, and the production requires a wide range of meat and non-meat ingredients. Due to these characteristics, frankfurters are products that can be easily adulterated with lower value meats, and the presence of undeclared species. Adulterations are often still difficult to detect, due the fact that the adulterant components are usually very similar to the authentic product. In this work, FT-Raman spectroscopy was employed as a rapid technique for assessing the quality of frankfurters. Based on information provided by the Raman spectra, a multivariate classification model was developed to identify the frankfurter type. The aim was to study three types of frankfurters (chicken, turkey and mixed meat) according to their Raman spectra, based on the fatty vibrational bands. Classification model was built using partial least square discriminant analysis (PLS-DA) and the performance model was evaluated in terms of sensitivity, specificity, accuracy, efficiency and Matthews's correlation coefficient. The PLS-DA models give sensitivity and specificity values on the test set in the ranges of 88%-100%, showing good performance of the classification models. The work shows the Raman spectroscopy with chemometric tools can be used as an analytical tool in quality control of frankfurters.
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To compare the distributions of patients with clinical-pathological subtypes of luminal B-like breast cancer according to the 2011 and 2013 St. Gallen International Breast Cancer Conference Expert Panel. We studied 142 women with breast cancer who were positive to estrogen receptor and had been treated in São Paulo state, southeast Brazil. The expression of the following receptors was assessed by immunohistochemistry: estrogen, progesterone (PR) and Ki-67. The expression of HER-2 was measured by fluorescent in situ hybridization analysis in tissue microarray. There were 29 cases of luminal A breast cancers according to the 2011 St. Gallen International Breast Cancer Conference Expert Panel that were classified as luminal B-like in the 2013 version. Among the 65 luminal B-like breast cancer cases, 29 (45%) were previous luminal A tumors, 15 cases (20%) had a Ki-67 >14% and were at least 20% PR positive and 21 cases (35%) had Ki-67 >14% and more than 20% were PR positive. The 2013 St. Gallen consensus updated the definition of intrinsic molecular subtypes and increased the number of patients classified as having luminal B-like breast cancer in our series, for whom the use of cytotoxic drugs will probably be proposed with additional treatment cost.