WorldWideScience

Sample records for primarily paleotopographic features

  1. Model identification and control of development of deeply buried paleokarst reservoir in the central Tarim Basin, northwest China

    Science.gov (United States)

    Yu, Jingbo; Li, Zhong; Yang, Liu; Han, Yinxue

    2018-04-01

    The paleokarst reservoirs of the Ordovician Yingshan formation, rich in oil and gas, are deeply buried in the central Tarim Basin, northwest China. Dozens of imaging well-logs in this region reveal five typical paleokarst features, including solution vugs, solution-enlarged fractures, filled caves, unfilled caves and collapsed caves, as well as two typical paleokarst structures located in different paleotopographic sites, including paleokarst vadose and phreatic zones. For seismic data, the large wave impedance contrast between the paleocave system and the surrounding rocks leads to a strong seismic reflection, which is highlighted as a bead-like ‘bright spot’ in a seismic section. By quantitatively estimating the seismic resolution limits of deep seismic reflections, a single paleocave cannot be identified from a seismic profile, and the bead-like reflection represents an entire paleocave complex. The spectral decomposition technique was employed to depict the planar shape and semi-quantitatively measure the size of the paleocave complexes. The results indicate that the sizes of the paleokarst caves are all small, and most of the karst caves are nearly completely filled by clay and calcite. The small cave size and the effective support of cave fills for the overlying strata mean that some individual paleocaves in a paleocave complex are preserved at a burial depth of more than 6000 m. Paleotopography and faults strongly impact the distribution of paleokarst reservoirs. Well-developed paleokarst reservoirs are generally located in paleotopographic highlands and on slopes, and for a specific paleotopographic site, the distribution of paleokarst reservoirs is obviously controlled by NW-SE trending faults. The most favorable area for paleokarst development is the Tazhong No. 10 fault zone, a faulted anticline bounded by two NW-SE trending back thrusts.

  2. Feature Binding in Zebrafish

    Directory of Open Access Journals (Sweden)

    P Neri

    2012-07-01

    Full Text Available Binding operations are primarily ascribed to cortex or similarly complex avian structures. My experiments show that the zebrafish, a lower vertebrate lacking cortex, supports visual feature binding of form and motion for the purpose of social behavior. These results challenge the notion that feature binding may require highly evolved neural structures and demonstrate that the nervous system of lower vertebrates can afford unexpectedly complex computations.

  3. Mio-Pliocene to Pleistocene paleotopographic evolution of Brittany (France) from a sequence stratigraphic analysis: relative influence of tectonics and climate

    Science.gov (United States)

    Brault, N.; Bourquin, S.; Guillocheau, F.; Dabard, M.-P.; Bonnet, S.; Courville, P.; Estéoule-Choux, J.; Stepanoff, F.

    2004-01-01

    this study, five paleogeographic maps were drawn up also indicating paleocurrent directions: three maps for the lower cycle (Tortonian retrogradational trend, Late Tortonian to Early Messinian maximum flooding surface and Messinian progradational trend) and two for the upper cycle (Pliocene retrogradational trend and Piacenzian maximum flooding surface). These maps show (1) the variations of paleocurrent directions during the Mio-Pliocene, (2) the extent of estuarine environments during the maximum flooding intervals and (3) a paleodrainage watershed oriented NNW-SSE following the regional Quessoy/Nort-sur-Erdre Fault during the retrogradational trend of the upper cycle and possibly during the progradational trend of the lower cycle. The present-day morphology of the Armorican Massif is characterized by (1) incised valleys and jagged topography, in contrast with the "smooth" morphology described for Mio-Pliocene times and (2) a main East-West drainage watershed, located to the north, separating rivers flowing towards the English Channel from rivers flowing towards the Atlantic Ocean. The Mio-Pliocene/Pleistocene paleotopographic changes seem to be controlled by climatic effects. These can be related to the change in runoff associated with warmer and wetter conditions during the Mio-Pliocene, which control the river discharge and lead to the development of extensive fluvial sheetflood deposits. Tectonic or eustatic factors exert a second-order control.

  4. Addressing scalability while feature requests persist. A look at NASA Worldview's new features and their implementation.

    Science.gov (United States)

    King, B. A.

    2017-12-01

    Worldview is a high-traffic web mapping application created using the JavaScript mapping library, OpenLayers. This presentation will primarily focus on three new features: A wrapping component that seamlessly shows satellite imagery over the dateline where most maps either stop or wrap the imagery of the same date. An animation feature that allows users to select date ranges over which they can animate. An A/B comparison feature that gives users the power to compare imagery between dates and layers. In response to an increasingly large codebase caused by ongoing feature requests, Worldview is transitioning to a smaller core codebase comprised of external reusable modules. When creating a module with the intention of having someone else reuse it for a different task, one inherently starts generating code that is easier to read and easier to maintain. This presentation will show demos of these features and cover development techniques used to create them.

  5. Dips, ramps, and rolls- Evidence for paleotopographic and syn-depositional fault control on the Western Kentucky No. 4 coal bed, tradewater formation (Bolsovian) Illinois Basin

    Science.gov (United States)

    Greb, S.F.; Eble, C.F.; Williams, D.A.; Nelson, W.J.

    2001-01-01

    The Western Kentucky No. 4 coal is a high-volatile B to high-volatile C bituminous coal that has been heavily mined along the southern margin of the Western Kentucky Coal Field. The seam has a reputation for rolling floor elevation. Elongate trends of floor depressions are referred to as "dips" and "rolls" by miners. Some are relatively narrow and straight to slightly curvilinear in plan view, with generally symmetric to slightly asymmetric cross-sections. Others are broader and asymmetric in section, with sharp dips on one limb and gradual, ramp-like dips on the other. Some limbs change laterally from gradual dip, to sharp dip, to offset of the coal. Lateral changes in the rate of floor elevation dip are often associated with changes in coal thickness, and in underground mines, changes in floor elevation are sometimes associated with roof falls and haulage problems. In order to test if coal thickness changes within floor depressions were associated with changes in palynology, petrography and coal quality, the coal was sampled at a surface mine across a broad. ramp-like depression that showed down-dip coal thickening. Increment samples of coal from a thick (150 cm), down-ramp and thinner (127 cm), up-ramp position at one surface mine correlate well between sample sites (a distance of 60 m) except for a single increment. The anomalous increment (31 cm) in the lower-middle part of the thick coal bed contained 20% more Lycospora orbicula spores. The rolling floor elevations noted in the study mines are inferred to have been formed as a result of pre-peat paleotopographic depressions, syn-depositional faulting, fault-controlled pre-peat paleotopography, and from compaction beneath post-depositional channels and slumps. Although the association of thick coal with linear trends and inferred faults has been used in other basins to infer syn-depositional faulting, changes in palynology within increment samples of the seam along a structural ramp in this study provide

  6. 29 CFR 780.607 - “Primarily employed” in agriculture.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 3 2010-07-01 2010-07-01 false âPrimarily employedâ in agriculture. 780.607 Section 780... AGRICULTURE, PROCESSING OF AGRICULTURAL COMMODITIES, AND RELATED SUBJECTS UNDER THE FAIR LABOR STANDARDS ACT Employment in Agriculture and Livestock Auction Operations Under the Section 13(b)(13) Exemption Requirements...

  7. Disgust sensitivity is primarily associated with purity-based moral judgments.

    Science.gov (United States)

    Wagemans, Fieke M A; Brandt, Mark J; Zeelenberg, Marcel

    2018-03-01

    Individual differences in disgust sensitivity are associated with a range of judgments and attitudes related to the moral domain. Some perspectives suggest that the association between disgust sensitivity and moral judgments will be equally strong across all moral domains (i.e., purity, authority, loyalty, care, fairness, and liberty). Other perspectives predict that disgust sensitivity is primarily associated with judgments of specific moral domains (e.g., primarily purity). However, no study has systematically tested if disgust sensitivity is associated with moral judgments of the purity domain specifically, more generally to moral judgments of the binding moral domains, or to moral judgments of all of the moral domains equally. Across 5 studies (total N = 1,104), we find consistent evidence for the notion that disgust sensitivity relates more strongly to moral condemnation of purity-based transgressions (meta-analytic r = .40) than to moral condemnation of transgressions of any of the other domains (range meta-analytic rs: .07-.27). Our findings are in line with predictions from Moral Foundations Theory, which predicts that personality characteristics like disgust sensitivity make people more sensitive to a certain set of moral issues. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  8. Primarily Experimental Results for a W Wire Array Z Pinch

    International Nuclear Information System (INIS)

    Kuai Bin; Aici, Qiu; Wang Liangping; Zeng Zhengzhong; Wang Wensheng; Cong Peitian; Gai Tongyang; Wei Fuli; Guo Ning; Zhang Zhong

    2006-01-01

    Primarily experimental results are given for a W wire array Z pinch imploded with up to 2 MA in 100 ns on a Qiangguang-I pulsed power generator. The configuration and parameters of the generator, the W wire array load assembly and the diagnostic system for the experiment are described. The total X-ray energy has been obtained with a averaged power of X-ray radiation of 1.28 TW

  9. Prostate cancer detection: Fusion of cytological and textural features.

    Science.gov (United States)

    Nguyen, Kien; Jain, Anil K; Sabata, Bikash

    2011-01-01

    A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i) to locate cancer regions in a large digitized tissue biopsy, and (ii) to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli) in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000×7,000 pixels) and 1 1 whole-slide test images (each of which has approximately 5,000×23,000 pixels). All images are at 20X magnification.

  10. More than one kind of inference: re-examining what's learned in feature inference and classification.

    Science.gov (United States)

    Sweller, Naomi; Hayes, Brett K

    2010-08-01

    Three studies examined how task demands that impact on attention to typical or atypical category features shape the category representations formed through classification learning and inference learning. During training categories were learned via exemplar classification or by inferring missing exemplar features. In the latter condition inferences were made about missing typical features alone (typical feature inference) or about both missing typical and atypical features (mixed feature inference). Classification and mixed feature inference led to the incorporation of typical and atypical features into category representations, with both kinds of features influencing inferences about familiar (Experiments 1 and 2) and novel (Experiment 3) test items. Those in the typical inference condition focused primarily on typical features. Together with formal modelling, these results challenge previous accounts that have characterized inference learning as producing a focus on typical category features. The results show that two different kinds of inference learning are possible and that these are subserved by different kinds of category representations.

  11. Human punishment is not primarily motivated by inequality.

    Science.gov (United States)

    Marczyk, Jesse

    2017-01-01

    Previous theorizing about punishment has suggested that humans desire to punish inequality per se. However, the research supporting such an interpretation contains important methodological confounds. The main objective of the current experiment was to remove those confounds in order to test whether generating inequality per se is punished. Participants were recruited from an online market to take part in a wealth-alteration game with an ostensible second player. The participants were given an option to deduct from the other player's payment as punishment for their behavior during the game. The results suggest that human punishment does not appear to be motivated by inequality per se, as inequality that was generated without inflicting costs on others was not reliably punished. Instead, punishment seems to respond primarily to the infliction of costs, with inequality only becoming relevant as a secondary input for punishment decisions. The theoretical significance of this finding is discussed in the context of its possible adaptive value.

  12. Human punishment is not primarily motivated by inequality

    Science.gov (United States)

    Marczyk, Jesse

    2017-01-01

    Previous theorizing about punishment has suggested that humans desire to punish inequality per se. However, the research supporting such an interpretation contains important methodological confounds. The main objective of the current experiment was to remove those confounds in order to test whether generating inequality per se is punished. Participants were recruited from an online market to take part in a wealth-alteration game with an ostensible second player. The participants were given an option to deduct from the other player’s payment as punishment for their behavior during the game. The results suggest that human punishment does not appear to be motivated by inequality per se, as inequality that was generated without inflicting costs on others was not reliably punished. Instead, punishment seems to respond primarily to the infliction of costs, with inequality only becoming relevant as a secondary input for punishment decisions. The theoretical significance of this finding is discussed in the context of its possible adaptive value. PMID:28187166

  13. Human punishment is not primarily motivated by inequality.

    Directory of Open Access Journals (Sweden)

    Jesse Marczyk

    Full Text Available Previous theorizing about punishment has suggested that humans desire to punish inequality per se. However, the research supporting such an interpretation contains important methodological confounds. The main objective of the current experiment was to remove those confounds in order to test whether generating inequality per se is punished. Participants were recruited from an online market to take part in a wealth-alteration game with an ostensible second player. The participants were given an option to deduct from the other player's payment as punishment for their behavior during the game. The results suggest that human punishment does not appear to be motivated by inequality per se, as inequality that was generated without inflicting costs on others was not reliably punished. Instead, punishment seems to respond primarily to the infliction of costs, with inequality only becoming relevant as a secondary input for punishment decisions. The theoretical significance of this finding is discussed in the context of its possible adaptive value.

  14. Prostate cancer detection: Fusion of cytological and textural features

    Directory of Open Access Journals (Sweden)

    Kien Nguyen

    2011-01-01

    Full Text Available A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i to locate cancer regions in a large digitized tissue biopsy, and (ii to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000x7,000 pixels and 1 1 whole-slide test images (each of which has approximately 5,000x23,000 pixels. All images are at 20X magnification.

  15. Technical considerations for the development of an engineering safety features control system with PLC

    International Nuclear Information System (INIS)

    Lee, C. K.; Kim, C. H.; Han, J. B.; Kim, H.; Lee, S. S.

    2002-01-01

    Technical considerations are summarized for the development of an ESFCS(Engineered Safety Features Control System) with PLC (Programmable Logic Controller). The ESFCS is required for the mitigation of plant accident conditions and therefore developed in conformance with the design requirements applied to the safety critical system. The design of ESFCS primarily considered its safety, and the system has an architecture that will be able to minimize spurious actuation. The PLC based functional distribution and redundant design features are adopted, and the fieldbus is applied in the communication of information and control signals between PLC processors. It is expected that the ESFCS will have several advanced design features compared with the conventional systems supplied by foreign vendors

  16. Feature Interactions Enable Decoding of Sensorimotor Transformations for Goal-Directed Movement

    Science.gov (United States)

    Barany, Deborah A.; Della-Maggiore, Valeria; Viswanathan, Shivakumar; Cieslak, Matthew

    2014-01-01

    Neurophysiology and neuroimaging evidence shows that the brain represents multiple environmental and body-related features to compute transformations from sensory input to motor output. However, it is unclear how these features interact during goal-directed movement. To investigate this issue, we examined the representations of sensory and motor features of human hand movements within the left-hemisphere motor network. In a rapid event-related fMRI design, we measured cortical activity as participants performed right-handed movements at the wrist, with either of two postures and two amplitudes, to move a cursor to targets at different locations. Using a multivoxel analysis technique with rigorous generalization tests, we reliably distinguished representations of task-related features (primarily target location, movement direction, and posture) in multiple regions. In particular, we identified an interaction between target location and movement direction in the superior parietal lobule, which may underlie a transformation from the location of the target in space to a movement vector. In addition, we found an influence of posture on primary motor, premotor, and parietal regions. Together, these results reveal the complex interactions between different sensory and motor features that drive the computation of sensorimotor transformations. PMID:24828640

  17. Finding an optimum immuno-histochemical feature set to distinguish benign phyllodes from fibroadenoma.

    Science.gov (United States)

    Maity, Priti Prasanna; Chatterjee, Subhamoy; Das, Raunak Kumar; Mukhopadhyay, Subhalaxmi; Maity, Ashok; Maulik, Dhrubajyoti; Ray, Ajoy Kumar; Dhara, Santanu; Chatterjee, Jyotirmoy

    2013-05-01

    Benign phyllodes and fibroadenoma are two well-known breast tumors with remarkable diagnostic ambiguity. The present study is aimed at determining an optimum set of immuno-histochemical features to distinguish them by analyzing important observations on expressions of important genes in fibro-glandular tissue. Immuno-histochemically, the expressions of p63 and α-SMA in myoepithelial cells and collagen I, III and CD105 in stroma of tumors and their normal counterpart were studied. Semi-quantified features were analyzed primarily by ANOVA and ranked through F-scores for understanding relative importance of group of features in discriminating three classes followed by reduction in F-score arranged feature space dimension and application of inter-class Bhattacharyya distances to distinguish tumors with an optimum set of features. Among thirteen studied features except one all differed significantly in three study classes. F-Ranking of features revealed highest discriminative potential of collagen III (initial region). F-Score arranged feature space dimension and application of Bhattacharyya distance gave rise to a feature set of lower dimension which can discriminate benign phyllodes and fibroadenoma effectively. The work definitely separated normal breast, fibroadenoma and benign phyllodes, through an optimal set of immuno-histochemical features which are not only useful to address diagnostic ambiguity of the tumors but also to spell about malignant potentiality. Copyright © 2013 Elsevier Ltd. All rights reserved.

  18. Significance of Joint Features Derived from the Modified Group Delay Function in Speech Processing

    Directory of Open Access Journals (Sweden)

    Murthy Hema A

    2007-01-01

    Full Text Available This paper investigates the significance of combining cepstral features derived from the modified group delay function and from the short-time spectral magnitude like the MFCC. The conventional group delay function fails to capture the resonant structure and the dynamic range of the speech spectrum primarily due to pitch periodicity effects. The group delay function is modified to suppress these spikes and to restore the dynamic range of the speech spectrum. Cepstral features are derived from the modified group delay function, which are called the modified group delay feature (MODGDF. The complementarity and robustness of the MODGDF when compared to the MFCC are also analyzed using spectral reconstruction techniques. Combination of several spectral magnitude-based features and the MODGDF using feature fusion and likelihood combination is described. These features are then used for three speech processing tasks, namely, syllable, speaker, and language recognition. Results indicate that combining MODGDF with MFCC at the feature level gives significant improvements for speech recognition tasks in noise. Combining the MODGDF and the spectral magnitude-based features gives a significant increase in recognition performance of 11% at best, while combining any two features derived from the spectral magnitude does not give any significant improvement.

  19. Online feature selection with streaming features.

    Science.gov (United States)

    Wu, Xindong; Yu, Kui; Ding, Wei; Wang, Hao; Zhu, Xingquan

    2013-05-01

    We propose a new online feature selection framework for applications with streaming features where the knowledge of the full feature space is unknown in advance. We define streaming features as features that flow in one by one over time whereas the number of training examples remains fixed. This is in contrast with traditional online learning methods that only deal with sequentially added observations, with little attention being paid to streaming features. The critical challenges for Online Streaming Feature Selection (OSFS) include 1) the continuous growth of feature volumes over time, 2) a large feature space, possibly of unknown or infinite size, and 3) the unavailability of the entire feature set before learning starts. In the paper, we present a novel Online Streaming Feature Selection method to select strongly relevant and nonredundant features on the fly. An efficient Fast-OSFS algorithm is proposed to improve feature selection performance. The proposed algorithms are evaluated extensively on high-dimensional datasets and also with a real-world case study on impact crater detection. Experimental results demonstrate that the algorithms achieve better compactness and higher prediction accuracy than existing streaming feature selection algorithms.

  20. Understanding Legacy Features with Featureous

    DEFF Research Database (Denmark)

    Olszak, Andrzej; Jørgensen, Bo Nørregaard

    2011-01-01

    Java programs called Featureous that addresses this issue. Featureous allows a programmer to easily establish feature-code traceability links and to analyze their characteristics using a number of visualizations. Featureous is an extension to the NetBeans IDE, and can itself be extended by third...

  1. Cauda equina syndrome as the initial presenting clinical feature of medulloblastoma: a case report

    Directory of Open Access Journals (Sweden)

    Al-Otaibi Faisal

    2012-05-01

    Full Text Available Abstract Introduction Medulloblastoma is one of the most common pediatric brain malignancies. The usual presenting clinical features are related to posterior fossa syndrome or/and hydrocephalus. Cauda equina syndrome is a very rare presentation for this disease. Case presentation We describe the case of a three-year-old boy with cauda equina syndrome as the initial presenting clinical feature for medulloblastoma. He was initially diagnosed as having a spinal tumor by magnetic resonance imaging scan. Subsequently, a cranial magnetic resonance imaging scan revealed a posterior fossa tumor with features of dissemination. He had substantial improvement after treatment. This case report is complemented by a literature review related to this unusual presentation. Conclusions Medulloblastoma primarily presenting with cauda equina syndrome is very rare. However, spinal drop metastasis should be considered in the pediatric age group to avoid suboptimal management.

  2. 49 CFR 37.195 - Purchase or lease of OTRBs by private entities not primarily in the business of transporting people.

    Science.gov (United States)

    2010-10-01

    ... primarily in the business of transporting people. 37.195 Section 37.195 Transportation Office of the... transporting people. This section applies to all purchases or leases of new vehicles by private entities which are not primarily engaged in the business of transporting people, with respect to buses delivered to...

  3. Lamin A/C mutation affecting primarily the right side of the heart

    Directory of Open Access Journals (Sweden)

    Laura Ollila

    2013-04-01

    Full Text Available LMNA mutations are amongst the most important causes of familial dilated cardiomyopathy. The most important cause of arrhythmogenic right ventricular cardiomyopathy (ARVC is desmosomal pathology. The aim of the study was to elucidate the role of LMNA mutations among Finnish cardiomyopathy patients. We screened 135 unrelated cardiomyopathy patients for LMNA mutations. Because of unusual phenotype, two patients were screened for the known Finnish ARVC-related mutations of desmosomal genes, and their Plakophilin-2b gene was sequenced. Myocardial samples from two patients were examined by immunohistochemical plakoglobin staining and in one case by electron microscopy. We found a new LMNA mutation Phe237Ser in a family of five affected members with a cardiomyopathy affecting primarily the right side of the heart. The phenotype resembles ARVC but does not fulfill the Task Force Criteria. The main clinical manifestations of the mutation were severe tricuspid insufficiency, right ventricular enlargement and failure. Three of the affected patients died of the heart disease, and the two living patients received heart transplants at ages 44 and 47. Electron microscopy showed nuclear blebbing compatible with laminopathy. Immunohisto - chemical analysis did not suggest desmosomal pathology. No desmosomal mutations were found. The Phe237Ser LMNA mutation causes a phenotype different from traditional cardiolaminopathy. Our findings suggest that cardiomyopathy affecting primarily the right side of the heart is not always caused by desmosomal pathology. Our observations highlight the challenges in classifying cardiomyopathies, as there often is significant overlap between the traditional categories.

  4. Whole-genome phylogeny of Escherichia coli/Shigella group by feature frequency profiles (FFPs)

    Science.gov (United States)

    Sims, Gregory E.; Kim, Sung-Hou

    2011-01-01

    A whole-genome phylogeny of the Escherichia coli/Shigella group was constructed by using the feature frequency profile (FFP) method. This alignment-free approach uses the frequencies of l-mer features of whole genomes to infer phylogenic distances. We present two phylogenies that accentuate different aspects of E. coli/Shigella genomic evolution: (i) one based on the compositions of all possible features of length l = 24 (∼8.4 million features), which are likely to reveal the phenetic grouping and relationship among the organisms and (ii) the other based on the compositions of core features with low frequency and low variability (∼0.56 million features), which account for ∼69% of all commonly shared features among 38 taxa examined and are likely to have genome-wide lineal evolutionary signal. Shigella appears as a single clade when all possible features are used without filtering of noncore features. However, results using core features show that Shigella consists of at least two distantly related subclades, implying that the subclades evolved into a single clade because of a high degree of convergence influenced by mobile genetic elements and niche adaptation. In both FFP trees, the basal group of the E. coli/Shigella phylogeny is the B2 phylogroup, which contains primarily uropathogenic strains, suggesting that the E. coli/Shigella ancestor was likely a facultative or opportunistic pathogen. The extant commensal strains diverged relatively late and appear to be the result of reductive evolution of genomes. We also identify clade distinguishing features and their associated genomic regions within each phylogroup. Such features may provide useful information for understanding evolution of the groups and for quick diagnostic identification of each phylogroup. PMID:21536867

  5. Hydrogen peroxide production is not primarily increased in human myotubes established from type 2 diabetic subjects.

    Science.gov (United States)

    Minet, A D; Gaster, M

    2011-09-01

    Increased oxidative stress and mitochondrial dysfunction have been implicated in the development of insulin resistance in type 2 diabetes. To date, it is unknown whether increased mitochondrial reactive oxygen species (ROS) production in skeletal muscle from patients with type 2 diabetes is primarily increased or a secondary adaptation to environmental, lifestyle, and hormonal factors. This study investigates whether ROS production is primarily increased in isolated diabetic myotubes. Mitochondrial membrane potential, hydrogen peroxide (H(2)O(2)), superoxide, and mitochondrial mass were determined in human myotubes precultured under normophysiological conditions. Furthermore, the corresponding ATP synthesis was measured in isolated mitochondria. Muscle biopsies were taken from 10 lean subjects, 10 obese subjects, and 10 subjects with type 2 diabetes; satellite cells were isolated, cultured, and differentiated to myotubes. Mitochondrial mass, membrane potential/mitochondrial mass, and superoxide-production/mitochondrial mass were not different between groups. In contrast, H(2)O(2) production/mitochondrial mass and ATP production were significantly reduced in diabetic myotubes compared to lean controls (P production is not primarily increased in diabetic myotubes but rather is reduced. Moreover, the comparable ATP/H(2)O(2) ratios indicate that the reduced ROS production in diabetic myotubes parallels the reduced ATP production because ROS production in diabetic myotubes must be considered to be in a proportion comparable to lean. Thus, the increased ROS production seen in skeletal muscle of type 2 diabetic patients is an adaptation to the in vivo conditions.

  6. Plasma features and alpha particle transport in low-aspect ratio tokamak reactor

    International Nuclear Information System (INIS)

    Xu Qiang; Wang Shaojie

    1997-06-01

    The results of the experiment and theory from low-aspect ratio tokamak devices have proved that the MHD stability will be improved. Based on present plasma physics and extrapolation to reduced aspect ratio, the feature of physics of low-aspect ratio tokamak reactor is discussed primarily. Alpha particle confinement and loss in the self-justified low-aspect ratio tokamak reactor parameters and the effect of alpha particle confinement and loss for different aspect ratio are calculated. The results provide a reference for the feasible research of compact tokamak reactor. (9 refs., 2 figs., 3 tabs.)

  7. Angiographic features of 26 children with Takayasu's arteritis

    International Nuclear Information System (INIS)

    McCulloch, M.; Goddard, E.; Sinclair, P.; Andronikou, S.; Mandelstam, S.; Beningfield, S.J.; Lawrenson, J.; Millar, A.J.W.

    2003-01-01

    Background: Takayasu's arteritis (TA) is a chronic idiopathic inflammatory disease affecting primarily the aorta, its proximal branches and the pulmonary arteries Objectives: To retrospectively review the angiograms of children with TA so as to describe the patterns of vascular involvement. Patients and methods: Twenty-six children with TA who differed from most other studies in that almost all of them presented with hypertension, reflecting the incidence of abdominal aortic and renal artery involvement. Results: The most consistent finding was stenosis of the aorta. Marginal irregularity/undulation of the aorta was also a useful angiographic diagnostic feature in subtle disease. The incidence of aneurysms was high compared to other studies and both fusiform and saccular aneurysms were encountered. Percutaneous transluminal angioplasty (PTA) was successful in all eight patients in whom it was performed. MRI, CT angiography and US are discussed as less invasive imaging alternatives. TA is a significant cause of renovascular hypertension in children in South Africa where there is a high incidence of tuberculous infection. Knowledge of the angiographic features and pattern of aortic involvement is essential for diagnosis and initiation of early and appropriate treatment, including PTA. (orig.)

  8. Skeletal Muscle Laminopathies: A Review of Clinical and Molecular Features

    Directory of Open Access Journals (Sweden)

    Lorenzo Maggi

    2016-08-01

    Full Text Available LMNA-related disorders are caused by mutations in the LMNA gene, which encodes for the nuclear envelope proteins, lamin A and C, via alternative splicing. Laminopathies are associated with a wide range of disease phenotypes, including neuromuscular, cardiac, metabolic disorders and premature aging syndromes. The most frequent diseases associated with mutations in the LMNA gene are characterized by skeletal and cardiac muscle involvement. This review will focus on genetics and clinical features of laminopathies affecting primarily skeletal muscle. Although only symptomatic treatment is available for these patients, many achievements have been made in clarifying the pathogenesis and improving the management of these diseases.

  9. X-ray and CT signs of connective tissue dysplasia in patients with primarily diagnosed infiltrative pulmonary tuberculosis

    International Nuclear Information System (INIS)

    Sukhanova, L.A.; Sharmazanova, O.P.

    2009-01-01

    The x-ray signs of connective tissue systemic dysplasia (CTSD) in patients with primarily diagnosed pulmonary tuberculosis was investigated. Fifty-four patients (28 med and 26 women aged 18-70) with primarily diagnosed infiltrative pulmonary tuberculosis underwent x-ray study. In patients with infiltration pulmonary tuberculosis CTSD in the lungs manifests by their diminishing, deformity of the lung pattern, high position of the diaphragm cupola, mediastinum shift to the side of the pathology, which is better seen on CT. The degree of CTSD x-ray signs in the lungs depends on the number of phenotypical signs that is the degree of the disease manifestation. CT allows more accurate determining of the signs of connective tissue dysplasia in which tuberculosis develops

  10. How a central bank perceives the (visual) communication of security features on its banknotes

    Science.gov (United States)

    Tornare, Roland

    1998-04-01

    The banknotes of earlier generations were protected by two or three security features with which the general public was familiar: watermark, security thread, intaglio printing. The remaining features pleased primarily printers and central banks, with little thought being given to public perception. The philosophy adopted two decades ago was based on a certain measure of discretion. It required patience and perseverance to discover the built-in security features of the banknotes. When colour photocopiers appeared on the scene in the mid- eighties we were compelled to take precautionary measures to protect our banknotes. One such measure consisted of an information campaign to prepare ourselves for this new potential threat. At this point, we actually became fully aware of the complex design of our banknotes and how difficult it is to communicate clearly the difference between a genuine and a counterfeit banknote. This difficult experience has nevertheless been a great benefit. It badgered us continually during the initial phase of designing the banknotes and preparing the information campaign.

  11. Histogram-based adaptive gray level scaling for texture feature classification of colorectal polyps

    Science.gov (United States)

    Pomeroy, Marc; Lu, Hongbing; Pickhardt, Perry J.; Liang, Zhengrong

    2018-02-01

    Texture features have played an ever increasing role in computer aided detection (CADe) and diagnosis (CADx) methods since their inception. Texture features are often used as a method of false positive reduction for CADe packages, especially for detecting colorectal polyps and distinguishing them from falsely tagged residual stool and healthy colon wall folds. While texture features have shown great success there, the performance of texture features for CADx have lagged behind primarily because of the more similar features among different polyps types. In this paper, we present an adaptive gray level scaling and compare it to the conventional equal-spacing of gray level bins. We use a dataset taken from computed tomography colonography patients, with 392 polyp regions of interest (ROIs) identified and have a confirmed diagnosis through pathology. Using the histogram information from the entire ROI dataset, we generate the gray level bins such that each bin contains roughly the same number of voxels Each image ROI is the scaled down to two different numbers of gray levels, using both an equal spacing of Hounsfield units for each bin, and our adaptive method. We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas), we find that the adaptive gray level scaling can improve performance based on the area under the receiver operating characteristic curve by up to 4.6%.

  12. A COMPARATIVE ANALYSIS OF SINGLE AND COMBINATION FEATURE EXTRACTION TECHNIQUES FOR DETECTING CERVICAL CANCER LESIONS

    Directory of Open Access Journals (Sweden)

    S. Pradeep Kumar Kenny

    2016-02-01

    Full Text Available Cervical cancer is the third most common form of cancer affecting women especially in third world countries. The predominant reason for such alarming rate of death is primarily due to lack of awareness and proper health care. As they say, prevention is better than cure, a better strategy has to be put in place to screen a large number of women so that an early diagnosis can help in saving their lives. One such strategy is to implement an automated system. For an automated system to function properly a proper set of features have to be extracted so that the cancer cell can be detected efficiently. In this paper we compare the performances of detecting a cancer cell using a single feature versus a combination feature set technique to see which will suit the automated system in terms of higher detection rate. For this each cell is segmented using multiscale morphological watershed segmentation technique and a series of features are extracted. This process is performed on 967 images and the data extracted is subjected to data mining techniques to determine which feature is best for which stage of cancer. The results thus obtained clearly show a higher percentage of success for combination feature set with 100% accurate detection rate.

  13. Radiation protection for children. Special features of pediatric radiology

    International Nuclear Information System (INIS)

    Schweiger, Bernd

    2012-01-01

    Due to the morphology of the small body and the special feature of athe growing organism children are notably radiation sensitive. It is an aggravating fact that due to missing adaptation of examination parameters the infantile bodies can be exposed to needless high radiation doses. This is especially the fact in case of computerized tomography that has reached increased importance during the last years. Therefore it is recommended to use primarily ultrasonography or MRT. X-ray examinations of children require specific adapted examination protocols targeted to optimized dose reduction. The author discusses the issues physical aspects, anatomic differences, tissue radiation sensitivity, life expectation and genetic risk, critical indication tracking in pediatrics, adaptation of examination parameters to body size and anatomy.

  14. An integrated multi-sensor fusion-based deep feature learning approach for rotating machinery diagnosis

    Science.gov (United States)

    Liu, Jie; Hu, Youmin; Wang, Yan; Wu, Bo; Fan, Jikai; Hu, Zhongxu

    2018-05-01

    The diagnosis of complicated fault severity problems in rotating machinery systems is an important issue that affects the productivity and quality of manufacturing processes and industrial applications. However, it usually suffers from several deficiencies. (1) A considerable degree of prior knowledge and expertise is required to not only extract and select specific features from raw sensor signals, and but also choose a suitable fusion for sensor information. (2) Traditional artificial neural networks with shallow architectures are usually adopted and they have a limited ability to learn the complex and variable operating conditions. In multi-sensor-based diagnosis applications in particular, massive high-dimensional and high-volume raw sensor signals need to be processed. In this paper, an integrated multi-sensor fusion-based deep feature learning (IMSFDFL) approach is developed to identify the fault severity in rotating machinery processes. First, traditional statistics and energy spectrum features are extracted from multiple sensors with multiple channels and combined. Then, a fused feature vector is constructed from all of the acquisition channels. Further, deep feature learning with stacked auto-encoders is used to obtain the deep features. Finally, the traditional softmax model is applied to identify the fault severity. The effectiveness of the proposed IMSFDFL approach is primarily verified by a one-stage gearbox experimental platform that uses several accelerometers under different operating conditions. This approach can identify fault severity more effectively than the traditional approaches.

  15. Triacylglycerol Accumulation is not primarily affected in Myotubes established from Type 2 Diabetic Subjects

    DEFF Research Database (Denmark)

    Gaster, Michael; Beck-Nielsen, Henning

    2006-01-01

    In the present study, we investigated triacylglycerol (TAG) accumulation, glucose and fatty acid (FA) uptake, and glycogen synthesis (GS) in human myotubes from healthy, lean, and obese subjects with and without type 2 diabetes (T2D), exposed to increasing palmitate (PA) and oleate (OA...... uptake (P0.05). These results indicate that (1) TAG accumulation is not primarily affected in skeletal muscle tissue of obese and T2D; (2) induced inhibition of oxidative phosphorylation is followed by TAG accumulation...... in skeletal muscle of obese and T2D subjects is adaptive....

  16. Chromomycosis presenting as soft-tissue mass: report of a case with MRI features

    International Nuclear Information System (INIS)

    Bahk, Won-Jong; Chang, Eun-Deok; Chun, Kyung-Ah; Lee, An-Hi; Park, Jung-Mi; Bahk, Yong-Whee

    2009-01-01

    Chromomycosis is primarily a skin disease that superficially presents as slowly growing, verrucous lesions, often warty or cauliflower-like in appearance. It may occasionally create a flat, plaque-like lesion in the skin but deep-seated tumorous presentation has not previously been reported. As the lesion is limited to the cutaneous and superficial subcutaneous tissues, hitherto reported cases have been described from the view point of dermatology and, so, without MRI study. We report a patient with pathologically proven chromomycosis that produced a subcutaneous mass in the dorsum of the hand with an emphasis on MRI features. (orig.)

  17. Chromomycosis presenting as soft-tissue mass: report of a case with MRI features

    Energy Technology Data Exchange (ETDEWEB)

    Bahk, Won-Jong [Uijongbu St. Mary' s Hospital, The Catholic University of Korea, Department of Orthopaedic Surgery, Gyunggido (Korea); Chang, Eun-Deok; Chun, Kyung-Ah; Lee, An-Hi; Park, Jung-Mi [The Catholic University of Korea School of Medicine, Musculoskeletal Oncology Group, Gyunggido (Korea); Bahk, Yong-Whee [SungAe General Hospital, PET CT Center, Seoul (Korea)

    2009-02-15

    Chromomycosis is primarily a skin disease that superficially presents as slowly growing, verrucous lesions, often warty or cauliflower-like in appearance. It may occasionally create a flat, plaque-like lesion in the skin but deep-seated tumorous presentation has not previously been reported. As the lesion is limited to the cutaneous and superficial subcutaneous tissues, hitherto reported cases have been described from the view point of dermatology and, so, without MRI study. We report a patient with pathologically proven chromomycosis that produced a subcutaneous mass in the dorsum of the hand with an emphasis on MRI features. (orig.)

  18. On the Origin of the Bolivian High and Related Circulation Features of the South American Climate.

    Science.gov (United States)

    Lenters, J. D.; Cook, K. H.

    1997-03-01

    The climatological structure in the upper-tropospheric summertime circulation over South America is diagnosed using a GCM (with and without South American topography), a linear model, and observational data. Emphasis is placed on understanding the origin of observed features such as the Bolivian high and the accompanying `Nordeste low' to the east. Results from the linear model indicate that these two features are generated in response to precipitation over the Amazon basin, central Andes, and South Atlantic convergence zone, with African precipitation also playing a crucial role in the formation of the Nordeste low. The direct mechanical and sensible heating effects of the Andes are minimal, acting only to induce a weak lee trough in midlatitudes and a shallow monsoonal circulation over the central Andes. In the GCM, the effects of the Andes include a strengthening of the Bolivian high and northward shift of the Nordeste low, primarily through changes in the precipitation field. The position of the Bolivian high is primarily determined by Amazonian precipitation and is little affected by the removal of the Andes. Strong subsidence to the west of the high is found to be important for the maintenance of the high's warm core, while large-scale convective overshooting to the east is responsible for a layer of cold air above the high.

  19. LMD Based Features for the Automatic Seizure Detection of EEG Signals Using SVM.

    Science.gov (United States)

    Zhang, Tao; Chen, Wanzhong

    2017-08-01

    Achieving the goal of detecting seizure activity automatically using electroencephalogram (EEG) signals is of great importance and significance for the treatment of epileptic seizures. To realize this aim, a newly-developed time-frequency analytical algorithm, namely local mean decomposition (LMD), is employed in the presented study. LMD is able to decompose an arbitrary signal into a series of product functions (PFs). Primarily, the raw EEG signal is decomposed into several PFs, and then the temporal statistical and non-linear features of the first five PFs are calculated. The features of each PF are fed into five classifiers, including back propagation neural network (BPNN), K-nearest neighbor (KNN), linear discriminant analysis (LDA), un-optimized support vector machine (SVM) and SVM optimized by genetic algorithm (GA-SVM), for five classification cases, respectively. Confluent features of all PFs and raw EEG are further passed into the high-performance GA-SVM for the same classification tasks. Experimental results on the international public Bonn epilepsy EEG dataset show that the average classification accuracy of the presented approach are equal to or higher than 98.10% in all the five cases, and this indicates the effectiveness of the proposed approach for automated seizure detection.

  20. Examining Change in K-3 Teachers' Mathematical Knowledge, Attitudes, and Beliefs: The Case of Primarily Math

    Science.gov (United States)

    Kutaka, T. S.; Ren, L.; Smith, W. M.; Beattie, H. L.; Edwards, C. P.; Green, J. L.; Chernyavskiy, P.; Stroup, W.; Heaton, R. M.; Lewis, W. J.

    2018-01-01

    This study examines the impact of the Primarily Math Elementary Mathematics Specialist program on K-3 teachers' mathematical content knowledge for teaching, attitudes toward learning mathematics, and beliefs about mathematics teaching and learning. Three cohorts of teachers participating in the program were compared to a similar group of…

  1. Subsurface mapping of Rustenburg Layered Suite (RLS), Bushveld Complex, South Africa: Inferred structural features using borehole data and spatial analysis

    Science.gov (United States)

    Bamisaiye, O. A.; Eriksson, P. G.; Van Rooy, J. L.; Brynard, H. M.; Foya, S.; Billay, A. Y.; Nxumalo, V.

    2017-08-01

    Faults and other structural features within the mafic-ultramafic layers of the Bushveld Complex have been a major issue mainly for exploration and mine planning. This study employed a new approach in detecting faults with both regional and meter scale offsets, which was not possible with the usually applied structure contour mapping. Interpretations of faults from structural and isopach maps were previously based on geological experience, while meter-scale faults were virtually impossible to detect from such maps. Spatial analysis was performed using borehole data primarily. This resulted in the identification of previously known structures and other hitherto unsuspected structural features. Consequently, the location, trends, and geometry of faults and some regional features within the Rustenburg Layered Suite (RLS) that might not be easy to detect through field mapping are adequately described in this study.

  2. A prototype feature system for feature retrieval using relationships

    Science.gov (United States)

    Choi, J.; Usery, E.L.

    2009-01-01

    Using a feature data model, geographic phenomena can be represented effectively by integrating space, theme, and time. This paper extends and implements a feature data model that supports query and visualization of geographic features using their non-spatial and temporal relationships. A prototype feature-oriented geographic information system (FOGIS) is then developed and storage of features named Feature Database is designed. Buildings from the U.S. Marine Corps Base, Camp Lejeune, North Carolina and subways in Chicago, Illinois are used to test the developed system. The results of the applications show the strength of the feature data model and the developed system 'FOGIS' when they utilize non-spatial and temporal relationships in order to retrieve and visualize individual features.

  3. Direct healthcare costs of selected diseases primarily or partially transmitted by water.

    Science.gov (United States)

    Collier, S A; Stockman, L J; Hicks, L A; Garrison, L E; Zhou, F J; Beach, M J

    2012-11-01

    Despite US sanitation advancements, millions of waterborne disease cases occur annually, although the precise burden of disease is not well quantified. Estimating the direct healthcare cost of specific infections would be useful in prioritizing waterborne disease prevention activities. Hospitalization and outpatient visit costs per case and total US hospitalization costs for ten waterborne diseases were calculated using large healthcare claims and hospital discharge databases. The five primarily waterborne diseases in this analysis (giardiasis, cryptosporidiosis, Legionnaires' disease, otitis externa, and non-tuberculous mycobacterial infection) were responsible for over 40 000 hospitalizations at a cost of $970 million per year, including at least $430 million in hospitalization costs for Medicaid and Medicare patients. An additional 50 000 hospitalizations for campylobacteriosis, salmonellosis, shigellosis, haemolytic uraemic syndrome, and toxoplasmosis cost $860 million annually ($390 million in payments for Medicaid and Medicare patients), a portion of which can be assumed to be due to waterborne transmission.

  4. Anomalous South Pacific lithosphere dynamics derived from new total sediment thickness estimates off the West Antarctic margin

    Science.gov (United States)

    Wobbe, Florian; Lindeque, Ansa; Gohl, Karsten

    2014-12-01

    Paleotopographic models of the West Antarctic margin, which are essential for robust simulations of paleoclimate scenarios, lack information on sediment thickness and geodynamic conditions, resulting in large uncertainties. A new total sediment thickness grid spanning the Ross Sea-Amundsen Sea-Bellingshausen Sea basins is presented and is based on all the available seismic reflection, borehole, and gravity modeling data offshore West Antarctica. This grid was combined with NGDC's global 5 arc minute grid of ocean sediment thickness (Whittaker et al., 2013) and extends the NGDC grid further to the south. Sediment thickness along the West Antarctic margin tends to be 3-4 km larger than previously assumed. The sediment volume in the Bellingshausen, Amundsen, and Ross Sea basins amounts to 3.61, 3.58, and 2.78 million km3, respectively. The residual basement topography of the South Pacific has been revised and the new data show an asymmetric trend over the Pacific-Antarctic Ridge. Values are anomalously high south of the spreading ridge and in the Ross Sea area, where the topography seems to be affected by persistent mantle processes. In contrast, the basement topography offshore Marie Byrd Land cannot be attributed to dynamic topography, but rather to crustal thickening due to intraplate volcanism. Present-day dynamic topography models disagree with the presented revised basement topography of the South Pacific, rendering paleotopographic reconstructions with such a limited dataset still fairly uncertain.

  5. Enhancing facial features by using clear facial features

    Science.gov (United States)

    Rofoo, Fanar Fareed Hanna

    2017-09-01

    The similarity of features between individuals of same ethnicity motivated the idea of this project. The idea of this project is to extract features of clear facial image and impose them on blurred facial image of same ethnic origin as an approach to enhance a blurred facial image. A database of clear images containing 30 individuals equally divided to five different ethnicities which were Arab, African, Chines, European and Indian. Software was built to perform pre-processing on images in order to align the features of clear and blurred images. And the idea was to extract features of clear facial image or template built from clear facial images using wavelet transformation to impose them on blurred image by using reverse wavelet. The results of this approach did not come well as all the features did not align together as in most cases the eyes were aligned but the nose or mouth were not aligned. Then we decided in the next approach to deal with features separately but in the result in some cases a blocky effect was present on features due to not having close matching features. In general the available small database did not help to achieve the goal results, because of the number of available individuals. The color information and features similarity could be more investigated to achieve better results by having larger database as well as improving the process of enhancement by the availability of closer matches in each ethnicity.

  6. Spatial features register: toward standardization of spatial features

    Science.gov (United States)

    Cascio, Janette

    1994-01-01

    As the need to share spatial data increases, more than agreement on a common format is needed to ensure that the data is meaningful to both the importer and the exporter. Effective data transfer also requires common definitions of spatial features. To achieve this, part 2 of the Spatial Data Transfer Standard (SDTS) provides a model for a spatial features data content specification and a glossary of features and attributes that fit this model. The model provides a foundation for standardizing spatial features. The glossary now contains only a limited subset of hydrographic and topographic features. For it to be useful, terms and definitions must be included for other categories, such as base cartographic, bathymetric, cadastral, cultural and demographic, geodetic, geologic, ground transportation, international boundaries, soils, vegetation, water, and wetlands, and the set of hydrographic and topographic features must be expanded. This paper will review the philosophy of the SDTS part 2 and the current plans for creating a national spatial features register as one mechanism for maintaining part 2.

  7. Wet meadow ecosystems and the longevity of biologically-mediated geomorphic features

    Science.gov (United States)

    Nash, C.; Grant, G.; O'Connor, J. E.

    2016-12-01

    Upland meadows represent a ubiquitous feature of montane landscapes in the U.S. West and beyond. Characterized by flat valley floors flanked by higher-gradient hillslopes, these meadows are important features, both for the diverse ecosystems they support but also because they represent depositional features in what is primarily an erosional environment. As such, they serve as long-term chronometers of both geological and ecological processes in a portion of the landscape where such records are rare, and provide a useful microcosm for exploring many of the questions motivating critical zone science. Specifically, meadows can offer insights into questions regarding the longevity of theses biologically-mediated landscapes, and the geomorphic thresholds associated with transitions between metastable landscape states. Though categorically depositional, wet meadows have been shown to rapidly shift into erosional landscapes characterized by deep arroyos, declining water tables, and sparse, semi-arid ecosystems. Numerous hypotheses have been proposed explaining this shift: intensive ungulate usage, removal of beaver, climatic shifts, and intrinsic geomorphic evolution. Even less is known about the mechanisms controlling the construction of these meadow features. Evidence seems to suggest these channels oscillate between two metastable conditions: deeply incised, single-threaded channels and sheet-flow dominated valley-spanning wetlands. We present new evidence exploring the subsurface architecture of wet meadows and the bidirectional process cascades potentially responsible for their temporal evolution. Using a combination of near surface geophysical techniques and detailed stratigraphic descriptions of incised and un-incised meadows throughout the Silvies River Basin, OR, we examine mechanisms responsible both for the construction of these features and their apparently rapid transition from depositional to erosional. Our investigation focuses specifically on potential

  8. FEATURE SELECTION METHODS BASED ON MUTUAL INFORMATION FOR CLASSIFYING HETEROGENEOUS FEATURES

    Directory of Open Access Journals (Sweden)

    Ratri Enggar Pawening

    2016-06-01

    Full Text Available Datasets with heterogeneous features can affect feature selection results that are not appropriate because it is difficult to evaluate heterogeneous features concurrently. Feature transformation (FT is another way to handle heterogeneous features subset selection. The results of transformation from non-numerical into numerical features may produce redundancy to the original numerical features. In this paper, we propose a method to select feature subset based on mutual information (MI for classifying heterogeneous features. We use unsupervised feature transformation (UFT methods and joint mutual information maximation (JMIM methods. UFT methods is used to transform non-numerical features into numerical features. JMIM methods is used to select feature subset with a consideration of the class label. The transformed and the original features are combined entirely, then determine features subset by using JMIM methods, and classify them using support vector machine (SVM algorithm. The classification accuracy are measured for any number of selected feature subset and compared between UFT-JMIM methods and Dummy-JMIM methods. The average classification accuracy for all experiments in this study that can be achieved by UFT-JMIM methods is about 84.47% and Dummy-JMIM methods is about 84.24%. This result shows that UFT-JMIM methods can minimize information loss between transformed and original features, and select feature subset to avoid redundant and irrelevant features.

  9. Retinal Identification Based on an Improved Circular Gabor Filter and Scale Invariant Feature Transform

    Directory of Open Access Journals (Sweden)

    Xiaoming Xi

    2013-07-01

    Full Text Available Retinal identification based on retinal vasculatures in the retina provides the most secure and accurate means of authentication among biometrics and has primarily been used in combination with access control systems at high security facilities. Recently, there has been much interest in retina identification. As digital retina images always suffer from deformations, the Scale Invariant Feature Transform (SIFT, which is known for its distinctiveness and invariance for scale and rotation, has been introduced to retinal based identification. However, some shortcomings like the difficulty of feature extraction and mismatching exist in SIFT-based identification. To solve these problems, a novel preprocessing method based on the Improved Circular Gabor Transform (ICGF is proposed. After further processing by the iterated spatial anisotropic smooth method, the number of uninformative SIFT keypoints is decreased dramatically. Tested on the VARIA and eight simulated retina databases combining rotation and scaling, the developed method presents promising results and shows robustness to rotations and scale changes.

  10. Spatial Policy оf Exporting Direct Investments: Features оf China

    Directory of Open Access Journals (Sweden)

    Alina Nikolaevna Novopashina

    2014-03-01

    Full Text Available In recent years, China has shown rapid growth in volumes of foreign direct investment (FDI, which is the consequence of implementing policy. However, the structure of FDI does not correspond to the government-supported areas. Existing theoretical and empirical studies don’t reveal the causes of China’s FDI. Results of the regression analysis (based on panel data for 2003-2010 prove that the most attractive for Chinese investors were countries with following features: 1 rich in mineral resources, 2 possessing advanced technologies, 3 higher than in China income levels, 4 geographic proximity to China and 5 foreign trade openness. Furthermore, features of the current institutional environment in China affect the directions of foreign direct investment. Investors from PRC direct FDI in developing countries which have low quality of institutions as well as China. Investing in these countries is primarily aimed at getting access to their mineral resources and consumer markets. As for investing in developed countries, the reason is acquisition of advanced technologies which they possess. Directions of FDI in these countries, on the contrary, are determined by the high quality of institutions

  11. The effect of feature-based attention on flanker interference processing: An fMRI-constrained source analysis.

    Science.gov (United States)

    Siemann, Julia; Herrmann, Manfred; Galashan, Daniela

    2018-01-25

    The present study examined whether feature-based cueing affects early or late stages of flanker conflict processing using EEG and fMRI. Feature cues either directed participants' attention to the upcoming colour of the target or were neutral. Validity-specific modulations during interference processing were investigated using the N200 event-related potential (ERP) component and BOLD signal differences. Additionally, both data sets were integrated using an fMRI-constrained source analysis. Finally, the results were compared with a previous study in which spatial instead of feature-based cueing was applied to an otherwise identical flanker task. Feature-based and spatial attention recruited a common fronto-parietal network during conflict processing. Irrespective of attention type (feature-based; spatial), this network responded to focussed attention (valid cueing) as well as context updating (invalid cueing), hinting at domain-general mechanisms. However, spatially and non-spatially directed attention also demonstrated domain-specific activation patterns for conflict processing that were observable in distinct EEG and fMRI data patterns as well as in the respective source analyses. Conflict-specific activity in visual brain regions was comparable between both attention types. We assume that the distinction between spatially and non-spatially directed attention types primarily applies to temporal differences (domain-specific dynamics) between signals originating in the same brain regions (domain-general localization).

  12. Assessing the impact of representational and contextual problem features on student use of right-hand rules

    Science.gov (United States)

    Kustusch, Mary Bridget

    2016-06-01

    Students in introductory physics struggle with vector algebra and these challenges are often associated with contextual and representational features of the problems. Performance on problems about cross product direction is particularly poor and some research suggests that this may be primarily due to misapplied right-hand rules. However, few studies have had the resolution to explore student use of right-hand rules in detail. This study reviews literature in several disciplines, including spatial cognition, to identify ten contextual and representational problem features that are most likely to influence performance on problems requiring a right-hand rule. Two quantitative measures of performance (correctness and response time) and two qualitative measures (methods used and type of errors made) were used to explore the impact of these problem features on student performance. Quantitative results are consistent with expectations from the literature, but reveal that some features (such as the type of reasoning required and the physical awkwardness of using a right-hand rule) have a greater impact than others (such as whether the vectors are placed together or separate). Additional insight is gained by the qualitative analysis, including identifying sources of difficulty not previously discussed in the literature and revealing that the use of supplemental methods, such as physically rotating the paper, can mitigate errors associated with certain features.

  13. Identifying significant environmental features using feature recognition.

    Science.gov (United States)

    2015-10-01

    The Department of Environmental Analysis at the Kentucky Transportation Cabinet has expressed an interest in feature-recognition capability because it may help analysts identify environmentally sensitive features in the landscape, : including those r...

  14. Clinical and epidemiological features of AIDS/tuberculosis comorbidity

    Directory of Open Access Journals (Sweden)

    Song Alice Tung Wan

    2003-01-01

    Full Text Available Considering the relevance of AIDS/tuberculosis comorbidity worldwide, especially in Brazil, this study was developed to describe the clinical and epidemiological features of the comorbid cases identified from 1989 to 1997 by the epidemiology service of the Hospital das Clínicas of the Universidade de São Paulo. METHODS: Databases containing information on all identified AIDS/tuberculosis cases cared for at the hospital were used to gather information on comorbid cases. RESULTS: During the period, 559 patients were identified as presenting with AIDS/tuberculosis comorbidity. Risk behavior for AIDS was primarily heterosexual contact (38.9%, followed by intravenous drug use (29.3% and homosexual/bisexual contact (23.2%. Regarding clinical features, there were higher rates of extrapulmonary tuberculosis when compared to tuberculosis without comorbidity. There was an increase in reporting of AIDS by ambulatory units during the period. Epidemiologically, there was a decrease in the male/female ratio, a predominance in the 20 to 39 year-old age group, and a majority of individuals who had less than 8 years of schooling and had low professional qualifications. CONCLUSIONS: High rates of AIDS/tuberculosis cases at our hospital indicate the need for better attention towards early detection of tuberculosis, especially in its extrapulmonary form. Since the population that attends this hospital tends to be of a lower socioeconomic status, better management of AIDS and tuberculosis is required to increase the rates of treatment adherence and thus lower the social costs.

  15. Psychogenic Tremor: A Video Guide to Its Distinguishing Features

    Directory of Open Access Journals (Sweden)

    Joseph Jankovic

    2014-08-01

    Full Text Available Background: Psychogenic tremor is the most common psychogenic movement disorder. It has characteristic clinical features that can help distinguish it from other tremor disorders. There is no diagnostic gold standard and the diagnosis is based primarily on clinical history and examination. Despite proposed diagnostic criteria, the diagnosis of psychogenic tremor can be challenging. While there are numerous studies evaluating psychogenic tremor in the literature, there are no publications that provide a video/visual guide that demonstrate the clinical characteristics of psychogenic tremor. Educating clinicians about psychogenic tremor will hopefully lead to earlier diagnosis and treatment. Methods: We selected videos from the database at the Parkinson's Disease Center and Movement Disorders Clinic at Baylor College of Medicine that illustrate classic findings supporting the diagnosis of psychogenic tremor.Results: We include 10 clinical vignettes with accompanying videos that highlight characteristic clinical signs of psychogenic tremor including distractibility, variability, entrainability, suggestibility, and coherence.Discussion: Psychogenic tremor should be considered in the differential diagnosis of patients presenting with tremor, particularly if it is of abrupt onset, intermittent, variable and not congruous with organic tremor. The diagnosis of psychogenic tremor, however, should not be simply based on exclusion of organic tremor, such as essential, parkinsonian, or cerebellar tremor, but on positive criteria demonstrating characteristic features. Early recognition and management are critical for good long-term outcome.

  16. Computed Tomography and Magnetic Resonance Features of Renal Ewing Sarcoma

    International Nuclear Information System (INIS)

    Ekram, T.; Elsayes, K.M.; Cohan, R.H.; Francis, I.R.

    2008-01-01

    Ewing sarcoma (ES) is a rare malignant tumor that primarily involves long and flat bones but can develop in almost any bone or soft tissue. ES accounts for 2.3-3.5% of tumors in patients under the age of 19, and is rarely found in the adult population. Sarcomas, in general, account for less than 1% of tumors in adults. Several reports of renal ES have been described in the pediatric population, but only a few cases have been described in the adult population. To the best of our knowledge, fewer than 10 cases of renal Ewing sarcoma in adults have been described in the English literature. None of these cases described the computed tomography (CT) and magnetic resonance imaging (MRI) features. We report a case of a 46-year-old woman, including CT and MRI characteristics

  17. Assessment of Vegetation Variation on Primarily Creation Zones of the Dust Storms Around the Euphrates Using Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Jamil Amanollahi

    2012-06-01

    Full Text Available Recently, period frequency and effect domain of the dust storms that enter Iran from Iraq have increased. In this study, in addition to detecting the creation zones of the dust storms, the effect of vegetation cover variation on their creation was investigated using remote sensing. Moderate resolution image Spectroradiometer (MODIS and Landsat Thematic Mapper (TM5 have been utilized to identify the primarily creation zones of the dust storms and to assess the vegetation cover variation, respectively. Vegetation cover variation was studied using Normalized Differences Vegetation Index (NDVI obtained from band 3 and band 4 of the Landsate satellite. The results showed that the surrounding area of the Euphrates in Syria, the desert in the vicinity of this river in Iraq, including the deserts of Alanbar Province, and the north deserts of Saudi Arabia are the primarily creation zones of the dust storms entering west and south west of Iran. The results of NDVI showed that excluding the deserts in the border of Syria and Iraq, the area with very weak vegetation cover have increased between 2.44% and 20.65% from 1991 to 2009. In the meanwhile, the retention pound surface areas in the south deserts of Syria as well as the deserts in its border with Iraq have decreased 6320 and 4397 hectares, respectively. As it can be concluded from the findings, one of the main environmental parameters initiating these dust storms is the decrease in the vegetation cover in their primarily creation zones.

  18. Analytical Features: A Knowledge-Based Approach to Audio Feature Generation

    Directory of Open Access Journals (Sweden)

    Pachet François

    2009-01-01

    Full Text Available We present a feature generation system designed to create audio features for supervised classification tasks. The main contribution to feature generation studies is the notion of analytical features (AFs, a construct designed to support the representation of knowledge about audio signal processing. We describe the most important aspects of AFs, in particular their dimensional type system, on which are based pattern-based random generators, heuristics, and rewriting rules. We show how AFs generalize or improve previous approaches used in feature generation. We report on several projects using AFs for difficult audio classification tasks, demonstrating their advantage over standard audio features. More generally, we propose analytical features as a paradigm to bring raw signals into the world of symbolic computation.

  19. Novel Fluorinated Indanone, Tetralone and Naphthone Derivatives: Synthesis and Unique Structural Features

    Directory of Open Access Journals (Sweden)

    Joseph C. Sloop

    2012-02-01

    Full Text Available Several fluorinated and trifluoromethylated indanone, tetralone and naphthone derivatives have been prepared via Claisen condensations and selective fluorinations in yields ranging from 22–60%. In addition, we report the synthesis of new, selectively fluorinated bindones in yields ranging from 72–92%. Of particular interest is the fluorination and trifluoroacetylation regiochemistry observed in these fluorinated products. We also note unusual transformations including a novel one pot, dual trifluoroacetylation, trifluoroacetylnaphthone synthesis via a deacetylation as well as an acetyl-trifluoroacetyl group exchange. Solid-state structural features exhibited by these compounds were investigated using crystallographic methods. Crystallographic results, supported by spectroscopic data, show that trifluoroacetylated ketones prefer a chelated cis-enol form whereas fluorinated bindone products exist primarily as the cross-conjugated triketo form.

  20. Downstream Antisense Transcription Predicts Genomic Features That Define the Specific Chromatin Environment at Mammalian Promoters.

    Directory of Open Access Journals (Sweden)

    Christopher A Lavender

    2016-08-01

    Full Text Available Antisense transcription is a prevalent feature at mammalian promoters. Previous studies have primarily focused on antisense transcription initiating upstream of genes. Here, we characterize promoter-proximal antisense transcription downstream of gene transcription starts sites in human breast cancer cells, investigating the genomic context of downstream antisense transcription. We find extensive correlations between antisense transcription and features associated with the chromatin environment at gene promoters. Antisense transcription downstream of promoters is widespread, with antisense transcription initiation observed within 2 kb of 28% of gene transcription start sites. Antisense transcription initiates between nucleosomes regularly positioned downstream of these promoters. The nucleosomes between gene and downstream antisense transcription start sites carry histone modifications associated with active promoters, such as H3K4me3 and H3K27ac. This region is bound by chromatin remodeling and histone modifying complexes including SWI/SNF subunits and HDACs, suggesting that antisense transcription or resulting RNA transcripts contribute to the creation and maintenance of a promoter-associated chromatin environment. Downstream antisense transcription overlays additional regulatory features, such as transcription factor binding, DNA accessibility, and the downstream edge of promoter-associated CpG islands. These features suggest an important role for antisense transcription in the regulation of gene expression and the maintenance of a promoter-associated chromatin environment.

  1. Featureous: infrastructure for feature-centric analysis of object-oriented software

    DEFF Research Database (Denmark)

    Olszak, Andrzej; Jørgensen, Bo Nørregaard

    2010-01-01

    The decentralized nature of collaborations between objects in object-oriented software makes it difficult to understand how user-observable program features are implemented and how their implementations relate to each other. It is worthwhile to improve this situation, since feature-centric program...... understanding and modification are essential during software evolution and maintenance. In this paper, we present an infrastructure built on top of the NetBeans IDE called Featureous that allows for rapid construction of tools for feature-centric analysis of object-oriented software. Our infrastructure...... encompasses a lightweight feature location mechanism, a number of analytical views and an API allowing for addition of third-party extensions. To form a common conceptual framework for future feature-centric extensions, we propose to structure feature centric analysis along three dimensions: perspective...

  2. Temporal integration of loudness in listeners with hearing losses of primarily cochlear origin

    DEFF Research Database (Denmark)

    Buus, Søren; Florentine, Mary; Poulsen, Torben

    1999-01-01

    To investigate how hearing loss of primarily cochlear origin affects the loudness of brief tones, loudness matches between 5- and 200-ms tones were obtained as a function of level for 15 listeners with cochlear impairments and for seven age-matched controls. Three frequencies, usually 0.5, 1, and 4...... of temporal integration—defined as the level difference between equally loud short and long tones—varied nonmonotonically with level and was largest at moderate levels. No consistent effect of frequency was apparent. The impaired listeners varied widely, but most showed a clear effect of level on the amount...... of temporal integration. Overall, their results appear consistent with expectations based on knowledge of the general properties of their loudness-growth functions and the equal-loudness-ratio hypothesis, which states that the loudness ratio between equal-SPL long and brief tones is the same at all SPLs...

  3. Feature Article

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education. Feature Article. Articles in Resonance – Journal of Science Education. Volume 1 Issue 1 January 1996 pp 80-85 Feature Article. What's New in Computers Windows 95 · Vijnan Shastri · More Details Fulltext PDF. Volume 1 Issue 1 January 1996 pp 86-89 Feature ...

  4. Featureous: A Tool for Feature-Centric Analysis of Java Software

    DEFF Research Database (Denmark)

    Olszak, Andrzej; Jørgensen, Bo Nørregaard

    2010-01-01

    Feature-centric comprehension of source code is necessary for incorporating user-requested modifications during software evolution and maintenance. However, such comprehension is difficult to achieve in case of large object-oriented programs due to the size, complexity, and implicit character...... of mappings between features and source code. To support programmers in overcoming these difficulties, we present a feature-centric analysis tool, Featureous. Our tool extends the NetBeans IDE with mechanisms for efficient location of feature implementations in legacy source code, and an extensive analysis...

  5. Distinct neural networks for target feature versus dimension changes in visual search, as revealed by EEG and fMRI.

    Science.gov (United States)

    Becker, Stefanie I; Grubert, Anna; Dux, Paul E

    2014-11-15

    In visual search, responses are slowed, from one trial to the next, both when the target dimension changes (e.g., from a color target to a size target) and when the target feature changes (e.g., from a red target to a green target) relative to being repeated across trials. The present study examined whether such feature and dimension switch costs can be attributed to the same underlying mechanism(s). Contrary to this contention, an EEG study showed that feature changes influenced visual selection of the target (i.e., delayed N2pc onset), whereas dimension changes influenced the later process of response selection (i.e., delayed s-LRP onset). An fMRI study provided convergent evidence for the two-system view: Compared with repetitions, feature changes led to increased activation in the occipital cortex, and superior and inferior parietal lobules, which have been implicated in spatial attention. By contrast, dimension changes led to activation of a fronto-posterior network that is primarily linked with response selection (i.e., pre-motor cortex, supplementary motor area and frontal areas). Taken together, the results suggest that feature and dimension switch costs are based on different processes. Specifically, whereas target feature changes delay attention shifts to the target, target dimension changes interfere with later response selection operations. Crown Copyright © 2014. Published by Elsevier Inc. All rights reserved.

  6. Computed Tomography Features of Pulmonary Nocardiosis in Immunocompromised and Immunocompetent Patients

    International Nuclear Information System (INIS)

    Mehrian, Payam; Esfandiari, Ehsan; Karimi, Mohammad Ali; Memari, Behzad

    2015-01-01

    Nocardiosis primarily occurs in the setting of immunocompromising conditions. However, it may also occur in immunocompetent patients. We described computed tomography features of pulmonary nocardiosis and compared immunocompetent and immunocompromised patients. CT images of 25 patients (Mean age of 39.5 years; 76% male) with pulmonary nocardiosis proved by bronchoalveolar lavage or biopsy were reviewed by two experienced pulmonary radiologists and detailed findings were reported on. Fourteen patients (56%) were immunocompetent, while 44% had an underlying immunocompromising condition, including chronic granulomatous disease (CGD) (n=4), diabetes mellitus (DM) (n=2), malignancy (n=2), HIV (n=1), concomitant CGD and DM (n=1), and steroid therapy for nephrotic syndrome (n=1). Most patients had bilateral involvement with no zonal predominance. Multiple pulmonary nodules (96%) were the most common CT findings, followed by consolidation (76%) and cavity (52%). Other findings included bronchiectasis (48%), pleural thickening (40%), ground glass opacity (32%), mass-like consolidation (20%), intrathoracic lymphadenopathy (16%), pleural effusion (12%), reticular infiltration (4%), and pericardial effusion (4%). There was no statistically significant difference in the CT findings of immunocompromised and immunocompetent groups. Pulmonary nocardiosis presents mainly as multiple pulmonary nodules, consolidations, and cavity in both immunocompromised and immunocompetent patients. However, these features are more suggestive of nocardiosis in the setting of an underling immunocompromised condition

  7. Fault-tolerant feature-based estimation of space debris rotational motion during active removal missions

    Science.gov (United States)

    Biondi, Gabriele; Mauro, Stefano; Pastorelli, Stefano; Sorli, Massimo

    2018-05-01

    One of the key functionalities required by an Active Debris Removal mission is the assessment of the target kinematics and inertial properties. Passive sensors, such as stereo cameras, are often included in the onboard instrumentation of a chaser spacecraft for capturing sequential photographs and for tracking features of the target surface. A plenty of methods, based on Kalman filtering, are available for the estimation of the target's state from feature positions; however, to guarantee the filter convergence, they typically require continuity of measurements and the capability of tracking a fixed set of pre-defined features of the object. These requirements clash with the actual tracking conditions: failures in feature detection often occur and the assumption of having some a-priori knowledge about the shape of the target could be restrictive in certain cases. The aim of the presented work is to propose a fault-tolerant alternative method for estimating the angular velocity and the relative magnitudes of the principal moments of inertia of the target. Raw data regarding the positions of the tracked features are processed to evaluate corrupted values of a 3-dimentional parameter which entirely describes the finite screw motion of the debris and which primarily is invariant on the particular set of considered features of the object. Missing values of the parameter are completely restored exploiting the typical periodicity of the rotational motion of an uncontrolled satellite: compressed sensing techniques, typically adopted for recovering images or for prognostic applications, are herein used in a completely original fashion for retrieving a kinematic signal that appears sparse in the frequency domain. Due to its invariance about the features, no assumptions are needed about the target's shape and continuity of the tracking. The obtained signal is useful for the indirect evaluation of an attitude signal that feeds an unscented Kalman filter for the estimation of

  8. Definitions of engineered safety features and related features for nuclear power plants

    International Nuclear Information System (INIS)

    1986-01-01

    In light water moderated, light water cooled nuclear power plants, definitions are given of engineered safety features which are designed to suppress or prevent dispersion of radioactive materials due to damage etc. of fuel at the times of power plant failures, and of related features which are designed to actuate or operate the engineered safety features. Contents are the following: scope of engineered safety features and of related features; classification of engineered safety features (direct systems and indirect systems) and of related features (auxiliaries, emergency power supply, and protective means). (Mori, K.)

  9. A database of semantic features for chosen concepts (Attested in 8- to 10-year-old Czech pupils

    Directory of Open Access Journals (Sweden)

    Konečná Kristýna

    2017-06-01

    Full Text Available In this paper, a database of semantic features is presented. 104 nominal concepts from 13 semantic categories were described by young Czech school children. They were asked to respond to the question “what is it, what does it mean?” by listing different kinds of properties for concepts in writing. Their responses were broken down into semantic features and the database was prepared using a set of pre-established rules. The method of database design, with an emphasis on the way features were recorded, is described in detail within this article. The data were statistically analysed and interpreted and the results along with database usage methodologies are discussed. The goal of this research is to produce a complex database to be used in future research relating to semantic features and therefore it has been published online for use by the wider academic community. At present, databases have been published based on data gathered from adult English and Czech speakers; however participation in this study was limited specifically to young Czech-speaking children. Thus, this database is characteristically unique as it provides important insight into this specific age and language group’s conceptual knowledge. The research is inspired primarily by research papers concerning semantic feature production obtained from adult English speakers (McRae, de Sa, and Seidenberg, 1997; McRae, Cree, Seidenberg, and McNorgan, 2005; Vinson and Vigliocco, 2008.

  10. Giordano Bruno crater on the Moon: Detection and Mapping of Hydration Features of Endogenic and/or Exogenic Nature

    Science.gov (United States)

    Saran Bhiravarasu, Sriram; Bhattacharya, Satadru; Chauhan, Prakash

    2017-10-01

    We analyze high resolution spectral and spatial data from the recent lunar missions and report the presence of strong hydration features within the inner flank, hummocky floor, ejecta and impact melt deposits of crater Giordano Bruno. Hydroxyl-bearing lithologies at Giordano Bruno are characterized primarily by a prominent absorption feature near 2800 nm, the band minima of which goes beyond 3000 nm. The hydration features are found to be associated with low-Ca pyroxene-bearing noritic lithologies along the inner crater flanks, whereas similar features are also seen within the hummocky crater floor in association with shocked plagioclase-bearing anorthositic lithology. Interestingly, the ejecta blanket is characterized by sharp, narrow features centered near 2800 nm similar to the features previously reported from Compton-Belkovich volcanic complex and central peak of crater Theophilus. The low-Ca pyroxene-bearing rock exposures within the crater inner flanks are characterized by both presence and absence of the hydration features. Enhanced hydration is also seen within the ejecta blanket covering the nearby Harkhebi K and J craters. We also analyze the impact melts and ejecta using radar images at regions interior and exterior to the Giordano Bruno crater rim.Anomalous behaviors of hydration feature associated with low-Ca pyroxene-rich exposures, its nature and occurrences within the impact melt sheets inside the crater along with the ejecta blankets could possibly indicate endogenic and/or exogenic nature of the observed hydration feature. Initial results indicate the presence of strongest hydration feature in the partially shadowed pole-facing slopes (with low-Ca pyroxene-bearing exposures) and its complete absence in the equator-facing sun-lit slopes. This hints at a possible exogenic origin, whereas the same feature occurring (with same mineral) under both sun-lit and shadowed conditions suggest it to be of magmatic origin. We propose that the heterogeneous

  11. Overlapping features of polymyositis and inclusion body myositis in HIV-infected patients

    Science.gov (United States)

    Lloyd, Thomas E.; Pinal-Fernandez, Iago; Michelle, E. Harlan; Christopher-Stine, Lisa; Pak, Katherine; Sacktor, Ned

    2017-01-01

    Objective: To characterize patients with myositis with HIV infection. Methods: All HIV-positive patients with myositis seen at the Johns Hopkins Myositis Center from 2003 to 2013 were included in this case series. Muscle biopsy features, weakness pattern, serum creatine kinase (CK) level, and anti–nucleotidase 1A (NT5C1A) status of HIV-positive patients with myositis were assessed. Results: Eleven of 1,562 (0.7%) patients with myositis were HIV-positive. Myositis was the presenting feature of HIV infection in 3 patients. Eight of 11 patients had weakness onset at age 45 years or less. The mean time from the onset of weakness to the diagnosis of myositis was 3.6 years (SD 3.2 years). The mean of the highest measured CK levels was 2,796 IU/L (SD 1,592 IU/L). On muscle biopsy, 9 of 10 (90%) had endomysial inflammation, 7 of 10 (70%) had rimmed vacuoles, and none had perifascicular atrophy. Seven of 11 (64%) patients were anti-NT5C1A-positive. Upon presentation, all had proximal and distal weakness. Five of 6 (83%) patients followed 1 year or longer on immunosuppressive therapy had improved proximal muscle strength. However, each eventually developed weakness primarily affecting wrist flexors, finger flexors, knee extensors, or ankle dorsiflexors. Conclusions: HIV-positive patients with myositis may present with some characteristic polymyositis features including young age at onset, very high CK levels, or proximal weakness that improves with treatment. However, all HIV-positive patients with myositis eventually develop features most consistent with inclusion body myositis, including finger and wrist flexor weakness, rimmed vacuoles on biopsy, or anti-NT5C1A autoantibodies. PMID:28283597

  12. Evaluation of design feature No.20 -- Ground support options

    International Nuclear Information System (INIS)

    Duan, F.

    2000-01-01

    Ground support options are primarily evaluated for emplacement drifts while ground support systems for non-emplacement openings such as access mains and ventilation drifts are not evaluated against LADS evaluation criteria in this report. Considerations include functional requirements for ground support, the use of a steel-lined system, and the feasibility of using an unlined ground support system principally with grouted rock bolts for permanent ground support. The feature evaluation also emphasizes the postclosure effects of ground support materials on waste isolation and the preclosure aspects such as durability, maintainability, constructibility, safety, engineering acceptability, and cost. This evaluation is to: (A) Review the existing analyses, reports, and studies regarding this design feature, and compile relevant information on performance characteristics. (B) Develop an appropriate evaluation approach for evaluating ground support options against evaluation criteria provided by the LADS team. (C) Evaluate ground support options not only for their preclosure performance in terms of drift stability, material durability, maintenance, constructibility, and cost, but also for their postclosure performance in terms of chemical effects of ground support materials (i.e., concrete, steel) on waste isolation and radionuclide transport. Specifically, the scope for ground support options evaluation include: (1) all steel-lined drifts (no cementitious materials), (2) unlined drifts with minimum cementitious materials (e.g., grout for rockbolts), and (3) concrete-lined drifts, with the focus on the postclosure acceptability evaluation. In addition, unlined drifts with zero cementitious materials (e.g., use of frictional bolts such as split sets, Swellex bolts) are briefly discussed. (D) Identify candidate ground support systems that have the potential to enhance the repository performance based on the feature evaluation. and (E) Provide conclusions and recommendations

  13. JCE Feature Columns

    Science.gov (United States)

    Holmes, Jon L.

    1999-05-01

    The Features area of JCE Online is now readily accessible through a single click from our home page. In the Features area each column is linked to its own home page. These column home pages also have links to them from the online Journal Table of Contents pages or from any article published as part of that feature column. Using these links you can easily find abstracts of additional articles that are related by topic. Of course, JCE Online+ subscribers are then just one click away from the entire article. Finding related articles is easy because each feature column "site" contains links to the online abstracts of all the articles that have appeared in the column. In addition, you can find the mission statement for the column and the email link to the column editor that I mentioned above. At the discretion of its editor, a feature column site may contain additional resources. As an example, the Chemical Information Instructor column edited by Arleen Somerville will have a periodically updated bibliography of resources for teaching and using chemical information. Due to the increase in the number of these resources available on the WWW, it only makes sense to publish this information online so that you can get to these resources with a simple click of the mouse. We expect that there will soon be additional information and resources at several other feature column sites. Following in the footsteps of the Chemical Information Instructor, up-to-date bibliographies and links to related online resources can be made available. We hope to extend the online component of our feature columns with moderated online discussion forums. If you have a suggestion for an online resource you would like to see included, let the feature editor or JCE Online (jceonline@chem.wisc.edu) know about it. JCE Internet Features JCE Internet also has several feature columns: Chemical Education Resource Shelf, Conceptual Questions and Challenge Problems, Equipment Buyers Guide, Hal's Picks, Mathcad

  14. Use of liquefaction-induced features for paleoseismic analysis - An overview of how seismic liquefaction features can be distinguished from other features and how their regional distribution and properties of source sediment can be used to infer the location and strength of Holocene paleo-earthquakes

    Science.gov (United States)

    Obermeier, S.F.

    1996-01-01

    Liquefaction features can be used in many field settings to estimate the recurrence interval and magnitude of strong earthquakes through much of the Holocene. These features include dikes, craters, vented sand, sills, and laterally spreading landslides. The relatively high seismic shaking level required for their formation makes them particularly valuable as records of strong paleo-earthquakes. This state-of-the-art summary for using liquefaction-induced features for paleoseismic interpretation and analysis takes into account both geological and geotechnical engineering perspectives. The driving mechanism for formation of the features is primarily the increased pore-water pressure associated with liquefaction of sand-rich sediment. The role of this mechanism is often supplemented greatly by the direct action of seismic shaking at the ground surface, which strains and breaks the clay-rich cap that lies immediately above the sediment that liquefied. Discussed in the text are the processes involved in formation of the features, as well as their morphology and characteristics in field settings. Whether liquefaction occurs is controlled mainly by sediment grain size, sediment packing, depth to the water table, and strength and duration of seismic shaking. Formation of recognizable features in the field generally requires a low-permeability cap above the sediment that liquefied. Field manifestations are controlled largely by the severity of liquefaction and the thickness and properties of the low-permeability cap. Criteria are presented for determining whether observed sediment deformation in the field originated by seismically induced liquefaction. These criteria have been developed mainly by observing historic effects of liquefaction in varied field settings. The most important criterion is that a seismic liquefaction origin requires widespread, regional development of features around a core area where the effects are most severe. In addition, the features must have a

  15. Principal Feature Analysis: A Multivariate Feature Selection Method for fMRI Data

    Directory of Open Access Journals (Sweden)

    Lijun Wang

    2013-01-01

    Full Text Available Brain decoding with functional magnetic resonance imaging (fMRI requires analysis of complex, multivariate data. Multivoxel pattern analysis (MVPA has been widely used in recent years. MVPA treats the activation of multiple voxels from fMRI data as a pattern and decodes brain states using pattern classification methods. Feature selection is a critical procedure of MVPA because it decides which features will be included in the classification analysis of fMRI data, thereby improving the performance of the classifier. Features can be selected by limiting the analysis to specific anatomical regions or by computing univariate (voxel-wise or multivariate statistics. However, these methods either discard some informative features or select features with redundant information. This paper introduces the principal feature analysis as a novel multivariate feature selection method for fMRI data processing. This multivariate approach aims to remove features with redundant information, thereby selecting fewer features, while retaining the most information.

  16. The development and characterization of a primarily mineral calcium phosphate - poly(epsilon-caprolactone) biocomposite

    Science.gov (United States)

    Dunkley, Ian Robert

    Orthopaedic reconstruction often involves the surgical introduction of structural implants that provide for rigid fixation, skeletal stabilization, and bone integration. The high stresses incurred by these implanted devices have historically limited material choices to metallic and select polymeric formulations. While mechanical requirements are achieved, these non-degradable materials do not participate actively in the remodeling of the skeleton and present the possibility of long-term failure or rejection. This is particularly relevant in cervical fusion, an orthopaedic procedure to treat damaged, degenerative or diseased intervertebral discs. A significant improvement on the available synthetic bone replacement/regeneration options for implants to treat these conditions in the cervical spine may be achieved with the development of primarily mineral biocomposites comprised of a bioactive ceramic matrix reinforced with a biodegradable polymer. Such a biocomposite may be engineered to possess the clinically required mechanical properties of a particular application, while maintaining the ability to be remodeled completely by the body. A biocomposite of Si-doped calcium phosphate (Si-CaP) and poly(epsilon-caprolactone) (PCL) was developed for application as such a synthetic bone material for potential use as a fusion device in the cervical spine. In this thesis, a method by which high mineral content Si-CaP/PCL biocomposites with interpenetrating matrices of mineral and polymer phases may be prepared will be demonstrated, in addition to the effects of the various preparation parameters on the biocomposite density, porosity and mechanical properties. This new technique by which dense, primarily ceramic Si-CaP/PCL biocomposites were prepared, allowed for the incorporation of mineral contents ranging between 45-97vol%. Polymer infiltration, accomplished solely by passive capillary uptake over several days, was found to be capable of fully infiltrating the microporosity

  17. Classification Influence of Features on Given Emotions and Its Application in Feature Selection

    Science.gov (United States)

    Xing, Yin; Chen, Chuang; Liu, Li-Long

    2018-04-01

    In order to solve the problem that there is a large amount of redundant data in high-dimensional speech emotion features, we analyze deeply the extracted speech emotion features and select better features. Firstly, a given emotion is classified by each feature. Secondly, the recognition rate is ranked in descending order. Then, the optimal threshold of features is determined by rate criterion. Finally, the better features are obtained. When applied in Berlin and Chinese emotional data set, the experimental results show that the feature selection method outperforms the other traditional methods.

  18. Millennial Filipino Student Engagement Analyzer Using Facial Feature Classification

    Science.gov (United States)

    Manseras, R.; Eugenio, F.; Palaoag, T.

    2018-03-01

    Millennials has been a word of mouth of everybody and a target market of various companies nowadays. In the Philippines, they comprise one third of the total population and most of them are still in school. Having a good education system is important for this generation to prepare them for better careers. And a good education system means having quality instruction as one of the input component indicators. In a classroom environment, teachers use facial features to measure the affect state of the class. Emerging technologies like Affective Computing is one of today’s trends to improve quality instruction delivery. This, together with computer vision, can be used in analyzing affect states of the students and improve quality instruction delivery. This paper proposed a system of classifying student engagement using facial features. Identifying affect state, specifically Millennial Filipino student engagement, is one of the main priorities of every educator and this directed the authors to develop a tool to assess engagement percentage. Multiple face detection framework using Face API was employed to detect as many student faces as possible to gauge current engagement percentage of the whole class. The binary classifier model using Support Vector Machine (SVM) was primarily set in the conceptual framework of this study. To achieve the most accuracy performance of this model, a comparison of SVM to two of the most widely used binary classifiers were tested. Results show that SVM bested RandomForest and Naive Bayesian algorithms in most of the experiments from the different test datasets.

  19. Nitric oxide circulates in mammalian plasma primarily as an S-nitroso adduct of serum albumin.

    Science.gov (United States)

    Stamler, J S; Jaraki, O; Osborne, J; Simon, D I; Keaney, J; Vita, J; Singel, D; Valeri, C R; Loscalzo, J

    1992-01-01

    We have recently shown that nitric oxide or authentic endothelium-derived relaxing factor generated in a biologic system reacts in the presence of specific protein thiols to form S-nitrosoprotein derivatives that have endothelium-derived relaxing factor-like properties. The single free cysteine of serum albumin, Cys-34, is particularly reactive toward nitrogen oxides (most likely nitrosonium ion) under physiologic conditions, primarily because of its anomalously low pK; given its abundance in plasma, where it accounts for approximately 0.5 mM thiol, we hypothesized that this plasma protein serves as a reservoir for nitric oxide produced by the endothelial cell. To test this hypothesis, we developed a methodology, which involves UV photolytic cleavage of the S--NO bond before reaction with ozone for chemiluminescence detection, with which to measure free nitric oxide, S-nitrosothiols, and S-nitrosoproteins in biologic systems. We found that human plasma contains approximately 7 microM S-nitrosothiols, of which 96% are S-nitrosoproteins, 82% of which is accounted for by S-nitroso-serum albumin. By contrast, plasma levels of free nitric oxide are only in the 3-nM range. In rabbits, plasma S-nitrosothiols are present at approximately 1 microM; 60 min after administration of NG-monomethyl-L-arginine at 50 mg/ml, a selective and potent inhibitor of nitric oxide synthetases, S-nitrosothiols decreased by approximately 40% (greater than 95% of which were accounted for by S-nitrosoproteins, and approximately 80% of which was S-nitroso-serum albumin); this decrease was accompanied by a concomitant increase in mean arterial blood pressure of 22%. These data suggest that naturally produced nitric oxide circulates in plasma primarily complexed in S-nitrosothiol species, principal among which is S-nitroso-serum albumin. This abundant, relatively long-lived adduct likely serves as a reservoir with which plasma levels of highly reactive, short-lived free nitric oxide can be

  20. A Novel Approach for Automatic Machining Feature Recognition with Edge Blend Feature

    OpenAIRE

    Keong Chen Wong; Yusof Yusri

    2017-01-01

    This paper presents an algorithm for efficiently recognizing and determining the convexity of an edge blend feature. The algorithm first recognizes all of the edge blend features from the Boundary Representation of a part; then a series of convexity test have been run on the recognized edge blend features. The novelty of the presented algorithm lies in, instead of each recognized blend feature is suppressed as most of researchers did, the recognized blend features of this research are gone th...

  1. Nanoparticles affect PCR primarily via surface interactions with PCR components: using amino-modified silica-coated magnetic nanoparticles as a main model

    Science.gov (United States)

    Nanomaterials have been widely reported to affect the polymerase chain reaction (PCR). However, many studies in which these effects were observed were not comprehensive, and many of the proposed mechanisms have been primarily speculative. In this work, we used amino-modified silica-coated magnetic n...

  2. Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

    Science.gov (United States)

    Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

    2018-02-05

    Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. The Serotonin Transporter Undergoes Constitutive Internalization and Is Primarily Sorted to Late Endosomes and Lysosomal Degradation*

    Science.gov (United States)

    Rahbek-Clemmensen, Troels; Bay, Tina; Eriksen, Jacob; Gether, Ulrik; Jørgensen, Trine Nygaard

    2014-01-01

    The serotonin transporter (SERT) plays a critical role in regulating serotonin signaling by mediating reuptake of serotonin from the extracellular space. The molecular and cellular mechanisms controlling SERT levels in the membrane remain poorly understood. To study trafficking of the surface resident SERT, two functional epitope-tagged variants were generated. Fusion of a FLAG-tagged one-transmembrane segment protein Tac to the SERT N terminus generated a transporter with an extracellular epitope suited for trafficking studies (TacSERT). Likewise, a construct with an extracellular antibody epitope was generated by introducing an HA (hemagglutinin) tag in the extracellular loop 2 of SERT (HA-SERT). By using TacSERT and HA-SERT in antibody-based internalization assays, we show that SERT undergoes constitutive internalization in a dynamin-dependent manner. Confocal images of constitutively internalized SERT demonstrated that SERT primarily co-localized with the late endosomal/lysosomal marker Rab7, whereas little co-localization was observed with the Rab11, a marker of the “long loop” recycling pathway. This sorting pattern was distinct from that of a prototypical recycling membrane protein, the β2-adrenergic receptor. Furthermore, internalized SERT co-localized with the lysosomal marker LysoTracker and not with transferrin. The sorting pattern was further confirmed by visualizing internalization of SERT using the fluorescent cocaine analog JHC1-64 and by reversible and pulse-chase biotinylation assays showing evidence for lysosomal degradation of the internalized transporter. Finally, we found that SERT internalized in response to stimulation with 12-myristate 13-acetate co-localized primarily with Rab7- and LysoTracker-positive compartments. We conclude that SERT is constitutively internalized and that the internalized transporter is sorted mainly to degradation. PMID:24973209

  4. Efficient transfection of DNA into primarily cultured rat sertoli cells by electroporation.

    Science.gov (United States)

    Li, Fuping; Yamaguchi, Kohei; Okada, Keisuke; Matsushita, Kei; Enatsu, Noritoshi; Chiba, Koji; Yue, Huanxun; Fujisawa, Masato

    2013-03-01

    The expression of exogenous DNA in Sertoli cells is essential for studying its functional genomics, pathway analysis, and medical applications. Electroporation is a valuable tool for nucleic acid delivery, even in primarily cultured cells, which are considered difficult to transfect. In this study, we developed an optimized protocol for electroporation-based transfection of Sertoli cells and compared its efficiency with conventional lipofection. Sertoli cells were transfected with pCMV-GFP plasmid by square-wave electroporation under different conditions. After transfection of plasmid into Sertoli cells, enhanced green fluorescent protein (EGFP) expression could be easily detected by fluorescent microscopy, and cell survival was evaluated by dye exclusion assay using Trypan blue. In terms of both cell survival and the percentage expressing EGFP, 250 V was determined to produce the greatest number of transiently transfected cells. Keeping the voltage constant (250 V), relatively high cell survival (76.5% ± 3.4%) and transfection efficiency (30.6% ± 5.6%) were observed with a pulse length of 20 μm. The number of pulses significantly affected cell survival and EGFP expression (P transfection methods, the transfection efficiency of electroporation (21.5% ± 5.7%) was significantly higher than those of Lipofectamine 2000 (2.9% ± 1.0%) and Effectene (1.9% ± 0.8%) in this experiment (P transfection of Sertoli cells.

  5. Unsupervised Feature Subset Selection

    DEFF Research Database (Denmark)

    Søndberg-Madsen, Nicolaj; Thomsen, C.; Pena, Jose

    2003-01-01

    This paper studies filter and hybrid filter-wrapper feature subset selection for unsupervised learning (data clustering). We constrain the search for the best feature subset by scoring the dependence of every feature on the rest of the features, conjecturing that these scores discriminate some ir...... irrelevant features. We report experimental results on artificial and real data for unsupervised learning of naive Bayes models. Both the filter and hybrid approaches perform satisfactorily....

  6. When do letter features migrate? A boundary condition for feature-integration theory.

    Science.gov (United States)

    Butler, B E; Mewhort, D J; Browse, R A

    1991-01-01

    Feature-integration theory postulates that a lapse of attention will allow letter features to change position and to recombine as illusory conjunctions (Treisman & Paterson, 1984). To study such errors, we used a set of uppercase letters known to yield illusory conjunctions in each of three tasks. The first, a bar-probe task, showed whole-character mislocations but not errors based on feature migration and recombination. The second, a two-alternative forced-choice detection task, allowed subjects to focus on the presence or absence of subletter features and showed illusory conjunctions based on feature migration and recombination. The third was also a two-alternative forced-choice detection task, but we manipulated the subjects' knowledge of the shape of the stimuli: In the case-certain condition, the stimuli were always in uppercase, but in the case-uncertain condition, the stimuli could appear in either upper- or lowercase. Subjects in the case-certain condition produced illusory conjunctions based on feature recombination, whereas subjects in the case-uncertain condition did not. The results suggest that when subjects can view the stimuli as feature groups, letter features regroup as illusory conjunctions; when subjects encode the stimuli as letters, whole items may be mislocated, but subletter features are not. Thus, illusory conjunctions reflect the subject's processing strategy, rather than the architecture of the visual system.

  7. Featureous: an Integrated Approach to Location, Analysis and Modularization of Features in Java Applications

    DEFF Research Database (Denmark)

    Olszak, Andrzej

    , it is essential that features are properly modularized within the structural organization of software systems. Nevertheless, in many object-oriented applications, features are not represented explicitly. Consequently, features typically end up scattered and tangled over multiple source code units......, such as architectural layers, packages and classes. This lack of modularization is known to make application features difficult to locate, to comprehend and to modify in isolation from one another. To overcome these problems, this thesis proposes Featureous, a novel approach to location, analysis and modularization...... quantitative and qualitative results suggest that Featureous succeeds at efficiently locating features in unfamiliar codebases, at aiding feature-oriented comprehension and modification, and at improving modularization of features using Java packages....

  8. Innovations in individual feature history management - The significance of feature-based temporal model

    Science.gov (United States)

    Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

    2008-01-01

    A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

  9. Dependency Parsing with Transformed Feature

    Directory of Open Access Journals (Sweden)

    Fuxiang Wu

    2017-01-01

    Full Text Available Dependency parsing is an important subtask of natural language processing. In this paper, we propose an embedding feature transforming method for graph-based parsing, transform-based parsing, which directly utilizes the inner similarity of the features to extract information from all feature strings including the un-indexed strings and alleviate the feature sparse problem. The model transforms the extracted features to transformed features via applying a feature weight matrix, which consists of similarities between the feature strings. Since the matrix is usually rank-deficient because of similar feature strings, it would influence the strength of constraints. However, it is proven that the duplicate transformed features do not degrade the optimization algorithm: the margin infused relaxed algorithm. Moreover, this problem can be alleviated by reducing the number of the nearest transformed features of a feature. In addition, to further improve the parsing accuracy, a fusion parser is introduced to integrate transformed and original features. Our experiments verify that both transform-based and fusion parser improve the parsing accuracy compared to the corresponding feature-based parser.

  10. Tensor decomposition-based unsupervised feature extraction identifies candidate genes that induce post-traumatic stress disorder-mediated heart diseases.

    Science.gov (United States)

    Taguchi, Y-H

    2017-12-21

    Although post-traumatic stress disorder (PTSD) is primarily a mental disorder, it can cause additional symptoms that do not seem to be directly related to the central nervous system, which PTSD is assumed to directly affect. PTSD-mediated heart diseases are some of such secondary disorders. In spite of the significant correlations between PTSD and heart diseases, spatial separation between the heart and brain (where PTSD is primarily active) prevents researchers from elucidating the mechanisms that bridge the two disorders. Our purpose was to identify genes linking PTSD and heart diseases. In this study, gene expression profiles of various murine tissues observed under various types of stress or without stress were analyzed in an integrated manner using tensor decomposition (TD). Based upon the obtained features, ∼ 400 genes were identified as candidate genes that may mediate heart diseases associated with PTSD. Various gene enrichment analyses supported biological reliability of the identified genes. Ten genes encoding protein-, DNA-, or mRNA-interacting proteins-ILF2, ILF3, ESR1, ESR2, RAD21, HTT, ATF2, NR3C1, TP53, and TP63-were found to be likely to regulate expression of most of these ∼ 400 genes and therefore are candidate primary genes that cause PTSD-mediated heart diseases. Approximately 400 genes in the heart were also found to be strongly affected by various drugs whose known adverse effects are related to heart diseases and/or fear memory conditioning; these data support the reliability of our findings. TD-based unsupervised feature extraction turned out to be a useful method for gene selection and successfully identified possible genes causing PTSD-mediated heart diseases.

  11. The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

    Science.gov (United States)

    St-Yves, Ghislain; Naselaris, Thomas

    2017-06-20

    We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

  12. Development and Sensitivity Analysis of a Frost Risk model based primarily on freely distributed Earth Observation data

    Science.gov (United States)

    Louka, Panagiota; Petropoulos, George; Papanikolaou, Ioannis

    2015-04-01

    The ability to map the spatiotemporal distribution of extreme climatic conditions, such as frost, is a significant tool in successful agricultural management and decision making. Nowadays, with the development of Earth Observation (EO) technology, it is possible to obtain accurately, timely and in a cost-effective way information on the spatiotemporal distribution of frost conditions, particularly over large and otherwise inaccessible areas. The present study aimed at developing and evaluating a frost risk prediction model, exploiting primarily EO data from MODIS and ASTER sensors and ancillary ground observation data. For the evaluation of our model, a region in north-western Greece was selected as test site and a detailed sensitivity analysis was implemented. The agreement between the model predictions and the observed (remotely sensed) frost frequency obtained by MODIS sensor was evaluated thoroughly. Also, detailed comparisons of the model predictions were performed against reference frost ground observations acquired from the Greek Agricultural Insurance Organization (ELGA) over a period of 10-years (2000-2010). Overall, results evidenced the ability of the model to produce reasonably well the frost conditions, following largely explainable patterns in respect to the study site and local weather conditions characteristics. Implementation of our proposed frost risk model is based primarily on satellite imagery analysis provided nowadays globally at no cost. It is also straightforward and computationally inexpensive, requiring much less effort in comparison for example to field surveying. Finally, the method is adjustable to be potentially integrated with other high resolution data available from both commercial and non-commercial vendors. Keywords: Sensitivity analysis, frost risk mapping, GIS, remote sensing, MODIS, Greece

  13. Language Features and Culture Features on Short Message

    Institute of Scientific and Technical Information of China (English)

    王佳

    2013-01-01

    Mobile phone is regarded as“the fifth media”after newspaper,radio,TV and the Internet.The mobile phone short message further highlights the importance of written signs in communication.“The thumb revolution”is eagerly anticipating one kind of trend by the hand replace of mouth,sound substitute for the quiet around us. My paper will analyze the language features and the culture features of mobile phone short messages which are written in Chinese and English.

  14. FADD Expression as a Prognosticator in Early-Stage Glottic Squamous Cell Carcinoma of the Larynx Treated Primarily With Radiotherapy

    International Nuclear Information System (INIS)

    Schrijvers, Michiel L.; Pattje, Wouter J.; Slagter-Menkema, Lorian; Mastik, Mirjam F.; Gibcus, Johan H.; Langendijk, Johannes A.; Wal, Jacqueline E. van der; Laan, Bernard F.A.M. vn der; Schuuring, E.

    2012-01-01

    Purpose: We recently reported on the identification of the Fas-associated death domain (FADD) as a possible driver of the chromosome 11q13 amplicon and the association between increased FADD expression and disease-specific survival in advanced-stage laryngeal carcinoma. The aim of this study was to examine whether expression of FADD and its Ser194-phosphorylated isoform (pFADD) predicts local control in patients with early-stage glottic carcinoma primarily treated with radiotherapy only. Methods and Materials: Immunohistochemical staining for FADD and pFADD was performed on pretreatment biopsy specimens of 92 patients with T1–T2 glottic squamous cell carcinoma primarily treated with radiotherapy between 1996 and 2005. Cox regression analysis was used to correlate expression levels with local control. Results: High levels of pFADD were associated with significantly better local control (hazard ratio, 2.40; 95% confidence interval, 1.04–5.55; p = 0.040). FADD overexpression showed a trend toward better local control (hazard ratio, 3.656; 95% confidence interval, 0.853–15.663; p = 0.081). Multivariate Cox regression analysis showed that high pFADD expression was the best predictor of local control after radiotherapy. Conclusions: This study showed that expression of phosphorylated FADD is a new prognostic biomarker for better local control after radiotherapy in patients with early-stage glottic carcinomas.

  15. Feature selection for splice site prediction: A new method using EDA-based feature ranking

    Directory of Open Access Journals (Sweden)

    Rouzé Pierre

    2004-05-01

    Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

  16. Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

    Directory of Open Access Journals (Sweden)

    Jin-Jia Wang

    2015-01-01

    Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

  17. Estimating changes in riparian and channel features along the Trinity River downstream of Lewiston Dam, California, 1980 to 2011

    Science.gov (United States)

    Curtis, Jennifer A.

    2015-01-01

    Dam construction, flow diversion, and legacy landuse effects reduced the transport capacity, sediment supply, channel complexity and floodplain-connectivity along the Trinity River, CA below Lewiston Dam. This study documents the geomorphic evolution of the Trinity River Restoration Program’s intensively managed 65-km long restoration reach from 1980 to 2011. The nature and extent of riparian and channel changes were assessed using a series of geomorphic feature maps constructed from ortho-rectified photography acquired at low flow conditions in 1980, 1997, 2001, 2006, 2009, and 2011. Since 1980 there has been a general conversion of riparian to channel features and expansion of the active channel area. The primary mechanism for expansion of the active channel was bank erosion from 1980 to 1997 and channel widening was well distributed longitudinally throughout the study reach. Subsequent net bar accretion from 1997 to 2001, followed by slightly higher net bar scour from 2001 to 2006, occurred primarily in the central and lower reaches of the study area. In comparison, post-2006 bank and bar changes were spatially-limited to reaches with sufficient local transport capacity or sediment supply supported by gravel augmentation, mechanical channel rehabilitation, and tributary contributions to flow and sediment supply. A series of tributary floods in 1997, 1998 and 2006 were the primary factors leading to documented increases in channel complexity and floodplain connectivity. During the post-2006 period managed flow releases, in the absence of large magnitude tributary flooding, combined with gravel augmentation and mechanical restoration caused localized increases in sediment supply and transport capacity leading to smaller but measurable increases in channel complexity and floodplain connectivity primarily in the upper river below Lewiston Dam.

  18. Coding of visual object features and feature conjunctions in the human brain.

    Science.gov (United States)

    Martinovic, Jasna; Gruber, Thomas; Müller, Matthias M

    2008-01-01

    Object recognition is achieved through neural mechanisms reliant on the activity of distributed coordinated neural assemblies. In the initial steps of this process, an object's features are thought to be coded very rapidly in distinct neural assemblies. These features play different functional roles in the recognition process--while colour facilitates recognition, additional contours and edges delay it. Here, we selectively varied the amount and role of object features in an entry-level categorization paradigm and related them to the electrical activity of the human brain. We found that early synchronizations (approx. 100 ms) increased quantitatively when more image features had to be coded, without reflecting their qualitative contribution to the recognition process. Later activity (approx. 200-400 ms) was modulated by the representational role of object features. These findings demonstrate that although early synchronizations may be sufficient for relatively crude discrimination of objects in visual scenes, they cannot support entry-level categorization. This was subserved by later processes of object model selection, which utilized the representational value of object features such as colour or edges to select the appropriate model and achieve identification.

  19. Exterior orientation of CBERS-2B imagery using multi-feature control and orbital data

    Science.gov (United States)

    Marcato Junior, J.; Tommaselli, A. M. G.

    2013-05-01

    The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced.

  20. An object-oriented feature-based design system face-based detection of feature interactions

    International Nuclear Information System (INIS)

    Ariffin Abdul Razak

    1999-01-01

    This paper presents an object-oriented, feature-based design system which supports the integration of design and manufacture by ensuring that part descriptions fully account for any feature interactions. Manufacturing information is extracted from the feature descriptions in the form of volumes and Tool Access Directions, TADs. When features interact, both volumes and TADs are updated. This methodology has been demonstrated by developing a prototype system in which ACIS attributes are used to record feature information within the data structure of the solid model. The system implemented in the C++ programming language and embedded in a menu-driven X-windows user interface to the ACIS 3D Toolkit. (author)

  1. Feature-Based Retinal Image Registration Using D-Saddle Feature

    Directory of Open Access Journals (Sweden)

    Roziana Ramli

    2017-01-01

    Full Text Available Retinal image registration is important to assist diagnosis and monitor retinal diseases, such as diabetic retinopathy and glaucoma. However, registering retinal images for various registration applications requires the detection and distribution of feature points on the low-quality region that consists of vessels of varying contrast and sizes. A recent feature detector known as Saddle detects feature points on vessels that are poorly distributed and densely positioned on strong contrast vessels. Therefore, we propose a multiresolution difference of Gaussian pyramid with Saddle detector (D-Saddle to detect feature points on the low-quality region that consists of vessels with varying contrast and sizes. D-Saddle is tested on Fundus Image Registration (FIRE Dataset that consists of 134 retinal image pairs. Experimental results show that D-Saddle successfully registered 43% of retinal image pairs with average registration accuracy of 2.329 pixels while a lower success rate is observed in other four state-of-the-art retinal image registration methods GDB-ICP (28%, Harris-PIIFD (4%, H-M (16%, and Saddle (16%. Furthermore, the registration accuracy of D-Saddle has the weakest correlation (Spearman with the intensity uniformity metric among all methods. Finally, the paired t-test shows that D-Saddle significantly improved the overall registration accuracy of the original Saddle.

  2. Screening for Plant Features

    NARCIS (Netherlands)

    Heijden, van der G.W.A.M.; Polder, G.

    2015-01-01

    In this chapter, an overview of different plant features is given, from (sub)cellular to canopy level. A myriad of methods is available to measure these features using image analysis, and often, multiple methods can be used to measure the same feature. Several criteria are listed for choosing a

  3. Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

    Science.gov (United States)

    Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

    2017-11-01

    Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

  4. Perceptions of Mindfulness in a Low-income, Primarily African American Treatment-Seeking Sample.

    Science.gov (United States)

    Spears, Claire Adams; Houchins, Sean C; Bamatter, Wendy P; Barrueco, Sandra; Hoover, Diana Stewart; Perskaudas, Rokas

    2017-12-01

    Individuals with low socioeconomic status (SES) and members of racial/ethnic minority groups often experience profound disparities in mental health and physical well-being. Mindfulness-based interventions show promise for improving mood and health behaviors in higher-SES and non-Latino White populations. However, research is needed to explore what types of adaptations, if any, are needed to best support underserved populations. This study used qualitative methods to gain information about a) perceptions of mindfulness, b) experiences with meditation, c) barriers to practicing mindfulness, and d) recommendations for tailoring mindfulness-based interventions in a low-income, primarily African American treatment-seeking sample. Eight focus groups were conducted with 32 adults (16 men and 16 women) currently receiving services at a community mental health center. Most participants (91%) were African American. Focus group data were transcribed and analyzed using NVivo 10. A team of coders reviewed the transcripts to identify salient themes. Relevant themes included beliefs that mindfulness practice might improve mental health (e.g., managing stress and anger more effectively) and physical health (e.g., improving sleep and chronic pain, promoting healthier behaviors). Participants also discussed ways in which mindfulness might be consistent with, and even enhance, their religious and spiritual practices. Results could be helpful in tailoring mindfulness-based treatments to optimize feasibility and effectiveness for low-SES adults receiving mental health services.

  5. GOLD HULL AND INTERNODE2 encodes a primarily multifunctional cinnamyl-alcohol dehydrogenase in rice.

    Science.gov (United States)

    Zhang, Kewei; Qian, Qian; Huang, Zejun; Wang, Yiqin; Li, Ming; Hong, Lilan; Zeng, Dali; Gu, Minghong; Chu, Chengcai; Cheng, Zhukuan

    2006-03-01

    Lignin content and composition are two important agronomic traits for the utilization of agricultural residues. Rice (Oryza sativa) gold hull and internode phenotype is a classical morphological marker trait that has long been applied to breeding and genetics study. In this study, we have cloned the GOLD HULL AND INTERNODE2 (GH2) gene in rice using a map-based cloning approach. The result shows that the gh2 mutant is a lignin-deficient mutant, and GH2 encodes a cinnamyl-alcohol dehydrogenase (CAD). Consistent with this finding, extracts from roots, internodes, hulls, and panicles of the gh2 plants exhibited drastically reduced CAD activity and undetectable sinapyl alcohol dehydrogenase activity. When expressed in Escherichia coli, purified recombinant GH2 was found to exhibit strong catalytic ability toward coniferaldehyde and sinapaldehyde, while the mutant protein gh2 completely lost the corresponding CAD and sinapyl alcohol dehydrogenase activities. Further phenotypic analysis of the gh2 mutant plants revealed that the p-hydroxyphenyl, guaiacyl, and sinapyl monomers were reduced in almost the same ratio compared to the wild type. Our results suggest GH2 acts as a primarily multifunctional CAD to synthesize coniferyl and sinapyl alcohol precursors in rice lignin biosynthesis.

  6. Dissociation between Features and Feature Relations in Infant Memory: Effects of Memory Load.

    Science.gov (United States)

    Bhatt, Ramesh S.; Rovee-Collier, Carolyn

    1997-01-01

    Four experiments examined effects of the number of features and feature relations on learning and long-term memory in 3-month olds. Findings suggested that memory load size selectively constrained infants' long-term memory for relational information, suggesting that in infants, features and relations are psychologically distinct and that memory…

  7. Radiologic features of all-trans-retinoic acid syndrome (ATRAS) - case report

    International Nuclear Information System (INIS)

    Konarzewska, J.; Bianek-Bodzak, A.; Szatkowski, D.; Szarmach, D.

    2007-01-01

    ATRA Syndrome appears as a side effect of acute promyelocytic leukemia treatment with ATRA, vitamin A derivative. The etiopathogenesis of the syndrome remains unclear. Fever, generalized edema, pleural or pericardial effusion, respiratory distress, coagulation disorders and sometimes renal failure are the most common clinical symptoms of ATRAS. Radiological features of the syndrome are very diverse. Early diagnosis followed by introduction of appropriate treatment (corticosteroids) prevents worsening of the patients' condition and significantly reduces the risk of death. Although clinical symptomatology of ATRAS has been widely described, there are still few descriptions of its radiological manifestation. A 53-year-old female was referred to the Hematology Department for further detailed diagnostics and appropriate therapy from the district hospital, where she had been primarily admitted due to weakness, easy fatigue, loss of appetite and blood extravasations on the skin of the extremities. The patient's general condition on admission was assessed as quite good. Acute promyelocytic leukemia (AML M3 according to FAB classification) was diagnosed. The introduced treatment included ATRA. On the second day of treatment, the patient developed fever, dyspnea, generalized edema, and coagulation disorders increased. Chest X-ray findings reminded ARDS. The diagnosis of ATRAS was established, which resulted in ATRA withdrawal. After administration of corticosteroids, the patient's condition improved gradually within a few days. ATRA was reintroduced then, since the signs of leukemia had intensified. The patient remains in charge of the Hematology Department. Changes of chest X-ray pictures in AML patients treated with ATRA should be interpreted in clinical context due to lack of radiological features specific for ATRAS. (author)

  8. Depth estimation of features in video frames with improved feature matching technique using Kinect sensor

    Science.gov (United States)

    Sharma, Kajal; Moon, Inkyu; Kim, Sung Gaun

    2012-10-01

    Estimating depth has long been a major issue in the field of computer vision and robotics. The Kinect sensor's active sensing strategy provides high-frame-rate depth maps and can recognize user gestures and human pose. This paper presents a technique to estimate the depth of features extracted from video frames, along with an improved feature-matching method. In this paper, we used the Kinect camera developed by Microsoft, which captured color and depth images for further processing. Feature detection and selection is an important task for robot navigation. Many feature-matching techniques have been proposed earlier, and this paper proposes an improved feature matching between successive video frames with the use of neural network methodology in order to reduce the computation time of feature matching. The features extracted are invariant to image scale and rotation, and different experiments were conducted to evaluate the performance of feature matching between successive video frames. The extracted features are assigned distance based on the Kinect technology that can be used by the robot in order to determine the path of navigation, along with obstacle detection applications.

  9. Doubly sparse factor models for unifying feature transformation and feature selection

    International Nuclear Information System (INIS)

    Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato; Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko

    2010-01-01

    A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

  10. Doubly sparse factor models for unifying feature transformation and feature selection

    Energy Technology Data Exchange (ETDEWEB)

    Katahira, Kentaro; Okanoya, Kazuo; Okada, Masato [ERATO, Okanoya Emotional Information Project, Japan Science Technology Agency, Saitama (Japan); Matsumoto, Narihisa; Sugase-Miyamoto, Yasuko, E-mail: okada@k.u-tokyo.ac.j [Human Technology Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki (Japan)

    2010-06-01

    A number of unsupervised learning methods for high-dimensional data are largely divided into two groups based on their procedures, i.e., (1) feature selection, which discards irrelevant dimensions of the data, and (2) feature transformation, which constructs new variables by transforming and mixing over all dimensions. We propose a method that both selects and transforms features in a common Bayesian inference procedure. Our method imposes a doubly automatic relevance determination (ARD) prior on the factor loading matrix. We propose a variational Bayesian inference for our model and demonstrate the performance of our method on both synthetic and real data.

  11. Feature Import Vector Machine: A General Classifier with Flexible Feature Selection.

    Science.gov (United States)

    Ghosh, Samiran; Wang, Yazhen

    2015-02-01

    The support vector machine (SVM) and other reproducing kernel Hilbert space (RKHS) based classifier systems are drawing much attention recently due to its robustness and generalization capability. General theme here is to construct classifiers based on the training data in a high dimensional space by using all available dimensions. The SVM achieves huge data compression by selecting only few observations which lie close to the boundary of the classifier function. However when the number of observations are not very large (small n ) but the number of dimensions/features are large (large p ), then it is not necessary that all available features are of equal importance in the classification context. Possible selection of an useful fraction of the available features may result in huge data compression. In this paper we propose an algorithmic approach by means of which such an optimal set of features could be selected. In short, we reverse the traditional sequential observation selection strategy of SVM to that of sequential feature selection. To achieve this we have modified the solution proposed by Zhu and Hastie (2005) in the context of import vector machine (IVM), to select an optimal sub-dimensional model to build the final classifier with sufficient accuracy.

  12. Internal versus external features in triggering the brain waveforms for conjunction and feature faces in recognition.

    Science.gov (United States)

    Nie, Aiqing; Jiang, Jingguo; Fu, Qiao

    2014-08-20

    Previous research has found that conjunction faces (whose internal features, e.g. eyes, nose, and mouth, and external features, e.g. hairstyle and ears, are from separate studied faces) and feature faces (partial features of these are studied) can produce higher false alarms than both old and new faces (i.e. those that are exactly the same as the studied faces and those that have not been previously presented) in recognition. The event-related potentials (ERPs) that relate to conjunction and feature faces at recognition, however, have not been described as yet; in addition, the contributions of different facial features toward ERPs have not been differentiated. To address these issues, the present study compared the ERPs elicited by old faces, conjunction faces (the internal and the external features were from two studied faces), old internal feature faces (whose internal features were studied), and old external feature faces (whose external features were studied) with those of new faces separately. The results showed that old faces not only elicited an early familiarity-related FN400, but a more anterior distributed late old/new effect that reflected recollection. Conjunction faces evoked similar late brain waveforms as old internal feature faces, but not to old external feature faces. These results suggest that, at recognition, old faces hold higher familiarity than compound faces in the profiles of ERPs and internal facial features are more crucial than external ones in triggering the brain waveforms that are characterized as reflecting the result of familiarity.

  13. The ir emission features: Emission from PAH (Polycyclic Aromatic Hydrocarbons) molecules and amorphous carbon particles

    Energy Technology Data Exchange (ETDEWEB)

    Allamandola, L.J.; Tielens, A.G.G.M.; Barker, J.R.

    1986-01-01

    PAHs can have several forms in the interstellar medium. To assess the importance of each requires the availability of a collection of high quality, complete mid-ir interstellar emission spectra, a collection of laboratory spectra of PAH samples prepared under realistic conditions and a firm understanding of the microscopic emission mechanism. Given what we currently know about PAHs, the spectroscopic data suggests that there are at least two components which contribute to the interstellar emission spectrum: free molecule sized PAHs producing the narrow features and amorphous carbon particles (which are primarily made up of an irregular ''lattice'' of PAHs) contributing to the broad underlying components. An exact treatment of the ir fluorescence from highly vibrationally excited large molecules shows that species containing between 20 and 30 carbon atoms are responsible for the narrow features, although the spectra match more closely with the spectra of amorphous carbon particles. Since little is known about the spectroscopic properties of free PAHs and PAH clusters, much laboratory work is called for in conjunction with an observational program which focuses on the spatial characteristics of the spectra. In this way the distribution and evolution of carbon from molecule to particle can be traced. 38 refs., 9 figs.

  14. The ir emission features: Emission from PAH [Polycyclic Aromatic Hydrocarbons] molecules and amorphous carbon particles

    International Nuclear Information System (INIS)

    Allamandola, L.J.; Tielens, A.G.G.M.; Barker, J.R.

    1986-01-01

    PAHs can have several forms in the interstellar medium. To assess the importance of each requires the availability of a collection of high quality, complete mid-ir interstellar emission spectra, a collection of laboratory spectra of PAH samples prepared under realistic conditions and a firm understanding of the microscopic emission mechanism. Given what we currently know about PAHs, the spectroscopic data suggests that there are at least two components which contribute to the interstellar emission spectrum: free molecule sized PAHs producing the narrow features and amorphous carbon particles (which are primarily made up of an irregular ''lattice'' of PAHs) contributing to the broad underlying components. An exact treatment of the ir fluorescence from highly vibrationally excited large molecules shows that species containing between 20 and 30 carbon atoms are responsible for the narrow features, although the spectra match more closely with the spectra of amorphous carbon particles. Since little is known about the spectroscopic properties of free PAHs and PAH clusters, much laboratory work is called for in conjunction with an observational program which focuses on the spatial characteristics of the spectra. In this way the distribution and evolution of carbon from molecule to particle can be traced. 38 refs., 9 figs

  15. Attentional Selection of Feature Conjunctions Is Accomplished by Parallel and Independent Selection of Single Features.

    Science.gov (United States)

    Andersen, Søren K; Müller, Matthias M; Hillyard, Steven A

    2015-07-08

    Experiments that study feature-based attention have often examined situations in which selection is based on a single feature (e.g., the color red). However, in more complex situations relevant stimuli may not be set apart from other stimuli by a single defining property but by a specific combination of features. Here, we examined sustained attentional selection of stimuli defined by conjunctions of color and orientation. Human observers attended to one out of four concurrently presented superimposed fields of randomly moving horizontal or vertical bars of red or blue color to detect brief intervals of coherent motion. Selective stimulus processing in early visual cortex was assessed by recordings of steady-state visual evoked potentials (SSVEPs) elicited by each of the flickering fields of stimuli. We directly contrasted attentional selection of single features and feature conjunctions and found that SSVEP amplitudes on conditions in which selection was based on a single feature only (color or orientation) exactly predicted the magnitude of attentional enhancement of SSVEPs when attending to a conjunction of both features. Furthermore, enhanced SSVEP amplitudes elicited by attended stimuli were accompanied by equivalent reductions of SSVEP amplitudes elicited by unattended stimuli in all cases. We conclude that attentional selection of a feature-conjunction stimulus is accomplished by the parallel and independent facilitation of its constituent feature dimensions in early visual cortex. The ability to perceive the world is limited by the brain's processing capacity. Attention affords adaptive behavior by selectively prioritizing processing of relevant stimuli based on their features (location, color, orientation, etc.). We found that attentional mechanisms for selection of different features belonging to the same object operate independently and in parallel: concurrent attentional selection of two stimulus features is simply the sum of attending to each of those

  16. The relation between rumination and temporal features of emotion intensity.

    Science.gov (United States)

    Résibois, Maxime; Kalokerinos, Elise K; Verleysen, Gregory; Kuppens, Peter; Van Mechelen, Iven; Fossati, Philippe; Verduyn, Philippe

    2018-03-01

    Intensity profiles of emotional experience over time have been found to differ primarily in explosiveness (i.e. whether the profile has a steep vs. a gentle start) and accumulation (i.e. whether intensity increases over time vs. goes back to baseline). However, the determinants of these temporal features remain poorly understood. In two studies, we examined whether emotion regulation strategies are predictive of the degree of explosiveness and accumulation of negative emotional episodes. Participants were asked to draw profiles reflecting changes in the intensity of emotions elicited either by negative social feedback in the lab (Study 1) or by negative events in daily life (Study 2). In addition, trait (Study 1 & 2), and state (Study 2) usage of a set of emotion regulation strategies was assessed. Multilevel analyses revealed that trait rumination (especially the brooding component) was positively associated with emotion accumulation (Study 1 & 2). State rumination was also positively associated with emotion accumulation and, to a lesser extent, with emotion explosiveness (Study 2). These results provide support for emotion regulation theories, which hypothesise that rumination is a central mechanism underlying the maintenance of negative emotions.

  17. Evaluating the Stability of Feature Selectors that Optimize Feature Subset Cardinality

    Czech Academy of Sciences Publication Activity Database

    Somol, Petr; Novovičová, Jana

    2008-01-01

    Roč. 2008, č. 5342 (2008), s. 956-966 ISSN 0302-9743. [Joint IAPR International Workshops SSPR 2008 and SPR 2008. Orlando , 04.12.2008-06.12.2008] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA ČR GA102/07/1594 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Feature selection * stability * relative weighted consistency measure * sequential search * floating search Subject RIV: IN - Informatics, Computer Science http://library.utia.cas.cz/separaty/2008/RO/somol-evaluating the stability of feature selectors that optimize feature subset cardinality.pdf

  18. RESEARCH ON FEATURE POINTS EXTRACTION METHOD FOR BINARY MULTISCALE AND ROTATION INVARIANT LOCAL FEATURE DESCRIPTOR

    Directory of Open Access Journals (Sweden)

    Hongwei Ying

    2014-08-01

    Full Text Available An extreme point of scale space extraction method for binary multiscale and rotation invariant local feature descriptor is studied in this paper in order to obtain a robust and fast method for local image feature descriptor. Classic local feature description algorithms often select neighborhood information of feature points which are extremes of image scale space, obtained by constructing the image pyramid using certain signal transform method. But build the image pyramid always consumes a large amount of computing and storage resources, is not conducive to the actual applications development. This paper presents a dual multiscale FAST algorithm, it does not need to build the image pyramid, but can extract feature points of scale extreme quickly. Feature points extracted by proposed method have the characteristic of multiscale and rotation Invariant and are fit to construct the local feature descriptor.

  19. Guilt by Association: The 13 micron Dust Feature in Circumstellar Shells and Related Spectral Features

    Science.gov (United States)

    Sloan, G. C.; Kraemer, K. E.; Goebel, J. H.; Price, S. D.

    A study of spectra from the SWS on ISO of optically thin oxygen-rich dust shells shows that the strength of the 13 micron dust emission feature is correlated with the CO2 bands (13--17 microns) and dust emission features at 19.8 and 28.1 microns. SRb variables tend to show stronger 13 micron features than Mira variables, suggesting that the presence of the 13 micron and related features depends on pulsation mode and mass-loss rate. The absence of any correlation to dust emission features at 16.8 and 32 microns makes spinel an unlikely carrier. The most plausible carrier of the 13 micron feature remains crystalline alumina, and we suggest that the related dust features may be crystalline silicates. When dust forms in regions of low density, it may condense into crystalline grain structures.

  20. Feature displacement interpolation

    DEFF Research Database (Denmark)

    Nielsen, Mads; Andresen, Per Rønsholt

    1998-01-01

    Given a sparse set of feature matches, we want to compute an interpolated dense displacement map. The application may be stereo disparity computation, flow computation, or non-rigid medical registration. Also estimation of missing image data, may be phrased in this framework. Since the features...... often are very sparse, the interpolation model becomes crucial. We show that a maximum likelihood estimation based on the covariance properties (Kriging) show properties more expedient than methods such as Gaussian interpolation or Tikhonov regularizations, also including scale......-selection. The computational complexities are identical. We apply the maximum likelihood interpolation to growth analysis of the mandibular bone. Here, the features used are the crest-lines of the object surface....

  1. Mid-Infrared Emission Features in the ISM: Feature-to-Features Flux Ratios

    Science.gov (United States)

    Lu, N. Y.

    1998-01-01

    Using a limited, but representative sample of sources in the ISM of our Galaxy with published spectra from the Infrared Space Observatory, we analyze flux ratios between the major mid-IR emission features (EFs) centered around 6.2, 7.7, 8.6 and 11.3 mu, respectively.

  2. FEATUREOUS: AN INTEGRATED ENVIRONMENT FOR FEATURE-CENTRIC ANALYSIS AND MODIFICATION OF OBJECT-ORIENTED SOFTWARE

    DEFF Research Database (Denmark)

    Olszak, Andrzej; Jørgensen, Bo Nørregaard

    2011-01-01

    The decentralized nature of collaborations between objects in object-oriented software makes it difficult to understand the implementations of user-observable program features and their respective interdependencies. As feature-centric program understanding and modification are essential during...... software maintenance and evolution, this situation needs to change. In this paper, we present Featureous, an integrated development environment built on top of the NetBeans IDE that facilitates feature-centric analysis of object-oriented software. Our integrated development environment encompasses...... a lightweight feature location mechanism, a number of reusable analytical views, and necessary APIs for supporting future extensions. The base of the integrated development environment is a conceptual framework comprising of three complementary dimensions of comprehension: perspective, abstraction...

  3. Incidence of diseases primarily affecting the skin by age group: population-based epidemiologic study in Olmsted County, Minnesota, and comparison with age-specific incidence rates worldwide.

    Science.gov (United States)

    Wessman, Laurel L; Andersen, Louise K; Davis, Mark D P

    2018-01-29

    Understanding the effects of age on the epidemiology of diseases primarily affecting the skin is important to the practice of dermatology, both for proper allocation of resources and for optimal patient-centered care. To fully appreciate the effect that age may have on the population-based calculations of incidence of diseases primarily affecting the skin in Olmsted County, Minnesota, and worldwide, we performed a review of all relevant Rochester Epidemiology Project-published data and compared them to similar reports in the worldwide English literature. Using the Rochester Epidemiology Project, population-based epidemiologic studies have been performed to estimate the incidence of specific skin diseases over the past 50 years. In older persons (>65 years), nonmelanoma skin cancer, lentigo maligna, herpes zoster, delusional infestation, venous stasis syndrome, venous ulcer, and burning mouth syndrome were more commonly diagnosed. In those younger than 65 years, atypical nevi, psoriatic arthritis, pityriasis rosea, herpes progenitalis, genital warts, alopecia areata, hidradenitis suppurativa, infantile hemangioma, Behçet's disease, and sarcoidosis (isolated cutaneous, with sarcoidosis-specific cutaneous lesions and with erythema nodosum) had a higher incidence. Many of the incidence rates by age group of diseases primarily affecting the skin derived from the Rochester Epidemiology Project were similar to those reported elsewhere. © 2018 The International Society of Dermatology.

  4. High-dose interleukin 2 in patients with metastatic renal cell carcinoma with sarcomatoid features.

    Science.gov (United States)

    Achkar, Tala; Arjunan, Ananth; Wang, Hong; Saul, Melissa; Davar, Diwakar; Appleman, Leonard J; Friedland, David; Parikh, Rahul A

    2017-01-01

    High-dose interleukin-2 (HD IL-2) is used in the treatment of metastatic renal cell carcinoma (mRCC) and has an overall response rate (ORR) of 12-20% and a complete response rate (CR) of 8% in unselected populations with predominantly clear cell type renal cell carcinoma. Nearly 10-15% of patients with renal cell carcinoma exhibit sarcomatoid differentiation, a feature which correlates with a median overall survival (OS) of 9 months and overall poor prognosis. We report a single institution experience with 21 patients with mRCC with sarcomatoid features post-nephrectomy who were treated with HD IL-2. Twenty one patients with mRCC with sarcomatoid features post-nephrectomy who underwent therapy with HD IL-2 were identified at the University of Pittsburgh Medical Center from 2004 to 2016. Baseline patient characteristics, HD IL-2 cycles, time to progression, and subsequent therapies were evaluated. OS and progression-free survival (PFS) in the cohort were calculated using the Kaplan-Meier method. Disease characteristics were evaluated for significance using the Fischer's exact test and Wilcoxon rank sum test. Patients were predominantly Caucasian males with a median age of 54 years. A majority, 86% of these patients, had metastatic disease at time of initial presentation, primarily with lung and lymph node involvement. The ORR and CR with HD IL-2 was 10% and 5%, respectively. Initial localized disease presentation is the only variable that was significantly associated with response to HD IL-2 (p = 0.0158). Number of HD IL-2 doses did not correlate with response with a mean of 16.5 and 15.0 total doses in responders and non-responders, respectively (p = 0.53). Median PFS with HD IL-2 was 7.9 months (95% CI, 5.0-21.3). Median OS was 30.5 months (95% CI 13.3-57.66). Within the subset of patients who had progression on IL-2, median OS was 19.4 months (95% CI, 13.3-35.3). In patients who received second-line therapy, median PFS was 7.9 months (95% CI 2.4-10.2). In

  5. Improving Naive Bayes with Online Feature Selection for Quick Adaptation to Evolving Feature Usefulness

    Energy Technology Data Exchange (ETDEWEB)

    Pon, R K; Cardenas, A F; Buttler, D J

    2007-09-19

    The definition of what makes an article interesting varies from user to user and continually evolves even for a single user. As a result, for news recommendation systems, useless document features can not be determined a priori and all features are usually considered for interestingness classification. Consequently, the presence of currently useless features degrades classification performance [1], particularly over the initial set of news articles being classified. The initial set of document is critical for a user when considering which particular news recommendation system to adopt. To address these problems, we introduce an improved version of the naive Bayes classifier with online feature selection. We use correlation to determine the utility of each feature and take advantage of the conditional independence assumption used by naive Bayes for online feature selection and classification. The augmented naive Bayes classifier performs 28% better than the traditional naive Bayes classifier in recommending news articles from the Yahoo! RSS feeds.

  6. Multi-Province Listeriosis Outbreak Linked to Contaminated Deli Meat Consumed Primarily in Institutional Settings, Canada, 2008.

    Science.gov (United States)

    Currie, Andrea; Farber, Jeffrey M; Nadon, Céline; Sharma, Davendra; Whitfield, Yvonne; Gaulin, Colette; Galanis, Eleni; Bekal, Sadjia; Flint, James; Tschetter, Lorelee; Pagotto, Franco; Lee, Brenda; Jamieson, Fred; Badiani, Tina; MacDonald, Diane; Ellis, Andrea; May-Hadford, Jennifer; McCormick, Rachel; Savelli, Carmen; Middleton, Dean; Allen, Vanessa; Tremblay, Francois-William; MacDougall, Laura; Hoang, Linda; Shyng, Sion; Everett, Doug; Chui, Linda; Louie, Marie; Bangura, Helen; Levett, Paul N; Wilkinson, Krista; Wylie, John; Reid, Janet; Major, Brian; Engel, Dave; Douey, Donna; Huszczynski, George; Di Lecci, Joe; Strazds, Judy; Rousseau, Josée; Ma, Kenneth; Isaac, Leah; Sierpinska, Urszula

    2015-08-01

    A multi-province outbreak of listeriosis occurred in Canada from June to November 2008. Fifty-seven persons were infected with 1 of 3 similar outbreak strains defined by pulsed-field gel electrophoresis, and 24 (42%) individuals died. Forty-one (72%) of 57 individuals were residents of long-term care facilities or hospital inpatients during their exposure period. Descriptive epidemiology, product traceback, and detection of the outbreak strains of Listeria monocytogenes in food samples and the plant environment confirmed delicatessen meat manufactured by one establishment and purchased primarily by institutions was the source of the outbreak. The food safety investigation identified a plant environment conducive to the introduction and proliferation of L. monocytogenes and persistently contaminated with Listeria spp. This outbreak demonstrated the need for improved listeriosis surveillance, strict control of L. monocytogenes in establishments producing ready-to-eat foods, and advice to vulnerable populations and institutions serving these populations regarding which high-risk foods to avoid.

  7. Feature confirmation in object perception: Feature integration theory 26 years on from the Treisman Bartlett lecture.

    Science.gov (United States)

    Humphreys, Glyn W

    2016-10-01

    The Treisman Bartlett lecture, reported in the Quarterly Journal of Experimental Psychology in 1988, provided a major overview of the feature integration theory of attention. This has continued to be a dominant account of human visual attention to this day. The current paper provides a summary of the work reported in the lecture and an update on critical aspects of the theory as applied to visual object perception. The paper highlights the emergence of findings that pose significant challenges to the theory and which suggest that revisions are required that allow for (a) several rather than a single form of feature integration, (b) some forms of feature integration to operate preattentively, (c) stored knowledge about single objects and interactions between objects to modulate perceptual integration, (d) the application of feature-based inhibition to object files where visual features are specified, which generates feature-based spreading suppression and scene segmentation, and (e) a role for attention in feature confirmation rather than feature integration in visual selection. A feature confirmation account of attention in object perception is outlined.

  8. Complex Topographic Feature Ontology Patterns

    Science.gov (United States)

    Varanka, Dalia E.; Jerris, Thomas J.

    2015-01-01

    Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

  9. Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection.

    Science.gov (United States)

    Melendez, Jaime; Sánchez, Clara I; van Ginneken, Bram; Karssemeijer, Nico

    2014-08-01

    Mass candidate detection is a crucial component of multistep computer-aided detection (CAD) systems. It is usually performed by combining several local features by means of a classifier. When these features are processed on a per-image-location basis (e.g., for each pixel), mismatching problems may arise while constructing feature vectors for classification, which is especially true when the behavior expected from the evaluated features is a peaked response due to the presence of a mass. In this study, two of these problems, consisting of maxima misalignment and differences of maxima spread, are identified and two solutions are proposed. The first proposed method, feature maxima propagation, reproduces feature maxima through their neighboring locations. The second method, local feature selection, combines different subsets of features for different feature vectors associated with image locations. Both methods are applied independently and together. The proposed methods are included in a mammogram-based CAD system intended for mass detection in screening. Experiments are carried out with a database of 382 digital cases. Sensitivity is assessed at two sets of operating points. The first one is the interval of 3.5-15 false positives per image (FPs/image), which is typical for mass candidate detection. The second one is 1 FP/image, which allows to estimate the quality of the mass candidate detector's output for use in subsequent steps of the CAD system. The best results are obtained when the proposed methods are applied together. In that case, the mean sensitivity in the interval of 3.5-15 FPs/image significantly increases from 0.926 to 0.958 (p < 0.0002). At the lower rate of 1 FP/image, the mean sensitivity improves from 0.628 to 0.734 (p < 0.0002). Given the improved detection performance, the authors believe that the strategies proposed in this paper can render mass candidate detection approaches based on image location classification more robust to feature

  10. Opinion mining feature-level using Naive Bayes and feature extraction based analysis dependencies

    Science.gov (United States)

    Sanda, Regi; Baizal, Z. K. Abdurahman; Nhita, Fhira

    2015-12-01

    Development of internet and technology, has major impact and providing new business called e-commerce. Many e-commerce sites that provide convenience in transaction, and consumers can also provide reviews or opinions on products that purchased. These opinions can be used by consumers and producers. Consumers to know the advantages and disadvantages of particular feature of the product. Procuders can analyse own strengths and weaknesses as well as it's competitors products. Many opinions need a method that the reader can know the point of whole opinion. The idea emerged from review summarization that summarizes the overall opinion based on sentiment and features contain. In this study, the domain that become the main focus is about the digital camera. This research consisted of four steps 1) giving the knowledge to the system to recognize the semantic orientation of an opinion 2) indentify the features of product 3) indentify whether the opinion gives a positive or negative 4) summarizing the result. In this research discussed the methods such as Naï;ve Bayes for sentiment classification, and feature extraction algorithm based on Dependencies Analysis, which is one of the tools in Natural Language Processing (NLP) and knowledge based dictionary which is useful for handling implicit features. The end result of research is a summary that contains a bunch of reviews from consumers on the features and sentiment. With proposed method, accuration for sentiment classification giving 81.2 % for positive test data, 80.2 % for negative test data, and accuration for feature extraction reach 90.3 %.

  11. Feature Selection by Reordering

    Czech Academy of Sciences Publication Activity Database

    Jiřina, Marcel; Jiřina jr., M.

    2005-01-01

    Roč. 2, č. 1 (2005), s. 155-161 ISSN 1738-6438 Institutional research plan: CEZ:AV0Z10300504 Keywords : feature selection * data reduction * ordering of features Subject RIV: BA - General Mathematics

  12. DYNAMIC FEATURE SELECTION FOR WEB USER IDENTIFICATION ON LINGUISTIC AND STYLISTIC FEATURES OF ONLINE TEXTS

    Directory of Open Access Journals (Sweden)

    A. A. Vorobeva

    2017-01-01

    Full Text Available The paper deals with identification and authentication of web users participating in the Internet information processes (based on features of online texts.In digital forensics web user identification based on various linguistic features can be used to discover identity of individuals, criminals or terrorists using the Internet to commit cybercrimes. Internet could be used as a tool in different types of cybercrimes (fraud and identity theft, harassment and anonymous threats, terrorist or extremist statements, distribution of illegal content and information warfare. Linguistic identification of web users is a kind of biometric identification, it can be used to narrow down the suspects, identify a criminal and prosecute him. Feature set includes various linguistic and stylistic features extracted from online texts. We propose dynamic feature selection for each web user identification task. Selection is based on calculating Manhattan distance to k-nearest neighbors (Relief-f algorithm. This approach improves the identification accuracy and minimizes the number of features. Experiments were carried out on several datasets with different level of class imbalance. Experiment results showed that features relevance varies in different set of web users (probable authors of some text; features selection for each set of web users improves identification accuracy by 4% at the average that is approximately 1% higher than with the use of static set of features. The proposed approach is most effective for a small number of training samples (messages per user.

  13. Temporal Feature Integration for Music Organisation

    DEFF Research Database (Denmark)

    Meng, Anders

    2006-01-01

    This Ph.D. thesis focuses on temporal feature integration for music organisation. Temporal feature integration is the process of combining all the feature vectors of a given time-frame into a single new feature vector in order to capture relevant information in the frame. Several existing methods...... for handling sequences of features are formulated in the temporal feature integration framework. Two datasets for music genre classification have been considered as valid test-beds for music organisation. Human evaluations of these, have been obtained to access the subjectivity on the datasets. Temporal...... ranking' approach is proposed for ranking the short-time features at larger time-scales according to their discriminative power in a music genre classification task. The multivariate AR (MAR) model has been proposed for temporal feature integration. It effectively models local dynamical structure...

  14. Feature Inference Learning and Eyetracking

    Science.gov (United States)

    Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

    2009-01-01

    Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

  15. Specific feature of magnetooptical images of stray fields of magnets of various geometrical shapes

    Science.gov (United States)

    Ivanov, V. E.; Koveshnikov, A. V.; Andreev, S. V.

    2017-08-01

    Specific features of magnetooptical images (MOIs) of stray fields near the faces of prismatic hard magnetic elements have been studied. Attention has primarily been focused on MOIs of fields near faces oriented perpendicular to the magnetic moment of hard magnetic elements. With regard to the polar sensitivity, MOIs have practically uniform brightness and geometrically they coincide with the figures of the bases of the elements. With regard to longitudinal sensitivity, MOIs consist of several sectors, the number of which is determined by the number of angles of the image. Each angle is divided by the bisectrix into two sectors of different brightnesses; therefore, the MOI of a triangular magnet consists of three sectors. A rectangle consists of four sectors separated by the bisectrices of the interior angles. In all types of figures, these lines converge at the center of the figure and form a singular point of the source or sink type.

  16. The time-course of feature interference in agreement comprehension: Multiple mechanisms and asymmetrical attraction.

    Science.gov (United States)

    Tanner, Darren; Nicol, Janet; Brehm, Laurel

    2014-10-01

    Attraction interference in language comprehension and production may be as a result of common or different processes. In the present paper, we investigate attraction interference during language comprehension, focusing on the contexts in which interference arises and the time-course of these effects. Using evidence from event-related brain potentials (ERPs) and sentence judgment times, we show that agreement attraction in comprehension is best explained as morphosyntactic interference during memory retrieval. This stands in contrast to attraction as a message-level process involving the representation of the subject NP's number features, which is a strong contributor to attraction in production. We thus argue that the cognitive antecedents of agreement attraction in comprehension are non-identical with those of attraction in production, and moreover, that attraction in comprehension is primarily a consequence of similarity-based interference in cue-based memory retrieval processes. We suggest that mechanisms responsible for attraction during language comprehension are a subset of those involved in language production.

  17. Identification of a novel CoA synthase isoform, which is primarily expressed in Brain

    International Nuclear Information System (INIS)

    Nemazanyy, Ivan; Panasyuk, Ganna; Breus, Oksana; Zhyvoloup, Alexander; Filonenko, Valeriy; Gout, Ivan T.

    2006-01-01

    CoA and its derivatives Acetyl-CoA and Acyl-CoA are important players in cellular metabolism and signal transduction. CoA synthase is a bifunctional enzyme which mediates the final stages of CoA biosynthesis. In previous studies, we have reported molecular cloning, biochemical characterization, and subcellular localization of CoA synthase (CoASy). Here, we describe the existence of a novel CoA synthase isoform, which is the product of alternative splicing and possesses a 29aa extension at the N-terminus. We termed it CoASy β and originally identified CoA synthase, CoASy α. The transcript specific for CoASy β was identified by electronic screening and by RT-PCR analysis of various rat tissues. The existence of this novel isoform was further confirmed by immunoblot analysis with antibodies directed to the N-terminal peptide of CoASy β. In contrast to CoASy α, which shows ubiquitous expression, CoASy β is primarily expressed in Brain. Using confocal microscopy, we demonstrated that both isoforms are localized on mitochondria. The N-terminal extension does not affect the activity of CoA synthase, but possesses a proline-rich sequence which can bring the enzyme into complexes with signalling proteins containing SH3 or WW domains. The role of this novel isoform in CoA biosynthesis, especially in Brain, requires further elucidation

  18. Hypothesis testing for differentially correlated features.

    Science.gov (United States)

    Sheng, Elisa; Witten, Daniela; Zhou, Xiao-Hua

    2016-10-01

    In a multivariate setting, we consider the task of identifying features whose correlations with the other features differ across conditions. Such correlation shifts may occur independently of mean shifts, or differences in the means of the individual features across conditions. Previous approaches for detecting correlation shifts consider features simultaneously, by computing a correlation-based test statistic for each feature. However, since correlations involve two features, such approaches do not lend themselves to identifying which feature is the culprit. In this article, we instead consider a serial testing approach, by comparing columns of the sample correlation matrix across two conditions, and removing one feature at a time. Our method provides a novel perspective and favorable empirical results compared with competing approaches. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  19. Emergent interfaces for feature modularization

    CERN Document Server

    Ribeiro, Márcio; Brabrand, Claus

    2014-01-01

    Developers frequently introduce errors into software systems when they fail to recognise module dependencies. Using forty-three software families and Software Product Lines (SPLs), where the majority are commonly used in industrial practice, the authors reports on the feature modularization problem and provides a study of how often it may occur in practice. To solve the problem they present the concept of emergent feature modularization which aims to establish contracts between features to prevent developers from breaking other features when performing a maintenance task.

  20. Writer identification using curvature-free features

    NARCIS (Netherlands)

    He, Sheng; Schomaker, Lambertus

    2017-01-01

    Feature engineering takes a very important role in writer identification which has been widely studied in the literature. Previous works have shown that the joint feature distribution of two properties can improve the performance. The joint feature distribution makes feature relationships explicit

  1. Patterns of Dysmorphic Features in Schizophrenia

    Science.gov (United States)

    Scutt, L.E.; Chow, E.W.C.; Weksberg, R.; Honer, W.G.; Bassett, Anne S.

    2011-01-01

    Congenital dysmorphic features are prevalent in schizophrenia and may reflect underlying neurodevelopmental abnormalities. A cluster analysis approach delineating patterns of dysmorphic features has been used in genetics to classify individuals into more etiologically homogeneous subgroups. In the present study, this approach was applied to schizophrenia, using a sample with a suspected genetic syndrome as a testable model. Subjects (n = 159) with schizophrenia or schizoaffective disorder were ascertained from chronic patient populations (random, n=123) or referred with possible 22q11 deletion syndrome (referred, n = 36). All subjects were evaluated for presence or absence of 70 reliably assessed dysmorphic features, which were used in a three-step cluster analysis. The analysis produced four major clusters with different patterns of dysmorphic features. Significant between-cluster differences were found for rates of 37 dysmorphic features (P dysmorphic features (P = 0.0001), and validating features not used in the cluster analysis: mild mental retardation (P = 0.001) and congenital heart defects (P = 0.002). Two clusters (1 and 4) appeared to represent more developmental subgroups of schizophrenia with elevated rates of dysmorphic features and validating features. Cluster 1 (n = 27) comprised mostly referred subjects. Cluster 4 (n= 18) had a different pattern of dysmorphic features; one subject had a mosaic Turner syndrome variant. Two other clusters had lower rates and patterns of features consistent with those found in previous studies of schizophrenia. Delineating patterns of dysmorphic features may help identify subgroups that could represent neurodevelopmental forms of schizophrenia with more homogeneous origins. PMID:11803519

  2. Object feature extraction and recognition model

    International Nuclear Information System (INIS)

    Wan Min; Xiang Rujian; Wan Yongxing

    2001-01-01

    The characteristics of objects, especially flying objects, are analyzed, which include characteristics of spectrum, image and motion. Feature extraction is also achieved. To improve the speed of object recognition, a feature database is used to simplify the data in the source database. The feature vs. object relationship maps are stored in the feature database. An object recognition model based on the feature database is presented, and the way to achieve object recognition is also explained

  3. Solar Features

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Collection includes a variety of solar feature datasets contributed by a number of national and private solar observatories located worldwide.

  4. Search features of digital libraries

    Directory of Open Access Journals (Sweden)

    Alastair G. Smith

    2000-01-01

    Full Text Available Traditional on-line search services such as Dialog, DataStar and Lexis provide a wide range of search features (boolean and proximity operators, truncation, etc. This paper discusses the use of these features for effective searching, and argues that these features are required, regardless of advances in search engine technology. The literature on on-line searching is reviewed, identifying features that searchers find desirable for effective searching. A selective survey of current digital libraries available on the Web was undertaken, identifying which search features are present. The survey indicates that current digital libraries do not implement a wide range of search features. For instance: under half of the examples included controlled vocabulary, under half had proximity searching, only one enabled browsing of term indexes, and none of the digital libraries enable searchers to refine an initial search. Suggestions are made for enhancing the search effectiveness of digital libraries, for instance by: providing a full range of search operators, enabling browsing of search terms, enhancement of records with controlled vocabulary, enabling the refining of initial searches, etc.

  5. [Feature extraction for breast cancer data based on geometric algebra theory and feature selection using differential evolution].

    Science.gov (United States)

    Li, Jing; Hong, Wenxue

    2014-12-01

    The feature extraction and feature selection are the important issues in pattern recognition. Based on the geometric algebra representation of vector, a new feature extraction method using blade coefficient of geometric algebra was proposed in this study. At the same time, an improved differential evolution (DE) feature selection method was proposed to solve the elevated high dimension issue. The simple linear discriminant analysis was used as the classifier. The result of the 10-fold cross-validation (10 CV) classification of public breast cancer biomedical dataset was more than 96% and proved superior to that of the original features and traditional feature extraction method.

  6. Healthy younger and older adults control foot placement to avoid small obstacles during gait primarily by modulating step width

    Directory of Open Access Journals (Sweden)

    Schulz Brian W

    2012-10-01

    Full Text Available Abstract Background Falls are a significant problem in the older population. Most falls occur during gait, which is primarily regulated by foot placement. Variability of foot placement has been associated with falls, but these associations are inconsistent and generally for smooth, level flooring. This study investigates the control of foot placement and the associated gait variability in younger and older men and women (N=7/group, total N=28 while walking at three different speeds (slow, preferred, and fast across a control surface with no obstacles and surfaces with multiple (64 small (10cm long ×13mm high visible and hidden obstacles. Results Minimum obstacle distance between the shoe and nearest obstacle during each footfall was greater on the visible obstacles surface for older subjects because some of them chose to actively avoid obstacles. This obstacle avoidance strategy was implemented primarily by modulating step width and to a lesser extent step length as indicated by linear regressions of step width and length variability on minimum obstacle distance. Mean gait speed, step length, step width, and step time did not significantly differ by subject group, flooring surface, or obstacle avoidance strategy. Conclusions Some healthy older subjects choose to actively avoid small obstacles that do not substantially perturb their gait by modulating step width and, to a lesser extent, step length. It is not clear if this obstacle avoidance strategy is appropriate and beneficial or overcautious and maladaptive, as it results in fewer obstacles encountered at a consequence of a less efficient gait pattern that has been shown to indicate increased fall risk. Further research is needed on the appropriateness of strategy selection when the environmental demands and/or task requirements have multiple possible completion strategies with conflicting objectives (i.e. perceived safety vs. efficiency.

  7. Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

    Science.gov (United States)

    Li, Baopu; Meng, Max Q-H

    2012-05-01

    Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.

  8. Gender, Sexual Orientation, and Rape Myth Acceptance: Preliminary Findings From a Sample of Primarily LGBQ-Identified Survey Respondents.

    Science.gov (United States)

    Schulze, Corina; Koon-Magnin, Sarah

    2017-02-01

    This study is among the first to examine the relationship between sexual orientation and rape myth adherence using a nationwide survey of primarily lesbian, gay, bisexual, and queer (LGBQ) respondents (n = 184). The more established Illinois Rape Myth Acceptance Scale and a modified Male Rape Survey serve as the primary instruments to test both rape myth adherence and instrument-appropriateness. Results suggest that respondents were most likely to support myths that discredit sexual assault allegations or excuse rape as a biological imperative and least likely to support myths related to physical resistance. Consistent with previous work, men exhibited higher levels of rape myth adherence than women. Regarding sexual orientation, respondents who identified as queer consistently exhibited lower levels of rape myth adherence than respondents who identified as gay.

  9. How Lovebirds Maneuver Rapidly Using Super-Fast Head Saccades and Image Feature Stabilization.

    Directory of Open Access Journals (Sweden)

    Daniel Kress

    Full Text Available Diurnal flying animals such as birds depend primarily on vision to coordinate their flight path during goal-directed flight tasks. To extract the spatial structure of the surrounding environment, birds are thought to use retinal image motion (optical flow that is primarily induced by motion of their head. It is unclear what gaze behaviors birds perform to support visuomotor control during rapid maneuvering flight in which they continuously switch between flight modes. To analyze this, we measured the gaze behavior of rapidly turning lovebirds in a goal-directed task: take-off and fly away from a perch, turn on a dime, and fly back and land on the same perch. High-speed flight recordings revealed that rapidly turning lovebirds perform a remarkable stereotypical gaze behavior with peak saccadic head turns up to 2700 degrees per second, as fast as insects, enabled by fast neck muscles. In between saccades, gaze orientation is held constant. By comparing saccade and wingbeat phase, we find that these super-fast saccades are coordinated with the downstroke when the lateral visual field is occluded by the wings. Lovebirds thus maximize visual perception by overlying behaviors that impair vision, which helps coordinate maneuvers. Before the turn, lovebirds keep a high contrast edge in their visual midline. Similarly, before landing, the lovebirds stabilize the center of the perch in their visual midline. The perch on which the birds land swings, like a branch in the wind, and we find that retinal size of the perch is the most parsimonious visual cue to initiate landing. Our observations show that rapidly maneuvering birds use precisely timed stereotypic gaze behaviors consisting of rapid head turns and frontal feature stabilization, which facilitates optical flow based flight control. Similar gaze behaviors have been reported for visually navigating humans. This finding can inspire more effective vision-based autopilots for drones.

  10. Volcanic features of Io

    International Nuclear Information System (INIS)

    Carr, M.H.; Masursky, H.; Strom, R.G.; Terrile, R.J.

    1979-01-01

    The volcanic features of Io as detected during the Voyager mission are discussed. The volcanic activity is apparently higher than on any other body in the Solar System. Its volcanic landforms are compared with features on Earth to indicate the type of volcanism present on Io. (U.K.)

  11. Evaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality

    Czech Academy of Sciences Publication Activity Database

    Somol, Petr; Novovičová, Jana

    2010-01-01

    Roč. 32, č. 11 (2010), s. 1921-1939 ISSN 0162-8828 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593; GA ČR GA102/07/1594 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : feature selection * feature stability * stability measures * similarity measures * sequential search * individual ranking * feature subset-size optimization * high dimensionality * small sample size Subject RIV: BD - Theory of Information Impact factor: 5.027, year: 2010 http://library.utia.cas.cz/separaty/2010/RO/somol-0348726.pdf

  12. Site Features

    Data.gov (United States)

    U.S. Environmental Protection Agency — This dataset consists of various site features from multiple Superfund sites in U.S. EPA Region 8. These data were acquired from multiple sources at different times...

  13. New features in MEDM

    International Nuclear Information System (INIS)

    Evans, K. Jr.

    1999-01-01

    MEDM, which is derived from Motif Editor and Display Manager, is the primary graphical interface to the EPICS control system. This paper describes new features that have been added to MEDM in the last two years. These features include new editing capabilities, a PV Info dialog box, a means of specifying limits and precision, a new implementation of the Cartesian Plot, new features for several objects, new capability for the Related Display, help, a user-configurable Execute Menu, reconfigured start-up options, and availability for Windows 95/98/NT. Over one hundred bugs have been fixed, and the program is quite stable and in extensive use

  14. GOLD HULL AND INTERNODE2 Encodes a Primarily Multifunctional Cinnamyl-Alcohol Dehydrogenase in Rice1

    Science.gov (United States)

    Zhang, Kewei; Qian, Qian; Huang, Zejun; Wang, Yiqin; Li, Ming; Hong, Lilan; Zeng, Dali; Gu, Minghong; Chu, Chengcai; Cheng, Zhukuan

    2006-01-01

    Lignin content and composition are two important agronomic traits for the utilization of agricultural residues. Rice (Oryza sativa) gold hull and internode phenotype is a classical morphological marker trait that has long been applied to breeding and genetics study. In this study, we have cloned the GOLD HULL AND INTERNODE2 (GH2) gene in rice using a map-based cloning approach. The result shows that the gh2 mutant is a lignin-deficient mutant, and GH2 encodes a cinnamyl-alcohol dehydrogenase (CAD). Consistent with this finding, extracts from roots, internodes, hulls, and panicles of the gh2 plants exhibited drastically reduced CAD activity and undetectable sinapyl alcohol dehydrogenase activity. When expressed in Escherichia coli, purified recombinant GH2 was found to exhibit strong catalytic ability toward coniferaldehyde and sinapaldehyde, while the mutant protein gh2 completely lost the corresponding CAD and sinapyl alcohol dehydrogenase activities. Further phenotypic analysis of the gh2 mutant plants revealed that the p-hydroxyphenyl, guaiacyl, and sinapyl monomers were reduced in almost the same ratio compared to the wild type. Our results suggest GH2 acts as a primarily multifunctional CAD to synthesize coniferyl and sinapyl alcohol precursors in rice lignin biosynthesis. PMID:16443696

  15. Tolerance-Based Feature Transforms

    NARCIS (Netherlands)

    Reniers, Dennie; Telea, Alexandru

    2007-01-01

    Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs on binary

  16. Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

    Science.gov (United States)

    Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

    2016-01-01

    An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

  17. Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features.

    Directory of Open Access Journals (Sweden)

    Seyed Mostafa Mousavi Kahaki

    Full Text Available An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics--such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient--are insufficient for achieving adequate results under different image deformations. Thus, new descriptor's similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence.

  18. Crowding with conjunctions of simple features.

    Science.gov (United States)

    Põder, Endel; Wagemans, Johan

    2007-11-20

    Several recent studies have related crowding with the feature integration stage in visual processing. In order to understand the mechanisms involved in this stage, it is important to use stimuli that have several features to integrate, and these features should be clearly defined and measurable. In this study, Gabor patches were used as target and distractor stimuli. The stimuli differed in three dimensions: spatial frequency, orientation, and color. A group of 3, 5, or 7 objects was presented briefly at 4 deg eccentricity of the visual field. The observers' task was to identify the object located in the center of the group. A strong effect of the number of distractors was observed, consistent with various spatial pooling models. The analysis of incorrect responses revealed that these were a mix of feature errors and mislocalizations of the target object. Feature errors were not purely random, but biased by the features of distractors. We propose a simple feature integration model that predicts most of the observed regularities.

  19. Light and electron microscopy of the European beaver (Castor fiber) stomach reveal unique morphological features with possible general biological significance.

    Science.gov (United States)

    Ziółkowska, Natalia; Lewczuk, Bogdan; Petryński, Wojciech; Palkowska, Katarzyna; Prusik, Magdalena; Targońska, Krystyna; Giżejewski, Zygmunt; Przybylska-Gornowicz, Barbara

    2014-01-01

    Anatomical, histological, and ultrastructural studies of the European beaver stomach revealed several unique morphological features. The prominent attribute of its gross morphology was the cardiogastric gland (CGG), located near the oesophageal entrance. Light microscopy showed that the CGG was formed by invaginations of the mucosa into the submucosa, which contained densely packed proper gastric glands comprised primarily of parietal and chief cells. Mucous neck cells represented beaver stomach was the presence of specific mucus with a thickness up to 950 µm (in frozen, unfixed sections) that coated the mucosa. Our observations suggest that the formation of this mucus is complex and includes the secretory granule accumulation in the cytoplasm of pit cells, the granule aggregation inside cells, and the incorporation of degenerating cells into the mucus.

  20. Sensitivity to feature displacement in familiar and unfamiliar faces: beyond the internal/external feature distinction.

    Science.gov (United States)

    Brooks, Kevin R; Kemp, Richard I

    2007-01-01

    Previous studies of face recognition and of face matching have shown a general improvement for the processing of internal features as a face becomes more familiar to the participant. In this study, we used a psychophysical two-alternative forced-choice paradigm to investigate thresholds for the detection of a displacement of the eyes, nose, mouth, or ears for familiar and unfamiliar faces. No clear division between internal and external features was observed. Rather, for familiar (compared to unfamiliar) faces participants were more sensitive to displacements of internal features such as the eyes or the nose; yet, for our third internal feature-the mouth no such difference was observed. Despite large displacements, many subjects were unable to perform above chance when stimuli involved shifts in the position of the ears. These results are consistent with the proposal that familiarity effects may be mediated by the construction of a robust representation of a face, although the involvement of attention in the encoding of face stimuli cannot be ruled out. Furthermore, these effects are mediated by information from a spatial configuration of features, rather than by purely feature-based information.

  1. Feature extraction for magnetic domain images of magneto-optical recording films using gradient feature segmentation

    International Nuclear Information System (INIS)

    Quanqing, Zhu.; Xinsai, Wang; Xuecheng, Zou; Haihua, Li; Xiaofei, Yang

    2002-01-01

    In this paper, we present a method to realize feature extraction on low contrast magnetic domain images of magneto-optical recording films. The method is based on the following three steps: first, Lee-filtering method is adopted to realize pre-filtering and noise reduction; this is followed by gradient feature segmentation, which separates the object area from the background area; finally the common linking method is adopted and the characteristic parameters of magnetic domain are calculated. We describe these steps with particular emphasis on the gradient feature segmentation. The results show that this method has advantages over other traditional ones for feature extraction of low contrast images

  2. Discrete Feature Model (DFM) User Documentation

    Energy Technology Data Exchange (ETDEWEB)

    Geier, Joel (Clearwater Hardrock Consulting, Corvallis, OR (United States))

    2008-06-15

    This manual describes the Discrete-Feature Model (DFM) software package for modelling groundwater flow and solute transport in networks of discrete features. A discrete-feature conceptual model represents fractures and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which is usually treated as impermeable. This approximation may be valid for crystalline rocks such as granite or basalt, which have very low permeability if macroscopic fractures are excluded. A discrete feature is any entity that can conduct water and permit solute transport through bedrock, and can be reasonably represented as a piecewise-planar conductor. Examples of such entities may include individual natural fractures (joints or faults), fracture zones, and disturbed-zone features around tunnels (e.g. blasting-induced fractures or stress-concentration induced 'onion skin' fractures around underground openings). In a more abstract sense, the effectively discontinuous nature of pathways through fractured crystalline bedrock may be idealized as discrete, equivalent transmissive features that reproduce large-scale observations, even if the details of connective paths (and unconnected domains) are not precisely known. A discrete-feature model explicitly represents the fundamentally discontinuous and irregularly connected nature of systems of such systems, by constraining flow and transport to occur only within such features and their intersections. Pathways for flow and solute transport in this conceptualization are a consequence not just of the boundary conditions and hydrologic properties (as with continuum models), but also the irregularity of connections between conductive/transmissive features. The DFM software package described here is an extensible code for investigating problems of flow and transport in geological (natural or human-altered) systems that can be characterized effectively in terms of discrete features. With this

  3. Discrete Feature Model (DFM) User Documentation

    International Nuclear Information System (INIS)

    Geier, Joel

    2008-06-01

    This manual describes the Discrete-Feature Model (DFM) software package for modelling groundwater flow and solute transport in networks of discrete features. A discrete-feature conceptual model represents fractures and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which is usually treated as impermeable. This approximation may be valid for crystalline rocks such as granite or basalt, which have very low permeability if macroscopic fractures are excluded. A discrete feature is any entity that can conduct water and permit solute transport through bedrock, and can be reasonably represented as a piecewise-planar conductor. Examples of such entities may include individual natural fractures (joints or faults), fracture zones, and disturbed-zone features around tunnels (e.g. blasting-induced fractures or stress-concentration induced 'onion skin' fractures around underground openings). In a more abstract sense, the effectively discontinuous nature of pathways through fractured crystalline bedrock may be idealized as discrete, equivalent transmissive features that reproduce large-scale observations, even if the details of connective paths (and unconnected domains) are not precisely known. A discrete-feature model explicitly represents the fundamentally discontinuous and irregularly connected nature of systems of such systems, by constraining flow and transport to occur only within such features and their intersections. Pathways for flow and solute transport in this conceptualization are a consequence not just of the boundary conditions and hydrologic properties (as with continuum models), but also the irregularity of connections between conductive/transmissive features. The DFM software package described here is an extensible code for investigating problems of flow and transport in geological (natural or human-altered) systems that can be characterized effectively in terms of discrete features. With this software, the

  4. Morphological features of the neonatal brain support development of subsequent cognitive, language, and motor abilities.

    Science.gov (United States)

    Spann, Marisa N; Bansal, Ravi; Rosen, Tove S; Peterson, Bradley S

    2014-09-01

    Knowledge of the role of brain maturation in the development of cognitive abilities derives primarily from studies of school-age children to adults. Little is known about the morphological features of the neonatal brain that support the subsequent development of abilities in early childhood, when maturation of the brain and these abilities are the most dynamic. The goal of our study was to determine whether brain morphology during the neonatal period supports early cognitive development through 2 years of age. We correlated morphological features of the cerebral surface assessed using deformation-based measures (surface distances) of high-resolution MRI scans for 33 healthy neonates, scanned between the first to sixth week of postmenstrual life, with subsequent measures of their motor, language, and cognitive abilities at ages 6, 12, 18, and 24 months. We found that morphological features of the cerebral surface of the frontal, mesial prefrontal, temporal, and occipital regions correlated with subsequent motor scores, posterior parietal regions correlated with subsequent language scores, and temporal and occipital regions correlated with subsequent cognitive scores. Measures of the anterior and middle portions of the cingulate gyrus correlated with scores across all three domains of ability. Most of the significant findings were inverse correlations located bilaterally in the brain. The inverse correlations may suggest either that a more protracted morphological maturation or smaller local volumes of neonatal brain tissue supports better performance on measures of subsequent motor, language, and cognitive abilities throughout the first 2 years of postnatal life. The correlations of morphological measures of the cingulate with measures of performance across all domains of ability suggest that the cingulate supports a broad range of skills in infancy and early childhood, similar to its functions in older children and adults. Copyright © 2014 Wiley Periodicals, Inc.

  5. Interferon-gamma and tumor necrosis factor-alpha sensitize primarily resistant human endometrial stromal cells to Fas-mediated apoptosis

    DEFF Research Database (Denmark)

    Fluhr, Herbert; Krenzer, Stefanie; Stein, Gerburg M

    2007-01-01

    The subtle interaction between the implanting embryo and the maternal endometrium plays a pivotal role during the process of implantation. Human endometrial stromal cells (ESCs) express Fas and the implanting trophoblast cells secrete Fas ligand (FASLG, FasL), suggesting a possible role for Fas......-mediated signaling during early implantation. Here we show that ESCs are primarily resistant to Fas-mediated apoptosis independently of their state of hormonal differentiation. Pre-treatment of ESCs with interferon (IFN)-gamma and tumor necrosis factor (TNF)-alpha sensitizes them to become apoptotic upon stimulation...... of Fas by an agonistic anti-Fas antibody. Incubation of ESCs with the early embryonic signal human chorionic gonadotropin (hCG, CGB) does not influence their reaction to Fas stimulation. The sensitizing effect of IFN-gamma and TNF-alpha was accompanied by a significant upregulation of Fas and FLICE...

  6. Degree of contribution (DoC) feature selection algorithm for structural brain MRI volumetric features in depression detection.

    Science.gov (United States)

    Kipli, Kuryati; Kouzani, Abbas Z

    2015-07-01

    Accurate detection of depression at an individual level using structural magnetic resonance imaging (sMRI) remains a challenge. Brain volumetric changes at a structural level appear to have importance in depression biomarkers studies. An automated algorithm is developed to select brain sMRI volumetric features for the detection of depression. A feature selection (FS) algorithm called degree of contribution (DoC) is developed for selection of sMRI volumetric features. This algorithm uses an ensemble approach to determine the degree of contribution in detection of major depressive disorder. The DoC is the score of feature importance used for feature ranking. The algorithm involves four stages: feature ranking, subset generation, subset evaluation, and DoC analysis. The performance of DoC is evaluated on the Duke University Multi-site Imaging Research in the Analysis of Depression sMRI dataset. The dataset consists of 115 brain sMRI scans of 88 healthy controls and 27 depressed subjects. Forty-four sMRI volumetric features are used in the evaluation. The DoC score of forty-four features was determined as the accuracy threshold (Acc_Thresh) was varied. The DoC performance was compared with that of four existing FS algorithms. At all defined Acc_Threshs, DoC outperformed the four examined FS algorithms for the average classification score and the maximum classification score. DoC has a good ability to generate reduced-size subsets of important features that could yield high classification accuracy. Based on the DoC score, the most discriminant volumetric features are those from the left-brain region.

  7. Flow-like Features On Europa

    Science.gov (United States)

    1997-01-01

    This image shows features on Jupiter's moon Europa that may be 'flows' from ice volcanoes. It was taken by the Galileo spacecraft solid state imaging (CCD) system during its seventh orbit around Jupiter. North is to the top of the image. The sun illuminates the scene from the left, showing features with shapes similar to lava flows on Earth. Two such features can be seen in the northwest corner of the image. The southern feature appears to have flowed over a ridge along its western edge. Scientists use these types of relationships to determine which feature formed first. In this case, the ridge probably formed before the flow-like feature that covers it.The image, centered at 22.6 degrees north latitude and 106.7 degrees west longitude, covers an area of 180 by 215 kilometers (112 by 134 miles). The smallest distinguishable features in the image are about 1.1 kilometers (0.7 miles) across. This image was obtained on April 28, 1997, when Galileo was 27,590 kilometers (16,830 miles) from Europa.The Jet Propulsion Laboratory, Pasadena, CA manages the Galileo mission for NASA's Office of Space Science, Washington, DC. JPL is an operating division of California Institute of Technology (Caltech).This image and other images and data received from Galileo are posted on the World Wide Web, on the Galileo mission home page at URL http://galileo.jpl.nasa.gov. Background information and educational context for the images can be found at URL http://www.jpl.nasa.gov/galileo/sepo

  8. Feature Extraction

    CERN Document Server

    CERN. Geneva

    2015-01-01

    Feature selection and reduction are key to robust multivariate analyses. In this talk I will focus on pros and cons of various variable selection methods and focus on those that are most relevant in the context of HEP.

  9. Video genre classification using multimodal features

    Science.gov (United States)

    Jin, Sung Ho; Bae, Tae Meon; Choo, Jin Ho; Ro, Yong Man

    2003-12-01

    We propose a video genre classification method using multimodal features. The proposed method is applied for the preprocessing of automatic video summarization or the retrieval and classification of broadcasting video contents. Through a statistical analysis of low-level and middle-level audio-visual features in video, the proposed method can achieve good performance in classifying several broadcasting genres such as cartoon, drama, music video, news, and sports. In this paper, we adopt MPEG-7 audio-visual descriptors as multimodal features of video contents and evaluate the performance of the classification by feeding the features into a decision tree-based classifier which is trained by CART. The experimental results show that the proposed method can recognize several broadcasting video genres with a high accuracy and the classification performance with multimodal features is superior to the one with unimodal features in the genre classification.

  10. Particle swarm optimization based feature enhancement and feature selection for improved emotion recognition in speech and glottal signals.

    Science.gov (United States)

    Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

    2015-01-01

    In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature.

  11. MRI features associated with acute appendicitis

    NARCIS (Netherlands)

    Leeuwenburgh, Marjolein M. N.; Jensch, Sebastiaan; Gratama, Jan W. C.; Spilt, Aart; Wiarda, Bart M.; van Es, H. Wouter; Cobben, Lodewijk P. J.; Bossuyt, Patrick M. M.; Boermeester, Marja A.; Stoker, Jaap; Bouma, Wim H.; Houdijk, Alexander P. J.; Richir, Milan C.; Stockmann, Hein B. A. C.; Wiezer, Marinus J.; Verhagen, Thijs

    2014-01-01

    To identify MRI features associated with appendicitis. Features expected to be associated with appendicitis were recorded in consensus by two expert radiologists on 223 abdominal MRIs in patients with suspected appendicitis. Nine MRI features were studied: appendix diameter >7 mm, appendicolith,

  12. Hong Kong English: phonological features

    OpenAIRE

    Irina-Ana Drobot

    2008-01-01

    The aim of the paper is to present phonological features of Hong Kong English, which is a variety of New English. I examine features of the sound system (vowel and consonantal systems), characteristics of stress, rhythm, intonation, and phonological processes of the English spoken by Hongkongers. The way in which the accent and characteristics of the Hong Kong variety of English differs from standard, RP English is pointed out. Influences of Chinese and Cantonese on the phonological features ...

  13. Cascaded face alignment via intimacy definition feature

    Science.gov (United States)

    Li, Hailiang; Lam, Kin-Man; Chiu, Man-Yau; Wu, Kangheng; Lei, Zhibin

    2017-09-01

    Recent years have witnessed the emerging popularity of regression-based face aligners, which directly learn mappings between facial appearance and shape-increment manifolds. We propose a random-forest based, cascaded regression model for face alignment by using a locally lightweight feature, namely intimacy definition feature. This feature is more discriminative than the pose-indexed feature, more efficient than the histogram of oriented gradients feature and the scale-invariant feature transform feature, and more compact than the local binary feature (LBF). Experimental validation of our algorithm shows that our approach achieves state-of-the-art performance when testing on some challenging datasets. Compared with the LBF-based algorithm, our method achieves about twice the speed, 20% improvement in terms of alignment accuracy and saves an order of magnitude on memory requirement.

  14. Extract the Relational Information of Static Features and Motion Features for Human Activities Recognition in Videos

    Directory of Open Access Journals (Sweden)

    Li Yao

    2016-01-01

    Full Text Available Both static features and motion features have shown promising performance in human activities recognition task. However, the information included in these features is insufficient for complex human activities. In this paper, we propose extracting relational information of static features and motion features for human activities recognition. The videos are represented by a classical Bag-of-Word (BoW model which is useful in many works. To get a compact and discriminative codebook with small dimension, we employ the divisive algorithm based on KL-divergence to reconstruct the codebook. After that, to further capture strong relational information, we construct a bipartite graph to model the relationship between words of different feature set. Then we use a k-way partition to create a new codebook in which similar words are getting together. With this new codebook, videos can be represented by a new BoW vector with strong relational information. Moreover, we propose a method to compute new clusters from the divisive algorithm’s projective function. We test our work on the several datasets and obtain very promising results.

  15. Temporal feature integration for music genre classification

    DEFF Research Database (Denmark)

    Meng, Anders; Ahrendt, Peter; Larsen, Jan

    2007-01-01

    , but they capture neither the temporal dynamics nor dependencies among the individual feature dimensions. Here, a multivariate autoregressive feature model is proposed to solve this problem for music genre classification. This model gives two different feature sets, the diagonal autoregressive (DAR......) and multivariate autoregressive (MAR) features which are compared against the baseline mean-variance as well as two other temporal feature integration techniques. Reproducibility in performance ranking of temporal feature integration methods were demonstrated using two data sets with five and eleven music genres...

  16. Inflation and WMAP three year data. Features have a feature.

    Energy Technology Data Exchange (ETDEWEB)

    Covi, L.; Hamann, J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Melchiorri, A. [INFN, Roma (Italy)]|[Rome-3 Univ. (Italy). Dipt. di Fisica; Slosar, A. [Ljubljana Univ. (Slovenia). Faculty of Mathematics and Physics; Sorbera, I. [Rome-3 Univ. (Italy). Dipt. di Fisica

    2006-06-15

    The new three year WMAP data seem to confirm the presence of non-standard large scale features in the Cosmic Microwave Anisotropies power spectrum. While these features may hint at uncorrected experimental systematics, it is also possible to generate, in a cosmological way, oscillations on large angular scales by introducing a sharp step in the inflaton potential. Using current cosmological data, we derive constraints on the position, magnitude and gradient of a possible step in the inflaton potential. We show that a step in the potential, while strongly constrained by current data, is still allowed and may provide an interesting explanation to the currently measured deviations from the standard featureless spectrum. (Orig.)

  17. Feature singletons attract spatial attention independently of feature priming.

    Science.gov (United States)

    Yashar, Amit; White, Alex L; Fang, Wanghaoming; Carrasco, Marisa

    2017-08-01

    People perform better in visual search when the target feature repeats across trials (intertrial feature priming [IFP]). Here, we investigated whether repetition of a feature singleton's color modulates stimulus-driven shifts of spatial attention by presenting a probe stimulus immediately after each singleton display. The task alternated every two trials between a probe discrimination task and a singleton search task. We measured both stimulus-driven spatial attention (via the distance between the probe and singleton) and IFP (via repetition of the singleton's color). Color repetition facilitated search performance (IFP effect) when the set size was small. When the probe appeared at the singleton's location, performance was better than at the opposite location (stimulus-driven attention effect). The magnitude of this attention effect increased with the singleton's set size (which increases its saliency) but did not depend on whether the singleton's color repeated across trials, even when the previous singleton had been attended as a search target. Thus, our findings show that repetition of a salient singleton's color affects performance when the singleton is task relevant and voluntarily attended (as in search trials). However, color repetition does not affect performance when the singleton becomes irrelevant to the current task, even though the singleton does capture attention (as in probe trials). Therefore, color repetition per se does not make a singleton more salient for stimulus-driven attention. Rather, we suggest that IFP requires voluntary selection of color singletons in each consecutive trial.

  18. Quantitative paleotopography and paleogeography around the Gibraltar Arc (South Spain) during the Messinian Salinity Crisis

    Science.gov (United States)

    Elez, Javier; Silva, Pablo G.; Huerta, Pedro; Perucha, M. Ángeles; Civis, Jorge; Roquero, Elvira; Rodríguez-Pascua, Miguel A.; Bardají, Teresa; Giner-Robles, Jorge L.; Martínez-Graña, Antonio

    2016-12-01

    The Malaga basin contains an important geological record documenting the complex paleogeographic evolution of the Gibraltar Arc before, during and after the closure and desiccation of the Mediterranean Sea triggered by the "Messinian Salinity crisis" (MSC). Proxy paleo-elevation data, estimated from the stratigraphic and geomorphological records, allow the building of quantitative paleogeoid, paleotopographic and paleogeographic models for the three main paleogeographic stages: pre-MSC (Tortonian-early Messinian), syn-MSC (late Messinian) and post-MSC (early Pliocene). The methodological workflow combines classical contouring procedures used in geology and isobase map models from geomorphometric analyses and proxy data overprinted on present Digital Terrain Models. The resulting terrain quantitative models have been arranged, managed and computed in a GIS environment. The computed terrain models enable the exploration of past landscapes usually beyond the reach of classical geomorphological analyses and strongly improve the paleogeographic and paleotopographic knowledge of the study area. The resulting models suggest the occurrence of a set of uplifted littoral erosive and paleokarstic landforms that evolved during pre-MSC times. These uplifted landform assemblages can explain the origin of key elements of the present landscape, such as the Torcal de Antequera and the large amount of mogote-like relict hills present in the zone, in terms of ancient uplifted tropical islands. The most prominent landform is the extensive erosional platform dominating the Betic frontal zone that represents the relic Atlantic wave cut platform elaborated during late-Tortonian to early Messinian times. The amount of uplift derived from paleogeoid models suggests that the area rose by about 340 m during the MSC. This points to isostatic uplift triggered by differential erosional unloading (towards the Mediterranean) as the main factor controlling landscape evolution in the area during

  19. MRI features associated with acute appendicitis

    Energy Technology Data Exchange (ETDEWEB)

    Leeuwenburgh, Marjolein M.N. [University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands); Academic Medical Center, Department of Radiology (G1-223.1), Amsterdam (Netherlands); Jensch, Sebastiaan [Sint Lucas Andreas Hospital, Department of Radiology, Amsterdam (Netherlands); Gratama, Jan W.C. [Gelre Hospitals, Department of Radiology, Apeldoorn (Netherlands); Spilt, Aart [Kennemer Gasthuis, Department of Radiology, Haarlem (Netherlands); Wiarda, Bart M. [Alkmaar Medical Center, Department of Radiology, Alkmaar (Netherlands); Es, H.W. van [Sint Antonius Hospital, Department of Radiology, Nieuwegein (Netherlands); Cobben, Lodewijk P.J. [Haaglanden Medical Center, Department of Radiology, Leidschendam (Netherlands); Bossuyt, Patrick M.M. [University of Amsterdam, Department of Clinical Epidemiology, Academic Medical Center, Amsterdam (Netherlands); Boermeester, Marja A. [University of Amsterdam, Department of Surgery, Academic Medical Center, Amsterdam (Netherlands); Stoker, Jaap [University of Amsterdam, Department of Radiology, Academic Medical Center, Amsterdam (Netherlands); Collaboration: on behalf of the OPTIMAP study group

    2014-01-15

    To identify MRI features associated with appendicitis. Features expected to be associated with appendicitis were recorded in consensus by two expert radiologists on 223 abdominal MRIs in patients with suspected appendicitis. Nine MRI features were studied: appendix diameter >7 mm, appendicolith, peri-appendiceal fat infiltration, peri-appendiceal fluid, absence of gas in the appendix, appendiceal wall destruction, restricted diffusion of the appendiceal wall, lumen or focal fluid collections. Appendicitis was assigned as the final diagnosis in 117/223 patients. Associations between imaging features and appendicitis were evaluated with logistic regression analysis. All investigated features were significantly associated with appendicitis in univariate analysis. Combinations of two and three features were associated with a probability of appendicitis of 88 % and 92 %, respectively. In patients without any of the nine features, appendicitis was present in 2 % of cases. After multivariate analysis, only an appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall were significantly associated with appendicitis. The probability of appendicitis was 96 % in their presence and 2 % in their absence. An appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall have the strongest association with appendicitis on MRI. (orig.)

  20. MRI features associated with acute appendicitis

    International Nuclear Information System (INIS)

    Leeuwenburgh, Marjolein M.N.; Jensch, Sebastiaan; Gratama, Jan W.C.; Spilt, Aart; Wiarda, Bart M.; Es, H.W. van; Cobben, Lodewijk P.J.; Bossuyt, Patrick M.M.; Boermeester, Marja A.; Stoker, Jaap

    2014-01-01

    To identify MRI features associated with appendicitis. Features expected to be associated with appendicitis were recorded in consensus by two expert radiologists on 223 abdominal MRIs in patients with suspected appendicitis. Nine MRI features were studied: appendix diameter >7 mm, appendicolith, peri-appendiceal fat infiltration, peri-appendiceal fluid, absence of gas in the appendix, appendiceal wall destruction, restricted diffusion of the appendiceal wall, lumen or focal fluid collections. Appendicitis was assigned as the final diagnosis in 117/223 patients. Associations between imaging features and appendicitis were evaluated with logistic regression analysis. All investigated features were significantly associated with appendicitis in univariate analysis. Combinations of two and three features were associated with a probability of appendicitis of 88 % and 92 %, respectively. In patients without any of the nine features, appendicitis was present in 2 % of cases. After multivariate analysis, only an appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall were significantly associated with appendicitis. The probability of appendicitis was 96 % in their presence and 2 % in their absence. An appendix diameter >7 mm, peri-appendiceal fat infiltration and restricted diffusion of the appendiceal wall have the strongest association with appendicitis on MRI. (orig.)

  1. Clinical Features of Patients with Diffuse Alveolar Hemorrhage due to Negative-Pressure Pulmonary Edema.

    Science.gov (United States)

    Contou, Damien; Voiriot, Guillaume; Djibré, Michel; Labbé, Vincent; Fartoukh, Muriel; Parrot, Antoine

    2017-08-01

    Diffuse alveolar hemorrhage (DAH) with negative-pressure pulmonary edema (NPPE) is an uncommon yet life-threatening condition. We aimed at describing the circumstances, clinical, radiological, and bronchoscopic features, as well as the outcome of patients with NPPE-related DAH. We performed a retrospective, observational cohort study, using data prospectively collected over 35 years in an intensive care unit (ICU). Of the 149 patients admitted for DAH, we identified 18 NPPE episodes in 15 patients, one admitted four times for recurrent NPPE-related DAH. The patients were primarily young, male, and athletic. The NPPE setting was postoperative (n = 12/18, 67%) or following generalized tonic-clonic seizures (n = 6/18, 33%). Hemoptysis was almost constant (n = 17/18, 94%), yet rarely massive (>200 cc, n = 1/18, 6%), with anemia observed in 10 (56%) episodes. The DAH triad (hemoptysis, anemia, and pulmonary infiltrates) was observed in 50% of episodes (n = 9/18), and acute respiratory failure in 94% (n = 17/18). Chest computed tomography revealed diffuse bilateral ground glass opacities (n = 10/10, 100%), while bronchoscopy detected bilateral hemorrhage (n = 12/12, 100%) and macroscopically bloody bronchoalveolar lavage, with siderophage absence in most (n = 7/8, 88%), indicating acute DAH. While one episode proved fatal, the other 17 recovered rapidly, with a mean ICU stay lasting 4.6 (2-15) days. Typically, the evolution was rapidly favorable under supportive care. NPPE-related DAH is a rare life-threatening condition occurring primarily after tonic-clonic generalized seizure or generalized anesthesia. Clinical circumstances are a key to its diagnosis. Early diagnosis and recognition likely allow for successful management of this potentially serious complication, whereas ictal-DAH appears ominous in epileptic patients.

  2. Textural features for radar image analysis

    Science.gov (United States)

    Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

    1981-01-01

    Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

  3. Epidemiology and Clinical Features of Ciguatera Fish Poisoning in Hong Kong

    Directory of Open Access Journals (Sweden)

    Thomas Y. K. Chan

    2014-10-01

    Full Text Available In the present review, the main objective was to describe the epidemiology and clinical features of ciguatera fish poisoning in Hong Kong. From 1989 to 2008, the annual incidence of ciguatera varied between 3.3 and 64.9 (median 10.2 per million people. The groupers have replaced the snappers as the most important cause of ciguatera. Pacific-ciguatoxins (CTX are most commonly present in reef fish samples implicated in ciguatera outbreaks. In affected subjects, the gastrointestinal symptoms often subside within days, whereas the neurological symptoms can persist for weeks or even months. Bradycardia and hypotension, which can be life-threatening, are common. Treatment of ciguatera is primarily supportive and symptomatic. Intravenous mannitol (1 g/kg has also been suggested. To prevent ciguatera outbreaks, the public should be educated to avoid eating large coral reef fishes, especially the CTX-rich parts. A Code of Practice on Import and Sale of Live Marine Fish for Human Consumption for Prevention and Control of Ciguatera Fish Poisoning was introduced from 2004 to 2013. The Food Safety Ordinance with a tracing mechanism came into full effect in February 2012. The Government would be able to trace the sources of the fishes more effectively and take prompt action when dealing with ciguatera incidents.

  4. Epidemiology and clinical features of ciguatera fish poisoning in Hong Kong.

    Science.gov (United States)

    Chan, Thomas Y K

    2014-10-20

    In the present review, the main objective was to describe the epidemiology and clinical features of ciguatera fish poisoning in Hong Kong. From 1989 to 2008, the annual incidence of ciguatera varied between 3.3 and 64.9 (median 10.2) per million people. The groupers have replaced the snappers as the most important cause of ciguatera. Pacific-ciguatoxins (CTX) are most commonly present in reef fish samples implicated in ciguatera outbreaks. In affected subjects, the gastrointestinal symptoms often subside within days, whereas the neurological symptoms can persist for weeks or even months. Bradycardia and hypotension, which can be life-threatening, are common. Treatment of ciguatera is primarily supportive and symptomatic. Intravenous mannitol (1 g/kg) has also been suggested. To prevent ciguatera outbreaks, the public should be educated to avoid eating large coral reef fishes, especially the CTX-rich parts. A Code of Practice on Import and Sale of Live Marine Fish for Human Consumption for Prevention and Control of Ciguatera Fish Poisoning was introduced from 2004 to 2013. The Food Safety Ordinance with a tracing mechanism came into full effect in February 2012. The Government would be able to trace the sources of the fishes more effectively and take prompt action when dealing with ciguatera incidents.

  5. Epidemiology and Clinical Features of Ciguatera Fish Poisoning in Hong Kong

    Science.gov (United States)

    Chan, Thomas Y. K.

    2014-01-01

    In the present review, the main objective was to describe the epidemiology and clinical features of ciguatera fish poisoning in Hong Kong. From 1989 to 2008, the annual incidence of ciguatera varied between 3.3 and 64.9 (median 10.2) per million people. The groupers have replaced the snappers as the most important cause of ciguatera. Pacific-ciguatoxins (CTX) are most commonly present in reef fish samples implicated in ciguatera outbreaks. In affected subjects, the gastrointestinal symptoms often subside within days, whereas the neurological symptoms can persist for weeks or even months. Bradycardia and hypotension, which can be life-threatening, are common. Treatment of ciguatera is primarily supportive and symptomatic. Intravenous mannitol (1 g/kg) has also been suggested. To prevent ciguatera outbreaks, the public should be educated to avoid eating large coral reef fishes, especially the CTX-rich parts. A Code of Practice on Import and Sale of Live Marine Fish for Human Consumption for Prevention and Control of Ciguatera Fish Poisoning was introduced from 2004 to 2013. The Food Safety Ordinance with a tracing mechanism came into full effect in February 2012. The Government would be able to trace the sources of the fishes more effectively and take prompt action when dealing with ciguatera incidents. PMID:25333356

  6. How lovebirds maneuver rapidly using super-fast head saccades and image feature stabilization

    NARCIS (Netherlands)

    Kress, Daniel; Bokhorst, Van Evelien; Lentink, David

    2015-01-01

    Diurnal flying animals such as birds depend primarily on vision to coordinate their flight path during goal-directed flight tasks. To extract the spatial structure of the surrounding environment, birds are thought to use retinal image motion (optical flow) that is primarily induced by motion of

  7. Conjunctive Coding of Complex Object Features

    Science.gov (United States)

    Erez, Jonathan; Cusack, Rhodri; Kendall, William; Barense, Morgan D.

    2016-01-01

    Critical to perceiving an object is the ability to bind its constituent features into a cohesive representation, yet the manner by which the visual system integrates object features to yield a unified percept remains unknown. Here, we present a novel application of multivoxel pattern analysis of neuroimaging data that allows a direct investigation of whether neural representations integrate object features into a whole that is different from the sum of its parts. We found that patterns of activity throughout the ventral visual stream (VVS), extending anteriorly into the perirhinal cortex (PRC), discriminated between the same features combined into different objects. Despite this sensitivity to the unique conjunctions of features comprising objects, activity in regions of the VVS, again extending into the PRC, was invariant to the viewpoints from which the conjunctions were presented. These results suggest that the manner in which our visual system processes complex objects depends on the explicit coding of the conjunctions of features comprising them. PMID:25921583

  8. Cost that is Directly Incurred as a Result of Operating the Train Service on the 1520 mm Rail with Primarily Freight Transportation

    OpenAIRE

    Hudenko, J; Ribakova, N; Počs, R

    2016-01-01

    Under the Directive 2012/34/EU (21 November 2012) "the charges for … [rail] infrastructure … shall be set at the cost that is directly incurred as a result of operating the train service". This charging rule is new for Baltic States’ railways, where due to the favorable geographic position a full cost application without detalization was possible. Although, a big number of relevant studies on the issue was made in EU, all of them covered only 1435mm railways with primarily passenger transport...

  9. Hong Kong English: phonological features

    Directory of Open Access Journals (Sweden)

    Irina-Ana Drobot

    2008-01-01

    Full Text Available The aim of the paper is to present phonological features of Hong Kong English, which is a variety of New English. I examine features of the sound system (vowel and consonantal systems, characteristics of stress, rhythm, intonation, and phonological processes of the English spoken by Hongkongers. The way in which the accent and characteristics of the Hong Kong variety of English differs from standard, RP English is pointed out. Influences of Chinese and Cantonese on the phonological features of Hong Kong English are noticeable

  10. Personality Features of Motorists

    Directory of Open Access Journals (Sweden)

    Andrej Justinek

    1997-12-01

    Full Text Available Justinek tries to answer the question whether or not motorists have specific personality features which predispose them for safe and well-mannered driving. A good driver should have sensory abilities which enable psycho-motor coordiation of a vehicle, intellectual and cognitive features that are important for solving problems in new, unknown situations, and emotional and motivational trails defining a driver's maturity. Justmek advocates the belief that in training future drivers greater attention should be paid to developing these features which are vital for safe driving and appropriate behaviour of drivers in traffic. He also suggests certain learning methods leading to development of the above­ mentioned personality traits. Justinek introduces the notion of the 'philosophy of driving' as an essential educational category in training future drivers.

  11. Structural features of flower trichomes in drug eyebright (Euphrasia stricta D. Wolff EX J. F. Lehm.

    Directory of Open Access Journals (Sweden)

    Weronika Haratym

    2014-01-01

    Full Text Available Euphrasia stricta D. Wolff ex J. F. Lehm. (Orobanchaceae is a representative of plants that are widely used in folk medicine, phytomedicine, and homeopathy. The medicinal raw material derived from the drug eyebright is applied primarily in treatment of ophthalmic diseases. The investigations of trichomes in drug eyebright (Euphrasia stricta D. Wolff ex J. F. Lehm were conducted in 2010–2011. Using light microscopy and scanning electron microscopy, their location and morphological and anatomical features were identified. Three types of non-glandular trichomes were found: short unicellular, long 1–2 celled, and long 2-celled with wall ornamentation. Additionally, 7 types of glandular trichomes were found; these included: unicellular clavate, 2–3-celled clavate, capitate with a unicellular head and a 3-cel- led stalk, capitate with a unicellular head and a 2-celled stalk, capitate with a 2-celled head, conical papillae, and ribbon-like trichomes with wall thickening.

  12. Features for detecting smoke in laparoscopic videos

    Directory of Open Access Journals (Sweden)

    Jalal Nour Aldeen

    2017-09-01

    Full Text Available Video-based smoke detection in laparoscopic surgery has different potential applications, such as the automatic addressing of surgical events associated with the electrocauterization task and the development of automatic smoke removal. In the literature, video-based smoke detection has been studied widely for fire surveillance systems. Nevertheless, the proposed methods are insufficient for smoke detection in laparoscopic videos because they often depend on assumptions which rarely hold in laparoscopic surgery such as static camera. In this paper, ten visual features based on motion, texture and colour of smoke are proposed and evaluated for smoke detection in laparoscopic videos. These features are RGB channels, energy-based feature, texture features based on gray level co-occurrence matrix (GLCM, HSV colour space feature, features based on the detection of moving regions using optical flow and the smoke colour in HSV colour space. These features were tested on four laparoscopic cholecystectomy videos. Experimental observations show that each feature can provide valuable information in performing the smoke detection task. However, each feature has weaknesses to detect the presence of smoke in some cases. By combining all proposed features smoke with high and even low density can be identified robustly and the classification accuracy increases significantly.

  13. Novel Features for Brain-Computer Interfaces

    Science.gov (United States)

    Woon, W. L.; Cichocki, A.

    2007-01-01

    While conventional approaches of BCI feature extraction are based on the power spectrum, we have tried using nonlinear features for classifying BCI data. In this paper, we report our test results and findings, which indicate that the proposed method is a potentially useful addition to current feature extraction techniques. PMID:18364991

  14. Shallow gas accumulation in sediments of the Patos Lagoon, Southern Brazil

    Energy Technology Data Exchange (ETDEWEB)

    Weschenfelder, Jair; Corrrea, Iran C.S.; Pereira, Carla M.; Vasconcellos, Vinicius E.B. de [Universidade Federal do Rio Grande do Sul, Porto Alegre, RS (Brazil). Inst. de Geociencias; Aliotta, Salvador [Instituto Argentino de Oceanografia Complejo CRIBABB, Bahia Blanca (Argentina)

    2006-07-15

    A high resolution seismic survey was conducted in the Patos Lagoon, southern Brazil, aboard of the research vessel LARUS of the Fundacao Universidade Federal do Rio Grande (FURG). Around 400 km of 3.5 k Hz seismic profiles were collected, which provided acoustic signals of good penetration depth and resolution. Seismic anomalies, including turbidity and pocket gas, revealed that gas-charged sediments are common in several areas of the lagoon. The gas accumulations in the Patos Lagoon are controlled by the spatial distribution of the sedimentary facies. Either in 'curtains' or in 'acoustic turbid zones', the main gas accumulations occur in areas with paleotopographic lows related to fluvial channels and valleys developed in the Rio Grande do Sul coastal plain during regressive/transgressive events of the Quaternary. (author)

  15. Diet Quality and Nutrient Intake of Urban Overweight and Obese Primarily African American Older Adults with Osteoarthritis

    Directory of Open Access Journals (Sweden)

    Sevasti Vergis

    2018-04-01

    Full Text Available Diet quality may be a unique target for preventing and managing obesity-related osteoarthritis (OA. Using the Healthy Eating Index-2010 (HEI-2010, this study examined the nutrient intake and diet quality of 400 urban overweight and obese primarily African American older adults with self-reported lower extremity OA. Associations between sociodemographic and health-related factors and diet quality were explored. Participants (mean age 67.8 years, SD 5.9 were included. Habitual dietary intake was assessed using a food frequency questionnaire (FFQ. Nutrient intake and diet quality were calculated from the FFQ. Results indicated that diet quality needs improvement (HEI-2010: 66.3 (SD 10.5. Age, body mass index, employment (multivariable model only, and OA severity (bivariate model only were significant predictors of HEI-2010 total score in linear models. Mean intakes for fiber, calcium, and vitamin D were below recommendations, while percentage of calories as total fat exceeded recommendations. These findings can inform future dietary intervention trials and public health messaging for a sub-population at a high risk for obesity-related OA.

  16. Fragment-Specific Fixation Versus Volar Locking Plates in Primarily Nonreducible or Secondarily Redisplaced Distal Radius Fractures: A Randomized Controlled Study.

    Science.gov (United States)

    Landgren, Marcus; Abramo, Antonio; Geijer, Mats; Kopylov, Philippe; Tägil, Magnus

    2017-03-01

    To compare the patient-reported, clinical, and radiographic outcome of 2 methods of internal fixation in distal radius fractures. Fifty patients, mean age 56 years (range, 21-69 years) with primarily nonreducible or secondarily redisplaced distal radius fractures were randomized to open reduction internal fixation using volar locking plates (n = 25) or fragment-specific fixation (n = 25). The patients were assessed on grip strength, range of motion, patient-reported outcome (Quick Disabilities of the Arm, Shoulder, and Hand), pain (visual analog scale), health-related quality of life (Short Form-12 [SF-12]), and radiographic evaluation. Grip strength at 12 months was the primary outcome measure. At 12 months, no difference was found in grip strength, which was 90% of the uninjured side in the volar plate group and 87% in the fragment-specific fixation group. No differences were found in range of motion and the median Quick Disabilities of the Arm, Shoulder, and Hand score was 5 in both groups. The overall complication rate was significant, 21% in the volar locking plate group, compared with 52% in the fragment-specific group. In treatment of primarily nonreducible or secondarily redisplaced distal radius fractures, volar locking plates and fragment-specific fixation both achieve good and similar patient-reported outcomes, although more complications were recorded in the fragment-specific group. Therapeutic II. Copyright © 2017 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

  17. Ontology patterns for complex topographic feature yypes

    Science.gov (United States)

    Varanka, Dalia E.

    2011-01-01

    Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

  18. Using features of a Creole language to reconstruct population history and cultural evolution: tracing the English origins of Sranan.

    Science.gov (United States)

    Sherriah, André C; Devonish, Hubert; Thomas, Ewart A C; Creanza, Nicole

    2018-04-05

    Creole languages are formed in conditions where speakers from distinct languages are brought together without a shared first language, typically under the domination of speakers from one of the languages and particularly in the context of the transatlantic slave trade and European colonialism. One such Creole in Suriname, Sranan, developed around the mid-seventeenth century, primarily out of contact between varieties of English from England, spoken by the dominant group, and multiple West African languages. The vast majority of the basic words in Sranan come from the language of the dominant group, English. Here, we compare linguistic features of modern-day Sranan with those of English as spoken in 313 localities across England. By way of testing proposed hypotheses for the origin of English words in Sranan, we find that 80% of the studied features of Sranan can be explained by similarity to regional dialect features at two distinct input locations within England, a cluster of locations near the port of Bristol and another cluster near Essex in eastern England. Our new hypothesis is supported by the geographical distribution of specific regional dialect features, such as post-vocalic rhoticity and word-initial 'h', and by phylogenetic analysis of these features, which shows evidence favouring input from at least two English dialects in the formation of Sranan. In addition to explicating the dialect features most prominent in the linguistic evolution of Sranan, our historical analyses also provide supporting evidence for two distinct hypotheses about the likely geographical origins of the English speakers whose language was an input to Sranan. The emergence as a likely input to Sranan of the speech forms of a cluster near Bristol is consistent with historical records, indicating that most of the indentured servants going to the Americas between 1654 and 1666 were from Bristol and nearby counties, and that of the cluster near Essex is consistent with documents

  19. Architectural evidence of dune collapse in the Navajo Sandstone, Zion National Park, Utah

    Science.gov (United States)

    Ford, Colby; Bryant, Gerald; Nick, Kevin E.

    2016-10-01

    The Canyon Overlook Trail of Zion National Park follows an outcrop of Navajo Sandstone, which displays a uniquely well-exposed assemblage of features associated with failure of the lee face of a large eolian dune, and run-out over an expanse of interdune sediments downwind of that bedform. Exposed features include dramatic folds in the interdune succession and a stacked series of thrust sheets incorporating both interdune and overlying dune deposits. Thrust surfaces display consistent strikes, parallel to those of undeformed foresets, and incorporate zones of brittle failure and fluid deformation, including folds overturned in the direction of foreset dip. These features correspond to predictions made by a previous researcher's model of dune collapse, formulated from less fortuitously exposed architectures in the Navajo Sandstone. Unlike the previous model, however, this site preserves distinct indications that the bulk of deformed material accumulated above the level of the contemporary interdune surface, in an aggradational succession. Paleotopographic reconstruction, based on preserved facies relationships at this site, indicates the presence of a large dune, partially encroached upon a well-developed wet interdune succession, made up of two half-meter carbonate mud layers, separated by a meter of medium-grained sand. Trapping of pore water pressure between these mud layers during liquefaction reduced shear strength in this interval, facilitating the collapse of the lee face of the upwind dune into the interdune area, and transmitted resultant shear forces to distal portions of the interdune expanse, in the shallow subsurface. Shear failure developed along bedding planes in the horizontally laminated carbonate muds, which provided both lubrication of the shear surfaces and structural support for the preservation of coherent thrust sheets during production of an imbricated succession of shear zones in the toe portion of the slump. Individual shear surfaces

  20. Feature-level domain adaptation

    DEFF Research Database (Denmark)

    Kouw, Wouter M.; Van Der Maaten, Laurens J P; Krijthe, Jesse H.

    2016-01-01

    -level domain adaptation (flda), that models the dependence between the two domains by means of a feature-level transfer model that is trained to describe the transfer from source to target domain. Subsequently, we train a domain-adapted classifier by minimizing the expected loss under the resulting transfer...... modeled via a dropout distribution, which allows the classiffier to adapt to differences in the marginal probability of features in the source and the target domain. Our experiments on several real-world problems show that flda performs on par with state-of-the-art domainadaptation techniques.......Domain adaptation is the supervised learning setting in which the training and test data are sampled from different distributions: training data is sampled from a source domain, whilst test data is sampled from a target domain. This paper proposes and studies an approach, called feature...

  1. Light field morphing using 2D features.

    Science.gov (United States)

    Wang, Lifeng; Lin, Stephen; Lee, Seungyong; Guo, Baining; Shum, Heung-Yeung

    2005-01-01

    We present a 2D feature-based technique for morphing 3D objects represented by light fields. Existing light field morphing methods require the user to specify corresponding 3D feature elements to guide morph computation. Since slight errors in 3D specification can lead to significant morphing artifacts, we propose a scheme based on 2D feature elements that is less sensitive to imprecise marking of features. First, 2D features are specified by the user in a number of key views in the source and target light fields. Then the two light fields are warped view by view as guided by the corresponding 2D features. Finally, the two warped light fields are blended together to yield the desired light field morph. Two key issues in light field morphing are feature specification and warping of light field rays. For feature specification, we introduce a user interface for delineating 2D features in key views of a light field, which are automatically interpolated to other views. For ray warping, we describe a 2D technique that accounts for visibility changes and present a comparison to the ideal morphing of light fields. Light field morphing based on 2D features makes it simple to incorporate previous image morphing techniques such as nonuniform blending, as well as to morph between an image and a light field.

  2. Nonmotor Features in Atypical Parkinsonism.

    Science.gov (United States)

    Bhatia, Kailash P; Stamelou, Maria

    2017-01-01

    Atypical parkinsonism (AP) comprises mainly multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD), which are distinct pathological entities, presenting with a wide phenotypic spectrum. The classic syndromes are now called MSA-parkinsonism (MSA-P), MSA-cerebellar type (MSA-C), Richardson's syndrome, and corticobasal syndrome. Nonmotor features in AP have been recognized almost since the initial description of these disorders; however, research has been limited. Autonomic dysfunction is the most prominent nonmotor feature of MSA, but also gastrointestinal symptoms, sleep dysfunction, and pain, can be a feature. In PSP and CBD, the most prominent nonmotor symptoms comprise those deriving from the cognitive/neuropsychiatric domain. Apart from assisting the clinician in the differential diagnosis with Parkinson's disease, nonmotor features in AP have a big impact on quality of life and prognosis of AP and their treatment poses a major challenge for clinicians. © 2017 Elsevier Inc. All rights reserved.

  3. Wilson’s disease: Atypical imaging features

    Directory of Open Access Journals (Sweden)

    Venugopalan Y Vishnu

    2016-10-01

    Full Text Available Wilson’s disease is a genetic movement disorder with characteristic clinical and imaging features. We report a 17- year-old boy who presented with sialorrhea, hypophonic speech, paraparesis with repeated falls and recurrent seizures along with cognitive decline. He had bilateral Kayser Flescher rings. Other than the typical features of Wilson’s disease in cranial MRI, there were extensive white matter signal abnormalities (T2 and FLAIR hyperintensities and gyriform contrast enhancement which are rare imaging features in Wilson's disease. A high index of suspicion is required to diagnose Wilson’s disease when atypical imaging features are present.

  4. Multimodal Feature Learning for Video Captioning

    Directory of Open Access Journals (Sweden)

    Sujin Lee

    2018-01-01

    Full Text Available Video captioning refers to the task of generating a natural language sentence that explains the content of the input video clips. This study proposes a deep neural network model for effective video captioning. Apart from visual features, the proposed model learns additionally semantic features that describe the video content effectively. In our model, visual features of the input video are extracted using convolutional neural networks such as C3D and ResNet, while semantic features are obtained using recurrent neural networks such as LSTM. In addition, our model includes an attention-based caption generation network to generate the correct natural language captions based on the multimodal video feature sequences. Various experiments, conducted with the two large benchmark datasets, Microsoft Video Description (MSVD and Microsoft Research Video-to-Text (MSR-VTT, demonstrate the performance of the proposed model.

  5. Language identification using excitation source features

    CERN Document Server

    Rao, K Sreenivasa

    2015-01-01

    This book discusses the contribution of excitation source information in discriminating language. The authors focus on the excitation source component of speech for enhancement of language identification (LID) performance. Language specific features are extracted using two different modes: (i) Implicit processing of linear prediction (LP) residual and (ii) Explicit parameterization of linear prediction residual. The book discusses how in implicit processing approach, excitation source features are derived from LP residual, Hilbert envelope (magnitude) of LP residual and Phase of LP residual; and in explicit parameterization approach, LP residual signal is processed in spectral domain to extract the relevant language specific features. The authors further extract source features from these modes, which are combined for enhancing the performance of LID systems. The proposed excitation source features are also investigated for LID in background noisy environments. Each chapter of this book provides the motivatio...

  6. Guilt by Association: The 13 Micron Dust Emission Feature and Its Correlation to Other Gas and Dust Features

    Science.gov (United States)

    Sloan, G. C.; Kraemer, Kathleen E.; Goebel, J. H.; Price, Stephan D.

    2003-09-01

    A study of all full-scan spectra of optically thin oxygen-rich circumstellar dust shells in the database produced by the Short Wavelength Spectrometer on ISO reveals that the strength of several infrared spectral features correlates with the strength of the 13 μm dust feature. These correlated features include dust features at 19.8 and 28.1 μm and the bands produced by warm carbon dioxide molecules (the strongest of which are at 13.9, 15.0, and 16.2 μm). The database does not provide any evidence for a correlation of the 13 μm feature with a dust feature at 32 μm, and it is more likely that a weak emission feature at 16.8 μm arises from carbon dioxide gas rather than dust. The correlated dust features at 13, 20, and 28 μm tend to be stronger with respect to the total dust emission in semiregular and irregular variables associated with the asymptotic giant branch than in Mira variables or supergiants. This family of dust features also tends to be stronger in systems with lower infrared excesses and thus lower mass-loss rates. We hypothesize that the dust features arise from crystalline forms of alumina (13 μm) and silicates (20 and 28 μm). Based on observations with the ISO, a European Space Agency (ESA) project with instruments funded by ESA member states (especially the Principal Investigator countries: France, Germany, the Netherlands, and the United Kingdom) and with the participation of the Institute of Space and Astronautical Science (ISAS) and the National Aeronautics and Space Administration (NASA).

  7. Comparison of advanced mid-sized reactors regarding passive features, core damage frequencies and core melt retention features

    International Nuclear Information System (INIS)

    Wider, H.

    2005-01-01

    New Light Water Reactors, whose regular safety systems are complemented by passive safety systems, are ready for the market. The special aspect of passive safety features is their actuation and functioning independent of the operator. They add significantly to reduce the core damage frequency (CDF) since the operator continues to play its independent role in actuating the regular safety devices based on modern instrumentation and control (I and C). The latter also has passive features regarding the prevention of accidents. Two reactors with significant passive features that are presently offered on the market are the AP1000 PWR and the SWR 1000 BWR. Their passive features are compared and also their core damage frequencies (CDF). The latter are also compared with those of a VVER-1000. A further discussion about the two passive plants concerns their mitigating features for severe accidents. Regarding core-melt retention both rely on in-vessel cooling of the melt. The new VVER-1000 reactor, on the other hand features a validated ex-vessel concept. (author)

  8. Controllable edge feature sharpening for dental applications.

    Science.gov (United States)

    Fan, Ran; Jin, Xiaogang

    2014-01-01

    This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

  9. Controllable Edge Feature Sharpening for Dental Applications

    Directory of Open Access Journals (Sweden)

    Ran Fan

    2014-01-01

    Full Text Available This paper presents a new approach to sharpen blurred edge features in scanned tooth preparation surfaces generated by structured-light scanners. It aims to efficiently enhance the edge features so that the embedded feature lines can be easily identified in dental CAD systems, and to avoid unnatural oversharpening geometry. We first separate the feature regions using graph-cut segmentation, which does not require a user-defined threshold. Then, we filter the face normal vectors to propagate the geometry from the smooth region to the feature region. In order to control the degree of the sharpness, we propose a feature distance measure which is based on normal tensor voting. Finally, the vertex positions are updated according to the modified face normal vectors. We have applied the approach to scanned tooth preparation models. The results show that the blurred edge features are enhanced without unnatural oversharpening geometry.

  10. FeatureMap3D - a tool to map protein features and sequence conservation onto homologous structures in the PDB

    DEFF Research Database (Denmark)

    Wernersson, Rasmus; Rapacki, Krzysztof; Stærfeldt, Hans Henrik

    2006-01-01

    FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) f...

  11. Glacial Features (Point) - Quad 168 (EPPING, NH)

    Data.gov (United States)

    University of New Hampshire — The Glacial Features (Point) layer describes point features associated with surficial geology. These glacial features include, but are not limited to, delta forsets,...

  12. Partial Epilepsy with Auditory Features

    Directory of Open Access Journals (Sweden)

    J Gordon Millichap

    2004-07-01

    Full Text Available The clinical characteristics of 53 sporadic (S cases of idiopathic partial epilepsy with auditory features (IPEAF were analyzed and compared to previously reported familial (F cases of autosomal dominant partial epilepsy with auditory features (ADPEAF in a study at the University of Bologna, Italy.

  13. Feature Extraction Using Fractal Codes

    NARCIS (Netherlands)

    B.A.M. Schouten (Ben); P.M. de Zeeuw (Paul)

    1999-01-01

    htmlabstractFast and successful searching for an object in a multimedia database is a highly desirable functionality. Several approaches to content based retrieval for multimedia databases can be found in the literature [9,10,12,14,17]. The approach we consider is feature extraction. A feature can

  14. Remodularizing Java programs for comprehension of features

    DEFF Research Database (Denmark)

    Olszak, Andrzej; Jørgensen, Bo Nørregaard

    2009-01-01

    . In absence of these mechanisms, feature implementations tend to be scattered and tangled in terms of object-oriented abstractions, making the code implementing features difficult to locate and comprehend. In this paper we present a semi-automatic method for feature-oriented remodularization of Java programs....... Our method uses execution traces to locate implementations of features, and Java packages to establish explicit feature modules. To evaluate usefulness of the approach, we present a case study where we apply our method to two real-world software systems. The obtained results indicate a significant...

  15. Patch layout generation by detecting feature networks

    KAUST Repository

    Cao, Yuanhao

    2015-02-01

    The patch layout of 3D surfaces reveals the high-level geometric and topological structures. In this paper, we study the patch layout computation by detecting and enclosing feature loops on surfaces. We present a hybrid framework which combines several key ingredients, including feature detection, feature filtering, feature curve extension, patch subdivision and boundary smoothing. Our framework is able to compute patch layouts through concave features as previous approaches, but also able to generate nice layouts through smoothing regions. We demonstrate the effectiveness of our framework by comparing with the state-of-the-art methods.

  16. Feature coding for image representation and recognition

    CERN Document Server

    Huang, Yongzhen

    2015-01-01

    This brief presents a comprehensive introduction to feature coding, which serves as a key module for the typical object recognition pipeline. The text offers a rich blend of theory and practice while reflects the recent developments on feature coding, covering the following five aspects: (1) Review the state-of-the-art, analyzing the motivations and mathematical representations of various feature coding methods; (2) Explore how various feature coding algorithms evolve along years; (3) Summarize the main characteristics of typical feature coding algorithms and categorize them accordingly; (4) D

  17. Evaluating a County-Sponsored Social Marketing Campaign to Increase Mothers' Initiation of HPV Vaccine for their Pre-teen Daughters in a Primarily Rural Area.

    Science.gov (United States)

    Cates, Joan R; Shafer, Autumn; Diehl, Sandra J; Deal, Allison M

    2011-01-01

    Routine vaccination against human papillomavirus (HPV), the main cause of cervical cancer, is recommended for 11-12 year old girls, yet vaccine uptake is low. This study evaluates a social marketing campaign initiated by 13 North Carolina counties to raise awareness among parents and reduce barriers to accessing the vaccine in a primarily rural area. The 3-month campaign targeted mothers of girls ages 11-12 and healthcare practices serving pre-teen girls in four counties. Principles of social marketing were: product (recommended vaccine against HPV), price (cost, perception of safety and efficacy, and access), promotion (posters, brochures, website, news releases, doctor's recommendation), and place (doctors' offices, retail outlets). We analyzed (1) website traffic, hotline calls, and media placement; (2) cross-sectional surveys of mothers and providers; and (3) HPV immunization rates in intervention versus non-intervention counties. Of respondent mothers (n=225), 82% heard or saw campaign messages or materials. Of respondent providers (n=35), 94% used campaign brochures regularly or occasionally in conversations with parents. HPV vaccination rates within six months of campaign launch were 2% higher for 9-13 year old girls in two of the four intervention counties compared to 96 non-intervention counties. This evaluation supports campaign use in other primarily rural and underserved areas.

  18. Currency features for visually impaired people

    Science.gov (United States)

    Hyland, Sandra L.; Legge, Gordon E.; Shannon, Robert R.; Baer, Norbert S.

    1996-03-01

    The estimated 3.7 million Americans with low vision experience a uniquely difficult task in identifying the denominations of U.S. banknotes because the notes are remarkably uniform in size, color, and general design. The National Research Council's Committee on Currency Features Usable by the Visually Impaired assessed features that could be used by people who are visually disabled to distinguish currency from other documents and to denominate and authenticate banknotes using available technology. Variation of length and height, introduction of large numerals on a uniform, high-contrast background, use of different colors for each of the six denominations printed, and the introduction of overt denomination codes that could lead to development of effective, low-cost devices for examining banknotes were all deemed features available now. Issues affecting performance, including the science of visual and tactile perception, were addressed for these features, as well as for those features requiring additional research and development. In this group the committee included durable tactile features such as those printed with transparent ink, and the production of currency with holes to indicate denomination. Among long-range approaches considered were the development of technologically advanced devices and smart money.

  19. Fall Detection Using Smartphone Audio Features.

    Science.gov (United States)

    Cheffena, Michael

    2016-07-01

    An automated fall detection system based on smartphone audio features is developed. The spectrogram, mel frequency cepstral coefficents (MFCCs), linear predictive coding (LPC), and matching pursuit (MP) features of different fall and no-fall sound events are extracted from experimental data. Based on the extracted audio features, four different machine learning classifiers: k-nearest neighbor classifier (k-NN), support vector machine (SVM), least squares method (LSM), and artificial neural network (ANN) are investigated for distinguishing between fall and no-fall events. For each audio feature, the performance of each classifier in terms of sensitivity, specificity, accuracy, and computational complexity is evaluated. The best performance is achieved using spectrogram features with ANN classifier with sensitivity, specificity, and accuracy all above 98%. The classifier also has acceptable computational requirement for training and testing. The system is applicable in home environments where the phone is placed in the vicinity of the user.

  20. Flexible feature interface for multimedia sources

    Science.gov (United States)

    Coffland, Douglas R [Livermore, CA

    2009-06-09

    A flexible feature interface for multimedia sources system that includes a single interface for the addition of features and functions to multimedia sources and for accessing those features and functions from remote hosts. The interface utilizes the export statement: export "C" D11Export void FunctionName(int argc, char ** argv,char * result, SecureSession *ctrl) or the binary equivalent of the export statement.

  1. Prostatic adenocarcinoma with glomeruloid features.

    Science.gov (United States)

    Pacelli, A; Lopez-Beltran, A; Egan, A J; Bostwick, D G

    1998-05-01

    A wide variety of architectural patterns of adenocarcinoma may be seen in the prostate. We have recently encountered a hitherto-undescribed pattern of growth characterized by intraluminal ball-like clusters of cancer cells reminiscent of renal glomeruli, which we refer to as prostatic adenocarcinoma with glomeruloid features. To define the architectural features, frequency, and distribution of prostatic adenocarcinoma with glomeruloid features, we reviewed 202 totally embedded radical prostatectomy specimens obtained between October 1992 and April 1994 from the files of the Mayo Clinic. This series was supplemented by 100 consecutive needle biopsies with prostatic cancer from January to February 1996. Prostatic adenocarcinoma with glomeruloid features was characterized by round to oval epithelial tufts growing within malignant acini, often supported by a fibrovascular core. The epithelial cells were sometimes arranged in semicircular concentric rows separated by clefted spaces. In the radical prostatectomy specimens, nine cases (4.5%) had glomeruloid features. The glomeruloid pattern constituted 5% to 20% of each cancer (mean, 8.33%) and was usually located at the apex or in the peripheral zone of the prostate. Seven cases were associated with a high Gleason score (7 or 8), one with a score of 6, and one with a score of 5. All cases were associated with high-grade prostatic intraepithelial neoplasia and extensive perineural invasion. Pathological stages included T2c (three cases), T3b (four cases), and T3c (two cases); one of the T3b cases had lymph node metastases (N1). Three (3%) of 100 consecutive routine needle biopsy specimens with cancer showed glomeruloid features, and this pattern constituted 5% to 10% of each cancer (mean, 6.7%). The Gleason score was 6 for two cases and 8 for one case. Two cases were associated with high-grade prostatic intraepithelial neoplasia, and one case had perineural invasion. Glomeruloid features were not observed in any benign or

  2. Feature extraction using fractal codes

    NARCIS (Netherlands)

    B.A.M. Ben Schouten; Paul M. de Zeeuw

    1999-01-01

    Fast and successful searching for an object in a multimedia database is a highly desirable functionality. Several approaches to content based retrieval for multimedia databases can be found in the literature [9,10,12,14,17]. The approach we consider is feature extraction. A feature can be seen as a

  3. Iris recognition based on key image feature extraction.

    Science.gov (United States)

    Ren, X; Tian, Q; Zhang, J; Wu, S; Zeng, Y

    2008-01-01

    In iris recognition, feature extraction can be influenced by factors such as illumination and contrast, and thus the features extracted may be unreliable, which can cause a high rate of false results in iris pattern recognition. In order to obtain stable features, an algorithm was proposed in this paper to extract key features of a pattern from multiple images. The proposed algorithm built an iris feature template by extracting key features and performed iris identity enrolment. Simulation results showed that the selected key features have high recognition accuracy on the CASIA Iris Set, where both contrast and illumination variance exist.

  4. Vehicle barriers: emphasis on natural features

    International Nuclear Information System (INIS)

    Adams, K.G.; Roscoe, B.J.

    1985-07-01

    The recent increase in the use of car and truck bombs by terrorist organizations has led NRC to evaluate the adequacy of licensee security against such threats. As part of this evaluation, one of the factors is the effectiveness of terrain and vegetation in providing barriers against the vehicle entry. The effectiveness of natural features is presented in two contexts. First, certain natural features are presented. Second, the effectiveness of combinations of features is presented. In addition to the discussion of natural features, this report provides a discussion of methods to slow vehicles. Also included is an overview of man-made barrier systems, with particular attention to ditches. 17 refs., 49 figs

  5. Contextual Multi-armed Bandits under Feature Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Yun, Seyoung [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nam, Jun Hyun [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of); Mo, Sangwoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of); Shin, Jinwoo [Korea Advanced Inst. Science and Technology (KAIST), Daejeon (Korea, Republic of)

    2017-03-03

    We study contextual multi-armed bandit problems under linear realizability on rewards and uncertainty (or noise) on features. For the case of identical noise on features across actions, we propose an algorithm, coined NLinRel, having O(T⁷/₈(log(dT)+K√d)) regret bound for T rounds, K actions, and d-dimensional feature vectors. Next, for the case of non-identical noise, we observe that popular linear hypotheses including NLinRel are impossible to achieve such sub-linear regret. Instead, under assumption of Gaussian feature vectors, we prove that a greedy algorithm has O(T²/₃√log d)regret bound with respect to the optimal linear hypothesis. Utilizing our theoretical understanding on the Gaussian case, we also design a practical variant of NLinRel, coined Universal-NLinRel, for arbitrary feature distributions. It first runs NLinRel for finding the ‘true’ coefficient vector using feature uncertainties and then adjust it to minimize its regret using the statistical feature information. We justify the performance of Universal-NLinRel on both synthetic and real-world datasets.

  6. Unsupervised feature learning for autonomous rock image classification

    Science.gov (United States)

    Shu, Lei; McIsaac, Kenneth; Osinski, Gordon R.; Francis, Raymond

    2017-09-01

    Autonomous rock image classification can enhance the capability of robots for geological detection and enlarge the scientific returns, both in investigation on Earth and planetary surface exploration on Mars. Since rock textural images are usually inhomogeneous and manually hand-crafting features is not always reliable, we propose an unsupervised feature learning method to autonomously learn the feature representation for rock images. In our tests, rock image classification using the learned features shows that the learned features can outperform manually selected features. Self-taught learning is also proposed to learn the feature representation from a large database of unlabelled rock images of mixed class. The learned features can then be used repeatedly for classification of any subclass. This takes advantage of the large dataset of unlabelled rock images and learns a general feature representation for many kinds of rocks. We show experimental results supporting the feasibility of self-taught learning on rock images.

  7. Naive Bayes-Guided Bat Algorithm for Feature Selection

    Directory of Open Access Journals (Sweden)

    Ahmed Majid Taha

    2013-01-01

    Full Text Available When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets.

  8. Naive Bayes-Guided Bat Algorithm for Feature Selection

    Science.gov (United States)

    Taha, Ahmed Majid; Mustapha, Aida; Chen, Soong-Der

    2013-01-01

    When the amount of data and information is said to double in every 20 months or so, feature selection has become highly important and beneficial. Further improvements in feature selection will positively affect a wide array of applications in fields such as pattern recognition, machine learning, or signal processing. Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. The performance of the proposed feature selection algorithm was investigated using twelve benchmark datasets from different domains and was compared to three other well-known feature selection algorithms. Discussion focused on four perspectives: number of features, classification accuracy, stability, and feature generalization. The results showed that BANB significantly outperformed other algorithms in selecting lower number of features, hence removing irrelevant, redundant, or noisy features while maintaining the classification accuracy. BANB is also proven to be more stable than other methods and is capable of producing more general feature subsets. PMID:24396295

  9. Less common CT features of medulloblastoma

    International Nuclear Information System (INIS)

    Zee, C.S; Segall, H.D.; Miller, C.; Ahmad, J.; McComb, J.G.; Han, J.S.; Park, S.H.

    1982-01-01

    While many medulloblastomas have characteristic features on computed tomography (CT), a significant number have atypical features, including a cystic or necrotic component, calcification, hemorrhage, lack of contrast enhancement, and eccentric location, and/or direct supratentorial extension. Of 30 consecutive untreated cases reviewed by the authors, 14 (47%) had such findings. Failure to make the proper diagnosis will result in some cases if these features are not recognized as possible signs of medulloblastoma

  10. Improving scale invariant feature transform-based descriptors with shape-color alliance robust feature

    Science.gov (United States)

    Wang, Rui; Zhu, Zhengdan; Zhang, Liang

    2015-05-01

    Constructing appropriate descriptors for interest points in image matching is a critical aspect task in computer vision and pattern recognition. A method as an extension of the scale invariant feature transform (SIFT) descriptor called shape-color alliance robust feature (SCARF) descriptor is presented. To address the problem that SIFT is designed mainly for gray images and lack of global information for feature points, the proposed approach improves the SIFT descriptor by means of a concentric-rings model, as well as integrating the color invariant space and shape context with SIFT to construct the SCARF descriptor. The SCARF method developed is more robust than the conventional SIFT with respect to not only the color and photometrical variations but also the measuring similarity as a global variation between two shapes. A comparative evaluation of different descriptors is carried out showing that the SCARF approach provides better results than the other four state-of-the-art related methods.

  11. Structural damage identification using damping: a compendium of uses and features

    Science.gov (United States)

    Cao, M. S.; Sha, G. G.; Gao, Y. F.; Ostachowicz, W.

    2017-04-01

    The vibration responses of structures under controlled or ambient excitation can be used to detect structural damage by correlating changes in structural dynamic properties extracted from responses with damage. Typical dynamic properties refer to modal parameters: natural frequencies, mode shapes, and damping. Among these parameters, natural frequencies and mode shapes have been investigated extensively for their use in damage characterization by associating damage with reduction in local stiffness of structures. In contrast, the use of damping as a dynamic property to represent structural damage has not been comprehensively elucidated, primarily due to the complexities of damping measurement and analysis. With advances in measurement technologies and analysis tools, the use of damping to identify damage is becoming a focus of increasing attention in the damage detection community. Recently, a number of studies have demonstrated that damping has greater sensitivity for characterizing damage than natural frequencies and mode shapes in various applications, but damping-based damage identification is still a research direction ‘in progress’ and is not yet well resolved. This situation calls for an overall survey of the state-of-the-art and the state-of-the-practice of using damping to detect structural damage. To this end, this study aims to provide a comprehensive survey of uses and features of applying damping in structural damage detection. First, we present various methods for damping estimation in different domains including the time domain, the frequency domain, and the time-frequency domain. Second, we investigate the features and applications of damping-based damage detection methods on the basis of two predominant infrastructure elements, reinforced concrete structures and fiber-reinforced composites. Third, we clarify the influential factors that can impair the capability of damping to characterize damage. Finally, we recommend future research directions

  12. Accumulation of a poly(hydroxyalkanoate) copolymer containing primarily 3-hydroxyvalerate from simple carbohydrate substrates by Rhodococcus sp. NCIMB 40126.

    Science.gov (United States)

    Haywood, G W; Anderson, A J; Williams, D R; Dawes, E A; Ewing, D F

    1991-04-01

    A number of taxonomically-related bacteria have been identified which accumulate poly(hydroxyalkanoate) (PHA) copolymers containing primarily 3-hydroxyvalerate (3HV) monomer units from a range of unrelated single carbon sources. One of these, Rhodococcus sp. NCIMB 40126, was further investigated and shown to produce a copolymer containing 75 mol% 3HV and 25 mol% 3-hydroxybutyrate (3HB) from glucose as sole carbon source. Polyesters containing both 3HV and 3HB monomer units, together with 4-hydroxybutyrate (4HB), 5-hydroxyvalerate (5HV) or 3-hydroxyhexanoate (3HHx), were also produced by this organism from certain accumulation substrates. With valeric acid as substrate, almost pure (99 mol% 3HV) poly(3-hydroxyvalerate) was produced. N.m.r. analysis confirmed the composition of these polyesters. The thermal properties and molecular weight of the copolymer produced from glucose were comparable to those of PHB produced by Alcaligenes eutrophus.

  13. Discriminative semi-supervised feature selection via manifold regularization.

    Science.gov (United States)

    Xu, Zenglin; King, Irwin; Lyu, Michael Rung-Tsong; Jin, Rong

    2010-07-01

    Feature selection has attracted a huge amount of interest in both research and application communities of data mining. We consider the problem of semi-supervised feature selection, where we are given a small amount of labeled examples and a large amount of unlabeled examples. Since a small number of labeled samples are usually insufficient for identifying the relevant features, the critical problem arising from semi-supervised feature selection is how to take advantage of the information underneath the unlabeled data. To address this problem, we propose a novel discriminative semi-supervised feature selection method based on the idea of manifold regularization. The proposed approach selects features through maximizing the classification margin between different classes and simultaneously exploiting the geometry of the probability distribution that generates both labeled and unlabeled data. In comparison with previous semi-supervised feature selection algorithms, our proposed semi-supervised feature selection method is an embedded feature selection method and is able to find more discriminative features. We formulate the proposed feature selection method into a convex-concave optimization problem, where the saddle point corresponds to the optimal solution. To find the optimal solution, the level method, a fairly recent optimization method, is employed. We also present a theoretic proof of the convergence rate for the application of the level method to our problem. Empirical evaluation on several benchmark data sets demonstrates the effectiveness of the proposed semi-supervised feature selection method.

  14. Clinical and laboratory features of systemic sclerosis complicated with localized scleroderma.

    Science.gov (United States)

    Toki, Sayaka; Motegi, Sei-ichiro; Yamada, Kazuya; Uchiyama, Akihiko; Kanai, Sahori; Yamanaka, Masayoshi; Ishikawa, Osamu

    2015-03-01

    Localized scleroderma (LSc) primarily affects skin, whereas systemic sclerosis (SSc) affects skin and various internal organs. LSc and SSc are considered to be basically different diseases, and there is no transition between them. However, LSc and SSc have several common characteristics, including endothelial cell dysfunction, immune activation, and excess fibrosis of the skin, and there exist several SSc cases complicated with LSc during the course of SSc. Clinical and laboratory characteristics of SSc patients with LSc remain unclear. We investigated the clinical and laboratory features of 8 SSc patients with LSc among 220 SSc patients (3.6%). The types of LSc included plaque (5/8), guttate (2/8), and linear type (1/8). All cases were diagnosed as having SSc within 5 years before or after the appearance of LSc. In three cases of SSc with LSc (37.5%), LSc skin lesions preceded clinical symptoms of SSc. Young age, negative antinuclear antibody, and positive anti-RNA polymerase III antibody were significantly prevalent in SSc patients with LSc. The positivity of anticentromere antibody tended to be prevalent in SSc patients without LSc. No significant difference in the frequency of complications, such as interstitial lung disease, reflux esophagitis, and pulmonary artery hypertension, was observed. The awareness of these characteristic of SSc with LSc are essential to establish an early diagnosis and treatment. © 2015 Japanese Dermatological Association.

  15. Feature Evaluation for Building Facade Images - AN Empirical Study

    Science.gov (United States)

    Yang, M. Y.; Förstner, W.; Chai, D.

    2012-08-01

    The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

  16. Schizophrenia classification using functional network features

    Science.gov (United States)

    Rish, Irina; Cecchi, Guillermo A.; Heuton, Kyle

    2012-03-01

    This paper focuses on discovering statistical biomarkers (features) that are predictive of schizophrenia, with a particular focus on topological properties of fMRI functional networks. We consider several network properties, such as node (voxel) strength, clustering coefficients, local efficiency, as well as just a subset of pairwise correlations. While all types of features demonstrate highly significant statistical differences in several brain areas, and close to 80% classification accuracy, the most remarkable results of 93% accuracy are achieved by using a small subset of only a dozen of most-informative (lowest p-value) correlation features. Our results suggest that voxel-level correlations and functional network features derived from them are highly informative about schizophrenia and can be used as statistical biomarkers for the disease.

  17. Characterizing the effects of feature salience and top-down attention in the early visual system.

    Science.gov (United States)

    Poltoratski, Sonia; Ling, Sam; McCormack, Devin; Tong, Frank

    2017-07-01

    The visual system employs a sophisticated balance of attentional mechanisms: salient stimuli are prioritized for visual processing, yet observers can also ignore such stimuli when their goals require directing attention elsewhere. A powerful determinant of visual salience is local feature contrast: if a local region differs from its immediate surround along one or more feature dimensions, it will appear more salient. We used high-resolution functional MRI (fMRI) at 7T to characterize the modulatory effects of bottom-up salience and top-down voluntary attention within multiple sites along the early visual pathway, including visual areas V1-V4 and the lateral geniculate nucleus (LGN). Observers viewed arrays of spatially distributed gratings, where one of the gratings immediately to the left or right of fixation differed from all other items in orientation or motion direction, making it salient. To investigate the effects of directed attention, observers were cued to attend to the grating to the left or right of fixation, which was either salient or nonsalient. Results revealed reliable additive effects of top-down attention and stimulus-driven salience throughout visual areas V1-hV4. In comparison, the LGN exhibited significant attentional enhancement but was not reliably modulated by orientation- or motion-defined salience. Our findings indicate that top-down effects of spatial attention can influence visual processing at the earliest possible site along the visual pathway, including the LGN, whereas the processing of orientation- and motion-driven salience primarily involves feature-selective interactions that take place in early cortical visual areas. NEW & NOTEWORTHY While spatial attention allows for specific, goal-driven enhancement of stimuli, salient items outside of the current focus of attention must also be prioritized. We used 7T fMRI to compare salience and spatial attentional enhancement along the early visual hierarchy. We report additive effects of

  18. Classification Using Markov Blanket for Feature Selection

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Luo, Jian

    2009-01-01

    Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

  19. Hierarchical feature selection for erythema severity estimation

    Science.gov (United States)

    Wang, Li; Shi, Chenbo; Shu, Chang

    2014-10-01

    At present PASI system of scoring is used for evaluating erythema severity, which can help doctors to diagnose psoriasis [1-3]. The system relies on the subjective judge of doctors, where the accuracy and stability cannot be guaranteed [4]. This paper proposes a stable and precise algorithm for erythema severity estimation. Our contributions are twofold. On one hand, in order to extract the multi-scale redness of erythema, we design the hierarchical feature. Different from traditional methods, we not only utilize the color statistical features, but also divide the detect window into small window and extract hierarchical features. Further, a feature re-ranking step is introduced, which can guarantee that extracted features are irrelevant to each other. On the other hand, an adaptive boosting classifier is applied for further feature selection. During the step of training, the classifier will seek out the most valuable feature for evaluating erythema severity, due to its strong learning ability. Experimental results demonstrate the high precision and robustness of our algorithm. The accuracy is 80.1% on the dataset which comprise 116 patients' images with various kinds of erythema. Now our system has been applied for erythema medical efficacy evaluation in Union Hosp, China.

  20. Discriminating Induced-Microearthquakes Using New Seismic Features

    Science.gov (United States)

    Mousavi, S. M.; Horton, S.

    2016-12-01

    We studied characteristics of induced-microearthquakes on the basis of the waveforms recorded on a limited number of surface receivers using machine-learning techniques. Forty features in the time, frequency, and time-frequency domains were measured on each waveform, and several techniques such as correlation-based feature selection, Artificial Neural Networks (ANNs), Logistic Regression (LR) and X-mean were used as research tools to explore the relationship between these seismic features and source parameters. The results show that spectral features have the highest correlation to source depth. Two new measurements developed as seismic features for this study, spectral centroids and 2D cross-correlations in the time-frequency domain, performed better than the common seismic measurements. These features can be used by machine learning techniques for efficient automatic classification of low energy signals recorded at one or more seismic stations. We applied the technique to 440 microearthquakes-1.7Reference: Mousavi, S.M., S.P. Horton, C. A. Langston, B. Samei, (2016) Seismic features and automatic discrimination of deep and shallow induced-microearthquakes using neural network and logistic regression, Geophys. J. Int. doi: 10.1093/gji/ggw258.

  1. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

    Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

  2. Feature-specific encoding flexibility in visual working memory.

    Directory of Open Access Journals (Sweden)

    Aki Kondo

    Full Text Available The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location, and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape can be flexibly added to object representations.

  3. Feature-specific encoding flexibility in visual working memory.

    Science.gov (United States)

    Kondo, Aki; Saiki, Jun

    2012-01-01

    The current study examined selective encoding in visual working memory by systematically investigating interference from task-irrelevant features. The stimuli were objects defined by three features (color, shape, and location), and during a delay period, any of the features could switch between two objects. Additionally, single- and whole-probe trials were randomized within experimental blocks to investigate effects of memory retrieval. A series of relevant-feature switch detection tasks, where one feature was task-irrelevant, showed that interference from the task-irrelevant feature was only observed in the color-shape task, suggesting that color and shape information could be successfully filtered out, but location information could not, even when location was a task-irrelevant feature. Therefore, although location information is added to object representations independent of task demands in a relatively automatic manner, other features (e.g., color, shape) can be flexibly added to object representations.

  4. Homogenous stretching or detachment faulting? Which process is primarily extending the Aegean crust

    Science.gov (United States)

    Kumerics, C.; Ring, U.

    2003-04-01

    In extending orogens like the Aegean Sea of Greece and the Basin-and-Range province of the western United States, knowledge of rates of tectonic processes are important for understanding which process is primarily extending the crust. Platt et al. (1998) proposed that homogeneous stretching of the lithosphere (i.e. vertical ductile thinning associated with a subhorizontal foliation) at rates of 4-5 km Myr-1 is the dominant process that formed the Alboran Sea in the western Mediterranean. The Aegean Sea in the eastern Mediterranean is well-known for its low-angle normal faults (detachments) (Lister et al., 1984; Lister &Forster, 1996) suggesting that detachment faulting may have been the primary agent achieving ~>250 km (McKenzie, 1978) of extension since the Miocene. Ring et al. (2003) provided evidence for a very fast-slipping detachment on the islands of Syros and Tinos in the western Cyclades, which suggests that normal faulting was the dominant tectonic process that formed the Aegean Sea. However, most extensional detachments in the Aegean do not allow to quantify the amount of vertical ductile thinning associated with extension and therefore a full evaluation of the significance of vertical ductile thinning is not possible. On the Island of Ikaria in the eastern Aegean Sea, a subhorizontal extensional ductile shear zone is well exposed. We studied this shear zone in detail to quantify the amount of vertical ductile thinning associated with extension. Numerous studies have shown that natural shear zones usually deviate significantly from progressive simple shear and are characterized by pronounced shortening perpendicular to the shear zone. Numerous deformed pegmatitic veins in this shear zone on Ikaria allow the reconstruction of deformation and flow parameters (Passchier, 1990), which are necessary for quantifying the amount of vertical ductile thinning in the shear zone. Furthermore, a flow-path and finite-strain study in a syn-tectonic granite, which

  5. Evaluating a County-Sponsored Social Marketing Campaign to Increase Mothers’ Initiation of HPV Vaccine for their Pre-teen Daughters in a Primarily Rural Area

    Science.gov (United States)

    Cates, Joan R.; Shafer, Autumn; Diehl, Sandra J.; Deal, Allison M.

    2011-01-01

    Routine vaccination against human papillomavirus (HPV), the main cause of cervical cancer, is recommended for 11–12 year old girls, yet vaccine uptake is low. This study evaluates a social marketing campaign initiated by 13 North Carolina counties to raise awareness among parents and reduce barriers to accessing the vaccine in a primarily rural area. The 3-month campaign targeted mothers of girls ages 11–12 and healthcare practices serving pre-teen girls in four counties. Principles of social marketing were: product (recommended vaccine against HPV), price (cost, perception of safety and efficacy, and access), promotion (posters, brochures, website, news releases, doctor’s recommendation), and place (doctors’ offices, retail outlets). We analyzed (1) website traffic, hotline calls, and media placement; (2) cross-sectional surveys of mothers and providers; and (3) HPV immunization rates in intervention versus non-intervention counties. Of respondent mothers (n=225), 82% heard or saw campaign messages or materials. Of respondent providers (n=35), 94% used campaign brochures regularly or occasionally in conversations with parents. HPV vaccination rates within six months of campaign launch were 2% higher for 9–13 year old girls in two of the four intervention counties compared to 96 non-intervention counties. This evaluation supports campaign use in other primarily rural and underserved areas. PMID:21804767

  6. EEG feature selection method based on decision tree.

    Science.gov (United States)

    Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

    2015-01-01

    This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

  7. Text feature extraction based on deep learning: a review.

    Science.gov (United States)

    Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

    2017-01-01

    Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

  8. The Non-motor Features of Essential Tremor: A Primary Disease Feature or Just a Secondary Phenomenon?

    Directory of Open Access Journals (Sweden)

    Ketan Jhunjhunwala

    2014-08-01

    Full Text Available Essential tremor (ET is a pathologically heterogeneous neurodegenerative disorder with both motor and increasingly recognized non-motor features. It is debated whether the non-motor manifestations in ET result from widespread neurodegeneration or are merely secondary to impaired motor functions and decreased quality of life due to tremor. It is important to review these features to determine how to best treat the non-motor symptoms of patients and to understand the basic pathophysiology of the disease and develop appropriate pharmacotherapies. In this review, retrospective and prospective clinical studies were critically analyzed to identify possible correlations between the severities of non-motor features and tremor. We speculated that if such a correlation existed, the non-motor features were likely to be secondary to tremor. According to the current literature, the deficits in executive function, attention, concentration, and memory often observed in ET are likely to be a primary manifestation of the disease. It has also been documented that patients with ET often exhibit characteristic personality traits. However, it remains to be determined whether the other non-motor features often seen in ET, such as anxiety, depression, and sleep disturbances are primary or secondary to motor manifestations of ET and subsequent poor quality of life. Finally, there is evidence that patients with ET can also have impaired color vision, disturbances of olfaction, and hearing impairments, though there are few studies in these areas. Further investigations of large cohorts of patients with ET are required to understand the prevalence, nature, and true significance of the non-motor features in ET.

  9. CT features of renal epithelioid angiomyolipomas

    International Nuclear Information System (INIS)

    Hu Xiaoyun; Fang Xiangming; Hu Chunhong; Chen Hongwei; Cui Lei; Bao Jian; Yao Xuanjun

    2010-01-01

    Objective: To explore the CT and pathological features of renal epithelioid angiomyolipoma (EAML). Methods: Clinical data and CT images from ten cases with EAML proved by surgery and pathology were retrospectively analyzed. All cases were performed with plain and contrast enhanced CT scans. Results: CT features: higher pre-contrasted density than kidney, bulging from kidney, absent of fat, markedly heterogeneous enhancement (quick wash-in and slow wash-out), big size without lobular sign, complete capsule with clear margin and mild necrostic area. Pathological features: diffuse sheets of epithelioid cells were found under microscopy with immunohistochemistrical findings including positivity for HMB-45 and negativity for EMA. Conclusion: Some specific CT features, which is correlated well with the pathological findings, provide helpful information in the primary diagnosis of EAML. (authors)

  10. Feature Extraction in Radar Target Classification

    Directory of Open Access Journals (Sweden)

    Z. Kus

    1999-09-01

    Full Text Available This paper presents experimental results of extracting features in the Radar Target Classification process using the J frequency band pulse radar. The feature extraction is based on frequency analysis methods, the discrete-time Fourier Transform (DFT and Multiple Signal Characterisation (MUSIC, based on the detection of Doppler effect. The analysis has turned to the preference of DFT with implemented Hanning windowing function. We assumed to classify targets-vehicles into two classes, the wheeled vehicle and tracked vehicle. The results show that it is possible to classify them only while moving. The feature of the class results from a movement of moving parts of the vehicle. However, we have not found any feature to classify the wheeled and tracked vehicles while non-moving, although their engines are on.

  11. Eningiomas: outcome, and analysis of prognostic factors of primarily resected tumors

    International Nuclear Information System (INIS)

    Stafford, S.L.; Perry, A.; Suman, V.; Meyer, B.; Scheithauer, B.W.; Shaw, E.G.; Earle, J.D.

    1996-01-01

    Purpose: 582 consecutive cases of primary intracranial meningioma undergoing resection at the Mayo Clinic, (Rochester, MN) were reviewed to determine overall survival (OS), progression free survival(PFS), prognostic factors predicting recurrence, and to determine the importance of radiation therapy in the management of this tumor. Materials and Methods: Between 1978-1988, 582 cases of primarily resected meningiomas were identified based on the tumor and operative registries where diagnosis was between 1978-1988 inclusive. PFS was identified by radiographic progression. Follow-up was accomplished by chart review, and a detailed questionnaire sent to patients and referring physicians. Estimation of OS and PFS distributions were done by the Kaplan-Meier method. The log rank test was used to assess which factors were associated with PFS. Proportional hazard modeling was performed to obtain a subset of independent predictors of PFS. Results: the median age was 57(5-93). 67% were female. CT identified the tumor in 91% of cases. There was associated edema in 21% and 2% were radiographically en plaque. There were 17 patients with multiple tumors, four of whom had a known diagnosis of neurofibromatosis. Gross total resection (GTR) was accomplished in 80%, radical subtotal or subtotal resection(STR) in 20%, and biopsy in 53) cellularity, and four or more mitoses per 10 HPF. Multivariate analysis indicated young age, male sex, en plaque at surgery, were significant for decreased PFS when only patient characteristics were considered. When treatment and pathologic factors were also considered, then young age, male sex, less than GTR, and tumor sheeting were predictors for decreased PFS. 10 patients had RT after initial resection, two of whom recurred. There were 107 first recurrences. 50 were observed(no intervention within 3 months), 35 treated by surgery alone, 11 had S+RT, and 11 were treated with RT alone. Considering those patients treated at recurrence (n=57), PFS was at

  12. Review of research in feature based design

    NARCIS (Netherlands)

    Salomons, O.W.; van Houten, Frederikus J.A.M.; Kals, H.J.J.

    1993-01-01

    Research in feature-based design is reviewed. Feature-based design is regarded as a key factor towards CAD/CAPP integration from a process planning point of view. From a design point of view, feature-based design offers possibilities for supporting the design process better than current CAD systems

  13. Elevated plasma 8-iso-prostaglandin F2α levels in human smokers originate primarily from enzymatic instead of non-enzymatic lipid peroxidation.

    Science.gov (United States)

    van 't Erve, Thomas J; Lih, Fred B; Kadiiska, Maria B; Deterding, Leesa J; Mason, Ronald P

    2018-02-01

    It is widely accepted that free radicals in tobacco smoke lead to oxidative stress and generate the popular lipid peroxidation biomarker 8-iso-prostaglandin F 2α (8-iso-PGF 2α ). However, 8-iso-PGF 2α can simultaneously be produced in vivo by the prostaglandin-endoperoxide synthases (PGHS) induced by inflammation. This inflammation-dependent mechanism has never been considered as a source of elevated 8-iso-PGF 2α in tobacco smokers. The goal of this study is to quantify the distribution of chemical- and PGHS-dependent 8-iso-PGF 2α formation in the plasma of tobacco smokers and non-smokers. The influences of gender and hormonal contraceptive use were accounted for. The distribution was determined by measuring the 8-iso-PGF 2α /prostaglandin F 2α (PGF 2α ) ratio. When comparing smokers (n = 28) against non-smokers (n = 30), there was a statistically significant increase in the 8-iso-PGF 2α concentration. The source of this increased 8-iso-PGF 2α was primarily from PGHS. When stratifying for gender, the increase in 8-iso-PGF 2α in male smokers (n = 9) was primarily from PGHS. Interestingly, female smokers on hormonal contraceptives had increased 8-iso-PGF 2α in both pathways, whereas those not on hormonal contraceptives did not have increased 8-iso-PGF 2α . In conclusion, increased plasma 8-iso-PGF 2α in tobacco smokers has complex origins, with PGHS-dependent formation as the primary source. Accounting for both pathways provides a definitive measurement of both oxidative stress and inflammation. Published by Elsevier Inc.

  14. Genetic search feature selection for affective modeling

    DEFF Research Database (Denmark)

    Martínez, Héctor P.; Yannakakis, Georgios N.

    2010-01-01

    Automatic feature selection is a critical step towards the generation of successful computational models of affect. This paper presents a genetic search-based feature selection method which is developed as a global-search algorithm for improving the accuracy of the affective models built....... The method is tested and compared against sequential forward feature selection and random search in a dataset derived from a game survey experiment which contains bimodal input features (physiological and gameplay) and expressed pairwise preferences of affect. Results suggest that the proposed method...

  15. Feature Scaling via Second-Order Cone Programming

    Directory of Open Access Journals (Sweden)

    Zhizheng Liang

    2016-01-01

    Full Text Available Feature scaling has attracted considerable attention during the past several decades because of its important role in feature selection. In this paper, a novel algorithm for learning scaling factors of features is proposed. It first assigns a nonnegative scaling factor to each feature of data and then adopts a generalized performance measure to learn the optimal scaling factors. It is of interest to note that the proposed model can be transformed into a convex optimization problem: second-order cone programming (SOCP. Thus the scaling factors of features in our method are globally optimal in some sense. Several experiments on simulated data, UCI data sets, and the gene data set are conducted to demonstrate that the proposed method is more effective than previous methods.

  16. Shielding voices: The modulation of binding processes between voice features and response features by task representations.

    Science.gov (United States)

    Bogon, Johanna; Eisenbarth, Hedwig; Landgraf, Steffen; Dreisbach, Gesine

    2017-09-01

    Vocal events offer not only semantic-linguistic content but also information about the identity and the emotional-motivational state of the speaker. Furthermore, most vocal events have implications for our actions and therefore include action-related features. But the relevance and irrelevance of vocal features varies from task to task. The present study investigates binding processes for perceptual and action-related features of spoken words and their modulation by the task representation of the listener. Participants reacted with two response keys to eight different words spoken by a male or a female voice (Experiment 1) or spoken by an angry or neutral male voice (Experiment 2). There were two instruction conditions: half of participants learned eight stimulus-response mappings by rote (SR), and half of participants applied a binary task rule (TR). In both experiments, SR instructed participants showed clear evidence for binding processes between voice and response features indicated by an interaction between the irrelevant voice feature and the response. By contrast, as indicated by a three-way interaction with instruction, no such binding was found in the TR instructed group. These results are suggestive of binding and shielding as two adaptive mechanisms that ensure successful communication and action in a dynamic social environment.

  17. Brain iron accumulation affects myelin-related molecular systems implicated in a rare neurogenetic disease family with neuropsychiatric features.

    Science.gov (United States)

    Heidari, M; Johnstone, D M; Bassett, B; Graham, R M; Chua, A C G; House, M J; Collingwood, J F; Bettencourt, C; Houlden, H; Ryten, M; Olynyk, J K; Trinder, D; Milward, E A

    2016-11-01

    The 'neurodegeneration with brain iron accumulation' (NBIA) disease family entails movement or cognitive impairment, often with psychiatric features. To understand how iron loading affects the brain, we studied mice with disruption of two iron regulatory genes, hemochromatosis (Hfe) and transferrin receptor 2 (Tfr2). Inductively coupled plasma atomic emission spectroscopy demonstrated increased iron in the Hfe -/- × Tfr2 mut brain (P=0.002, n ≥5/group), primarily localized by Perls' staining to myelinated structures. Western immunoblotting showed increases of the iron storage protein ferritin light polypeptide and microarray and real-time reverse transcription-PCR revealed decreased transcript levels (Pgross myelin structure and integrity appear unaffected (P>0.05). Overlap (P0.05). These results implicate myelin-related systems involved in NBIA neuropathogenesis in early responses to iron loading. This may contribute to behavioral symptoms in NBIA and hemochromatosis and is relevant to patients with abnormal iron status and psychiatric disorders involving myelin abnormalities or resistant to conventional treatments.

  18. Integrated Phoneme Subspace Method for Speech Feature Extraction

    Directory of Open Access Journals (Sweden)

    Park Hyunsin

    2009-01-01

    Full Text Available Speech feature extraction has been a key focus in robust speech recognition research. In this work, we discuss data-driven linear feature transformations applied to feature vectors in the logarithmic mel-frequency filter bank domain. Transformations are based on principal component analysis (PCA, independent component analysis (ICA, and linear discriminant analysis (LDA. Furthermore, this paper introduces a new feature extraction technique that collects the correlation information among phoneme subspaces and reconstructs feature space for representing phonemic information efficiently. The proposed speech feature vector is generated by projecting an observed vector onto an integrated phoneme subspace (IPS based on PCA or ICA. The performance of the new feature was evaluated for isolated word speech recognition. The proposed method provided higher recognition accuracy than conventional methods in clean and reverberant environments.

  19. Does Attention Serve to Integrate Features?

    Science.gov (United States)

    Navon, David; Treisman, Anne

    1990-01-01

    An article and two commentaries consider the attentional feature-integration theory proposed by A. Treisman and colleagues. Hypotheses about the encoding of conjunctions are reviewed. Whether or not data support perceptual feature-integration is argued. (SLD)

  20. 14 CFR 35.7 - Features and characteristics.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Features and characteristics. 35.7 Section... AIRWORTHINESS STANDARDS: PROPELLERS General § 35.7 Features and characteristics. (a) The propeller may not have features or characteristics, revealed by any test or analysis or known to the applicant, that make it...

  1. Finger vein recognition based on the hyperinformation feature

    Science.gov (United States)

    Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Yang, Lu

    2014-01-01

    The finger vein is a promising biometric pattern for personal identification due to its advantages over other existing biometrics. In finger vein recognition, feature extraction is a critical step, and many feature extraction methods have been proposed to extract the gray, texture, or shape of the finger vein. We treat them as low-level features and present a high-level feature extraction framework. Under this framework, base attribute is first defined to represent the characteristics of a certain subcategory of a subject. Then, for an image, the correlation coefficient is used for constructing the high-level feature, which reflects the correlation between this image and all base attributes. Since the high-level feature can reveal characteristics of more subcategories and contain more discriminative information, we call it hyperinformation feature (HIF). Compared with low-level features, which only represent the characteristics of one subcategory, HIF is more powerful and robust. In order to demonstrate the potential of the proposed framework, we provide a case study to extract HIF. We conduct comprehensive experiments to show the generality of the proposed framework and the efficiency of HIF on our databases, respectively. Experimental results show that HIF significantly outperforms the low-level features.

  2. Multi-scale salient feature extraction on mesh models

    KAUST Repository

    Yang, Yongliang; Shen, ChaoHui

    2012-01-01

    We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.

  3. Passive Safety Features for Small Modular Reactors

    International Nuclear Information System (INIS)

    Ingersoll, Daniel T.

    2010-01-01

    The rapid growth in the size and complexity of commercial nuclear power plants in the 1970s spawned an interest in smaller, simpler designs that are inherently or intrinsically safe through the use of passive design features. Several designs were developed, but none were ever built, although some of their passive safety features were incorporated into large commercial plant designs that are being planned or built today. In recent years, several reactor vendors are actively redeveloping small modular reactor (SMR) designs with even greater use of passive features. Several designs incorporate the ultimate in passive safety they completely eliminate specific accident initiators from the design. Other design features help to reduce the likelihood of an accident or help to mitigate the accidents consequences, should one occur. While some passive safety features are common to most SMR designs, irrespective of the coolant technology, other features are specific to water, gas, or liquid-metal cooled SMR designs. The extensive use of passive safety features in SMRs promise to make these plants highly robust, protecting both the general public and the owner/investor. Once demonstrated, these plants should allow nuclear power to be used confidently for a broader range of customers and applications than will be possible with large plants alone.

  4. Effective traffic features selection algorithm for cyber-attacks samples

    Science.gov (United States)

    Li, Yihong; Liu, Fangzheng; Du, Zhenyu

    2018-05-01

    By studying the defense scheme of Network attacks, this paper propose an effective traffic features selection algorithm based on k-means++ clustering to deal with the problem of high dimensionality of traffic features which extracted from cyber-attacks samples. Firstly, this algorithm divide the original feature set into attack traffic feature set and background traffic feature set by the clustering. Then, we calculates the variation of clustering performance after removing a certain feature. Finally, evaluating the degree of distinctiveness of the feature vector according to the result. Among them, the effective feature vector is whose degree of distinctiveness exceeds the set threshold. The purpose of this paper is to select out the effective features from the extracted original feature set. In this way, it can reduce the dimensionality of the features so as to reduce the space-time overhead of subsequent detection. The experimental results show that the proposed algorithm is feasible and it has some advantages over other selection algorithms.

  5. Prominent feature extraction for review analysis: an empirical study

    Science.gov (United States)

    Agarwal, Basant; Mittal, Namita

    2016-05-01

    Sentiment analysis (SA) research has increased tremendously in recent times. SA aims to determine the sentiment orientation of a given text into positive or negative polarity. Motivation for SA research is the need for the industry to know the opinion of the users about their product from online portals, blogs, discussion boards and reviews and so on. Efficient features need to be extracted for machine-learning algorithm for better sentiment classification. In this paper, initially various features are extracted such as unigrams, bi-grams and dependency features from the text. In addition, new bi-tagged features are also extracted that conform to predefined part-of-speech patterns. Furthermore, various composite features are created using these features. Information gain (IG) and minimum redundancy maximum relevancy (mRMR) feature selection methods are used to eliminate the noisy and irrelevant features from the feature vector. Finally, machine-learning algorithms are used for classifying the review document into positive or negative class. Effects of different categories of features are investigated on four standard data-sets, namely, movie review and product (book, DVD and electronics) review data-sets. Experimental results show that composite features created from prominent features of unigram and bi-tagged features perform better than other features for sentiment classification. mRMR is a better feature selection method as compared with IG for sentiment classification. Boolean Multinomial Naïve Bayes) algorithm performs better than support vector machine classifier for SA in terms of accuracy and execution time.

  6. MCNP4A: Features and philosophy

    International Nuclear Information System (INIS)

    Hendricks, J.S.

    1993-01-01

    This paper describes MCNP, states its philosophy, introduces a number of new features becoming available with version MCNP4A, and answers a number of questions asked by participants in the workshop. MCNP is a general-purpose three-dimensional neutron, photon and electron transport code. Its philosophy is ''Quality, Value and New Features.'' Quality is exemplified by new software quality assurance practices and a program of benchmarking against experiments. Value includes a strong emphasis on documentation and code portability. New features are the third priority. MCNP4A is now available at Los Alamos. New features in MCNP4A include enhanced statistical analysis, distributed processor multitasking, new photon libraries, ENDF/B-VI capabilities, X-Windows graphics, dynamic memory allocation, expanded criticality output, periodic boundaries, plotting of particle tracks via SABRINA, and many other improvements. 23 refs

  7. Hurricane impacts on coastal wetlands: a half-century record of storm-generated features from southern Louisiana

    Science.gov (United States)

    Morton, Robert A.; Barras, John A.

    2011-01-01

    Temporally and spatially repeated patterns of wetland erosion, deformation, and deposition are observed on remotely sensed images and in the field after hurricanes cross the coast of Louisiana. The diagnostic morphological wetland features are products of the coupling of high-velocity wind and storm-surge water and their interaction with the underlying, variably resistant, wetland vegetation and soils. Erosional signatures include construction of orthogonal-elongate ponds and amorphous ponds, pond expansion, plucked marsh, marsh denudation, and shoreline erosion. Post-storm gravity reflux of floodwater draining from the wetlands forms dendritic incisions around the pond margins and locally integrates drainage pathways forming braided channels. Depositional signatures include emplacement of broad zones of organic wrack on topographic highs and inorganic deposits of variable thicknesses and lateral extents in the form of shore-parallel sandy washover terraces and interior-marsh mud blankets. Deformational signatures primarily involve laterally compressed marsh and displaced marsh mats and balls. Prolonged water impoundment and marsh salinization also are common impacts associated with wetland flooding by extreme storms. Many of the wetland features become legacies that record prior storm impacts and locally influence subsequent storm-induced morphological changes. Wetland losses caused by hurricane impacts depend directly on impact duration, which is controlled by the diameter of hurricane-force winds, forward speed of the storm, and wetland distance over which the storm passes. Distinguishing between wetland losses caused by storm impacts and losses associated with long-term delta-plain processes is critical for accurate modeling and prediction of future conversion of land to open water.

  8. Interplay of a multiplicity of security features

    Science.gov (United States)

    Moser, Jean-Frederic

    2000-04-01

    The great variety of existing security features can cause difficulty in choosing the adequate set for a particular security document. Considering the cost/benefit aspects with respect to the overall protection performance requested, a choice has to be made, for example, between either few features of high-security value or numerous many, less- resistant features. Another choice is the high versus low complexity of one particular features. A study aimed at providing a decision basis is a challenging matter because it involves human factors. Attention, perception, physiology of seeing and habits - to name some of the factors - are intangibles and are subject to evaluations involving normally a great number of experiments, if they are to be representative. The opportunity was given for a case study with the introduction of new Swiss banknotes between 1995 and 1998, because the new banknotes represent a novelty in the sense of the multiplicity and interplay of its optical security features. We have analyzed 652 articles which appeared in the press media concerning the new banknotes, seeking especially for peoples' reaction towards the security features.

  9. Feature Vector Construction Method for IRIS Recognition

    Science.gov (United States)

    Odinokikh, G.; Fartukov, A.; Korobkin, M.; Yoo, J.

    2017-05-01

    One of the basic stages of iris recognition pipeline is iris feature vector construction procedure. The procedure represents the extraction of iris texture information relevant to its subsequent comparison. Thorough investigation of feature vectors obtained from iris showed that not all the vector elements are equally relevant. There are two characteristics which determine the vector element utility: fragility and discriminability. Conventional iris feature extraction methods consider the concept of fragility as the feature vector instability without respect to the nature of such instability appearance. This work separates sources of the instability into natural and encodinginduced which helps deeply investigate each source of instability independently. According to the separation concept, a novel approach of iris feature vector construction is proposed. The approach consists of two steps: iris feature extraction using Gabor filtering with optimal parameters and quantization with separated preliminary optimized fragility thresholds. The proposed method has been tested on two different datasets of iris images captured under changing environmental conditions. The testing results show that the proposed method surpasses all the methods considered as a prior art by recognition accuracy on both datasets.

  10. Disruption of visual feature binding in working memory.

    Science.gov (United States)

    Ueno, Taiji; Allen, Richard J; Baddeley, Alan D; Hitch, Graham J; Saito, Satoru

    2011-01-01

    In a series of five experiments, we studied the effect of a visual suffix on the retention in short-term visual memory of both individual visual features and objects involving the binding of two features. Experiments 1A, 1B, and 2 involved suffixes consisting of features external to the to-be-remembered set and revealed a modest but equivalent disruption on individual and bound feature conditions. Experiments 3A and 3B involved suffixes comprising features that could potentially have formed part of the to-be-remembered set (but did not on that trial). Both experiments showed greater disruption of retention for objects comprising bound features than for their individual features. The results are interpreted as differentiating two components of suffix interference, one affecting memory for features and bindings equally, the other affecting memory for bindings. The general component is tentatively identified with the attentional cost of operating a filter to prevent the suffix from entering visual working memory, whereas the specific component is attributed to the particular fragility of bound representations when the filter fails.

  11. Feature-based Alignment of Volumetric Multi-modal Images

    Science.gov (United States)

    Toews, Matthew; Zöllei, Lilla; Wells, William M.

    2014-01-01

    This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

  12. Feature-Oriented Programming with Object Algebras

    NARCIS (Netherlands)

    B.C.d.S. Oliveira (Bruno); T. van der Storm (Tijs); A. Loh; W.R. Cook

    2013-01-01

    htmlabstractObject algebras are a new programming technique that enables a simple solution to basic extensibility and modularity issues in programming languages. While object algebras excel at defining modular features, the composition mechanisms for object algebras (and features) are still

  13. Predictors of moderated drinking in a primarily alcohol dependent sample of men who have sex with men

    Science.gov (United States)

    Kuerbis, Alexis; Morgenstern, Jon; Hail, Lisa

    2012-01-01

    Understanding for whom moderated drinking is a viable, achievable, and sustainable goal among those with a range of alcohol use disorders (AUD) remains an important public health question. Despite common acceptance as severe risk factors, there is little empirical evidence to conclude whether co-occurring mental health disorders or drug dependence contribute to an individual’s inability to successfully moderate his drinking. Utilizing secondary data analysis, the purpose of this study was to identify predictors of moderation among both treatment seeking and non-treatment seeking, primarily alcohol dependent, problem drinking men who have sex with men (MSM), with an emphasis on the high risk factors psychiatric comorbidity and drug dependence. Problem drinkers (N=187) were assessed, provided feedback about their drinking, given the option to receive brief AUD treatment or change their drinking on their own, and then followed for 15 months. Findings revealed that neither psychiatric comorbidity or drug dependence predicted ability to achieve moderation when controlling for alcohol dependence severity. Those who were younger, more highly educated, and had more mild alcohol dependence were more likely to achieve moderated drinking. Impact of treatment on predictors is explored. Limitations of this study and arenas for future research are discussed. PMID:22201219

  14. Biometric feature extraction using local fractal auto-correlation

    International Nuclear Information System (INIS)

    Chen Xi; Zhang Jia-Shu

    2014-01-01

    Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme: (i) using two-dimensional Gabor filter to extract the texture features of biometric images; (ii) calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and (iii) linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach. (condensed matter: structural, mechanical, and thermal properties)

  15. Image feature detectors and descriptors foundations and applications

    CERN Document Server

    Hassaballah, Mahmoud

    2016-01-01

    This book provides readers with a selection of high-quality chapters that cover both theoretical concepts and practical applications of image feature detectors and descriptors. It serves as reference for researchers and practitioners by featuring survey chapters and research contributions on image feature detectors and descriptors. Additionally, it emphasizes several keywords in both theoretical and practical aspects of image feature extraction. The keywords include acceleration of feature detection and extraction, hardware implantations, image segmentation, evolutionary algorithm, ordinal measures, as well as visual speech recognition. .

  16. Organization Features and School Performance

    OpenAIRE

    Atkins, Lois Major

    2005-01-01

    The purpose of this study was to determine the odds of school organization features predicting schools meeting district or state performance goals. The school organization features were organizational complexity, shared decision making, and leadership behavior. The dependent variable was school performance, operationally defined as a principalâ s yes response or no response to the question, â did your school meet district or state performance goals.â The independent variables representing...

  17. Designing attractive gamification features for collaborative storytelling websites.

    Science.gov (United States)

    Hsu, Shang Hwa; Chang, Jen-Wei; Lee, Chun-Chia

    2013-06-01

    Gamification design is considered as the predictor of collaborative storytelling websites' success. Although aforementioned studies have mentioned a broad range of factors that may influence gamification, they neither depicted the actual design features nor relative attractiveness among them. This study aims to identify attractive gamification features for collaborative storytelling websites. We first constructed a hierarchical system structure of gamification design of collaborative storytelling websites and conducted a focus group interview with eighteen frequent users to identify 35gamification features. After that, this study determined the relative attractiveness of these gamification features by administrating an online survey to 6333 collaborative storytelling websites users. The results indicated that the top 10 most attractive gamification features could account for more than 50% of attractiveness among these 35 gamification features. The feature of unpredictable time pressure is important to website users, yet not revealed in previous relevant studies. Implications of the findings were discussed.

  18. Discovering highly informative feature set over high dimensions

    KAUST Repository

    Zhang, Chongsheng; Masseglia, Florent; Zhang, Xiangliang

    2012-01-01

    For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.

  19. Discovering highly informative feature set over high dimensions

    KAUST Repository

    Zhang, Chongsheng

    2012-11-01

    For many textual collections, the number of features is often overly large. These features can be very redundant, it is therefore desirable to have a small, succinct, yet highly informative collection of features that describes the key characteristics of a dataset. Information theory is one such tool for us to obtain this feature collection. With this paper, we mainly contribute to the improvement of efficiency for the process of selecting the most informative feature set over high-dimensional unlabeled data. We propose a heuristic theory for informative feature set selection from high dimensional data. Moreover, we design data structures that enable us to compute the entropies of the candidate feature sets efficiently. We also develop a simple pruning strategy that eliminates the hopeless candidates at each forward selection step. We test our method through experiments on real-world data sets, showing that our proposal is very efficient. © 2012 IEEE.

  20. Feature Selection for Chemical Sensor Arrays Using Mutual Information

    Science.gov (United States)

    Wang, X. Rosalind; Lizier, Joseph T.; Nowotny, Thomas; Berna, Amalia Z.; Prokopenko, Mikhail; Trowell, Stephen C.

    2014-01-01

    We address the problem of feature selection for classifying a diverse set of chemicals using an array of metal oxide sensors. Our aim is to evaluate a filter approach to feature selection with reference to previous work, which used a wrapper approach on the same data set, and established best features and upper bounds on classification performance. We selected feature sets that exhibit the maximal mutual information with the identity of the chemicals. The selected features closely match those found to perform well in the previous study using a wrapper approach to conduct an exhaustive search of all permitted feature combinations. By comparing the classification performance of support vector machines (using features selected by mutual information) with the performance observed in the previous study, we found that while our approach does not always give the maximum possible classification performance, it always selects features that achieve classification performance approaching the optimum obtained by exhaustive search. We performed further classification using the selected feature set with some common classifiers and found that, for the selected features, Bayesian Networks gave the best performance. Finally, we compared the observed classification performances with the performance of classifiers using randomly selected features. We found that the selected features consistently outperformed randomly selected features for all tested classifiers. The mutual information filter approach is therefore a computationally efficient method for selecting near optimal features for chemical sensor arrays. PMID:24595058

  1. The radiographic features of familial expansile osteolysis

    International Nuclear Information System (INIS)

    Crone, M.D.; Wallace, R.G.H.

    1990-01-01

    The radiographic features of a unique autosomal dominant bone dysplasia are presented. The features are classified as generalised and/or focal. Generalised features are either altered trabecular pattern or modelling abnormalities. Focal features comprise lytic areas which progressively enlarge, producing expansion of the bone and eventual disintegration due to fibrous and finally fatty replacement of the normal medulla. Almost 90% of these lesions occur in the appendicular skeleton. Clinically, hearing loss is the earliest manifestation of the disease, presenting sometimes as early as 4 years of age. Apical and cervical resorption of teeth is extremely common, resulting in premature loss of teeth. Radiologically, the differential diagnosis refers to Paget's disease, polyostotic fibrous dysplasia, and osteofibrous dysplasia. The progressive destruction of the bone is similar to massive osteolysis (Gorham's disease). The radiographic features in combination with the histopathology render the condition unique. (orig.)

  2. Probabilistic Slow Features for Behavior Analysis

    NARCIS (Netherlands)

    Zafeiriou, Lazaros; Nicolaou, Mihalis A.; Zafeiriou, Stefanos; Nikitidis, Symeon; Pantic, Maja

    A recently introduced latent feature learning technique for time-varying dynamic phenomena analysis is the so-called slow feature analysis (SFA). SFA is a deterministic component analysis technique for multidimensional sequences that, by minimizing the variance of the first-order time derivative

  3. Learning slow features for behavior analysis

    NARCIS (Netherlands)

    Zafeiriou, Lazaros; Nicolaou, Mihalis A.; Zafeiriou, Stefanos; Nikitids, Symeon; Pantic, Maja

    2013-01-01

    A recently introduced latent feature learning technique for time varying dynamic phenomena analysis is the socalled Slow Feature Analysis (SFA). SFA is a deterministic component analysis technique for multi-dimensional sequences that by minimizing the variance of the first order time derivative

  4. The immunobiology and clinical features of type 1 autoimmune polyglandular syndrome (APS-1).

    Science.gov (United States)

    Guo, Can-Jie; Leung, Patrick S C; Zhang, Weici; Ma, Xiong; Gershwin, M Eric

    2018-01-01

    Autoimmune Polyglandular Syndrome type 1 (APS-1) is a subtype of the autoimmune polyendocrine syndrome characterized by the simultaneous or sequential dysfunction of multiple endocrine or non-endocrine glands. A clinical diagnosis of APS-1 is typically based on the presence of at least two of three following criteria: chronic mucocutaneous candidiasis, hypoparathyroidism and adrenal insufficiency. The first identified causative mutated gene for APS-1 is autoimmune regulator (AIRE) encoding a critical transcription factor, which is primarily expressed in the medullary thymic epithelial cells (mTECs) for generating central immune tolerance. A wide range of chronic, debilitating complications, with no obvious correlation with genetics, makes a diagnosis of APS-1 challenging early in the disease course. Managing APS-1 is difficult due to its complexity, especially the intricate relationships within manifestations and genetic mutations. The past decades have witnessed dramatic progress in elucidating the function of AIRE and conducting large-scale cohort studies in APS-1. However, no clear evidence-based guidelines have been established in APS-1. In this review, we provide a detailed critical overview of the study history, epidemiology, clinical features, and related mechanisms of autoimmunity in APS-1, as well as currently available therapies for this autoimmune disorder. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Aging, selective attention, and feature integration.

    Science.gov (United States)

    Plude, D J; Doussard-Roosevelt, J A

    1989-03-01

    This study used feature-integration theory as a means of determining the point in processing at which selective attention deficits originate. The theory posits an initial stage of processing in which features are registered in parallel and then a serial process in which features are conjoined to form complex stimuli. Performance of young and older adults on feature versus conjunction search is compared. Analyses of reaction times and error rates suggest that elderly adults in addition to young adults, can capitalize on the early parallel processing stage of visual information processing, and that age decrements in visual search arise as a result of the later, serial stage of processing. Analyses of a third, unconfounded, conjunction search condition reveal qualitatively similar modes of conjunction search in young and older adults. The contribution of age-related data limitations is found to be secondary to the contribution of age decrements in selective attention.

  6. Behind every innovative solution lies an obscure feature

    Directory of Open Access Journals (Sweden)

    Lee Spector (Fellow ISGEC

    2012-06-01

    Full Text Available The Obscure Features Hypothesis (OFH for innovation states that a two-step process undergirds almost all innovative solutions: (1 notice an infrequently observed or new (i.e., obscure feature of the problem and (2 construct an interaction involving the obscure feature that produces the desired effects to solve the problem. The OFH leads to a systematic derivation of innovation-enhancing techniques by engaging in two tasks. First, we developed a 32-category system of the types of features possessable by a physical object or material. This Feature Type Taxonomy (FTT provides a panoramic view of the space of features and assists in searches for the obscure ones. Second, we are articulating the many cognitive reasons that obscure features are overlooked and are developing countering techniques for each known reason. We present the implications and techniques of the OFH, as well as indicate how software can assist innovators in the effective use of these innovation-enhancing techniques.

  7. Mammographic feature enhancement by multiscale analysis

    International Nuclear Information System (INIS)

    Laine, A.F.; Schuler, S.; Fan, J.; Huda, W.

    1994-01-01

    This paper introduces a novel approach for accomplishing mammographic feature analysis by overcomplete multiresolution representations. The authors show that efficient representations may be identified within a continuum of scale-space and used to enhance features of importance to mammography. Methods of contrast enhancement are described based on three overcomplete multiscale representations: (1) the dyadic wavelet transform (separable), (2) the var-phi-transform (nonseparable, nonorthogonal), and (3) the hexagonal wavelet transform (nonseparable). Multiscale edges identified within distinct levels of transform space provide local support for image enhancement. Mammograms are reconstructed from wavelet coefficients modified at one or more levels by local and global nonlinear operators. In each case, edges and gain parameters are identified adaptively by a measure of energy within each level of scale-space. The authors show quantitatively that transform coefficients, modified by adaptive nonlinear operators, can make more obvious unseen or barely seen features of mammography without requiring additional radiation. The results are compared with traditional image enhancement techniques by measuring the local contrast of known mammographic features. The authors demonstrate that features extracted from multiresolution representations can provide an adaptive mechanism for accomplishing local contrast enhancement. By improving the visualization of breast pathology, they can improve chances of early detection while requiring less time to evaluate mammograms for most patients

  8. Laboratory simulation of infrared astrophysical features

    International Nuclear Information System (INIS)

    Rose, L.A.

    1979-01-01

    Laboratory infrared emission and absorption spectra have been taken of terrestrial silicates, meteorites and lunar soils in the form of micrometer and sub-micrometer grains. The emission spectra were taken in a way that imitates telescopic observations. The purpose was to see which materials best simulate the 10 μm astrophysical feature. The emission spectra of dunite, fayalite and Allende give a good fit to the 10 μm broadband emission feature of comets Bennett and Kohoutek. A study of the effect of grain size on the presence of the 10 μm emission features of dunite shows that for particles larger than 37 μm no feature is seen. The emission spectrum of the Murray meteorite, a Type 2 carbonaceous chondrite, is quite similar to the intermediate resolution spectrum of comet Kohoutek in the 10 μm region. Hydrous silicates or amorphous magnesium silicates in combination with high-temperature condensates, such as olivine or anorthite, would yield spectra that match the intermediate resolution spectrum of comet Kohoutek in the 10 μm region. Glassy olivine and glassy anorthite in approximately equal proportions would also give a spectrum that is a good fit to the cometary 10 μm feature. (Auth.)

  9. Joint Feature Selection and Classification for Multilabel Learning.

    Science.gov (United States)

    Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

    2018-03-01

    Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

  10. Automatic feature-based grouping during multiple object tracking.

    Science.gov (United States)

    Erlikhman, Gennady; Keane, Brian P; Mettler, Everett; Horowitz, Todd S; Kellman, Philip J

    2013-12-01

    Contour interpolation automatically binds targets with distractors to impair multiple object tracking (Keane, Mettler, Tsoi, & Kellman, 2011). Is interpolation special in this regard or can other features produce the same effect? To address this question, we examined the influence of eight features on tracking: color, contrast polarity, orientation, size, shape, depth, interpolation, and a combination (shape, color, size). In each case, subjects tracked 4 of 8 objects that began as undifferentiated shapes, changed features as motion began (to enable grouping), and returned to their undifferentiated states before halting. We found that intertarget grouping improved performance for all feature types except orientation and interpolation (Experiment 1 and Experiment 2). Most importantly, target-distractor grouping impaired performance for color, size, shape, combination, and interpolation. The impairments were, at times, large (>15% decrement in accuracy) and occurred relative to a homogeneous condition in which all objects had the same features at each moment of a trial (Experiment 2), and relative to a "diversity" condition in which targets and distractors had different features at each moment (Experiment 3). We conclude that feature-based grouping occurs for a variety of features besides interpolation, even when irrelevant to task instructions and contrary to the task demands, suggesting that interpolation is not unique in promoting automatic grouping in tracking tasks. Our results also imply that various kinds of features are encoded automatically and in parallel during tracking.

  11. Superpixel-Based Feature for Aerial Image Scene Recognition

    Directory of Open Access Journals (Sweden)

    Hongguang Li

    2018-01-01

    Full Text Available Image scene recognition is a core technology for many aerial remote sensing applications. Different landforms are inputted as different scenes in aerial imaging, and all landform information is regarded as valuable for aerial image scene recognition. However, the conventional features of the Bag-of-Words model are designed using local points or other related information and thus are unable to fully describe landform areas. This limitation cannot be ignored when the aim is to ensure accurate aerial scene recognition. A novel superpixel-based feature is proposed in this study to characterize aerial image scenes. Then, based on the proposed feature, a scene recognition method of the Bag-of-Words model for aerial imaging is designed. The proposed superpixel-based feature that utilizes landform information establishes top-task superpixel extraction of landforms to bottom-task expression of feature vectors. This characterization technique comprises the following steps: simple linear iterative clustering based superpixel segmentation, adaptive filter bank construction, Lie group-based feature quantification, and visual saliency model-based feature weighting. Experiments of image scene recognition are carried out using real image data captured by an unmanned aerial vehicle (UAV. The recognition accuracy of the proposed superpixel-based feature is 95.1%, which is higher than those of scene recognition algorithms based on other local features.

  12. Spatiotemporal Features for Asynchronous Event-based Data

    Directory of Open Access Journals (Sweden)

    Xavier eLagorce

    2015-02-01

    Full Text Available Bio-inspired asynchronous event-based vision sensors are currently introducing a paradigm shift in visual information processing. These new sensors rely on a stimulus-driven principle of light acquisition similar to biological retinas. They are event-driven and fully asynchronous, thereby reducing redundancy and encoding exact times of input signal changes, leading to a very precise temporal resolution. Approaches for higher-level computer vision often rely on the realiable detection of features in visual frames, but similar definitions of features for the novel dynamic and event-based visual input representation of silicon retinas have so far been lacking. This article addresses the problem of learning and recognizing features for event-based vision sensors, which capture properties of truly spatiotemporal volumes of sparse visual event information. A novel computational architecture for learning and encoding spatiotemporal features is introduced based on a set of predictive recurrent reservoir networks, competing via winner-take-all selection. Features are learned in an unsupervised manner from real-world input recorded with event-based vision sensors. It is shown that the networks in the architecture learn distinct and task-specific dynamic visual features, and can predict their trajectories over time.

  13. Selective Audiovisual Semantic Integration Enabled by Feature-Selective Attention.

    Science.gov (United States)

    Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Li, Peijun; Fang, Fang; Sun, Pei

    2016-01-13

    An audiovisual object may contain multiple semantic features, such as the gender and emotional features of the speaker. Feature-selective attention and audiovisual semantic integration are two brain functions involved in the recognition of audiovisual objects. Humans often selectively attend to one or several features while ignoring the other features of an audiovisual object. Meanwhile, the human brain integrates semantic information from the visual and auditory modalities. However, how these two brain functions correlate with each other remains to be elucidated. In this functional magnetic resonance imaging (fMRI) study, we explored the neural mechanism by which feature-selective attention modulates audiovisual semantic integration. During the fMRI experiment, the subjects were presented with visual-only, auditory-only, or audiovisual dynamical facial stimuli and performed several feature-selective attention tasks. Our results revealed that a distribution of areas, including heteromodal areas and brain areas encoding attended features, may be involved in audiovisual semantic integration. Through feature-selective attention, the human brain may selectively integrate audiovisual semantic information from attended features by enhancing functional connectivity and thus regulating information flows from heteromodal areas to brain areas encoding the attended features.

  14. Critical feature analysis of a radiotherapy machine

    International Nuclear Information System (INIS)

    Rae, Andrew; Jackson, Daniel; Ramanan, Prasad; Flanz, Jay; Leyman, Didier

    2005-01-01

    The software implementation of the emergency shutdown feature in a major radiotherapy system was analyzed, using a directed form of code review based on module dependences. Dependences between modules are labelled by particular assumptions; this allows one to trace through the code, and identify those fragments responsible for critical features. An 'assumption tree' is constructed in parallel, showing the assumptions which each module makes about others. The root of the assumption tree is the critical feature of interest, and its leaves represent assumptions which, if not valid, might cause the critical feature to fail. The analysis revealed some unexpected assumptions that motivated improvements to the code

  15. Analysing Feature Model Changes using FMDiff

    NARCIS (Netherlands)

    Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

    2015-01-01

    Evolving a large scale, highly variable sys- tems is a challenging task. For such a system, evolution operations often require to update consistently both their implementation and its feature model. In this con- text, the evolution of the feature model closely follows the evolution of the system.

  16. Graphical matching rules for cardinality based service feature diagrams

    Directory of Open Access Journals (Sweden)

    Faiza Kanwal

    2017-03-01

    Full Text Available To provide efficient services to end-users, variability and commonality among the features of the product line is a challenge for industrialist and researchers. Feature modeling provides great services to deal with variability and commonality among the features of product line. Cardinality based service feature diagrams changed the basic framework of service feature diagrams by putting constraints to them, which make service specifications more flexible, but apart from their variation in selection third party services may have to be customizable. Although to control variability, cardinality based service feature diagrams provide high level visual notations. For specifying variability, the use of cardinality based service feature diagrams raises the problem of matching a required feature diagram against the set of provided diagrams.

  17. Robust emotion recognition using spectral and prosodic features

    CERN Document Server

    Rao, K Sreenivasa

    2013-01-01

    In this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner. The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus.

  18. Video Scene Parsing with Predictive Feature Learning

    OpenAIRE

    Jin, Xiaojie; Li, Xin; Xiao, Huaxin; Shen, Xiaohui; Lin, Zhe; Yang, Jimei; Chen, Yunpeng; Dong, Jian; Liu, Luoqi; Jie, Zequn; Feng, Jiashi; Yan, Shuicheng

    2016-01-01

    In this work, we address the challenging video scene parsing problem by developing effective representation learning methods given limited parsing annotations. In particular, we contribute two novel methods that constitute a unified parsing framework. (1) \\textbf{Predictive feature learning}} from nearly unlimited unlabeled video data. Different from existing methods learning features from single frame parsing, we learn spatiotemporal discriminative features by enforcing a parsing network to ...

  19. Characters Feature Extraction Based on Neat Oracle Bone Rubbings

    OpenAIRE

    Lei Guo

    2013-01-01

    In order to recognize characters on the neat oracle bone rubbings, a new mesh point feature extraction algorithm was put forward in this paper by researching and improving of the existing coarse mesh feature extraction algorithm and the point feature extraction algorithm. Some improvements of this algorithm were as followings: point feature was introduced into the coarse mesh feature, the absolute address was converted to relative address, and point features have been changed grid and positio...

  20. Speech recognition using articulatory and excitation source features

    CERN Document Server

    Rao, K Sreenivasa

    2017-01-01

    This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.

  1. Natural Gas : Physical Properties and Combustion Features

    OpenAIRE

    Corre, Olivier Le; Loubar, Khaled

    2010-01-01

    The actual composition of natural gas depends primarily on the production field from which it is extracted and limited variations in composition must therefore be accepted. Moreover, at a local distribution level, seasonal adjustments by the local gas distributor may cause significant variations in the gas composition. Consequently, physical properties and energy content are subject to variations and their calculation / estimation is of great importance for technical and economical aspects. I...

  2. MRI features of placenta accreta

    International Nuclear Information System (INIS)

    Cao Manrui; Du Mu; Huang Yi; Liu Bingguang; Zhang Fangjing; Guo Jimin; Zhu Zhijun

    2012-01-01

    Objective: To investigate the MRI features of placenta accreta. Methods: From Apr 2009 to Jun 2011, 15 patients with placenta accrete received MRI examination. In them, placenta accreta was diagnosed based on clinical manifestations or postoperative histopathology. The MR features of placenta accreta in them (study group) were retrospectively analyzed and compared with those in 15 pregnant women without placenta accreta (control group) with Fisher exact test. Results: In the 15 patients with placenta accreta,uterine bulging and (or) a focal outward contour bulge was detected in 14 patients; heterogeneous signal intensity in the placenta was detected in 15 patients; dark intraplacental bands on T 2 -weighted images was detected in 15 patients; and increased subplacental vascularity was detected in 11 patients on T 1 - weighted images. In the study group, 14 patients showed at least three of the above four features, and in all of them uterine bulging and (or) a focal outward contour bulge, heterogeneous signal intensity in the placenta and dark intraplacental bands on T 2 -weighted images were detected; one patient showed heterogeneous signal intensity in the placenta, dark intraplacental bands on T 2 -weighted images and increased subplacental vascularity. In the control group,none patient had three of the above features.Uterine bulging and (or) a focal outward contour bulge, heterogeneous signal intensity in the placenta, dark intraplacental bands on T 2 -weighted images and increased subplacental vascularity were detected in 3, 6, 3 and 4 patients (P=0.000, 0.001, 0.000 and 0.027), respectively. Conclusions: The main MRI features of placenta accreta are uterine bulging and (or) a focal outward contour bulge, heterogeneous signal intensity in the placenta and dark intraplacental bands on T 2 -weighted images Besides, increased subplacental vascularity also could provide useful information for the diagnosis of placenta accreta. (authors)

  3. A study on feature analysis for musical instrument classification.

    Science.gov (United States)

    Deng, Jeremiah D; Simmermacher, Christian; Cranefield, Stephen

    2008-04-01

    In tackling data mining and pattern recognition tasks, finding a compact but effective set of features has often been found to be a crucial step in the overall problem-solving process. In this paper, we present an empirical study on feature analysis for recognition of classical instrument, using machine learning techniques to select and evaluate features extracted from a number of different feature schemes. It is revealed that there is significant redundancy between and within feature schemes commonly used in practice. Our results suggest that further feature analysis research is necessary in order to optimize feature selection and achieve better results for the instrument recognition problem.

  4. FISCAL FEATURES SPECIFIC TO INTRA-COMMUNITY TRANSACTIONS OF NEW MEANS OF TRANSPORTATION AND EXCISABLE PRODUCTS

    Directory of Open Access Journals (Sweden)

    PALIU - POPA LUCIA

    2012-06-01

    Full Text Available With a view to our country's accession to the Community space, the Romanian legislation has undergone many changes, and we should point out among others those in the tax system, that primarily aims to ensure the functioning of the national economy in the globalization of the economic and social activities worldwide. Although at first sight the new procedures have a positive impact on the development of intra-Community commercial businesses, due to the elimination of customs formalities and hence of the fees paid to customs officials, however there are costs generated by the application of EU law, which should not be neglected. Considering the many situations that arise in carrying out intra-Community commercial transactions, that are aimed at the differentiated tax procedures from the value added tax perspective, we considered appropriate, to address below the tax features related to intra-Community acquisitions and supplies of new means of transport and excisable products, because these are two important categories of goods that generate differential tax treatments, so that after the tax analysis we should be able to draw some relevant conclusions.

  5. Audio feature extraction using probability distribution function

    Science.gov (United States)

    Suhaib, A.; Wan, Khairunizam; Aziz, Azri A.; Hazry, D.; Razlan, Zuradzman M.; Shahriman A., B.

    2015-05-01

    Voice recognition has been one of the popular applications in robotic field. It is also known to be recently used for biometric and multimedia information retrieval system. This technology is attained from successive research on audio feature extraction analysis. Probability Distribution Function (PDF) is a statistical method which is usually used as one of the processes in complex feature extraction methods such as GMM and PCA. In this paper, a new method for audio feature extraction is proposed which is by using only PDF as a feature extraction method itself for speech analysis purpose. Certain pre-processing techniques are performed in prior to the proposed feature extraction method. Subsequently, the PDF result values for each frame of sampled voice signals obtained from certain numbers of individuals are plotted. From the experimental results obtained, it can be seen visually from the plotted data that each individuals' voice has comparable PDF values and shapes.

  6. Temporality of Features in Near-Death Experience Narratives

    Directory of Open Access Journals (Sweden)

    Charlotte Martial

    2017-06-01

    Full Text Available Background: After an occurrence of a Near-Death Experience (NDE, Near-Death Experiencers (NDErs usually report extremely rich and detailed narratives. Phenomenologically, a NDE can be described as a set of distinguishable features. Some authors have proposed regular patterns of NDEs, however, the actual temporality sequence of NDE core features remains a little explored area.Objectives: The aim of the present study was to investigate the frequency distribution of these features (globally and according to the position of features in narratives as well as the most frequently reported temporality sequences of features.Methods: We collected 154 French freely expressed written NDE narratives (i.e., Greyson NDE scale total score ≥ 7/32. A text analysis was conducted on all narratives in order to infer temporal ordering and frequency distribution of NDE features.Results: Our analyses highlighted the following most frequently reported sequence of consecutive NDE features: Out-of-Body Experience, Experiencing a tunnel, Seeing a bright light, Feeling of peace. Yet, this sequence was encountered in a very limited number of NDErs.Conclusion: These findings may suggest that NDEs temporality sequences can vary across NDErs. Exploring associations and relationships among features encountered during NDEs may complete the rigorous definition and scientific comprehension of the phenomenon.

  7. Feature Optimization for Long-Range Visual Homing in Changing Environments

    Directory of Open Access Journals (Sweden)

    Qidan Zhu

    2014-02-01

    Full Text Available This paper introduces a feature optimization method for robot long-range feature-based visual homing in changing environments. To cope with the changing environmental appearance, the optimization procedure is introduced to distinguish the most relevant features for feature-based visual homing, including the spatial distribution, selection and updating. In the previous research on feature-based visual homing, less effort has been spent on the way to improve the feature distribution to get uniformly distributed features, which are closely related to homing performance. This paper presents a modified feature extraction algorithm to decrease the influence of anisotropic feature distribution. In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments. To verify the feasibility of the proposal, several comprehensive evaluations are conducted. The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.

  8. Acoustic Features Influence Musical Choices Across Multiple Genres.

    Science.gov (United States)

    Barone, Michael D; Bansal, Jotthi; Woolhouse, Matthew H

    2017-01-01

    Based on a large behavioral dataset of music downloads, two analyses investigate whether the acoustic features of listeners' preferred musical genres influence their choice of tracks within non-preferred, secondary musical styles. Analysis 1 identifies feature distributions for pairs of genre-defined subgroups that are distinct. Using correlation analysis, these distributions are used to test the degree of similarity between subgroups' main genres and the other music within their download collections. Analysis 2 explores the issue of main-to-secondary genre influence through the production of 10 feature-influence matrices, one per acoustic feature, in which cell values indicate the percentage change in features for genres and subgroups compared to overall population averages. In total, 10 acoustic features and 10 genre-defined subgroups are explored within the two analyses. Results strongly indicate that the acoustic features of people's main genres influence the tracks they download within non-preferred, secondary musical styles. The nature of this influence and its possible actuating mechanisms are discussed with respect to research on musical preference, personality, and statistical learning.

  9. Imaging features of kaposiform lymphangiomatosis

    International Nuclear Information System (INIS)

    Goyal, Pradeep; Alomari, Ahmad I.; Shaikh, Raja; Chaudry, Gulraiz; Kozakewich, Harry P.; Perez-Atayde, Antonio R.; Trenor, Cameron C.; Fishman, Steven J.; Greene, Arin K.

    2016-01-01

    Kaposiform lymphangiomatosis is a rare, aggressive lymphatic disorder. The imaging and presenting features of kaposiform lymphangiomatosis can overlap with those of central conducting lymphatic anomaly and generalized lymphatic anomaly. To analyze the imaging findings of kaposiform lymphangiomatosis disorder and highlight features most suggestive of this diagnosis. We retrospectively identified and characterized 20 children and young adults with histopathological diagnosis of kaposiform lymphangiomatosis and radiologic imaging referred to the vascular anomalies center between 1995 and 2015. The median age at onset was 6.5 years (range 3 months to 27 years). The most common presenting features were respiratory compromise (dyspnea, cough, chest pain; 55.5%), swelling/mass (25%), bleeding (15%) and fracture (5%). The thoracic cavity was involved in all patients; all patients had mediastinal involvement followed by lung parenchymal disease (90%) and pleural (85%) and pericardial (50%) effusions. The most common extra-thoracic sites of disease were the retroperitoneum (80%), bone (60%), abdominal viscera (55%) and muscles (45%). There was characteristic enhancing and infiltrative soft-tissue thickening in the mediastinum and retroperitoneum extending along the lymphatic distribution. Kaposiform lymphangiomatosis has overlapping imaging features with central conducting lymphatic anomaly and generalized lymphatic anomaly. Presence of mediastinal or retroperitoneal enhancing and infiltrative soft-tissue disease along the lymphatic distribution, hemorrhagic effusions and moderate thrombocytopenia (50-100,000/μl) should favor diagnosis of kaposiform lymphangiomatosis. (orig.)

  10. Spectral features in the cosmic ray fluxes

    Science.gov (United States)

    Lipari, Paolo

    2018-01-01

    The cosmic ray energy distributions contain spectral features, that is narrow energy regions where the slope of the spectrum changes rapidly. The identification and study of these features is of great importance to understand the astrophysical mechanisms of acceleration and propagation that form the spectra. In first approximation a spectral feature is often described as a discontinuous change in slope, however very valuable information is also contained in its width, that is the length of the energy interval where the change in spectral index develops. In this work we discuss the best way to define and parameterize the width a spectral feature, and for illustration discuss some of the most prominent known structures.

  11. A Novel Real-Time Feature Matching Scheme

    Directory of Open Access Journals (Sweden)

    Ying Liu

    2014-02-01

    Full Text Available Affine Scale Invariant Feature Transform (ASIFT can obtain fully affine invariance, however, its time cost reaches about twice that in Scale Invariant Feature Transform (SIFT. We propose an improved ASIFT algorithm based on feature points in scale space for real-time application. In order to detect the affine invariant feature point, we establish a second-order difference of Gaussian (DOG pyramid and replace the extreme detection in the DOG pyramid by zero detection in the proposed second-order DOG pyramid, which decreases the complexity of the scheme. Experimental results show that the proposed method has a big progress in the real-time performance compared to the traditional one, while preserving the fully affine invariance and precision.

  12. Single-labelled music genre classification using content-based features

    CSIR Research Space (South Africa)

    Ajoodha, R

    2015-11-01

    Full Text Available In this paper we use content-based features to perform automatic classification of music pieces into genres. We categorise these features into four groups: features extracted from the Fourier transform’s magnitude spectrum, features designed...

  13. SIP-FS: a novel feature selection for data representation

    Directory of Open Access Journals (Sweden)

    Yiyou Guo

    2018-02-01

    Full Text Available Abstract Multiple features are widely used to characterize real-world datasets. It is desirable to select leading features with stability and interpretability from a set of distinct features for a comprehensive data description. However, most of existing feature selection methods focus on the predictability (e.g., prediction accuracy of selected results yet neglect stability. To obtain compact data representation, a novel feature selection method is proposed to improve stability, and interpretability without sacrificing predictability (SIP-FS. Instead of mutual information, generalized correlation is adopted in minimal redundancy maximal relevance to measure the relation between different feature types. Several feature types (each contains a certain number of features can then be selected and evaluated quantitatively to determine what types contribute to a specific class, thereby enhancing the so-called interpretability of features. Moreover, stability is introduced in the criterion of SIP-FS to obtain consistent results of ranking. We conduct experiments on three publicly available datasets using one-versus-all strategy to select class-specific features. The experiments illustrate that SIP-FS achieves significant performance improvements in terms of stability and interpretability with desirable prediction accuracy and indicates advantages over several state-of-the-art approaches.

  14. Integration of heterogeneous features for remote sensing scene classification

    Science.gov (United States)

    Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

    2018-01-01

    Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

  15. EOG feature relevance determination for microsleep detection

    Directory of Open Access Journals (Sweden)

    Golz Martin

    2017-09-01

    Full Text Available Automatic relevance determination (ARD was applied to two-channel EOG recordings for microsleep event (MSE recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC and logarithmic power spectral densities (PSD averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM, in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 – 4.9 % and 1.9 – 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 – 0.006 % and 0.002 – 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respectively. GRLVQ permits objective feature reduction by inclusion of all processing stages, but is not as accurate as SVM.

  16. EOG feature relevance determination for microsleep detection

    Directory of Open Access Journals (Sweden)

    Golz Martin

    2017-09-01

    Full Text Available Automatic relevance determination (ARD was applied to two-channel EOG recordings for microsleep event (MSE recognition. 10 s immediately before MSE and also before counterexamples of fatigued, but attentive driving were analysed. Two type of signal features were extracted: the maximum cross correlation (MaxCC and logarithmic power spectral densities (PSD averaged in spectral bands of 0.5 Hz width ranging between 0 and 8 Hz. Generalised learn-ing vector quantisation (GRLVQ was used as ARD method to show the potential of feature reduction. This is compared to support-vector machines (SVM, in which the feature reduction plays a much smaller role. Cross validation yielded mean normalised relevancies of PSD features in the range of 1.6 - 4.9 % and 1.9 - 10.4 % for horizontal and vertical EOG, respectively. MaxCC relevancies were 0.002 - 0.006 % and 0.002 - 0.06 %, respectively. This shows that PSD features of vertical EOG are indispensable, whereas MaxCC can be neglected. Mean classification accuracies were estimated at 86.6±b 1.3 % and 92.3±b 0.2 % for GRLVQ and SVM, respec-tively. GRLVQ permits objective feature reduction by inclu-sion of all processing stages, but is not as accurate as SVM.

  17. Tunable features of magnetoelectric transformers.

    Science.gov (United States)

    Dong, Shuxiang; Zhai, Junyi; Priya, Shashank; Li, Jie-Fang; Viehland, Dwight

    2009-06-01

    We have found that magnetostrictive FeBSiC alloy ribbons laminated with piezoelectric Pb(Zr,Ti)O(3) fiber can act as a tunable transformer when driven under resonant conditions. These composites were also found to exhibit the strongest resonant magnetoelectric voltage coefficient of 750 V/cm-Oe. The tunable features were achieved by applying small dc magnetic biases of -5 transformer features can be attributed to large changes in the piezomagnetic coefficient and permeability of the magnetostrictive phase under H(dc).

  18. Enhanced feature integration in musicians

    DEFF Research Database (Denmark)

    Hansen, Niels Christian; Højlund, Andreas; Møller, Cecilie

    the classical oddball control paradigm which used identical sounds. This novel finding supports the dependent processing hypothesis suggesting that musicians recruit overlapping neural resources facilitating more holistic representations of domain-relevant stimuli. These specialised refinements in predictive......Distinguishing and integrating features of sensory input is essential to human survival and no less paramount in music perception and cognition. Yet, little is known about training-induced plasticity of neural mechanisms for auditory feature integration. This study aimed to contrast the two...

  19. Solving jigsaw puzzles using image features

    DEFF Research Database (Denmark)

    Nielsen, Ture R.; Drewsen, Peter; Hansen, Klaus

    2008-01-01

    In this article, we describe a method for automatic solving of the jigsaw puzzle problem based on using image features instead of the shape of the pieces. The image features are used for obtaining an accurate measure for edge similarity to be used in a new edge matching algorithm. The algorithm i...

  20. FEATURE EVALUATION FOR BUILDING FACADE IMAGES – AN EMPIRICAL STUDY

    Directory of Open Access Journals (Sweden)

    M. Y. Yang

    2012-08-01

    Full Text Available The classification of building facade images is a challenging problem that receives a great deal of attention in the photogrammetry community. Image classification is critically dependent on the features. In this paper, we perform an empirical feature evaluation task for building facade images. Feature sets we choose are basic features, color features, histogram features, Peucker features, texture features, and SIFT features. We present an approach for region-wise labeling using an efficient randomized decision forest classifier and local features. We conduct our experiments with building facade image classification on the eTRIMS dataset, where our focus is the object classes building, car, door, pavement, road, sky, vegetation, and window.

  1. Learning Transferable Features with Deep Adaptation Networks

    OpenAIRE

    Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.

    2015-01-01

    Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...

  2. SIFT based algorithm for point feature tracking

    Directory of Open Access Journals (Sweden)

    Adrian BURLACU

    2007-12-01

    Full Text Available In this paper a tracking algorithm for SIFT features in image sequences is developed. For each point feature extracted using SIFT algorithm a descriptor is computed using information from its neighborhood. Using an algorithm based on minimizing the distance between two descriptors tracking point features throughout image sequences is engaged. Experimental results, obtained from image sequences that capture scaling of different geometrical type object, reveal the performances of the tracking algorithm.

  3. Mining Videos for Features that Drive Attention

    Science.gov (United States)

    2015-04-01

    that can be added or removed from the final saliency computation. Examples of these features include intensity contrast, motion energy , color opponent...corresponding to the image. Each pixel in the feature map indicates the energy that the feature in question contributes at that location. In the standard...eye and head animation using a neurobio - logical model of visual attention. In: Bosacchi B, Fogel DB, Bezdek JC (eds) Proceedings of SPIE 48th annual

  4. Radiographic features of periapical cysts and granulomas

    OpenAIRE

    Zain, R. B.; Roswati, N.; Ismail, K.

    1989-01-01

    Many studies have been reported on radiographic lesion sizes of periapical lesions. However no studies have been reported on prevalences of subjective radiographic features in these lesions except for the early assumption that a periapical cyst usually exhibit a radiopaque cortex. This study is conducted to evaluate the prevalences of several subjective radiographic features of periapical cysts and granulomas in the hope to identify features that maybe suggestive of either diagnosis. The resu...

  5. PROBLEMATIC FEATURES OF THE POLITICAL DECISION MAKERS

    OpenAIRE

    Aleksey Sergeevih Voynov

    2014-01-01

    Purpose: identify the most important features in the process of making political decisions that affect the effectiveness of problem-solving situationsScientific novelty: as a result of the analysis identified the problematic features of major importance for the efficiency of the development and adoption of the most rational solution to a problem situation.Results: the analysis of the most significant features affecting the quality of decisions among them the interest of the person making deci...

  6. Recognition of handwritten characters using local gradient feature descriptors

    NARCIS (Netherlands)

    Surinta, Olarik; Karaaba, Mahir F.; Schomaker, Lambert R.B.; Wiering, Marco A.

    2015-01-01

    Abstract In this paper we propose to use local gradient feature descriptors, namely the scale invariant feature transform keypoint descriptor and the histogram of oriented gradients, for handwritten character recognition. The local gradient feature descriptors are used to extract feature vectors

  7. MetaFIND: A feature analysis tool for metabolomics data

    Directory of Open Access Journals (Sweden)

    Cunningham Pádraig

    2008-11-01

    Full Text Available Abstract Background Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis produces a set of peaks, or features, indicative of the metabolic composition of the sample and may be used as a basis for sample classification. Feature selection may be employed to improve classification accuracy or aid model explanation by establishing a subset of class discriminating features. Factors such as experimental noise, choice of technique and threshold selection may adversely affect the set of selected features retrieved. Furthermore, the high dimensionality and multi-collinearity inherent within metabolomics data may exacerbate discrepancies between the set of features retrieved and those required to provide a complete explanation of metabolite signatures. Given these issues, the latter in particular, we present the MetaFIND application for 'post-feature selection' correlation analysis of metabolomics data. Results In our evaluation we show how MetaFIND may be used to elucidate metabolite signatures from the set of features selected by diverse techniques over two metabolomics datasets. Importantly, we also show how MetaFIND may augment standard feature selection and aid the discovery of additional significant features, including those which represent novel class discriminating metabolites. MetaFIND also supports the discovery of higher level metabolite correlations. Conclusion Standard feature selection techniques may fail to capture the full set of relevant features in the case of high dimensional, multi-collinear metabolomics data. We show that the MetaFIND 'post-feature selection' analysis tool may aid metabolite signature elucidation, feature discovery and inference of metabolic correlations.

  8. Interactive music composition driven by feature evolution.

    Science.gov (United States)

    Kaliakatsos-Papakostas, Maximos A; Floros, Andreas; Vrahatis, Michael N

    2016-01-01

    Evolutionary music composition is a prominent technique for automatic music generation. The immense adaptation potential of evolutionary algorithms has allowed the realisation of systems that automatically produce music through feature and interactive-based composition approaches. Feature-based composition employs qualitatively descriptive music features as fitness landmarks. Interactive composition systems on the other hand, derive fitness directly from human ratings and/or selection. The paper at hand introduces a methodological framework that combines the merits of both evolutionary composition methodologies. To this end, a system is presented that is organised in two levels: the higher level of interaction and the lower level of composition. The higher level incorporates the particle swarm optimisation algorithm, along with a proposed variant and evolves musical features according to user ratings. The lower level realizes feature-based music composition with a genetic algorithm, according to the top level features. The aim of this work is not to validate the efficiency of the currently utilised setup in each level, but to examine the convergence behaviour of such a two-level technique in an objective manner. Therefore, an additional novelty in this work concerns the utilisation of artificial raters that guide the system through the space of musical features, allowing the exploration of its convergence characteristics: does the system converge to optimal melodies, is this convergence fast enough for potential human listeners and is the trajectory to convergence "interesting' and "creative" enough? The experimental results reveal that the proposed methodological framework represents a fruitful and robust, novel approach to interactive music composition.

  9. Feature-aware natural texture synthesis

    KAUST Repository

    Wu, Fuzhang

    2014-12-04

    This article presents a framework for natural texture synthesis and processing. This framework is motivated by the observation that given examples captured in natural scene, texture synthesis addresses a critical problem, namely, that synthesis quality can be affected adversely if the texture elements in an example display spatially varied patterns, such as perspective distortion, the composition of different sub-textures, and variations in global color pattern as a result of complex illumination. This issue is common in natural textures and is a fundamental challenge for previously developed methods. Thus, we address it from a feature point of view and propose a feature-aware approach to synthesize natural textures. The synthesis process is guided by a feature map that represents the visual characteristics of the input texture. Moreover, we present a novel adaptive initialization algorithm that can effectively avoid the repeat and verbatim copying artifacts. Our approach improves texture synthesis in many images that cannot be handled effectively with traditional technologies.

  10. Histological image classification using biologically interpretable shape-based features

    International Nuclear Information System (INIS)

    Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

    2013-01-01

    Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions

  11. Grammar-based feature generation for time-series prediction

    CERN Document Server

    De Silva, Anthony Mihirana

    2015-01-01

    This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method ...

  12. Treatment recommendations for DSM-5-defined mixed features.

    Science.gov (United States)

    Rosenblat, Joshua D; McIntyre, Roger S

    2017-04-01

    The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) mixed features specifier provides a less restrictive definition of mixed mood states, compared to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR), including mood episodes that manifest with subthreshold symptoms of the opposite mood state. A limited number of studies have assessed the efficacy of treatments specifically for DSM-5-defined mixed features in mood disorders. As such, there is currently an inadequate amount of data to appropriately inform evidence-based treatment guidelines of DSM-5 defined mixed features. However, given the high prevalence and morbidity of mixed features, treatment recommendations based on the currently available evidence along with expert opinion may be of benefit. This article serves to provide these interim treatment recommendations while humbly acknowledging the limited amount of evidence currently available. Second-generation antipsychotics (SGAs) appear to have the greatest promise in the treatment of bipolar disorder (BD) with mixed features. Conventional mood stabilizing agents (ie, lithium and divalproex) may also be of benefit; however, they have been inadequately studied. In the treatment of major depressive disorder (MDD) with mixed features, the comparable efficacy of antidepressants versus other treatments, such as SGAs, remains unknown. As such, antidepressants remain first-line treatment of MDD with or without mixed features; however, there are significant safety concerns associated with antidepressant monotherapy when mixed features are present, which merits increased monitoring. Lurasidone is the only SGA monotherapy that has been shown to be efficacious specifically in the treatment of MDD with mixed features. Further research is needed to accurately determine the efficacy, safety, and tolerability of treatments specifically for mood episodes with mixed features to adequately inform

  13. A feature dictionary supporting a multi-domain medical knowledge base.

    Science.gov (United States)

    Naeymi-Rad, F

    1989-01-01

    Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.

  14. Online Feature Selection for Classifying Emphysema in HRCT Images

    Directory of Open Access Journals (Sweden)

    M. Prasad

    2008-06-01

    Full Text Available Feature subset selection, applied as a pre- processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier performance. In the classic formulation of the feature selection problem, it is assumed that all the features are available at the beginning. However, in many real world problems, there are scenarios where not all features are present initially and must be integrated as they become available. In such scenarios, online feature selection provides an efficient way to sort through a large space of features. It is in this context that we introduce online feature selection for the classification of emphysema, a smoking related disease that appears as low attenuation regions in High Resolution Computer Tomography (HRCT images. The technique was successfully evaluated on 61 HRCT scans and compared with different online feature selection approaches, including hill climbing, best first search, grafting, and correlation-based feature selection. The results were also compared against ldensity maskr, a standard approach used for emphysema detection in medical image analysis.

  15. Feature Selection via Chaotic Antlion Optimization.

    Directory of Open Access Journals (Sweden)

    Hossam M Zawbaa

    Full Text Available Selecting a subset of relevant properties from a large set of features that describe a dataset is a challenging machine learning task. In biology, for instance, the advances in the available technologies enable the generation of a very large number of biomarkers that describe the data. Choosing the more informative markers along with performing a high-accuracy classification over the data can be a daunting task, particularly if the data are high dimensional. An often adopted approach is to formulate the feature selection problem as a biobjective optimization problem, with the aim of maximizing the performance of the data analysis model (the quality of the data training fitting while minimizing the number of features used.We propose an optimization approach for the feature selection problem that considers a "chaotic" version of the antlion optimizer method, a nature-inspired algorithm that mimics the hunting mechanism of antlions in nature. The balance between exploration of the search space and exploitation of the best solutions is a challenge in multi-objective optimization. The exploration/exploitation rate is controlled by the parameter I that limits the random walk range of the ants/prey. This variable is increased iteratively in a quasi-linear manner to decrease the exploration rate as the optimization progresses. The quasi-linear decrease in the variable I may lead to immature convergence in some cases and trapping in local minima in other cases. The chaotic system proposed here attempts to improve the tradeoff between exploration and exploitation. The methodology is evaluated using different chaotic maps on a number of feature selection datasets. To ensure generality, we used ten biological datasets, but we also used other types of data from various sources. The results are compared with the particle swarm optimizer and with genetic algorithm variants for feature selection using a set of quality metrics.

  16. Features Selection for Skin Micro-Image Symptomatic Recognition

    Institute of Scientific and Technical Information of China (English)

    HUYue-li; CAOJia-lin; ZHAOQian; FENGXu

    2004-01-01

    Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92% using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

  17. Features Selection for Skin Micro-Image Symptomatic Recognition

    Institute of Scientific and Technical Information of China (English)

    HU Yue-li; CAO Jia-lin; ZHAO Qian; FENG Xu

    2004-01-01

    Automatic recognition of skin micro-image symptom is important in skin diagnosis and treatment. Feature selection is to improve the classification performance of skin micro-image symptom.This paper proposes a hybrid approach based on the support vector machine (SVM) technique and genetic algorithm (GA) to select an optimum feature subset from the feature group extracted from the skin micro-images. An adaptive GA is introduced for maintaining the convergence rate. With the proposed method, the average cross validation accuracy is increased from 88.25% using all features to 96.92 % using only selected features provided by a classifier for classification of 5 classes of skin symptoms. The experimental results are satisfactory.

  18. Teaching World Music through Feature Films

    Science.gov (United States)

    Lum, Chee-Hoo

    2009-01-01

    When used effectively, feature films can bring a plethora of visual and aural stimulation to students and enhance their learning about world cultures. Feature films can take students to places, sights, and sounds that they have yet to experience. After watching these films, students might become new admirers or even keen followers of the subject…

  19. Recent Development of the Two-Stroke Engine. II - Design Features. 2; Design Features

    Science.gov (United States)

    Zeman, J.

    1945-01-01

    Completing the first paper dealing with charging methods and arrangements, the present paper discusses the design forms of two-stroke engines. Features which largely influence piston running are: (a) The shape and surface condition of the sliding parts. (b) The cylinder and piston materials. (c) Heat conditions in the piston, and lubrication. There is little essential difference between four-stroke and two-stroke engines with ordinary pistons. In large engines, for example, are always found separately cast or welded frames in which the stresses are taken up by tie rods. Twin piston and timing piston engines often differ from this design. Examples can be found in many engines of German or foreign make. Their methods of operation will be dealt with in the third part of the present paper, which also includes the bibliography. The development of two-stroke engine design is, of course, mainly concerned with such features as are inherently difficult to master; that is, the piston barrel and the design of the gudgeon pin bearing. Designers of four-stroke engines now-a-days experience approximately the same difficulties, since heat stresses have increased to the point of influencing conditions in the piston barrel. Features which notably affect this are: (a) The material. (b) Prevailing heat conditions.

  20. New features of the Helioviewer Project

    Science.gov (United States)

    Ireland, J.; Zahniy, S.; Nicula, B.; Mueller, D.; Felix, S.; Verstringe, F.; Bourgoignie, B.

    2016-12-01

    This year saw the release of major new upgrades to the capabilities of helioviewer.org and JHelioviewer. The helioviewer.org interface was completely re-designed, and now provides image and feature/event time-lines and data download capabilities. JHelioviewer introduced interactive time-series, the ability to query different servers for different data, and image reprojection. We introduce the new features of these software releases and give use cases. We will summarize our latest usage statistics, and discuss what's coming up next for the Helioviewer Project. We will also be soliciting bug reports, requests for new features and comments on the effectiveness of helioviewer.org and JHelioviewer. What would you like to see next from the Helioviewer Project?

  1. Temporal resolution for the perception of features and conjunctions.

    Science.gov (United States)

    Bodelón, Clara; Fallah, Mazyar; Reynolds, John H

    2007-01-24

    The visual system decomposes stimuli into their constituent features, represented by neurons with different feature selectivities. How the signals carried by these feature-selective neurons are integrated into coherent object representations is unknown. To constrain the set of possible integrative mechanisms, we quantified the temporal resolution of perception for color, orientation, and conjunctions of these two features. We find that temporal resolution is measurably higher for each feature than for their conjunction, indicating that time is required to integrate features into a perceptual whole. This finding places temporal limits on the mechanisms that could mediate this form of perceptual integration.

  2. Feature Binding and the Hebb Repetition Effect

    OpenAIRE

    Barrett, Maeve

    2008-01-01

    Previous studies have found no evidence that long-term learning of integrated objects and individual features benefit visual short term memory tasks (Logie, Brockmole, & Vandenbroucke, in press; Olson & Jiang, 2004; Treisman, 2006). These findings may have been due to stimulus interference as a restricted number of features were utilised in these studies to form objects in the stimulus arrays. In these studies, participants would have needed to break apart the features of several objects in a...

  3. Preliminary global paleogeographic maps through the Greenhouse-Icehouse transition: forcing of the Drake Passage and Asian Monsoons.

    Science.gov (United States)

    Poblete, Fernando; Dupont-Nivet, Guillaume; Licht, Alexis; van Hinsbergen, Douwe; Roperch, Pierrick; Guillocheau, Francois; Baby, Guillaume; Baatsen, Michiel

    2017-04-01

    Paleogeographic maps are essential for understanding Earth dynamics. They provide the necessary boundary conditions for climate and geodynamic modeling, surface processes and biotic interactions. In particular, the opening and closing of ocean gateways and the growth of major mountain belts are major drivers of climate changes and biotic interchange. However, the timing and spatial extent of such events are highly controversial and regularly questioned by new data. As part of the ERC "MAGIC" project focusing on Asian Monsoons during the Icehouse to Greenhouse transition we thus produced a set of worldwide Cenozoic paleogeographic maps in the period time between 60 to 20 Ma, with a set of boundary conditions specific to the India-Asia collision zone and the Drake Passage. The creation of a paleogeographic map followed a rigorous and reproductively methodology that integrates paleobathymetric, paleoshoreline and paleotopographic data into a coherent plate tectonic model using the open source software GPlates. (1) We use the model provided by Seton et al. (2012) as a first order tectonic model modified to integrate the full restoration of five regions: the Andes, the Scotia Arc, Africa, The Mediterranean Sea and the Tibet-Himalayan collision zone. (2) The paleobathymetry was provided by Müller et al. (2008) using age-depth relationships and assuming symmetric ridge spreading. (3) Paleoshoreline maps were modified according to the fossil database from fossilworks.org and the geological record and were used to represent the boundary between terrestrial and marine paleo-environments. (4) To reconstruct paleoelevations, the most controversial task, we compiled a wide range of data including stable isotope, leaf physiognomy, and thermochronology combined with regional fossil and geological records (tectonic setting) and geomorphological data. Finally, we use the open source GMT software and a set of masks to modify the current Earth relief model (ETOPO) according to the

  4. Optimized feature subsets for epileptic seizure prediction studies.

    Science.gov (United States)

    Direito, Bruno; Ventura, Francisco; Teixeira, César; Dourado, António

    2011-01-01

    The reduction of the number of EEG features to give as inputs to epilepsy seizure predictors is a needed step towards the development of a transportable device for real-time warning. This paper presents a comparative study of three feature selection methods, based on Support Vector Machines. Minimum-Redundancy Maximum-Relevance, Recursive Feature Elimination, Genetic Algorithms, show that, for three patients of the European Database on Epilepsy, the most important univariate features are related to spectral information and statistical moments.

  5. Imaging features of thalassemia

    Energy Technology Data Exchange (ETDEWEB)

    Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B. [Dept. of Radiology, Istanbul Univ. (Turkey); Dincol, G. [Dept. of Internal Medicine, Istanbul Univ. (Turkey)

    1999-07-01

    Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of {beta}-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

  6. Imaging features of thalassemia

    International Nuclear Information System (INIS)

    Tunaci, M.; Tunaci, A.; Engin, G.; Oezkorkmaz, B.; Acunas, G.; Acunas, B.; Dincol, G.

    1999-01-01

    Thalassemia is a kind of chronic, inherited, microcytic anemia characterized by defective hemoglobin synthesis and ineffective erythropoiesis. In all thalassemias clinical features that result from anemia, transfusional, and absorptive iron overload are similar but vary in severity. The radiographic features of β-thalassemia are due in large part to marrow hyperplasia. Markedly expanded marrow space lead to various skeletal manifestations including spine, skull, facial bones, and ribs. Extramedullary hematopoiesis (ExmH), hemosiderosis, and cholelithiasis are among the non-skeletal manifestations of thalassemia. The skeletal X-ray findings show characteristics of chronic overactivity of the marrow. In this article both skeletal and non-skeletal manifestations of thalassemia are discussed with an overview of X-ray findings, including MRI and CT findings. (orig.)

  7. Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

    Science.gov (United States)

    Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

    2017-09-22

    DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

  8. Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods

    Directory of Open Access Journals (Sweden)

    Kaiyang Qu

    2017-09-01

    Full Text Available DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF, is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

  9. Low-Dimensional Feature Representation for Instrument Identification

    Science.gov (United States)

    Ihara, Mizuki; Maeda, Shin-Ichi; Ikeda, Kazushi; Ishii, Shin

    For monophonic music instrument identification, various feature extraction and selection methods have been proposed. One of the issues toward instrument identification is that the same spectrum is not always observed even in the same instrument due to the difference of the recording condition. Therefore, it is important to find non-redundant instrument-specific features that maintain information essential for high-quality instrument identification to apply them to various instrumental music analyses. For such a dimensionality reduction method, the authors propose the utilization of linear projection methods: local Fisher discriminant analysis (LFDA) and LFDA combined with principal component analysis (PCA). After experimentally clarifying that raw power spectra are actually good for instrument classification, the authors reduced the feature dimensionality by LFDA or by PCA followed by LFDA (PCA-LFDA). The reduced features achieved reasonably high identification performance that was comparable or higher than those by the power spectra and those achieved by other existing studies. These results demonstrated that our LFDA and PCA-LFDA can successfully extract low-dimensional instrument features that maintain the characteristic information of the instruments.

  10. Hindi vowel classification using QCN-MFCC features

    Directory of Open Access Journals (Sweden)

    Shipra Mishra

    2016-09-01

    Full Text Available In presence of environmental noise, speakers tend to emphasize their vocal effort to improve the audibility of voice. This involuntary adjustment is known as Lombard effect (LE. Due to LE the signal to noise ratio of speech increases, but at the same time the loudness, pitch and duration of phonemes changes. Hence, accuracy of automatic speech recognition systems degrades. In this paper, the effect of unsupervised equalization of Lombard effect is investigated for Hindi vowel classification task using Hindi database designed at TIFR Mumbai, India. Proposed Quantile-based Dynamic Cepstral Normalization MFCC (QCN-MFCC along with baseline MFCC features have been used for vowel classification. Hidden Markov Model (HMM is used as classifier. It is observed that QCN-MFCC features have given a maximum improvement of 5.97% and 5% over MFCC features for context-dependent and context-independent cases respectively. It is also observed that QCN-MFCC features have given improvement of 13% and 11.5% over MFCC features for context-dependent and context-independent classification of mid vowels.

  11. Breast Cancer Detection with Reduced Feature Set

    Directory of Open Access Journals (Sweden)

    Ahmet Mert

    2015-01-01

    Full Text Available This paper explores feature reduction properties of independent component analysis (ICA on breast cancer decision support system. Wisconsin diagnostic breast cancer (WDBC dataset is reduced to one-dimensional feature vector computing an independent component (IC. The original data with 30 features and reduced one feature (IC are used to evaluate diagnostic accuracy of the classifiers such as k-nearest neighbor (k-NN, artificial neural network (ANN, radial basis function neural network (RBFNN, and support vector machine (SVM. The comparison of the proposed classification using the IC with original feature set is also tested on different validation (5/10-fold cross-validations and partitioning (20%–40% methods. These classifiers are evaluated how to effectively categorize tumors as benign and malignant in terms of specificity, sensitivity, accuracy, F-score, Youden’s index, discriminant power, and the receiver operating characteristic (ROC curve with its criterion values including area under curve (AUC and 95% confidential interval (CI. This represents an improvement in diagnostic decision support system, while reducing computational complexity.

  12. Feature-based tolerancing for intelligent inspection process definition

    International Nuclear Information System (INIS)

    Brown, C.W.

    1993-07-01

    This paper describes a feature-based tolerancing capability that complements a geometric solid model with an explicit representation of conventional and geometric tolerances. This capability is focused on supporting an intelligent inspection process definition system. The feature-based tolerance model's benefits include advancing complete product definition initiatives (e.g., STEP -- Standard for Exchange of Product model dam), suppling computer-integrated manufacturing applications (e.g., generative process planning and automated part programming) with product definition information, and assisting in the solution of measurement performance issues. A feature-based tolerance information model was developed based upon the notion of a feature's toleranceable aspects and describes an object-oriented scheme for representing and relating tolerance features, tolerances, and datum reference frames. For easy incorporation, the tolerance feature entities are interconnected with STEP solid model entities. This schema will explicitly represent the tolerance specification for mechanical products, support advanced dimensional measurement applications, and assist in tolerance-related methods divergence issues

  13. Dynamic Features for Iris Recognition.

    Science.gov (United States)

    da Costa, R M; Gonzaga, A

    2012-08-01

    The human eye is sensitive to visible light. Increasing illumination on the eye causes the pupil of the eye to contract, while decreasing illumination causes the pupil to dilate. Visible light causes specular reflections inside the iris ring. On the other hand, the human retina is less sensitive to near infra-red (NIR) radiation in the wavelength range from 800 nm to 1400 nm, but iris detail can still be imaged with NIR illumination. In order to measure the dynamic movement of the human pupil and iris while keeping the light-induced reflexes from affecting the quality of the digitalized image, this paper describes a device based on the consensual reflex. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light. In this paper, we propose to capture images of the pupil of one eye using NIR illumination while illuminating the other eye using a visible-light pulse. This new approach extracts iris features called "dynamic features (DFs)." This innovative methodology proposes the extraction of information about the way the human eye reacts to light, and to use such information for biometric recognition purposes. The results demonstrate that these features are discriminating features, and, even using the Euclidean distance measure, an average accuracy of recognition of 99.1% was obtained. The proposed methodology has the potential to be "fraud-proof," because these DFs can only be extracted from living irises.

  14. Performance Evaluation of Feature Sets of Minutiae Quadruplets ...

    African Journals Online (AJOL)

    The features proposed in this paper are derived from minutiae quadruplets and are applicable in matching and indexing ngerprint images. In this work nineteen different possibilities of features were explored for indexing and the performances of some of the feature sets were mixed: some giving good performances on ...

  15. ANATOMIC AND PHYSIOLOGICAL FEATURES OF DISTAL LOWER LEG AND THEIR INFLUENCE ON THE PROCESS OF OSTEOGENESIS

    Directory of Open Access Journals (Sweden)

    Desimir Mladenović

    2010-06-01

    Full Text Available Osteogenesis is the process of bone tissue forming, i.e. bone or callus regeneration. This process is influenced by many factors, and the degree of bone fragments’ stability and vascularization in the fracture area are the basic local factors which determine the nature of reparative process. Regenerative process of all bone structures increases with increasing of blood supply.The distal lower leg has its specific biomechanical features, and plays an important role in the transfer of body weight to foot. The distal part of tibia has a small diameter, which as a consequence has reduced diameter in medullar cave. Through this anatomic feature, the medullar network in the lower tibia part is also reduced.As for anatomic aspect, vascularization in the lower end of tibia is poor. It primarily depends on periosteal vascularization, because medullar vascularization is reduced. Fasciae, tendons and skin cover the lower part of the leg, and there is no muscle mass. These tissues have poor vascular network and that is why the extraosseous blood circulation in tibia is poor, and does not participate in the osteogenesis process. For these reasons, distal lower leg represents a predelection site for delayed osteogenesis and pseudoarthrosys development.Osteosynthesis causes secondary damage to bone and soft tissue circulation. The screw plate damages the periosteal circulation – in the lower part of tibia it is the main source of vascularization, and for this reason, this method of osteosynthesis should not be applied. The external fixator has a sparing role regarding vascularization, and that is the reason why this method is recommended for fracture stabilization at the level of distal lower leg.

  16. Feature Selection for Audio Surveillance in Urban Environment

    Directory of Open Access Journals (Sweden)

    KIKTOVA Eva

    2014-05-01

    Full Text Available This paper presents the work leading to the acoustic event detection system, which is designed to recognize two types of acoustic events (shot and breaking glass in urban environment. For this purpose, a huge front-end processing was performed for the effective parametric representation of an input sound. MFCC features and features computed during their extraction (MELSPEC and FBANK, then MPEG-7 audio descriptors and other temporal and spectral characteristics were extracted. High dimensional feature sets were created and in the next phase reduced by the mutual information based selection algorithms. Hidden Markov Model based classifier was applied and evaluated by the Viterbi decoding algorithm. Thus very effective feature sets were identified and also the less important features were found.

  17. Research on oral test modeling based on multi-feature fusion

    Science.gov (United States)

    Shi, Yuliang; Tao, Yiyue; Lei, Jun

    2018-04-01

    In this paper, the spectrum of speech signal is taken as an input of feature extraction. The advantage of PCNN in image segmentation and other processing is used to process the speech spectrum and extract features. And a new method combining speech signal processing and image processing is explored. At the same time of using the features of the speech map, adding the MFCC to establish the spectral features and integrating them with the features of the spectrogram to further improve the accuracy of the spoken language recognition. Considering that the input features are more complicated and distinguishable, we use Support Vector Machine (SVM) to construct the classifier, and then compare the extracted test voice features with the standard voice features to achieve the spoken standard detection. Experiments show that the method of extracting features from spectrograms using PCNN is feasible, and the fusion of image features and spectral features can improve the detection accuracy.

  18. Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection

    Directory of Open Access Journals (Sweden)

    Jaesung Lee

    2016-11-01

    Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

  19. Features of upbringing children in civil law

    OpenAIRE

    Лобжанідзе, Давид

    2014-01-01

    The paper analyzes the features of upbringing children in civil law, in particular under the Civil Code of Georgia. The author examines the concept of the family as a social phenomenon and its underlying principles. Attention is paid also to the court practice of upbringing children and determining the place of their residence. English abstract D. Lobzhanidze Features of upbringing children in civil law. The paper analyzes the features of upbringing children in civil law, in particular u...

  20. Clinical features of radiation retinopathy

    International Nuclear Information System (INIS)

    Tabuchi, Shoko; Oda, Itsuo; Okawa, Tomohiko

    1977-01-01

    The clinical features of 25 cases with radiation retinopathy are described. Retinopathy was induced following therapeutic irradiation of paraobital malignancies with megavoltage Linac x-ray of 3,000 rads or more. Retinal vessels, particularly the proximal portion of retinal arteries, seemed to be the primary site of damage due to radiation. According to the type of lesion and dosage, fundus features simulated papillitis, retinal angiosclerosis, or hard exudates due to capillary obliteration. Acute obstruction of the central retinal artery and ischemic optic neuropathy could result from heavy irradiation of over 5,000 rads. (Evans, J.)

  1. News and Features Updates from USA.gov

    Data.gov (United States)

    General Services Administration — Stay on top of important government news and information with the USA.gov Updates: News and Features RSS feed. We'll update this feed when we add news and featured...

  2. Realistic Free-Spins Features Increase Preference for Slot Machines.

    Science.gov (United States)

    Taylor, Lorance F; Macaskill, Anne C; Hunt, Maree J

    2017-06-01

    Despite increasing research into how the structural characteristics of slot machines influence gambling behaviour there have been no experimental investigations into the effect of free-spins bonus features-a structural characteristic that is commonly central to the design of slot machines. This series of three experiments investigated the free-spins feature using slot machine simulations to determine whether participants allocate more wagers to a machine with free spins, and, which components of free-spins features drive this preference. In each experiment, participants were exposed to two computer-simulated slot machines-one with a free-spins feature or similar bonus feature and one without. Participants then completed a testing phase where they could freely switch between the two machines. In Experiment 1, participants did not prefer the machine with a simple free-spins feature. In Experiment 2 the free-spins feature incorporated additional elements such as sounds, animations, and an increased win frequency; participants preferred to gamble on this machine. The Experiment 3 "bonus feature" machine resembled the free spins machine in Experiment 2 except spins were not free; participants showed a clear preference for this machine also. These findings indicate that (1) free-spins features have a major influence over machine choice and (2) the "freeness" of the free-spins bonus features is not an important driver of preference, contrary to self-report and interview research with gamblers.

  3. Abdominal cocoon: sonographic features.

    Science.gov (United States)

    Vijayaraghavan, S Boopathy; Palanivelu, Chinnusamy; Sendhilkumar, Karuppusamy; Parthasarathi, Ramakrishnan

    2003-07-01

    An abdominal cocoon is a rare condition in which the small bowel is encased in a membrane. The diagnosis is usually established at surgery. Here we describe the sonographic features of this condition.

  4. A randomized trial of a DWI intervention program for first offenders: intervention outcomes and interactions with antisocial personality disorder among a primarily American-Indian sample.

    Science.gov (United States)

    Woodall, W Gill; Delaney, Harold D; Kunitz, Stephen J; Westerberg, Verner S; Zhao, Hongwei

    2007-06-01

    Randomized trial evidence on the effectiveness of incarceration and treatment of first-time driving while intoxicated (DWI) offenders who are primarily American Indian has yet to be reported in the literature on DWI prevention. Further, research has confirmed the association of antisocial personality disorder (ASPD) with problems with alcohol including DWI. A randomized clinical trial was conducted, in conjunction with 28 days of incarceration, of a treatment program incorporating motivational interviewing principles for first-time DWI offenders. The sample of 305 offenders including 52 diagnosed as ASPD by the Diagnostic Interview Schedule were assessed before assignment to conditions and at 6, 12, and 24 months after discharge. Self-reported frequency of drinking and driving as well as various measures of drinking over the preceding 90 days were available at all assessments for 244 participants. Further, DWI rearrest data for 274 participants were available for analysis. Participants randomized to receive the first offender incarceration and treatment program reported greater reductions in alcohol consumption from baseline levels when compared with participants who were only incarcerated. Antisocial personality disorder participants reported heavier and more frequent drinking but showed significantly greater declines in drinking from intake to posttreatment assessments. Further, the treatment resulted in larger effects relative to the control on ASPD than non-ASPD participants. Nonconfrontational treatment may significantly enhance outcomes for DWI offenders with ASPD when delivered in an incarcerated setting, and in the present study, such effects were found in a primarily American-Indian sample.

  5. Clinical features of AIDS patients with Hodgkin's lymphoma with isolated bone marrow involvement: report of 12 cases at a single institution

    International Nuclear Information System (INIS)

    Corti, Marcelo; Villafañe, Maria; Minue, Gonzalo; Campitelli, Ana; Narbaitz, Marina; Gilardi, Leonardo

    2015-01-01

    To study the main clinical and histopathological features of 12 patients with Hodgkin’s lymphoma (HL) diagnosed primarily from bone marrow (BM) involvement. We included 12 acquired immunodeficiency syndrome (AIDS) patients with HL assisted in the F. J. Muñiz Infectious Diseases Hospital since January 2002 to December 2013. The diagnosis of HL with primary BM involvement in patients was confirmed by clinical, histopathological, and immunohistochemical findings. All patients presented “B” symptoms and pancytopenia. All of them had stage IV neoplasm disease because of BM infiltration. The median of CD4 + T-cell counts was 114 cells/μL, and mixed cellularity (MC) was the most frequent histopathological subtype of 92% cases. When other causes are excluded, BM biopsy should be performed in AIDS patients with “B” symptoms and pancytopenia to evaluate BM infiltration by atypical lymphocytes

  6. Are Haar-like Rectangular Features for Biometric Recognition Reducible?

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Moeslund, Thomas B.

    2013-01-01

    Biometric recognition is still a very difficult task in real-world scenarios wherein unforeseen changes in degradations factors like noise, occlusion, blurriness and illumination can drastically affect the extracted features from the biometric signals. Very recently Haar-like rectangular features...... which have usually been used for object detection were introduced for biometric recognition resulting in systems that are robust against most of the mentioned degradations [9]. The problem with these features is that one can define many different such features for a given biometric signal...... and it is not clear whether all of these features are required for the actual recognition or not. This is exactly what we are dealing with in this paper: How can an initial set of Haar-like rectangular features, that have been used for biometric recognition, be reduced to a set of most influential features...

  7. Automatic processing of unattended object features by functional connectivity

    Directory of Open Access Journals (Sweden)

    Katja Martina Mayer

    2013-05-01

    Full Text Available Observers can selectively attend to object features that are relevant for a task. However, unattended task-irrelevant features may still be processed and possibly integrated with the attended features. This study investigated the neural mechanisms for processing both task-relevant (attended and task-irrelevant (unattended object features. The Garner paradigm was adapted for functional magnetic resonance imaging (fMRI to test whether specific brain areas process the conjunction of features or whether multiple interacting areas are involved in this form of feature integration. Observers attended to shape, colour, or non-rigid motion of novel objects while unattended features changed from trial to trial (change blocks or remained constant (no-change blocks during a given block. This block manipulation allowed us to measure the extent to which unattended features affected neural responses which would reflect the extent to which multiple object features are automatically processed. We did not find Garner interference at the behavioural level. However, we designed the experiment to equate performance across block types so that any fMRI results could not be due solely to differences in task difficulty between change and no-change blocks. Attention to specific features localised several areas known to be involved in object processing. No area showed larger responses on change blocks compared to no-change blocks. However, psychophysiological interaction analyses revealed that several functionally-localised areas showed significant positive interactions with areas in occipito-temporal and frontal areas that depended on block type. Overall, these findings suggest that both regional responses and functional connectivity are crucial for processing multi-featured objects.

  8. TreeBASIS Feature Descriptor and Its Hardware Implementation

    Directory of Open Access Journals (Sweden)

    Spencer Fowers

    2014-01-01

    Full Text Available This paper presents a novel feature descriptor called TreeBASIS that provides improvements in descriptor size, computation time, matching speed, and accuracy. This new descriptor uses a binary vocabulary tree that is computed using basis dictionary images and a test set of feature region images. To facilitate real-time implementation, a feature region image is binary quantized and the resulting quantized vector is passed into the BASIS vocabulary tree. A Hamming distance is then computed between the feature region image and the effectively descriptive basis dictionary image at a node to determine the branch taken and the path the feature region image takes is saved as a descriptor. The TreeBASIS feature descriptor is an excellent candidate for hardware implementation because of its reduced descriptor size and the fact that descriptors can be created and features matched without the use of floating point operations. The TreeBASIS descriptor is more computationally and space efficient than other descriptors such as BASIS, SIFT, and SURF. Moreover, it can be computed entirely in hardware without the support of a CPU for additional software-based computations. Experimental results and a hardware implementation show that the TreeBASIS descriptor compares well with other descriptors for frame-to-frame homography computation while requiring fewer hardware resources.

  9. High Dimensional Classification Using Features Annealed Independence Rules.

    Science.gov (United States)

    Fan, Jianqing; Fan, Yingying

    2008-01-01

    Classification using high-dimensional features arises frequently in many contemporary statistical studies such as tumor classification using microarray or other high-throughput data. The impact of dimensionality on classifications is largely poorly understood. In a seminal paper, Bickel and Levina (2004) show that the Fisher discriminant performs poorly due to diverging spectra and they propose to use the independence rule to overcome the problem. We first demonstrate that even for the independence classification rule, classification using all the features can be as bad as the random guessing due to noise accumulation in estimating population centroids in high-dimensional feature space. In fact, we demonstrate further that almost all linear discriminants can perform as bad as the random guessing. Thus, it is paramountly important to select a subset of important features for high-dimensional classification, resulting in Features Annealed Independence Rules (FAIR). The conditions under which all the important features can be selected by the two-sample t-statistic are established. The choice of the optimal number of features, or equivalently, the threshold value of the test statistics are proposed based on an upper bound of the classification error. Simulation studies and real data analysis support our theoretical results and demonstrate convincingly the advantage of our new classification procedure.

  10. 3-D FEATURE-BASED MATCHING BY RSTG APPROACH

    Directory of Open Access Journals (Sweden)

    J.-J. Jaw

    2012-07-01

    Full Text Available 3-D feature matching is the essential kernel in a fully automated feature-based LiDAR point cloud registration. After feasible procedures of feature acquisition, connecting corresponding features in different data frames is imperative to be solved. The objective addressed in this paper is developing an approach coined RSTG to retrieve corresponding counterparts of unsorted multiple 3-D features extracted from sets of LiDAR point clouds. RSTG stands for the four major processes, "Rotation alignment"; "Scale estimation"; "Translation alignment" and "Geometric check," strategically formulated towards finding out matching solution with high efficiency and leading to accomplishing the 3-D similarity transformation among all sets. The workable types of features to RSTG comprise points, lines, planes and clustered point groups. Each type of features can be employed exclusively or combined with others, if sufficiently supplied, throughout the matching scheme. The paper gives a detailed description of the matching methodology and discusses on the matching effects based on the statistical assessment which revealed that the RSTG approach reached an average matching rate of success up to 93% with around 6.6% of statistical type 1 error. Notably, statistical type 2 error, the critical indicator of matching reliability, was kept 0% throughout all the experiments.

  11. Parabolic features and the erosion rate on Venus

    Science.gov (United States)

    Strom, Robert G.

    1993-01-01

    The impact cratering record on Venus consists of 919 craters covering 98 percent of the surface. These craters are remarkably well preserved, and most show pristine structures including fresh ejecta blankets. Only 35 craters (3.8 percent) have had their ejecta blankets embayed by lava and most of these occur in the Atla-Beta Regio region; an area thought to be recently active. parabolic features are associated with 66 of the 919 craters. These craters range in size from 6 to 105 km diameter. The parabolic features are thought to be the result of the deposition of fine-grained ejecta by winds in the dense venusian atmosphere. The deposits cover about 9 percent of the surface and none appear to be embayed by younger volcanic materials. However, there appears to be a paucity of these deposits in the Atla-Beta Regio region, and this may be due to the more recent volcanism in this area of Venus. Since parabolic features are probably fine-grain, wind-deposited ejecta, then all impact craters on Venus probably had these deposits at some time in the past. The older deposits have probably been either eroded or buried by eolian processes. Therefore, the present population of these features is probably associated with the most recent impact craters on the planet. Furthermore, the size/frequency distribution of craters with parabolic features is virtually identical to that of the total crater population. This suggests that there has been little loss of small parabolic features compared to large ones, otherwise there should be a significant and systematic paucity of craters with parabolic features with decreasing size compared to the total crater population. Whatever is erasing the parabolic features apparently does so uniformly regardless of the areal extent of the deposit. The lifetime of parabolic features and the eolian erosion rate on Venus can be estimated from the average age of the surface and the present population of parabolic features.

  12. Real-time hypothesis driven feature extraction on parallel processing architectures

    DEFF Research Database (Denmark)

    Granmo, O.-C.; Jensen, Finn Verner

    2002-01-01

    the problem of higher-order feature-content/feature-feature correlation, causally complexly interacting features are identified through Bayesian network d-separation analysis and combined into joint features. When used on a moderately complex object-tracking case, the technique is able to select...... extraction, which selectively extract relevant features one-by-one, have in some cases achieved real-time performance on single processing element architectures. In this paperwe propose a novel technique which combines the above two approaches. Features are selectively extracted in parallelizable sets...

  13. Feature representation of RGB-D images using joint spatial-depth feature pooling

    DEFF Research Database (Denmark)

    Pan, Hong; Olsen, Søren Ingvor; Zhu, Yaping

    2016-01-01

    Recent development in depth imaging technology makes acquisition of depth information easier. With the additional depth cue, RGB-D cameras can provide effective support for many RGB-D perception tasks beyond traditional RGB information. However, current feature representation based on RGB-D image...

  14. Biophysical modelling of intra-ring variations in tracheid features and wood density of Pinus pinaster trees exposed to seasonal droughts.

    Science.gov (United States)

    Wilkinson, Sarah; Ogée, Jérôme; Domec, Jean-Christophe; Rayment, Mark; Wingate, Lisa

    2015-03-01

    Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus pinaster (L.) Aït.) stand exposed to seasonal droughts. Intra-annual variations in tracheid anatomy and wood density were identified through image analysis and X-ray densitometry on stem cores covering the growth period 1999-2010. A cambial growth model was integrated with modelled plant water status and sugar availability from the soil-plant-atmosphere transfer model MuSICA to generate estimates of cell number, cell volume, cell mass and wood density on a weekly time step. The model successfully predicted inter-annual variations in cell number, ring width and maximum wood density. The model was also able to predict the occurrence of special anatomical features such as intra-annual density fluctuations (IADFs) in growth rings. Since cell wall thickness remained surprisingly constant within and between growth rings, variations in wood density were primarily the result of variations in lumen diameter, both in the model and anatomical data. In the model, changes in plant water status were identified as the main driver of the IADFs through a direct effect on cell volume. The anatomy data also revealed that a trade-off existed between hydraulic safety and hydraulic efficiency. Although a simplified description of cambial physiology is presented, this integrated modelling approach shows potential value for identifying universal patterns of tree-ring growth and anatomical features over a broad climatic gradient. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  15. Dynamic binding of visual features by neuronal/stimulus synchrony.

    Science.gov (United States)

    Iwabuchi, A

    1998-05-01

    When people see a visual scene, certain parts of the visual scene are treated as belonging together and we regard them as a perceptual unit, which is called a "figure". People focus on figures, and the remaining parts of the scene are disregarded as "ground". In Gestalt psychology this process is called "figure-ground segregation". According to current perceptual psychology, a figure is formed by binding various visual features in a scene, and developments in neuroscience have revealed that there are many feature-encoding neurons, which respond to such features specifically. It is not known, however, how the brain binds different features of an object into a coherent visual object representation. Recently, the theory of binding by neuronal synchrony, which argues that feature binding is dynamically mediated by neuronal synchrony of feature-encoding neurons, has been proposed. This review article portrays the problem of figure-ground segregation and features binding, summarizes neurophysiological and psychophysical experiments and theory relevant to feature binding by neuronal/stimulus synchrony, and suggests possible directions for future research on this topic.

  16. Effective Feature Selection for Classification of Promoter Sequences.

    Directory of Open Access Journals (Sweden)

    Kouser K

    Full Text Available Exploring novel computational methods in making sense of biological data has not only been a necessity, but also productive. A part of this trend is the search for more efficient in silico methods/tools for analysis of promoters, which are parts of DNA sequences that are involved in regulation of expression of genes into other functional molecules. Promoter regions vary greatly in their function based on the sequence of nucleotides and the arrangement of protein-binding short-regions called motifs. In fact, the regulatory nature of the promoters seems to be largely driven by the selective presence and/or the arrangement of these motifs. Here, we explore computational classification of promoter sequences based on the pattern of motif distributions, as such classification can pave a new way of functional analysis of promoters and to discover the functionally crucial motifs. We make use of Position Specific Motif Matrix (PSMM features for exploring the possibility of accurately classifying promoter sequences using some of the popular classification techniques. The classification results on the complete feature set are low, perhaps due to the huge number of features. We propose two ways of reducing features. Our test results show improvement in the classification output after the reduction of features. The results also show that decision trees outperform SVM (Support Vector Machine, KNN (K Nearest Neighbor and ensemble classifier LibD3C, particularly with reduced features. The proposed feature selection methods outperform some of the popular feature transformation methods such as PCA and SVD. Also, the methods proposed are as accurate as MRMR (feature selection method but much faster than MRMR. Such methods could be useful to categorize new promoters and explore regulatory mechanisms of gene expressions in complex eukaryotic species.

  17. Feature-based RNN target recognition

    Science.gov (United States)

    Bakircioglu, Hakan; Gelenbe, Erol

    1998-09-01

    Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.

  18. Adversarial Feature Selection Against Evasion Attacks.

    Science.gov (United States)

    Zhang, Fei; Chan, Patrick P K; Biggio, Battista; Yeung, Daniel S; Roli, Fabio

    2016-03-01

    Pattern recognition and machine learning techniques have been increasingly adopted in adversarial settings such as spam, intrusion, and malware detection, although their security against well-crafted attacks that aim to evade detection by manipulating data at test time has not yet been thoroughly assessed. While previous work has been mainly focused on devising adversary-aware classification algorithms to counter evasion attempts, only few authors have considered the impact of using reduced feature sets on classifier security against the same attacks. An interesting, preliminary result is that classifier security to evasion may be even worsened by the application of feature selection. In this paper, we provide a more detailed investigation of this aspect, shedding some light on the security properties of feature selection against evasion attacks. Inspired by previous work on adversary-aware classifiers, we propose a novel adversary-aware feature selection model that can improve classifier security against evasion attacks, by incorporating specific assumptions on the adversary's data manipulation strategy. We focus on an efficient, wrapper-based implementation of our approach, and experimentally validate its soundness on different application examples, including spam and malware detection.

  19. Neural Architecture for Feature Binding in Visual Working Memory.

    Science.gov (United States)

    Schneegans, Sebastian; Bays, Paul M

    2017-04-05

    Binding refers to the operation that groups different features together into objects. We propose a neural architecture for feature binding in visual working memory that employs populations of neurons with conjunction responses. We tested this model using cued recall tasks, in which subjects had to memorize object arrays composed of simple visual features (color, orientation, and location). After a brief delay, one feature of one item was given as a cue, and the observer had to report, on a continuous scale, one or two other features of the cued item. Binding failure in this task is associated with swap errors, in which observers report an item other than the one indicated by the cue. We observed that the probability of swapping two items strongly correlated with the items' similarity in the cue feature dimension, and found a strong correlation between swap errors occurring in spatial and nonspatial report. The neural model explains both swap errors and response variability as results of decoding noisy neural activity, and can account for the behavioral results in quantitative detail. We then used the model to compare alternative mechanisms for binding nonspatial features. We found the behavioral results fully consistent with a model in which nonspatial features are bound exclusively via their shared location, with no indication of direct binding between color and orientation. These results provide evidence for a special role of location in feature binding, and the model explains how this special role could be realized in the neural system. SIGNIFICANCE STATEMENT The problem of feature binding is of central importance in understanding the mechanisms of working memory. How do we remember not only that we saw a red and a round object, but that these features belong together to a single object rather than to different objects in our environment? Here we present evidence for a neural mechanism for feature binding in working memory, based on encoding of visual

  20. Hepatozoon martis n. sp. (Adeleorina: Hepatozoidae): Morphological and pathological features of a Hepatozoon species infecting martens (family Mustelidae).

    Science.gov (United States)

    Hodžić, Adnan; Alić, Amer; Beck, Relja; Beck, Ana; Huber, Doroteja; Otranto, Domenico; Baneth, Gad; Duscher, Georg G

    2018-05-01

    Species of the genus Hepatozoon (Adeleorina: Hepatozoidae) are arthropod-transmitted protozoan parasites that infect a wide range of vertebrate hosts. In the present study, we describe a new species of Hepatozoon primarily infecting martens and propose the name Hepatozoon martis n. sp., based on its unique morphological, molecular and pathogenic features. The overall prevalence of infection with H. martis n. sp. assessed by PCR in European pine martens (Martes martes) from Bosnia and Herzegovina and stone martens (Martes foina) from Croatia was 100% and 64%, respectively. Gamonts were found in neutrophils and monocytes, and various developmental stages were described in tissue cross-sections. Hepatozoon martis n. sp. shows a high predilection for muscle tissue, and the heart was the most frequently affected organ among the tissues tested by histopathology. Microscopically, pyogranulomatous lesions associated with the presence of the parasitic forms were observed in the cardiac and skeletal muscles of all positive animals examined. Furthermore, the possible existence of alternative, non-vectorial routes of transmission is discussed. Copyright © 2018 Elsevier GmbH. All rights reserved.

  1. Efficient Generation and Selection of Combined Features for Improved Classification

    KAUST Repository

    Shono, Ahmad N.

    2014-05-01

    This study contributes a methodology and associated toolkit developed to allow users to experiment with the use of combined features in classification problems. Methods are provided for efficiently generating combined features from an original feature set, for efficiently selecting the most discriminating of these generated combined features, and for efficiently performing a preliminary comparison of the classification results when using the original features exclusively against the results when using the selected combined features. The potential benefit of considering combined features in classification problems is demonstrated by applying the developed methodology and toolkit to three sample data sets where the discovery of combined features containing new discriminating information led to improved classification results.

  2. Y-Chromosomal Diversity in Europe Is Clinal and Influenced Primarily by Geography, Rather than by Language

    Science.gov (United States)

    Rosser, Zoë H.; Zerjal, Tatiana; Hurles, Matthew E.; Adojaan, Maarja; Alavantic, Dragan; Amorim, António; Amos, William; Armenteros, Manuel; Arroyo, Eduardo; Barbujani, Guido; Beckman, Gunhild; Beckman, Lars; Bertranpetit, Jaume; Bosch, Elena; Bradley, Daniel G.; Brede, Gaute; Cooper, Gillian; Côrte-Real, Helena B. S. M.; de Knijff, Peter; Decorte, Ronny; Dubrova, Yuri E.; Evgrafov, Oleg; Gilissen, Anja; Glisic, Sanja; Gölge, Mukaddes; Hill, Emmeline W.; Jeziorowska, Anna; Kalaydjieva, Luba; Kayser, Manfred; Kivisild, Toomas; Kravchenko, Sergey A.; Krumina, Astrida; Kučinskas, Vaidutis; Lavinha, João; Livshits, Ludmila A.; Malaspina, Patrizia; Maria, Syrrou; McElreavey, Ken; Meitinger, Thomas A.; Mikelsaar, Aavo-Valdur; Mitchell, R. John; Nafa, Khedoudja; Nicholson, Jayne; Nørby, Søren; Pandya, Arpita; Parik, Jüri; Patsalis, Philippos C.; Pereira, Luísa; Peterlin, Borut; Pielberg, Gerli; Prata, Maria João; Previderé, Carlo; Roewer, Lutz; Rootsi, Siiri; Rubinsztein, D. C.; Saillard, Juliette; Santos, Fabrício R.; Stefanescu, Gheorghe; Sykes, Bryan C.; Tolun, Aslihan; Villems, Richard; Tyler-Smith, Chris; Jobling, Mark A.

    2000-01-01

    Clinal patterns of autosomal genetic diversity within Europe have been interpreted in previous studies in terms of a Neolithic demic diffusion model for the spread of agriculture; in contrast, studies using mtDNA have traced many founding lineages to the Paleolithic and have not shown strongly clinal variation. We have used 11 human Y-chromosomal biallelic polymorphisms, defining 10 haplogroups, to analyze a sample of 3,616 Y chromosomes belonging to 47 European and circum-European populations. Patterns of geographic differentiation are highly nonrandom, and, when they are assessed using spatial autocorrelation analysis, they show significant clines for five of six haplogroups analyzed. Clines for two haplogroups, representing 45% of the chromosomes, are continentwide and consistent with the demic diffusion hypothesis. Clines for three other haplogroups each have different foci and are more regionally restricted and are likely to reflect distinct population movements, including one from north of the Black Sea. Principal-components analysis suggests that populations are related primarily on the basis of geography, rather than on the basis of linguistic affinity. This is confirmed in Mantel tests, which show a strong and highly significant partial correlation between genetics and geography but a low, nonsignificant partial correlation between genetics and language. Genetic-barrier analysis also indicates the primacy of geography in the shaping of patterns of variation. These patterns retain a strong signal of expansion from the Near East but also suggest that the demographic history of Europe has been complex and influenced by other major population movements, as well as by linguistic and geographic heterogeneities and the effects of drift. PMID:11078479

  3. Cherubism: Clinicoradiographic Features and Treatment

    Directory of Open Access Journals (Sweden)

    Luiz Antonio Guimarães Cabral

    2010-04-01

    Full Text Available Objectives: Cherubism is a congenital childhood disease of autosomal dominant inheritance. This disease is characterized by painless bilateral enlargement of the jaws, in which bone is replaced with fibrous tissue. The condition has sui generis clinical, radiographic and histological features, of which the clinician should be aware for a better differential diagnosis in the presence of a fibro-osseous lesion affecting the bones of the maxillomandibular complex. The purpose of present paper was to review the literature and to report the most important aspects of cherubism in order to facilitate the study of this disease.Material and Methods: Literature was reviewed about cherubism, emphasizing the relevant clinicoradiographic features and treatment. Literature was selected through a search of PubMed and Scielo electronic databases. The keywords used for search were adolescent, cherubism, cherubism/physiopathology, cherubism/treatment, cherubism/radiography. A manual search of the reference lists of the identified articles and the authors’ article files and recent reviews was conducted to identify additional publications. Those studies that described new features about cherubism were included in this review.Results: In total 44 literature sources were obtained and reviewed. Studies that described new features about cherubism physiopathology, diagnostics and treatment were reviewed.Conclusions: Despite the exceptions, cherubism is a clinically well-characterized disease. In cases of a suspicion of cherubism, radiographic examination is essential since the clinical presentation, the location and distribution of the lesions may define the diagnosis. Histopathological examination is complementary. Nowadays, genetic tests should be used for final diagnosis of cherubism.

  4. Improving Music Genre Classification by Short-Time Feature Integration

    DEFF Research Database (Denmark)

    Meng, Anders; Ahrendt, Peter; Larsen, Jan

    2005-01-01

    Many different short-time features, using time windows in the size of 10-30 ms, have been proposed for music segmentation, retrieval and genre classification. However, often the available time frame of the music to make the actual decision or comparison (the decision time horizon) is in the range...... of seconds instead of milliseconds. The problem of making new features on the larger time scale from the short-time features (feature integration) has only received little attention. This paper investigates different methods for feature integration and late information fusion for music genre classification...

  5. Effects of Individual Differences and Situational Features on Age Differences in Mindless Reading.

    Science.gov (United States)

    Shake, Matthew C; Shulley, Leah J; Soto-Freita, Angelica M

    2016-09-01

    Mindless reading occurs when an individual shifts their attention away from the text and toward other off-task thoughts. This study examined whether previously reported age-related declines in mindless reading episodes are due primarily to (a) situational features related to the text itself (e.g., text genre or interest in the text) and/or (b) individual differences in cognitive ability. Participants read 2 texts written in different genres but about the same topic. During reading, they were randomly probed to indicate whether they were on-task or mind-wandering. They also indicated their perceptions regarding the interest and difficulty of the text, and completed a battery of cognitive ability measures. The results showed that (a) text genre may engender some age differences in mindless reading and (b) greater age and perceived interest in the text were each uniquely predictive of reduced mindless reading for both text genres. Individual differences in cognitive abilities (e.g., working memory, vocabulary) did not account for additional significant variance in mindless reading after interest and age were taken into account. Our findings are discussed in terms of implications for age differences in lapses of attention during reading and predictors of mind-wandering generally. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  6. Classification of Textures Using Filter Based Local Feature Extraction

    Directory of Open Access Journals (Sweden)

    Bocekci Veysel Gokhan

    2016-01-01

    Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

  7. Face recognition algorithm using extended vector quantization histogram features.

    Science.gov (United States)

    Yan, Yan; Lee, Feifei; Wu, Xueqian; Chen, Qiu

    2018-01-01

    In this paper, we propose a face recognition algorithm based on a combination of vector quantization (VQ) and Markov stationary features (MSF). The VQ algorithm has been shown to be an effective method for generating features; it extracts a codevector histogram as a facial feature representation for face recognition. Still, the VQ histogram features are unable to convey spatial structural information, which to some extent limits their usefulness in discrimination. To alleviate this limitation of VQ histograms, we utilize Markov stationary features (MSF) to extend the VQ histogram-based features so as to add spatial structural information. We demonstrate the effectiveness of our proposed algorithm by achieving recognition results superior to those of several state-of-the-art methods on publicly available face databases.

  8. Uniform competency-based local feature extraction for remote sensing images

    Science.gov (United States)

    Sedaghat, Amin; Mohammadi, Nazila

    2018-01-01

    Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.

  9. Prostate cancer multi-feature analysis using trans-rectal ultrasound images

    International Nuclear Information System (INIS)

    Mohamed, S S; Salama, M M A; Kamel, M; El-Saadany, E F; Rizkalla, K; Chin, J

    2005-01-01

    This note focuses on extracting and analysing prostate texture features from trans-rectal ultrasound (TRUS) images for tissue characterization. One of the principal contributions of this investigation is the use of the information of the images' frequency domain features and spatial domain features to attain a more accurate diagnosis. Each image is divided into regions of interest (ROIs) by the Gabor multi-resolution analysis, a crucial stage, in which segmentation is achieved according to the frequency response of the image pixels. The pixels with a similar response to the same filter are grouped to form one ROI. Next, from each ROI two different statistical feature sets are constructed; the first set includes four grey level dependence matrix (GLDM) features and the second set consists of five grey level difference vector (GLDV) features. These constructed feature sets are then ranked by the mutual information feature selection (MIFS) algorithm. Here, the features that provide the maximum mutual information of each feature and class (cancerous and non-cancerous) and the minimum mutual information of the selected features are chosen, yeilding a reduced feature subset. The two constructed feature sets, GLDM and GLDV, as well as the reduced feature subset, are examined in terms of three different classifiers: the condensed k-nearest neighbour (CNN), the decision tree (DT) and the support vector machine (SVM). The accuracy classification results range from 87.5% to 93.75%, where the performance of the SVM and that of the DT are significantly better than the performance of the CNN. (note)

  10. Including product features in process redesign

    DEFF Research Database (Denmark)

    Hvam, Lars; Hauksdóttir, Dagný; Mortensen, Niels Henrik

    2017-01-01

    do not take into account how the product features are applied throughout the process, which makes it difficult to obtain a comprehensive understanding of the activities in the processes and to generate significant improvements. The suggested approach models the product family using the so......This article suggests a visual modelling method for integrating models of product features with business process models for redesigning the business processes involving specifications of customer-tailored products and services. The current methods for redesigning these types of business processes......-called product variant master and the business process modelling notation for modelling the process flow. The product model is combined with the process map by identifying features used in each step of the process flow. Additionally, based on the information absorbed from the integrated model, the value stream...

  11. Detection of fraudulent emails by employing advanced feature abundance

    Directory of Open Access Journals (Sweden)

    Sarwat Nizamani

    2014-11-01

    Full Text Available In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features are incorporated step by step. The detection of fraudulent email has been considered as a classification problem and it is evaluated using various state-of-the art algorithms and on CCM (Nizamani et al., 2011 [1] which is authors’ previous cluster based classification model. The experiments have been performed on diverse feature sets and the different classification methods. The comparison of the results is also presented and the evaluation show that for the fraudulent email detection tasks, the feature set is more important regardless of classification method. The results of the study suggest that the task of fraudulent emails detection requires the better choice of feature set; while the choice of classification method is of less importance.

  12. Salient Region Detection via Feature Combination and Discriminative Classifier

    Directory of Open Access Journals (Sweden)

    Deming Kong

    2015-01-01

    Full Text Available We introduce a novel approach to detect salient regions of an image via feature combination and discriminative classifier. Our method, which is based on hierarchical image abstraction, uses the logistic regression approach to map the regional feature vector to a saliency score. Four saliency cues are used in our approach, including color contrast in a global context, center-boundary priors, spatially compact color distribution, and objectness, which is as an atomic feature of segmented region in the image. By mapping a four-dimensional regional feature to fifteen-dimensional feature vector, we can linearly separate the salient regions from the clustered background by finding an optimal linear combination of feature coefficients in the fifteen-dimensional feature space and finally fuse the saliency maps across multiple levels. Furthermore, we introduce the weighted salient image center into our saliency analysis task. Extensive experiments on two large benchmark datasets show that the proposed approach achieves the best performance over several state-of-the-art approaches.

  13. Influence of Familiar Features on Diagnosis: Instantiated Features in an Applied Setting

    Science.gov (United States)

    Dore, Kelly L.; Brooks, Lee R.; Weaver, Bruce; Norman, Geoffrey R.

    2012-01-01

    Medical diagnosis can be viewed as a categorization task. There are two mechanisms whereby humans make categorical judgments: "analytical reasoning," based on explicit consideration of features and "nonanalytical reasoning," an unconscious holistic process of matching against prior exemplars. However, there is evidence that prior experience can…

  14. Mesoblastic nephroma: Pathological features

    African Journals Online (AJOL)

    N.M. El-Badawy

    determined mainly by its histologic type, we found it worthwhile to elaborate more on the gross and microscopic features of ... behavior of mesoblastic nephroma is determined mainly by its his- .... However, it exhibits a nodular growth pattern at.

  15. Genome-wide analyses of borderline personality features

    NARCIS (Netherlands)

    Lubke, G.H.; Laurin, C.; Amin, N.; Hottenga, J.J.; Willemsen, G.; Grootheest, G.; Abdellaoui, A.; Karssen, L.C.; Oostra, B.A.; van Duijn, C.M.; Penninx, B.W.J.H.; Boomsma, D.I.

    2014-01-01

    The heritability of borderline personality (BP) features has been established in multiple twin and family studies. Using data from the borderline subscale of the Personality Assessment Inventory Borderline Features Scale (PAI-BOR) collected in two Dutch cohorts (N=7125), the Netherlands Twin

  16. Shapes and features of the primordial bispectrum

    Energy Technology Data Exchange (ETDEWEB)

    Gong, Jinn-Ouk [Asia Pacific Center for Theoretical Physics, Cheongam-ro 67, Pohang, 37673 (Korea, Republic of); Palma, Gonzalo A.; Sypsas, Spyros, E-mail: jinn-ouk.gong@apctp.org, E-mail: gpalmaquilod@ing.uchile.cl, E-mail: s.sypsas@gmail.com [Departamento de Física, FCFM, Universidad de Chile, Blanco Encalada 2008, Santiago, 837.0415 Chile (Chile)

    2017-05-01

    If time-dependent disruptions from slow-roll occur during inflation, the correlation functions of the primordial curvature perturbation should have scale-dependent features, a case which is marginally supported from the cosmic microwave background (CMB) data. We offer a new approach to analyze the appearance of such features in the primordial bispectrum that yields new consistency relations and justifies the search of oscillating patterns modulated by orthogonal and local templates. Under the assumption of sharp features, we find that the cubic couplings of the curvature perturbation can be expressed in terms of the bispectrum in two specific momentum configurations, for example local and equilateral. This allows us to derive consistency relations among different bispectrum shapes, which in principle could be tested in future CMB surveys. Furthermore, based on the form of the consistency relations, we construct new two-parameter templates for features that include all the known shapes.

  17. An Effective Combined Feature For Web Based Image Retrieval

    Directory of Open Access Journals (Sweden)

    H.M.R.B Herath

    2015-08-01

    Full Text Available Abstract Technology advances as well as the emergence of large scale multimedia applications and the revolution of the World Wide Web has changed the world into a digital age. Anybody can use their mobile phone to take a photo at any time anywhere and upload that image to ever growing image databases. Development of effective techniques for visual and multimedia retrieval systems is one of the most challenging and important directions of the future research. This paper proposes an effective combined feature for web based image retrieval. Frequently used colour and texture features are explored in order to develop a combined feature for this purpose. Widely used three colour features Colour moments Colour coherence vector and Colour Correlogram and three texture features Grey Level Co-occurrence matrix Tamura features and Gabor filter were analyzed for their performance. Precision and Recall were used to evaluate the performance of each of these techniques. By comparing precision and recall values the methods that performed best were taken and combined to form a hybrid feature. The developed combined feature was evaluated by developing a web based CBIR system. A web crawler was used to first crawl through Web sites and images found in those sites are downloaded and the combined feature representation technique was used to extract image features. The test results indicated that this web system can be used to index web images with the combined feature representation schema and to find similar images. Random image retrievals using the web system shows that the combined feature can be used to retrieve images belonging to the general image domain. Accuracy of the retrieval can be noted high for natural images like outdoor scenes images of flowers etc. Also images which have a similar colour and texture distribution were retrieved as similar even though the images were belonging to deferent semantic categories. This can be ideal for an artist who wants

  18. Adaptive feature selection using v-shaped binary particle swarm optimization.

    Science.gov (United States)

    Teng, Xuyang; Dong, Hongbin; Zhou, Xiurong

    2017-01-01

    Feature selection is an important preprocessing method in machine learning and data mining. This process can be used not only to reduce the amount of data to be analyzed but also to build models with stronger interpretability based on fewer features. Traditional feature selection methods evaluate the dependency and redundancy of features separately, which leads to a lack of measurement of their combined effect. Moreover, a greedy search considers only the optimization of the current round and thus cannot be a global search. To evaluate the combined effect of different subsets in the entire feature space, an adaptive feature selection method based on V-shaped binary particle swarm optimization is proposed. In this method, the fitness function is constructed using the correlation information entropy. Feature subsets are regarded as individuals in a population, and the feature space is searched using V-shaped binary particle swarm optimization. The above procedure overcomes the hard constraint on the number of features, enables the combined evaluation of each subset as a whole, and improves the search ability of conventional binary particle swarm optimization. The proposed algorithm is an adaptive method with respect to the number of feature subsets. The experimental results show the advantages of optimizing the feature subsets using the V-shaped transfer function and confirm the effectiveness and efficiency of the feature subsets obtained under different classifiers.

  19. Feature-based morphometry: discovering group-related anatomical patterns.

    Science.gov (United States)

    Toews, Matthew; Wells, William; Collins, D Louis; Arbel, Tal

    2010-02-01

    This paper presents feature-based morphometry (FBM), a new fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1). Copyright (c) 2009 Elsevier Inc. All rights reserved.

  20. Physical model for the 2175 A interstellar extinction feature

    International Nuclear Information System (INIS)

    Hecht, J.H.

    1986-01-01

    Recent IUE observations have shown that the 2175 A interstellar extinction feature is constant in wavelength but varies in width. A model has been constructed to explain these results. It is proposed that the 2175 A feature will only be seen when there is extinction due to carbon grains which have lost their hydrogen. In particular, the feature is caused by a separate population of small (less than 50 A radius), hydrogen-free carbon grains. The variations in width would be due to differences in either their temperature, size distribution, or impurity content. All other carbon grains retain hydrogen, which causes the feature to be suppressed. If this model is correct, then it implies that the grains responsible for the unidentified IR emission features would not generally cause the 2175 A feature. 53 references

  1. Consistency relations for sharp inflationary non-Gaussian features

    Energy Technology Data Exchange (ETDEWEB)

    Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris [Departamento de Física, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile, Blanco Encalada 2008, Santiago (Chile); Soto, Alex, E-mail: sander.mooij@ing.uchile.cl, E-mail: gpalmaquilod@ing.uchile.cl, E-mail: gpanotop@ing.uchile.cl, E-mail: gatogeno@gmail.com [Departamento de Física, Facultad de Ciencias, Universidad de Chile, Las Palmeras 3425, Ñuñoa, Santiago (Chile)

    2016-09-01

    If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.

  2. Consistency relations for sharp inflationary non-Gaussian features

    International Nuclear Information System (INIS)

    Mooij, Sander; Palma, Gonzalo A.; Panotopoulos, Grigoris; Soto, Alex

    2016-01-01

    If cosmic inflation suffered tiny time-dependent deviations from the slow-roll regime, these would induce the existence of small scale-dependent features imprinted in the primordial spectra, with their shapes and sizes revealing information about the physics that produced them. Small sharp features could be suppressed at the level of the two-point correlation function, making them undetectable in the power spectrum, but could be amplified at the level of the three-point correlation function, offering us a window of opportunity to uncover them in the non-Gaussian bispectrum. In this article, we show that sharp features may be analyzed using only data coming from the three point correlation function parametrizing primordial non-Gaussianity. More precisely, we show that if features appear in a particular non-Gaussian triangle configuration (e.g. equilateral, folded, squeezed), these must reappear in every other configuration according to a specific relation allowing us to correlate features across the non-Gaussian bispectrum. As a result, we offer a method to study scale-dependent features generated during inflation that depends only on data coming from measurements of non-Gaussianity, allowing us to omit data from the power spectrum.

  3. Character feature integration of Chinese calligraphy and font

    Science.gov (United States)

    Shi, Cao; Xiao, Jianguo; Jia, Wenhua; Xu, Canhui

    2013-01-01

    A framework is proposed in this paper to effectively generate a new hybrid character type by means of integrating local contour feature of Chinese calligraphy with structural feature of font in computer system. To explore traditional art manifestation of calligraphy, multi-directional spatial filter is applied for local contour feature extraction. Then the contour of character image is divided into sub-images. The sub-images in the identical position from various characters are estimated by Gaussian distribution. According to its probability distribution, the dilation operator and erosion operator are designed to adjust the boundary of font image. And then new Chinese character images are generated which possess both contour feature of artistical calligraphy and elaborate structural feature of font. Experimental results demonstrate the new characters are visually acceptable, and the proposed framework is an effective and efficient strategy to automatically generate the new hybrid character of calligraphy and font.

  4. Multistage feature extraction for accurate face alignment

    NARCIS (Netherlands)

    Zuo, F.; With, de P.H.N.

    2004-01-01

    We propose a novel multistage facial feature extraction approach using a combination of 'global' and 'local' techniques. At the first stage, we use template matching, based on an Edge-Orientation-Map for fast feature position estimation. Using this result, a statistical framework applying the Active

  5. Second feature of the matter two-point function

    Science.gov (United States)

    Tansella, Vittorio

    2018-05-01

    We point out the existence of a second feature in the matter two-point function, besides the acoustic peak, due to the baryon-baryon correlation in the early Universe and positioned at twice the distance of the peak. We discuss how the existence of this feature is implied by the well-known heuristic argument that explains the baryon bump in the correlation function. A standard χ2 analysis to estimate the detection significance of the second feature is mimicked. We conclude that, for realistic values of the baryon density, a SKA-like galaxy survey will not be able to detect this feature with standard correlation function analysis.

  6. Image fusion using sparse overcomplete feature dictionaries

    Science.gov (United States)

    Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

    2015-10-06

    Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

  7. Feature Importance for Human Epithelial (HEp-2 Cell Image Classification

    Directory of Open Access Journals (Sweden)

    Vibha Gupta

    2018-02-01

    Full Text Available Indirect Immuno-Fluorescence (IIF microscopy imaging of human epithelial (HEp-2 cells is a popular method for diagnosing autoimmune diseases. Considering large data volumes, computer-aided diagnosis (CAD systems, based on image-based classification, can help in terms of time, effort, and reliability of diagnosis. Such approaches are based on extracting some representative features from the images. This work explores the selection of the most distinctive features for HEp-2 cell images using various feature selection (FS methods. Considering that there is no single universally optimal feature selection technique, we also propose hybridization of one class of FS methods (filter methods. Furthermore, the notion of variable importance for ranking features, provided by another type of approaches (embedded methods such as Random forest, Random uniform forest is exploited to select a good subset of features from a large set, such that addition of new features does not increase classification accuracy. In this work, we have also, with great consideration, designed class-specific features to capture morphological visual traits of the cell patterns. We perform various experiments and discussions to demonstrate the effectiveness of FS methods along with proposed and a standard feature set. We achieve state-of-the-art performance even with small number of features, obtained after the feature selection.

  8. Slow feature analysis: unsupervised learning of invariances.

    Science.gov (United States)

    Wiskott, Laurenz; Sejnowski, Terrence J

    2002-04-01

    Invariant features of temporally varying signals are useful for analysis and classification. Slow feature analysis (SFA) is a new method for learning invariant or slowly varying features from a vectorial input signal. It is based on a nonlinear expansion of the input signal and application of principal component analysis to this expanded signal and its time derivative. It is guaranteed to find the optimal solution within a family of functions directly and can learn to extract a large number of decorrelated features, which are ordered by their degree of invariance. SFA can be applied hierarchically to process high-dimensional input signals and extract complex features. SFA is applied first to complex cell tuning properties based on simple cell output, including disparity and motion. Then more complicated input-output functions are learned by repeated application of SFA. Finally, a hierarchical network of SFA modules is presented as a simple model of the visual system. The same unstructured network can learn translation, size, rotation, contrast, or, to a lesser degree, illumination invariance for one-dimensional objects, depending on only the training stimulus. Surprisingly, only a few training objects suffice to achieve good generalization to new objects. The generated representation is suitable for object recognition. Performance degrades if the network is trained to learn multiple invariances simultaneously.

  9. Rotation invariant fast features for large-scale recognition

    Science.gov (United States)

    Takacs, Gabriel; Chandrasekhar, Vijay; Tsai, Sam; Chen, David; Grzeszczuk, Radek; Girod, Bernd

    2012-10-01

    We present an end-to-end feature description pipeline which uses a novel interest point detector and Rotation- Invariant Fast Feature (RIFF) descriptors. The proposed RIFF algorithm is 15× faster than SURF1 while producing large-scale retrieval results that are comparable to SIFT.2 Such high-speed features benefit a range of applications from Mobile Augmented Reality (MAR) to web-scale image retrieval and analysis.

  10. Features of MCNP6

    International Nuclear Information System (INIS)

    Goorley, T.; James, M.; Booth, T.; Brown, F.; Bull, J.; Cox, L.J.; Durkee, J.; Elson, J.; Fensin, M.; Forster, R.A.; Hendricks, J.; Hughes, H.G.; Johns, R.; Kiedrowski, B.; Martz, R.; Mashnik, S.; McKinney, G.; Pelowitz, D.; Prael, R.; Sweezy, J.

    2016-01-01

    Highlights: • MCNP6 is simply and accurately described as the merger of MCNP5 and MCNPX capabilities, but it is much more than the sum of these two computer codes. • MCNP6 is the result of six years of effort by the MCNP5 and MCNPX code development teams. • These groups of people, residing in Los Alamos National Laboratory’s X Computational Physics Division, Monte Carlo Codes Group (XCP-3) and Nuclear Engineering and Nonproliferation Division, Radiation Transport Modeling Team (NEN-5) respectively, have combined their code development efforts to produce the next evolution of MCNP. • While maintenance and major bug fixes will continue for MCNP5 1.60 and MCNPX 2.7.0 for upcoming years, new code development capabilities only will be developed and released in MCNP6. • In fact, the initial release of MCNP6 contains numerous new features not previously found in either code. • These new features are summarized in this document. • Packaged with MCNP6 is also the new production release of the ENDF/B-VII.1 nuclear data files usable by MCNP. • The high quality of the overall merged code, usefulness of these new features, along with the desire in the user community to start using the merged code, have led us to make the first MCNP6 production release: MCNP6 version 1. • High confidence in the MCNP6 code is based on its performance with the verification and validation test suites, comparisons to its predecessor codes, our automated nightly software debugger tests, the underlying high quality nuclear and atomic databases, and significant testing by many beta testers. - Abstract: MCNP6 can be described as the merger of MCNP5 and MCNPX capabilities, but it is much more than the sum of these two computer codes. MCNP6 is the result of six years of effort by the MCNP5 and MCNPX code development teams. These groups of people, residing in Los Alamos National Laboratory’s X Computational Physics Division, Monte Carlo Codes Group (XCP-3) and Nuclear Engineering and

  11. A performance evaluation of point pair features

    DEFF Research Database (Denmark)

    Kiforenko, Lilita; Drost, Bertram; Tombari, Federico

    2018-01-01

    have low resolution data, where local histogram features show a higher performance than PPFs. We also found that PPFs compared to most local histogram features degrade faster under disturbances such as occlusion and clutter, however, PPFs still remain more descriptive on an absolute scale. The main...

  12. Feature Selection with the Boruta Package

    OpenAIRE

    Kursa, Miron B.; Rudnicki, Witold R.

    2010-01-01

    This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm. It iteratively removes the features which are proved by a statistical test to be less relevant than random probes. The Boruta package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.

  13. Turkish Music Genre Classification using Audio and Lyrics Features

    Directory of Open Access Journals (Sweden)

    Önder ÇOBAN

    2017-05-01

    Full Text Available Music Information Retrieval (MIR has become a popular research area in recent years. In this context, researchers have developed music information systems to find solutions for such major problems as automatic playlist creation, hit song detection, and music genre or mood classification. Meta-data information, lyrics, or melodic content of music are used as feature resource in previous works. However, lyrics do not often used in MIR systems and the number of works in this field is not enough especially for Turkish. In this paper, firstly, we have extended our previously created Turkish MIR (TMIR dataset, which comprises of Turkish lyrics, by including the audio file of each song. Secondly, we have investigated the effect of using audio and textual features together or separately on automatic Music Genre Classification (MGC. We have extracted textual features from lyrics using different feature extraction models such as word2vec and traditional Bag of Words. We have conducted our experiments on Support Vector Machine (SVM algorithm and analysed the impact of feature selection and different feature groups on MGC. We have considered lyrics based MGC as a text classification task and also investigated the effect of term weighting method. Experimental results show that textual features can also be effective as well as audio features for Turkish MGC, especially when a supervised term weighting method is employed. We have achieved the highest success rate as 99,12\\% by using both audio and textual features together.

  14. Feature selection gait-based gender classification under different circumstances

    Science.gov (United States)

    Sabir, Azhin; Al-Jawad, Naseer; Jassim, Sabah

    2014-05-01

    This paper proposes a gender classification based on human gait features and investigates the problem of two variations: clothing (wearing coats) and carrying bag condition as addition to the normal gait sequence. The feature vectors in the proposed system are constructed after applying wavelet transform. Three different sets of feature are proposed in this method. First, Spatio-temporal distance that is dealing with the distance of different parts of the human body (like feet, knees, hand, Human Height and shoulder) during one gait cycle. The second and third feature sets are constructed from approximation and non-approximation coefficient of human body respectively. To extract these two sets of feature we divided the human body into two parts, upper and lower body part, based on the golden ratio proportion. In this paper, we have adopted a statistical method for constructing the feature vector from the above sets. The dimension of the constructed feature vector is reduced based on the Fisher score as a feature selection method to optimize their discriminating significance. Finally k-Nearest Neighbor is applied as a classification method. Experimental results demonstrate that our approach is providing more realistic scenario and relatively better performance compared with the existing approaches.

  15. Online Feature Transformation Learning for Cross-Domain Object Category Recognition.

    Science.gov (United States)

    Zhang, Xuesong; Zhuang, Yan; Wang, Wei; Pedrycz, Witold

    2017-06-09

    In this paper, we introduce a new research problem termed online feature transformation learning in the context of multiclass object category recognition. The learning of a feature transformation is viewed as learning a global similarity metric function in an online manner. We first consider the problem of online learning a feature transformation matrix expressed in the original feature space and propose an online passive aggressive feature transformation algorithm. Then these original features are mapped to kernel space and an online single kernel feature transformation (OSKFT) algorithm is developed to learn a nonlinear feature transformation. Based on the OSKFT and the existing Hedge algorithm, a novel online multiple kernel feature transformation algorithm is also proposed, which can further improve the performance of online feature transformation learning in large-scale application. The classifier is trained with k nearest neighbor algorithm together with the learned similarity metric function. Finally, we experimentally examined the effect of setting different parameter values in the proposed algorithms and evaluate the model performance on several multiclass object recognition data sets. The experimental results demonstrate the validity and good performance of our methods on cross-domain and multiclass object recognition application.

  16. Classification of radiolarian images with hand-crafted and deep features

    Science.gov (United States)

    Keçeli, Ali Seydi; Kaya, Aydın; Keçeli, Seda Uzunçimen

    2017-12-01

    Radiolarians are planktonic protozoa and are important biostratigraphic and paleoenvironmental indicators for paleogeographic reconstructions. Radiolarian paleontology still remains as a low cost and the one of the most convenient way to obtain dating of deep ocean sediments. Traditional methods for identifying radiolarians are time-consuming and cannot scale to the granularity or scope necessary for large-scale studies. Automated image classification will allow making these analyses promptly. In this study, a method for automatic radiolarian image classification is proposed on Scanning Electron Microscope (SEM) images of radiolarians to ease species identification of fossilized radiolarians. The proposed method uses both hand-crafted features like invariant moments, wavelet moments, Gabor features, basic morphological features and deep features obtained from a pre-trained Convolutional Neural Network (CNN). Feature selection is applied over deep features to reduce high dimensionality. Classification outcomes are analyzed to compare hand-crafted features, deep features, and their combinations. Results show that the deep features obtained from a pre-trained CNN are more discriminative comparing to hand-crafted ones. Additionally, feature selection utilizes to the computational cost of classification algorithms and have no negative effect on classification accuracy.

  17. Hybrid feature selection for supporting lightweight intrusion detection systems

    Science.gov (United States)

    Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

    2017-08-01

    Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

  18. FEATURE EXTRACTION FOR EMG BASED PROSTHESES CONTROL

    Directory of Open Access Journals (Sweden)

    R. Aishwarya

    2013-01-01

    Full Text Available The control of prosthetic limb would be more effective if it is based on Surface Electromyogram (SEMG signals from remnant muscles. The analysis of SEMG signals depend on a number of factors, such as amplitude as well as time- and frequency-domain properties. Time series analysis using Auto Regressive (AR model and Mean frequency which is tolerant to white Gaussian noise are used as feature extraction techniques. EMG Histogram is used as another feature vector that was seen to give more distinct classification. The work was done with SEMG dataset obtained from the NINAPRO DATABASE, a resource for bio robotics community. Eight classes of hand movements hand open, hand close, Wrist extension, Wrist flexion, Pointing index, Ulnar deviation, Thumbs up, Thumb opposite to little finger are taken into consideration and feature vectors are extracted. The feature vectors can be given to an artificial neural network for further classification in controlling the prosthetic arm which is not dealt in this paper.

  19. Reductio ad discrimen: Where features come from

    Directory of Open Access Journals (Sweden)

    Elizabeth Cowper

    2015-04-01

    Full Text Available This paper addresses two fundamental questions about the nature of formal features in phonology and morphosyntax: what is their expressive power, and where do they come from? To answer these questions, we begin with the most restrictive possible hypothesis (all features are privative, and are wholly dictated by Universal Grammar, with no room for cross-linguistic variation, and examine the extent to which empirical evidence from a variety of languages compels a retreat from this position. We argue that there is little to be gained by positing a universal set of specific features, and propose instead that the crucial contribution of UG is the language learner's ability to construct features by identifying correlations between contrasts at different levels of linguistic structure. This view resonates with current research on how the interaction between UG and external 'third factors' shapes the structure of language, while at the same time harking back to the Saussurean notion that contrast is the central function of linguistic representations.

  20. Individual discriminative face recognition models based on subsets of features

    DEFF Research Database (Denmark)

    Clemmensen, Line Katrine Harder; Gomez, David Delgado; Ersbøll, Bjarne Kjær

    2007-01-01

    The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection is used to identify meaningful and important features in face recognition. Modelling the characteristics which distinguish one...... person from another using only subsets of features will both decrease the computational cost and increase the generalization capacity of the face recognition algorithm. Moreover, identifying which are the features that better discriminate between persons will also provide a deeper understanding...... of the face recognition problem. The elastic net model is able to select a subset of features with low computational effort compared to other state-of-the-art feature selection methods. Furthermore, the fact that the number of features usually is larger than the number of images in the data base makes feature...

  1. Saliency image of feature building for image quality assessment

    Science.gov (United States)

    Ju, Xinuo; Sun, Jiyin; Wang, Peng

    2011-11-01

    The purpose and method of image quality assessment are quite different for automatic target recognition (ATR) and traditional application. Local invariant feature detectors, mainly including corner detectors, blob detectors and region detectors etc., are widely applied for ATR. A saliency model of feature was proposed to evaluate feasibility of ATR in this paper. The first step consisted of computing the first-order derivatives on horizontal orientation and vertical orientation, and computing DoG maps in different scales respectively. Next, saliency images of feature were built based auto-correlation matrix in different scale. Then, saliency images of feature of different scales amalgamated. Experiment were performed on a large test set, including infrared images and optical images, and the result showed that the salient regions computed by this model were consistent with real feature regions computed by mostly local invariant feature extraction algorithms.

  2. Boosting Discriminant Learners for Gait Recognition Using MPCA Features

    Directory of Open Access Journals (Sweden)

    Haiping Lu

    2009-01-01

    Full Text Available This paper proposes a boosted linear discriminant analysis (LDA solution on features extracted by the multilinear principal component analysis (MPCA to enhance gait recognition performance. Three-dimensional gait objects are projected in the MPCA space first to obtain low-dimensional tensorial features. Then, lower-dimensional vectorial features are obtained through discriminative feature selection. These feature vectors are then fed into an LDA-style booster, where several regularized and weakened LDA learners work together to produce a strong learner through a novel feature weighting and sampling process. The LDA learner employs a simple nearest-neighbor classifier with a weighted angle distance measure for classification. The experimental results on the NIST/USF “Gait Challenge” data-sets show that the proposed solution has successfully improved the gait recognition performance and outperformed several state-of-the-art gait recognition algorithms.

  3. Detection of Fraudulent Emails by Employing Advanced Feature Abundance

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Glasdam, Mathies

    2014-01-01

    In this paper, we present a fraudulent email detection model using advanced feature choice. We extracted various kinds of features and compared the performance of each category of features with the others in terms of the fraudulent email detection rate. The different types of features...... are incorporated step by step. The detection of fraudulent email has been considered as a classification problem and it is evaluated using various state-of-the art algorithms and on CCM [1] which is authors' previous cluster based classification model. The experiments have been performed on diverse feature sets...... and the different classification methods. The comparison of the results is also presented and the evaluations shows that for the fraudulent email detection tasks, the feature set is more important regardless of classification method. The results of the study suggest that the task of fraudulent emails detection...

  4. Cloud field classification based on textural features

    Science.gov (United States)

    Sengupta, Sailes Kumar

    1989-01-01

    An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes

  5. A TALE OF THREE MYSTERIOUS SPECTRAL FEATURES IN CARBON-RICH EVOLVED STARS: THE 21 μm, 30 μm, AND “UNIDENTIFIED INFRARED” EMISSION FEATURES

    Energy Technology Data Exchange (ETDEWEB)

    Mishra, Ajay; Li, Aigen [Department of Physics and Astronomy, University of Missouri, Columbia, MO 65211 (United States); Jiang, B. W., E-mail: amishra@mail.missouri.edu, E-mail: lia@missouri.edu, E-mail: bjiang@bnu.edu.cn [Department of Astronomy, Beijing Normal University, Beijing 100875 (China)

    2015-03-20

    The mysterious “21 μm” emission feature seen almost exclusively in the short-lived protoplanetary nebula (PPN) phase of stellar evolution remains unidentified since its discovery two decades ago. This feature is always accompanied by the equally mysterious, unidentified “30 μm” feature and the so-called “unidentified infrared” (UIR) features at 3.3, 6.2, 7.7, 8.6, and 11.3 μm which are generally attributed to polycyclic aromatic hydrocarbon (PAH) molecules. The 30 μm feature is commonly observed in all stages of stellar evolution from the asymptotic giant branch through PPN to the planetary nebula phase. We explore the interrelations among the mysterious 21, 30 μm, and UIR features of the 21 μm sources. We derive the fluxes emitted in the observed UIR, 21, and 30 μm features from published Infrared Space Observatory or Spitzer/IRS spectra. We find that none of these spectral features correlate with each other. This argues against a common carrier (e.g., thiourea) for both the 21 μm feature and the 30 μm feature. This also does not support large PAH clusters as a possible carrier for the 21 μm feature.

  6. Multithreaded hybrid feature tracking for markerless augmented reality.

    Science.gov (United States)

    Lee, Taehee; Höllerer, Tobias

    2009-01-01

    We describe a novel markerless camera tracking approach and user interaction methodology for augmented reality (AR) on unprepared tabletop environments. We propose a real-time system architecture that combines two types of feature tracking. Distinctive image features of the scene are detected and tracked frame-to-frame by computing optical flow. In order to achieve real-time performance, multiple operations are processed in a synchronized multi-threaded manner: capturing a video frame, tracking features using optical flow, detecting distinctive invariant features, and rendering an output frame. We also introduce user interaction methodology for establishing a global coordinate system and for placing virtual objects in the AR environment by tracking a user's outstretched hand and estimating a camera pose relative to it. We evaluate the speed and accuracy of our hybrid feature tracking approach, and demonstrate a proof-of-concept application for enabling AR in unprepared tabletop environments, using bare hands for interaction.

  7. Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

    Science.gov (United States)

    Kim, Deok-Hwan

    As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

  8. Infants' Developing Sensitivity to Object Function: Attention to Features and Feature Correlations

    Science.gov (United States)

    Baumgartner, Heidi A.; Oakes, Lisa M.

    2011-01-01

    When learning object function, infants must detect relations among features--for example, that squeezing is associated with squeaking or that objects with wheels roll. Previously, Perone and Oakes (2006) found 10-month-old infants were sensitive to relations between object appearances and actions, but not to relations between appearances and…

  9. A Study of Feature Extraction Using Divergence Analysis of Texture Features

    Science.gov (United States)

    Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

    1982-01-01

    An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

  10. Dependence of oil and gas formation on lithogenesis features in the Pacific Ocean tectonic zone

    Energy Technology Data Exchange (ETDEWEB)

    Burlin, Y K

    1981-01-01

    The clearly pronounced climate and tectonic factors have a primary influence on lithogenesis in the Pacific Ocean zone. At the same time, both the eastern and western parts of the zone have their own specific features, primarily in a tectonic respect. This leaves its imprint on the nature of the lithogenesis processes. The main condi- tions are analyzed for sediment genesis in both halves of the zone. The conducted analysis demonstrates that the processes of oil and gas formation are linked to the change in the geosyncline development and nature of sediment genesis and subsequent lithogenesis. It is expedient to make a prediction of oil and gas content with regard for the fact of the stage of development at which a certain sedimentary basin is. The formation composition of deposits of a certain group of basins makes it possible to predict which kind of hydrocarbons will dominate in them and in which section, since each formation is unique in relation to the generation of hydrocarbons and time of development. Both the stage of development and the formation complexes must be con- sidered in classifying and predicting the sedimentary basins. Development and refine- mend of the oil and gas-genetic criteria of different types of masses is a task of the new trend, formational naphthidogeny.

  11. Creating fair lineups for suspects with distinctive features

    OpenAIRE

    Zarkadi, Theodora; Wade, Kimberley A.; Stewart, Neil

    2009-01-01

    In their descriptions, eyewitnesses often refer to a culprit's distinctive facial features. However, in a police lineup, selecting the only member with the described distinctive feature is unfair to the suspect and provides the police with little further information. For fair and informative lineups, the distinctive feature should be either replicated across foils or concealed on the target. In the present experiments, replication produced more correct identifications in target-present lineup...

  12. Bread crumb classification using fractal and multifractal features

    OpenAIRE

    Baravalle, Rodrigo Guillermo; Delrieux, Claudio Augusto; Gómez, Juan Carlos

    2017-01-01

    Adequate image descriptors are fundamental in image classification and object recognition. Main requirements for image features are robustness and low dimensionality which would lead to low classification errors in a variety of situations and with a reasonable computational cost. In this context, the identification of materials poses a significant challenge, since typical (geometric and/or differential) feature extraction methods are not robust enough. Texture features based on Fourier or wav...

  13. Sequence-based classification using discriminatory motif feature selection.

    Directory of Open Access Journals (Sweden)

    Hao Xiong

    Full Text Available Most existing methods for sequence-based classification use exhaustive feature generation, employing, for example, all k-mer patterns. The motivation behind such (enumerative approaches is to minimize the potential for overlooking important features. However, there are shortcomings to this strategy. First, practical constraints limit the scope of exhaustive feature generation to patterns of length ≤ k, such that potentially important, longer (> k predictors are not considered. Second, features so generated exhibit strong dependencies, which can complicate understanding of derived classification rules. Third, and most importantly, numerous irrelevant features are created. These concerns can compromise prediction and interpretation. While remedies have been proposed, they tend to be problem-specific and not broadly applicable. Here, we develop a generally applicable methodology, and an attendant software pipeline, that is predicated on discriminatory motif finding. In addition to the traditional training and validation partitions, our framework entails a third level of data partitioning, a discovery partition. A discriminatory motif finder is used on sequences and associated class labels in the discovery partition to yield a (small set of features. These features are then used as inputs to a classifier in the training partition. Finally, performance assessment occurs on the validation partition. Important attributes of our approach are its modularity (any discriminatory motif finder and any classifier can be deployed and its universality (all data, including sequences that are unaligned and/or of unequal length, can be accommodated. We illustrate our approach on two nucleosome occupancy datasets and a protein solubility dataset, previously analyzed using enumerative feature generation. Our method achieves excellent performance results, with and without optimization of classifier tuning parameters. A Python pipeline implementing the approach is

  14. Feature-Based Statistical Analysis of Combustion Simulation Data

    Energy Technology Data Exchange (ETDEWEB)

    Bennett, J; Krishnamoorthy, V; Liu, S; Grout, R; Hawkes, E; Chen, J; Pascucci, V; Bremer, P T

    2011-11-18

    We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion

  15. Discrete-Feature Model Implementation of SDM-Site Forsmark

    Energy Technology Data Exchange (ETDEWEB)

    Geier, Joel (Clearwater Hardrock Consulting, Corvallis, OR (United States))

    2010-03-15

    A discrete-feature model (DFM) was implemented for the Forsmark repository site based on the final site descriptive model from surface based investigations. The discrete-feature conceptual model represents deformation zones, individual fractures, and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which, in the present study, is treated as impermeable. This approximation is reasonable for sites in crystalline rock which has very low permeability, apart from that which results from macroscopic fracturing. Models are constructed based on the geological and hydrogeological description of the sites and engineering designs. Hydraulic heads and flows through the network of water-conducting features are calculated by the finite-element method, and are used in turn to simulate migration of non-reacting solute by a particle-tracking method, in order to estimate the properties of pathways by which radionuclides could be released to the biosphere. Stochastic simulation is used to evaluate portions of the model that can only be characterized in statistical terms, since many water-conducting features within the model volume cannot be characterized deterministically. Chapter 2 describes the methodology by which discrete features are derived to represent water-conducting features around the hypothetical repository at Forsmark (including both natural features and features that result from the disturbance of excavation), and then assembled to produce a discrete-feature network model for numerical simulation of flow and transport. Chapter 3 describes how site-specific data and repository design are adapted to produce the discrete-feature model. Chapter 4 presents results of the calculations. These include utilization factors for deposition tunnels based on the emplacement criteria that have been set forth by the implementers, flow distributions to the deposition holes, and calculated properties of discharge paths as well as

  16. Discrete-Feature Model Implementation of SDM-Site Forsmark

    International Nuclear Information System (INIS)

    Geier, Joel

    2010-03-01

    A discrete-feature model (DFM) was implemented for the Forsmark repository site based on the final site descriptive model from surface based investigations. The discrete-feature conceptual model represents deformation zones, individual fractures, and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which, in the present study, is treated as impermeable. This approximation is reasonable for sites in crystalline rock which has very low permeability, apart from that which results from macroscopic fracturing. Models are constructed based on the geological and hydrogeological description of the sites and engineering designs. Hydraulic heads and flows through the network of water-conducting features are calculated by the finite-element method, and are used in turn to simulate migration of non-reacting solute by a particle-tracking method, in order to estimate the properties of pathways by which radionuclides could be released to the biosphere. Stochastic simulation is used to evaluate portions of the model that can only be characterized in statistical terms, since many water-conducting features within the model volume cannot be characterized deterministically. Chapter 2 describes the methodology by which discrete features are derived to represent water-conducting features around the hypothetical repository at Forsmark (including both natural features and features that result from the disturbance of excavation), and then assembled to produce a discrete-feature network model for numerical simulation of flow and transport. Chapter 3 describes how site-specific data and repository design are adapted to produce the discrete-feature model. Chapter 4 presents results of the calculations. These include utilization factors for deposition tunnels based on the emplacement criteria that have been set forth by the implementers, flow distributions to the deposition holes, and calculated properties of discharge paths as well as

  17. A new approach for detecting local features

    DEFF Research Database (Denmark)

    Nguyen, Phuong Giang; Andersen, Hans Jørgen

    2010-01-01

    Local features up to now are often mentioned in the meaning of interest points. A patch around each point is formed to compute descriptors or feature vectors. Therefore, in order to satisfy different invariant imaging conditions such as scales and viewpoints, an input image is often represented i...

  18. Meta-Level Runtime Feature Awareness for Java

    DEFF Research Database (Denmark)

    Olszak, Andrzej; Jensen, Martin Lykke Rytter; Jørgensen, Bo Nørregaard

    2011-01-01

    introduce the concept of runtime feature awareness that enables a running program to establish and make use of its own feature-code traceability links. We present an implementation of this idea, a dynamic-analysis Java library called JAwareness. JAwareness provides a meta-level architecture that can be non...

  19. Constraint solving for direct manipulation of features

    NARCIS (Netherlands)

    Lourenco, D.; Oliveira, P.; Noort, A.; Bidarra, R.

    2006-01-01

    In current commercial feature modeling systems, support for direct manipulation of features is not commonly available. This is partly due to the strong reliance of such systems on constraints, but also to the lack of speed of current constraint solvers. In this paper, an approach to the optimization

  20. Building Footprints, Primarily residential, at risk buildings such as hospitals, nursing homes, etc for use in Emergency Management Hazard Mitigation planning., Published in 2010, 1:4800 (1in=400ft) scale, Carroll County Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Building Footprints dataset current as of 2010. Primarily residential, at risk buildings such as hospitals, nursing homes, etc for use in Emergency Management Hazard...

  1. Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion

    Directory of Open Access Journals (Sweden)

    Dane Brown

    2017-07-01

    Full Text Available The feature level, unlike the match score level, lacks multi-modal fusion guidelines. This work demonstrates a new approach for improved image-based biometric feature-fusion. The approach extracts and combines the face, fingerprint and palmprint at the feature level for improved human identification accuracy. Feature-fusion guidelines, proposed in our recent work, are extended by adding a new face segmentation method and the support vector machine classifier. The new face segmentation method improves the face identification equal error rate (EER by 10%. The support vector machine classifier combined with the new feature selection approach, proposed in our recent work, outperforms other classifiers when using a single training sample. Feature-fusion guidelines take the form of strengths and weaknesses as observed in the applied feature processing modules during preliminary experiments. The guidelines are used to implement an effective biometric fusion system at the feature level, using a novel feature-fusion methodology, reducing the EER of two groups of three datasets namely: SDUMLA face, SDUMLA fingerprint and IITD palmprint; MUCT Face, MCYT Fingerprint and CASIA Palmprint.

  2. Alexnet Feature Extraction and Multi-Kernel Learning for Objectoriented Classification

    Science.gov (United States)

    Ding, L.; Li, H.; Hu, C.; Zhang, W.; Wang, S.

    2018-04-01

    In view of the fact that the deep convolutional neural network has stronger ability of feature learning and feature expression, an exploratory research is done on feature extraction and classification for high resolution remote sensing images. Taking the Google image with 0.3 meter spatial resolution in Ludian area of Yunnan Province as an example, the image segmentation object was taken as the basic unit, and the pre-trained AlexNet deep convolution neural network model was used for feature extraction. And the spectral features, AlexNet features and GLCM texture features are combined with multi-kernel learning and SVM classifier, finally the classification results were compared and analyzed. The results show that the deep convolution neural network can extract more accurate remote sensing image features, and significantly improve the overall accuracy of classification, and provide a reference value for earthquake disaster investigation and remote sensing disaster evaluation.

  3. ALEXNET FEATURE EXTRACTION AND MULTI-KERNEL LEARNING FOR OBJECTORIENTED CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    L. Ding

    2018-04-01

    Full Text Available In view of the fact that the deep convolutional neural network has stronger ability of feature learning and feature expression, an exploratory research is done on feature extraction and classification for high resolution remote sensing images. Taking the Google image with 0.3 meter spatial resolution in Ludian area of Yunnan Province as an example, the image segmentation object was taken as the basic unit, and the pre-trained AlexNet deep convolution neural network model was used for feature extraction. And the spectral features, AlexNet features and GLCM texture features are combined with multi-kernel learning and SVM classifier, finally the classification results were compared and analyzed. The results show that the deep convolution neural network can extract more accurate remote sensing image features, and significantly improve the overall accuracy of classification, and provide a reference value for earthquake disaster investigation and remote sensing disaster evaluation.

  4. Adolescent Pornography Use and Dating Violence among a Sample of Primarily Black and Hispanic, Urban-Residing, Underage Youth

    Directory of Open Access Journals (Sweden)

    Emily F. Rothman

    2015-12-01

    Full Text Available This cross-sectional study was designed to characterize the pornography viewing preferences of a sample of U.S.-based, urban-residing, economically disadvantaged, primarily Black and Hispanic youth (n = 72, and to assess whether pornography use was associated with experiences of adolescent dating abuse (ADA victimization. The sample was recruited from a large, urban, safety net hospital, and participants were 53% female, 59% Black, 19% Hispanic, 14% Other race, 6% White, and 1% Native American. All were 16–17 years old. More than half (51% had been asked to watch pornography together by a dating or sexual partner, and 44% had been asked to do something sexual that a partner saw in pornography. Adolescent dating abuse (ADA victimization was associated with more frequent pornography use, viewing pornography in the company of others, being asked to perform a sexual act that a partner first saw in pornography, and watching pornography during or after marijuana use. Approximately 50% of ADA victims and 32% of non-victims reported that they had been asked to do a sexual act that their partner saw in pornography (p = 0.15, and 58% did not feel happy to have been asked. Results suggest that weekly pornography use among underage, urban-residing youth is common, and may be associated with ADA victimization.

  5. Adolescent Pornography Use and Dating Violence among a Sample of Primarily Black and Hispanic, Urban-Residing, Underage Youth

    Science.gov (United States)

    Rothman, Emily F.; Adhia, Avanti

    2015-01-01

    This cross-sectional study was designed to characterize the pornography viewing preferences of a sample of U.S.-based, urban-residing, economically disadvantaged, primarily Black and Hispanic youth (n = 72), and to assess whether pornography use was associated with experiences of adolescent dating abuse (ADA) victimization. The sample was recruited from a large, urban, safety net hospital, and participants were 53% female, 59% Black, 19% Hispanic, 14% Other race, 6% White, and 1% Native American. All were 16–17 years old. More than half (51%) had been asked to watch pornography together by a dating or sexual partner, and 44% had been asked to do something sexual that a partner saw in pornography. Adolescent dating abuse (ADA) victimization was associated with more frequent pornography use, viewing pornography in the company of others, being asked to perform a sexual act that a partner first saw in pornography, and watching pornography during or after marijuana use. Approximately 50% of ADA victims and 32% of non-victims reported that they had been asked to do a sexual act that their partner saw in pornography (p = 0.15), and 58% did not feel happy to have been asked. Results suggest that weekly pornography use among underage, urban-residing youth may be common, and may be associated with ADA victimization. PMID:26703744

  6. Stylistic Features of the Legal Discourse | Alabi | UJAH: Unizik ...

    African Journals Online (AJOL)

    Every profession, every occupation, for example architecture, journalism, medicine, sports, has its specialised language features. These features may be viewed at the phonological, semantic, syntactic, lexical and graphological levels, among others. The language features identified with certain professions are most of the ...

  7. A keyword spotting model using perceptually significant energy features

    Science.gov (United States)

    Umakanthan, Padmalochini

    The task of a keyword recognition system is to detect the presence of certain words in a conversation based on the linguistic information present in human speech. Such keyword spotting systems have applications in homeland security, telephone surveillance and human-computer interfacing. General procedure of a keyword spotting system involves feature generation and matching. In this work, new set of features that are based on the psycho-acoustic masking nature of human speech are proposed. After developing these features a time aligned pattern matching process was implemented to locate the words in a set of unknown words. A word boundary detection technique based on frame classification using the nonlinear characteristics of speech is also addressed in this work. Validation of this keyword spotting model was done using widely acclaimed Cepstral features. The experimental results indicate the viability of using these perceptually significant features as an augmented feature set in keyword spotting.

  8. Feature Selection Criteria for Real Time EKF-SLAM Algorithm

    Directory of Open Access Journals (Sweden)

    Fernando Auat Cheein

    2010-02-01

    Full Text Available This paper presents a seletion procedure for environmet features for the correction stage of a SLAM (Simultaneous Localization and Mapping algorithm based on an Extended Kalman Filter (EKF. This approach decreases the computational time of the correction stage which allows for real and constant-time implementations of the SLAM. The selection procedure consists in chosing the features the SLAM system state covariance is more sensible to. The entire system is implemented on a mobile robot equipped with a range sensor laser. The features extracted from the environment correspond to lines and corners. Experimental results of the real time SLAM algorithm and an analysis of the processing-time consumed by the SLAM with the feature selection procedure proposed are shown. A comparison between the feature selection approach proposed and the classical sequential EKF-SLAM along with an entropy feature selection approach is also performed.

  9. Feature Selection with the Boruta Package

    Directory of Open Access Journals (Sweden)

    Miron B. Kursa

    2010-10-01

    Full Text Available This article describes a R package Boruta, implementing a novel feature selection algorithm for finding emph{all relevant variables}. The algorithm is designed as a wrapper around a Random Forest classification algorithm. It iteratively removes the features which are proved by a statistical test to be less relevant than random probes. The Boruta package provides a convenient interface to the algorithm. The short description of the algorithm and examples of its application are presented.

  10. Quantitative Comparison of Tolerance-Based Feature Transforms

    NARCIS (Netherlands)

    Reniers, Dennie; Telea, Alexandru

    2006-01-01

    Tolerance-based feature transforms (TFTs) assign to each pixel in an image not only the nearest feature pixels on the boundary (origins), but all origins from the minimum distance up to a user-defined tolerance. In this paper, we compare four simple-to-implement methods for computing TFTs for binary

  11. W-transform method for feature-oriented multiresolution image retrieval

    Energy Technology Data Exchange (ETDEWEB)

    Kwong, M.K.; Lin, B. [Argonne National Lab., IL (United States). Mathematics and Computer Science Div.

    1995-07-01

    Image database management is important in the development of multimedia technology. Since an enormous amount of digital images is likely to be generated within the next few decades in order to integrate computers, television, VCR, cables, telephone and various imaging devices. Effective image indexing and retrieval systems are urgently needed so that images can be easily organized, searched, transmitted, and presented. Here, the authors present a local-feature-oriented image indexing and retrieval method based on Kwong, and Tang`s W-transform. Multiresolution histogram comparison is an effective method for content-based image indexing and retrieval. However, most recent approaches perform multiresolution analysis for whole images but do not exploit the local features present in the images. Since W-transform is featured by its ability to handle images of arbitrary size, with no periodicity assumptions, it provides a natural tool for analyzing local image features and building indexing systems based on such features. In this approach, the histograms of the local features of images are used in the indexing, system. The system not only can retrieve images that are similar or identical to the query images but also can retrieve images that contain features specified in the query images, even if the retrieved images as a whole might be very different from the query images. The local-feature-oriented method also provides a speed advantage over the global multiresolution histogram comparison method. The feature-oriented approach is expected to be applicable in managing large-scale image systems such as video databases and medical image databases.

  12. Diffusion tensor image registration using hybrid connectivity and tensor features.

    Science.gov (United States)

    Wang, Qian; Yap, Pew-Thian; Wu, Guorong; Shen, Dinggang

    2014-07-01

    Most existing diffusion tensor imaging (DTI) registration methods estimate structural correspondences based on voxelwise matching of tensors. The rich connectivity information that is given by DTI, however, is often neglected. In this article, we propose to integrate complementary information given by connectivity features and tensor features for improved registration accuracy. To utilize connectivity information, we place multiple anchors representing different brain anatomies in the image space, and define the connectivity features for each voxel as the geodesic distances from all anchors to the voxel under consideration. The geodesic distance, which is computed in relation to the tensor field, encapsulates information of brain connectivity. We also extract tensor features for every voxel to reflect the local statistics of tensors in its neighborhood. We then combine both connectivity features and tensor features for registration of tensor images. From the images, landmarks are selected automatically and their correspondences are determined based on their connectivity and tensor feature vectors. The deformation field that deforms one tensor image to the other is iteratively estimated and optimized according to the landmarks and their associated correspondences. Experimental results show that, by using connectivity features and tensor features simultaneously, registration accuracy is increased substantially compared with the cases using either type of features alone. Copyright © 2013 Wiley Periodicals, Inc.

  13. Acoustic features of objects matched by an echolocating bottlenose dolphin.

    Science.gov (United States)

    Delong, Caroline M; Au, Whitlow W L; Lemonds, David W; Harley, Heidi E; Roitblat, Herbert L

    2006-03-01

    The focus of this study was to investigate how dolphins use acoustic features in returning echolocation signals to discriminate among objects. An echolocating dolphin performed a match-to-sample task with objects that varied in size, shape, material, and texture. After the task was completed, the features of the object echoes were measured (e.g., target strength, peak frequency). The dolphin's error patterns were examined in conjunction with the between-object variation in acoustic features to identify the acoustic features that the dolphin used to discriminate among the objects. The present study explored two hypotheses regarding the way dolphins use acoustic information in echoes: (1) use of a single feature, or (2) use of a linear combination of multiple features. The results suggested that dolphins do not use a single feature across all object sets or a linear combination of six echo features. Five features appeared to be important to the dolphin on four or more sets: the echo spectrum shape, the pattern of changes in target strength and number of highlights as a function of object orientation, and peak and center frequency. These data suggest that dolphins use multiple features and integrate information across echoes from a range of object orientations.

  14. Intuitiveness of Symbol Features for Air Traffic Management

    Science.gov (United States)

    Ngo, Mary Kim; Vu, Kim-Phuong L.; Thorpe, Elaine; Battiste, Vernol; Strybel, Thomas Z.

    2012-01-01

    We present the results of two online surveys asking participants to indicate what type of air traffic information might be conveyed by a number of symbols and symbol features (color, fill, text, and shape). The results of this initial study suggest that the well-developed concepts of ownership, altitude, and trajectory are readily associated with certain symbol features, while the relatively novel concept of equipage was not clearly associated with any specific symbol feature.

  15. Classification of line features from remote sensing data

    OpenAIRE

    Kolankiewiczová, Soňa

    2009-01-01

    This work deals with object-based classification of high resolution data. The aim of the thesis (paper, work) is to develope an acceptable classification process of linear features (roads and railways) from high-resolution satellite images. The first part shows different approaches of the linear feature classification and compares theoretic differences between an object-oriented and a pixel-based classification. Linear feature classification was created in the second part. The high-resolution...

  16. Characteristic features of the exotic superconductors: A summary

    International Nuclear Information System (INIS)

    Brandow, B.

    1997-09-01

    The authors summarize the results of a comprehensive examination of the characteristic features of the exotic superconductors, the superconductors so-labelled by Uemura and co-workers. In both the electronic and the crystal-chemistry properties, they find anomalous features which appear to be universal for these materials, as well as other features which are clearly not universal but common enough to be considered typical for these materials. Some implications of these anomalies are discussed

  17. Pedestrian count estimation using texture feature with spatial distribution

    Directory of Open Access Journals (Sweden)

    Hongyu Hu

    2016-12-01

    Full Text Available We present a novel pedestrian count estimation approach based on global image descriptors formed from multi-scale texture features that considers spatial distribution. For regions of interest, local texture features are represented based on histograms of multi-scale block local binary pattern, which jointly constitute the feature vector of the whole image. Therefore, to achieve an effective estimation of pedestrian count, principal component analysis is used to reduce the dimension of the global representation features, and a fitting model between image global features and pedestrian count is constructed via support vector regression. The experimental result shows that the proposed method exhibits high accuracy on pedestrian count estimation and can be applied well in the real world.

  18. Breast image feature learning with adaptive deconvolutional networks

    Science.gov (United States)

    Jamieson, Andrew R.; Drukker, Karen; Giger, Maryellen L.

    2012-03-01

    Feature extraction is a critical component of medical image analysis. Many computer-aided diagnosis approaches employ hand-designed, heuristic lesion extracted features. An alternative approach is to learn features directly from images. In this preliminary study, we explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based image retrieval (CBIR). ADNs (Zeiler, et. al., 2011), are recently-proposed unsupervised, generative hierarchical models that decompose images via convolution sparse coding and max pooling. We trained the ADNs to learn multiple layers of representation for two breast image data sets on two different modalities (739 full field digital mammography (FFDM) and 2393 ultrasound images). Feature map calculations were accelerated by use of GPUs. Following Zeiler et. al., we applied the Spatial Pyramid Matching (SPM) kernel (Lazebnik, et. al., 2006) on the inferred feature maps and combined this with a linear support vector machine (SVM) classifier for the task of binary classification between cancer and non-cancer breast mass lesions. Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships learned. Performance was found to be competitive with current CADx schemes that use human-designed features, e.g., achieving a 0.632+ bootstrap AUC (by case) of 0.83 [0.78, 0.89] for an ultrasound image set (1125 cases).

  19. Divided spatial attention and feature-mixing errors.

    Science.gov (United States)

    Golomb, Julie D

    2015-11-01

    Spatial attention is thought to play a critical role in feature binding. However, often multiple objects or locations are of interest in our environment, and we need to shift or split attention between them. Recent evidence has demonstrated that shifting and splitting spatial attention results in different types of feature-binding errors. In particular, when two locations are simultaneously sharing attentional resources, subjects are susceptible to feature-mixing errors; that is, they tend to report a color that is a subtle blend of the target color and the color at the other attended location. The present study was designed to test whether these feature-mixing errors are influenced by target-distractor similarity. Subjects were cued to split attention across two different spatial locations, and were subsequently presented with an array of colored stimuli, followed by a postcue indicating which color to report. Target-distractor similarity was manipulated by varying the distance in color space between the two attended stimuli. Probabilistic modeling in all cases revealed shifts in the response distribution consistent with feature-mixing errors; however, the patterns differed considerably across target-distractor color distances. With large differences in color, the findings replicated the mixing result, but with small color differences, repulsion was instead observed, with the reported target color shifted away from the other attended color.

  20. Face Alignment via Regressing Local Binary Features.

    Science.gov (United States)

    Ren, Shaoqing; Cao, Xudong; Wei, Yichen; Sun, Jian

    2016-03-01

    This paper presents a highly efficient and accurate regression approach for face alignment. Our approach has two novel components: 1) a set of local binary features and 2) a locality principle for learning those features. The locality principle guides us to learn a set of highly discriminative local binary features for each facial landmark independently. The obtained local binary features are used to jointly learn a linear regression for the final output. This approach achieves the state-of-the-art results when tested on the most challenging benchmarks to date. Furthermore, because extracting and regressing local binary features are computationally very cheap, our system is much faster than previous methods. It achieves over 3000 frames per second (FPS) on a desktop or 300 FPS on a mobile phone for locating a few dozens of landmarks. We also study a key issue that is important but has received little attention in the previous research, which is the face detector used to initialize alignment. We investigate several face detectors and perform quantitative evaluation on how they affect alignment accuracy. We find that an alignment friendly detector can further greatly boost the accuracy of our alignment method, reducing the error up to 16% relatively. To facilitate practical usage of face detection/alignment methods, we also propose a convenient metric to measure how good a detector is for alignment initialization.

  1. Face-iris multimodal biometric scheme based on feature level fusion

    Science.gov (United States)

    Huo, Guang; Liu, Yuanning; Zhu, Xiaodong; Dong, Hongxing; He, Fei

    2015-11-01

    Unlike score level fusion, feature level fusion demands all the features extracted from unimodal traits with high distinguishability, as well as homogeneity and compatibility, which is difficult to achieve. Therefore, most multimodal biometric research focuses on score level fusion, whereas few investigate feature level fusion. We propose a face-iris recognition method based on feature level fusion. We build a special two-dimensional-Gabor filter bank to extract local texture features from face and iris images, and then transform them by histogram statistics into an energy-orientation variance histogram feature with lower dimensions and higher distinguishability. Finally, through a fusion-recognition strategy based on principal components analysis and support vector machine (FRSPS), feature level fusion and one-to-n identification are accomplished. The experimental results demonstrate that this method can not only effectively extract face and iris features but also provide higher recognition accuracy. Compared with some state-of-the-art fusion methods, the proposed method has a significant performance advantage.

  2. A comparative analysis of DNA barcode microarray feature size

    Directory of Open Access Journals (Sweden)

    Smith Andrew M

    2009-10-01

    Full Text Available Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density, but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO collection used for screens of pooled yeast (Saccharomyces cerevisiae deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.

  3. Cuticular features as indicators of environmental pollution

    Science.gov (United States)

    G. K. Sharma

    1976-01-01

    Several leaf cuticular features such as stomatal frequency, stomatal size, trichome length, type, and frequency, and subsidiary cell complex respond to environmental pollution in different ways and hence can be used as indicators of environmental pollution in an area. Several modifications in cuticular features under polluted environments seem to indicate ecotypic or...

  4. A Meta-Heuristic Regression-Based Feature Selection for Predictive Analytics

    Directory of Open Access Journals (Sweden)

    Bharat Singh

    2014-11-01

    Full Text Available A high-dimensional feature selection having a very large number of features with an optimal feature subset is an NP-complete problem. Because conventional optimization techniques are unable to tackle large-scale feature selection problems, meta-heuristic algorithms are widely used. In this paper, we propose a particle swarm optimization technique while utilizing regression techniques for feature selection. We then use the selected features to classify the data. Classification accuracy is used as a criterion to evaluate classifier performance, and classification is accomplished through the use of k-nearest neighbour (KNN and Bayesian techniques. Various high dimensional data sets are used to evaluate the usefulness of the proposed approach. Results show that our approach gives better results when compared with other conventional feature selection algorithms.

  5. The importance of internal facial features in learning new faces.

    Science.gov (United States)

    Longmore, Christopher A; Liu, Chang Hong; Young, Andrew W

    2015-01-01

    For familiar faces, the internal features (eyes, nose, and mouth) are known to be differentially salient for recognition compared to external features such as hairstyle. Two experiments are reported that investigate how this internal feature advantage accrues as a face becomes familiar. In Experiment 1, we tested the contribution of internal and external features to the ability to generalize from a single studied photograph to different views of the same face. A recognition advantage for the internal features over the external features was found after a change of viewpoint, whereas there was no internal feature advantage when the same image was used at study and test. In Experiment 2, we removed the most salient external feature (hairstyle) from studied photographs and looked at how this affected generalization to a novel viewpoint. Removing the hair from images of the face assisted generalization to novel viewpoints, and this was especially the case when photographs showing more than one viewpoint were studied. The results suggest that the internal features play an important role in the generalization between different images of an individual's face by enabling the viewer to detect the common identity-diagnostic elements across non-identical instances of the face.

  6. Component Composition Using Feature Models

    DEFF Research Database (Denmark)

    Eichberg, Michael; Klose, Karl; Mitschke, Ralf

    2010-01-01

    interface description languages. If this variability is relevant when selecting a matching component then human interaction is required to decide which components can be bound. We propose to use feature models for making this variability explicit and (re-)enabling automatic component binding. In our...... approach, feature models are one part of service specifications. This enables to declaratively specify which service variant is provided by a component. By referring to a service's variation points, a component that requires a specific service can list the requirements on the desired variant. Using...... these specifications, a component environment can then determine if a binding of the components exists that satisfies all requirements. The prototypical environment Columbus demonstrates the feasibility of the approach....

  7. Multimodal Discrimination of Schizophrenia Using Hybrid Weighted Feature Concatenation of Brain Functional Connectivity and Anatomical Features with an Extreme Learning Machine

    Directory of Open Access Journals (Sweden)

    Muhammad Naveed Iqbal Qureshi

    2017-09-01

    Full Text Available Multimodal features of structural and functional magnetic resonance imaging (MRI of the human brain can assist in the diagnosis of schizophrenia. We performed a classification study on age, sex, and handedness-matched subjects. The dataset we used is publicly available from the Center for Biomedical Research Excellence (COBRE and it consists of two groups: patients with schizophrenia and healthy controls. We performed an independent component analysis and calculated global averaged functional connectivity-based features from the resting-state functional MRI data for all the cortical and subcortical anatomical parcellation. Cortical thickness along with standard deviation, surface area, volume, curvature, white matter volume, and intensity measures from the cortical parcellation, as well as volume and intensity from sub-cortical parcellation and overall volume of cortex features were extracted from the structural MRI data. A novel hybrid weighted feature concatenation method was used to acquire maximal 99.29% (P < 0.0001 accuracy which preserves high discriminatory power through the weight of the individual feature type. The classification was performed by an extreme learning machine, and its efficiency was compared to linear and non-linear (radial basis function support vector machines, linear discriminant analysis, and random forest bagged tree ensemble algorithms. This article reports the predictive accuracy of both unimodal and multimodal features after 10-by-10-fold nested cross-validation. A permutation test followed the classification experiment to assess the statistical significance of the classification results. It was concluded that, from a clinical perspective, this feature concatenation approach may assist the clinicians in schizophrenia diagnosis.

  8. MRI features of chondroblastoma

    International Nuclear Information System (INIS)

    Cheng Xiaoguang; Liu Xia; Cheng Kebin; Liu Wei

    2009-01-01

    Objective: To evaluate the MR imaging features of chondroblastoma. Methods: MRI examinations of 20 patients with histological proven chondmblastoma were reviewed retrospectively. The MRI findings of chondroblastoma including the signal intensity, the shape, the growth patterns, and the surrounding bone marrow edema and the adjacent soft tissue edema, the periosteal reaction, the adjacent joint effusion were analyzed. Results: All 20 cases demonstrated heterogeneous MR signal intensity on T 1 WI and T 2 WI images and showed lobular margins. Sixteen cases demonstrated expansive growth patterns. Surrounding bone marrow edema was found in 18 cases and adjacent soft tissue edema in 14 cases. Periosteal reaction was identified in 6 cases. In 7 cases the tumor extended to adjacent soft tissue. Adjacent joint effusion was visible on MRI in 6 cases. Conclusion: Heterogeneous signal intensity, lobular margins and expansive growth pattern, adjacent bone marrow and soft tissue edema were the common features of chondroblastoma on MRI. (authors)

  9. Extracting Feature Model Changes from the Linux Kernel Using FMDiff

    NARCIS (Netherlands)

    Dintzner, N.J.R.; Van Deursen, A.; Pinzger, M.

    2014-01-01

    The Linux kernel feature model has been studied as an example of large scale evolving feature model and yet details of its evolution are not known. We present here a classification of feature changes occurring on the Linux kernel feature model, as well as a tool, FMDiff, designed to automatically

  10. Embedded Incremental Feature Selection for Reinforcement Learning

    Science.gov (United States)

    2012-05-01

    Prior to this work, feature selection for reinforce- ment learning has focused on linear value function ap- proximation ( Kolter and Ng, 2009; Parr et al...InProceed- ings of the the 23rd International Conference on Ma- chine Learning, pages 449–456. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature

  11. Individual Identification Using Linear Projection of Heartbeat Features

    Directory of Open Access Journals (Sweden)

    Yogendra Narain Singh

    2014-01-01

    Full Text Available This paper presents a novel method to use the electrocardiogram (ECG signal as biometrics for individual identification. The ECG characterization is performed using an automated approach consisting of analytical and appearance methods. The analytical method extracts the fiducial features from heartbeats while the appearance method extracts the morphological features from the ECG trace. We linearly project the extracted features into a subspace of lower dimension using an orthogonal basis that represent the most significant features for distinguishing heartbeats among the subjects. Result demonstrates that the proposed characterization of the ECG signal and subsequently derived eigenbeat features are insensitive to signal variations and nonsignal artifacts. The proposed system utilizing ECG biometric method achieves the best identification rates of 85.7% for the subjects of MIT-BIH arrhythmia database and 92.49% for the healthy subjects of our IIT (BHU database. These results are significantly better than the classification accuracies of 79.55% and 84.9%, reported using support vector machine on the tested subjects of MIT-BIH arrhythmia database and our IIT (BHU database, respectively.

  12. Joint Tensor Feature Analysis For Visual Object Recognition.

    Science.gov (United States)

    Wong, Wai Keung; Lai, Zhihui; Xu, Yong; Wen, Jiajun; Ho, Chu Po

    2015-11-01

    Tensor-based object recognition has been widely studied in the past several years. This paper focuses on the issue of joint feature selection from the tensor data and proposes a novel method called joint tensor feature analysis (JTFA) for tensor feature extraction and recognition. In order to obtain a set of jointly sparse projections for tensor feature extraction, we define the modified within-class tensor scatter value and the modified between-class tensor scatter value for regression. The k-mode optimization technique and the L(2,1)-norm jointly sparse regression are combined together to compute the optimal solutions. The convergent analysis, computational complexity analysis and the essence of the proposed method/model are also presented. It is interesting to show that the proposed method is very similar to singular value decomposition on the scatter matrix but with sparsity constraint on the right singular value matrix or eigen-decomposition on the scatter matrix with sparse manner. Experimental results on some tensor datasets indicate that JTFA outperforms some well-known tensor feature extraction and selection algorithms.

  13. Face recognition using slow feature analysis and contourlet transform

    Science.gov (United States)

    Wang, Yuehao; Peng, Lingling; Zhe, Fuchuan

    2018-04-01

    In this paper we propose a novel face recognition approach based on slow feature analysis (SFA) in contourlet transform domain. This method firstly use contourlet transform to decompose the face image into low frequency and high frequency part, and then takes technological advantages of slow feature analysis for facial feature extraction. We named the new method combining the slow feature analysis and contourlet transform as CT-SFA. The experimental results on international standard face database demonstrate that the new face recognition method is effective and competitive.

  14. Unique features in the ARIES glovebox line

    International Nuclear Information System (INIS)

    Martinez, H.E.; Brown, W.G.; Flamm, B.; James, C.A.; Laskie, R.; Nelson, T.O.; Wedman, D.E.

    1998-01-01

    A series of unique features have been incorporated into the Advanced Recovery and Integrated Extraction System (ARIES) at the Los Alamos National Laboratory, TA-55 Plutonium Facility. The features enhance the material handling in the process of the dismantlement of nuclear weapon primaries in the glovebox line. Incorporated into these features are the various plutonium process module's different ventilation zone requirements that the material handling systems must meet. These features include a conveyor system that consists of a remotely controlled cart that transverses the length of the conveyor glovebox, can be operated from a remote location and can deliver process components to the entrance of any selected module glovebox. Within the modules there exists linear motion material handling systems with lifting hoist, which are controlled via an Allen Bradley control panel or local control panels. To remove the packaged products from the hot process line, the package is processed through an air lock/electrolytic decontamination process that removes the radioactive contamination from the outside of the package container and allows the package to be removed from the process line

  15. Mobility as a feature: Evidence from Zulu

    Directory of Open Access Journals (Sweden)

    Jochen Zeller

    2016-01-01

    Full Text Available This paper provides evidence for the view that syntactic movement of an element Y to a position X is not driven by features of the target X, but by features of the moving element Y. The data that constitute evidence for this type of analysis come from A-bar movement constructions (object left and right dislocation; object relativisation in the Bantu language Zulu. As I show, only object-DPs that move out of the VP in Zulu are active Goals for Agree-relations and can trigger object agreement with the verb. The fact that the functional head responsible for object agreement must be able to identify a DP in its c-command domain as an active Goal entails that the “mobility” of this DP must be encoded as a property of the DP. Based on this conclusion, I also discuss two proposals about the nature of the feature that activates a DP for movement in Zulu and examine the conditions that determine how this feature is checked and deleted through movement.

  16. Feature Selection Methods for Zero-Shot Learning of Neural Activity

    Directory of Open Access Journals (Sweden)

    Carlos A. Caceres

    2017-06-01

    Full Text Available Dimensionality poses a serious challenge when making predictions from human neuroimaging data. Across imaging modalities, large pools of potential neural features (e.g., responses from particular voxels, electrodes, and temporal windows have to be related to typically limited sets of stimuli and samples. In recent years, zero-shot prediction models have been introduced for mapping between neural signals and semantic attributes, which allows for classification of stimulus classes not explicitly included in the training set. While choices about feature selection can have a substantial impact when closed-set accuracy, open-set robustness, and runtime are competing design objectives, no systematic study of feature selection for these models has been reported. Instead, a relatively straightforward feature stability approach has been adopted and successfully applied across models and imaging modalities. To characterize the tradeoffs in feature selection for zero-shot learning, we compared correlation-based stability to several other feature selection techniques on comparable data sets from two distinct imaging modalities: functional Magnetic Resonance Imaging and Electrocorticography. While most of the feature selection methods resulted in similar zero-shot prediction accuracies and spatial/spectral patterns of selected features, there was one exception; A novel feature/attribute correlation approach was able to achieve those accuracies with far fewer features, suggesting the potential for simpler prediction models that yield high zero-shot classification accuracy.

  17. Imaging features of aggressive angiomyxoma

    International Nuclear Information System (INIS)

    Jeyadevan, N.N.; Sohaib, S.A.A.; Thomas, J.M.; Jeyarajah, A.; Shepherd, J.H.; Fisher, C.

    2003-01-01

    AIM: To describe the imaging features of aggressive angiomyxoma in a rare benign mesenchymal tumour most frequently arising from the perineum in young female patients. MATERIALS AND METHODS: We reviewed the computed tomography (CT) and magnetic resonance (MR) imaging features of patients with aggressive angiomyxoma who were referred to our hospital. The imaging features were correlated with clinical information and pathology in all patients. RESULTS: Four CT and five MR studies were available for five patients (all women, mean age 39, range 24-55). Three patients had recurrent tumour at follow-up. CT and MR imaging demonstrated a well-defined mass-displacing adjacent structures. The tumour was of low attenuation relative to muscle on CT. On MR, the tumour was isointense relative to muscle on T1-weighted image, hyperintense on T2-weighted image and enhanced avidly after gadolinium contrast with a characteristic 'swirled' internal pattern. MR imaging demonstrates the extent of the tumour and its relation to the pelvic floor. Recurrent tumour has a similar appearance to the primary lesion. CONCLUSION: The MR appearances of aggressive angiomyxomas are characteristic, and the diagnosis should be considered in any young woman presenting with a well-defined mass arising from the perineum. Jeyadevan, N. N. etal. (2003). Clinical Radiology58, 157--162

  18. Sexual dimorphism in medulloblastoma features.

    Science.gov (United States)

    Zannoni, Gian Franco; Ciucci, Alessandra; Marucci, Gianluca; Travaglia, Daniele; Stigliano, Egidio; Foschini, Maria Pia; Scambia, Giovanni; Gallo, Daniela

    2016-03-01

    Male sex is a risk factor for medulloblastoma (MB), and is also a negative predictor for clinical outcome. The aim of this study was to assess sex differences in tumour biological features and hormone receptor profiles in a cohort of MB patients. Sixty-four MBs and five normal cerebella were included in the study. Cell proliferation (Ki67), apoptosis (cleaved caspase-3) and microvessel density (CD31) were evaluated in tumours by immunohistochemistry. Tissues were analysed for oestrogen receptor (ER)α, ERβ1, ERβ2, ERβ5 and androgen receptor (AR) expression. The results demonstrated sex-specific features in MBs, with tumours from females showing a higher apoptosis/proliferation ratio and less tumour vascularization than tumours from males. MBs were negative for ERα and AR, but expressed ERβ isoforms at similar levels between the sexes. Altogether, these findings indicate that signalling mechanisms that control cell turnover and angiogenesis operate more efficiently in females than in males. The lack of sex differences in the hormone receptor profiles suggests that circulating oestrogens could be the major determinants of the sexual dimorphism observed in MB features. Here, we provide molecular support for epidemiological data showing sex differences in MB incidence and outcome, completely defining the hormone receptor profile of the tumours. © 2015 John Wiley & Sons Ltd.

  19. Feature hashing for fast image retrieval

    Science.gov (United States)

    Yan, Lingyu; Fu, Jiarun; Zhang, Hongxin; Yuan, Lu; Xu, Hui

    2018-03-01

    Currently, researches on content based image retrieval mainly focus on robust feature extraction. However, due to the exponential growth of online images, it is necessary to consider searching among large scale images, which is very timeconsuming and unscalable. Hence, we need to pay much attention to the efficiency of image retrieval. In this paper, we propose a feature hashing method for image retrieval which not only generates compact fingerprint for image representation, but also prevents huge semantic loss during the process of hashing. To generate the fingerprint, an objective function of semantic loss is constructed and minimized, which combine the influence of both the neighborhood structure of feature data and mapping error. Since the machine learning based hashing effectively preserves neighborhood structure of data, it yields visual words with strong discriminability. Furthermore, the generated binary codes leads image representation building to be of low-complexity, making it efficient and scalable to large scale databases. Experimental results show good performance of our approach.

  20. MRI features of tuberculosis of peripheral joints

    Energy Technology Data Exchange (ETDEWEB)

    Sawlani, V.; Chandra, T.; Mishra, R.N.; Aggarwal, A.; Jain, U.K.; Gujral, R.B. E-mail: gujralrb@sgpgi.ac.in

    2003-10-01

    The aim of this article is to present the magnetic resonance imaging (MRI) features of peripheral tubercular arthritis. The clinical presentation of peripheral tubercular arthritis is variable and simulates other chronic inflammatory arthritic disorders. MRI is a highly sensitive technique which demonstrates fine anatomical details and identifies the early changes of arthritis, which are not visible on radiographs. The MRI features of tubercular arthritis include synovitis, effusion, central and peripheral erosions, active and chronic pannus, abscess, bone chips and hypo-intense synovium. These imaging features in an appropriate clinical setting may help in the diagnosis of tubercular arthritis. Early diagnosis and treatment can effectively eliminate the long-term morbidity of joints affected by tuberculosis.

  1. MRI features of tuberculosis of peripheral joints

    International Nuclear Information System (INIS)

    Sawlani, V.; Chandra, T.; Mishra, R.N.; Aggarwal, A.; Jain, U.K.; Gujral, R.B.

    2003-01-01

    The aim of this article is to present the magnetic resonance imaging (MRI) features of peripheral tubercular arthritis. The clinical presentation of peripheral tubercular arthritis is variable and simulates other chronic inflammatory arthritic disorders. MRI is a highly sensitive technique which demonstrates fine anatomical details and identifies the early changes of arthritis, which are not visible on radiographs. The MRI features of tubercular arthritis include synovitis, effusion, central and peripheral erosions, active and chronic pannus, abscess, bone chips and hypo-intense synovium. These imaging features in an appropriate clinical setting may help in the diagnosis of tubercular arthritis. Early diagnosis and treatment can effectively eliminate the long-term morbidity of joints affected by tuberculosis

  2. Feature selection for high-dimensional integrated data

    KAUST Repository

    Zheng, Charles

    2012-04-26

    Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.

  3. Feature selection for high-dimensional integrated data

    KAUST Repository

    Zheng, Charles; Schwartz, Scott; Chapkin, Robert S.; Carroll, Raymond J.; Ivanov, Ivan

    2012-01-01

    Motivated by the problem of identifying correlations between genes or features of two related biological systems, we propose a model of feature selection in which only a subset of the predictors Xt are dependent on the multidimensional variate Y, and the remainder of the predictors constitute a “noise set” Xu independent of Y. Using Monte Carlo simulations, we investigated the relative performance of two methods: thresholding and singular-value decomposition, in combination with stochastic optimization to determine “empirical bounds” on the small-sample accuracy of an asymptotic approximation. We demonstrate utility of the thresholding and SVD feature selection methods to with respect to a recent infant intestinal gene expression and metagenomics dataset.

  4. Palmprint Based Verification System Using SURF Features

    Science.gov (United States)

    Srinivas, Badrinath G.; Gupta, Phalguni

    This paper describes the design and development of a prototype of robust biometric system for verification. The system uses features extracted using Speeded Up Robust Features (SURF) operator of human hand. The hand image for features is acquired using a low cost scanner. The palmprint region extracted is robust to hand translation and rotation on the scanner. The system is tested on IITK database of 200 images and PolyU database of 7751 images. The system is found to be robust with respect to translation and rotation. It has FAR 0.02%, FRR 0.01% and accuracy of 99.98% and can be a suitable system for civilian applications and high-security environments.

  5. The analysis of image feature robustness using cometcloud

    Directory of Open Access Journals (Sweden)

    Xin Qi

    2012-01-01

    Full Text Available The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval.

  6. Feature learning and change feature classification based on deep learning for ternary change detection in SAR images

    Science.gov (United States)

    Gong, Maoguo; Yang, Hailun; Zhang, Puzhao

    2017-07-01

    Ternary change detection aims to detect changes and group the changes into positive change and negative change. It is of great significance in the joint interpretation of spatial-temporal synthetic aperture radar images. In this study, sparse autoencoder, convolutional neural networks (CNN) and unsupervised clustering are combined to solve ternary change detection problem without any supervison. Firstly, sparse autoencoder is used to transform log-ratio difference image into a suitable feature space for extracting key changes and suppressing outliers and noise. And then the learned features are clustered into three classes, which are taken as the pseudo labels for training a CNN model as change feature classifier. The reliable training samples for CNN are selected from the feature maps learned by sparse autoencoder with certain selection rules. Having training samples and the corresponding pseudo labels, the CNN model can be trained by using back propagation with stochastic gradient descent. During its training procedure, CNN is driven to learn the concept of change, and more powerful model is established to distinguish different types of changes. Unlike the traditional methods, the proposed framework integrates the merits of sparse autoencoder and CNN to learn more robust difference representations and the concept of change for ternary change detection. Experimental results on real datasets validate the effectiveness and superiority of the proposed framework.

  7. Topographic features over the continental shelf off Visakhapatnam

    Digital Repository Service at National Institute of Oceanography (India)

    Rao, T.C.S.; Machado, T.; Murthy, K.S.R.

    water depth and the continental shelfedge several interesting topographic features such as Terraces, Karstic structures associated with pinnacles and troughs and smooth dome shaped reef structures are recorded. The nature of these features...

  8. Arabic Feature-Based Level Sentiment Analysis Using Lexicon ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... structured reviews being prior knowledge for mining unstructured reviews. ... FDSO has been introduced, which defines a space of product features ... polarity of a review using feature ontology and sentiment lexicons.

  9. An Integrated Account of Generalization across Objects and Features

    Science.gov (United States)

    Kemp, Charles; Shafto, Patrick; Tenenbaum, Joshua B.

    2012-01-01

    Humans routinely make inductive generalizations about unobserved features of objects. Previous accounts of inductive reasoning often focus on inferences about a single object or feature: accounts of causal reasoning often focus on a single object with one or more unobserved features, and accounts of property induction often focus on a single…

  10. CT features of intussusception through an Ileostomy

    Energy Technology Data Exchange (ETDEWEB)

    Jung, Mi Ran; Park, Mi Hyun; Jee, Keum Nahn; Namgung, Hwan [Dankook University School of Medicine, Cheonan (Korea, Republic of)

    2017-08-15

    Intussusception of the small bowel through an ileostomy is very rare; when it causes necrosis of the bowel, immediate surgery is required. Computed tomography (CT) features of intussusception through an ileostomy have not been reported in the literature. Herein, we report the typical CT features of intussusception through an ileostomy, followed by a brief literature review.

  11. What features do Dutch university students prefer in a smartphone application for promotion of physical activity? A qualitative approach.

    Science.gov (United States)

    Middelweerd, Anouk; van der Laan, Danielle M; van Stralen, Maartje M; Mollee, Julia S; Stuij, Mirjam; te Velde, Saskia J; Brug, Johannes

    2015-03-01

    The transition from adolescence to early adulthood is a critical period in which there is a decline in physical activity (PA). College and university students make up a large segment of this age group. Smartphones may be used to promote and support PA. The purpose of this qualitative study was to explore Dutch students' preferences regarding a PA application (PA app) for smartphones. Thirty Dutch students (aged 18-25 years) used a PA app for three weeks and subsequently attended a focus group discussion (k = 5). To streamline the discussion, a discussion guide was developed covering seven main topics, including general app usage, usage and appreciation of the PA app, appreciation of and preferences for its features and the sharing of PA accomplishments through social media. The discussions were audio and video recorded, transcribed and analysed according to conventional content analysis. The participants, aged 21 ± 2 years, were primarily female (67%). Several themes emerged: app usage, technical aspects, PA assessment, coaching aspects and sharing through social media. Participants most often used social networking apps (e.g., Facebook or Twitter), communication apps (e.g., WhatsApp) and content apps (e.g., news reports or weather forecasts). They preferred a simple and structured layout without unnecessary features. Ideally, the PA app should enable users to tailor it to their personal preferences by including the ability to hide features. Participants preferred a companion website for detailed information about their accomplishments and progress, and they liked tracking their workout using GPS. They preferred PA apps that coached and motivated them and provided tailored feedback toward personally set goals. They appreciated PA apps that enabled competition with friends by ranking or earning rewards, but only if the reward system was transparent. They were not willing to share their regular PA accomplishments through social media unless they were

  12. An enhanced feature set for pattern recognition based contrast enhancement of contact-less captured latent fingerprints in digitized crime scene forensics

    Science.gov (United States)

    Hildebrandt, Mario; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus

    2014-02-01

    In crime scene forensics latent fingerprints are found on various substrates. Nowadays primarily physical or chemical preprocessing techniques are applied for enhancing the visibility of the fingerprint trace. In order to avoid altering the trace it has been shown that contact-less sensors offer a non-destructive acquisition approach. Here, the exploitation of fingerprint or substrate properties and the utilization of signal processing techniques are an essential requirement to enhance the fingerprint visibility. However, especially the optimal sensory is often substrate-dependent. An enhanced generic pattern recognition based contrast enhancement approach for scans of a chromatic white light sensor is introduced in Hildebrandt et al.1 using statistical, structural and Benford's law2 features for blocks of 50 micron. This approach achieves very good results for latent fingerprints on cooperative, non-textured, smooth substrates. However, on textured and structured substrates the error rates are very high and the approach thus unsuitable for forensic use cases. We propose the extension of the feature set with semantic features derived from known Gabor filter based exemplar fingerprint enhancement techniques by suggesting an Epsilon-neighborhood of each block in order to achieve an improved accuracy (called fingerprint ridge orientation semantics). Furthermore, we use rotation invariant Hu moments as an extension of the structural features and two additional preprocessing methods (separate X- and Y Sobel operators). This results in a 408-dimensional feature space. In our experiments we investigate and report the recognition accuracy for eight substrates, each with ten latent fingerprints: white furniture surface, veneered plywood, brushed stainless steel, aluminum foil, "Golden-Oak" veneer, non-metallic matte car body finish, metallic car body finish and blued metal. In comparison to Hildebrandt et al.,1 our evaluation shows a significant reduction of the error rates

  13. Improved pulmonary nodule classification utilizing quantitative lung parenchyma features.

    Science.gov (United States)

    Dilger, Samantha K N; Uthoff, Johanna; Judisch, Alexandra; Hammond, Emily; Mott, Sarah L; Smith, Brian J; Newell, John D; Hoffman, Eric A; Sieren, Jessica C

    2015-10-01

    Current computer-aided diagnosis (CAD) models for determining pulmonary nodule malignancy characterize nodule shape, density, and border in computed tomography (CT) data. Analyzing the lung parenchyma surrounding the nodule has been minimally explored. We hypothesize that improved nodule classification is achievable by including features quantified from the surrounding lung tissue. To explore this hypothesis, we have developed expanded quantitative CT feature extraction techniques, including volumetric Laws texture energy measures for the parenchyma and nodule, border descriptors using ray-casting and rubber-band straightening, histogram features characterizing densities, and global lung measurements. Using stepwise forward selection and leave-one-case-out cross-validation, a neural network was used for classification. When applied to 50 nodules (22 malignant and 28 benign) from high-resolution CT scans, 52 features (8 nodule, 39 parenchymal, and 5 global) were statistically significant. Nodule-only features yielded an area under the ROC curve of 0.918 (including nodule size) and 0.872 (excluding nodule size). Performance was improved through inclusion of parenchymal (0.938) and global features (0.932). These results show a trend toward increased performance when the parenchyma is included, coupled with the large number of significant parenchymal features that support our hypothesis: the pulmonary parenchyma is influenced differentially by malignant versus benign nodules, assisting CAD-based nodule characterizations.

  14. Feature Detector and Descriptor for Medical Images

    Science.gov (United States)

    Sargent, Dusty; Chen, Chao-I.; Tsai, Chang-Ming; Wang, Yuan-Fang; Koppel, Daniel

    2009-02-01

    The ability to detect and match features across multiple views of a scene is a crucial first step in many computer vision algorithms for dynamic scene analysis. State-of-the-art methods such as SIFT and SURF perform successfully when applied to typical images taken by a digital camera or camcorder. However, these methods often fail to generate an acceptable number of features when applied to medical images, because such images usually contain large homogeneous regions with little color and intensity variation. As a result, tasks like image registration and 3D structure recovery become difficult or impossible in the medical domain. This paper presents a scale, rotation and color/illumination invariant feature detector and descriptor for medical applications. The method incorporates elements of SIFT and SURF while optimizing their performance on medical data. Based on experiments with various types of medical images, we combined, adjusted, and built on methods and parameter settings employed in both algorithms. An approximate Hessian based detector is used to locate scale invariant keypoints and a dominant orientation is assigned to each keypoint using a gradient orientation histogram, providing rotation invariance. Finally, keypoints are described with an orientation-normalized distribution of gradient responses at the assigned scale, and the feature vector is normalized for contrast invariance. Experiments show that the algorithm detects and matches far more features than SIFT and SURF on medical images, with similar error levels.

  15. Feature and Region Selection for Visual Learning.

    Science.gov (United States)

    Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

    2016-03-01

    Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

  16. Novel acoustic features for speech emotion recognition

    Institute of Scientific and Technical Information of China (English)

    ROH; Yong-Wan; KIM; Dong-Ju; LEE; Woo-Seok; HONG; Kwang-Seok

    2009-01-01

    This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech.The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform(FFT) spectral entropy,delta FFT spectral entropy,Mel-frequency filter bank(MFB) spectral entropy,and Delta MFB spectral entropy.Spectral-based entropy features are simple.They reflect frequency characteristic and changing characteristic in frequency of speech.We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance.Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results,respectively.These scores are first obtained from a pattern recognition procedure.The pattern recognition phase uses the Gaussian mixture model(GMM).We classify the four emotional states as anger,sadness,happiness and neutrality.The proposed method is evaluated using 45 sentences in each emotion for 30 subjects,15 males and 15 females.Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy,Zero Crossing Rate(ZCR),linear prediction coefficient(LPC),and pitch parameters.We demonstrate the effectiveness of the proposed approach.One of the proposed features,combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods.We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

  17. Novel acoustic features for speech emotion recognition

    Institute of Scientific and Technical Information of China (English)

    ROH Yong-Wan; KIM Dong-Ju; LEE Woo-Seok; HONG Kwang-Seok

    2009-01-01

    This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech. The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform (FFT) spectral entropy, delta FFT spectral entropy, Mel-frequency filter bank (MFB)spectral entropy, and Delta MFB spectral entropy. Spectral-based entropy features are simple. They reflect frequency characteristic and changing characteristic in frequency of speech. We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance. Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results, respectively.These scores are first obtained from a pattern recognition procedure. The pattern recognition phase uses the Gaussian mixture model (GMM). We classify the four emotional states as anger, sadness,happiness and neutrality. The proposed method is evaluated using 45 sentences in each emotion for 30 subjects, 15 males and 15 females. Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy, Zero Crossing Rate (ZCR),linear prediction coefficient (LPC), and pitch parameters. We demonstrate the effectiveness of the proposed approach. One of the proposed features, combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods. We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

  18. Associations Between PET Textural Features and GLUT1 Expression, and the Prognostic Significance of Textural Features in Lung Adenocarcinoma.

    Science.gov (United States)

    Koh, Young Wha; Park, Seong Yong; Hyun, Seung Hyup; Lee, Su Jin

    2018-02-01

    We evaluated the association between positron emission tomography (PET) textural features and glucose transporter 1 (GLUT1) expression level and further investigated the prognostic significance of textural features in lung adenocarcinoma. We evaluated 105 adenocarcinoma patients. We extracted texture-based PET parameters of primary tumors. Conventional PET parameters were also measured. The relationships between PET parameters and GLUT1 expression levels were evaluated. The association between PET parameters and overall survival (OS) was assessed using Cox's proportional hazard regression models. In terms of PET textural features, tumors expressing high levels of GLUT1 exhibited significantly lower coarseness, contrast, complexity, and strength, but significantly higher busyness. On univariate analysis, the metabolic tumor volume, total lesion glycolysis, contrast, busyness, complexity, and strength were significant predictors of OS. Multivariate analysis showed that lower complexity (HR=2.017, 95%CI=1.032-3.942, p=0.040) was independently associated with poorer survival. PET textural features may aid risk stratification in lung adenocarcinoma patients. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  19. Search asymmetry: a diagnostic for preattentive processing of separable features.

    Science.gov (United States)

    Treisman, A; Souther, J

    1985-09-01

    The search rate for a target among distractors may vary dramatically depending on which stimulus plays the role of target and which that of distractors. For example, the time required to find a circle distinguished by an intersecting line is independent of the number of regular circles in the display, whereas the time to find a regular circle among circles with lines increases linearly with the number of distractors. The pattern of performance suggests parallel processing when the target has a unique distinguishing feature and serial self-terminating search when the target is distinguished only by the absence of a feature that is present in all the distractors. The results are consistent with feature-integration theory (Treisman & Gelade, 1980), which predicts that a single feature should be detected by the mere presence of activity in the relevant feature map, whereas tasks that require subjects to locate multiple instances of a feature demand focused attention. Search asymmetries may therefore offer a new diagnostic to identify the primitive features of early vision. Several candidate features are examined in this article: Colors, line ends or terminators, and closure (in the sense of a partly or wholly enclosed area) appear to be functional features; connectedness, intactness (absence of an intersecting line), and acute angles do not.

  20. Pre-Alleghenian (Pennsylvanian-Permian) hydrocarbon emplacement along Ordovician Knox unconformity, eastern Tennessee

    Energy Technology Data Exchange (ETDEWEB)

    Haynes, F.M.; Kesler, S.E.

    1989-03-01

    Cores taken during exploration for Mississippi Valley-type lead and zinc ores in the Mascot-Jefferson City zinc district of eastern Tennessee commonly contain hydrocarbon residues in carbonate rocks of the Knox Group immediately below the Lower Ordovician Knox unconformity. The location and number of these residue-bearing strata reveal information about the Paleozoic history of hydrocarbon emplacement in the region. Contour maps, generated from nearly 800 holes covering more than 20 km/sup 2/, indicate that zones with elevated organic content in the uppermost 30 m of the Lower Ordovician Mascot Dolomite show a strong spatial correlation with Middle Ordovician paleotopographic highs. These same zones show no spatial association with present-day structural highs, which were formed during Pennsylvanian-Permian Alleghenian tectonism. This suggests that the physical entrapment of hydrocarbons migrating through the upper permeable units of the Mascot must have occurred prior to the principal tectonism of the Alleghenian orogeny. 7 figures, 1 table.