Computer vision approach to morphometric feature analysis of basal cell nuclei for evaluating malignant potentiality of oral submucous fibrosis.

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Muthu Rama Krishnan, M; Pal, Mousumi; Paul, Ranjan Rashmi; Chakraborty, Chandan; Chatterjee, Jyotirmoy; Ray, Ajoy K

2012-06-01

This research work presents a quantitative approach for analysis of histomorphometric features of the basal cell nuclei in respect to their size, shape and intensity of staining, from surface epithelium of Oral Submucous Fibrosis showing dysplasia (OSFD) to that of the Normal Oral Mucosa (NOM). For all biological activity, the basal cells of the surface epithelium form the proliferative compartment and therefore their morphometric changes will spell the intricate biological behavior pertaining to normal cellular functions as well as in premalignant and malignant status. In view of this, the changes in shape, size and intensity of staining of the nuclei in the basal cell layer of the NOM and OSFD have been studied. Geometric, Zernike moments and Fourier descriptor (FD) based as well as intensity based features are extracted for histomorphometric pattern analysis of the nuclei. All these features are statistically analyzed along with 3D visualization in order to discriminate the groups. Results showed increase in the dimensions (area and perimeter), shape parameters and decreasing mean nuclei intensity of the nuclei in OSFD in respect to NOM. Further, the selected features are fed to the Bayesian classifier to discriminate normal and OSFD. The morphometric and intensity features provide a good sensitivity of 100%, specificity of 98.53% and positive predicative accuracy of 97.35%. This comparative quantitative characterization of basal cell nuclei will be of immense help for oral onco-pathologists, researchers and clinicians to assess the biological behavior of OSFD, specially relating to their premalignant and malignant potentiality. As a future direction more extensive study involving more number of disease subjects is observed.

Watershed-based Morphometric Analysis: A Review

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Sukristiyanti, S.; Maria, R.; Lestiana, H.

2018-02-01

Drainage basin/watershed analysis based on morphometric parameters is very important for watershed planning. Morphometric analysis of watershed is the best method to identify the relationship of various aspects in the area. Despite many technical papers were dealt with in this area of study, there is no particular standard classification and implication of each parameter. It is very confusing to evaluate a value of every morphometric parameter. This paper deals with the meaning of values of the various morphometric parameters, with adequate contextual information. A critical review is presented on each classification, the range of values, and their implications. Besides classification and its impact, the authors also concern about the quality of input data, either in data preparation or scale/the detail level of mapping. This review paper hopefully can give a comprehensive explanation to assist the upcoming research dealing with morphometric analysis.

Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

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Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

2012-02-01

Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

Morphometric analysis with open source software to explore shallow hydrogeological features in Senegal and Guinea

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Fussi, Fabio; Di Leo, Margherita; Bonomi, Tullia; Di Mauro, Biagio; Fava, Francesco; Fumagalli, Letizia; Hamidou Kane, Cheikh; Faye, Gayane; Niang, Magatte; Wade, Souleye; Hamidou, Barry; Colombo, Roberto

2015-04-01

stratigraphic logs from water boreholes. We observed the relationships between the spatial distribution of hydrogeological features and the morphology, applying multivariate statistical analysis. The ultimate goal of this study is to infer hydrogeological information of shallow aquifers, exploiting morphometric parameters (together with other layers of information from existing thematic maps and remote sensing) and to reconstruct the geometry and the characteristic of shallow porous aquifer. This research is part of a larger project financed by NERC (National Environment Research Council, UK) in the framework of the program UPGRO (Unlocking the Potential of Groundwater for the Poors), with the collaboration of different partners from Italy, Senegal and Guinea

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.

Influence of delayed placement and dietary lysine levels on small intestine morphometrics and performance of broilers

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JRG Franco

2006-12-01

Full Text Available This experiment studied the influence of delayed placement (HI and digestible lysine level (DL on the morphometrics of the intestinal mucosa and on the performance of broilers. A total number of 1,705 Cobb 500 male chicks were used in a completely randomized experimental design in a factorial arrangement with four HI (12, 24, 36 and 48h, and two DL level in the starter diet (1.143 and 1.267%, with four replicates and 55 birds per experimental unit. The amino acids methionine-cystine, threonine, and tryptophan were balanced according to the ideal protein (IP concept. Small intestine morphometrics was evaluated using histology slides of the duodenum and jejunum. There was no interaction between HI and DL levels for any of the studied parameters. The 1.143% level of DL promoted better performance results at 21 and 42 days of age, as well as higher duodenum and jejunum crypt depth, and duodenum villi height at 21 days of age. HI negatively influenced the morphometrics of the small intestine during the starter phase, and the performance of broilers up to 42 days of age. There was no effect of the treatments on yolk sac utilization or abdominal fat percentage. It was concluded that the use of 1.143% DL and HI of 12 hours promoted better development of the small intestine mucosa up to 21 days of age, and broiler performance at market age.

Feature-Fusion Guidelines for Image-Based Multi-Modal Biometric Fusion

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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.

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

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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.

Geoinformatics for assessing the morphometric control on ...

Indian Academy of Sciences (India)

natural disasters are one of the serious geo-hazards, ... Natural features such as land use and land cover, soil and .... steps followed for the generation of morphometric ... language. Infiltration number. Area, perimeter, basin length, min & max.

Aneurysms of the anterior and posterior cerebral circulation: comparison of the morphometric features.

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Tykocki, Tomasz; Kostkiewicz, Bogusław

2014-09-01

Intracranial aneurysms (IAs) located in the posterior circulation are considered to have higher annual bleed rates than those in the anterior circulation. The aim of the study was to compare the morphometric factors differentiating between IAs located in the anterior and posterior cerebral circulation. A total number of 254 IAs diagnosed between 2009 and 2012 were retrospectively analyzed. All patients qualified for diagnostic, three-dimensional rotational angiography. IAs were assigned to either the anterior or posterior cerebral circulation subsets for the analysis. Means were compared with a t-test. The univariate and stepwise logistic regression analyses were used to determine the predictors of morphometric differences between the groups. For the defined predictors, ROC (receiver-operating characteristic) curves and interactive dot diagrams were calculated with the cutoff values of the morphometric factors. The number of anterior cerebral circulation IAs was 179 (70.5 %); 141 (55.5 %) aneurysms were ruptured. Significant differences between anterior and posterior circulation IAs were found for: the parent artery size (5.08 ± 1.8 mm vs. 3.95 ± 1.5 mm; p 45) and aspect ratio (AR) (1.91 ± 0.8 vs. 2.75 ± 1.8; p = 0.02). Predicting factors differentiating anterior and posterior circulation IAs were: the AR (OR = 2.20; 95 % CI 1.80-270; Is 270 correct or should it be 2.70 and parent artery size (OR = 0.44; 95 % CI 0.38-0.54). The cutoff point in the ROC curve was 2.185 for the AR and 4.89 mm for parent artery size. Aspect ratio and parent artery size were found to be predictive morphometric factors in differentiating between anterior and posterior cerebral IAs.

Multi-dimension feature fusion for action recognition

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Dong, Pei; Li, Jie; Dong, Junyu; Qi, Lin

2018-04-01

Typical human actions last several seconds and exhibit characteristic spatio-temporal structure. The challenge for action recognition is to capture and fuse the multi-dimension information in video data. In order to take into account these characteristics simultaneously, we present a novel method that fuses multiple dimensional features, such as chromatic images, depth and optical flow fields. We built our model based on the multi-stream deep convolutional networks with the help of temporal segment networks and extract discriminative spatial and temporal features by fusing ConvNets towers multi-dimension, in which different feature weights are assigned in order to take full advantage of this multi-dimension information. Our architecture is trained and evaluated on the currently largest and most challenging benchmark NTU RGB-D dataset. The experiments demonstrate that the performance of our method outperforms the state-of-the-art methods.

Morphometric analysis of craniofacial features in mono- and dizygotic twins discordant for unilateral cleft lip and palate.

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Tessler, Alexis Y; Franchi, Lorenzo; McNamara, James A; Baccetti, Tiziano

2011-09-01

To compare craniofacial differences between twins discordant for surgically repaired unilateral cleft lip and palate (CLP) during the developmental ages and to test the effect of zygosity on the shape and size of the craniofacial skeleton of the same twins by means of thin plate spline (TPS) analysis. Lateral and posteroanterior (PA) cephalometric films from 19 sets of monozygotic (MZ) twins (15 male and 4 female) and 10 dizygotic (DZ) twins (7 male and 3 female) were analyzed. TPS analysis evaluated statistically significant differences in the craniofacial shape and size between affected and unaffected twins within MZ and DZ twin couples. No statistically significant differences in craniofacial shape or size between CLP and non-CLP MZ or DZ twins were observed. The level of morphological similarity in CLP vs non-CLP MZ twins was statistically greater than in DZ twins. Morphometric analysis showed that surgically repaired CLP does not produce significant shape or size differences in the craniofacial features of MZ or DZ twins discordant for unilateral CLP.

Tile-Level Annotation of Satellite Images Using Multi-Level Max-Margin Discriminative Random Field

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Hong Sun

2013-05-01

Full Text Available This paper proposes a multi-level max-margin discriminative analysis (M3DA framework, which takes both coarse and fine semantics into consideration, for the annotation of high-resolution satellite images. In order to generate more discriminative topic-level features, the M3DA uses the maximum entropy discrimination latent Dirichlet Allocation (MedLDA model. Moreover, for improving the spatial coherence of visual words neglected by M3DA, conditional random field (CRF is employed to optimize the soft label field composed of multiple label posteriors. The framework of M3DA enables one to combine word-level features (generated by support vector machines and topic-level features (generated by MedLDA via the bag-of-words representation. The experimental results on high-resolution satellite images have demonstrated that, using the proposed method can not only obtain suitable semantic interpretation, but also improve the annotation performance by taking into account the multi-level semantics and the contextual information.

PATHOMORPHOLOGICAL FEATURES OF BONE LESIONS AND CORRELATION OF CLINICAL, LABORATORY AND MORPHOMETRIC CRITERIA IN PATIENTS WITH LATENT SCLEROSING HEMATOGENOUS OSTEOMYELITIS (GARRÉ

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V. V. Grigorovsky

2018-01-01

correlation dependencies was reported between clinical and laboratorial criteria on the one hand, and with morphometric criteria — on the other hand.Conclusion. Pathomorphological features of bone lesions in sclerosing hematogenous osteomyelitis are nonhomogeneous. Every case in the study demonstrated stereotype alterations such as substantial diffuse fibroses of marrow spaces in cancellous bone and bone regenerate, remodeling of bone tissues with gradual acceleration of osteosclerosis and persisting productive inflammation. Only in sone cases featured small sites of exudative inflammation — microabscesses with microsequestration.

Quantification of Runoff as Influenced by Morphometric Characteristics in a Rural Complex Catchment

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Abdulkareem, Jabir Haruna; Pradhan, Biswajeet; Sulaiman, Wan Nor Azmin; Jamil, Nor Rohaizah

2018-03-01

This study addresses the critical scientific question of assessing the relationship between morphometric features and the hydrological factors that increase the risk of flooding in Kelantan River basin, Malaysia. Two hypotheses were developed to achieve this aim, namely: the alternate hypothesis (runoff, is influenced by morphometric characteristics in the study watershed) and the null hypothesis (runoff is not influenced by morphometric characteristics). First, the watershed was delineated into four major catchments, namely: Galas, Pergau, Lebir, and Nenggiri. Next, quantitative morphometric characters such as linear aspects, areal aspects, and relief aspects were determined on each of these catchments. Furthermore, HEC-HMS and flood response analyses were employed to simulate the hydrological response of the catchments. From the results of morphometric analysis, profound spatial changes were observed between runoff features of Kelantan River and the morphometric characteristics. The length of overflow that was related to drainage density and constant channel maintenance was found to be 0.12 in Pergau, 0.04 in both Nenggiri and Lebir, and 0.03 in Galas. Drainage density as influenced by geology and vegetation density was found to be low in all the catchments (0.07-0.24). Results of hydrological response indicated that Lebir, Nenggiri, Galas, and Pergau recorded a flood response factor of 0.75, 0.63, 0.40, and 0.05, respectively. Therefore, Lebir and Nenggiri are more likely to be flooded during a rainstorm. There was no clear indication with regard to the catchment that emerged as the most prevailing in all the morphological features. Hence, the alternate hypothesis was affirmed. This study can be replicated in other catchments with different hydrologic setup.

A three-dimensional comparison of a morphometric and conventional cephalometric midsagittal planes for craniofacial asymmetry.

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Damstra, Janalt; Fourie, Zacharias; De Wit, Marnix; Ren, Yijin

2012-02-01

Morphometric methods are used in biology to study object symmetry in living organisms and to determine the true plane of symmetry. The aim of this study was to determine if there are clinical differences between three-dimensional (3D) cephalometric midsagittal planes used to describe craniofacial asymmetry and a true symmetry plane derived from a morphometric method based on visible facial features. The sample consisted of 14 dry skulls (9 symmetric and 5 asymmetric) with metallic markers which were imaged with cone-beam computed tomography. An error study and statistical analysis were performed to validate the morphometric method. The morphometric and conventional cephalometric planes were constructed and compared. The 3D cephalometric planes constructed as perpendiculars to the Frankfort horizontal plane resembled the morphometric plane the most in both the symmetric and asymmetric groups with mean differences of less than 1.00 mm for most variables. However, the standard deviations were often large and clinically significant for these variables. There were clinically relevant differences (>1.00 mm) between the different 3D cephalometric midsagittal planes and the true plane of symmetry determined by the visible facial features. The difference between 3D cephalometric midsagittal planes and the true plane of symmetry determined by the visible facial features were clinically relevant. Care has to be taken using cephalometric midsagittal planes for diagnosis and treatment planning of craniofacial asymmetry as they might differ from the true plane of symmetry as determined by morphometrics.

Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery

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Huang, Xin; Chen, Huijun; Gong, Jianya

2018-01-01

Spaceborne multi-angle images with a high-resolution are capable of simultaneously providing spatial details and three-dimensional (3D) information to support detailed and accurate classification of complex urban scenes. In recent years, satellite-derived digital surface models (DSMs) have been increasingly utilized to provide height information to complement spectral properties for urban classification. However, in such a way, the multi-angle information is not effectively exploited, which is mainly due to the errors and difficulties of the multi-view image matching and the inaccuracy of the generated DSM over complex and dense urban scenes. Therefore, it is still a challenging task to effectively exploit the available angular information from high-resolution multi-angle images. In this paper, we investigate the potential for classifying urban scenes based on local angular properties characterized from high-resolution ZY-3 multi-view images. Specifically, three categories of angular difference features (ADFs) are proposed to describe the angular information at three levels (i.e., pixel, feature, and label levels): (1) ADF-pixel: the angular information is directly extrapolated by pixel comparison between the multi-angle images; (2) ADF-feature: the angular differences are described in the feature domains by comparing the differences between the multi-angle spatial features (e.g., morphological attribute profiles (APs)). (3) ADF-label: label-level angular features are proposed based on a group of urban primitives (e.g., buildings and shadows), in order to describe the specific angular information related to the types of primitive classes. In addition, we utilize spatial-contextual information to refine the multi-level ADF features using superpixel segmentation, for the purpose of alleviating the effects of salt-and-pepper noise and representing the main angular characteristics within a local area. The experiments on ZY-3 multi-angle images confirm that the proposed

Multi-level learning: improving the prediction of protein, domain and residue interactions by allowing information flow between levels

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McDermott Drew

2009-08-01

Full Text Available Abstract Background Proteins interact through specific binding interfaces that contain many residues in domains. Protein interactions thus occur on three different levels of a concept hierarchy: whole-proteins, domains, and residues. Each level offers a distinct and complementary set of features for computationally predicting interactions, including functional genomic features of whole proteins, evolutionary features of domain families and physical-chemical features of individual residues. The predictions at each level could benefit from using the features at all three levels. However, it is not trivial as the features are provided at different granularity. Results To link up the predictions at the three levels, we propose a multi-level machine-learning framework that allows for explicit information flow between the levels. We demonstrate, using representative yeast interaction networks, that our algorithm is able to utilize complementary feature sets to make more accurate predictions at the three levels than when the three problems are approached independently. To facilitate application of our multi-level learning framework, we discuss three key aspects of multi-level learning and the corresponding design choices that we have made in the implementation of a concrete learning algorithm. 1 Architecture of information flow: we show the greater flexibility of bidirectional flow over independent levels and unidirectional flow; 2 Coupling mechanism of the different levels: We show how this can be accomplished via augmenting the training sets at each level, and discuss the prevention of error propagation between different levels by means of soft coupling; 3 Sparseness of data: We show that the multi-level framework compounds data sparsity issues, and discuss how this can be dealt with by building local models in information-rich parts of the data. Our proof-of-concept learning algorithm demonstrates the advantage of combining levels, and opens up

Vitamin B12 deficiency: Characterization of psychometrics and MRI morphometrics.

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Hsu, Yen-Hsuan; Huang, Ching-Feng; Lo, Chung-Ping; Wang, Tzu-Lan; Tu, Min-Chien

2016-01-01

Vitamin B12 is essential for the integrity of the central nervous system. However, performances in different cognitive domains relevant to vitamin B12 deficiency remain to be detailed. To date, there have been limited studies that examined the relationships between cognitions and structural neuroimaging in a single cohort of low-vitamin B12 status. The present study aimed to depict psychometrics and magnetic resonance imaging (MRI) morphometrics among patients with vitamin B12 deficiency, and to examine their inter-relations. We compared 34 consecutive patients with vitamin B12 deficiency (serum level ≤ 250 pg/ml) to 34 demographically matched controls by their cognitive performances and morphometric indices of brain MRI. The correlations between psychometrics and morphometrics were analyzed. The vitamin B12 deficiency group had lower scores than the controls on total scores of Mini-Mental Status Examination (MMSE) and Cognitive Abilities Screening Instrument (CASI) (both P psychometric and morphometric indices, pronounced correlations between bicaudate ratio and long-term memory, mental manipulation, orientation, language, and verbal fluency were noted (all P < 0.01). Vitamin B12 deficiency is associated with a global cognition decline with language, orientation, and mental manipulation selectively impaired. Preferential atrophy in frontal regions is the main neuroimaging feature. Although the frontal ratio highlights the relevant atrophy among patients, the bicaudate ratio might be the best index on the basis of its strong association with global cognition and related cognitive domains, implying dysfunction of fronto-subcortical circuits as the fundamental pathogenesis related to vitamin B12 deficiency.

Assessing population-level morphometric variation of the Mountain Mullet Agonostomus monticola (Teleostei: Mugilidae across its Middle American distribution

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Bertha P. Díaz-Murillo

2017-12-01

Full Text Available ABSTRACT Population-level morphometric variation of the Mountain Mullet (Agonostomus monticola was assessed in 419 adult specimens from 25 sample sites (river basins across its Middle American distribution (Pacific and Atlantic-Caribbean drainages. This analysis was based on 36 standardized linear measurements and 19 landmarks on geometric morphometrics approach. Discriminant function analysis (DFA revealed 19 linear morphological characters with significant variation among groups. Geometrically, the most notable changes were associated to the curvature of the frontal region of the head, the anterior and posterior insertion of the first dorsal and anal fins. The resulting grouping based on the DFA and geometric morphometrics techniques (Pacific-A, Pacific-B and NE México-Caribbean were similar to those previously recovered by genetic techniques, where the Pacific-B (Ayuquila river basin was the most different group. Our results provide morphological evidence for considering Agonostomus monticola as a complex of evolutionary entities, represented by two forms in the Pacific Ocean and another in the Atlantic Ocean.

Morphometric Characterization of Small Cell Lymphocytic Lymphoma

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Chisoi Anca

2014-11-01

Full Text Available The morphometry in histopathology is used to characterize cell populations belonging to different tissues and to identify differences in their parameters with prognostic implications. To achieve morphometric examination were selected 6 of 24 cases identified as small cell lymphocytic lymphoma. For each case analysis was done on five fields, for each field measuring the parameters of 20 cells. The studied parameters were for cytoplasm: cytoplasmic area, maximum and minimum cytoplasmic diameter, cytoplasmic perimeter; for nucleus were measured: nuclear area, minimum and maximum nuclear diameter, nuclear perimeter, nuclear contour index, nuclear ellipticity index, nuclear irregularity index. Also the nucleocytoplasmic ratio was calculated in all studied cases. Small cell lymphocytic lymphoma is characterized in morphometric terms having a small cytoplasmic area (average 29.206 and also a small nuclear area (mean 28.939 having a nucleo-cytoplasmic ratio appearance suggestive for adult lymphocyte. A nuclear contour index small value (3.946, ellipticity index value also small (3.521 and small nuclear irregularity index (3.965. Standard deviations, in any of the studied morphometric categories, is around or below 1 suggesting monomorphic cell appearance. These morphometric and microscopic features characterized mainly by a small population of adult lymphocytes, monomorphic, with rounded hipercromic nuclei, dense chromatin, support the framing into indolent lymphoma group in terms of clinical outcome.

Clinical, morphologic, and morphometric features of cranial thoracic spinal stenosis in large and giant breed dogs.

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Johnson, Philippa; De Risio, Luisa; Sparkes, Andrew; McConnell, Fraser; Holloway, Andrew

2012-01-01

The clinical, morphologic, and morphometric features of cranial thoracic spinal stenosis were investigated in large and giant breed dogs. Seventy-nine magnetic resonance imaging studies of the cranial thoracic spine were assessed. Twenty-six were retrieved retrospectively and 53 were acquired prospectively using the same inclusion criteria. Images were evaluated using a modified compression scale as: no osseous stenosis (grade 0), osseous stenosis without spinal cord compression (grade 1), and osseous stenosis with spinal cord compression (grade 2). Morphometric analysis was performed and compared to the subjective grading system. Grades 1 and 2 cranial thoracic spinal stenosis were identified on 24 imaging studies in 23 dogs. Sixteen of 23 dogs had a conformation typified by Molosser breeds and 21/23 were male. The most common sites of stenosis were T2-3 and T3-4. The articular process joints were enlarged with abnormal oblique orientation. Stenosis was dorsolateral, lateralized, or dorsoventral. Concurrent osseous cervical spondylomyelopathy was recognized in six dogs and other neurologic disease in five dogs. Cranial thoracic spinal stenosis was the only finding in 12 dogs. In 9 of these 12 dogs (all grade 2) neurolocalization was to the T3-L3 spinal segment. The median age of these dogs was 9.5 months. In the remaining three dogs neurologic signs were not present. Stenosis ratios were of limited benefit in detecting stenotic sites. Grade 2 cranial thoracic spinal stenosis causing direct spinal cord compression may lead to neurologic signs, however milder stenosis (grade 1) is likely to be subclinical or incidental. © 2012 Veterinary Radiology & Ultrasound.

Multi-task feature selection in microarray data by binary integer programming.

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Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

TargetCrys: protein crystallization prediction by fusing multi-view features with two-layered SVM.

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Hu, Jun; Han, Ke; Li, Yang; Yang, Jing-Yu; Shen, Hong-Bin; Yu, Dong-Jun

2016-11-01

The accurate prediction of whether a protein will crystallize plays a crucial role in improving the success rate of protein crystallization projects. A common critical problem in the development of machine-learning-based protein crystallization predictors is how to effectively utilize protein features extracted from different views. In this study, we aimed to improve the efficiency of fusing multi-view protein features by proposing a new two-layered SVM (2L-SVM) which switches the feature-level fusion problem to a decision-level fusion problem: the SVMs in the 1st layer of the 2L-SVM are trained on each of the multi-view feature sets; then, the outputs of the 1st layer SVMs, which are the "intermediate" decisions made based on the respective feature sets, are further ensembled by a 2nd layer SVM. Based on the proposed 2L-SVM, we implemented a sequence-based protein crystallization predictor called TargetCrys. Experimental results on several benchmark datasets demonstrated the efficacy of the proposed 2L-SVM for fusing multi-view features. We also compared TargetCrys with existing sequence-based protein crystallization predictors and demonstrated that the proposed TargetCrys outperformed most of the existing predictors and is competitive with the state-of-the-art predictors. The TargetCrys webserver and datasets used in this study are freely available for academic use at: http://csbio.njust.edu.cn/bioinf/TargetCrys .

Feature-based Alignment of Volumetric Multi-modal Images

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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

Multi-Stage Recognition of Speech Emotion Using Sequential Forward Feature Selection

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Liogienė Tatjana

2016-07-01

Full Text Available The intensive research of speech emotion recognition introduced a huge collection of speech emotion features. Large feature sets complicate the speech emotion recognition task. Among various feature selection and transformation techniques for one-stage classification, multiple classifier systems were proposed. The main idea of multiple classifiers is to arrange the emotion classification process in stages. Besides parallel and serial cases, the hierarchical arrangement of multi-stage classification is most widely used for speech emotion recognition. In this paper, we present a sequential-forward-feature-selection-based multi-stage classification scheme. The Sequential Forward Selection (SFS and Sequential Floating Forward Selection (SFFS techniques were employed for every stage of the multi-stage classification scheme. Experimental testing of the proposed scheme was performed using the German and Lithuanian emotional speech datasets. Sequential-feature-selection-based multi-stage classification outperformed the single-stage scheme by 12–42 % for different emotion sets. The multi-stage scheme has shown higher robustness to the growth of emotion set. The decrease in recognition rate with the increase in emotion set for multi-stage scheme was lower by 10–20 % in comparison with the single-stage case. Differences in SFS and SFFS employment for feature selection were negligible.

Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

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Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

2015-04-01

In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

Manifold regularized multi-task feature selection for multi-modality classification in Alzheimer's disease.

Science.gov (United States)

Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2013-01-01

Accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method.

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)

A Hierarchical Feature Extraction Model for Multi-Label Mechanical Patent Classification

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Jie Hu

2018-01-01

Full Text Available Various studies have focused on feature extraction methods for automatic patent classification in recent years. However, most of these approaches are based on the knowledge from experts in related domains. Here we propose a hierarchical feature extraction model (HFEM for multi-label mechanical patent classification, which is able to capture both local features of phrases as well as global and temporal semantics. First, a n-gram feature extractor based on convolutional neural networks (CNNs is designed to extract salient local lexical-level features. Next, a long dependency feature extraction model based on the bidirectional long–short-term memory (BiLSTM neural network model is proposed to capture sequential correlations from higher-level sequence representations. Then the HFEM algorithm and its hierarchical feature extraction architecture are detailed. We establish the training, validation and test datasets, containing 72,532, 18,133, and 2679 mechanical patent documents, respectively, and then check the performance of HFEMs. Finally, we compared the results of the proposed HFEM and three other single neural network models, namely CNN, long–short-term memory (LSTM, and BiLSTM. The experimental results indicate that our proposed HFEM outperforms the other compared models in both precision and recall.

MixDroid: A multi-features and multi-classifiers bagging system for Android malware detection

Science.gov (United States)

Huang, Weiqing; Hou, Erhang; Zheng, Liang; Feng, Weimiao

2018-05-01

In the past decade, Android platform has rapidly taken over the mobile market for its superior convenience and open source characteristics. However, with the popularity of Android, malwares targeting on Android devices are increasing rapidly, while the conventional rule-based and expert-experienced approaches are no longer able to handle such explosive growth. In this paper, combining with the theory of natural language processing and machine learning, we not only implement the basic feature extraction of permission application features, but also propose two innovative schemes of feature extraction: Dalvik opcode features and malicious code image, and implement an automatic Android malware detection system MixDroid which is based on multi-features and multi-classifiers. According to our experiment results on 20,000 Android applications, detection accuracy of MixDroid is 98.1%, which proves our schemes' effectiveness in Android malware detection.

BIOCHEMICAL AND MORPHOMETRIC PARAMETERS OF PRE-LARVAE OF THREE SALMONIDS SPECIES AT ONE-DAY AGE

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Ye. Barylo

2016-06-01

Full Text Available Purpose. To study and analyze the morphometric and some biochemical parameters of pre-larval brown trout, rainbow trout and brook trout in post-embryonic period under the conditions of "Rybnyi Potik” farm in the Transcarpathian region for further use of the obtained data in scientific and practical works related to the cultivation of the juveniles of valuable salmonid species. Methodology. One-day free embryos (pre-larvae of brown trout, rainbow trout and brook trout we used as study materials. Morphometric parameters we studied by the methods of N. O. Lange, E. N. Dmitrieva. The content of total lipids was determined in accordance with Folch. in the tissuesm, which were taken for biochemical studies. Separate classes of lipids were received by thin layer chromatography. Findings. We carried out a comparative analysis of morphometric measurements and biochemical parameters of one-day pre-larval brown trout, rainbow trout and brook trout based on the obtained data. We investigated morphometric and biochemical specific features of pre-larvae in post-embryonic period and showed the species differences of morphometric measurements. Significant differences were observed between the content of lipids in the body and yolk sac of free embryos. In particular, a higher content of phospholipids and triglycerides was observed in the body of brook trout compared to brown trout. We also recorded higher contents of mono- and diacylglycerols, free cholesterol, non-etherified fatty acids (NEFA, triacylglycerols and cholesterol esters in the yolk sac of brook trout. Compared to brown trout, rainbow trout had a significant increase in mono- and diacylglycerols, free cholesterol and NEFA in both body and yolk sac as well higher levels of total lipids, triacylglycerols and cholesterol esters were registered in yolk sac. Originality. For the first time we carried out and compared the specific features of pre-larval brown trout, rainbow trout and brook trout in the

Manifold Regularized Multi-Task Feature Selection for Multi-Modality Classification in Alzheimer’s Disease

Science.gov (United States)

Jie, Biao; Cheng, Bo

2014-01-01

Accurate diagnosis of Alzheimer’s disease (AD), as well as its pro-dromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method. PMID:24505676

SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

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Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

Cloud Detection by Fusing Multi-Scale Convolutional Features

Science.gov (United States)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

Modeling Multi-Level Systems

CERN Document Server

Iordache, Octavian

2011-01-01

This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale sy...

Oriented Edge-Based Feature Descriptor for Multi-Sensor Image Alignment and Enhancement

Directory of Open Access Journals (Sweden)

Myung-Ho Ju

2013-10-01

Full Text Available In this paper, we present an efficient image alignment and enhancement method for multi-sensor images. The shape of the object captured in a multi-sensor images can be determined by comparing variability of contrast using corresponding edges across multi-sensor image. Using this cue, we construct a robust feature descriptor based on the magnitudes of the oriented edges. Our proposed method enables fast image alignment by identifying matching features in multi-sensor images. We enhance the aligned multi-sensor images through the fusion of the salient regions from each image. The results of stitching the multi-sensor images and their enhancement demonstrate that our proposed method can align and enhance multi-sensor images more efficiently than previous methods.

An effective method for cirrhosis recognition based on multi-feature fusion

Science.gov (United States)

Chen, Yameng; Sun, Gengxin; Lei, Yiming; Zhang, Jinpeng

2018-04-01

Liver disease is one of the main causes of human healthy problem. Cirrhosis, of course, is the critical phase during the development of liver lesion, especially the hepatoma. Many clinical cases are still influenced by the subjectivity of physicians in some degree, and some objective factors such as illumination, scale, edge blurring will affect the judgment of clinicians. Then the subjectivity will affect the accuracy of diagnosis and the treatment of patients. In order to solve the difficulty above and improve the recognition rate of liver cirrhosis, we propose a method of multi-feature fusion to obtain more robust representations of texture in ultrasound liver images, the texture features we extract include local binary pattern(LBP), gray level co-occurrence matrix(GLCM) and histogram of oriented gradient(HOG). In this paper, we firstly make a fusion of multi-feature to recognize cirrhosis and normal liver based on parallel combination concept, and the experimental results shows that the classifier is effective for cirrhosis recognition which is evaluated by the satisfying classification rate, sensitivity and specificity of receiver operating characteristic(ROC), and cost time. Through the method we proposed, it will be helpful to improve the accuracy of diagnosis of cirrhosis and prevent the development of liver lesion towards hepatoma.

Morphometric and landsliding analyses in chain domain: the Roccella basin, NE Sicily, Italy

Science.gov (United States)

Rapisarda, Francesco

2009-10-01

The dynamic interaction of endogenic and exogenic processes in active geodynamic context leads to the deterioration of the physico-mechanical characteristics of the rocks, inducing slopes instability. In such context, the morphometric parameters and the analysis of landslide distribution contribute to appraise the evolutive state of hydrographic basins. The aim of the study is the morphometric characterization of the Roccella Torrent basin (Rtb) located in South Italy. Landsliding and tectonic structure dynamically interact with the drainage pattern that records these effects and permits the definition of the evolutive geomorphic stage of the basin. The Air Photograph Investigation and field surveys permitted to draw the main geomorphic features, the drainage pattern of the Rtb, to calculate the morphometric parameters and to delimit the landslides’ bodies. Detailed analysis about the landslide distribution within a test site 17 km2 wide were carried out to elaborate indicative indexes of the landslides type and to single out the lithotypes that are more involved in slope instability phenomena. The morphometric parameters indicate the rejuvenation state within the Rtb where the stream reaches show the effects of increased energy relief in agreement with the geological settings of this sector of the Apennine-Maghrebian Chain.

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.

Morphometric analysis of sub-watershed in parts of Western Ghats, South India using ASTER DEM

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Evangelin Ramani Sujatha

2015-05-01

Full Text Available Morphometric analysis is a key to understand the hydrological process and hence is a prerequisite for the assessment of hydrological characteristics of surface water basin. Morphometric analysis to determine the drainage characteristics of Palar sub-watershed, a part of Shanmukha watershed in the Amaravati sub-catchment is done using Advanced Space-borne Thermal Emission and Reflection Global Digital Elevation Model (ASTER GDEM data, and is supplemented with topographical maps in geographical information systems platform. This study uses ASTER GDEM data to extract morphometric features of a mountain stream at micro-watershed level. The sub-watershed is divided into six micro-watersheds. The sub-watershed includes a sixth-order stream. Lower stream orders, in particular first-order streams, dominate the sub-watershed. Development of stream segments is controlled by slope and local relief. Drainage pattern of the sub-watershed and micro-watersheds is dendritic in general. The mean bifurcation ratio of the sub-watershed is 3.69 but its variation between the various stream orders suggests structural control in the development of stream network. The shape factors reveal the elongation of the sub-watershed and micro-watersheds.The relief ratio reveals the high discharge capability of the sub-watershed and meagre groundwater potential. This study is a useful tool for planning strategies in control of soil erosion and soil conservation.

Multi-stage decoding of multi-level modulation codes

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Lin, Shu; Kasami, Tadao; Costello, Daniel J., Jr.

1991-01-01

Various types of multi-stage decoding for multi-level modulation codes are investigated. It is shown that if the component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. Particularly, it is shown that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum soft-decision decoding of the code is very small, only a fraction of dB loss in signal to noise ratio at a bit error rate (BER) of 10(exp -6).

Tensor-based Multi-view Feature Selection with Applications to Brain Diseases

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Cao, Bokai; He, Lifang; Kong, Xiangnan; Yu, Philip S.; Hao, Zhifeng; Ragin, Ann B.

2015-01-01

In the era of big data, we can easily access information from multiple views which may be obtained from different sources or feature subsets. Generally, different views provide complementary information for learning tasks. Thus, multi-view learning can facilitate the learning process and is prevalent in a wide range of application domains. For example, in medical science, measurements from a series of medical examinations are documented for each subject, including clinical, imaging, immunologic, serologic and cognitive measures which are obtained from multiple sources. Specifically, for brain diagnosis, we can have different quantitative analysis which can be seen as different feature subsets of a subject. It is desirable to combine all these features in an effective way for disease diagnosis. However, some measurements from less relevant medical examinations can introduce irrelevant information which can even be exaggerated after view combinations. Feature selection should therefore be incorporated in the process of multi-view learning. In this paper, we explore tensor product to bring different views together in a joint space, and present a dual method of tensor-based multi-view feature selection (dual-Tmfs) based on the idea of support vector machine recursive feature elimination. Experiments conducted on datasets derived from neurological disorder demonstrate the features selected by our proposed method yield better classification performance and are relevant to disease diagnosis. PMID:25937823

Morphometric Identification of Queens, Workers and Intermediates in In Vitro Reared Honey Bees (Apis mellifera).

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De Souza, Daiana A; Wang, Ying; Kaftanoglu, Osman; De Jong, David; Amdam, Gro V; Gonçalves, Lionel S; Francoy, Tiago M

2015-01-01

In vitro rearing is an important and useful tool for honey bee (Apis mellifera L.) studies. However, it often results in intercastes between queens and workers, which are normally are not seen in hive-reared bees, except when larvae older than three days are grafted for queen rearing. Morphological classification (queen versus worker or intercastes) of bees produced by this method can be subjective and generally depends on size differences. Here, we propose an alternative method for caste classification of female honey bees reared in vitro, based on weight at emergence, ovariole number, spermatheca size and size and shape, and features of the head, mandible and basitarsus. Morphological measurements were made with both traditional morphometric and geometric morphometrics techniques. The classifications were performed by principal component analysis, using naturally developed queens and workers as controls. First, the analysis included all the characters. Subsequently, a new analysis was made without the information about ovariole number and spermatheca size. Geometric morphometrics was less dependent on ovariole number and spermatheca information for caste and intercaste identification. This is useful, since acquiring information concerning these reproductive structures requires time-consuming dissection and they are not accessible when abdomens have been removed for molecular assays or in dried specimens. Additionally, geometric morphometrics divided intercastes into more discrete phenotype subsets. We conclude that morphometric geometrics are superior to traditional morphometrics techniques for identification and classification of honey bee castes and intermediates.

Agent-based model with multi-level herding for complex financial systems

Science.gov (United States)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Interconnected Levels of Multi-Stage Marketing

DEFF Research Database (Denmark)

Vedel, Mette; Geersbro, Jens; Ritter, Thomas

2012-01-01

different levels of multi-stage marketing and illustrates these stages with a case study. In addition, a triadic perspective is introduced as an analytical tool for multi-stage marketing research. The results from the case study indicate that multi-stage marketing exists on different levels. Thus, managers...... must not only decide in general on the merits of multi-stage marketing for their firm, but must also decide on which level they will engage in multi-stage marketing. The triadic perspective enables a rich and multi-dimensional understanding of how different business relationships influence each other...... in a multi-stage marketing context. This understanding assists managers in assessing and balancing different aspects of multi- stage marketing. The triadic perspective also offers avenues for further research....

Multi-level trellis coded modulation and multi-stage decoding

Science.gov (United States)

Costello, Daniel J., Jr.; Wu, Jiantian; Lin, Shu

1990-01-01

Several constructions for multi-level trellis codes are presented and many codes with better performance than previously known codes are found. These codes provide a flexible trade-off between coding gain, decoding complexity, and decoding delay. New multi-level trellis coded modulation schemes using generalized set partitioning methods are developed for Quadrature Amplitude Modulation (QAM) and Phase Shift Keying (PSK) signal sets. New rotationally invariant multi-level trellis codes which can be combined with differential encoding to resolve phase ambiguity are presented.

An Improved Rotation Forest for Multi-Feature Remote-Sensing Imagery Classification

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Yingchang Xiu

2017-11-01

Full Text Available Multi-feature, especially multi-temporal, remote-sensing data have the potential to improve land cover classification accuracy. However, sometimes it is difficult to utilize all the features efficiently. To enhance classification performance based on multi-feature imagery, an improved rotation forest, combining Principal Component Analysis (PCA and a boosting naïve Bayesian tree (NBTree, is proposed. First, feature extraction was carried out with PCA. The feature set was randomly split into several disjoint subsets; then, PCA was applied to each subset, and new training data for linear extracted features based on original training data were obtained. These steps were repeated several times. Second, based on the new training data, a boosting naïve Bayesian tree was constructed as the base classifier, which aims to achieve lower prediction error than a decision tree in the original rotation forest. At the classification phase, the improved rotation forest has two-layer voting. It first obtains several predictions through weighted voting in a boosting naïve Bayesian tree; then, the first-layer vote predicts by majority to obtain the final result. To examine the classification performance, the improved rotation forest was applied to multi-feature remote-sensing images, including MODIS Enhanced Vegetation Index (EVI imagery time series, MODIS Surface Reflectance products and ancillary data in Shandong Province for 2013. The EVI imagery time series was preprocessed using harmonic analysis of time series (HANTS to reduce the noise effects. The overall accuracy of the final classification result was 89.17%, and the Kappa coefficient was 0.71, which outperforms the original rotation forest and other classifier ensemble results, as well as the NASA land cover product. However, this new algorithm requires more computational time, meaning the efficiency needs to be further improved. Generally, the improved rotation forest has a potential advantage in

The evaluation of multi-structure, multi-atlas pelvic anatomy features in a prostate MR lymphography CAD system

Science.gov (United States)

Meijs, M.; Debats, O.; Huisman, H.

2015-03-01

In prostate cancer, the detection of metastatic lymph nodes indicates progression from localized disease to metastasized cancer. The detection of positive lymph nodes is, however, a complex and time consuming task for experienced radiologists. Assistance of a two-stage Computer-Aided Detection (CAD) system in MR Lymphography (MRL) is not yet feasible due to the large number of false positives in the first stage of the system. By introducing a multi-structure, multi-atlas segmentation, using an affine transformation followed by a B-spline transformation for registration, the organ location is given by a mean density probability map. The atlas segmentation is semi-automatically drawn with ITK-SNAP, using Active Contour Segmentation. Each anatomic structure is identified by a label number. Registration is performed using Elastix, using Mutual Information and an Adaptive Stochastic Gradient optimization. The dataset consists of the MRL scans of ten patients, with lymph nodes manually annotated in consensus by two expert readers. The feature map of the CAD system consists of the Multi-Atlas and various other features (e.g. Normalized Intensity and multi-scale Blobness). The voxel-based Gentleboost classifier is evaluated using ROC analysis with cross validation. We show in a set of 10 studies that adding multi-structure, multi-atlas anatomical structure likelihood features improves the quality of the lymph node voxel likelihood map. Multiple structure anatomy maps may thus make MRL CAD more feasible.

Middle latency response correlates of single and double deviant stimuli in a multi-feature paradigm.

Science.gov (United States)

Althen, H; Huotilainen, M; Grimm, S; Escera, C

2016-01-01

This study aimed to test single and double deviance-related modulations of the middle latency response (MLR) and the applicability of the optimum-2 multi-feature paradigm. The MLR and the MMN to frequency, intensity and double-feature deviants of an optimum-2 multi-feature paradigm and the MMN to double-feature deviants of an oddball paradigm were recorded in young adults. Double deviants elicited significant enhancements of the Nb and Pb MLR waves compared with the waves elicited by standard stimuli. These enhancements equalled approximately the sum of the numerical amplitude differences elicited by the single deviants. In contrast, the MMN to double deviants did not show such additivity. MMNs elicited by double deviants of the multi-feature and the oddball paradigm showed no significant difference in amplitude or latency. The optimum-2 multi-feature paradigm is suitable for recording double deviance-related modulations of the MLR. Interspersed intensity and frequency deviants in the standard trace of the optimum-2 condition multi-feature paradigm did not weaken the double MMN. The optimum-2 multi-feature paradigm could be especially beneficial for clinical studies on early deviance-related modulations in the MLR, due to its optimized utilization of the recording time. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Quantitative diagnosis of bladder cancer by morphometric analysis of HE images

Science.gov (United States)

Wu, Binlin; Nebylitsa, Samantha V.; Mukherjee, Sushmita; Jain, Manu

2015-02-01

In clinical practice, histopathological analysis of biopsied tissue is the main method for bladder cancer diagnosis and prognosis. The diagnosis is performed by a pathologist based on the morphological features in the image of a hematoxylin and eosin (HE) stained tissue sample. This manuscript proposes algorithms to perform morphometric analysis on the HE images, quantify the features in the images, and discriminate bladder cancers with different grades, i.e. high grade and low grade. The nuclei are separated from the background and other types of cells such as red blood cells (RBCs) and immune cells using manual outlining, color deconvolution and image segmentation. A mask of nuclei is generated for each image for quantitative morphometric analysis. The features of the nuclei in the mask image including size, shape, orientation, and their spatial distributions are measured. To quantify local clustering and alignment of nuclei, we propose a 1-nearest-neighbor (1-NN) algorithm which measures nearest neighbor distance and nearest neighbor parallelism. The global distributions of the features are measured using statistics of the proposed parameters. A linear support vector machine (SVM) algorithm is used to classify the high grade and low grade bladder cancers. The results show using a particular group of nuclei such as large ones, and combining multiple parameters can achieve better discrimination. This study shows the proposed approach can potentially help expedite pathological diagnosis by triaging potentially suspicious biopsies.

Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification.

Science.gov (United States)

Zhang, Yong; Gong, Dun-Wei; Cheng, Jian

2017-01-01

Feature selection is an important data-preprocessing technique in classification problems such as bioinformatics and signal processing. Generally, there are some situations where a user is interested in not only maximizing the classification performance but also minimizing the cost that may be associated with features. This kind of problem is called cost-based feature selection. However, most existing feature selection approaches treat this task as a single-objective optimization problem. This paper presents the first study of multi-objective particle swarm optimization (PSO) for cost-based feature selection problems. The task of this paper is to generate a Pareto front of nondominated solutions, that is, feature subsets, to meet different requirements of decision-makers in real-world applications. In order to enhance the search capability of the proposed algorithm, a probability-based encoding technology and an effective hybrid operator, together with the ideas of the crowding distance, the external archive, and the Pareto domination relationship, are applied to PSO. The proposed PSO-based multi-objective feature selection algorithm is compared with several multi-objective feature selection algorithms on five benchmark datasets. Experimental results show that the proposed algorithm can automatically evolve a set of nondominated solutions, and it is a highly competitive feature selection method for solving cost-based feature selection problems.

Multi-stage decoding for multi-level block modulation codes

Science.gov (United States)

Lin, Shu

1991-01-01

In this paper, we investigate various types of multi-stage decoding for multi-level block modulation codes, in which the decoding of a component code at each stage can be either soft-decision or hard-decision, maximum likelihood or bounded-distance. Error performance of codes is analyzed for a memoryless additive channel based on various types of multi-stage decoding, and upper bounds on the probability of an incorrect decoding are derived. Based on our study and computation results, we find that, if component codes of a multi-level modulation code and types of decoding at various stages are chosen properly, high spectral efficiency and large coding gain can be achieved with reduced decoding complexity. In particular, we find that the difference in performance between the suboptimum multi-stage soft-decision maximum likelihood decoding of a modulation code and the single-stage optimum decoding of the overall code is very small: only a fraction of dB loss in SNR at the probability of an incorrect decoding for a block of 10(exp -6). Multi-stage decoding of multi-level modulation codes really offers a way to achieve the best of three worlds, bandwidth efficiency, coding gain, and decoding complexity.

Multi level configuration of ETO products

DEFF Research Database (Denmark)

Petersen, Thomas Ditlev; Jørgensen, Kaj Asbjørn; Hvolby, Hans-Henrik

2007-01-01

The paper introduces and defines central concepts related to multi level configuration and analyzes which challenges an engineer to order company must deal with to be able to realize a multi level configuration system. It is argued that high flexibility can be achieved and focus can be directed...... in certain business processes if a multi level configuration system is realized....

Morphological and morphometric features of nematode-cysts in Gymnotus inaequilabiatus liver in the Brazilian Pantanal.

Science.gov (United States)

Galindo, Gizela Melina; Rodrigues, Robson Andrade; Marcondes, Sandriely Fernanda; Soares, Priscilla; Tavares, Luiz Eduardo Roland; Fernandes, Carlos Eurico

2017-01-01

The aim of this study was to determine the morphometric measures and morphological aspects of nematode-cysts in Gymnotus inaequilabiatus, and the presence of melanomacrophage centers (MMCs) associated with the periphery of cysts and in the liver parenchyma. Adult specimens, 34 female (123.1 ± 43.9g) and 45 male (135.5 ± 43.4g), from Paraguay River, Corumbá, Brazil, were used. The number of nematode-cysts was determined in 79 livers and 25 of them randomly selected for histopathological analysis and morphometric measures of nematode-cysts (mean diameter, thickness of collagen layer, and cyst-wall layer). The percentage of cysts with MMCs on the periphery and density in the liver parenchyma was estimated. The average number of macroscopic cysts was of 48.7 ± 2.78. Granulomatous reaction was observed surrounding the cysts. Diameter, collagen layer and cyst-wall measurements were 293.0 ± 75.18 (µm), 17.72 ± 6.01 (µm) and 12.21 ± 9.51 (µm), respectively. The number of nematode-cysts was correlated with hepatosomatic index, (r=0.26, Pcyst diameter (r=0.62, Pnematode-cysts number. Morphological characteristics of hepatic tissue and cysts-nematodes measures suggest that G. inaequilabiatus acts as a paratenic host to nematodes in the larval stage.

Morphometric and Histological Study of Osteophytes in Human Cadaveric Lumbar Vertebrae

Directory of Open Access Journals (Sweden)

Ashwini Aithal Padur

2017-10-01

Full Text Available Introduction: Osteophytes are bony outgrowth on the vertebral column. Its prevalence in the lumbar region and clinical importance mandates to conduct a detailed study of lumbar osteophytes in the cadaveric vertebral column. Aim: The present study was conducted to study the detailed features of lumbar osteophytes and document its prevalence, morphometric and histological structure. Materials and Methods: This was an observational study in which frequency of occurrence of lumbar osteophytes was studied in 40 cadaveric vertebral columns over a period of four years. The lumbar part of the vertebral columns was dissected and examined meticulously. The occurrence of lumbar osteophytes with their vertebral levels and morphometric measurements were recorded. A small excision of the osteophyte was processed histologically to study its microscopic details using routine Haematoxylin & Eosin stain. Results: Lumbar osteophytes were present in 4 specimens (10%. They were mostly found on the right side of the vertebral bodies. Histopathological examination of the osteophytes revealed degenerative osteophytic cartilage and fibrillation overlying the trabecular bone enclosing fatty marrow spaces containing haematopoietic elements. Conclusion: Lumbar osteophytes were found in 10% of the specimens studied and it is assumed that these cadaveric reports deserve further attention given their potential clinical implications. Knowledge regarding occurrence and incidence of osteophytes is essential for management of common degenerative changes of the vertebral column.

Sperm kinematic, head morphometric and kinetic-morphometric subpopulations in the blue fox (Alopex lagopus

Directory of Open Access Journals (Sweden)

Carles Soler

2017-01-01

Full Text Available This work provides information on the blue fox ejaculated sperm quality needed for seminal dose calculations. Twenty semen samples, obtained by masturbation, were analyzed for kinematic and morphometric parameters by using CASA-Mot and CASA-Morph system and principal component (PC analysis. For motility, eight kinematic parameters were evaluated, which were reduced to PC1, related to linear variables, and PC2, related to oscillatory movement. The whole population was divided into three independent subpopulations: SP1, fast cells with linear movement; SP2, slow cells and nonoscillatory motility; and SP3, medium speed cells and oscillatory movement. In almost all cases, the subpopulation distribution by animal was significantly different. Head morphology analysis generated four size and four shape parameters, which were reduced to PC1, related to size, and PC2, related to shape of the cells. Three morphometric subpopulations existed: SP1: large oval cells; SP2: medium size elongated cells; and SP3: small and short cells. The subpopulation distribution differed between animals. Combining the kinematic and morphometric datasets produced PC1, related to morphometric parameters, and PC2, related to kinematics, which generated four sperm subpopulations - SP1: high oscillatory motility, large and short heads; SP2: medium velocity with small and short heads; SP3: slow motion small and elongated cells; and SP4: high linear speed and large elongated cells. Subpopulation distribution was different in all animals. The establishment of sperm subpopulations from kinematic, morphometric, and combined variables not only improves the well-defined fox semen characteristics and offers a good conceptual basis for fertility and sperm preservation techniques in this species, but also opens the door to use this approach in other species, included humans.

Multi-Level Secure Local Area Network

OpenAIRE

Naval Postgraduate School (U.S.); Center for Information Systems Studies Security and Research (CISR)

2011-01-01

Multi-Level Secure Local Area Network is a cost effective, multi-level, easy to use office environment leveraging existing high assurance technology. The Department of Defense and U.S. Government have an identified need to securely share information classified at differing security levels. Because there exist no commercial solutions to this problem, NPS is developing a MLS LAN. The MLS LAN extends high assurance capabilities of an evaluated multi-level secure system to commercial personal com...

A SCHEME FOR TEMPLATE SECURITY AT FEATURE FUSION LEVEL IN MULTIMODAL BIOMETRIC SYSTEM

Directory of Open Access Journals (Sweden)

Arvind Selwal

2016-09-01

Full Text Available Biometric is the science of human recognition based upon using their biological, chemical or behavioural traits. These systems are used in many real life applications simply from biometric based attendance system to providing security at very sophisticated level. A biometric system deals with raw data captured using a sensor and feature template extracted from raw image. One of the challenges being faced by designers of these systems is to secure template data extracted from the biometric modalities of the user and protect the raw images. To minimize spoof attacks on biometric systems by unauthorised users one of the solutions is to use multi-biometric systems. Multi-modal biometric system works by using fusion technique to merge feature templates generated from different modalities of the human. In this work a new scheme is proposed to secure template during feature fusion level. Scheme is based on union operation of fuzzy relations of templates of modalities during fusion process of multimodal biometric systems. This approach serves dual purpose of feature fusion as well as transformation of templates into a single secured non invertible template. The proposed technique is cancelable and experimentally tested on a bimodal biometric system comprising of fingerprint and hand geometry. Developed scheme removes the problem of an attacker learning the original minutia position in fingerprint and various measurements of hand geometry. Given scheme provides improved performance of the system with reduction in false accept rate and improvement in genuine accept rate.

AN AUTOMATIC OPTICAL AND SAR IMAGE REGISTRATION METHOD USING ITERATIVE MULTI-LEVEL AND REFINEMENT MODEL

Directory of Open Access Journals (Sweden)

C. Xu

2016-06-01

Full Text Available Automatic image registration is a vital yet challenging task, particularly for multi-sensor remote sensing images. Given the diversity of the data, it is unlikely that a single registration algorithm or a single image feature will work satisfactorily for all applications. Focusing on this issue, the mainly contribution of this paper is to propose an automatic optical-to-SAR image registration method using –level and refinement model: Firstly, a multi-level strategy of coarse-to-fine registration is presented, the visual saliency features is used to acquire coarse registration, and then specific area and line features are used to refine the registration result, after that, sub-pixel matching is applied using KNN Graph. Secondly, an iterative strategy that involves adaptive parameter adjustment for re-extracting and re-matching features is presented. Considering the fact that almost all feature-based registration methods rely on feature extraction results, the iterative strategy improve the robustness of feature matching. And all parameters can be automatically and adaptively adjusted in the iterative procedure. Thirdly, a uniform level set segmentation model for optical and SAR images is presented to segment conjugate features, and Voronoi diagram is introduced into Spectral Point Matching (VSPM to further enhance the matching accuracy between two sets of matching points. Experimental results show that the proposed method can effectively and robustly generate sufficient, reliable point pairs and provide accurate registration.

Pixel-Level Deep Segmentation: Artificial Intelligence Quantifies Muscle on Computed Tomography for Body Morphometric Analysis.

Science.gov (United States)

Lee, Hyunkwang; Troschel, Fabian M; Tajmir, Shahein; Fuchs, Georg; Mario, Julia; Fintelmann, Florian J; Do, Synho

2017-08-01

Pretreatment risk stratification is key for personalized medicine. While many physicians rely on an "eyeball test" to assess whether patients will tolerate major surgery or chemotherapy, "eyeballing" is inherently subjective and difficult to quantify. The concept of morphometric age derived from cross-sectional imaging has been found to correlate well with outcomes such as length of stay, morbidity, and mortality. However, the determination of the morphometric age is time intensive and requires highly trained experts. In this study, we propose a fully automated deep learning system for the segmentation of skeletal muscle cross-sectional area (CSA) on an axial computed tomography image taken at the third lumbar vertebra. We utilized a fully automated deep segmentation model derived from an extended implementation of a fully convolutional network with weight initialization of an ImageNet pre-trained model, followed by post processing to eliminate intramuscular fat for a more accurate analysis. This experiment was conducted by varying window level (WL), window width (WW), and bit resolutions in order to better understand the effects of the parameters on the model performance. Our best model, fine-tuned on 250 training images and ground truth labels, achieves 0.93 ± 0.02 Dice similarity coefficient (DSC) and 3.68 ± 2.29% difference between predicted and ground truth muscle CSA on 150 held-out test cases. Ultimately, the fully automated segmentation system can be embedded into the clinical environment to accelerate the quantification of muscle and expanded to volume analysis of 3D datasets.

Multi-level damage identification with response reconstruction

Science.gov (United States)

Zhang, Chao-Dong; Xu, You-Lin

2017-10-01

Damage identification through finite element (FE) model updating usually forms an inverse problem. Solving the inverse identification problem for complex civil structures is very challenging since the dimension of potential damage parameters in a complex civil structure is often very large. Aside from enormous computation efforts needed in iterative updating, the ill-condition and non-global identifiability features of the inverse problem probably hinder the realization of model updating based damage identification for large civil structures. Following a divide-and-conquer strategy, a multi-level damage identification method is proposed in this paper. The entire structure is decomposed into several manageable substructures and each substructure is further condensed as a macro element using the component mode synthesis (CMS) technique. The damage identification is performed at two levels: the first is at macro element level to locate the potentially damaged region and the second is over the suspicious substructures to further locate as well as quantify the damage severity. In each level's identification, the damage searching space over which model updating is performed is notably narrowed down, not only reducing the computation amount but also increasing the damage identifiability. Besides, the Kalman filter-based response reconstruction is performed at the second level to reconstruct the response of the suspicious substructure for exact damage quantification. Numerical studies and laboratory tests are both conducted on a simply supported overhanging steel beam for conceptual verification. The results demonstrate that the proposed multi-level damage identification via response reconstruction does improve the identification accuracy of damage localization and quantization considerably.

A web-system of virtual morphometric globes

Science.gov (United States)

Florinsky, Igor; Garov, Andrei; Karachevtseva, Irina

2017-04-01

Virtual globes — programs implementing interactive three-dimensional (3D) models of planets — are increasingly used in geo- and planetary sciences. We develop a web-system of virtual morphometric globes. As the initial data, we used the following global digital elevation models (DEMs): (1) a DEM of the Earth extracted from SRTM30_PLUS database; (2) a DEM of Mars extracted from the Mars Orbiter Laser Altimeter (MOLA) gridded data record archive; and (3) A DEM of the Moon extracted from the Lunar Orbiter Laser Altimeter (LOLA) gridded data record archive. From these DEMs, we derived global digital models of the following 16 local, nonlocal, and combined morphometric variables: horizontal curvature, vertical curvature, mean curvature, Gaussian curvature, minimal curvature, maximal curvature, unsphericity curvature, difference curvature, vertical excess curvature, horizontal excess curvature, ring curvature, accumulation curvature, catchment area, dispersive area, topographic index, and stream power index (definitions, formulae, and interpretations can be found elsewhere [1]). To calculate local morphometric variables, we applied a finite-difference method intended for spheroidal equal angular grids [1]. Digital models of a nonlocal and combined morphometric variables were derived by a method of Martz and de Jong adapted to spheroidal equal angular grids [1]. DEM processing was performed in the software LandLord [1]. The calculated morphometric models were integrated into the testing version of the system. The following main functions are implemented in the system: (1) selection of a celestial body; (2) selection of a morphometric variable; (3) 2D visualization of a calculated global morphometric model (a map in equirectangular projection); (4) 3D visualization of a calculated global morphometric model on the sphere surface (a globe by itself); (5) change of a globe scale (zooming); and (6) globe rotation by an arbitrary angle. The testing version of the system

Machine Learning for Nuclear Mechano-Morphometric Biomarkers in Cancer Diagnosis.

Science.gov (United States)

Radhakrishnan, Adityanarayanan; Damodaran, Karthik; Soylemezoglu, Ali C; Uhler, Caroline; Shivashankar, G V

2017-12-20

Current cancer diagnosis employs various nuclear morphometric measures. While these have allowed accurate late-stage prognosis, early diagnosis is still a major challenge. Recent evidence highlights the importance of alterations in mechanical properties of single cells and their nuclei as critical drivers for the onset of cancer. We here present a method to detect subtle changes in nuclear morphometrics at single-cell resolution by combining fluorescence imaging and deep learning. This assay includes a convolutional neural net pipeline and allows us to discriminate between normal and human breast cancer cell lines (fibrocystic and metastatic states) as well as normal and cancer cells in tissue slices with high accuracy. Further, we establish the sensitivity of our pipeline by detecting subtle alterations in normal cells when subjected to small mechano-chemical perturbations that mimic tumor microenvironments. In addition, our assay provides interpretable features that could aid pathological inspections. This pipeline opens new avenues for early disease diagnostics and drug discovery.

An improved feature extraction algorithm based on KAZE for multi-spectral image

Science.gov (United States)

Yang, Jianping; Li, Jun

2018-02-01

Multi-spectral image contains abundant spectral information, which is widely used in all fields like resource exploration, meteorological observation and modern military. Image preprocessing, such as image feature extraction and matching, is indispensable while dealing with multi-spectral remote sensing image. Although the feature matching algorithm based on linear scale such as SIFT and SURF performs strong on robustness, the local accuracy cannot be guaranteed. Therefore, this paper proposes an improved KAZE algorithm, which is based on nonlinear scale, to raise the number of feature and to enhance the matching rate by using the adjusted-cosine vector. The experiment result shows that the number of feature and the matching rate of the improved KAZE are remarkably than the original KAZE algorithm.

Vibration and acoustic frequency spectra for industrial process modeling using selective fusion multi-condition samples and multi-source features

Science.gov (United States)

Tang, Jian; Qiao, Junfei; Wu, ZhiWei; Chai, Tianyou; Zhang, Jian; Yu, Wen

2018-01-01

Frequency spectral data of mechanical vibration and acoustic signals relate to difficult-to-measure production quality and quantity parameters of complex industrial processes. A selective ensemble (SEN) algorithm can be used to build a soft sensor model of these process parameters by fusing valued information selectively from different perspectives. However, a combination of several optimized ensemble sub-models with SEN cannot guarantee the best prediction model. In this study, we use several techniques to construct mechanical vibration and acoustic frequency spectra of a data-driven industrial process parameter model based on selective fusion multi-condition samples and multi-source features. Multi-layer SEN (MLSEN) strategy is used to simulate the domain expert cognitive process. Genetic algorithm and kernel partial least squares are used to construct the inside-layer SEN sub-model based on each mechanical vibration and acoustic frequency spectral feature subset. Branch-and-bound and adaptive weighted fusion algorithms are integrated to select and combine outputs of the inside-layer SEN sub-models. Then, the outside-layer SEN is constructed. Thus, "sub-sampling training examples"-based and "manipulating input features"-based ensemble construction methods are integrated, thereby realizing the selective information fusion process based on multi-condition history samples and multi-source input features. This novel approach is applied to a laboratory-scale ball mill grinding process. A comparison with other methods indicates that the proposed MLSEN approach effectively models mechanical vibration and acoustic signals.

A Container-based Trusted Multi-level Security Mechanism

Directory of Open Access Journals (Sweden)

Li Xiao-Yong

2017-01-01

Full Text Available Multi-level security mechanism has been widely applied in the military, government, defense and other domains in which information is required to be divided by security-level. Through this type of security mechanism, users at different security levels are provided with information at corresponding security levels. Traditional multi-level security mechanism which depends on the safety of operating system finally proved to be not practical. We propose a container-based trusted multi-level security mechanism in this paper to improve the applicability of the multi-level mechanism. It guarantees multi-level security of the system through a set of multi-level security policy rules and trusted techniques. The technical feasibility and application scenarios are also discussed. The ease of realization, strong practical significance and low cost of our method will largely expand the application of multi-level security mechanism in real life.

Morphometric and Histological Study of Osteophytes in Human Cadaveric Lumbar Vertebrae

OpenAIRE

Ashwini Aithal Padur; Naveen Kumar; Swamy Ravindra Shanthakumar; Arijit Bishnu

2017-01-01

Introduction: Osteophytes are bony outgrowth on the vertebral column. Its prevalence in the lumbar region and clinical importance mandates to conduct a detailed study of lumbar osteophytes in the cadaveric vertebral column. Aim: The present study was conducted to study the detailed features of lumbar osteophytes and document its prevalence, morphometric and histological structure. Materials and Methods: This was an observational study in which frequency of occurrence of lumbar osteophyt...

Use of the discriminant Fourier-derived cepstrum with feature-level post-processing for surface electromyographic signal classification

International Nuclear Information System (INIS)

Chen, Xinpu; Zhu, Xiangyang; Zhang, Dingguo

2009-01-01

Myoelectrical pattern classification is a crucial part in multi-functional prosthesis control. This paper investigates a discriminant Fourier-derived cepstrum (DFC) and feature-level post-processing (FLPP) to discriminate hand and wrist motions using the surface electromyographic signal. The Fourier-derived cepstrum takes advantage of the Fourier magnitude or sub-band power energy of signals directly and provides flexible use of spectral information changing with different motions. Appropriate cepstral coefficients are selected by a proposed separability criterion to construct DFC features. For the post-processing, FLPP which combines features from several analysis windows is used to improve the feature performance further. In this work, two classifiers (a linear discriminant classifier and quadratic discriminant classifier) without hyper-parameter optimization are employed to simplify the training procedure and avoid the possible bias of feature evaluation. Experimental results of the 11-motion problem show that the proposed DFC feature outperforms traditional features such as time-domain statistics and autoregressive-derived cepstrum in terms of the classification accuracy, and it is a promising method for the multi-functionality and high-accuracy control of myoelectric prostheses

Morphometric analysis of peroxisome proliferation by phthalate esters in rat liver

NARCIS (Netherlands)

Dormans JAMA; Jansen EHJM; de Vlugt-van den Koedijk FM; Riool-Nesselaar G

1992-01-01

Morphometric analysis was performed on liver sections of rats at light (LM) and electron microscopical (EM) level to demonstrate proliferation of peroxisomes after administration of di (2-ethylhexyl)phthalate at dietary levels of 0, 60, 200, 600, 2000 and 6000 mg/kg diet for 2 weeks. Enzyme

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.

Multi-Level Model

Directory of Open Access Journals (Sweden)

Constanta Nicoleta BODEA

2008-01-01

Full Text Available Is an original paper, which contains a hierarchical model with three levels, for determining the linearized non-homogeneous and homogeneous credibility premiums at company level, at sector level and at contract level, founded on the relevant covariance relations between the risk premium, the observations and the weighted averages. We give a rather explicit description of the input data for the multi- level hierarchical model used, only to show that in practical situations, there will always be enough data to apply credibility theory to a real insurance portfolio.

Feature Selection using Multi-objective Genetic Algorith m: A Hybrid Approach

OpenAIRE

Ahuja, Jyoti; GJUST - Guru Jambheshwar University of Sciecne and Technology; Ratnoo, Saroj Dahiya; GJUST - Guru Jambheshwar University of Sciecne and Technology

2015-01-01

Feature selection is an important pre-processing task for building accurate and comprehensible classification models. Several researchers have applied filter, wrapper or hybrid approaches using genetic algorithms which are good candidates for optimization problems that involve large search spaces like in the case of feature selection. Moreover, feature selection is an inherently multi-objective problem with many competing objectives involving size, predictive power and redundancy of the featu...

Variability of morphometric parameters of human trabecular tissue from coxo-arthritis and osteoporotic samples

Directory of Open Access Journals (Sweden)

Franco Marinozzi

2012-01-01

Full Text Available Morphometric and architectural bone parameters change in diseases such as osteoarthritis and osteoporosis. The mechanical strength of bone is primarily influenced by bone quantity and quality. Bone quality is defined by parameters such as trabecular thickness, trabecular separation, trabecular density and degree of anisotropy that describe the micro-architectural structure of bone. Recently, many studies have validated microtomography as a valuable investigative technique to assess bone morphometry, thanks to micro-CT non-destructive, non-invasive and reliability features, in comparison to traditional techniques such as histology. The aim of this study is the analysis by micro-computed tomography of six specimens, extracted from patients affected by osteoarthritis and osteoporosis, in order to observe the tridimensional structure and calculate several morphometric parameters.

Geometric morphometrics in primatology: craniofacial variation in Homo sapiens and Pan troglodytes.

Science.gov (United States)

Lynch, J M; Wood, C G; Luboga, S A

1996-01-01

Traditionally, morphometric studies have relied on statistical analysis of distances, angles or ratios to investigate morphometric variation among taxa. Recently, geometric techniques have been developed for the direct analysis of landmark data. In this paper, we offer a summary (with examples) of three of these newer techniques, namely shape coordinate, thin-plate spline and relative warp analyses. Shape coordinate analysis detected significant craniofacial variation between 4 modern human populations, with African and Australian Aboriginal specimens being relatively prognathous compared with their Eurasian counterparts. In addition, the Australian specimens exhibited greater basicranial flexion than all other samples. The observed relationships between size and craniofacial shape were weak. The decomposition of shape variation into affine and non-affine components is illustrated via a thin-plate spline analysis of Homo and Pan cranial landmarks. We note differences between Homo and Pan in the degree of prognathism and basicranial flexion and the position and orientation of the foramen magnum. We compare these results with previous studies of these features in higher primates and discuss the utility of geometric morphometrics as a tool in primatology and physical anthropology. We conclude that many studies of morphological variation, both within and between taxa, would benefit from the graphical nature of these techniques.

Topological Data Analysis as a Morphometric Method: Using Persistent Homology to Demarcate a Leaf Morphospace

Directory of Open Access Journals (Sweden)

Mao Li

2018-04-01

Full Text Available Current morphometric methods that comprehensively measure shape cannot compare the disparate leaf shapes found in seed plants and are sensitive to processing artifacts. We explore the use of persistent homology, a topological method applied as a filtration across simplicial complexes (or more simply, a method to measure topological features of spaces across different spatial resolutions, to overcome these limitations. The described method isolates subsets of shape features and measures the spatial relationship of neighboring pixel densities in a shape. We apply the method to the analysis of 182,707 leaves, both published and unpublished, representing 141 plant families collected from 75 sites throughout the world. By measuring leaves from throughout the seed plants using persistent homology, a defined morphospace comparing all leaves is demarcated. Clear differences in shape between major phylogenetic groups are detected and estimates of leaf shape diversity within plant families are made. The approach predicts plant family above chance. The application of a persistent homology method, using topological features, to measure leaf shape allows for a unified morphometric framework to measure plant form, including shapes, textures, patterns, and branching architectures.

Morphological and morphometric features of nematode-cysts in Gymnotus inaequilabiatus liver in the Brazilian Pantanal

Directory of Open Access Journals (Sweden)

Gizela Melina Galindo

2017-08-01

Full Text Available Abstract The aim of this study was to determine the morphometric measures and morphological aspects of nematode-cysts in Gymnotus inaequilabiatus, and the presence of melanomacrophage centers (MMCs associated with the periphery of cysts and in the liver parenchyma. Adult specimens, 34 female (123.1 ± 43.9g and 45 male (135.5 ± 43.4g, from Paraguay River, Corumbá, Brazil, were used. The number of nematode-cysts was determined in 79 livers and 25 of them randomly selected for histopathological analysis and morphometric measures of nematode-cysts (mean diameter, thickness of collagen layer, and cyst-wall layer. The percentage of cysts with MMCs on the periphery and density in the liver parenchyma was estimated. The average number of macroscopic cysts was of 48.7 ± 2.78. Granulomatous reaction was observed surrounding the cysts. Diameter, collagen layer and cyst-wall measurements were 293.0 ± 75.18 (µm, 17.72 ± 6.01 (µm and 12.21 ± 9.51 (µm, respectively. The number of nematode-cysts was correlated with hepatosomatic index, (r=0.26, P<0.05. Collagen layer was correlated with cyst diameter (r=0.62, P<0.01. Pericystic and parenchymatous MMCs were moderately (r=0.48 and highly (r=0.90 correlated with nematode-cysts number. Morphological characteristics of hepatic tissue and cysts-nematodes measures suggest that G. inaequilabiatus acts as a paratenic host to nematodes in the larval stage.

Hydrological inferences through morphometric analysis of lower Kosi river basin of India for water resource management based on remote sensing data

Science.gov (United States)

Rai, Praveen Kumar; Chandel, Rajeev Singh; Mishra, Varun Narayan; Singh, Prafull

2018-03-01

Satellite based remote sensing technology has proven to be an effectual tool in analysis of drainage networks, study of surface morphological features and their correlation with groundwater management prospect at basin level. The present study highlights the effectiveness and advantage of remote sensing and GIS-based analysis for quantitative and qualitative assessment of flood plain region of lower Kosi river basin based on morphometric analysis. In this study, ASTER DEM is used to extract the vital hydrological parameters of lower Kosi river basin in ARC GIS software. Morphometric parameters, e.g., stream order, stream length, bifurcation ratio, drainage density, drainage frequency, drainage texture, form factor, circularity ratio, elongation ratio, etc., have been calculated for the Kosi basin and their hydrological inferences were discussed. Most of the morphometric parameters such as bifurcation ratio, drainage density, drainage frequency, drainage texture concluded that basin has good prospect for water management program for various purposes and also generated data base that can provide scientific information for site selection of water-harvesting structures and flood management activities in the basin. Land use land cover (LULC) of the basin were also prepared from Landsat data of 2005, 2010 and 2015 to assess the change in dynamic of the basin and these layers are very noteworthy for further watershed prioritization.

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...

Generating description with multi-feature fusion and saliency maps of image

Science.gov (United States)

Liu, Lisha; Ding, Yuxuan; Tian, Chunna; Yuan, Bo

2018-04-01

Generating description for an image can be regard as visual understanding. It is across artificial intelligence, machine learning, natural language processing and many other areas. In this paper, we present a model that generates description for images based on RNN (recurrent neural network) with object attention and multi-feature of images. The deep recurrent neural networks have excellent performance in machine translation, so we use it to generate natural sentence description for images. The proposed method uses single CNN (convolution neural network) that is trained on ImageNet to extract image features. But we think it can not adequately contain the content in images, it may only focus on the object area of image. So we add scene information to image feature using CNN which is trained on Places205. Experiments show that model with multi-feature extracted by two CNNs perform better than which with a single feature. In addition, we make saliency weights on images to emphasize the salient objects in images. We evaluate our model on MSCOCO based on public metrics, and the results show that our model performs better than several state-of-the-art methods.

Wearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang Transform.

Science.gov (United States)

Xu, Huile; Liu, Jinyi; Hu, Haibo; Zhang, Yi

2016-12-02

Wearable sensors-based human activity recognition introduces many useful applications and services in health care, rehabilitation training, elderly monitoring and many other areas of human interaction. Existing works in this field mainly focus on recognizing activities by using traditional features extracted from Fourier transform (FT) or wavelet transform (WT). However, these signal processing approaches are suitable for a linear signal but not for a nonlinear signal. In this paper, we investigate the characteristics of the Hilbert-Huang transform (HHT) for dealing with activity data with properties such as nonlinearity and non-stationarity. A multi-features extraction method based on HHT is then proposed to improve the effect of activity recognition. The extracted multi-features include instantaneous amplitude (IA) and instantaneous frequency (IF) by means of empirical mode decomposition (EMD), as well as instantaneous energy density (IE) and marginal spectrum (MS) derived from Hilbert spectral analysis. Experimental studies are performed to verify the proposed approach by using the PAMAP2 dataset from the University of California, Irvine for wearable sensors-based activity recognition. Moreover, the effect of combining multi-features vs. a single-feature are investigated and discussed in the scenario of a dependent subject. The experimental results show that multi-features combination can further improve the performance measures. Finally, we test the effect of multi-features combination in the scenario of an independent subject. Our experimental results show that we achieve four performance indexes: recall, precision, F-measure, and accuracy to 0.9337, 0.9417, 0.9353, and 0.9377 respectively, which are all better than the achievements of related works.

Multi-level decision making models, methods and applications

CERN Document Server

Zhang, Guangquan; Gao, Ya

2015-01-01

This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.  

Multi-task feature learning by using trace norm regularization

Directory of Open Access Journals (Sweden)

Jiangmei Zhang

2017-11-01

Full Text Available Multi-task learning can extract the correlation of multiple related machine learning problems to improve performance. This paper considers applying the multi-task learning method to learn a single task. We propose a new learning approach, which employs the mixture of expert model to divide a learning task into several related sub-tasks, and then uses the trace norm regularization to extract common feature representation of these sub-tasks. A nonlinear extension of this approach by using kernel is also provided. Experiments conducted on both simulated and real data sets demonstrate the advantage of the proposed approach.

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.

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.

The sound of music: Differentiating musicians using a fast, musical multi-feature mismatch negativity paradigm

DEFF Research Database (Denmark)

Vuust, Peter; Brattico, Elvira; Seppänen, Miia

2012-01-01

to the other deviants in jazz musicians and left lateralization of the MMN to timbre in classical musicians. These findings indicate that the characteristics of the style/genre of music played by musicians influence their perceptual skills and the brain processing of sound features embedded in a musical......Musicians' skills in auditory processing depend highly on instrument, performance practice, and on level of expertise. Yet, it is not known though whether the style/genre of music might shape auditory processing in the brains of musicians. Here, we aimed at tackling the role of musical style....../genre on modulating neural and behavioral responses to changes in musical features. Using a novel, fast and musical sounding multi-feature paradigm, we measured the mismatch negativity (MMN), a pre-attentive brain response, to six types of musical feature change in musicians playing three distinct styles of music...

MORPHOMETRIC CHARACTERISTICS OF TROPICAL SHALLOW RESERVOIR USED FOR AQUACULTURE AND AGRICULTURE IN THE MEXICAN PLATEAU

Directory of Open Access Journals (Sweden)

Aldama GR

2013-01-01

Full Text Available Morphometric characteristics of a tropical shallow reservoir situated in the Southern Mexican Highlands were studied. Seventeen morphometric parameters were measured. Results of the morphometric parameters showed that this reservoir presented a soft and roughness bottom, with an ellipsoid form and a concave depression that allow the mix up of water and sediments, causing turbidity and broken thermal gradients; its slight slopes allowed the colonization of submerged macrophyte and halophyte plants and they improve the incidence of sunlight on water surface increasing evaporation and primary productivity. Tropical shallow reservoirs have fluctuations in area and volume according to the amount of rainfall, the effect of evaporation, the temperature levels, lost of volume due to irrigation, and other causes.

Detection of relationships among multi-modal brain imaging meta-features via information flow.

Science.gov (United States)

Miller, Robyn L; Vergara, Victor M; Calhoun, Vince D

2018-01-15

Neuroscientists and clinical researchers are awash in data from an ever-growing number of imaging and other bio-behavioral modalities. This flow of brain imaging data, taken under resting and various task conditions, combines with available cognitive measures, behavioral information, genetic data plus other potentially salient biomedical and environmental information to create a rich but diffuse data landscape. The conditions being studied with brain imaging data are often extremely complex and it is common for researchers to employ more than one imaging, behavioral or biological data modality (e.g., genetics) in their investigations. While the field has advanced significantly in its approach to multimodal data, the vast majority of studies still ignore joint information among two or more features or modalities. We propose an intuitive framework based on conditional probabilities for understanding information exchange between features in what we are calling a feature meta-space; that is, a space consisting of many individual featurae spaces. Features can have any dimension and can be drawn from any data source or modality. No a priori assumptions are made about the functional form (e.g., linear, polynomial, exponential) of captured inter-feature relationships. We demonstrate the framework's ability to identify relationships between disparate features of varying dimensionality by applying it to a large multi-site, multi-modal clinical dataset, balance between schizophrenia patients and controls. In our application it exposes both expected (previously observed) relationships, and novel relationships rarely considered investigated by clinical researchers. To the best of our knowledge there is not presently a comparably efficient way to capture relationships of indeterminate functional form between features of arbitrary dimension and type. We are introducing this method as an initial foray into a space that remains relatively underpopulated. The framework we propose is

Multi-level predictive maintenance for multi-component systems

International Nuclear Information System (INIS)

Nguyen, Kim-Anh; Do, Phuc; Grall, Antoine

2015-01-01

In this paper, a novel predictive maintenance policy with multi-level decision-making is proposed for multi-component system with complex structure. The main idea is to propose a decision-making process considered on two levels: system level and component one. The goal of the decision rules at the system level is to address if preventive maintenance actions are needed regarding the predictive reliability of the system. At component level the decision rules aim at identifying optimally a group of several components to be preventively maintained when preventive maintenance is trigged due to the system level decision. Selecting optimal components is based on a cost-based group improvement factor taking into account the predictive reliability of the components, the economic dependencies as well as the location of the components in the system. Moreover, a cost model is developed to find the optimal maintenance decision variables. A 14-component system is finally introduced to illustrate the use and the performance of the proposed predictive maintenance policy. Different sensitivity analysis are also investigated and discussed. Indeed, the proposed policy provides more flexibility in maintenance decision-making for complex structure systems, hence leading to significant profits in terms of maintenance cost when compared with existing policies. - Highlights: • A predictive maintenance policy for complex structure systems is proposed. • Multi-level decision process based on prognostic results is proposed. • A cost-based group importance measure is introduced for decision-making. • Both positive and negative dependencies between components are investigated. • A cost model and Monte Carlo simulation are developed for optimization process.

Wearable Sensor-Based Human Activity Recognition Method with Multi-Features Extracted from Hilbert-Huang Transform

Directory of Open Access Journals (Sweden)

Huile Xu

2016-12-01

Full Text Available Wearable sensors-based human activity recognition introduces many useful applications and services in health care, rehabilitation training, elderly monitoring and many other areas of human interaction. Existing works in this field mainly focus on recognizing activities by using traditional features extracted from Fourier transform (FT or wavelet transform (WT. However, these signal processing approaches are suitable for a linear signal but not for a nonlinear signal. In this paper, we investigate the characteristics of the Hilbert-Huang transform (HHT for dealing with activity data with properties such as nonlinearity and non-stationarity. A multi-features extraction method based on HHT is then proposed to improve the effect of activity recognition. The extracted multi-features include instantaneous amplitude (IA and instantaneous frequency (IF by means of empirical mode decomposition (EMD, as well as instantaneous energy density (IE and marginal spectrum (MS derived from Hilbert spectral analysis. Experimental studies are performed to verify the proposed approach by using the PAMAP2 dataset from the University of California, Irvine for wearable sensors-based activity recognition. Moreover, the effect of combining multi-features vs. a single-feature are investigated and discussed in the scenario of a dependent subject. The experimental results show that multi-features combination can further improve the performance measures. Finally, we test the effect of multi-features combination in the scenario of an independent subject. Our experimental results show that we achieve four performance indexes: recall, precision, F-measure, and accuracy to 0.9337, 0.9417, 0.9353, and 0.9377 respectively, which are all better than the achievements of related works.

Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

Science.gov (United States)

Ma, Xu; Cheng, Yongmei; Hao, Shuai

2016-12-10

Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

Morphometric variations of laelapine mite (Acari: Mesostigmata populations infesting small mammals (Mammalia in Brazil

Directory of Open Access Journals (Sweden)

F. Martins-Hatano

Full Text Available The goal of this study was to evaluate the morphometric variation of laelapine populations (Acari, Mesostigmata associated with neotropical oryzomyine rodents at different geographic localities in Brazil. Three nominal mite species were selected for study, all infesting the pelage of small mammals at different localities in Rio de Janeiro, Espírito Santo, Bahia, and the Federal District, Brazil. To analyse morphometric characteristics, thirty-seven morphological characters distributed across the whole body of each specimen were measured. We use the Analysis of Principal Components, extracting the three first axes and projecting each mite in these axes. Major species level changes in the taxonomy of the host mammals allows an independent examination of morphometric variation of mites infesting a set of distinctly different host species at different geographic localities. Gigantolaelaps vitzthumi and Laelaps differens are associated with oryzomyine rodents of the genus Cerradomys, and consistently showed a tendency to cluster by host phylogeny. Laelaps manguinhosi associated with Nectomys rattus in central Brazil is morphometrically distinct from mites infesting N. squamipes in the coastal restingas of Rio de Janeiro and Espírito Santo. The results obtained here indicate that laelapine mite populations can vary among geographic areas and among phylogenetically related host species. Clearly, the study of these mites at the population level can be an important tool for clarifying the taxonomy of both mites and hosts.

Morphometric variations of laelapine mite (Acari: Mesostigmata) populations infesting small mammals (Mammalia) in Brazil.

Science.gov (United States)

Martins-Hatano, F; Gettinger, D; Manhães, M L; Bergallo, H G

2012-08-01

The goal of this study was to evaluate the morphometric variation of laelapine populations (Acari, Mesostigmata) associated with neotropical oryzomyine rodents at different geographic localities in Brazil. Three nominal mite species were selected for study, all infesting the pelage of small mammals at different localities in Rio de Janeiro, Espírito Santo, Bahia, and the Federal District, Brazil. To analyse morphometric characteristics, thirty-seven morphological characters distributed across the whole body of each specimen were measured. We use the Analysis of Principal Components, extracting the three first axes and projecting each mite in these axes. Major species level changes in the taxonomy of the host mammals allows an independent examination of morphometric variation of mites infesting a set of distinctly different host species at different geographic localities. Gigantolaelaps vitzthumi and Laelaps differens are associated with oryzomyine rodents of the genus Cerradomys, and consistently showed a tendency to cluster by host phylogeny. Laelaps manguinhosi associated with Nectomys rattus in central Brazil is morphometrically distinct from mites infesting N. squamipes in the coastal restingas of Rio de Janeiro and Espírito Santo. The results obtained here indicate that laelapine mite populations can vary among geographic areas and among phylogenetically related host species. Clearly, the study of these mites at the population level can be an important tool for clarifying the taxonomy of both mites and hosts.

MORPHOMETRICAL PARAMETERS OF GUT MICROFLORA IN HUMAN VOLUNTEERS

NARCIS (Netherlands)

Wilkinson, M.H.F.; Meijer, B.C

1991-01-01

The morphology of faecal microflora of nine healthy human volunteers was studied by digital image analysis of microscopic slides. Weekly specimens were collected during an 8-week period. Seven morphometrical parameters were derived: the means and medians of components 1, 2 and 3, and morphometrical

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

Science.gov (United States)

Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

2018-05-10

Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

Variability of the morphometric features of Calliphora vicina (Diptera, Calliphoridae under the varying and constant micro-climatic condi-tions

Directory of Open Access Journals (Sweden)

L. I. Faly

2013-03-01

Full Text Available Variability of the main morphometric features of imago flies Calliphora vicina R.-D. (Diptera, Calliphoridae of two samples was studied. First sample consists of individuals caught in the wild (park ecosystems of Dnipropetrovsk, the second one – specimens cultured in the laboratory under the constant temperature and humidity. Possible using of C. vicina R.-D. as a bioindicator of anthropogenic factors is analysed. Environmental factors may act as the stimulators of adaptive changes in physiological functions, as the constraints that cause impossibility of the existence of certain species in particular conditions, and as modifiers that determine the morpho- anatomical and physiological changes in organisms. The most significant differences between studied samples were found for the width (“laboratory” individuals are characterized by larger head size and for the length of limbs segments. The fluctuating range of the head width in specimens collected in the wild is much wider, due to the heterogeneity of the micro-climatic conditions of the larvae development and trophic resources. Maximal negative asymmetry of the head width is observed in individuals C. vicina R.-D. of the “natural” sample as compared with “laboratory” individuals. Among imagoes caught in the wild the individuals with a relatively wide head are dominated, as evidenced by the large positive value of kurtosis. At the same time, the distribution of values in “laboratory” individuals is almost normal. In adults bred in the laboratory the shortening of segments of the leg pair I is observed in comparison with the individuals of “natural” sample. Similar results were recorded for other insect groups cultivated in a laboratory. For most other linear measurements of the C. vicina R.-D. body the differences between samples are not registered. Ephemeral existence of the substrate of blow flies leads to higher prevailing evolutionary adaptation of species to varying

A multi-band, multi-level, multi-electron model for efficient FDTD simulations of electromagnetic interactions with semiconductor quantum wells

Science.gov (United States)

Ravi, Koustuban; Wang, Qian; Ho, Seng-Tiong

2015-08-01

We report a new computational model for simulations of electromagnetic interactions with semiconductor quantum well(s) (SQW) in complex electromagnetic geometries using the finite-difference time-domain method. The presented model is based on an approach of spanning a large number of electron transverse momentum states in each SQW sub-band (multi-band) with a small number of discrete multi-electron states (multi-level, multi-electron). This enables accurate and efficient two-dimensional (2-D) and three-dimensional (3-D) simulations of nanophotonic devices with SQW active media. The model includes the following features: (1) Optically induced interband transitions between various SQW conduction and heavy-hole or light-hole sub-bands are considered. (2) Novel intra sub-band and inter sub-band transition terms are derived to thermalize the electron and hole occupational distributions to the correct Fermi-Dirac distributions. (3) The terms in (2) result in an explicit update scheme which circumvents numerically cumbersome iterative procedures. This significantly augments computational efficiency. (4) Explicit update terms to account for carrier leakage to unconfined states are derived, which thermalize the bulk and SQW populations to a common quasi-equilibrium Fermi-Dirac distribution. (5) Auger recombination and intervalence band absorption are included. The model is validated by comparisons to analytic band-filling calculations, simulations of SQW optical gain spectra, and photonic crystal lasers.

Study on the construction of multi-dimensional Remote Sensing feature space for hydrological drought

International Nuclear Information System (INIS)

Xiang, Daxiang; Tan, Debao; Wen, Xiongfei; Shen, Shaohong; Li, Zhe; Cui, Yuanlai

2014-01-01

Hydrological drought refers to an abnormal water shortage caused by precipitation and surface water shortages or a groundwater imbalance. Hydrological drought is reflected in a drop of surface water, decrease of vegetation productivity, increase of temperature difference between day and night and so on. Remote sensing permits the observation of surface water, vegetation, temperature and other information from a macro perspective. This paper analyzes the correlation relationship and differentiation of both remote sensing and surface measured indicators, after the selection and extraction a series of representative remote sensing characteristic parameters according to the spectral characterization of surface features in remote sensing imagery, such as vegetation index, surface temperature and surface water from HJ-1A/B CCD/IRS data. Finally, multi-dimensional remote sensing features such as hydrological drought are built on a intelligent collaborative model. Further, for the Dong-ting lake area, two drought events are analyzed for verification of multi-dimensional features using remote sensing data with different phases and field observation data. The experiments results proved that multi-dimensional features are a good method for hydrological drought

Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

Energy Technology Data Exchange (ETDEWEB)

Jing, Yaqi; Meng, Qinghao, E-mail: qh-meng@tju.edu.cn; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen [Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072 (China)

2014-05-15

An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively.

Electronic nose with a new feature reduction method and a multi-linear classifier for Chinese liquor classification

International Nuclear Information System (INIS)

Jing, Yaqi; Meng, Qinghao; Qi, Peifeng; Zeng, Ming; Li, Wei; Ma, Shugen

2014-01-01

An electronic nose (e-nose) was designed to classify Chinese liquors of the same aroma style. A new method of feature reduction which combined feature selection with feature extraction was proposed. Feature selection method used 8 feature-selection algorithms based on information theory and reduced the dimension of the feature space to 41. Kernel entropy component analysis was introduced into the e-nose system as a feature extraction method and the dimension of feature space was reduced to 12. Classification of Chinese liquors was performed by using back propagation artificial neural network (BP-ANN), linear discrimination analysis (LDA), and a multi-linear classifier. The classification rate of the multi-linear classifier was 97.22%, which was higher than LDA and BP-ANN. Finally the classification of Chinese liquors according to their raw materials and geographical origins was performed using the proposed multi-linear classifier and classification rate was 98.75% and 100%, respectively

An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach.

Directory of Open Access Journals (Sweden)

Zhila Esna Ashari

Full Text Available Type IV secretion systems (T4SS are multi-protein complexes in a number of bacterial pathogens that can translocate proteins and DNA to the host. Most T4SSs function in conjugation and translocate DNA; however, approximately 13% function to secrete proteins, delivering effector proteins into the cytosol of eukaryotic host cells. Upon entry, these effectors manipulate the host cell's machinery for their own benefit, which can result in serious illness or death of the host. For this reason recognition of T4SS effectors has become an important subject. Much previous work has focused on verifying effectors experimentally, a costly endeavor in terms of money, time, and effort. Having good predictions for effectors will help to focus experimental validations and decrease testing costs. In recent years, several scoring and machine learning-based methods have been suggested for the purpose of predicting T4SS effector proteins. These methods have used different sets of features for prediction, and their predictions have been inconsistent. In this paper, an optimal set of features is presented for predicting T4SS effector proteins using a statistical approach. A thorough literature search was performed to find features that have been proposed. Feature values were calculated for datasets of known effectors and non-effectors for T4SS-containing pathogens for four genera with a sufficient number of known effectors, Legionella pneumophila, Coxiella burnetii, Brucella spp, and Bartonella spp. The features were ranked, and less important features were filtered out. Correlations between remaining features were removed, and dimensional reduction was accomplished using principal component analysis and factor analysis. Finally, the optimal features for each pathogen were chosen by building logistic regression models and evaluating each model. The results based on evaluation of our logistic regression models confirm the effectiveness of our four optimal sets of

A novel framework for feature extraction in multi-sensor action potential sorting.

Science.gov (United States)

Wu, Shun-Chi; Swindlehurst, A Lee; Nenadic, Zoran

2015-09-30

Extracellular recordings of multi-unit neural activity have become indispensable in neuroscience research. The analysis of the recordings begins with the detection of the action potentials (APs), followed by a classification step where each AP is associated with a given neural source. A feature extraction step is required prior to classification in order to reduce the dimensionality of the data and the impact of noise, allowing source clustering algorithms to work more efficiently. In this paper, we propose a novel framework for multi-sensor AP feature extraction based on the so-called Matched Subspace Detector (MSD), which is shown to be a natural generalization of standard single-sensor algorithms. Clustering using both simulated data and real AP recordings taken in the locust antennal lobe demonstrates that the proposed approach yields features that are discriminatory and lead to promising results. Unlike existing methods, the proposed algorithm finds joint spatio-temporal feature vectors that match the dominant subspace observed in the two-dimensional data without needs for a forward propagation model and AP templates. The proposed MSD approach provides more discriminatory features for unsupervised AP sorting applications. Copyright © 2015 Elsevier B.V. All rights reserved.

Morphometric analysis of llama (Lama glama) sperm head.

Science.gov (United States)

Casaretto, C; Lombardo, D M; Giuliano, S; Gambarotta, M; Carretero, M I; Miragaya, M H

2012-05-01

Llama production in Argentina has increased, as the international interest in breeding this type of animals has grown in the last years. Considering the great polymorphism that llama spermatozoa present at evaluation using light microscopy, the aim of this study was to objectively evaluate llama sperm head morphometry using digital morphometric analysis. Five ejaculates from each of eight males were obtained to evaluate morphometric parameters of 8000 sperm heads stained with Tinción 15(®). The following average results were obtained for each parameter: size parameters: area 20.09 μm(2), length 6.60 μm, width 4.14 μm, equivalent circle diameter 5.06 μm, curve length 5.79 μm and curve width 3.48 μm; boundary parameters: perimeter 18.54 μm and convex perimeter 17.34 μm; and shape parameters: roundness 1.28 and elongation 1.59. Morphometric parameters of sperm head were compared between ejaculates of the same male and between males. Significant differences between ejaculates of the same male were found for all parameters evaluated (P < 0.01). Significant differences between males were found for all morphometric parameters (P < 0.01) except for curve length, curve width and perimeter. The differences detected would indicate that there is not a single morphometric pattern for Lama glama sperm head, because parameter values cannot be standardised. © 2011 Blackwell Verlag GmbH.

Interactive Approach for Multi-Level Multi-Objective Fractional Programming Problems with Fuzzy Parameters

Directory of Open Access Journals (Sweden)

M.S. Osman

2018-03-01

Full Text Available In this paper, an interactive approach for solving multi-level multi-objective fractional programming (ML-MOFP problems with fuzzy parameters is presented. The proposed interactive approach makes an extended work of Shi and Xia (1997. In the first phase, the numerical crisp model of the ML-MOFP problem has been developed at a confidence level without changing the fuzzy gist of the problem. Then, the linear model for the ML-MOFP problem is formulated. In the second phase, the interactive approach simplifies the linear multi-level multi-objective model by converting it into separate multi-objective programming problems. Also, each separate multi-objective programming problem of the linear model is solved by the ∊-constraint method and the concept of satisfactoriness. Finally, illustrative examples and comparisons with the previous approaches are utilized to evince the feasibility of the proposed approach.

Vehicle license plate recognition based on geometry restraints and multi-feature decision

Science.gov (United States)

Wu, Jianwei; Wang, Zongyue

2005-10-01

Vehicle license plate (VLP) recognition is of great importance to many traffic applications. Though researchers have paid much attention to VLP recognition there has not been a fully operational VLP recognition system yet for many reasons. This paper discusses a valid and practical method for vehicle license plate recognition based on geometry restraints and multi-feature decision including statistical and structural features. In general, the VLP recognition includes the following steps: the location of VLP, character segmentation, and character recognition. This paper discusses the three steps in detail. The characters of VLP are always declining caused by many factors, which makes it more difficult to recognize the characters of VLP, therefore geometry restraints such as the general ratio of length and width, the adjacent edges being perpendicular are used for incline correction. Image Moment has been proved to be invariant to translation, rotation and scaling therefore image moment is used as one feature for character recognition. Stroke is the basic element for writing and hence taking it as a feature is helpful to character recognition. Finally we take the image moment, the strokes and the numbers of each stroke for each character image and some other structural features and statistical features as the multi-feature to match each character image with sample character images so that each character image can be recognized by BP neural net. The proposed method combines statistical and structural features for VLP recognition, and the result shows its validity and efficiency.

Morphometric evaluation of Arbor Acre parent stock broilers reared ...

African Journals Online (AJOL)

Morphometric evaluation of Arbor Acre parent stock broilers reared in ... Economic importance of morphometric parameters such as live weight and body ... (R2) value of 60.30 included forecast indices such as BL, WS, WL, TL, BG and SL.

Digital Morphometrics: A New Upper Airway Phenotyping Paradigm in OSA.

Science.gov (United States)

Schwab, Richard J; Leinwand, Sarah E; Bearn, Cary B; Maislin, Greg; Rao, Ramya Bhat; Nagaraja, Adithya; Wang, Stephen; Keenan, Brendan T

2017-08-01

OSA is associated with changes in pharyngeal anatomy. The goal of this study was to objectively and reproducibly quantify pharyngeal anatomy by using digital morphometrics based on a laser ruler and to assess differences between subjects with OSA and control subjects and associations with the apnea-hypopnea index (AHI). To the best of our knowledge, this study is the first to use digital morphometrics to quantify intraoral risk factors for OSA. Digital photographs were obtained by using an intraoral laser ruler and digital camera in 318 control subjects (mean AHI, 4.2 events/hour) and 542 subjects with OSA (mean AHI, 39.2 events/hour). The digital morphometric paradigm was validated and reproducible over time and camera distances. A larger modified Mallampati score and having a nonvisible airway were associated with a higher AHI, both unadjusted (P digital morphometrics is an accurate, high-throughput, and noninvasive technique to identify anatomic OSA risk factors. Morphometrics may also provide a more reproducible and standardized measurement of the Mallampati score. Digital morphometrics represent an efficient and cost-effective method of examining intraoral crowding and tongue size when examining large populations, genetics, or screening for OSA. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Microtomographic and morphometric characterization of a bioceramic bone substitute in dental implantology

Directory of Open Access Journals (Sweden)

Deborah Meleo

2012-01-01

Full Text Available In recent years, bone tissue regeneration studies have led to a deeper knowledge of chemical and structural features of the best biomaterials to be used as replacements for lost bone structures, with the autologus bone still today the only graft material able to ostegenerate, osteinduct and/or osteoconduct. The difficulties of the small available amount of autologus bone, together with morbidity of a second surgical operation on the same patient, have been overcome using both synthetic and biologic substitute bones. The possibility of investigating morphometric characteristics of substitute bones makes it possible to evaluate the predictability of regenerative processes and, so far, a range of different methods have been used for the purpose. X-ray microtomography (micro-CT is a miniaturized form of conventional tomography, able to analyze the internal structure of small objects, performing three-dimensional images with high spatial resolution (<10 micron pixel size. For a correct analysis, samples need not be altered or treated in any way, as micro-CT is a non-invasive and non-destructive technique. It shows promising results in biomaterial studies and tissue engineering. This work shows the potential applications of this microtomographic technique by means of an in vitro analysis system, in characterizing morphometric features of human bone tissue, and contributes to the use of this technique in studies concerning biomaterials and bioscaffolds inserted in bone tissue.

Cancer microarray data feature selection using multi-objective binary particle swarm optimization algorithm

Science.gov (United States)

Annavarapu, Chandra Sekhara Rao; Dara, Suresh; Banka, Haider

2016-01-01

Cancer investigations in microarray data play a major role in cancer analysis and the treatment. Cancer microarray data consists of complex gene expressed patterns of cancer. In this article, a Multi-Objective Binary Particle Swarm Optimization (MOBPSO) algorithm is proposed for analyzing cancer gene expression data. Due to its high dimensionality, a fast heuristic based pre-processing technique is employed to reduce some of the crude domain features from the initial feature set. Since these pre-processed and reduced features are still high dimensional, the proposed MOBPSO algorithm is used for finding further feature subsets. The objective functions are suitably modeled by optimizing two conflicting objectives i.e., cardinality of feature subsets and distinctive capability of those selected subsets. As these two objective functions are conflicting in nature, they are more suitable for multi-objective modeling. The experiments are carried out on benchmark gene expression datasets, i.e., Colon, Lymphoma and Leukaemia available in literature. The performance of the selected feature subsets with their classification accuracy and validated using 10 fold cross validation techniques. A detailed comparative study is also made to show the betterment or competitiveness of the proposed algorithm. PMID:27822174

Segmental distribution and morphometric features of primary sensory neurons projecting to the tibial periosteum in the rat.

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Tadeusz Cichocki

2004-07-01

Full Text Available Previous reports have demonstrated very rich innervation pattern in the periosteum. Most of the periosteal fibers were found to be sensory in nature. The aim of this study was to identify the primary sensory neurons that innervate the tibial periosteum in the adult rat and to describe the morphometric features of their perikarya. To this end, an axonal fluorescent carbocyanine tracer, DiI, was injected into the periosteum on the medial surface of the tibia. The perikarya of the sensory fibers were traced back in the dorsal root ganglia (DRG L1-L6 by means of fluorescent microscopy on cryosections. DiI-containing neurons were counted in each section and their segmental distribution was determined. Using PC-assisted image analysis system, the size and shape of the traced perikarya were analyzed. DiI-labeled sensory neurons innervating the periosteum of the tibia were located in the DRG ipsilateral to the injection site, with the highest distribution in L3 and L4 (57% and 23%, respectively. The majority of the traced neurons were of small size (area < 850 microm2, which is consistent with the size distribution of CGRP- and SP-containing cells, regarded as primary sensory neurons responsible for perception of pain and temperature. A small proportion of labeled cells had large perikarya and probably supplied corpuscular sense receptors observed in the periosteum. No differences were found in the shape distribution of neurons belonging to different size classes.

Establishing some Correlations between Certain Morphometric Parameters and Embryo Quality

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Nicolae Păcală

2011-05-01

Full Text Available The aim of this paper was to establish some correlations between certain morphometric parameters and embryo quality. The morphometric parameters taken into consideration were: zona pellucida thickness, outer and inner diameter, and outer and inner perimeter. For experiments we used embryos recovered at 24 hours from mouse females superovulated with gonadotrope hormones (eCG and hCG. The embryos recovered were cultivated in KSOM media, supplemented with amino acids, and during the in vitro cultivation they were measured at different time intervals for establishing morphometric parameters. The data obtained were statistically analyzed using Minitab 15, using Fitted Line Plot regression that allows testing of the linear and polynomial regression of one variable. After statistical analyze of the data we found that the thickness of the zona pellucida can constitute a morphometric parameter that can be used as an indicator of subsequent development of the 2 cell embryos to morula and blastocyst stage respectively. The other morphometric parameters studied (outer and inner diameter, and outer and inner perimeter cannot be used as indicators of the embryo development.

Morphometric Analysis of Didessa River Catchment in Blue Nile ...

African Journals Online (AJOL)

Morphometric Analysis of Didessa River Catchment in Blue Nile Basin, Western Ethiopia. ... In the present paper an attempt has been made to study the morphometric characteristics of Didessa ... Stream networks and watersheds were delineated in ArcGIS 10.1 software environment by utilizing ... HOW TO USE AJOL.

ROUNDSCALE SPEARFISH branchiostegal morphometric data

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The morphometric characteristics that separate white marlin Kajikia albidus from roundscale spearfish Tetrapturus georgii can be difficult for non-experts to...

Automatic Generalizability Method of Urban Drainage Pipe Network Considering Multi-Features

Science.gov (United States)

Zhu, S.; Yang, Q.; Shao, J.

2018-05-01

Urban drainage systems are indispensable dataset for storm-flooding simulation. Given data availability and current computing power, the structure and complexity of urban drainage systems require to be simplify. However, till data, the simplify procedure mainly depend on manual operation that always leads to mistakes and lower work efficiency. This work referenced the classification methodology of road system, and proposed a conception of pipeline stroke. Further, length of pipeline, angle between two pipelines, the pipeline belonged road level and diameter of pipeline were chosen as the similarity criterion to generate the pipeline stroke. Finally, designed the automatic method to generalize drainage systems with the concern of multi-features. This technique can improve the efficiency and accuracy of the generalization of drainage systems. In addition, it is beneficial to the study of urban storm-floods.

Automatic Multi-Level Thresholding Segmentation Based on Multi-Objective Optimization

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L. DJEROU,

2012-01-01

Full Text Available In this paper, we present a new multi-level image thresholding technique, called Automatic Threshold based on Multi-objective Optimization "ATMO" that combines the flexibility of multi-objective fitness functions with the power of a Binary Particle Swarm Optimization algorithm "BPSO", for searching the "optimum" number of the thresholds and simultaneously the optimal thresholds of three criteria: the between-class variances criterion, the minimum error criterion and the entropy criterion. Some examples of test images are presented to compare our segmentation method, based on the multi-objective optimization approach with Otsu’s, Kapur’s and Kittler’s methods. Our experimental results show that the thresholding method based on multi-objective optimization is more efficient than the classical Otsu’s, Kapur’s and Kittler’s methods.

Panel Data with Cross-Sectional Dependence Characterized by a Multi-Level Factor Structure

DEFF Research Database (Denmark)

Rodríguez-Caballero, Carlos Vladimir

A panel data model with a multi-level cross-sectional dependence is proposed. The factor structure is driven by top-level common factors as well as non-pervasive factors. I propose a simple method to filter out the full factor structure that overcomes limitations in standard procedures which may...... mix up both levels of unobservable factors and may hamper the identification of the model. The model covers both stationary and non-stationary cases and takes into account other relevant features that make the model well suited to the analysis of many types of time series frequently addressed...

Morphometric Characteristics and Length-Weight Relationship of Russian Sturgeon Juveniles Fed with Different Ratio

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Raluca Cristina ANDREI(GURIENCU

2017-11-01

Full Text Available The aim of this paper was to analyze some morphometric characteristics and the correlation between them for Russian sturgeon juveniles (Acipenser gueldenstaedtii reared in a recirculating aquaculture system fed at different fed with different ratio: 1% body weight (BW, 1.5% BW, 2% BW and ad libitum feeding (which was around 2.8% BW.Fish, with an average body mass around 248.194 ± 1.59 g. Following biometric measurements were made for each fish, including weight (W, total length (TL, standard length (SL, fork length (FL, maximum body depth (last depth of caudal peduncle, H; preanal distance (AD, predorsal distance (PD, length of head (C, preorbital distance (PO, length of pectoral fin (LPF, interorbital distance (ID, maximum width of head (MH, width of mouth (WM, width of the head at the level of the mouth (WHM. The obtained results showed significant differences between all morphometric measurements (p<0.05 for all the experimental variants, emphasizing that in the ad libitum feeding all morphometric measurements were significantly higher than in the other experimental variants. In order to highlight more eloquent these differences, were developed some linear regressions between the morphometric measurements and significant positive correlation (p<0.05 between dependent and independent variables were found.

Linguatula serrata prevalence and morphometrical features: an abattoir survey on water buffaloes in Iran

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Hossein Tajik

2010-09-01

Full Text Available The prevalence and morphometrical characteristics of Linguatula serrata (L. serrata nymphs in mesenteric lymph nodes (MLNs, livers and lungs of 366 Iranian water buffaloes were investigated. The infestation rate increased with age (P0.1. In this study, 7.65% of animals had L. serrata nymphs with infection rates of 5.73% for MLNs, 1.63% for livers and 0.27% for lungs. Greyish-white coloured nymphs measured 3.5 to 4.5 mm in length, 82 to 84 mm in body segments, 44 to 46 mm in transversely striated spines and 4 mm in oral hooks. The results indicated a high rate of infestation of lymph nodes in buffaloes in Iran. Due to consumption of raw or under-cooked liver and visceral organs of buffaloes by local people, the importance of a thorough inspection at slaughter-time seems imperative.

Optimizing survivability of multi-state systems with multi-level protection by multi-processor genetic algorithm

International Nuclear Information System (INIS)

Levitin, Gregory; Dai Yuanshun; Xie Min; Leng Poh, Kim

2003-01-01

In this paper we consider vulnerable systems which can have different states corresponding to different combinations of available elements composing the system. Each state can be characterized by a performance rate, which is the quantitative measure of a system's ability to perform its task. Both the impact of external factors (stress) and internal causes (failures) affect system survivability, which is determined as probability of meeting a given demand. In order to increase the survivability of the system, a multi-level protection is applied to its subsystems. This means that a subsystem and its inner level of protection are in their turn protected by the protection of an outer level. This double-protected subsystem has its outer protection and so forth. In such systems, the protected subsystems can be destroyed only if all of the levels of their protection are destroyed. Each level of protection can be destroyed only if all of the outer levels of protection are destroyed. We formulate the problem of finding the structure of series-parallel multi-state system (including choice of system elements, choice of structure of multi-level protection and choice of protection methods) in order to achieve a desired level of system survivability by the minimal cost. An algorithm based on the universal generating function method is used for determination of the system survivability. A multi-processor version of genetic algorithm is used as optimization tool in order to solve the structure optimization problem. An application example is presented to illustrate the procedure presented in this paper

Landmark-based geometric morphometric analysis of wing shape among certain species of Aedes mosquitoes in District Dehradun (Uttarakhand), India.

Science.gov (United States)

Mondal, Ritwik; Devi, N Pemola; Jauhari, R K

2015-06-01

Insect wing morphology has been used in many studies to describe variations among species and populations using traditional morphometrics, and more recently geometric morphometrics. A landmark-based geometric morphometric analysis of the wings of three species of Aedes (Diptera: Culicidae), viz. Ae. aegypti, Ae. albopictus and Ae. pseudotaeniatus, at District Dehradun was conducted belling on the fact that it can provide insight into the population structure, ecology and taxonomic identification. Adult Aedes mosquito specimens were randomly collected using aerial nets and morphologically examined and identified. The landmarks were identified on the basis of landmark based geometric morphometric analysis thin-plate spline (mainly the software tps-Util 1.28; tps-Dig 1.40; tps-Relw 1.53; and tps-Spline 1.20) and integrated morphometrics programme (mainly twogroup win8 and PCA win8) were utilized. In relative warp (RW) analysis, the first two RW of Ae. aegypti accounted for the highest value (95.82%), followed by Ae. pseudotaeniatus (90.89%), while the lowest (90.12%) being recorded for Ae. albopictus. The bending energies of Ae. aegypti and Ae. pseudotaeniatus were quite identical being 0.1882 and 0.1858 respectively, while Ae. albopictus recorded the highest value of 0.9774. The mean difference values of the distances among Aedes species performing Hotelling's T 2 test were significantly high, predicting major differences among the taxa. In PCA analysis, the horizontal and vertical axis summarized 52.41 and 23.30% of variances respectively. The centroid size exhibited significant differences among populations (non-parametric Kruskal-Wallis test, H = 10.56, p < 0.01). It has been marked out that the geometric morphometrics utilizes powerful and comprehensive statistical procedures to analyze the shape differences of a morphological feature, assuming that the studied mosquitoes may represent different genotypes and probably come from one diverse gene pool.

Developing Multi-Level Institutions from Top-Down Ancestors

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Martha Dowsley

2007-11-01

Full Text Available The academic literature contains numerous examples of the failures of both top-down and bottom-up common pool resource management frameworks. Many authors agree that management regimes instead need to utilize a multi-level governance approach to meet diverse objectives in management. However, many currently operating systems do not have that history. This paper explores the conversion of ancestral top-down regimes to complex systems involving multiple scales, levels and objectives through the management of the polar bear (Ursus maritimus in its five range countries. The less successful polar bear management systems continue to struggle with the challenges of developing institutions with the capacity to learn and change, addressing multiple objectives while recognizing the conservation backbone to management, and matching the institutional scale with biophysical, economic and social scales. The comparatively successful institutions incorporate these features, but reveal on-going problems with vertical links that are partially dealt with through the creation of links to other groups.

Morphometrical differences between resectable and non-resectable pancreatic cancer: a fractal analysis.

Science.gov (United States)

Vasilescu, Catalin; Giza, Dana Elena; Petrisor, Petre; Dobrescu, Radu; Popescu, Irinel; Herlea, Vlad

2012-01-01

Pancreatic cancer is a highly aggressive cancer with a rising incidence and poor prognosis despite active surgical treatment. Candidates for surgical resection should be carefully selected. In order to avoid unnecessary laparotomy it is useful to identify reliable factors that may predict resectability. Nuclear morphometry and fractal dimension of pancreatic nuclear features could provide important preoperative information in assessing pancreas resectability. Sixty-one patients diagnosed with pancreatic cancer were enrolled in this retrospective study between 2003 and 2005. Patients were divided into two groups: one resectable cancer group and one with non-resectable pancreatic cancer. Morphometric parameters measured were: nuclear area, length of minor axis and length of major axis. Nuclear shape and chromatin distribution of the pancreatic tumor cells were both estimated using fractal dimension. Morphometric measurements have shown significant differences between the nuclear area of the resectable group and the non-resectable group (61.9 ± 19.8µm vs. 42.2 ± 15.6µm). Fractal dimension of the nuclear outlines and chromatin distribution was found to have a higher value in the non-resectable group (p<0.05). Objective measurements should be performed to improve risk assessment and therapeutic decisions in pancreatic cancer. Nuclear morphometry of the pancreatic nuclear features can provide important pre-operative information in resectability assessment. The fractal dimension of the nuclear shape and chromatin distribution may be considered a new promising adjunctive tool for conventional pathological analysis.

A FRAMEWORK OF CHANGE DETECTION BASED ON COMBINED MORPHOLOGICA FEATURES AND MULTI-INDEX CLASSIFICATION

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S. Li

2017-09-01

Full Text Available Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI, the differential water index (NDWI are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

Science.gov (United States)

Li, S.; Zhang, S.; Yang, D.

2017-09-01

Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

[The relationship of attachment features and multi-impulsive symptoms in eating disorders].

Science.gov (United States)

Szalai, Tamás Dömötör

2017-07-01

Attachment dysfunctions determine borderline personality disorder, which is a frequent background factor of multi-impulsivity; however, the relationship between attachment and multi-impulsive eating disorders is almost unexplored. To compare attachment features of multi-impulsive and classical eating disorder patients with individuals without eating disorders, and to test attachment as a predictor of multi-impulsivity. A cross-sectional survey (148 females, mean age: 30.9 years) investigated maternal, paternal and adult attachment, depression, anxiety, eating disorder and multi-impulsive symptoms in these groups. Altogether 41.3% of the individuals without eating disorders, 17.6% of classical and 11.8% of multi-impulsive eating disorder patients had secure attachment. Multi-impulsive patients had the most severe eating disorder symptoms (F (2) = 17.733) and the lowest paternal care (F (2) = 3.443). Preoccupied and fearful attachment explained 14.5% of multi-impulsive symptoms; however, with adjustment for depression only latter one remained the predictor of multi-impulsivity (t = 5.166, peating disorder patients from the aspects of both symptoms and attachment. Handling their negative moods may hold therapeutic potentials. Longitudinal studies are required to investigate the therapeutic value of paternal care, attachment preoccupation and fearfulness. Orv Hetil. 2017; 158(27): 1058-1066.

AUTOMATIC GENERALIZABILITY METHOD OF URBAN DRAINAGE PIPE NETWORK CONSIDERING MULTI-FEATURES

Directory of Open Access Journals (Sweden)

S. Zhu

2018-05-01

Full Text Available Urban drainage systems are indispensable dataset for storm-flooding simulation. Given data availability and current computing power, the structure and complexity of urban drainage systems require to be simplify. However, till data, the simplify procedure mainly depend on manual operation that always leads to mistakes and lower work efficiency. This work referenced the classification methodology of road system, and proposed a conception of pipeline stroke. Further, length of pipeline, angle between two pipelines, the pipeline belonged road level and diameter of pipeline were chosen as the similarity criterion to generate the pipeline stroke. Finally, designed the automatic method to generalize drainage systems with the concern of multi-features. This technique can improve the efficiency and accuracy of the generalization of drainage systems. In addition, it is beneficial to the study of urban storm-floods.

Parasites and Morphometric Indices of Frozen Fish Sold in Nsukka ...

African Journals Online (AJOL)

The parasites and morphometric indices of frozen fish sold in Nsukka Urban Market in Nsukka Local Government Area of Enugu State, Nigeria were investigated between June and December 2008 to determine the parasite prevalence, mean intensity and abundance and some morphometric indices associated with ...

Understanding of morphometric features for adequate water resource management in arid environments

Science.gov (United States)

Elhag, Mohamed; Galal, Hanaa K.; Alsubaie, Haneen

2017-08-01

Hydrological characteristics such as topographic parameters, drainage attributes, and land use/land cover patterns are essential to evaluate the water resource management of a watershed area. In the current study, delineation of a watershed and calculation of morphometric characteristics were undertaken using the ASTER global digital elevation model (GDEM). The drainage density of the basin was estimated to be very high, which indicates that the watershed possesses highly permeable soils and low to medium relief. The stream order of the area ranges from first to sixth order, showing a semi-dendritic and radial drainage pattern that indicates heterogeneity in textural characteristics, and it is influenced by structural characteristics in the study area. The bifurcation ratio (Rb) of the basin ranges from 2.0 to 4.42, and the mean bifurcation ratio is 3.84 in the entire study area, which signifies that the drainage pattern of the entire basin is controlled much more by the lithological and geological structure. The elongation ratio is 0.14, which indicates that the shape of the basin has a narrow and elongated shape. A land use/land cover map was generated by using a Landsat-8 image acquired on 10 August 2015 and classified to distinguish mainly the alluvial deposit from the mountainous rock.

Understanding of morphometric features for adequate water resource management in arid environments

Directory of Open Access Journals (Sweden)

M. Elhag

2017-08-01

Full Text Available Hydrological characteristics such as topographic parameters, drainage attributes, and land use/land cover patterns are essential to evaluate the water resource management of a watershed area. In the current study, delineation of a watershed and calculation of morphometric characteristics were undertaken using the ASTER global digital elevation model (GDEM. The drainage density of the basin was estimated to be very high, which indicates that the watershed possesses highly permeable soils and low to medium relief. The stream order of the area ranges from first to sixth order, showing a semi-dendritic and radial drainage pattern that indicates heterogeneity in textural characteristics, and it is influenced by structural characteristics in the study area. The bifurcation ratio (Rb of the basin ranges from 2.0 to 4.42, and the mean bifurcation ratio is 3.84 in the entire study area, which signifies that the drainage pattern of the entire basin is controlled much more by the lithological and geological structure. The elongation ratio is 0.14, which indicates that the shape of the basin has a narrow and elongated shape. A land use/land cover map was generated by using a Landsat-8 image acquired on 10 August 2015 and classified to distinguish mainly the alluvial deposit from the mountainous rock.

Morphometric analysis of the arteries of Willis Polygon

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Canaz Huseyin

2018-03-01

Full Text Available Objective: Willis polygon forms the basis of the arterial circulation of the cerebrum. Willis polygon is a vascular structure whom variations are not rare. Knowledge of the anatomy and preservation of its integrity is crucial for performing neurovascular surgery and intracranial tumour surgery. Because of the important vascular and neurological structures, approaches to this region are considered extremely risky. One of the main variations in-person basis is the diameter differences of the arteries, which forms Willis polygon, between the left and right hemispheres. About structure and variations, studies of Rhoton and Yasargil had formed the touchstone. Our aim is to contribute to the literature and clinical studies, to be done in the future, by comparing our results with previous studies about variations and morphometric features of Willis polygon.

A study of trabecular bone strength and morphometric analysis of bone microstructure from digital radiographic image

International Nuclear Information System (INIS)

Han, Seung Yun; Lee, Sun Bok; Oh, Sung Ook; Heo, Min Suk; Lee, Sam Sun; Choi, Soon Chul; Park, Tae Won; Kim, Jong Dae

2003-01-01

To evaluate the relationship between morphometric analysis of microstructure from digital radiographic image and trabecular bone strength. One hundred eleven bone specimens with 5 mm thickness were obtained from the mandibles of 5 pigs. Digital images of specimens were taken using a direct digital intraoral radiographic system. After selection of ROI(100 x 100 pixel) within the trabecular bone, mean gray level and standard deviation were obtained. Fractal dimension and the variants of morphometric analysis (trabecular area, periphery, length of skeletonized trabeculae, number of terminal point, number of branch point) were obtained from ROI. Punch sheer strength analysis was performed using Instron (model 4465, Instron Corp., USA). The loading force (loading speed 1mm/min) was applied to ROI of bone specimen by a 2 mm diameter punch. Stress-deformation curve was obtained from the punch sheer strength analysis and maximum stress, yield stress, Young's modulus were measured. Maximum stress had a negative linear correlation with mean gray level and fractal dimension significantly (p<0.05). Yield stress had a negative linear correlation with mean gray level, periphery, fractal dimension and the length of skeletonized trabeculae significantly (p<0.05). Young's modulus had a negative linear correlation with mean gray level and fractal dimension significantly (p<0.05). The strength of cancellous bone exhibited a significantly linear relationship between mean gray level, fractal dimension and morphometric analysis. The methods described above can be easily used to evaluate bone quality clinically.

Reproducibility of morphometric X-ray absorptiometry

International Nuclear Information System (INIS)

Culton, N.; Pocock, N.

1999-01-01

Full text: Morphometric X-ray absorptiometry (MXA) using DXA is potentially a useful clinical tool which may provide additional vertebral fracture information with low radiation exposure. While morphometric analysis is semi-automated, operator intervention is crucial for the accurate positioning of the six data points quantifying the vertebral heights at the anterior, middle and posterior positions. Our study evaluated intra-operator reproducibility of MXA in an elderly patient population and assessed the effect of training and experience on vertebral height precision. Ten patients, with a mean lumbar T score of - 2.07, were studied. Images were processed by a trained operator who had initially only limited morphometric experience. The analysis of the data files were repeated at 2 and 6 weeks, during which time the operator had obtained further experience and training. The intra-operator precision of vertebral height measurements was calculated using the three separate combinations of paired analyses, and expressed as the coefficient of variation. This study confirms the importance of adequate training and attention to detail in MXA analysis. The data indicate that the precision of MXA is adequate for its use in the diagnosis of vertebral fractures, based on a 20% deformity criteria. Use of MXA for monitoring would require approximately an 8% change in vertebral heights to achieve statistical significance

Morphometric analysis of the Marmara Sea river basins, Turkey

Science.gov (United States)

Elbaşı, Emre; Ozdemir, Hasan

2014-05-01

(GIS). This study shows that morphometric analysis of the basins in regional level are very important to understand general morphological characteristics of the basins. In this case, tectonic and lithological conditions of the basins have greatly affected the morphometric characteristics of the north and south basins of the Marmara Sea. References Abrahams, AD. 1984. Channel Networks: A Geomorphological Perspective. Water Resources Research, Volume 20, Issue 2, pages 161-188. Horton, R.E. 1932. Drainage basin characteristics. Trans Am Geophys Union 13:350-361. Keller, E.A., Pinter, N. 2002. Active Tectonics Earthquakes, Uplift, and Landscape, Second Edition, Prentice Hall, New Jersey. Ozdemir H., Bird D. 2009. Evaluation of morphometric parameters of drainage networks derived from topographic maps and DEM in point of floods, Environmental Geology, vol.56, pp.1405-1415. Schumm, S.A. 1956. Evolution of drainage systems and slopes in badlands at Perth Amboy, New Jersey. Geol Soc Am Bull 67:597-646. Strahler, A.N. 1957. Quantitative geomorphology of drainage and channel networks. In: Chow YT (ed) Handbook of appliecl hydrology. Me Graw Hill Book Company, New York. Verstappen, H.Th. 1983. Applied geomorphology. ITC, Enschede.

Optimal Multi-Level Lot Sizing for Requirements Planning Systems

OpenAIRE

Earle Steinberg; H. Albert Napier

1980-01-01

The wide spread use of advanced information systems such as Material Requirements Planning (MRP) has significantly altered the practice of dependent demand inventory management. Recent research has focused on development of multi-level lot sizing heuristics for such systems. In this paper, we develop an optimal procedure for the multi-period, multi-product, multi-level lot sizing problem by modeling the system as a constrained generalized network with fixed charge arcs and side constraints. T...

Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System

Directory of Open Access Journals (Sweden)

Hongqiang Li

2016-10-01

Full Text Available Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; this method employs kernel-independent component analysis in nonlinear feature extraction and uses discrete wavelet transform to extract frequency domain features. The proposed system utilises a support vector machine classifier optimized with a genetic algorithm to recognize different types of heartbeats. An ECG acquisition experimental platform, in which ECG beats are collected as ECG data for classification, is constructed to demonstrate the effectiveness of the system in ECG beat classification. The presented system, when applied to the MIT-BIH arrhythmia database, achieves a high classification accuracy of 98.8%. Experimental results based on the ECG acquisition experimental platform show that the system obtains a satisfactory classification accuracy of 97.3% and is able to classify ECG beats efficiently for the automatic identification of cardiac arrhythmias.

On multi-level thinking and scientific understanding

Science.gov (United States)

McIntyre, Michael Edgeworth

2017-10-01

Professor Duzheng YE's name has been familiar to me ever since my postdoctoral years at MIT with Professors Jule CHARNEY and Norman PHILLIPS, back in the late 1960s. I had the enormous pleasure of meeting Professor YE personally in 1992 in Beijing. His concern to promote the very best science and to use it well, and his thinking on multi-level orderly human activities, reminds me not only of the communication skills we need as scientists but also of the multi-level nature of science itself. Here I want to say something (a) about what science is; (b) about why multi-level thinking—and taking more than one viewpoint—is so important for scientific as well as for other forms of understanding; and (c) about what is meant, at a deep level, by "scientific understanding" and trying to communicate it, not only with lay persons but also across professional disciplines. I hope that Professor YE would approve.

Interconnected levels of Multi-Stage Marketing – A Triadic approach

DEFF Research Database (Denmark)

Vedel, Mette; Geersbro, Jens; Ritter, Thomas

2012-01-01

must not only decide in general on the merits of multi-stage marketing for their firm, but must also decide on which level they will engage in multi-stage marketing. The triadic perspective enables a rich and multi-dimensional understanding of how different business relationships influence each other......Multi-stage marketing gains increasing attention as knowledge of and influence on the customer's customer become more critical for the firm's success. Despite this increasing managerial relevance, systematic approaches for analyzing multi-stage marketing are still missing. This paper conceptualizes...... different levels of multi-stage marketing and illustrates these stages with a case study. In addition, a triadic perspective is introduced as an analytical tool for multi-stage marketing research. The results from the case study indicate that multi-stage marketing exists on different levels. Thus, managers...

A multi-level surface rebalancing approach for efficient convergence acceleration of 3D full core multi-group fine grid nodal diffusion iterations

International Nuclear Information System (INIS)

Geemert, René van

2014-01-01

Highlights: • New type of multi-level rebalancing approach for nodal transport. • Generally improved and more mesh-independent convergence behavior. • Importance for intended regime of 3D pin-by-pin core computations. - Abstract: A new multi-level surface rebalancing (MLSR) approach has been developed, aimed at enabling an improved non-linear acceleration of nodal flux iteration convergence in 3D steady-state and transient reactor simulation. This development is meant specifically for anticipating computational needs for solving envisaged multi-group diffusion-like SP N calculations with enhanced mesh resolution (i.e. 3D multi-box up to 3D pin-by-pin grid). For the latter grid refinement regime, the previously available multi-level coarse mesh rebalancing (MLCMR) strategy has been observed to become increasingly inefficient with increasing 3D mesh resolution. Furthermore, for very fine 3D grids that feature a very fine axial mesh as well, non-convergence phenomena have been observed to emerge. In the verifications pursued up to now, these problems have been resolved by the new approach. The novelty arises from taking the interface current balance equations defined over all Cartesian box edges, instead of the nodal volume-integrated process-rate balance equation, as an appropriate restriction basis for setting up multi-level acceleration of fine grid interface current iterations. The new restriction strategy calls for the use of a newly derived set of adjoint spectral equations that are needed for computing a limited set of spectral response vectors per node. This enables a straightforward determination of group-condensed interface current spectral coupling operators that are of crucial relevance in the new rebalancing setup. Another novelty in the approach is a new variational method for computing the neutronic eigenvalue. Within this context, the latter is treated as a control parameter for driving another, newly defined and numerically more fundamental

MULTI-SCALE SEGMENTATION OF HIGH RESOLUTION REMOTE SENSING IMAGES BY INTEGRATING MULTIPLE FEATURES

Directory of Open Access Journals (Sweden)

Y. Di

2017-05-01

Full Text Available Most of multi-scale segmentation algorithms are not aiming at high resolution remote sensing images and have difficulty to communicate and use layers’ information. In view of them, we proposes a method of multi-scale segmentation of high resolution remote sensing images by integrating multiple features. First, Canny operator is used to extract edge information, and then band weighted distance function is built to obtain the edge weight. According to the criterion, the initial segmentation objects of color images can be gained by Kruskal minimum spanning tree algorithm. Finally segmentation images are got by the adaptive rule of Mumford–Shah region merging combination with spectral and texture information. The proposed method is evaluated precisely using analog images and ZY-3 satellite images through quantitative and qualitative analysis. The experimental results show that the multi-scale segmentation of high resolution remote sensing images by integrating multiple features outperformed the software eCognition fractal network evolution algorithm (highest-resolution network evolution that FNEA on the accuracy and slightly inferior to FNEA on the efficiency.

Thermo-mechanical analysis for multi-level HLW repository concept

International Nuclear Information System (INIS)

Kwon, Sang Ki; Choi, Jong Won

2004-01-01

This work aims to investigate the influence of design parameters for the underground high-level nuclear waste repository with multi-level concept. B. Necessity o In order to construct an HLW repository in deep underground, it is required to select a site, which is far from major discontinuities. To dispose the whole spent fuels generated from the Korean nuclear power plants in a repository, the underground area of about 4km 2 is required. This would be a constraints for selecting an adequate repository site. It is recommended to dispose the two different spent fuels, PWR and CANDU, in different areas at the operation efficiency point of view. It is necessary to investigate the influence of parameters, which can affect the stability of multi-level repository. It is also needed to consider the influence of heat generated from the HLW and the high in situ stress in deep location. Therefore, thermo-mechanical coupling analysis should be carried out and the results should be compared with the results from single-level repository concept. Three-dimensional analysis is required to model the disposal tunnel and deposition hole. It is recommended to use the Korean geological condition and actually measured rock properties in Korea in order to achieve reliable modeling results. A FISH routine developed for effective modeling of Thermal-Mechanical coupling was implemented in the modeling using FLAC3D, which is a commercial three-dimensional FDM code. The thermal and mechanical properties of rock and rock mass achieved from Yusung drilling site, were used for the computer modeling. Different parameters such as level distance, waste type disposed on different levels, and time interval between the operation on different levels, were considered in the three-dimensional analysis. From the analysis, it was possible to derive adequate multi-level repository concept. Results and recommendations for application From the thermal-mechanical analysis for the multi-level repository

PELAKSANAAN JUAL BELI MELALUI SISTEM MULTI LEVEL MARKETING PERSPEKTIF HUKUM ISLAM

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Ayu Dewi Utami

2016-03-01

Full Text Available Bisnis Multi Level Marketing (MLM cukup berperan dalam menggerakkan roda perekonomian masyarakat. Dalam sejumlah kasus, Multi Level Marketing (MLM kerap dijadikan kedok dari bisnis money game dan mendewakan passive income. Bertolak dari kasus kasus seperti itulah, Majelis Ulama Indonesia (MUI telah menggodok prinsip-prinsip bisnis ini secara syariah termasuk marketing plannya. Tujuannya untuk melindungi pengusaha dan mitra bisnisnya (masyarakat dari praktik bisnis yang haram atau syubhat. Dari prinsip-prinsip yang ditentukan oleh Majelis Ulama Indonesia (MUI, peneliti mengadakan penelitian ini dengan tujuan untuk mengetahui bagaimana mekanisme bisnis Multi Level Marketing (MLM, serta untuk mengetahui bagaimana bisnis Multi Level Marketing (MLM menurut hukum Islam. Metode yang digunakan dalam penelitian ini adalah menggunakan metode pendekatan yuridis normatif, spesifikasi penelitian yang digunakan adalah deskriptif analitis, sedangkan penentuan sampel menggunakan metode Non Random sampling. Alat penelitian meliputi studi kepustakaan dan wawancara. Metode analisis data dilakukan dengan analisis kualitatif. Ada dua aspek untuk menilai apakah bisnis Multi Level Marketing (MLM itu sesuai dengan syariah atau tidak, yaitu aspek produk atau jasa yang dijual dan sistem dari Multi Level Marketing (MLM itu sendiri. Bagaimana sistem pemberian bonus yang terdapat dalam perusahaan Multi Level Marketing (MLM apakah terbebas dari unsus garar maupun maisir. Penelitian ini bertujuan untuk mengkaji lebih dalam tentang Multi Level Marketing (MLM khususnya dalam Hukum Islam. Sisi negatif yang terdapat pada sistem Multi Level Marketing (MLM tidak mewakili keharaman secara keseluruhan terhadap bisnis yang berbasis Multi Level Marketing (MLM lainnya.

Revisiting the Robustness of PET-Based Textural Features in the Context of Multi-Centric Trials.

Science.gov (United States)

Bailly, Clément; Bodet-Milin, Caroline; Couespel, Solène; Necib, Hatem; Kraeber-Bodéré, Françoise; Ansquer, Catherine; Carlier, Thomas

2016-01-01

This study aimed to investigate the variability of textural features (TF) as a function of acquisition and reconstruction parameters within the context of multi-centric trials. The robustness of 15 selected TFs were studied as a function of the number of iterations, the post-filtering level, input data noise, the reconstruction algorithm and the matrix size. A combination of several reconstruction and acquisition settings was devised to mimic multi-centric conditions. We retrospectively studied data from 26 patients enrolled in a diagnostic study that aimed to evaluate the performance of PET/CT 68Ga-DOTANOC in gastro-entero-pancreatic neuroendocrine tumors. Forty-one tumors were extracted and served as the database. The coefficient of variation (COV) or the absolute deviation (for the noise study) was derived and compared statistically with SUVmax and SUVmean results. The majority of investigated TFs can be used in a multi-centric context when each parameter is considered individually. The impact of voxel size and noise in the input data were predominant as only 4 TFs presented a high/intermediate robustness against SUV-based metrics (Entropy, Homogeneity, RP and ZP). When combining several reconstruction settings to mimic multi-centric conditions, most of the investigated TFs were robust enough against SUVmax except Correlation, Contrast, LGRE, LGZE and LZLGE. Considering previously published results on either reproducibility or sensitivity against delineation approach and our findings, it is feasible to consider Homogeneity, Entropy, Dissimilarity, HGRE, HGZE and ZP as relevant for being used in multi-centric trials.

The Multi-Feature Hypothesis: Connectionist Guidelines for L2 Task Design

Science.gov (United States)

Moonen, Machteld; de Graaff, Rick; Westhoff, Gerard; Brekelmans, Mieke

2014-01-01

This study focuses on the effects of task type on the retention and ease of activation of second language (L2) vocabulary, based on the multi-feature hypothesis (Moonen, De Graaff, & Westhoff, 2006). Two tasks were compared: a writing task and a list-learning task. It was hypothesized that performing the writing task would yield higher…

Exploring Eucladoceros ecomorphology using geometric morphometrics.

Science.gov (United States)

Curran, Sabrina C

2015-01-01

An increasingly common method for reconstructing paleoenvironmental parameters of hominin sites is ecological functional morphology (ecomorphology). This study provides a geometric morphometric study of cervid rearlimb morphology as it relates to phylogeny, size, and ecomorphology. These methods are then applied to an extinct Pleistocene cervid, Eucladoceros, which is found in some of the earliest hominin-occupied sites in Eurasia. Variation in cervid postcranial functional morphology associated with different habitats can be summarized as trade-offs between joint stability versus mobility and rapid movement versus power-generation. Cervids in open habitats emphasize limb stability to avoid joint dislocation during rapid flight from predators. Closed-adapted cervids require more joint mobility to rapidly switch directions in complex habitats. Two skeletal features (of the tibia and calcaneus) have significant phylogenetic signals, while two (the femur and third phalanx) do not. Additionally, morphology of two of these features (tibia and third phalanx) were correlated with body size. For the tibial analysis (but not the third phalanx) this correlation was ameliorated when phylogeny was taken into account. Eucladoceros specimens from France and Romania fall on the more open side of the habitat continuum, a result that is at odds with reconstructions of their diet as browsers, suggesting that they may have had a behavioral regime unlike any extant cervid. © 2014 Wiley Periodicals, Inc.

A MORPHOMETRIC STUDY OF THE SELLA TURCICA; GENDER EFFECT

OpenAIRE

Ashraf Mohamed Elsayed Ali SAKRAN *1, Mohammad Afzal KHAN 2, Faris Mohammed Nour ALTAF 3, Hassan Elsiddig Hassan FARAGALLA 4, Amal Yousif Ahmed Elhaj MUSTAFA 5, Muhammad Mazhar HIJAZI 6, Rayan Abdulshakur NIYAZI 7, Abrar Jamal TAWAKUL 8, Abeer Zubair MALEBARI 9, Amal AbdulAziz SALEM 10.

2015-01-01

Background and objective: Precise anatomical knowledge of the sella turcica is important for neurologists and surgeons operating in the region of cavernous sinus or the surrounding structures. The current study was undertaken to record normal morphometric parameters for future reference and to determine if there is any significance difference in the sella turcica morphometry regarding the gender. Methodology: A Morphometric analysis of the Sella Turcica and structures in vicinity were done...

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.

A sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image

Science.gov (United States)

Li, Jing; Xie, Weixin; Pei, Jihong

2018-03-01

Sea-land segmentation is one of the key technologies of sea target detection in remote sensing images. At present, the existing algorithms have the problems of low accuracy, low universality and poor automatic performance. This paper puts forward a sea-land segmentation algorithm based on multi-feature fusion for a large-field remote sensing image removing island. Firstly, the coastline data is extracted and all of land area is labeled by using the geographic information in large-field remote sensing image. Secondly, three features (local entropy, local texture and local gradient mean) is extracted in the sea-land border area, and the three features combine a 3D feature vector. And then the MultiGaussian model is adopted to describe 3D feature vectors of sea background in the edge of the coastline. Based on this multi-gaussian sea background model, the sea pixels and land pixels near coastline are classified more precise. Finally, the coarse segmentation result and the fine segmentation result are fused to obtain the accurate sea-land segmentation. Comparing and analyzing the experimental results by subjective vision, it shows that the proposed method has high segmentation accuracy, wide applicability and strong anti-disturbance ability.

Morphometric Controls on Glacier Mass Balance of the Puruogangri Ice Field, Central Tibetan Plateau

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Lin Liu

2016-11-01

Full Text Available Evaluating the impacts of climatic changes and morphometric features on glacier mass balance is crucial to providing insight into glacier changes and their effects on regional water resources and ecosystems. Here, we presented an evaluation of morphometric effects on the glacier mass balances of the Puruogangri ice field (PIF on the Tibetan Plateau. A clear spatial variability of glacier mass balances, ranging from −0.035 to +0.019 m·w.e.·year−1, was estimated by comparing the TanDEM-X DEM (2012 with the SRTM-X DEM (2000. In general, the observed glacier mass changes were consistent with our fieldwork investigations. Furthermore, by applying the method of linear regression analysis, we found that the mass changes of individual glaciers on the PIF were mainly dominated by the mean altitude (R = 0.84, p < 0.001, however, they were statistically independent of glacier size, aspect, and surface velocity. At a local scale (grid size of 10 × 10 pixels, apart from the factor of altitude, surface velocity was correlated with glacier mass change.

Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

Science.gov (United States)

Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

2017-12-01

Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

Governing the energy challenge : Canada and Germany in a multi-level regional and global context

International Nuclear Information System (INIS)

Eberlein, B.; Doern, G.B.; Exeter Univ.,

2009-01-01

This book features essays by leading energy and public policy specialists from Canada and Germany. It originated in the Transatlantic Energy Conference which was hosted by the Canadian Centre for German and European Studies at Toronto's York University in September 2005. The conference was attended by leading energy scholars and experts from Canadian and European universities, research institutes and governmental and non-governmental organizations. The purpose of this book was to compare the dynamics of multi-level energy regulatory governance in Germany and Canada, notably the energy policy challenges that include energy security, environmental sustainability and a competitive resource economy. Many strategies to produce more efficient and sustainable energy are presented in the book. Part 1 of the book focuses on the energy industry, with particular emphasise on electricity, nuclear energy and natural gas. Part 2 of the book focuses on domestic patterns of multi-level energy governance and regulation in the two countries. As a member of the European Union, Germany is more advanced in dealing with multi-level governmental and sustainability constraints than Canada is as a member of the North American Free Trade Agreement (NAFTA). The book focuses on the influence that the energy sector and multi-level institutional arrangements have on energy governance, with particular attention to the link between environmental study, climate change issues and economic market reforms. The growing differences between NAFTA and European Union member countries were highlighted. refs., tabs., figs.

Intestinal morphometric and biomechanical changes during aging in rats

DEFF Research Database (Denmark)

Zhao, Jingbo; Gregersen, Hans

2015-01-01

Background and aim: Previously we demonstrated pronounced morphometric and biomechanical remodeling in the rat intestine during physiological growth up to 32 weeks of age. The aim of the present study is to study intestinal geometric and biomechanical changes in aging rats. Materials and methods...... in the circumferential direction. In conclusion pronounced morphometric and biomechanical remodeling occurred in the rat intestine during aging. The observed changes likely reflect the changes of the physiological function of the intestine during ageing, similar to other tissues where function, mechanical loading......: Twenty-four male Wistar rats, aged from 6 to 22 months, were used in the study. The body weight and the wet weight per length of duodenal and ileal segments were measured at the termination of experiment. Morphometric data were obtained by measuring the wall thickness and wall cross-sectional area...

Assessment of the relationships between morphometric characteristics of relief with quantitative and qualitative characteristics of forests using ASTER and SRTM digital terrain models

Directory of Open Access Journals (Sweden)

D. M. Chernikhovsky

2017-06-01

Full Text Available In the article are shown results of assessment of relationships between quantitative and qualitative characteristics of forests and morphometric characteristics of relief on an example model plot in Nanayskoe forest district of Khabarovsk Territory. The relevance of the investigation is connected with need for improvement of the system of forest evaluation operations in the Russian Federation, including with use of the landscape approach. The tasks of the investigation were assessment of relationships between characteristics of relief and characteristics of forest vegetation cover on different levels of forest management; evaluation of morphometric characteristics of relief are important for structure and productivity of forests; comparison of the results obtained through the use of digital terrain models ASTER and SRTM. Geoinformatic projects were formed for a model plot on the basis of digital terrain models and data of forest mensuration and State (National Forest Inventory. On the basis of the developed method with use geoinformatic technologies were estimated morphometric characteristics of relief (average height, standard deviation of height, entropy, exposition and gradient of slopes, indexes of ruggedness and roughness, quantitative and qualitative characteristics of forests. The multifactor regression analysis, where characteristics of forests (as dependent variables and morphometric characteristics of relief (as independent variables were used, have been done. As a result of research, the set of morphometric characteristics of relief able to influence to variability of quantitative and qualitative characteristics of forests was identified. The set of linear regression equations able to explain 30–50 % of variability of dependent variables was obtained. The regression equations, obtained on base of digital terrain models ASTER and SRTM, comparable to each other in strength of relations (coefficients of determination, but includes the

Multi-Accuracy-Level Burning Plasma Simulations

International Nuclear Information System (INIS)

Artaud, J. F.; Basiuk, V.; Garcia, J.; Giruzzi, G.; Huynh, P.; Huysmans, G.; Imbeaux, F.; Johner, J.; Scheider, M.

2007-01-01

The design of a reactor grade tokamak is based on a hierarchy of tools. We present here three codes that are presently used for the simulations of burning plasmas. At the first level there is a 0-dimensional code that allows to choose a reasonable range of global parameters; in our case the HELIOS code was used for this task. For the second level we have developed a mixed 0-D / 1-D code called METIS that allows to study the main properties of a burning plasma, including profiles and all heat and current sources, but always under the constraint of energy and other empirical scaling laws. METIS is a fast code that permits to perform a large number of runs (a run takes about one minute) and design the main features of a scenario, or validate the results of the 0-D code on a full time evolution. At the top level, we used the full 1D1/2 suite of codes CRONOS that gives access to a detailed study of the plasma profiles evolution. CRONOS can use a variety of modules for source terms and transport coefficients computation with different level of complexity and accuracy: from simple estimators to highly sophisticated physics calculations. Thus it is possible to vary the accuracy of burning plasma simulations, as a trade-off with computation time. A wide range of scenario studies can thus be made with CRONOS and then validated with post-processing tools like MHD stability analysis. We will present in this paper results of this multi-level analysis applied to the ITER hybrid scenario. This specific example will illustrate the importance of having several tools for the study of burning plasma scenarios, especially in a domain that present devices cannot access experimentally. (Author)

A Single Rod Multi-modality Multi-interface Level Sensor Using an AC Current Source

Directory of Open Access Journals (Sweden)

Abdulgader Hwili

2008-05-01

Full Text Available Crude oil separation is an important process in the oil industry. To make efficient use of the separators, it is important to know their internal behaviour, and to measure the levels of multi-interfaces between different materials, such as gas-foam, foam-oil, oil-emulsion, emulsion-water and water-solids. A single-rod multi-modality multi-interface level sensor is presented, which has a current source, and electromagnetic modalities. Some key issues have been addressed, including the effect of salt content and temperature i.e. conductivity on the measurement.

Chinese Medical Question Answer Matching Using End-to-End Character-Level Multi-Scale CNNs

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Sheng Zhang

2017-07-01

Full Text Available This paper focuses mainly on the problem of Chinese medical question answer matching, which is arguably more challenging than open-domain question answer matching in English due to the combination of its domain-restricted nature and the language-specific features of Chinese. We present an end-to-end character-level multi-scale convolutional neural framework in which character embeddings instead of word embeddings are used to avoid Chinese word segmentation in text preprocessing, and multi-scale convolutional neural networks (CNNs are then introduced to extract contextual information from either question or answer sentences over different scales. The proposed framework can be trained with minimal human supervision and does not require any handcrafted features, rule-based patterns, or external resources. To validate our framework, we create a new text corpus, named cMedQA, by harvesting questions and answers from an online Chinese health and wellness community. The experimental results on the cMedQA dataset show that our framework significantly outperforms several strong baselines, and achieves an improvement of top-1 accuracy by up to 19%.

Scaling mimesis: Morphometric and ecomorphological similarities in three sympatric plant-mimetic fish of the family Carangidae (Teleostei).

Science.gov (United States)

Queiroz, Alexya Cunha de; Vallinoto, Marcelo; Sakai, Yoichi; Giarrizzo, Tommaso; Barros, Breno

2018-01-01

The mimetic juveniles of a number of carangid fish species resemble plant parts floating near the water surface, such as leaves, seeds and other plant debris. The present study is the first to verify the morphological similarities and ecomorphological relationships between three carangids (Oligoplites saurus, Oligoplites palometa and Trachinotus falcatus) and their associated plant models. Behavioral observations were conducted in the estuary of Curuçá River, in northeastern Pará (Brazil) between August 2015 and July 2016. Individual fishes and associated floating objects (models) were sampled for comparative analysis using both geometric and morphometric approaches. While the mimetic fish and their models retain their own distinct, intrinsic morphological features, a high degree of morphological similarity was found between each fish species and its model. The morphometric analyses revealed a general tendency of isometric development in all three fish species, probably related to their pelagic habitats, during all ontogenetic stages.

Multi-level spondylolysis.

Science.gov (United States)

Hersh, David S; Kim, Yong H; Razi, Afshin

2011-01-01

The incidence of isthmic spondylolysis is approximately 3% to 6% in the general population. Spondylolytic defects involving multiple vertebral levels, on the other hand, are extremely rare. Only a handful of reports have examined the outcomes of surgical treatment of multi-level spondylolysis. Here, we present one case of bilateral pars defects at L3, L4, and L5. The patient, a 46-year-old female, presented with lower back pain radiating into the left lower extremity. Radiographs and CT scans of the lumbar spine revealed bilateral pars defects at L3-L5. The patient underwent lumbar discectomy and interbody fusion of L4-S1 as well as direct repair of the pars defect at L3. There were no postoperative complications, and by seven months the patient had improved clinically. While previous reports describe the use of either direct repair or fusion in the treatment of spondylolysis, we are unaware of reports describing the use of both techniques at adjacent levels.

Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features

Science.gov (United States)

Lei, Sen; Zou, Zhengxia; Liu, Dunge; Xia, Zhenghuan; Shi, Zhenwei

2018-06-01

Sea-land segmentation is a key step for the information processing of ocean remote sensing images. Traditional sea-land segmentation algorithms ignore the local similarity prior of sea and land, and thus fail in complex scenarios. In this paper, we propose a new sea-land segmentation method for infrared remote sensing images to tackle the problem based on superpixels and multi-scale features. Considering the connectivity and local similarity of sea or land, we interpret the sea-land segmentation task in view of superpixels rather than pixels, where similar pixels are clustered and the local similarity are explored. Moreover, the multi-scale features are elaborately designed, comprising of gray histogram and multi-scale total variation. Experimental results on infrared bands of Landsat-8 satellite images demonstrate that the proposed method can obtain more accurate and more robust sea-land segmentation results than the traditional algorithms.

Revisiting the Robustness of PET-Based Textural Features in the Context of Multi-Centric Trials.

Directory of Open Access Journals (Sweden)

Clément Bailly

Full Text Available This study aimed to investigate the variability of textural features (TF as a function of acquisition and reconstruction parameters within the context of multi-centric trials.The robustness of 15 selected TFs were studied as a function of the number of iterations, the post-filtering level, input data noise, the reconstruction algorithm and the matrix size. A combination of several reconstruction and acquisition settings was devised to mimic multi-centric conditions. We retrospectively studied data from 26 patients enrolled in a diagnostic study that aimed to evaluate the performance of PET/CT 68Ga-DOTANOC in gastro-entero-pancreatic neuroendocrine tumors. Forty-one tumors were extracted and served as the database. The coefficient of variation (COV or the absolute deviation (for the noise study was derived and compared statistically with SUVmax and SUVmean results.The majority of investigated TFs can be used in a multi-centric context when each parameter is considered individually. The impact of voxel size and noise in the input data were predominant as only 4 TFs presented a high/intermediate robustness against SUV-based metrics (Entropy, Homogeneity, RP and ZP. When combining several reconstruction settings to mimic multi-centric conditions, most of the investigated TFs were robust enough against SUVmax except Correlation, Contrast, LGRE, LGZE and LZLGE.Considering previously published results on either reproducibility or sensitivity against delineation approach and our findings, it is feasible to consider Homogeneity, Entropy, Dissimilarity, HGRE, HGZE and ZP as relevant for being used in multi-centric trials.

Utilizing Multi-Field Text Features for Efficient Email Spam Filtering

Directory of Open Access Journals (Sweden)

Wuying Liu

2012-06-01

Full Text Available Large-scale spam emails cause a serious waste of time and resources. This paper investigates the text features of email documents and the feature noises among multi-field texts, resulting in an observation of a power law distribution of feature strings within each text field. According to the observation, we propose an efficient filtering approach including a compound weight method and a lightweight field text classification algorithm. The compound weight method considers both the historical classifying ability of each field classifier and the classifying contribution of each text field in the current classified email. The lightweight field text classification algorithm straightforwardly calculates the arithmetical average of multiple conditional probabilities predicted from feature strings according to a string-frequency index for labeled emails storing. The string-frequency index structure has a random-sampling-based compressible property owing to the power law distribution and can largely reduce the storage space. The experimental results in the TREC spam track show that the proposed approach can complete the filtering task in low space cost and high speed, whose overall performance 1-ROCA exceeds the best one among the participators at the trec07p evaluation.

Morphometric characteristics of sycamore maple (Acer pseudoplatanus L. fruits in Novi Sad urban populations

Directory of Open Access Journals (Sweden)

Kostić Saša

2017-01-01

Full Text Available This paper shows the results of the analysis of the fruit morphometric characteristics of 29 trees of sycamore maple (Acer pseudoplatanus L. and red - leaf sycamore maple (Acer pseudoplatanus ‘Аtropurpureum’ Späth. in Novi Sad area. Based on the test trees, it can be concluded that the analyzed secondary population of sycamore maple has a high level of intra - populations variability, based on different degrees of variability of measured parameters and statistically significant differences of all analyzed parameters within the analysed genotypes. The results indicate that there are certain differences between fruit of sycamore maple and its red - leaf variety. Given that there is no statistically significant difference between sites and different urban spaces, it can be concluded that stress factors caused by a high degree of urbanity do not affect the morphometric characteristics of fruits in the analyzed test trees. Testing the symmetry of fruits indicates a high level of genetic variability within the analyzed population.

Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition

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Kun-Ching Wang

2015-01-01

Full Text Available The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI. In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII. The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.

Feature level fusion of hand and face biometrics

Science.gov (United States)

Ross, Arun A.; Govindarajan, Rohin

2005-03-01

Multibiometric systems utilize the evidence presented by multiple biometric sources (e.g., face and fingerprint, multiple fingers of a user, multiple matchers, etc.) in order to determine or verify the identity of an individual. Information from multiple sources can be consolidated in several distinct levels, including the feature extraction level, match score level and decision level. While fusion at the match score and decision levels have been extensively studied in the literature, fusion at the feature level is a relatively understudied problem. In this paper we discuss fusion at the feature level in 3 different scenarios: (i) fusion of PCA and LDA coefficients of face; (ii) fusion of LDA coefficients corresponding to the R,G,B channels of a face image; (iii) fusion of face and hand modalities. Preliminary results are encouraging and help in highlighting the pros and cons of performing fusion at this level. The primary motivation of this work is to demonstrate the viability of such a fusion and to underscore the importance of pursuing further research in this direction.

Geometric morphometrics as a tool for improving the comparative study of behavioural postures.

Science.gov (United States)

Fureix, Carole; Hausberger, Martine; Seneque, Emilie; Morisset, Stéphane; Baylac, Michel; Cornette, Raphaël; Biquand, Véronique; Deleporte, Pierre

2011-07-01

Describing postures has always been a central concern when studying behaviour. However, attempts to compare postures objectively at phylogenetical, populational, inter- or intra-individual levels generally either rely upon a few key elements or remain highly subjective. Here, we propose a novel approach, based on well-established geometric morphometrics, to describe and to analyse postures globally (i.e. considering the animal's body posture in its entirety rather than focusing only on a few salient elements, such as head or tail position). Geometric morphometrics is concerned with describing and comparing variation and changes in the form (size and shape) of organisms using the coordinates of a series of homologous landmarks (i.e. positioned in relation to skeletal or muscular cues that are the same for different species for every variety of form and function and that have derived from a common ancestor, i.e. they have a common evolutionary ancestry, e.g. neck, wings, flipper/hand). We applied this approach to horses, using global postures (1) to characterise behaviours that correspond to different arousal levels, (2) to test potential impact of environmental changes on postures. Our application of geometric morphometrics to horse postures showed that this method can be used to characterise behavioural categories, to evaluate the impact of environmental factors (here human actions) and to compare individuals and groups. Beyond its application to horses, this promising approach could be applied to all questions involving the analysis of postures (evolution of displays, expression of emotions, stress and welfare, behavioural repertoires…) and could lead to a whole new line of research.

Exploiting Higher Order and Multi-modal Features for 3D Object Detection

DEFF Research Database (Denmark)

Kiforenko, Lilita

that describe object visual appearance such as shape, colour, texture etc. This thesis focuses on robust object detection and pose estimation of rigid objects using 3D information. The thesis main contributions are novel feature descriptors together with object detection and pose estimation algorithms....... The initial work introduces a feature descriptor that uses edge categorisation in combination with a local multi-modal histogram descriptor in order to detect objects with little or no texture or surface variation. The comparison is performed with a state-of-the-art method, which is outperformed...... of the methods work well for one type of objects in a specific scenario, in another scenario or with different objects they might fail, therefore more robust solutions are required. The typical problem solution is the design of robust feature descriptors, where feature descriptors contain information...

Morphometric Atlas Selection for Automatic Brachial Plexus Segmentation

International Nuclear Information System (INIS)

Van de Velde, Joris; Wouters, Johan; Vercauteren, Tom; De Gersem, Werner; Duprez, Fréderic; De Neve, Wilfried; Van Hoof, Tom

2015-01-01

Purpose: The purpose of this study was to determine the effects of atlas selection based on different morphometric parameters, on the accuracy of automatic brachial plexus (BP) segmentation for radiation therapy planning. The segmentation accuracy was measured by comparing all of the generated automatic segmentations with anatomically validated gold standard atlases developed using cadavers. Methods and Materials: Twelve cadaver computed tomography (CT) atlases (3 males, 9 females; mean age: 73 years) were included in the study. One atlas was selected to serve as a patient, and the other 11 atlases were registered separately onto this “patient” using deformable image registration. This procedure was repeated for every atlas as a patient. Next, the Dice and Jaccard similarity indices and inclusion index were calculated for every registered BP with the original gold standard BP. In parallel, differences in several morphometric parameters that may influence the BP segmentation accuracy were measured for the different atlases. Specific brachial plexus-related CT-visible bony points were used to define the morphometric parameters. Subsequently, correlations between the similarity indices and morphometric parameters were calculated. Results: A clear negative correlation between difference in protraction-retraction distance and the similarity indices was observed (mean Pearson correlation coefficient = −0.546). All of the other investigated Pearson correlation coefficients were weak. Conclusions: Differences in the shoulder protraction-retraction position between the atlas and the patient during planning CT influence the BP autosegmentation accuracy. A greater difference in the protraction-retraction distance between the atlas and the patient reduces the accuracy of the BP automatic segmentation result

The Speech multi features fusion perceptual hash algorithm based on tensor decomposition

Science.gov (United States)

Huang, Y. B.; Fan, M. H.; Zhang, Q. Y.

2018-03-01

With constant progress in modern speech communication technologies, the speech data is prone to be attacked by the noise or maliciously tampered. In order to make the speech perception hash algorithm has strong robustness and high efficiency, this paper put forward a speech perception hash algorithm based on the tensor decomposition and multi features is proposed. This algorithm analyses the speech perception feature acquires each speech component wavelet packet decomposition. LPCC, LSP and ISP feature of each speech component are extracted to constitute the speech feature tensor. Speech authentication is done by generating the hash values through feature matrix quantification which use mid-value. Experimental results showing that the proposed algorithm is robust for content to maintain operations compared with similar algorithms. It is able to resist the attack of the common background noise. Also, the algorithm is highly efficiency in terms of arithmetic, and is able to meet the real-time requirements of speech communication and complete the speech authentication quickly.

Multi-level Bayesian analyses for single- and multi-vehicle freeway crashes.

Science.gov (United States)

Yu, Rongjie; Abdel-Aty, Mohamed

2013-09-01

This study presents multi-level analyses for single- and multi-vehicle crashes on a mountainous freeway. Data from a 15-mile mountainous freeway section on I-70 were investigated. Both aggregate and disaggregate models for the two crash conditions were developed. Five years of crash data were used in the aggregate investigation, while the disaggregate models utilized one year of crash data along with real-time traffic and weather data. For the aggregate analyses, safety performance functions were developed for the purpose of revealing the contributing factors for each crash type. Two methodologies, a Bayesian bivariate Poisson-lognormal model and a Bayesian hierarchical Poisson model with correlated random effects, were estimated to simultaneously analyze the two crash conditions with consideration of possible correlations. Except for the factors related to geometric characteristics, two exposure parameters (annual average daily traffic and segment length) were included. Two different sets of significant explanatory and exposure variables were identified for the single-vehicle (SV) and multi-vehicle (MV) crashes. It was found that the Bayesian bivariate Poisson-lognormal model is superior to the Bayesian hierarchical Poisson model, the former with a substantially lower DIC and more significant variables. In addition to the aggregate analyses, microscopic real-time crash risk evaluation models were developed for the two crash conditions. Multi-level Bayesian logistic regression models were estimated with the random parameters accounting for seasonal variations, crash-unit-level diversity and segment-level random effects capturing unobserved heterogeneity caused by the geometric characteristics. The model results indicate that the effects of the selected variables on crash occurrence vary across seasons and crash units; and that geometric characteristic variables contribute to the segment variations: the more unobserved heterogeneity have been accounted, the better

Quantum state preparation using multi-level-atom optics

International Nuclear Information System (INIS)

Busch, Th; Deasy, K; Chormaic, S Nic

2007-01-01

One of the most important characteristics for controlling processes on the quantum scale is the fidelity or robustness of the techniques being used. In the case of single atoms localized in micro-traps, it was recently shown that the use of time-dependent tunnelling interactions in a multi-trap setup can be viewed as analogous to the area of multi-level optics. The atom's centre-of-mass can then be controlled with a high fidelity, using a STIRAP-type process. Here, we review previous work that led to the development of multi-level atom optics and present two examples of our most recent work on quantum state preparation

Multi-Level Marketing as a business model

Directory of Open Access Journals (Sweden)

Bogdan Gregor

2013-03-01

Full Text Available Multi Level Marketing is a very popular business model in the Western countries. It is a kind of hybrid of the method of distribution of goods and the method of building a sales network. It is one of the safest (carries a very low risk ways of conducting a business activity. The knowledge about functioning of this business model, both among theoreticians (scanty literature on the subject and practitioners, is still insufficient in Poland. Thus, the presented paper has been prepared as — in the Authors' opinion — it, at least infinitesimally, bridges the gap in the recognition of Multi Level Marketing issues. The aim of the study was, first of all, to describe Multi Level Marketing, to indicate practical benefits of this business model as well as to present basic systems of calculating a commission, which are used in marketing plans of companies. The discussion was based on the study of literature and the knowledge gained in the course of free-form interviews with the leaders of the sector.

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.

Multi-source feature extraction and target recognition in wireless sensor networks based on adaptive distributed wavelet compression algorithms

Science.gov (United States)

Hortos, William S.

2008-04-01

Proposed distributed wavelet-based algorithms are a means to compress sensor data received at the nodes forming a wireless sensor network (WSN) by exchanging information between neighboring sensor nodes. Local collaboration among nodes compacts the measurements, yielding a reduced fused set with equivalent information at far fewer nodes. Nodes may be equipped with multiple sensor types, each capable of sensing distinct phenomena: thermal, humidity, chemical, voltage, or image signals with low or no frequency content as well as audio, seismic or video signals within defined frequency ranges. Compression of the multi-source data through wavelet-based methods, distributed at active nodes, reduces downstream processing and storage requirements along the paths to sink nodes; it also enables noise suppression and more energy-efficient query routing within the WSN. Targets are first detected by the multiple sensors; then wavelet compression and data fusion are applied to the target returns, followed by feature extraction from the reduced data; feature data are input to target recognition/classification routines; targets are tracked during their sojourns through the area monitored by the WSN. Algorithms to perform these tasks are implemented in a distributed manner, based on a partition of the WSN into clusters of nodes. In this work, a scheme of collaborative processing is applied for hierarchical data aggregation and decorrelation, based on the sensor data itself and any redundant information, enabled by a distributed, in-cluster wavelet transform with lifting that allows multiple levels of resolution. The wavelet-based compression algorithm significantly decreases RF bandwidth and other resource use in target processing tasks. Following wavelet compression, features are extracted. The objective of feature extraction is to maximize the probabilities of correct target classification based on multi-source sensor measurements, while minimizing the resource expenditures at

Mathematical model comparing of the multi-level economics systems

Science.gov (United States)

Brykalov, S. M.; Kryanev, A. V.

2017-12-01

The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.

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...

A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets.

Science.gov (United States)

Fernández, Alberto; Carmona, Cristobal José; José Del Jesus, María; Herrera, Francisco

2017-09-01

Imbalanced classification is related to those problems that have an uneven distribution among classes. In addition to the former, when instances are located into the overlapped areas, the correct modeling of the problem becomes harder. Current solutions for both issues are often focused on the binary case study, as multi-class datasets require an additional effort to be addressed. In this research, we overcome these problems by carrying out a combination between feature and instance selections. Feature selection will allow simplifying the overlapping areas easing the generation of rules to distinguish among the classes. Selection of instances from all classes will address the imbalance itself by finding the most appropriate class distribution for the learning task, as well as possibly removing noise and difficult borderline examples. For the sake of obtaining an optimal joint set of features and instances, we embedded the searching for both parameters in a Multi-Objective Evolutionary Algorithm, using the C4.5 decision tree as baseline classifier in this wrapper approach. The multi-objective scheme allows taking a double advantage: the search space becomes broader, and we may provide a set of different solutions in order to build an ensemble of classifiers. This proposal has been contrasted versus several state-of-the-art solutions on imbalanced classification showing excellent results in both binary and multi-class problems.

Use of morphometric analysis and self-organizing maps for alluvial fan classification: case study on Ostorankooh altitudes, Iran

International Nuclear Information System (INIS)

Mokarram, Marzieh; Seif, Abdollah; Sathyamoorthy, Dinesh

2014-01-01

The aim of this study is to classify alluvial fans formed by high-gradient braided streams and torrents that discharge into the Oshtorankook altitudes in the Lorestan province, Iran. The morphology of the fans and their watershed is quantitatively described through estimated morphometric parameters. For relationships between geomorphological features of the fans and their drainage basins, self-organizingmaps (SOM) were used. In SOM, according to both qualitative data and morphometric variables, the clustering tendency of alluvial fans was investigated using 15 alluvial fans parameters. The results of the analysis showed that several morphologically different fan types were recognizedbased on their geomorphological characteristics in the study area. A strong positive relationship was found between the drainage basin area and size of the fan with a simple power function. In addition, the relationship between fan slope and drainage area was found to be negative and moderately strong with a simple power function

The effects of fire severity on ectomycorrhizal colonization and morphometric features in Pinus pinaster Ait. seedlings

Energy Technology Data Exchange (ETDEWEB)

Vásquez-Gassibe, P.; Oria-de-Rueda, J.A.; Santos-del-Blanco, L.; Martín-Pinto, P.

2016-07-01

Aim of study: Mycorrhizal fungi in Mediterranean forests play a key role in the complex process of recovery after wildfires. A broader understanding of an important pyrophytic species as Pinus pinaster and its fungal symbionts is thus necessary for forest restoration purposes. This study aims to assess the effects of ectomycorrhizal symbiosis on maritime pine seedlings and how fire severity affects fungal colonization ability. Area of study: Central Spain, in a Mediterranean region typically affected by wildfires dominated by Pinus pinaster, a species adapted to fire disturbance. Material and Methods: We studied P. pinaster root apexes from seedlings grown in soils collected one year after fire in undisturbed sites, sites moderately affected by fire and sites highly affected by fire. Natural ectomycorrhization was observed at the whole root system level as well as at two root vertical sections (0-10 cm and 10-20 cm). We also measured several morphometric traits (tap root length, shoot length, dry biomass of shoots and root/shoot ratio), which were used to test the influence of fire severity and soil chemistry upon them. Main results: Ectomycorrhizal colonization in undisturbed soils for total and separated root vertical sections was higher than in soils that had been affected by fire to some degree. Inversely, seedling vegetative size increased according to fire severity. Research highlights: Fire severity affected soil properties and mycorrhizal colonization one year after occurrence, thus affecting plant development. These findings can contribute to a better knowledge of the factors mediating successful establishment of P. pinaster in Mediterranean forests after wildfires. (Author)

Entamoeba Clone-Recognition Experiments: Morphometrics, Aggregative Behavior, and Cell-Signaling Characterization.

Science.gov (United States)

Espinosa, Avelina; Paz-Y-Miño-C, Guillermo; Hackey, Meagan; Rutherford, Scott

2016-05-01

Studies on clone- and kin-discrimination in protists have proliferated during the past decade. We report clone-recognition experiments in seven Entamoeba lineages (E. invadens IP-1, E. invadens VK-1:NS, E. terrapinae, E. moshkovskii Laredo, E. moshkovskii Snake, E. histolytica HM-1:IMSS and E. dispar). First, we characterized morphometrically each clone (length, width, and cell-surface area) and documented how they differed statistically from one another (as per single-variable or canonical-discriminant analyses). Second, we demonstrated that amebas themselves could discriminate self (clone) from different (themselves vs. other clones). In mix-cell-line cultures between closely-related (E. invadens IP-1 vs. E. invadens VK-1:NS) or distant-phylogenetic clones (E. terrapinae vs. E. moshkovskii Laredo), amebas consistently aggregated with same-clone members. Third, we identified six putative cell-signals secreted by the amebas (RasGap/Ankyrin, coronin-WD40, actin, protein kinases, heat shock 70, and ubiquitin) and which known functions in Entamoeba spp. included: cell proliferation, cell adhesion, cell movement, and stress-induced encystation. To our knowledge, this is the first multi-clone characterization of Entamoeba spp. morphometrics, aggregative behavior, and cell-signaling secretion in the context of clone-recognition. Protists allow us to study cell-cell recognition from ecological and evolutionary perspectives. Modern protistan lineages can be central to studies about the origins and evolution of multicellularity. © 2016 The Author(s) Journal of Eukaryotic Microbiology © 2016 International Society of Protistologists.

Multi-Level Formation of Complex Software Systems

Directory of Open Access Journals (Sweden)

Hui Li

2016-05-01

Full Text Available We present a multi-level formation model for complex software systems. The previous works extract the software systems to software networks for further studies, but usually investigate the software networks at the class level. In contrast to these works, our treatment of software systems as multi-level networks is more realistic. In particular, the software networks are organized by three levels of granularity, which represents the modularity and hierarchy in the formation process of real-world software systems. More importantly, simulations based on this model have generated more realistic structural properties of software networks, such as power-law, clustering and modularization. On the basis of this model, how the structure of software systems effects software design principles is then explored, and it could be helpful for understanding software evolution and software engineering practices.

Joint Multi-scale Convolution Neural Network for Scene Classification of High Resolution Remote Sensing Imagery

Directory of Open Access Journals (Sweden)

ZHENG Zhuo

2018-05-01

Full Text Available High resolution remote sensing imagery scene classification is important for automatic complex scene recognition, which is the key technology for military and disaster relief, etc. In this paper, we propose a novel joint multi-scale convolution neural network (JMCNN method using a limited amount of image data for high resolution remote sensing imagery scene classification. Different from traditional convolutional neural network, the proposed JMCNN is an end-to-end training model with joint enhanced high-level feature representation, which includes multi-channel feature extractor, joint multi-scale feature fusion and Softmax classifier. Multi-channel and scale convolutional extractors are used to extract scene middle features, firstly. Then, in order to achieve enhanced high-level feature representation in a limit dataset, joint multi-scale feature fusion is proposed to combine multi-channel and scale features using two feature fusions. Finally, enhanced high-level feature representation can be used for classification by Softmax. Experiments were conducted using two limit public UCM and SIRI datasets. Compared to state-of-the-art methods, the JMCNN achieved improved performance and great robustness with average accuracies of 89.3% and 88.3% on the two datasets.

Keabsahan Dan Kekuatan Hukum Layanan Multi Level Marketing Di Kota Manado

OpenAIRE

Mandang, Christian Leonardo

2016-01-01

Tujuan dilakukannya penelitian ini adalah untuk mengetahui apa landasan hukum yang mendasari keabsahan layanan Multi Level Marketing dan bagaimana sebuah Perusahaan dapat memenuhi syarat untuk menjalankan sistem Multi Level Marketing. Dengan menggunakan metode penelitian yuridis normatif, maka dapat disimpulkan: 1. Kehadiran Perusahaan dan kegiatan USAha Multi Level Marketing baik secara global maupun secara nasional, khususnya kehadirannya di negara Indonesia berperan untuk membantu berbagai...

Van Buchem disease: lifetime evolution of radioclinical features

Energy Technology Data Exchange (ETDEWEB)

Vanhoenacker, Filip M.; De Schepper, Arthur M.; Bernaerts, Anja [Department of Radiology, University Hospital Antwerp, Wilrijkstraat 10, 2650, Edegem (Belgium); Balemans, Wendy; Hul, Wim Van [Department of Medical Genetics, University of Antwerp, Universiteitsplein 1, 2610, Antwerp (Belgium); Tan, Gregorius J. [Department of Radiology, Dr. Janssen Ziekenhuis, Urkerweg 1, 8303, Emmeloord (Netherlands); Dikkers, Frederik G. [Department of Otorhinolaryngology, University Hospital Groningen, Hanzeplein 1, 9713, Groningen (Netherlands); Mathysen, Danny G.P. [Department of Ophthalmology, University Hospital Antwerp, Wilrijkstraat 10, 2650, Edegem (Belgium)

2003-12-01

The purpose of this study was to evaluate the lifetime evolution of the radioclinical features in a large family with van Buchem disease. The study population included 13 patients, ranging between 6 and 69 years. The evolution of the clinical features has been assessed by retrospective analysis of the clinical records of the patients. The age-related evolution of the cortical hyperostosis and defective modeling at the tubular bones was evaluated by morphometric analysis of hand films in 9 patients, compared with 9 control individuals. Progression of sclerosis of the craniofacial bones was evaluated by analysis of the skull radiographs of eleven van Buchem patients, taken at different age. Radioclinical features, including sclerosis of the cranial and tubular bones and cranial nerve deficit, become more prominent in older patients. Defective modeling of tubular bones, cortical thickness and medullary width progress with age. Radioclinical abnormalities of van Buchem patients become more prominent in older patients, which suggests that the van Buchem gene is very actively involved in bone metabolism throughout life. Morphometric analysis of the plain films supports the hypothesis that the physiological function of the van Buchem gene is to inhibit bone formation and possibly to regulate bone remodeling. (orig.)

Morphometric study of Euchiton (Gnaphalieae: Asteraceae)

NARCIS (Netherlands)

Flann, C.M.

2010-01-01

A morphometric study was undertaken to survey taxa in the genus Euchiton Cass., distributed across Australia, New Zealand and South-east Asia. Phenetic analyses of herbarium specimens showed several taxa to be well delimited, including E. brassii (Mattf.) Anderb., E. breviscapus (Mattf.) Anderb., E.

Geomorphological change detection using object-based feature extraction from multi-temporal LIDAR data

NARCIS (Netherlands)

Seijmonsbergen, A.C.; Anders, N.S.; Bouten, W.; Feitosa, R.Q.; da Costa, G.A.O.P.; de Almeida, C.M.; Fonseca, L.M.G.; Kux, H.J.H.

2012-01-01

Multi-temporal LiDAR DTMs are used for the development and testing of a method for geomorphological change analysis in western Austria. Our test area is located on a mountain slope in the Gargellen Valley in western Austria. Six geomorphological features were mapped by using stratified Object-Based

Interconnected levels of multi-stage marketing: A triadic approach

OpenAIRE

Vedel, Mette; Geersbro, Jens; Ritter, Thomas

2012-01-01

Multi-stage marketing gains increasing attention as knowledge of and influence on the customer's customer become more critical for the firm's success. Despite this increasing managerial relevance, systematic approaches for analyzing multi-stage marketing are still missing. This paper conceptualizes different levels of multi-stage marketing and illustrates these stages with a case study. In addition, a triadic perspective is introduced as an analytical tool for multi-stage marketing research. ...

Classification of Focal and Non Focal Epileptic Seizures Using Multi-Features and SVM Classifier.

Science.gov (United States)

Sriraam, N; Raghu, S

2017-09-02

Identifying epileptogenic zones prior to surgery is an essential and crucial step in treating patients having pharmacoresistant focal epilepsy. Electroencephalogram (EEG) is a significant measurement benchmark to assess patients suffering from epilepsy. This paper investigates the application of multi-features derived from different domains to recognize the focal and non focal epileptic seizures obtained from pharmacoresistant focal epilepsy patients from Bern Barcelona database. From the dataset, five different classification tasks were formed. Total 26 features were extracted from focal and non focal EEG. Significant features were selected using Wilcoxon rank sum test by setting p-value (p z > 1.96) at 95% significance interval. Hypothesis was made that the effect of removing outliers improves the classification accuracy. Turkey's range test was adopted for pruning outliers from feature set. Finally, 21 features were classified using optimized support vector machine (SVM) classifier with 10-fold cross validation. Bayesian optimization technique was adopted to minimize the cross-validation loss. From the simulation results, it was inferred that the highest sensitivity, specificity, and classification accuracy of 94.56%, 89.74%, and 92.15% achieved respectively and found to be better than the state-of-the-art approaches. Further, it was observed that the classification accuracy improved from 80.2% with outliers to 92.15% without outliers. The classifier performance metrics ensures the suitability of the proposed multi-features with optimized SVM classifier. It can be concluded that the proposed approach can be applied for recognition of focal EEG signals to localize epileptogenic zones.

Device-Level Models Using Multi-Valley Effective Mass

Science.gov (United States)

Baczewski, Andrew D.; Frees, Adam; Gamble, John King; Gao, Xujiao; Jacobson, N. Tobias; Mitchell, John A.; Montaño, Inès; Muller, Richard P.; Nielsen, Erik

2015-03-01

Continued progress in quantum electronics depends critically on the availability of robust device-level modeling tools that capture a wide range of physics and effective mass theory (EMT) is one means of building such models. Recent developments in multi-valley EMT show quantitative agreement with more detailed atomistic tight-binding calculations of phosphorus donors in silicon (Gamble, et. al., arXiv:1408.3159). Leveraging existing PDE solvers, we are developing a framework in which this multi-valley EMT is coupled to an integrated device-level description of several experimentally active qubit technologies. Device-level simulations of quantum operations will be discussed, as well as the extraction of process matrices at this level of theory. The authors gratefully acknowledge support from the Sandia National Laboratories Truman Fellowship Program, which is funded by the Laboratory Directed Research and Development (LDRD) Program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Security Administration under contract DE-AC04-94AL85000.

Morphometric synaptology of a whole neuron profile using a semiautomatic interactive computer system.

Science.gov (United States)

Saito, K; Niki, K

1983-07-01

We propose a new method of dealing with morphometric synaptology that processes all synapses and boutons around the HRP marked neuron on a large composite electron micrograph, rather than a qualitative or a piecemeal quantitative study of a particular synapse and/or bouton that is not positioned on the surface of the neuron. This approach requires the development of both neuroanatomical procedures, by which a specific whole neuronal profile is identified, and valuable specialized tools, which support the collection and analysis of a great volume of morphometric data from composite electron micrographs, in order to reduce the burden of the morphologist. The present report is also concerned with the total and reliable semi-automatic interactive computer system for gathering and analyzing morphometric data that has been under development in our laboratory. A morphologist performs the pattern recognition portion by using a large-sized tablet digitizer and a menu-sheet command, and the system registers the various morphometric values of many different neurons and performs statistical analysis. Some examples of morphometric measurements and analysis show the usefulness and efficiency of the proposed system and method.

Pracovní motivace v multi-level marketingu

OpenAIRE

Mrázková, Tereza

2015-01-01

The purpose of this work is to analyse the motivation in multi-level marketing company. The thesis introduces basic general marketing tools, but also multi-level marketing and the theory of motivation. The research in practical part was done in the form of electronical survey, which was completed by 71 responders. The responders were employees of specific company. The thesis does not only focus on the motivation in work in general, but also on the difference in motivation between male and fem...

High-level intuitive features (HLIFs) for intuitive skin lesion description.

Science.gov (United States)

Amelard, Robert; Glaister, Jeffrey; Wong, Alexander; Clausi, David A

2015-03-01

A set of high-level intuitive features (HLIFs) is proposed to quantitatively describe melanoma in standard camera images. Melanoma is the deadliest form of skin cancer. With rising incidence rates and subjectivity in current clinical detection methods, there is a need for melanoma decision support systems. Feature extraction is a critical step in melanoma decision support systems. Existing feature sets for analyzing standard camera images are comprised of low-level features, which exist in high-dimensional feature spaces and limit the system's ability to convey intuitive diagnostic rationale. The proposed HLIFs were designed to model the ABCD criteria commonly used by dermatologists such that each HLIF represents a human-observable characteristic. As such, intuitive diagnostic rationale can be conveyed to the user. Experimental results show that concatenating the proposed HLIFs with a full low-level feature set increased classification accuracy, and that HLIFs were able to separate the data better than low-level features with statistical significance. An example of a graphical interface for providing intuitive rationale is given.

A Generic multi-dimensional feature extraction method using multiobjective genetic programming.

Science.gov (United States)

Zhang, Yang; Rockett, Peter I

2009-01-01

In this paper, we present a generic feature extraction method for pattern classification using multiobjective genetic programming. This not only evolves the (near-)optimal set of mappings from a pattern space to a multi-dimensional decision space, but also simultaneously optimizes the dimensionality of that decision space. The presented framework evolves vector-to-vector feature extractors that maximize class separability. We demonstrate the efficacy of our approach by making statistically-founded comparisons with a wide variety of established classifier paradigms over a range of datasets and find that for most of the pairwise comparisons, our evolutionary method delivers statistically smaller misclassification errors. At very worst, our method displays no statistical difference in a few pairwise comparisons with established classifier/dataset combinations; crucially, none of the misclassification results produced by our method is worse than any comparator classifier. Although principally focused on feature extraction, feature selection is also performed as an implicit side effect; we show that both feature extraction and selection are important to the success of our technique. The presented method has the practical consequence of obviating the need to exhaustively evaluate a large family of conventional classifiers when faced with a new pattern recognition problem in order to attain a good classification accuracy.

Ethnical evaluation of Bangladeshi young adults in terms of morphometrically-analyzed craniofacial skeleton

Directory of Open Access Journals (Sweden)

Hasan Md. Rizvi

2013-01-01

Full Text Available Morphometric study for the craniofacial relations and variations in humans have long been used to differentiate various racial groups in physical anthropology. The objective of this study was to describe the morphological features of craniofacial skeleton in Bangladeshi young adults and to compare it with already reported standards for the Caucasian population as well as cephalometric values of other Indian races using Steiner′s reference norms. The study was conducted for 52 Bangladeshi young adults (27 male and 25 females, aged 21-27 years, having balanced and harmonious facial profiles, clinically acceptable occlusion with permanent dentition and no history of orthodontic treatment. Lateral cephalograms taken of these subjects were used for a series of morphometric analyses. Bangladeshi subjects were more protrusive skeletally and dentally than Caucasians. Furthermore, the mandibular plane angle was smaller in Bangladeshi subjects than in the Caucasians. Present results also suggest that the Astrics, Dravidians, and Armenoid who penetrated into Bengal in the early ages may have contributed substantially to the morphogenesis of craniofacial skeleton in the present Bengalis. The results of this study support the idea that a single standard of facial esthetics should not be applied to all racial and ethnic groups.

Governance and the Commons in a Multi-Level World

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Derek Armitage

2007-11-01

Full Text Available Multi-level governance may facilitate learning and adaptation in complex social-ecological circumstances. Such arrangements should connect community-based management with regional/national government-level management, link scientific management and traditional management systems, encourage the sharing of knowledge and information, and promote collaboration and dialogue around goals and outcomes. Governance innovations of this type can thus build capacity to adapt to change and manage for resilience. However, critical reflection on the emergence of adaptive, multi-level governance for the commons is warranted. Drawing on examples from the North and South, the purpose of this review is to connect three complementary bodies of scholarship with insights for commons governance in a multi-level world: common property theory, resilience thinking and political ecology. From the commons and resilience literature, normative principles of adaptive, multi-level governance are synthesized (e.g., participation, accountability, leadership, knowledge pluralism, learning and trust. Political ecological interpretations, however, help to reveal the challenge of actualizing these principles and the contextual forces that make entrenched, top-down management systems resilient to change. These forces include the role of power, scale and levels of organization, knowledge valuation, the positioning of social actors and social constructions of nature. Also addressed are the policy narratives that shape governance, and the dialectic relationship among ecological systems and social change. tekst

Effects of freezing on white perch Morone americana (Gmelin, 1789): Implications for multivariate morphometrics

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Kocovsky, Patrick

2016-01-01

This study tested the hypothesis that duration of freezing differentially affects whole-body morphometrics of a derived teleost. Whole-body morphometrics are frequently analyzed to test hypotheses of different species, or stocks within a species, of fishes. Specimens used for morphometric analyses are typically fixed or preserved prior to analysis, yet little research has been done on how fixation or preservation methods or duration of preservation of specimens might affect outcomes of multivariate statistical analyses of differences in shape. To determine whether whole-body morphometrics changed as a result of freezing, 23 whole-body morphometrics of age-1 white perch (Morone americana) from western Lake Erie (n = 211) were analyzed immediately after capture, after being held on ice overnight, and after freezing for 100 or 200 days. Discriminant function analysis revealed that all four groups differed significantly from one another (P time to avoid biases related to the length of time they were frozen. Similar experiments should be conducted on other species and also using formalin- and alcohol-preserved specimens.

Multi-Level Wavelet Shannon Entropy-Based Method for Single-Sensor Fault Location

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Qiaoning Yang

2015-10-01

Full Text Available In actual application, sensors are prone to failure because of harsh environments, battery drain, and sensor aging. Sensor fault location is an important step for follow-up sensor fault detection. In this paper, two new multi-level wavelet Shannon entropies (multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are defined. They take full advantage of sensor fault frequency distribution and energy distribution across multi-subband in wavelet domain. Based on the multi-level wavelet Shannon entropy, a method is proposed for single sensor fault location. The method firstly uses a criterion of maximum energy-to-Shannon entropy ratio to select the appropriate wavelet base for signal analysis. Then multi-level wavelet time Shannon entropy and multi-level wavelet time-energy Shannon entropy are used to locate the fault. The method is validated using practical chemical gas concentration data from a gas sensor array. Compared with wavelet time Shannon entropy and wavelet energy Shannon entropy, the experimental results demonstrate that the proposed method can achieve accurate location of a single sensor fault and has good anti-noise ability. The proposed method is feasible and effective for single-sensor fault location.

Three essays on multi-level optimization models and applications

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Rahdar, Mohammad

The general form of a multi-level mathematical programming problem is a set of nested optimization problems, in which each level controls a series of decision variables independently. However, the value of decision variables may also impact the objective function of other levels. A two-level model is called a bilevel model and can be considered as a Stackelberg game with a leader and a follower. The leader anticipates the response of the follower and optimizes its objective function, and then the follower reacts to the leader's action. The multi-level decision-making model has many real-world applications such as government decisions, energy policies, market economy, network design, etc. However, there is a lack of capable algorithms to solve medium and large scale these types of problems. The dissertation is devoted to both theoretical research and applications of multi-level mathematical programming models, which consists of three parts, each in a paper format. The first part studies the renewable energy portfolio under two major renewable energy policies. The potential competition for biomass for the growth of the renewable energy portfolio in the United States and other interactions between two policies over the next twenty years are investigated. This problem mainly has two levels of decision makers: the government/policy makers and biofuel producers/electricity generators/farmers. We focus on the lower-level problem to predict the amount of capacity expansions, fuel production, and power generation. In the second part, we address uncertainty over demand and lead time in a multi-stage mathematical programming problem. We propose a two-stage tri-level optimization model in the concept of rolling horizon approach to reducing the dimensionality of the multi-stage problem. In the third part of the dissertation, we introduce a new branch and bound algorithm to solve bilevel linear programming problems. The total time is reduced by solving a smaller relaxation

A scale-entropy diffusion equation to describe the multi-scale features of turbulent flames near a wall

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Queiros-Conde, D.; Foucher, F.; Mounaïm-Rousselle, C.; Kassem, H.; Feidt, M.

2008-12-01

Multi-scale features of turbulent flames near a wall display two kinds of scale-dependent fractal features. In scale-space, an unique fractal dimension cannot be defined and the fractal dimension of the front is scale-dependent. Moreover, when the front approaches the wall, this dependency changes: fractal dimension also depends on the wall-distance. Our aim here is to propose a general geometrical framework that provides the possibility to integrate these two cases, in order to describe the multi-scale structure of turbulent flames interacting with a wall. Based on the scale-entropy quantity, which is simply linked to the roughness of the front, we thus introduce a general scale-entropy diffusion equation. We define the notion of “scale-evolutivity” which characterises the deviation of a multi-scale system from the pure fractal behaviour. The specific case of a constant “scale-evolutivity” over the scale-range is studied. In this case, called “parabolic scaling”, the fractal dimension is a linear function of the logarithm of scale. The case of a constant scale-evolutivity in the wall-distance space implies that the fractal dimension depends linearly on the logarithm of the wall-distance. We then verified experimentally, that parabolic scaling represents a good approximation of the real multi-scale features of turbulent flames near a wall.

Morphometric relations of fractal-skeletal based channel network model

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B. S. Daya Sagar

1998-01-01

Full Text Available A fractal-skeletal based channel network (F-SCN model is proposed. Four regular sided initiator-basins are transformed as second order fractal basins by following a specific generating mechanism with non-random rule. The morphological skeletons, hereafter referred to as channel networks, are extracted from these fractal basins. The morphometric and fractal relationships of these F-SCNs are shown. The fractal dimensions of these fractal basins, channel networks, and main channel lengths (computed through box counting method are compared with those of estimated length–area measures. Certain morphometric order ratios to show fractal relations are also highlighted.

Interrelationships between morphometric variables and rounded fish body yields evaluated by path analysis

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Rafael Vilhena Reis Neto

2012-07-01

Full Text Available The objective of this study was to verify which morphometric measures and ratios are more directly associated with the weight and body yields of rounded fish. A total of 225 specimens of rounded fish (59 pacus, 61 tambaquis, 52 tambacus and 53 paquis with average weight of 972.43 g (±115.52 g were sampled, stunned, slaughtered, weighed, measured, and processed for morphometric and processing yield analysis. The morphometric measures taken were: standard length (CP; head length (CC; head height (AC; body height (A1; and body width (L1. For completeness, the following morphometric ratios were calculated: CC/CP, AC/CP, A1/CP, L1/CP, CC/A1, AC/A1, L1/A1, CC/AC and L1/CC. The yields of carcass, filet, rib and filet with rib were estimated after processing. Initially, a "stepwise" procedure was performed in order to eliminate multicollinearity problems among the morphometric variables, and the phenotypic correlations were then calculated for the dependent variables (weight and body yields and independent variables (morphometric measurements and ratios. These correlations were later deployed in direct and indirect effects through path analysis, and the direct and indirect contributions of each variable were measured in percentage terms. The CC and A1 measures were important for determining the weight of rounded fish. The CC/A1 ratio was the variable most directly associated with carcass yield. For filet, filet with rib and rib yields, the L1/CC ratio was found to be more appropriate and can be used directly.

Multi-level iteration optimization for diffusive critical calculation

International Nuclear Information System (INIS)

Li Yunzhao; Wu Hongchun; Cao Liangzhi; Zheng Youqi

2013-01-01

In nuclear reactor core neutron diffusion calculation, there are usually at least three levels of iterations, namely the fission source iteration, the multi-group scattering source iteration and the within-group iteration. Unnecessary calculations occur if the inner iterations are converged extremely tight. But the convergence of the outer iteration may be affected if the inner ones are converged insufficiently tight. Thus, a common scheme suit for most of the problems was proposed in this work to automatically find the optimized settings. The basic idea is to optimize the relative error tolerance of the inner iteration based on the corresponding convergence rate of the outer iteration. Numerical results of a typical thermal neutron reactor core problem and a fast neutron reactor core problem demonstrate the effectiveness of this algorithm in the variational nodal method code NODAL with the Gauss-Seidel left preconditioned multi-group GMRES algorithm. The multi-level iteration optimization scheme reduces the number of multi-group and within-group iterations respectively by a factor of about 1-2 and 5-21. (authors)

Bat Species Comparisons Based on External Morphology: A Test of Traditional versus Geometric Morphometric Approaches.

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Schmieder, Daniela A; Benítez, Hugo A; Borissov, Ivailo M; Fruciano, Carmelo

2015-01-01

External morphology is commonly used to identify bats as well as to investigate flight and foraging behavior, typically relying on simple length and area measures or ratios. However, geometric morphometrics is increasingly used in the biological sciences to analyse variation in shape and discriminate among species and populations. Here we compare the ability of traditional versus geometric morphometric methods in discriminating between closely related bat species--in this case European horseshoe bats (Rhinolophidae, Chiroptera)--based on morphology of the wing, body and tail. In addition to comparing morphometric methods, we used geometric morphometrics to detect interspecies differences as shape changes. Geometric morphometrics yielded improved species discrimination relative to traditional methods. The predicted shape for the variation along the between group principal components revealed that the largest differences between species lay in the extent to which the wing reaches in the direction of the head. This strong trend in interspecific shape variation is associated with size, which we interpret as an evolutionary allometry pattern.

Bat Species Comparisons Based on External Morphology: A Test of Traditional versus Geometric Morphometric Approaches.

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Daniela A Schmieder

Full Text Available External morphology is commonly used to identify bats as well as to investigate flight and foraging behavior, typically relying on simple length and area measures or ratios. However, geometric morphometrics is increasingly used in the biological sciences to analyse variation in shape and discriminate among species and populations. Here we compare the ability of traditional versus geometric morphometric methods in discriminating between closely related bat species--in this case European horseshoe bats (Rhinolophidae, Chiroptera--based on morphology of the wing, body and tail. In addition to comparing morphometric methods, we used geometric morphometrics to detect interspecies differences as shape changes. Geometric morphometrics yielded improved species discrimination relative to traditional methods. The predicted shape for the variation along the between group principal components revealed that the largest differences between species lay in the extent to which the wing reaches in the direction of the head. This strong trend in interspecific shape variation is associated with size, which we interpret as an evolutionary allometry pattern.

Low-Level Color and Texture Feature Extraction of Coral Reef Components

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Ma. Sheila Angeli Marcos

2003-06-01

Full Text Available The purpose of this study is to develop a computer-based classifier that automates coral reef assessmentfrom digitized underwater video. We extract low-level color and texture features from coral images toserve as input to a high-level classifier. Low-level features for color were labeled blue, green, yellow/brown/orange, and gray/white, which are described by the normalized chromaticity histograms of thesemajor colors. The color matching capability of these features was determined through a technique called“Histogram Backprojection”. The low-level texture feature marks a region as coarse or fine dependingon the gray-level variance of the region.

Combining morphometric features and convolutional networks fusion for glaucoma diagnosis

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Perdomo, Oscar; Arevalo, John; González, Fabio A.

2017-11-01

Glaucoma is an eye condition that leads to loss of vision and blindness. Ophthalmoscopy exam evaluates the shape, color and proportion between the optic disc and physiologic cup, but the lack of agreement among experts is still the main diagnosis problem. The application of deep convolutional neural networks combined with automatic extraction of features such as: the cup-to-disc distance in the four quadrants, the perimeter, area, eccentricity, the major radio, the minor radio in optic disc and cup, in addition to all the ratios among the previous parameters may help with a better automatic grading of glaucoma. This paper presents a strategy to merge morphological features and deep convolutional neural networks as a novel methodology to support the glaucoma diagnosis in eye fundus images.

The sound of music: differentiating musicians using a fast, musical multi-feature mismatch negativity paradigm.

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Vuust, Peter; Brattico, Elvira; Seppänen, Miia; Näätänen, Risto; Tervaniemi, Mari

2012-06-01

Musicians' skills in auditory processing depend highly on instrument, performance practice, and on level of expertise. Yet, it is not known though whether the style/genre of music might shape auditory processing in the brains of musicians. Here, we aimed at tackling the role of musical style/genre on modulating neural and behavioral responses to changes in musical features. Using a novel, fast and musical sounding multi-feature paradigm, we measured the mismatch negativity (MMN), a pre-attentive brain response, to six types of musical feature change in musicians playing three distinct styles of music (classical, jazz, rock/pop) and in non-musicians. Jazz and classical musicians scored higher in the musical aptitude test than band musicians and non-musicians, especially with regards to tonal abilities. These results were extended by the MMN findings: jazz musicians had larger MMN-amplitude than all other experimental groups across the six different sound features, indicating a greater overall sensitivity to auditory outliers. In particular, we found enhanced processing of pith and sliding up to pitches in jazz musicians only. Furthermore, we observed a more frontal MMN to pitch and location compared to the other deviants in jazz musicians and left lateralization of the MMN to timbre in classical musicians. These findings indicate that the characteristics of the style/genre of music played by musicians influence their perceptual skills and the brain processing of sound features embedded in a musical context. Musicians' brain is hence shaped by the type of training, musical style/genre, and listening experiences. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multi-level methods and approximating distribution functions

International Nuclear Information System (INIS)

Wilson, D.; Baker, R. E.

2016-01-01

Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.

Multi-level methods and approximating distribution functions

Energy Technology Data Exchange (ETDEWEB)

Wilson, D., E-mail: daniel.wilson@dtc.ox.ac.uk; Baker, R. E. [Mathematical Institute, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG (United Kingdom)

2016-07-15

Biochemical reaction networks are often modelled using discrete-state, continuous-time Markov chains. System statistics of these Markov chains usually cannot be calculated analytically and therefore estimates must be generated via simulation techniques. There is a well documented class of simulation techniques known as exact stochastic simulation algorithms, an example of which is Gillespie’s direct method. These algorithms often come with high computational costs, therefore approximate stochastic simulation algorithms such as the tau-leap method are used. However, in order to minimise the bias in the estimates generated using them, a relatively small value of tau is needed, rendering the computational costs comparable to Gillespie’s direct method. The multi-level Monte Carlo method (Anderson and Higham, Multiscale Model. Simul. 10:146–179, 2012) provides a reduction in computational costs whilst minimising or even eliminating the bias in the estimates of system statistics. This is achieved by first crudely approximating required statistics with many sample paths of low accuracy. Then correction terms are added until a required level of accuracy is reached. Recent literature has primarily focussed on implementing the multi-level method efficiently to estimate a single system statistic. However, it is clearly also of interest to be able to approximate entire probability distributions of species counts. We present two novel methods that combine known techniques for distribution reconstruction with the multi-level method. We demonstrate the potential of our methods using a number of examples.

A single-phase multi-level D-STATCOM inverter using modular multi-level converter (MMC) topology for renewable energy sources

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Sotoodeh, Pedram

This dissertation presents the design of a novel multi-level inverter with FACTS capability for small to mid-size (10-20kW) permanent-magnet wind installations using modular multi-level converter (MMC) topology. The aim of the work is to design a new type of inverter with D-STATCOM option to provide utilities with more control on active and reactive power transfer of distribution lines. The inverter is placed between the renewable energy source, specifically a wind turbine, and the distribution grid in order to fix the power factor of the grid at a target value, regardless of wind speed, by regulating active and reactive power required by the grid. The inverter is capable of controlling active and reactive power by controlling the phase angle and modulation index, respectively. The unique contribution of the proposed work is to combine the two concepts of inverter and D-STATCOM using a novel voltage source converter (VSC) multi-level topology in a single unit without additional cost. Simulations of the proposed inverter, with 5 and 11 levels, have been conducted in MATLAB/Simulink for two systems including 20 kW/kVAR and 250 W/VAR. To validate the simulation results, a scaled version (250 kW/kVAR) of the proposed inverter with 5 and 11 levels has been built and tested in the laboratory. Experimental results show that the reduced-scale 5- and 11-level inverter is able to fix PF of the grid as well as being compatible with IEEE standards. Furthermore, total cost of the prototype models, which is one of the major objectives of this research, is comparable with market prices.

On decoding of multi-level MPSK modulation codes

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Lin, Shu; Gupta, Alok Kumar

1990-01-01

The decoding problem of multi-level block modulation codes is investigated. The hardware design of soft-decision Viterbi decoder for some short length 8-PSK block modulation codes is presented. An effective way to reduce the hardware complexity of the decoder by reducing the branch metric and path metric, using a non-uniform floating-point to integer mapping scheme, is proposed and discussed. The simulation results of the design are presented. The multi-stage decoding (MSD) of multi-level modulation codes is also investigated. The cases of soft-decision and hard-decision MSD are considered and their performance are evaluated for several codes of different lengths and different minimum squared Euclidean distances. It is shown that the soft-decision MSD reduces the decoding complexity drastically and it is suboptimum. The hard-decision MSD further simplifies the decoding while still maintaining a reasonable coding gain over the uncoded system, if the component codes are chosen properly. Finally, some basic 3-level 8-PSK modulation codes using BCH codes as component codes are constructed and their coding gains are found for hard decision multistage decoding.

Multi-level deep supervised networks for retinal vessel segmentation.

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Mo, Juan; Zhang, Lei

2017-12-01

Changes in the appearance of retinal blood vessels are an important indicator for various ophthalmologic and cardiovascular diseases, including diabetes, hypertension, arteriosclerosis, and choroidal neovascularization. Vessel segmentation from retinal images is very challenging because of low blood vessel contrast, intricate vessel topology, and the presence of pathologies such as microaneurysms and hemorrhages. To overcome these challenges, we propose a neural network-based method for vessel segmentation. A deep supervised fully convolutional network is developed by leveraging multi-level hierarchical features of the deep networks. To improve the discriminative capability of features in lower layers of the deep network and guide the gradient back propagation to overcome gradient vanishing, deep supervision with auxiliary classifiers is incorporated in some intermediate layers of the network. Moreover, the transferred knowledge learned from other domains is used to alleviate the issue of insufficient medical training data. The proposed approach does not rely on hand-crafted features and needs no problem-specific preprocessing or postprocessing, which reduces the impact of subjective factors. We evaluate the proposed method on three publicly available databases, the DRIVE, STARE, and CHASE_DB1 databases. Extensive experiments demonstrate that our approach achieves better or comparable performance to state-of-the-art methods with a much faster processing speed, making it suitable for real-world clinical applications. The results of cross-training experiments demonstrate its robustness with respect to the training set. The proposed approach segments retinal vessels accurately with a much faster processing speed and can be easily applied to other biomedical segmentation tasks.

Multi-level governance in EU climate law

NARCIS (Netherlands)

Vedder, Hans; Woerdman, Edwin; Roggenkamp, Martha; Holwerda, Marijn

2015-01-01

This chapter analyses the multi-level governance in EU climate law; it connects the international arena, with EU and national decision-making and relates climate change considerations to competitiveness concerns.

Analysis of Morphological Features of Benign and Malignant Breast Cell Extracted From FNAC Microscopic Image Using the Pearsonian System of Curves.

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Rajbongshi, Nijara; Bora, Kangkana; Nath, Dilip C; Das, Anup K; Mahanta, Lipi B

2018-01-01

Cytological changes in terms of shape and size of nuclei are some of the common morphometric features to study breast cancer, which can be observed by careful screening of fine needle aspiration cytology (FNAC) images. This study attempts to categorize a collection of FNAC microscopic images into benign and malignant classes based on family of probability distribution using some morphometric features of cell nuclei. For this study, features namely area, perimeter, eccentricity, compactness, and circularity of cell nuclei were extracted from FNAC images of both benign and malignant samples using an image processing technique. All experiments were performed on a generated FNAC image database containing 564 malignant (cancerous) and 693 benign (noncancerous) cell level images. The five-set extracted features were reduced to three-set (area, perimeter, and circularity) based on the mean statistic. Finally, the data were fitted to the generalized Pearsonian system of frequency curve, so that the resulting distribution can be used as a statistical model. Pearsonian system is a family of distributions where kappa (κ) is the selection criteria computed as functions of the first four central moments. For the benign group, kappa (κ) corresponding to area, perimeter, and circularity was -0.00004, 0.0000, and 0.04155 and for malignant group it was 1016942, 0.01464, and -0.3213, respectively. Thus, the family of distribution related to these features for the benign and malignant group were different, and therefore, characterization of their probability curve will also be different.

Morphometric evaluation of keratocystic odontogenic tumor before and after marsupialization

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Deborah Campos Telles

2013-12-01

Full Text Available The aim of the present study was the morphometric evaluation of the epithelial lining and fibrous capsule in histological specimens of keratocystic odontogenic tumors (KOTs before and after marsupialization. Histological sections from six KOTs that had undergone marsupialization followed by enucleation were photographed. The thickness and features of the capsule and of the epithelial lining of the tumor were evaluated upon marsupialization and upon subsequent enucleation using Axion Vision software. The histological specimens taken upon marsupialization presented an epithelial lining that is typical of KOTs. After marsupialization, the enucleated specimens had a modified epithelial lining and a fibrous capsule that both presented a greater median thickness (p = 0.0277 and p = 0.0212, respectively, morphological changes, and significant enlargement. These modifications can facilitate full surgical treatment and may well be related to a low KOT recurrence rate.

The multi-level perspective analysis: Indonesia geothermal energy transition study

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Wisaksono, A.; Murphy, J.; Sharp, J. H.; Younger, P. L.

2018-01-01

The study adopts a multi-level perspective in technology transition to analyse how the transition process in the development of geothermal energy in Indonesia is able to compete against the incumbent fossil-fuelled energy sources. Three levels of multi-level perspective are socio-technical landscape (ST-landscape), socio-technical regime (ST-regime) and niche innovations in Indonesia geothermal development. The identification, mapping and analysis of the dynamic relationship between each level are the important pillars of the multi-level perspective framework. The analysis considers the set of rules, actors and controversies that may arise in the technological transition process. The identified geothermal resource risks are the basis of the emerging geothermal technological innovations in Indonesian geothermal. The analysis of this study reveals the transition pathway, which yields a forecast for the Indonesian geothermal technology transition in the form of scenarios and probable impacts.

Physical and morphometric characterization of indigenous cattle of Assam

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A. Haque

2011-01-01

Full Text Available The present investigation was undertaken to study the physical and morphometric characteristics in indigenous cattle of Assam. The data pertain to 339 indigenous cattle of different categories. The physical characteristics included colour pattern of body coat, muzzle, tail switch, hoof and horn. Body length, height at wither, heart girth, pouch girth, length of tail, switch, neck, ear and head were taken up for morphometric characterization. The main body coat colour of indigenous cattle was brown (31.18% followed by white (28.53%, fawn (15.29%, grey (13.53%, black (4.41% and mixed (7.06%. The prominent colour of tail switch was black (74.53%. Most of animals had black muzzle (86.47%, black hooves (84.71% and black horn (100%. Morphometric characteristics data obtained were classified according to location, age group and sex of the animal. The means for body length, height at wither, heart girth, pouch girth, length of tail, switch, neck, ear and head were 83.668±0.590, 91.942±0.55, 113.146±0.738, 121.181±0.761, 54.196±0.527, 26.098±0.186, 32.705±0.166, 18.131±0.111 and 35.035±0.195 cm respectively. Age and sex had significant effect on all the morphometric characters however, location effect was non significant. The indigenous cattle of Assam are comparatively smaller in size than most of the recognized breeds of cattle however coat colour showed sizeable variation. The data generated for indigenous cattle of Assam would be useful to characterize them.

MORPHOMETRIC PARAMETERS AND MICRORELIEF OF THE LUMBRICUS CELOMOCYTES IN THE CONDITIONS OF THE OSMOTIC PRESSURE

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Andrey Andreevich Prisnyi

2017-10-01

Full Text Available Background: Study the morphometric parameters and microrelief of the coelomocytes membrane of the Lumbricus representatives in normal and under osmotic pressure. Materials and methods: In the experiments, representatives of three species belonging to the genus Lumbricus were used. To conduct each series of experiments a coelomic liquid of 15 representatives of each species was used. From the circulation system of each individual examined, at least 250 cells were processed. The study of morphometric parameters of coelomocytes was carried out in isotonic conditions, and also with the use of osmotic tests in vitro. The features of the surface topography of coelomocytes were study using the “Integra Vita Probe Nanaboratorium” (NT-MDT, Russia. The analysis of amplitude and functional average statistical parameters of membrane roughness is carried out. The results of the research were processed using statistics methods using the Microsoft Excel 7.0 analysis package. Results: The Lumbricus representatives of revealed differences in the responses of amoebocytes and eleocytes to the effect of osmotic stress. Under the conditions of osmotic pressure, several morphologically different forms were found among the cells of each type. This indicates the potential ability of coelomocytes to spread out on the substrate for any type of osmotic pressure. The change in the topography of the cell membrane of coelomocytes under the hypoosmotic pressure is characterized by a smoothing of the microrelief structures with a decrease in the size of the microvysings and microinvaginations. Conclusion: The microrelief of the coelomocytes membrane reflects the features of their functional status changing under the influence of environmental factors.

Experimental researches and comparison on aerodynamic parameters and cleaning efficiency of multi-level multi-channel cyclone

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Aleksandras Chlebnikovas

2015-10-01

Full Text Available Multi-level multi-channel cyclone – the lately designed air cleaning device that can remove ultra-fine 20 μm particulatematter (PM from dusted air and reach over 95% of the overall cleaning efficiency. Multi-channel cyclone technology is based on centrifugal forces and has the resulting additional filtering process operation. Multi-level structure of cyclone allows to achieve higher air flow cleaning capacity at the same dimensions of the device, thus saving installation space required for the job, production and operating costs. Studies have examined the air flow parameters change in one–, two– and three–levels multichannel cyclone. These constructions differ according to the productivity of cleaned air under the constant peripheral and transitional (50/50 case air flow relations. Accordance with the results of air flow dynamics – velocity distribution of multi-channel cyclone, aerodynamic resistance and efficiency can be judged on the flow turbulence, the flow channel cross-section and select the most appropriate application. Cleaning efficiency studies were carried out using fine granite and wood ashes PM. The maximum cleaning efficiency was 93.3%, at an average of 4.5 g/m3, the aerodynamic resistance was equal to 1525 Pa.

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features

Science.gov (United States)

Wang, Min; Cui, Qi; Wang, Jie; Ming, Dongping; Lv, Guonian

2017-01-01

In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance.

Discovery and fusion of salient multimodal features toward news story segmentation

Science.gov (United States)

Hsu, Winston; Chang, Shih-Fu; Huang, Chih-Wei; Kennedy, Lyndon; Lin, Ching-Yung; Iyengar, Giridharan

2003-12-01

In this paper, we present our new results in news video story segmentation and classification in the context of TRECVID video retrieval benchmarking event 2003. We applied and extended the Maximum Entropy statistical model to effectively fuse diverse features from multiple levels and modalities, including visual, audio, and text. We have included various features such as motion, face, music/speech types, prosody, and high-level text segmentation information. The statistical fusion model is used to automatically discover relevant features contributing to the detection of story boundaries. One novel aspect of our method is the use of a feature wrapper to address different types of features -- asynchronous, discrete, continuous and delta ones. We also developed several novel features related to prosody. Using the large news video set from the TRECVID 2003 benchmark, we demonstrate satisfactory performance (F1 measures up to 0.76 in ABC news and 0.73 in CNN news), present how these multi-level multi-modal features construct the probabilistic framework, and more importantly observe an interesting opportunity for further improvement.

Chinese buffer material for high-level radiowaste disposal-basic features of GMZ-1

International Nuclear Information System (INIS)

Wen, Zhijian

2005-01-01

Radioactive wastes arising from a wide range of human activities are in many different physical and chemical forms, contaminated with varying radioactivity. Their common feature is the potential hazard associated with their radioactivity and the need to manage them in such a way as to protect the human environment. The geological disposal is regarded as the most reasonable and effective way to safety disposal high-level radioactive wastes in the world. The conceptual model of geological disposal in China is based on a multi-barrier system that combines an isolating geological environment with an engineered barrier system. The buffer is one of the main engineered barriers for HLW repository. The buffer material is expected to maintain its low water permeability, self-sealing property, radio nuclides adsorption and retardation property, thermal conductivity, chemical buffering property, overpack supporting property, stress buffering property over a long period of time. Bentonite is selected as the main content of buffer material that can satisfy above. GMZ deposit is selected as the candidate supplier for Chinese buffer material of High Level Radioactive waste repository. This paper presents geological features of GMZ deposit and basic property of GMZ Na bentonite. GMZ bentonite deposit is a super large scale deposits with high content of Montmorillonite (about 75%) and GMZ-1, which is Na-bentonite produced from GMZ deposit is selected as reference material for Chinese buffer material study

Quadrilateral mesh fitting that preserves sharp features based on multi-normals for Laplacian energy

Directory of Open Access Journals (Sweden)

Yusuke Imai

2014-04-01

Full Text Available Because the cost of performance testing using actual products is expensive, manufacturers use lower-cost computer-aided design simulations for this function. In this paper, we propose using hexahedral meshes, which are more accurate than tetrahedral meshes, for finite element analysis. We propose automatic hexahedral mesh generation with sharp features to precisely represent the corresponding features of a target shape. Our hexahedral mesh is generated using a voxel-based algorithm. In our previous works, we fit the surface of the voxels to the target surface using Laplacian energy minimization. We used normal vectors in the fitting to preserve sharp features. However, this method could not represent concave sharp features precisely. In this proposal, we improve our previous Laplacian energy minimization by adding a term that depends on multi-normal vectors instead of using normal vectors. Furthermore, we accentuate a convex/concave surface subset to represent concave sharp features.

Integrating Multi-omic features exploiting Chromosome Conformation Capture data

Directory of Open Access Journals (Sweden)

Ivan eMerelli

2015-02-01

Full Text Available The representation, integration and interpretation of omic data is a complex task, in particular considering the huge amount of information that is daily produced in molecular biology laboratories all around the world. The reason is that sequencing data regarding expression profiles, methylation patterns, and chromatin domains is difficult to harmonize in a systems biology view, since genome browsers only allow coordinate-based representations, discarding functional clusters created by the spatial conformation of the DNA in the nucleus. In this context, recent progresses in high throughput molecular biology techniques and bioinformatics have provided insights into chromatin interactions on a larger scale and offer a formidable support for the interpretation of multi-omic data. In particular, a novel sequencing technique called Chromosome Conformation Capture (3C allows the analysis of the chromosome organization in the cell’s natural state. While performed genome wide, this technique is usually called Hi-C. Inspired by service applications such as Google Maps, we developed NuChart, an R package that integrates Hi-C data to describe the chromosomal neighbourhood starting from the information about gene positions, with the possibility of mapping on the achieved graphs genomic features such as methylation patterns and histone modifications, along with expression profiles. In this paper we show the importance of the NuChart application for the integration of multi-omic data in a systems biology fashion, with particular interest in cytogenetic applications of these techniques. Moreover, we demonstrate how the integration of multi-omic data can provide useful information in understanding why genes are in certain specific positions inside the nucleus and how epigenetic patterns correlate with their expression.

Sequence-based genotyping clarifies conflicting historical morphometric and biological data for 5 Eimeria species infecting turkeys.

Science.gov (United States)

El-Sherry, S; Ogedengbe, M E; Hafeez, M A; Sayf-Al-Din, M; Gad, N; Barta, J R

2015-02-01

Unlike with Eimeria species infecting chickens, specific identification and nomenclature of Eimeria species infecting turkeys is complicated, and in the absence of molecular data, imprecise. In an attempt to reconcile contradictory data reported on oocyst morphometrics and biological descriptions of various Eimeria species infecting turkey, we established single oocyst derived lines of 5 important Eimeria species infecting turkeys, Eimeria meleagrimitis (USMN08-01 strain), Eimeria adenoeides (Guelph strain), Eimeria gallopavonis (Weybridge strain), Eimeria meleagridis (USAR97-01 strain), and Eimeria dispersa (Briston strain). Short portions (514 bp) of mitochondrial cytochrome c oxidase subunit I gene (mt COI) from each were amplified and sequenced. Comparison of these sequences showed sufficient species-specific sequence variation to recommend these short mt COI sequences as species-specific markers. Uniformity of oocyst features (dimensions and oocyst structure) of each pure line was observed. Additional morphological features of the oocysts of these species are described as useful for the microscopic differentiation of these Eimeria species. Combined molecular and morphometric data on these single species lines compared with the original species descriptions and more recent data have helped to clarify some confusing, and sometimes conflicting, features associated with these Eimeria spp. For example, these new data suggest that the KCH and KR strains of E. adenoeides reported previously represent 2 distinct species, E. adenoeides and E. meleagridis, respectively. Likewise, analysis of the Weybridge strain of E. adenoeides, which has long been used as a reference strain in various studies conducted on the pathogenicity of E. adenoeides, indicates that this coccidium is actually a strain of E. gallopavonis. We highly recommend mt COI sequence-based genotyping be incorporated into all studies using Eimeria spp. of turkeys to confirm species identifications and so

Multi-level Reconfigurable Self-organization in Overlay Services

NARCIS (Netherlands)

Pournaras, E.

2013-01-01

Large-scale decentralized systems organized in overlay networks are complex to manage. Such systems integrate organizational complexity in the application-level resulting in low abstraction and modularity in their services. This thesis introduces a multi-level conceptual architecture for overlay

Monthly morphometric data on captive Kemps ridley sea turtles from 1998-2014 (NCEI Accession 0156880)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data contains monthly morphometric measurements on captive reared sea turtles at the Galveston, TX NOAA lab. Morphometric measurements are taken to track growth...

PENGEMBANGAN MEDIA LUBANG MULTI LEVEL UNTUK PEMBELAJARAN LEMPAR TANGKAP BOLA KECIL

Directory of Open Access Journals (Sweden)

Tri Aryo Trubus Anom

2017-02-01

Full Text Available This research aims to develop a media Hole Multi Level to capture the small ball throwing learning grade IV elementary school level that can increase students roll control. The model of the research is the development of research and data analysis in the form of a percentage of data types with a description of the qualitative and quantitative. Procedure development include; 1 Potential problems, 2 Data collection, 3 Early media product design Multi Level Hole, 4 Design Validation by expert penjas and learning experts, 5 Revision products I, 6 Trials I in MI Ma’arif NU Darmakradenan, 7 Product revision II, 8 Trial II at four elementary school in the village of Darmakradenan, 9 Product revision III, 10 And products. The results of expert validation against the media Pit Multi Level was 80%, I Test of 83,23%, and II trials of 85.97%. Those results can be concluded that the development of the media Pit Multi Level can be used to capture the small ball throwing learning grade IV elementary school level.

Leaf morphology, taxonomy and geometric morphometrics: a simplified protocol for beginners.

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Vincenzo Viscosi

Full Text Available Taxonomy relies greatly on morphology to discriminate groups. Computerized geometric morphometric methods for quantitative shape analysis measure, test and visualize differences in form in a highly effective, reproducible, accurate and statistically powerful way. Plant leaves are commonly used in taxonomic analyses and are particularly suitable to landmark based geometric morphometrics. However, botanists do not yet seem to have taken advantage of this set of methods in their studies as much as zoologists have done. Using free software and an example dataset from two geographical populations of sessile oak leaves, we describe in detailed but simple terms how to: a compute size and shape variables using Procrustes methods; b test measurement error and the main levels of variation (population and trees using a hierachical design; c estimate the accuracy of group discrimination; d repeat this estimate after controlling for the effect of size differences on shape (i.e., allometry. Measurement error was completely negligible; individual variation in leaf morphology was large and differences between trees were generally bigger than within trees; differences between the two geographic populations were small in both size and shape; despite a weak allometric trend, controlling for the effect of size on shape slighly increased discrimination accuracy. Procrustes based methods for the analysis of landmarks were highly efficient in measuring the hierarchical structure of differences in leaves and in revealing very small-scale variation. In taxonomy and many other fields of botany and biology, the application of geometric morphometrics contributes to increase scientific rigour in the description of important aspects of the phenotypic dimension of biodiversity. Easy to follow but detailed step by step example studies can promote a more extensive use of these numerical methods, as they provide an introduction to the discipline which, for many biologists, is

Morphometric analysis of three normal facial types in mixed dentition using posteroanterior cephalometric radiographs: preliminary results

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Renato Bigliazzi

2017-08-01

Full Text Available The aim of the present investigation was to evaluate the craniofacial features of subjects with normal occlusion with different vertical patterns in the mixed dentition using morphometric analysis (Thin-Plate Spline analysis - TPS applied to posteroanterior (PA films. The sample comprised 39 individuals (18 females and 21 males, all in mixed dentition, aged from 8.4 to 10 years with satisfactory occlusion and balanced profile and with no history of orthodontic or facial orthopedic treatment. The sample was divided into three groups (mesofacial, brachyfacial and dolichofacial according to the facial types proposed by Ricketts (1989. The average craniofacial configurations of each study group were obtained by orthogonal superimposition of Procrustes, thereby eliminating size differences and allowing only shape differences between groups to be analyzed by viewing the TPS deformation grid. Significant differences were found among the three facial types but were more remarkable between mesofacials and dolichofacials than between mesofacials and brachyfacials. TPS morphometric analysis proved efficient for accurate visualization of transverse and vertical differences among facial types even before pubertal growth spurt. These differences cannot be easily detected by traditional posteroanterior cephalometry.

Foot morphometric phenomena.

Science.gov (United States)

Agić, Ante

2007-06-01

Knowledge of the foot morphometry is important for proper foot structure and function. Foot structure as a vital part of human body is important for many reasons. The foot anthropometric and morphology phenomena are analyzed together with hidden biomechanical descriptors in order to fully characterize foot functionality. For Croatian student population the scatter data of the individual foot variables were interpolated by multivariate statistics. Foot morphometric descriptors are influenced by many factors, such as life style, climate, and things of great importance in human society. Dominant descriptors related to fit and comfort are determined by the use 3D foot shape and advanced foot biomechanics. Some practical recommendations and conclusions for medical, sportswear and footwear practice are highlighted.

Retrospective Morphometric Analysis of the Infraorbital Foramen ...

African Journals Online (AJOL)

Objective: The aim of our study is to examine the morphometric characteristics of the infraorbital foramen (IOF) and its anatomic localization by using conebeam computerized tomography (CBCT). Materials and Methods: In our study, the anatomic characteristics of the IOF were identified by studying retrospectively the CBCT ...

A geometric morphometric assessment of the optic cup in glaucoma.

Science.gov (United States)

Sanfilippo, Paul G; Cardini, Andrea; Sigal, Ian A; Ruddle, Jonathan B; Chua, Brian E; Hewitt, Alex W; Mackey, David A

2010-09-01

The morphologic appearance of the optic disc is of interest in glaucoma. In contrast to descriptive classification systems that are currently used, a quantitative approach to the analysis of optic disc morphology is required. Our goal was to determine the optimal method for quantifying optic cup shape by comparing traditional (ovality, form-factor and neuroretinal rim (NRR) width ratio) and geometric morphometric approaches. Left optic disc stereophotographs of 160 (80 normal and 80 glaucomatous (stratified by severity)) subjects were examined. The optic cup margins were stereoscopically delineated with a custom tracing system and saved as a series of discrete points. The geometric morphometric methods of elliptic Fourier analysis (EFA) and sliding semi-landmark analysis (SSLA) were used to eliminate variation unrelated to shape (e.g. size) and yield a series of shape variables. Differences in optic cup shape between normal and glaucoma groups were investigated. Discriminant functions were computed and the sensitivity and specificity of each technique determined. Receiver operator characteristic (ROC) curves were calculated for all methods and evaluated in their potential to discriminate between normal and glaucomatous eyes based on the shape variables. All geometric morphometric methods revealed differences between normal and glaucomatous eyes in optic cup shape, in addition to the traditional parameters of ovality, form-factor and NRR width ratio (pgeometric morphometric approach for discriminating between normal and glaucomatous eyes in optic cup shape is superior to that provided by traditional single parameter shape measures. Such analytical techniques could be incorporated into future automated optic disc screening modalities. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

A data-driven multi-model methodology with deep feature selection for short-term wind forecasting

International Nuclear Information System (INIS)

Feng, Cong; Cui, Mingjian; Hodge, Bri-Mathias; Zhang, Jie

2017-01-01

Highlights: • An ensemble model is developed to produce both deterministic and probabilistic wind forecasts. • A deep feature selection framework is developed to optimally determine the inputs to the forecasting methodology. • The developed ensemble methodology has improved the forecasting accuracy by up to 30%. - Abstract: With the growing wind penetration into the power system worldwide, improving wind power forecasting accuracy is becoming increasingly important to ensure continued economic and reliable power system operations. In this paper, a data-driven multi-model wind forecasting methodology is developed with a two-layer ensemble machine learning technique. The first layer is composed of multiple machine learning models that generate individual forecasts. A deep feature selection framework is developed to determine the most suitable inputs to the first layer machine learning models. Then, a blending algorithm is applied in the second layer to create an ensemble of the forecasts produced by first layer models and generate both deterministic and probabilistic forecasts. This two-layer model seeks to utilize the statistically different characteristics of each machine learning algorithm. A number of machine learning algorithms are selected and compared in both layers. This developed multi-model wind forecasting methodology is compared to several benchmarks. The effectiveness of the proposed methodology is evaluated to provide 1-hour-ahead wind speed forecasting at seven locations of the Surface Radiation network. Numerical results show that comparing to the single-algorithm models, the developed multi-model framework with deep feature selection procedure has improved the forecasting accuracy by up to 30%.

Rapid islanding detection using multi-level inverter for grid-interactive PV system

International Nuclear Information System (INIS)

Tsang, K.M.; Chan, W.L.

2014-01-01

Graphical abstract: - Highlights: • Novel reference signal is used to form an islanding detection scheme for PV system. • Supply fixed magnitude sinusoidal signal even if utility grid is disconnected. • Seamless transfer between grid-connected and stand-alone modes is possible. - Abstract: A novel reference signal generator is combined with a multi-level inverter to form a rapid islanding detection scheme for grid-interactive PV system. The reference signal generator can easily be synchronized with the utility grid signal and produced a fixed magnitude and very low total harmonic distortion (THD) sinusoidal signal which is in phase with the utility grid signal. Unlike conventional phase-locked loop (PLL) circuitry, the reference signal generator can also provide a fixed magnitude sinusoidal signal even if the utility grid is disconnected and automatically re-synchronous with the grid rapidly. Consequently, seamless transfer between grid-connected and stand-alone modes could easily be achieved if anti-islanding protection is not required. If a saturation element is applied to the raw reference signal followed by the synthesis of the truncated signal using a multi-level inverter, the distinct flat-top feature of the synthesized signal can quickly and easily be identified if the network is in islanding mode at the point of common coupling. Experimental results are included to demonstrate the effectiveness of the proposed detection scheme

An investigation of face and fingerprint feature-fusion guidelines

CSIR Research Space (South Africa)

Brown, Dane

2016-05-01

Full Text Available There are a lack of multi-modal biometric fusion guidelines at the feature-level. This paper investigates face and fingerprint features in the form of their strengths and weaknesses. This serves as a set of guidelines to authors that are planning...

Morphometric analysis of cinder cones on Tenerife (Canary Islands, Spain): results and applications

International Nuclear Information System (INIS)

Doniz Paez, F. J.

2009-01-01

This paper applied morphometric to the cinder cones of Tenerife. The technical morphometric allows to establish simple models of morphology, and size to the most frequent volcanoes of Tenerife's mafic volcanism. The obtained classification allow to distinguish four morphological types of scoria cones and three size groups, which is also extended to other volcanic regions. (Author) 5 refs.

Histopathological and Digital Morphometrical Evaluation of Uterine Leiomyoma in Brazilian Women

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Ana Paula Fernandes da Silva

2016-01-01

Full Text Available The current study aims to evaluate histopathological and digital morphometrical aspects associated with uterine leiomyomas in one hundred and fifty (150 patients diagnosed with leiomyoma. Uterine tissues were subjected to the histopathological and digital morphometric analyses of the interstitial collagen distribution. The analysis of medical records indicates that most of the women diagnosed with uterine leiomyomas (68.7% are between 37 and 48 years old. As for the anatomic location of the tumors, approximately 61.4% of the patients had intramural and subserosal lesions. In 50% of the studied cases, the patients developed uterine leiomyomatosis (with more than eight tumors. As for the morphometric study, the average size of the interstitial collagen distribution held approximately 28.53% of the capture area, whereas it was of 7.43% in the normal tissue adjacent to the tumor. Another important aspect observed in the current study was the high rate of young women subjected to total hysterectomy, a fact that resulted in early and definitive sterility.

Level of energy restriction alters body condition score and morphometric profile in obese Shetland ponies.

Science.gov (United States)

Bruynsteen, L; Moons, C P H; Janssens, G P J; Harris, P A; Vandevelde, K; Lefère, L; Duchateau, L; Hesta, M

2015-10-01

Due to the high prevalence of obesity in some horses and ponies (especially in the leisure horse sector), effective and safe weight loss strategies are required. The present study evaluated the effect of two different energy restriction rates on physical, morphometric and welfare parameters in 18 obese (body condition score [BCS] 7-9/9) Shetland geldings. The trial was divided into three periods: (1) a 4 week adaptation period, during which the maintenance energy intakes to maintain a stable obese bodyweight were determined (100% MERob); (2) a 16.5-week weight loss period during which the ponies were randomly divided into three groups (n = 6/group) comprising a control group (CONTROL), moderate energy restricted (MOD), and severe energy restricted (SEV) groups that were respectively fed at 100%, 80% and 60% of their individual MERob; and (3) a 3 week follow up period in which the ponies were again fed at their outset individual 100% MERob. Between the start and end of the weight loss period, significant pairwise differences between the three treatment groups were seen for bodyweight, BCS, heart girth, belly girth, and relative ultrasound fat depth at the level of loin and ribs at several time points (P < 0.05). The higher energy restriction was associated with a faster decrease in BCS, tail head, and heart plus belly girth, but no gastric ulcers or stereotypic behaviours were seen. Copyright © 2015 Elsevier Ltd. All rights reserved.

In situ morphometric survey elucidates the evolutionary systematics of the Eurasian Himantoglossum clade (Orchidaceae: Orchidinae

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Richard M. Bateman

2017-01-01

Full Text Available Background and Aims The charismatic Himantoglossum s.l. clade of Eurasian orchids contains an unusually large proportion of taxa that are of controversial circumscriptions and considerable conservation concern. Whereas our previously published study addressed the molecular phylogenetics and phylogeography of every named taxon within the clade, here we use detailed morphometric data obtained from the same populations to compare genotypes with associated phenotypes, in order to better explore taxonomic circumscription and character evolution within the clade. Methods Between one and 12 plants found in 25 populations that encompassed the entire distribution of the Himantoglossum s.l. clade were measured in situ for 51 morphological characters. Results for 45 of those characters were subjected to detailed multivariate and univariate analyses. Key Results Multivariate analyses readily separate subgenus Barlia and subgenus Comperia from subgenus Himantoglossum, and also the early-divergent H. formosum from the less divergent remainder of subgenus Himantoglossum. The sequence of divergence of these four lineages is confidently resolved. Our experimental approach to morphometric character analysis demonstrates clearly that phenotypic evolution within Himantoglossum is unusually multi-dimensional. Conclusions Degrees of divergence between taxa shown by morphological analyses approximate those previously shown using molecular analyses. Himantoglossum s.l. is readily divisible into three subgenera. The three sections of subgenus Himantoglossum—hircinum, caprinum and formosum—are arrayed from west to east with only limited geographical overlap. At this taxonomic level, their juxtaposition combines with conflict between contrasting datasets to complicate attempts to distinguish between clinal variation and the discontinuities that by definition separate bona fide species. All taxa achieve allogamy via food deceit and have only weak pollinator specificity

High prevalence of morphometric vertebral deformities in patients with inflammatory bowel disease.

Science.gov (United States)

Heijckmann, Anna Caroline; Huijberts, Maya S P; Schoon, Erik J; Geusens, Piet; de Vries, Jolanda; Menheere, Paul P C A; van der Veer, Eveline; Wolffenbuttel, Bruce H R; Stockbrugger, Reinhold W; Dumitrescu, Bianca; Nieuwenhuijzen Kruseman, Arie C

2008-08-01

Earlier studies have documented that the prevalence of decreased bone mineral density (BMD) is elevated in patients with inflammatory bowel disease. The objective of this study was to investigate the prevalence of vertebral deformities in inflammatory bowel disease patients and their relation with BMD and bone turnover. One hundred and nine patients with Crohn's disease (CD) and 72 with ulcerative colitis (UC) (age 44.5+/-14.2 years) were studied. BMD of the hip (by dual X-ray absorptiometry) was measured and a lateral single energy densitometry of the spine for assessment of vertebral deformities was performed. Serum markers of bone resorption (carboxy-terminal cross-linked telopeptide of type I collagen) and formation (procollagen type I amino-terminal propeptide) were measured, and determinants of prevalent vertebral deformities were assessed using logistic regression analysis. Vertebral deformities were found in 25% of both CD and UC patients. Comparing patients with and without vertebral deformities, no significant difference was found between Z-scores and T-scores of BMD, or levels of serum carboxy-terminal cross-linked telopeptide of type I collagen and serum procollagen type I amino-terminal propeptide. Using logistic regression analysis the only determinant of any morphometric vertebral deformity was sex. The presence of multiple vertebral deformities was associated with older age and glucocorticoid use. The prevalence of morphometric vertebral deformities is high in CD and UC. Male sex, but neither disease activity, bone turnover markers, clinical risk factors, nor BMD predicted their presence. The determinants for having more than one vertebral deformity were age and glucocorticoid use. This implies that in addition to screening for low BMD, morphometric assessment of vertebral deformities is warranted in CD and UC.

Multi-floor cascading ferroelectric nanostructures: multiple data writing-based multi-level non-volatile memory devices

Science.gov (United States)

Hyun, Seung; Kwon, Owoong; Lee, Bom-Yi; Seol, Daehee; Park, Beomjin; Lee, Jae Yong; Lee, Ju Hyun; Kim, Yunseok; Kim, Jin Kon

2016-01-01

Multiple data writing-based multi-level non-volatile memory has gained strong attention for next-generation memory devices to quickly accommodate an extremely large number of data bits because it is capable of storing multiple data bits in a single memory cell at once. However, all previously reported devices have failed to store a large number of data bits due to the macroscale cell size and have not allowed fast access to the stored data due to slow single data writing. Here, we introduce a novel three-dimensional multi-floor cascading polymeric ferroelectric nanostructure, successfully operating as an individual cell. In one cell, each floor has its own piezoresponse and the piezoresponse of one floor can be modulated by the bias voltage applied to the other floor, which means simultaneously written data bits in both floors can be identified. This could achieve multi-level memory through a multiple data writing process.Multiple data writing-based multi-level non-volatile memory has gained strong attention for next-generation memory devices to quickly accommodate an extremely large number of data bits because it is capable of storing multiple data bits in a single memory cell at once. However, all previously reported devices have failed to store a large number of data bits due to the macroscale cell size and have not allowed fast access to the stored data due to slow single data writing. Here, we introduce a novel three-dimensional multi-floor cascading polymeric ferroelectric nanostructure, successfully operating as an individual cell. In one cell, each floor has its own piezoresponse and the piezoresponse of one floor can be modulated by the bias voltage applied to the other floor, which means simultaneously written data bits in both floors can be identified. This could achieve multi-level memory through a multiple data writing process. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr07377d

Vehicle logo recognition using multi-level fusion model

Science.gov (United States)

Ming, Wei; Xiao, Jianli

2018-04-01

Vehicle logo recognition plays an important role in manufacturer identification and vehicle recognition. This paper proposes a new vehicle logo recognition algorithm. It has a hierarchical framework, which consists of two fusion levels. At the first level, a feature fusion model is employed to map the original features to a higher dimension feature space. In this space, the vehicle logos become more recognizable. At the second level, a weighted voting strategy is proposed to promote the accuracy and the robustness of the recognition results. To evaluate the performance of the proposed algorithm, extensive experiments are performed, which demonstrate that the proposed algorithm can achieve high recognition accuracy and work robustly.

Flexible feature-space-construction architecture and its VLSI implementation for multi-scale object detection

Science.gov (United States)

Luo, Aiwen; An, Fengwei; Zhang, Xiangyu; Chen, Lei; Huang, Zunkai; Jürgen Mattausch, Hans

2018-04-01

Feature extraction techniques are a cornerstone of object detection in computer-vision-based applications. The detection performance of vison-based detection systems is often degraded by, e.g., changes in the illumination intensity of the light source, foreground-background contrast variations or automatic gain control from the camera. In order to avoid such degradation effects, we present a block-based L1-norm-circuit architecture which is configurable for different image-cell sizes, cell-based feature descriptors and image resolutions according to customization parameters from the circuit input. The incorporated flexibility in both the image resolution and the cell size for multi-scale image pyramids leads to lower computational complexity and power consumption. Additionally, an object-detection prototype for performance evaluation in 65 nm CMOS implements the proposed L1-norm circuit together with a histogram of oriented gradients (HOG) descriptor and a support vector machine (SVM) classifier. The proposed parallel architecture with high hardware efficiency enables real-time processing, high detection robustness, small chip-core area as well as low power consumption for multi-scale object detection.

Features, Events, and Processes: System Level

Energy Technology Data Exchange (ETDEWEB)

D. McGregor

2004-04-19

The primary purpose of this analysis is to evaluate System Level features, events, and processes (FEPs). The System Level FEPs typically are overarching in nature, rather than being focused on a particular process or subsystem. As a result, they are best dealt with at the system level rather than addressed within supporting process-level or subsystem level analyses and models reports. The System Level FEPs also tend to be directly addressed by regulations, guidance documents, or assumptions listed in the regulations; or are addressed in background information used in development of the regulations. This evaluation determines which of the System Level FEPs are excluded from modeling used to support the total system performance assessment for license application (TSPA-LA). The evaluation is based on the information presented in analysis reports, model reports, direct input, or corroborative documents that are cited in the individual FEP discussions in Section 6.2 of this analysis report.

A collision dynamics model of a multi-level train

Science.gov (United States)

2006-11-05

In train collisions, multi-level rail passenger vehicles can deform in modes that are different from the behavior of single level cars. The deformation in single level cars usually occurs at the front end during a collision. In one particular inciden...

A morphometry map and a new method for honey bee morphometric analysis by using the ArcGIS

Directory of Open Access Journals (Sweden)

Hossam F. Abou-Shaara

2013-12-01

Full Text Available The morphometric analysis of honey bees has a substantial importance for honey bee subspecies characterization and discrimination while the ArcGIS is a geographical program for data analysis. In the present research, the combination between the morphometric data and the spatial analysis options of the ArcGIS was done and subsequently tested in creating a morphometry map for honey bees from some regions in Egypt as well as for the discrimination between two honey bee subspecies. Therefore, I present a model for creating the morphometry maps and a new method for the morphometric analysis by the transformation of the morphometric data to raster data layers. The obtained results showed that the created morphometry map classified the regions successfully according to the morphological character means. The morphometric analysis was successfully performed by using trend analysis and raster difference range. The analysis of the morphometric data as raster layers showed high sensitivity for the differences between subspecies and regions. The presented model and the method are effective and can be applied for the discrimination between subspecies, regions and colonies as well as can be used with other insects.

Full-color, large area, transmissive holograms enabled by multi-level diffractive optics.

Science.gov (United States)

Mohammad, Nabil; Meem, Monjurul; Wan, Xiaowen; Menon, Rajesh

2017-07-19

We show that multi-level diffractive microstructures can enable broadband, on-axis transmissive holograms that can project complex full-color images, which are invariant to viewing angle. Compared to alternatives like metaholograms, diffractive holograms utilize much larger minimum features (>10 µm), much smaller aspect ratios (30 mm ×30 mm). We designed, fabricated and characterized holograms that encode various full-color images. Our devices demonstrate absolute transmission efficiencies of >86% across the visible spectrum from 405 nm to 633 nm (peak value of about 92%), and excellent color fidelity. Furthermore, these devices do not exhibit polarization dependence. Finally, we emphasize that our devices exhibit negligible absorption and are phase-only holograms with high diffraction efficiency.

Multi-level machine learning prediction of protein–protein interactions in Saccharomyces cerevisiae

Directory of Open Access Journals (Sweden)

Julian Zubek

2015-07-01

Full Text Available Accurate identification of protein–protein interactions (PPI is the key step in understanding proteins’ biological functions, which are typically context-dependent. Many existing PPI predictors rely on aggregated features from protein sequences, however only a few methods exploit local information about specific residue contacts. In this work we present a two-stage machine learning approach for prediction of protein–protein interactions. We start with the carefully filtered data on protein complexes available for Saccharomyces cerevisiae in the Protein Data Bank (PDB database. First, we build linear descriptions of interacting and non-interacting sequence segment pairs based on their inter-residue distances. Secondly, we train machine learning classifiers to predict binary segment interactions for any two short sequence fragments. The final prediction of the protein–protein interaction is done using the 2D matrix representation of all-against-all possible interacting sequence segments of both analysed proteins. The level-I predictor achieves 0.88 AUC for micro-scale, i.e., residue-level prediction. The level-II predictor improves the results further by a more complex learning paradigm. We perform 30-fold macro-scale, i.e., protein-level cross-validation experiment. The level-II predictor using PSIPRED-predicted secondary structure reaches 0.70 precision, 0.68 recall, and 0.70 AUC, whereas other popular methods provide results below 0.6 threshold (recall, precision, AUC. Our results demonstrate that multi-scale sequence features aggregation procedure is able to improve the machine learning results by more than 10% as compared to other sequence representations. Prepared datasets and source code for our experimental pipeline are freely available for download from: http://zubekj.github.io/mlppi/ (open source Python implementation, OS independent.

[Automated morphometric evaluation of the chromatin structure of liver cell nuclei after vagotomy].

Science.gov (United States)

Butusova, N N; Zhukotskiĭ, A V; Sherbo, I V; Gribkov, E N; Dubovaia, T K

1989-05-01

The morphometric analysis of the interphase chromatine structure of the hepatic cells nuclei was carried out on the automated TV installation for the quantitative analysis of images "IBAS-2" (by the OPTON firm, the FRG) according to 50 optical and geometric parameters during various periods (1.2 and 4 weeks) after the vagotomy operation. It is determined that upper-molecular organisation of chromatine undergoes the biggest changes one week after operation, and changes of granular component are more informative than changes of the nongranular component (with the difference 15-20%). It was also revealed that chromatine components differ in tinctorial properties, which are evidently dependent on physicochemical characteristics of the chromatine under various functional conditions of the cell. As a result of the correlation analysis the group of morphometric indices of chromatine structure was revealed, which are highly correlated with level of transcription activity of chromatine during various terms after denervation. The correlation quotient of these parameters is 0.85-0.97. The summing up: vagus denervation of the liver causes changes in the morphofunctional organisation of the chromatine.

MORPHOMETRIC EVIDENCE FOR NUTRITIONAL STRESS IN ENGLISH SOLE

Science.gov (United States)

We present an application of the powerful thin plate spline method of morphometric analysis to demonstrate its utility for detecting environmental stress in an estuarine flatfish. Juvenile English sole (Pleuronectes vetulus) were captured from Yaquina Bay, Oregon, photographed w...

Reviewing the upper Pleistocene human footprints from the 'Sala dei Misteri' in the Grotta della Bàsura (Toirano, northern Italy) cave: An integrated morphometric and morpho-classificatory approach

Science.gov (United States)

Paolo Citton; Romano, Marco; Salvador, Isabella; Avanzini, Marco

2017-08-01

About thirty human footprints made approximately 12,000 years B.P. inside the 'Sala dei Misteri' Cave of Básura near Toirano, Liguria, northern Italy, were studied by standard ichnological analysis. Eleven of the best-preserved tracks were examined further using morpho-classificatory and morphometric approaches, in order to estimate the minimum number of trackmakers; biometric measurements were also used to tentatively determine their physical characteristics (e.g., height and age). Results indicate at least three different producers, two youths and the third of tender age. Analysis of the data demonstrate the power of 3D, of landmark-based morphometrics, and the utility of methods of forensic anthropology in the determination of human footprints. The study of the number of trackmakers using the principal component analysis (PCA) on 'multi-trampling' surfaces could represent a model in the ichnological study of cave sites.

Loggerhead sea turtle oral cavity morphometrics and size class from 2001 to 2004 (NCEI Accession 0164321)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This data set contains standard external morphometrics and internal oral cavity morphometrics from wild and captive reared loggerhead sea turtles in size classes...

Processing of word stress related acoustic information: A multi-feature MMN study.

Science.gov (United States)

Honbolygó, Ferenc; Kolozsvári, Orsolya; Csépe, Valéria

2017-08-01

In the present study, we investigated the processing of word stress related acoustic features in a word context. In a passive oddball multi-feature MMN experiment, we presented a disyllabic pseudo-word with two acoustically similar syllables as standard stimulus, and five contrasting deviants that differed from the standard in that they were either stressed on the first syllable or contained a vowel change. Stress was realized by an increase of f0, intensity, vowel duration or consonant duration. The vowel change was used to investigate if phonemic and prosodic changes elicit different MMN components. As a control condition, we presented non-speech counterparts of the speech stimuli. Results showed all but one feature (non-speech intensity deviant) eliciting the MMN component, which was larger for speech compared to non-speech stimuli. Two other components showed stimulus related effects: the N350 and the LDN (Late Discriminative Negativity). The N350 appeared to the vowel duration and consonant duration deviants, specifically to features related to the temporal characteristics of stimuli, while the LDN was present for all features, and it was larger for speech than for non-speech stimuli. We also found that the f0 and consonant duration features elicited a larger MMN than other features. These results suggest that stress as a phonological feature is processed based on long-term representations, and listeners show a specific sensitivity to segmental and suprasegmental cues signaling the prosodic boundaries of words. These findings support a two-stage model in the perception of stress and phoneme related acoustical information. Copyright © 2017 Elsevier B.V. All rights reserved.

Morphometric analyses of the river basins in Goa

Digital Repository Service at National Institute of Oceanography (India)

Iyer, S.D.; Wagle, B.G.

Morphometric analyses of seven river basins in Goa, India have been carried out. The linear and areal aspects of these basins are reported here. The plots of stream order versus stream numbers and stream orders versus mean stream lengths are found...

A comparative study of different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron

OpenAIRE

Das, Nibaran; Mollah, Ayatullah Faruk; Sarkar, Ram; Basu, Subhadip

2010-01-01

The work presents a comparative assessment of seven different feature sets for recognition of handwritten Arabic numerals using a Multi Layer Perceptron (MLP) based classifier. The seven feature sets employed here consist of shadow features, octant centroids, longest runs, angular distances, effective spans, dynamic centers of gravity, and some of their combinations. On experimentation with a database of 3000 samples, the maximum recognition rate of 95.80% is observed with both of two separat...

A Depth Video-based Human Detection and Activity Recognition using Multi-features and Embedded Hidden Markov Models for Health Care Monitoring Systems

Directory of Open Access Journals (Sweden)

Ahmad Jalal

2017-08-01

Full Text Available Increase in number of elderly people who are living independently needs especial care in the form of healthcare monitoring systems. Recent advancements in depth video technologies have made human activity recognition (HAR realizable for elderly healthcare applications. In this paper, a depth video-based novel method for HAR is presented using robust multi-features and embedded Hidden Markov Models (HMMs to recognize daily life activities of elderly people living alone in indoor environment such as smart homes. In the proposed HAR framework, initially, depth maps are analyzed by temporal motion identification method to segment human silhouettes from noisy background and compute depth silhouette area for each activity to track human movements in a scene. Several representative features, including invariant, multi-view differentiation and spatiotemporal body joints features were fused together to explore gradient orientation change, intensity differentiation, temporal variation and local motion of specific body parts. Then, these features are processed by the dynamics of their respective class and learned, modeled, trained and recognized with specific embedded HMM having active feature values. Furthermore, we construct a new online human activity dataset by a depth sensor to evaluate the proposed features. Our experiments on three depth datasets demonstrated that the proposed multi-features are efficient and robust over the state of the art features for human action and activity recognition.

Morphometric analysis of the mandible in the Durban Metropolitan population of South Africa.

Science.gov (United States)

Ishwarkumar, S; Pillay, P; Haffajee, M R; Satyapal, K S

2017-01-01

The identification of an individual from skeletal remains plays a vital role in forensic investigation as it is essential for the identification of the individual's age, sex, and/or race and further analysis. Skeletal characteristics differ from one population group to another since population-specific osteometric standards exist for sex determination. Since the mandible is the largest, strongest and most durable compact facial bone, it is the best preserved after death. While sexual dimorphism of the mandible is indicated by its shape and size, morphometric analysis is more accurate in the determination of sex from the skull. The aim of this study was to evaluate the morphometric parameters of the mandible in the Durban Metropolitan population. Various morphometric parameters of the mandible were measured and assessed in 265 digital panoramic radiographs aged between 16 and 30 years (n = 530). Each parameter recorded was statistically analysed using SPSS to determine if a relationship existed between the parameter, and sex and age. In this study the morphometric parameters of the male mandibles were greater than that of the females. This concurred with the findings of previous studies. The length of the mandibular ramus on the right and left sides was statistically significant with sex. This correlated with previous studies, indicating that the length of the mandibular ramus generally has higher sexual dimorphism than any other morphometric mandibular parameter (p = 0.000). However, only the length of the right mandibular body was statistically significant when compared with sex (p = 0.040). The findings of this study may assist forensic investigators, anatomists, anthropologists and maxillo-facial surgeons.

Jupiter's Multi-level Clouds

Science.gov (United States)

1997-01-01

Clouds and hazes at various altitudes within the dynamic Jovian atmosphere are revealed by multi-color imaging taken by the Near-Infrared Mapping Spectrometer (NIMS) onboard the Galileo spacecraft. These images were taken during the second orbit (G2) on September 5, 1996 from an early-morning vantage point 2.1 million kilometers (1.3 million miles) above Jupiter. They show the planet's appearance as viewed at various near-infrared wavelengths, with distinct differences due primarily to variations in the altitudes and opacities of the cloud systems. The top left and right images, taken at 1.61 microns and 2.73 microns respectively, show relatively clear views of the deep atmosphere, with clouds down to a level about three times the atmospheric pressure at the Earth's surface.By contrast, the middle image in top row, taken at 2.17 microns, shows only the highest altitude clouds and hazes. This wavelength is severely affected by the absorption of light by hydrogen gas, the main constituent of Jupiter's atmosphere. Therefore, only the Great Red Spot, the highest equatorial clouds, a small feature at mid-northern latitudes, and thin, high photochemical polar hazes can be seen. In the lower left image, at 3.01 microns, deeper clouds can be seen dimly against gaseous ammonia and methane absorption. In the lower middle image, at 4.99 microns, the light observed is the planet's own indigenous heat from the deep, warm atmosphere.The false color image (lower right) succinctly shows various cloud and haze levels seen in the Jovian atmosphere. This image indicates the temperature and altitude at which the light being observed is produced. Thermally-rich red areas denote high temperatures from photons in the deep atmosphere leaking through minimal cloud cover; green denotes cool temperatures of the tropospheric clouds; blue denotes cold of the upper troposphere and lower stratosphere. The polar regions appear purplish, because small-particle hazes allow leakage and reflectivity

Sensor-Based Auto-Focusing System Using Multi-Scale Feature Extraction and Phase Correlation Matching

Directory of Open Access Journals (Sweden)

Jinbeum Jang

2015-03-01

Full Text Available This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing system. In order to solve this problem, a multi-resolution feature extraction algorithm is proposed. Given the extracted features, the proposed auto-focusing system can provide the ideal focusing position using phase correlation matching. The proposed auto-focusing (AF algorithm consists of four steps: (i acquisition of left and right images using AF points in the region-of-interest; (ii feature extraction in the left image under low illumination and out-of-focus blur; (iii the generation of two feature images using the phase difference between the left and right images; and (iv estimation of the phase shifting vector using phase correlation matching. Since the proposed system accurately estimates the phase difference in the out-of-focus blurred image under low illumination, it can provide faster, more robust auto focusing than existing systems.

Interevent time distributions of human multi-level activity in a virtual world

Science.gov (United States)

Mryglod, O.; Fuchs, B.; Szell, M.; Holovatch, Yu.; Thurner, S.

2015-02-01

Studying human behavior in virtual environments provides extraordinary opportunities for a quantitative analysis of social phenomena with levels of accuracy that approach those of the natural sciences. In this paper we use records of player activities in the massive multiplayer online game Pardus over 1238 consecutive days, and analyze dynamical features of sequences of actions of players. We build on previous work where temporal structures of human actions of the same type were quantified, and provide an empirical understanding of human actions of different types. This study of multi-level human activity can be seen as a dynamic counterpart of static multiplex network analysis. We show that the interevent time distributions of actions in the Pardus universe follow highly non-trivial distribution functions, from which we extract action-type specific characteristic 'decay constants'. We discuss characteristic features of interevent time distributions, including periodic patterns on different time scales, bursty dynamics, and various functional forms on different time scales. We comment on gender differences of players in emotional actions, and find that while males and females act similarly when performing some positive actions, females are slightly faster for negative actions. We also observe effects on the age of players: more experienced players are generally faster in making decisions about engaging in and terminating enmity and friendship, respectively.

Two-Level Evaluation on Sensor Interoperability of Features in Fingerprint Image Segmentation

Directory of Open Access Journals (Sweden)

Ya-Shuo Li

2012-03-01

Full Text Available Features used in fingerprint segmentation significantly affect the segmentation performance. Various features exhibit different discriminating abilities on fingerprint images derived from different sensors. One feature which has better discriminating ability on images derived from a certain sensor may not adapt to segment images derived from other sensors. This degrades the segmentation performance. This paper empirically analyzes the sensor interoperability problem of segmentation feature, which refers to the feature’s ability to adapt to the raw fingerprints captured by different sensors. To address this issue, this paper presents a two-level feature evaluation method, including the first level feature evaluation based on segmentation error rate and the second level feature evaluation based on decision tree. The proposed method is performed on a number of fingerprint databases which are obtained from various sensors. Experimental results show that the proposed method can effectively evaluate the sensor interoperability of features, and the features with good evaluation results acquire better segmentation accuracies of images originating from different sensors.

Multi-level analysis in information systems research: the case of enterprise resource planning system usage in China

Science.gov (United States)

Sun, Yuan; Bhattacherjee, Anol

2011-11-01

Information technology (IT) usage within organisations is a multi-level phenomenon that is influenced by individual-level and organisational-level variables. Yet, current theories, such as the unified theory of acceptance and use of technology, describe IT usage as solely an individual-level phenomenon. This article postulates a model of organisational IT usage that integrates salient organisational-level variables such as user training, top management support and technical support within an individual-level model to postulate a multi-level model of IT usage. The multi-level model was then empirically validated using multi-level data collected from 128 end users and 26 managers in 26 firms in China regarding their use of enterprise resource planning systems and analysed using the multi-level structural equation modelling (MSEM) technique. We demonstrate the utility of MSEM analysis of multi-level data relative to the more common structural equation modelling analysis of single-level data and show how single-level data can be aggregated to approximate multi-level analysis when multi-level data collection is not possible. We hope that this article will motivate future scholars to employ multi-level data and multi-level analysis for understanding organisational phenomena that are truly multi-level in nature.

STUDY OF MORPHOMETRIC CHANGES OF FOETAL STOMACH

Directory of Open Access Journals (Sweden)

Mohammed Aneesur Rahman

2017-07-01

Full Text Available BACKGROUND Interest in human development is very widespread largely because of the curiosity about our beginnings and desire to improve the quality of life. Understanding of the processes involved in the formation of various organs and systems has unrevealed most cryptic secrets of the nature. Human development begins at fertilisation when a male gamete or sperm unites with a female gamete or oocyte to form a single cell, a zygote. With the formation of zygote (single-celled stage, foetal development begins. The aim of the study is to- 1 Study the morphometric parameters of foetal stomach at various gestational ages. 2 Compare these observations with the previous studies. MATERIALS AND METHODS Present work was the cross-sectional study carried out in the Department of Anatomy in collaboration with the Department of Obstetrics and Gynaecology at SRTRGMC and Hospital, Ambajogai Dist., Beed, Maharashtra. For this, approval of Institutional Ethical Committee was taken. 30 aborted human foetuses of different age groups ranging from 12 to 36 weeks of fertilisation were taken from the Department of OB-GYN. Foetuses were preserved by using 10% formalin. Age of foetuses were determined by crown-rump length and history given by mother. Foetuses were dissected after preservation for 15 days and morphometric studies were done on stomach. RESULTS Various quantitative parameters like weight of foetus, crown-rump length, total length of stomach, weight of stomach, length of greater curvature, lesser curvature, width of cardia and width of pylorus were used. For the purpose of study and comparison with other researchers, the foetuses were divided into 3 groups. Morphometric changes were observed in different groups and compared with previous studies. CONCLUSION With the increase in the body weight, crown-rump length and gestational age of the foetus, there is gradual increase on various parameters of stomach.

Combining low level features and visual attributes for VHR remote sensing image classification

Science.gov (United States)

Zhao, Fumin; Sun, Hao; Liu, Shuai; Zhou, Shilin

2015-12-01

Semantic classification of very high resolution (VHR) remote sensing images is of great importance for land use or land cover investigation. A large number of approaches exploiting different kinds of low level feature have been proposed in the literature. Engineers are often frustrated by their conclusions and a systematic assessment of various low level features for VHR remote sensing image classification is needed. In this work, we firstly perform an extensive evaluation of eight features including HOG, dense SIFT, SSIM, GIST, Geo color, LBP, Texton and Tiny images for classification of three public available datasets. Secondly, we propose to transfer ground level scene attributes to remote sensing images. Thirdly, we combine both low-level features and mid-level visual attributes to further improve the classification performance. Experimental results demonstrate that i) Dene SIFT and HOG features are more robust than other features for VHR scene image description. ii) Visual attribute competes with a combination of low level features. iii) Multiple feature combination achieves the best performance under different settings.

Representation of Block-Based Image Features in a Multi-Scale Framework for Built-Up Area Detection

Directory of Open Access Journals (Sweden)

Zhongwen Hu

2016-02-01

Full Text Available The accurate extraction and mapping of built-up areas play an important role in many social, economic, and environmental studies. In this paper, we propose a novel approach for built-up area detection from high spatial resolution remote sensing images, using a block-based multi-scale feature representation framework. First, an image is divided into small blocks, in which the spectral, textural, and structural features are extracted and represented using a multi-scale framework; a set of refined Harris corner points is then used to select blocks as training samples; finally, a built-up index image is obtained by minimizing the normalized spectral, textural, and structural distances to the training samples, and a built-up area map is obtained by thresholding the index image. Experiments confirm that the proposed approach is effective for high-resolution optical and synthetic aperture radar images, with different scenes and different spatial resolutions.

Solving multi-objective job shop problem using nature-based algorithms: new Pareto approximation features

Directory of Open Access Journals (Sweden)

Jarosław Rudy

2015-01-01

Full Text Available In this paper the job shop scheduling problem (JSP with minimizing two criteria simultaneously is considered. JSP is frequently used model in real world applications of combinatorial optimization. Multi-objective job shop problems (MOJSP were rarely studied. We implement and compare two multi-agent nature-based methods, namely ant colony optimization (ACO and genetic algorithm (GA for MOJSP. Both of those methods employ certain technique, taken from the multi-criteria decision analysis in order to establish ranking of solutions. ACO and GA differ in a method of keeping information about previously found solutions and their quality, which affects the course of the search. In result, new features of Pareto approximations provided by said algorithms are observed: aside from the slight superiority of the ACO method the Pareto frontier approximations provided by both methods are disjoint sets. Thus, both methods can be used to search mutually exclusive areas of the Pareto frontier.

Multi-Level Security Cannot Realise NEC Objectives

NARCIS (Netherlands)

Schotanus, H.A.; Hartog, T.; Verkoelen, C.A.A.

2012-01-01

Multi-Level Security (MLS) is often viewed as the holy grail of information security, especially in those environments where information of different classifications is being processed. In this paper we argue that MLS cannot facilitate the right balance between need-to-protect and duty-to-share as

Morphometric analysis of Dactylorhiza hatagirea (D. Don), a critically ...

African Journals Online (AJOL)

Admin

2012-07-12

Jul 12, 2012 ... interplay of climate, geographical history and evolutionary dynamics in ... morphometric analysis of living plant (Dressler and. Dodson, 1960) and to the .... Number of flowers. 25. UPPINT ..... Classification and phylogeny in the.

Perturbational treatment of spin-orbit coupling for generally applicable high-level multi-reference methods

International Nuclear Information System (INIS)

Mai, Sebastian; Marquetand, Philipp; González, Leticia; Müller, Thomas; Plasser, Felix; Lischka, Hans

2014-01-01

An efficient perturbational treatment of spin-orbit coupling within the framework of high-level multi-reference techniques has been implemented in the most recent version of the COLUMBUS quantum chemistry package, extending the existing fully variational two-component (2c) multi-reference configuration interaction singles and doubles (MRCISD) method. The proposed scheme follows related implementations of quasi-degenerate perturbation theory (QDPT) model space techniques. Our model space is built either from uncontracted, large-scale scalar relativistic MRCISD wavefunctions or based on the scalar-relativistic solutions of the linear-response-theory-based multi-configurational averaged quadratic coupled cluster method (LRT-MRAQCC). The latter approach allows for a consistent, approximatively size-consistent and size-extensive treatment of spin-orbit coupling. The approach is described in detail and compared to a number of related techniques. The inherent accuracy of the QDPT approach is validated by comparing cuts of the potential energy surfaces of acrolein and its S, Se, and Te analoga with the corresponding data obtained from matching fully variational spin-orbit MRCISD calculations. The conceptual availability of approximate analytic gradients with respect to geometrical displacements is an attractive feature of the 2c-QDPT-MRCISD and 2c-QDPT-LRT-MRAQCC methods for structure optimization and ab inito molecular dynamics simulations

Perturbational treatment of spin-orbit coupling for generally applicable high-level multi-reference methods

Energy Technology Data Exchange (ETDEWEB)

Mai, Sebastian; Marquetand, Philipp; González, Leticia [Institute of Theoretical Chemistry, University of Vienna, Währinger Str. 17, 1090 Vienna (Austria); Müller, Thomas, E-mail: th.mueller@fz-juelich.de [Institute for Advanced Simulation, Jülich Supercomputing Centre, Forschungszentrum Jülich, 52425 Jülich (Germany); Plasser, Felix [Interdisciplinary Center for Scientific Computing, University of Heidelberg, Im Neuenheimer Feld 368, 69120 Heidelberg (Germany); Lischka, Hans [Institute of Theoretical Chemistry, University of Vienna, Währinger Str. 17, 1090 Vienna (Austria); Department of Chemistry and Biochemistry, Texas Tech University, Lubbock, Texas 79409-1061 (United States)

2014-08-21

An efficient perturbational treatment of spin-orbit coupling within the framework of high-level multi-reference techniques has been implemented in the most recent version of the COLUMBUS quantum chemistry package, extending the existing fully variational two-component (2c) multi-reference configuration interaction singles and doubles (MRCISD) method. The proposed scheme follows related implementations of quasi-degenerate perturbation theory (QDPT) model space techniques. Our model space is built either from uncontracted, large-scale scalar relativistic MRCISD wavefunctions or based on the scalar-relativistic solutions of the linear-response-theory-based multi-configurational averaged quadratic coupled cluster method (LRT-MRAQCC). The latter approach allows for a consistent, approximatively size-consistent and size-extensive treatment of spin-orbit coupling. The approach is described in detail and compared to a number of related techniques. The inherent accuracy of the QDPT approach is validated by comparing cuts of the potential energy surfaces of acrolein and its S, Se, and Te analoga with the corresponding data obtained from matching fully variational spin-orbit MRCISD calculations. The conceptual availability of approximate analytic gradients with respect to geometrical displacements is an attractive feature of the 2c-QDPT-MRCISD and 2c-QDPT-LRT-MRAQCC methods for structure optimization and ab inito molecular dynamics simulations.

Multi-phase flow monitoring with electrical impedance tomography using level set based method

International Nuclear Information System (INIS)

Liu, Dong; Khambampati, Anil Kumar; Kim, Sin; Kim, Kyung Youn

2015-01-01

Highlights: • LSM has been used for shape reconstruction to monitor multi-phase flow using EIT. • Multi-phase level set model for conductivity is represented by two level set functions. • LSM handles topological merging and breaking naturally during evolution process. • To reduce the computational time, a narrowband technique was applied. • Use of narrowband and optimization approach results in efficient and fast method. - Abstract: In this paper, a level set-based reconstruction scheme is applied to multi-phase flow monitoring using electrical impedance tomography (EIT). The proposed scheme involves applying a narrowband level set method to solve the inverse problem of finding the interface between the regions having different conductivity values. The multi-phase level set model for the conductivity distribution inside the domain is represented by two level set functions. The key principle of the level set-based method is to implicitly represent the shape of interface as the zero level set of higher dimensional function and then solve a set of partial differential equations. The level set-based scheme handles topological merging and breaking naturally during the evolution process. It also offers several advantages compared to traditional pixel-based approach. Level set-based method for multi-phase flow is tested with numerical and experimental data. It is found that level set-based method has better reconstruction performance when compared to pixel-based method

Healthy full-term infants' brain responses to emotionally and linguistically relevant sounds using a multi-feature mismatch negativity (MMN) paradigm.

Science.gov (United States)

Kostilainen, Kaisamari; Wikström, Valtteri; Pakarinen, Satu; Videman, Mari; Karlsson, Linnea; Keskinen, Maria; Scheinin, Noora M; Karlsson, Hasse; Huotilainen, Minna

2018-03-23

We evaluated the feasibility of a multi-feature mismatch negativity (MMN) paradigm in studying auditory processing of healthy newborns. The aim was to examine the automatic change-detection and processing of semantic and emotional information in speech in newborns. Brain responses of 202 healthy newborns were recorded with a multi-feature paradigm including a Finnish bi-syllabic pseudo-word/ta-ta/as a standard stimulus, six linguistically relevant deviant stimuli and three emotionally relevant stimuli (happy, sad, angry). Clear responses to emotional sounds were found already at the early latency window 100-200 ms, whereas responses to linguistically relevant minor changes and emotional stimuli at the later latency window 300-500 ms did not reach significance. Moreover, significant interaction between gender and emotional stimuli was found in the early latency window. Further studies on using multi-feature paradigms with linguistic and emotional stimuli in newborns are needed, especially those containing of follow-ups, enabling the assessment of the predictive value of early variations between subjects. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Detecting bots using multi-level traffic analysis

DEFF Research Database (Denmark)

Stevanovic, Matija; Pedersen, Jens Myrup

2016-01-01

introduces a novel multi-level botnet detection approach that performs network traffic analysis of three protocols widely considered as the main carriers of botnet Command and Control (C&C) and attack traffic, i.e. TCP, UDP and DNS. The proposed method relies on supervised machine learning for identifying...

First metatarsophalangeal joint motion in Homo sapiens: theoretical association of two-axis kinematics and specific morphometrics.

Science.gov (United States)

Durrant, Michael N; McElroy, Tucker; Durrant, Lara

2012-01-01

The metatarsal head and proximal phalanx exhibit considerable asymmetry in their shape and geometry, but there is little documentation in the literature regarding the prevalence of structural characteristics that occur in a given population. Although there is a considerable volume of in vivo and in vitro experiments demonstrating first metatarsal inversion around its longitudinal axis with dorsiflexion, little is known regarding the applicability of specific morphometrics to these motions. Nine distinctive osseous characteristics in the metatarsal head and phalanx were selected based on their location, geometry, and perceived functional relationship to previous studies describing metatarsal motion as inversion with dorsiflexion. The prevalences of the chosen characteristics were determined in a cohort of 21 randomly selected skeletal specimens, 19 of which were provided by the anatomical preparation office at the University of California, San Diego, and two of which were in the possession of one of us (M.D.). The frequency of occurrence of each selected morphological characteristic in this sample and the relevant summary statistics confirm a strong association between the selected features and a conceptual two-axis kinematic model of the metatarsophalangeal joint. The selected morphometrics are consistent with inversion of the metatarsal around its longitudinal axis as it dorsiflexes.

Multi-level and Multi-component Bitmap Encoding for Efficient Search Operations

Directory of Open Access Journals (Sweden)

Madhu BHAN, Department of Computer Applications

2012-12-01

Full Text Available The growing interest in data warehousing for decision makers is becoming more and more crucial to make faster and efficient decisions. On-line decision needs short response times. Many indexing techniques have been created to achieve this goal in read only environments. Indexing technique that has attracted attention in multidimensional databases is Bitmap Indexing. The paper discusses the various existing bitmap indexing techniques along with their performance characteristics. The paper proposes two new bitmap indexing techniques in the class of multi-level and multi-component encoding schemes and prove that the two techniques have better space–time performance than some of the existing techniques used for range queries. We provide an analytical model for comparing the performance of our proposed encoding schemes with that of the existing ones.

An insight into morphometric descriptors of cell shape that pertain to regenerative medicine.

Science.gov (United States)

Lobo, Joana; See, Eugene Yong-Shun; Biggs, Manus; Pandit, Abhay

2016-07-01

Cellular morphology has recently been indicated as a powerful indicator of cellular function. The analysis of cell shape has evolved from rudimentary forms of microscopic visual inspection to more advanced methodologies that utilize high-resolution microscopy coupled with sophisticated computer hardware and software for data analysis. Despite this progress, there is still a lack of standardization in quantification of morphometric parameters. In addition, uncertainty remains as to which methodologies and parameters of cell morphology will yield meaningful data, which methods should be utilized to categorize cell shape, and the extent of reliability of measurements and the interpretation of the resulting analysis. A large range of descriptors has been employed to objectively assess the cellular morphology in two-dimensional and three-dimensional domains. Intuitively, simple and applicable morphometric descriptors are preferable and standardized protocols for cell shape analysis can be achieved with the help of computerized tools. In this review, cellular morphology is discussed as a descriptor of cellular function and the current morphometric parameters that are used quantitatively in two- and three-dimensional environments are described. Furthermore, the current problems associated with these morphometric measurements are addressed. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Conformation of phylogenetic relationship of Penaeidae shrimp based on morphometric and molecular investigations.

Science.gov (United States)

Rajakumaran, P; Vaseeharan, B; Jayakumar, R; Chidambara, R

2014-01-01

Understanding of accurate phylogenetic relationship among Penaeidae shrimp is important for academic and fisheries industry. The Morphometric and Randomly amplified polymorphic DNA (RAPD) analysis was used to make the phylogenetic relationsip among 13 Penaeidae shrimp. For morphometric analysis forty variables and total lengths of shrimp were measured for each species, and removed the effect of size variation. The size normalized values obtained was subjected to UPGMA (Unweighted Pair-Group Method with Arithmetic Mean) cluster analysis. For RAPD analysis, the four primers showed reliable differentiation between species, and used correlation coefficient between the DNA banding patterns of 13 Penaeidae species to construct UPGMA dendrogram. Phylogenetic relationship from morphometric and molecular analysis for Penaeidae species found to be congruent. We concluded that as the results from morphometry investigations concur with molecular one, phylogenetic relationship obtained for the studied Penaeidae are considered to be reliable.

Morphometric Analysis to Prioritize Sub-Watershed for Flood Risk Assessment in Central Karakoram National Park Using Gis/rs Approach

Science.gov (United States)

Syed, N. H.; Rehman, A. A.; Hussain, D.; Ishaq, S.; Khan, A. A.

2017-11-01

Morphometric analysis is vital for any watershed investigation and it is inevitable for flood risk assessment in sub-watershed basins. Present study undertaken to carry out critical evaluation and assessment of sub watershed morphological parameters for flood risk assessment of Central Karakorum National Park (CKNP), where Geographical information system and remote sensing (GIS & RS) approach used for quantifying the parameter and mapping of sub watershed units. ASTER DEM used as a geo-spatial data for watershed delineation and stream network. Morphometric analysis carried out using spatial analyst tool of ArcGIS 10.2. The parameters included were bifurcation ratio (Rb), Drainage Texture (Rt), Circulatory ratio (Rc), Elongated ratio (Re), Drainage density (Dd), Stream Length (Lu), Stream order (Su), Slope and Basin length (Lb) have calculated separately. The analysis revealed that the stream order varies from order 1 to 6 and the total numbers of stream segments of all orders were 52. Multi criteria analysis process used to calculate the risk factor. As an accomplished result, map of sub watershed prioritization developed using weighted standardized risk factor. These results helped to understand sensitivity of flush floods in different sub watersheds of the study area and leaded to better management of the mountainous regions in prospect of flush floods.

Application of Multilevel Models to Morphometric Data. Part 1. Linear Models and Hypothesis Testing

Directory of Open Access Journals (Sweden)

O. Tsybrovskyy

2003-01-01

Full Text Available Morphometric data usually have a hierarchical structure (i.e., cells are nested within patients, which should be taken into consideration in the analysis. In the recent years, special methods of handling hierarchical data, called multilevel models (MM, as well as corresponding software have received considerable development. However, there has been no application of these methods to morphometric data yet. In this paper we report our first experience of analyzing karyometric data by means of MLwiN – a dedicated program for multilevel modeling. Our data were obtained from 34 follicular adenomas and 44 follicular carcinomas of the thyroid. We show examples of fitting and interpreting MM of different complexity, and draw a number of interesting conclusions about the differences in nuclear morphology between follicular thyroid adenomas and carcinomas. We also demonstrate substantial advantages of multilevel models over conventional, single‐level statistics, which have been adopted previously to analyze karyometric data. In addition, some theoretical issues related to MM as well as major statistical software for MM are briefly reviewed.

The comparison of MSCT multi-phase scan features between benign prostatic hyperplasia and prostate cancer

International Nuclear Information System (INIS)

Liu Jingang; Wang Xizhen; Niu Qingliang; Lu Hongkai; Wang Bin

2009-01-01

Objective: To investigate the multi-phase contrast-enhanced features of multi-slice computed tomography (MSCT) of benign prostatic hyperplasia (BPH) and prostate cancer (PCa). Methods: Thirty-five BPH and twenty- seven PCa were examined with multi-phase contrast-enhanced MSCT scan. The peak time, maximum attenuation value (MAV) and time density curve (TDC) were recorded, and the slope of the contrast media uptake curve was calculated. Result: Significant differences between BPH and PCa in the type of the curves and the peak time were observed (P<0.01). The slopes of BPH and PCa were 0.45+0.25 and 0.7 6+0.34 respectively, the slope of PCa was higher than that of BPH (P<0.05). MAVs of BPH and PCa were (44.057±10.261) HU and (46.778±11.140) HU respectively, and there was no significant difference between them (P>0.05). Conclusion: The multi-phase MSCT scan can reflect the blood supply and enhancement characters of BPH and PCa, which are important in detection and differential diagnosis of the prostate diseases. (authors)

Interspecific variation in the tetradactyl manus of modern tapirs (Perissodactyla: Tapirus) exposed using geometric morphometrics.

Science.gov (United States)

MacLaren, Jamie A; Nauwelaerts, Sandra

2017-11-01

The distal forelimb (autopodium) of quadrupedal mammals is a key morphological unit involved in locomotion, body support, and interaction with the substrate. The manus of the tapir (Perissodactyla: Tapirus) is unique within modern perissodactyls, as it retains the plesiomorphic tetradactyl (four-toed) condition also exhibited by basal equids and rhinoceroses. Tapirs are known to exhibit anatomical mesaxonic symmetry in the manus, although interspecific differences and biomechanical mesaxony have yet to be rigorously tested. Here, we investigate variation in the manus morphology of four modern tapir species (Tapirus indicus, Tapirus bairdii, Tapirus pinchaque, and Tapirus terrestris) using a geometric morphometric approach. Autopodial bones were laser scanned to capture surface shape and morphology was quantified using 3D-landmark analysis. Landmarks were aligned using Generalised Procrustes Analysis, with discriminant function and partial least square analyses performed on aligned coordinate data to identify features that significantly separate tapir species. Overall, our results support the previously held hypothesis that T. indicus is morphologically separate from neotropical tapirs; however, previous conclusions regarding function from morphological differences are shown to require reassessment. We find evidence indicating that T. bairdii exhibits reduced reliance on the lateral fifth digit compared to other tapirs. Morphometric assessment of the metacarpophalangeal joint and the morphology of the distal facets of the lunate lend evidence toward high loading on the lateral digits of both the large T. indicus (large body mass) and the small, long limbed T. pinchaque (ground impact). Our results support other recent studies on T. pinchaque, suggesting subtle but important adaptations to a compliant but inclined habitat. In conclusion, we demonstrate further evidence that the modern tapir forelimb is a variable locomotor unit with a range of interspecific features

Adjusting to Social Change - A Multi-Level Analysis in Three Cultures

Science.gov (United States)

2013-08-01

example, coping may be more collective in collectivist , compared to individualist , societies (Chang & Sivam, 2004). Some cultures have a greater sense...AFRL-AFOSR-UK-TR-2013-0041 Adjusting to Social Change - A multi-level Analysis in three cultures Prof Robin Goodwin...COVERED (From – To) 23 May 2012 – 22 May 2013 4. TITLE AND SUBTITLE Adjusting to Social Change - A multi-level Analysis in three cultures

Morphometric and landuse analysis: implications on flood hazards ...

African Journals Online (AJOL)

This study assessed the morphometric, landuse and lithological attributes of five basins (Iwaraja, Ilesa, Olupona, Osogbo I and Osogbo II) with particular reference to flood hazards in Ilesa and Osogbo metropolis, Osun State Nigeria. Ilesa town is situated within Iwaraja and Ilesa basins while Osogbo metropolis spread ...

Hybridization within a Pilosella population: a morphometric analysis

Czech Academy of Sciences Publication Activity Database

Urfus, Tomáš; Krahulec, František; Krahulcová, Anna

2014-01-01

Roč. 49, č. 2 (2014), s. 223-238 ISSN 1211-9520 R&D Projects: GA ČR GA206/08/0890 Institutional research plan: CEZ:AV0Z60050516 Institutional support: RVO:67985939 Keywords : hybridization * introgression * multivariate morphometrics Subject RIV: EF - Botanics Impact factor: 1.778, year: 2014

TOXOPLASMOSIS: MORPHOLOGICAL AND MORPHOMETRIC EVALUATION OF SPINAL CORD NEURONS FROM NONSYMPTOMATIC SEROPOSITIVE DOGS

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Alessandra Cristina Francischini de Carvalho

2015-04-01

Full Text Available The aim of this work was to analyze the neuron morphology and morphometry of cervical, thoracic and lumbar areas of nonsymptomatic seropositive dogs’ spinal cord for toxoplasmosis. Twenty indefinite-breed adult dogs were used; ten dogs were healthy, with negative serology for toxoplasmosis, and were used as the control group (group 1, and ten dogs were nonsymptomatic but seropositive for toxoplasmosis (group 2. After the microtomy, with interval of 100 micrometers (µm, the histological 5-µm-thick cuts were dyed by hematoxylin-eosin and Masson's trichrome techniques. The glass slides were analyzed under light microscope to examine the neuron morphology. The parameters considered for the morphometric analysis were area, perimeter, maximum diameter, minimum diameter and shape factor of cytoplasm and nucleus of neuron. The results were statistically analyzed by Student’s t test at 5% probability level. The morphological characteristics between the two groups were similar and according to literature. The morphometric results showed that there were changes in neurons size and structure, and increase and loss of star shape were noticed in seropositive animals. The results suggest that the neurons of these dogs, yet nonsymptomatic, can have lost their conductor function.

Multi-example feature-constrained back-projection method for image super-resolution

Institute of Scientific and Technical Information of China (English)

Junlei Zhang; Dianguang Gai; Xin Zhang; Xuemei Li

2017-01-01

Example-based super-resolution algorithms,which predict unknown high-resolution image information using a relationship model learnt from known high- and low-resolution image pairs, have attracted considerable interest in the field of image processing. In this paper, we propose a multi-example feature-constrained back-projection method for image super-resolution. Firstly, we take advantage of a feature-constrained polynomial interpolation method to enlarge the low-resolution image. Next, we consider low-frequency images of different resolutions to provide an example pair. Then, we use adaptive k NN search to find similar patches in the low-resolution image for every image patch in the high-resolution low-frequency image, leading to a regression model between similar patches to be learnt. The learnt model is applied to the low-resolution high-frequency image to produce high-resolution high-frequency information. An iterative back-projection algorithm is used as the final step to determine the final high-resolution image.Experimental results demonstrate that our method improves the visual quality of the high-resolution image.

ANALISIS KARAKTER TRUSS MORPHOMETRICS PADA IKAN KEMPRIT (Ilisha megaloptera FAMILIA PRISTIGASTERIDAE

Directory of Open Access Journals (Sweden)

Tri Wijayanti

2017-06-01

Full Text Available The fish auction site at Ocean Fishing Port of Cilacap is one of the major fish landings sites in Indonesia. Fishes landed in this port mainly of large pelagic fish, bycatch, crustaceans including kemprit fish (Ilisha megaloptera Swainson,1839. Kemprit fish is a member of the family Pristigasteridae, which has an elongated body shape-sprawl. Fishers use this fish as the main ingredient to produce fish crackers and dried salted fish. Overfishing is the greatest threat to kemprit fish, and without conservation efforts the future population is uncertain. Fish farming is one right answer in kemprit fish conservation. However, information on this fish biology is insufficient. One of the biological aspects is sexual dimorphism, the morphological properties that can be used to distinguish between male and female fish. Truss morphometrics can measure the morphological traits differences of male and female. This technique in which the measurement of the distance Truss morphometrics in certain parts, by the benchmark points (dots Truss morphometrics, then compared with standard size. The result of the preliminary survey indicated that kemprit fish did not show sexual dimorphism, therefore truss morphometric technique applies to distinguish sexes of this fish. This research was a survey, and purposive sampling techniques were used to collect data. Data were then analyzed using the “t” test. The results showed that distinct truss distance between male and female fish was the distance between the anterior base of the dorsal fin to the anterior base of the ventral fins and the distance between the posterior base of the dorsal fin to the anterior base of the anal fin.

Ablation mass features in multi-pulses femtosecond laser ablate molybdenum target

Science.gov (United States)

Zhao, Dongye; Gierse, Niels; Wegner, Julian; Pretzler, Georg; Oelmann, Jannis; Brezinsek, Sebastijan; Liang, Yunfeng; Neubauer, Olaf; Rasinski, Marcin; Linsmeier, Christian; Ding, Hongbin

2018-03-01

In this study, the ablation mass features related to reflectivity of bulk Molybdenum (Mo) were investigated by a Ti: Sa 6 fs laser pulse at central wavelength 790 nm. The ablated mass removal was determined using Confocal Microscopy (CM) technique. The surface reflectivity was calibrated and measured by a Lambda 950 spectrophotometer as well as a CCD camera during laser ablation. The ablation mass loss per pulse increase with the increasing of laser shots, meanwhile the surface reflectivity decrease. The multi-pulses (100 shots) ablation threshold of Mo was determined to be 0.15 J/cm2. The incubation coefficient was estimated as 0.835. The reflectivity change of the Mo target surface following multi-pulses laser ablation were studied as a function of laser ablation shots at various laser fluences from 1.07 J/cm2 to 36.23 J/cm2. The results of measured reflectivity indicate that surface reflectivity of Mo target has a significant decline in the first 3-laser pulses at the various fluences. These results are important for developing a quantitative analysis model for laser induced ablation and laser induced breakdown spectroscopy for the first wall diagnosis of EAST tokamak.

MORPHOMETRIC CHARACTERISTICS OF RED BLOOD CELLS OF Telestes metohiensis (Steindachner, 1901

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Radoslav Dekić

2013-02-01

Full Text Available The paper presents the morphometric characteristics of red blood cells of endemic fish species of Bosnia and Herzegovina, Telestes metohiensis (Steindachner, 1901 inhabiting the Vrijeka river in the Dabar field. A total of 30 fish were sampled during August, 2010. Morphological measurements included the following parameters: axes of the red blood cells and nuclei, the surface of the red blood cells and nuclei and the thickness of the red blood cells. Morphometric characteristics of the erythrocyte maturation stages (acidophilic and polychromatic erythroblasts were also studied as well as their proportion in the peripheral blood. 100 mature forms were measured for each individual. The propotion of the immature forms was expressed per 1000 erythrocytes. Results showed that dimensions of the erythrocytes differed in systematic categories as well as fish types. Dimensions of mature erythrocytes and their maturation stages of the same species differed in shape and size of the nuclei. Proportion of the erythrocyte maturation stages was very low in comparison with the mature erythrocytes, indicating the optimal environmental conditions for the studied species.Key words: morphometric characteristics, erythrocytes, Telestes metohiensis, proportion of immature stages

Morphometric analysis of Dactylorhiza hatagirea (D. Don), a critically ...

African Journals Online (AJOL)

The morphometric study was conducted during 2009 to 2010. About 28 morphological characters were measured under 13 natural populations of Dactylorhiza hatagirea. Geographic variation in morphology reflects phenotypic responses to environmental gradients and evolutionary history of populations and species.

Multi-Modality Cascaded Convolutional Neural Networks for Alzheimer's Disease Diagnosis.

Science.gov (United States)

Liu, Manhua; Cheng, Danni; Wang, Kundong; Wang, Yaping

2018-03-23

Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and development of future treatment. Structural and functional neuroimages, such as magnetic resonance images (MRI) and positron emission tomography (PET), are providing powerful imaging modalities to help understand the anatomical and functional neural changes related to AD. In recent years, machine learning methods have been widely studied on analysis of multi-modality neuroimages for quantitative evaluation and computer-aided-diagnosis (CAD) of AD. Most existing methods extract the hand-craft imaging features after image preprocessing such as registration and segmentation, and then train a classifier to distinguish AD subjects from other groups. This paper proposes to construct cascaded convolutional neural networks (CNNs) to learn the multi-level and multimodal features of MRI and PET brain images for AD classification. First, multiple deep 3D-CNNs are constructed on different local image patches to transform the local brain image into more compact high-level features. Then, an upper high-level 2D-CNN followed by softmax layer is cascaded to ensemble the high-level features learned from the multi-modality and generate the latent multimodal correlation features of the corresponding image patches for classification task. Finally, these learned features are combined by a fully connected layer followed by softmax layer for AD classification. The proposed method can automatically learn the generic multi-level and multimodal features from multiple imaging modalities for classification, which are robust to the scale and rotation variations to some extent. No image segmentation and rigid registration are required in pre-processing the brain images. Our method is evaluated on the baseline MRI and PET images of 397 subjects including 93 AD patients, 204 mild cognitive impairment (MCI, 76 pMCI +128 sMCI) and 100 normal controls (NC) from Alzheimer's Disease Neuroimaging

Multi-level programming paradigm for extreme computing

International Nuclear Information System (INIS)

Petiton, S.; Sato, M.; Emad, N.; Calvin, C.; Tsuji, M.; Dandouna, M.

2013-01-01

In order to propose a framework and programming paradigms for post peta-scale computing, on the road to exa-scale computing and beyond, we introduced new languages, associated with a hierarchical multi-level programming paradigm, allowing scientific end-users and developers to program highly hierarchical architectures designed for extreme computing. In this paper, we explain the interest of such hierarchical multi-level programming paradigm for extreme computing and its well adaptation to several large computational science applications, such as for linear algebra solvers used for reactor core physic. We describe the YML language and framework allowing describing graphs of parallel components, which may be developed using PGAS-like language such as XMP, scheduled and computed on supercomputers. Then, we propose experimentations on supercomputers (such as the 'K' and 'Hooper' ones) of the hybrid method MERAM (Multiple Explicitly Restarted Arnoldi Method) as a case study for iterative methods manipulating sparse matrices, and the block Gauss-Jordan method as a case study for direct method manipulating dense matrices. We conclude proposing evolutions for this programming paradigm. (authors)

Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

Science.gov (United States)

Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

2013-10-01

The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

FGP Approach for Solving Multi-level Multi-objective Quadratic Fractional Programming Problem with Fuzzy parameters

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m. s. osman

2017-09-01

Full Text Available In this paper, we consider fuzzy goal programming (FGP approach for solving multi-level multi-objective quadratic fractional programming (ML-MOQFP problem with fuzzy parameters in the constraints. Firstly, the concept of the ?-cut approach is applied to transform the set of fuzzy constraints into a common deterministic one. Then, the quadratic fractional objective functions in each level are transformed into quadratic objective functions based on a proposed transformation. Secondly, the FGP approach is utilized to obtain a compromise solution for the ML-MOQFP problem by minimizing the sum of the negative deviational variables. Finally, an illustrative numerical example is given to demonstrate the applicability and performance of the proposed approach.

Level Sets and Voronoi based Feature Extraction from any Imagery

DEFF Research Database (Denmark)

Sharma, O.; Anton, François; Mioc, Darka

2012-01-01

Polygon features are of interest in many GEOProcessing applications like shoreline mapping, boundary delineation, change detection, etc. This paper presents a unique new GPU-based methodology to automate feature extraction combining level sets, or mean shift based segmentation together with Voron...

Morphometric studies on a part of Central Indian Ocean

Digital Repository Service at National Institute of Oceanography (India)

Kodagali, V.N.

Morphometric and slope angle studies carried out on a part of Indian Ocean Basin have shown that gentle slope angle ranges dominate, 92% of the area represented by 0-3 degrees slopes. Young's hypothesis of log-normal distribution of slope angle...

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.

Multi-level Control Framework for Enhanced Flexibility of Active Distribution Network

DEFF Research Database (Denmark)

Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

2017-01-01

In this paper, the control objectives of future active distribution networks with high penetration of renewables and flexible loads are analyzed and reviewed. From a state of the art review, the important control objectives seen from the perspective of a distribution system operator are identifie......-ordination and management of the network assets at different voltage levels and geographical locations. The paper finally shows the applicability of the multi-level control architecture to some of the key challenges in the distribution system operation by relevant scenarios....... to be hosting capacity improvement, high reliable operation and cost effective network management. Based on this review and a state of the art review concerning future distribution network control methods, a multi-level control architecture is constructed for an active distribution network, which satisfies...... the selected control objectives and provides enhanced flexibility. The control architecture is supported by generation/load forecasting and distribution state estimation techniques to improve the controllability of the network. The multi-level control architecture consists of three levels of hierarchical...

Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2014-09-20

Nonnegative matrix factorization (NMF), a popular part-based representation technique, does not capture the intrinsic local geometric structure of the data space. Graph regularized NMF (GNMF) was recently proposed to avoid this limitation by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant features and nonlinear distributions of data samples. Second, one possible way to handle the nonlinear distribution of data samples is by kernel embedding. However, it is often difficult to choose the most suitable kernel. To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively. Instead of using a fixed graph as in GNMF, the two proposed methods learn the nearest neighbor graph that is adaptive to the selected features and learned multiple kernels, respectively. For each method, we propose a unified objective function to conduct feature selection/multi-kernel learning, NMF and adaptive graph regularization simultaneously. We further develop two iterative algorithms to solve the two optimization problems. Experimental results on two challenging pattern classification tasks demonstrate that the proposed methods significantly outperform state-of-the-art data representation methods.

Simple Multi-level Microchannel Fabrication by Pseudo-Grayscale Backside Diffused Light Lithography.

Science.gov (United States)

Lai, David; Labuz, Joseph M; Kim, Jiwon; Luker, Gary D; Shikanov, Ariella; Takayama, Shuichi

2013-11-14

Photolithography of multi-level channel features in microfluidics is laborious and/or costly. Grayscale photolithography is mostly used with positive photoresists and conventional front side exposure, but the grayscale masks needed are generally costly and positive photoresists are not commonly used in microfluidic rapid prototyping. Here we introduce a simple and inexpensive alternative that uses pseudo-grayscale (pGS) photomasks in combination with backside diffused light lithography (BDLL) and the commonly used negative photoresist, SU-8. BDLL can produce smooth multi-level channels of gradually changing heights without use of true grayscale masks because of the use of diffused light. Since the exposure is done through a glass slide, the photoresist is cross-linked from the substrate side up enabling well-defined and stable structures to be fabricated from even unspun photoresist layers. In addition to providing unique structures and capabilities, the method is compatible with the "garage microfluidics" concept of creating useful tools at low cost since pGS BDLL can be performed with the use of only hot plates and a UV transilluminator: equipment commonly found in biology labs. Expensive spin coaters or collimated UV aligners are not needed. To demonstrate the applicability of pGS BDLL, a variety of weir-type cell traps were constructed with a single UV exposure to separate cancer cells (MDA-MB-231, 10-15 μm in size) from red blood cells (RBCs, 2-8 μm in size) as well as follicle clusters (40-50 μm in size) from cancer cells (MDA-MB-231, 10-15 μm in size).

Predicting human splicing branchpoints by combining sequence-derived features and multi-label learning methods.

Science.gov (United States)

Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping

2017-12-01

Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.

An improved AE detection method of rail defect based on multi-level ANC with VSS-LMS

Science.gov (United States)

Zhang, Xin; Cui, Yiming; Wang, Yan; Sun, Mingjian; Hu, Hengshan

2018-01-01

In order to ensure the safety and reliability of railway system, Acoustic Emission (AE) method is employed to investigate rail defect detection. However, little attention has been paid to the defect detection at high speed, especially for noise interference suppression. Based on AE technology, this paper presents an improved rail defect detection method by multi-level ANC with VSS-LMS. Multi-level noise cancellation based on SANC and ANC is utilized to eliminate complex noises at high speed, and tongue-shaped curve with index adjustment factor is proposed to enhance the performance of variable step-size algorithm. Defect signals and reference signals are acquired by the rail-wheel test rig. The features of noise signals and defect signals are analyzed for effective detection. The effectiveness of the proposed method is demonstrated by comparing with the previous study, and different filter lengths are investigated to obtain a better noise suppression performance. Meanwhile, the detection ability of the proposed method is verified at the top speed of the test rig. The results clearly illustrate that the proposed method is effective in detecting rail defects at high speed, especially for noise interference suppression.

Discriminant analysis of morphometric differentiation in the West ...

African Journals Online (AJOL)

This study evaluated the usefulness of morphological characteristics to distinguish two important indigenous goat breeds in Nigeria. Fifteen morphometric traits were measured on West African Dwarf – WAD (n = 160) and Red Sokoto – RS (n = 142) goats that ranged in age of up to 19 months and were reared extensively in ...

External morphometric study of hatchery reared mahseer ( Tor ...

African Journals Online (AJOL)

Different samples of Mahseer (Tor putitora) were examined for the study of external morphometric characters of the fish. Slopes of log transformed data were used for comparison with an isometric slopes (b=1, b= 0.33 or b= 3). Relationships between wet body weight and external body parts lengths showed that increasing ...

Using a multi-feature paradigm to measure mismatch responses to minimal sound contrasts in children with cochlear implants and hearing aids.

Science.gov (United States)

Uhlén, Inger; Engström, Elisabet; Kallioinen, Petter; Nakeva von Mentzer, Cecilia; Lyxell, Björn; Sahlén, Birgitta; Lindgren, Magnus; Ors, Marianne

2017-10-01

Our aim was to explore whether a multi-feature paradigm (Optimum-1) for eliciting mismatch negativity (MMN) would objectively capture difficulties in perceiving small sound contrasts in children with hearing impairment (HI) listening through their hearing aids (HAs) and/or cochlear implants (CIs). Children aged 5-7 years with HAs, CIs and children with normal hearing (NH) were tested in a free-field setting using a multi-feature paradigm with deviations in pitch, intensity, gap, duration, and location. There were significant mismatch responses across all subjects that were positive (p-MMR) for the gap and pitch deviants (F(1,43) = 5.17, p = 0.028 and F(1,43) = 6.56, p = 0.014, respectively) and negative (MMN) for the duration deviant (F(1,43) = 4.74, p = 0.035). Only the intensity deviant showed a significant group interaction with MMN in the HA group and p-MMR in the CI group (F(2,43) = 3.40, p = 0.043). The p-MMR correlated negatively with age, with the strongest correlation in the NH subjects. In the CI group, the late discriminative negativity (LDN) was replaced by a late positivity with a significant group interaction for the location deviant. Children with severe HI can be assessed through their hearing device with a fast multi-feature paradigm. For further studies a multi-feature paradigm including more complex speech sounds may better capture variation in auditory processing in these children. © 2017 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

An Indoor Slam Method Based on Kinect and Multi-Feature Extended Information Filter

Science.gov (United States)

Chang, M.; Kang, Z.

2017-09-01

Based on the frame of ORB-SLAM in this paper the transformation parameters between adjacent Kinect image frames are computed using ORB keypoints, from which priori information matrix and information vector are calculated. The motion update of multi-feature extended information filter is then realized. According to the point cloud data formed by depth image, ICP algorithm was used to extract the point features of the point cloud data in the scene and built an observation model while calculating a-posteriori information matrix and information vector, and weakening the influences caused by the error accumulation in the positioning process. Furthermore, this paper applied ORB-SLAM frame to realize autonomous positioning in real time in interior unknown environment. In the end, Lidar was used to get data in the scene in order to estimate positioning accuracy put forward in this paper.

AN INDOOR SLAM METHOD BASED ON KINECT AND MULTI-FEATURE EXTENDED INFORMATION FILTER

Directory of Open Access Journals (Sweden)

M. Chang

2017-09-01

Full Text Available Based on the frame of ORB-SLAM in this paper the transformation parameters between adjacent Kinect image frames are computed using ORB keypoints, from which priori information matrix and information vector are calculated. The motion update of multi-feature extended information filter is then realized. According to the point cloud data formed by depth image, ICP algorithm was used to extract the point features of the point cloud data in the scene and built an observation model while calculating a-posteriori information matrix and information vector, and weakening the influences caused by the error accumulation in the positioning process. Furthermore, this paper applied ORB-SLAM frame to realize autonomous positioning in real time in interior unknown environment. In the end, Lidar was used to get data in the scene in order to estimate positioning accuracy put forward in this paper.

Cities, Europeanization and Multi-level Governance: Governing Climate Change through Transnational Municipal Networks

NARCIS (Netherlands)

Kern, K.; Bulkeley, H.

2009-01-01

This article focuses on a variant of multi-level governance and Europeanization, i.e. the transnational networking of local authorities. Focusing on local climate change policy, the article examines how transnational municipal networks (TMNs) govern in the context of multi-level European governance.

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%.

Morphometrical Analysis and Peak Runoff Estimation for the Sub-Lower Niger River Basin, Nigeria

Directory of Open Access Journals (Sweden)

Salami Adebayo Wahab

2016-03-01

Full Text Available This study utilized Spatial Information Technology (SIT such as Remote Sensing (RS, a Geographical Information System (GIS, the Global Positioning System (GPS and a high-resolution Digital Elevation Model (DEM for a morphometrical analysis of five sub-basins within the Lower Niger River Basin, Nigeria. Morpho-metrical parameters, such as the total relief, relative relief, relief ratio, ruggedness number, texture ratio, elongation ratio, circularity ratio, form factor ratio, drainage density, stream frequency, sinuosity factor and bifurcation ratio, have been computed and analyzed. The study revealed that the contribution of the morphometric parameters to flooding suggest catchment No. 1 has the least concentration time and the highest runoff depth. Catchment No. 4 has the highest circularity ratio (0.35 as the most hazardous site where floods could reach a great volume over a small area.

Weight and morphometric growth of different strains of tilapia (Oreochromis sp

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Ivan Bezerra Allaman

2013-05-01

Full Text Available The objective of this study was to evaluate the morphometric growth and weight gain of strains of tilapia (Thai, Red, UFLA and Commercial by nonlinear models. Initially, 500 male fingerlings of each strain, at 85 (Red and UFLA and 86 (Thai and Commercial days of age, were stocked separately in raceways with 56 m³. Twenty fish of each strain were randomly sampled, weighed and measured monthly. Five nonlinear models (Brody, von Bertalanffy, Gompertz, logistic and exponential were tested, choosing one that best fit to the data. The variables studied were: weight, standard length (SL, head length (HL, height 1 (H1, height 2 (H2, height 3 (H3, first distance (D1, second distance (D2, first width (W1, second width (W2 and third width (W3. The exponential model had the best fit to weight and morphometric data, with the exception of W2, in which the best fitted model was von Bertalanffy. The convergence of the exponential model to data indicates that the cultivation period studied was not enough for the strains to reach maturity weight. The UFLA strain presented the lowest value for parameter "a" (initial weight estimate, 8.71 g, and the highest for parameter k (specific growth rate, 0.0127, when compared with other evaluated strains. However, the highest k of UFLA was not enough to overcome the final weight observed for the Commercial strain (603.1 g, which was higher than all other strains. Regarding the morphometric measurements, the UFLA strain also had the highest k for the variables SL, HL, HH, H1, H2, H3 and D2, and similar k to Commercial and Thai strains for the variables D1 and W3 respectively. The strains differ as to weight gain and morphometric growth.

Morphometric and molecular differentiation between quetzal subspecies of Pharomachrus mocinno (Trogoniformes: Trogonidae).

Science.gov (United States)

Solórzano, Sofía; Oyama, Ken

2010-03-01

The resplendent Quetzal (Pharomachrus mocinno) is an endemic Mesoamerican bird species of conservation concern. Within this species, the subspecies P. m. costaricensis and P. m. mocinno, have been recognized by apparent morphometric differences; however, presently there is no sufficient data for confirmation. We analyzed eight morphometric attributes of the body from 41 quetzals: body length, tarsus and cord wing, as well as the length, wide and depth of the bill, body weight; and in the case of the males, the length of the long upper-tail cover feathers. We used multivariate analyses to discriminate morphometric differences between subspecies and contrasted each morphometric attribute between and within subspecies with paired non-parametric Wilcoxon test. In order to review the intraspecific taxonomic status of this bird, we added phylogenetic analysis, and genetic divergence and differentiation based on nucleotide variations in four sequences of mtDNA. The nucleotide variation was estimated in control region, subunit NDH6, and tRNAGlu and tRNAPhe in 26 quetzals from eight localities distributed in five countries. We estimated the genetic divergence and differentiation between subspecies according to a mutation-drift equilibrium model. We obtained the best mutation nucleotide model following the procedure implemented in model test program. We constructed the phylogenetic relationships between subspecies by maximum parsimony and maximum likelihood using PAUP, as well as with Bayesian statistics. The multivariate analyses showed two different morphometric groups, and individuals clustered according to the subspecies that they belong. The paired comparisons between subspecies showed strong differences in most of the attributes analyzed. Along the four mtDNA sequences, we identified 32 nucleotide positions that have a particular nucleotide according to the quetzals subspecies. The genetic divergence and the differentiation was strong and markedly showed two groups

Neural Tuning to Low-Level Features of Speech throughout the Perisylvian Cortex.

Science.gov (United States)

Berezutskaya, Julia; Freudenburg, Zachary V; Güçlü, Umut; van Gerven, Marcel A J; Ramsey, Nick F

2017-08-16

Despite a large body of research, we continue to lack a detailed account of how auditory processing of continuous speech unfolds in the human brain. Previous research showed the propagation of low-level acoustic features of speech from posterior superior temporal gyrus toward anterior superior temporal gyrus in the human brain (Hullett et al., 2016). In this study, we investigate what happens to these neural representations past the superior temporal gyrus and how they engage higher-level language processing areas such as inferior frontal gyrus. We used low-level sound features to model neural responses to speech outside of the primary auditory cortex. Two complementary imaging techniques were used with human participants (both males and females): electrocorticography (ECoG) and fMRI. Both imaging techniques showed tuning of the perisylvian cortex to low-level speech features. With ECoG, we found evidence of propagation of the temporal features of speech sounds along the ventral pathway of language processing in the brain toward inferior frontal gyrus. Increasingly coarse temporal features of speech spreading from posterior superior temporal cortex toward inferior frontal gyrus were associated with linguistic features such as voice onset time, duration of the formant transitions, and phoneme, syllable, and word boundaries. The present findings provide the groundwork for a comprehensive bottom-up account of speech comprehension in the human brain. SIGNIFICANCE STATEMENT We know that, during natural speech comprehension, a broad network of perisylvian cortical regions is involved in sound and language processing. Here, we investigated the tuning to low-level sound features within these regions using neural responses to a short feature film. We also looked at whether the tuning organization along these brain regions showed any parallel to the hierarchy of language structures in continuous speech. Our results show that low-level speech features propagate throughout the

Morphometric variation in the Tunisian green frog, Rana saharica ...

African Journals Online (AJOL)

Rana saharica is the most widely distributed anuran in Tunisia. We examined morphological variation in 124 specimens as a function of their geographical origin, using univariate and multivariate statistics with traditional morphometrics. Our results supported the existence of three morphotypes of this species, correctly ...

A morphometric analysis of the genus Ficus Linn. (moraceae ...

African Journals Online (AJOL)

Foliar parameters of Ficus in Nigeria were subjected to quantitative analysis. The morphometric analysis is based on ten quantitative parameters of the leaves of species. Principal compound analysis produced six groups whose characters are described. Highly significant positive correlation exists between leaf length and ...

Correlation between three-dimensional power Doppler and morphometric measurement of endometrial vascularity at the time of embryo implantation in women with unexplained recurrent miscarriage.

Science.gov (United States)

Chen, Xiaoyan; Saravelos, Sotirios H; Liu, Yingyu; Huang, Jin; Wang, Chi Chiu; Li, Tin Chiu

2017-06-01

Power Doppler in combination with three-dimensional (3D-PD) ultrasonography has been used as a noninvasive tool to evaluate the vascularity. However, it is unclear whether 3D-PD can accurately reflect endometrial vascularization and replace the invasive endometrial biopsy. This study aims to investigate the correlation between 3D-PD and micro vessel morphometric measurement of endometrial vascularity. Twenty-five women with unexplained recurrent miscarriage were recruited for 3D-PD and endometrial biopsy on precisely day LH + 7. Immunohistochemistry using vWF was employed to identify micro vessels in endometrial biopsy specimens followed by the use of morphometric technique to measure the mean vessel diameter and volume fractions. The vascularization index (VI), flow index (FI) and vascularization flow index (VFI) assessed by 3D-PD were calculated for both the endometrial and sub-endometrial regions. There were no significant correlations between any of the ultrasonographic measurements (endometrial thickness, endometrial volume, endometrial VI/FI/VFI, sub-endometrial volume, sub-endometrial VI/FI/VFI) and morphometric features (number of micro vessel, mean diameter of micro vessel and volume fraction measurement of vessel). This study indicates that endometrial vascularity assessed by 3D-PD could not be used to reflect changes in micro vessels of the endometrium at the time of embryo implantation in women with unexplained recurrent miscarriage.

Multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement

Science.gov (United States)

Yan, Dan; Bai, Lianfa; Zhang, Yi; Han, Jing

2018-02-01

For the problems of missing details and performance of the colorization based on sparse representation, we propose a conceptual model framework for colorizing gray-scale images, and then a multi-sparse dictionary colorization algorithm based on the feature classification and detail enhancement (CEMDC) is proposed based on this framework. The algorithm can achieve a natural colorized effect for a gray-scale image, and it is consistent with the human vision. First, the algorithm establishes a multi-sparse dictionary classification colorization model. Then, to improve the accuracy rate of the classification, the corresponding local constraint algorithm is proposed. Finally, we propose a detail enhancement based on Laplacian Pyramid, which is effective in solving the problem of missing details and improving the speed of image colorization. In addition, the algorithm not only realizes the colorization of the visual gray-scale image, but also can be applied to the other areas, such as color transfer between color images, colorizing gray fusion images, and infrared images.

Unveiling the neurotoxicity of methylmercury in fish (Diplodus sargus) through a regional morphometric analysis of brain and swimming behavior assessment.

Science.gov (United States)

Puga, Sónia; Pereira, Patrícia; Pinto-Ribeiro, Filipa; O'Driscoll, Nelson J; Mann, Erin; Barata, Marisa; Pousão-Ferreira, Pedro; Canário, João; Almeida, Armando; Pacheco, Mário

2016-11-01

The current study aims to shed light on the neurotoxicity of MeHg in fish (white seabream - Diplodus sargus) by the combined assessment of: (i) MeHg toxicokinetics in the brain, (ii) brain morphometry (volume and number of neurons plus glial cells in specific brain regions) and (iii) fish swimming behavior (endpoints associated with the motor performance and the fear/anxiety-like status). Fish were surveyed for all the components after 7 (E7) and 14 (E14) days of dietary exposure to MeHg (8.7μgg -1 ), as well as after a post-exposure period of 28days (PE28). MeHg was accumulated in the brain of D. sargus after a short time (E7) and reached a maximum at the end of the exposure period (E14), suggesting an efficient transport of this toxicant into fish brain. Divalent inorganic Hg was also detected in fish brain along the experiment (indicating demethylation reactions), although levels were 100-200 times lower than MeHg, which pinpoints the organic counterpart as the great liable for the recorded effects. In this regard, a decreased number of cells in medial pallium and optic tectum, as well as an increased hypothalamic volume, occurred at E7. Such morphometric alterations were followed by an impairment of fish motor condition as evidenced by a decrease in the total swimming time, while the fear/anxiety-like status was not altered. Moreover, at E14 fish swam a greater distance, although no morphometric alterations were found in any of the brain areas, probably due to compensatory mechanisms. Additionally, although MeHg decreased almost two-fold in the brain during post-exposure, the levels were still high and led to a loss of cells in the optic tectum at PE28. This is an interesting result that highlights the optic tectum as particularly vulnerable to MeHg exposure in fish. Despite the morphometric alterations reported in the optic tectum at PE28, no significant changes were found in fish behavior. Globally, the effects of MeHg followed a multiphasic profile, where

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching.

Science.gov (United States)

Wang, Guohua; Liu, Qiong

2015-12-21

Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians' head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians' size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

Far-Infrared Based Pedestrian Detection for Driver-Assistance Systems Based on Candidate Filters, Gradient-Based Feature and Multi-Frame Approval Matching

Directory of Open Access Journals (Sweden)

Guohua Wang

2015-12-01

Full Text Available Far-infrared pedestrian detection approaches for advanced driver-assistance systems based on high-dimensional features fail to simultaneously achieve robust and real-time detection. We propose a robust and real-time pedestrian detection system characterized by novel candidate filters, novel pedestrian features and multi-frame approval matching in a coarse-to-fine fashion. Firstly, we design two filters based on the pedestrians’ head and the road to select the candidates after applying a pedestrian segmentation algorithm to reduce false alarms. Secondly, we propose a novel feature encapsulating both the relationship of oriented gradient distribution and the code of oriented gradient to deal with the enormous variance in pedestrians’ size and appearance. Thirdly, we introduce a multi-frame approval matching approach utilizing the spatiotemporal continuity of pedestrians to increase the detection rate. Large-scale experiments indicate that the system works in real time and the accuracy has improved about 9% compared with approaches based on high-dimensional features only.

Evaluating two-dimensional skeletal structure parameters using radiological bone morphometric analysis

International Nuclear Information System (INIS)

Asa, Kensuke; Sakurai, Takashi; Kashima, Isamu; Kumasaka, Satsuki

2005-01-01

The objectives of this study was to investigate the reliability of two-dimensional (2D) skeletal structure parameters obtained using radiological bone morphometric analysis. The 2D skeletal parameters in the regions of interest (ROIs) were measured on computed radiography (CR) images of first phalanges from racehorses, using radiological bone morphometric analysis. Cancellous bone blocks were made from the phalanges in the same position as the ROI determined on CR images. Three-dimensional (3D) trabecular parameters were measured using micro-computed tomography (μCT). The correlations between the 2D skeletal parameters and 3D trabecular parameters were evaluated in relation to the measured bone strength. The following 2D skeletal structure parameters were correlated with bone strength (r=0.61-0.69): skeletal perimeter (Sk.Pm), skeletal number (Sk.N), skeletal separation (Sk.Sp), skeletal spacing (Sk.Spac), fractal dimension (FD), and skeletal pattern factor (SkPf). The 3D trabecular structure parameters were closely correlated with bone strength (r=0.74-0.86). The 2D skeletal parameters Sk.N, Sk.Pm, FD, SkPf, and Sk.Spac were correlated with the 3D trabecular parameters (r=0.61-0.70). The 2D skeletal parameters obtained using radiological bone morphometric analysis may be useful indicators of trabecular strength. (author)

Examining multi-level effects on corporate social responsibility and irresponsibility

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Mazzei Matthew J.

2015-10-01

Full Text Available What influences firms to engage in socially responsible (irresponsible activities? Corporate social responsibility (CSR, the efforts of firms to create a positive and desirable impact on society, and corporate social irresponsibility (CSI, contrary actions of unethical behavior that negatively influence society, have become an important focus of discussion for both corporations and scholars. Despite this interest, our understanding of organizations’ socially responsible (irresponsible actions and their antecedents is still developing. A dearth of knowledge about the multi-level nature of the drivers of CSR and CSI continues to exist. Utilizing a longitudinal sample composed of 899 firms in 66 industries, we follow a prominent model to empirically examine industry-, firm-, and individual-level effects on CSR and CSI. Employing variance decomposition analysis, our results confirm that all three levels of investigation do indeed influence CSR and CSI. More substantively, our analysis estimates the magnitude of the effects attributable to each of the three levels for both CSR and CSI. We also compare multi-level influences on two separate CSR strategies, those targeting primary stakeholders (strategic CSR and those targeting secondary stakeholders (social CSR. We find greater industry- and firmlevel effects on social CSR, and higher individual-level effects on strategic CSR. Our results build on the conceptual work of previous authors by providing empirical analyses to confirm multilevel influences on CSR and extending prior multi-level theory to the concept of CSI. Further, we add to the emerging literature regarding stakeholder demands by examining the various influences on CSR strategies targeting different stakeholder groups.

Multi-level approach for parametric roll analysis

Science.gov (United States)

Kim, Taeyoung; Kim, Yonghwan

2011-03-01

The present study considers multi-level approach for the analysis of parametric roll phenomena. Three kinds of computation method, GM variation, impulse response function (IRF), and Rankine panel method, are applied for the multi-level approach. IRF and Rankine panel method are based on the weakly nonlinear formulation which includes nonlinear Froude- Krylov and restoring forces. In the computation result of parametric roll occurrence test in regular waves, IRF and Rankine panel method show similar tendency. Although the GM variation approach predicts the occurrence of parametric roll at twice roll natural frequency, its frequency criteria shows a little difference. Nonlinear roll motion in bichromatic wave is also considered in this study. To prove the unstable roll motion in bichromatic waves, theoretical and numerical approaches are applied. The occurrence of parametric roll is theoretically examined by introducing the quasi-periodic Mathieu equation. Instability criteria are well predicted from stability analysis in theoretical approach. From the Fourier analysis, it has been verified that difference-frequency effects create the unstable roll motion. The occurrence of unstable roll motion in bichromatic wave is also observed in the experiment.

13 Morphometric Analysis of Ogunpa and Ogbere Drainage Basins ...

African Journals Online (AJOL)

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significance of these landscape parameters was ... reported that the geomorphic characteristics of a drainage basins play ... form and process of drainage basins that may ... tropical rain forest of Nigeria occupying an area of .... morphometric parameters such as relief, shape ... on floodplains can be pulled down while areas.

The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research.

Science.gov (United States)

Woods, Christopher; Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia; Dickinson, Alexander

2017-01-01

This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique's application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets.

Determination of a novel size proxy in comparative morphometrics

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Andrew Gallagher

2015-09-01

Full Text Available Absolute size is a critical determinant of organismal biology, yet there exists no real consensus as to what particular metric of ‘size’ is empirically valid in assessments of extinct mammalian taxa. The methodological approach of JE Mosimann has found extensive favour in ‘size correction’ in comparative morphometrics, but not ‘size prediction’ in palaeontology and palaeobiology. Analyses of five distinct mammalian data sets confirm that a novel size variate (GMSize derived from k=8 dimensions of the postcranial skeleton effectively satisfies all expectations of the Jolicoeur–Mosimann theorem of univariate and multivariate size. On the basis of strong parametric correlations between the k=8 variates and between scores derived from the first principal component and geometric mean size (GMSize in all series, this novel size variable has considerable utility in comparative vertebrate morphometrics and palaeobiology as an appropriate descriptor of individual size in extant and extinct taxa.

A Multi-step and Multi-level approach for Computer Aided Molecular Design

DEFF Research Database (Denmark)

. The problem formulation step incorporates a knowledge base for the identification and setup of the design criteria. Candidate compounds are identified using a multi-level generate and test CAMD solution algorithm capable of designing molecules having a high level of molecular detail. A post solution step...... using an Integrated Computer Aided System (ICAS) for result analysis and verification is included in the methodology. Keywords: CAMD, separation processes, knowledge base, molecular design, solvent selection, substitution, group contribution, property prediction, ICAS Introduction The use of Computer...... Aided Molecular Design (CAMD) for the identification of compounds having specific physic...

HybridGO-Loc: mining hybrid features on gene ontology for predicting subcellular localization of multi-location proteins.

Science.gov (United States)

Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan

2014-01-01

Protein subcellular localization prediction, as an essential step to elucidate the functions in vivo of proteins and identify drugs targets, has been extensively studied in previous decades. Instead of only determining subcellular localization of single-label proteins, recent studies have focused on predicting both single- and multi-location proteins. Computational methods based on Gene Ontology (GO) have been demonstrated to be superior to methods based on other features. However, existing GO-based methods focus on the occurrences of GO terms and disregard their relationships. This paper proposes a multi-label subcellular-localization predictor, namely HybridGO-Loc, that leverages not only the GO term occurrences but also the inter-term relationships. This is achieved by hybridizing the GO frequencies of occurrences and the semantic similarity between GO terms. Given a protein, a set of GO terms are retrieved by searching against the gene ontology database, using the accession numbers of homologous proteins obtained via BLAST search as the keys. The frequency of GO occurrences and semantic similarity (SS) between GO terms are used to formulate frequency vectors and semantic similarity vectors, respectively, which are subsequently hybridized to construct fusion vectors. An adaptive-decision based multi-label support vector machine (SVM) classifier is proposed to classify the fusion vectors. Experimental results based on recent benchmark datasets and a new dataset containing novel proteins show that the proposed hybrid-feature predictor significantly outperforms predictors based on individual GO features as well as other state-of-the-art predictors. For readers' convenience, the HybridGO-Loc server, which is for predicting virus or plant proteins, is available online at http://bioinfo.eie.polyu.edu.hk/HybridGoServer/.

Morphometrics and Theriology. Homage to Marco Corti

Directory of Open Access Journals (Sweden)

Anna Loy

2008-02-01

Full Text Available Abstract This paper discusses the role of museum theriological collections in the context of twenty years of morphometric progresses. It also recalls twenty years of collaboration and friendship with Marco Corti, Italian theriologist and morphometrician, died on January 2007. The synthesis is addressed to the many young students that are picking up the baton and will likely contribute to the growth of the Italian school of morphometrics, to which Marco Corti dedicated most of his work at the University of Rome "La Sapienza". Riassunto Morfometria e teriologia. Omaggio a Marco Corti. Il lavoro discute il ruolo delle collezioni teriologiche alla luce di venti anni di progressi della morfometria. Esso rappresenta anche la sintesi di un’esperienza umana e professionale, avendo l’autore condiviso molte tappe della ‘rivoluzione morfometrica’ degli anni ottanta con molti dei suoi protagonisti, alcuni dei quali oggi non sono più con noi. In particolare Marco Corti, teriologo e morfometrista, scomparso nel 2007. La sintesi è anche dedicata ai molti giovani studenti e ricercatori che stanno contribuendo alla crescita della scuola italiana di morfometria, cui Marco Corti ha dedicato gli ultimi venti anni di insegnamento e ricerca all’Università di Roma "La Sapienza".

Extending the enterprise through multi-level supply control

NARCIS (Netherlands)

Vlist, van der P.; Hoppenbrouwers, J.J.E.M.; Hegge, H.M.H.

1997-01-01

Demands for flexibility require larger parts of the supply chain to become customer driven. This article describes multi-level supply control (MLSC) as a mechanism to facilitate that; it allows to specify gradually and thus to shift the customer order decoupling point well across the boundary to the

ADJUSTMENT OF MORPHOMETRIC PARAMETERS OF WATER BASINS BASED ON DIGITAL TERRAIN MODELS

Directory of Open Access Journals (Sweden)

Krasil'nikov Vitaliy Mikhaylovich

2012-10-01

Full Text Available The authors argue that effective use of water resources requires accurate morphometric characteristics of water basins. Accurate parameters are needed to analyze their condition, and to assure their appropriate control and operation. Today multiple water basins need their morphometric characteristics to be adjusted and properly stored. The procedure employed so far is based on plane geometric horizontals depicted onto topographic maps. It is described in the procedural guidelines issued in respect of the «Application of water resource regulations governing the operation of waterworks facilities of power plants». The technology described there is obsolete due to the availability of specialized software. The computer technique is based on a digital terrain model. The authors provide an overview of the technique implemented at Rybinsk and Gorkiy water basins in this article. Thus, the digital terrain model generated on the basis of the field data is used at Gorkiy water basin, while the model based on maps and charts is applied at Rybinsk water basin. The authors believe that the software technique can be applied to any other water basin on the basis of the analysis and comparison of morphometric characteristics of the two water basins.

Automatic Sleep Staging using Multi-dimensional Feature Extraction and Multi-kernel Fuzzy Support Vector Machine

Directory of Open Access Journals (Sweden)

Yanjun Zhang

2014-01-01

Full Text Available This paper employed the clinical Polysomnographic (PSG data, mainly including all-night Electroencephalogram (EEG, Electrooculogram (EOG and Electromyogram (EMG signals of subjects, and adopted the American Academy of Sleep Medicine (AASM clinical staging manual as standards to realize automatic sleep staging. Authors extracted eighteen different features of EEG, EOG and EMG in time domains and frequency domains to construct the vectors according to the existing literatures as well as clinical experience. By adopting sleep samples self-learning, the linear combination of weights and parameters of multiple kernels of the fuzzy support vector machine (FSVM were learned and the multi-kernel FSVM (MK-FSVM was constructed. The overall agreement between the experts' scores and the results presented was 82.53%. Compared with previous results, the accuracy of N1 was improved to some extent while the accuracies of other stages were approximate, which well reflected the sleep structure. The staging algorithm proposed in this paper is transparent, and worth further investigation.

Geometric morphometric footprint analysis of young women

OpenAIRE

Domjanic, Jacqueline; Fieder, Martin; Seidler, Horst; Mitteroecker, Philipp

2013-01-01

Background Most published attempts to quantify footprint shape are based on a small number of measurements. We applied geometric morphometric methods to study shape variation of the complete footprint outline in a sample of 83 adult women. Methods The outline of the footprint, including the toes, was represented by a comprehensive set of 85 landmarks and semilandmarks. Shape coordinates were computed by Generalized Procrustes Analysis. Results The first four principal components represented t...

Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

Science.gov (United States)

Kairuddin, Wan Nur Hafsha Wan; Mahmud, Wan Mahani Hafizah Wan

2017-08-01

Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.

Quantitative multi-parameter mapping of R1, PD*, MT and R2* at 3T: a multi-center validation

Directory of Open Access Journals (Sweden)

Nikolaus eWeiskopf

2013-06-01

Full Text Available Multi-center studies using magnetic resonance imaging facilitate studying small effect sizes, global population variance and rare diseases. The reliability and sensitivity of these multi-center studies crucially depend on the comparability of the data generated at different sites and time points. The level of inter-site comparability is still controversial for conventional anatomical T1-weighted MRI data. Quantitative multi-parameter mapping (MPM was designed to provide MR parameter measures that are comparable across sites and time points, i.e., 1mm high-resolution maps of the longitudinal relaxation rate (R1=1/T1, effective proton density (PD*, magnetization transfer saturation (MT and effective transverse relaxation rate (R2*=1/T2*. MPM was validated at 3T for use in multi-center studies by scanning five volunteers at three different sites. We determined the inter-site bias, inter-site and intra-site coefficient of variation (CoV for typical morphometric measures (i.e., gray matter probability maps used in voxel-based morphometry and the four quantitative parameters. The inter-site bias and CoV were smaller than 3.1% and 8%, respectively, except for the inter-site CoV of R2* (< 20%. The gray matter probability maps based on the MT parameter maps had a 14% higher inter-site reproducibility than maps based on conventional T1-weighted images. The low inter-site bias and variance in the parameters and derived gray matter probability maps confirm the high comparability of the quantitative maps across sites and time points. The reliability, short acquisition time, high resolution and the detailed insights into the brain microstructure provided by MPM makes it an efficient tool for multi-center imaging studies.

Joint Facial Action Unit Detection and Feature Fusion: A Multi-conditional Learning Approach.

Science.gov (United States)

Eleftheriadis, Stefanos; Rudovic, Ognjen; Pantic, Maja

2016-10-05

Automated analysis of facial expressions can benefit many domains, from marketing to clinical diagnosis of neurodevelopmental disorders. Facial expressions are typically encoded as a combination of facial muscle activations, i.e., action units. Depending on context, these action units co-occur in specific patterns, and rarely in isolation. Yet, most existing methods for automatic action unit detection fail to exploit dependencies among them, and the corresponding facial features. To address this, we propose a novel multi-conditional latent variable model for simultaneous fusion of facial features and joint action unit detection. Specifically, the proposed model performs feature fusion in a generative fashion via a low-dimensional shared subspace, while simultaneously performing action unit detection using a discriminative classification approach. We show that by combining the merits of both approaches, the proposed methodology outperforms existing purely discriminative/generative methods for the target task. To reduce the number of parameters, and avoid overfitting, a novel Bayesian learning approach based on Monte Carlo sampling is proposed, to integrate out the shared subspace. We validate the proposed method on posed and spontaneous data from three publicly available datasets (CK+, DISFA and Shoulder-pain), and show that both feature fusion and joint learning of action units leads to improved performance compared to the state-of-the-art methods for the task.

Morphometric characteristics in the horseshoe crab Tachypleus gigas (Arthropoda: Merostomata)

Digital Repository Service at National Institute of Oceanography (India)

Vijayakumar, R.; Das, S.; Chatterji, A.; Parulekar, A.H.

comparative morphometry. This study also emphasizes that care must be taken to apply morphometric for a uniform size group of horseshoe crab populations. It is known that the changes in the form of an animal cannot be described satisfactorily...

Morphometric Changes in the Cortical Microvascular Network in Alzheimer's Disease

NARCIS (Netherlands)

Richard, E.; van Gool, W.A.; Hoozemans, J.J.M.; van Haastert, E.S.; Eikelenboom, P.; Rozemuller, A.J.M.; van de Berg, W.D.J.

2010-01-01

Alzheimer's disease (AD) pathology is accompanied by abnormalities of the microvasculature. Despite the potential importance of morphometric changes in the cortical capillary network on neuronal dysfunction and cognitive impairment, few autopsy studies have addressed this issue. In the present

Image accuracy and representational enhancement through low-level, multi-sensor integration techniques

International Nuclear Information System (INIS)

Baker, J.E.

1993-05-01

Multi-Sensor Integration (MSI) is the combining of data and information from more than one source in order to generate a more reliable and consistent representation of the environment. The need for MSI derives largely from basic ambiguities inherent in our current sensor imaging technologies. These ambiguities exist as long as the mapping from reality to image is not 1-to-1. That is, if different 44 realities'' lead to identical images, a single image cannot reveal the particular reality which was the truth. MSI techniques can be divided into three categories based on the relative information content of the original images with that of the desired representation: (1) ''detail enhancement,'' wherein the relative information content of the original images is less rich than the desired representation; (2) ''data enhancement,'' wherein the MSI techniques axe concerned with improving the accuracy of the data rather than either increasing or decreasing the level of detail; and (3) ''conceptual enhancement,'' wherein the image contains more detail than is desired, making it difficult to easily recognize objects of interest. In conceptual enhancement one must group pixels corresponding to the same conceptual object and thereby reduce the level of extraneous detail. This research focuses on data and conceptual enhancement algorithms. To be useful in many real-world applications, e.g., autonomous or teleoperated robotics, real-time feedback is critical. But, many MSI/image processing algorithms require significant processing time. This is especially true of feature extraction, object isolation, and object recognition algorithms due to their typical reliance on global or large neighborhood information. This research attempts to exploit the speed currently available in state-of-the-art digitizers and highly parallel processing systems by developing MSI algorithms based on pixel rather than global-level features

Morphometric comparisons of Diaphorina citri (Hemiptera: Liviidae) populations from Iran, USA and Pakistan.

Science.gov (United States)

Lashkari, Mohammadreza; Hentz, Matthew G; Boykin, Laura M

2015-01-01

The Asian citrus psyllid (ACP), Diaphorina citri Kuwayama (Hemiptera: Liviidae), vector of citrus greening disease pathogen, Huanglongbing (HLB), is considered the most serious pest of citrus in the world. Prior molecular based studies have hypothesized a link between the D. citri in Iran and the USA (Florida). The purpose of this study was to collect morphometric data from D. citri populations from Iran (mtCOI haplotype-1), Florida (mtCOI haplotype-1), and Pakistan (mtCOI haplotype-6), to determine whether different mtCOI haplotypes have a relationship to a specific morphometric variation. 240 samples from 6 ACP populations (Iran-Jiroft, Chabahar; Florida-Ft. Pierce, Palm Beach Gardens, Port St. Lucie; and Pakistan-Punjab) were collected for comparison. Measurements of 20 morphological characters were selected, measured and analysed using ANOVA and MANOVA. The results indicate differences among the 6 ACP populations (Wilks' lambda = 0.0376, F = 7.29, P citri species in this study, (1) Iran, (2) USA (Florida) and (3) Pakistan population. Morphometric comparisons provided further resolution to the mtCOI haplotypes and distinguished the Florida and Iranian populations.

Multi-Source Multi-Target Dictionary Learning for Prediction of Cognitive Decline.

Science.gov (United States)

Zhang, Jie; Li, Qingyang; Caselli, Richard J; Thompson, Paul M; Ye, Jieping; Wang, Yalin

2017-06-01

Alzheimer's Disease (AD) is the most common type of dementia. Identifying correct biomarkers may determine pre-symptomatic AD subjects and enable early intervention. Recently, Multi-task sparse feature learning has been successfully applied to many computer vision and biomedical informatics researches. It aims to improve the generalization performance by exploiting the shared features among different tasks. However, most of the existing algorithms are formulated as a supervised learning scheme. Its drawback is with either insufficient feature numbers or missing label information. To address these challenges, we formulate an unsupervised framework for multi-task sparse feature learning based on a novel dictionary learning algorithm. To solve the unsupervised learning problem, we propose a two-stage Multi-Source Multi-Target Dictionary Learning (MMDL) algorithm. In stage 1, we propose a multi-source dictionary learning method to utilize the common and individual sparse features in different time slots. In stage 2, supported by a rigorous theoretical analysis, we develop a multi-task learning method to solve the missing label problem. Empirical studies on an N = 3970 longitudinal brain image data set, which involves 2 sources and 5 targets, demonstrate the improved prediction accuracy and speed efficiency of MMDL in comparison with other state-of-the-art algorithms.

Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification

Science.gov (United States)

Teffahi, Hanane; Yao, Hongxun; Belabid, Nasreddine; Chaib, Souleyman

2018-02-01

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Multi-Input Converter with MPPT Feature for Wind-PV Power Generation System

Directory of Open Access Journals (Sweden)

Chih-Lung Shen

2013-01-01

Full Text Available A multi-input converter (MIC to process wind-PV power is proposed, designed, analyzed, simulated, and implemented. The MIC cannot only process solar energy but deal with wind power, of which structure is derived from forward-type DC/DC converter to step-down/up voltage for charger systems, DC distribution applications, or grid connection. The MIC comprises an upper modified double-ended forward, a lower modified double-ended forward, a common output inductor, and a DSP-based system controller. The two modified double-ended forwards can operate individually or simultaneously so as to accommodate the variation of the hybrid renewable energy under different atmospheric conditions. While the MIC operates at interleaving mode, better performance can be achieved and volume also is reduced. The proposed MIC is capable of recycling the energy stored in the leakage inductance and obtaining high step-up output voltage. In order to draw maximum power from wind turbine and PV panel, perturb-and-observe method is adopted to achieve maximum power point tracking (MPPT feature. The MIC is constructed, analyzed, simulated, and tested. Simulations and hardware measurements have demonstrated the feasibility and functionality of the proposed multi-input converter.

Energy-related parameters and their association with age, gender, and morphometric measurements in healthy donkeys.

Science.gov (United States)

Mendoza, F J; Estepa, J C; Gonzalez-De Cara, C A; Aguilera-Aguilera, R; Toribio, R E; Perez-Ecija, A

2015-05-01

Donkeys are commonly afflicted by endocrine and metabolic disturbances but few studies have investigated endocrine variables involved in energy regulation and their association with morphometric indices, age or gender in this species. Hemostatic and clinical differences have been demonstrated between horses and donkeys, so to consider both species as metabolically and endocrinologically similar could lead to misdiagnosis. In this study, plasma concentrations of glucose, triglycerides and endocrine factors involved in energy homeostasis (insulin, glucagon, leptin, adiponectin, ghrelin and insulin-like growth factor [IGF]-1) were measured and their association with morphometric variables (body condition score, neck scoring and body mass index), gender and age was determined in 62 healthy donkeys. In addition, a neck scoring system specific for donkeys was developed. Insulin, glucagon, leptin and IGF-1 concentrations were found to be similar between donkeys and other species, but adiponectin and active ghrelin were lower in donkeys than horses. Donkeys with larger neck scores and body mass indices had higher triglyceride, leptin and IGF-1 concentrations. A sexual dimorphism was observed on all morphometric measurements and plasma glucose concentrations independent of adiposity. Younger animals had lower morphometric measurements and triglyceride and leptin concentrations. Copyright © 2015 Elsevier Ltd. All rights reserved.

A New Feature Extraction Method Based on EEMD and Multi-Scale Fuzzy Entropy for Motor Bearing

Directory of Open Access Journals (Sweden)

Huimin Zhao

2016-12-01

Full Text Available Feature extraction is one of the most important, pivotal, and difficult problems in mechanical fault diagnosis, which directly relates to the accuracy of fault diagnosis and the reliability of early fault prediction. Therefore, a new fault feature extraction method, called the EDOMFE method based on integrating ensemble empirical mode decomposition (EEMD, mode selection, and multi-scale fuzzy entropy is proposed to accurately diagnose fault in this paper. The EEMD method is used to decompose the vibration signal into a series of intrinsic mode functions (IMFs with a different physical significance. The correlation coefficient analysis method is used to calculate and determine three improved IMFs, which are close to the original signal. The multi-scale fuzzy entropy with the ability of effective distinguishing the complexity of different signals is used to calculate the entropy values of the selected three IMFs in order to form a feature vector with the complexity measure, which is regarded as the inputs of the support vector machine (SVM model for training and constructing a SVM classifier (EOMSMFD based on EDOMFE and SVM for fulfilling fault pattern recognition. Finally, the effectiveness of the proposed method is validated by real bearing vibration signals of the motor with different loads and fault severities. The experiment results show that the proposed EDOMFE method can effectively extract fault features from the vibration signal and that the proposed EOMSMFD method can accurately diagnose the fault types and fault severities for the inner race fault, the outer race fault, and rolling element fault of the motor bearing. Therefore, the proposed method provides a new fault diagnosis technology for rotating machinery.

Seed morphometric characteristics of European species of Elatine (Elatinaceae

Directory of Open Access Journals (Sweden)

Agnieszka Popiela

2017-05-01

Full Text Available Elatine L. contains ca. 25 small, herbaceous, annual species distributed in ephemeral waters in both hemispheres. All species are amphibious and characterized by a high degree of morphological variability. The importance of seed morphology in Elatine taxonomy has been emphasized by many authors. The degree of seed curvature and seed coat reticulation have been traditionally considered very important in recognizing individual species of this genus. Seed morphometric characteristics of 10 Elatine species, including all European native taxa, are provided on the basis of material from two or three populations of each species. A total of 24–50 seeds were studied from each population, altogether 1,260 images were used for the morphometric study. In total, six parameters were measured from SEM pictures: object surface area, profile specific perimeter (object circuit, rectangle of the object (a length, rectangle of the object (b width, angle of the seed curvature, and number of pits in the seed coat counted in the middle row. Our study shows that the range of morphological variation of seeds in European species of Elatine is great, both between the species and the populations. Discrimination analysis showed that all six traits significantly differentiate the populations studied (λ = 0.001, p < 0.001, and the greatest contributions were “number of pits”, “rectangle_a”, and “the angle curvature”. Multidimensional scaling based on a correlation matrix of Mahalanobis distance of the six features studied revealed the greatest similarity between the three populations of E. alsinastrum, E. macropoda, and E. hexandra. Regarding interspecific differences, a Kruskal–Wallis tests showed that, in many cases, lack of statistically significant differences between species relative to the studied seed traits. If distinction of species is only based on seeds, especially if only a few seeds are evaluated, the following species pairs can be easily

First 3D Cadastral Registration of Multi-level Ownerships Rights in the Netherlands

NARCIS (Netherlands)

Ploeger, H.D.; Stoter, J.E.; Roes, R; Van der Riet, E.; Biljecki, F.; Ledoux, H.

2016-01-01

This paper reports on the first 3D cadastral registration of multi-level ownerships rights in the Netherlands, which was accomplished in March 2016. It is the result of a study that was undertaken from 2013 to 2015 to determine how insight about multi-level ownership can be provided in 3D by the

Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models

International Nuclear Information System (INIS)

Khalvati, Farzad; Wong, Alexander; Haider, Masoom A.

2015-01-01

Prostate cancer is the most common form of cancer and the second leading cause of cancer death in North America. Auto-detection of prostate cancer can play a major role in early detection of prostate cancer, which has a significant impact on patient survival rates. While multi-parametric magnetic resonance imaging (MP-MRI) has shown promise in diagnosis of prostate cancer, the existing auto-detection algorithms do not take advantage of abundance of data available in MP-MRI to improve detection accuracy. The goal of this research was to design a radiomics-based auto-detection method for prostate cancer via utilizing MP-MRI data. In this work, we present new MP-MRI texture feature models for radiomics-driven detection of prostate cancer. In addition to commonly used non-invasive imaging sequences in conventional MP-MRI, namely T2-weighted MRI (T2w) and diffusion-weighted imaging (DWI), our proposed MP-MRI texture feature models incorporate computed high-b DWI (CHB-DWI) and a new diffusion imaging modality called correlated diffusion imaging (CDI). Moreover, the proposed texture feature models incorporate features from individual b-value images. A comprehensive set of texture features was calculated for both the conventional MP-MRI and new MP-MRI texture feature models. We performed feature selection analysis for each individual modality and then combined best features from each modality to construct the optimized texture feature models. The performance of the proposed MP-MRI texture feature models was evaluated via leave-one-patient-out cross-validation using a support vector machine (SVM) classifier trained on 40,975 cancerous and healthy tissue samples obtained from real clinical MP-MRI datasets. The proposed MP-MRI texture feature models outperformed the conventional model (i.e., T2w+DWI) with regard to cancer detection accuracy. Comprehensive texture feature models were developed for improved radiomics-driven detection of prostate cancer using MP-MRI. Using a

Non-linear interactions of multi-level atoms with a near-resonant standing wave

International Nuclear Information System (INIS)

O'Kane, T.J.; Scholten, R.E.; Walkiewicz, M.R.; Farrell, P.M.

1998-01-01

Using a semiclassical density matrix formalism we have calculated the behavior of multi-level atoms interacting with a standing wave field, and show how complex non-linear phenomena, including multi-photon effects, combine to produce saturation spectra as observed in experiments. We consider both 20-level sodium and 24-level rubidium models, contrasting these with a simple 2-level case. The influence of parameters such as atomic trajectory and the time the atom remains in the beam are shown to have a critical effect on the lineshape of these resonances and the emission/absorption processes. Stable oscillations in the excited state populations for both the two-level and multi-level cases are shown to be limit cycles. These limit cycles undergo period doubling as the system evolves into chaos. Finally, using a Monte Carlo treatment, these processes average to produce saturated absorption spectra complete with power and Doppler broadening effects consistent with experiment. (authors)

New techniques for multi-level cross section calculation and fitting

International Nuclear Information System (INIS)

Froehner, F.H.

1980-09-01

A number of recent developments in multi-level cross section work are described. A new iteration scheme for the conversion of Reich-Moore resonance parameters to Kapur-Peierls parameters allows application of Turing's method for Gaussian broadening of meromorphic functions directly to multi-level cross section expressions, without recourse to the Voigt profiles psi and chi. This makes calculation of Doppler-broadened Reich-Moore and MLBW cross sections practically as fast as SLBW and Adler-Adler cross section calculations involving the Voigt profiles. A convenient distant-level treatment utilizing average resonance parameters is presented. Apart from effectively dealing with edge effects in resonance fitting work it also leads to a simple prescription for the determination of bound levels which reproduce the thermal cross sections correctly. A brief discussion of improved resonance shape fitting techniques is included, with empahsis on the importance of correlated errors and proper use of prior information by application of Bayes' theorem. (orig.) [de

New techniques for multi-level cross section calculation and fitting

International Nuclear Information System (INIS)

Froehner, F.H.

1981-01-01

A number of recent developments in multi-level cross section work are described. A new iteration scheme for the conversion of Reich-Moore resonance parameters to Kapur-Peierls parameters allows application of Turing's method for Gaussian broadening of meromorphic functions directly to multi-level cross section expressions, without recourse to the Voigt profiles psi and chi. This makes calculation of Doppler-broadened Reich-Moore and MLBW cross sections practically as fast as SLBW and Adler-Adler cross section calculations involving the Voigt profiles. A convenient distant-level treatment utilizing average resonance parameters is presented. Apart from effectively dealing with edge effects in resonance fitting work it also leads to a simple prescription for the determination of bound levels which reproduce the thermal cross sections correctly. A brief discussion of improved resonance shape fitting techniques is included, with emphasis on the importance of correlated errors and proper use of prior information by application of Bayes' theorem

On the multi-level solution algorithm for Markov chains

Energy Technology Data Exchange (ETDEWEB)

Horton, G. [Univ. of Erlangen, Nuernberg (Germany)

1996-12-31

We discuss the recently introduced multi-level algorithm for the steady-state solution of Markov chains. The method is based on the aggregation principle, which is well established in the literature. Recursive application of the aggregation yields a multi-level method which has been shown experimentally to give results significantly faster than the methods currently in use. The algorithm can be reformulated as an algebraic multigrid scheme of Galerkin-full approximation type. The uniqueness of the scheme stems from its solution-dependent prolongation operator which permits significant computational savings in the evaluation of certain terms. This paper describes the modeling of computer systems to derive information on performance, measured typically as job throughput or component utilization, and availability, defined as the proportion of time a system is able to perform a certain function in the presence of component failures and possibly also repairs.

Progress and challenges in the development and qualification of multi-level multi-physics coupled methodologies for reactor analysis

International Nuclear Information System (INIS)

Ivanov, K.; Avramova, M.

2007-01-01

Current trends in nuclear power generation and regulation as well as the design of next generation reactor concepts along with the continuing computer technology progress stimulate the development, qualification and application of multi-physics multi-scale coupled code systems. The efforts have been focused on extending the analysis capabilities by coupling models, which simulate different phenomena or system components, as well as on refining the scale and level of detail of the coupling. This paper reviews the progress made in this area and outlines the remaining challenges. The discussion is illustrated with examples based on neutronics/thermohydraulics coupling in the reactor core modeling. In both fields recent advances and developments are towards more physics-based high-fidelity simulations, which require implementation of improved and flexible coupling methodologies. First, the progresses in coupling of different physics codes along with the advances in multi-level techniques for coupled code simulations are discussed. Second, the issues related to the consistent qualification of coupled multi-physics and multi-scale code systems for design and safety evaluation are presented. The increased importance of uncertainty and sensitivity analysis are discussed along with approaches to propagate the uncertainty quantification between the codes. The incoming OECD LWR Uncertainty Analysis in Modeling (UAM) benchmark is the first international activity to address this issue and it is described in the paper. Finally, the remaining challenges with multi-physics coupling are outlined. (authors)

Progress and challenges in the development and qualification of multi-level multi-physics coupled methodologies for reactor analysis

Energy Technology Data Exchange (ETDEWEB)

Ivanov, K.; Avramova, M. [Pennsylvania State Univ., University Park, PA (United States)

2007-07-01

Current trends in nuclear power generation and regulation as well as the design of next generation reactor concepts along with the continuing computer technology progress stimulate the development, qualification and application of multi-physics multi-scale coupled code systems. The efforts have been focused on extending the analysis capabilities by coupling models, which simulate different phenomena or system components, as well as on refining the scale and level of detail of the coupling. This paper reviews the progress made in this area and outlines the remaining challenges. The discussion is illustrated with examples based on neutronics/thermohydraulics coupling in the reactor core modeling. In both fields recent advances and developments are towards more physics-based high-fidelity simulations, which require implementation of improved and flexible coupling methodologies. First, the progresses in coupling of different physics codes along with the advances in multi-level techniques for coupled code simulations are discussed. Second, the issues related to the consistent qualification of coupled multi-physics and multi-scale code systems for design and safety evaluation are presented. The increased importance of uncertainty and sensitivity analysis are discussed along with approaches to propagate the uncertainty quantification between the codes. The incoming OECD LWR Uncertainty Analysis in Modeling (UAM) benchmark is the first international activity to address this issue and it is described in the paper. Finally, the remaining challenges with multi-physics coupling are outlined. (authors)

MORPHOMETRIC ASPECTS IN THE BÂRLAD BASIN

Directory of Open Access Journals (Sweden)

BĂLAN OANA

2015-03-01

Full Text Available Bârlad valley morphometry is strongly influenced by lithology, geological structure and climatic conditions. Between its springs and the outflow we noticed notable deviations from valley monocline structure and from the consecvent overall direction of the river system. Morphometric analysis of the Bârlad valley cumulates and summarizes the sequence of events that occurred in its hydrographic basin, which in turn has been actively reflected in indices such as generated the altimetry, the relief depth fragmentation.

PredPPCrys: accurate prediction of sequence cloning, protein production, purification and crystallization propensity from protein sequences using multi-step heterogeneous feature fusion and selection.

Directory of Open Access Journals (Sweden)

Huilin Wang

Full Text Available X-ray crystallography is the primary approach to solve the three-dimensional structure of a protein. However, a major bottleneck of this method is the failure of multi-step experimental procedures to yield diffraction-quality crystals, including sequence cloning, protein material production, purification, crystallization and ultimately, structural determination. Accordingly, prediction of the propensity of a protein to successfully undergo these experimental procedures based on the protein sequence may help narrow down laborious experimental efforts and facilitate target selection. A number of bioinformatics methods based on protein sequence information have been developed for this purpose. However, our knowledge on the important determinants of propensity for a protein sequence to produce high diffraction-quality crystals remains largely incomplete. In practice, most of the existing methods display poorer performance when evaluated on larger and updated datasets. To address this problem, we constructed an up-to-date dataset as the benchmark, and subsequently developed a new approach termed 'PredPPCrys' using the support vector machine (SVM. Using a comprehensive set of multifaceted sequence-derived features in combination with a novel multi-step feature selection strategy, we identified and characterized the relative importance and contribution of each feature type to the prediction performance of five individual experimental steps required for successful crystallization. The resulting optimal candidate features were used as inputs to build the first-level SVM predictor (PredPPCrys I. Next, prediction outputs of PredPPCrys I were used as the input to build second-level SVM classifiers (PredPPCrys II, which led to significantly enhanced prediction performance. Benchmarking experiments indicated that our PredPPCrys method outperforms most existing procedures on both up-to-date and previous datasets. In addition, the predicted crystallization

Pruning techniques for multi-objective system-level design space exploration

NARCIS (Netherlands)

Piscitelli, R.

2014-01-01

System-level design space exploration (DSE), which is performed early in the design process, is of eminent importance to the design of complex multi-processor embedded system architectures. During system-level DSE, system parameters like, e.g., the number and type of processors, the type and size of

Morphometric variations of three species of harvested cephalopods found in northern sea of Aceh Province, Indonesia

Directory of Open Access Journals (Sweden)

ZAINAL ABIDIN MUCHLISIN

2014-10-01

Full Text Available Muchlisin ZA, Zulkarnaini B, Purnawan S, Muhadjier A, Fadli N, Cheng SH. 2014. Morphometric variations of three species of harvested cephalopods found in northern sea of Aceh Province, Indonesia. Biodiversitas 15: 142-146. The purpose of the present study was to evaluate the morphometrics of three harvested cephalopods, Sepioteuthis lessoniana, Sepia officinalis and Uroteuthis sp. found in northern sea of Aceh Province, Indonesia. Sampling was conducted for six months from July to December 2012 in one week interval. A total of 318 cephalopods; 139 Sepioteuthis lessoniana, 139 Uroteuthis sp. and 40 Sepia officinalis were analyzed for morphometric study and 13 anatomical characters were measured to the nearest 0.01 mm using a digital calipers. Morphometric measurements were significantly different between the different species of cephalopods (ANOVA, p<0.05. S. officinalis differed in six morphological characters (head length, head width, tentacles length, gladius width, rancis width and length from the squid species. Fin width and length were significantly greater in S. lessoniana than in S. officinalis and Uroteuthis sp. On the other hand, Uroteuthis sp. had significantly greater mantle lengths, standard lengths and gladius lengths than the other two cephalopod species (Duncan Test, p<0.05. However, fin width was similar between S. lessoniana and Uroteuthis sp., while eye diameter was similar between S. officinalis and Uroteuthis sp. A Discriminant Function Analysis scatter plot successfully discriminated the three species indicating significant differences in morphological variation. This analysis also indicates that morphometrically, S. lessoniana and S. officinalis are more similar to each other despite being in different orders.

Features, Events, and Processes: system Level

Energy Technology Data Exchange (ETDEWEB)

D. McGregor

2004-10-15

The purpose of this analysis report is to evaluate and document the inclusion or exclusion of the system-level features, events, and processes (FEPs) with respect to modeling used to support the total system performance assessment for the license application (TSPA-LA). A screening decision, either Included or Excluded, is given for each FEP along with the technical basis for screening decisions. This information is required by the U.S. Nuclear Regulatory Commission (NRC) at 10 CFR 63.113 (d, e, and f) (DIRS 156605). The system-level FEPs addressed in this report typically are overarching in nature, rather than being focused on a particular process or subsystem. As a result, they are best dealt with at the system level rather than addressed within supporting process-level or subsystem-level analyses and models reports. The system-level FEPs also tend to be directly addressed by regulations, guidance documents, or assumptions listed in the regulations; or are addressed in background information used in development of the regulations. For included FEPs, this analysis summarizes the implementation of the FEP in the TSPA-LA (i.e., how the FEP is included). For excluded FEPs, this analysis provides the technical basis for exclusion from the TSPA-LA (i.e., why the FEP is excluded). The initial version of this report (Revision 00) was developed to support the total system performance assessment for site recommendation (TSPA-SR). This revision addresses the license application (LA) FEP List (DIRS 170760).

Features, Events, and Processes: system Level

International Nuclear Information System (INIS)

D. McGregor

2004-01-01

The purpose of this analysis report is to evaluate and document the inclusion or exclusion of the system-level features, events, and processes (FEPs) with respect to modeling used to support the total system performance assessment for the license application (TSPA-LA). A screening decision, either Included or Excluded, is given for each FEP along with the technical basis for screening decisions. This information is required by the U.S. Nuclear Regulatory Commission (NRC) at 10 CFR 63.113 (d, e, and f) (DIRS 156605). The system-level FEPs addressed in this report typically are overarching in nature, rather than being focused on a particular process or subsystem. As a result, they are best dealt with at the system level rather than addressed within supporting process-level or subsystem-level analyses and models reports. The system-level FEPs also tend to be directly addressed by regulations, guidance documents, or assumptions listed in the regulations; or are addressed in background information used in development of the regulations. For included FEPs, this analysis summarizes the implementation of the FEP in the TSPA-LA (i.e., how the FEP is included). For excluded FEPs, this analysis provides the technical basis for exclusion from the TSPA-LA (i.e., why the FEP is excluded). The initial version of this report (Revision 00) was developed to support the total system performance assessment for site recommendation (TSPA-SR). This revision addresses the license application (LA) FEP List (DIRS 170760)

Multi-Level Bitmap Indexes for Flash Memory Storage

Energy Technology Data Exchange (ETDEWEB)

Wu, Kesheng; Madduri, Kamesh; Canon, Shane

2010-07-23

Due to their low access latency, high read speed, and power-efficient operation, flash memory storage devices are rapidly emerging as an attractive alternative to traditional magnetic storage devices. However, tests show that the most efficient indexing methods are not able to take advantage of the flash memory storage devices. In this paper, we present a set of multi-level bitmap indexes that can effectively take advantage of flash storage devices. These indexing methods use coarsely binned indexes to answer queries approximately, and then use finely binned indexes to refine the answers. Our new methods read significantly lower volumes of data at the expense of an increased disk access count, thus taking full advantage of the improved read speed and low access latency of flash devices. To demonstrate the advantage of these new indexes, we measure their performance on a number of storage systems using a standard data warehousing benchmark called the Set Query Benchmark. We observe that multi-level strategies on flash drives are up to 3 times faster than traditional indexing strategies on magnetic disk drives.

Quantification of mold contamination in multi-level buildings using the Environmental Relative Moldiness Index

Science.gov (United States)

The goal of this study was to evaluate the possible use of the Environmental Relative Moldiness Index (ERMI) to quantify mold contamination in multi-level, office buildings. Settled-dust samples were collected in multi-level, office buildings and the ERMI value for each sample de...

Multi-level restricted maximum likelihood covariance estimation and kriging for large non-gridded spatial datasets

KAUST Repository

Castrillon, Julio

2015-11-10

We develop a multi-level restricted Gaussian maximum likelihood method for estimating the covariance function parameters and computing the best unbiased predictor. Our approach produces a new set of multi-level contrasts where the deterministic parameters of the model are filtered out thus enabling the estimation of the covariance parameters to be decoupled from the deterministic component. Moreover, the multi-level covariance matrix of the contrasts exhibit fast decay that is dependent on the smoothness of the covariance function. Due to the fast decay of the multi-level covariance matrix coefficients only a small set is computed with a level dependent criterion. We demonstrate our approach on problems of up to 512,000 observations with a Matérn covariance function and highly irregular placements of the observations. In addition, these problems are numerically unstable and hard to solve with traditional methods.

Topological structures of adiabatic phase for multi-level quantum systems

International Nuclear Information System (INIS)

Liu Zhengxin; Zhou Xiaoting; Liu Xin; Liu Xiongjun; Chen Jingling

2007-01-01

The topological properties of adiabatic gauge fields for multi-level (three-level in particular) quantum systems are studied in detail. Similar to the result that the adiabatic gauge field for SU(2) systems (e.g. two-level quantum system or angular momentum systems, etc) has a monopole structure, the curvature 2-forms of the adiabatic holonomies for SU(3) three-level and SU(3) eight-level quantum systems are shown to have monopole-like (for all levels) or instanton-like (for the degenerate levels) structures

The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research.

Directory of Open Access Journals (Sweden)

Christopher Woods

Full Text Available This paper introduces statistical shape modelling (SSM for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA. Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique's application was demonstrated for inter-sample comparison through analysis of the principal component (PC weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA and reconstruction from partial datasets.

space vector pulse width modulation of a multi-level diode clamped

African Journals Online (AJOL)

ES Obe

step by step development of MATLAB /SIMULINK modeling of the space vector ..... Pulse Width Mod. of Multi-Level Diode Clamped Converter 119 powergui. Discrete, .... Load. Figure 22: Block diagram of the three level DCC design. 3 LEVEL ...

Achieving strategic renewal: the multi-level influences of top and middle managers’ boundary-spanning

NARCIS (Netherlands)

Glaser, L.; Fourne, S.P.L.; Elfring, T.

2015-01-01

Drawing on corporate entrepreneurship (CE) and social network research, this study focuses on strategic renewal as a form of CE and examines the impact of boundary-spanning at top and middle management levels on business units’ exploratory innovation. Analyses of multi-source and multi-level data,

Genetic parameters and trends of morphometric traits of GIFT tilapia under selection for weight gain

Directory of Open Access Journals (Sweden)

Rafael Vilhena Reis Neto

2014-08-01

Full Text Available The main factor considered in breeding programs for fish is growth, which can be assessed in terms of a gain in either weight or body measurements. This study was undertaken to evaluate the morphometric traits of GIFT strain tilapia (Oreochromis sp. selected for weight gain. The data set used contained information on 6,650 animals. The genetic values of 8,590 animals in a relationship matrix of five generations were predicted. The following morphometric measurements were evaluated: standard length; body depth and body width. Body area and volume were also calculated. Bi-character analyses involving morphometric traits were used to estimate (covariance components. Heritability, larval and fingerling common environmental effects were estimated for each trait, together with the genetic and phenotypic correlations between traits. Bayesian procedures were utilised by Gibbs chains, and the convergence of the chains was tested using the Heidelberger and Welch method. Genetic trends were estimated by segmented regression of the fish breeding values of the generations considered in this study. Estimates of heritability (0.28 a 0.31 had moderate to high magnitudes for all traits. Genetic correlations between traits were all above 0.8, and the genetic gains were satisfactory from the third generation onwards. From the estimates of the genetic parameters and genetic gain the morphometric traits evaluated have good potential for selection.

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan

2016-12-29

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan; Tsang, Ivor Wai-Hung; Cui, Xuefeng; Lu, Zhiwu; Gao, Xin

2016-01-01

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Multi-level restricted maximum likelihood covariance estimation and kriging for large non-gridded spatial datasets

KAUST Repository

Castrillon, Julio; Genton, Marc G.; Yokota, Rio

2015-01-01

We develop a multi-level restricted Gaussian maximum likelihood method for estimating the covariance function parameters and computing the best unbiased predictor. Our approach produces a new set of multi-level contrasts where the deterministic

Morphometric Studies Of The Cerebellum And Forebrain Of The ...

African Journals Online (AJOL)

Morphometric studies were undertaken using the brains of six African giant rats. The mean of weights and lengths (tip of the olfactory bulb to the caudal border of the cerebellum) were observed tobe 4.88 0.183g and 4.40 0.193g, respectively. Similarly, the mean weight and length of the cerebellum and the forebrain ...

Effect of Genotype and Age on Some Morphometric, Body Linear ...

African Journals Online (AJOL)

A population of 231 roosters of the Nigerian indigenous chickens of normal feathered frizzle feathered and naked neck genotypes was evaluated for the effect of genotype and age on some morphometric body linear measurements and semen characteristics of three Nigerian chicken genotypes. 20 roosters from each ...

Sex determination from the frontal bone: a geometric morphometric study.

Science.gov (United States)

Perlaza, Néstor A

2014-09-01

Sex estimation in human skeletal remains when using the cranium through traditional methods is a fundamental pillar in human identification; however, it may be possible to incur in a margin of error due because of the state of preservation in incomplete or fragmented remains. The aim of this investigation was sex estimation through the geometric morphometric analysis of the frontal bone. The sample employed 60 lateral radiographs of adult subjects of both sexes (30 males and 30 females), aged between 18 and 40 years, with mean age for males of 28 ± 4 and 30 ± 6 years for females. Thin-plate splines evidenced strong expansion of the glabellar region in males and contraction in females. No significant differences were found between sexes with respect to size. The findings suggest differences in shape and size in the glabellar region, besides reaffirming the use of geometric morphometrics as a quantitative method in sex estimation. © 2014 American Academy of Forensic Sciences.

Are morphometrics sufficient for estimating age of pre-fledging birds in the field? A test using common terns (Sterna hirundo.

Directory of Open Access Journals (Sweden)

Christy N Wails

Full Text Available Age is a key component of fitness, affecting survival and reproductive capacities. Where it is not possible to study known individuals from birth, morphometrics (predominantly patterns of plumage development for birds are most often used to estimate age. Although criteria for age estimations exist for many species, the degree to which these criteria improve the precision of estimates remains to be tested, restricting their widespread acceptance. We develop a photographic tool for estimating ages of Common Tern (Sterna hirundo chicks and test it using 100 human observers of varying prior experience across four breeding colonies (three North American sites and one European site and under controlled laboratory conditions. We followed the design approach of other morphometric tools, expanding it to create a user-friendly guide (divided into six age groupings. The majority (86% of observers improved in chick-aging accuracy when using the tool by an average of 20.1% (±1.4 SE and correctly estimated 60.3% (±1.4 of chick ages. This was similar to the intrinsic aging ability of our best field observer (63.3%. Observers with limited experience showed the greatest increases in chick-aging accuracy over experienced observers who likely had established a method for estimating chick ages prior to using the tool. Even the best observers only correctly estimated ages of chicks 62.9% (±2.8 of the time in the field and 84.0% (±2.9 of the time in the lab when using the tool and typically underestimated ages. This indicates that developmental variation between individual chicks can prevent completely reliable age estimates and corroborates the few existing data that suggest that morphometric criteria fail to achieve robust levels of accuracy and may introduce error into studies that rely on them. We conclude that novel approaches for estimating age, not only morphometric criteria, must be pursued.

The design of multi-core DSP parallel model based on message passing and multi-level pipeline

Science.gov (United States)

Niu, Jingyu; Hu, Jian; He, Wenjing; Meng, Fanrong; Li, Chuanrong

2017-10-01

Currently, the design of embedded signal processing system is often based on a specific application, but this idea is not conducive to the rapid development of signal processing technology. In this paper, a parallel processing model architecture based on multi-core DSP platform is designed, and it is mainly suitable for the complex algorithms which are composed of different modules. This model combines the ideas of multi-level pipeline parallelism and message passing, and summarizes the advantages of the mainstream model of multi-core DSP (the Master-Slave model and the Data Flow model), so that it has better performance. This paper uses three-dimensional image generation algorithm to validate the efficiency of the proposed model by comparing with the effectiveness of the Master-Slave and the Data Flow model.

Visual Localization across Seasons Using Sequence Matching Based on Multi-Feature Combination.

Science.gov (United States)

Qiao, Yongliang

2017-10-25

Visual localization is widely used in autonomous navigation system and Advanced Driver Assistance Systems (ADAS). However, visual-based localization in seasonal changing situations is one of the most challenging topics in computer vision and the intelligent vehicle community. The difficulty of this task is related to the strong appearance changes that occur in scenes due to weather or season changes. In this paper, a place recognition based visual localization method is proposed, which realizes the localization by identifying previously visited places using the sequence matching method. It operates by matching query image sequences to an image database acquired previously (video acquired during traveling period). In this method, in order to improve matching accuracy, multi-feature is constructed by combining a global GIST descriptor and local binary feature CSLBP (Center-symmetric local binary patterns) to represent image sequence. Then, similarity measurement according to Chi-square distance is used for effective sequences matching. For experimental evaluation, the relationship between image sequence length and sequences matching performance is studied. To show its effectiveness, the proposed method is tested and evaluated in four seasons outdoor environments. The results have shown improved precision-recall performance against the state-of-the-art SeqSLAM algorithm.

Bio-mechanical and morphometric evaluation of late radiation-induced changes in the mouse rectum

International Nuclear Information System (INIS)

Lundby, L.

1998-01-01

The overall aim of this thesis was to study the development of late radiation induced damage of the rectum and describe the histopathological and morphometric characteristics of the late injury. This required the design of a new, small probe for rectal measurements of cross-sectional area and distension pressure in mice. The impedance planimetric method was developed and validated in vitro and applied in in vivo studies of normal mice. The study of radiation induced damage of the rectum also required a new set-up for selective irradiation of a specific part of the rectum, shielding other organs. Mice were irradiated with varying single doses and followed with impedance planimetric measurements at regular intervals until death of the animals. In order to compare observed changes of the functional properties of the rectum following irradiation, a description of morphometric and morphologic characteristics by a stereolic technique was planned. A simplified stereological method has been applied to this study to describe late morphometric changes in the different intestinal layers after irradiation with varying single doses. (EG)

Loading Analysis of Modular Multi-level Converter for Offshore High-voltage DC Application under Various Grid Faults

DEFF Research Database (Denmark)

Liu, Hui; Ma, Ke; Loh, Poh Chiang

2016-01-01

challenges but may also result in overstressed components for the modular multi-level converter. However, the thermal loading of the modular multi-level converter under various grid faults has not yet been clarified. In this article, the power loss and thermal performance of the modular multi-level converter...... low-voltage ride-through strongly depend on the types and severity values of grid voltage dips. The thermal distribution among the three phases of the modular multi-level converter may be quite uneven, and some devices are much more stressed than the normal operating condition, which may...

A fast photo-counter with multi-level buffers

International Nuclear Information System (INIS)

Peng Hu; Zhou Peiling; Yao Kun; Guo Guangcan

1992-01-01

Digital Photon Correlator (DPC) is composed of a Photo-counter and a data processing unit. The performance of Photo-counter in data acquisition system has a direct influence on data processing. The Photo-counter with fast carry designed here has multi-level buffers. Photon pulses can be correctly and dynamically recorded by the Photo-counter and processed by a single chip computer

Ship Detection in Optical Remote Sensing Images Based on Wavelet Transform and Multi-Level False Alarm Identification

Directory of Open Access Journals (Sweden)

Fang Xu

2017-09-01

Full Text Available Ship detection by Unmanned Airborne Vehicles (UAVs and satellites plays an important role in a spectrum of related military and civil applications. To improve the detection efficiency, accuracy, and speed, a novel ship detection method from coarse to fine is presented. Ship targets are viewed as uncommon regions in the sea background caused by the differences in colors, textures, shapes, or other factors. Inspired by this fact, a global saliency model is constructed based on high-frequency coefficients of the multi-scale and multi-direction wavelet decomposition, which can characterize different feature information from edge to texture of the input image. To further reduce the false alarms, a new and effective multi-level discrimination method is designed based on the improved entropy and pixel distribution, which is robust against the interferences introduced by islands, coastlines, clouds, and shadows. The experimental results on optical remote sensing images validate that the presented saliency model outperforms the comparative models in terms of the area under the receiver operating characteristic curves core and the accuracy in the images with different sizes. After the target identification, the locations and the number of the ships in various sizes and colors can be detected accurately and fast with high robustness.

Customized binary and multi-level HfO2-x-based memristors tuned by oxidation conditions.

Science.gov (United States)

He, Weifan; Sun, Huajun; Zhou, Yaxiong; Lu, Ke; Xue, Kanhao; Miao, Xiangshui

2017-08-30

The memristor is a promising candidate for the next generation non-volatile memory, especially based on HfO 2-x , given its compatibility with advanced CMOS technologies. Although various resistive transitions were reported independently, customized binary and multi-level memristors in unified HfO 2-x material have not been studied. Here we report Pt/HfO 2-x /Ti memristors with double memristive modes, forming-free and low operation voltage, which were tuned by oxidation conditions of HfO 2-x films. As O/Hf ratios of HfO 2-x films increase, the forming voltages, SET voltages, and R off /R on windows increase regularly while their resistive transitions undergo from gradually to sharply in I/V sweep. Two memristors with typical resistive transitions were studied to customize binary and multi-level memristive modes, respectively. For binary mode, high-speed switching with 10 3 pulses (10 ns) and retention test at 85 °C (>10 4 s) were achieved. For multi-level mode, the 12-levels stable resistance states were confirmed by ongoing multi-window switching (ranging from 10 ns to 1 μs and completing 10 cycles of each pulse). Our customized binary and multi-level HfO 2-x -based memristors show high-speed switching, multi-level storage and excellent stability, which can be separately applied to logic computing and neuromorphic computing, further suitable for in-memory computing chip when deposition atmosphere may be fine-tuned.

Morphometric study of the Habo dome, Kachchh, Gujarat, India: implications on neotectonic activity

Science.gov (United States)

Bhattacharjee, N.; Mohanty, S. P.

2017-12-01

The Kachchh Basin of western India was developed during the separation of the Indian plate from the Gondwanaland in Mesozoic. Series of E-W striking master faults were generated during this extensional phase. The collision of the Indian and Eurasian plates in Eocene time resulted in the change of stress regime to a compressional setting when the built-up stress developed NNW-SSE to NNE-SSW striking transverse faults and reactivated the earlier E-W master faults. The present work was carried out in the Habo dome, located in the central part of the Kachchh Basin, to analyse the morphometric features such as the bifurcation ratio, circulation ratio, drainage texture, asymmetric factor, hypsometric indices and mountain front sinuosity of selected sub-watersheds of the area to understand the effects of fault reactivation and neotectonic activities on the geometry of the dome. Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM) data were used to extract drainage network for morphometric analysis of the Kaswati, Khari, and Pur river basins. The study area is elliptical in outline with the long axis trending approximately E-W. The evolution of this domal structure is interpreted to be the result of fault-bound nature of the block. The northern slope of the dome is bound by the Kachchh Mainland Fault and the eastern and western boundaries are marked by transverse faults. The undulating topography was developed by differential movements along several transverse faults striking NW-SE, N-S, and NE-SW. The earlier interpretation of laccolith intrusion into the sedimentary rocks is not supported by the data analysis and field mapping. Stress propagations from the Himalayan range in the northeast and Sulaiman range in the northwest are identified to be the causative factor for historical seismicity and drainage anomalies in the area. Keywords: Basin morphometry, Geographical Information System, Lineament patterns, Kachchh basin, Neotectonics, Fault reactivation

Morphometric Analysis of Mandibular Growth in Skeletal Class III Malocclusion

Directory of Open Access Journals (Sweden)

Jenny Zwei-Chieng Chang

2006-01-01

Conclusion: We conclude that thin-plate spline analysis and the finite element morphometric method are efficient for the localization and quantification of size and shape changes that occur during mandibular growth. Plots of maximum and minimum principal directions can provide useful information about the trends of growth changes.

A linear bi-level multi-objective program for optimal allocation of water resources.

Directory of Open Access Journals (Sweden)

Ijaz Ahmad

Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.

Multi-focus and multi-level techniques for visualization and analysis of networks with thematic data

Science.gov (United States)

Cossalter, Michele; Mengshoel, Ole J.; Selker, Ted

2013-01-01

Information-rich data sets bring several challenges in the areas of visualization and analysis, even when associated with node-link network visualizations. This paper presents an integration of multi-focus and multi-level techniques that enable interactive, multi-step comparisons in node-link networks. We describe NetEx, a visualization tool that enables users to simultaneously explore different parts of a network and its thematic data, such as time series or conditional probability tables. NetEx, implemented as a Cytoscape plug-in, has been applied to the analysis of electrical power networks, Bayesian networks, and the Enron e-mail repository. In this paper we briefly discuss visualization and analysis of the Enron social network, but focus on data from an electrical power network. Specifically, we demonstrate how NetEx supports the analytical task of electrical power system fault diagnosis. Results from a user study with 25 subjects suggest that NetEx enables more accurate isolation of complex faults compared to an especially designed software tool.

Multi-scale Analysis of High Resolution Topography: Feature Extraction and Identification of Landscape Characteristic Scales

Science.gov (United States)

Passalacqua, P.; Sangireddy, H.; Stark, C. P.

2015-12-01

With the advent of digital terrain data, detailed information on terrain characteristics and on scale and location of geomorphic features is available over extended areas. Our ability to observe landscapes and quantify topographic patterns has greatly improved, including the estimation of fluxes of mass and energy across landscapes. Challenges still remain in the analysis of high resolution topography data; the presence of features such as roads, for example, challenges classic methods for feature extraction and large data volumes require computationally efficient extraction and analysis methods. Moreover, opportunities exist to define new robust metrics of landscape characterization for landscape comparison and model validation. In this presentation we cover recent research in multi-scale and objective analysis of high resolution topography data. We show how the analysis of the probability density function of topographic attributes such as slope, curvature, and topographic index contains useful information for feature localization and extraction. The analysis of how the distributions change across scales, quantified by the behavior of modal values and interquartile range, allows the identification of landscape characteristic scales, such as terrain roughness. The methods are introduced on synthetic signals in one and two dimensions and then applied to a variety of landscapes of different characteristics. Validation of the methods includes the analysis of modeled landscapes where the noise distribution is known and features of interest easily measured.

Integration of multi-level marketing management systems geographically industry development

OpenAIRE

Aleksandr Lavrov; Lada Polikarpova; Alla Handramai

2015-01-01

In the article the authors attempt to develop a multi-level management system territorially industry development in market conditions, built in the widespread use of various types of marketing and their horizontal and vertical integration.

Morphological and Morphometrical Description of Trichostrongylus Species Isolated from Domestic Ruminants in Khuzestan Province, Southwest Iran

Directory of Open Access Journals (Sweden)

B Golestan

2011-09-01

Full Text Available Backgrounds: Genus Trichostrongylus (Nematoda: Trichostrongylidae is one of the most impor­tant zoonotic nematodes with wide geographic distribution in the world. The purpose of the present study was to describe morphological and morphometrical characteristics of male Trichostrongylus species, currently prevalent in domestic ruminants of Khuzestan Province, south­west Iran.Methods: Gastro-intestinal organs of 1600 sheep, goats, cattle, and buffalos, slaughtered in Khuzestan Province, southwest Iran, were examined for infectivity with Trichostrongylus spe­cies. For examination and measurements of helminthes, Azo-carmine staining was per­formed, followed by camera lucida drawings of morphological characters and measurements of morphometrical criteria with a calibrated microscope. Using valid nematodes systematic keys, almost all the parasites were identified at the level of species.Results: Overall, 114 animals were found infected with at least one species of Trichostrongy­lus. Considering morphological characteristics of male Trichostrongylus, six species were identi­fied including T. colubriformis, T. vitrinus, T. probolorus, T. capricola, T. longispicu­laris and Trichostrongylus sp. Conclusion: Although, compared to the previous decades, currently Trichostrongylus is much less prevalent in the domestic ruminants of the study area, but still different species occur in these animals.

URBAN FEATURES AND ENERGY CONSUMPTION AT LOCAL LEVEL

Directory of Open Access Journals (Sweden)

Ali Soltani

2012-12-01

Full Text Available There has been a growing interest in discovering the human effects on the environment and energy consumption in recent decades. It is estimated that the share of energy consumed in transportation and housing systems are around 20 and 30 percent of total energy consumption respectively. Furthermore, the residential greenhouse emissions depend on urban form and structure. This paper explores the effects of urban features on residential energy consumption at neighborhood level using data collected through household questionnaire (n=140. Two residential districts in metropolitan Shiraz, south of Iran, were selected as case study areas. Different features of two areas were compared including building density, typology, housing location, parcel size, floor area and construction materials. Ordinary linear regression was used to discover the impact of explanatory variables on energy consumption. It was found that some physical variables such as parcel size, setback and number of floors played significant roles in explaining the variances exist in energy use level. The results can be used by governmental agencies to modify land use policies and subdivision rules in hope of saving energy and achieving a sustainable community.

Morphometric analysis of hepatic steatosis in chronic hepatitis C infection

International Nuclear Information System (INIS)

Zubair, Alia; Jamal Shahid; Mubarik Azhar

2009-01-01

To quantitatively assess steatosis by a morphometric method and to study its relationship with other histological features of chronic hepatitis C (CHC). This was a comparative descriptive study. The study was carried out in the Department of Histopathology, Army Medical College, Rawalpindi, Pakistan, from March 2006 to March 2007. Patients who had undergone a liver biopsy for the evaluation of hepatitis C virus (HCV) infection were included in the study. Demographic characteristics and laboratory data were collected at the time of biopsy. The first hundred biopsy specimens that met the inclusion criteria were assessed for grades of steatosis (semiquantitatively), diameter of fat globules (by a morphometric method), necroinflammation, and fibrosis (semiquantitatively). Liver biopsies were processed for paraffin embedding, stained with hematoxylin and eosin, whereas Gomori's Reticulin stain was used for the evaluation of fibrosis. Out of 46 cases showing fatty change, pansteatosis was observed in 24 (52%) patients: 12 (26%) cases had a pericentral and mid zonal distribution of fat globules and eight (17.5%) cases revealed a mid zonal pattern only. There were two (4.5%) cases in which fat globules were found in periportal and mid zonal areas. None of the histological parameters (the stage of fibrosis and grades of inflammation) had any significant correlation with these distribution patterns of steatosis. The diameter of fat droplets was quantified by morphometry. A mixed pattern of steatosis was observed more frequently (21 out of 46 cases): 17 cases had microglobules and eight biopsies showed macroglobules. The size of the fat globules exhibited a significant correlation with the stage of fibrosis ( P < 0.0001). The analysis of the grades of necroinflammation did not reveal any significant relationship with the diameter of fat globules. A mixed pattern of fat globules is more frequently observed in CHC, but macrovesicular steatosis is associated with a higher stage

Morphometric magnetic resonance imaging and genetic testing in cerebellar abiotrophy in Arabian horses

Science.gov (United States)

2013-01-01

Background Cerebellar abiotrophy (CA) is a rare but significant disease in Arabian horses caused by progressive death of the Purkinje cells resulting in cerebellar ataxia characterized by a typical head tremor, jerky head movements and lack of menace response. The specific role of magnetic resonance imaging (MRI) to support clinical diagnosis has been discussed. However, as yet MR imaging has only been described in one equine CA case. The role of MR morphometry in this regard is currently unknown. Due to the hereditary nature of the disease, genetic testing can support the diagnosis of CA. Therefore, the objective of this study was to perform MR morphometric analysis and genetic testing in four CA-affected Arabian horses and one German Riding Pony with purebred Arabian bloodlines in the third generation. Results CA was diagnosed pathohistologically in the five affected horses (2 months - 3 years) supported by clinical signs, necropsy, and genetic testing which confirmed the TOE1:g.2171G>A SNP genotype A/A in all CA-affected horses. On MR images morphometric analysis of the relative cerebellar size and relative cerebellar cerebrospinal fluid (CSF) space were compared to control images of 15 unaffected horses. It was demonstrated that in MR morphometric analyses, CA affected horses displayed a relatively smaller cerebellum compared to the entire brain mass than control animals (P = 0.0088). The relative cerebellar CSF space was larger in affected horses (P = 0.0017). Using a cut off value of 11.0% for relative cerebellar CSF space, the parameter differentiated between CA-affected horses and controls with a sensitivity of 100% and a specificity of 93.3%. Conclusions In conclusion, morphometric MRI and genetic analysis could be helpful to support the diagnosis of CA in vivo. PMID:23702154

An Approach for Patient-Specific Multi-domain Vascular Mesh Generation Featuring Spatially Varying Wall Thickness Modeling

OpenAIRE

Raut, Samarth S.; Liu, Peng; Finol, Ender A.

2015-01-01

In this work, we present a computationally efficient image-derived volume mesh generation approach for vasculatures that implements spatially varying patient-specific wall thickness with a novel inward extrusion of the wall surface mesh. Multi-domain vascular meshes with arbitrary numbers, locations, and patterns of both iliac bifurcations and thrombi can be obtained without the need to specify features or landmark points as input. In addition, the mesh output is coordinate-frame independent ...

Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic.

Science.gov (United States)

Neumayr, Bernd; Schuetz, Christoph G; Jeusfeld, Manfred A; Schrefl, Michael

2018-01-01

An enterprise database contains a global, integrated, and consistent representation of a company's data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.

Quantitative morphologic assessment of thoracolumbar vertebrae in Korean women by morphometric x-ray absorptiometry

International Nuclear Information System (INIS)

Cheon, Bong Jin; Huh, Jin Do; Kim, Sung Min; Oh, Kyong Seung; Kim, Jong Min; Jung, Gyoo Sik; Joh, Young Duk

1999-01-01

To compare the accuracy of lateral radiography of the spine with that of morphometric X-ray absorptiometry(MXA) in vertebral morphometry, and to evaluate normal vertebral morphometry using MXA in Korean women. A spine phantom was constructed using copper pipe. Its anterior and posterior heights were measured directly, with lateral radiographs and with MXA, and the values thus obtained were compared. Inter- and intra-observer variations were evaluated by three radiologists. The vertebral morphometry of 30 young women volunteers were imaged using thoracic and lumbar lateral radiographs and MXA, and analysis included the measurement of anterior and posterior heights from T4 to L4. We also obtained the vertebral morphometry of 200 normal Korean women who underwent MXA between March 1995 and February 1996, though those with osteoporosis and other spinal lesions were excluded from this study. Thoracolumbar vertebral indexes were statistically correlated with age, height and bone mineral density. There were no statistically significant differences in the heights of spine phantom measured by MXA compared with actual size (mean difference=0.28mm). Simple radiographs were magnified by 23.7% at a phantom-table distance of 15cm, and distortion ranged from 0.5% to 22.5%, depending on phantom level and phantom-table distance. In the study of volunteers, the magnification rate between a simple radiograph and MXA was about 26.6%. Anterior height increased progressively from the thoracic to the lumbar spine, though posterior height peaked at L2, and L4 was less than anterior height. In Korean women, indices of vertebral morphometry decreased significantly with aging, with the most prominent decrease occurring during the seventh decade. The mineral density of spinal bone decreased markedly after the sixth decade. Radiographs showed more magnification and distortion than did MXA, though between morphometric X-ray absorptiometry (MXA) and actual size, there was no significant

Space Vector Pulse Width Modulation of a Multi-Level Diode ...

African Journals Online (AJOL)

Space Vector Pulse Width Modulation of a Multi-Level Diode Clamped ... of MATLAB /SIMULINK modeling of the space vector pulse-width modulation and the ... two adjacent active vectors in determining the switching process of the multilevel ...

Extended multi-configuration quasi-degenerate perturbation theory: the new approach to multi-state multi-reference perturbation theory.

Science.gov (United States)

Granovsky, Alexander A

2011-06-07

The distinctive desirable features, both mathematically and physically meaningful, for all partially contracted multi-state multi-reference perturbation theories (MS-MR-PT) are explicitly formulated. The original approach to MS-MR-PT theory, called extended multi-configuration quasi-degenerate perturbation theory (XMCQDPT), having most, if not all, of the desirable properties is introduced. The new method is applied at the second order of perturbation theory (XMCQDPT2) to the 1(1)A(')-2(1)A(') conical intersection in allene molecule, the avoided crossing in LiF molecule, and the 1(1)A(1) to 2(1)A(1) electronic transition in cis-1,3-butadiene. The new theory has several advantages compared to those of well-established approaches, such as second order multi-configuration quasi-degenerate perturbation theory and multi-state-second order complete active space perturbation theory. The analysis of the prevalent approaches to the MS-MR-PT theory performed within the framework of the XMCQDPT theory unveils the origin of their common inherent problems. We describe the efficient implementation strategy that makes XMCQDPT2 an especially useful general-purpose tool in the high-level modeling of small to large molecular systems. © 2011 American Institute of Physics

Urban Area Extent Extraction in Spaceborne HR and VHR Data Using Multi-Resolution Features

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Gianni Cristian Iannelli

2014-09-01

Full Text Available Detection of urban area extents by means of remotely sensed data is a difficult task, especially because of the multiple, diverse definitions of what an “urban area” is. The models of urban areas listed in technical literature are based on the combination of spectral information with spatial patterns, possibly at different spatial resolutions. Starting from the same data set, “urban area” extraction may thus lead to multiple outputs. If this is done in a well-structured framework, however, this may be considered as an advantage rather than an issue. This paper proposes a novel framework for urban area extent extraction from multispectral Earth Observation (EO data. The key is to compute and combine spectral and multi-scale spatial features. By selecting the most adequate features, and combining them with proper logical rules, the approach allows matching multiple urban area models. Experimental results for different locations in Brazil and Kenya using High-Resolution (HR data prove the usefulness and flexibility of the framework.

Morphometric traits in arbor-acres broiler chicken ( Gallus gallus )fed ...

African Journals Online (AJOL)

Fifty sixth day morphometric and body weight measurements were taken on one hundred and forty eight Arbor Acres broiler chickens reared under the Deep Litter system in the guinea savana Zone of Nigeria. This study aimed to determine the effects of substituting treated and untreated Cocoa Bean Shell (CBS) at 50 and ...

Multi-Level Risk Assessment of a Power Plant Gas Turbine Applying ...

African Journals Online (AJOL)

Multi-Level Risk Assessment of a Power Plant Gas Turbine Applying the Criticality Index Model. ... Journal of the Nigerian Association of Mathematical Physics ... This study has carefully shown and expressed a step by step computation of the severity level of the Turbine component parts, using the Criticality Index model.

Heritability of face shape in twins: a preliminary study using 3D stereophotogrammetry and geometric morphometrics

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Seth M. Weinberg

2013-11-01

Full Text Available Introduction: Previous research suggests that aspects of facial surface morphology are heritable.  Traditionally, heritability studies have used a limited set of linear distances to quantify facial morphology and often employ statistical methods poorly designed to deal with biological shape.  In this preliminary report, we use a combination of 3D photogrammetry and landmark-based morphometrics to explore which aspects of face shape show the strongest evidence of heritability in a sample of twins. Methods: 3D surface images were obtained from 21 twin pairs (10 monozygotic, 11 same-sex dizygotic.  Thirteen 3D landmarks were collected from each facial surface and their coordinates subjected to geometric morphometric analysis.  This involved superimposing the individual landmark configurations and then subjecting the resulting shape coordinates to a principal components analysis.  The resulting PC scores were then used to calculate rough narrow-sense heritability estimates. Results: Three principal components displayed evidence of moderate to high heritability and were associated with variation in the breadth of orbital and nasal structures, upper lip height and projection, and the vertical and forward projection of the root of the nose due to variation in the position of nasion. Conclusions: Aspects of facial shape, primarily related to variation in length and breadth of central midfacial structures, were shown to demonstrate evidence of strong heritability. An improved understanding of which facial features are under strong genetic control is an important step in the identification of specific genes that underlie normal facial variation.

BMI and WHR Are Reflected in Female Facial Shape and Texture: A Geometric Morphometric Image Analysis.

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Christine Mayer

Full Text Available Facial markers of body composition are frequently studied in evolutionary psychology and are important in computational and forensic face recognition. We assessed the association of body mass index (BMI and waist-to-hip ratio (WHR with facial shape and texture (color pattern in a sample of young Middle European women by a combination of geometric morphometrics and image analysis. Faces of women with high BMI had a wider and rounder facial outline relative to the size of the eyes and lips, and relatively lower eyebrows. Furthermore, women with high BMI had a brighter and more reddish skin color than women with lower BMI. The same facial features were associated with WHR, even though BMI and WHR were only moderately correlated. Yet BMI was better predictable than WHR from facial attributes. After leave-one-out cross-validation, we were able to predict 25% of variation in BMI and 10% of variation in WHR by facial shape. Facial texture predicted only about 3-10% of variation in BMI and WHR. This indicates that facial shape primarily reflects total fat proportion, rather than the distribution of fat within the body. The association of reddish facial texture in high-BMI women may be mediated by increased blood pressure and superficial blood flow as well as diet. Our study elucidates how geometric morphometric image analysis serves to quantify the effect of biological factors such as BMI and WHR to facial shape and color, which in turn contributes to social perception.

A novel method for a multi-level hierarchical composite with brick-and-mortar structure.

Science.gov (United States)

Brandt, Kristina; Wolff, Michael F H; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A

2013-01-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.

A novel method for a multi-level hierarchical composite with brick-and-mortar structure

Science.gov (United States)

Brandt, Kristina; Wolff, Michael F. H.; Salikov, Vitalij; Heinrich, Stefan; Schneider, Gerold A.

2013-07-01

The fascination for hierarchically structured hard tissues such as enamel or nacre arises from their unique structure-properties-relationship. During the last decades this numerously motivated the synthesis of composites, mimicking the brick-and-mortar structure of nacre. However, there is still a lack in synthetic engineering materials displaying a true hierarchical structure. Here, we present a novel multi-step processing route for anisotropic 2-level hierarchical composites by combining different coating techniques on different length scales. It comprises polymer-encapsulated ceramic particles as building blocks for the first level, followed by spouted bed spray granulation for a second level, and finally directional hot pressing to anisotropically consolidate the composite. The microstructure achieved reveals a brick-and-mortar hierarchical structure with distinct, however not yet optimized mechanical properties on each level. It opens up a completely new processing route for the synthesis of multi-level hierarchically structured composites, giving prospects to multi-functional structure-properties relationships.

Linear versus geometric morphometric approaches for the analysis of head shape dimorphism in lizards.

Science.gov (United States)

Fabre, Anne-Claire; Cornette, Raphäel; Huyghe, Katleen; Andrade, Denis V; Herrel, Anthony

2014-09-01

Differences between the sexes may arise because of differences in reproductive strategy, with females investing more in traits related to reproductive output and males investing more in traits related to resource holding capacity and territory defence. Sexual dimorphism is widespread in lizards and in many species males and females also differ in head shape. Males typically have bigger heads than females resulting in intersexual differences in bite force. Whereas most studies documenting differences in head dimensions between sexes use linear dimensions, the use of geometric morphometrics has been advocated as more appropriate to characterize such differences. This method may allow the characterization of local shape differences that may have functional consequences, and provides unbiased indicators of shape. Here, we explore whether the two approaches provide similar results in an analyses of head shape in Tupinambis merianae. The Argentine black and white tegu differs dramatically in body size, head size, and bite force between the sexes. However, whether the intersexual differences in bite force are simply the result of differences in head size or whether more subtle modifications (e.g., in muscle insertion areas) are involved remains currently unknown. Based on the crania and mandibles of 19 lizards with known bite force, we show intersexual differences in the shape of the cranium and mandible using both linear and geometric morphometric approaches. Although both types of analyses showed generally similar results for the mandible, this was not the case for the cranium. Geometric morphometric approaches provided better insights into the underlying functional relationships between the cranium and the jaw musculature, as illustrated by shape differences in muscle insertion areas not detected using linear morphometric data. © 2014 Wiley Periodicals, Inc.

Effects of Temperature, Photoperiod, and Rainfall on Morphometric Variation of Diaphorina citri (Hemiptera: Liviidae).

Science.gov (United States)

Paris, Thomson M; Allan, Sandra A; Hall, David G; Hentz, Matthew G; Croxton, Scott D; Ainpudi, Niharika; Stansly, Philip A

2017-02-01

Phenotypic plasticity provides a mechanism by which an organism can adapt to new or changing environments. Earlier studies have demonstrated the variability of Diaphorina citri Kuwayama (Asian citrus psyllid) population dynamics, but no analysis of morphological changes induced by seasonal or artificial laboratory-induced conditions has yet been documented. Such morphometric variation has been found to correspond in dispersal capabilities in several insect taxa. In this study, the effects of temperature and photoperiod on morphometric variation of D. citri were examined through laboratory rearing of psyllids under controlled temperatures (20 °C, 28 °C, and 30 °C) and under a short photoperiod of 10.5:13.5 (L:D) h and a long photoperiod of 16:8 (L:D) h. Diaphorina citri were field-collected monthly from three citrus groves in Fort Pierce, Gainesville, and Immokalee, FL, to evaluate potential field-associated environmental effects. Both traditional and geometric morphometric data were used to analyze the correlation between environmental and morphometric variation. A strong correlation was found between temperature and shape change, with larger and broader wings at colder temperatures in the laboratory. Short day length resulted in shorter and narrower wings as well. From the field, temperature, rainfall, and photoperiod were moderately associated with shape parameters. Adult D. citri with blue/green abdomens collected in the laboratory and field studies were larger in size and shape than those with brown/gray abdomens. Published by Oxford University Press on behalf of Entomological Society of America 2016. This work is written by US Government employees and is in the public domain in the US.

The impact of image reconstruction settings on 18F-FDG PET radiomic features. Multi-scanner phantom and patient studies

International Nuclear Information System (INIS)

Shiri, Isaac; Abdollahi, Hamid; Rahmim, Arman; Ghaffarian, Pardis; Geramifar, Parham; Bitarafan-Rajabi, Ahmad

2017-01-01

The purpose of this study was to investigate the robustness of different PET/CT image radiomic features over a wide range of different reconstruction settings. Phantom and patient studies were conducted, including two PET/CT scanners. Different reconstruction algorithms and parameters including number of sub-iterations, number of subsets, full width at half maximum (FWHM) of Gaussian filter, scan time per bed position and matrix size were studied. Lesions were delineated and one hundred radiomic features were extracted. All radiomics features were categorized based on coefficient of variation (COV). Forty seven percent features showed COV ≤ 5% and 10% of which showed COV > 20%. All geometry based, 44% and 41% of intensity based and texture based features were found as robust respectively. In regard to matrix size, 56% and 6% of all features were found non-robust (COV > 20%) and robust (COV ≤ 5%) respectively. Variability and robustness of PET/CT image radiomics in advanced reconstruction settings is feature-dependent, and different settings have different effects on different features. Radiomic features with low COV can be considered as good candidates for reproducible tumour quantification in multi-center studies. (orig.)

The impact of image reconstruction settings on 18F-FDG PET radiomic features. Multi-scanner phantom and patient studies

Energy Technology Data Exchange (ETDEWEB)

Shiri, Isaac; Abdollahi, Hamid [Iran University of Medical Sciences, Department of Medical Physics, School of Medicine, Tehran (Iran, Islamic Republic of); Rahmim, Arman [Johns Hopkins University, Department of Radiology, Baltimore, MD (United States); Johns Hopkins University, Department of Electrical and Computer Engineering, Baltimore, MD (United States); Ghaffarian, Pardis [Shahid Beheshti University of Medical Sciences, Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Tehran (Iran, Islamic Republic of); Shahid Beheshti University of Medical Sciences, PET/CT and Cyclotron Center, Masih Daneshvari Hospital, Tehran (Iran, Islamic Republic of); Geramifar, Parham [Tehran University of Medical Sciences, Research Center for Nuclear Medicine, Shariati Hospital, Tehran (Iran, Islamic Republic of); Bitarafan-Rajabi, Ahmad [Iran University of Medical Sciences, Department of Medical Physics, School of Medicine, Tehran (Iran, Islamic Republic of); Iran University of Medical Sciences, Department of Nuclear Medicine, Rajaei Cardiovascular, Medical and Research Center, Tehran (Iran, Islamic Republic of)

2017-11-15

The purpose of this study was to investigate the robustness of different PET/CT image radiomic features over a wide range of different reconstruction settings. Phantom and patient studies were conducted, including two PET/CT scanners. Different reconstruction algorithms and parameters including number of sub-iterations, number of subsets, full width at half maximum (FWHM) of Gaussian filter, scan time per bed position and matrix size were studied. Lesions were delineated and one hundred radiomic features were extracted. All radiomics features were categorized based on coefficient of variation (COV). Forty seven percent features showed COV ≤ 5% and 10% of which showed COV > 20%. All geometry based, 44% and 41% of intensity based and texture based features were found as robust respectively. In regard to matrix size, 56% and 6% of all features were found non-robust (COV > 20%) and robust (COV ≤ 5%) respectively. Variability and robustness of PET/CT image radiomics in advanced reconstruction settings is feature-dependent, and different settings have different effects on different features. Radiomic features with low COV can be considered as good candidates for reproducible tumour quantification in multi-center studies. (orig.)

Comparative morphometrics of two populations of Mugil curema (Pisces: Mugilidae on the Atlantic and Mexican Pacific coasts

Directory of Open Access Journals (Sweden)

Ana Laura Ibáñez-Aguirre

2006-03-01

Full Text Available A population of Mugil curema in the Gulf of Mexico was compared with one in the Pacific Ocean using nine morphometric variables. The allometries of each measurement were estimated in relation to total length. Morphometric variations were analyzed using the normalization of the individuals of each group and two multivariate methods: correspondence analysis, used to explore the information, and discriminant analysis. Results indicated that the diameter of the eye differentiated the populations of both coasts, the Atlantic population showed a larger eye diameter. However, other than this and the body width (which can be strongly influenced by sexual maturation there was no difference between the shapes of both populations. We discuss the larger morphometric variability of the Atlantic population which may be due to the presence of more than one population unlike the Pacific population.

The Inappropriate Symmetries of Multivariate Statistical Analysis in Geometric Morphometrics.

Science.gov (United States)

Bookstein, Fred L

In today's geometric morphometrics the commonest multivariate statistical procedures, such as principal component analysis or regressions of Procrustes shape coordinates on Centroid Size, embody a tacit roster of symmetries -axioms concerning the homogeneity of the multiple spatial domains or descriptor vectors involved-that do not correspond to actual biological fact. These techniques are hence inappropriate for any application regarding which we have a-priori biological knowledge to the contrary (e.g., genetic/morphogenetic processes common to multiple landmarks, the range of normal in anatomy atlases, the consequences of growth or function for form). But nearly every morphometric investigation is motivated by prior insights of this sort. We therefore need new tools that explicitly incorporate these elements of knowledge, should they be quantitative, to break the symmetries of the classic morphometric approaches. Some of these are already available in our literature but deserve to be known more widely: deflated (spatially adaptive) reference distributions of Procrustes coordinates, Sewall Wright's century-old variant of factor analysis, the geometric algebra of importing explicit biomechanical formulas into Procrustes space. Other methods, not yet fully formulated, might involve parameterized models for strain in idealized forms under load, principled approaches to the separation of functional from Brownian aspects of shape variation over time, and, in general, a better understanding of how the formalism of landmarks interacts with the many other approaches to quantification of anatomy. To more powerfully organize inferences from the high-dimensional measurements that characterize so much of today's organismal biology, tomorrow's toolkit must rely neither on principal component analysis nor on the Procrustes distance formula, but instead on sound prior biological knowledge as expressed in formulas whose coefficients are not all the same. I describe the problems

Visual perception as retrospective Bayesian decoding from high- to low-level features.

Science.gov (United States)

Ding, Stephanie; Cueva, Christopher J; Tsodyks, Misha; Qian, Ning

2017-10-24

When a stimulus is presented, its encoding is known to progress from low- to high-level features. How these features are decoded to produce perception is less clear, and most models assume that decoding follows the same low- to high-level hierarchy of encoding. There are also theories arguing for global precedence, reversed hierarchy, or bidirectional processing, but they are descriptive without quantitative comparison with human perception. Moreover, observers often inspect different parts of a scene sequentially to form overall perception, suggesting that perceptual decoding requires working memory, yet few models consider how working-memory properties may affect decoding hierarchy. We probed decoding hierarchy by comparing absolute judgments of single orientations and relative/ordinal judgments between two sequentially presented orientations. We found that lower-level, absolute judgments failed to account for higher-level, relative/ordinal judgments. However, when ordinal judgment was used to retrospectively decode memory representations of absolute orientations, striking aspects of absolute judgments, including the correlation and forward/backward aftereffects between two reported orientations in a trial, were explained. We propose that the brain prioritizes decoding of higher-level features because they are more behaviorally relevant, and more invariant and categorical, and thus easier to specify and maintain in noisy working memory, and that more reliable higher-level decoding constrains less reliable lower-level decoding. Published under the PNAS license.

Empirically Examining the Performance of Approaches to Multi-Level Matching to Study the Effect of School-Level Interventions

Science.gov (United States)

Hallberg, Kelly; Cook, Thomas D.; Figlio, David

2013-01-01

The goal of this paper is to provide guidance for applied education researchers in using multi-level data to study the effects of interventions implemented at the school level. Two primary approaches are currently employed in observational studies of the effect of school-level interventions. One approach employs intact school matching: matching…

Gross and morphometric anatomical changes of the thyroid gland in ...

African Journals Online (AJOL)

Gross and morphometric anatomical changes of the thyroid gland in the West African Dwarf Goat ( Capra hircus ) during the foetal and post-natal periods of development. ... The right lobe was more cranially located on the larynx and trachea than the left lobe in all age groups. Thyroid isthmus was absent in few foetal thyroid ...

Visual Localization across Seasons Using Sequence Matching Based on Multi-Feature Combination

Directory of Open Access Journals (Sweden)

Yongliang Qiao

2017-10-01

Full Text Available Visual localization is widely used in autonomous navigation system and Advanced Driver Assistance Systems (ADAS. However, visual-based localization in seasonal changing situations is one of the most challenging topics in computer vision and the intelligent vehicle community. The difficulty of this task is related to the strong appearance changes that occur in scenes due to weather or season changes. In this paper, a place recognition based visual localization method is proposed, which realizes the localization by identifying previously visited places using the sequence matching method. It operates by matching query image sequences to an image database acquired previously (video acquired during traveling period. In this method, in order to improve matching accuracy, multi-feature is constructed by combining a global GIST descriptor and local binary feature CSLBP (Center-symmetric local binary patterns to represent image sequence. Then, similarity measurement according to Chi-square distance is used for effective sequences matching. For experimental evaluation, the relationship between image sequence length and sequences matching performance is studied. To show its effectiveness, the proposed method is tested and evaluated in four seasons outdoor environments. The results have shown improved precision–recall performance against the state-of-the-art SeqSLAM algorithm.

Homo floresiensis contextualized: a geometric morphometric comparative analysis of fossil and pathological human samples.

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Karen L Baab

Full Text Available The origin of hominins found on the remote Indonesian island of Flores remains highly contentious. These specimens may represent a new hominin species, Homo floresiensis, descended from a local population of Homo erectus or from an earlier (pre-H. erectus migration of a small-bodied and small-brained hominin out of Africa. Alternatively, some workers suggest that some or all of the specimens recovered from Liang Bua are pathological members of a small-bodied modern human population. Pathological conditions proposed to explain their documented anatomical features include microcephaly, myxoedematous endemic hypothyroidism ("cretinism" and Laron syndrome (primary growth hormone insensitivity. This study evaluates evolutionary and pathological hypotheses through comparative analysis of cranial morphology. Geometric morphometric analyses of landmark data show that the sole Flores cranium (LB1 is clearly distinct from healthy modern humans and from those exhibiting hypothyroidism and Laron syndrome. Modern human microcephalic specimens converge, to some extent, on crania of extinct species of Homo. However in the features that distinguish these two groups, LB1 consistently groups with fossil hominins and is most similar to H. erectus. Our study provides further support for recognizing the Flores hominins as a distinct species, H. floresiensis, whose affinities lie with archaic Homo.

Homo floresiensis Contextualized: A Geometric Morphometric Comparative Analysis of Fossil and Pathological Human Samples

Science.gov (United States)

Baab, Karen L.; McNulty, Kieran P.; Harvati, Katerina

2013-01-01

The origin of hominins found on the remote Indonesian island of Flores remains highly contentious. These specimens may represent a new hominin species, Homo floresiensis, descended from a local population of Homo erectus or from an earlier (pre-H. erectus) migration of a small-bodied and small-brained hominin out of Africa. Alternatively, some workers suggest that some or all of the specimens recovered from Liang Bua are pathological members of a small-bodied modern human population. Pathological conditions proposed to explain their documented anatomical features include microcephaly, myxoedematous endemic hypothyroidism (“cretinism”) and Laron syndrome (primary growth hormone insensitivity). This study evaluates evolutionary and pathological hypotheses through comparative analysis of cranial morphology. Geometric morphometric analyses of landmark data show that the sole Flores cranium (LB1) is clearly distinct from healthy modern humans and from those exhibiting hypothyroidism and Laron syndrome. Modern human microcephalic specimens converge, to some extent, on crania of extinct species of Homo. However in the features that distinguish these two groups, LB1 consistently groups with fossil hominins and is most similar to H. erectus. Our study provides further support for recognizing the Flores hominins as a distinct species, H. floresiensis, whose affinities lie with archaic Homo. PMID:23874886

Performance Evaluation of Fusing Protected Fingerprint Minutiae Templates on the Decision Level

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Raymond N. J. Veldhuis

2012-04-01

Full Text Available In a biometric authentication system using protected templates, a pseudonymous identifier is the part of a protected template that can be directly compared. Each compared pair of pseudonymous identifiers results in a decision testing whether both identifiers are derived from the same biometric characteristic. Compared to an unprotected system, most existing biometric template protection methods cause to a certain extent degradation in biometric performance. Fusion is therefore a promising way to enhance the biometric performance in template-protected biometric systems. Compared to feature level fusion and score level fusion, decision level fusion has not only the least fusion complexity, but also the maximum interoperability across different biometric features, template protection and recognition algorithms, templates formats, and comparison score rules. However, performance improvement via decision level fusion is not obvious. It is influenced by both the dependency and the performance gap among the conducted tests for fusion. We investigate in this paper several fusion scenarios (multi-sample, multi-instance, multi-sensor, multi-algorithm, and their combinations on the binary decision level, and evaluate their biometric performance and fusion efficiency on a multi-sensor fingerprint database with 71,994 samples.

Performance Evaluation of Fusing Protected Fingerprint Minutiae Templates on the Decision Level

Science.gov (United States)

Yang, Bian; Busch, Christoph; de Groot, Koen; Xu, Haiyun; Veldhuis, Raymond N. J.

2012-01-01

In a biometric authentication system using protected templates, a pseudonymous identifier is the part of a protected template that can be directly compared. Each compared pair of pseudonymous identifiers results in a decision testing whether both identifiers are derived from the same biometric characteristic. Compared to an unprotected system, most existing biometric template protection methods cause to a certain extent degradation in biometric performance. Fusion is therefore a promising way to enhance the biometric performance in template-protected biometric systems. Compared to feature level fusion and score level fusion, decision level fusion has not only the least fusion complexity, but also the maximum interoperability across different biometric features, template protection and recognition algorithms, templates formats, and comparison score rules. However, performance improvement via decision level fusion is not obvious. It is influenced by both the dependency and the performance gap among the conducted tests for fusion. We investigate in this paper several fusion scenarios (multi-sample, multi-instance, multi-sensor, multi-algorithm, and their combinations) on the binary decision level, and evaluate their biometric performance and fusion efficiency on a multi-sensor fingerprint database with 71,994 samples. PMID:22778583

Microcontroller based multi-channel ultrasonic level monitoring system

International Nuclear Information System (INIS)

Ambastha, K.P.; Chaudhari, Y.V.; Singh, Inder Jeet; Chadda, V.K.

2004-01-01

Microcontroller based Multi-channel Ultrasonic Level Monitoring System developed by Computer Division is based on echo ranging techniques to monitor level. The transmitter directs an ultrasonic burst towards the liquid, which gets reflected from the top of the liquid surface. The time taken for ultrasound to travel from the transmitter to the top of liquid surface is measured and used to calculate the liquid level. The system provides for temperature compensation for accurate measurement as the ultrasound velocity depends on the ambient temperature. It can measure liquid level up to 5 meters. A single monitor can be used to measure level in 6 tanks. PC connectivity has been provided via RS 232 and RS 485 for remote operation and data logging of level. A GUI program developed using LABVIEW package displays level on PC monitor. The program provides for pictorial as well as numerical display for level and temperature in the front panel on the PC monitor. A user can monitor level for any or all tanks from the PC. One unit is installed at CIRUS for measuring level in Acid/ Alkali tanks and one is installed at APSARA for measuring water level in the reactor pool. (author)

Influence of High Level Features of HVS on Performance of FSIM

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P. Dostal

2013-12-01

Full Text Available In this paper the influence of information about high level features of Human Visual System (HVS on objective quality assessment is studied. This was done by extending the existing full-reference objective image quality metric – FSIM – where the different importance of certain areas of image is considered using Phase Congruency (PC algorithm. Here, the estimation of Region of Interest (ROI based on this algorithm is complemented by Fixation Density Maps (FDM containing the information about high level features of HVS. Use of another low level features based algorithm (Phase Spectrum of Fourier Transform was also considered and compared to the PC algorithm. The performance was evaluated qualitatively on images reconstructed according to ROI and quantitatively on images from LIVE database. The correlation between subjective and objective tests was calculated using Pearson’s Correlation Coefficient and Spearman’s Rank Order Coefficient. The statistical significance of the difference between correlation coefficients was assessed by Fisher r-to-z transformation. The performance of the metric was also compared to other state-of-the-art image quality metrics (SSIM, MS-SSIM, and FSIM.

Elastogram quality assessment score in vibration-controlled transient elastography: Diagnostic performance compared to digital morphometric analysis of liver biopsy in chronic hepatitis C.

Science.gov (United States)

Mendes, L C; Ferreira, P A; Miotto, N; Zanaga, L; Gonçales, E S L; Pedro, M N; Lazarini, M S; Júnior, F L G; Stucchi, R S B; Vigani, A G

2018-04-01

Vibration-controlled transient elastography (VCTE) is widely used for noninvasive fibrosis staging in chronic hepatitis C. However, internal validation is based solely on variability and success rate and lacks reproducible quality indicators. We analysed the graphic representation of shear wave propagation in comparison with morphometric results of liver biopsy, eliminating observer variability bias. Individual elastograms were classified according to two morphologic criteria: extension of wave propagation (length of the graphic representation) and shear wave dispersal (level of parallelism displayed in the elastogram). Then, a score based on these criteria stratified the elastogram in classes I through III (highest to lowest technical quality). Liver stiffness results of each measurement were compared with collagen contents in liver biopsy by morphometric analysis. A total of 3243 elastograms were studied (316 patients). Digital morphometry in liver biopsy showed significant fibrosis in 66% of samples and advanced fibrosis in 31%. Elastogram quality analysis resulted in 1438 class I measurements (44%), 1070 class II (34%) and 735 class III. Area under the receiver operating curve (AUROC) for severe fibrosis according to class (I, II and III) was 0.941, 0.887 and 0.766, respectively. For advanced fibrosis, AUROCs were 0.977, 0.883 and 0.781, respectively. Spearman's correlation testing for all classes and levels of fibrosis demonstrated significant independent association (r 2  = -.95, P digital morphometric imaging analysis. We concluded that VCTE performance is significantly influenced by quality assessment of individual measurements. Considering these criteria in clinical practice may improve accuracy. © 2017 John Wiley & Sons Ltd.

Antecedents of Organisational Creativity: A Multi-Level Approach

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Ritu Gupta

2016-06-01

Full Text Available The purpose of this literature review is to provide a better understanding of the antecedents of organisational creativity with a multi-level approach. Organisational creativity is a sum total of the creativity accounted for by the individual employees of the organisation, the cumulative creativity of a team or group and creativity arising out of different structural components of an organisation. Some of the antecedents identified from the literature include personality, intrinsic motivation, group cohesion, social inhibition, cognitive interference, leader member exchange, organisational culture and climate, amongst others at individual, group and organisational level. Based on the literature review, suggestions for future research and research propositions have been proposed.

Pelvic Floor Morphometric Differences in Elderly Women with or without Urinary Incontinence.

Science.gov (United States)

Fradet, Sarah; Morin, Mélanie; Kruger, Jennifer; Dumoulin, Chantale

2018-01-01

Purpose: Urinary incontinence (UI) affects as many as 50% of women aged 60 years and older, but UI pathophysiology, specifically in elderly women, remains unclear. A better understanding of morphometric differences between continent and urinary incontinent elderly women is needed to improve the effectiveness of conservative treatment approaches. We hypothesized that morphometric differences in the pelvic floor muscles (PFM) among elderly women with and without UI could be observed using three- and four-dimensional (3D/4D) transperineal ultrasound (TPU) imaging. Method: A total of 40 elderly women (20 women with and 20 women without UI), with a mean age of 67.10 (SD 4.94) years, participated in the study. This was a case-control study in which TPU images were taken under three conditions: rest, maximal voluntary contraction (MVC), and Valsalva. Independent t -tests were conducted to compare measurements between the groups. Results: The study revealed statistically significant differences between the groups. At rest, the levator hiatal area and transverse diameter were bigger, and the PFM position was lower in the incontinent group. During MVC, all axial plane parameters were bigger in the incontinent group. In the sagittal plane, PFM position was again lower in the incontinent group. During Valsalva, the anorectal angle was wider in the women with incontinence. Conclusion: PFM morphometric differences were present and were observed using 3D/4D TPU imaging in elderly women with and without UI.

A Dynamic Multi-Level Factor Model with Long-Range Dependence

DEFF Research Database (Denmark)

Ergemen, Yunus Emre; Rodríguez-Caballero, Carlos Vladimir

A dynamic multi-level factor model with stationary or nonstationary global and regional factors is proposed. In the model, persistence in global and regional common factors as well as innovations allows for the study of fractional cointegrating relationships. Estimation of global and regional...

Effect of different levels of sunflower meal and multi-enzyme ...

African Journals Online (AJOL)

Helianthus annus; SFM) levels and a multi-enzyme complex (Natuzyme P50) on performance, biochemical parameters and antioxidant status of laying hens. A total of 288 Hy-Line W-36 laying hens (39-wk-old) were divided into six groups with six ...

Habit, custom, and power: a multi-level theory of population health.

Science.gov (United States)

Zimmerman, Frederick J

2013-03-01

In multi-level theory, individual behavior flows from cognitive habits, either directly through social referencing, rules of thumb, or automatic behaviors; or indirectly through the shaping of rationality itself by framing or heuristics. Although behavior does not arise from individually rational optimization, it generally appears to be rational, because the cognitive habits that guide behavior evolve toward optimality. However, power imbalances shaped by particular social, political, and economic structures can distort this evolution, leading to individual behavior that fails to maximize individual or social well-being. Replacing the dominant rational-choice paradigm with a multi-level theoretical paradigm involving habit, custom, and power will enable public health to engage in rigorous new areas of research. Copyright © 2013 Elsevier Ltd. All rights reserved.

Morphometric growth characteristics and body composition of bullfrog tadpoles in captivity

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Cleber Menegasso Mansano

2014-10-01

Full Text Available Feed management needs to be improved in frog farming to reduce the indirect effects of inadequate feeding and, consequently, to increase growth rates and nutrient deposition, obtaining better quality animals. The objective of this study was to establish morphometric growth curves for bullfrog tadpoles (Lithobates catesbeianus and to determine nutrient deposition in the carcass. A total of 6,480 bullfrogs (Gosner stage 25 received an experimental diet (26.23% digestible protein and 32.68% crude protein and a commercial diet (37.92% crude protein ad libitum. A Gompertz model was used to describe the growth curve. Tadpoles fed the experimental diet presented higher final protein deposition. In addition, the sigmoidal curve was much more homogenous, indicating a more constant daily protein deposition rate. The Gompertz model provided an excellent fit of the data to describe the morphometric growth curve and carcass nutrient deposition of bullfrog tadpoles, showing that animals fed the experimental diet presented a better growth rate and nutrient deposition.

Probabilistic Teleportation of Multi-particle d-Level Quantum State

Institute of Scientific and Technical Information of China (English)

CAO Min; ZHU Shi-Qun

2005-01-01

The general scheme for teleportation of a multi-particle d-level quantum state is presented when m pairs of partially entangled particles are utilized as quantum channels. The probabilistic teleportation can be achieved with a successful probability of d-1∏N=0(CN0)2/dM,which is determined by the smallest coefficients of each entangled channels.

Digestive enzymes and gut morphometric parameters of threespine stickleback (Gasterosteus aculeatus): Influence of body size and temperature.

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Hani, Younes Mohamed Ismail; Marchand, Adrien; Turies, Cyril; Kerambrun, Elodie; Palluel, Olivier; Bado-Nilles, Anne; Beaudouin, Rémy; Porcher, Jean-Marc; Geffard, Alain; Dedourge-Geffard, Odile

2018-01-01

Determining digestive enzyme activity is of potential interest to obtain and understand valuable information about fish digestive physiology, since digestion is an elementary process of fish metabolism. We described for the first time (i) three digestive enzymes: amylase, trypsin and intestinal alkaline phosphatase (IAP), and (ii) three gut morphometric parameters: relative gut length (RGL), relative gut mass (RGM) and Zihler's index (ZI) in threespine stickleback (Gasterosteus aculeatus), and we studied the effect of temperature and body size on these parameters. When mimicking seasonal variation in temperature, body size had no effect on digestive enzyme activity. The highest levels of amylase and trypsin activity were observed at 18°C, while the highest IAP activity was recorded at 20°C. When sticklebacks were exposed to three constant temperatures (16, 18 and 21°C), a temporal effect correlated to fish growth was observed with inverse evolution patterns between amylase activity and the activities of trypsin and IAP. Temperature (in both experiments) had no effect on morphometric parameters. However, a temporal variation was recorded for both RGM (in the second experiment) and ZI (in both experiments), and the later was correlated to fish body mass.

Digestive enzymes and gut morphometric parameters of threespine stickleback (Gasterosteus aculeatus): Influence of body size and temperature

Science.gov (United States)

Marchand, Adrien; Turies, Cyril; Kerambrun, Elodie; Palluel, Olivier; Bado-Nilles, Anne; Beaudouin, Rémy; Porcher, Jean-Marc; Geffard, Alain; Dedourge-Geffard, Odile

2018-01-01

Determining digestive enzyme activity is of potential interest to obtain and understand valuable information about fish digestive physiology, since digestion is an elementary process of fish metabolism. We described for the first time (i) three digestive enzymes: amylase, trypsin and intestinal alkaline phosphatase (IAP), and (ii) three gut morphometric parameters: relative gut length (RGL), relative gut mass (RGM) and Zihler’s index (ZI) in threespine stickleback (Gasterosteus aculeatus), and we studied the effect of temperature and body size on these parameters. When mimicking seasonal variation in temperature, body size had no effect on digestive enzyme activity. The highest levels of amylase and trypsin activity were observed at 18°C, while the highest IAP activity was recorded at 20°C. When sticklebacks were exposed to three constant temperatures (16, 18 and 21°C), a temporal effect correlated to fish growth was observed with inverse evolution patterns between amylase activity and the activities of trypsin and IAP. Temperature (in both experiments) had no effect on morphometric parameters. However, a temporal variation was recorded for both RGM (in the second experiment) and ZI (in both experiments), and the later was correlated to fish body mass. PMID:29614133

Morphological and morphometric evaluation of prepubertal gilt ovaries, uterine tubes and uterus at different oestrus cycle stages

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Guilherme Oberlender

2014-01-01

Full Text Available Studies are performed in developing techniques/procedures that provide greater reproductive performance in farm animals, including pigs. In this sense, the study of gilts reproductive organs at different oestrus cycle stages for assessing the presence of abnormalities and/or other parameters that may affect the future animal fertility is important. In order to evaluate the morphological, morphometric and histomorphometric features of ovaries, uterus and uterine tubes (UTs characteristics of prepubertal gilts at different oestrus cycle stages, reproductive tracts from 48 animals immediately after slaughter were obtained. After, the structures were dissected and removed, and the ovaries were used for classification of oestrus cycle stage of each gilt in follicular phase (FP and luteal phase (FL. Then, morphometric evaluations of ovaries, UTs, uterine horns and uterine body were performed. Besides that, medial segments of UTs and uterus were fixed in Bouin solution, processed and included in paraffin, when histological sections of 5.0 micrometers (µm were obtained and stained with Hematoxylin and Eosin. Histomorphometric analyzes using image capture system and specific software were performed. Afterwards, data were submitted to Student's t test for assessment the statistical differences (P0.05 between morphometric parameters of ovaries, UTs and uterus of gilts in FP and LP. Likewise, in respect to the placement of reproductive structures, both in the oestrus cycle stages, as in the general average, there was no difference (P>0.05. Regarding the histomorphometric variables, gilts classified in FP presented a higher (P<0.05 height of glandular and UT epithelium compared to animals in LP. On the other hand, the diameter of endometrial glands was higher (P<0.05 in gilts at LP compared to FP. Furthermore, gilts in LP presented a higher (P<0.05 proportion of endometrium occupied by glands, whereas animals in FP had a higher (P<0.05 proportion of

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.

Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study.

Science.gov (United States)

Ginsburg, Shoshana B; Algohary, Ahmad; Pahwa, Shivani; Gulani, Vikas; Ponsky, Lee; Aronen, Hannu J; Boström, Peter J; Böhm, Maret; Haynes, Anne-Maree; Brenner, Phillip; Delprado, Warick; Thompson, James; Pulbrock, Marley; Taimen, Pekka; Villani, Robert; Stricker, Phillip; Rastinehad, Ardeshir R; Jambor, Ivan; Madabhushi, Anant

2017-07-01

To evaluate in a multi-institutional study whether radiomic features useful for prostate cancer (PCa) detection from 3 Tesla (T) multi-parametric MRI (mpMRI) in the transition zone (TZ) differ from those in the peripheral zone (PZ). 3T mpMRI, including T2-weighted (T2w), apparent diffusion coefficient (ADC) maps, and dynamic contrast-enhanced MRI (DCE-MRI), were retrospectively obtained from 80 patients at three institutions. This study was approved by the institutional review board of each participating institution. First-order statistical, co-occurrence, and wavelet features were extracted from T2w MRI and ADC maps, and contrast kinetic features were extracted from DCE-MRI. Feature selection was performed to identify 10 features for PCa detection in the TZ and PZ, respectively. Two logistic regression classifiers used these features to detect PCa and were evaluated by area under the receiver-operating characteristic curve (AUC). Classifier performance was compared with a zone-ignorant classifier. Radiomic features that were identified as useful for PCa detection differed between TZ and PZ. When classification was performed on a per-voxel basis, a PZ-specific classifier detected PZ tumors on an independent test set with significantly higher accuracy (AUC = 0.61-0.71) than a zone-ignorant classifier trained to detect cancer throughout the entire prostate (P  0.14) were obtained for all institutions. A zone-aware classifier significantly improves the accuracy of cancer detection in the PZ. 3 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:184-193. © 2016 International Society for Magnetic Resonance in Medicine.