Feature Subset Selection and Instance Filtering for Cross-project Defect Prediction - Classification and Ranking

Directory of Open Access Journals (Sweden)

Faimison Porto

2016-12-01

Full Text Available The defect prediction models can be a good tool on organizing the project's test resources. The models can be constructed with two main goals: 1 to classify the software parts - defective or not; or 2 to rank the most defective parts in a decreasing order. However, not all companies maintain an appropriate set of historical defect data. In this case, a company can build an appropriate dataset from known external projects - called Cross-project Defect Prediction (CPDP. The CPDP models, however, present low prediction performances due to the heterogeneity of data. Recently, Instance Filtering methods were proposed in order to reduce this heterogeneity by selecting the most similar instances from the training dataset. Originally, the similarity is calculated based on all the available dataset features (or independent variables. We propose that using only the most relevant features on the similarity calculation can result in more accurate filtered datasets and better prediction performances. In this study we extend our previous work. We analyse both prediction goals - Classification and Ranking. We present an empirical evaluation of 41 different methods by associating Instance Filtering methods with Feature Selection methods. We used 36 versions of 11 open source projects on experiments. The results show similar evidences for both prediction goals. First, the defect prediction performance of CPDP models can be improved by associating Feature Selection and Instance Filtering. Second, no evaluated method presented general better performances. Indeed, the most appropriate method can vary according to the characteristics of the project being predicted.

MaMiCo: Transient multi-instance molecular-continuum flow simulation on supercomputers

Science.gov (United States)

Neumann, Philipp; Bian, Xin

2017-11-01

We present extensions of the macro-micro-coupling tool MaMiCo, which was designed to couple continuum fluid dynamics solvers with discrete particle dynamics. To enable local extraction of smooth flow field quantities especially on rather short time scales, sampling over an ensemble of molecular dynamics simulations is introduced. We provide details on these extensions including the transient coupling algorithm, open boundary forcing, and multi-instance sampling. Furthermore, we validate the coupling in Couette flow using different particle simulation software packages and particle models, i.e. molecular dynamics and dissipative particle dynamics. Finally, we demonstrate the parallel scalability of the molecular-continuum simulations by using up to 65 536 compute cores of the supercomputer Shaheen II located at KAUST. Program Files doi:http://dx.doi.org/10.17632/w7rgdrhb85.1 Licensing provisions: BSD 3-clause Programming language: C, C++ External routines/libraries: For compiling: SCons, MPI (optional) Subprograms used: ESPResSo, LAMMPS, ls1 mardyn, waLBerla For installation procedures of the MaMiCo interfaces, see the README files in the respective code directories located in coupling/interface/impl. Journal reference of previous version: P. Neumann, H. Flohr, R. Arora, P. Jarmatz, N. Tchipev, H.-J. Bungartz. MaMiCo: Software design for parallel molecular-continuum flow simulations, Computer Physics Communications 200: 324-335, 2016 Does the new version supersede the previous version?: Yes. The functionality of the previous version is completely retained in the new version. Nature of problem: Coupled molecular-continuum simulation for multi-resolution fluid dynamics: parts of the domain are resolved by molecular dynamics or another particle-based solver whereas large parts are covered by a mesh-based CFD solver, e.g. a lattice Boltzmann automaton. Solution method: We couple existing MD and CFD solvers via MaMiCo (macro-micro coupling tool). Data exchange and

Polarimetric Segmentation Using Wishart Test Statistic

DEFF Research Database (Denmark)

Skriver, Henning; Schou, Jesper; Nielsen, Allan Aasbjerg

2002-01-01

A newly developed test statistic for equality of two complex covariance matrices following the complex Wishart distribution and an associated asymptotic probability for the test statistic has been used in a segmentation algorithm. The segmentation algorithm is based on the MUM (merge using moments......) approach, which is a merging algorithm for single channel SAR images. The polarimetric version described in this paper uses the above-mentioned test statistic for merging. The segmentation algorithm has been applied to polarimetric SAR data from the Danish dual-frequency, airborne polarimetric SAR, EMISAR...

Multiple-instance learning as a classifier combining problem

DEFF Research Database (Denmark)

Li, Yan; Tax, David M. J.; Duin, Robert P. W.

2013-01-01

In multiple-instance learning (MIL), an object is represented as a bag consisting of a set of feature vectors called instances. In the training set, the labels of bags are given, while the uncertainty comes from the unknown labels of instances in the bags. In this paper, we study MIL with the ass...

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.

Compliance with Segment Disclosure Initiatives

DEFF Research Database (Denmark)

Arya, Anil; Frimor, Hans; Mittendorf, Brian

2013-01-01

Regulatory oversight of capital markets has intensified in recent years, with a particular emphasis on expanding financial transparency. A notable instance is efforts by the Financial Accounting Standards Board that push firms to identify and report performance of individual business units...... (segments). This paper seeks to address short-run and long-run consequences of stringent enforcement of and uniform compliance with these segment disclosure standards. To do so, we develop a parsimonious model wherein a regulatory agency promulgates disclosure standards and either permits voluntary...... by increasing transparency and leveling the playing field. However, our analysis also demonstrates that in the long run, if firms are unable to use discretion in reporting to maintain their competitive edge, they may seek more destructive alternatives. Accounting for such concerns, in the long run, voluntary...

Enhanced Sensitivity to Subphonemic Segments in Dyslexia: A New Instance of Allophonic Perception

Science.gov (United States)

Serniclaes, Willy; Seck, M’ballo

2018-01-01

Although dyslexia can be individuated in many different ways, it has only three discernable sources: a visual deficit that affects the perception of letters, a phonological deficit that affects the perception of speech sounds, and an audio-visual deficit that disturbs the association of letters with speech sounds. However, the very nature of each of these core deficits remains debatable. The phonological deficit in dyslexia, which is generally attributed to a deficit of phonological awareness, might result from a specific mode of speech perception characterized by the use of allophonic (i.e., subphonemic) units. Here we will summarize the available evidence and present new data in support of the “allophonic theory” of dyslexia. Previous studies have shown that the dyslexia deficit in the categorical perception of phonemic features (e.g., the voicing contrast between /t/ and /d/) is due to the enhanced sensitivity to allophonic features (e.g., the difference between two variants of /d/). Another consequence of allophonic perception is that it should also give rise to an enhanced sensitivity to allophonic segments, such as those that take place within a consonant cluster. This latter prediction is validated by the data presented in this paper. PMID:29587419

Experimental Matching of Instances to Heuristics for Constraint Satisfaction Problems.

Science.gov (United States)

Moreno-Scott, Jorge Humberto; Ortiz-Bayliss, José Carlos; Terashima-Marín, Hugo; Conant-Pablos, Santiago Enrique

2016-01-01

Constraint satisfaction problems are of special interest for the artificial intelligence and operations research community due to their many applications. Although heuristics involved in solving these problems have largely been studied in the past, little is known about the relation between instances and the respective performance of the heuristics used to solve them. This paper focuses on both the exploration of the instance space to identify relations between instances and good performing heuristics and how to use such relations to improve the search. Firstly, the document describes a methodology to explore the instance space of constraint satisfaction problems and evaluate the corresponding performance of six variable ordering heuristics for such instances in order to find regions on the instance space where some heuristics outperform the others. Analyzing such regions favors the understanding of how these heuristics work and contribute to their improvement. Secondly, we use the information gathered from the first stage to predict the most suitable heuristic to use according to the features of the instance currently being solved. This approach proved to be competitive when compared against the heuristics applied in isolation on both randomly generated and structured instances of constraint satisfaction problems.

Parallel multiple instance learning for extremely large histopathology image analysis.

Science.gov (United States)

Xu, Yan; Li, Yeshu; Shen, Zhengyang; Wu, Ziwei; Gao, Teng; Fan, Yubo; Lai, Maode; Chang, Eric I-Chao

2017-08-03

Histopathology images are critical for medical diagnosis, e.g., cancer and its treatment. A standard histopathology slice can be easily scanned at a high resolution of, say, 200,000×200,000 pixels. These high resolution images can make most existing imaging processing tools infeasible or less effective when operated on a single machine with limited memory, disk space and computing power. In this paper, we propose an algorithm tackling this new emerging "big data" problem utilizing parallel computing on High-Performance-Computing (HPC) clusters. Experimental results on a large-scale data set (1318 images at a scale of 10 billion pixels each) demonstrate the efficiency and effectiveness of the proposed algorithm for low-latency real-time applications. The framework proposed an effective and efficient system for extremely large histopathology image analysis. It is based on the multiple instance learning formulation for weakly-supervised learning for image classification, segmentation and clustering. When a max-margin concept is adopted for different clusters, we obtain further improvement in clustering performance.

Multi scales based sparse matrix spectral clustering image segmentation

Science.gov (United States)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

Constrained Deep Weak Supervision for Histopathology Image Segmentation.

Science.gov (United States)

Jia, Zhipeng; Huang, Xingyi; Chang, Eric I-Chao; Xu, Yan

2017-11-01

In this paper, we develop a new weakly supervised learning algorithm to learn to segment cancerous regions in histopathology images. This paper is under a multiple instance learning (MIL) framework with a new formulation, deep weak supervision (DWS); we also propose an effective way to introduce constraints to our neural networks to assist the learning process. The contributions of our algorithm are threefold: 1) we build an end-to-end learning system that segments cancerous regions with fully convolutional networks (FCNs) in which image-to-image weakly-supervised learning is performed; 2) we develop a DWS formulation to exploit multi-scale learning under weak supervision within FCNs; and 3) constraints about positive instances are introduced in our approach to effectively explore additional weakly supervised information that is easy to obtain and enjoy a significant boost to the learning process. The proposed algorithm, abbreviated as DWS-MIL, is easy to implement and can be trained efficiently. Our system demonstrates the state-of-the-art results on large-scale histopathology image data sets and can be applied to various applications in medical imaging beyond histopathology images, such as MRI, CT, and ultrasound images.

Reproducibility of myelin content-based human habenula segmentation at 3 Tesla.

Science.gov (United States)

Kim, Joo-Won; Naidich, Thomas P; Joseph, Joshmi; Nair, Divya; Glasser, Matthew F; O'halloran, Rafael; Doucet, Gaelle E; Lee, Won Hee; Krinsky, Hannah; Paulino, Alejandro; Glahn, David C; Anticevic, Alan; Frangou, Sophia; Xu, Junqian

2018-03-26

In vivo morphological study of the human habenula, a pair of small epithalamic nuclei adjacent to the dorsomedial thalamus, has recently gained significant interest for its role in reward and aversion processing. However, segmenting the habenula from in vivo magnetic resonance imaging (MRI) is challenging due to the habenula's small size and low anatomical contrast. Although manual and semi-automated habenula segmentation methods have been reported, the test-retest reproducibility of the segmented habenula volume and the consistency of the boundaries of habenula segmentation have not been investigated. In this study, we evaluated the intra- and inter-site reproducibility of in vivo human habenula segmentation from 3T MRI (0.7-0.8 mm isotropic resolution) using our previously proposed semi-automated myelin contrast-based method and its fully-automated version, as well as a previously published manual geometry-based method. The habenula segmentation using our semi-automated method showed consistent boundary definition (high Dice coefficient, low mean distance, and moderate Hausdorff distance) and reproducible volume measurement (low coefficient of variation). Furthermore, the habenula boundary in our semi-automated segmentation from 3T MRI agreed well with that in the manual segmentation from 7T MRI (0.5 mm isotropic resolution) of the same subjects. Overall, our proposed semi-automated habenula segmentation showed reliable and reproducible habenula localization, while its fully-automated version offers an efficient way for large sample analysis. © 2018 Wiley Periodicals, Inc.

Deformable segmentation via sparse representation and dictionary learning.

Science.gov (United States)

Zhang, Shaoting; Zhan, Yiqiang; Metaxas, Dimitris N

2012-10-01

"Shape" and "appearance", the two pillars of a deformable model, complement each other in object segmentation. In many medical imaging applications, while the low-level appearance information is weak or mis-leading, shape priors play a more important role to guide a correct segmentation, thanks to the strong shape characteristics of biological structures. Recently a novel shape prior modeling method has been proposed based on sparse learning theory. Instead of learning a generative shape model, shape priors are incorporated on-the-fly through the sparse shape composition (SSC). SSC is robust to non-Gaussian errors and still preserves individual shape characteristics even when such characteristics is not statistically significant. Although it seems straightforward to incorporate SSC into a deformable segmentation framework as shape priors, the large-scale sparse optimization of SSC has low runtime efficiency, which cannot satisfy clinical requirements. In this paper, we design two strategies to decrease the computational complexity of SSC, making a robust, accurate and efficient deformable segmentation system. (1) When the shape repository contains a large number of instances, which is often the case in 2D problems, K-SVD is used to learn a more compact but still informative shape dictionary. (2) If the derived shape instance has a large number of vertices, which often appears in 3D problems, an affinity propagation method is used to partition the surface into small sub-regions, on which the sparse shape composition is performed locally. Both strategies dramatically decrease the scale of the sparse optimization problem and hence speed up the algorithm. Our method is applied on a diverse set of biomedical image analysis problems. Compared to the original SSC, these two newly-proposed modules not only significant reduce the computational complexity, but also improve the overall accuracy. Copyright © 2012 Elsevier B.V. All rights reserved.

Utilising Tree-Based Ensemble Learning for Speaker Segmentation

DEFF Research Database (Denmark)

Abou-Zleikha, Mohamed; Tan, Zheng-Hua; Christensen, Mads Græsbøll

2014-01-01

In audio and speech processing, accurate detection of the changing points between multiple speakers in speech segments is an important stage for several applications such as speaker identification and tracking. Bayesian Information Criteria (BIC)-based approaches are the most traditionally used...... for a certain condition, the model becomes biased to the data used for training limiting the model’s generalisation ability. In this paper, we propose a BIC-based tuning-free approach for speaker segmentation through the use of ensemble-based learning. A forest of segmentation trees is constructed in which each...... tree is trained using a sampled version of the speech segment. During the tree construction process, a set of randomly selected points in the input sequence is examined as potential segmentation points. The point that yields the highest ΔBIC is chosen and the same process is repeated for the resultant...

An instance theory of associative learning.

Science.gov (United States)

Jamieson, Randall K; Crump, Matthew J C; Hannah, Samuel D

2012-03-01

We present and test an instance model of associative learning. The model, Minerva-AL, treats associative learning as cued recall. Memory preserves the events of individual trials in separate traces. A probe presented to memory contacts all traces in parallel and retrieves a weighted sum of the traces, a structure called the echo. Learning of a cue-outcome relationship is measured by the cue's ability to retrieve a target outcome. The theory predicts a number of associative learning phenomena, including acquisition, extinction, reacquisition, conditioned inhibition, external inhibition, latent inhibition, discrimination, generalization, blocking, overshadowing, overexpectation, superconditioning, recovery from blocking, recovery from overshadowing, recovery from overexpectation, backward blocking, backward conditioned inhibition, and second-order retrospective revaluation. We argue that associative learning is consistent with an instance-based approach to learning and memory.

Proportional crosstalk correction for the segmented clover at iThemba LABS

International Nuclear Information System (INIS)

Bucher, T D; Noncolela, S P; Lawrie, E A; Dinoko, T R S; Easton, J L; Erasmus, N; Lawrie, J J; Mthembu, S H; Mtshali, W X; Shirinda, O; Orce, J N

2017-01-01

Reaching new depths in nuclear structure investigations requires new experimental equipment and new techniques of data analysis. The modern γ -ray spectrometers, like AGATA and GRETINA are now built of new-generation segmented germanium detectors. These most advanced detectors are able to reconstruct the trajectory of a γ -ray inside the detector. These are powerful detectors, but they need careful characterization, since their output signals are more complex. For instance for each γ -ray interaction that occurs in a segment of such a detector additional output signals (called proportional crosstalk), falsely appearing as an independent (often negative) energy depositions, are registered on the non-interacting segments. A failure to implement crosstalk correction results in incorrectly measured energies on the segments for two- and higher-fold events. It affects all experiments which rely on the recorded segment energies. Furthermore incorrectly recorded energies on the segments cause a failure to reconstruct the γ -ray trajectories using Compton scattering analysis. The proportional crosstalk for the iThemba LABS segmented clover was measured and a crosstalk correction was successfully implemented. The measured crosstalk-corrected energies show good agreement with the true γ -ray energies independent on the number of hit segments and an improved energy resolution for the segment sum energy was obtained. (paper)

Instance-specific algorithm configuration

CERN Document Server

Malitsky, Yuri

2014-01-01

This book presents a modular and expandable technique in the rapidly emerging research area of automatic configuration and selection of the best algorithm for the instance at hand. The author presents the basic model behind ISAC and then details a number of modifications and practical applications. In particular, he addresses automated feature generation, offline algorithm configuration for portfolio generation, algorithm selection, adaptive solvers, online tuning, and parallelization.    The author's related thesis was honorably mentioned (runner-up) for the ACP Dissertation Award in 2014,

Orthographic Transparency Enhances Morphological Segmentation in Children Reading Hebrew Words

Science.gov (United States)

Haddad, Laurice; Weiss, Yael; Katzir, Tami; Bitan, Tali

2018-01-01

Morphological processing of derived words develops simultaneously with reading acquisition. However, the reader’s engagement in morphological segmentation may depend on the language morphological richness and orthographic transparency, and the readers’ reading skills. The current study tested the common idea that morphological segmentation is enhanced in non-transparent orthographies to compensate for the absence of phonological information. Hebrew’s rich morphology and the dual version of the Hebrew script (with and without diacritic marks) provides an opportunity to study the interaction of orthographic transparency and morphological segmentation on the development of reading skills in a within-language design. Hebrew speaking 2nd (N = 27) and 5th (N = 29) grade children read aloud 96 noun words. Half of the words were simple mono-morphemic words and half were bi-morphemic derivations composed of a productive root and a morphemic pattern. In each list half of the words were presented in the transparent version of the script (with diacritic marks), and half in the non-transparent version (without diacritic marks). Our results show that in both groups, derived bi-morphemic words were identified more accurately than mono-morphemic words, but only for the transparent, pointed, script. For the un-pointed script the reverse was found, namely, that bi-morphemic words were read less accurately than mono-morphemic words, especially in second grade. Second grade children also read mono-morphemic words faster than bi-morphemic words. Finally, correlations with a standardized measure of morphological awareness were found only for second grade children, and only in bi-morphemic words. These results, showing greater morphological effects in second grade compared to fifth grade children suggest that for children raised in a language with a rich morphology, common and easily segmented morphemic units may be more beneficial for younger compared to older readers. Moreover

Orthographic Transparency Enhances Morphological Segmentation in Children Reading Hebrew Words

Directory of Open Access Journals (Sweden)

Laurice Haddad

2018-01-01

Full Text Available Morphological processing of derived words develops simultaneously with reading acquisition. However, the reader’s engagement in morphological segmentation may depend on the language morphological richness and orthographic transparency, and the readers’ reading skills. The current study tested the common idea that morphological segmentation is enhanced in non-transparent orthographies to compensate for the absence of phonological information. Hebrew’s rich morphology and the dual version of the Hebrew script (with and without diacritic marks provides an opportunity to study the interaction of orthographic transparency and morphological segmentation on the development of reading skills in a within-language design. Hebrew speaking 2nd (N = 27 and 5th (N = 29 grade children read aloud 96 noun words. Half of the words were simple mono-morphemic words and half were bi-morphemic derivations composed of a productive root and a morphemic pattern. In each list half of the words were presented in the transparent version of the script (with diacritic marks, and half in the non-transparent version (without diacritic marks. Our results show that in both groups, derived bi-morphemic words were identified more accurately than mono-morphemic words, but only for the transparent, pointed, script. For the un-pointed script the reverse was found, namely, that bi-morphemic words were read less accurately than mono-morphemic words, especially in second grade. Second grade children also read mono-morphemic words faster than bi-morphemic words. Finally, correlations with a standardized measure of morphological awareness were found only for second grade children, and only in bi-morphemic words. These results, showing greater morphological effects in second grade compared to fifth grade children suggest that for children raised in a language with a rich morphology, common and easily segmented morphemic units may be more beneficial for younger compared to older

Resource Planning for Massive Number of Process Instances

Science.gov (United States)

Xu, Jiajie; Liu, Chengfei; Zhao, Xiaohui

Resource allocation has been recognised as an important topic for business process execution. In this paper, we focus on planning resources for a massive number of process instances to meet the process requirements and cater for rational utilisation of resources before execution. After a motivating example, we present a model for planning resources for process instances. Then we design a set of heuristic rules that take both optimised planning at build time and instance dependencies at run time into account. Based on these rules we propose two strategies, one is called holistic and the other is called batched, for resource planning. Both strategies target a lower cost, however, the holistic strategy can achieve an earlier deadline while the batched strategy aims at rational use of resources. We discuss how to find balance between them in the paper with a comprehensive experimental study on these two approaches.

Hepatobiliary scintigraphy in the assessment of long-term complication after biliary-enteric anastomosis: role in the diagnosis of post-operative segmental or total biliary obstruction

Energy Technology Data Exchange (ETDEWEB)

Kim, Jae Seung; Moon, Dae Hyuk; Lee, Sung Gyu; Lee, Yung Joo; Park, Kwang Min; Shin, Jung Woo; Ryu, Jin Sook; Lee, Hee Kyung [Asan Medicial Center, Seoul (Korea, Republic of)

1998-07-01

The purpose of this study was to investigate the accuracy of hepatobiliary scintigraphy (HBS) in the diagnosis of segmental or total biliary obstruction during long-term follow-up period after curative radical surgery with biliary-enteric anastomosis. The study population included 80 patients who underwent biliary-enteric anastomoses for benign (n=33) or malignant (n=47) biliary disease. Fifty-six of these 80 patients also underwent curative hepatic resection. Ninety eight hepatobiliary scintigrams using {sup 99m}Tc-DISIDA were performed at least 1 month after surgery (median 9 month). The scintigraphic criteria of total biliary obstruction we used were intestinal excretion beyond one hour or delayed hepatobiliary washout despite the presence of intestinal excretion. Segmental biliary obstruction was defined as delayed segmental excretion. The accuracy for biliary obstruction was evaluated according to different clinical situations. There were 9 instances with total biliary obstruction and 23 with segmental bile duct obstruction. Diagnosis of biliary obstruction was confirmed by percutaneous transhepatic cholangiography or surgery in 13, and follow-up clinical data for at least 6 months in 19 instances. Among the 32 instances with biliary symptoms and abnormal liver function, HBS allowed correct diagnosis in all 32(9 total, 14 segmental obstruction and 9 non-obstruction). Of the 40 with nonspecific symptom or isolated elevation of serum alkaline phosphatase, HBS diagnosed 8 of the 9 segmental biliary obstruction and 30 of the 31 non-obstruction. There were no biliary obstruction and no false positive result of scintigraphy in 26 instances which had no clinical symptom or signs of biliary obstruction. Diagnostic sensitivity of HBS was 100% (9/9) for total biliary obstruction, and 96%(22/23) for segmental bile obstruction. Specificity was 98%(39/40) in patients who had abnormal symptom or sign. Hepatobiliary scintigraphy is a highly accurate modality in the

Hepatobiliary scintigraphy in the assessment of long-term complication after biliary-enteric anastomosis: role in the diagnosis of post-operative segmental or total biliary obstruction

International Nuclear Information System (INIS)

Kim, Jae Seung; Moon, Dae Hyuk; Lee, Sung Gyu; Lee, Yung Joo; Park, Kwang Min; Shin, Jung Woo; Ryu, Jin Sook; Lee, Hee Kyung

1998-01-01

The purpose of this study was to investigate the accuracy of hepatobiliary scintigraphy (HBS) in the diagnosis of segmental or total biliary obstruction during long-term follow-up period after curative radical surgery with biliary-enteric anastomosis. The study population included 80 patients who underwent biliary-enteric anastomoses for benign (n=33) or malignant (n=47) biliary disease. Fifty-six of these 80 patients also underwent curative hepatic resection. Ninety eight hepatobiliary scintigrams using 99m Tc-DISIDA were performed at least 1 month after surgery (median 9 month). The scintigraphic criteria of total biliary obstruction we used were intestinal excretion beyond one hour or delayed hepatobiliary washout despite the presence of intestinal excretion. Segmental biliary obstruction was defined as delayed segmental excretion. The accuracy for biliary obstruction was evaluated according to different clinical situations. There were 9 instances with total biliary obstruction and 23 with segmental bile duct obstruction. Diagnosis of biliary obstruction was confirmed by percutaneous transhepatic cholangiography or surgery in 13, and follow-up clinical data for at least 6 months in 19 instances. Among the 32 instances with biliary symptoms and abnormal liver function, HBS allowed correct diagnosis in all 32(9 total, 14 segmental obstruction and 9 non-obstruction). Of the 40 with nonspecific symptom or isolated elevation of serum alkaline phosphatase, HBS diagnosed 8 of the 9 segmental biliary obstruction and 30 of the 31 non-obstruction. There were no biliary obstruction and no false positive result of scintigraphy in 26 instances which had no clinical symptom or signs of biliary obstruction. Diagnostic sensitivity of HBS was 100% (9/9) for total biliary obstruction, and 96%(22/23) for segmental bile obstruction. Specificity was 98%(39/40) in patients who had abnormal symptom or sign. Hepatobiliary scintigraphy is a highly accurate modality in the evaluation of

Multidimensional Brain MRI segmentation using graph cuts

International Nuclear Information System (INIS)

Lecoeur, Jeremy

2010-01-01

This thesis deals with the segmentation of multimodal brain MRIs by graph cuts method. First, we propose a method that utilizes three MRI modalities by merging them. The border information given by the spectral gradient is then challenged by a region information, given by the seeds selected by the user, using a graph cut algorithm. Then, we propose three enhancements of this method. The first consists in finding an optimal spectral space because the spectral gradient is based on natural images and then inadequate for multimodal medical images. This results in a learning based segmentation method. We then explore the automation of the graph cut method. Here, the various pieces of information usually given by the user are inferred from a robust expectation-maximization algorithm. We show the performance of these two enhanced versions on multiple sclerosis lesions. Finally, we integrate atlases for the automatic segmentation of deep brain structures. These three new techniques show the adaptability of our method to various problems. Our different segmentation methods are better than most of nowadays techniques, speaking of computation time or segmentation accuracy. (authors)

Japanese migration in contemporary Japan: economic segmentation and interprefectural migration.

Science.gov (United States)

Fukurai, H

1991-01-01

This paper examines the economic segmentation model in explaining 1985-86 Japanese interregional migration. The analysis takes advantage of statistical graphic techniques to illustrate the following substantive issues of interregional migration: (1) to examine whether economic segmentation significantly influences Japanese regional migration and (2) to explain socioeconomic characteristics of prefectures for both in- and out-migration. Analytic techniques include a latent structural equation (LISREL) methodology and statistical residual mapping. The residual dispersion patterns, for instance, suggest the extent to which socioeconomic and geopolitical variables explain migration differences by showing unique clusters of unexplained residuals. The analysis further points out that extraneous factors such as high residential land values, significant commuting populations, and regional-specific cultures and traditions need to be incorporated in the economic segmentation model in order to assess the extent of the model's reliability in explaining the pattern of interprefectural migration.

Learning concept mappings from instance similarity

NARCIS (Netherlands)

Wang, S.; Englebienne, G.; Schlobach, S.

2008-01-01

Finding mappings between compatible ontologies is an important but difficult open problem. Instance-based methods for solving this problem have the advantage of focusing on the most active parts of the ontologies and reflect concept semantics as they are actually being used. However such methods

User-assisted Object Detection by Segment Based Similarity Measures in Mobile Laser Scanner Data

NARCIS (Netherlands)

Oude Elberink, S.J.; Kemboi, B.J.

2014-01-01

This paper describes a method that aims to find all instances of a certain object in Mobile Laser Scanner (MLS) data. In a userassisted approach, a sample segment of an object is selected, and all similar objects are to be found. By selecting samples from multiple classes, a classification can be

Jansen-MIDAS: A multi-level photomicrograph segmentation software based on isotropic undecimated wavelets.

Science.gov (United States)

de Siqueira, Alexandre Fioravante; Cabrera, Flávio Camargo; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Job, Aldo Eloizo

2018-01-01

Image segmentation, the process of separating the elements within a picture, is frequently used for obtaining information from photomicrographs. Segmentation methods should be used with reservations, since incorrect results can mislead when interpreting regions of interest (ROI). This decreases the success rate of extra procedures. Multi-Level Starlet Segmentation (MLSS) and Multi-Level Starlet Optimal Segmentation (MLSOS) were developed to be an alternative for general segmentation tools. These methods gave rise to Jansen-MIDAS, an open-source software. A scientist can use it to obtain several segmentations of hers/his photomicrographs. It is a reliable alternative to process different types of photomicrographs: previous versions of Jansen-MIDAS were used to segment ROI in photomicrographs of two different materials, with an accuracy superior to 89%. © 2017 Wiley Periodicals, Inc.

Domain Adaptation for Machine Translation with Instance Selection

Directory of Open Access Journals (Sweden)

Biçici Ergun

2015-04-01

Full Text Available Domain adaptation for machine translation (MT can be achieved by selecting training instances close to the test set from a larger set of instances. We consider 7 different domain adaptation strategies and answer 7 research questions, which give us a recipe for domain adaptation in MT. We perform English to German statistical MT (SMT experiments in a setting where test and training sentences can come from different corpora and one of our goals is to learn the parameters of the sampling process. Domain adaptation with training instance selection can obtain 22% increase in target 2-gram recall and can gain up to 3:55 BLEU points compared with random selection. Domain adaptation with feature decay algorithm (FDA not only achieves the highest target 2-gram recall and BLEU performance but also perfectly learns the test sample distribution parameter with correlation 0:99. Moses SMT systems built with FDA selected 10K training sentences is able to obtain F1 results as good as the baselines that use up to 2M sentences. Moses SMT systems built with FDA selected 50K training sentences is able to obtain F1 point better results than the baselines.

Horror Image Recognition Based on Context-Aware Multi-Instance Learning.

Science.gov (United States)

Li, Bing; Xiong, Weihua; Wu, Ou; Hu, Weiming; Maybank, Stephen; Yan, Shuicheng

2015-12-01

Horror content sharing on the Web is a growing phenomenon that can interfere with our daily life and affect the mental health of those involved. As an important form of expression, horror images have their own characteristics that can evoke extreme emotions. In this paper, we present a novel context-aware multi-instance learning (CMIL) algorithm for horror image recognition. The CMIL algorithm identifies horror images and picks out the regions that cause the sensation of horror in these horror images. It obtains contextual cues among adjacent regions in an image using a random walk on a contextual graph. Borrowing the strength of the fuzzy support vector machine (FSVM), we define a heuristic optimization procedure based on the FSVM to search for the optimal classifier for the CMIL. To improve the initialization of the CMIL, we propose a novel visual saliency model based on the tensor analysis. The average saliency value of each segmented region is set as its initial fuzzy membership in the CMIL. The advantage of the tensor-based visual saliency model is that it not only adaptively selects features, but also dynamically determines fusion weights for saliency value combination from different feature subspaces. The effectiveness of the proposed CMIL model is demonstrated by its use in horror image recognition on two large-scale image sets collected from the Internet.

Dissimilarity-based multiple instance learning

DEFF Research Database (Denmark)

Sørensen, Lauge; Loog, Marco; Tax, David M. J.

2010-01-01

In this paper, we propose to solve multiple instance learning problems using a dissimilarity representation of the objects. Once the dissimilarity space has been constructed, the problem is turned into a standard supervised learning problem that can be solved with a general purpose supervised cla...... between distributions of within- and between set point distances, thereby taking relations within and between sets into account. Experiments on five publicly available data sets show competitive performance in terms of classification accuracy compared to previously published results....

An Efficient Metric of Automatic Weight Generation for Properties in Instance Matching Technique

OpenAIRE

Seddiqui, Md. Hanif; Nath, Rudra Pratap Deb; Aono, Masaki

2015-01-01

The proliferation of heterogeneous data sources of semantic knowledge base intensifies the need of an automatic instance matching technique. However, the efficiency of instance matching is often influenced by the weight of a property associated to instances. Automatic weight generation is a non-trivial, however an important task in instance matching technique. Therefore, identifying an appropriate metric for generating weight for a property automatically is nevertheless a formidab...

Just how literal is the King James Version?

OpenAIRE

Jan (JH) Kroeze; Manie (CM) van den Heever; Bertus (AJ) van Rooy

2010-01-01

Many scholars have the perception that the King James Version (KJV) is a literal translation. However, it is not so easy to define the concept of "literal translation". The simplest definition may be to regard it as word-for-word translation. However, when one compares the KJV carefully with the original Hebrew Bible, there are numerous instances where lexical items are changed to adapt the idiom to that of the target language. In this article, a measuring instrument will be proposed and u...

Introduction to the enhanced logistics intratheater support tool (ELIST) mission application and its segments : global data segment version 8.1.0.0, database instance segment version 8.1.0.0, ...[elided] and reference data segment version 8.1.0.0 for solaris 7.; TOPICAL

International Nuclear Information System (INIS)

Dritz, K.

2002-01-01

The ELIST mission application simulates and evaluates the feasibility of intratheater transportation logistics primarily for the theater portion of a course of action. It performs a discrete event simulation of a series of movement requirements over a constrained infrastructure network using specified transportation assets. ELIST addresses the question of whether transportation infrastructures and lift allocations are adequate to support the movements of specific force structures and supplies to their destinations on time

Stochastic Learning of Multi-Instance Dictionary for Earth Mover's Distance based Histogram Comparison

OpenAIRE

Fan, Jihong; Liang, Ru-Ze

2016-01-01

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover's distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However, up to now, there is no existing multi-instance dictionary learning methods designed for EMD based histogram comparison. To fill this gap, we develop the first EMD-optimal dictionary learning method using stochastic optimization method. In the stoc...

GPU-based relative fuzzy connectedness image segmentation

International Nuclear Information System (INIS)

Zhuge Ying; Ciesielski, Krzysztof C.; Udupa, Jayaram K.; Miller, Robert W.

2013-01-01

Purpose:Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. Methods: The most common FC segmentations, optimizing an ℓ ∞ -based energy, are known as relative fuzzy connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA’s Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Results: Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8×, 22.9×, 20.9×, and 17.5×, correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. Conclusions: A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology.

GPU-based relative fuzzy connectedness image segmentation

Energy Technology Data Exchange (ETDEWEB)

Zhuge Ying; Ciesielski, Krzysztof C.; Udupa, Jayaram K.; Miller, Robert W. [Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892 (United States); Department of Mathematics, West Virginia University, Morgantown, West Virginia 26506 (United States) and Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Radiation Oncology Branch, National Cancer Institute, National Institutes of Health, Bethesda, Maryland 20892 (United States)

2013-01-15

Purpose:Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. Methods: The most common FC segmentations, optimizing an Script-Small-L {sub {infinity}}-based energy, are known as relative fuzzy connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA's Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Results: Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8 Multiplication-Sign , 22.9 Multiplication-Sign , 20.9 Multiplication-Sign , and 17.5 Multiplication-Sign , correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. Conclusions: A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology.

GPU-based relative fuzzy connectedness image segmentation.

Science.gov (United States)

Zhuge, Ying; Ciesielski, Krzysztof C; Udupa, Jayaram K; Miller, Robert W

2013-01-01

Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. The most common FC segmentations, optimizing an [script-l](∞)-based energy, are known as relative fuzzy connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA's Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8×, 22.9×, 20.9×, and 17.5×, correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology.

GPU-based relative fuzzy connectedness image segmentation

Science.gov (United States)

Zhuge, Ying; Ciesielski, Krzysztof C.; Udupa, Jayaram K.; Miller, Robert W.

2013-01-01

Purpose: Recently, clinical radiological research and practice are becoming increasingly quantitative. Further, images continue to increase in size and volume. For quantitative radiology to become practical, it is crucial that image segmentation algorithms and their implementations are rapid and yield practical run time on very large data sets. The purpose of this paper is to present a parallel version of an algorithm that belongs to the family of fuzzy connectedness (FC) algorithms, to achieve an interactive speed for segmenting large medical image data sets. Methods: The most common FC segmentations, optimizing an ℓ∞-based energy, are known as relative fuzzy connectedness (RFC) and iterative relative fuzzy connectedness (IRFC). Both RFC and IRFC objects (of which IRFC contains RFC) can be found via linear time algorithms, linear with respect to the image size. The new algorithm, P-ORFC (for parallel optimal RFC), which is implemented by using NVIDIA’s Compute Unified Device Architecture (CUDA) platform, considerably improves the computational speed of the above mentioned CPU based IRFC algorithm. Results: Experiments based on four data sets of small, medium, large, and super data size, achieved speedup factors of 32.8×, 22.9×, 20.9×, and 17.5×, correspondingly, on the NVIDIA Tesla C1060 platform. Although the output of P-ORFC need not precisely match that of IRFC output, it is very close to it and, as the authors prove, always lies between the RFC and IRFC objects. Conclusions: A parallel version of a top-of-the-line algorithm in the family of FC has been developed on the NVIDIA GPUs. An interactive speed of segmentation has been achieved, even for the largest medical image data set. Such GPU implementations may play a crucial role in automatic anatomy recognition in clinical radiology. PMID:23298094

Time and activity sequence prediction of business process instances

DEFF Research Database (Denmark)

Polato, Mirko; Sperduti, Alessandro; Burattin, Andrea

2018-01-01

The ability to know in advance the trend of running process instances, with respect to different features, such as the expected completion time, would allow business managers to timely counteract to undesired situations, in order to prevent losses. Therefore, the ability to accurately predict...... future features of running business process instances would be a very helpful aid when managing processes, especially under service level agreement constraints. However, making such accurate forecasts is not easy: many factors may influence the predicted features. Many approaches have been proposed...

Scheduling jobs in the cloud using on-demand and reserved instances

NARCIS (Netherlands)

Shen, S.; Deng, K.; Iosup, A.; Epema, D.H.J.; Wolf, F.; Mohr, B.; Mey, an D.

2013-01-01

Deploying applications in leased cloud infrastructure is increasingly considered by a variety of business and service integrators. However, the challenge of selecting the leasing strategy — larger or faster instances? on-demand or reserved instances? etc.— and to configure the leasing strategy with

Efficient Algorithms for Segmentation of Item-Set Time Series

Science.gov (United States)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

Multimodality and children's participation in classrooms: Instances of ...

African Journals Online (AJOL)

Multimodality and children's participation in classrooms: Instances of research. ... deficit models of children, drawing on their everyday experiences and their existing ... It outlines the theoretical framework supporting the pedagogical approach, ...

Automatic detection and recognition of multiple macular lesions in retinal optical coherence tomography images with multi-instance multilabel learning

Science.gov (United States)

Fang, Leyuan; Yang, Liumao; Li, Shutao; Rabbani, Hossein; Liu, Zhimin; Peng, Qinghua; Chen, Xiangdong

2017-06-01

Detection and recognition of macular lesions in optical coherence tomography (OCT) are very important for retinal diseases diagnosis and treatment. As one kind of retinal disease (e.g., diabetic retinopathy) may contain multiple lesions (e.g., edema, exudates, and microaneurysms) and eye patients may suffer from multiple retinal diseases, multiple lesions often coexist within one retinal image. Therefore, one single-lesion-based detector may not support the diagnosis of clinical eye diseases. To address this issue, we propose a multi-instance multilabel-based lesions recognition (MIML-LR) method for the simultaneous detection and recognition of multiple lesions. The proposed MIML-LR method consists of the following steps: (1) segment the regions of interest (ROIs) for different lesions, (2) compute descriptive instances (features) for each lesion region, (3) construct multilabel detectors, and (4) recognize each ROI with the detectors. The proposed MIML-LR method was tested on 823 clinically labeled OCT images with normal macular and macular with three common lesions: epiretinal membrane, edema, and drusen. For each input OCT image, our MIML-LR method can automatically identify the number of lesions and assign the class labels, achieving the average accuracy of 88.72% for the cases with multiple lesions, which better assists macular disease diagnosis and treatment.

Semantic Segmentation of Real-time Sensor Data Stream for Complex Activity Recognition

OpenAIRE

Triboan, Darpan; Chen, Liming; Chen, Feng; Wang, Zumin

2016-01-01

Department of Information Engineering, Dalian University, China The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. Data segmentation plays a critical role in performing human activity recognition (HAR) in the ambient assistant living (AAL) systems. It is particularly important for complex activity recognition when the events occur in short bursts with attributes of multiple sub-tasks. Althou...

Improving Multi-Instance Multi-Label Learning by Extreme Learning Machine

Directory of Open Access Journals (Sweden)

Ying Yin

2016-05-01

Full Text Available Multi-instance multi-label learning is a learning framework, where every object is represented by a bag of instances and associated with multiple labels simultaneously. The existing degeneration strategy-based methods often suffer from some common drawbacks: (1 the user-specific parameter for the number of clusters may incur the effective problem; (2 SVM may bring a high computational cost when utilized as the classifier builder. In this paper, we propose an algorithm, namely multi-instance multi-label (MIML-extreme learning machine (ELM, to address the problems. To our best knowledge, we are the first to utilize ELM in the MIML problem and to conduct the comparison of ELM and SVM on MIML. Extensive experiments have been conducted on real datasets and synthetic datasets. The results show that MIMLELM tends to achieve better generalization performance at a higher learning speed.

A Streamlined Artificial Variable Free Version of Simplex Method

OpenAIRE

Inayatullah, Syed; Touheed, Nasir; Imtiaz, Muhammad

2015-01-01

This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new ...

Stochastic learning of multi-instance dictionary for earth mover’s distance-based histogram comparison

KAUST Repository

Fan, Jihong; Liang, Ru-Ze

2016-01-01

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover’s distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However

Simulating the 2012 High Plains drought using three single column versions (SCM) of BUGS5

Science.gov (United States)

Medina, I. D.; Denning, S.

2013-12-01

The impact of changes in the frequency and severity of drought on fresh water sustainability is a great concern for many regions of the world. One such location is the High Plains, where the local economy is primarily driven by fresh water withdrawals from the Ogallala Aquifer, which accounts for approximately 30% of total irrigation withdrawals from all U.S. aquifers combined. Modeling studies that focus on the feedback mechanisms that control the climate and eco-hydrology during times of drought are limited, and have used conventional General Circulation Models (GCMs) with grid length scales ranging from one hundred to several hundred kilometers. Additionally, these models utilize crude statistical parameterizations of cloud processes for estimating sub-grid fluxes of heat and moisture and have a poor representation of land surface heterogeneity. For this research, we will focus on the 2012 High Plains drought and will perform numerical simulations using three single column versions (SCM) of BUGS5 (Colorado State University (CSU) GCM coupled to the Simple Biosphere Model (SiB3)) at multiple sites overlying the Ogallala Aquifer for the 2011-2012 periods. In the first version of BUGS5, the model will be used in its standard bulk setting (single atmospheric column coupled to a single instance of SiB3), secondly, the Super-Parameterized Community Atmospheric Model (SP-CAM), a cloud resolving model (CRM consists of 64 atmospheric columns), will replace the single CSU GCM atmospheric parameterization and will be coupled to a single instance of SiB3, and for the third version of BUGS5, an instance of SiB3 will be coupled to each CRM column of the SP-CAM (64 CRM columns coupled to 64 instances of SiB3). To assess the physical realism of the land-atmosphere feedbacks simulated at each site by all versions of BUGS5, differences in simulated energy and moisture fluxes will be computed between the 2011 and 2012 period and will be compared to differences calculated using

Simplified Model Surgery Technique for Segmental Maxillary Surgeries

Directory of Open Access Journals (Sweden)

Namit Nagar

2011-01-01

Full Text Available Model surgery is the dental cast version of cephalometric prediction of surgical results. Patients having vertical maxillary excess with prognathism invariably require Lefort I osteotomy with maxillary segmentation and maxillary first premolar extractions during surgery. Traditionally, model surgeries in these cases have been done by sawing the model through the first premolar interproximal area and removing that segment. This clinical innovation employed the use of X-ray film strips as separators in maxillary first premolar interproximal area. The method advocated is a time-saving procedure where no special clinical or laboratory tools, such as plaster saw (with accompanying plaster dust, were required and reusable separators were made from old and discarded X-ray films.

A streamlined artificial variable free version of simplex method.

Directory of Open Access Journals (Sweden)

Syed Inayatullah

Full Text Available This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new method has also been presented which provides a way to easily implement the phase 1 of traditional dual simplex method. For a problem having an initial basis which is both primal and dual infeasible, our methods provide full freedom to the user, that whether to start with primal artificial free version or dual artificial free version without making any reformulation to the LP structure. Last but not the least, it provides a teaching aid for the teachers who want to teach feasibility achievement as a separate topic before teaching optimality achievement.

A streamlined artificial variable free version of simplex method.

Science.gov (United States)

Inayatullah, Syed; Touheed, Nasir; Imtiaz, Muhammad

2015-01-01

This paper proposes a streamlined form of simplex method which provides some great benefits over traditional simplex method. For instance, it does not need any kind of artificial variables or artificial constraints; it could start with any feasible or infeasible basis of an LP. This method follows the same pivoting sequence as of simplex phase 1 without showing any explicit description of artificial variables which also makes it space efficient. Later in this paper, a dual version of the new method has also been presented which provides a way to easily implement the phase 1 of traditional dual simplex method. For a problem having an initial basis which is both primal and dual infeasible, our methods provide full freedom to the user, that whether to start with primal artificial free version or dual artificial free version without making any reformulation to the LP structure. Last but not the least, it provides a teaching aid for the teachers who want to teach feasibility achievement as a separate topic before teaching optimality achievement.

Stochastic learning of multi-instance dictionary for earth mover’s distance-based histogram comparison

KAUST Repository

Fan, Jihong

2016-09-17

Dictionary plays an important role in multi-instance data representation. It maps bags of instances to histograms. Earth mover’s distance (EMD) is the most effective histogram distance metric for the application of multi-instance retrieval. However, up to now, there is no existing multi-instance dictionary learning methods designed for EMD-based histogram comparison. To fill this gap, we develop the first EMD-optimal dictionary learning method using stochastic optimization method. In the stochastic learning framework, we have one triplet of bags, including one basic bag, one positive bag, and one negative bag. These bags are mapped to histograms using a multi-instance dictionary. We argue that the EMD between the basic histogram and the positive histogram should be smaller than that between the basic histogram and the negative histogram. Base on this condition, we design a hinge loss. By minimizing this hinge loss and some regularization terms of the dictionary, we update the dictionary instances. The experiments over multi-instance retrieval applications shows its effectiveness when compared to other dictionary learning methods over the problems of medical image retrieval and natural language relation classification. © 2016 The Natural Computing Applications Forum

Time efficient optimization of instance based problems with application to tone onset detection

OpenAIRE

Bauer, Nadja; Friedrichs, Klaus; Weihs, Claus

2016-01-01

A time efficient optimization technique for instance based problems is proposed, where for each parameter setting the target function has to be evaluated on a large set of problem instances. Computational time is reduced by beginning with a performance estimation based on the evaluation of a representative subset of instances. Subsequently, only promising settings are evaluated on the whole data set. As application a comprehensive music onset detection algorithm is introduce...

28 CFR 51.46 - Reconsideration of objection at the instance of the Attorney General.

Science.gov (United States)

2010-07-01

... instance of the Attorney General. 51.46 Section 51.46 Judicial Administration DEPARTMENT OF JUSTICE... Processing of Submissions § 51.46 Reconsideration of objection at the instance of the Attorney General. (a... may be reconsidered, if it is deemed appropriate, at the instance of the Attorney General. (b) Notice...

SIFT Meets CNN: A Decade Survey of Instance Retrieval.

Science.gov (United States)

Zheng, Liang; Yang, Yi; Tian, Qi

2018-05-01

In the early days, content-based image retrieval (CBIR) was studied with global features. Since 2003, image retrieval based on local descriptors (de facto SIFT) has been extensively studied for over a decade due to the advantage of SIFT in dealing with image transformations. Recently, image representations based on the convolutional neural network (CNN) have attracted increasing interest in the community and demonstrated impressive performance. Given this time of rapid evolution, this article provides a comprehensive survey of instance retrieval over the last decade. Two broad categories, SIFT-based and CNN-based methods, are presented. For the former, according to the codebook size, we organize the literature into using large/medium-sized/small codebooks. For the latter, we discuss three lines of methods, i.e., using pre-trained or fine-tuned CNN models, and hybrid methods. The first two perform a single-pass of an image to the network, while the last category employs a patch-based feature extraction scheme. This survey presents milestones in modern instance retrieval, reviews a broad selection of previous works in different categories, and provides insights on the connection between SIFT and CNN-based methods. After analyzing and comparing retrieval performance of different categories on several datasets, we discuss promising directions towards generic and specialized instance retrieval.

Quantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation

Directory of Open Access Journals (Sweden)

Kazemi K

2014-03-01

Full Text Available Background: Accurate brain tissue segmentation from magnetic resonance (MR images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM, white matter (WM and cerebrospinal fluid (CSF is needed for the neuroimaging applications. Methods: In this paper, performance evaluation of three widely used brain segmentation software packages SPM8, FSL and Brainsuite is presented. Segmentation with SPM8 has been performed in three frameworks: i default segmentation, ii SPM8 New-segmentation and iii modified version using hidden Markov random field as implemented in SPM8-VBM toolbox. Results: The accuracy of the segmented GM, WM and CSF and the robustness of the tools against changes of image quality has been assessed using Brainweb simulated MR images and IBSR real MR images. The calculated similarity between the segmented tissues using different tools and corresponding ground truth shows variations in segmentation results. Conclusion: A few studies has investigated GM, WM and CSF segmentation. In these studies, the skull stripping and bias correction are performed separately and they just evaluated the segmentation. Thus, in this study, assessment of complete segmentation framework consisting of pre-processing and segmentation of these packages is performed. The obtained results can assist the users in choosing an appropriate segmentation software package for the neuroimaging application of interest.

THE EXECUTION INSTANCE OF THE JUDICIAL JUDGEMENTS SENTENCED IN THE LITIGATIONS OF ADMINISTRATIVE CONTENTIOUS

Directory of Open Access Journals (Sweden)

ADRIANA ELENA BELU

2012-05-01

Full Text Available The instance which solved the fund of the litigation rising from an administrative contract differs depending on the material competence sanctioned by law, in contrast to the subject of the commercial law where the execution instance is the court. In this matter the High Court stated in a decision1 that in a first case the competence of solving the legal contest against the proper forced execution and of the legal contest that has in view the explanation of the meaning of spreading and applying the enforceable title which does not proceed from a jurisdiction organ is in the authority of the court. The Law of the Administrative Contentious no 554/2004 defines in Article 2 paragraph 1 letter t the notion of execution instance, providing that this is the instance which solved the fund of the litigation of administrative contentious, so even in the case of the administrative contracts the execution instance is the one which solved the litigation rising from the contract. Corroborating this disposal with the ones existing in articles 22 and 25 in the Law, it can be shown that no matter the instance which decision is an enforceable title, the execution of the law will be done by the instance which solved the fund of the litigation regarding the administrative contentious.

Improving iris recognition performance using segmentation, quality enhancement, match score fusion, and indexing.

Science.gov (United States)

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2008-08-01

This paper proposes algorithms for iris segmentation, quality enhancement, match score fusion, and indexing to improve both the accuracy and the speed of iris recognition. A curve evolution approach is proposed to effectively segment a nonideal iris image using the modified Mumford-Shah functional. Different enhancement algorithms are concurrently applied on the segmented iris image to produce multiple enhanced versions of the iris image. A support-vector-machine-based learning algorithm selects locally enhanced regions from each globally enhanced image and combines these good-quality regions to create a single high-quality iris image. Two distinct features are extracted from the high-quality iris image. The global textural feature is extracted using the 1-D log polar Gabor transform, and the local topological feature is extracted using Euler numbers. An intelligent fusion algorithm combines the textural and topological matching scores to further improve the iris recognition performance and reduce the false rejection rate, whereas an indexing algorithm enables fast and accurate iris identification. The verification and identification performance of the proposed algorithms is validated and compared with other algorithms using the CASIA Version 3, ICE 2005, and UBIRIS iris databases.

Human-Like Room Segmentation for Domestic Cleaning Robots

Directory of Open Access Journals (Sweden)

David Fleer

2017-11-01

Full Text Available Autonomous mobile robots have recently become a popular solution for automating cleaning tasks. In one application, the robot cleans a floor space by traversing and covering it completely. While fulfilling its task, such a robot may create a map of its surroundings. For domestic indoor environments, these maps often consist of rooms connected by passageways. Segmenting the map into these rooms has several uses, such as hierarchical planning of cleaning runs by the robot, or the definition of cleaning plans by the user. Especially in the latter application, the robot-generated room segmentation should match the human understanding of rooms. Here, we present a novel method that solves this problem for the graph of a topo-metric map: first, a classifier identifies those graph edges that cross a border between rooms. This classifier utilizes data from multiple robot sensors, such as obstacle measurements and camera images. Next, we attempt to segment the map at these room–border edges using graph clustering. By training the classifier on user-annotated data, this produces a human-like room segmentation. We optimize and test our method on numerous realistic maps generated by our cleaning-robot prototype and its simulated version. Overall, we find that our method produces more human-like room segmentations compared to mere graph clustering. However, unusual room borders that differ from the training data remain a challenge.

Developing a Procedure for Segmenting Meshed Heat Networks of Heat Supply Systems without Outflows

Science.gov (United States)

Tokarev, V. V.

2018-06-01

The heat supply systems of cities have, as a rule, a ring structure with the possibility of redistributing the flows. Despite the fact that a ring structure is more reliable than a radial one, the operators of heat networks prefer to use them in normal modes according to the scheme without overflows of the heat carrier between the heat mains. With such a scheme, it is easier to adjust the networks and to detect and locate faults in them. The article proposes a formulation of the heat network segmenting problem. The problem is set in terms of optimization with the heat supply system's excessive hydraulic power used as the optimization criterion. The heat supply system computer model has a hierarchically interconnected multilevel structure. Since iterative calculations are only carried out for the level of trunk heat networks, decomposing the entire system into levels allows the dimensionality of the solved subproblems to be reduced by an order of magnitude. An attempt to solve the problem by fully enumerating possible segmentation versions does not seem to be feasible for systems of really existing sizes. The article suggests a procedure for searching rational segmentation of heat supply networks with limiting the search to versions of dividing the system into segments near the flow convergence nodes with subsequent refining of the solution. The refinement is performed in two stages according to the total excess hydraulic power criterion. At the first stage, the loads are redistributed among the sources. After that, the heat networks are divided into independent fragments, and the possibility of increasing the excess hydraulic power in the obtained fragments is checked by shifting the division places inside a fragment. The proposed procedure has been approbated taking as an example a municipal heat supply system involving six heat mains fed from a common source, 24 loops within the feeding mains plane, and more than 5000 consumers. Application of the proposed

Instance Selection for Classifier Performance Estimation in Meta Learning

Directory of Open Access Journals (Sweden)

Marcin Blachnik

2017-11-01

Full Text Available Building an accurate prediction model is challenging and requires appropriate model selection. This process is very time consuming but can be accelerated with meta-learning–automatic model recommendation by estimating the performances of given prediction models without training them. Meta-learning utilizes metadata extracted from the dataset to effectively estimate the accuracy of the model in question. To achieve that goal, metadata descriptors must be gathered efficiently and must be informative to allow the precise estimation of prediction accuracy. In this paper, a new type of metadata descriptors is analyzed. These descriptors are based on the compression level obtained from the instance selection methods at the data-preprocessing stage. To verify their suitability, two types of experiments on real-world datasets have been conducted. In the first one, 11 instance selection methods were examined in order to validate the compression–accuracy relation for three classifiers: k-nearest neighbors (kNN, support vector machine (SVM, and random forest. From this analysis, two methods are recommended (instance-based learning type 2 (IB2, and edited nearest neighbor (ENN which are then compared with the state-of-the-art metaset descriptors. The obtained results confirm that the two suggested compression-based meta-features help to predict accuracy of the base model much more accurately than the state-of-the-art solution.

Unwinding focal segmental glomerulosclerosis [version 1; referees: 3 approved

Directory of Open Access Journals (Sweden)

Vasil Peev

2017-04-01

Full Text Available Focal segmental glomerulosclerosis (FSGS represents the most common primary glomerular disease responsible for the development of end-stage renal disease (ESRD in the United States (US. The disease progresses from podocyte injury to chronic kidney disease (CKD, ultimately leading to total nephron degeneration. Extensive basic science research has been conducted to unwind the mechanisms of FSGS and, with those insights, understand major contributors of CKD in general. As a result, several putative molecules and pathways have been studied, all implicated in the disease; some serve, in addition, as early biomarkers. The ongoing research is currently focusing on understanding how these molecules and pathways can interplay and be utilized as potential diagnostic and therapeutic targets. Among these molecules, the soluble urokinase plasminogen activating receptor (suPAR has been studied in detail, both clinically and from a basic science perspective. By now, it has emerged as the earliest and most robust marker of future CKD. Other circulating factors harming podocytes include anti-CD40 auto-antibody and possibly cardiotrophin-like cytokine factor-1. Understanding these factors will aid our efforts to ultimately cure FSGS and possibly treat a larger portion of CKD patients much more effectively.

Locality in Generic Instance Search from One Example

NARCIS (Netherlands)

Tao, R.; Gavves, E.; Snoek, C.G.M.; Smeulders, A.W.M.

2014-01-01

This paper aims for generic instance search from a single example. Where the state-of-the-art relies on global image representation for the search, we proceed by including locality at all steps of the method. As the first novelty, we consider many boxes per database image as candidate targets to

EU adoption of the IFRS 8 standard on operating segments

OpenAIRE

Nicolas Véron

2007-01-01

In this paper, presented to the Economic and Monetary Affairs Committee of the European Parliament, Nicolas Véron discusses whether the EU should adopt the controversial IFRS 8 standard, a convergence project on how companies should report the performance of their individual business segments. Vérons recommendation is for the European Union not to adopt the current version of IFRS 8.

Memory for Instances and Categories in Children and Adults

Science.gov (United States)

Tighe, Thomas J.; And Others

1975-01-01

Two studies of 7-year-olds and college students tested the hypothesis of a developmental difference in the degree to which subjects' memory performance was controlled by categorical properties vs. specific instance properties of test items. (GO)

Korean WA-DGNSS User Segment Software Design

Directory of Open Access Journals (Sweden)

Sayed Chhattan Shah

2013-03-01

Full Text Available Korean WA-DGNSS is a large scale research project funded by Ministry of Land, Transport and Maritime Affairs Korea. It aims to augment the Global Navigation Satellite System by broadcasting additional signals from geostationary satellites and providing differential correction messages and integrity data for the GNSS satellites. The project is being carried out by a consortium of universities and research institutes. The research team at Electronics and Telecommunications Research Institute is involved in design and development of data processing softwares for wide area reference station and user segment. This paper focuses on user segment software design. Korean WA-DGNSS user segment software is designed to perform several functions such as calculation of pseudorange, ionosphere and troposphere delays, application of fast and slow correction messages, and data verification. It is based on a layered architecture that provides a model to develop flexible and reusable software and is divided into several independent, interchangeable and reusable components to reduce complexity and maintenance cost. The current version is designed to collect and process GPS and WA-DGNSS data however it is flexible to accommodate future GNSS systems such as GLONASS and Galileo.

Simulating the 2012 High Plains Drought Using Three Single Column Model Versions of the Community Earth System Model (SCM-CESM)

Science.gov (United States)

Medina, I. D.; Denning, S.

2014-12-01

The impact of changes in the frequency and severity of drought on fresh water sustainability is a great concern for many regions of the world. One such location is the High Plains, where the local economy is primarily driven by fresh water withdrawals from the Ogallala Aquifer, which accounts for approximately 30% of total irrigation withdrawals from all U.S. aquifers combined. Modeling studies that focus on the feedback mechanisms that control the climate and eco-hydrology during times of drought are limited in the sense that they use conventional General Circulation Models (GCMs) with grid length scales ranging from one hundred to several hundred kilometers. Additionally, these models utilize crude statistical parameterizations of cloud processes for estimating sub-grid fluxes of heat and moisture and have a poor representation of land surface heterogeneity. For this research, we focus on the 2012 High Plains drought, and will perform numerical simulations using three single column model versions of the Community Earth System Model (SCM-CESM) at multiple sites overlying the Ogallala Aquifer for the 2010-2012 period. In the first version of SCM-CESM, CESM will be used in standard mode (Community Atmospheric Model (CAM) coupled to a single instance of the Community Land Model (CLM)), secondly, CESM will be used in Super-Parameterized mode (SP-CESM), where a cloud resolving model (CRM consists of 32 atmospheric columns) replaces the standard CAM atmospheric parameterization and is coupled to a single instance of CLM, and thirdly, CESM is used in "Multi Instance" SP-CESM mode, where an instance of CLM is coupled to each CRM column of SP-CESM (32 CRM columns coupled to 32 instances of CLM). To assess the physical realism of the land-atmosphere feedbacks simulated at each site by all versions of SCM-CESM, differences in simulated energy and moisture fluxes will be computed between years for the 2010-2012 period, and will be compared to differences calculated using

Kernel Methods for Mining Instance Data in Ontologies

Science.gov (United States)

Bloehdorn, Stephan; Sure, York

The amount of ontologies and meta data available on the Web is constantly growing. The successful application of machine learning techniques for learning of ontologies from textual data, i.e. mining for the Semantic Web, contributes to this trend. However, no principal approaches exist so far for mining from the Semantic Web. We investigate how machine learning algorithms can be made amenable for directly taking advantage of the rich knowledge expressed in ontologies and associated instance data. Kernel methods have been successfully employed in various learning tasks and provide a clean framework for interfacing between non-vectorial data and machine learning algorithms. In this spirit, we express the problem of mining instances in ontologies as the problem of defining valid corresponding kernels. We present a principled framework for designing such kernels by means of decomposing the kernel computation into specialized kernels for selected characteristics of an ontology which can be flexibly assembled and tuned. Initial experiments on real world Semantic Web data enjoy promising results and show the usefulness of our approach.

Brain tumor segmentation in multi-spectral MRI using convolutional neural networks (CNN).

Science.gov (United States)

Iqbal, Sajid; Ghani, M Usman; Saba, Tanzila; Rehman, Amjad

2018-04-01

A tumor could be found in any area of the brain and could be of any size, shape, and contrast. There may exist multiple tumors of different types in a human brain at the same time. Accurate tumor area segmentation is considered primary step for treatment of brain tumors. Deep Learning is a set of promising techniques that could provide better results as compared to nondeep learning techniques for segmenting timorous part inside a brain. This article presents a deep convolutional neural network (CNN) to segment brain tumors in MRIs. The proposed network uses BRATS segmentation challenge dataset which is composed of images obtained through four different modalities. Accordingly, we present an extended version of existing network to solve segmentation problem. The network architecture consists of multiple neural network layers connected in sequential order with the feeding of Convolutional feature maps at the peer level. Experimental results on BRATS 2015 benchmark data thus show the usability of the proposed approach and its superiority over the other approaches in this area of research. © 2018 Wiley Periodicals, Inc.

Coarse-Grain QoS-Aware Dynamic Instance Provisioning for Interactive Workload in the Cloud

Directory of Open Access Journals (Sweden)

Jianxiong Wan

2014-01-01

Full Text Available Cloud computing paradigm renders the Internet service providers (ISPs with a new approach to deliver their service with less cost. ISPs can rent virtual machines from the Infrastructure-as-a-Service (IaaS provided by the cloud rather than purchasing them. In addition, commercial cloud providers (CPs offer diverse VM instance rental services in various time granularities, which provide another opportunity for ISPs to reduce cost. We investigate a Coarse-grain QoS-aware Dynamic Instance Provisioning (CDIP problem for interactive workload in the cloud from the perspective of ISPs. We formulate the CDIP problem as an optimization problem where the objective is to minimize the VM instance rental cost and the constraint is the percentile delay bound. Since the Internet traffic shows a strong self-similar property, it is hard to get an analytical form of the percentile delay constraint. To address this issue, we purpose a lookup table structure together with a learning algorithm to estimate the performance of the instance provisioning policy. This approach is further extended with two function approximations to enhance the scalability of the learning algorithm. We also present an efficient dynamic instance provisioning algorithm, which takes full advantage of the rental service diversity, to determine the instance rental policy. Extensive simulations are conducted to validate the effectiveness of the proposed algorithms.

Data-aware remaining time prediction of business process instances

NARCIS (Netherlands)

Polato, M.; Sperduti, A.; Burattin, A.; Leoni, de M.

2014-01-01

Accurate prediction of the completion time of a business process instance would constitute a valuable tool when managing processes under service level agreement constraints. Such prediction, however, is a very challenging task. A wide variety of factors could influence the trend of a process

Topology and robustness in the Drosophila segment polarity network.

Directory of Open Access Journals (Sweden)

Nicholas T Ingolia

2004-06-01

Full Text Available A complex hierarchy of genetic interactions converts a single-celled Drosophila melanogaster egg into a multicellular embryo with 14 segments. Previously, von Dassow et al. reported that a mathematical model of the genetic interactions that defined the polarity of segments (the segment polarity network was robust (von Dassow et al. 2000. As quantitative information about the system was unavailable, parameters were sampled randomly. A surprisingly large fraction of these parameter sets allowed the model to maintain and elaborate on the segment polarity pattern. This robustness is due to the positive feedback of gene products on their own expression, which induces individual cells in a model segment to adopt different stable expression states (bistability corresponding to different cell types in the segment polarity pattern. A positive feedback loop will only yield multiple stable states when the parameters that describe it satisfy a particular inequality. By testing which random parameter sets satisfy these inequalities, I show that bistability is necessary to form the segment polarity pattern and serves as a strong predictor of which parameter sets will succeed in forming the pattern. Although the original model was robust to parameter variation, it could not reproduce the observed effects of cell division on the pattern of gene expression. I present a modified version that incorporates recent experimental evidence and does successfully mimic the consequences of cell division. The behavior of this modified model can also be understood in terms of bistability in positive feedback of gene expression. I discuss how this topological property of networks provides robust pattern formation and how large changes in parameters can change the specific pattern produced by a network.

Intensity-based hierarchical clustering in CT-scans: application to interactive segmentation in cardiology

Science.gov (United States)

Hadida, Jonathan; Desrosiers, Christian; Duong, Luc

2011-03-01

The segmentation of anatomical structures in Computed Tomography Angiography (CTA) is a pre-operative task useful in image guided surgery. Even though very robust and precise methods have been developed to help achieving a reliable segmentation (level sets, active contours, etc), it remains very time consuming both in terms of manual interactions and in terms of computation time. The goal of this study is to present a fast method to find coarse anatomical structures in CTA with few parameters, based on hierarchical clustering. The algorithm is organized as follows: first, a fast non-parametric histogram clustering method is proposed to compute a piecewise constant mask. A second step then indexes all the space-connected regions in the piecewise constant mask. Finally, a hierarchical clustering is achieved to build a graph representing the connections between the various regions in the piecewise constant mask. This step builds up a structural knowledge about the image. Several interactive features for segmentation are presented, for instance association or disassociation of anatomical structures. A comparison with the Mean-Shift algorithm is presented.

Dual-Layer Density Estimation for Multiple Object Instance Detection

Directory of Open Access Journals (Sweden)

Qiang Zhang

2016-01-01

Full Text Available This paper introduces a dual-layer density estimation-based architecture for multiple object instance detection in robot inventory management applications. The approach consists of raw scale-invariant feature transform (SIFT feature matching and key point projection. The dominant scale ratio and a reference clustering threshold are estimated using the first layer of the density estimation. A cascade of filters is applied after feature template reconstruction and refined feature matching to eliminate false matches. Before the second layer of density estimation, the adaptive threshold is finalized by multiplying an empirical coefficient for the reference value. The coefficient is identified experimentally. Adaptive threshold-based grid voting is applied to find all candidate object instances. Error detection is eliminated using final geometric verification in accordance with Random Sample Consensus (RANSAC. The detection results of the proposed approach are evaluated on a self-built dataset collected in a supermarket. The results demonstrate that the approach provides high robustness and low latency for inventory management application.

Instances or Sequences? Improving the State of the Art of Qualitative Research

Directory of Open Access Journals (Sweden)

David Silverman

2005-09-01

Full Text Available Numbers apparently talk. With few numbers, qualitative researchers appear to rely on examples or instances to support their analysis. Hence research reports routinely display data extracts which serve as telling instances of some claimed phenomenon. However, the use of such an evidential base rightly provokes the charge of (possible anecdotalism, i.e. choosing just those extracts which support your argument. I suggest that this methodological problem is best addressed by returning to those features of our theoretical roots which tend to distinguish what we do from the work of quantitative social scientists. Although SAUSSURE is most cited in linguistics and structural anthropology, he provides a simple rule that applies to us all. In a rebuke to our reli­ance on instances, SAUSSURE tells us "no mean­ing exists in a single item". Everything depends upon how single items (elements are articulated. One everyday activity in which the social world is articulated is through the construction of se­quences. Just as participants attend to the se­quential placing of interactional "events", so should social scientists. Using examples drawn from focus groups, fieldnotes and audiotapes, I argue that the identification of such sequences rather than the citing of instances should constitute a prime test for the adequacy of any claim about qualitative data. URN: urn:nbn:de:0114-fqs0503301

Automatic provisioning, deployment and orchestration for load-balancing THREDDS instances

Science.gov (United States)

Cofino, A. S.; Fernández-Tejería, S.; Kershaw, P.; Cimadevilla, E.; Petri, R.; Pryor, M.; Stephens, A.; Herrera, S.

2017-12-01

THREDDS is a widely used web server to provide to different scientific communities with data access and discovery. Due to THREDDS's lack of horizontal scalability and automatic configuration management and deployment, this service usually deals with service downtimes and time consuming configuration tasks, mainly when an intensive use is done as is usual within the scientific community (e.g. climate). Instead of the typical installation and configuration of a single or multiple independent THREDDS servers, manually configured, this work presents an automatic provisioning, deployment and orchestration cluster of THREDDS servers. This solution it's based on Ansible playbooks, used to control automatically the deployment and configuration setup on a infrastructure and to manage the datasets available in THREDDS instances. The playbooks are based on modules (or roles) of different backends and frontends load-balancing setups and solutions. The frontend load-balancing system enables horizontal scalability by delegating requests to backend workers, consisting in a variable number of instances for the THREDDS server. This implementation allows to configure different infrastructure and deployment scenario setups, as more workers are easily added to the cluster by simply declaring them as Ansible variables and executing the playbooks, and also provides fault-tolerance and better reliability since if any of the workers fail another instance of the cluster can take over it. In order to test the solution proposed, two real scenarios are analyzed in this contribution: The JASMIN Group Workspaces at CEDA and the User Data Gateway (UDG) at the Data Climate Service from the University of Cantabria. On the one hand, the proposed configuration has provided CEDA with a higher level and more scalable Group Workspaces (GWS) service than the previous one based on Unix permissions, improving also the data discovery and data access experience. On the other hand, the UDG has improved its

Identification of everyday objects on the basis of Gaborized outline versions.

Science.gov (United States)

Sassi, Michaël; Vancleef, Kathleen; Machilsen, Bart; Panis, Sven; Wagemans, Johan

2010-01-01

Using outlines derived from a widely used set of line drawings, we created stimuli geared towards the investigation of contour integration and texture segmentation using shapes of everyday objects. Each stimulus consisted of Gabor elements positioned and oriented curvilinearly along the outline of an object, embedded within a larger Gabor array of homogeneous density. We created six versions of the resulting Gaborized outline stimuli by varying the orientations of elements inside and outside the outline. Data from two experiments, in which participants attempted to identify the objects in the stimuli, provide norms for identifiability and name agreement, and show differences in identifiability between stimulus versions. While there was substantial variability between the individual objects in our stimulus set, further analyses suggest a number of stimulus properties which are generally predictive of identification performance. The stimuli and the accompanying normative data, both available on our website (http://www.gestaltrevision.be/sources/gaboroutlines), provide a useful tool to further investigate contour integration and texture segmentation in both normal and clinical populations, especially when top-down influences on these processes, such as the role of prior knowledge of familiar objects, are of main interest.

Segmentation: Identification of consumer segments

DEFF Research Database (Denmark)

Høg, Esben

2005-01-01

It is very common to categorise people, especially in the advertising business. Also traditional marketing theory has taken in consumer segments as a favorite topic. Segmentation is closely related to the broader concept of classification. From a historical point of view, classification has its...... origin in other sciences as for example biology, anthropology etc. From an economic point of view, it is called segmentation when specific scientific techniques are used to classify consumers to different characteristic groupings. What is the purpose of segmentation? For example, to be able to obtain...... a basic understanding of grouping people. Advertising agencies may use segmentation totarget advertisements, while food companies may usesegmentation to develop products to various groups of consumers. MAPP has for example investigated the positioning of fish in relation to other food products...

First instance competence of the Higher Administrative Court

International Nuclear Information System (INIS)

Anon.

1988-01-01

(1) An interlocutory judgement can determine the admissibility of a legal action, also with regard to single procedural prerequisites (following BVerwG decision 14, 273). (2) The first instance competence for disputes about the dismantling of a decommissioned nuclear installation lies with the administrative courts and not with the higher administrative courts. Federal Administrative Court, decision of May 19, 1988 - 7 C 43.88 - (VGH Munich). (orig.) [de

Semi-automatic geographic atrophy segmentation for SD-OCT images.

Science.gov (United States)

Chen, Qiang; de Sisternes, Luis; Leng, Theodore; Zheng, Luoluo; Kutzscher, Lauren; Rubin, Daniel L

2013-01-01

Geographic atrophy (GA) is a condition that is associated with retinal thinning and loss of the retinal pigment epithelium (RPE) layer. It appears in advanced stages of non-exudative age-related macular degeneration (AMD) and can lead to vision loss. We present a semi-automated GA segmentation algorithm for spectral-domain optical coherence tomography (SD-OCT) images. The method first identifies and segments a surface between the RPE and the choroid to generate retinal projection images in which the projection region is restricted to a sub-volume of the retina where the presence of GA can be identified. Subsequently, a geometric active contour model is employed to automatically detect and segment the extent of GA in the projection images. Two image data sets, consisting on 55 SD-OCT scans from twelve eyes in eight patients with GA and 56 SD-OCT scans from 56 eyes in 56 patients with GA, respectively, were utilized to qualitatively and quantitatively evaluate the proposed GA segmentation method. Experimental results suggest that the proposed algorithm can achieve high segmentation accuracy. The mean GA overlap ratios between our proposed method and outlines drawn in the SD-OCT scans, our method and outlines drawn in the fundus auto-fluorescence (FAF) images, and the commercial software (Carl Zeiss Meditec proprietary software, Cirrus version 6.0) and outlines drawn in FAF images were 72.60%, 65.88% and 59.83%, respectively.

Basics of XBRL Instance for Financial Reporting

Directory of Open Access Journals (Sweden)

Mihaela Enachi

2011-10-01

Full Text Available The development of XBRL (eXtensible Business Reporting Language for financial reporting has significantly changed the way which financial statements are presented to differentusers and implicitly the quantity and quality of information provided through such a modern format. Following a standard structure, but adaptable to the regulations from different countriesor regions of the world, we can communicate and process financial accounting information more efficient and effective. This paper tries to clarify the manner of preparation and presentation ofthe financial statements if using XBRL as reporting tool.Keywords: XML, XBRL, financial reporting, specification, taxonomy, instance

Adaptation of the Maracas algorithm for carotid artery segmentation and stenosis quantification on CT images

International Nuclear Information System (INIS)

Maria A Zuluaga; Maciej Orkisz; Edgar J F Delgado; Vincent Dore; Alfredo Morales Pinzon; Marcela Hernandez Hoyos

2010-01-01

This paper describes the adaptations of Maracas algorithm to the segmentation and quantification of vascular structures in CTA images of the carotid artery. The maracas algorithm, which is based on an elastic model and on a multi-scale Eigen-analysis of the inertia matrix, was originally designed to segment a single artery in MRA images. The modifications are primarily aimed at addressing the specificities of CT images and the bifurcations. The algorithms implemented in this new version are classified into two levels. 1. The low-level processing (filtering of noise and directional artifacts, enhancement and pre-segmentation) to improve the quality of the image and to pre-segment it. These techniques are based on a priori information about noise, artifacts and typical gray levels ranges of lumen, background and calcifications. 2. The high-level processing to extract the centerline of the artery, to segment the lumen and to quantify the stenosis. At this level, we apply a priori knowledge of shape and anatomy of vascular structures. The method was evaluated on 31 datasets from the carotid lumen segmentation and stenosis grading grand challenge 2009. The segmentation results obtained an average of 80:4% dice similarity score, compared to reference segmentation, and the mean stenosis quantification error was 14.4%.

Performing the processing required for automatically get a PDF/A version of the CERN Library documentation

CERN Document Server

Molina Garcia-Retamero, Antonio

2015-01-01

The aim of the project was to perform the processing required for automatically get a PDF/A version of the CERN Library documentation. For this, it is necessary to extract as much metadata as possible from the sources files, inject the required data into the original source files creating new ones ready for being compiled with all related dependencies. Besides, I’ve proposed the creation of a HTML version consistent with the PDF and navigable for easy access, I’ve been trying to perform some Natural Language Processing for extracting metadata, I’ve proposed the injection of the cern library documentation into the HTML version of the long writeups where it is referenced (for instance, when a CERN Library function is referenced in a sample code) Finally, I’ve designed and implemented a Graphical User Interface in order to simplify the process for the user.

Solving large instances of the quadratic cost of partition problem on dense graphs by data correcting algorithms

NARCIS (Netherlands)

Goldengorin, Boris; Vink, Marius de

1999-01-01

The Data-Correcting Algorithm (DCA) corrects the data of a hard problem instance in such a way that we obtain an instance of a well solvable special case. For a given prescribed accuracy of the solution, the DCA uses a branch and bound scheme to make sure that the solution of the corrected instance

Status of the segment interconnect, cable segment ancillary logic, and the cable segment hybrid driver projects

International Nuclear Information System (INIS)

Swoboda, C.; Barsotti, E.; Chappa, S.; Downing, R.; Goeransson, G.; Lensy, D.; Moore, G.; Rotolo, C.; Urish, J.

1985-01-01

The FASTBUS Segment Interconnect (SI) provides a communication path between two otherwise independent, asynchronous bus segments. In particular, the Segment Interconnect links a backplane crate segment to a cable segment. All standard FASTBUS address and data transactions can be passed through the SI or any number of SIs and segments in a path. Thus systems of arbitrary connection complexity can be formed, allowing simultaneous independent processing, yet still permitting devices associated with one segment to be accessed from others. The model S1 Segment Interconnect and the Cable Segment Ancillary Logic covered in this report comply with all the mandatory features stated in the FASTBUS specification document DOE/ER-0189. A block diagram of the SI is shown

Feature selection is the ReliefF for multiple instance learning

NARCIS (Netherlands)

Zafra, A.; Pechenizkiy, M.; Ventura, S.

2010-01-01

Dimensionality reduction and feature selection in particular are known to be of a great help for making supervised learning more effective and efficient. Many different feature selection techniques have been proposed for the traditional settings, where each instance is expected to have a label. In

Instance-based Policy Learning by Real-coded Genetic Algorithms and Its Application to Control of Nonholonomic Systems

Science.gov (United States)

Miyamae, Atsushi; Sakuma, Jun; Ono, Isao; Kobayashi, Shigenobu

The stabilization control of nonholonomic systems have been extensively studied because it is essential for nonholonomic robot control problems. The difficulty in this problem is that the theoretical derivation of control policy is not necessarily guaranteed achievable. In this paper, we present a reinforcement learning (RL) method with instance-based policy (IBP) representation, in which control policies for this class are optimized with respect to user-defined cost functions. Direct policy search (DPS) is an approach for RL; the policy is represented by parametric models and the model parameters are directly searched by optimization techniques including genetic algorithms (GAs). In IBP representation an instance consists of a state and an action pair; a policy consists of a set of instances. Several DPSs with IBP have been previously proposed. In these methods, sometimes fail to obtain optimal control policies when state-action variables are continuous. In this paper, we present a real-coded GA for DPSs with IBP. Our method is specifically designed for continuous domains. Optimization of IBP has three difficulties; high-dimensionality, epistasis, and multi-modality. Our solution is designed for overcoming these difficulties. The policy search with IBP representation appears to be high-dimensional optimization; however, instances which can improve the fitness are often limited to active instances (instances used for the evaluation). In fact, the number of active instances is small. Therefore, we treat the search problem as a low dimensional problem by restricting search variables only to active instances. It has been commonly known that functions with epistasis can be efficiently optimized with crossovers which satisfy the inheritance of statistics. For efficient search of IBP, we propose extended crossover-like mutation (extended XLM) which generates a new instance around an instance with satisfying the inheritance of statistics. For overcoming multi-modality, we

Version pressure feedback mechanisms for speculative versioning caches

Science.gov (United States)

Eichenberger, Alexandre E.; Gara, Alan; O& #x27; Brien, Kathryn M.; Ohmacht, Martin; Zhuang, Xiaotong

2013-03-12

Mechanisms are provided for controlling version pressure on a speculative versioning cache. Raw version pressure data is collected based on one or more threads accessing cache lines of the speculative versioning cache. One or more statistical measures of version pressure are generated based on the collected raw version pressure data. A determination is made as to whether one or more modifications to an operation of a data processing system are to be performed based on the one or more statistical measures of version pressure, the one or more modifications affecting version pressure exerted on the speculative versioning cache. An operation of the data processing system is modified based on the one or more determined modifications, in response to a determination that one or more modifications to the operation of the data processing system are to be performed, to affect the version pressure exerted on the speculative versioning cache.

Object-based implicit learning in visual search: perceptual segmentation constrains contextual cueing.

Science.gov (United States)

Conci, Markus; Müller, Hermann J; von Mühlenen, Adrian

2013-07-09

In visual search, detection of a target is faster when it is presented within a spatial layout of repeatedly encountered nontarget items, indicating that contextual invariances can guide selective attention (contextual cueing; Chun & Jiang, 1998). However, perceptual regularities may interfere with contextual learning; for instance, no contextual facilitation occurs when four nontargets form a square-shaped grouping, even though the square location predicts the target location (Conci & von Mühlenen, 2009). Here, we further investigated potential causes for this interference-effect: We show that contextual cueing can reliably occur for targets located within the region of a segmented object, but not for targets presented outside of the object's boundaries. Four experiments demonstrate an object-based facilitation in contextual cueing, with a modulation of context-based learning by relatively subtle grouping cues including closure, symmetry, and spatial regularity. Moreover, the lack of contextual cueing for targets located outside the segmented region was due to an absence of (latent) learning of contextual layouts, rather than due to an attentional bias towards the grouped region. Taken together, these results indicate that perceptual segmentation provides a basic structure within which contextual scene regularities are acquired. This in turn argues that contextual learning is constrained by object-based selection.

Metabolically active tumour volume segmentation from dynamic [(18)F]FLT PET studies in non-small cell lung cancer.

Science.gov (United States)

Hoyng, Lieke L; Frings, Virginie; Hoekstra, Otto S; Kenny, Laura M; Aboagye, Eric O; Boellaard, Ronald

2015-01-01

Positron emission tomography (PET) with (18)F-3'-deoxy-3'-fluorothymidine ([(18)F]FLT) can be used to assess tumour proliferation. A kinetic-filtering (KF) classification algorithm has been suggested for segmentation of tumours in dynamic [(18)F]FLT PET data. The aim of the present study was to evaluate KF segmentation and its test-retest performance in [(18)F]FLT PET in non-small cell lung cancer (NSCLC) patients. Nine NSCLC patients underwent two 60-min dynamic [(18)F]FLT PET scans within 7 days prior to treatment. Dynamic scans were reconstructed with filtered back projection (FBP) as well as with ordered subsets expectation maximisation (OSEM). Twenty-eight lesions were identified by an experienced physician. Segmentation was performed using KF applied to the dynamic data set and a source-to-background corrected 50% threshold (A50%) was applied to the sum image of the last three frames (45- to 60-min p.i.). Furthermore, several adaptations of KF were tested. Both for KF and A50% test-retest (TRT) variability of metabolically active tumour volume and standard uptake value (SUV) were evaluated. KF performed better on OSEM- than on FBP-reconstructed PET images. The original KF implementation segmented 15 out of 28 lesions, whereas A50% segmented each lesion. Adapted KF versions, however, were able to segment 26 out of 28 lesions. In the best performing adapted versions, metabolically active tumour volume and SUV TRT variability was similar to those of A50%. KF misclassified certain tumour areas as vertebrae or liver tissue, which was shown to be related to heterogeneous [(18)F]FLT uptake areas within the tumour. For [(18)F]FLT PET studies in NSCLC patients, KF and A50% show comparable tumour volume segmentation performance. The KF method needs, however, a site-specific optimisation. The A50% is therefore a good alternative for tumour segmentation in NSCLC [(18)F]FLT PET studies in multicentre studies. Yet, it was observed that KF has the potential to subsegment

Segmented block copolymers with monodisperse aramide end-segments

NARCIS (Netherlands)

Araichimani, A.; Gaymans, R.J.

2008-01-01

Segmented block copolymers were synthesized using monodisperse diaramide (TT) as hard segments and PTMO with a molecular weight of 2 900 g · mol-1 as soft segments. The aramide: PTMO segment ratio was increased from 1:1 to 2:1 thereby changing the structure from a high molecular weight multi-block

Mean curvature and texture constrained composite weighted random walk algorithm for optic disc segmentation towards glaucoma screening.

Science.gov (United States)

Panda, Rashmi; Puhan, N B; Panda, Ganapati

2018-02-01

Accurate optic disc (OD) segmentation is an important step in obtaining cup-to-disc ratio-based glaucoma screening using fundus imaging. It is a challenging task because of the subtle OD boundary, blood vessel occlusion and intensity inhomogeneity. In this Letter, the authors propose an improved version of the random walk algorithm for OD segmentation to tackle such challenges. The algorithm incorporates the mean curvature and Gabor texture energy features to define the new composite weight function to compute the edge weights. Unlike the deformable model-based OD segmentation techniques, the proposed algorithm remains unaffected by curve initialisation and local energy minima problem. The effectiveness of the proposed method is verified with DRIVE, DIARETDB1, DRISHTI-GS and MESSIDOR database images using the performance measures such as mean absolute distance, overlapping ratio, dice coefficient, sensitivity, specificity and precision. The obtained OD segmentation results and quantitative performance measures show robustness and superiority of the proposed algorithm in handling the complex challenges in OD segmentation.

Segmentation of consumer's markets and evaluation of market's segments

OpenAIRE

ŠVECOVÁ, Iveta

2013-01-01

The goal of this bachelor thesis was to explain a possibly segmentation of consumer´s markets for a chosen company, and to present a suitable goods offer, so it would be suitable to the needs of selected segments. The work is divided into theoretical and practical part. First part describes marketing, segmentation, segmentation of consumer's markets, consumer's market, market's segments a other terms. Second part describes an evaluation of questionnaire survey, discovering of market's segment...

Multi-Class Simultaneous Adaptive Segmentation and Quality Control of Point Cloud Data

Directory of Open Access Journals (Sweden)

Ayman Habib

2016-01-01

Full Text Available 3D modeling of a given site is an important activity for a wide range of applications including urban planning, as-built mapping of industrial sites, heritage documentation, military simulation, and outdoor/indoor analysis of airflow. Point clouds, which could be either derived from passive or active imaging systems, are an important source for 3D modeling. Such point clouds need to undergo a sequence of data processing steps to derive the necessary information for the 3D modeling process. Segmentation is usually the first step in the data processing chain. This paper presents a region-growing multi-class simultaneous segmentation procedure, where planar, pole-like, and rough regions are identified while considering the internal characteristics (i.e., local point density/spacing and noise level of the point cloud in question. The segmentation starts with point cloud organization into a kd-tree data structure and characterization process to estimate the local point density/spacing. Then, proceeding from randomly-distributed seed points, a set of seed regions is derived through distance-based region growing, which is followed by modeling of such seed regions into planar and pole-like features. Starting from optimally-selected seed regions, planar and pole-like features are then segmented. The paper also introduces a list of hypothesized artifacts/problems that might take place during the region-growing process. Finally, a quality control process is devised to detect, quantify, and mitigate instances of partially/fully misclassified planar and pole-like features. Experimental results from airborne and terrestrial laser scanning as well as image-based point clouds are presented to illustrate the performance of the proposed segmentation and quality control framework.

TNO at TRECVID 2013: Multimedia Event Detection and Instance Search

NARCIS (Netherlands)

Bouma, H.; Azzopardi, G.; Spitters, M.M.; Wit, J.J. de; Versloot, C.A.; Zon, R.W.L. van der; Eendebak, P.T.; Baan, J.; Hove, R.J.M. ten; Eekeren, A.W.M. van; Haar, F.B. ter; Hollander, R.J.M. den; Huis, R.J. van; Boer, M.H.T. de; Antwerpen, G. van; Broekhuijsen, B.J.; Daniele, L.M.; Brandt, P.; Schavemaker, J.G.M.; Kraaij, W.; Schutte, K.

2013-01-01

We describe the TNO system and the evaluation results for TRECVID 2013 Multimedia Event Detection (MED) and instance search (INS) tasks. The MED system consists of a bag-of-word (BOW) approach with spatial tiling that uses low-level static and dynamic visual features, an audio feature and high-level

Le contentieux camerounais devant les instances sportives internationales

Directory of Open Access Journals (Sweden)

Dikoume François Claude

2016-01-01

Les acteurs du sport depuis lors, utilisent donc les voies de recours au niveau international soit vers les fédérations sportives internationales ou encore et surtout vers le TAS qui s'occupe des litiges de toutes les disciplines sportives. Il est question ici de faire un inventaire casuistique descriptif non exhaustif des requêtes contentieuses camerounaises portées devant les diverses instances sportives internationales ; ceci permettra de questionner l'esprit processuel et la qualité technique de leurs réclamations juridiques en matière sportive.

Clinical validation of a non-heteronormative version of the Social Interaction Anxiety Scale (SIAS).

Science.gov (United States)

Lindner, Philip; Martell, Christopher; Bergström, Jan; Andersson, Gerhard; Carlbring, Per

2013-12-19

Despite welcomed changes in societal attitudes and practices towards sexual minorities, instances of heteronormativity can still be found within healthcare and research. The Social Interaction Anxiety Scale (SIAS) is a valid and reliable self-rating scale of social anxiety, which includes one item (number 14) with an explicit heteronormative assumption about the respondent's sexual orientation. This heteronormative phrasing may confuse, insult or alienate sexual minority respondents. A clinically validated version of the SIAS featuring a non-heteronormative phrasing of item 14 is thus needed. 129 participants with diagnosed social anxiety disorder, enrolled in an Internet-based intervention trial, were randomly assigned to responding to the SIAS featuring either the original or a novel non-heteronormative phrasing of item 14, and then answered the other item version. Within-subject, correlation between item versions was calculated and the two scores were statistically compared. The two items' correlations with the other SIAS items and other psychiatric rating scales were also statistically compared. Item versions were highly correlated and scores did not differ statistically. The two items' correlations with other measures did not differ statistically either. The SIAS can be revised with a non-heteronormative formulation of item 14 with psychometric equivalence on item and scale level. Implications for other psychiatric instruments with heteronormative phrasings are discussed.

Increasing the detection of minority class instances in financial statement fraud

CSIR Research Space (South Africa)

Moepya, Stephen

2017-04-01

Full Text Available -1 Asian Conference on Intelligent Information and Database Systems, 3-5 April 2017, Kanazawa, Japan Increasing the detection of minority class instances in financial statement fraud Stephen Obakeng Moepya1,2(B), Fulufhelo V. Nelwamondo1...

A Hybrid Instance Selection Using Nearest-Neighbor for Cross-Project Defect Prediction

Institute of Scientific and Technical Information of China (English)

Duksan Ryu; Jong-In Jang; Jongmoon Baik; Member; ACM; IEEE

2015-01-01

Software defect prediction (SDP) is an active research field in software engineering to identify defect-prone modules. Thanks to SDP, limited testing resources can be effectively allocated to defect-prone modules. Although SDP requires suffcient local data within a company, there are cases where local data are not available, e.g., pilot projects. Companies without local data can employ cross-project defect prediction (CPDP) using external data to build classifiers. The major challenge of CPDP is different distributions between training and test data. To tackle this, instances of source data similar to target data are selected to build classifiers. Software datasets have a class imbalance problem meaning the ratio of defective class to clean class is far low. It usually lowers the performance of classifiers. We propose a Hybrid Instance Selection Using Nearest-Neighbor (HISNN) method that performs a hybrid classification selectively learning local knowledge (via k-nearest neighbor) and global knowledge (via na¨ıve Bayes). Instances having strong local knowledge are identified via nearest-neighbors with the same class label. Previous studies showed low PD (probability of detection) or high PF (probability of false alarm) which is impractical to use. The experimental results show that HISNN produces high overall performance as well as high PD and low PF.

A practical approximation algorithm for solving massive instances of hybridization number

NARCIS (Netherlands)

Iersel, van L.J.J.; Kelk, S.M.; Lekic, N.; Scornavacca, C.; Raphael, B.; Tang, J.

2012-01-01

Reticulate events play an important role in determining evolutionary relationships. The problem of computing the minimum number of such events to explain discordance between two phylogenetic trees is a hard computational problem. In practice, exact solvers struggle to solve instances with

Placental fetal stem segmentation in a sequence of histology images

Science.gov (United States)

Athavale, Prashant; Vese, Luminita A.

2012-02-01

Recent research in perinatal pathology argues that analyzing properties of the placenta may reveal important information on how certain diseases progress. One important property is the structure of the placental fetal stems. Analysis of the fetal stems in a placenta could be useful in the study and diagnosis of some diseases like autism. To study the fetal stem structure effectively, we need to automatically and accurately track fetal stems through a sequence of digitized hematoxylin and eosin (H&E) stained histology slides. There are many problems in successfully achieving this goal. A few of the problems are: large size of images, misalignment of the consecutive H&E slides, unpredictable inaccuracies of manual tracing, very complicated texture patterns of various tissue types without clear characteristics, just to name a few. In this paper we propose a novel algorithm to achieve automatic tracing of the fetal stem in a sequence of H&E images, based on an inaccurate manual segmentation of a fetal stem in one of the images. This algorithm combines global affine registration, local non-affine registration and a novel 'dynamic' version of the active contours model without edges. We first use global affine image registration of all the images based on displacement, scaling and rotation. This gives us approximate location of the corresponding fetal stem in the image that needs to be traced. We then use the affine registration algorithm "locally" near this location. At this point, we use a fast non-affine registration based on L2-similarity measure and diffusion regularization to get a better location of the fetal stem. Finally, we have to take into account inaccuracies in the initial tracing. This is achieved through a novel dynamic version of the active contours model without edges where the coefficients of the fitting terms are computed iteratively to ensure that we obtain a unique stem in the segmentation. The segmentation thus obtained can then be used as an

Unsupervised motion-based object segmentation refined by color

Science.gov (United States)

Piek, Matthijs C.; Braspenning, Ralph; Varekamp, Chris

2003-06-01

For various applications, such as data compression, structure from motion, medical imaging and video enhancement, there is a need for an algorithm that divides video sequences into independently moving objects. Because our focus is on video enhancement and structure from motion for consumer electronics, we strive for a low complexity solution. For still images, several approaches exist based on colour, but these lack in both speed and segmentation quality. For instance, colour-based watershed algorithms produce a so-called oversegmentation with many segments covering each single physical object. Other colour segmentation approaches exist which somehow limit the number of segments to reduce this oversegmentation problem. However, this often results in inaccurate edges or even missed objects. Most likely, colour is an inherently insufficient cue for real world object segmentation, because real world objects can display complex combinations of colours. For video sequences, however, an additional cue is available, namely the motion of objects. When different objects in a scene have different motion, the motion cue alone is often enough to reliably distinguish objects from one another and the background. However, because of the lack of sufficient resolution of efficient motion estimators, like the 3DRS block matcher, the resulting segmentation is not at pixel resolution, but at block resolution. Existing pixel resolution motion estimators are more sensitive to noise, suffer more from aperture problems or have less correspondence to the true motion of objects when compared to block-based approaches or are too computationally expensive. From its tendency to oversegmentation it is apparent that colour segmentation is particularly effective near edges of homogeneously coloured areas. On the other hand, block-based true motion estimation is particularly effective in heterogeneous areas, because heterogeneous areas improve the chance a block is unique and thus decrease the

A critique of medicalisation: three instances.

Science.gov (United States)

Ryang, Sonia

2017-12-01

By briefly exploring three different examples where the existence of mental illness and developmental delay has been presumed, this paper sheds light on the way what Foucault calls the emergence of a regime of truth, i.e. where something that does not exist is made to exist through the construction of a system of truth around it. The first example concerns the direct marketing of pharmaceutical products to consumers in the US, the second the use of psychology in semi-post-Cold War Korea, and the third the persisting authority of psychology in the treatment of the developmentally delayed. While these instances are not innately connected, looking at these as part of the process by which the authoritative knowledge is established will help us understand, albeit partially, the mechanism by which mental illness penetrates our lives as truth, and how this regime of truth is supported by the authority of psychology, psychiatry and psychoanalysis, what Foucault calls the 'psy-function,' reinforcing the medicalisation of our lives.

Robust segmentation of medical images using competitive hop field neural network as a clustering tool

International Nuclear Information System (INIS)

Golparvar Roozbahani, R.; Ghassemian, M. H.; Sharafat, A. R.

2001-01-01

This paper presents the application of competitive Hop field neural network for medical images segmentation. Our proposed approach consists of Two steps: 1) translating segmentation of the given medical image into an optimization problem, and 2) solving this problem by a version of Hop field network known as competitive Hop field neural network. Segmentation is considered as a clustering problem and its validity criterion is based on both intra set distance and inter set distance. The algorithm proposed in this paper is based on gray level features only. This leads to near optimal solutions if both intra set distance and inter set distance are considered at the same time. If only one of these distances is considered, the result of segmentation process by competitive Hop field neural network will be far from optimal solution and incorrect even for very simple cases. Furthermore, sometimes the algorithm receives at unacceptable states. Both these problems may be solved by contributing both in tera distance and inter distances in the segmentation (optimization) process. The performance of the proposed algorithm is tested on both phantom and real medical images. The promising results and the robustness of algorithm to system noises show near optimal solutions

Towards End-to-End Lane Detection: an Instance Segmentation Approach

OpenAIRE

Neven, Davy; De Brabandere, Bert; Georgoulis, Stamatios; Proesmans, Marc; Van Gool, Luc

2018-01-01

Modern cars are incorporating an increasing number of driver assist features, among which automatic lane keeping. The latter allows the car to properly position itself within the road lanes, which is also crucial for any subsequent lane departure or trajectory planning decision in fully autonomous cars. Traditional lane detection methods rely on a combination of highly-specialized, hand-crafted features and heuristics, usually followed by post-processing techniques, that are computationally e...

Breaking Newton’s third law: electromagnetic instances

International Nuclear Information System (INIS)

Kneubil, Fabiana B

2016-01-01

In this work, three instances are discussed within electromagnetism which highlight failures in the validity of Newton’s third law, all of them related to moving charged particles. It is well known that electromagnetic theory paved the way for relativity and that it disclosed new phenomena which were not compatible with the laws of mechanics. However, even if widely known in its generality, this issue is not clearly approached in introductory textbooks and it is difficult for students to perceive by themselves. Three explicit concrete situations involving the breaking of Newton’s third law are presented in this paper, together with a didactical procedure to construct graphically the configurations of electric field lines, which allow pictures produced by interactive radiation simulators available in websites to be better understood. (paper)

Clustering with Instance and Attribute Level Side Information

Directory of Open Access Journals (Sweden)

Jinlong Wang

2010-12-01

Full Text Available Selecting a suitable proximity measure is one of the fundamental tasks in clustering. How to effectively utilize all available side information, including the instance level information in the form of pair-wise constraints, and the attribute level information in the form of attribute order preferences, is an essential problem in metric learning. In this paper, we propose a learning framework in which both the pair-wise constraints and the attribute order preferences can be incorporated simultaneously. The theory behind it and the related parameter adjusting technique have been described in details. Experimental results on benchmark data sets demonstrate the effectiveness of proposed method.

EOS MLS Level 2 Data Processing Software Version 3

Science.gov (United States)

Livesey, Nathaniel J.; VanSnyder, Livesey W.; Read, William G.; Schwartz, Michael J.; Lambert, Alyn; Santee, Michelle L.; Nguyen, Honghanh T.; Froidevaux, Lucien; wang, Shuhui; Manney, Gloria L.;

Ultrasonographic evaluation of myometrial thickness and prediction of a successful external cephalic version.

Science.gov (United States)

Buhimschi, Catalin S; Buhimschi, Irina A; Wehrum, Mark J; Molaskey-Jones, Sherry; Sfakianaki, Anna K; Pettker, Christian M; Thung, Stephen; Campbell, Katherine H; Dulay, Antonette T; Funai, Edmund F; Bahtiyar, Mert O

2011-10-01

To test the hypothesis that myometrial thickness predicts the success of external cephalic version. Abdominal ultrasonographic scans were performed in 114 consecutive pregnant women with breech singletons before an external cephalic version maneuver. Myometrial thickness was measured by a standardized protocol at three sites: the lower segment, midanterior wall, and the fundal uterine wall. Independent variables analyzed in conjunction with myometrial thickness were: maternal age, parity, body mass index, abdominal wall thickness, estimated fetal weight, amniotic fluid index, placental thickness and location, fetal spine position, breech type, and delivery outcomes such as final mode of delivery and birth weight. Successful version was associated with a thicker ultrasonographic fundal myometrium (unsuccessful: 6.7 [5.5-8.4] compared with successful: 7.4 [6.6-9.7] mm, P=.037). Multivariate regression analysis showed that increased fundal myometrial thickness, high amniotic fluid index, and nonfrank breech presentation were the strongest independent predictors of external cephalic version success (Pexternal cephalic versions (fundal myometrial thickness: odds ratio [OR] 2.4, 95% confidence interval [CI] 1.1-5.2, P=.029; amniotic fluid index: OR 2.8, 95% CI 1.3-6.0, P=.008). Combining the two variables resulted in an absolute risk reduction for a failed version of 27.6% (95% CI 7.1-48.1) and a number needed to treat of four (95% CI 2.1-14.2). Fundal myometrial thickness and amniotic fluid index contribute to success of external cephalic version and their evaluation can be easily incorporated in algorithms before the procedure. III.

AssesSeg—A Command Line Tool to Quantify Image Segmentation Quality: A Test Carried Out in Southern Spain from Satellite Imagery

Directory of Open Access Journals (Sweden)

Antonio Novelli

2017-01-01

Full Text Available This letter presents the capabilities of a command line tool created to assess the quality of segmented digital images. The executable source code, called AssesSeg, was written in Python 2.7 using open source libraries. AssesSeg (University of Almeria, Almeria, Spain; Politecnico di Bari, Bari, Italy implements a modified version of the supervised discrepancy measure named Euclidean Distance 2 (ED2 and was tested on different satellite images (Sentinel-2, Landsat 8, and WorldView-2. The segmentation was applied to plastic covered greenhouse detection in the south of Spain (Almería. AssesSeg outputs were utilized to find the best band combinations for the performed segmentations of the images and showed a clear positive correlation between segmentation accuracy and the quantity of available reference data. This demonstrates the importance of a high number of reference data in supervised segmentation accuracy assessment problems.

CLIPS 6.0 - C LANGUAGE INTEGRATED PRODUCTION SYSTEM, VERSION 6.0 (UNIX VERSION)

Science.gov (United States)

Donnell, B.

1994-01-01

COOL (that is, a rule can pattern match on objects created using COOL). CLIPS 6.0 provides the capability to define functions, overloaded functions, and global variables interactively. In addition, CLIPS can be embedded within procedural code, called as a subroutine, and integrated with languages such as C, FORTRAN and Ada. CLIPS can be easily extended by a user through the use of several well-defined protocols. CLIPS provides several delivery options for programs including the ability to generate stand alone executables or to load programs from text or binary files. CLIPS 6.0 provides support for the modular development and execution of knowledge bases with the defmodule construct. CLIPS modules allow a set of constructs to be grouped together such that explicit control can be maintained over restricting the access of the constructs by other modules. This type of control is similar to global and local scoping used in languages such as C or Ada. By restricting access to deftemplate and defclass constructs, modules can function as blackboards, permitting only certain facts and instances to be seen by other modules. Modules are also used by rules to provide execution control. The CRSV (Cross-Reference, Style, and Verification) utility included with previous version of CLIPS is no longer supported. The capabilities provided by this tool are now available directly within CLIPS 6.0 to aid in the development, debugging, and verification of large rule bases. COSMIC offers four distribution versions of CLIPS 6.0: UNIX (MSC-22433), VMS (MSC-22434), MACINTOSH (MSC-22429), and IBM PC (MSC-22430). Executable files, source code, utilities, documentation, and examples are included on the program media. All distribution versions include identical source code for the command line version of CLIPS 6.0. This source code should compile on any platform with an ANSI C compiler. Each distribution version of CLIPS 6.0, except that for the Macintosh platform, includes an executable for the

CLIPS 6.0 - C LANGUAGE INTEGRATED PRODUCTION SYSTEM, VERSION 6.0 (MACINTOSH VERSION)

Science.gov (United States)

Riley, G.

1994-01-01

COOL (that is, a rule can pattern match on objects created using COOL). CLIPS 6.0 provides the capability to define functions, overloaded functions, and global variables interactively. In addition, CLIPS can be embedded within procedural code, called as a subroutine, and integrated with languages such as C, FORTRAN and Ada. CLIPS can be easily extended by a user through the use of several well-defined protocols. CLIPS provides several delivery options for programs including the ability to generate stand alone executables or to load programs from text or binary files. CLIPS 6.0 provides support for the modular development and execution of knowledge bases with the defmodule construct. CLIPS modules allow a set of constructs to be grouped together such that explicit control can be maintained over restricting the access of the constructs by other modules. This type of control is similar to global and local scoping used in languages such as C or Ada. By restricting access to deftemplate and defclass constructs, modules can function as blackboards, permitting only certain facts and instances to be seen by other modules. Modules are also used by rules to provide execution control. The CRSV (Cross-Reference, Style, and Verification) utility included with previous version of CLIPS is no longer supported. The capabilities provided by this tool are now available directly within CLIPS 6.0 to aid in the development, debugging, and verification of large rule bases. COSMIC offers four distribution versions of CLIPS 6.0: UNIX (MSC-22433), VMS (MSC-22434), MACINTOSH (MSC-22429), and IBM PC (MSC-22430). Executable files, source code, utilities, documentation, and examples are included on the program media. All distribution versions include identical source code for the command line version of CLIPS 6.0. This source code should compile on any platform with an ANSI C compiler. Each distribution version of CLIPS 6.0, except that for the Macintosh platform, includes an executable for the

Brookhaven segment interconnect

International Nuclear Information System (INIS)

Morse, W.M.; Benenson, G.; Leipuner, L.B.

1983-01-01

We have performed a high energy physics experiment using a multisegment Brookhaven FASTBUS system. The system was composed of three crate segments and two cable segments. We discuss the segment interconnect module which permits communication between the various segments

Active Segmentation.

Science.gov (United States)

Mishra, Ajay; Aloimonos, Yiannis

2009-01-01

The human visual system observes and understands a scene/image by making a series of fixations. Every fixation point lies inside a particular region of arbitrary shape and size in the scene which can either be an object or just a part of it. We define as a basic segmentation problem the task of segmenting that region containing the fixation point. Segmenting the region containing the fixation is equivalent to finding the enclosing contour- a connected set of boundary edge fragments in the edge map of the scene - around the fixation. This enclosing contour should be a depth boundary.We present here a novel algorithm that finds this bounding contour and achieves the segmentation of one object, given the fixation. The proposed segmentation framework combines monocular cues (color/intensity/texture) with stereo and/or motion, in a cue independent manner. The semantic robots of the immediate future will be able to use this algorithm to automatically find objects in any environment. The capability of automatically segmenting objects in their visual field can bring the visual processing to the next level. Our approach is different from current approaches. While existing work attempts to segment the whole scene at once into many areas, we segment only one image region, specifically the one containing the fixation point. Experiments with real imagery collected by our active robot and from the known databases 1 demonstrate the promise of the approach.

GeoSegmenter: A statistically learned Chinese word segmenter for the geoscience domain

Science.gov (United States)

Huang, Lan; Du, Youfu; Chen, Gongyang

2015-03-01

Unlike English, the Chinese language has no space between words. Segmenting texts into words, known as the Chinese word segmentation (CWS) problem, thus becomes a fundamental issue for processing Chinese documents and the first step in many text mining applications, including information retrieval, machine translation and knowledge acquisition. However, for the geoscience subject domain, the CWS problem remains unsolved. Although a generic segmenter can be applied to process geoscience documents, they lack the domain specific knowledge and consequently their segmentation accuracy drops dramatically. This motivated us to develop a segmenter specifically for the geoscience subject domain: the GeoSegmenter. We first proposed a generic two-step framework for domain specific CWS. Following this framework, we built GeoSegmenter using conditional random fields, a principled statistical framework for sequence learning. Specifically, GeoSegmenter first identifies general terms by using a generic baseline segmenter. Then it recognises geoscience terms by learning and applying a model that can transform the initial segmentation into the goal segmentation. Empirical experimental results on geoscience documents and benchmark datasets showed that GeoSegmenter could effectively recognise both geoscience terms and general terms.

Multi-View Multi-Instance Learning Based on Joint Sparse Representation and Multi-View Dictionary Learning.

Science.gov (United States)

Li, Bing; Yuan, Chunfeng; Xiong, Weihua; Hu, Weiming; Peng, Houwen; Ding, Xinmiao; Maybank, Steve

2017-12-01

In multi-instance learning (MIL), the relations among instances in a bag convey important contextual information in many applications. Previous studies on MIL either ignore such relations or simply model them with a fixed graph structure so that the overall performance inevitably degrades in complex environments. To address this problem, this paper proposes a novel multi-view multi-instance learning algorithm (MIL) that combines multiple context structures in a bag into a unified framework. The novel aspects are: (i) we propose a sparse -graph model that can generate different graphs with different parameters to represent various context relations in a bag, (ii) we propose a multi-view joint sparse representation that integrates these graphs into a unified framework for bag classification, and (iii) we propose a multi-view dictionary learning algorithm to obtain a multi-view graph dictionary that considers cues from all views simultaneously to improve the discrimination of the MIL. Experiments and analyses in many practical applications prove the effectiveness of the M IL.

Single-segment and double-segment INTACS for post-LASIK ectasia.

Directory of Open Access Journals (Sweden)

Hassan Hashemi

2014-09-01

Full Text Available The objective of the present study was to compare single segment and double segment INTACS rings in the treatment of post-LASIK ectasia. In this interventional study, 26 eyes with post-LASIK ectasia were assessed. Ectasia was defined as progressive myopia regardless of astigmatism, along with topographic evidence of inferior steepening of the cornea after LASIK. We excluded those with a history of intraocular surgery, certain eye conditions, and immune disorders, as well as monocular, pregnant and lactating patients. A total of 11 eyes had double ring and 15 eyes had single ring implantation. Visual and refractive outcomes were compared with preoperative values based on the number of implanted INTACS rings. Pre and postoperative spherical equivalent were -3.92 and -2.29 diopter (P=0.007. The spherical equivalent decreased by 1 ± 3.2 diopter in the single-segment group and 2.56 ± 1.58 diopter in the double-segment group (P=0.165. Mean preoperative astigmatism was 2.38 ± 1.93 diopter which decreased to 2.14 ± 1.1 diopter after surgery (P=0.508; 0.87 ± 1.98 diopter decrease in the single-segment group and 0.67 ± 1.2 diopter increase in the double-segment group (P=0.025. Nineteen patients (75% gained one or two lines, and only three, who were all in the double-segment group, lost one or two lines of best corrected visual acuity. The spherical equivalent and vision significantly decreased in all patients. In these post-LASIK ectasia patients, the spherical equivalent was corrected better with two segments compared to single segment implantation; nonetheless, the level of astigmatism in the single-segment group was significantly better than that in the double-segment group.

First validation of the new continuous energy version of the MORET5 Monte Carlo code

International Nuclear Information System (INIS)

Miss, Joachim; Bernard, Franck; Forestier, Benoit; Haeck, Wim; Richet, Yann; Jacquet, Olivier

2008-01-01

The 5.A.1 version is the next release of the MORET Monte Carlo code dedicated to criticality and reactor calculations. This new version combines all the capabilities that are already available in the multigroup version with many new and enhanced features. The main capabilities of the previous version are the powerful association of a deterministic and Monte Carlo approach (like for instance APOLLO-MORET), the modular geometry, five source sampling techniques and two simulation strategies. The major advance in MORET5 is the ability to perform calculations either a multigroup or a continuous energy simulation. Thanks to these new developments, we now have better control over the whole process of criticality calculations, from reading the basic nuclear data to the Monte Carlo simulation itself. Moreover, this new capability enables us to better validate the deterministic-Monte Carlo multigroup calculations by performing continuous energy calculations with the same code, using the same geometry and tracking algorithms. The aim of this paper is to describe the main options available in this new release, and to present the first results. Comparisons of the MORET5 continuous-energy results with experimental measurements and against another continuous-energy Monte Carlo code are provided in terms of validation and time performance. Finally, an analysis of the interest of using a unified energy grid for continuous energy Monte Carlo calculations is presented. (authors)

Detection of plant leaf diseases using image segmentation and soft computing techniques

Directory of Open Access Journals (Sweden)

Vijai Singh

2017-03-01

Full Text Available Agricultural productivity is something on which economy highly depends. This is the one of the reasons that disease detection in plants plays an important role in agriculture field, as having disease in plants are quite natural. If proper care is not taken in this area then it causes serious effects on plants and due to which respective product quality, quantity or productivity is affected. For instance a disease named little leaf disease is a hazardous disease found in pine trees in United States. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself it detects the symptoms of diseases i.e. when they appear on plant leaves. This paper presents an algorithm for image segmentation technique which is used for automatic detection and classification of plant leaf diseases. It also covers survey on different diseases classification techniques that can be used for plant leaf disease detection. Image segmentation, which is an important aspect for disease detection in plant leaf disease, is done by using genetic algorithm.

Glenoid version by CT scan: an analysis of clinical measurement error and introduction of a protocol to reduce variability

Energy Technology Data Exchange (ETDEWEB)

Bunt, Fabian van de [VU University Medical Center, Amsterdam (Netherlands); Pearl, Michael L.; Lee, Eric K.; Peng, Lauren; Didomenico, Paul [Kaiser Permanente, Los Angeles, CA (United States)

2015-11-15

Recent studies have challenged the accuracy of conventional measurements of glenoid version. Variability in the orientation of the scapula from individual anatomical differences and patient positioning, combined with differences in observer measurement practices, have been identified as sources of variability. The purpose of this study was to explore the utility and reliability of clinically available software that allows manipulation of three-dimensional images in order to bridge the variance between clinical and anatomic version in a clinical setting. Twenty CT scans of normal glenoids of patients who had proximal humerus fractures were measured for version. Four reviewers first measured version in a conventional manner (clinical version), measurements were made again (anatomic version) after employing a protocol for reformatting the CT data to align the coronal and sagittal planes with the superior-inferior axis of the glenoid, and the scapular body, respectively. The average value of clinical retroversion for all reviewers and all subjects was -1.4 (range, -16 to 21 ), as compared to -3.2 (range, -21 to 6 ) when measured from reformatted images. The mean difference between anatomical and clinical version was 1.9 ± 5.6 but ranged on individual measurements from -13 to 26 . In no instance did all four observers choose the same image slice from the sequence of images. This study confirmed the variation in glenoid version dependent on scapular orientation previously identified in other studies using scapular models, and presents a clinically accessible protocol to correct for scapular orientation from the patient's CT data. (orig.)

Glenoid version by CT scan: an analysis of clinical measurement error and introduction of a protocol to reduce variability

International Nuclear Information System (INIS)

Bunt, Fabian van de; Pearl, Michael L.; Lee, Eric K.; Peng, Lauren; Didomenico, Paul

2015-01-01

Recent studies have challenged the accuracy of conventional measurements of glenoid version. Variability in the orientation of the scapula from individual anatomical differences and patient positioning, combined with differences in observer measurement practices, have been identified as sources of variability. The purpose of this study was to explore the utility and reliability of clinically available software that allows manipulation of three-dimensional images in order to bridge the variance between clinical and anatomic version in a clinical setting. Twenty CT scans of normal glenoids of patients who had proximal humerus fractures were measured for version. Four reviewers first measured version in a conventional manner (clinical version), measurements were made again (anatomic version) after employing a protocol for reformatting the CT data to align the coronal and sagittal planes with the superior-inferior axis of the glenoid, and the scapular body, respectively. The average value of clinical retroversion for all reviewers and all subjects was -1.4 (range, -16 to 21 ), as compared to -3.2 (range, -21 to 6 ) when measured from reformatted images. The mean difference between anatomical and clinical version was 1.9 ± 5.6 but ranged on individual measurements from -13 to 26 . In no instance did all four observers choose the same image slice from the sequence of images. This study confirmed the variation in glenoid version dependent on scapular orientation previously identified in other studies using scapular models, and presents a clinically accessible protocol to correct for scapular orientation from the patient's CT data. (orig.)

A medley of meanings: Insights from an instance of gameplay in League of Legends

Directory of Open Access Journals (Sweden)

Max Watson

2015-06-01

Full Text Available This article engages with the notion of insightful gameplay. It recounts debates about what, if anything, makes play meaningful. Through these, it contends that while some games are explicitly designed to foster insightful gameplay, most are not and many might even be considered utterly meaningless. It notes how discussions about what makes playing games meaningful raise concomitant questions about what playing means. It then strives to reconcile these two interrelated questions by offering the notion of a medley of meanings. A medley of meanings is the notion that each player brings their own subjective disposition to playing to a particular instance of gameplay; no participant to gameplay should be considered as in a state that is “not playing”. Because these subjective dispositions to playing can be quite divergent, players can and often do clash in instances of gameplay. This article then contends that these clashes can in turn render the most seemingly meaningless games potential hotbeds of insightful gameplay. The second half of this article discusses the ethnographic example of an instance of gameplay in the digital game League of Legends in order to explicate the notion of a medley of meanings.

Classification and Weakly Supervised Pain Localization using Multiple Segment Representation.

Science.gov (United States)

Sikka, Karan; Dhall, Abhinav; Bartlett, Marian Stewart

2014-10-01

Automatic pain recognition from videos is a vital clinical application and, owing to its spontaneous nature, poses interesting challenges to automatic facial expression recognition (AFER) research. Previous pain vs no-pain systems have highlighted two major challenges: (1) ground truth is provided for the sequence, but the presence or absence of the target expression for a given frame is unknown, and (2) the time point and the duration of the pain expression event(s) in each video are unknown. To address these issues we propose a novel framework (referred to as MS-MIL) where each sequence is represented as a bag containing multiple segments, and multiple instance learning (MIL) is employed to handle this weakly labeled data in the form of sequence level ground-truth. These segments are generated via multiple clustering of a sequence or running a multi-scale temporal scanning window, and are represented using a state-of-the-art Bag of Words (BoW) representation. This work extends the idea of detecting facial expressions through 'concept frames' to 'concept segments' and argues through extensive experiments that algorithms such as MIL are needed to reap the benefits of such representation. The key advantages of our approach are: (1) joint detection and localization of painful frames using only sequence-level ground-truth, (2) incorporation of temporal dynamics by representing the data not as individual frames but as segments, and (3) extraction of multiple segments, which is well suited to signals with uncertain temporal location and duration in the video. Extensive experiments on UNBC-McMaster Shoulder Pain dataset highlight the effectiveness of the approach by achieving competitive results on both tasks of pain classification and localization in videos. We also empirically evaluate the contributions of different components of MS-MIL. The paper also includes the visualization of discriminative facial patches, important for pain detection, as discovered by our

CLIPS 6.0 - C LANGUAGE INTEGRATED PRODUCTION SYSTEM, VERSION 6.0 (IBM PC VERSION)

Science.gov (United States)

Donnell, B.

1994-01-01

COOL (that is, a rule can pattern match on objects created using COOL). CLIPS 6.0 provides the capability to define functions, overloaded functions, and global variables interactively. In addition, CLIPS can be embedded within procedural code, called as a subroutine, and integrated with languages such as C, FORTRAN and Ada. CLIPS can be easily extended by a user through the use of several well-defined protocols. CLIPS provides several delivery options for programs including the ability to generate stand alone executables or to load programs from text or binary files. CLIPS 6.0 provides support for the modular development and execution of knowledge bases with the defmodule construct. CLIPS modules allow a set of constructs to be grouped together such that explicit control can be maintained over restricting the access of the constructs by other modules. This type of control is similar to global and local scoping used in languages such as C or Ada. By restricting access to deftemplate and defclass constructs, modules can function as blackboards, permitting only certain facts and instances to be seen by other modules. Modules are also used by rules to provide execution control. The CRSV (Cross-Reference, Style, and Verification) utility included with previous version of CLIPS is no longer supported. The capabilities provided by this tool are now available directly within CLIPS 6.0 to aid in the development, debugging, and verification of large rule bases. COSMIC offers four distribution versions of CLIPS 6.0: UNIX (MSC-22433), VMS (MSC-22434), MACINTOSH (MSC-22429), and IBM PC (MSC-22430). Executable files, source code, utilities, documentation, and examples are included on the program media. All distribution versions include identical source code for the command line version of CLIPS 6.0. This source code should compile on any platform with an ANSI C compiler. Each distribution version of CLIPS 6.0, except that for the Macintosh platform, includes an executable for the

Accounting for segment correlations in segmented gamma-ray scans

International Nuclear Information System (INIS)

Sheppard, G.A.; Prettyman, T.H.; Piquette, E.C.

1994-01-01

In a typical segmented gamma-ray scanner (SGS), the detector's field of view is collimated so that a complete horizontal slice or segment of the desired thickness is visible. Ordinarily, the collimator is not deep enough to exclude gamma rays emitted from sample volumes above and below the segment aligned with the collimator. This can lead to assay biases, particularly for certain radioactive-material distributions. Another consequence of the collimator's low aspect ratio is that segment assays at the top and bottom of the sample are biased low because the detector's field of view is not filled. This effect is ordinarily countered by placing the sample on a low-Z pedestal and scanning one or more segment thicknesses below and above the sample. This takes extra time, however, We have investigated a number of techniques that both account for correlated segments and correct for end effects in SGS assays. Also, we have developed an algorithm that facilitates estimates of assay precision. Six calculation methods have been compared by evaluating the results of thousands of simulated, assays for three types of gamma-ray source distribution and ten masses. We will report on these computational studies and their experimental verification

Synergistic Instance-Level Subspace Alignment for Fine-Grained Sketch-Based Image Retrieval.

Science.gov (United States)

Li, Ke; Pang, Kaiyue; Song, Yi-Zhe; Hospedales, Timothy M; Xiang, Tao; Zhang, Honggang

2017-08-25

We study the problem of fine-grained sketch-based image retrieval. By performing instance-level (rather than category-level) retrieval, it embodies a timely and practical application, particularly with the ubiquitous availability of touchscreens. Three factors contribute to the challenging nature of the problem: (i) free-hand sketches are inherently abstract and iconic, making visual comparisons with photos difficult, (ii) sketches and photos are in two different visual domains, i.e. black and white lines vs. color pixels, and (iii) fine-grained distinctions are especially challenging when executed across domain and abstraction-level. To address these challenges, we propose to bridge the image-sketch gap both at the high-level via parts and attributes, as well as at the low-level, via introducing a new domain alignment method. More specifically, (i) we contribute a dataset with 304 photos and 912 sketches, where each sketch and image is annotated with its semantic parts and associated part-level attributes. With the help of this dataset, we investigate (ii) how strongly-supervised deformable part-based models can be learned that subsequently enable automatic detection of part-level attributes, and provide pose-aligned sketch-image comparisons. To reduce the sketch-image gap when comparing low-level features, we also (iii) propose a novel method for instance-level domain-alignment, that exploits both subspace and instance-level cues to better align the domains. Finally (iv) these are combined in a matching framework integrating aligned low-level features, mid-level geometric structure and high-level semantic attributes. Extensive experiments conducted on our new dataset demonstrate effectiveness of the proposed method.

Fast Segmentation From Blurred Data in 3D Fluorescence Microscopy.

Science.gov (United States)

Storath, Martin; Rickert, Dennis; Unser, Michael; Weinmann, Andreas

2017-10-01

We develop a fast algorithm for segmenting 3D images from linear measurements based on the Potts model (or piecewise constant Mumford-Shah model). To that end, we first derive suitable space discretizations of the 3D Potts model, which are capable of dealing with 3D images defined on non-cubic grids. Our discretization allows us to utilize a specific splitting approach, which results in decoupled subproblems of moderate size. The crucial point in the 3D setup is that the number of independent subproblems is so large that we can reasonably exploit the parallel processing capabilities of the graphics processing units (GPUs). Our GPU implementation is up to 18 times faster than the sequential CPU version. This allows to process even large volumes in acceptable runtimes. As a further contribution, we extend the algorithm in order to deal with non-negativity constraints. We demonstrate the efficiency of our method for combined image deconvolution and segmentation on simulated data and on real 3D wide field fluorescence microscopy data.

Spotting Separator Points at Line Terminals in Compressed Document Images for Text-line Segmentation

OpenAIRE

R, Amarnath; Nagabhushan, P.

2017-01-01

Line separators are used to segregate text-lines from one another in document image analysis. Finding the separator points at every line terminal in a document image would enable text-line segmentation. In particular, identifying the separators in handwritten text could be a thrilling exercise. Obviously it would be challenging to perform this in the compressed version of a document image and that is the proposed objective in this research. Such an effort would prevent the computational burde...

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.

Hydrophilic segmented block copolymers based on poly(ethylene oxide) and monodisperse amide segments

NARCIS (Netherlands)

Husken, D.; Feijen, Jan; Gaymans, R.J.

2007-01-01

Segmented block copolymers based on poly(ethylene oxide) (PEO) flexible segments and monodisperse crystallizable bisester tetra-amide segments were made via a polycondensation reaction. The molecular weight of the PEO segments varied from 600 to 4600 g/mol and a bisester tetra-amide segment (T6T6T)

Image annotation based on positive-negative instances learning

Science.gov (United States)

Zhang, Kai; Hu, Jiwei; Liu, Quan; Lou, Ping

2017-07-01

Automatic image annotation is now a tough task in computer vision, the main sense of this tech is to deal with managing the massive image on the Internet and assisting intelligent retrieval. This paper designs a new image annotation model based on visual bag of words, using the low level features like color and texture information as well as mid-level feature as SIFT, and mixture the pic2pic, label2pic and label2label correlation to measure the correlation degree of labels and images. We aim to prune the specific features for each single label and formalize the annotation task as a learning process base on Positive-Negative Instances Learning. Experiments are performed using the Corel5K Dataset, and provide a quite promising result when comparing with other existing methods.

Spinal segmental dysgenesis

Directory of Open Access Journals (Sweden)

N Mahomed

2009-06-01

Full Text Available Spinal segmental dysgenesis is a rare congenital spinal abnormality , seen in neonates and infants in which a segment of the spine and spinal cord fails to develop normally . The condition is segmental with normal vertebrae above and below the malformation. This condition is commonly associated with various abnormalities that affect the heart, genitourinary, gastrointestinal tract and skeletal system. We report two cases of spinal segmental dysgenesis and the associated abnormalities.

Automatic speech signal segmentation based on the innovation adaptive filter

Directory of Open Access Journals (Sweden)

Makowski Ryszard

2014-06-01

Full Text Available Speech segmentation is an essential stage in designing automatic speech recognition systems and one can find several algorithms proposed in the literature. It is a difficult problem, as speech is immensely variable. The aim of the authors’ studies was to design an algorithm that could be employed at the stage of automatic speech recognition. This would make it possible to avoid some problems related to speech signal parametrization. Posing the problem in such a way requires the algorithm to be capable of working in real time. The only such algorithm was proposed by Tyagi et al., (2006, and it is a modified version of Brandt’s algorithm. The article presents a new algorithm for unsupervised automatic speech signal segmentation. It performs segmentation without access to information about the phonetic content of the utterances, relying exclusively on second-order statistics of a speech signal. The starting point for the proposed method is time-varying Schur coefficients of an innovation adaptive filter. The Schur algorithm is known to be fast, precise, stable and capable of rapidly tracking changes in second order signal statistics. A transfer from one phoneme to another in the speech signal always indicates a change in signal statistics caused by vocal track changes. In order to allow for the properties of human hearing, detection of inter-phoneme boundaries is performed based on statistics defined on the mel spectrum determined from the reflection coefficients. The paper presents the structure of the algorithm, defines its properties, lists parameter values, describes detection efficiency results, and compares them with those for another algorithm. The obtained segmentation results, are satisfactory.

CLIPS 6.0 - C LANGUAGE INTEGRATED PRODUCTION SYSTEM, VERSION 6.0 (DEC VAX VMS VERSION)

Science.gov (United States)

Donnell, B.

1994-01-01

COOL (that is, a rule can pattern match on objects created using COOL). CLIPS 6.0 provides the capability to define functions, overloaded functions, and global variables interactively. In addition, CLIPS can be embedded within procedural code, called as a subroutine, and integrated with languages such as C, FORTRAN and Ada. CLIPS can be easily extended by a user through the use of several well-defined protocols. CLIPS provides several delivery options for programs including the ability to generate stand alone executables or to load programs from text or binary files. CLIPS 6.0 provides support for the modular development and execution of knowledge bases with the defmodule construct. CLIPS modules allow a set of constructs to be grouped together such that explicit control can be maintained over restricting the access of the constructs by other modules. This type of control is similar to global and local scoping used in languages such as C or Ada. By restricting access to deftemplate and defclass constructs, modules can function as blackboards, permitting only certain facts and instances to be seen by other modules. Modules are also used by rules to provide execution control. The CRSV (Cross-Reference, Style, and Verification) utility included with previous version of CLIPS is no longer supported. The capabilities provided by this tool are now available directly within CLIPS 6.0 to aid in the development, debugging, and verification of large rule bases. COSMIC offers four distribution versions of CLIPS 6.0: UNIX (MSC-22433), VMS (MSC-22434), MACINTOSH (MSC-22429), and IBM PC (MSC-22430). Executable files, source code, utilities, documentation, and examples are included on the program media. All distribution versions include identical source code for the command line version of CLIPS 6.0. This source code should compile on any platform with an ANSI C compiler. Each distribution version of CLIPS 6.0, except that for the Macintosh platform, includes an executable for the

A prosthesis-specific multi-link segment model of lower-limb amputee sprinting.

Science.gov (United States)

Rigney, Stacey M; Simmons, Anne; Kark, Lauren

2016-10-03

Lower-limb amputees commonly utilize non-articulating energy storage and return (ESAR) prostheses for high impact activities such as sprinting. Despite these prostheses lacking an articulating ankle joint, amputee gait analysis conventionally features a two-link segment model of the prosthetic foot. This paper investigated the effects of the selected link segment model׳s marker-set and geometry on a unilateral amputee sprinter׳s calculated lower-limb kinematics, kinetics and energetics. A total of five lower-limb models of the Ottobock ® 1E90 Sprinter were developed, including two conventional shank-foot models that each used a different version of the Plug-in-Gait (PiG) marker-set to test the effect of prosthesis ankle marker location. Two Hybrid prosthesis-specific models were then developed, also using the PiG marker-sets, with the anatomical shank and foot replaced by prosthesis-specific geometry separated into two segments. Finally, a Multi-link segment (MLS) model was developed, consisting of six segments for the prosthesis as defined by a custom marker-set. All full-body musculoskeletal models were tested using four trials of experimental marker trajectories within OpenSim 3.2 (Stanford, California, USA) to find the affected and unaffected hip, knee and ankle kinematics, kinetics and energetics. The geometry of the selected lower-limb prosthesis model was found to significantly affect all variables on the affected leg (p prosthesis-specific spatial, inertial and elastic properties from full-body models significantly affects the calculated amputee gait characteristics, and we therefore recommend the implementation of a MLS model. Copyright © 2016 Elsevier Ltd. All rights reserved.

A method and software for segmentation of anatomic object ensembles by deformable m-reps

International Nuclear Information System (INIS)

Pizer, Stephen M.; Fletcher, P. Thomas; Joshi, Sarang; Gash, A. Graham; Stough, Joshua; Thall, Andrew; Tracton, Gregg; Chaney, Edward L.

2005-01-01

Deformable shape models (DSMs) comprise a general approach that shows great promise for automatic image segmentation. Published studies by others and our own research results strongly suggest that segmentation of a normal or near-normal object from 3D medical images will be most successful when the DSM approach uses (1) knowledge of the geometry of not only the target anatomic object but also the ensemble of objects providing context for the target object and (2) knowledge of the image intensities to be expected relative to the geometry of the target and contextual objects. The segmentation will be most efficient when the deformation operates at multiple object-related scales and uses deformations that include not just local translations but the biologically important transformations of bending and twisting, i.e., local rotation, and local magnification. In computer vision an important class of DSM methods uses explicit geometric models in a Bayesian statistical framework to provide a priori information used in posterior optimization to match the DSM against a target image. In this approach a DSM of the object to be segmented is placed in the target image data and undergoes a series of rigid and nonrigid transformations that deform the model to closely match the target object. The deformation process is driven by optimizing an objective function that has terms for the geometric typicality and model-to-image match for each instance of the deformed model. The success of this approach depends strongly on the object representation, i.e., the structural details and parameter set for the DSM, which in turn determines the analytic form of the objective function. This paper describes a form of DSM called m-reps that has or allows these properties, and a method of segmentation consisting of large to small scale posterior optimization of m-reps. Segmentation by deformable m-reps, together with the appropriate data representations, visualizations, and user interface, has been

Instances of Use of United States Armed Forces Abroad, 1798-2014

Science.gov (United States)

2014-09-15

Garcia, and Thomas J. Nicola . Instances of Use of United States Armed Forces Abroad, 1798-2014 Congressional Research Service Contents...landing zones near the U.S. Embassy in Saigon and the Tan Son Nhut Airfield. Mayaguez incident. On May 15, 1975, President Ford reported he had ordered...Report R41989, Congressional Authority to Limit Military Operations, by Jennifer K. Elsea, Michael John Garcia and Thomas J. Nicola . CRS Report R43344

Automatic segmentation of thoracic and pelvic CT images for radiotherapy planning using implicit anatomic knowledge and organ-specific segmentation strategies

International Nuclear Information System (INIS)

Haas, B; Coradi, T; Scholz, M; Kunz, P; Huber, M; Oppitz, U; Andre, L; Lengkeek, V; Huyskens, D; Esch, A van; Reddick, R

2008-01-01

Automatic segmentation of anatomical structures in medical images is a valuable tool for efficient computer-aided radiotherapy and surgery planning and an enabling technology for dynamic adaptive radiotherapy. This paper presents the design, algorithms and validation of new software for the automatic segmentation of CT images used for radiotherapy treatment planning. A coarse to fine approach is followed that consists of presegmentation, anatomic orientation and structure segmentation. No user input or a priori information about the image content is required. In presegmentation, the body outline, the bones and lung equivalent tissue are detected. Anatomic orientation recognizes the patient's position, orientation and gender and creates an elastic mapping of the slice positions to a reference scale. Structure segmentation is divided into localization, outlining and refinement, performed by procedures with implicit anatomic knowledge using standard image processing operations. The presented version of algorithms automatically segments the body outline and bones in any gender and patient position, the prostate, bladder and femoral heads for male pelvis in supine position, and the spinal canal, lungs, heart and trachea in supine position. The software was developed and tested on a collection of over 600 clinical radiotherapy planning CT stacks. In a qualitative validation on this test collection, anatomic orientation correctly detected gender, patient position and body region in 98% of the cases, a correct mapping was produced for 89% of thorax and 94% of pelvis cases. The average processing time for the entire segmentation of a CT stack was less than 1 min on a standard personal computer. Two independent retrospective studies were carried out for clinical validation. Study I was performed on 66 cases (30 pelvis, 36 thorax) with dosimetrists, study II on 52 cases (39 pelvis, 13 thorax) with radio-oncologists as experts. The experts rated the automatically produced

Automatic Melody Segmentation

NARCIS (Netherlands)

Rodríguez López, Marcelo

2016-01-01

The work presented in this dissertation investigates music segmentation. In the field of Musicology, segmentation refers to a score analysis technique, whereby notated pieces or passages of these pieces are divided into “units” referred to as sections, periods, phrases, and so on. Segmentation

HyDR-MI : A hybrid algorithm to reduce dimensionality in multiple instance learning

NARCIS (Netherlands)

Zafra, A.; Pechenizkiy, M.; Ventura, S.

2013-01-01

Feature selection techniques have been successfully applied in many applications for making supervised learning more effective and efficient. These techniques have been widely used and studied in traditional supervised learning settings, where each instance is expected to have a label. In multiple

Deictic Reference as a Means for Constructing the Character Image in a Dubbed Cartoon Snow Postman: Comparative Analysis of the Lithuanian, Russian and English Versions

Directory of Open Access Journals (Sweden)

Danguolė Satkauskaitė

2015-06-01

Full Text Available The article aims at examining how the main character Snowman’s image is constructed by applying an abundant number of deictic expressions in the Lithuanian, Russian and English versions of the cartoon Snow Postman. The research was based on M. Consten’s conception of direct and indirect reference and the model of visual-verbal cohesion proposed by N. Baumgarten. The study has revealed that in both, Russian and Lithuanian versions of the cartoon, the main character’s dialogues are loaded with deictic expressions which mark the same referents. In this way, the main character is shaped as a dull, forgetful being, unable to store and process a huge amount of information in his head. In the English version, deictic instances are sparsely used, thus the character image is quite different here: the snowman is less absent-minded and fuzzy.

Reversing Kristeva's first instance of abjection: the formation of self reconsidered.

Science.gov (United States)

McCabe, Janet L; Holmes, Dave

2011-03-01

Psychoanalyst Julia Kristeva defines the theoretical concept of abjection as an unconscious defence mechanism used to protect the self against threats to one's subjectivity. Kristeva suggests that the first instance of abjection in an individual's life occurs when the child abjects the mother. However, the instance of abjection addressed within this paper is the reverse of this: the abjection of the child, with a disability, by the parent, and more broadly society. Using the contemporary example of prenatal testing, the authors explore how parents of children with disabilities may be influenced in abjecting the child. The implications of abjection of the child are then used to explore normalization, routinization of care and the development of standardized care practices within health-care. Prenatal screening practices and standardized care permeate medical obstetric care and social discourses regarding pregnancy and childbirth, thereby affecting not only healthcare professionals but also parents in their position as consumers of health-care. In a time when the focus of health-care is increasingly placed on disease prevention and broader medical and social discourses glorify normalcy and consistency, the unconscious abjection of those that do not fit within these standards must be identified and addressed. © 2011 Blackwell Publishing Ltd.

Differences in axial segment reorientation during standing turns predict multiple falls in older adults

OpenAIRE

Wright, Rachel L.; Peters, Derek M.; Robinson, Paul D.; Sitch, Alice J.; Watt, Thomas N.; Hollands, Mark A.

2012-01-01

Author's version of an article in the journal: Gait and Posture. Also available from the publisher at: http://dx.doi.org/10.1016/j.gaitpost.2012.05.013 Background: The assessment of standing turning performance is proposed to predict fall risk in older adults. This study investigated differences in segmental coordination during a 360° standing turn task between older community-dwelling fallers and non-fallers. Methods: Thirty-five older adults age mean (SD) of 71 (5.4) years performed 360°...

Microsoft and the Court of First Instance: What Does it All Mean?

OpenAIRE

Renata Hesse

2007-01-01

As someone who has spent a considerable portion of the last five years working on issues involving Microsoft’s conduct and the competition laws, I read with interest the commentary that followed the issuance of the Court of First Instance’s decision on September 17.

Segmented trapped vortex cavity

Science.gov (United States)

Grammel, Jr., Leonard Paul (Inventor); Pennekamp, David Lance (Inventor); Winslow, Jr., Ralph Henry (Inventor)

2010-01-01

An annular trapped vortex cavity assembly segment comprising includes a cavity forward wall, a cavity aft wall, and a cavity radially outer wall there between defining a cavity segment therein. A cavity opening extends between the forward and aft walls at a radially inner end of the assembly segment. Radially spaced apart pluralities of air injection first and second holes extend through the forward and aft walls respectively. The segment may include first and second expansion joint features at distal first and second ends respectively of the segment. The segment may include a forward subcomponent including the cavity forward wall attached to an aft subcomponent including the cavity aft wall. The forward and aft subcomponents include forward and aft portions of the cavity radially outer wall respectively. A ring of the segments may be circumferentially disposed about an axis to form an annular segmented vortex cavity assembly.

Performance Analysis of Segmentation of Hyperspectral Images Based on Color Image Segmentation

Directory of Open Access Journals (Sweden)

Praveen Agarwal

2017-06-01

Full Text Available Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without texture. The final segmentation is simply achieved by a spatially color segmentation using feature vector with the set of color values contained around the pixel to be classified with some mathematical equations. The spatial constraint allows taking into account the inherent spatial relationships of any image and its color. This approach provides effective PSNR for the segmented image. These results have the better performance as the segmented images are compared with Watershed & Region Growing Algorithm and provide effective segmentation for the Spectral Images & Medical Images.

Multi-Instance Quotation System (SaaS) Based on Docker Containerizing Platform

OpenAIRE

Shekhamis, Anass

2016-01-01

This thesis covers the development of a quotation system that is built as a multi-instance SaaS. Quotation systems usually come as part of customer relationship management systems, but not necessarily included. They also tend to have invoicing alongside the original functionality; creating quotations for customers. The system uses Microservices Architecture were each service is a replaceable and upgradeable component that achieve certain functionality and easily integrate with other third-par...

Simultaneous segmentation of retinal surfaces and microcystic macular edema in SDOCT volumes

Science.gov (United States)

Antony, Bhavna J.; Lang, Andrew; Swingle, Emily K.; Al-Louzi, Omar; Carass, Aaron; Solomon, Sharon; Calabresi, Peter A.; Saidha, Shiv; Prince, Jerry L.

2016-03-01

Optical coherence tomography (OCT) is a noninvasive imaging modality that has begun to find widespread use in retinal imaging for the detection of a variety of ocular diseases. In addition to structural changes in the form of altered retinal layer thicknesses, pathological conditions may also cause the formation of edema within the retina. In multiple sclerosis, for instance, the nerve fiber and ganglion cell layers are known to thin. Additionally, the formation of pseudocysts called microcystic macular edema (MME) have also been observed in the eyes of about 5% of MS patients, and its presence has been shown to be correlated with disease severity. Previously, we proposed separate algorithms for the segmentation of retinal layers and MME, but since MME mainly occurs within specific regions of the retina, a simultaneous approach is advantageous. In this work, we propose an automated globally optimal graph-theoretic approach that simultaneously segments the retinal layers and the MME in volumetric OCT scans. SD-OCT scans from one eye of 12 MS patients with known MME and 8 healthy controls were acquired and the pseudocysts manually traced. The overall precision and recall of the pseudocyst detection was found to be 86.0% and 79.5%, respectively.

The Syriac versions of Old Testament quotations in Matthew

Directory of Open Access Journals (Sweden)

Herrie F. van Rooy

2015-12-01

Full Text Available In the Gospel of Matthew 10 quotations from the Old Testament are introduced by a formula containing the verb πληροῦν. This article explores the rendering of 9 of these 10 quotations in 3 Syriac versions of the New Testament, namely the Peshitta and the 2 versions of the Old Syriac Gospels (Sinaiticus and Curetonianus. The question addressed is the relationship of the Syriac versions to one another, to the Peshitta of the Old Testament and to the Greek Gospel. For the quotations in Matthew, their relationship to the Hebrew and Greek Old Testament is very important. In the quotations discussed, the Greek New Testament did not make much use of the Septuagint as it is known today. The Old Testament Peshitta influenced the Old Syriac, but not to the same extent in all instances. This influence could have been through Tatian’s Diatessaron. Tatian probably used the text of the Old Testament Peshitta for the quotations of the Old Testament in the gospels. In instances where the Curetonianus and the Sinaiticus differ, it could demonstrate attempts to bring the text closer to the Greek New Testament. The New Testament Peshitta normally started with a text close to the Old Syriac, but frequently adapted it to bring it closer to New Testament Greek. Die Siriese weergawes van die Ou-Testamentiese aanhalings in Matteus. Die Evangelie van Matteus het 10 aanhalings uit die Ou Testament wat deur ’n formule met die werkwoord, πληροῦν, ingelei word. Hierdie artikel ondersoek die weergawe van 9 van die 10 aanhalings in drie Siriese weergawes van die Nuwe Testament, naamlik die Peshitta en die twee weergawes van die Ou Siriese Evangelies (Sinaiticus en Curetonianus. Die vraagstuk handel oor dieverhouding van die drie Siriese weergawes tot mekaar, tot die Peshitta van die Ou Testament en die Griekse Evangelie. Vir die aanhalings in Matteus is hulle verhouding tot die Hebreeuse e Griekse Ou Testament baie belangrik. In die aanhalings wat bespreek

Segmental Vitiligo.

Science.gov (United States)

van Geel, Nanja; Speeckaert, Reinhart

2017-04-01

Segmental vitiligo is characterized by its early onset, rapid stabilization, and unilateral distribution. Recent evidence suggests that segmental and nonsegmental vitiligo could represent variants of the same disease spectrum. Observational studies with respect to its distribution pattern point to a possible role of cutaneous mosaicism, whereas the original stated dermatomal distribution seems to be a misnomer. Although the exact pathogenic mechanism behind the melanocyte destruction is still unknown, increasing evidence has been published on the autoimmune/inflammatory theory of segmental vitiligo. Copyright © 2016 Elsevier Inc. All rights reserved.

Segmental vitiligo with segmental morphea: An autoimmune link?

Directory of Open Access Journals (Sweden)

Pravesh Yadav

2014-01-01

Full Text Available An 18-year old girl with segmental vitiligo involving the left side of the trunk and left upper limb with segmental morphea involving the right side of trunk and right upper limb without any deeper involvement is illustrated. There was no history of preceding drug intake, vaccination, trauma, radiation therapy, infection, or hormonal therapy. Family history of stable vitiligo in her brother and a history of type II diabetes mellitus in the father were elicited. Screening for autoimmune diseases and antithyroid antibody was negative. An autoimmune link explaining the co-occurrence has been proposed. Cutaneous mosiacism could explain the presence of both the pathologies in a segmental distribution.

Market Segmentation in Business Technology Base: The Case of Segmentation of Sparkling

Directory of Open Access Journals (Sweden)

Valéria Riscarolli

2014-08-01

Full Text Available A common market segmentation premise for products and services rules consumer behavior as the segmentation center piece. Would this be the logic for segmentation used by small technology based companies? In this article we target at determining the principles of market segmentation used by a vitiwinery company, as research object. This company is recognized by its products excellence, either in domestic as well as in the foreign market, among 13 distinct countries. The research method used is a case study, through information from the company’s CEOs and crossed by primary information from observation and formal registries and documents of the company. In this research we look at sparkling wines market segmentation. Main results indicate that the winery studied considers only technological elements as the basis to build a market segment. One may conclude that a market segmentation for this company is based upon technological dominion of sparkling wines production, aligned with a premium-price policy. In the company, directorship believes that as sparkling wines market is still incipient in the country, sparkling wine market segments will form and consolidate after the evolution of consumers tasting preferences, depending on technologies that boost sparkling wines quality. 

The importance of having an appropriate relational data segmentation in ATLAS

International Nuclear Information System (INIS)

Dimitrov, G

2015-01-01

In this paper we describe specific technical solutions put in place in various database applications of the ATLAS experiment at LHC where we make use of several partitioning techniques available in Oracle 11g. With the broadly used range partitioning and its option of automatic interval partitioning we add our own logic in PLSQL procedures and scheduler jobs to sustain data sliding windows in order to enforce various data retention policies. We also make use of the new Oracle 11g reference partitioning in the Nightly Build System to achieve uniform data segmentation. However the most challenging issue was to segment the data of the new ATLAS Distributed Data Management system (Rucio), which resulted in tens of thousands list type partitions and sub-partitions. Partition and sub-partition management, index strategy, statistics gathering and queries execution plan stability are important factors when choosing an appropriate physical model for the application data management. The so-far accumulated knowledge and analysis on the new Oracle 12c version features that could be beneficial will be shared with the audience. (paper)

The importance of having an appropriate relational data segmentation in ATLAS

Science.gov (United States)

Dimitrov, G.

2015-12-01

In this paper we describe specific technical solutions put in place in various database applications of the ATLAS experiment at LHC where we make use of several partitioning techniques available in Oracle 11g. With the broadly used range partitioning and its option of automatic interval partitioning we add our own logic in PLSQL procedures and scheduler jobs to sustain data sliding windows in order to enforce various data retention policies. We also make use of the new Oracle 11g reference partitioning in the Nightly Build System to achieve uniform data segmentation. However the most challenging issue was to segment the data of the new ATLAS Distributed Data Management system (Rucio), which resulted in tens of thousands list type partitions and sub-partitions. Partition and sub-partition management, index strategy, statistics gathering and queries execution plan stability are important factors when choosing an appropriate physical model for the application data management. The so-far accumulated knowledge and analysis on the new Oracle 12c version features that could be beneficial will be shared with the audience.

Anaphoric Reference to Instances, Instantiated and Non-Instantiated Categories: A Reading Time Study.

Science.gov (United States)

Garnham, Alan

1981-01-01

Experiments using memory paradigms have shown that general terms receive context-dependent encodings. This experiment investigates the encoding of category and instance nouns. The results indicate that representations set up during reading are the product of both the linguistic input and of general knowledge. (Author/KC)

Fluence map segmentation

International Nuclear Information System (INIS)

Rosenwald, J.-C.

2008-01-01

The lecture addressed the following topics: 'Interpreting' the fluence map; The sequencer; Reasons for difference between desired and actual fluence map; Principle of 'Step and Shoot' segmentation; Large number of solutions for given fluence map; Optimizing 'step and shoot' segmentation; The interdigitation constraint; Main algorithms; Conclusions on segmentation algorithms (static mode); Optimizing intensity levels and monitor units; Sliding window sequencing; Synchronization to avoid the tongue-and-groove effect; Accounting for physical characteristics of MLC; Importance of corrections for leaf transmission and offset; Accounting for MLC mechanical constraints; The 'complexity' factor; Incorporating the sequencing into optimization algorithm; Data transfer to the treatment machine; Interface between R and V and accelerator; and Conclusions on fluence map segmentation (Segmentation is part of the overall inverse planning procedure; 'Step and Shoot' and 'Dynamic' options are available for most TPS (depending on accelerator model; The segmentation phase tends to come into the optimization loop; The physical characteristics of the MLC have a large influence on final dose distribution; The IMRT plans (MU and relative dose distribution) must be carefully validated). (P.A.)

Strategic market segmentation

Directory of Open Access Journals (Sweden)

Maričić Branko R.

2015-01-01

Full Text Available Strategic planning of marketing activities is the basis of business success in modern business environment. Customers are not homogenous in their preferences and expectations. Formulating an adequate marketing strategy, focused on realization of company's strategic objectives, requires segmented approach to the market that appreciates differences in expectations and preferences of customers. One of significant activities in strategic planning of marketing activities is market segmentation. Strategic planning imposes a need to plan marketing activities according to strategically important segments on the long term basis. At the same time, there is a need to revise and adapt marketing activities on the short term basis. There are number of criteria based on which market segmentation is performed. The paper will consider effectiveness and efficiency of different market segmentation criteria based on empirical research of customer expectations and preferences. The analysis will include traditional criteria and criteria based on behavioral model. The research implications will be analyzed from the perspective of selection of the most adequate market segmentation criteria in strategic planning of marketing activities.

Why segmentation matters: Experience-driven segmentation errors impair "morpheme" learning.

Science.gov (United States)

Finn, Amy S; Hudson Kam, Carla L

2015-09-01

We ask whether an adult learner's knowledge of their native language impedes statistical learning in a new language beyond just word segmentation (as previously shown). In particular, we examine the impact of native-language word-form phonotactics on learners' ability to segment words into their component morphemes and learn phonologically triggered variation of morphemes. We find that learning is impaired when words and component morphemes are structured to conflict with a learner's native-language phonotactic system, but not when native-language phonotactics do not conflict with morpheme boundaries in the artificial language. A learner's native-language knowledge can therefore have a cascading impact affecting word segmentation and the morphological variation that relies upon proper segmentation. These results show that getting word segmentation right early in learning is deeply important for learning other aspects of language, even those (morphology) that are known to pose a great difficulty for adult language learners. (c) 2015 APA, all rights reserved).

Gaussian Multiple Instance Learning Approach for Mapping the Slums of the World Using Very High Resolution Imagery

Energy Technology Data Exchange (ETDEWEB)

Vatsavai, Raju [ORNL

2013-01-01

In this paper, we present a computationally efficient algo- rithm based on multiple instance learning for mapping infor- mal settlements (slums) using very high-resolution remote sensing imagery. From remote sensing perspective, infor- mal settlements share unique spatial characteristics that dis- tinguish them from other urban structures like industrial, commercial, and formal residential settlements. However, regular pattern recognition and machine learning methods, which are predominantly single-instance or per-pixel classi- fiers, often fail to accurately map the informal settlements as they do not capture the complex spatial patterns. To overcome these limitations we employed a multiple instance based machine learning approach, where groups of contigu- ous pixels (image patches) are modeled as generated by a Gaussian distribution. We have conducted several experi- ments on very high-resolution satellite imagery, represent- ing four unique geographic regions across the world. Our method showed consistent improvement in accurately iden- tifying informal settlements.

A practical approximation algorithm for solving massive instances of hybridization number for binary and nonbinary trees.

Science.gov (United States)

van Iersel, Leo; Kelk, Steven; Lekić, Nela; Scornavacca, Celine

2014-05-05

Reticulate events play an important role in determining evolutionary relationships. The problem of computing the minimum number of such events to explain discordance between two phylogenetic trees is a hard computational problem. Even for binary trees, exact solvers struggle to solve instances with reticulation number larger than 40-50. Here we present CycleKiller and NonbinaryCycleKiller, the first methods to produce solutions verifiably close to optimality for instances with hundreds or even thousands of reticulations. Using simulations, we demonstrate that these algorithms run quickly for large and difficult instances, producing solutions that are very close to optimality. As a spin-off from our simulations we also present TerminusEst, which is the fastest exact method currently available that can handle nonbinary trees: this is used to measure the accuracy of the NonbinaryCycleKiller algorithm. All three methods are based on extensions of previous theoretical work (SIDMA 26(4):1635-1656, TCBB 10(1):18-25, SIDMA 28(1):49-66) and are publicly available. We also apply our methods to real data.

Medical image segmentation by combining graph cuts and oriented active appearance models.

Science.gov (United States)

Chen, Xinjian; Udupa, Jayaram K; Bagci, Ulas; Zhuge, Ying; Yao, Jianhua

2012-04-01

In this paper, we propose a novel method based on a strategic combination of the active appearance model (AAM), live wire (LW), and graph cuts (GCs) for abdominal 3-D organ segmentation. The proposed method consists of three main parts: model building, object recognition, and delineation. In the model building part, we construct the AAM and train the LW cost function and GC parameters. In the recognition part, a novel algorithm is proposed for improving the conventional AAM matching method, which effectively combines the AAM and LW methods, resulting in the oriented AAM (OAAM). A multiobject strategy is utilized to help in object initialization. We employ a pseudo-3-D initialization strategy and segment the organs slice by slice via a multiobject OAAM method. For the object delineation part, a 3-D shape-constrained GC method is proposed. The object shape generated from the initialization step is integrated into the GC cost computation, and an iterative GC-OAAM method is used for object delineation. The proposed method was tested in segmenting the liver, kidneys, and spleen on a clinical CT data set and also on the MICCAI 2007 Grand Challenge liver data set. The results show the following: 1) The overall segmentation accuracy of true positive volume fraction TPVF > 94.3% and false positive volume fraction can be achieved; 2) the initialization performance can be improved by combining the AAM and LW; 3) the multiobject strategy greatly facilitates initialization; 4) compared with the traditional 3-D AAM method, the pseudo-3-D OAAM method achieves comparable performance while running 12 times faster; and 5) the performance of the proposed method is comparable to state-of-the-art liver segmentation algorithm. The executable version of the 3-D shape-constrained GC method with a user interface can be downloaded from http://xinjianchen.wordpress.com/research/.

[External cephalic version].

Science.gov (United States)

Navarro-Santana, B; Duarez-Coronado, M; Plaza-Arranz, J

2016-08-01

To analyze the rate of successful external cephalic versions in our center and caesarean sections that would be avoided with the use of external cephalic versions. From January 2012 to March 2016 external cephalic versions carried out at our center, which were a total of 52. We collected data about female age, gestational age at the time of the external cephalic version, maternal body mass index (BMI), fetal variety and situation, fetal weight, parity, location of the placenta, amniotic fluid index (ILA), tocolysis, analgesia, and newborn weight at birth, minor adverse effects (dizziness, hypotension and maternal pain) and major adverse effects (tachycardia, bradycardia, decelerations and emergency cesarean section). 45% of the versions were unsuccessful and 55% were successful. The percentage of successful vaginal delivery in versions was 84% (4% were instrumental) and 15% of caesarean sections. With respect to the variables studied, only significant differences in birth weight were found; suggesting that birth weight it is related to the outcome of external cephalic version. Probably we did not find significant differences due to the number of patients studied. For women with breech presentation, we recommend external cephalic version before the expectant management or performing a cesarean section. The external cephalic version increases the proportion of fetuses in cephalic presentation and also decreases the rate of caesarean sections.

A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI

DEFF Research Database (Denmark)

Iglesias, Juan Eugenio; Augustinack, Jean C.; Nguyen, Khoa

2015-01-01

level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise...... datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer......'s disease subjects and elderly controls with 88% accuracy in standard resolution (1 mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and classification based on whole hippocampal volume (82% accuracy)....

GEODESIC RECONSTRUCTION, SADDLE ZONES & HIERARCHICAL SEGMENTATION

Directory of Open Access Journals (Sweden)

Serge Beucher

2011-05-01

Full Text Available The morphological reconstruction based on geodesic operators, is a powerful tool in mathematical morphology. The general definition of this reconstruction supposes the use of a marker function f which is not necessarily related to the function g to be built. However, this paper deals with operations where the marker function is defined from given characteristic regions of the initial function f, as it is the case, for instance, for the extrema (maxima or minima but also for the saddle zones. Firstly, we show that the intuitive definition of a saddle zone is not easy to handle, especially when digitised images are involved. However, some of these saddle zones (regional ones also called overflow zones can be defined, this definition providing a simple algorithm to extract them. The second part of the paper is devoted to the use of these overflow zones as markers in image reconstruction. This reconstruction provides a new function which exhibits a new hierarchy of extrema. This hierarchy is equivalent to the hierarchy produced by the so-called waterfall algorithm. We explain why the waterfall algorithm can be achieved by performing a watershed transform of the function reconstructed by its initial watershed lines. Finally, some examples of use of this hierarchical segmentation are described.

3D marker-controlled watershed for kidney segmentation in clinical CT exams.

Science.gov (United States)

Wieclawek, Wojciech

2018-02-27

Image segmentation is an essential and non trivial task in computer vision and medical image analysis. Computed tomography (CT) is one of the most accessible medical examination techniques to visualize the interior of a patient's body. Among different computer-aided diagnostic systems, the applications dedicated to kidney segmentation represent a relatively small group. In addition, literature solutions are verified on relatively small databases. The goal of this research is to develop a novel algorithm for fully automated kidney segmentation. This approach is designed for large database analysis including both physiological and pathological cases. This study presents a 3D marker-controlled watershed transform developed and employed for fully automated CT kidney segmentation. The original and the most complex step in the current proposition is an automatic generation of 3D marker images. The final kidney segmentation step is an analysis of the labelled image obtained from marker-controlled watershed transform. It consists of morphological operations and shape analysis. The implementation is conducted in a MATLAB environment, Version 2017a, using i.a. Image Processing Toolbox. 170 clinical CT abdominal studies have been subjected to the analysis. The dataset includes normal as well as various pathological cases (agenesis, renal cysts, tumors, renal cell carcinoma, kidney cirrhosis, partial or radical nephrectomy, hematoma and nephrolithiasis). Manual and semi-automated delineations have been used as a gold standard. Wieclawek Among 67 delineated medical cases, 62 cases are 'Very good', whereas only 5 are 'Good' according to Cohen's Kappa interpretation. The segmentation results show that mean values of Sensitivity, Specificity, Dice, Jaccard, Cohen's Kappa and Accuracy are 90.29, 99.96, 91.68, 85.04, 91.62 and 99.89% respectively. All 170 medical cases (with and without outlines) have been classified by three independent medical experts as 'Very good' in 143

Deformable meshes for medical image segmentation accurate automatic segmentation of anatomical structures

CERN Document Server

Kainmueller, Dagmar

2014-01-01

? Segmentation of anatomical structures in medical image data is an essential task in clinical practice. Dagmar Kainmueller introduces methods for accurate fully automatic segmentation of anatomical structures in 3D medical image data. The author's core methodological contribution is a novel deformation model that overcomes limitations of state-of-the-art Deformable Surface approaches, hence allowing for accurate segmentation of tip- and ridge-shaped features of anatomical structures. As for practical contributions, she proposes application-specific segmentation pipelines for a range of anatom

Memory-Efficient Onboard Rock Segmentation

Science.gov (United States)

Burl, Michael C.; Thompson, David R.; Bornstein, Benjamin J.; deGranville, Charles K.

2013-01-01

Rockster-MER is an autonomous perception capability that was uploaded to the Mars Exploration Rover Opportunity in December 2009. This software provides the vision front end for a larger software system known as AEGIS (Autonomous Exploration for Gathering Increased Science), which was recently named 2011 NASA Software of the Year. As the first step in AEGIS, Rockster-MER analyzes an image captured by the rover, and detects and automatically identifies the boundary contours of rocks and regions of outcrop present in the scene. This initial segmentation step reduces the data volume from millions of pixels into hundreds (or fewer) of rock contours. Subsequent stages of AEGIS then prioritize the best rocks according to scientist- defined preferences and take high-resolution, follow-up observations. Rockster-MER has performed robustly from the outset on the Mars surface under challenging conditions. Rockster-MER is a specially adapted, embedded version of the original Rockster algorithm ("Rock Segmentation Through Edge Regrouping," (NPO- 44417) Software Tech Briefs, September 2008, p. 25). Although the new version performs the same basic task as the original code, the software has been (1) significantly upgraded to overcome the severe onboard re source limitations (CPU, memory, power, time) and (2) "bulletproofed" through code reviews and extensive testing and profiling to avoid the occurrence of faults. Because of the limited computational power of the RAD6000 flight processor on Opportunity (roughly two orders of magnitude slower than a modern workstation), the algorithm was heavily tuned to improve its speed. Several functional elements of the original algorithm were removed as a result of an extensive cost/benefit analysis conducted on a large set of archived rover images. The algorithm was also required to operate below a stringent 4MB high-water memory ceiling; hence, numerous tricks and strategies were introduced to reduce the memory footprint. Local filtering

Land Cover Segmentation of Airborne LiDAR Data Using Stochastic Atrous Network

Directory of Open Access Journals (Sweden)

Hasan Asy’ari Arief

2018-06-01

Full Text Available Inspired by the success of deep learning techniques in dense-label prediction and the increasing availability of high precision airborne light detection and ranging (LiDAR data, we present a research process that compares a collection of well-proven semantic segmentation architectures based on the deep learning approach. Our investigation concludes with the proposition of some novel deep learning architectures for generating detailed land resource maps by employing a semantic segmentation approach. The contribution of our work is threefold. (1 First, we implement the multiclass version of the intersection-over-union (IoU loss function that contributes to handling highly imbalanced datasets and preventing overfitting. (2 Thereafter, we propose a novel deep learning architecture integrating the deep atrous network architecture with the stochastic depth approach for speeding up the learning process, and impose a regularization effect. (3 Finally, we introduce an early fusion deep layer that combines image-based and LiDAR-derived features. In a benchmark study carried out using the Follo 2014 LiDAR data and the NIBIO AR5 land resources dataset, we compare our proposals to other deep learning architectures. A quantitative comparison shows that our best proposal provides more than 5% relative improvement in terms of mean intersection-over-union over the atrous network, providing a basis for a more frequent and improved use of LiDAR data for automatic land cover segmentation.

Segmentation of the Infant Food Market

OpenAIRE

Hrůzová, Daniela

2015-01-01

The theoretical part covers general market segmentation, namely the marketing importance of differences among consumers, the essence of market segmentation, its main conditions and the process of segmentation, which consists of four consecutive phases - defining the market, determining important criteria, uncovering segments and developing segment profiles. The segmentation criteria, segmentation approaches, methods and techniques for the process of market segmentation are also described in t...

Pancreas and cyst segmentation

Science.gov (United States)

Dmitriev, Konstantin; Gutenko, Ievgeniia; Nadeem, Saad; Kaufman, Arie

2016-03-01

Accurate segmentation of abdominal organs from medical images is an essential part of surgical planning and computer-aided disease diagnosis. Many existing algorithms are specialized for the segmentation of healthy organs. Cystic pancreas segmentation is especially challenging due to its low contrast boundaries, variability in shape, location and the stage of the pancreatic cancer. We present a semi-automatic segmentation algorithm for pancreata with cysts. In contrast to existing automatic segmentation approaches for healthy pancreas segmentation which are amenable to atlas/statistical shape approaches, a pancreas with cysts can have even higher variability with respect to the shape of the pancreas due to the size and shape of the cyst(s). Hence, fine results are better attained with semi-automatic steerable approaches. We use a novel combination of random walker and region growing approaches to delineate the boundaries of the pancreas and cysts with respective best Dice coefficients of 85.1% and 86.7%, and respective best volumetric overlap errors of 26.0% and 23.5%. Results show that the proposed algorithm for pancreas and pancreatic cyst segmentation is accurate and stable.

Phasing multi-segment undulators

International Nuclear Information System (INIS)

Chavanne, J.; Elleaume, P.; Vaerenbergh, P. Van

1996-01-01

An important issue in the manufacture of multi-segment undulators as a source of synchrotron radiation or as a free-electron laser (FEL) is the phasing between successive segments. The state of the art is briefly reviewed, after which a novel pure permanent magnet phasing section that is passive and does not require any current is presented. The phasing section allows the introduction of a 6 mm longitudinal gap between each segment, resulting in complete mechanical independence and reduced magnetic interaction between segments. The tolerance of the longitudinal positioning of one segment with respect to the next is found to be 2.8 times lower than that of conventional phasing. The spectrum at all gaps and useful harmonics is almost unchanged when compared with a single-segment undulator of the same total length. (au) 3 refs

FRAMEWORK FOR COMPARING SEGMENTATION ALGORITHMS

Directory of Open Access Journals (Sweden)

G. Sithole

2015-05-01

Full Text Available The notion of a ‘Best’ segmentation does not exist. A segmentation algorithm is chosen based on the features it yields, the properties of the segments (point sets it generates, and the complexity of its algorithm. The segmentation is then assessed based on a variety of metrics such as homogeneity, heterogeneity, fragmentation, etc. Even after an algorithm is chosen its performance is still uncertain because the landscape/scenarios represented in a point cloud have a strong influence on the eventual segmentation. Thus selecting an appropriate segmentation algorithm is a process of trial and error. Automating the selection of segmentation algorithms and their parameters first requires methods to evaluate segmentations. Three common approaches for evaluating segmentation algorithms are ‘goodness methods’, ‘discrepancy methods’ and ‘benchmarks’. Benchmarks are considered the most comprehensive method of evaluation. This paper shortcomings in current benchmark methods are identified and a framework is proposed that permits both a visual and numerical evaluation of segmentations for different algorithms, algorithm parameters and evaluation metrics. The concept of the framework is demonstrated on a real point cloud. Current results are promising and suggest that it can be used to predict the performance of segmentation algorithms.

Global Precipitation Climatology Project (GPCP) - Monthly, Version 2.2 (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Version 2.2 of the dataset has been superseded by a newer version. Users should not use version 2.2 except in rare cases (e.g., when reproducing previous studies...

Why segmentation matters: experience-driven segmentation errors impair “morpheme” learning

Science.gov (United States)

Finn, Amy S.; Hudson Kam, Carla L.

2015-01-01

We ask whether an adult learner’s knowledge of their native language impedes statistical learning in a new language beyond just word segmentation (as previously shown). In particular, we examine the impact of native-language word-form phonotactics on learners’ ability to segment words into their component morphemes and learn phonologically triggered variation of morphemes. We find that learning is impaired when words and component morphemes are structured to conflict with a learner’s native-language phonotactic system, but not when native-language phonotactics do not conflict with morpheme boundaries in the artificial language. A learner’s native-language knowledge can therefore have a cascading impact affecting word segmentation and the morphological variation that relies upon proper segmentation. These results show that getting word segmentation right early in learning is deeply important for learning other aspects of language, even those (morphology) that are known to pose a great difficulty for adult language learners. PMID:25730305

Segment-Tube: Spatio-Temporal Action Localization in Untrimmed Videos with Per-Frame Segmentation

OpenAIRE

Le Wang; Xuhuan Duan; Qilin Zhang; Zhenxing Niu; Gang Hua; Nanning Zheng

2018-01-01

Inspired by the recent spatio-temporal action localization efforts with tubelets (sequences of bounding boxes), we present a new spatio-temporal action localization detector Segment-tube, which consists of sequences of per-frame segmentation masks. The proposed Segment-tube detector can temporally pinpoint the starting/ending frame of each action category in the presence of preceding/subsequent interference actions in untrimmed videos. Simultaneously, the Segment-tube detector produces per-fr...

Health-related quality of life after segmental resection of the lateral mandible: Free fibula flap versus plate reconstruction.

Science.gov (United States)

van Gemert, Johannes; Holtslag, Irene; van der Bilt, Andries; Merkx, Matthias; Koole, Ron; Van Cann, Ellen

2015-06-01

Segmental resection of the mandible causes functional, aesthetic and social problems affecting health-related quality of life (HRQoL). It is often assumed that reconstruction with composite free flaps guarantees better function and aesthetics than bridging the defect with reconstruction plates. Using the European Organization for Research and Treatment of Cancer questionnaires (EORTC QLQ-C30 version 3.0 and EORTC QLQ-H&N35), we compared HRQoL in patients who received free fibula flaps versus reconstruction plates after segmental resection of the lateral mandible. Thirty-seven completed questionnaires (18 fibula reconstructions and 19 patients with reconstruction plates) were available. Reconstruction with a free fibula flap did not provide clear additional benefit to bridging the defect with a reconstruction plate after segmental resection of the lateral mandible. In particular aspects known to have the most impact on HRQoL like swallowing, speech and chewing were not influenced by the type of reconstruction. Reconstruction of segmental defects of the lateral mandible with free fibula flap and reconstruction plate resulted in comparable HRQoL. If dental rehabilitation by means of dental implants is not anticipated in the fibula, then plate reconstruction with adequate soft tissue remains a suitable technique for the reconstruction of segmental defects of the lateral mandible. Copyright © 2015 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

On Combining Multiple-Instance Learning and Active Learning for Computer-Aided Detection of Tuberculosis

NARCIS (Netherlands)

Melendez Rodriguez, J.C.; Ginneken, B. van; Maduskar, P.; Philipsen, R.H.H.M.; Ayles, H.; Sanchez, C.I.

2016-01-01

The major advantage of multiple-instance learning (MIL) applied to a computer-aided detection (CAD) system is that it allows optimizing the latter with case-level labels instead of accurate lesion outlines as traditionally required for a supervised approach. As shown in previous work, a MIL-based

Global Historical Climatology Network (GHCN), Version 1 (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Please note, this dataset has been superseded by a newer version (see below). Users should not use this version except in rare cases (e.g., when reproducing previous...

A p-version embedded model for simulation of concrete temperature fields with cooling pipes

Directory of Open Access Journals (Sweden)

Sheng Qiang

2015-07-01

Full Text Available Pipe cooling is an effective method of mass concrete temperature control, but its accurate and convenient numerical simulation is still a cumbersome problem. An improved embedded model, considering the water temperature variation along the pipe, was proposed for simulating the temperature field of early-age concrete structures containing cooling pipes. The improved model was verified with an engineering example. Then, the p-version self-adaption algorithm for the improved embedded model was deduced, and the initial values and boundary conditions were examined. Comparison of some numerical samples shows that the proposed model can provide satisfying precision and a higher efficiency. The analysis efficiency can be doubled at the same precision, even for a large-scale element. The p-version algorithm can fit grids of different sizes for the temperature field simulation. The convenience of the proposed algorithm lies in the possibility of locating more pipe segments in one element without the need of so regular a shape as in the explicit model.

Guide en matière d'évaluation à l'intention des instances qui ...

International Development Research Centre (IDRC) Digital Library (Canada)

Les évaluations sont un élément clé de la recherche pour le développement, puisqu'elles ... Comprendre le rôle des instances qui commandent des évaluations ... Avec l'aide du CRDI, l'Instituto de la Salud, Medio Ambiente, Economia y ...

Joint shape segmentation with linear programming

KAUST Repository

Huang, Qixing

2011-01-01

We present an approach to segmenting shapes in a heterogenous shape database. Our approach segments the shapes jointly, utilizing features from multiple shapes to improve the segmentation of each. The approach is entirely unsupervised and is based on an integer quadratic programming formulation of the joint segmentation problem. The program optimizes over possible segmentations of individual shapes as well as over possible correspondences between segments from multiple shapes. The integer quadratic program is solved via a linear programming relaxation, using a block coordinate descent procedure that makes the optimization feasible for large databases. We evaluate the presented approach on the Princeton segmentation benchmark and show that joint shape segmentation significantly outperforms single-shape segmentation techniques. © 2011 ACM.

Instance selection in digital soil mapping: a study case in Rio Grande do Sul, Brazil

Directory of Open Access Journals (Sweden)

Elvio Giasson

2015-09-01

Full Text Available A critical issue in digital soil mapping (DSM is the selection of data sampling method for model training. One emerging approach applies instance selection to reduce the size of the dataset by drawing only relevant samples in order to obtain a representative subset that is still large enough to preserve relevant information, but small enough to be easily handled by learning algorithms. Although there are suggestions to distribute data sampling as a function of the soil map unit (MU boundaries location, there are still contradictions among research recommendations for locating samples either closer or more distant from soil MU boundaries. A study was conducted to evaluate instance selection methods based on spatially-explicit data collection using location in relation to soil MU boundaries as the main criterion. Decision tree analysis was performed for modeling digital soil class mapping using two different sampling schemes: a selecting sampling points located outside buffers near soil MU boundaries, and b selecting sampling points located within buffers near soil MU boundaries. Data was prepared for generating classification trees to include only data points located within or outside buffers with widths of 60, 120, 240, 360, 480, and 600m near MU boundaries. Instance selection methods using both spatial selection of methods was effective for reduced size of the dataset used for calibrating classification tree models, but failed to provide advantages to digital soil mapping because of potential reduction in the accuracy of classification tree models.

Extension of instance search technique by geometric coding and quantization error compensation

OpenAIRE

García Del Molino, Ana

2013-01-01

[ANGLÈS] This PFC analyzes two ways of improving the video retrieval techniques for instance search problem. In one hand, "Pairing Interest Points for a better Signature using Sparse Detector's Spatial Information", allows the Bag-of-Words model to keep some spatial information. In the other, "Study of the Hamming Embedding Signature Symmetry in Video Retrieval" provides binary signatures that refine the matching based on visual words, and aims to find the best way of matching taking into acc...

Rediscovering market segmentation.

Science.gov (United States)

Yankelovich, Daniel; Meer, David

2006-02-01

In 1964, Daniel Yankelovich introduced in the pages of HBR the concept of nondemographic segmentation, by which he meant the classification of consumers according to criteria other than age, residence, income, and such. The predictive power of marketing studies based on demographics was no longer strong enough to serve as a basis for marketing strategy, he argued. Buying patterns had become far better guides to consumers' future purchases. In addition, properly constructed nondemographic segmentations could help companies determine which products to develop, which distribution channels to sell them in, how much to charge for them, and how to advertise them. But more than 40 years later, nondemographic segmentation has become just as unenlightening as demographic segmentation had been. Today, the technique is used almost exclusively to fulfill the needs of advertising, which it serves mainly by populating commercials with characters that viewers can identify with. It is true that psychographic types like "High-Tech Harry" and "Joe Six-Pack" may capture some truth about real people's lifestyles, attitudes, self-image, and aspirations. But they are no better than demographics at predicting purchase behavior. Thus they give corporate decision makers very little idea of how to keep customers or capture new ones. Now, Daniel Yankelovich returns to these pages, with consultant David Meer, to argue the case for a broad view of nondemographic segmentation. They describe the elements of a smart segmentation strategy, explaining how segmentations meant to strengthen brand identity differ from those capable of telling a company which markets it should enter and what goods to make. And they introduce their "gravity of decision spectrum", a tool that focuses on the form of consumer behavior that should be of the greatest interest to marketers--the importance that consumers place on a product or product category.

Comprehensive Cost Minimization in Distribution Networks Using Segmented-time Feeder Reconfiguration and Reactive Power Control of Distributed Generators

DEFF Research Database (Denmark)

Chen, Shuheng; Hu, Weihao; Chen, Zhe

2016-01-01

In this paper, an efficient methodology is proposed to deal with segmented-time reconfiguration problem of distribution networks coupled with segmented-time reactive power control of distributed generators. The target is to find the optimal dispatching schedule of all controllable switches...... and distributed generators’ reactive powers in order to minimize comprehensive cost. Corresponding constraints, including voltage profile, maximum allowable daily switching operation numbers (MADSON), reactive power limits, and so on, are considered. The strategy of grouping branches is used to simplify...... (FAHPSO) is implemented in VC++ 6.0 program language. A modified version of the typical 70-node distribution network and several real distribution networks are used to test the performance of the proposed method. Numerical results show that the proposed methodology is an efficient method for comprehensive...

Seeing is believing: video classification for computed tomographic colonography using multiple-instance learning.

Science.gov (United States)

Wang, Shijun; McKenna, Matthew T; Nguyen, Tan B; Burns, Joseph E; Petrick, Nicholas; Sahiner, Berkman; Summers, Ronald M

2012-05-01

In this paper, we present development and testing results for a novel colonic polyp classification method for use as part of a computed tomographic colonography (CTC) computer-aided detection (CAD) system. Inspired by the interpretative methodology of radiologists using 3-D fly-through mode in CTC reading, we have developed an algorithm which utilizes sequences of images (referred to here as videos) for classification of CAD marks. For each CAD mark, we created a video composed of a series of intraluminal, volume-rendered images visualizing the detection from multiple viewpoints. We then framed the video classification question as a multiple-instance learning (MIL) problem. Since a positive (negative) bag may contain negative (positive) instances, which in our case depends on the viewing angles and camera distance to the target, we developed a novel MIL paradigm to accommodate this class of problems. We solved the new MIL problem by maximizing a L2-norm soft margin using semidefinite programming, which can optimize relevant parameters automatically. We tested our method by analyzing a CTC data set obtained from 50 patients from three medical centers. Our proposed method showed significantly better performance compared with several traditional MIL methods.

Reflection symmetry-integrated image segmentation.

Science.gov (United States)

Sun, Yu; Bhanu, Bir

2012-09-01

This paper presents a new symmetry-integrated region-based image segmentation method. The method is developed to obtain improved image segmentation by exploiting image symmetry. It is realized by constructing a symmetry token that can be flexibly embedded into segmentation cues. Interesting points are initially extracted from an image by the SIFT operator and they are further refined for detecting the global bilateral symmetry. A symmetry affinity matrix is then computed using the symmetry axis and it is used explicitly as a constraint in a region growing algorithm in order to refine the symmetry of the segmented regions. A multi-objective genetic search finds the segmentation result with the highest performance for both segmentation and symmetry, which is close to the global optimum. The method has been investigated experimentally in challenging natural images and images containing man-made objects. It is shown that the proposed method outperforms current segmentation methods both with and without exploiting symmetry. A thorough experimental analysis indicates that symmetry plays an important role as a segmentation cue, in conjunction with other attributes like color and texture.

Lung segment geometry study: simulation of largest possible tumours that fit into bronchopulmonary segments.

Science.gov (United States)

Welter, S; Stöcker, C; Dicken, V; Kühl, H; Krass, S; Stamatis, G

2012-03-01

Segmental resection in stage I non-small cell lung cancer (NSCLC) has been well described and is considered to have similar survival rates as lobectomy but with increased rates of local tumour recurrence due to inadequate parenchymal margins. In consequence, today segmentectomy is only performed when the tumour is smaller than 2 cm. Three-dimensional reconstructions from 11 thin-slice CT scans of bronchopulmonary segments were generated, and virtual spherical tumours were placed over the segments, respecting all segmental borders. As a next step, virtual parenchymal safety margins of 2 cm and 3 cm were subtracted and the size of the remaining tumour calculated. The maximum tumour diameters with a 30-mm parenchymal safety margin ranged from 26.1 mm in right-sided segments 7 + 8 to 59.8 mm in the left apical segments 1-3. Using a three-dimensional reconstruction of lung CT scans, we demonstrated that segmentectomy or resection of segmental groups should be feasible with adequate margins, even for larger tumours in selected cases. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

The Karlin-McGregor formula for a variant of a discrete version of Walsh's spider

International Nuclear Information System (INIS)

Gruenbaum, F Alberto

2009-01-01

We consider a variant of a discrete space version of Walsh's spider, see Walsh (1978 Temps Locaux, Asterisque vol 52-53 (Paris: Soc. Math. de France)) as well as Evans and Sowers (2003 Ann. Probab. 31 486-527 and its references). This process can be seen as an instance of a quasi-birth-and-death process, a class of random walks for which the classical theory of Karlin and McGregor can be nicely adapted as in Dette, Reuther, Studden and Zygmunt (2006 SIAM J. Matrix Anal. Appl. 29 117-42), Gruenbaum (2007 Probability, Geometry and Integrable Systems ed Pinsky and Birnir vol 55 (Berkeley, CA: MSRI publication) pp. 241-60, see also arXiv math PR/0703375), Gruenbaum (2007 Dagstuhl Seminar Proc. 07461 on Numerical Methods in Structured Markov Chains ed Bini), Gruenbaum (2008 Proceedings of IWOTA) and Gruenbaum and de la Iglesia (2008 SIAM J. Matrix Anal. Appl. 30 741-63). We give here a weight matrix that makes the corresponding matrix-valued orthogonal polynomials orthogonal to each other. We also determine the polynomials themselves and thus obtain all the ingredients to apply a matrix-valued version of the Karlin-McGregor formula.

Sipunculans and segmentation

DEFF Research Database (Denmark)

Wanninger, Andreas; Kristof, Alen; Brinkmann, Nora

2009-01-01

mechanisms may act on the level of gene expression, cell proliferation, tissue differentiation and organ system formation in individual segments. Accordingly, in some polychaete annelids the first three pairs of segmental peripheral neurons arise synchronously, while the metameric commissures of the ventral...

Interpreting Black-Box Classifiers Using Instance-Level Visual Explanations

Energy Technology Data Exchange (ETDEWEB)

Tamagnini, Paolo; Krause, Josua W.; Dasgupta, Aritra; Bertini, Enrico

2017-05-14

To realize the full potential of machine learning in diverse real- world domains, it is necessary for model predictions to be readily interpretable and actionable for the human in the loop. Analysts, who are the users but not the developers of machine learning models, often do not trust a model because of the lack of transparency in associating predictions with the underlying data space. To address this problem, we propose Rivelo, a visual analytic interface that enables analysts to understand the causes behind predictions of binary classifiers by interactively exploring a set of instance-level explanations. These explanations are model-agnostic, treating a model as a black box, and they help analysts in interactively probing the high-dimensional binary data space for detecting features relevant to predictions. We demonstrate the utility of the interface with a case study analyzing a random forest model on the sentiment of Yelp reviews about doctors.

Using Predictability for Lexical Segmentation.

Science.gov (United States)

Çöltekin, Çağrı

2017-09-01

This study investigates a strategy based on predictability of consecutive sub-lexical units in learning to segment a continuous speech stream into lexical units using computational modeling and simulations. Lexical segmentation is one of the early challenges during language acquisition, and it has been studied extensively through psycholinguistic experiments as well as computational methods. However, despite strong empirical evidence, the explicit use of predictability of basic sub-lexical units in models of segmentation is underexplored. This paper presents an incremental computational model of lexical segmentation for exploring the usefulness of predictability for lexical segmentation. We show that the predictability cue is a strong cue for segmentation. Contrary to earlier reports in the literature, the strategy yields state-of-the-art segmentation performance with an incremental computational model that uses only this particular cue in a cognitively plausible setting. The paper also reports an in-depth analysis of the model, investigating the conditions affecting the usefulness of the strategy. Copyright © 2016 Cognitive Science Society, Inc.

Efficient graph-cut tattoo segmentation

Science.gov (United States)

Kim, Joonsoo; Parra, Albert; Li, He; Delp, Edward J.

2015-03-01

Law enforcement is interested in exploiting tattoos as an information source to identify, track and prevent gang-related crimes. Many tattoo image retrieval systems have been described. In a retrieval system tattoo segmentation is an important step for retrieval accuracy since segmentation removes background information in a tattoo image. Existing segmentation methods do not extract the tattoo very well when the background includes textures and color similar to skin tones. In this paper we describe a tattoo segmentation approach by determining skin pixels in regions near the tattoo. In these regions graph-cut segmentation using a skin color model and a visual saliency map is used to find skin pixels. After segmentation we determine which set of skin pixels are connected with each other that form a closed contour including a tattoo. The regions surrounded by the closed contours are considered tattoo regions. Our method segments tattoos well when the background includes textures and color similar to skin.

Fold distributions at clover, crystal and segment levels for segmented clover detectors

International Nuclear Information System (INIS)

Kshetri, R; Bhattacharya, P

2014-01-01

Fold distributions at clover, crystal and segment levels have been extracted for an array of segmented clover detectors for various gamma energies. A simple analysis of the results based on a model independant approach has been presented. For the first time, the clover fold distribution of an array and associated array addback factor have been extracted. We have calculated the percentages of the number of crystals and segments that fire for a full energy peak event

Enhancements to the CALIOP Aerosol Subtyping and Lidar Ratio Selection Algorithms for Level II Version 4

Science.gov (United States)

Omar, A. H.; Tackett, J. L.; Vaughan, M. A.; Kar, J.; Trepte, C. R.; Winker, D. M.

2016-12-01

This presentation describes several enhancements planned for the version 4 aerosol subtyping and lidar ratio selection algorithms of the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. The CALIOP subtyping algorithm determines the most likely aerosol type from CALIOP measurements (attenuated backscatter, estimated particulate depolarization ratios δe, layer altitude), and surface type. The aerosol type, so determined, is associated with a lidar ratio (LR) from a discrete set of values. Some of these lidar ratios have been updated in the version 4 algorithms. In particular, the dust and polluted dust will be adjusted to reflect the latest measurements and model studies of these types. Version 4 eliminates the confusion between smoke and clean marine aerosols seen in version 3 by modifications to the elevated layer flag definitions used to identify smoke aerosols over the ocean. In the subtyping algorithms pure dust is determined by high estimated particulate depolarization ratios [δe > 0.20]. Mixtures of dust and other aerosol types are determined by intermediate values of the estimated depolarization ratio [0.075limited to mixtures of dust and smoke, the so called polluted dust aerosol type. To differentiate between mixtures of dust and smoke, and dust and marine aerosols, a new aerosol type will be added in the version 4 data products. In the revised classification algorithms, polluted dust will still defined as dust + smoke/pollution but in the marine boundary layer instances of moderate depolarization will be typed as dusty marine aerosols with a lower lidar ratio than polluted dust. The dusty marine type introduced in version 4 is modeled as a mixture of dust + marine aerosol. To account for fringes, the version 4 Level 2 algorithms implement Subtype Coalescence Algorithm for AeRosol Fringes (SCAARF) routine to detect and classify fringe of aerosol plumes that are detected at 20 km or 80 km horizontal resolution at the plume base. These

Intercalary bone segment transport in treatment of segmental tibial defects

International Nuclear Information System (INIS)

Iqbal, A.; Amin, M.S.

2002-01-01

Objective: To evaluate the results and complications of intercalary bone segment transport in the treatment of segmental tibial defects. Design: This is a retrospective analysis of patients with segmental tibial defects who were treated with intercalary bone segment transport method. Place and Duration of Study: The study was carried out at Combined Military Hospital, Rawalpindi from September 1997 to April 2001. Subjects and methods: Thirteen patients were included in the study who had developed tibial defects either due to open fractures with bone loss or subsequent to bone debridement of infected non unions. The mean bone defect was 6.4 cms and there were eight associated soft tissue defects. Locally made unilateral 'Naseer-Awais' (NA) fixator was used for bone segment transport. The distraction was done at the rate of 1mm/day after 7-10 days of osteotomy. The patients were followed-up fortnightly during distraction and monthly thereafter. The mean follow-up duration was 18 months. Results: The mean time in external fixation was 9.4 months. The m ean healing index' was 1.47 months/cm. Satisfactory union was achieved in all cases. Six cases (46.2%) required bone grafting at target site and in one of them grafting was required at the level of regeneration as well. All the wounds healed well with no residual infection. There was no residual leg length discrepancy of more than 20 mm nd one angular deformity of more than 5 degrees. The commonest complication encountered was pin track infection seen in 38% of Shanz Screws applied. Loosening occurred in 6.8% of Shanz screws, requiring re-adjustment. Ankle joint contracture with equinus deformity and peroneal nerve paresis occurred in one case each. The functional results were graded as 'good' in seven, 'fair' in four, and 'poor' in two patients. Overall, thirteen patients had 31 (minor/major) complications with a ratio of 2.38 complications per patient. To treat the bone defects and associated complications, a mean of

Market segmentation in behavioral perspective.

OpenAIRE

Wells, V.K.; Chang, S.W.; Oliveira-Castro, J.M.; Pallister, J.

2010-01-01

A segmentation approach is presented using both traditional demographic segmentation bases (age, social class/occupation, and working status) and a segmentation by benefits sought. The benefits sought in this case are utilitarian and informational reinforcement, variables developed from the Behavioral Perspective Model (BPM). Using data from 1,847 consumers and from a total of 76,682 individual purchases, brand choice and price and reinforcement responsiveness were assessed for each segment a...

Noise destroys feedback enhanced figure-ground segmentation but not feedforward figure-ground segmentation

Science.gov (United States)

Romeo, August; Arall, Marina; Supèr, Hans

2012-01-01

Figure-ground (FG) segmentation is the separation of visual information into background and foreground objects. In the visual cortex, FG responses are observed in the late stimulus response period, when neurons fire in tonic mode, and are accompanied by a switch in cortical state. When such a switch does not occur, FG segmentation fails. Currently, it is not known what happens in the brain on such occasions. A biologically plausible feedforward spiking neuron model was previously devised that performed FG segmentation successfully. After incorporating feedback the FG signal was enhanced, which was accompanied by a change in spiking regime. In a feedforward model neurons respond in a bursting mode whereas in the feedback model neurons fired in tonic mode. It is known that bursts can overcome noise, while tonic firing appears to be much more sensitive to noise. In the present study, we try to elucidate how the presence of noise can impair FG segmentation, and to what extent the feedforward and feedback pathways can overcome noise. We show that noise specifically destroys the feedback enhanced FG segmentation and leaves the feedforward FG segmentation largely intact. Our results predict that noise produces failure in FG perception. PMID:22934028

ADVANCED CLUSTER BASED IMAGE SEGMENTATION

Directory of Open Access Journals (Sweden)

D. Kesavaraja

2011-11-01

Full Text Available This paper presents efficient and portable implementations of a useful image segmentation technique which makes use of the faster and a variant of the conventional connected components algorithm which we call parallel Components. In the Modern world majority of the doctors are need image segmentation as the service for various purposes and also they expect this system is run faster and secure. Usually Image segmentation Algorithms are not working faster. In spite of several ongoing researches in Conventional Segmentation and its Algorithms might not be able to run faster. So we propose a cluster computing environment for parallel image Segmentation to provide faster result. This paper is the real time implementation of Distributed Image Segmentation in Clustering of Nodes. We demonstrate the effectiveness and feasibility of our method on a set of Medical CT Scan Images. Our general framework is a single address space, distributed memory programming model. We use efficient techniques for distributing and coalescing data as well as efficient combinations of task and data parallelism. The image segmentation algorithm makes use of an efficient cluster process which uses a novel approach for parallel merging. Our experimental results are consistent with the theoretical analysis and practical results. It provides the faster execution time for segmentation, when compared with Conventional method. Our test data is different CT scan images from the Medical database. More efficient implementations of Image Segmentation will likely result in even faster execution times.

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

Energy Technology Data Exchange (ETDEWEB)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich [Departments of Electrical and Computer Engineering and Internal Medicine, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16, A-8010 Graz (Austria); Department of Electrical and Computer Engineering, Iowa Institute for Biomedical Imaging, University of Iowa, Iowa City, Iowa 52242 (United States); Department of Radiology, Medical University Graz, Auenbruggerplatz 34, A-8010 Graz (Austria)

2012-03-15

Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods

International Nuclear Information System (INIS)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

2012-01-01

Purpose: Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. Methods: A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and/or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Results: Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of

Liver segmentation in contrast enhanced CT data using graph cuts and interactive 3D segmentation refinement methods.

Science.gov (United States)

Beichel, Reinhard; Bornik, Alexander; Bauer, Christian; Sorantin, Erich

2012-03-01

Liver segmentation is an important prerequisite for the assessment of liver cancer treatment options like tumor resection, image-guided radiation therapy (IGRT), radiofrequency ablation, etc. The purpose of this work was to evaluate a new approach for liver segmentation. A graph cuts segmentation method was combined with a three-dimensional virtual reality based segmentation refinement approach. The developed interactive segmentation system allowed the user to manipulate volume chunks and∕or surfaces instead of 2D contours in cross-sectional images (i.e, slice-by-slice). The method was evaluated on twenty routinely acquired portal-phase contrast enhanced multislice computed tomography (CT) data sets. An independent reference was generated by utilizing a currently clinically utilized slice-by-slice segmentation method. After 1 h of introduction to the developed segmentation system, three experts were asked to segment all twenty data sets with the proposed method. Compared to the independent standard, the relative volumetric segmentation overlap error averaged over all three experts and all twenty data sets was 3.74%. Liver segmentation required on average 16 min of user interaction per case. The calculated relative volumetric overlap errors were not found to be significantly different [analysis of variance (ANOVA) test, p = 0.82] between experts who utilized the proposed 3D system. In contrast, the time required by each expert for segmentation was found to be significantly different (ANOVA test, p = 0.0009). Major differences between generated segmentations and independent references were observed in areas were vessels enter or leave the liver and no accepted criteria for defining liver boundaries exist. In comparison, slice-by-slice based generation of the independent standard utilizing a live wire tool took 70.1 min on average. A standard 2D segmentation refinement approach applied to all twenty data sets required on average 38.2 min of user interaction

Cluster Ensemble-Based Image Segmentation

Directory of Open Access Journals (Sweden)

Xiaoru Wang

2013-07-01

Full Text Available Image segmentation is the foundation of computer vision applications. In this paper, we propose a new cluster ensemble-based image segmentation algorithm, which overcomes several problems of traditional methods. We make two main contributions in this paper. First, we introduce the cluster ensemble concept to fuse the segmentation results from different types of visual features effectively, which can deliver a better final result and achieve a much more stable performance for broad categories of images. Second, we exploit the PageRank idea from Internet applications and apply it to the image segmentation task. This can improve the final segmentation results by combining the spatial information of the image and the semantic similarity of regions. Our experiments on four public image databases validate the superiority of our algorithm over conventional single type of feature or multiple types of features-based algorithms, since our algorithm can fuse multiple types of features effectively for better segmentation results. Moreover, our method is also proved to be very competitive in comparison with other state-of-the-art segmentation algorithms.

Albedo estimation for scene segmentation

Energy Technology Data Exchange (ETDEWEB)

Lee, C H; Rosenfeld, A

1983-03-01

Standard methods of image segmentation do not take into account the three-dimensional nature of the underlying scene. For example, histogram-based segmentation tacitly assumes that the image intensity is piecewise constant, and this is not true when the scene contains curved surfaces. This paper introduces a method of taking 3d information into account in the segmentation process. The image intensities are adjusted to compensate for the effects of estimated surface orientation; the adjusted intensities can be regarded as reflectivity estimates. When histogram-based segmentation is applied to these new values, the image is segmented into parts corresponding to surfaces of constant reflectivity in the scene. 7 references.

Segmenting the Adult Education Market.

Science.gov (United States)

Aurand, Tim

1994-01-01

Describes market segmentation and how the principles of segmentation can be applied to the adult education market. Indicates that applying segmentation techniques to adult education programs results in programs that are educationally and financially satisfying and serve an appropriate population. (JOW)

Gamifying Video Object Segmentation.

Science.gov (United States)

Spampinato, Concetto; Palazzo, Simone; Giordano, Daniela

2017-10-01

Video object segmentation can be considered as one of the most challenging computer vision problems. Indeed, so far, no existing solution is able to effectively deal with the peculiarities of real-world videos, especially in cases of articulated motion and object occlusions; limitations that appear more evident when we compare the performance of automated methods with the human one. However, manually segmenting objects in videos is largely impractical as it requires a lot of time and concentration. To address this problem, in this paper we propose an interactive video object segmentation method, which exploits, on one hand, the capability of humans to identify correctly objects in visual scenes, and on the other hand, the collective human brainpower to solve challenging and large-scale tasks. In particular, our method relies on a game with a purpose to collect human inputs on object locations, followed by an accurate segmentation phase achieved by optimizing an energy function encoding spatial and temporal constraints between object regions as well as human-provided location priors. Performance analysis carried out on complex video benchmarks, and exploiting data provided by over 60 users, demonstrated that our method shows a better trade-off between annotation times and segmentation accuracy than interactive video annotation and automated video object segmentation approaches.

INDC/NEANDC nuclear standards file 1980 version

International Nuclear Information System (INIS)

1981-09-01

This working document of the Nuclear Standards Subcommittee of the International Nuclear Data Committee (INDC) summarizes the status of nuclear standards as of the 11th INDC meeting (6/'80) with selective updating to approximately 5/'81. This version of the file is presented in two sections as per the following. The first section (A) consists of numerical tabulations of the respective quantities generally including quantitative definition of the uncertainties. Most of these numerical values are taken from the ENDF/B-V file which is available on a world-wide basis through the 4-Center network. Some guidelines as to appropriate usage are also given. The objective is the provision of a concise and readily used reference guide to essential standard-nuclear quantities useful for a diversity of basic and applied endeavors. The second section (B) briefly summarizes the contemporary status of each of the standards tabulated in Section A and additional items, including recent relevant work and areas of continuing uncertainty. These brief reviews were prepared under the auspices of the Committee by outstanding specialists in the respective fields. In many instances they are new statements but, where review indicates that the previous statement (see INDC-30/L+sp) remains appropriate, the previous summaries were retained; often with additional remarks by the editor

User's manual (UM) for the enhanced logistics intratheater support tool (ELIST) software segment version 8.1.0.0 for solaris 7.; TOPICAL

International Nuclear Information System (INIS)

Dritz, K.

2002-01-01

This document is the User's Manual (UM) for the Enhanced Logistics Intratheater Support Tool (ELIST) Software Segment. It tells how to use the end-user and administrative features of the segment. The instructions in Sections 4.2.1, 5.3.1, and 5.3.2 for the end-user features (Run ELIST and Run ETEdit) only cover the launching of those features in the DII COE environment; full details on the operation of ELIST and ETEdit in any environment can be found in the documents listed in Section 2.1.3 and referenced elsewhere in this document. On the other hand, complete instructions for the administrative features (Add Map Data and Delete Map Data) are presented in Sections 4.2.2, 5.3.3, and 5.3.4 of this document

U.S. Army Custom Segmentation System

Science.gov (United States)

2007-06-01

segmentation is individual or intergroup differences in response to marketing - mix variables. Presumptions about segments: •different demands in a...product or service category, •respond differently to changes in the marketing mix Criteria for segments: •The segments must exist in the environment

Normatization of the symbol digit modalities test-oral version in a Latin American country.

Science.gov (United States)

Vanotti, Sandra; Cores, Evangelina Valeria; Eizaguirre, Barbara; Angeles, Merino; Rey, Raul; Villa, Andres; Cáceres, Fernando

2015-01-01

The aim of this study was to standardize the Symbol Digit Modalities Test (SDMT)-Oral version in a healthy population living in Argentina and to analyze the influence that age, gender, and education have on the SDMT. Secondarily, it is intended to analyze the performance of patients with multiple sclerosis (MS) on this test. Two hundred ninety-seven healthy participants were evaluated; they had an average age of 39.28 years and 13.87 years of schooling; 77.8% were women. The sample was segmented according to age in three groups: younger than 35 years old, 36 to 50 years old, and 51 to 70 years old. The sample was also segmented according to years of schooling in three groups: 11 years or less, 12 to 16 years, and more than 16 years. All participants were evaluated with the oral version of the SDMT. A clinical sample of 111 patients with MS was also assessed. The mean on the SDMT for the total sample was 51.34 (SD=12.76). The differences were significant between all groups, p<.05, according to age. The participants with a higher level of education performed better than did those with moderate education and those with less schooling, p<.05. There was a significant difference between patients with MS and healthy controls, p<.01. The SDMT is influenced by age as well as by schooling, although not by gender. The norms displayed here will be useful to accurately evaluate the yield of the patients in the neuropsychological clinic when comparing them with their group of reference. It was also demonstrated that the SDMT can discriminate between patients with MS and healthy people.

Poly(ether amide) segmented block copolymers with adipicacid based tetra amide segments

NARCIS (Netherlands)

Biemond, G.J.E.; Feijen, Jan; Gaymans, R.J.

2007-01-01

Poly(tetramethylene oxide)-based poly(ether ester amide)s with monodisperse tetraamide segments were synthesized. The tetraamide segment was based on adipic acid, terephthalic acid, and hexamethylenediamine. The synthesis method of the copolymers and the influence of the tetraamide concentration,

Metric Learning for Hyperspectral Image Segmentation

Science.gov (United States)

Bue, Brian D.; Thompson, David R.; Gilmore, Martha S.; Castano, Rebecca

2011-01-01

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Correspondence of Concept Hierarchies in Semantic Web Based upon Global Instances and its Application to Facility Management Database

Science.gov (United States)

Takahashi, Hiroki; Nishi, Yuusuke; Gion, Tomohiro; Minami, Shinichi; Fukunaga, Tatsuya; Ogata, Jiro; Yoshie, Osamu

Semantic Web is the technology which determines the relevance of data over the Web using meta-data and which enables advanced search of global information. It is now desired to develop and apply this technology to many situations of facility management. In facility management, vocabulary should be unified to share the database of facilities for generating optimal maintenance schedule and so on. Under such situations, ontology databases are usually used to describe composition or hierarchy of facility parts. However, these vocabularies used in databases are not unified even between factories of same company, and this situation causes communication hazard between them. Moreover, concept involved in the hierarchy cannot be corresponded each other. There are some methods to correspond concepts of different hierarchy. But these methods have some defects, because they only attend target hierarchy itself and the number of instances. We propose improved method for corresponding concepts between different concepts' hierarchies, which uses other hierarchies all over the world of Web and the distance of instances to identify their relations. Our method can work even if the sets of instances belonging to the concepts are not identical.

Market Segmentation for Information Services.

Science.gov (United States)

Halperin, Michael

1981-01-01

Discusses the advantages and limitations of market segmentation as strategy for the marketing of information services made available by nonprofit organizations, particularly libraries. Market segmentation is defined, a market grid for libraries is described, and the segmentation of information services is outlined. A 16-item reference list is…

Probabilistic Segmentation of Folk Music Recordings

Directory of Open Access Journals (Sweden)

Ciril Bohak

2016-01-01

Full Text Available The paper presents a novel method for automatic segmentation of folk music field recordings. The method is based on a distance measure that uses dynamic time warping to cope with tempo variations and a dynamic programming approach to handle pitch drifting for finding similarities and estimating the length of repeating segment. A probabilistic framework based on HMM is used to find segment boundaries, searching for optimal match between the expected segment length, between-segment similarities, and likely locations of segment beginnings. Evaluation of several current state-of-the-art approaches for segmentation of commercial music is presented and their weaknesses when dealing with folk music are exposed, such as intolerance to pitch drift and variable tempo. The proposed method is evaluated and its performance analyzed on a collection of 206 folk songs of different ensemble types: solo, two- and three-voiced, choir, instrumental, and instrumental with singing. It outperforms current commercial music segmentation methods for noninstrumental music and is on a par with the best for instrumental recordings. The method is also comparable to a more specialized method for segmentation of solo singing folk music recordings.

Automated medical image segmentation techniques

Directory of Open Access Journals (Sweden)

Sharma Neeraj

2010-01-01

Full Text Available Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT and Magnetic resonance (MR imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images.

Prognostic validation of a 17-segment score derived from a 20-segment score for myocardial perfusion SPECT interpretation.

Science.gov (United States)

Berman, Daniel S; Abidov, Aiden; Kang, Xingping; Hayes, Sean W; Friedman, John D; Sciammarella, Maria G; Cohen, Ishac; Gerlach, James; Waechter, Parker B; Germano, Guido; Hachamovitch, Rory

2004-01-01

Recently, a 17-segment model of the left ventricle has been recommended as an optimally weighted approach for interpreting myocardial perfusion single photon emission computed tomography (SPECT). Methods to convert databases from previous 20- to new 17-segment data and criteria for abnormality for the 17-segment scores are needed. Initially, for derivation of the conversion algorithm, 65 patients were studied (algorithm population) (pilot group, n = 28; validation group, n = 37). Three conversion algorithms were derived: algorithm 1, which used mid, distal, and apical scores; algorithm 2, which used distal and apical scores alone; and algorithm 3, which used maximal scores of the distal septal, lateral, and apical segments in the 20-segment model for 3 corresponding segments of the 17-segment model. The prognosis population comprised 16,020 consecutive patients (mean age, 65 +/- 12 years; 41% women) who had exercise or vasodilator stress technetium 99m sestamibi myocardial perfusion SPECT and were followed up for 2.1 +/- 0.8 years. In this population, 17-segment scores were derived from 20-segment scores by use of algorithm 2, which demonstrated the best agreement with expert 17-segment reading in the algorithm population. The prognostic value of the 20- and 17-segment scores was compared by converting the respective summed scores into percent myocardium abnormal. Conversion algorithm 2 was found to be highly concordant with expert visual analysis by the 17-segment model (r = 0.982; kappa = 0.866) in the algorithm population. In the prognosis population, 456 cardiac deaths occurred during follow-up. When the conversion algorithm was applied, extent and severity of perfusion defects were nearly identical by 20- and derived 17-segment scores. The receiver operating characteristic curve areas by 20- and 17-segment perfusion scores were identical for predicting cardiac death (both 0.77 +/- 0.02, P = not significant). The optimal prognostic cutoff value for either 20

Emancipation trough the Artistic Experience and the Meaning of Handicap as Instance of Otherness

Directory of Open Access Journals (Sweden)

Robi Kroflič

2014-03-01

Full Text Available The key hypothesis of the article is that successful inter-mediation of art to vulnerable groups of people (including children depends on the correct identification of the nature of an artistic act and on the meaning that handicap—as an instance of otherness—has in the life of artists and spectators. A just access to the artistic experience is basically not the question of the distribution of artistic production (since if artistic object is principally accessible to all people, it will not reach vulnerable groups of spectators, but of ensuring artistic creativity and presentation. This presupposes a spectator as a competent being who is able to interact with the artistic object without our interpretative explanation and who is sensible to the instance of otherness (handicap is merely a specific form of otherness. The theory of emancipation from J. Ranciere, the theory of recognition from A. Honneth, and the theory of narration from P. Ricoeur and R. Kearney, as well as our experiences with a comprehensive inductive approach and artistic experience as one of its basic educational methods offer us a theoretical framework for such a model of art inter-mediation.

NUCLEAR SEGMENTATION IN MICROSCOPE CELL IMAGES: A HAND-SEGMENTED DATASET AND COMPARISON OF ALGORITHMS

OpenAIRE

Coelho, Luís Pedro; Shariff, Aabid; Murphy, Robert F.

2009-01-01

Image segmentation is an essential step in many image analysis pipelines and many algorithms have been proposed to solve this problem. However, they are often evaluated subjectively or based on a small number of examples. To fill this gap, we hand-segmented a set of 97 fluorescence microscopy images (a total of 4009 cells) and objectively evaluated some previously proposed segmentation algorithms.

Generalized pixel profiling and comparative segmentation with application to arteriovenous malformation segmentation.

Science.gov (United States)

Babin, D; Pižurica, A; Bellens, R; De Bock, J; Shang, Y; Goossens, B; Vansteenkiste, E; Philips, W

2012-07-01

Extraction of structural and geometric information from 3-D images of blood vessels is a well known and widely addressed segmentation problem. The segmentation of cerebral blood vessels is of great importance in diagnostic and clinical applications, with a special application in diagnostics and surgery on arteriovenous malformations (AVM). However, the techniques addressing the problem of the AVM inner structure segmentation are rare. In this work we present a novel method of pixel profiling with the application to segmentation of the 3-D angiography AVM images. Our algorithm stands out in situations with low resolution images and high variability of pixel intensity. Another advantage of our method is that the parameters are set automatically, which yields little manual user intervention. The results on phantoms and real data demonstrate its effectiveness and potentials for fine delineation of AVM structure. Copyright © 2012 Elsevier B.V. All rights reserved.

Robust shape regression for supervised vessel segmentation and its application to coronary segmentation in CTA

DEFF Research Database (Denmark)

Schaap, Michiel; van Walsum, Theo; Neefjes, Lisan

2011-01-01

This paper presents a vessel segmentation method which learns the geometry and appearance of vessels in medical images from annotated data and uses this knowledge to segment vessels in unseen images. Vessels are segmented in a coarse-to-fine fashion. First, the vessel boundaries are estimated...

Vortex dynamics in nonrelativistic version of Abelian Higgs model: Effects of the medium on the vortex motion

Directory of Open Access Journals (Sweden)

Kozhevnikov Arkadii

2016-01-01

Full Text Available The closed vortex dynamics is considered in the nonrelativistic version of the Abelian Higgs Model. The effect of the exchange of excitations propagating in the medium on the vortex string motion is taken into account. The obtained are the effective action and the equation of motion both including the exchange of the propagating excitations between the distant segments of the vortex and the possibility of its interaction with the static fermion asymmetric background. They are applied to the derivation of the time dependence of the basic geometrical contour characteristics.

Automatic segmentation of phase-correlated CT scans through nonrigid image registration using geometrically regularized free-form deformation

International Nuclear Information System (INIS)

Shekhar, Raj; Lei, Peng; Castro-Pareja, Carlos R.; Plishker, William L.; D'Souza, Warren D.

2007-01-01

Conventional radiotherapy is planned using free-breathing computed tomography (CT), ignoring the motion and deformation of the anatomy from respiration. New breath-hold-synchronized, gated, and four-dimensional (4D) CT acquisition strategies are enabling radiotherapy planning utilizing a set of CT scans belonging to different phases of the breathing cycle. Such 4D treatment planning relies on the availability of tumor and organ contours in all phases. The current practice of manual segmentation is impractical for 4D CT, because it is time consuming and tedious. A viable solution is registration-based segmentation, through which contours provided by an expert for a particular phase are propagated to all other phases while accounting for phase-to-phase motion and anatomical deformation. Deformable image registration is central to this task, and a free-form deformation-based nonrigid image registration algorithm will be presented. Compared with the original algorithm, this version uses novel, computationally simpler geometric constraints to preserve the topology of the dense control-point grid used to represent free-form deformation and prevent tissue fold-over. Using mean squared difference as an image similarity criterion, the inhale phase is registered to the exhale phase of lung CT scans of five patients and of characteristically low-contrast abdominal CT scans of four patients. In addition, using expert contours for the inhale phase, the corresponding contours were automatically generated for the exhale phase. The accuracy of the segmentation (and hence deformable image registration) was judged by comparing automatically segmented contours with expert contours traced directly in the exhale phase scan using three metrics: volume overlap index, root mean square distance, and Hausdorff distance. The accuracy of the segmentation (in terms of radial distance mismatch) was approximately 2 mm in the thorax and 3 mm in the abdomen, which compares favorably to the

Structure-properties relationships of novel poly(carbonate-co-amide) segmented copolymers with polyamide-6 as hard segments and polycarbonate as soft segments

Science.gov (United States)

Yang, Yunyun; Kong, Weibo; Yuan, Ye; Zhou, Changlin; Cai, Xufu

2018-04-01

Novel poly(carbonate-co-amide) (PCA) block copolymers are prepared with polycarbonate diol (PCD) as soft segments, polyamide-6 (PA6) as hard segments and 4,4'-diphenylmethane diisocyanate (MDI) as coupling agent through reactive processing. The reactive processing strategy is eco-friendly and resolve the incompatibility between polyamide segments and PCD segments in preparation processing. The chemical structure, crystalline properties, thermal properties, mechanical properties and water resistance were extensively studied by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Differential scanning calorimetry (DSC), Thermal gravity analysis (TGA), Dynamic mechanical analysis (DMA), tensile testing, water contact angle and water absorption, respectively. The as-prepared PCAs exhibit obvious microphase separation between the crystalline hard PA6 phase and amorphous PCD soft segments. Meanwhile, PCAs showed outstanding mechanical with the maximum tensile strength of 46.3 MPa and elongation at break of 909%. The contact angle and water absorption results indicate that PCAs demonstrate outstanding water resistance even though possess the hydrophilic surfaces. The TGA measurements prove that the thermal stability of PCA can satisfy the requirement of multiple-processing without decomposition.

Segmentation and informality in Vietnam : a survey of the literature: country case study on labour market segmentation

OpenAIRE

Cling, Jean-Pierre; Razafindrakoto, Mireille; Roubaud, François

2014-01-01

Labour market segmentation is usually defined as the division of the labour markets into separate sub-markets or segments, distinguished by different characteristics and behavioural rules (incomes, contracts, etc.). The economic debate on the segmentation issue has been focusing in developed countries, and especially in Europe, on contractual segmentation and dualism.

Global Historical Climatology Network - Daily (GHCN-Daily), Version 2 (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Please note, this dataset has been superseded by a newer version (see below). Users should not use this version except in rare cases (e.g., when reproducing previous...

Segmentation by Large Scale Hypothesis Testing - Segmentation as Outlier Detection

DEFF Research Database (Denmark)

Darkner, Sune; Dahl, Anders Lindbjerg; Larsen, Rasmus

2010-01-01

a microscope and we show how the method can handle transparent particles with significant glare point. The method generalizes to other problems. THis is illustrated by applying the method to camera calibration images and MRI of the midsagittal plane for gray and white matter separation and segmentation......We propose a novel and efficient way of performing local image segmentation. For many applications a threshold of pixel intensities is sufficient but determine the appropriate threshold value can be difficult. In cases with large global intensity variation the threshold value has to be adapted...... locally. We propose a method based on large scale hypothesis testing with a consistent method for selecting an appropriate threshold for the given data. By estimating the background distribution we characterize the segment of interest as a set of outliers with a certain probability based on the estimated...

Detection and analysis of ancient segmental duplications in mammalian genomes.

Science.gov (United States)

Pu, Lianrong; Lin, Yu; Pevzner, Pavel A

2018-05-07

Although segmental duplications (SDs) represent hotbeds for genomic rearrangements and emergence of new genes, there are still no easy-to-use tools for identifying SDs. Moreover, while most previous studies focused on recently emerged SDs, detection of ancient SDs remains an open problem. We developed an SDquest algorithm for SD finding and applied it to analyzing SDs in human, gorilla, and mouse genomes. Our results demonstrate that previous studies missed many SDs in these genomes and show that SDs account for at least 6.05% of the human genome (version hg19), a 17% increase as compared to the previous estimate. Moreover, SDquest classified 6.42% of the latest GRCh38 version of the human genome as SDs, a large increase as compared to previous studies. We thus propose to re-evaluate evolution of SDs based on their accurate representation across multiple genomes. Toward this goal, we analyzed the complex mosaic structure of SDs and decomposed mosaic SDs into elementary SDs, a prerequisite for follow-up evolutionary analysis. We also introduced the concept of the breakpoint graph of mosaic SDs that revealed SD hotspots and suggested that some SDs may have originated from circular extrachromosomal DNA (ecDNA), not unlike ecDNA that contributes to accelerated evolution in cancer. © 2018 Pu et al.; Published by Cold Spring Harbor Laboratory Press.

Joint Segmentation and Shape Regularization with a Generalized Forward Backward Algorithm.

Science.gov (United States)

Stefanoiu, Anca; Weinmann, Andreas; Storath, Martin; Navab, Nassir; Baust, Maximilian

2016-05-11

This paper presents a method for the simultaneous segmentation and regularization of a series of shapes from a corresponding sequence of images. Such series arise as time series of 2D images when considering video data, or as stacks of 2D images obtained by slicewise tomographic reconstruction. We first derive a model where the regularization of the shape signal is achieved by a total variation prior on the shape manifold. The method employs a modified Kendall shape space to facilitate explicit computations together with the concept of Sobolev gradients. For the proposed model, we derive an efficient and computationally accessible splitting scheme. Using a generalized forward-backward approach, our algorithm treats the total variation atoms of the splitting via proximal mappings, whereas the data terms are dealt with by gradient descent. The potential of the proposed method is demonstrated on various application examples dealing with 3D data. We explain how to extend the proposed combined approach to shape fields which, for instance, arise in the context of 3D+t imaging modalities, and show an application in this setup as well.

Pavement management segment consolidation

Science.gov (United States)

1998-01-01

Dividing roads into "homogeneous" segments has been a major problem for all areas of highway engineering. SDDOT uses Deighton Associates Limited software, dTIMS, to analyze life-cycle costs for various rehabilitation strategies on each segment of roa...

User's manual (UM) for the enhanced logistics intratheater support tool (ELIST) database utility segment version 8.1.0.0 for solaris 7.; TOPICAL

International Nuclear Information System (INIS)

Dritz, K.

2002-01-01

This document is the User's Manual (UM) for the Enhanced Logistics Intratheater Support Tool (ELIST) Database Utility Segment. It tells how to use its features to administer ELIST database user accounts

Automatic segmentation of vertebrae from radiographs

DEFF Research Database (Denmark)

Mysling, Peter; Petersen, Peter Kersten; Nielsen, Mads

2011-01-01

Segmentation of vertebral contours is an essential task in the design of automatic tools for vertebral fracture assessment. In this paper, we propose a novel segmentation technique which does not require operator interaction. The proposed technique solves the segmentation problem in a hierarchical...... is constrained by a conditional shape model, based on the variability of the coarse spine location estimates. The technique is evaluated on a data set of manually annotated lumbar radiographs. The results compare favorably to the previous work in automatic vertebra segmentation, in terms of both segmentation...

A combined segmenting and non-segmenting approach to signal quality estimation for ambulatory photoplethysmography

International Nuclear Information System (INIS)

Wander, J D; Morris, D

2014-01-01

Continuous cardiac monitoring of healthy and unhealthy patients can help us understand the progression of heart disease and enable early treatment. Optical pulse sensing is an excellent candidate for continuous mobile monitoring of cardiovascular health indicators, but optical pulse signals are susceptible to corruption from a number of noise sources, including motion artifact. Therefore, before higher-level health indicators can be reliably computed, corrupted data must be separated from valid data. This is an especially difficult task in the presence of artifact caused by ambulation (e.g. walking or jogging), which shares significant spectral energy with the true pulsatile signal. In this manuscript, we present a machine-learning-based system for automated estimation of signal quality of optical pulse signals that performs well in the presence of periodic artifact. We hypothesized that signal processing methods that identified individual heart beats (segmenting approaches) would be more error-prone than methods that did not (non-segmenting approaches) when applied to data contaminated by periodic artifact. We further hypothesized that a fusion of segmenting and non-segmenting approaches would outperform either approach alone. Therefore, we developed a novel non-segmenting approach to signal quality estimation that we then utilized in combination with a traditional segmenting approach. Using this system we were able to robustly detect differences in signal quality as labeled by expert human raters (Pearson’s r = 0.9263). We then validated our original hypotheses by demonstrating that our non-segmenting approach outperformed the segmenting approach in the presence of contaminated signal, and that the combined system outperformed either individually. Lastly, as an example, we demonstrated the utility of our signal quality estimation system in evaluating the trustworthiness of heart rate measurements derived from optical pulse signals. (paper)

Rhythm-based segmentation of Popular Chinese Music

DEFF Research Database (Denmark)

Jensen, Karl Kristoffer

2005-01-01

We present a new method to segment popular music based on rhythm. By computing a shortest path based on the self-similarity matrix calculated from a model of rhythm, segmenting boundaries are found along the di- agonal of the matrix. The cost of a new segment is opti- mized by matching manual...... and automatic segment boundaries. We compile a small song database of 21 randomly selected popular Chinese songs which come from Chinese Mainland, Taiwan and Hong Kong. The segmenting results on the small corpus show that 78% manual segmentation points are detected and 74% auto- matic segmentation points...

Unsupervised Performance Evaluation of Image Segmentation

Directory of Open Access Journals (Sweden)

Chabrier Sebastien

2006-01-01

Full Text Available We present in this paper a study of unsupervised evaluation criteria that enable the quantification of the quality of an image segmentation result. These evaluation criteria compute some statistics for each region or class in a segmentation result. Such an evaluation criterion can be useful for different applications: the comparison of segmentation results, the automatic choice of the best fitted parameters of a segmentation method for a given image, or the definition of new segmentation methods by optimization. We first present the state of art of unsupervised evaluation, and then, we compare six unsupervised evaluation criteria. For this comparative study, we use a database composed of 8400 synthetic gray-level images segmented in four different ways. Vinet's measure (correct classification rate is used as an objective criterion to compare the behavior of the different criteria. Finally, we present the experimental results on the segmentation evaluation of a few gray-level natural images.

Methods of evaluating segmentation characteristics and segmentation of major faults

Energy Technology Data Exchange (ETDEWEB)

Lee, Kie Hwa; Chang, Tae Woo; Kyung, Jai Bok [Seoul National Univ., Seoul (Korea, Republic of)] (and others)

2000-03-15

Seismological, geological, and geophysical studies were made for reasonable segmentation of the Ulsan fault and the results are as follows. One- and two- dimensional electrical surveys revealed clearly the fault fracture zone enlarges systematically northward and southward from the vicinity of Mohwa-ri, indicating Mohwa-ri is at the seismic segment boundary. Field Geological survey and microscope observation of fault gouge indicates that the Quaternary faults in the area are reactivated products of the preexisting faults. Trench survey of the Chonbuk fault Galgok-ri revealed thrust faults and cumulative vertical displacement due to faulting during the late Quaternary with about 1.1-1.9 m displacement per event; the latest event occurred from 14000 to 25000 yrs. BP. The seismic survey showed the basement surface os cut by numerous reverse faults and indicated the possibility that the boundary between Kyeongsangbukdo and Kyeongsannamdo may be segment boundary.

Methods of evaluating segmentation characteristics and segmentation of major faults

International Nuclear Information System (INIS)

Lee, Kie Hwa; Chang, Tae Woo; Kyung, Jai Bok

2000-03-01

Seismological, geological, and geophysical studies were made for reasonable segmentation of the Ulsan fault and the results are as follows. One- and two- dimensional electrical surveys revealed clearly the fault fracture zone enlarges systematically northward and southward from the vicinity of Mohwa-ri, indicating Mohwa-ri is at the seismic segment boundary. Field Geological survey and microscope observation of fault gouge indicates that the Quaternary faults in the area are reactivated products of the preexisting faults. Trench survey of the Chonbuk fault Galgok-ri revealed thrust faults and cumulative vertical displacement due to faulting during the late Quaternary with about 1.1-1.9 m displacement per event; the latest event occurred from 14000 to 25000 yrs. BP. The seismic survey showed the basement surface os cut by numerous reverse faults and indicated the possibility that the boundary between Kyeongsangbukdo and Kyeongsannamdo may be segment boundary

A new framework for interactive images segmentation

International Nuclear Information System (INIS)

Ashraf, M.; Sarim, M.; Shaikh, A.B.

2017-01-01

Image segmentation has become a widely studied research problem in image processing. There exist different graph based solutions for interactive image segmentation but the domain of image segmentation still needs persistent improvements. The segmentation quality of existing techniques generally depends on the manual input provided in beginning, therefore, these algorithms may not produce quality segmentation with initial seed labels provided by a novice user. In this work we investigated the use of cellular automata in image segmentation and proposed a new algorithm that follows a cellular automaton in label propagation. It incorporates both the pixel's local and global information in the segmentation process. We introduced the novel global constraints in automata evolution rules; hence proposed scheme of automata evolution is more effective than the automata based earlier evolution schemes. Global constraints are also effective in deceasing the sensitivity towards small changes made in manual input; therefore proposed approach is less dependent on label seed marks. It can produce the quality segmentation with modest user efforts. Segmentation results indicate that the proposed algorithm performs better than the earlier segmentation techniques. (author)

International EUREKA: Initialization Segment

International Nuclear Information System (INIS)

1982-02-01

The Initialization Segment creates the starting description of the uranium market. The starting description includes the international boundaries of trade, the geologic provinces, resources, reserves, production, uranium demand forecasts, and existing market transactions. The Initialization Segment is designed to accept information of various degrees of detail, depending on what is known about each region. It must transform this information into a specific data structure required by the Market Segment of the model, filling in gaps in the information through a predetermined sequence of defaults and built in assumptions. A principal function of the Initialization Segment is to create diagnostic messages indicating any inconsistencies in data and explaining which assumptions were used to organize the data base. This permits the user to manipulate the data base until such time the user is satisfied that all the assumptions used are reasonable and that any inconsistencies are resolved in a satisfactory manner

Image Segmentation Using Minimum Spanning Tree

Science.gov (United States)

Dewi, M. P.; Armiati, A.; Alvini, S.

2018-04-01

This research aim to segmented the digital image. The process of segmentation is to separate the object from the background. So the main object can be processed for the other purposes. Along with the development of technology in digital image processing application, the segmentation process becomes increasingly necessary. The segmented image which is the result of the segmentation process should accurate due to the next process need the interpretation of the information on the image. This article discussed the application of minimum spanning tree on graph in segmentation process of digital image. This method is able to separate an object from the background and the image will change to be the binary images. In this case, the object that being the focus is set in white, while the background is black or otherwise.

Mild toxic anterior segment syndrome mimicking delayed onset toxic anterior segment syndrome after cataract surgery

Directory of Open Access Journals (Sweden)

Su-Na Lee

2014-01-01

Full Text Available Toxic anterior segment syndrome (TASS is an acute sterile postoperative anterior segment inflammation that may occur after anterior segment surgery. I report herein a case that developed mild TASS in one eye after bilateral uneventful cataract surgery, which was masked during early postoperative period under steroid eye drop and mimicking delayed onset TASS after switching to weaker steroid eye drop.

Scorpion image segmentation system

Science.gov (United States)

Joseph, E.; Aibinu, A. M.; Sadiq, B. A.; Bello Salau, H.; Salami, M. J. E.

2013-12-01

Death as a result of scorpion sting has been a major public health problem in developing countries. Despite the high rate of death as a result of scorpion sting, little report exists in literature of intelligent device and system for automatic detection of scorpion. This paper proposed a digital image processing approach based on the floresencing characteristics of Scorpion under Ultra-violet (UV) light for automatic detection and identification of scorpion. The acquired UV-based images undergo pre-processing to equalize uneven illumination and colour space channel separation. The extracted channels are then segmented into two non-overlapping classes. It has been observed that simple thresholding of the green channel of the acquired RGB UV-based image is sufficient for segmenting Scorpion from other background components in the acquired image. Two approaches to image segmentation have also been proposed in this work, namely, the simple average segmentation technique and K-means image segmentation. The proposed algorithm has been tested on over 40 UV scorpion images obtained from different part of the world and results obtained show an average accuracy of 97.7% in correctly classifying the pixel into two non-overlapping clusters. The proposed 1system will eliminate the problem associated with some of the existing manual approaches presently in use for scorpion detection.

Brain Tumor Image Segmentation in MRI Image

Science.gov (United States)

Peni Agustin Tjahyaningtijas, Hapsari

2018-04-01

Brain tumor segmentation plays an important role in medical image processing. Treatment of patients with brain tumors is highly dependent on early detection of these tumors. Early detection of brain tumors will improve the patient’s life chances. Diagnosis of brain tumors by experts usually use a manual segmentation that is difficult and time consuming because of the necessary automatic segmentation. Nowadays automatic segmentation is very populer and can be a solution to the problem of tumor brain segmentation with better performance. The purpose of this paper is to provide a review of MRI-based brain tumor segmentation methods. There are number of existing review papers, focusing on traditional methods for MRI-based brain tumor image segmentation. this paper, we focus on the recent trend of automatic segmentation in this field. First, an introduction to brain tumors and methods for brain tumor segmentation is given. Then, the state-of-the-art algorithms with a focus on recent trend of full automatic segmentaion are discussed. Finally, an assessment of the current state is presented and future developments to standardize MRI-based brain tumor segmentation methods into daily clinical routine are addressed.

Colour application on mammography image segmentation

Science.gov (United States)

Embong, R.; Aziz, N. M. Nik Ab.; Karim, A. H. Abd; Ibrahim, M. R.

2017-09-01

The segmentation process is one of the most important steps in image processing and computer vision since it is vital in the initial stage of image analysis. Segmentation of medical images involves complex structures and it requires precise segmentation result which is necessary for clinical diagnosis such as the detection of tumour, oedema, and necrotic tissues. Since mammography images are grayscale, researchers are looking at the effect of colour in the segmentation process of medical images. Colour is known to play a significant role in the perception of object boundaries in non-medical colour images. Processing colour images require handling more data, hence providing a richer description of objects in the scene. Colour images contain ten percent (10%) additional edge information as compared to their grayscale counterparts. Nevertheless, edge detection in colour image is more challenging than grayscale image as colour space is considered as a vector space. In this study, we implemented red, green, yellow, and blue colour maps to grayscale mammography images with the purpose of testing the effect of colours on the segmentation of abnormality regions in the mammography images. We applied the segmentation process using the Fuzzy C-means algorithm and evaluated the percentage of average relative error of area for each colour type. The results showed that all segmentation with the colour map can be done successfully even for blurred and noisy images. Also the size of the area of the abnormality region is reduced when compare to the segmentation area without the colour map. The green colour map segmentation produced the smallest percentage of average relative error (10.009%) while yellow colour map segmentation gave the largest percentage of relative error (11.367%).

A computational atlas of the hippocampal formation using ex vivo, ultra-high resolution MRI: Application to adaptive segmentation of in vivo MRI.

Science.gov (United States)

Iglesias, Juan Eugenio; Augustinack, Jean C; Nguyen, Khoa; Player, Christopher M; Player, Allison; Wright, Michelle; Roy, Nicole; Frosch, Matthew P; McKee, Ann C; Wald, Lawrence L; Fischl, Bruce; Van Leemput, Koen

2015-07-15

Automated analysis of MRI data of the subregions of the hippocampus requires computational atlases built at a higher resolution than those that are typically used in current neuroimaging studies. Here we describe the construction of a statistical atlas of the hippocampal formation at the subregion level using ultra-high resolution, ex vivo MRI. Fifteen autopsy samples were scanned at 0.13 mm isotropic resolution (on average) using customized hardware. The images were manually segmented into 13 different hippocampal substructures using a protocol specifically designed for this study; precise delineations were made possible by the extraordinary resolution of the scans. In addition to the subregions, manual annotations for neighboring structures (e.g., amygdala, cortex) were obtained from a separate dataset of in vivo, T1-weighted MRI scans of the whole brain (1mm resolution). The manual labels from the in vivo and ex vivo data were combined into a single computational atlas of the hippocampal formation with a novel atlas building algorithm based on Bayesian inference. The resulting atlas can be used to automatically segment the hippocampal subregions in structural MRI images, using an algorithm that can analyze multimodal data and adapt to variations in MRI contrast due to differences in acquisition hardware or pulse sequences. The applicability of the atlas, which we are releasing as part of FreeSurfer (version 6.0), is demonstrated with experiments on three different publicly available datasets with different types of MRI contrast. The results show that the atlas and companion segmentation method: 1) can segment T1 and T2 images, as well as their combination, 2) replicate findings on mild cognitive impairment based on high-resolution T2 data, and 3) can discriminate between Alzheimer's disease subjects and elderly controls with 88% accuracy in standard resolution (1mm) T1 data, significantly outperforming the atlas in FreeSurfer version 5.3 (86% accuracy) and

What are Segments in Google Analytics

Science.gov (United States)

Segments find all sessions that meet a specific condition. You can then apply this segment to any report in Google Analytics (GA). Segments are a way of identifying sessions and users while filters identify specific events, like pageviews.

Segmentation-less Digital Rock Physics

Science.gov (United States)

Tisato, N.; Ikeda, K.; Goldfarb, E. J.; Spikes, K. T.

2017-12-01

In the last decade, Digital Rock Physics (DRP) has become an avenue to investigate physical and mechanical properties of geomaterials. DRP offers the advantage of simulating laboratory experiments on numerical samples that are obtained from analytical methods. Potentially, DRP could allow sparing part of the time and resources that are allocated to perform complicated laboratory tests. Like classic laboratory tests, the goal of DRP is to estimate accurately physical properties of rocks like hydraulic permeability or elastic moduli. Nevertheless, the physical properties of samples imaged using micro-computed tomography (μCT) are estimated through segmentation of the μCT dataset. Segmentation proves to be a challenging and arbitrary procedure that typically leads to inaccurate estimates of physical properties. Here we present a novel technique to extract physical properties from a μCT dataset without the use of segmentation. We show examples in which we use segmentation-less method to simulate elastic wave propagation and pressure wave diffusion to estimate elastic properties and permeability, respectively. The proposed method takes advantage of effective medium theories and uses the density and the porosity that are measured in the laboratory to constrain the results. We discuss the results and highlight that segmentation-less DRP is more accurate than segmentation based DRP approaches and theoretical modeling for the studied rock. In conclusion, the segmentation-less approach here presented seems to be a promising method to improve accuracy and to ease the overall workflow of DRP.

Segmentation, advertising and prices

NARCIS (Netherlands)

Galeotti, Andrea; Moraga González, José

This paper explores the implications of market segmentation on firm competitiveness. In contrast to earlier work, here market segmentation is minimal in the sense that it is based on consumer attributes that are completely unrelated to tastes. We show that when the market is comprised by two

Towards a new procreation ethic: the exemplary instance of cleft lip and palate.

Science.gov (United States)

Le Dref, Gaëlle; Grollemund, Bruno; Danion-Grilliat, Anne; Weber, Jean-Christophe

2013-08-01

The improvement of ultrasound scan techniques is enabling ever earlier prenatal diagnosis of developmental anomalies. In France, apart from cases where the mother's life is endangered, the detection of "particularly serious" conditions, and conditions that are "incurable at the time of diagnosis" are the only instances in which a therapeutic abortion can be performed, this applying up to the 9th month of pregnancy. Thus numerous conditions, despite the fact that they cause distress or pain or are socially disabling, do not qualify for therapeutic abortion, despite sometimes pressing demands from parents aware of the difficulties in store for their child and themselves, in a society that is not very favourable towards the integration and self-fulfilment of people with a disability. Cleft lip and palate (CLP), although it can be completely treated, is one of the conditions that considerably complicates the lives of child and parents. Nevertheless, the recent scope for making very early diagnosis of CLP, before the deadline for legal voluntary abortion, has not led to any wave of abortions. CLP in France has the benefit of a exceptional care plan, targeting both the health and the integration of the individuals affected. This article sets out, via the emblematic instance of CLP, to show how present fears of an emerging "domestic" or liberal eugenic trend could become redundant if disability is addressed politically and medically, so that individuals with a disability have the same social rights as any other citizen.

Chromosome condensation and segmentation

International Nuclear Information System (INIS)

Viegas-Pequignot, E.M.

1981-01-01

Some aspects of chromosome condensation in mammalians -humans especially- were studied by means of cytogenetic techniques of chromosome banding. Two further approaches were adopted: a study of normal condensation as early as prophase, and an analysis of chromosome segmentation induced by physical (temperature and γ-rays) or chemical agents (base analogues, antibiotics, ...) in order to show out the factors liable to affect condensation. Here 'segmentation' means an abnormal chromosome condensation appearing systematically and being reproducible. The study of normal condensation was made possible by the development of a technique based on cell synchronization by thymidine and giving prophasic and prometaphasic cells. Besides, the possibility of inducing R-banding segmentations on these cells by BrdU (5-bromodeoxyuridine) allowed a much finer analysis of karyotypes. Another technique was developed using 5-ACR (5-azacytidine), it allowed to induce a segmentation similar to the one obtained using BrdU and identify heterochromatic areas rich in G-C bases pairs [fr

Track segment synthesis method for NTA film

International Nuclear Information System (INIS)

Kumazawa, Shigeru

1980-03-01

A method is presented for synthesizing track segments extracted from a gray-level digital picture of NTA film in automatic counting system. In order to detect each track in an arbitrary direction, even if it has some gaps, as a set of the track segments, the method links extracted segments along the track, in succession, to the linked track segments, according to whether each extracted segment bears a similarity of direction to the track or not and whether it is connected with the linked track segments or not. In the case of a large digital picture, the method is applied to each subpicture, which is a strip of the picture, and then concatenates subsets of track segments linked at each subpicture as a set of track segments belonging to a track. The method was applied to detecting tracks in various directions over the eight 364 x 40-pixel subpictures with the gray scale of 127/pixel (picture element) of the microphotograph of NTA film. It was proved to be able to synthesize track segments correctly for every track in the picture. (author)

Proactive Alleviation Procedure to Handle Black Hole Attack and Its Version

Science.gov (United States)

Babu, M. Rajesh; Dian, S. Moses; Chelladurai, Siva; Palaniappan, Mathiyalagan

2015-01-01

The world is moving towards a new realm of computing such as Internet of Things. The Internet of Things, however, envisions connecting almost all objects within the world to the Internet by recognizing them as smart objects. In doing so, the existing networks which include wired, wireless, and ad hoc networks should be utilized. Moreover, apart from other networks, the ad hoc network is full of security challenges. For instance, the MANET (mobile ad hoc network) is susceptible to various attacks in which the black hole attacks and its versions do serious damage to the entire MANET infrastructure. The severity of this attack increases, when the compromised MANET nodes work in cooperation with each other to make a cooperative black hole attack. Therefore this paper proposes an alleviation procedure which consists of timely mandate procedure, hole detection algorithm, and sensitive guard procedure to detect the maliciously behaving nodes. It has been observed that the proposed procedure is cost-effective and ensures QoS guarantee by assuring resource availability thus making the MANET appropriate for Internet of Things. PMID:26495430

Proactive Alleviation Procedure to Handle Black Hole Attack and Its Version.

Science.gov (United States)

Babu, M Rajesh; Dian, S Moses; Chelladurai, Siva; Palaniappan, Mathiyalagan

2015-01-01

The world is moving towards a new realm of computing such as Internet of Things. The Internet of Things, however, envisions connecting almost all objects within the world to the Internet by recognizing them as smart objects. In doing so, the existing networks which include wired, wireless, and ad hoc networks should be utilized. Moreover, apart from other networks, the ad hoc network is full of security challenges. For instance, the MANET (mobile ad hoc network) is susceptible to various attacks in which the black hole attacks and its versions do serious damage to the entire MANET infrastructure. The severity of this attack increases, when the compromised MANET nodes work in cooperation with each other to make a cooperative black hole attack. Therefore this paper proposes an alleviation procedure which consists of timely mandate procedure, hole detection algorithm, and sensitive guard procedure to detect the maliciously behaving nodes. It has been observed that the proposed procedure is cost-effective and ensures QoS guarantee by assuring resource availability thus making the MANET appropriate for Internet of Things.

NCDC International Best Track Archive for Climate Stewardship (IBTrACS) Project, Version 2 (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Version 2 of the dataset has been superseded by a newer version. Users should not use version 2 except in rare cases (e.g., when reproducing previous studies that...

NCDC International Best Track Archive for Climate Stewardship (IBTrACS) Project, Version 1 (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Version 1 of the dataset has been superseded by a newer version. Users should not use version 1 except in rare cases (e.g., when reproducing previous studies that...

Versioning Complex Data

Energy Technology Data Exchange (ETDEWEB)

Macduff, Matt C.; Lee, Benno; Beus, Sherman J.

2014-06-29

Using the history of ARM data files, we designed and demonstrated a data versioning paradigm that is feasible. Assigning versions to sets of files that are modified with some special assumptions and domain specific rules was effective in the case of ARM data, which has more than 5000 datastreams and 500TB of data.

Temperature and Humidity Profiles in the TqJoint Data Group of AIRS Version 6 Product for the Climate Model Evaluation

Science.gov (United States)

Ding, Feng; Fang, Fan; Hearty, Thomas J.; Theobald, Michael; Vollmer, Bruce; Lynnes, Christopher

2014-01-01

The Atmospheric Infrared Sounder (AIRS) mission is entering its 13th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing long-wave radiation, cloud properties, and trace gases. Thus AIRS data have been widely used, among other things, for short-term climate research and observational component for model evaluation. One instance is the fifth phase of the Coupled Model Intercomparison Project (CMIP5) which uses AIRS version 5 data in the climate model evaluation. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for data from the AIRS mission. The GES DISC, in collaboration with the AIRS Project, released data from the version 6 algorithm in early 2013. The new algorithm represents a significant improvement over previous versions in terms of greater stability, yield, and quality of products. The ongoing Earth System Grid for next generation climate model research project, a collaborative effort of GES DISC and NASA JPL, will bring temperature and humidity profiles from AIRS version 6. The AIRS version 6 product adds a new "TqJoint" data group, which contains data for a common set of observations across water vapor and temperature at all atmospheric levels and is suitable for climate process studies. How different may the monthly temperature and humidity profiles in "TqJoint" group be from the "Standard" group where temperature and water vapor are not always valid at the same time? This study aims to answer the question by comprehensively comparing the temperature and humidity profiles from the "TqJoint" group and the "Standard" group. The comparison includes mean differences at different levels globally and over land and ocean. We are also working on examining the sampling differences between the "TqJoint" and "Standard" group using MERRA data.

LIFE-STYLE SEGMENTATION WITH TAILORED INTERVIEWING

NARCIS (Netherlands)

KAMAKURA, WA; WEDEL, M

The authors present a tailored interviewing procedure for life-style segmentation. The procedure assumes that a life-style measurement instrument has been designed. A classification of a sample of consumers into life-style segments is obtained using a latent-class model. With these segments, the

Segmented rail linear induction motor

Science.gov (United States)

Cowan, Jr., Maynard; Marder, Barry M.

1996-01-01

A segmented rail linear induction motor has a segmented rail consisting of a plurality of nonferrous electrically conductive segments aligned along a guideway. The motor further includes a carriage including at least one pair of opposed coils fastened to the carriage for moving the carriage. A power source applies an electric current to the coils to induce currents in the conductive surfaces to repel the coils from adjacent edges of the conductive surfaces.

Responsiveness of the Spanish Version of the “Skin Cancer Index”

Directory of Open Access Journals (Sweden)

M. de Troya-Martín

2016-01-01

Full Text Available Background. Skin Cancer Index (SCI is a specific questionnaire measuring health related quality of life (HRQL in patients with cervicofacial non-melanoma skin cancer (CFNMSC. The original scale has recently been adapted and validated into Spanish. Objectives. Evaluate the responsiveness of the Spanish version of SCI. Methods. Patients with CFNMSC candidate for surgical treatment were administered the questionnaire at time of diagnostic (t0, 7 days after surgery (t1, and 5 months after surgery (t2. The scale and subscales scores (C1: social/appearance, C2: emotional were then evaluated. Differences between t0-t1, t1-t2, and t0-t2 were determined and a gender-and-age segmented analysis was performed. Results. 88 patients, 54.8% male, mean age 62.5 years, completed the study. Differences between t0-t1 and t1-t2 scores were statistically significant (p<0.05. The lowest values were found at time of diagnosis and postsurgery. Women and patients under 65 years showed the lowest values at the three times. Limitations. Concrete geographic and cultural area. Clinical and histological variables are not analysed. Conclusions. Our results confirm responsiveness of the Spanish version of the SCI. Further development of the instrument in Spanish-speaking countries and populations will make it possible to extend worldwide research and knowledge horizons on skin cancer.

Deformable segmentation via sparse shape representation.

Science.gov (United States)

Zhang, Shaoting; Zhan, Yiqiang; Dewan, Maneesh; Huang, Junzhou; Metaxas, Dimitris N; Zhou, Xiang Sean

2011-01-01

Appearance and shape are two key elements exploited in medical image segmentation. However, in some medical image analysis tasks, appearance cues are weak/misleading due to disease/artifacts and often lead to erroneous segmentation. In this paper, a novel deformable model is proposed for robust segmentation in the presence of weak/misleading appearance cues. Owing to the less trustable appearance information, this method focuses on the effective shape modeling with two contributions. First, a shape composition method is designed to incorporate shape prior on-the-fly. Based on two sparsity observations, this method is robust to false appearance information and adaptive to statistically insignificant shape modes. Second, shape priors are modeled and used in a hierarchical fashion. More specifically, by using affinity propagation method, our deformable surface is divided into multiple partitions, on which local shape models are built independently. This scheme facilitates a more compact shape prior modeling and hence a more robust and efficient segmentation. Our deformable model is applied on two very diverse segmentation problems, liver segmentation in PET-CT images and rodent brain segmentation in MR images. Compared to state-of-art methods, our method achieves better performance in both studies.

Segmenting hospitals for improved management strategy.

Science.gov (United States)

Malhotra, N K

1989-09-01

The author presents a conceptual framework for the a priori and clustering-based approaches to segmentation and evaluates them in the context of segmenting institutional health care markets. An empirical study is reported in which the hospital market is segmented on three state-of-being variables. The segmentation approach also takes into account important organizational decision-making variables. The sophisticated Thurstone Case V procedure is employed. Several marketing implications for hospitals, other health care organizations, hospital suppliers, and donor publics are identified.

IMU-to-Segment Assignment and Orientation Alignment for the Lower Body Using Deep Learning.

Science.gov (United States)

Zimmermann, Tobias; Taetz, Bertram; Bleser, Gabriele

2018-01-19

Human body motion analysis based on wearable inertial measurement units (IMUs) receives a lot of attention from both the research community and the and industrial community. This is due to the significant role in, for instance, mobile health systems, sports and human computer interaction. In sensor based activity recognition, one of the major issues for obtaining reliable results is the sensor placement/assignment on the body. For inertial motion capture (joint kinematics estimation) and analysis, the IMU-to-segment (I2S) assignment and alignment are central issues to obtain biomechanical joint angles. Existing approaches for I2S assignment usually rely on hand crafted features and shallow classification approaches (e.g., support vector machines), with no agreement regarding the most suitable features for the assignment task. Moreover, estimating the complete orientation alignment of an IMU relative to the segment it is attached to using a machine learning approach has not been shown in literature so far. This is likely due to the high amount of training data that have to be recorded to suitably represent possible IMU alignment variations. In this work, we propose online approaches for solving the assignment and alignment tasks for an arbitrary amount of IMUs with respect to a biomechanical lower body model using a deep learning architecture and windows of 128 gyroscope and accelerometer data samples. For this, we combine convolutional neural networks (CNNs) for local filter learning with long-short-term memory (LSTM) recurrent networks as well as generalized recurrent units (GRUs) for learning time dynamic features. The assignment task is casted as a classification problem, while the alignment task is casted as a regression problem. In this framework, we demonstrate the feasibility of augmenting a limited amount of real IMU training data with simulated alignment variations and IMU data for improving the recognition/estimation accuracies. With the proposed

IMU-to-Segment Assignment and Orientation Alignment for the Lower Body Using Deep Learning

Directory of Open Access Journals (Sweden)

Tobias Zimmermann

2018-01-01

Full Text Available Human body motion analysis based on wearable inertial measurement units (IMUs receives a lot of attention from both the research community and the and industrial community. This is due to the significant role in, for instance, mobile health systems, sports and human computer interaction. In sensor based activity recognition, one of the major issues for obtaining reliable results is the sensor placement/assignment on the body. For inertial motion capture (joint kinematics estimation and analysis, the IMU-to-segment (I2S assignment and alignment are central issues to obtain biomechanical joint angles. Existing approaches for I2S assignment usually rely on hand crafted features and shallow classification approaches (e.g., support vector machines, with no agreement regarding the most suitable features for the assignment task. Moreover, estimating the complete orientation alignment of an IMU relative to the segment it is attached to using a machine learning approach has not been shown in literature so far. This is likely due to the high amount of training data that have to be recorded to suitably represent possible IMU alignment variations. In this work, we propose online approaches for solving the assignment and alignment tasks for an arbitrary amount of IMUs with respect to a biomechanical lower body model using a deep learning architecture and windows of 128 gyroscope and accelerometer data samples. For this, we combine convolutional neural networks (CNNs for local filter learning with long-short-term memory (LSTM recurrent networks as well as generalized recurrent units (GRUs for learning time dynamic features. The assignment task is casted as a classification problem, while the alignment task is casted as a regression problem. In this framework, we demonstrate the feasibility of augmenting a limited amount of real IMU training data with simulated alignment variations and IMU data for improving the recognition/estimation accuracies. With the

Review of segmentation process in consumer markets

Directory of Open Access Journals (Sweden)

Veronika Jadczaková

2013-01-01

Full Text Available Although there has been a considerable debate on market segmentation over five decades, attention was merely devoted to single stages of the segmentation process. In doing so, stages as segmentation base selection or segments profiling have been heavily covered in the extant literature, whereas stages as implementation of the marketing strategy or market definition were of a comparably lower interest. Capitalizing on this shortcoming, this paper strives to close the gap and provide each step of the segmentation process with equal treatment. Hence, the objective of this paper is two-fold. First, a snapshot of the segmentation process in a step-by-step fashion will be provided. Second, each step (where possible will be evaluated on chosen criteria by means of description, comparison, analysis and synthesis of 32 academic papers and 13 commercial typology systems. Ultimately, the segmentation stages will be discussed with empirical findings prevalent in the segmentation studies and last but not least suggestions calling for further investigation will be presented. This seven-step-framework may assist when segmenting in practice allowing for more confidential targeting which in turn might prepare grounds for creating of a differential advantage.

FCNN-MR: A Parallel Instance Selection Method Based on Fast Condensed Nearest Neighbor Rule

OpenAIRE

Lu Si; Jie Yu; Shasha Li; Jun Ma; Lei Luo; Qingbo Wu; Yongqi Ma; Zhengji Liu

2017-01-01

Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rul...

The Unified Extensional Versioning Model

DEFF Research Database (Denmark)

Asklund, U.; Bendix, Lars Gotfred; Christensen, H. B.

1999-01-01

Versioning of components in a system is a well-researched field where various adequate techniques have already been established. In this paper, we look at how versioning can be extended to cover also the structural aspects of a system. There exist two basic techniques for versioning - intentional...

Polyether based segmented copolymers with uniform aramid units

NARCIS (Netherlands)

Niesten, M.C.E.J.

2000-01-01

Segmented copolymers with short, glassy or crystalline hard segments and long, amorphous soft segments (multi-block copolymers) are thermoplastic elastomers (TPE’s). The hard segments form physical crosslinks for the amorphous (rubbery) soft segments. As a result, this type of materials combines

Geophysical Multiphase Flow With Interphase Exchanges - Hydrodynamic and Thermodynamic Models, and Numerical Techniques, Version GMFIX-1.61, Design Document Attachment 1

International Nuclear Information System (INIS)

Dartevelle, S.

2006-01-01

Since the multiphase system is made up of a large number of particles, it is impractical to solve the motion of each individual particle; hence GMFIX v1.61 is based upon the Implicit Multi-Field formalism (IMF) which treats all phases in the system as interpenetrating continua. Each instantaneous local point variable (mass, velocity, temperature, pressure, so forth) must be treated to acknowledge the fact that any given arbitrary volume can be shared by different phases at the same time. This treatment may involve, for instance, an averaging or a smoothing process. GMFIX is the geophysical version of MFIX codes developed by NETL and ORNL. MFIX comes after 30 years of continuous developments and improvements from K-FIX codes from LANL. At the time this manuscript was ready for publication (March 2005), some differences exist between the current versions of GMFIX (v. 1.61) and MFIX (v: 1.60) regarding the exact formulation of the energy and momentum equations, the interfacial closures, and the turbulence formulation. Yet both GMFIX and MFIX are being improved, and developed tightly sides by sides

Market Segmentation from a Behavioral Perspective

Science.gov (United States)

Wells, Victoria K.; Chang, Shing Wan; Oliveira-Castro, Jorge; Pallister, John

2010-01-01

A segmentation approach is presented using both traditional demographic segmentation bases (age, social class/occupation, and working status) and a segmentation by benefits sought. The benefits sought in this case are utilitarian and informational reinforcement, variables developed from the Behavioral Perspective Model (BPM). Using data from 1,847…

Skip segment Hirschsprung disease and Waardenburg syndrome

OpenAIRE

Gross, Erica R.; Geddes, Gabrielle C.; McCarrier, Julie A.; Jarzembowski, Jason A.; Arca, Marjorie J.

2015-01-01

Skip segment Hirschsprung disease describes a segment of ganglionated bowel between two segments of aganglionated bowel. It is a rare phenomenon that is difficult to diagnose. We describe a recent case of skip segment Hirschsprung disease in a neonate with a family history of Waardenburg syndrome and the genetic profile that was identified.

Spinal cord grey matter segmentation challenge.

Science.gov (United States)

Prados, Ferran; Ashburner, John; Blaiotta, Claudia; Brosch, Tom; Carballido-Gamio, Julio; Cardoso, Manuel Jorge; Conrad, Benjamin N; Datta, Esha; Dávid, Gergely; Leener, Benjamin De; Dupont, Sara M; Freund, Patrick; Wheeler-Kingshott, Claudia A M Gandini; Grussu, Francesco; Henry, Roland; Landman, Bennett A; Ljungberg, Emil; Lyttle, Bailey; Ourselin, Sebastien; Papinutto, Nico; Saporito, Salvatore; Schlaeger, Regina; Smith, Seth A; Summers, Paul; Tam, Roger; Yiannakas, Marios C; Zhu, Alyssa; Cohen-Adad, Julien

2017-05-15

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Assessment of radionuclide databases in CAP88 mainframe version 1.0 and Windows-based version 3.0.

Science.gov (United States)

LaBone, Elizabeth D; Farfán, Eduardo B; Lee, Patricia L; Jannik, G Timothy; Donnelly, Elizabeth H; Foley, Trevor Q

2009-09-01

In this study the radionuclide databases for two versions of the Clean Air Act Assessment Package-1988 (CAP88) computer model were assessed in detail. CAP88 estimates radiation dose and the risk of health effects to human populations from radionuclide emissions to air. This program is used by several U.S. Department of Energy (DOE) facilities to comply with National Emission Standards for Hazardous Air Pollutants regulations. CAP88 Mainframe, referred to as version 1.0 on the U.S. Environmental Protection Agency Web site (http://www.epa.gov/radiation/assessment/CAP88/), was the very first CAP88 version released in 1988. Some DOE facilities including the Savannah River Site still employ this version (1.0) while others use the more user-friendly personal computer Windows-based version 3.0 released in December 2007. Version 1.0 uses the program RADRISK based on International Commission on Radiological Protection Publication 30 as its radionuclide database. Version 3.0 uses half-life, dose, and risk factor values based on Federal Guidance Report 13. Differences in these values could cause different results for the same input exposure data (same scenario), depending on which version of CAP88 is used. Consequently, the differences between the two versions are being assessed in detail at Savannah River National Laboratory. The version 1.0 and 3.0 database files contain 496 and 838 radionuclides, respectively, and though one would expect the newer version to include all the 496 radionuclides, 35 radionuclides are listed in version 1.0 that are not included in version 3.0. The majority of these has either extremely short or long half-lives or is no longer in production; however, some of the short-lived radionuclides might produce progeny of great interest at DOE sites. In addition, 122 radionuclides were found to have different half-lives in the two versions, with 21 over 3 percent different and 12 over 10 percent different.

On the instance of misuse of unprofitable energy prices under cartel law

International Nuclear Information System (INIS)

Schoening, M.

1993-01-01

The practice of fixing prices which do not cover the costs can on principle not be considered an instance of misuse pursuant to Articles 22 Section 4 Clause 2 No. 2, 103 Section 5 Clause 2 No. 2 of the GWB (cartel laws). If the authority for the supervision of cartels takes action against companies operating with unprofitable prices, this constitutes a violation not only of cartel law, but also of the constitution. The cartel authorities have no right to dismiss a dominating company's referral to poor business prospects on the ground that its business report is theoretically manipulable. Rather, the burden of proof of concealment is on the authorities. (orig.) [de

Multi-scale Modelling of Segmentation

DEFF Research Database (Denmark)

Hartmann, Martin; Lartillot, Olivier; Toiviainen, Petri

2016-01-01

pieces. In a second experiment on non-real-time segmentation, musicians indicated boundaries and their strength for six examples. Kernel density estimation was used to develop multi-scale segmentation models. Contrary to previous research, no relationship was found between boundary strength and boundary......While listening to music, people often unwittingly break down musical pieces into constituent chunks such as verses and choruses. Music segmentation studies have suggested that some consensus regarding boundary perception exists, despite individual differences. However, neither the effects...

JEnsembl: a version-aware Java API to Ensembl data systems.

Science.gov (United States)

Paterson, Trevor; Law, Andy

2012-11-01

The Ensembl Project provides release-specific Perl APIs for efficient high-level programmatic access to data stored in various Ensembl database schema. Although Perl scripts are perfectly suited for processing large volumes of text-based data, Perl is not ideal for developing large-scale software applications nor embedding in graphical interfaces. The provision of a novel Java API would facilitate type-safe, modular, object-orientated development of new Bioinformatics tools with which to access, analyse and visualize Ensembl data. The JEnsembl API implementation provides basic data retrieval and manipulation functionality from the Core, Compara and Variation databases for all species in Ensembl and EnsemblGenomes and is a platform for the development of a richer API to Ensembl datasources. The JEnsembl architecture uses a text-based configuration module to provide evolving, versioned mappings from database schema to code objects. A single installation of the JEnsembl API can therefore simultaneously and transparently connect to current and previous database instances (such as those in the public archive) thus facilitating better analysis repeatability and allowing 'through time' comparative analyses to be performed. Project development, released code libraries, Maven repository and documentation are hosted at SourceForge (http://jensembl.sourceforge.net).

Skip segment Hirschsprung disease and Waardenburg syndrome

Directory of Open Access Journals (Sweden)

Erica R. Gross

2015-04-01

Full Text Available Skip segment Hirschsprung disease describes a segment of ganglionated bowel between two segments of aganglionated bowel. It is a rare phenomenon that is difficult to diagnose. We describe a recent case of skip segment Hirschsprung disease in a neonate with a family history of Waardenburg syndrome and the genetic profile that was identified.

Segmentation-Based And Segmentation-Free Methods for Spotting Handwritten Arabic Words

OpenAIRE

Ball , Gregory R.; Srihari , Sargur N.; Srinivasan , Harish

2006-01-01

http://www.suvisoft.com; Given a set of handwritten documents, a common goal is to search for a relevant subset. Attempting to find a query word or image in such a set of documents is called word spotting. Spotting handwritten words in documents written in the Latin alphabet, and more recently in Arabic, has received considerable attention. One issue is generating candidate word regions on a page. Attempting to definitely segment the document into such regions (automatic segmentation) can mee...

Monitoring fish distributions along electrofishing segments

Science.gov (United States)

Miranda, Leandro E.

2014-01-01

Electrofishing is widely used to monitor fish species composition and relative abundance in streams and lakes. According to standard protocols, multiple segments are selected in a body of water to monitor population relative abundance as the ratio of total catch to total sampling effort. The standard protocol provides an assessment of fish distribution at a macrohabitat scale among segments, but not within segments. An ancillary protocol was developed for assessing fish distribution at a finer scale within electrofishing segments. The ancillary protocol was used to estimate spacing, dispersion, and association of two species along shore segments in two local reservoirs. The added information provided by the ancillary protocol may be useful for assessing fish distribution relative to fish of the same species, to fish of different species, and to environmental or habitat characteristics.

Color image Segmentation using automatic thresholding techniques

International Nuclear Information System (INIS)

Harrabi, R.; Ben Braiek, E.

2011-01-01

In this paper, entropy and between-class variance based thresholding methods for color images segmentation are studied. The maximization of the between-class variance (MVI) and the entropy (ME) have been used as a criterion functions to determine an optimal threshold to segment images into nearly homogenous regions. Segmentation results from the two methods are validated and the segmentation sensitivity for the test data available is evaluated, and a comparative study between these methods in different color spaces is presented. The experimental results demonstrate the superiority of the MVI method for color image segmentation.

Process Segmentation Typology in Czech Companies

Directory of Open Access Journals (Sweden)

Tucek David

2016-03-01

Full Text Available This article describes process segmentation typology during business process management implementation in Czech companies. Process typology is important for a manager’s overview of process orientation as well as for a manager’s general understanding of business process management. This article provides insight into a process-oriented organizational structure. The first part analyzes process segmentation typology itself as well as some original results of quantitative research evaluating process segmentation typology in the specific context of Czech company strategies. Widespread data collection was carried out in 2006 and 2013. The analysis of this data showed that managers have more options regarding process segmentation and its selection. In terms of practicality and ease of use, the most frequently used method of process segmentation (managerial, main, and supportive stems directly from the requirements of ISO 9001. Because of ISO 9001:2015, managers must now apply risk planning in relation to the selection of processes that are subjected to process management activities. It is for this fundamental reason that this article focuses on process segmentation typology.

POSTERIOR SEGMENT CAUSES OF BLINDNESS AMONG CHILDREN IN BLIND SCHOOLS

Directory of Open Access Journals (Sweden)

Sandhya

2015-09-01

Full Text Available BACKGROUND: It is estimated that there are 1.4 million irreversibly blind children in the world out of which 1 million are in Asia alone. India has the highest number of blind children than any other country. Nearly 70% of the childhood blindness is avoidable. There i s paucity of data available on the causes of childhood blindness. This study focuses on the posterior segment causes of blindness among children attending blind schools in 3 adjacent districts of Andhra Pradesh. MATERIAL & METHODS: This is a cross sectiona l study conducted among 204 blind children aged 6 - 16 years age. Detailed eye examination was done by the same investigator to avoid bias. Posterior segment examination was done using a direct and/or indirect ophthalmoscope after dilating pupil wherever nec essary. The standard WHO/PBL for blindness and low vision examination protocol was used to categorize the causes of blindness. A major anatomical site and underlying cause was selected for each child. The study was carried out during July 2014 to June 2015 . The results were analyzed using MS excel software and Epi - info 7 software version statistical software. RESULTS: Majority of the children was found to be aged 13 - 16 years (45.1% and males (63.7%. Family history of blindness was noted in 26.0% and consa nguinity was reported in 29.9% cases. A majority of them were belonged to fulfill WHO grade of blindness (73.0% and in majority of the cases, the onset of blindness was since birth (83.7%. The etiology of blindness was unknown in majority of cases (57.4% while hereditary causes constituted 25.4% cases. Posterior segment causes were responsible in 33.3% cases with retina being the most commonly involved anatomical site (19.1% followed by optic nerve (14.2%. CONCLUSIONS: There is a need for mandatory oph thalmic evaluation, refraction and assessment of low vision prior to admission into blind schools with periodic evaluation every 2 - 3 years

Algorithms for Cytoplasm Segmentation of Fluorescence Labelled Cells

Directory of Open Access Journals (Sweden)

Carolina Wählby

2002-01-01

Full Text Available Automatic cell segmentation has various applications in cytometry, and while the nucleus is often very distinct and easy to identify, the cytoplasm provides a lot more challenge. A new combination of image analysis algorithms for segmentation of cells imaged by fluorescence microscopy is presented. The algorithm consists of an image pre‐processing step, a general segmentation and merging step followed by a segmentation quality measurement. The quality measurement consists of a statistical analysis of a number of shape descriptive features. Objects that have features that differ to that of correctly segmented single cells can be further processed by a splitting step. By statistical analysis we therefore get a feedback system for separation of clustered cells. After the segmentation is completed, the quality of the final segmentation is evaluated. By training the algorithm on a representative set of training images, the algorithm is made fully automatic for subsequent images created under similar conditions. Automatic cytoplasm segmentation was tested on CHO‐cells stained with calcein. The fully automatic method showed between 89% and 97% correct segmentation as compared to manual segmentation.

NETS - A NEURAL NETWORK DEVELOPMENT TOOL, VERSION 3.0 (MACINTOSH VERSION)

Science.gov (United States)

Phillips, T. A.

1994-01-01

allows the user to generate C code to implement the network loaded into the system. This permits the placement of networks as components, or subroutines, in other systems. In short, once a network performs satisfactorily, the Generate C Code option provides the means for creating a program separate from NETS to run the network. Other features: files may be stored in binary or ASCII format; multiple input propagation is permitted; bias values may be included; capability to scale data without writing scaling code; quick interactive testing of network from the main menu; and several options that allow the user to manipulate learning efficiency. NETS is written in ANSI standard C language to be machine independent. The Macintosh version (MSC-22108) includes code for both a graphical user interface version and a command line interface version. The machine independent version (MSC-21588) only includes code for the command line interface version of NETS 3.0. The Macintosh version requires a Macintosh II series computer and has been successfully implemented under System 7. Four executables are included on these diskettes, two for floating point operations and two for integer arithmetic. It requires Think C 5.0 to compile. A minimum of 1Mb of RAM is required for execution. Sample input files and executables for both the command line version and the Macintosh user interface version are provided on the distribution medium. The Macintosh version is available on a set of three 3.5 inch 800K Macintosh format diskettes. The machine independent version has been successfully implemented on an IBM PC series compatible running MS-DOS, a DEC VAX running VMS, a SunIPC running SunOS, and a CRAY Y-MP running UNICOS. Two executables for the IBM PC version are included on the MS-DOS distribution media, one compiled for floating point operations and one for integer arithmetic. The machine independent version is available on a set of three 5.25 inch 360K MS-DOS format diskettes (standard

Benchmarking of Remote Sensing Segmentation Methods

Czech Academy of Sciences Publication Activity Database

Mikeš, Stanislav; Haindl, Michal; Scarpa, G.; Gaetano, R.

2015-01-01

Roč. 8, č. 5 (2015), s. 2240-2248 ISSN 1939-1404 R&D Projects: GA ČR(CZ) GA14-10911S Institutional support: RVO:67985556 Keywords : benchmark * remote sensing segmentation * unsupervised segmentation * supervised segmentation Subject RIV: BD - Theory of Information Impact factor: 2.145, year: 2015 http://library.utia.cas.cz/separaty/2015/RO/haindl-0445995.pdf

Unsupervised Retinal Vessel Segmentation Using Combined Filters.

Directory of Open Access Journals (Sweden)

Wendeson S Oliveira

Full Text Available Image segmentation of retinal blood vessels is a process that can help to predict and diagnose cardiovascular related diseases, such as hypertension and diabetes, which are known to affect the retinal blood vessels' appearance. This work proposes an unsupervised method for the segmentation of retinal vessels images using a combined matched filter, Frangi's filter and Gabor Wavelet filter to enhance the images. The combination of these three filters in order to improve the segmentation is the main motivation of this work. We investigate two approaches to perform the filter combination: weighted mean and median ranking. Segmentation methods are tested after the vessel enhancement. Enhanced images with median ranking are segmented using a simple threshold criterion. Two segmentation procedures are applied when considering enhanced retinal images using the weighted mean approach. The first method is based on deformable models and the second uses fuzzy C-means for the image segmentation. The procedure is evaluated using two public image databases, Drive and Stare. The experimental results demonstrate that the proposed methods perform well for vessel segmentation in comparison with state-of-the-art methods.

Automatic segmentation of psoriasis lesions

Science.gov (United States)

Ning, Yang; Shi, Chenbo; Wang, Li; Shu, Chang

2014-10-01

The automatic segmentation of psoriatic lesions is widely researched these years. It is an important step in Computer-aid methods of calculating PASI for estimation of lesions. Currently those algorithms can only handle single erythema or only deal with scaling segmentation. In practice, scaling and erythema are often mixed together. In order to get the segmentation of lesions area - this paper proposes an algorithm based on Random forests with color and texture features. The algorithm has three steps. The first step, the polarized light is applied based on the skin's Tyndall-effect in the imaging to eliminate the reflection and Lab color space are used for fitting the human perception. The second step, sliding window and its sub windows are used to get textural feature and color feature. In this step, a feature of image roughness has been defined, so that scaling can be easily separated from normal skin. In the end, Random forests will be used to ensure the generalization ability of the algorithm. This algorithm can give reliable segmentation results even the image has different lighting conditions, skin types. In the data set offered by Union Hospital, more than 90% images can be segmented accurately.

Simultaneous minimizing monitor units and number of segments without leaf end abutment for segmental intensity modulated radiation therapy delivery

International Nuclear Information System (INIS)

Li Kaile; Dai Jianrong; Ma Lijun

2004-01-01

Leaf end abutment is seldom studied when delivering segmental intensity modulated radiation therapy (IMRT) fields. We developed an efficient leaf sequencing method to eliminate leaf end abutment for segmental IMRT delivery. Our method uses simple matrix and sorting operations to obtain a solution that simultaneously minimizes total monitor units and number of segments without leaf end abutment between segments. We implemented and demonstrated our method for multiple clinical cases. We compared the results of our method with the results from exhaustive search method. We found that our solution without leaf end abutment produced equivalent results to the unconstrained solutions in terms of minimum total monitor units and minimum number of leaf segments. We conclude that the leaf end abutment fields can be avoided without affecting the efficiency of segmental IMRT delivery. The major strength of our method is its simplicity and high computing speed. This potentially provides a useful means for generating segmental IMRT fields that require high spatial resolution or complex intensity distributions

Hierarchical image segmentation for learning object priors

Energy Technology Data Exchange (ETDEWEB)

Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.; Li, Nan [TEMPLE UNIV.

2010-11-10

The proposed segmentation approach naturally combines experience based and image based information. The experience based information is obtained by training a classifier for each object class. For a given test image, the result of each classifier is represented as a probability map. The final segmentation is obtained with a hierarchial image segmentation algorithm that considers both the probability maps and the image features such as color and edge strength. We also utilize image region hierarchy to obtain not only local but also semi-global features as input to the classifiers. Moreover, to get robust probability maps, we take into account the region context information by averaging the probability maps over different levels of the hierarchical segmentation algorithm. The obtained segmentation results are superior to the state-of-the-art supervised image segmentation algorithms.

Effect of the average soft-segment length on the morphology and properties of segmented polyurethane nanocomposites

International Nuclear Information System (INIS)

Finnigan, Bradley; Halley, Peter; Jack, Kevin; McDowell, Alasdair; Truss, Rowan; Casey, Phil; Knott, Robert; Martin, Darren

2006-01-01

Two organically modified layered silicates (with small and large diameters) were incorporated into three segmented polyurethanes with various degrees of microphase separation. Microphase separation increased with the molecular weight of the poly(hexamethylene oxide) soft segment. The molecular weight of the soft segment did not influence the amount of polyurethane intercalating the interlayer spacing. Small-angle neutron scattering and differential scanning calorimetry data indicated that the layered silicates did not affect the microphase morphology of any host polymer, regardless of the particle diameter. The stiffness enhancement on filler addition increased as the microphase separation of the polyurethane decreased, presumably because a greater number of urethane linkages were available to interact with the filler. For comparison, the small nanofiller was introduced into a polyurethane with a poly(tetramethylene oxide) soft segment, and a significant increase in the tensile strength and a sharper upturn in the stress-strain curve resulted. No such improvement occurred in the host polymers with poly(hexamethylene oxide) soft segments. It is proposed that the nanocomposite containing the more hydrophilic and mobile poly(tetramethylene oxide) soft segment is capable of greater secondary bonding between the polyurethane chains and the organosilicate surface, resulting in improved stress transfer to the filler and reduced molecular slippage.

Essays in international market segmentation

NARCIS (Netherlands)

Hofstede, ter F.

1999-01-01

The primary objective of this thesis is to develop and validate new methodologies to improve the effectiveness of international segmentation strategies. The current status of international market segmentation research is reviewed in an introductory chapter, which provided a number of

Roentgenological diagnoss of central segmental lung cancer

International Nuclear Information System (INIS)

Gurevich, L.A.; Fedchenko, G.G.

1984-01-01

Basing on an analysis of the results of clinicoroentgenological examination of 268 patments roentgenological semiotics of segmental lung cancer is presented. Some peculiarities of the X-ray picture of cancer of different segments of the lungs were revealed depending on tumor site and growth type. For the syndrome of segmental darkening the comprehensive X-ray methods where the chief method is tomography of the segmental bronchi are proposed

Method of manufacturing a large-area segmented photovoltaic module

Science.gov (United States)

Lenox, Carl

2013-11-05

One embodiment of the invention relates to a segmented photovoltaic (PV) module which is manufactured from laminate segments. The segmented PV module includes rectangular-shaped laminate segments formed from rectangular-shaped PV laminates and further includes non-rectangular-shaped laminate segments formed from rectangular-shaped and approximately-triangular-shaped PV laminates. The laminate segments are mechanically joined and electrically interconnected to form the segmented module. Another embodiment relates to a method of manufacturing a large-area segmented photovoltaic module from laminate segments of various shapes. Other embodiments relate to processes for providing a photovoltaic array for installation at a site. Other embodiments and features are also disclosed.

Study of the morphology exhibited by linear segmented polyurethanes

International Nuclear Information System (INIS)

Pereira, I.M.; Orefice, R.L.

2009-01-01

Five series of segmented polyurethanes with different hard segment content were prepared by the prepolymer mixing method. The nano-morphology of the obtained polyurethanes and their microphase separation were investigated by infrared spectroscopy, modulated differential scanning calorimetry and small-angle X-ray scattering. Although highly hydrogen bonded hard segments were formed, high hard segment contents promoted phase mixture and decreased the chain mobility, decreasing the hard segment domain precipitation and the soft segments crystallization. The applied techniques were able to show that the hard-segment content and the hard-segment interactions were the two controlling factors for determining the structure of segmented polyurethanes. (author)

Verification of RESRAD-RDD. (Version 2.01)

Energy Technology Data Exchange (ETDEWEB)

Cheng, Jing-Jy [Argonne National Lab. (ANL), Argonne, IL (United States); Flood, Paul E. [Argonne National Lab. (ANL), Argonne, IL (United States); LePoire, David [Argonne National Lab. (ANL), Argonne, IL (United States); Kamboj, Sunita [Argonne National Lab. (ANL), Argonne, IL (United States); Yu, Charley [Argonne National Lab. (ANL), Argonne, IL (United States)

2015-09-01

In this report, the results generated by RESRAD-RDD version 2.01 are compared with those produced by RESRAD-RDD version 1.7 for different scenarios with different sets of input parameters. RESRAD-RDD version 1.7 is spreadsheet-driven, performing calculations with Microsoft Excel spreadsheets. RESRAD-RDD version 2.01 revamped version 1.7 by using command-driven programs designed with Visual Basic.NET to direct calculations with data saved in Microsoft Access database, and re-facing the graphical user interface (GUI) to provide more flexibility and choices in guideline derivation. Because version 1.7 and version 2.01 perform the same calculations, the comparison of their results serves as verification of both versions. The verification covered calculation results for 11 radionuclides included in both versions: Am-241, Cf-252, Cm-244, Co-60, Cs-137, Ir-192, Po-210, Pu-238, Pu-239, Ra-226, and Sr-90. At first, all nuclidespecific data used in both versions were compared to ensure that they are identical. Then generic operational guidelines and measurement-based radiation doses or stay times associated with a specific operational guideline group were calculated with both versions using different sets of input parameters, and the results obtained with the same set of input parameters were compared. A total of 12 sets of input parameters were used for the verification, and the comparison was performed for each operational guideline group, from A to G, sequentially. The verification shows that RESRAD-RDD version 1.7 and RESRAD-RDD version 2.01 generate almost identical results; the slight differences could be attributed to differences in numerical precision with Microsoft Excel and Visual Basic.NET. RESRAD-RDD version 2.01 allows the selection of different units for use in reporting calculation results. The results of SI units were obtained and compared with the base results (in traditional units) used for comparison with version 1.7. The comparison shows that RESRAD

Prototype implementation of segment assembling software

Directory of Open Access Journals (Sweden)

Pešić Đorđe

2018-01-01

Full Text Available IT education is very important and a lot of effort is put into the development of tools for helping students to acquire programming knowledge and for helping teachers in automating the examination process. This paper describes a prototype of the program segment assembling software used in the context of making tests in the field of algorithmic complexity. The proposed new program segment assembling model uses rules and templates. A template is a simple program segment. A rule defines combining method and data dependencies if they exist. One example of program segment assembling by the proposed system is given. Graphical user interface is also described.

Smart markers for watershed-based cell segmentation.

Directory of Open Access Journals (Sweden)

Can Fahrettin Koyuncu

Full Text Available Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

Smart markers for watershed-based cell segmentation.

Science.gov (United States)

Koyuncu, Can Fahrettin; Arslan, Salim; Durmaz, Irem; Cetin-Atalay, Rengul; Gunduz-Demir, Cigdem

2012-01-01

Automated cell imaging systems facilitate fast and reliable analysis of biological events at the cellular level. In these systems, the first step is usually cell segmentation that greatly affects the success of the subsequent system steps. On the other hand, similar to other image segmentation problems, cell segmentation is an ill-posed problem that typically necessitates the use of domain-specific knowledge to obtain successful segmentations even by human subjects. The approaches that can incorporate this knowledge into their segmentation algorithms have potential to greatly improve segmentation results. In this work, we propose a new approach for the effective segmentation of live cells from phase contrast microscopy. This approach introduces a new set of "smart markers" for a marker-controlled watershed algorithm, for which the identification of its markers is critical. The proposed approach relies on using domain-specific knowledge, in the form of visual characteristics of the cells, to define the markers. We evaluate our approach on a total of 1,954 cells. The experimental results demonstrate that this approach, which uses the proposed definition of smart markers, is quite effective in identifying better markers compared to its counterparts. This will, in turn, be effective in improving the segmentation performance of a marker-controlled watershed algorithm.

HANFORD TANK WASTE OPERATIONS SIMULATOR VERSION DESCRIPTION DOCUMENT

International Nuclear Information System (INIS)

ALLEN, G.K.

2003-01-01

This document describes the software version controls established for the Hanford Tank Waste Operations Simulator (HTWOS). It defines: the methods employed to control the configuration of HTWOS; the version of each of the 26 separate modules for the version 1.0 of HTWOS; the numbering rules for incrementing the version number of each module; and a requirement to include module version numbers in each case results documentation. Version 1.0 of HTWOS is the first version under formal software version control. HTWOS contains separate revision numbers for each of its 26 modules. Individual module version numbers do not reflect the major release HTWOS configured version number

An unsupervised strategy for biomedical image segmentation

Directory of Open Access Journals (Sweden)

Roberto Rodríguez

2010-09-01

Full Text Available Roberto Rodríguez1, Rubén Hernández21Digital Signal Processing Group, Institute of Cybernetics, Mathematics, and Physics, Havana, Cuba; 2Interdisciplinary Professional Unit of Engineering and Advanced Technology, IPN, MexicoAbstract: Many segmentation techniques have been published, and some of them have been widely used in different application problems. Most of these segmentation techniques have been motivated by specific application purposes. Unsupervised methods, which do not assume any prior scene knowledge can be learned to help the segmentation process, and are obviously more challenging than the supervised ones. In this paper, we present an unsupervised strategy for biomedical image segmentation using an algorithm based on recursively applying mean shift filtering, where entropy is used as a stopping criterion. This strategy is proven with many real images, and a comparison is carried out with manual segmentation. With the proposed strategy, errors less than 20% for false positives and 0% for false negatives are obtained.Keywords: segmentation, mean shift, unsupervised segmentation, entropy

MOVING WINDOW SEGMENTATION FRAMEWORK FOR POINT CLOUDS

Directory of Open Access Journals (Sweden)

G. Sithole

2012-07-01

Full Text Available As lidar point clouds become larger streamed processing becomes more attractive. This paper presents a framework for the streamed segmentation of point clouds with the intention of segmenting unstructured point clouds in real-time. The framework is composed of two main components. The first component segments points within a window shifting over the point cloud. The second component stitches the segments within the windows together. In this fashion a point cloud can be streamed through these two components in sequence, thus producing a segmentation. The algorithm has been tested on airborne lidar point cloud and some results of the performance of the framework are presented.

The comparison of CAP88-PC version 2.0 versus CAP88-PC version 1.0

International Nuclear Information System (INIS)

Yakubovich, B.A.; Klee, K.O.; Palmer, C.R.; Spotts, P.B.

1997-12-01

40 CFR Part 61 (Subpart H of the NESHAP) requires DOE facilities to use approved sampling procedures, computer models, or other approved procedures when calculating Effective Dose Equivalent (EDE) values to members of the public. Currently version 1.0 of the approved computer model CAP88-PC is used to calculate EDE values. The DOE has upgraded the CAP88-PC software to version 2.0. This version provides simplified data entry, better printing characteristics, the use of a mouse, and other features. The DOE has developed and released version 2.0 for testing and comment. This new software is a WINDOWS based application that offers a new graphical user interface with new utilities for preparing and managing population and weather data, and several new decay chains. The program also allows the user to view results before printing. This document describes a test that confirmed CAP88-PC version 2.0 generates results comparable to the original version of the CAP88-PC program

Review of segmentation process in consumer markets

OpenAIRE

Veronika Jadczaková

2013-01-01

Although there has been a considerable debate on market segmentation over five decades, attention was merely devoted to single stages of the segmentation process. In doing so, stages as segmentation base selection or segments profiling have been heavily covered in the extant literature, whereas stages as implementation of the marketing strategy or market definition were of a comparably lower interest. Capitalizing on this shortcoming, this paper strives to close the gap and provide each step...

IFRS 8 – OPERATING SEGMENTS

Directory of Open Access Journals (Sweden)

BOCHIS LEONICA

2009-05-01

Full Text Available Segment reporting in accordance with IFRS 8 will be mandatory for annual financial statements covering periods beginning on or after 1 January 2009. The standards replaces IAS 14, Segment Reporting, from that date. The objective of IFRS 8 is to require

Earthquake cycle modeling of multi-segmented faults: dynamic rupture and ground motion simulation of the 1992 Mw 7.3 Landers earthquake.

Science.gov (United States)

Petukhin, A.; Galvez, P.; Somerville, P.; Ampuero, J. P.

2017-12-01

We perform earthquake cycle simulations to study the characteristics of source scaling relations and strong ground motions and in multi-segmented fault ruptures. For earthquake cycle modeling, a quasi-dynamic solver (QDYN, Luo et al, 2016) is used to nucleate events and the fully dynamic solver (SPECFEM3D, Galvez et al., 2014, 2016) is used to simulate earthquake ruptures. The Mw 7.3 Landers earthquake has been chosen as a target earthquake to validate our methodology. The SCEC fault geometry for the three-segmented Landers rupture is included and extended at both ends to a total length of 200 km. We followed the 2-D spatial correlated Dc distributions based on Hillers et. al. (2007) that associates Dc distribution with different degrees of fault maturity. The fault maturity is related to the variability of Dc on a microscopic scale. Large variations of Dc represents immature faults and lower variations of Dc represents mature faults. Moreover we impose a taper (a-b) at the fault edges and limit the fault depth to 15 km. Using these settings, earthquake cycle simulations are performed to nucleate seismic events on different sections of the fault, and dynamic rupture modeling is used to propagate the ruptures. The fault segmentation brings complexity into the rupture process. For instance, the change of strike between fault segments enhances strong variations of stress. In fact, Oglesby and Mai (2012) show the normal stress varies from positive (clamping) to negative (unclamping) between fault segments, which leads to favorable or unfavorable conditions for rupture growth. To replicate these complexities and the effect of fault segmentation in the rupture process, we perform earthquake cycles with dynamic rupture modeling and generate events similar to the Mw 7.3 Landers earthquake. We extract the asperities of these events and analyze the scaling relations between rupture area, average slip and combined area of asperities versus moment magnitude. Finally, the

The Hierarchy of Segment Reports

Directory of Open Access Journals (Sweden)

Danilo Dorović

2015-05-01

Full Text Available The article presents an attempt to find the connection between reports created for managers responsible for different business segments. With this purpose, the hierarchy of the business reporting segments is proposed. This can lead to better understanding of the expenses under common responsibility of more than one manager since these expenses should be in more than one report. The structure of cost defined per business segment hierarchy with the aim of new, unusual but relevant cost structure for management can be established. Both could potentially bring new information benefits for management in the context of profit reporting.

Segmental dilatation of the ileum

Directory of Open Access Journals (Sweden)

Tune-Yie Shih

2017-01-01

Full Text Available A 2-year-old boy was sent to the emergency department with the chief problem of abdominal pain for 1 day. He was just discharged from the pediatric ward with the diagnosis of mycoplasmal pneumonia and paralytic ileus. After initial examinations and radiographic investigations, midgut volvulus was impressed. An emergency laparotomy was performed. Segmental dilatation of the ileum with volvulus was found. The operative procedure was resection of the dilated ileal segment with anastomosis. The postoperative recovery was uneventful. The unique abnormality of gastrointestinal tract – segmental dilatation of the ileum, is described in details and the literature is reviewed.

Techniques on semiautomatic segmentation using the Adobe Photoshop

Science.gov (United States)

Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae

2005-04-01

The purpose of this research is to enable anybody to semiautomatically segment the anatomical structures in the MRIs, CTs, and other medical images on the personal computer. The segmented images are used for making three-dimensional images, which are helpful in medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was MR scanned to make 557 MRIs, which were transferred to a personal computer. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL; successively, manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a likewise manner, 11 anatomical structures in the 8,500 anatomcial images were segmented. Also, 12 brain and 10 heart anatomical structures in anatomical images were segmented. Proper segmentation was verified by making and examining the coronal, sagittal, and three-dimensional images from the segmented images. During semiautomatic segmentation on Adobe Photoshop, suitable algorithm could be used, the extent of automatization could be regulated, convenient user interface could be used, and software bugs rarely occurred. The techniques of semiautomatic segmentation using Adobe Photoshop are expected to be widely used for segmentation of the anatomical structures in various medical images.

CT identification of bronchopulmonary segments: 50 normal subjects

International Nuclear Information System (INIS)

Osbourne, D.; Vock, P.; Godwin, J.D.; Silverman, P.M.

1984-01-01

A systematic evaluation of the fissures, segmental bronchi and arteries, bronchopulmonary segments, and peripheral pulmonary parenchyma was made from computed tomographic (CT) scans of 50 patients with normal chest radiographs. Seventy percent of the segmental bronchi and 76% of the segmental arteries were identified. Arteries could be traced to their sixth- and seventh-order branches; their orientation to the plane of the CT section allowed gross identification and localization of bronchopulmonary segments

Segmentation of liver tumors on CT images

International Nuclear Information System (INIS)

Pescia, D.

2011-01-01

This thesis is dedicated to 3D segmentation of liver tumors in CT images. This is a task of great clinical interest since it allows physicians benefiting from reproducible and reliable methods for segmenting such lesions. Accurate segmentation would indeed help them during the evaluation of the lesions, the choice of treatment and treatment planning. Such a complex segmentation task should cope with three main scientific challenges: (i) the highly variable shape of the structures being sought, (ii) their similarity of appearance compared with their surrounding medium and finally (iii) the low signal to noise ratio being observed in these images. This problem is addressed in a clinical context through a two step approach, consisting of the segmentation of the entire liver envelope, before segmenting the tumors which are present within the envelope. We begin by proposing an atlas-based approach for computing pathological liver envelopes. Initially images are pre-processed to compute the envelopes that wrap around binary masks in an attempt to obtain liver envelopes from estimated segmentation of healthy liver parenchyma. A new statistical atlas is then introduced and used to segmentation through its diffeomorphic registration to the new image. This segmentation is achieved through the combination of image matching costs as well as spatial and appearance prior using a multi-scale approach with MRF. The second step of our approach is dedicated to lesions segmentation contained within the envelopes using a combination of machine learning techniques and graph based methods. First, an appropriate feature space is considered that involves texture descriptors being determined through filtering using various scales and orientations. Then, state of the art machine learning techniques are used to determine the most relevant features, as well as the hyper plane that separates the feature space of tumoral voxels to the ones corresponding to healthy tissues. Segmentation is then

SIPHER: Scalable Implementation of Primitives for Homomorphic Encryption

Science.gov (United States)

2015-11-01

595–618. 2009. [Ajt96] M. Ajtai. Generating hard instances of lattice problems. Quaderni di Matematica , 13:1–32, 2004. Preliminary version in STOC...1), pages 403–415. 2011. [Ajt96] M. Ajtai. Generating hard instances of lattice problems. Quaderni di Matematica , 13:1–32, 2004. Preliminary version...learning with errors. In ASIACRYPT. 2011. To appear. [Ajt96] M. Ajtai. Generating hard instances of lattice problems. Quaderni di Matematica , 13:1–32

Segmentation of knee injury swelling on infrared images

Science.gov (United States)

Puentes, John; Langet, Hélène; Herry, Christophe; Frize, Monique

2011-03-01

Interpretation of medical infrared images is complex due to thermal noise, absence of texture, and small temperature differences in pathological zones. Acute inflammatory response is a characteristic symptom of some knee injuries like anterior cruciate ligament sprains, muscle or tendons strains, and meniscus tear. Whereas artificial coloring of the original grey level images may allow to visually assess the extent inflammation in the area, their automated segmentation remains a challenging problem. This paper presents a hybrid segmentation algorithm to evaluate the extent of inflammation after knee injury, in terms of temperature variations and surface shape. It is based on the intersection of rapid color segmentation and homogeneous region segmentation, to which a Laplacian of a Gaussian filter is applied. While rapid color segmentation enables to properly detect the observed core of swollen area, homogeneous region segmentation identifies possible inflammation zones, combining homogeneous grey level and hue area segmentation. The hybrid segmentation algorithm compares the potential inflammation regions partially detected by each method to identify overlapping areas. Noise filtering and edge segmentation are then applied to common zones in order to segment the swelling surfaces of the injury. Experimental results on images of a patient with anterior cruciate ligament sprain show the improved performance of the hybrid algorithm with respect to its separated components. The main contribution of this work is a meaningful automatic segmentation of abnormal skin temperature variations on infrared thermography images of knee injury swelling.

Reliability of a Seven-Segment Foot Model with Medial and Lateral Midfoot and Forefoot Segments During Walking Gait.

Science.gov (United States)

Cobb, Stephen C; Joshi, Mukta N; Pomeroy, Robin L

2016-12-01

In-vitro and invasive in-vivo studies have reported relatively independent motion in the medial and lateral forefoot segments during gait. However, most current surface-based models have not defined medial and lateral forefoot or midfoot segments. The purpose of the current study was to determine the reliability of a 7-segment foot model that includes medial and lateral midfoot and forefoot segments during walking gait. Three-dimensional positions of marker clusters located on the leg and 6 foot segments were tracked as 10 participants completed 5 walking trials. To examine the reliability of the foot model, coefficients of multiple correlation (CMC) were calculated across the trials for each participant. Three-dimensional stance time series and range of motion (ROM) during stance were also calculated for each functional articulation. CMCs for all of the functional articulations were ≥ 0.80. Overall, the rearfoot complex (leg-calcaneus segments) was the most reliable articulation and the medial midfoot complex (calcaneus-navicular segments) was the least reliable. With respect to ROM, reliability was greatest for plantarflexion/dorsiflexion and least for abduction/adduction. Further, the stance ROM and time-series patterns results between the current study and previous invasive in-vivo studies that have assessed actual bone motion were generally consistent.

Market Segmentation: An Instructional Module.

Science.gov (United States)

Wright, Peter H.

A concept-based introduction to market segmentation is provided in this instructional module for undergraduate and graduate transportation-related courses. The material can be used in many disciplines including engineering, business, marketing, and technology. The concept of market segmentation is primarily a transportation planning technique by…

A comparison of the Space Station version of ASTROMAG with two free-flyer versions

International Nuclear Information System (INIS)

Green, M.A.

1992-06-01

This Report compares the Space Station version of ASTROMAG with free-flyer versions of ASTROMAG which could fly on an Atlas lla rocket and a Delta rocket. Launch with either free-flyer imposes severe weight limits on the magnet and its cryogenic system. Both versions of ASTROMAG magnet which fly on free-flying satellites do not have to be charged more than once during the mission. This permits one to simplify the charging system and the cryogenic system. The helium ll pump loop which supplies helium to the gas cooled electrical leads can be eliminated in both of the free-flyer versions of the ASTROMAG magnet. This report describes the superconducting dipole moment correction coils which are necessary for the magnet to operate on a free-flying satellite

Medical image segmentation using genetic algorithms.

Science.gov (United States)

Maulik, Ujjwal

2009-03-01

Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.

Versioning of printed products

Science.gov (United States)

Tuijn, Chris

2005-01-01

During the definition of a printed product in an MIS system, a lot of attention is paid to the production process. The MIS systems typically gather all process-related parameters at such a level of detail that they can determine what the exact cost will be to make a specific product. This information can then be used to make a quote for the customer. Considerably less attention is paid to the content of the products since this does not have an immediate impact on the production costs (assuming that the number of inks or plates is known in advance). The content management is typically carried out either by the prepress systems themselves or by dedicated workflow servers uniting all people that contribute to the manufacturing of a printed product. Special care must be taken when considering versioned products. With versioned products we here mean distinct products that have a number of pages or page layers in common. Typical examples are comic books that have to be printed in different languages. In this case, the color plates can be shared over the different versions and the black plate will be different. Other examples are nation-wide magazines or newspapers that have an area with regional pages or advertising leaflets in different languages or currencies. When considering versioned products, the content will become an important cost factor. First of all, the content management (and associated proofing and approval cycles) becomes much more complex and, therefore, the risk that mistakes will be made increases considerably. Secondly, the real production costs are very much content-dependent because the content will determine whether plates can be shared across different versions or not and how many press runs will be needed. In this paper, we will present a way to manage different versions of a printed product. First, we will introduce a data model for version management. Next, we will show how the content of the different versions can be supplied by the customer

Remote sensing image segmentation based on Hadoop cloud platform

Science.gov (United States)

Li, Jie; Zhu, Lingling; Cao, Fubin

2018-01-01

To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

Metrics for image segmentation

Science.gov (United States)

Rees, Gareth; Greenway, Phil; Morray, Denise

1998-07-01

An important challenge in mapping image-processing techniques onto applications is the lack of quantitative performance measures. From a systems engineering perspective these are essential if system level requirements are to be decomposed into sub-system requirements which can be understood in terms of algorithm selection and performance optimization. Nowhere in computer vision is this more evident than in the area of image segmentation. This is a vigorous and innovative research activity, but even after nearly two decades of progress, it remains almost impossible to answer the question 'what would the performance of this segmentation algorithm be under these new conditions?' To begin to address this shortcoming, we have devised a well-principled metric for assessing the relative performance of two segmentation algorithms. This allows meaningful objective comparisons to be made between their outputs. It also estimates the absolute performance of an algorithm given ground truth. Our approach is an information theoretic one. In this paper, we describe the theory and motivation of our method, and present practical results obtained from a range of state of the art segmentation methods. We demonstrate that it is possible to measure the objective performance of these algorithms, and to use the information so gained to provide clues about how their performance might be improved.

Incorporation of squalene into rod outer segments

International Nuclear Information System (INIS)

Keller, R.K.; Fliesler, S.J.

1990-01-01

We have reported previously that squalene is the major radiolabeled nonsaponifiable lipid product derived from [ 3 H]acetate in short term incubations of frog retinas. In the present study, we demonstrate that newly synthesized squalene is incorporated into rod outer segments under similar in vitro conditions. We show further that squalene is an endogenous constituent of frog rod outer segment membranes; its concentration is approximately 9.5 nmol/mumol of phospholipid or about 9% of the level of cholesterol. Pulse-chase experiments with radiolabeled precursors revealed no metabolism of outer segment squalene to sterols in up to 20 h of chase. Taken together with our previous absolute rate studies, these results suggest that most, if not all, of the squalene synthesized by the frog retina is transported to rod outer segments. Synthesis of protein is not required for squalene transport since puromycin had no effect on squalene incorporation into outer segments. Conversely, inhibition of isoprenoid synthesis with mevinolin had no effect on the incorporation of opsin into the outer segment. These latter results support the conclusion that the de novo synthesis and subsequent intracellular trafficking of opsin and isoprenoid lipids destined for the outer segment occur via independent mechanisms

Interactive segmentation techniques algorithms and performance evaluation

CERN Document Server

He, Jia; Kuo, C-C Jay

2013-01-01

This book focuses on interactive segmentation techniques, which have been extensively studied in recent decades. Interactive segmentation emphasizes clear extraction of objects of interest, whose locations are roughly indicated by human interactions based on high level perception. This book will first introduce classic graph-cut segmentation algorithms and then discuss state-of-the-art techniques, including graph matching methods, region merging and label propagation, clustering methods, and segmentation methods based on edge detection. A comparative analysis of these methods will be provided

Market segmentation using perceived constraints

Science.gov (United States)

Jinhee Jun; Gerard Kyle; Andrew Mowen

2008-01-01

We examined the practical utility of segmenting potential visitors to Cleveland Metroparks using their constraint profiles. Our analysis identified three segments based on their scores on the dimensions of constraints: Other priorities--visitors who scored the highest on 'other priorities' dimension; Highly Constrained--visitors who scored relatively high on...

Reduplication Facilitates Early Word Segmentation

Science.gov (United States)

Ota, Mitsuhiko; Skarabela, Barbora

2018-01-01

This study explores the possibility that early word segmentation is aided by infants' tendency to segment words with repeated syllables ("reduplication"). Twenty-four nine-month-olds were familiarized with passages containing one novel reduplicated word and one novel non-reduplicated word. Their central fixation times in response to…

Recognition Using Classification and Segmentation Scoring

National Research Council Canada - National Science Library

Kimball, Owen; Ostendorf, Mari; Rohlicek, Robin

1992-01-01

.... We describe an approach to connected word recognition that allows the use of segmental information through an explicit decomposition of the recognition criterion into classification and segmentation scoring...

NETS - A NEURAL NETWORK DEVELOPMENT TOOL, VERSION 3.0 (MACHINE INDEPENDENT VERSION)

Science.gov (United States)

Baffes, P. T.

1994-01-01

allows the user to generate C code to implement the network loaded into the system. This permits the placement of networks as components, or subroutines, in other systems. In short, once a network performs satisfactorily, the Generate C Code option provides the means for creating a program separate from NETS to run the network. Other features: files may be stored in binary or ASCII format; multiple input propagation is permitted; bias values may be included; capability to scale data without writing scaling code; quick interactive testing of network from the main menu; and several options that allow the user to manipulate learning efficiency. NETS is written in ANSI standard C language to be machine independent. The Macintosh version (MSC-22108) includes code for both a graphical user interface version and a command line interface version. The machine independent version (MSC-21588) only includes code for the command line interface version of NETS 3.0. The Macintosh version requires a Macintosh II series computer and has been successfully implemented under System 7. Four executables are included on these diskettes, two for floating point operations and two for integer arithmetic. It requires Think C 5.0 to compile. A minimum of 1Mb of RAM is required for execution. Sample input files and executables for both the command line version and the Macintosh user interface version are provided on the distribution medium. The Macintosh version is available on a set of three 3.5 inch 800K Macintosh format diskettes. The machine independent version has been successfully implemented on an IBM PC series compatible running MS-DOS, a DEC VAX running VMS, a SunIPC running SunOS, and a CRAY Y-MP running UNICOS. Two executables for the IBM PC version are included on the MS-DOS distribution media, one compiled for floating point operations and one for integer arithmetic. The machine independent version is available on a set of three 5.25 inch 360K MS-DOS format diskettes (standard

NOAA Climate Data Record (CDR) of Ocean Heat Fluxes, Version 1.0 (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Please note, this dataset has been superseded by a newer version (see below). Users should not use this version except in rare cases (e.g., when reproducing previous...

Multifractal-based nuclei segmentation in fish images.

Science.gov (United States)

Reljin, Nikola; Slavkovic-Ilic, Marijeta; Tapia, Coya; Cihoric, Nikola; Stankovic, Srdjan

2017-09-01

The method for nuclei segmentation in fluorescence in-situ hybridization (FISH) images, based on the inverse multifractal analysis (IMFA) is proposed. From the blue channel of the FISH image in RGB format, the matrix of Holder exponents, with one-by-one correspondence with the image pixels, is determined first. The following semi-automatic procedure is proposed: initial nuclei segmentation is performed automatically from the matrix of Holder exponents by applying predefined hard thresholding; then the user evaluates the result and is able to refine the segmentation by changing the threshold, if necessary. After successful nuclei segmentation, the HER2 (human epidermal growth factor receptor 2) scoring can be determined in usual way: by counting red and green dots within segmented nuclei, and finding their ratio. The IMFA segmentation method is tested over 100 clinical cases, evaluated by skilled pathologist. Testing results show that the new method has advantages compared to already reported methods.

A Branch-and-Price Algorithm for Two Multi-Compartment Vehicle Routing Problems

DEFF Research Database (Denmark)

Mirzaei, Samira; Wøhlk, Sanne

2017-01-01

by comparing the optimal costs of the two versions. Computational results are presented for instances with up to 100 customers and the algorithm can solve instances with up to 50 customers and 4 commodities to optimality. NOTE: An early version of the paper was made public on the website of the journal...

The Importance of Marketing Segmentation

Science.gov (United States)

Martin, Gillian

2011-01-01

The rationale behind marketing segmentation is to allow businesses to focus on their consumers' behaviors and purchasing patterns. If done effectively, marketing segmentation allows an organization to achieve its highest return on investment (ROI) in turn for its marketing and sales expenses. If an organization markets its products or services to…

GENII Version 2 Users’ Guide

Energy Technology Data Exchange (ETDEWEB)

Napier, Bruce A.

2004-03-08

The GENII Version 2 computer code was developed for the Environmental Protection Agency (EPA) at Pacific Northwest National Laboratory (PNNL) to incorporate the internal dosimetry models recommended by the International Commission on Radiological Protection (ICRP) and the radiological risk estimating procedures of Federal Guidance Report 13 into updated versions of existing environmental pathway analysis models. The resulting environmental dosimetry computer codes are compiled in the GENII Environmental Dosimetry System. The GENII system was developed to provide a state-of-the-art, technically peer-reviewed, documented set of programs for calculating radiation dose and risk from radionuclides released to the environment. The codes were designed with the flexibility to accommodate input parameters for a wide variety of generic sites. Operation of a new version of the codes, GENII Version 2, is described in this report. Two versions of the GENII Version 2 code system are available, a full-featured version and a version specifically designed for demonstrating compliance with the dose limits specified in 40 CFR 61.93(a), the National Emission Standards for Hazardous Air Pollutants (NESHAPS) for radionuclides. The only differences lie in the limitation of the capabilities of the user to change specific parameters in the NESHAPS version. This report describes the data entry, accomplished via interactive, menu-driven user interfaces. Default exposure and consumption parameters are provided for both the average (population) and maximum individual; however, these may be modified by the user. Source term information may be entered as radionuclide release quantities for transport scenarios, or as basic radionuclide concentrations in environmental media (air, water, soil). For input of basic or derived concentrations, decay of parent radionuclides and ingrowth of radioactive decay products prior to the start of the exposure scenario may be considered. A single code run can

A constructive version of AIP revisited

NARCIS (Netherlands)

Barros, A.; Hou, T.

2008-01-01

In this paper, we review a constructive version of the Approximation Induction Principle. This version states that bisimilarity of regular processes can be decided by observing only a part of their behaviour. We use this constructive version to formulate a complete inference system for the Algebra

Boundary segmentation for fluorescence microscopy using steerable filters

Science.gov (United States)

Ho, David Joon; Salama, Paul; Dunn, Kenneth W.; Delp, Edward J.

2017-02-01

Fluorescence microscopy is used to image multiple subcellular structures in living cells which are not readily observed using conventional optical microscopy. Moreover, two-photon microscopy is widely used to image structures deeper in tissue. Recent advancement in fluorescence microscopy has enabled the generation of large data sets of images at different depths, times, and spectral channels. Thus, automatic object segmentation is necessary since manual segmentation would be inefficient and biased. However, automatic segmentation is still a challenging problem as regions of interest may not have well defined boundaries as well as non-uniform pixel intensities. This paper describes a method for segmenting tubular structures in fluorescence microscopy images of rat kidney and liver samples using adaptive histogram equalization, foreground/background segmentation, steerable filters to capture directional tendencies, and connected-component analysis. The results from several data sets demonstrate that our method can segment tubular boundaries successfully. Moreover, our method has better performance when compared to other popular image segmentation methods when using ground truth data obtained via manual segmentation.

Model-based version management system framework

International Nuclear Information System (INIS)

Mehmood, W.

2016-01-01

In this paper we present a model-based version management system. Version Management System (VMS) a branch of software configuration management (SCM) aims to provide a controlling mechanism for evolution of software artifacts created during software development process. Controlling the evolution requires many activities to perform, such as, construction and creation of versions, identification of differences between versions, conflict detection and merging. Traditional VMS systems are file-based and consider software systems as a set of text files. File based VMS systems are not adequate for performing software configuration management activities such as, version control on software artifacts produced in earlier phases of the software life cycle. New challenges of model differencing, merge, and evolution control arise while using models as central artifact. The goal of this work is to present a generic framework model-based VMS which can be used to overcome the problem of tradition file-based VMS systems and provide model versioning services. (author)

Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging

Directory of Open Access Journals (Sweden)

Xiaodong Zhang

2016-01-01

Full Text Available Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually. In this paper, a sparse representation based classification method is explored. For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation. Elastic net is adopted to replace the traditional L0-norm/L1-norm constraints on sparse representation to stabilize sparse code. To decrease computation cost and to reduce false positives, regions-of-interest are determined to confine candidate infarct voxels. The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset. It is shown that the proposed method could handle well infarcts with intensity variability and ill-defined edges to yield significantly higher Dice coefficient (0.755 ± 0.118 than the other two methods and their enhanced versions by confining their segmentations within the regions-of-interest (average Dice coefficient less than 0.610. The proposed method could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyperacute stage with accuracy and speed to assist the decision making especially for thrombolytic therapy.

Segmentation and visual analysis of whole-body mouse skeleton microSPECT.

Directory of Open Access Journals (Sweden)

Artem Khmelinskii

Full Text Available Whole-body SPECT small animal imaging is used to study cancer, and plays an important role in the development of new drugs. Comparing and exploring whole-body datasets can be a difficult and time-consuming task due to the inherent heterogeneity of the data (high volume/throughput, multi-modality, postural and positioning variability. The goal of this study was to provide a method to align and compare side-by-side multiple whole-body skeleton SPECT datasets in a common reference, thus eliminating acquisition variability that exists between the subjects in cross-sectional and multi-modal studies. Six whole-body SPECT/CT datasets of BALB/c mice injected with bone targeting tracers (99mTc-methylene diphosphonate ((99mTc-MDP and (99mTc-hydroxymethane diphosphonate ((99mTc-HDP were used to evaluate the proposed method. An articulated version of the MOBY whole-body mouse atlas was used as a common reference. Its individual bones were registered one-by-one to the skeleton extracted from the acquired SPECT data following an anatomical hierarchical tree. Sequential registration was used while constraining the local degrees of freedom (DoFs of each bone in accordance to the type of joint and its range of motion. The Articulated Planar Reformation (APR algorithm was applied to the segmented data for side-by-side change visualization and comparison of data. To quantitatively evaluate the proposed algorithm, bone segmentations of extracted skeletons from the correspondent CT datasets were used. Euclidean point to surface distances between each dataset and the MOBY atlas were calculated. The obtained results indicate that after registration, the mean Euclidean distance decreased from 11.5±12.1 to 2.6±2.1 voxels. The proposed approach yielded satisfactory segmentation results with minimal user intervention. It proved to be robust for "incomplete" data (large chunks of skeleton missing and for an intuitive exploration and comparison of multi-modal SPECT

Connecting textual segments

DEFF Research Database (Denmark)

Brügger, Niels

2017-01-01

history than just the years of the emergence of the web, the chapter traces the history of how segments of text have deliberately been connected to each other by the use of specific textual and media features, from clay tablets, manuscripts on parchment, and print, among others, to hyperlinks on stand......In “Connecting textual segments: A brief history of the web hyperlink” Niels Brügger investigates the history of one of the most fundamental features of the web: the hyperlink. Based on the argument that the web hyperlink is best understood if it is seen as another step in a much longer and broader...

A comparative study on medical image segmentation methods

Directory of Open Access Journals (Sweden)

Praylin Selva Blessy SELVARAJ ASSLEY

2014-03-01

Full Text Available Image segmentation plays an important role in medical images. It has been a relevant research area in computer vision and image analysis. Many segmentation algorithms have been proposed for medical images. This paper makes a review on segmentation methods for medical images. In this survey, segmentation methods are divided into five categories: region based, boundary based, model based, hybrid based and atlas based. The five different categories with their principle ideas, advantages and disadvantages in segmenting different medical images are discussed.

Distance measures for image segmentation evaluation

OpenAIRE

Monteiro, Fernando C.; Campilho, Aurélio

2012-01-01

In this paper we present a study of evaluation measures that enable the quantification of the quality of an image segmentation result. Despite significant advances in image segmentation techniques, evaluation of these techniques thus far has been largely subjective. Typically, the effectiveness of a new algorithm is demonstrated only by the presentation of a few segmented images and is otherwise left to subjective evaluation by the reader. Such an evaluation criterion can be useful for differ...

Determining Optimal Decision Version

Directory of Open Access Journals (Sweden)

Olga Ioana Amariei

2014-06-01

Full Text Available In this paper we start from the calculation of the product cost, applying the method of calculating the cost of hour- machine (THM, on each of the three cutting machines, namely: the cutting machine with plasma, the combined cutting machine (plasma and water jet and the cutting machine with a water jet. Following the calculation of cost and taking into account the precision of manufacturing of each machine, as well as the quality of the processed surface, the optimal decisional version needs to be determined regarding the product manufacturing. To determine the optimal decisional version, we resort firstly to calculating the optimal version on each criterion, and then overall using multiattribute decision methods.

Multiple instance learning tracking method with local sparse representation

KAUST Repository

Xie, Chengjun

2013-10-01

When objects undergo large pose change, illumination variation or partial occlusion, most existed visual tracking algorithms tend to drift away from targets and even fail in tracking them. To address this issue, in this study, the authors propose an online algorithm by combining multiple instance learning (MIL) and local sparse representation for tracking an object in a video system. The key idea in our method is to model the appearance of an object by local sparse codes that can be formed as training data for the MIL framework. First, local image patches of a target object are represented as sparse codes with an overcomplete dictionary, where the adaptive representation can be helpful in overcoming partial occlusion in object tracking. Then MIL learns the sparse codes by a classifier to discriminate the target from the background. Finally, results from the trained classifier are input into a particle filter framework to sequentially estimate the target state over time in visual tracking. In addition, to decrease the visual drift because of the accumulative errors when updating the dictionary and classifier, a two-step object tracking method combining a static MIL classifier with a dynamical MIL classifier is proposed. Experiments on some publicly available benchmarks of video sequences show that our proposed tracker is more robust and effective than others. © The Institution of Engineering and Technology 2013.

Segmentation of complex document

Directory of Open Access Journals (Sweden)

Souad Oudjemia

2014-06-01

Full Text Available In this paper we present a method for segmentation of documents image with complex structure. This technique based on GLCM (Grey Level Co-occurrence Matrix used to segment this type of document in three regions namely, 'graphics', 'background' and 'text'. Very briefly, this method is to divide the document image, in block size chosen after a series of tests and then applying the co-occurrence matrix to each block in order to extract five textural parameters which are energy, entropy, the sum entropy, difference entropy and standard deviation. These parameters are then used to classify the image into three regions using the k-means algorithm; the last step of segmentation is obtained by grouping connected pixels. Two performance measurements are performed for both graphics and text zones; we have obtained a classification rate of 98.3% and a Misclassification rate of 1.79%.

Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries

Science.gov (United States)

Davuluri, Pavani; Wu, Jie; Tang, Yang; Cockrell, Charles H.; Ward, Kevin R.; Najarian, Kayvan; Hargraves, Rosalyn H.

2012-01-01

Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising. PMID:22919433

SALIENCY BASED SEGMENTATION OF SATELLITE IMAGES

Directory of Open Access Journals (Sweden)

A. Sharma

2015-03-01

Full Text Available Saliency gives the way as humans see any image and saliency based segmentation can be eventually helpful in Psychovisual image interpretation. Keeping this in view few saliency models are used along with segmentation algorithm and only the salient segments from image have been extracted. The work is carried out for terrestrial images as well as for satellite images. The methodology used in this work extracts those segments from segmented image which are having higher or equal saliency value than a threshold value. Salient and non salient regions of image become foreground and background respectively and thus image gets separated. For carrying out this work a dataset of terrestrial images and Worldview 2 satellite images (sample data are used. Results show that those saliency models which works better for terrestrial images are not good enough for satellite image in terms of foreground and background separation. Foreground and background separation in terrestrial images is based on salient objects visible on the images whereas in satellite images this separation is based on salient area rather than salient objects.

Segmentation precedes face categorization under suboptimal conditions

Directory of Open Access Journals (Sweden)

Carlijn eVan Den Boomen

2015-05-01

Full Text Available Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and category-selective responses in the brain, using electroencephalography (EEG. Surface segmentation and category content were both manipulated using texture-defined objects, including faces. This allowed us to study brain activity related to segmentation and to categorization. In the main experiment, participants viewed texture-defined objects for a duration of 800 ms. EEG results revealed that segmentation-related responses precede category-selective responses. Three additional experiments revealed that the presence and timing of categorization depends on stimulus properties and presentation duration. Photographic objects were presented for a long and short (92 ms duration and evoked fast category-selective responses in both cases. On the other hand, presentation of texture-defined objects for a short duration only evoked segmentation-related but no category-selective responses. Category-selective responses were much slower when evoked by texture-defined than by photographic objects. We suggest that in case of categorization of objects under suboptimal conditions, such as when low-level stimulus properties are not sufficient for fast object categorization, segmentation facilitates the slower categorization process.

A Kalman Filtering Perspective for Multiatlas Segmentation*

Science.gov (United States)

Gao, Yi; Zhu, Liangjia; Cates, Joshua; MacLeod, Rob S.; Bouix, Sylvain; Tannenbaum, Allen

2016-01-01

In multiatlas segmentation, one typically registers several atlases to the novel image, and their respective segmented label images are transformed and fused to form the final segmentation. In this work, we provide a new dynamical system perspective for multiatlas segmentation, inspired by the following fact: The transformation that aligns the current atlas to the novel image can be not only computed by direct registration but also inferred from the transformation that aligns the previous atlas to the image together with the transformation between the two atlases. This process is similar to the global positioning system on a vehicle, which gets position by inquiring from the satellite and by employing the previous location and velocity—neither answer in isolation being perfect. To solve this problem, a dynamical system scheme is crucial to combine the two pieces of information; for example, a Kalman filtering scheme is used. Accordingly, in this work, a Kalman multiatlas segmentation is proposed to stabilize the global/affine registration step. The contributions of this work are twofold. First, it provides a new dynamical systematic perspective for standard independent multiatlas registrations, and it is solved by Kalman filtering. Second, with very little extra computation, it can be combined with most existing multiatlas segmentation schemes for better registration/segmentation accuracy. PMID:26807162

Segmentation precedes face categorization under suboptimal conditions.

Science.gov (United States)

Van Den Boomen, Carlijn; Fahrenfort, Johannes J; Snijders, Tineke M; Kemner, Chantal

2015-01-01

Both categorization and segmentation processes play a crucial role in face perception. However, the functional relation between these subprocesses is currently unclear. The present study investigates the temporal relation between segmentation-related and category-selective responses in the brain, using electroencephalography (EEG). Surface segmentation and category content were both manipulated using texture-defined objects, including faces. This allowed us to study brain activity related to segmentation and to categorization. In the main experiment, participants viewed texture-defined objects for a duration of 800 ms. EEG results revealed that segmentation-related responses precede category-selective responses. Three additional experiments revealed that the presence and timing of categorization depends on stimulus properties and presentation duration. Photographic objects were presented for a long and short (92 ms) duration and evoked fast category-selective responses in both cases. On the other hand, presentation of texture-defined objects for a short duration only evoked segmentation-related but no category-selective responses. Category-selective responses were much slower when evoked by texture-defined than by photographic objects. We suggest that in case of categorization of objects under suboptimal conditions, such as when low-level stimulus properties are not sufficient for fast object categorization, segmentation facilitates the slower categorization process.

Improved document image segmentation algorithm using multiresolution morphology

Science.gov (United States)

Bukhari, Syed Saqib; Shafait, Faisal; Breuel, Thomas M.

2011-01-01

Page segmentation into text and non-text elements is an essential preprocessing step before optical character recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage characters due to the presence of non-text elements. This paper describes modifications to the text/non-text segmentation algorithm presented by Bloomberg,1 which is also available in his open-source Leptonica library.2The modifications result in significant improvements and achieved better segmentation accuracy than the original algorithm for UW-III, UNLV, ICDAR 2009 page segmentation competition test images and circuit diagram datasets.

Apparatus For Laminating Segmented Core For Electric Machine

Science.gov (United States)

Lawrence, Robert Anthony; Stabel, Gerald R

2003-06-17

A segmented core for an electric machine includes segments stamped from coated electric steel. The segments each have a first end, a second end, and winding openings. A predetermined number of segments are placed end-to-end to form layers. The layers are stacked such that each of the layers is staggered from adjacent layers by a predetermined rotation angle. The winding openings of each of the layers are in vertical alignment with the winding openings of the adjacent layers. The stack of layers is secured to form the segmented core.

Prediction of Ionizing Radiation Resistance in Bacteria Using a Multiple Instance Learning Model.

Science.gov (United States)

Aridhi, Sabeur; Sghaier, Haïtham; Zoghlami, Manel; Maddouri, Mondher; Nguifo, Engelbert Mephu

2016-01-01

Ionizing-radiation-resistant bacteria (IRRB) are important in biotechnology. In this context, in silico methods of phenotypic prediction and genotype-phenotype relationship discovery are limited. In this work, we analyzed basal DNA repair proteins of most known proteome sequences of IRRB and ionizing-radiation-sensitive bacteria (IRSB) in order to learn a classifier that correctly predicts this bacterial phenotype. We formulated the problem of predicting bacterial ionizing radiation resistance (IRR) as a multiple-instance learning (MIL) problem, and we proposed a novel approach for this purpose. We provide a MIL-based prediction system that classifies a bacterium to either IRRB or IRSB. The experimental results of the proposed system are satisfactory with 91.5% of successful predictions.

SEGMENTATION OF SME PORTFOLIO IN BANKING SYSTEM

Directory of Open Access Journals (Sweden)

Namolosu Simona Mihaela

2013-07-01

Full Text Available The Small and Medium Enterprises (SMEs represent an important target market for commercial Banks. In this respect, finding the best methods for designing and implementing the optimal marketing strategies (for this target are a continuous concern for the marketing specialists and researchers from the banking system; the purpose is to find the most suitable service model for these companies. SME portfolio of a bank is not homogeneous, different characteristics and behaviours being identified. The current paper reveals empirical evidence about SME portfolio characteristics and segmentation methods used in banking system. Its purpose is to identify if segmentation has an impact in finding the optimal marketing strategies and service model and if this hypothesis might be applicable for any commercial bank, irrespective of country/ region. Some banks are segmenting the SME portfolio by a single criterion: the annual company (official turnover; others are considering also profitability and other financial indicators of the company. In some cases, even the banking behaviour becomes a criterion. For all cases, creating scenarios with different thresholds and estimating the impact in profitability and volumes are two mandatory steps in establishing the final segmentation (criteria matrix. Details about each of these segmentation methods may be found in the paper. Testing the final matrix of criteria is also detailed, with the purpose of making realistic estimations. Example for lending products is provided; the product offer is presented as responding to needs of targeted sub segment and therefore being correlated with the sub segment characteristics. Identifying key issues and trends leads to further action plan proposal. Depending on overall strategy and commercial target of the bank, the focus may shift, one or more sub segments becoming high priority (for acquisition/ activation/ retention/ cross sell/ up sell/ increase profitability etc., while

Event segmentation ability uniquely predicts event memory.

Science.gov (United States)

Sargent, Jesse Q; Zacks, Jeffrey M; Hambrick, David Z; Zacks, Rose T; Kurby, Christopher A; Bailey, Heather R; Eisenberg, Michelle L; Beck, Taylor M

2013-11-01

Memory for everyday events plays a central role in tasks of daily living, autobiographical memory, and planning. Event memory depends in part on segmenting ongoing activity into meaningful units. This study examined the relationship between event segmentation and memory in a lifespan sample to answer the following question: Is the ability to segment activity into meaningful events a unique predictor of subsequent memory, or is the relationship between event perception and memory accounted for by general cognitive abilities? Two hundred and eight adults ranging from 20 to 79years old segmented movies of everyday events and attempted to remember the events afterwards. They also completed psychometric ability tests and tests measuring script knowledge for everyday events. Event segmentation and script knowledge both explained unique variance in event memory above and beyond the psychometric measures, and did so as strongly in older as in younger adults. These results suggest that event segmentation is a basic cognitive mechanism, important for memory across the lifespan. Copyright © 2013 Elsevier B.V. All rights reserved.

DIONISIO 2.0: New version of the code for simulating a whole nuclear fuel rod under extended irradiation

Energy Technology Data Exchange (ETDEWEB)

Soba, Alejandro, E-mail: soba@cnea.gov.ar; Denis, Alicia

2015-10-15

Highlights: • A new version of the DIONISIO code is developed. • DIONISIO is devoted to simulating the behavior of a nuclear fuel rod in operation. • The formerly two-dimensional simulation of a pellet-cladding segment is now extended to the whole rod length. • An acceptable and more realistic agreement with experimental data is obtained. • The prediction range of our code is extended up to average burnup of 60 MWd/kgU. - Abstract: The version 2.0 of the DIONISIO code, that incorporates diverse new aspects, has been recently developed. One of them is referred to the code architecture that allows taking into account the axial variation of the conditions external to the rod. With this purpose, the rod is divided into a number of axial segments. In each one the program considers the system formed by a pellet and the corresponding cladding portion and solves the numerous phenomena that take place under the local conditions of linear power and coolant temperature, which are given as input parameters. To do this a bi-dimensional domain in the r–z plane is considered where cylindrical symmetry and also symmetry with respect to the pellet mid-plane are assumed. The results obtained for this representative system are assumed valid for the complete segment. The program thus produces in each rod section the values of the temperature, stress, strain, among others as outputs, as functions of the local coordinates r and z. Then, the general rod parameters (internal rod pressure, amount of fission gas released, pellet stack elongation, etc.) are evaluated. Moreover, new calculation tools designed to extend the application range of the code to high burnup, which were reported elsewhere, have also been incorporated to DIONISIO 2.0 in recent times. With these improvements, the code results are compared with some 33 experiments compiled in the IFPE data base, that cover more than 380 fuel rods irradiated up to average burnup levels of 40–60 MWd/kgU. The results of these

DIONISIO 2.0: New version of the code for simulating a whole nuclear fuel rod under extended irradiation

International Nuclear Information System (INIS)

Soba, Alejandro; Denis, Alicia

2015-01-01

Highlights: • A new version of the DIONISIO code is developed. • DIONISIO is devoted to simulating the behavior of a nuclear fuel rod in operation. • The formerly two-dimensional simulation of a pellet-cladding segment is now extended to the whole rod length. • An acceptable and more realistic agreement with experimental data is obtained. • The prediction range of our code is extended up to average burnup of 60 MWd/kgU. - Abstract: The version 2.0 of the DIONISIO code, that incorporates diverse new aspects, has been recently developed. One of them is referred to the code architecture that allows taking into account the axial variation of the conditions external to the rod. With this purpose, the rod is divided into a number of axial segments. In each one the program considers the system formed by a pellet and the corresponding cladding portion and solves the numerous phenomena that take place under the local conditions of linear power and coolant temperature, which are given as input parameters. To do this a bi-dimensional domain in the r–z plane is considered where cylindrical symmetry and also symmetry with respect to the pellet mid-plane are assumed. The results obtained for this representative system are assumed valid for the complete segment. The program thus produces in each rod section the values of the temperature, stress, strain, among others as outputs, as functions of the local coordinates r and z. Then, the general rod parameters (internal rod pressure, amount of fission gas released, pellet stack elongation, etc.) are evaluated. Moreover, new calculation tools designed to extend the application range of the code to high burnup, which were reported elsewhere, have also been incorporated to DIONISIO 2.0 in recent times. With these improvements, the code results are compared with some 33 experiments compiled in the IFPE data base, that cover more than 380 fuel rods irradiated up to average burnup levels of 40–60 MWd/kgU. The results of these

Retina image–based optic disc segmentation

Directory of Open Access Journals (Sweden)

Ching-Lin Wang

2016-05-01

Full Text Available The change of optic disc can be used to diagnose many eye diseases, such as glaucoma, diabetic retinopathy and macular degeneration. Moreover, retinal blood vessel pattern is unique for human beings even for identical twins. It is a highly stable pattern in biometric identification. Since optic disc is the beginning of the optic nerve and main blood vessels in retina, it can be used as a reference point of identification. Therefore, optic disc segmentation is an important technique for developing a human identity recognition system and eye disease diagnostic system. This article hence presents an optic disc segmentation method to extract the optic disc from a retina image. The experimental results show that the optic disc segmentation method can give impressive results in segmenting the optic disc from a retina image.

The Process of Marketing Segmentation Strategy Selection

OpenAIRE

Ionel Dumitru

2007-01-01

The process of marketing segmentation strategy selection represents the essence of strategical marketing. We present hereinafter the main forms of the marketing statategy segmentation: undifferentiated marketing, differentiated marketing, concentrated marketing and personalized marketing. In practice, the companies use a mix of these marketing segmentation methods in order to maximize the proffit and to satisfy the consumers’ needs.

Detailed analysis of the Japanese version of the Rapid Dementia Screening Test, revised version.

Science.gov (United States)

Moriyama, Yasushi; Yoshino, Aihide; Muramatsu, Taro; Mimura, Masaru

2017-11-01

The number-transcoding task on the Japanese version of the Rapid Dementia Screening Test (RDST-J) requires mutual conversion between Arabic and Chinese numerals (209 to , 4054 to , to 681, to 2027). In this task, question and answer styles of Chinese numerals are written horizontally. We investigated the impact of changing the task so that Chinese numerals are written vertically. Subjects were 211 patients with very mild to severe Alzheimer's disease and 42 normal controls. Mini-Mental State Examination scores ranged from 26 to 12, and Clinical Dementia Rating scores ranged from 0.5 to 3. Scores of all four subtasks of the transcoding task significantly improved in the revised version compared with the original version. The sensitivity and specificity of total scores ≥9 on the RDST-J original and revised versions for discriminating between controls and subjects with Clinical Dementia Rating scores of 0.5 were 63.8% and 76.6% on the original and 60.1% and 85.8% on revised version. The revised RDST-J total score had low sensitivity and high specificity compared with the original RDST-J for discriminating subjects with Clinical Dementia Rating scores of 0.5 from controls. © 2017 Japanese Psychogeriatric Society.

Possibilities of segmentation variables in relation with advertising

OpenAIRE

Erbanová, Nela

2011-01-01

The aim of this thesis is to capture significant segmentation variables that shape marketing communication with an emphasis on advertising. The theoretical part deals with the concepts of market segmentation, segmentation variables, marketing communication, advertising and research. The practical part is focused on the realization of the actual research using a questionnaire survey and the evaluation of questions from Market Media Lifestyle. Only traditional descriptive segmentation variables...

Version 2 of RSXMULTI

International Nuclear Information System (INIS)

Heinicke, P.; Berg, D.; Constanta-Fanourakis, P.; Quigg, E.K.

1985-01-01

MULTI is a general purpose, high speed, high energy physics interface to data acquisition and data investigation system that runs on PDP-11 and VAX architecture. This paper describes the latest version of MULTI, which runs under RSX-11M version 4.1 and supports a modular approach to the separate tasks that interface to it, allowing the same system to be used in single CPU test beam experiments as well as multiple interconnected CPU, large scale experiments. MULTI uses CAMAC (IEE-583) for control and monitoring of an experiment, and is written in FORTRAN-77 and assembler. The design of this version, which simplified the interface between tasks, and eliminated the need for a hard to maintain homegrown I/O system is also discussed

Open-source software platform for medical image segmentation applications

Science.gov (United States)

Namías, R.; D'Amato, J. P.; del Fresno, M.

2017-11-01

Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

SPAM- SPECTRAL ANALYSIS MANAGER (UNIX VERSION)

Science.gov (United States)

Solomon, J. E.

1994-01-01

The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different

Bayesian automated cortical segmentation for neonatal MRI

Science.gov (United States)

Chou, Zane; Paquette, Natacha; Ganesh, Bhavana; Wang, Yalin; Ceschin, Rafael; Nelson, Marvin D.; Macyszyn, Luke; Gaonkar, Bilwaj; Panigrahy, Ashok; Lepore, Natasha

2017-11-01

Several attempts have been made in the past few years to develop and implement an automated segmentation of neonatal brain structural MRI. However, accurate automated MRI segmentation remains challenging in this population because of the low signal-to-noise ratio, large partial volume effects and inter-individual anatomical variability of the neonatal brain. In this paper, we propose a learning method for segmenting the whole brain cortical grey matter on neonatal T2-weighted images. We trained our algorithm using a neonatal dataset composed of 3 fullterm and 4 preterm infants scanned at term equivalent age. Our segmentation pipeline combines the FAST algorithm from the FSL library software and a Bayesian segmentation approach to create a threshold matrix that minimizes the error of mislabeling brain tissue types. Our method shows promising results with our pilot training set. In both preterm and full-term neonates, automated Bayesian segmentation generates a smoother and more consistent parcellation compared to FAST, while successfully removing the subcortical structure and cleaning the edges of the cortical grey matter. This method show promising refinement of the FAST segmentation by considerably reducing manual input and editing required from the user, and further improving reliability and processing time of neonatal MR images. Further improvement will include a larger dataset of training images acquired from different manufacturers.

Moving Segmentation Up the Supply-Chain: Supply Chain Segmentation and Artificial Neural Networks

OpenAIRE

Erevelles, Sunil; Fukawa, Nobuyuki

2008-01-01

This paper explained the concept of supply-side segmentation and transvectional alignment, and applies these concepts in the artificial neural network (ANN). To the best of our knowledge, no research has applied ANN in explaining the heterogeneity of both the supply-side and demand-side of a market in forming relational entity that consists of firms at all levels of the supply chain and the demand chain. The ANN offers a way of operationalizing the concept of supply-side segmentation. In toda...

Segmentation in reading and film comprehension.

Science.gov (United States)

Zacks, Jeffrey M; Speer, Nicole K; Reynolds, Jeremy R

2009-05-01

When reading a story or watching a film, comprehenders construct a series of representations in order to understand the events depicted. Discourse comprehension theories and a recent theory of perceptual event segmentation both suggest that comprehenders monitor situational features such as characters' goals, to update these representations at natural boundaries in activity. However, the converging predictions of these theories had previously not been tested directly. Two studies provided evidence that changes in situational features such as characters, their locations, their interactions with objects, and their goals are related to the segmentation of events in both narrative texts and films. A 3rd study indicated that clauses with event boundaries are read more slowly than are other clauses and that changes in situational features partially mediate this relation. A final study suggested that the predictability of incoming information influences reading rate and possibly event segmentation. Taken together, these results suggest that processing situational changes during comprehension is an important determinant of how one segments ongoing activity into events and that this segmentation is related to the control of processing during reading. (c) 2009 APA, all rights reserved.

CT-based manual segmentation and evaluation of paranasal sinuses.

Science.gov (United States)

Pirner, S; Tingelhoff, K; Wagner, I; Westphal, R; Rilk, M; Wahl, F M; Bootz, F; Eichhorn, Klaus W G

2009-04-01

Manual segmentation of computed tomography (CT) datasets was performed for robot-assisted endoscope movement during functional endoscopic sinus surgery (FESS). Segmented 3D models are needed for the robots' workspace definition. A total of 50 preselected CT datasets were each segmented in 150-200 coronal slices with 24 landmarks being set. Three different colors for segmentation represent diverse risk areas. Extension and volumetric measurements were performed. Three-dimensional reconstruction was generated after segmentation. Manual segmentation took 8-10 h for each CT dataset. The mean volumes were: right maxillary sinus 17.4 cm(3), left side 17.9 cm(3), right frontal sinus 4.2 cm(3), left side 4.0 cm(3), total frontal sinuses 7.9 cm(3), sphenoid sinus right side 5.3 cm(3), left side 5.5 cm(3), total sphenoid sinus volume 11.2 cm(3). Our manually segmented 3D-models present the patient's individual anatomy with a special focus on structures in danger according to the diverse colored risk areas. For safe robot assistance, the high-accuracy models represent an average of the population for anatomical variations, extension and volumetric measurements. They can be used as a database for automatic model-based segmentation. None of the segmentation methods so far described provide risk segmentation. The robot's maximum distance to the segmented border can be adjusted according to the differently colored areas.

Modeling of market segmentation for new IT product development

Science.gov (United States)

Nasiopoulos, Dimitrios K.; Sakas, Damianos P.; Vlachos, D. S.; Mavrogianni, Amanda

2015-02-01

Businesses from all Information Technology sectors use market segmentation[1] in their product development[2] and strategic planning[3]. Many studies have concluded that market segmentation is considered as the norm of modern marketing. With the rapid development of technology, customer needs are becoming increasingly diverse. These needs can no longer be satisfied by a mass marketing approach and follow one rule. IT Businesses can face with this diversity by pooling customers[4] with similar requirements and buying behavior and strength into segments. The result of the best choices about which segments are the most appropriate to serve can then be made, thus making the best of finite resources. Despite the attention which segmentation gathers and the resources that are invested in it, growing evidence suggests that businesses have problems operationalizing segmentation[5]. These problems take various forms. There may have been a rule that the segmentation process necessarily results in homogeneous groups of customers for whom appropriate marketing programs and procedures for dealing with them can be developed. Then the segmentation process, that a company follows, can fail. This increases concerns about what causes segmentation failure and how it might be overcome. To prevent the failure, we created a dynamic simulation model of market segmentation[6] based on the basic factors leading to this segmentation.

Skin Segmentation Based on Graph Cuts

Institute of Scientific and Technical Information of China (English)

HU Zhilan; WANG Guijin; LIN Xinggang; YAN Hong

2009-01-01

Skin segmentation is widely used in many computer vision tasks to improve automated visualiza-tion. This paper presents a graph cuts algorithm to segment arbitrary skin regions from images. The detected face is used to determine the foreground skin seeds and the background non-skin seeds with the color probability distributions for the foreground represented by a single Gaussian model and for the background by a Gaussian mixture model. The probability distribution of the image is used for noise suppression to alle-viate the influence of the background regions having skin-like colors. Finally, the skin is segmented by graph cuts, with the regional parameter y optimally selected to adapt to different images. Tests of the algorithm on many real wodd photographs show that the scheme accurately segments skin regions and is robust against illumination variations, individual skin variations, and cluttered backgrounds.

Mixed segmentation

DEFF Research Database (Denmark)

Hansen, Allan Grutt; Bonde, Anders; Aagaard, Morten

content analysis and audience segmentation in a single-source perspective. The aim is to explain and understand target groups in relation to, on the one hand, emotional response to commercials or other forms of audio-visual communication and, on the other hand, living preferences and personality traits...

Review methods for image segmentation from computed tomography images

International Nuclear Information System (INIS)

Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik; Mahmud, Rozi

2014-01-01

Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affect the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan

Dynamics in international market segmentation of new product growth

NARCIS (Netherlands)

Lemmens, A.; Croux, C.; Stremersch, S.

2012-01-01

Prior international segmentation studies have been static in that they have identified segments that remain stable over time. This paper shows that country segments in new product growth are intrinsically dynamic. We propose a semiparametric hidden Markov model to dynamically segment countries based

Region segmentation along image sequence

International Nuclear Information System (INIS)

Monchal, L.; Aubry, P.

1995-01-01

A method to extract regions in sequence of images is proposed. Regions are not matched from one image to the following one. The result of a region segmentation is used as an initialization to segment the following and image to track the region along the sequence. The image sequence is exploited as a spatio-temporal event. (authors). 12 refs., 8 figs

NOAA Climate Data Record (CDR) of Sea Surface Temperature - WHOI, Version 1.0 (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Please note, this dataset has been superseded by a newer version (see below). Users should not use this version except in rare cases (e.g., when reproducing previous...

NOAA Climate Data Record (CDR) of Ocean Near Surface Atmospheric Properties, Version 1 (Version Superseded)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Please note, this dataset has been superseded by a newer version (see below). Users should not use this version except in rare cases (e.g., when reproducing previous...

Unsupervised Segmentation Methods of TV Contents

Directory of Open Access Journals (Sweden)

Elie El-Khoury

2010-01-01

Full Text Available We present a generic algorithm to address various temporal segmentation topics of audiovisual contents such as speaker diarization, shot, or program segmentation. Based on a GLR approach, involving the ΔBIC criterion, this algorithm requires the value of only a few parameters to produce segmentation results at a desired scale and on most typical low-level features used in the field of content-based indexing. Results obtained on various corpora are of the same quality level than the ones obtained by other dedicated and state-of-the-art methods.

Technical report on semiautomatic segmentation using the Adobe Photoshop.

Science.gov (United States)

Park, Jin Seo; Chung, Min Suk; Hwang, Sung Bae; Lee, Yong Sook; Har, Dong-Hwan

2005-12-01

The purpose of this research is to enable users to semiautomatically segment the anatomical structures in magnetic resonance images (MRIs), computerized tomographs (CTs), and other medical images on a personal computer. The segmented images are used for making 3D images, which are helpful to medical education and research. To achieve this purpose, the following trials were performed. The entire body of a volunteer was scanned to make 557 MRIs. On Adobe Photoshop, contours of 19 anatomical structures in the MRIs were semiautomatically drawn using MAGNETIC LASSO TOOL and manually corrected using either LASSO TOOL or DIRECT SELECTION TOOL to make 557 segmented images. In a similar manner, 13 anatomical structures in 8,590 anatomical images were segmented. Proper segmentation was verified by making 3D images from the segmented images. Semiautomatic segmentation using Adobe Photoshop is expected to be widely used for segmentation of anatomical structures in various medical images.

Graph run-length matrices for histopathological image segmentation.

Science.gov (United States)

Tosun, Akif Burak; Gunduz-Demir, Cigdem

2011-03-01

The histopathological examination of tissue specimens is essential for cancer diagnosis and grading. However, this examination is subject to a considerable amount of observer variability as it mainly relies on visual interpretation of pathologists. To alleviate this problem, it is very important to develop computational quantitative tools, for which image segmentation constitutes the core step. In this paper, we introduce an effective and robust algorithm for the segmentation of histopathological tissue images. This algorithm incorporates the background knowledge of the tissue organization into segmentation. For this purpose, it quantifies spatial relations of cytological tissue components by constructing a graph and uses this graph to define new texture features for image segmentation. This new texture definition makes use of the idea of gray-level run-length matrices. However, it considers the runs of cytological components on a graph to form a matrix, instead of considering the runs of pixel intensities. Working with colon tissue images, our experiments demonstrate that the texture features extracted from "graph run-length matrices" lead to high segmentation accuracies, also providing a reasonable number of segmented regions. Compared with four other segmentation algorithms, the results show that the proposed algorithm is more effective in histopathological image segmentation.

Reliability and validity of the Japanese version of the Resilience Scale and its short version

Directory of Open Access Journals (Sweden)

Kondo Maki

2010-11-01

Full Text Available Abstract Background The clinical relevance of resilience has received considerable attention in recent years. The aim of this study is to demonstrate the reliability and validity of the Japanese version of the Resilience Scale (RS and short version of the RS (RS-14. Findings The original English version of RS was translated to Japanese and the Japanese version was confirmed by back-translation. Participants were 430 nursing and university psychology students. The RS, Center for Epidemiologic Studies Depression Scale (CES-D, Rosenberg Self-Esteem Scale (RSES, Social Support Questionnaire (SSQ, Perceived Stress Scale (PSS, and Sheehan Disability Scale (SDS were administered. Internal consistency, convergent validity and factor loadings were assessed at initial assessment. Test-retest reliability was assessed using data collected from 107 students at 3 months after baseline. Mean score on the RS was 111.19. Cronbach's alpha coefficients for the RS and RS-14 were 0.90 and 0.88, respectively. The test-retest correlation coefficients for the RS and RS-14 were 0.83 and 0.84, respectively. Both the RS and RS-14 were negatively correlated with the CES-D and SDS, and positively correlated with the RSES, SSQ and PSS (all p Conclusions This study demonstrates that the Japanese version of RS has psychometric properties with high degrees of internal consistency, high test-retest reliability, and relatively low concurrent validity. RS-14 was equivalent to the RS in internal consistency, test-retest reliability, and concurrent validity. Low scores on the RS, a positive correlation between the RS and perceived stress, and a relatively low correlation between the RS and depressive symptoms in this study suggest that validity of the Japanese version of the RS might be relatively low compared with the original English version.

Segmentation of sows in farrowing pens

DEFF Research Database (Denmark)

Tu, Gang Jun; Karstoft, Henrik; Pedersen, Lene Juul

2014-01-01

The correct segmentation of a foreground object in video recordings is an important task for many surveillance systems. The development of an effective and practical algorithm to segment sows in grayscale video recordings captured under commercial production conditions is described...

Osmotic and Heat Stress Effects on Segmentation.

Directory of Open Access Journals (Sweden)

Julian Weiss

Full Text Available During vertebrate embryonic development, early skin, muscle, and bone progenitor populations organize into segments known as somites. Defects in this conserved process of segmentation lead to skeletal and muscular deformities, such as congenital scoliosis, a curvature of the spine caused by vertebral defects. Environmental stresses such as hypoxia or heat shock produce segmentation defects, and significantly increase the penetrance and severity of vertebral defects in genetically susceptible individuals. Here we show that a brief exposure to a high osmolarity solution causes reproducible segmentation defects in developing zebrafish (Danio rerio embryos. Both osmotic shock and heat shock produce border defects in a dose-dependent manner, with an increase in both frequency and severity of defects. We also show that osmotic treatment has a delayed effect on somite development, similar to that observed in heat shocked embryos. Our results establish osmotic shock as an alternate experimental model for stress, affecting segmentation in a manner comparable to other known environmental stressors. The similar effects of these two distinct environmental stressors support a model in which a variety of cellular stresses act through a related response pathway that leads to disturbances in the segmentation process.

Image segmentation evaluation for very-large datasets

Science.gov (United States)

Reeves, Anthony P.; Liu, Shuang; Xie, Yiting

2016-03-01

With the advent of modern machine learning methods and fully automated image analysis there is a need for very large image datasets having documented segmentations for both computer algorithm training and evaluation. Current approaches of visual inspection and manual markings do not scale well to big data. We present a new approach that depends on fully automated algorithm outcomes for segmentation documentation, requires no manual marking, and provides quantitative evaluation for computer algorithms. The documentation of new image segmentations and new algorithm outcomes are achieved by visual inspection. The burden of visual inspection on large datasets is minimized by (a) customized visualizations for rapid review and (b) reducing the number of cases to be reviewed through analysis of quantitative segmentation evaluation. This method has been applied to a dataset of 7,440 whole-lung CT images for 6 different segmentation algorithms designed to fully automatically facilitate the measurement of a number of very important quantitative image biomarkers. The results indicate that we could achieve 93% to 99% successful segmentation for these algorithms on this relatively large image database. The presented evaluation method may be scaled to much larger image databases.

Automated 3D closed surface segmentation: application to vertebral body segmentation in CT images.

Science.gov (United States)

Liu, Shuang; Xie, Yiting; Reeves, Anthony P

2016-05-01

A fully automated segmentation algorithm, progressive surface resolution (PSR), is presented in this paper to determine the closed surface of approximately convex blob-like structures that are common in biomedical imaging. The PSR algorithm was applied to the cortical surface segmentation of 460 vertebral bodies on 46 low-dose chest CT images, which can be potentially used for automated bone mineral density measurement and compression fracture detection. The target surface is realized by a closed triangular mesh, which thereby guarantees the enclosure. The surface vertices of the triangular mesh representation are constrained along radial trajectories that are uniformly distributed in 3D angle space. The segmentation is accomplished by determining for each radial trajectory the location of its intersection with the target surface. The surface is first initialized based on an input high confidence boundary image and then resolved progressively based on a dynamic attraction map in an order of decreasing degree of evidence regarding the target surface location. For the visual evaluation, the algorithm achieved acceptable segmentation for 99.35 % vertebral bodies. Quantitative evaluation was performed on 46 vertebral bodies and achieved overall mean Dice coefficient of 0.939 (with max [Formula: see text] 0.957, min [Formula: see text] 0.906 and standard deviation [Formula: see text] 0.011) using manual annotations as the ground truth. Both visual and quantitative evaluations demonstrate encouraging performance of the PSR algorithm. This novel surface resolution strategy provides uniform angular resolution for the segmented surface with computation complexity and runtime that are linearly constrained by the total number of vertices of the triangular mesh representation.

Market segmentation by motivation: The case of Switzerland

OpenAIRE

Bieger, Thomas; Laesser, Christian

2002-01-01

This contribution is about the segmentation of mature travel markets, as exemplified by Switzerland. Based on an extensive and representative travel survey covering 2,000 households and more than 11,000 trips, a situational, motivation-based travel market segmentation is proposed. The clustering of motivations proves to be a valuable means to segment markets. The results reveal a diminishing role of socio-demographic segment descriptors. It is more the (anticipated) travel profile and the att...

Algorithms for Cytoplasm Segmentation of Fluorescence Labelled Cells

OpenAIRE

Carolina Wählby; Joakim Lindblad; Mikael Vondrus; Ewert Bengtsson; Lennart Björkesten

2002-01-01

Automatic cell segmentation has various applications in cytometry, and while the nucleus is often very distinct and easy to identify, the cytoplasm provides a lot more challenge. A new combination of image analysis algorithms for segmentation of cells imaged by fluorescence microscopy is presented. The algorithm consists of an image pre?processing step, a general segmentation and merging step followed by a segmentation quality measurement. The quality measurement consists of a statistical ana...

Interactive segmentation: a scalable superpixel-based method

Science.gov (United States)

Mathieu, Bérengère; Crouzil, Alain; Puel, Jean-Baptiste

2017-11-01

This paper addresses the problem of interactive multiclass segmentation of images. We propose a fast and efficient new interactive segmentation method called superpixel α fusion (SαF). From a few strokes drawn by a user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SαF uses superpixel oversegmentation and support vector machine classification. We compare SαF with competing algorithms by evaluating its performances on reference benchmarks. We also suggest four new datasets to evaluate the scalability of interactive segmentation methods, using images from some thousand to several million pixels. We conclude with two applications of SαF.

Retrieving clinically relevant diabetic retinopathy images using a multi-class multiple-instance framework

Science.gov (United States)

Chandakkar, Parag S.; Venkatesan, Ragav; Li, Baoxin

2013-02-01

Diabetic retinopathy (DR) is a vision-threatening complication from diabetes mellitus, a medical condition that is rising globally. Unfortunately, many patients are unaware of this complication because of absence of symptoms. Regular screening of DR is necessary to detect the condition for timely treatment. Content-based image retrieval, using archived and diagnosed fundus (retinal) camera DR images can improve screening efficiency of DR. This content-based image retrieval study focuses on two DR clinical findings, microaneurysm and neovascularization, which are clinical signs of non-proliferative and proliferative diabetic retinopathy. The authors propose a multi-class multiple-instance image retrieval framework which deploys a modified color correlogram and statistics of steerable Gaussian Filter responses, for retrieving clinically relevant images from a database of DR fundus image database.

An anomaly detection and isolation scheme with instance-based learning and sequential analysis

International Nuclear Information System (INIS)

Yoo, T. S.; Garcia, H. E.

2006-01-01

This paper presents an online anomaly detection and isolation (FDI) technique using an instance-based learning method combined with a sequential change detection and isolation algorithm. The proposed method uses kernel density estimation techniques to build statistical models of the given empirical data (null hypothesis). The null hypothesis is associated with the set of alternative hypotheses modeling the abnormalities of the systems. A decision procedure involves a sequential change detection and isolation algorithm. Notably, the proposed method enjoys asymptotic optimality as the applied change detection and isolation algorithm is optimal in minimizing the worst mean detection/isolation delay for a given mean time before a false alarm or a false isolation. Applicability of this methodology is illustrated with redundant sensor data set and its performance. (authors)

Parallel fuzzy connected image segmentation on GPU

OpenAIRE

Zhuge, Ying; Cao, Yong; Udupa, Jayaram K.; Miller, Robert W.

2011-01-01

Purpose: Image segmentation techniques using fuzzy connectedness (FC) principles have shown their effectiveness in segmenting a variety of objects in several large applications. However, one challenge in these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays, commodity graphics hardware provides a highly parallel computing environment. In this paper, the authors present a parallel fuzzy connected image segmentation algorithm impleme...

IFRS 8 Operating Segments - A Closer Look

OpenAIRE

Muthupandian, K S

2008-01-01

The International Accounting Standards Board issued the International Financial Reporting Standard 8 Operating Segments. Segment information is one of the most vital aspects of financial reporting for investors and other users. The IFRS 8 requires an entity to adopt the ‘management approach’ to reporting on the financial performance of its operating segments. This article presents a closer look of the standard (objective, scope, and disclosures).

An interactive medical image segmentation framework using iterative refinement.

Science.gov (United States)

Kalshetti, Pratik; Bundele, Manas; Rahangdale, Parag; Jangra, Dinesh; Chattopadhyay, Chiranjoy; Harit, Gaurav; Elhence, Abhay

2017-04-01

Segmentation is often performed on medical images for identifying diseases in clinical evaluation. Hence it has become one of the major research areas. Conventional image segmentation techniques are unable to provide satisfactory segmentation results for medical images as they contain irregularities. They need to be pre-processed before segmentation. In order to obtain the most suitable method for medical image segmentation, we propose MIST (Medical Image Segmentation Tool), a two stage algorithm. The first stage automatically generates a binary marker image of the region of interest using mathematical morphology. This marker serves as the mask image for the second stage which uses GrabCut to yield an efficient segmented result. The obtained result can be further refined by user interaction, which can be done using the proposed Graphical User Interface (GUI). Experimental results show that the proposed method is accurate and provides satisfactory segmentation results with minimum user interaction on medical as well as natural images. Copyright © 2017 Elsevier Ltd. All rights reserved.

Automatic lung segmentation in the presence of alveolar collapse

Directory of Open Access Journals (Sweden)

Noshadi Areg

2017-09-01

Full Text Available Lung ventilation and perfusion analyses using chest imaging methods require a correct segmentation of the lung to offer anatomical landmarks for the physiological data. An automatic segmentation approach simplifies and accelerates the analysis. However, the segmentation of the lungs has shown to be difficult if collapsed areas are present that tend to share similar gray values with surrounding non-pulmonary tissue. Our goal was to develop an automatic segmentation algorithm that is able to approximate dorsal lung boundaries even if alveolar collapse is present in the dependent lung areas adjacent to the pleura. Computed tomography data acquired in five supine pigs with injured lungs were used for this purpose. First, healthy lung tissue was segmented using a standard 3D region growing algorithm. Further, the bones in the chest wall surrounding the lungs were segmented to find the contact points of ribs and pleura. Artificial boundaries of the dorsal lung were set by spline interpolation through these contact points. Segmentation masks of the entire lung including the collapsed regions were created by combining the splines with the segmentation masks of the healthy lung tissue through multiple morphological operations. The automatically segmented images were then evaluated by comparing them to manual segmentations and determining the Dice similarity coefficients (DSC as a similarity measure. The developed method was able to accurately segment the lungs including the collapsed regions (DSCs over 0.96.

OASIS is Automated Statistical Inference for Segmentation, with applications to multiple sclerosis lesion segmentation in MRI.

Science.gov (United States)

Sweeney, Elizabeth M; Shinohara, Russell T; Shiee, Navid; Mateen, Farrah J; Chudgar, Avni A; Cuzzocreo, Jennifer L; Calabresi, Peter A; Pham, Dzung L; Reich, Daniel S; Crainiceanu, Ciprian M

2013-01-01

Magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients and is essential for diagnosing the disease and monitoring its progression. In practice, lesion load is often quantified by either manual or semi-automated segmentation of MRI, which is time-consuming, costly, and associated with large inter- and intra-observer variability. We propose OASIS is Automated Statistical Inference for Segmentation (OASIS), an automated statistical method for segmenting MS lesions in MRI studies. We use logistic regression models incorporating multiple MRI modalities to estimate voxel-level probabilities of lesion presence. Intensity-normalized T1-weighted, T2-weighted, fluid-attenuated inversion recovery and proton density volumes from 131 MRI studies (98 MS subjects, 33 healthy subjects) with manual lesion segmentations were used to train and validate our model. Within this set, OASIS detected lesions with a partial area under the receiver operating characteristic curve for clinically relevant false positive rates of 1% and below of 0.59% (95% CI; [0.50%, 0.67%]) at the voxel level. An experienced MS neuroradiologist compared these segmentations to those produced by LesionTOADS, an image segmentation software that provides segmentation of both lesions and normal brain structures. For lesions, OASIS out-performed LesionTOADS in 74% (95% CI: [65%, 82%]) of cases for the 98 MS subjects. To further validate the method, we applied OASIS to 169 MRI studies acquired at a separate center. The neuroradiologist again compared the OASIS segmentations to those from LesionTOADS. For lesions, OASIS ranked higher than LesionTOADS in 77% (95% CI: [71%, 83%]) of cases. For a randomly selected subset of 50 of these studies, one additional radiologist and one neurologist also scored the images. Within this set, the neuroradiologist ranked OASIS higher than LesionTOADS in 76% (95% CI: [64%, 88%]) of cases, the neurologist 66% (95% CI: [52%, 78

Instance Analysis for the Error of Three-pivot Pressure Transducer Static Balancing Method for Hydraulic Turbine Runner

Science.gov (United States)

Weng, Hanli; Li, Youping

2017-04-01

The working principle, process device and test procedure of runner static balancing test method by weighting with three-pivot pressure transducers are introduced in this paper. Based on an actual instance of a V hydraulic turbine runner, the error and sensitivity of the three-pivot pressure transducer static balancing method are analysed. Suggestions about improving the accuracy and the application of the method are also proposed.

Brain MR image segmentation using NAMS in pseudo-color.

Science.gov (United States)

Li, Hua; Chen, Chuanbo; Fang, Shaohong; Zhao, Shengrong

2017-12-01

Image segmentation plays a crucial role in various biomedical applications. In general, the segmentation of brain Magnetic Resonance (MR) images is mainly used to represent the image with several homogeneous regions instead of pixels for surgical analyzing and planning. This paper proposes a new approach for segmenting MR brain images by using pseudo-color based segmentation with Non-symmetry and Anti-packing Model with Squares (NAMS). First of all, the NAMS model is presented. The model can represent the image with sub-patterns to keep the image content and largely reduce the data redundancy. Second, the key idea is proposed that convert the original gray-scale brain MR image into a pseudo-colored image and then segment the pseudo-colored image with NAMS model. The pseudo-colored image can enhance the color contrast in different tissues in brain MR images, which can improve the precision of segmentation as well as directly visual perceptional distinction. Experimental results indicate that compared with other brain MR image segmentation methods, the proposed NAMS based pseudo-color segmentation method performs more excellent in not only segmenting precisely but also saving storage.

Improving image segmentation by learning region affinities

Energy Technology Data Exchange (ETDEWEB)

Prasad, Lakshman [Los Alamos National Laboratory; Yang, Xingwei [TEMPLE UNIV.; Latecki, Longin J [TEMPLE UNIV.

2010-11-03

We utilize the context information of other regions in hierarchical image segmentation to learn new regions affinities. It is well known that a single choice of quantization of an image space is highly unlikely to be a common optimal quantization level for all categories. Each level of quantization has its own benefits. Therefore, we utilize the hierarchical information among different quantizations as well as spatial proximity of their regions. The proposed affinity learning takes into account higher order relations among image regions, both local and long range relations, making it robust to instabilities and errors of the original, pairwise region affinities. Once the learnt affinities are obtained, we use a standard image segmentation algorithm to get the final segmentation. Moreover, the learnt affinities can be naturally unutilized in interactive segmentation. Experimental results on Berkeley Segmentation Dataset and MSRC Object Recognition Dataset are comparable and in some aspects better than the state-of-art methods.

Aging and the segmentation of narrative film.

Science.gov (United States)

Kurby, Christopher A; Asiala, Lillian K E; Mills, Steven R

2014-01-01

The perception of event structure in continuous activity is important for everyday comprehension. Although the segmentation of experience into events is a normal concomitant of perceptual processing, previous research has shown age differences in the ability to perceive structure in naturalistic activity, such as a movie of someone washing a car. However, past research has also shown that older adults have a preserved ability to comprehend events in narrative text, which suggests that narrative may improve the event processing of older adults. This study tested whether there are age differences in event segmentation at the intersection of continuous activity and narrative: narrative film. Younger and older adults watched and segmented a narrative film, The Red Balloon, into coarse and fine events. Changes in situational features, such as changes in characters, goals, and objects predicted segmentation. Analyses revealed little age-difference in segmentation behavior. This suggests the possibility that narrative structure supports event understanding for older adults.

A Hybrid Technique for Medical Image Segmentation

Directory of Open Access Journals (Sweden)

Alamgir Nyma

2012-01-01

Full Text Available Medical image segmentation is an essential and challenging aspect in computer-aided diagnosis and also in pattern recognition research. This paper proposes a hybrid method for magnetic resonance (MR image segmentation. We first remove impulsive noise inherent in MR images by utilizing a vector median filter. Subsequently, Otsu thresholding is used as an initial coarse segmentation method that finds the homogeneous regions of the input image. Finally, an enhanced suppressed fuzzy c-means is used to partition brain MR images into multiple segments, which employs an optimal suppression factor for the perfect clustering in the given data set. To evaluate the robustness of the proposed approach in noisy environment, we add different types of noise and different amount of noise to T1-weighted brain MR images. Experimental results show that the proposed algorithm outperforms other FCM based algorithms in terms of segmentation accuracy for both noise-free and noise-inserted MR images.

Storing tooth segments for optimal esthetics

NARCIS (Netherlands)

Tuzuner, T.; Turgut, S.; Özen, B.; Kılınç, H.; Bagis, B.

2016-01-01

Objective: A fractured whole crown segment can be reattached to its remnant; crowns from extracted teeth may be used as pontics in splinting techniques. We aimed to evaluate the effect of different storage solutions on tooth segment optical properties after different durations. Study design: Sixty

Communication with market segments - travel agencies' perspective

OpenAIRE

Lorena Bašan; Jasmina Dlačić; Željko Trezner

2013-01-01

Purpose – The purpose of this paper is to research the travel agencies’ communication with market segments. Communication with market segments takes into account marketing communication means as well as the implementation of different business orientations. Design – Special emphasis is placed on the use of different marketing communication means and their efficiency. Research also explores business orientation adaptation when approaching different market segments. Methodology – In explo...

Speaker Segmentation and Clustering Using Gender Information

Science.gov (United States)

2006-02-01

used in the first stages of segmentation forder information in the clustering of the opposite-gender speaker diarization of news broadcasts. files, the...AFRL-HE-WP-TP-2006-0026 AIR FORCE RESEARCH LABORATORY Speaker Segmentation and Clustering Using Gender Information Brian M. Ore General Dynamics...COVERED (From - To) February 2006 ProceedinLgs 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Speaker Segmentation and Clustering Using Gender Information 5b

Landmark-based deep multi-instance learning for brain disease diagnosis.

Science.gov (United States)

Liu, Mingxia; Zhang, Jun; Adeli, Ehsan; Shen, Dinggang

2018-01-01

In conventional Magnetic Resonance (MR) image based methods, two stages are often involved to capture brain structural information for disease diagnosis, i.e., 1) manually partitioning each MR image into a number of regions-of-interest (ROIs), and 2) extracting pre-defined features from each ROI for diagnosis with a certain classifier. However, these pre-defined features often limit the performance of the diagnosis, due to challenges in 1) defining the ROIs and 2) extracting effective disease-related features. In this paper, we propose a landmark-based deep multi-instance learning (LDMIL) framework for brain disease diagnosis. Specifically, we first adopt a data-driven learning approach to discover disease-related anatomical landmarks in the brain MR images, along with their nearby image patches. Then, our LDMIL framework learns an end-to-end MR image classifier for capturing both the local structural information conveyed by image patches located by landmarks and the global structural information derived from all detected landmarks. We have evaluated our proposed framework on 1526 subjects from three public datasets (i.e., ADNI-1, ADNI-2, and MIRIAD), and the experimental results show that our framework can achieve superior performance over state-of-the-art approaches. Copyright © 2017 Elsevier B.V. All rights reserved.

Montage Version 3.0

Science.gov (United States)

Jacob, Joseph; Katz, Daniel; Prince, Thomas; Berriman, Graham; Good, John; Laity, Anastasia

2006-01-01

The final version (3.0) of the Montage software has been released. To recapitulate from previous NASA Tech Briefs articles about Montage: This software generates custom, science-grade mosaics of astronomical images on demand from input files that comply with the Flexible Image Transport System (FITS) standard and contain image data registered on projections that comply with the World Coordinate System (WCS) standards. This software can be executed on single-processor computers, multi-processor computers, and such networks of geographically dispersed computers as the National Science Foundation s TeraGrid or NASA s Information Power Grid. The primary advantage of running Montage in a grid environment is that computations can be done on a remote supercomputer for efficiency. Multiple computers at different sites can be used for different parts of a computation a significant advantage in cases of computations for large mosaics that demand more processor time than is available at any one site. Version 3.0 incorporates several improvements over prior versions. The most significant improvement is that this version is accessible to scientists located anywhere, through operational Web services that provide access to data from several large astronomical surveys and construct mosaics on either local workstations or remote computational grids as needed.

Segmentation and Quantification for Angle-Closure Glaucoma Assessment in Anterior Segment OCT.

Science.gov (United States)

Fu, Huazhu; Xu, Yanwu; Lin, Stephen; Zhang, Xiaoqin; Wong, Damon Wing Kee; Liu, Jiang; Frangi, Alejandro F; Baskaran, Mani; Aung, Tin

2017-09-01

Angle-closure glaucoma is a major cause of irreversible visual impairment and can be identified by measuring the anterior chamber angle (ACA) of the eye. The ACA can be viewed clearly through anterior segment optical coherence tomography (AS-OCT), but the imaging characteristics and the shapes and locations of major ocular structures can vary significantly among different AS-OCT modalities, thus complicating image analysis. To address this problem, we propose a data-driven approach for automatic AS-OCT structure segmentation, measurement, and screening. Our technique first estimates initial markers in the eye through label transfer from a hand-labeled exemplar data set, whose images are collected over different patients and AS-OCT modalities. These initial markers are then refined by using a graph-based smoothing method that is guided by AS-OCT structural information. These markers facilitate segmentation of major clinical structures, which are used to recover standard clinical parameters. These parameters can be used not only to support clinicians in making anatomical assessments, but also to serve as features for detecting anterior angle closure in automatic glaucoma screening algorithms. Experiments on Visante AS-OCT and Cirrus high-definition-OCT data sets demonstrate the effectiveness of our approach.

New developments in segment ancillary logic for FASTBUS

International Nuclear Information System (INIS)

Walz, H.V.; Bertolucci, B.

1983-01-01

Segment Ancillary Logic hardware for FASTBUS systems provides logical functions required in common by all devices attached to a segment. It controls the execution of arbitration cycles, and geographical address cycles, and generates the system handshake responses for broadcast operations. The mandatory requirements for Segment Ancillary Logic in the FASTBUS specifications are reviewed. A detailed implementation based on ECL logic is described, and the hardware to be used on an ECL cable segment for an experimental FASTBUS system at SLAC is shown

(A new application in segment reporting: IFRS 8)

OpenAIRE

Arsoy, Aylin Poroy

2008-01-01

IFRS 8 Operating Segments issued by the International Accounting Standards Board (IASB) on December 30th, 2006, changes the requirements of segment reporting. IAS 14 will cease to be effective when IFRS 8 will become effective from the beginning of 2009. After then, companies will be required to follow IFRS 8 for their segment reporting purposes. The main difference between IFRS 8 and IAS 14 is the approach that is adopted while determining the reportable segments. Also, it should be mentione...

Video segmentation using keywords

Science.gov (United States)

Ton-That, Vinh; Vong, Chi-Tai; Nguyen-Dao, Xuan-Truong; Tran, Minh-Triet

2018-04-01

At DAVIS-2016 Challenge, many state-of-art video segmentation methods achieve potential results, but they still much depend on annotated frames to distinguish between background and foreground. It takes a lot of time and efforts to create these frames exactly. In this paper, we introduce a method to segment objects from video based on keywords given by user. First, we use a real-time object detection system - YOLOv2 to identify regions containing objects that have labels match with the given keywords in the first frame. Then, for each region identified from the previous step, we use Pyramid Scene Parsing Network to assign each pixel as foreground or background. These frames can be used as input frames for Object Flow algorithm to perform segmentation on entire video. We conduct experiments on a subset of DAVIS-2016 dataset in half the size of its original size, which shows that our method can handle many popular classes in PASCAL VOC 2012 dataset with acceptable accuracy, about 75.03%. We suggest widely testing by combining other methods to improve this result in the future.

Fetomaternal hemorrhage during external cephalic version.

Science.gov (United States)

Boucher, Marc; Marquette, Gerald P; Varin, Jocelyne; Champagne, Josette; Bujold, Emmanuel

2008-07-01

To estimate the frequency and volume of fetomaternal hemorrhage during external cephalic version for term breech singleton fetuses and to identify risk factors involved with this complication. A prospective observational study was performed including all patients undergoing a trial of external cephalic version for a breech presentation of at least 36 weeks of gestation between 1987 and 2001 in our center. A search for fetal erythrocytes using the standard Kleihauer-Betke test was obtained before and after each external cephalic version. The frequency and volume of fetomaternal hemorrhage were calculated. Putative risk factors for fetomaternal hemorrhage were evaluated by chi(2) test and Mann-Whitney U test. A Kleihauer-Betke test result was available before and after 1,311 trials of external cephalic version. The Kleihauer-Betke test was positive in 67 (5.1%) before the procedure. Of the 1,244 women with a negative Kleihauer-Betke test before external cephalic version, 30 (2.4%) had a positive Kleihauer-Betke test after the procedure. Ten (0.8%) had an estimated fetomaternal hemorrhage greater than 1 mL, and one (0.08%) had an estimated fetomaternal hemorrhage greater than 30 mL. The risk of fetomaternal hemorrhage was not influenced by parity, gestational age, body mass index, number of attempts at version, placental location, or amniotic fluid index. The risk of detectable fetomaternal hemorrhage during external cephalic version was 2.4%, with fetomaternal hemorrhage more than 30 mL in less than 0.1% of cases. These data suggest that the performance of a Kleihauer-Betke test is unwarranted in uneventful external cephalic version and that in Rh-negative women, no further Rh immune globulin is necessary other than the routine 300-microgram dose at 28 weeks of gestation and postpartum. II.

Segmenting patients and physicians using preferences from discrete choice experiments.

Science.gov (United States)

Deal, Ken

2014-01-01

People often form groups or segments that have similar interests and needs and seek similar benefits from health providers. Health organizations need to understand whether the same health treatments, prevention programs, services, and products should be applied to everyone in the relevant population or whether different treatments need to be provided to each of several segments that are relatively homogeneous internally but heterogeneous among segments. Our objective was to explain the purposes, benefits, and methods of segmentation for health organizations, and to illustrate the process of segmenting health populations based on preference coefficients from a discrete choice conjoint experiment (DCE) using an example study of prevention of cyberbullying among university students. We followed a two-level procedure for investigating segmentation incorporating several methods for forming segments in Level 1 using DCE preference coefficients and testing their quality, reproducibility, and usability by health decision makers. Covariates (demographic, behavioral, lifestyle, and health state variables) were included in Level 2 to further evaluate quality and to support the scoring of large databases and developing typing tools for assigning those in the relevant population, but not in the sample, to the segments. Several segmentation solution candidates were found during the Level 1 analysis, and the relationship of the preference coefficients to the segments was investigated using predictive methods. Those segmentations were tested for their quality and reproducibility and three were found to be very close in quality. While one seemed better than others in the Level 1 analysis, another was very similar in quality and proved ultimately better in predicting segment membership using covariates in Level 2. The two segments in the final solution were profiled for attributes that would support the development and acceptance of cyberbullying prevention programs among university

Short segment search method for phylogenetic analysis using nested sliding windows

Science.gov (United States)

Iskandar, A. A.; Bustamam, A.; Trimarsanto, H.

2017-10-01

To analyze phylogenetics in Bioinformatics, coding DNA sequences (CDS) segment is needed for maximal accuracy. However, analysis by CDS cost a lot of time and money, so a short representative segment by CDS, which is envelope protein segment or non-structural 3 (NS3) segment is necessary. After sliding window is implemented, a better short segment than envelope protein segment and NS3 is found. This paper will discuss a mathematical method to analyze sequences using nested sliding window to find a short segment which is representative for the whole genome. The result shows that our method can find a short segment which more representative about 6.57% in topological view to CDS segment than an Envelope segment or NS3 segment.

Simultaneous tomographic reconstruction and segmentation with class priors

DEFF Research Database (Denmark)

Romanov, Mikhail; Dahl, Anders Bjorholm; Dong, Yiqiu

2015-01-01

are combined to produce a reconstruction that is identical to the segmentation. We consider instead a hybrid approach that simultaneously produces both a reconstructed image and segmentation. We incorporate priors about the desired classes of the segmentation through a Hidden Markov Measure Field Model, and we...

Progress Towards AIRS Science Team Version-7 at SRT

Science.gov (United States)

Susskind, Joel; Blaisdell, John; Iredell, Lena; Kouvaris, Louis

2016-01-01

The AIRS Science Team Version-6 retrieval algorithm is currently producing level-3 Climate Data Records (CDRs) from AIRS that have been proven useful to scientists in understanding climate processes. CDRs are gridded level-3 products which include all cases passing AIRS Climate QC. SRT has made significant further improvements to AIRS Version-6. At the last Science Team Meeting, we described results using SRT AIRS Version-6.22. SRT Version-6.22 is now an official build at JPL called 6.2.4. Version-6.22 results are significantly improved compared to Version-6, especially with regard to water vapor and ozone profiles. We have adapted AIRS Version-6.22 to run with CrIS/ATMS, at the Sounder SIPS which processed CrIS/ATMS data for August 2014. JPL AIRS Version-6.22 uses the Version-6 AIRS tuning coefficients. AIRS Version-6.22 has at least two limitations which must be improved before finalization of Version-7: Version-6.22 total O3 has spurious high values in the presence of Saharan dust over the ocean; and Version-6.22 retrieved upper stratospheric temperatures are very poor in polar winter. SRT Version-6.28 addresses the first concern. John Blaisdell ran the analog of AIRS Version-6.28 in his own sandbox at JPL for the 14th and 15th of every month in 2014 and all of July and October for 2014. AIRS Version-6.28a is hot off the presses and addresses the second concern.

SVM Pixel Classification on Colour Image Segmentation

Science.gov (United States)

Barui, Subhrajit; Latha, S.; Samiappan, Dhanalakshmi; Muthu, P.

2018-04-01

The aim of image segmentation is to simplify the representation of an image with the help of cluster pixels into something meaningful to analyze. Segmentation is typically used to locate boundaries and curves in an image, precisely to label every pixel in an image to give each pixel an independent identity. SVM pixel classification on colour image segmentation is the topic highlighted in this paper. It holds useful application in the field of concept based image retrieval, machine vision, medical imaging and object detection. The process is accomplished step by step. At first we need to recognize the type of colour and the texture used as an input to the SVM classifier. These inputs are extracted via local spatial similarity measure model and Steerable filter also known as Gabon Filter. It is then trained by using FCM (Fuzzy C-Means). Both the pixel level information of the image and the ability of the SVM Classifier undergoes some sophisticated algorithm to form the final image. The method has a well developed segmented image and efficiency with respect to increased quality and faster processing of the segmented image compared with the other segmentation methods proposed earlier. One of the latest application result is the Light L16 camera.

Classifier Directed Data Hybridization for Geographic Sample Supervised Segment Generation

Directory of Open Access Journals (Sweden)

Christoff Fourie

2014-11-01

Full Text Available Quality segment generation is a well-known challenge and research objective within Geographic Object-based Image Analysis (GEOBIA. Although methodological avenues within GEOBIA are diverse, segmentation commonly plays a central role in most approaches, influencing and being influenced by surrounding processes. A general approach using supervised quality measures, specifically user provided reference segments, suggest casting the parameters of a given segmentation algorithm as a multidimensional search problem. In such a sample supervised segment generation approach, spatial metrics observing the user provided reference segments may drive the search process. The search is commonly performed by metaheuristics. A novel sample supervised segment generation approach is presented in this work, where the spectral content of provided reference segments is queried. A one-class classification process using spectral information from inside the provided reference segments is used to generate a probability image, which in turn is employed to direct a hybridization of the original input imagery. Segmentation is performed on such a hybrid image. These processes are adjustable, interdependent and form a part of the search problem. Results are presented detailing the performances of four method variants compared to the generic sample supervised segment generation approach, under various conditions in terms of resultant segment quality, required computing time and search process characteristics. Multiple metrics, metaheuristics and segmentation algorithms are tested with this approach. Using the spectral data contained within user provided reference segments to tailor the output generally improves the results in the investigated problem contexts, but at the expense of additional required computing time.

Methods for recognition and segmentation of active fault

International Nuclear Information System (INIS)

Hyun, Chang Hun; Noh, Myung Hyun; Lee, Kieh Hwa; Chang, Tae Woo; Kyung, Jai Bok; Kim, Ki Young

2000-03-01

In order to identify and segment the active faults, the literatures of structural geology, paleoseismology, and geophysical explorations were investigated. The existing structural geological criteria for segmenting active faults were examined. These are mostly based on normal fault systems, thus, the additional criteria are demanded for application to different types of fault systems. Definition of the seismogenic fault, characteristics of fault activity, criteria and study results of fault segmentation, relationship between segmented fault length and maximum displacement, and estimation of seismic risk of segmented faults were examined in paleoseismic study. The history of earthquake such as dynamic pattern of faults, return period, and magnitude of the maximum earthquake originated by fault activity can be revealed by the study. It is confirmed through various case studies that numerous geophysical explorations including electrical resistivity, land seismic, marine seismic, ground-penetrating radar, magnetic, and gravity surveys have been efficiently applied to the recognition and segmentation of active faults

Intercomparison of ILAS-II version 1.4 and version 2 target parameters with MIPAS-Envisat measurements

Directory of Open Access Journals (Sweden)

A. Griesfeller

2008-02-01

Full Text Available This paper assesses the mean differences between the two ILAS-II data versions (1.4 and 2 by comparing them with MIPAS measurements made between May and October 2003. For comparison with ILAS-II results, MIPAS data processed at the Institut für Meteorologie und Klimaforschung, Karlsruhe, Germany (IMK in cooperation with the Instituto de Astrofísica de Andalucía (IAA in Granada, Spain, were used. The coincidence criteria of ±300 km in space and ±12 h in time for H₂O, N₂O, and CH₄ and the coincidence criteria of ±300 km in space and ±6 h in time for ClONO₂, O₃, and HNO₃ were used. The ILAS-II data were separated into sunrise (= Northern Hemisphere and sunset (= Southern Hemisphere. For the sunrise data, a clear improvement from version 1.4 to version 2 was observed for H₂O, CH₄, ClONO₂, and O₃. In particular, the ILAS-II version 1.4 mixing ratios of H₂O and CH₄ were unrealistically small, and those of ClONO₂ above altitudes of 30 km unrealistically large. For N₂O and HNO₃, there were no large differences between the two versions. Contrary to the Northern Hemisphere, where some exceptional profiles deviated significantly from known climatology, no such outlying profiles were found in the Southern Hemisphere for both versions. Generally, the ILAS-II version 2 data were in better agreement with the MIPAS data than the version 1.4, and are recommended for quantitative analysis in the stratosphere. For H₂O data in the Southern Hemisphere, further data quality evaluation is necessary.

Limb-segment selection in drawing behaviour

NARCIS (Netherlands)

Meulenbroek, R G; Rosenbaum, D A; Thomassen, A.J.W.M.; Schomaker, L R

How do we select combinations of limb segments to carry out physical tasks? Three possible determinants of limb-segment selection are hypothesized here: (1) optimal amplitudes and frequencies of motion for the effectors; (2) preferred movement axes for the effectors; and (3) a tendency to continue

LIMB-SEGMENT SELECTION IN DRAWING BEHAVIOR

NARCIS (Netherlands)

MEULENBROEK, RGJ; ROSENBAUM, DA; THOMASSEN, AJWM; SCHOMAKER, LRB; Schomaker, Lambertus

How do we select combinations of limb segments to carry out physical tasks? Three possible determinants of limb-segment selection are hypothesized here: (1) optimal amplitudes and frequencies of motion for the effectors; (2) preferred movement axes for the effectors; and (3) a tendency to continue

Scale selection for supervised image segmentation

DEFF Research Database (Denmark)

Li, Yan; Tax, David M J; Loog, Marco

2012-01-01

schemes are usually unsupervised, as they do not take into account the actual segmentation problem at hand. In this paper, we consider the problem of selecting scales, which aims at an optimal discrimination between user-defined classes in the segmentation. We show the deficiency of the classical...

Multilevel segmentation of intracranial aneurysms in CT angiography images

Energy Technology Data Exchange (ETDEWEB)

Wang, Yan [Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California 94122 and University of Lyon, CREATIS, CNRS UMR 5220, INSERM U1206, UCB Lyon1, INSA Lyon, Lyon 69100 (France); Zhang, Yue, E-mail: y.zhang525@gmail.com [Veterans Affairs Medical Center, San Francisco, California 94121 and University of Lyon, CREATIS, CNRS UMR 5220, INSERM U1206, UCB Lyon1, INSA Lyon, Lyon 69100 (France); Navarro, Laurent [Ecole Nationale Superieure des Mines de Saint-Etienne, Saint-Etienne 42015 (France); Eker, Omer Faruk [CHU Montpellier, Neuroradiologie, Montpellier 34000 (France); Corredor Jerez, Ricardo A. [Ecole Polytechnique Federale de Lausanne, Lausanne 1015 (Switzerland); Chen, Yu; Zhu, Yuemin; Courbebaisse, Guy [University of Lyon, CREATIS, CNRS UMR 5220, INSERM U1206, UCB Lyon1, INSA Lyon, Lyon 69100 (France)

2016-04-15

Purpose: Segmentation of aneurysms plays an important role in interventional planning. Yet, the segmentation of both the lumen and the thrombus of an intracranial aneurysm in computed tomography angiography (CTA) remains a challenge. This paper proposes a multilevel segmentation methodology for efficiently segmenting intracranial aneurysms in CTA images. Methods: The proposed methodology first uses the lattice Boltzmann method (LBM) to extract the lumen part directly from the original image. Then, the LBM is applied again on an intermediate image whose lumen part is filled by the mean gray-level value outside the lumen, to yield an image region containing part of the aneurysm boundary. After that, an expanding disk is introduced to estimate the complete contour of the aneurysm. Finally, the contour detected is used as the initial contour of the level set with ellipse to refine the aneurysm. Results: The results obtained on 11 patients from different hospitals showed that the proposed segmentation was comparable with manual segmentation, and that quantitatively, the average segmentation matching factor (SMF) reached 86.99%, demonstrating good segmentation accuracy. Chan–Vese method, Sen’s model, and Luca’s model were used to compare the proposed method and their average SMF values were 39.98%, 40.76%, and 77.11%, respectively. Conclusions: The authors have presented a multilevel segmentation method based on the LBM and level set with ellipse for accurate segmentation of intracranial aneurysms. Compared to three existing methods, for all eleven patients, the proposed method can successfully segment the lumen with the highest SMF values for nine patients and second highest SMF values for the two. It also segments the entire aneurysm with the highest SMF values for ten patients and second highest SMF value for the one. This makes it potential for clinical assessment of the volume and aspect ratio of the intracranial aneurysms.

Mixed raster content segmentation, compression, transmission

CERN Document Server

Pavlidis, George

2017-01-01

This book presents the main concepts in handling digital images of mixed content, traditionally referenced as mixed raster content (MRC), in two main parts. The first includes introductory chapters covering the scientific and technical background aspects, whereas the second presents a set of research and development approaches to tackle key issues in MRC segmentation, compression and transmission. The book starts with a review of color theory and the mechanism of color vision in humans. In turn, the second chapter reviews data coding and compression methods so as to set the background and demonstrate the complexity involved in dealing with MRC. Chapter three addresses the segmentation of images through an extensive literature review, which highlights the various approaches used to tackle MRC segmentation. The second part of the book focuses on the segmentation of color images for optimized compression, including multi-layered decomposition and representation of MRC and the processes that can be employed to op...

Segmentation and packaging reactor vessels internals

International Nuclear Information System (INIS)

Boucau, Joseph

2014-01-01

Document available in abstract form only, full text follows: With more than 25 years of experience in the development of reactor vessel internals and reactor vessel segmentation and packaging technology, Westinghouse has accumulated significant know-how in the reactor dismantling market. The primary challenges of a segmentation and packaging project are to separate the highly activated materials from the less-activated materials and package them into appropriate containers for disposal. Since disposal cost is a key factor, it is important to plan and optimize waste segmentation and packaging. The choice of the optimum cutting technology is also important for a successful project implementation and depends on some specific constraints. Detailed 3-D modeling is the basis for tooling design and provides invaluable support in determining the optimum strategy for component cutting and disposal in waste containers, taking account of the radiological and packaging constraints. The usual method is to start at the end of the process, by evaluating handling of the containers, the waste disposal requirements, what type and size of containers are available for the different disposal options, and working backwards to select a cutting method and finally the cut geometry required. The 3-D models can include intelligent data such as weight, center of gravity, curie content, etc, for each segmented piece, which is very useful when comparing various cutting, handling and packaging options. The detailed 3-D analyses and thorough characterization assessment can draw the attention to material potentially subject to clearance, either directly or after certain period of decay, to allow recycling and further disposal cost reduction. Westinghouse has developed a variety of special cutting and handling tools, support fixtures, service bridges, water filtration systems, video-monitoring systems and customized rigging, all of which are required for a successful reactor vessel internals

Causal judgment from contingency information: a systematic test of the pCI rule.

Science.gov (United States)

White, Peter A

2004-04-01

Contingency information is information about the occurrence or nonoccurrence of an effect when a possible cause is present or absent. Under the evidential evaluation model, instances of contingency information are transformed into evidence and causal judgment is based on the proportion of relevant instances evaluated as confirmatory for the candidate cause. In this article, two experiments are reported that were designed to test systematic manipulations of the proportion of confirming instances in relation to other variables: the proportion of instances on which the candidate cause is present, the proportion of instances in which the effect occurs when the cause is present, and the objective contingency. Results showed that both unweighted and weighted versions of the proportion-of-confirmatory-instances rule successfully predicted the main features of the results, with the weighted version proving more successful. Other models, including the power PC theory, failed to predict the results.

Clusterwise regression and market segmentation : developments and applications

NARCIS (Netherlands)

Wedel, M.

1990-01-01

The present work consists of two major parts. In the first part the literature on market segmentation is reviewed, in the second part a set of new methods for market segmentation are developed and applied.

Part 1 starts with a discussion of the segmentation concept, and proceeds

The Teaching Evaluation Process: Segmentation of Marketing Students.

Science.gov (United States)

Yau, Oliver H. M.; Kwan, Wayne

1993-01-01

A study applied the concept of market segmentation to student evaluation of college teaching, by assessing whether there exist several segments of students and how this relates to their evaluation of faculty. Subjects were 156 Australian undergraduate business administration students. Results suggest segments do exist, with different expectations…

Segment-segment interactions of poly(N-isopropylacrylamide) in aqueous methanol solutions by using small-angle scattering

International Nuclear Information System (INIS)

Shimizu, S.; Kurita, K.; Furusaka, M.

2002-01-01

Small-angle neutron and X-ray scattering from semidilute solutions of poly(N-isopropylacrylamide) in D 2 O, methanol and methanol-water mixtures has been measured in the poor solvent regime. The binary and the ternary cluster integrals of polymer segments were determined from the concentration dependence of the correlation length at several temperatures just below the lower critical solution temperature. Then, contributions of segment-segment interactions to the entropy and the enthalpy have been calculated from the temperature dependence of interaction parameters and it has been found that both values are positive in the D 2 O and the methanol-water systems at a small content of methanol, while both values are negative in the other system. (orig.)

Segmentation of medical images using explicit anatomical knowledge

Science.gov (United States)

Wilson, Laurie S.; Brown, Stephen; Brown, Matthew S.; Young, Jeanne; Li, Rongxin; Luo, Suhuai; Brandt, Lee

1999-07-01

Knowledge-based image segmentation is defined in terms of the separation of image analysis procedures and representation of knowledge. Such architecture is particularly suitable for medical image segmentation, because of the large amount of structured domain knowledge. A general methodology for the application of knowledge-based methods to medical image segmentation is described. This includes frames for knowledge representation, fuzzy logic for anatomical variations, and a strategy for determining the order of segmentation from the modal specification. This method has been applied to three separate problems, 3D thoracic CT, chest X-rays and CT angiography. The application of the same methodology to such a range of applications suggests a major role in medical imaging for segmentation methods incorporating representation of anatomical knowledge.

Fully convolutional network with cluster for semantic segmentation

Science.gov (United States)

Ma, Xiao; Chen, Zhongbi; Zhang, Jianlin

2018-04-01

At present, image semantic segmentation technology has been an active research topic for scientists in the field of computer vision and artificial intelligence. Especially, the extensive research of deep neural network in image recognition greatly promotes the development of semantic segmentation. This paper puts forward a method based on fully convolutional network, by cluster algorithm k-means. The cluster algorithm using the image's low-level features and initializing the cluster centers by the super-pixel segmentation is proposed to correct the set of points with low reliability, which are mistakenly classified in great probability, by the set of points with high reliability in each clustering regions. This method refines the segmentation of the target contour and improves the accuracy of the image segmentation.

Development of a Chinese version of the Oswestry Disability Index version 2.1.

Science.gov (United States)

Lue, Yi-Jing; Hsieh, Ching-Lin; Huang, Mao-Hsiung; Lin, Gau-Tyan; Lu, Yen-Mou

2008-10-01

Cross-cultural adaptation and cross-sectional psychometric testing in a convenience sample of patients with low back pain. To translate and culturally adapt the Oswestry Disability Index version 2.1 (ODI 2.1) into a Mandarin Chinese version and to assess its reliability and validity. The Chinese ODI 2.1 has not been developed and validated. The ODI 2.1 was translated and culturally adapted to the Chinese version. The validity of the translated Chinese version was assessed by examining the relationship between the ODI and other well-known measures. Test-retest reliability was examined in 52 of these patients, who completed a second questionnaire within 1 week. Internal consistency of the ODI 2.1 was excellent with Cronbach's alpha = 0.903. The intraclass correlation coefficient of test-retest reliability was 0.89. The minimal detectable change was 12.8. The convergent validity of the Chinese ODI is supported by its high correlation with other physical functional status measures (Roland Morris Disability Questionnaire and SF-36 physical functioning subscale, r = 0.76 and -0.75, respectively), and moderate correlation with other measures (Visual Analogue Scale, r = 0.68) and certain SF-36 subscales (role-physical, bodily pain, and social functioning, r range: -0.49 to -0.57). As expected, the ODI was least correlated with nonfunctional measures (SF-36 mental subscale and role-emotional subscale, r = -0.25 and -0.33, respectively). The results of this study indicate that the Chinese version of the ODI 2.1 is a reliable and valid instrument for the measurement of functional status in patients with low back pain.

User-guided segmentation for volumetric retinal optical coherence tomography images

Science.gov (United States)

Yin, Xin; Chao, Jennifer R.; Wang, Ruikang K.

2014-01-01

Abstract. Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method. PMID:25147962

Characterizing and reaching high-risk drinkers using audience segmentation.

Science.gov (United States)

Moss, Howard B; Kirby, Susan D; Donodeo, Fred

2009-08-01

Market or audience segmentation is widely used in social marketing efforts to help planners identify segments of a population to target for tailored program interventions. Market-based segments are typically defined by behaviors, attitudes, knowledge, opinions, or lifestyles. They are more helpful to health communication and marketing planning than epidemiologically defined groups because market-based segments are similar in respect to how they behave or might react to marketing and communication efforts. However, market segmentation has rarely been used in alcohol research. As an illustration of its utility, we employed commercial data that describes the sociodemographic characteristics of high-risk drinkers as an audience segment, including where they tend to live, lifestyles, interests, consumer behaviors, alcohol consumption behaviors, other health-related behaviors, and cultural values. Such information can be extremely valuable in targeting and planning public health campaigns, targeted mailings, prevention interventions, and research efforts. We described the results of a segmentation analysis of those individuals who self-reported to consume 5 or more drinks per drinking episode at least twice in the last 30 days. The study used the proprietary PRIZM (Claritas, Inc., San Diego, CA) audience segmentation database merged with the Center for Disease Control and Prevention's (CDC) Behavioral Risk Factor Surveillance System (BRFSS) database. The top 10 of the 66 PRIZM audience segments for this risky drinking pattern are described. For five of these segments we provided additional in-depth details about consumer behavior and the estimates of the market areas where these risky drinkers resided. The top 10 audience segments (PRIZM clusters) most likely to engage in high-risk drinking are described. The cluster with the highest concentration of binge-drinking behavior is referred to as the "Cyber Millenials." This cluster is characterized as "the nation's tech

Brain tumor segmentation based on a hybrid clustering technique

Directory of Open Access Journals (Sweden)

Eman Abdel-Maksoud

2015-03-01

This paper presents an efficient image segmentation approach using K-means clustering technique integrated with Fuzzy C-means algorithm. It is followed by thresholding and level set segmentation stages to provide an accurate brain tumor detection. The proposed technique can get benefits of the K-means clustering for image segmentation in the aspects of minimal computation time. In addition, it can get advantages of the Fuzzy C-means in the aspects of accuracy. The performance of the proposed image segmentation approach was evaluated by comparing it with some state of the art segmentation algorithms in case of accuracy, processing time, and performance. The accuracy was evaluated by comparing the results with the ground truth of each processed image. The experimental results clarify the effectiveness of our proposed approach to deal with a higher number of segmentation problems via improving the segmentation quality and accuracy in minimal execution time.

Congenital segmental dilatation of the colon

African Journals Online (AJOL)

Congenital segmental dilatation of the colon is a rare cause of intestinal obstruction in neonates. We report a case of congenital segmental dilatation of the colon and highlight the clinical, radiological, and histopathological features of this entity. Proper surgical treatment was initiated on the basis of preoperative radiological ...

Handwriting segmentation of unconstrained Oriya text

Indian Academy of Sciences (India)

Based on vertical projection profiles and structural features of Oriya characters, text lines are segmented into words. For character segmentation, at first, the isolated and connected (touching) characters in a word are detected. Using structural, topological and water reservoir concept-based features, characters of the word ...

47 CFR 101.1505 - Segmentation plan.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Segmentation plan. 101.1505 Section 101.1505 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) SAFETY AND SPECIAL RADIO SERVICES FIXED MICROWAVE SERVICES Service and Technical Rules for the 70/80/90 GHz Bands § 101.1505 Segmentation plan. (a) An entity...

Spinal segmental dysgenesis | Mahomed | SA Journal of Radiology

African Journals Online (AJOL)

Spinal segmental dysgenesis is a rare congenital spinal abnormality seen in neonates and infants, in which a segment of the spine and spinal cord fails to develop normally. The condition is segmental in nature, with vertebrae above and below the malformation. It is commonly associated with various abnormalities that ...

Variational mesh segmentation via quadric surface fitting

KAUST Repository

Yan, Dongming; Wang, Wen Ping; Liu, Yang; Yang, Zhouwang

2012-01-01

We present a new variational method for mesh segmentation by fitting quadric surfaces. Each component of the resulting segmentation is represented by a general quadric surface (including plane as a special case). A novel energy function is defined to evaluate the quality of the segmentation, which combines both L2 and L2 ,1 metrics from a triangle to a quadric surface. The Lloyd iteration is used to minimize the energy function, which repeatedly interleaves between mesh partition and quadric surface fitting. We also integrate feature-based and simplification-based techniques in the segmentation framework, which greatly improve the performance. The advantages of our algorithm are demonstrated by comparing with the state-of-the-art methods. © 2012 Elsevier Ltd. All rights reserved.

Variational mesh segmentation via quadric surface fitting

KAUST Repository

Yan, Dongming

2012-11-01

We present a new variational method for mesh segmentation by fitting quadric surfaces. Each component of the resulting segmentation is represented by a general quadric surface (including plane as a special case). A novel energy function is defined to evaluate the quality of the segmentation, which combines both L2 and L2 ,1 metrics from a triangle to a quadric surface. The Lloyd iteration is used to minimize the energy function, which repeatedly interleaves between mesh partition and quadric surface fitting. We also integrate feature-based and simplification-based techniques in the segmentation framework, which greatly improve the performance. The advantages of our algorithm are demonstrated by comparing with the state-of-the-art methods. © 2012 Elsevier Ltd. All rights reserved.

ELIPGRID-PC: Upgraded version

International Nuclear Information System (INIS)

Davidson, J.R.

1995-12-01

Evaluating the need for and the effectiveness of remedial cleanup at waste sites often includes finding average contaminant concentrations and identifying pockets of contamination called hot spots. The standard tool for calculating the probability of detecting pockets of contamination called hot spots has been the ELIPGRID code of singer and Wickman. The ELIPGRID-PC program has recently made this algorithm available for an IBM reg-sign personal computer (PC) or compatible. A new version of ELIPGRID-PC, incorporating Monte Carlo test results and simple graphics, is herein described. Various examples of how to use the program for both single and multiple hot spot cases are given. The code for an American National Standards Institute C version of the ELIPGRID algorithm is provided, and limitations and further work are noted. This version of ELIPGRID-PC reliably meets the goal of moving Singer's ELIPGRID algorithm to the PC

MRI Brain Tumor Segmentation Methods- A Review

OpenAIRE

Gursangeet, Kaur; Jyoti, Rani

2016-01-01

Medical image processing and its segmentation is an active and interesting area for researchers. It has reached at the tremendous place in diagnosing tumors after the discovery of CT and MRI. MRI is an useful tool to detect the brain tumor and segmentation is performed to carry out the useful portion from an image. The purpose of this paper is to provide an overview of different image segmentation methods like watershed algorithm, morphological operations, neutrosophic sets, thresholding, K-...

Current segmented gamma-ray scanner technology

International Nuclear Information System (INIS)

Bjork, C.W.

1987-01-01

A new generation of segmented gamma-ray scanners has been developed at Los Alamos for scrap and waste measurements at the Savannah River Plant and the Los Alamos Plutonium Facility. The new designs are highly automated and exhibit special features such as good segmentation and thorough shielding to improve performance

Reliability and validity of the Japanese version of the Resilience Scale and its short version.

Science.gov (United States)

Nishi, Daisuke; Uehara, Ritei; Kondo, Maki; Matsuoka, Yutaka

2010-11-17

The clinical relevance of resilience has received considerable attention in recent years. The aim of this study is to demonstrate the reliability and validity of the Japanese version of the Resilience Scale (RS) and short version of the RS (RS-14). The original English version of RS was translated to Japanese and the Japanese version was confirmed by back-translation. Participants were 430 nursing and university psychology students. The RS, Center for Epidemiologic Studies Depression Scale (CES-D), Rosenberg Self-Esteem Scale (RSES), Social Support Questionnaire (SSQ), Perceived Stress Scale (PSS), and Sheehan Disability Scale (SDS) were administered. Internal consistency, convergent validity and factor loadings were assessed at initial assessment. Test-retest reliability was assessed using data collected from 107 students at 3 months after baseline. Mean score on the RS was 111.19. Cronbach's alpha coefficients for the RS and RS-14 were 0.90 and 0.88, respectively. The test-retest correlation coefficients for the RS and RS-14 were 0.83 and 0.84, respectively. Both the RS and RS-14 were negatively correlated with the CES-D and SDS, and positively correlated with the RSES, SSQ and PSS (all p reliability, and relatively low concurrent validity. RS-14 was equivalent to the RS in internal consistency, test-retest reliability, and concurrent validity. Low scores on the RS, a positive correlation between the RS and perceived stress, and a relatively low correlation between the RS and depressive symptoms in this study suggest that validity of the Japanese version of the RS might be relatively low compared with the original English version.

Malignant pleural mesothelioma segmentation for photodynamic therapy planning.

Science.gov (United States)

Brahim, Wael; Mestiri, Makram; Betrouni, Nacim; Hamrouni, Kamel

2018-04-01

Medical imaging modalities such as computed tomography (CT) combined with computer-aided diagnostic processing have already become important part of clinical routine specially for pleural diseases. The segmentation of the thoracic cavity represents an extremely important task in medical imaging for different reasons. Multiple features can be extracted by analyzing the thoracic cavity space and these features are signs of pleural diseases including the malignant pleural mesothelioma (MPM) which is the main focus of our research. This paper presents a method that detects the MPM in the thoracic cavity and plans the photodynamic therapy in the preoperative phase. This is achieved by using a texture analysis of the MPM region combined with a thoracic cavity segmentation method. The algorithm to segment the thoracic cavity consists of multiple stages. First, the rib cage structure is segmented using various image processing techniques. We used the segmented rib cage to detect feature points which represent the thoracic cavity boundaries. Next, the proposed method segments the structures of the inner thoracic cage and fits 2D closed curves to the detected pleural cavity features in each slice. The missing bone structures are interpolated using a prior knowledge from manual segmentation performed by an expert. Next, the tumor region is segmented inside the thoracic cavity using a texture analysis approach. Finally, the contact surface between the tumor region and the thoracic cavity curves is reconstructed in order to plan the photodynamic therapy. Using the adjusted output of the thoracic cavity segmentation method and the MPM segmentation method, we evaluated the contact surface generated from these two steps by comparing it to the ground truth. For this evaluation, we used 10 CT scans with pathologically confirmed MPM at stages 1 and 2. We obtained a high similarity rate between the manually planned surface and our proposed method. The average value of Jaccard index

Loading effects of anterior cervical spine fusion on adjacent segments

Directory of Open Access Journals (Sweden)

Chien-Shiung Wang

2012-11-01

Full Text Available Adjacent segment degeneration typically follows anterior cervical spine fusion. However, the primary cause of adjacent segment degeneration remains unknown. Therefore, in order to identify the loading effects that cause adjacent segment degeneration, this study examined the loading effects to superior segments adjacent to fused bone following anterior cervical spine fusion. The C3–C6 cervical spine segments of 12 sheep were examined. Specimens were divided into the following groups: intact spine (group 1; and C5–C6 segments that were fused via cage-instrumented plate fixation (group 2. Specimens were cycled between 20° flexion and 15° extension with a displacement control of 1°/second. The tested parameters included the range of motion (ROM of each segment, torque and strain on both the body and inferior articular process at the superior segments (C3–C4 adjacent to the fused bone, and the position of the neutral axis of stress at under 20° flexion and 15° extension. Under flexion and Group 2, torque, ROM, and strain on both the bodies and facets of superior segments adjacent to the fused bone were higher than those of Group 1. Under extension and Group 2, ROM for the fused segment was less than that of Group 1; torque, ROM, and stress on both the bodies and facets of superior segments adjacent to the fused bone were higher than those of Group 1. These analytical results indicate that the muscles and ligaments require greater force to achieve cervical motion than the intact spine following anterior cervical spine fusion. In addition, ROM and stress on the bodies and facets of the joint segments adjacent to the fused bone were significantly increased. Under flexion, the neutral axis of the stress on the adjacent segment moved backward, and the stress on the bodies of the segments adjacent to the fused bone increased. These comparative results indicate that increased stress on the adjacent segments is caused by stress-shielding effects

Compound image segmentation of published biomedical figures.

Science.gov (United States)

Li, Pengyuan; Jiang, Xiangying; Kambhamettu, Chandra; Shatkay, Hagit

2018-04-01

Images convey essential information in biomedical publications. As such, there is a growing interest within the bio-curation and the bio-databases communities, to store images within publications as evidence for biomedical processes and for experimental results. However, many of the images in biomedical publications are compound images consisting of multiple panels, where each individual panel potentially conveys a different type of information. Segmenting such images into constituent panels is an essential first step toward utilizing images. In this article, we develop a new compound image segmentation system, FigSplit, which is based on Connected Component Analysis. To overcome shortcomings typically manifested by existing methods, we develop a quality assessment step for evaluating and modifying segmentations. Two methods are proposed to re-segment the images if the initial segmentation is inaccurate. Experimental results show the effectiveness of our method compared with other methods. The system is publicly available for use at: https://www.eecis.udel.edu/~compbio/FigSplit. The code is available upon request. shatkay@udel.edu. Supplementary data are available online at Bioinformatics.

Contour tracing for segmentation of mammographic masses

International Nuclear Information System (INIS)

Elter, Matthias; Held, Christian; Wittenberg, Thomas

2010-01-01

CADx systems have the potential to support radiologists in the difficult task of discriminating benign and malignant mammographic lesions. The segmentation of mammographic masses from the background tissue is an important module of CADx systems designed for the characterization of mass lesions. In this work, a novel approach to this task is presented. The segmentation is performed by automatically tracing the mass' contour in-between manually provided landmark points defined on the mass' margin. The performance of the proposed approach is compared to the performance of implementations of three state-of-the-art approaches based on region growing and dynamic programming. For an unbiased comparison of the different segmentation approaches, optimal parameters are selected for each approach by means of tenfold cross-validation and a genetic algorithm. Furthermore, segmentation performance is evaluated on a dataset of ROI and ground-truth pairs. The proposed method outperforms the three state-of-the-art methods. The benchmark dataset will be made available with publication of this paper and will be the first publicly available benchmark dataset for mass segmentation.