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Sample records for cell classification problem

  1. Classification problem in CBIR

    Directory of Open Access Journals (Sweden)

    Tatiana Jaworska

    2013-04-01

    Full Text Available At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR. Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results of fuzzy rule-based classification in our CBIR. Further-more, these results are used to construct a search engine taking into account data mining.

  2. Classification problem in CBIR

    OpenAIRE

    Tatiana Jaworska

    2013-01-01

    At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR). Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results ...

  3. The neuron classification problem

    OpenAIRE

    Bota, Mihail; Swanson, Larry W.

    2007-01-01

    A systematic account of neuron cell types is a basic prerequisite for determining the vertebrate nervous system global wiring diagram. With comprehensive lineage and phylogenetic information unavailable, a general ontology based on structure-function taxonomy is proposed and implemented in a knowledge management system, and a prototype analysis of select regions (including retina, cerebellum, and hypothalamus) presented. The supporting Brain Architecture Knowledge Management System (BAMS) Neu...

  4. Ensemble methods for noise in classification problems

    OpenAIRE

    Verbaeten, Sofie; Van Assche, Anneleen

    2003-01-01

    Ensemble methods combine a set of classifiers to construct a new classifier that is (often) more accurate than any of its component classifiers. In this paper, we use ensemble methods to identify noisy training examples. More precisely, we consider the problem of mislabeled training examples in classification tasks, and address this problem by pre-processing the training set, i.e. by identifying and removing outliers from the training set. We study a number of filter techniques that are based...

  5. Problems with 'Internet addiction' diagnosis and classification.

    Science.gov (United States)

    Hinić, Darko

    2011-06-01

    Owing to the fact that the Internet is spreading rapidly and influencing all aspects of everyday life, a task is assigned to the academic and clinical circles to establish a diagnosis and provide treatment for disorders brought about by its dysfunctional use. This paper presents a review of the most frequent problems and difficulties in dealing with individuals complaining of the symptoms of Internet use disorder, as well as some suggestions for overcoming and alleviating these problems. For the diagnostic criteria problem, a solution can be provided in the form of behavioural addictions category in order to solve the problem of the classification of not only this disorder but also other forms, such as pathological gambling, compulsive shopping etc. However, since there are obvious similarities with the compulsive behaviour, we suggest the term Internet Use Disorder, which appears most acceptable in terms of avoiding beforehand the indecisiveness of this disorder nature. Certainly, in the practical work with each client, by means of a precise and complex clinical interview, it would be further determined which subtype is under question and whether the mechanism of its realisation is more that of a compulsive or addictive nature. We also suggest an approach of defining a set of minimal key symptoms and manifestations of this problem, rather than singling out the personality profiles of individuals who constitute the population at risk. By prevention, the attentiveness of the public would be in that way directed towards the critical aspects of behaviour, and not towards a vague picture which causes panic and doubt, rather than reasonable ways of the problem solution. PMID:21685852

  6. Problems with 'Internet addiction' diagnosis and classification.

    Science.gov (United States)

    Hinić, Darko

    2011-06-01

    Owing to the fact that the Internet is spreading rapidly and influencing all aspects of everyday life, a task is assigned to the academic and clinical circles to establish a diagnosis and provide treatment for disorders brought about by its dysfunctional use. This paper presents a review of the most frequent problems and difficulties in dealing with individuals complaining of the symptoms of Internet use disorder, as well as some suggestions for overcoming and alleviating these problems. For the diagnostic criteria problem, a solution can be provided in the form of behavioural addictions category in order to solve the problem of the classification of not only this disorder but also other forms, such as pathological gambling, compulsive shopping etc. However, since there are obvious similarities with the compulsive behaviour, we suggest the term Internet Use Disorder, which appears most acceptable in terms of avoiding beforehand the indecisiveness of this disorder nature. Certainly, in the practical work with each client, by means of a precise and complex clinical interview, it would be further determined which subtype is under question and whether the mechanism of its realisation is more that of a compulsive or addictive nature. We also suggest an approach of defining a set of minimal key symptoms and manifestations of this problem, rather than singling out the personality profiles of individuals who constitute the population at risk. By prevention, the attentiveness of the public would be in that way directed towards the critical aspects of behaviour, and not towards a vague picture which causes panic and doubt, rather than reasonable ways of the problem solution.

  7. Some debatable problems of stratigraphic classification

    Science.gov (United States)

    Gladenkov, Yury

    2014-05-01

    Russian geologists perform large-scale geological mapping in Russia and abroad. Therefore we urge unification of legends of geological maps compiled in different countries. It seems important to continuously organize discussions on problems of stratigraphic classification. 1. The stratigraphic schools (conventionally called "European" and "American") define "stratigraphy" in different ways. The former prefers "single" stratigraphy that uses data proved by many methods. The latter divides stratigraphy into several independent stratigraphers (litho-, bio-, magneto- and others). Russian geologists classify stratigraphic units into general (chronostratigraphic) and special (in accordance with a method applied). 2. There exist different interpretations of chronostratigraphy. Some stratigraphers suppose that a chronostratigraphic unit corresponds to rock strata formed during a certain time interval (it is somewhat formalistic because a length of interval is frequently unspecified). Russian specialists emphasize the historical-geological background of chronostratigraphic units. Every stratigraphic unit (global and regional) reflects a stage of geological evolution of biosphere and stratisphere. 3. In the view of Russian stratigraphers, the main stratigraphic units may have different extent: a) global (stage), b) regional (regional stage,local zone), and c) local (suite). There is no such hierarchy in the ISG. 4. Russian specialists think that local "lithostratigraphic" units (formations) which may have diachronous boundaries are not chronostratigraphic ones in strict sense (actually they are lithological bodies). In this case "lithostratigraphy" can be considered as "prostratigraphy" and employed in initial studies of sequences. Therefore, a suite is a main local unit of the Russian Code and differs from a formation, although it is somewhat similar. It does not mean that lithostratigraphy is unnecessary. Usage of marker horizons, members and other bodies is of great help

  8. Classification of Ship Routing and Scheduling Problems in Liner Shipping

    DEFF Research Database (Denmark)

    Kjeldsen, Karina Hjortshøj

    2011-01-01

    This article provides a classification scheme for ship routing and scheduling problems in liner shipping in line with the current and future operational conditions of the liner shipping industry. Based on the classification, the literature is divided into groups whose main characteristics...

  9. A Classification Scheme for Phenomenological Universalities in Growth Problems

    CERN Document Server

    Castorina, P; Guiot, C

    2006-01-01

    A classification in universality classes of broad categories of phenomenologies, belonging to different disciplines, may be very useful for a crossfertilization among them and for the purpose of pattern recognition. We present here a simple scheme for the classification of nonlinear growth problems. The success of the scheme in predicting and characterizing the well known Gompertz, West and logistic models suggests to us the study of a hitherto unexplored class of nonlinear growth problems.

  10. Classification and prioritization of usability problems using an augmented classification scheme.

    Science.gov (United States)

    Khajouei, R; Peute, L W P; Hasman, A; Jaspers, M W M

    2011-12-01

    Various methods exist for conducting usability evaluation studies in health care. But although the methodology is clear, no usability evaluation method provides a framework by which the usability reporting activities are fully standardized. Despite the frequent use of forms to report the usability problems and their context-information, this reporting is often hindered by information losses. This is due to the fact that evaluators' problem descriptions are based on individual judgments of what they find salient about a usability problem at a certain moment in time. Moreover, usability problems are typically classified in terms of their type, number, and severity. These classes are usually devised by the evaluator for the purpose at hand and the used problem types often are not mutually exclusive, complete and distinct. Also the impact of usability problems on the task outcome is usually not taken into account. Consequently, problem descriptions are often vague and even when combined with their classification in type or severity leave room for multiple interpretations when discussed with system designers afterwards. Correct interpretation of these problem descriptions is then highly dependent upon the extent to which the evaluators can retrieve relevant details from memory. To remedy this situation a framework is needed guiding usability evaluators in high quality reporting and unique classification of usability problems. Such a framework should allow the disclosure of the underlying essence of problem causes, the severity rating and the classification of the impact of usability problems on the task outcome. The User Action Framework (UAF) is an existing validated classification framework that allows the unique classification of usability problems, but it does not include a severity rating nor does it contain an assessment of the potential impact of usability flaws on the final task outcomes. We therefore augmented the UAF with a severity rating based on Nielsen

  11. Predicting Assignment Submissions in a Multiclass Classification Problem

    Directory of Open Access Journals (Sweden)

    Bogdan Drăgulescu

    2015-08-01

    Full Text Available Predicting student failure is an important task that can empower educators to counteract the factors that affect student performance. In this paper, a part of the bigger problem of predicting student failure is addressed: predicting the students that do not complete their assignment tasks. For solving this problem, real data collected by our university’s educational platform was used. Because the problem consisted of predicting one of three possible classes (multi-class classification, the appropriate algorithms and methods were selected. Several experiments were carried out to find the best approach for this prediction problem and the used data set. An approach of time segmentation is proposed in order to facilitate the prediction from early on. Methods that address the problems of high dimensionality and imbalanced data were also evaluated. The outcome of each approach is shown and compared in order to select the best performing classification algorithm for the problem at hand.

  12. PROBLEMS AND CLASSIFICATION OF FORMER MILITARY AREAS

    Directory of Open Access Journals (Sweden)

    Svirezhev C.A.

    2014-09-01

    Full Text Available Integration of the Russian Federation in the international community, to find the most effective ways to implement the military and land reforms require a comprehensive study. The paper identifies the main problems that hinder the effective implementation of the reform of the conversion, the ways of their solutions, including use of the experience of the advanced countries of the European Union. Identified military objects to be conversion, shown combining them into groups according to various criteria. Proposed a typology of ex-military territories. Notes the role of the organization of effective land use conversion in the areas of land use planning, identifies the main documents required for the implementation of planned activities. The problems of land use planning conversion ex-military territories.

  13. Morphological classification of plant cell deaths

    DEFF Research Database (Denmark)

    van Doorn, W.G.; Beers, E.P.; Dangl, J.L.;

    2011-01-01

    Programmed cell death (PCD) is an integral part of plant development and of responses to abiotic stress or pathogens. Although the morphology of plant PCD is, in some cases, well characterised and molecular mechanisms controlling plant PCD are beginning to emerge, there is still confusion about...... the classification of PCD in plants. Here we suggest a classification based on morphological criteria. According to this classification, the use of the term 'apoptosis' is not justified in plants, but at least two classes of PCD can be distinguished: vacuolar cell death and necrosis. During vacuolar cell death......, the cell contents are removed by a combination of autophagy-like process and release of hydrolases from collapsed lytic vacuoles. Necrosis is characterised by early rupture of the plasma membrane, shrinkage of the protoplast and absence of vacuolar cell death features. Vacuolar cell death is common during...

  14. The Heidelberg classification of renal cell tumours

    NARCIS (Netherlands)

    Kovacs, G; Akhtar, M; Beckwith, BJ; Bugert, P; Cooper, CS; Delahunt, B; Eble, JN; Fleming, S; Ljungberg, B; Medeiros, LJ; Moch, H; Reuter, VE; Ritz, E; Roos, G; Schmidt, D; Srigley, [No Value; Storkel, S; VandenBerg, E; Zbar, B

    1997-01-01

    This paper presents the conclusions of a workshop entitled 'Impact of Molecular Genetics on the Classification of Renal Cell Tumours', which was held in Heidelberg in October 1996, The focus on 'renal cell tumours' excludes any discussion of Wilms' tumour and its variants, or of tumours metastatic t

  15. Consistency argument and classification problem in λ-calculus

    Institute of Scientific and Technical Information of China (English)

    王驹; 赵希顺; 黄且圆; 蒋颖

    1999-01-01

    Enlightened by Mal’cev theorem in universal algebra, a new criterion for consistency argument in λ-calculus has been introduced. It is equivalent to Jacopini and Baeten-Boerboom’ s, but more convenient to use. Based on the new criterion, one uses an enhanced technique to show a few results which provides a deeper insight in the classification problem of λ-terms with no normal forms.

  16. Multistrategy Self-Organizing Map Learning for Classification Problems

    Directory of Open Access Journals (Sweden)

    S. Hasan

    2011-01-01

    Full Text Available Multistrategy Learning of Self-Organizing Map (SOM and Particle Swarm Optimization (PSO is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test.

  17. SOLUTION CLASSIFICATION FOR THE NONPERSPECTIVE-THREE-POINT PROBLEM

    Institute of Scientific and Technical Information of China (English)

    Jianliang TANG; Wensheng CHEN

    2006-01-01

    In the PnP problem, the imaging devices follow the perspective rule and the imaging rays pass through a common point. However, there are many new imaging devices being developed for robot navigation or other fields with the advance in imaging technologies for machine vision. These devise are not necessarily being designed to follow the perspective rule in order to satisfy some design criterion and, thus, the imaging rays may not pass through a common point. Such generalized imaging devices may not be perspective and, therefore, their poses cannot be estimated with traditional perspective technique. Using the Wu-Ritt's zero decomposition method, the main component for the nonperspective-threepoint problem is given. We prove that there are at most eight solutions in the general case and give the solution classification for the NP3P problem.

  18. Simulation Modeling by Classification of Problems: A Case of Cellular Manufacturing

    Science.gov (United States)

    Afiqah, K. N.; Mahayuddin, Z. R.

    2016-02-01

    Cellular manufacturing provides good solution approach to manufacturing area by applying Group Technology concept. The evolution of cellular manufacturing can enhance performance of the cell and to increase the quality of the product manufactured but it triggers other problem. Generally, this paper highlights factors and problems which emerge commonly in cellular manufacturing. The aim of the research is to develop a thorough understanding of common problems in cellular manufacturing. A part from that, in order to find a solution to the problems exist using simulation technique, this classification framework is very useful to be adapted during model building. Biology evolution tool was used in the research in order to classify the problems emerge. The result reveals 22 problems and 25 factors using cladistic technique. In this research, the expected result is the cladogram established based on the problems in cellular manufacturing gathered.

  19. Fuel cells: Problems and prospects

    OpenAIRE

    Shukla, AK; Ramesh, KV; Kannan, AM

    1986-01-01

    n recent years, fuel cell technology has advanced significantly. Field trials on certain types of fuel cells have shown promise for electrical use. This article reviews the electrochemistry, problems and prospects of fuel cell systems.

  20. Long-publishing astronomers, or the problem of classification

    Science.gov (United States)

    Tenn, Joseph S.

    2012-03-01

    In response to several discussions among astronomers and historians of astronomy, I started out to prepare a paper on long-publishing astronomers-those who published for 70, 75, or even 80 years. However, I soon ran into a number of questions of classification, and that turned out to be at least as interesting. How do we decide on classifications? Every time we choose classes, such as asteroids, planets and stars, we run into objects that seem to be in between. In the present case a number of questions arise: Who is an astronomer? Several of those with the longest publication runs started out as physicists, published for years in that subject only, and later took up astrophysics, eventually publishing a few papers in astronomy journals. What is a publication? Should we count publications in physics, chemistry, or mathematics? What about philosophy of science or history of science? What about the elderly retired astronomer presenting a memoir of his or her own work? Abstracts of oral presentations? Monographs? Textbooks? Book reviews? Obituaries? Then there is the problem of posthumous publications. Probably most would include papers in the pipeline when the astronomer dies, but what about the case where the coauthor finally publishes the paper as much as twenty-two years after the death of the person of interest? I eventually decided to make two lists, one which would include most of the above, and one restricted to papers that make contributions to physical science. Note that I do not say 'refereed', as that presents its own problems, especially when applied to periods before the twentieth century. I present a list of astronomers who have published for periods of 68 to 80 years and discuss the problems of defining such terms as astronomer and publication.

  1. Building and Solving Odd-One-Out Classification Problems: A Systematic Approach

    Science.gov (United States)

    Ruiz, Philippe E.

    2011-01-01

    Classification problems ("find the odd-one-out") are frequently used as tests of inductive reasoning to evaluate human or animal intelligence. This paper introduces a systematic method for building the set of all possible classification problems, followed by a simple algorithm for solving the problems of the R-ASCM, a psychometric test derived…

  2. Oriented Shape Index Histograms for Cell Classification

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo; Dahl, Anders Bjorholm; Larsen, Rasmus

    2015-01-01

    evaluate our new feature descriptor using a public dataset consisting of HEp-2 cell images from indirect immunoflourescence lighting. Our results show that we can improve classification performance significantly when including the shape index orientation. Notably, we show that shape index orientation......We propose a novel extension to the shape index histogram feature descriptor where the orientation of the second-order curvature is included in the histograms. The orientation of the shape index is reminiscent but not equal to gradient orientation which is widely used for feature description. We...

  3. Classification for Chinese Libraries (CCL : Histories, Accomplishments, Problems and Its Comparisons

    Directory of Open Access Journals (Sweden)

    Wenxian Zhang

    2003-09-01

    Full Text Available China has a long history in library classifications, although modern classifications did not emerge until one hundred years ago when the Western classifications were introduced into the country. The Classification for Chinese Libraries (CCL was developed after years of collective work. The purposes of this article are to review the ancient history and modern efforts in developing Chinese library classifications, examine the organizations, accomplishments and problems of the CCL especially in the areas of philosophy and social sciences, and compare the CCL with the Library of Congress Classification (LCC in terms of their structures.

  4. Fuel cells problems and solutions

    CERN Document Server

    Bagotsky, Vladimir S

    2012-01-01

    The comprehensive, accessible introduction to fuel cells, their applications, and the challenges they pose Fuel cells-electrochemical energy devices that produce electricity and heat-present a significant opportunity for cleaner, easier, and more practical energy. However, the excitement over fuel cells within the research community has led to such rapid innovation and development that it can be difficult for those not intimately familiar with the science involved to figure out exactly how this new technology can be used. Fuel Cells: Problems and Solutions, Second Edition addresses this i

  5. CLASSIFICATION OF BIFURCATIONS FOR NONLINEAR DYNAMICAL PROBLEMS WITH CONSTRAINTS

    Institute of Scientific and Technical Information of China (English)

    吴志强; 陈予恕

    2002-01-01

    Bifurcation of periodic solutions widely existed in nonlinear dynamical systems isa kind of constrained one in intrinsic quality because its amplitude is always non-negative.Classification of the bifurcations with the type of constraint was discussed. All its six typesof transition sets are derived, in which three types are newly found and a method isproposed for analyzing the constrained bifurcation.

  6. Classification of anxiety and depressive disorders: problems and solutions.

    Science.gov (United States)

    Andrews, G; Anderson, T M; Slade, T; Sunderland, M

    2008-01-01

    The American Psychiatric Association and the World Health Organization have begun to revise their classifications of mental disorders. Four issues related to these revisions are discussed in this study: the structure of the classifications, the relationship between categories and dimensions, the sensitivity of categorical thresholds to definitions, and maximizing the utility and validity of the diagnostic process. There is now sufficient evidence to consider replacing the present groupings of disorders with an empirically based structure that reflects the actual similarities among disorders. For example, perhaps the present depression and anxiety disorders would be best grouped as internalizing disorders. Most mental disorders exist on a severity dimension. The reliability and validity of the classification might be improved if we accepted the dimensional nature of disorders while retaining the use of categorical diagnoses to enhance clinical utility. Definitions of the thresholds that define categories are very susceptible to detail. In International Classification of Diseases-11(ICD-11) and Diagnostic and Statistical Manual of Mental Disorders-V (DSM-V), disorders about which there is agreement should be identically defined, and disorders in which there is disagreement should be defined differently, so that research can identify which definition is more valid. The present diagnostic criteria are too complex to have acceptable clinical utility. We propose a reduced criterion set that can be remembered by clinicians and an enhanced criterion set for use with decision support tools.

  7. The Problem of Classification of Rumours: Peculliarities of Cultural Rumours

    Directory of Open Access Journals (Sweden)

    Valdas Pruskus

    2011-04-01

    Full Text Available The paper analyses classification of rumours. There were many attempts to classify rumours using different criteria. Some authors (A. Dmitrijev 1995 classify them in accordance with three main spheres of social life where they function: political, economic and ideological rumours. However, such a classification is rather conditional, thus it will always seem to be roughcast.Other authors (P. Sorokin 1991 classify rumours in accordance to social elements of interaction systems: the quality and quantity of communicating (interacting individuals, type of interaction and character of information conveyors. This classification seems to be more sociological because it enables to identify which groups spread rumours and how they do it. However, this classification does not mention other important things: the content of a rumour, its relation to reality and so on. The American sociologists W. A. Peterson and N. P. Gist (1951 classify rumours into types according to their content (political, economic, etc., time orientation (explaining past, predictive or foretelling, origin (spontaneous, purposive or relation with reality (rational, fantastic. So there is not one classification of rumours. Partially it is conditioned by a multiple nature of rumours. On the other hand, it is important not only to classify rumours but also to have some mechanism which is able to reveal functioning peculiarities of a particular rumour.The author of this study supposes that every rumour despite its topics has certain features which can be set using a particular system of criteria. There are ten criteria which can describe a rumour and name the peculiarities of its functioning and spread.They help to define any rumour and include the social actualness of a rumour (actual and unreal, the purpose of a rumour (popular, unpopular, the nature of a rumour (malicious or entertaining (jokes, the depth of a rumour (superficial or deep, the supplier (author of a rumour (known

  8. The brain MRI classification problem from wavelets perspective

    Science.gov (United States)

    Bendib, Mohamed M.; Merouani, Hayet F.; Diaba, Fatma

    2015-02-01

    Haar and Daubechies 4 (DB4) are the most used wavelets for brain MRI (Magnetic Resonance Imaging) classification. The former is simple and fast to compute while the latter is more complex and offers a better resolution. This paper explores the potential of both of them in performing Normal versus Pathological discrimination on the one hand, and Multiclassification on the other hand. The Whole Brain Atlas is used as a validation database, and the Random Forest (RF) algorithm is employed as a learning approach. The achieved results are discussed and statistically compared.

  9. Automatic music genres classification as a pattern recognition problem

    Science.gov (United States)

    Ul Haq, Ihtisham; Khan, Fauzia; Sharif, Sana; Shaukat, Arsalan

    2013-12-01

    Music genres are the simplest and effect descriptors for searching music libraries stores or catalogues. The paper compares the results of two automatic music genres classification systems implemented by using two different yet simple classifiers (K-Nearest Neighbor and Naïve Bayes). First a 10-12 second sample is selected and features are extracted from it, and then based on those features results of both classifiers are represented in the form of accuracy table and confusion matrix. An experiment carried out on test 60 taken from middle of a song represents the true essence of its genre as compared to the samples taken from beginning and ending of a song. The novel techniques have achieved an accuracy of 91% and 78% by using Naïve Bayes and KNN classifiers respectively.

  10. A molecular classification of human mesenchymal stromal cells

    OpenAIRE

    Rohart, Florian; Mason, Elizabeth A.; Matigian, Nicholas; Mosbergen, Rowland; Korn, Othmar; Chen, Tyrone; Butcher, Suzanne; Patel, Jatin; Atkinson, Kerry; Khosrotehrani, Kiarash; Fisk, Nicholas M.; Lê Cao, Kim-Anh; Wells, Christine A

    2016-01-01

    Mesenchymal stromal cells (MSC) are widely used for the study of mesenchymal tissue repair, and increasingly adopted for cell therapy, despite the lack of consensus on the identity of these cells. In part this is due to the lack of specificity of MSC markers. Distinguishing MSC from other stromal cells such as fibroblasts is particularly difficult using standard analysis of surface proteins, and there is an urgent need for improved classification approaches. Transcriptome profiling is commonl...

  11. The Problems of the Literary-historical Classification of Kafka's Texts

    Directory of Open Access Journals (Sweden)

    Mateja Clara Jelenčič

    2015-12-01

    Full Text Available Attempts at the literary classification of Kafka's texts often prove to be problematic. Most authors are at a loss, so they propose more than classification. The problem of the literary classification of Kafka's texts is treated only in a few German literary encyclopedias and in interpretations and analyses of his texts. In the interpretations and literary analyses Kafka is mostly classified as a Modernist, but some authors see him as a Postmodernist. Most German literary historians and encyclopedia writers are caught in a dilemma about this subject and so propose more than one literary classification: Kafka is assigned to Expressionism and also proclaimed as a representative of the Existentialism, Surrealism or Magic realism. However most German literary historians often assign Kafka to the Expressionism on historical grounds.

  12. Deep Learning in Label-free Cell Classification.

    Science.gov (United States)

    Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

    2016-03-15

    Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

  13. Deep Learning in Label-free Cell Classification

    Science.gov (United States)

    Chen, Claire Lifan; Mahjoubfar, Ata; Tai, Li-Chia; Blaby, Ian K.; Huang, Allen; Niazi, Kayvan Reza; Jalali, Bahram

    2016-03-01

    Label-free cell analysis is essential to personalized genomics, cancer diagnostics, and drug development as it avoids adverse effects of staining reagents on cellular viability and cell signaling. However, currently available label-free cell assays mostly rely only on a single feature and lack sufficient differentiation. Also, the sample size analyzed by these assays is limited due to their low throughput. Here, we integrate feature extraction and deep learning with high-throughput quantitative imaging enabled by photonic time stretch, achieving record high accuracy in label-free cell classification. Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a novel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phenotypic diagnosis and better understanding of the heterogeneous gene expressions in cells.

  14. Identification and Classification of Diseases: Fundamental Problems in Medical Ontology and Epistemology

    Directory of Open Access Journals (Sweden)

    Lennart Nordenfelt

    2013-05-01

    Full Text Available During the last three centuries there has been remarkable development in the area of the identification and classification of diseases. The taxonomic systems adopted in the 18th century by, for instance, Sauvages and Linnaeus bare no resemblance to the modern nomenclatures for pathological phenomena. The aim of this paper is to give a brief historical presentation, but also a critical analysis, of a number of crucial ideas and theories behind the construction of certain major disease classifications. My focus in the second half of the paper is on the most influential modern systems of classification, the International Statistical Classification of Diseases and Related Health Problems (ICD and the International Systematized Nomenclature of Human and Veterinary Medicine (SNOMED. The former is the official classification adopted by the World Health Organization and is used mainly for clinical and administrative purposes. The latter is a highly complex system of classification which has recently been developed for a variety of purposes (including medical research and is meant to be read and handled by computers. ICD, although widely used all over the world, has salient and well-known logical deficiencies. SNOMED has been introduced partly to remedy these deficiencies. I conclude, however, that SNOMED, in spite of its sophisticated resources, cannot completely replace ICD. For many clinical and administrative purposes there is need of a relatively simple system that can be handled by the ordinary doctor and the ordinary health-care administrator.

  15. Parallel computation for blood cell classification in medical hyperspectral imagery

    Science.gov (United States)

    Li, Wei; Wu, Lucheng; Qiu, Xianbo; Ran, Qiong; Xie, Xiaoming

    2016-09-01

    With the advantage of fine spectral resolution, hyperspectral imagery provides great potential for cell classification. This paper provides a promising classification system including the following three stages: (1) band selection for a subset of spectral bands with distinctive and informative features, (2) spectral-spatial feature extraction, such as local binary patterns (LBP), and (3) followed by an effective classifier. Moreover, these three steps are further implemented on graphics processing units (GPU) respectively, which makes the system real-time and more practical. The GPU parallel implementation is compared with the serial implementation on central processing units (CPU). Experimental results based on real medical hyperspectral data demonstrate that the proposed system is able to offer high accuracy and fast speed, which are appealing for cell classification in medical hyperspectral imagery.

  16. Using classifier fusion to improve the performance of multiclass classification problems

    Science.gov (United States)

    Lynch, Robert; Willett, Peter

    2013-05-01

    The problem of multiclass classification is often modeled by breaking it down into a collection of binary classifiers, as opposed to jointly modeling all classes with a single primary classifier. Various methods can be found in the literature for decomposing the multiclass problem into a collection of binary classifiers. Typical algorithms that are studied here include each versus all remaining (EVAR), each versus all individually (EVAI), and output correction coding (OCC). With each of these methods a classifier fusion based decision rule is formulated utilizing the various binary classifiers to determine the correct classification of an unknown data point. For example, with EVAR the binary classifier with maximum output is chosen. For EVAI, the correct class is chosen using a majority voting rule, and with OCC a comparison algorithm based minimum Hamming distance metric is used. In this paper, it is demonstrated how these various methods perform utilizing the Bayesian Reduction Algorithm (BDRA) as the primary classifier. BDRA is a discrete data classification method that quantizes and reduces the dimensionality of feature data for best classification performance. In this case, BDRA is used to not only train the appropriate binary classifier pairs, but it is also used to train on the discrete classifier outputs to formulate the correct classification decision of unknown data points. In this way, it is demonstrated how to predict which binary classification based algorithm method (i.e., EVAR, EVAI, or OCC) performs best with BDRA. Experimental results are shown with real data sets taken from the Knowledge Extraction based on Evolutionary Learning (KEEL) and University of California at Irvine (UCI) Repositories of classifier Databases. In general, and for the data sets considered, it is shown that the best classification method, based on performance with unlabeled test observations, can be predicted form performance on labeled training data. Specifically, the best

  17. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  18. The problem of multivariate classification of samples with radial (or V-shaped) chemical data.

    Science.gov (United States)

    Aruga, Roberto

    2003-07-27

    On the basis of the results of previous studies, the problem of multivariate classification in the presence of the so-called radial or V-shaped data has been briefly re-examined. Taking into account that the radial data, in the absence of preliminary transformations, usually lead to classifications of samples meaningless from a chemical point of view, five different data transformations have been evaluated and compared in the case of both hypothetical and real samples (real samples, in particular, consisted of archaeological ceramic shards to be classified on the basis of provenance). The following transformations have been used: closure to 100, log row centering, log double centering, row centering, and double centering. The transformed data were then classified by means of hierarchical clustering and principal component analysis (PCA). It has been demonstrated that only the first three transformations lead to correct classifications of radial data, and the causes of this fact have been explained. PMID:18969118

  19. Knowledge acquisition from natural language for expert systems based on classification problem-solving methods

    Science.gov (United States)

    Gomez, Fernando

    1989-01-01

    It is shown how certain kinds of domain independent expert systems based on classification problem-solving methods can be constructed directly from natural language descriptions by a human expert. The expert knowledge is not translated into production rules. Rather, it is mapped into conceptual structures which are integrated into long-term memory (LTM). The resulting system is one in which problem-solving, retrieval and memory organization are integrated processes. In other words, the same algorithm and knowledge representation structures are shared by these processes. As a result of this, the system can answer questions, solve problems or reorganize LTM.

  20. A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem

    Directory of Open Access Journals (Sweden)

    Zekić-Sušac Marijana

    2014-09-01

    Full Text Available Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART classification trees, support vector machines, and k-nearest neighbour on the same dataset in order to compare their efficiency in the sense of classification accuracy. The performance of each method was compared on ten subsamples in a 10-fold cross-validation procedure in order to assess computing sensitivity and specificity of each model. Results: The artificial neural network model based on multilayer perceptron yielded a higher classification rate than the models produced by other methods. The pairwise t-test showed a statistical significance between the artificial neural network and the k-nearest neighbour model, while the difference among other methods was not statistically significant. Conclusions: Tested machine learning methods are able to learn fast and achieve high classification accuracy. However, further advancement can be assured by testing a few additional methodological refinements in machine learning methods.

  1. CLASSIFICATION OF RESTRAINTS IN THE OPTIMIZATION PROBLEM OF A COLD-FORMED PROFILE

    Directory of Open Access Journals (Sweden)

    Agnieszka Łukowicz

    2015-11-01

    Full Text Available This work describes the restraints in the optimization problem. This is an important and complicated issue because it requires taking into account a vast range of information related to the design and production. In order to describe the relations of a specific optimization problem, it is essential to adopt appropriate criteria and to collect information on all kinds of restraints, i.e. boundary conditions. The following paper verifies the various restraints and defines three subsets: design assumptions, technological limitations and standard conditions. The provided classification was made with reference to the analysis of the construction applicability of the newly patented cold-formed profile.

  2. Development and validation of the Slovenian drug-related problem classification system based on the PCNE classification V 6.2.

    Science.gov (United States)

    Horvat, Nejc; Kos, Mitja

    2016-08-01

    Background Classifying drug-related problems increases pharmacists' awareness of patients' drug-related needs and supports the development of counselling skills through increased awareness of the nature and frequency of drug-related problems. No standardised classification system was used in daily pharmacy practice in Slovenia. Objective To translate, upgrade and validate the Pharmaceutical Care Network Europe (PCNE) classification V 6.2 for use in Slovenian community pharmacies. Setting Expert panel meetings at the Faculty of Pharmacy and home-based classification validation. Methods The PCNE classification V 6.2 was translated to Slovenian language by forward-backward translation procedure. An expert panel consisting of nine practicing pharmacists upgraded the content of the translated version. Thirty-one community pharmacists validated this version with the PCNE set of 18 patient cases by coding problems, risk factors and interventions they believed were present in each case. The expert panel discussed the results and upgraded the classification accordingly. Afterwards, 33 community pharmacists validated the upgraded version with a set of 40 actual Slovenian pharmacy patient cases. Based on the results, the expert panel formed a final version of the classification. Main outcome measure Coding consistency between community pharmacists. Results The expert panel performed some major modifications to the PCNE classification V 6.2: the potential problem was added as a sub domain to problems domain; the term adverse drug event was used instead of adverse drug reaction; the causes domain was renamed to risk factors and its sub domains were organized into prescribing, dispensing and use of drugs; dispensing errors were specified; use of drugs was organized into intentional and unintentional use of drugs; the sub domains in the interventions domain were divided according to the communication and agreement with the prescriber. The average coding consistencies in the first

  3. Classification of electrical problems detected by infrared thermography using a risk assessment process

    Science.gov (United States)

    McIntosh, Gregory B.; Huff, Roy

    2016-05-01

    For more than 40 years thermography has been used for electrical problem detection. In addition, since radiometric infrared cameras can establish apparent surface temperature of the problem, a classification system is often utilized based upon surface temperature, or temperature rise above normal operating temperature or ambient air temperature. This however can be an extremely unreliable classification method for a number of reasons including: emissivity and background energy; a lack of regard for failure modes and stressors; surface temperature variability with load and ambient conditions; temperature gradient from internal source to surface; and the presence of convection, just to name a few. Standards, such as NFPA 70B, try to address some of these issues by having very low threshold temperature limits, but this as well has issues including identifying an over-abundance of non-critical problems for immediate repair. This paper will present a risk assessment process and matrix which classifies electrical problems based upon a variety of factors affecting both probability and consequence of electrical component failure. Inherent in this process will be a discussion of understanding and analysing electrical connection failure modes and failure stressors, as well as consideration of both heat energy flow and stored energy rather than only considering surface temperature as a single point predictor of catastrophic failure.

  4. Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks.

    Science.gov (United States)

    Dürr, Oliver; Sick, Beate

    2016-10-01

    Deep learning methods are currently outperforming traditional state-of-the-art computer vision algorithms in diverse applications and recently even surpassed human performance in object recognition. Here we demonstrate the potential of deep learning methods to high-content screening-based phenotype classification. We trained a deep learning classifier in the form of convolutional neural networks with approximately 40,000 publicly available single-cell images from samples treated with compounds from four classes known to lead to different phenotypes. The input data consisted of multichannel images. The construction of appropriate feature definitions was part of the training and carried out by the convolutional network, without the need for expert knowledge or handcrafted features. We compare our results against the recent state-of-the-art pipeline in which predefined features are extracted from each cell using specialized software and then fed into various machine learning algorithms (support vector machine, Fisher linear discriminant, random forest) for classification. The performance of all classification approaches is evaluated on an untouched test image set with known phenotype classes. Compared to the best reference machine learning algorithm, the misclassification rate is reduced from 8.9% to 6.6%.

  5. CYTOGENETIC ANALYSIS OF EPITHELIAL RENAL-CELL TUMORS - RELATIONSHIP WITH A NEW HISTOPATHOLOGICAL CLASSIFICATION

    NARCIS (Netherlands)

    VANDENBERG, E; VANDERHOUT, AH; OOSTERHUIS, JW; STORKEL, S; DIJKHUIZEN, T; ZWEERS, HMM; MENSINK, HJA; BUYS, CHCM; DEJONG, B; Dam, A.

    1993-01-01

    Renal-cell carcinomas (RCC) are clinically, histologically and cytogenetically very heterogeneous. The present histological WHO classification shows no clear correlation between histologic subtypes and specific chromosomal abnormalities. In 1986, a new classification was proposed by Thoenes and Stor

  6. Classification of structural MRI images in Alzheimer's disease from the perspective of ill-posed problems.

    Directory of Open Access Journals (Sweden)

    Ramon Casanova

    Full Text Available BACKGROUND: Machine learning neuroimaging researchers have often relied on regularization techniques when classifying MRI images. Although these were originally introduced to deal with "ill-posed" problems it is rare to find studies that evaluate the ill-posedness of MRI image classification problems. In addition, to avoid the effects of the "curse of dimensionality" very often dimension reduction is applied to the data. METHODOLOGY: Baseline structural MRI data from cognitively normal and Alzheimer's disease (AD patients from the AD Neuroimaging Initiative database were used in this study. We evaluated here the ill-posedness of this classification problem across different dimensions and sample sizes and its relationship to the performance of regularized logistic regression (RLR, linear support vector machine (SVM and linear regression classifier (LRC. In addition, these methods were compared with their principal components space counterparts. PRINCIPAL FINDINGS: In voxel space the prediction performance of all methods increased as sample sizes increased. They were not only relatively robust to the increase of dimension, but they often showed improvements in accuracy. We linked this behavior to improvements in conditioning of the linear kernels matrices. In general the RLR and SVM performed similarly. Surprisingly, the LRC was often very competitive when the linear kernel matrices were best conditioned. Finally, when comparing these methods in voxel and principal component spaces, we did not find large differences in prediction performance. CONCLUSIONS AND SIGNIFICANCE: We analyzed the problem of classifying AD MRI images from the perspective of linear ill-posed problems. We demonstrate empirically the impact of the linear kernel matrix conditioning on different classifiers' performance. This dependence is characterized across sample sizes and dimensions. In this context we also show that increased dimensionality does not necessarily degrade

  7. Intraoperative neuropathology of glioma recurrence: cell detection and classification

    Science.gov (United States)

    Abas, Fazly S.; Gokozan, Hamza N.; Goksel, Behiye; Otero, Jose J.; Gurcan, Metin N.

    2016-03-01

    Intraoperative neuropathology of glioma recurrence represents significant visual challenges to pathologists as they carry significant clinical implications. For example, rendering a diagnosis of recurrent glioma can help the surgeon decide to perform more aggressive resection if surgically appropriate. In addition, the success of recent clinical trials for intraoperative administration of therapies, such as inoculation with oncolytic viruses, may suggest that refinement of the intraoperative diagnosis during neurosurgery is an emerging need for pathologists. Typically, these diagnoses require rapid/STAT processing lasting only 20-30 minutes after receipt from neurosurgery. In this relatively short time frame, only dyes, such as hematoxylin and eosin (H and E), can be implemented. The visual challenge lies in the fact that these patients have undergone chemotherapy and radiation, both of which induce cytological atypia in astrocytes, and pathologists are unable to implement helpful biomarkers in their diagnoses. Therefore, there is a need to help pathologists differentiate between astrocytes that are cytologically atypical due to treatment versus infiltrating, recurrent, neoplastic astrocytes. This study focuses on classification of neoplastic versus non-neoplastic astrocytes with the long term goal of providing a better neuropathological computer-aided consultation via classification of cells into reactive gliosis versus recurrent glioma. We present a method to detect cells in H and E stained digitized slides of intraoperative cytologic preparations. The method uses a combination of the `value' component of the HSV color space and `b*' component of the CIE L*a*b* color space to create an enhanced image that suppresses the background while revealing cells on an image. A composite image is formed based on the morphological closing of the hue-luminance combined image. Geometrical and textural features extracted from Discrete Wavelet Frames and combined to classify

  8. Tight bounds on the size of neural networks for classification problems

    Energy Technology Data Exchange (ETDEWEB)

    Beiu, V. [Los Alamos National Lab., NM (United States); Pauw, T. de [Universite Catholique de Louvain, Louvain-la-Neuve (Belgium). Dept. de Mathematique

    1997-06-01

    This paper relies on the entropy of a data-set (i.e., number-of-bits) to prove tight bounds on the size of neural networks solving a classification problem. First, based on a sequence of geometrical steps, the authors constructively compute an upper bound of O(mn) on the number-of-bits for a given data-set - here m is the number of examples and n is the number of dimensions (i.e., R{sup n}). This result is used further in a nonconstructive way to bound the size of neural networks which correctly classify that data-set.

  9. Using fuzzy logic for automatic control: Case study of a problem of cereals samples classification

    Directory of Open Access Journals (Sweden)

    Lakhoua Najeh Mohamed

    2009-01-01

    Full Text Available The aim of this paper is to present the use of fuzzy logic for automatic control of industrial systems particularly the way to approach a problem of classification. We present a case study of a grading system of cereals that allows us to determine the price of transactions of cereals in Tunisia. Our contribution in this work consists in proposing not only an application of the fuzzy logic on the grading system of cereals but also a methodology enabling the proposing of a new grading system based on the concept of 'Grade' while using the fuzzy logic techniques. .

  10. Accuracy and cut-off point selection in three-class classification problems using a generalization of the Youden index.

    Science.gov (United States)

    Nakas, Christos T; Alonzo, Todd A; Yiannoutsos, Constantin T

    2010-12-10

    We study properties of the index J(3), defined as the accuracy, or the maximum correct classification, for a given three-class classification problem. Specifically, using J(3) one can assess the discrimination between the three distributions and obtain an optimal pair of cut-off points c(1)sum of the correct classification proportions will be maximized. It also serves as the generalization of the Youden index in three-class problems. Parametric and non-parametric approaches for estimation and testing are considered and methods are applied to data from an MRS study on human immunodeficiency virus (HIV) patients.

  11. Nominal classification

    OpenAIRE

    Senft, G.

    2007-01-01

    This handbook chapter summarizes some of the problems of nominal classification in language, presents and illustrates the various systems or techniques of nominal classification, and points out why nominal classification is one of the most interesting topics in Cognitive Linguistics.

  12. Classification of dendritic cell phenotypes from gene expression data

    Directory of Open Access Journals (Sweden)

    Zolezzi Francesca

    2011-08-01

    Full Text Available Abstract Background The selection of relevant genes for sample classification is a common task in many gene expression studies. Although a number of tools have been developed to identify optimal gene expression signatures, they often generate gene lists that are too long to be exploited clinically. Consequently, researchers in the field try to identify the smallest set of genes that provide good sample classification. We investigated the genome-wide expression of the inflammatory phenotype in dendritic cells. Dendritic cells are a complex group of cells that play a critical role in vertebrate immunity. Therefore, the prediction of the inflammatory phenotype in these cells may help with the selection of immune-modulating compounds. Results A data mining protocol was applied to microarray data for murine cell lines treated with various inflammatory stimuli. The learning and validation data sets consisted of 155 and 49 samples, respectively. The data mining protocol reduced the number of probe sets from 5,802 to 10, then from 10 to 6 and finally from 6 to 3. The performances of a set of supervised classification models were compared. The best accuracy, when using the six following genes --Il12b, Cd40, Socs3, Irgm1, Plin2 and Lgals3bp-- was obtained by Tree Augmented Naïve Bayes and Nearest Neighbour (91.8%. Using the smallest set of three genes --Il12b, Cd40 and Socs3-- the performance remained satisfactory and the best accuracy was with Support Vector Machine (95.9%. These data mining models, using data for the genes Il12b, Cd40 and Socs3, were validated with a human data set consisting of 27 samples. Support Vector Machines (71.4% and Nearest Neighbour (92.6% gave the worst performances, but the remaining models correctly classified all the 27 samples. Conclusions The genes selected by the data mining protocol proposed were shown to be informative for discriminating between inflammatory and steady-state phenotypes in dendritic cells. The

  13. Health problems among detainees in Switzerland: a study using the ICPC-2 classification

    Directory of Open Access Journals (Sweden)

    Bertrand Dominique

    2011-04-01

    Full Text Available Abstract Background Little is known about the health status of prisoners in Switzerland. The aim of this study was to provide a detailed description of the health problems presented by detainees in Switzerland's largest remand prison. Methods In this retrospective cross-sectional study we reviewed the health records of all detainees leaving Switzerland's largest remand prison in 2007. The health problems were coded using the International Classification for Primary Care (ICPC-2. Analyses were descriptive, stratified by gender. Results A total of 2195 health records were reviewed. Mean age was 29.5 years (SD 9.5; 95% were male; 87.8% were migrants. Mean length of stay was 80 days (SD 160. Illicit drug use (40.2% and mental health problems (32.6% were frequent, but most of these detainees (57.6% had more generic primary care problems, such as skin (27.0%, infectious diseases (23.5%, musculoskeletal (19.2%, injury related (18.3%, digestive (15.0% or respiratory problems (14.0%. Furthermore, 7.9% reported exposure to violence during arrest by the police. Conclusion Morbidity is high in this young, predominantly male population of detainees, in particular in relation to substance abuse. Other health problems more commonly seen in general practice are also frequent. These findings support the further development of coordinated primary care and mental health services within detention centers.

  14. Sequential projection-based metacognitive learning in a radial basis function network for classification problems.

    Science.gov (United States)

    Babu, G S; Suresh, S

    2013-02-01

    In this paper, we present a sequential projection-based metacognitive learning algorithm in a radial basis function network (PBL-McRBFN) for classification problems. The algorithm is inspired by human metacognitive learning principles and has two components: a cognitive component and a metacognitive component. The cognitive component is a single-hidden-layer radial basis function network with evolving architecture. The metacognitive component controls the learning process in the cognitive component by choosing the best learning strategy for the current sample and adapts the learning strategies by implementing self-regulation. In addition, sample overlapping conditions and past knowledge of the samples in the form of pseudosamples are used for proper initialization of new hidden neurons to minimize the misclassification. The parameter update strategy uses projection-based direct minimization of hinge loss error. The interaction of the cognitive component and the metacognitive component addresses the what-to-learn, when-to-learn, and how-to-learn human learning principles efficiently. The performance of the PBL-McRBFN is evaluated using a set of benchmark classification problems from the University of California Irvine machine learning repository. The statistical performance evaluation on these problems proves the superior performance of the PBL-McRBFN classifier over results reported in the literature. Also, we evaluate the performance of the proposed algorithm on a practical Alzheimer's disease detection problem. The performance results on open access series of imaging studies and Alzheimer's disease neuroimaging initiative datasets, which are obtained from different demographic regions, clearly show that PBL-McRBFN can handle a problem with change in distribution.

  15. Classification-and Regression-Assisted Differential Evolution for Computationally Expensive Problems

    Institute of Scientific and Technical Information of China (English)

    Xiao-Fen Lu; Ke Tang

    2012-01-01

    Differential Evolution (DE) has been well accepted as an effective evolutionary optimization technique.However,it usually involves a large number of fitness evaluations to obtain a satisfactory solution.This disadvantage severely restricts its application to computationally expensive problems,for which a single fitness evaluation can be highly timeconsuming.In the past decade,a lot of investigations have been conducted to incorporate a surrogate model into an evolutionary algorithm (EA) to alleviate its computational burden in this scenario.However,only limited work was devoted to DE.More importantly,although various types of surrogate models,such as regression,ranking,and classification models,have been investigated separately:none of them consistently outperforms others.In this paper,we propose to construct a surrogate model by combining both regression and classification techniques.It is shown that due to the specific selection strategy of DE,a synergy can be established between these two types of models,and leads to a surrogate model that is more appropriate for DE.A novel surrogate model-assisted DE,named Classification-and Regression-Assisted DE (CRADE)is proposed on this basis.Experimental studies are carried out on a set of 16 benchmark functions,and CRADE has shown significant superiority over DE-assisted with only regression or classification models.Further comparison to three state-of-the-art DE variants,i.e.,DE with global and local neighborhoods (DEGL),JADE,and composite DE (CoDE),also demonstrates the superiority of CRADE.

  16. A HYBRID CLASSIFICATION ALGORITHM TO CLASSIFY ENGINEERING STUDENTS’ PROBLEMS AND PERKS

    Directory of Open Access Journals (Sweden)

    Mitali Desai

    2016-03-01

    Full Text Available The social networking sites have brought a new horizon for expressing views and opinions of individuals. Moreover, they provide medium to students to share their sentiments including struggles and joy during the learning process. Such informal information has a great venue for decision making. The large and growing scale of information needs automatic classification techniques. Sentiment analysis is one of the automated techniques to classify large data. The existing predictive sentiment analysis techniques are highly used to classify reviews on E-commerce sites to provide business intelligence. However, they are not much useful to draw decisions in education system since they classify the sentiments into merely three pre-set categories: positive, negative and neutral. Moreover, classifying the students’ sentiments into positive or negative category does not provide deeper insight into their problems and perks. In this paper, we propose a novel Hybrid Classification Algorithm to classify engineering students’ sentiments. Unlike traditional predictive sentiment analysis techniques, the proposed algorithm makes sentiment analysis process descriptive. Moreover, it classifies engineering students’ perks in addition to problems into several categories to help future students and education system in decision making.

  17. Charting the landscape of priority problems in psychiatry, part 1: classification and diagnosis.

    Science.gov (United States)

    Stephan, Klaas E; Bach, Dominik R; Fletcher, Paul C; Flint, Jonathan; Frank, Michael J; Friston, Karl J; Heinz, Andreas; Huys, Quentin J M; Owen, Michael J; Binder, Elisabeth B; Dayan, Peter; Johnstone, Eve C; Meyer-Lindenberg, Andreas; Montague, P Read; Schnyder, Ulrich; Wang, Xiao-Jing; Breakspear, Michael

    2016-01-01

    Contemporary psychiatry faces major challenges. Its syndrome-based disease classification is not based on mechanisms and does not guide treatment, which largely depends on trial and error. The development of therapies is hindered by ignorance of potential beneficiary patient subgroups. Neuroscientific and genetics research have yet to affect disease definitions or contribute to clinical decision making. In this challenging setting, what should psychiatric research focus on? In two companion papers, we present a list of problems nominated by clinicians and researchers from different disciplines as candidates for future scientific investigation of mental disorders. These problems are loosely grouped into challenges concerning nosology and diagnosis (this Personal View) and problems related to pathogenesis and aetiology (in the companion Personal View). Motivated by successful examples in other disciplines, particularly the list of Hilbert's problems in mathematics, this subjective and eclectic list of priority problems is intended for psychiatric researchers, helping to re-focus existing research and providing perspectives for future psychiatric science. PMID:26573970

  18. A spectral and morphologic method for white blood cell classification

    Science.gov (United States)

    Wang, Qian; Chang, Li; Zhou, Mei; Li, Qingli; Liu, Hongying; Guo, Fangmin

    2016-10-01

    The identification of white blood cells is important as it provides an assay for diagnosis of various diseases. To overcome the complexity and inaccuracy of traditional methods based on light microscopy, we proposed a spectral and morphologic method based on hyperspectral blood images. We applied mathematical morphology-based methods to extract spatial information and supervised method is employed for spectral analysis. Experimental results show that white blood cells could be segmented and classified into five types with an overall accuracy of more than 90%. Moreover, the experiments including spectral features reached higher accuracy than the spatial-only cases, with a maximum improvement of nearly 20%. By combing both spatial and spectral features, the proposed method provides higher classification accuracy than traditional methods.

  19. The types of retinal ganglion cells: current status and implications for neuronal classification.

    Science.gov (United States)

    Sanes, Joshua R; Masland, Richard H

    2015-07-01

    In the retina, photoreceptors pass visual information to interneurons, which process it and pass it to retinal ganglion cells (RGCs). Axons of RGCs then travel through the optic nerve, telling the rest of the brain all it will ever know about the visual world. Research over the past several decades has made clear that most RGCs are not merely light detectors, but rather feature detectors, which send a diverse set of parallel, highly processed images of the world on to higher centers. Here, we review progress in classification of RGCs by physiological, morphological, and molecular criteria, making a particular effort to distinguish those cell types that are definitive from those for which information is partial. We focus on the mouse, in which molecular and genetic methods are most advanced. We argue that there are around 30 RGC types and that we can now account for well over half of all RGCs. We also use RGCs to examine the general problem of neuronal classification, arguing that insights and methods from the retina can guide the classification enterprise in other brain regions. PMID:25897874

  20. An active learning based classification strategy for the minority class problem: application to histopathology annotation

    Directory of Open Access Journals (Sweden)

    Doyle Scott

    2011-10-01

    the number of annotations necessary to obtain balanced classes. The accuracy of our prediction is verified by empirically-observed costs. Finally, we find that over-sampling the minority class yields a marginal improvement in classifier accuracy but the improved performance comes at the expense of greater annotation cost. Conclusions We have combined AL with class balancing to yield a general training strategy applicable to most supervised classification problems where the dataset is expensive to obtain and which suffers from the minority class problem. An intelligent training strategy is a critical component of supervised classification, but the integration of AL and intelligent choice of class ratios, as well as the application of a general cost model, will help researchers to plan the training process more quickly and effectively.

  1. Cell morphology-based classification of red blood cells using holographic imaging informatics.

    Science.gov (United States)

    Yi, Faliu; Moon, Inkyu; Javidi, Bahram

    2016-06-01

    We present methods that automatically select a linear or nonlinear classifier for red blood cell (RBC) classification by analyzing the equality of the covariance matrices in Gabor-filtered holographic images. First, the phase images of the RBCs are numerically reconstructed from their holograms, which are recorded using off-axis digital holographic microscopy (DHM). Second, each RBC is segmented using a marker-controlled watershed transform algorithm and the inner part of the RBC is identified and analyzed. Third, the Gabor wavelet transform is applied to the segmented cells to extract a series of features, which then undergo a multivariate statistical test to evaluate the equality of the covariance matrices of the different shapes of the RBCs using selected features. When these covariance matrices are not equal, a nonlinear classification scheme based on quadratic functions is applied; otherwise, a linear classification is applied. We used the stomatocyte, discocyte, and echinocyte RBC for classifier training and testing. Simulation results demonstrated that 10 of the 14 RBC features are useful in RBC classification. Experimental results also revealed that the covariance matrices of the three main RBC groups are not equal and that a nonlinear classification method has a much lower misclassification rate. The proposed automated RBC classification method has the potential for use in drug testing and the diagnosis of RBC-related diseases. PMID:27375953

  2. A molecular classification of human mesenchymal stromal cells.

    Science.gov (United States)

    Rohart, Florian; Mason, Elizabeth A; Matigian, Nicholas; Mosbergen, Rowland; Korn, Othmar; Chen, Tyrone; Butcher, Suzanne; Patel, Jatin; Atkinson, Kerry; Khosrotehrani, Kiarash; Fisk, Nicholas M; Lê Cao, Kim-Anh; Wells, Christine A

    2016-01-01

    Mesenchymal stromal cells (MSC) are widely used for the study of mesenchymal tissue repair, and increasingly adopted for cell therapy, despite the lack of consensus on the identity of these cells. In part this is due to the lack of specificity of MSC markers. Distinguishing MSC from other stromal cells such as fibroblasts is particularly difficult using standard analysis of surface proteins, and there is an urgent need for improved classification approaches. Transcriptome profiling is commonly used to describe and compare different cell types; however, efforts to identify specific markers of rare cellular subsets may be confounded by the small sample sizes of most studies. Consequently, it is difficult to derive reproducible, and therefore useful markers. We addressed the question of MSC classification with a large integrative analysis of many public MSC datasets. We derived a sparse classifier (The Rohart MSC test) that accurately distinguished MSC from non-MSC samples with >97% accuracy on an internal training set of 635 samples from 41 studies derived on 10 different microarray platforms. The classifier was validated on an external test set of 1,291 samples from 65 studies derived on 15 different platforms, with >95% accuracy. The genes that contribute to the MSC classifier formed a protein-interaction network that included known MSC markers. Further evidence of the relevance of this new MSC panel came from the high number of Mendelian disorders associated with mutations in more than 65% of the network. These result in mesenchymal defects, particularly impacting on skeletal growth and function. The Rohart MSC test is a simple in silico test that accurately discriminates MSC from fibroblasts, other adult stem/progenitor cell types or differentiated stromal cells. It has been implemented in the www.stemformatics.org resource, to assist researchers wishing to benchmark their own MSC datasets or data from the public domain. The code is available from the CRAN

  3. A Novel SMOTE-Based Classification Approach to Online Data Imbalance Problem

    Directory of Open Access Journals (Sweden)

    Chunlin Gong

    2016-01-01

    Full Text Available In many practical engineering applications, data are usually collected in online pattern. However, if the classes of these data are severely imbalanced, the classification performance will be restricted. In this paper, a novel classification approach is proposed to solve the online data imbalance problem by integrating a fast and efficient learning algorithm, that is, Extreme Learning Machine (ELM, and a typical sampling strategy, that is, the synthetic minority oversampling technique (SMOTE. To reduce the severe imbalance, the granulation division for major-class samples is made according to the samples’ distribution characteristic, and the original samples are replaced by the obtained granule core to prepare a balanced sample set. In online stage, we firstly make granulation division for minor-class and then conduct oversampling using SMOTE in the region around granule core and granule border. Therefore, the training sample set is gradually balanced and the online ELM model is dynamically updated. We also theoretically introduce fuzzy information entropy to prove that the proposed approach has the lower bound of model reliability after undersampling. Numerical experiments are conducted on two different kinds of datasets, and the results demonstrate that the proposed approach outperforms some state-of-the-art methods in terms of the generalization performance and numerical stability.

  4. Giant cell arteritis. Part I. Terminology, classification, clinical manifestations, diagnosis

    Directory of Open Access Journals (Sweden)

    Azamat Makhmudovich Satybaldyev

    2012-01-01

    Full Text Available Giant cell arteritis (GCA is a vasculitis affecting mainly large and medium-sized arteries, which the classification of systemic vasculitides refers to as those mainly involving the large vessels. GCA is typified by the involvement of extracranial aortic branches and intracranial vessels, the aorta and its large vessels are being affected most frequently. The paper considers the terminology, classification, prevalence, major pathogenic mechanisms, and morphology of GCA. A broad spectrum of its clinical subtypes is due to target vessel stenosis caused by intimal hyperplasia. In 40% of cases, GCA is shown to be accompanied by polymyalgia rheumatica that may either precede or manifest simultaneously with GCA, or follow this disease. The menacing complications of GCA may be visual loss or ischemic strokes at various sites depending on the location of the occluded vessel. Along with the gold standard verification of the diagnosis of GCA, namely temporal artery biopsy, the author indicates other (noninvasive methods for detection of vascular lesions: color Doppler ultrasonography of the temporal arteries, fluorescein angiography of the retina, mag-netic resonance angiography, magnetic resonance imaging, and computed tomography to rule out aortic aneurysm. Dynamic 18F positron emission tomography is demonstrated to play a role in the evaluation of therapeutic effectiveness.

  5. Statistical-mechanics analysis of Gaussian labeled-unlabeled classification problems

    International Nuclear Information System (INIS)

    The labeled-unlabeled classification problem in semi-supervised learning is studied via statistical-mechanics approach. We analytically investigate performance of a learner with an equal-weight mixture of two symmetrically-located Gaussians, performing posterior mean estimation of the parameter vector on the basis of a dataset consisting of labeled and unlabeled data generated from the same probability model as that assumed by the learner. Under the assumption of replica symmetry, we have analytically obtained a set of saddle-point equations, which allows us to numerically evaluate performance of the learner. On the basis of the analytical result we have observed interesting phenomena, in particular the coexistence of good and bad solutions, which may happen when the number of unlabeled data is relatively large compared with that of labeled data

  6. Integrated knowledge-based modeling and its application for classification problems

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Knowledge discovery from data directly can hardly avoid the fact that it is biased towards the collected experimental data, whereas, expert systems are always baffled with the manual knowledge acquisition bottleneck. So it is believable that integrating the knowledge embedded in data and those possessed by experts can lead to a superior modeling approach. Aiming at the classification problems, a novel integrated knowledge-based modeling methodology, oriented by experts and driven by data, is proposed. It starts from experts identifying modeling parameters, and then the input space is partitioned followed by fuzzification. Afterwards, single rules are generated and then aggregated to form a rule base. on which a fuzzy inference mechanism is proposed. The experts are allowed to make necessary changes on the rule base to improve the model accuracy. A real-world application, welding fault diagnosis, is presented to demonstrate the effectiveness of the methodology.

  7. Improving classification of mature microRNA by solving class imbalance problem

    Science.gov (United States)

    Wang, Ying; Li, Xiaoye; Tao, Bairui

    2016-05-01

    MicroRNAs (miRNAs) are ~20–25 nucleotides non-coding RNAs, which regulated gene expression in the post-transcriptional level. The accurate rate of identifying the start sit of mature miRNA from a given pre-miRNA remains lower. It is noting that the mature miRNA prediction is a class-imbalanced problem which also leads to the unsatisfactory performance of these methods. We improved the prediction accuracy of classifier using balanced datasets and presented MatFind which is used for identifying 5‧ mature miRNAs candidates from their pre-miRNA based on ensemble SVM classifiers with idea of adaboost. Firstly, the balanced-dataset was extract based on K-nearest neighbor algorithm. Secondly, the multiple SVM classifiers were trained in orderly using the balance datasets base on represented features. At last, all SVM classifiers were combined together to form the ensemble classifier. Our results on independent testing dataset show that the proposed method is more efficient than one without treating class imbalance problem. Moreover, MatFind achieves much higher classification accuracy than other three approaches. The ensemble SVM classifiers and balanced-datasets can solve the class-imbalanced problem, as well as improve performance of classifier for mature miRNA identification. MatFind is an accurate and fast method for 5‧ mature miRNA identification.

  8. Improving classification of mature microRNA by solving class imbalance problem.

    Science.gov (United States)

    Wang, Ying; Li, Xiaoye; Tao, Bairui

    2016-01-01

    MicroRNAs (miRNAs) are ~20-25 nucleotides non-coding RNAs, which regulated gene expression in the post-transcriptional level. The accurate rate of identifying the start sit of mature miRNA from a given pre-miRNA remains lower. It is noting that the mature miRNA prediction is a class-imbalanced problem which also leads to the unsatisfactory performance of these methods. We improved the prediction accuracy of classifier using balanced datasets and presented MatFind which is used for identifying 5' mature miRNAs candidates from their pre-miRNA based on ensemble SVM classifiers with idea of adaboost. Firstly, the balanced-dataset was extract based on K-nearest neighbor algorithm. Secondly, the multiple SVM classifiers were trained in orderly using the balance datasets base on represented features. At last, all SVM classifiers were combined together to form the ensemble classifier. Our results on independent testing dataset show that the proposed method is more efficient than one without treating class imbalance problem. Moreover, MatFind achieves much higher classification accuracy than other three approaches. The ensemble SVM classifiers and balanced-datasets can solve the class-imbalanced problem, as well as improve performance of classifier for mature miRNA identification. MatFind is an accurate and fast method for 5' mature miRNA identification. PMID:27181057

  9. Revisiting Classification of Eating Disorders-toward Diagnostic and Statistical Manual of Mental Disorders-5 and International Statistical Classification of Diseases and Related Health Problems-11

    OpenAIRE

    Shrigopal Goyal; Yatan Pal Singh Balhara; Khandelwal, S.K.

    2012-01-01

    Two of the most commonly used nosological systems- International Statistical Classification of Diseases and Related Health Problems (ICD)-10 and Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV are under revision. This process has generated a lot of interesting debates with regards to future of the current diagnostic categories. In fact, the status of categorical approach in the upcoming versions of ICD and DSM is also being debated. The current article focuses on the debate wit...

  10. The cell method for electrical engineering and multiphysics problems an introduction

    CERN Document Server

    Alotto, Piergiorgio; Repetto, Maurizio; Rosso, Carlo

    2013-01-01

    This book presents a numerical scheme for the solution of field problems governed by partial differential equations: the cell method. The technique lends itself naturally to the solution of multiphysics problems with several interacting phenomena. The Cell Method, based on a space-time tessellation, is intimately related to the work of Tonti and to his ideas of classification diagrams or, as they are nowadays called, Tonti diagrams: a graphical representation of the problem's equations made possible by a suitable selection of a space-time framework relating physical variables to each other. The main features of the cell method are presented and links with many other discrete numerical methods (finite integration techniques, finite difference time domain, finite volumes, mimetic finite differences, etc.) are discussed. After outlining the theoretical basis of the method, a set of physical problems which have been solved with the cell method is described. These single and multiphysics problems stem from the aut...

  11. Renal cell carcinoma: histological classification and correlation with imaging findings

    International Nuclear Information System (INIS)

    Renal cell carcinoma (RCC) is the seventh most common histological type of cancer in the Western world and has shown a sustained increase in its prevalence. The histological classification of RCCs is of utmost importance, considering the significant prognostic and therapeutic implications of its histological subtypes. Imaging methods play an outstanding role in the diagnosis, staging and follow-up of RCC. Clear cell, papillary and chromophobe are the most common histological subtypes of RCC, and their preoperative radiological characterization, either followed or not by confirmatory percutaneous biopsy, may be particularly useful in cases of poor surgical condition, metastatic disease, central mass in a solitary kidney, and in patients eligible for molecular targeted therapy. New strategies recently developed for treating renal cancer, such as cryo and radiofrequency ablation, molecularly targeted therapy and active surveillance also require appropriate preoperative characterization of renal masses. Less common histological types, although sharing nonspecific imaging features, may be suspected on the basis of clinical and epidemiological data. The present study is aimed at reviewing the main clinical and imaging findings of histological RCC subtypes. (author)

  12. Renal cell carcinoma: histological classification and correlation with imaging findings

    Energy Technology Data Exchange (ETDEWEB)

    Muglia, Valdair F., E-mail: fmuglia@fmrp.usp.br [Universidade de Sao Paulo (CCIFM/FMRP/USP), Ribeirao Preto, SP (Brazil). Centro de Ciencias das Imagens e Fisica Medica. Faculdade de Medicina; Prando, Adilson [Universidade Estadual de Campinas (UNICAMP), SP (Brazil); Hospital Vera Cruz, Campinas, SP (Brazil). Dept. de Imaginologia

    2015-05-15

    Renal cell carcinoma (RCC) is the seventh most common histological type of cancer in the Western world and has shown a sustained increase in its prevalence. The histological classification of RCCs is of utmost importance, considering the significant prognostic and therapeutic implications of its histological subtypes. Imaging methods play an outstanding role in the diagnosis, staging and follow-up of RCC. Clear cell, papillary and chromophobe are the most common histological subtypes of RCC, and their preoperative radiological characterization, either followed or not by confirmatory percutaneous biopsy, may be particularly useful in cases of poor surgical condition, metastatic disease, central mass in a solitary kidney, and in patients eligible for molecular targeted therapy. New strategies recently developed for treating renal cancer, such as cryo and radiofrequency ablation, molecularly targeted therapy and active surveillance also require appropriate preoperative characterization of renal masses. Less common histological types, although sharing nonspecific imaging features, may be suspected on the basis of clinical and epidemiological data. The present study is aimed at reviewing the main clinical and imaging findings of histological RCC subtypes. (author)

  13. Revisiting classification of eating disorders-toward diagnostic and statistical manual of mental disorders-5 and International Statistical Classification of Diseases and Related Health Problems-11

    Directory of Open Access Journals (Sweden)

    Shrigopal Goyal

    2012-01-01

    Full Text Available Two of the most commonly used nosological systems- International Statistical Classification of Diseases and Related Health Problems (ICD-10 and Diagnostic and Statistical Manual of Mental Disorders (DSM-IV are under revision. This process has generated a lot of interesting debates with regards to future of the current diagnostic categories. In fact, the status of categorical approach in the upcoming versions of ICD and DSM is also being debated. The current article focuses on the debate with regards to the eating disorders. The existing classification of eating disorders has been criticized for its limitations. A host of new diagnostic categories have been recommended for inclusion in the upcoming revisions. Also the structure of the existing categories has also been put under scrutiny.

  14. Automatic approach to solve the morphological galaxy classification problem using the sparse representation technique and dictionary learning

    Science.gov (United States)

    Diaz-Hernandez, R.; Ortiz-Esquivel, A.; Peregrina-Barreto, H.; Altamirano-Robles, L.; Gonzalez-Bernal, J.

    2016-06-01

    The observation of celestial objects in the sky is a practice that helps astronomers to understand the way in which the Universe is structured. However, due to the large number of observed objects with modern telescopes, the analysis of these by hand is a difficult task. An important part in galaxy research is the morphological structure classification based on the Hubble sequence. In this research, we present an approach to solve the morphological galaxy classification problem in an automatic way by using the Sparse Representation technique and dictionary learning with K-SVD. For the tests in this work, we use a database of galaxies extracted from the Principal Galaxy Catalog (PGC) and the APM Equatorial Catalogue of Galaxies obtaining a total of 2403 useful galaxies. In order to represent each galaxy frame, we propose to calculate a set of 20 features such as Hu's invariant moments, galaxy nucleus eccentricity, gabor galaxy ratio and some other features commonly used in galaxy classification. A stage of feature relevance analysis was performed using Relief-f in order to determine which are the best parameters for the classification tests using 2, 3, 4, 5, 6 and 7 galaxy classes making signal vectors of different length values with the most important features. For the classification task, we use a 20-random cross-validation technique to evaluate classification accuracy with all signal sets achieving a score of 82.27 % for 2 galaxy classes and up to 44.27 % for 7 galaxy classes.

  15. At last: classification of human mammary cells elucidates breast cancer origins

    OpenAIRE

    Robert D Cardiff; Alexander D Borowsky

    2014-01-01

    Current breast cancer classification systems are based on molecular evaluation of tumor receptor status and do not account for distinct morphological phenotypes. In other types of cancer, taxonomy based on normal cell phenotypes has been extremely useful for diagnosis and treatment strategies. In this issue of the JCI, Santagata and colleagues developed a breast cancer classification scheme based on characterization of healthy mammary cells. Reclassification of breast cancer cells and breast ...

  16. Myocardial aging--a stem cell problem.

    Science.gov (United States)

    Anversa, Piero; Rota, Marcello; Urbanek, Konrad; Hosoda, Toru; Sonnenblick, Edmund H; Leri, Annarosa; Kajstura, Jan; Bolli, Roberto

    2005-11-01

    This review questions the old paradigm that describes the heart as a post-mitotic organ and introduces the notion of the heart as a self-renewing organ regulated by a compartment of multipotent cardiac stem cells (CSCs) capable of regenerating myocytes and coronary vessels throughout life. Because of this dramatic change in cardiac biology, the objective is to provide an alternative perspective of the aging process of the heart and stimulate research in an area that pertains to all of us without exception. The recent explosion of the field of stem cell biology, with the recognition that the possibility exists for extrinsic and intrinsic regeneration of myocytes and coronary vessels, necessitates reevaluation of cardiac homeostasis and myocardial aging. From birth to senescence, the mammalian heart is composed of non-dividing and dividing cells. Loss of telomeric DNA is minimal in fetal and neonatal myocardium but rather significant in the senescent heart. Aging affects the growth and differentiation potential of CSCs interfering not only with their ability to sustain physiological cell turnover but also with their capacity to adapt to increases in pressure and volume loads. The recognition of factors enhancing the activation of the CSC pool, their mobilization, and translocation, however, suggests that the detrimental effects of aging on the heart might be prevented or reversed by local stimulation of CSCs or the intramyocardial delivery of CSCs following their expansion and rejuvenation in vitro. CSC therapy may become, perhaps, a novel strategy for the devastating problem of heart failure in the old population. PMID:16237507

  17. Multi-borders classification

    OpenAIRE

    Mills, Peter

    2014-01-01

    The number of possible methods of generalizing binary classification to multi-class classification increases exponentially with the number of class labels. Often, the best method of doing so will be highly problem dependent. Here we present classification software in which the partitioning of multi-class classification problems into binary classification problems is specified using a recursive control language.

  18. Testing statistical hypothesis on random trees and applications to the protein classification problem

    OpenAIRE

    Busch, Jorge R.; Ferrari, Pablo A.; Flesia, Ana Georgina; Fraiman, Ricardo; Grynberg, Sebastian P.; Leonardi, Florencia

    2009-01-01

    Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a K...

  19. Definition and Classification of Acute Kidney Injury:Contributions and Problems in the Clinical Practice

    Institute of Scientific and Technical Information of China (English)

    CHEN Yi-pu

    2010-01-01

    @@ Definition and Classification of Acute Kidney Injury Before the RIFLE classification system of acute renal failure (ARF) was proposed in the Second Conference of Acute Dialysis Quality Initiative (ADQI, an international volunteer organization mainly composed of intensivists and nephrologists in developed countries) in 2002, there were more than 35 diagnostic criteria of ARF in different literatures, which led to confusion in clinical practice and epidemiological investigation(1).

  20. [Classification of cell-based medicinal products and legal implications: An overview and an update].

    Science.gov (United States)

    Scherer, Jürgen; Flory, Egbert

    2015-11-01

    In general, cell-based medicinal products do not represent a uniform class of medicinal products, but instead comprise medicinal products with diverse regulatory classification as advanced-therapy medicinal products (ATMP), medicinal products (MP), tissue preparations, or blood products. Due to the legal and scientific consequences of the development and approval of MPs, classification should be clarified as early as possible. This paper describes the legal situation in Germany and highlights specific criteria and concepts for classification, with a focus on, but not limited to, ATMPs and non-ATMPs. Depending on the stage of product development and the specific application submitted to a competent authority, legally binding classification is done by the German Länder Authorities, Paul-Ehrlich-Institut, or European Medicines Agency. On request by the applicants, the Committee for Advanced Therapies may issue scientific recommendations for classification.

  1. A modified decision tree algorithm based on genetic algorithm for mobile user classification problem.

    Science.gov (United States)

    Liu, Dong-sheng; Fan, Shu-jiang

    2014-01-01

    In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389

  2. Defining Characteristics of Diagnostic Classification Models and the Problem of Retrofitting in Cognitive Diagnostic Assessment

    Science.gov (United States)

    Gierl, Mark J.; Cui, Ying

    2008-01-01

    One promising application of diagnostic classification models (DCM) is in the area of cognitive diagnostic assessment in education. However, the successful application of DCM in educational testing will likely come with a price--and this price may be in the form of new test development procedures and practices required to yield data that satisfy…

  3. Learning semantic histopathological representation for basal cell carcinoma classification

    Science.gov (United States)

    Gutiérrez, Ricardo; Rueda, Andrea; Romero, Eduardo

    2013-03-01

    Diagnosis of a histopathology glass slide is a complex process that involves accurate recognition of several structures, their function in the tissue and their relation with other structures. The way in which the pathologist represents the image content and the relations between those objects yields a better and accurate diagnoses. Therefore, an appropriate semantic representation of the image content will be useful in several analysis tasks such as cancer classification, tissue retrieval and histopahological image analysis, among others. Nevertheless, to automatically recognize those structures and extract their inner semantic meaning are still very challenging tasks. In this paper we introduce a new semantic representation that allows to describe histopathological concepts suitable for classification. The approach herein identify local concepts using a dictionary learning approach, i.e., the algorithm learns the most representative atoms from a set of random sampled patches, and then models the spatial relations among them by counting the co-occurrence between atoms, while penalizing the spatial distance. The proposed approach was compared with a bag-of-features representation in a tissue classification task. For this purpose, 240 histological microscopical fields of view, 24 per tissue class, were collected. Those images fed a Support Vector Machine classifier per class, using 120 images as train set and the remaining ones for testing, maintaining the same proportion of each concept in the train and test sets. The obtained classification results, averaged from 100 random partitions of training and test sets, shows that our approach is more sensitive in average than the bag-of-features representation in almost 6%.

  4. HEp-2 Cell Classification Using Shape Index Histograms With Donut-Shaped Spatial Pooling

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo; Vestergaard, Jacob Schack; Larsen, Rasmus

    2014-01-01

    We present a new method for automatic classification of indirect immunoflourescence images of HEp-2 cells into different staining pattern classes. Our method is based on a new texture measure called shape index histograms that captures second-order image structure at multiple scales. Moreover, we...... introduce a spatial decomposition scheme which is radially symmetric and suitable for cell images. The spatial decomposition is performed using donut-shaped pooling regions of varying sizes when gathering histogram contributions. We evaluate our method using both the ICIP 2013 and the ICPR 2012 competition...... datasets. Our results show that shape index histograms are superior to other popular texture descriptors for HEp-2 cell classification. Moreover, when comparing to other automated systems for HEp-2 cell classification we show that shape index histograms are very competitive; especially considering...

  5. Cell nuclei attributed relational graphs for efficient representation and classification of gastric cancer in digital histopathology

    Science.gov (United States)

    Sharma, Harshita; Zerbe, Norman; Heim, Daniel; Wienert, Stephan; Lohmann, Sebastian; Hellwich, Olaf; Hufnagl, Peter

    2016-03-01

    This paper describes a novel graph-based method for efficient representation and subsequent classification in histological whole slide images of gastric cancer. Her2/neu immunohistochemically stained and haematoxylin and eosin stained histological sections of gastric carcinoma are digitized. Immunohistochemical staining is used in practice by pathologists to determine extent of malignancy, however, it is laborious to visually discriminate the corresponding malignancy levels in the more commonly used haematoxylin and eosin stain, and this study attempts to solve this problem using a computer-based method. Cell nuclei are first isolated at high magnification using an automatic cell nuclei segmentation strategy, followed by construction of cell nuclei attributed relational graphs of the tissue regions. These graphs represent tissue architecture comprehensively, as they contain information about cell nuclei morphology as vertex attributes, along with knowledge of neighborhood in the form of edge linking and edge attributes. Global graph characteristics are derived and ensemble learning is used to discriminate between three types of malignancy levels, namely, non-tumor, Her2/neu positive tumor and Her2/neu negative tumor. Performance is compared with state of the art methods including four texture feature groups (Haralick, Gabor, Local Binary Patterns and Varma Zisserman features), color and intensity features, and Voronoi diagram and Delaunay triangulation. Texture, color and intensity information is also combined with graph-based knowledge, followed by correlation analysis. Quantitative assessment is performed using two cross validation strategies. On investigating the experimental results, it can be concluded that the proposed method provides a promising way for computer-based analysis of histopathological images of gastric cancer.

  6. Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances.

    Science.gov (United States)

    Al-Sahaf, Harith; Zhang, Mengjie; Johnston, Mark

    2016-01-01

    In the computer vision and pattern recognition fields, image classification represents an important yet difficult task. It is a challenge to build effective computer models to replicate the remarkable ability of the human visual system, which relies on only one or a few instances to learn a completely new class or an object of a class. Recently we proposed two genetic programming (GP) methods, one-shot GP and compound-GP, that aim to evolve a program for the task of binary classification in images. The two methods are designed to use only one or a few instances per class to evolve the model. In this study, we investigate these two methods in terms of performance, robustness, and complexity of the evolved programs. We use ten data sets that vary in difficulty to evaluate these two methods. We also compare them with two other GP and six non-GP methods. The results show that one-shot GP and compound-GP outperform or achieve results comparable to competitor methods. Moreover, the features extracted by these two methods improve the performance of other classifiers with handcrafted features and those extracted by a recently developed GP-based method in most cases. PMID:25700148

  7. Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances.

    Science.gov (United States)

    Al-Sahaf, Harith; Zhang, Mengjie; Johnston, Mark

    2016-01-01

    In the computer vision and pattern recognition fields, image classification represents an important yet difficult task. It is a challenge to build effective computer models to replicate the remarkable ability of the human visual system, which relies on only one or a few instances to learn a completely new class or an object of a class. Recently we proposed two genetic programming (GP) methods, one-shot GP and compound-GP, that aim to evolve a program for the task of binary classification in images. The two methods are designed to use only one or a few instances per class to evolve the model. In this study, we investigate these two methods in terms of performance, robustness, and complexity of the evolved programs. We use ten data sets that vary in difficulty to evaluate these two methods. We also compare them with two other GP and six non-GP methods. The results show that one-shot GP and compound-GP outperform or achieve results comparable to competitor methods. Moreover, the features extracted by these two methods improve the performance of other classifiers with handcrafted features and those extracted by a recently developed GP-based method in most cases.

  8. Optimizing Ship Classification in the Arctic Ocean: A Case Study of Multi-Disciplinary Problem Solving

    Directory of Open Access Journals (Sweden)

    Mark Rahmes

    2014-08-01

    Full Text Available We describe a multi-disciplinary system model for determining decision making strategies based upon the ability to perform data mining and pattern discovery utilizing open source actionable information to prepare for specific events or situations from multiple information sources. We focus on combining detection theory with game theory for classifying ships in Arctic Ocean to verify ship reporting. More specifically, detection theory is used to determine probability of deciding if a ship or certain ship class is present or not. We use game theory to fuse information for optimal decision making on ship classification. Hierarchy game theory framework enables complex modeling of data in probabilistic modeling. However, applicability to big data is complicated by the difficulties of inference in complex probabilistic models, and by computational constraints. We provide a framework for fusing sensor inputs to help compare if the information of a ship matches its AIS reporting requirements using mixed probabilities from game theory. Our method can be further applied to optimizing other choke point scenarios where a decision is needed for classification of ground assets or signals. We model impact on decision making on accuracy by adding more parameters or sensors to the decision making process as sensitivity analysis.

  9. Image processing and classification algorithm for yeast cell morphology in a microfluidic chip

    Science.gov (United States)

    Yang Yu, Bo; Elbuken, Caglar; Ren, Carolyn L.; Huissoon, Jan P.

    2011-06-01

    The study of yeast cell morphology requires consistent identification of cell cycle phases based on cell bud size. A computer-based image processing algorithm is designed to automatically classify microscopic images of yeast cells in a microfluidic channel environment. The images were enhanced to reduce background noise, and a robust segmentation algorithm is developed to extract geometrical features including compactness, axis ratio, and bud size. The features are then used for classification, and the accuracy of various machine-learning classifiers is compared. The linear support vector machine, distance-based classification, and k-nearest-neighbor algorithm were the classifiers used in this experiment. The performance of the system under various illumination and focusing conditions were also tested. The results suggest it is possible to automatically classify yeast cells based on their morphological characteristics with noisy and low-contrast images.

  10. Molecular and Translational Classifications of DAMPs in Immunogenic Cell Death

    Directory of Open Access Journals (Sweden)

    Abhishek D Garg

    2015-11-01

    Full Text Available The immunogenicity of malignant cells has recently been acknowledged as a critical determinant of efficacy in cancer therapy. Thus, besides developing direct immunostimulatory regimens including dendritic cell-based vaccines, checkpoint-blocking therapies, and adoptive T-cell transfer, researchers have started to focus on the overall immunobiology of neoplastic cells. It is now clear that cancer cells can succumb to some anticancer therapies by undergoing a peculiar form of cell death that is characterized by an increased immunogenic potential, owing to the emission of so-called damage-associated molecular patterns (DAMPs. The emission of DAMPs and other immunostimulatory factors by cells succumbing to immunogenic cell death (ICD favors the establishment of a productive interface with the immune system. This results in the elicitation of tumor-targeting immune responses associated with the elimination of residual, treatment-resistant cancer cells, as well as with the establishment of immunological memory. Although ICD has been characterized with increased precision since its discovery, several questions remain to be addressed. Here, we summarize and tabulate the main molecular, immunological, preclinical and clinical aspects of ICD, in an attempt to capture the essence of this clinically relevant phenomenon, and identify future challenges for this rapidly expanding field of investigation.

  11. The cell method for electrical engineering and multiphysics problems. An introduction

    Energy Technology Data Exchange (ETDEWEB)

    Alotto, Piergiorgio [Padova Univ. (Italy). Dipt. di Ingegneria Industriale; Freschi, Fabio; Repetto, Maurizio [Politecnico di Torino (Italy). Dipt. Energia; Rosso, Carlo [Politecnico di Torino (Italy). Dipt. di Ingegneria Meccanica e Aerospaziale

    2013-03-01

    Introduction to the Cell Method, a numerical method for the solution of a large class of physical problems as an alternative to the classical Finite Element techniques. Presents important implementation aspects of the technique as well as a complete fully working computer code for the solution of three-dimensional stationary thermal problem. All chapters include extensive bibliographic references. This book presents a numerical scheme for the solution of field problems governed by partial differential equations: the cell method. The technique lends itself naturally to the solution of multiphysics problems with several interacting phenomena. The Cell Method, based on a space-time tessellation, is intimately related to the work of Tonti and to his ideas of classification diagrams or, as they are nowadays called, Tonti diagrams: a graphical representation of the problem's equations made possible by a suitable selection of a space-time framework relating physical variables to each other. The main features of the cell method are presented and links with many other discrete numerical methods (finite integration techniques, finite difference time domain, finite volumes, mimetic finite differences, etc.) are discussed. After outlining the theoretical basis of the method, a set of physical problems which have been solved with the cell method is described. These single and multiphysics problems stem from the authors' research experience in the fields of electromagnetism, elasticity, thermo-elasticity and others. Finally, the implementation of the numerical technique is described in all its main components: space-time discretization, problem formulation, solution and representation of the resulting physical fields.

  12. Multiparametric classification links tumor microenvironments with tumor cell phenotype.

    Directory of Open Access Journals (Sweden)

    Bojana Gligorijevic

    2014-11-01

    Full Text Available While it has been established that a number of microenvironment components can affect the likelihood of metastasis, the link between microenvironment and tumor cell phenotypes is poorly understood. Here we have examined microenvironment control over two different tumor cell motility phenotypes required for metastasis. By high-resolution multiphoton microscopy of mammary carcinoma in mice, we detected two phenotypes of motile tumor cells, different in locomotion speed. Only slower tumor cells exhibited protrusions with molecular, morphological, and functional characteristics associated with invadopodia. Each region in the primary tumor exhibited either fast- or slow-locomotion. To understand how the tumor microenvironment controls invadopodium formation and tumor cell locomotion, we systematically analyzed components of the microenvironment previously associated with cell invasion and migration. No single microenvironmental property was able to predict the locations of tumor cell phenotypes in the tumor if used in isolation or combined linearly. To solve this, we utilized the support vector machine (SVM algorithm to classify phenotypes in a nonlinear fashion. This approach identified conditions that promoted either motility phenotype. We then demonstrated that varying one of the conditions may change tumor cell behavior only in a context-dependent manner. In addition, to establish the link between phenotypes and cell fates, we photoconverted and monitored the fate of tumor cells in different microenvironments, finding that only tumor cells in the invadopodium-rich microenvironments degraded extracellular matrix (ECM and disseminated. The number of invadopodia positively correlated with degradation, while the inhibiting metalloproteases eliminated degradation and lung metastasis, consistent with a direct link among invadopodia, ECM degradation, and metastasis. We have detected and characterized two phenotypes of motile tumor cells in vivo, which

  13. Multiloculated hydrocephalus: a review of current problems in classification and treatment

    DEFF Research Database (Denmark)

    Andresen, Morten; Juhler, Marianne

    2012-01-01

    PURPOSE: Loculated hydrocephalus is a condition in which discrete fluid-filled compartments form in or in relation to the ventricular system of the brain. Both uni- and multiloculated variants exist, with marked differences in outcome. However, several competing and seemingly interchangeable...... of Systematic Reviews, and the U.S. NIH ClinicalTrials.gov database was carried out with the search terms: "multicystic," "multiloculated," "multicompartment," "uniloculated," and "loculated." All were used in conjunction with the search term "hydrocephalus." RESULTS: A single study with a control group......, evidence is in favor of the neuroendoscopic approach. CONCLUSIONS: In order to ensure a consistent nomenclature as well as to guide future research, we propose a new system of classification for loculated hydrocephalus. It acknowledges the differences between uniloculated and multiloculated hydrocephalus...

  14. Identifying (Quasi) Equally Informative Subsets in Feature Selection Problems for Classification: A Max-Relevance Min-Redundancy Approach.

    Science.gov (United States)

    Karakaya, Gulsah; Galelli, Stefano; Ahipasaoglu, Selin Damla; Taormina, Riccardo

    2016-06-01

    An emerging trend in feature selection is the development of two-objective algorithms that analyze the tradeoff between the number of features and the classification performance of the model built with these features. Since these two objectives are conflicting, a typical result stands in a set of Pareto-efficient subsets, each having a different cardinality and a corresponding discriminating power. However, this approach overlooks the fact that, for a given cardinality, there can be several subsets with similar information content. The study reported here addresses this problem, and introduces a novel multiobjective feature selection approach conceived to identify: 1) a subset that maximizes the performance of a given classifier and 2) a set of subsets that are quasi equally informative, i.e., have almost same classification performance, to the performance maximizing subset. The approach consists of a wrapper [Wrapper for Quasi Equally Informative Subset Selection (W-QEISS)] built on the formulation of a four-objective optimization problem, which is aimed at maximizing the accuracy of a classifier, minimizing the number of features, and optimizing two entropy-based measures of relevance and redundancy. This allows conducting the search in a larger space, thus enabling the wrapper to generate a large number of Pareto-efficient solutions. The algorithm is compared against the mRMR algorithm, a two-objective wrapper and a computationally efficient filter [Filter for Quasi Equally Informative Subset Selection (F-QEISS)] on 24 University of California, Irvine, (UCI) datasets including both binary and multiclass classification. Experimental results show that W-QEISS has the capability of evolving a rich and diverse set of Pareto-efficient solutions, and that their availability helps in: 1) studying the tradeoff between multiple measures of classification performance and 2) understanding the relative importance of each feature. The quasi equally informative subsets are

  15. Greedy heuristic algorithm for solving series of eee components classification problems*

    Science.gov (United States)

    Kazakovtsev, A. L.; Antamoshkin, A. N.; Fedosov, V. V.

    2016-04-01

    Algorithms based on using the agglomerative greedy heuristics demonstrate precise and stable results for clustering problems based on k- means and p-median models. Such algorithms are successfully implemented in the processes of production of specialized EEE components for using in space systems which include testing each EEE device and detection of homogeneous production batches of the EEE components based on results of the tests using p-median models. In this paper, authors propose a new version of the genetic algorithm with the greedy agglomerative heuristic which allows solving series of problems. Such algorithm is useful for solving the k-means and p-median clustering problems when the number of clusters is unknown. Computational experiments on real data show that the preciseness of the result decreases insignificantly in comparison with the initial genetic algorithm for solving a single problem.

  16. B-Cell waste classification sampling and analysis plan

    Energy Technology Data Exchange (ETDEWEB)

    HOBART, R.L.

    1999-09-22

    This report documents the methods used to collect and analyze samples to obtain data necessary to verify and/or determine the radionuclide content of the 324 Facility B-Cell decontamination and decommissioning waste stream.

  17. Comparison Between Supervised and Unsupervised Classifications of Neuronal Cell Types: A Case Study

    OpenAIRE

    Guerra, Luis; McGarry, Laura M.; Robles Forcada, Víctor; Bielza, Concha; Larrañaga Múgica, Pedro; Yuste, Rafael

    2010-01-01

    In the study of neural circuits, it becomes essential to discern the different neuronal cell types that build the circuit. Traditionally, neuronal cell types have been classified using qualitative descriptors. More recently, several attempts have been made to classify neurons quantitatively, using unsupervised clustering methods. While useful, these algorithms do not take advantage of previous information known to the investigator, which could improve the classification task. For neocortical ...

  18. Construction and analysis of tree models for chromosomal classification of diffuse large B-cell lymphomas

    Institute of Scientific and Technical Information of China (English)

    Hui-Yong Jiang; Zhong-Xi Huang; Xue-Feng Zhang; Richard Desper; Tong Zhao

    2007-01-01

    AIM: To construct tree models for classification of diffuse large B-cell lymphomas (DLBCL) by chromosome copy numbers, to compare them with cDNA microarray classification, and to explore models of multi-gene, multi-step and multi-pathway processes of DLBCL tumorigenesis.METHODS: Maximum-weight branching and distance based models were constructed based on the comparative genomic hybridization (CGH) data of 123 DLBCL samples using the established methods and software of Desper et al. A maximum likelihood tree model was also used to analyze the data. By comparing with the results reported in literature, values of tree models in the classification of DLBCL were elucidated.RESULTS: Both the branching and the distance-based trees classified DLBCL into three groups. We combined the classification methods of the two models and classified DLBCL into three categories according to their characteristics. The first group was marked by +Xq, +Xp, -17p and +13q; the second group by +3q, +18q and +18p; and the third group was marked by -6q and +6p. This chromosomal classification was consistent with cDNA classification. It indicated that -6q and +3q were two main events in the tumorigenesis of lymphoma.CONCLUSION: Tree models of lymphoma established from CGH data can be used in the classification of DLBCL. These models can suggest multi-gene, multi-step and multi-pathway processes of tumorigenesis.Two pathways, -6q preceding +6q and +3q preceding +18q, may be important in understanding tumorigenesis of DLBCL. The pathway, -6q preceding +6q, may have a close relationship with the tumorigenesis of non-GCB DLBCL.

  19. The Time Is Right for a New Classification System for Diabetes: Rationale and Implications of the β-Cell-Centric Classification Schema.

    Science.gov (United States)

    Schwartz, Stanley S; Epstein, Solomon; Corkey, Barbara E; Grant, Struan F A; Gavin, James R; Aguilar, Richard B

    2016-02-01

    The current classification system presents challenges to the diagnosis and treatment of patients with diabetes mellitus (DM), in part due to its conflicting and confounding definitions of type 1 DM, type 2 DM, and latent autoimmune diabetes of adults (LADA). The current schema also lacks a foundation that readily incorporates advances in our understanding of the disease and its treatment. For appropriate and coherent therapy, we propose an alternate classification system. The β-cell-centric classification of DM is a new approach that obviates the inherent and unintended confusions of the current system. The β-cell-centric model presupposes that all DM originates from a final common denominator-the abnormal pancreatic β-cell. It recognizes that interactions between genetically predisposed β-cells with a number of factors, including insulin resistance (IR), susceptibility to environmental influences, and immune dysregulation/inflammation, lead to the range of hyperglycemic phenotypes within the spectrum of DM. Individually or in concert, and often self-perpetuating, these factors contribute to β-cell stress, dysfunction, or loss through at least 11 distinct pathways. Available, yet underutilized, treatments provide rational choices for personalized therapies that target the individual mediating pathways of hyperglycemia at work in any given patient, without the risk of drug-related hypoglycemia or weight gain or imposing further burden on the β-cells. This article issues an urgent call for the review of the current DM classification system toward the consensus on a new, more useful system.

  20. The Time Is Right for a New Classification System for Diabetes: Rationale and Implications of the β-Cell-Centric Classification Schema.

    Science.gov (United States)

    Schwartz, Stanley S; Epstein, Solomon; Corkey, Barbara E; Grant, Struan F A; Gavin, James R; Aguilar, Richard B

    2016-02-01

    The current classification system presents challenges to the diagnosis and treatment of patients with diabetes mellitus (DM), in part due to its conflicting and confounding definitions of type 1 DM, type 2 DM, and latent autoimmune diabetes of adults (LADA). The current schema also lacks a foundation that readily incorporates advances in our understanding of the disease and its treatment. For appropriate and coherent therapy, we propose an alternate classification system. The β-cell-centric classification of DM is a new approach that obviates the inherent and unintended confusions of the current system. The β-cell-centric model presupposes that all DM originates from a final common denominator-the abnormal pancreatic β-cell. It recognizes that interactions between genetically predisposed β-cells with a number of factors, including insulin resistance (IR), susceptibility to environmental influences, and immune dysregulation/inflammation, lead to the range of hyperglycemic phenotypes within the spectrum of DM. Individually or in concert, and often self-perpetuating, these factors contribute to β-cell stress, dysfunction, or loss through at least 11 distinct pathways. Available, yet underutilized, treatments provide rational choices for personalized therapies that target the individual mediating pathways of hyperglycemia at work in any given patient, without the risk of drug-related hypoglycemia or weight gain or imposing further burden on the β-cells. This article issues an urgent call for the review of the current DM classification system toward the consensus on a new, more useful system. PMID:26798148

  1. The ISUP system of staging, grading and classification of renal cell neoplasia

    Directory of Open Access Journals (Sweden)

    Hemamali Samaratunga

    2014-07-01

    Full Text Available There have been significant changes in the staging, classification and grading of renal cell neoplasia in recent times. Major changes have occurred in our understanding of extra-renal extension by renal cell cancer and how gross specimens must be handled to optimally display extra-renal spread. Since the 1981 World Health Organization (WHO classification of renal tumors, in which only a handful of different entities were reported, many new morphological types have been described in the literature, resulting in 50 different entities reported in the 2004 WHO classification. Since 2004, further new entities have been recognized and reported necessitating an update of the renal tumor classification. There have also been numerous grading systems for renal cell carcinoma with Fuhrman grading, the most widely used system. In recent times, the prognostic value and the applicability of the Fuhrman grading system in practice has been shown to be, at best, suboptimal. To address these issues and to recommend reporting guidelines, the International Society of Urological Pathology (ISUP undertook a review of adult renal neoplasia through an international consensus conference in Vancouver in 2012. The conduct of the conference was based upon evidence from the literature and the current practice amongst recognized experts in the field. Working groups selected to deal with key topics evaluated current data and identified points of controversy. A pre-meeting survey of the ISUP membership was followed by the consensus conference at which a formal ballot was taken on each key issue. A 65% majority vote was taken as consensus. This review summarizes the outcome and recommendations of this conference with regards to staging, classification and grading of renal cell neoplasia.

  2. Structure Analysis and Classification of Precipitation Cells by Fractal Geometry

    Institute of Scientific and Technical Information of China (English)

    Nafissa Azzaz; Boualem Haddad

    2014-01-01

    This paper analyzes the possibility to discriminate between convective precipitation and stratiform precipitation. This study aims to improve the measurement of rainfall from teledetection data obtained both on the ground and in space. For this, two parameters, fractal dimension and fractal lacunarity, are considered. To calculate the fractal dimension, we use the approach of box-counting and show that the fractal dimension differs between convectives cells and stratiforms ones. And then the fractal lacunarity parameter is calculated by using the sliding boxes algorithm. The study for all the regions shows that precipitation cells can be described by different lacunarities whatever the scale of analysis. We deduce that the two parameters, fractal dimension and fractal lacunarity, can be used to classify precipitations in convective regime and stratiform regime.

  3. On the problem of topological classification of strange attractors of dynamical systems

    Energy Technology Data Exchange (ETDEWEB)

    Plykin, Romen V [Obninsk State Technical University for Nuclear Power Engineering, Obninsk, Kaluga Region (Russian Federation)

    2002-12-31

    This paper consists of two parts. The first, which is devoted to presenting results of Barge and Watkins, connects the closure of the union of the unstable manifolds of certain 'Smale horseshoes' with Knaster continua and projections on them of Vietoris-van Dantzig solenoids. In the second part the homeomorphism problem for expanding attractors of codimension 1 is solved when the dimension of the manifold generating the dynamical system is greater than two.

  4. Improvement of Bioactive Compound Classification through Integration of Orthogonal Cell-Based Biosensing Methods

    Directory of Open Access Journals (Sweden)

    Goran N. Jovanovic

    2007-01-01

    Full Text Available Lack of specificity for different classes of chemical and biological agents, and false positives and negatives, can limit the range of applications for cell-based biosensors. This study suggests that the integration of results from algal cells (Mesotaenium caldariorum and fish chromatophores (Betta splendens improves classification efficiency and detection reliability. Cells were challenged with paraquat, mercuric chloride, sodium arsenite and clonidine. The two detection systems were independently investigated for classification of the toxin set by performing discriminant analysis. The algal system correctly classified 72% of the bioactive compounds, whereas the fish chromatophore system correctly classified 68%. The combined classification efficiency was 95%. The algal sensor readout is based on fluorescence measurements of changes in the energy producing pathways of photosynthetic cells, whereas the response from fish chromatophores was quantified using optical density. Change in optical density reflects interference with the functioning of cellular signal transduction networks. Thus, algal cells and fish chromatophores respond to the challenge agents through sufficiently different mechanisms of action to be considered orthogonal.

  5. On the Variability of Neural Network Classification Measures in the Protein Secondary Structure Prediction Problem

    Directory of Open Access Journals (Sweden)

    Eric Sakk

    2013-01-01

    Full Text Available We revisit the protein secondary structure prediction problem using linear and backpropagation neural network architectures commonly applied in the literature. In this context, neural network mappings are constructed between protein training set sequences and their assigned structure classes in order to analyze the class membership of test data and associated measures of significance. We present numerical results demonstrating that classifier performance measures can vary significantly depending upon the classifier architecture and the structure class encoding technique. Furthermore, an analytic formulation is introduced in order to substantiate the observed numerical data. Finally, we analyze and discuss the ability of the neural network to accurately model fundamental attributes of protein secondary structure.

  6. Psychological and social problems in primary care patients - general practitioners' assessment and classification

    DEFF Research Database (Denmark)

    Rosendal, Marianne; Vedsted, Peter; Christensen, Kaj Sparle;

    2013-01-01

    I almen praksis får 11 % af patienterne en diagnose, der vedrører psykisk sygdom. Heraf har halvdelen en depression eller en belastningstilstand. Kun 18 af de 43 tilgængelige diagnoser i ICPC anvendes regelmæssigt. Sociale problemer angives sjældent som primær problemstilling (0,5 %). Uafhængigt ...... viden om relevante diagnosekoder. Derudover viser undersøgelsen, at den bio-psyko-sociale model helt generelt appliceres yderst skævt i almen praksis, og der kan være behov for fremadrettet at drøfte implikationerne heraf.......I almen praksis får 11 % af patienterne en diagnose, der vedrører psykisk sygdom. Heraf har halvdelen en depression eller en belastningstilstand. Kun 18 af de 43 tilgængelige diagnoser i ICPC anvendes regelmæssigt. Sociale problemer angives sjældent som primær problemstilling (0,5 %). Uafhængigt af...... diagnoser vægter praktiserende læger generelt det biomedicinske aspekt i en konsultation meget højt (78 % i gennemsnit), mens det sociale aspekt vægtes meget lavt (5 %). Det psykologiske aspekt ser ud til at få større vægt i opfølgende konsultationer i forhold til første henvendelse . Resultaterne stammer...

  7. Comprehensive Assessment and Classification of High-Grade B-cell Lymphomas.

    Science.gov (United States)

    Behdad, Amir; Bailey, Nathanael G

    2016-03-01

    High-grade B-cell lymphomas (HGBCLs) are a heterogeneous group of neoplasms that include subsets of diffuse large B-cell lymphoma, Burkitt lymphoma, and lymphomas with features intermediate between diffuse large B-cell lymphoma and Burkitt lymphoma. Morphologically indistinguishable HGBCLs may demonstrate variable clinical courses and responses to therapy. The morphologic evaluation and classification of these neoplasms must be followed by further genetic and immunophenotypic work-up. These additional diagnostic modalities lead to a comprehensive stratification of HGBCL that determines the prognosis and optimal therapy. This article reviews the well-established and emerging biomarkers that are most relevant to the clinical management of HGBCL. PMID:26940267

  8. 图书分类中的疑难问题及解析%Difficult Problems and Analysis of Book Classification

    Institute of Scientific and Technical Information of China (English)

    穆晓婷; 董颖

    2012-01-01

    图书分类是图书馆各项工作中的重点之一,其工作质量直接影响图书的利用率。由于图书分类工作具有复杂性,分类人员在进行图书分类时往往会遇到一些疑难问题,如类目涵义的划分与辨识、历史与现状的时间界限、政治与地理概况的区分、语言读物的区分等。图书分类人员应该根据自身情况总结并提高分类质量。%Book classification is one of important works in libraries,the quality of book classification affects the utilization of books directly.Due to the complexity of book classification,the personnel of book classification often encounter some problems during classifying books,such as the classification and identification of the category meaning,the time limit of the history and the status quo,the distinction of politics and geography situation,the distinction of language literatures,and so on.The personnel of book classification should summarize and improve the quality of classification according to their own case.

  9. Classification and identification of arabidopsis cell wall mutants using fourier transfrom infrared (FT-IR) microspectroscopy

    OpenAIRE

    Mouille, Grégory; Lecomte, Mannaïg; Pagant, Sylvère; Höfte, Hermanus

    2003-01-01

    We have developed a novel procedure for the rapid classification and identification of Arabidopsis mutants with altered cell wall architecture based on Fourier-Transform infrared (FT-IR) micro-spectroscopy. FT-IR transmission spectra were sampled from native 4 day-old dark-grown hypocotyls of 46 mutants and wild type treated with various drugs. The Mahalanobis distance between mutants, calculated from the spectral information after compression with the Discriminant Variables Selection procedu...

  10. A COMPREHENSIVE DEA APPROACH FOR THE RESOURCE ALLOCATION PROBLEM BASED ON SCALE ECONOMIES CLASSIFICATION

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    This paper is concerned with the resource allocation problem based on data envelopment analysis(DEA)which is generally found in practice such as in public services and in production process.In management context,the resource allocation has to achieve the effective-efficient-equality aim and tries to balance the different desires of two management layers:central manager and each sector.In mathematical programming context,to solve the resource allocation asks for introducing many optimization techniques such as multiple-objective programming and goal programming.We construct an algorithm framework by using comprehensive DEA tools including CCR,BCC models,inverse DEA model,the most compromising common weights analysis model,and extra resource allocation algorithm.Returns to scale characteristic is put major place for analyzing DMUs' scale economies and used to select DMU candidates before resource allocation.By combining extra resource allocation algorithm with scale economies target,we propose a resource allocation solution,which can achieve the effective-efficient-equality target and also provide information for future resource allocation.Many numerical examples are discussed in this paper,which also verify our work.

  11. Traffic Management as a Service: The Traffic Flow Pattern Classification Problem

    Directory of Open Access Journals (Sweden)

    Carlos T. Calafate

    2015-01-01

    Full Text Available Intelligent Transportation System (ITS technologies can be implemented to reduce both fuel consumption and the associated emission of greenhouse gases. However, such systems require intelligent and effective route planning solutions to reduce travel time and promote stable traveling speeds. To achieve such goal these systems should account for both estimated and real-time traffic congestion states, but obtaining reliable traffic congestion estimations for all the streets/avenues in a city for the different times of the day, for every day in a year, is a complex task. Modeling such a tremendous amount of data can be time-consuming and, additionally, centralized computation of optimal routes based on such time-dependencies has very high data processing requirements. In this paper we approach this problem through a heuristic to considerably reduce the modeling effort while maintaining the benefits of time-dependent traffic congestion modeling. In particular, we propose grouping streets by taking into account real traces describing the daily traffic pattern. The effectiveness of this heuristic is assessed for the city of Valencia, Spain, and the results obtained show that it is possible to reduce the required number of daily traffic flow patterns by a factor of 4210 while maintaining the essence of time-dependent modeling requirements.

  12. Semantic-Oriented Sentiment Classification for Chinese Product Reviews: An Experimental Study of Book and Cell Phone Reviews

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Sentiment classification is an automatic opinion classification method to classify the product reviews on web into positive or negative opinions to help consumers or sellers to understand the opinions and evaluations from existing customers. Semantic-oriented approach is one of the recent developments in sentiment classification. Up to now, most research of sentiment classification is on English reviews,and little work has been done on Chinese reviews using sentiment classification. The detailed techniques used in English review cannot be applied directly to Chinese reviews due to the different characteristics between these two languages. This study modified and improved the semantic-oriented approach to a 6-step process for Chinese review, focusing on the modification and improvement on the text segmentation and reference words pairs (RWPs) identification. Two experiments were conducted on book reviews and cell phone reviews. The results show that the performances of the proposed approach are comparable to those of the existing English reviews classification studies.

  13. Enhanced CellClassifier: a multi-class classification tool for microscopy images

    Directory of Open Access Journals (Sweden)

    Horvath Peter

    2010-01-01

    Full Text Available Abstract Background Light microscopy is of central importance in cell biology. The recent introduction of automated high content screening has expanded this technology towards automation of experiments and performing large scale perturbation assays. Nevertheless, evaluation of microscopy data continues to be a bottleneck in many projects. Currently, among open source software, CellProfiler and its extension Analyst are widely used in automated image processing. Even though revolutionizing image analysis in current biology, some routine and many advanced tasks are either not supported or require programming skills of the researcher. This represents a significant obstacle in many biology laboratories. Results We have developed a tool, Enhanced CellClassifier, which circumvents this obstacle. Enhanced CellClassifier starts from images analyzed by CellProfiler, and allows multi-class classification using a Support Vector Machine algorithm. Training of objects can be done by clicking directly "on the microscopy image" in several intuitive training modes. Many routine tasks like out-of focus exclusion and well summary are also supported. Classification results can be integrated with other object measurements including inter-object relationships. This makes a detailed interpretation of the image possible, allowing the differentiation of many complex phenotypes. For the generation of the output, image, well and plate data are dynamically extracted and summarized. The output can be generated as graphs, Excel-files, images with projections of the final analysis and exported as variables. Conclusion Here we describe Enhanced CellClassifier which allows multiple class classification, elucidating complex phenotypes. Our tool is designed for the biologist who wants both, simple and flexible analysis of images without requiring programming skills. This should facilitate the implementation of automated high-content screening.

  14. Phenotype classification of single cells using SRS microscopy, RNA sequencing, and microfluidics (Conference Presentation)

    Science.gov (United States)

    Streets, Aaron M.; Cao, Chen; Zhang, Xiannian; Huang, Yanyi

    2016-03-01

    Phenotype classification of single cells reveals biological variation that is masked in ensemble measurement. This heterogeneity is found in gene and protein expression as well as in cell morphology. Many techniques are available to probe phenotypic heterogeneity at the single cell level, for example quantitative imaging and single-cell RNA sequencing, but it is difficult to perform multiple assays on the same single cell. In order to directly track correlation between morphology and gene expression at the single cell level, we developed a microfluidic platform for quantitative coherent Raman imaging and immediate RNA sequencing (RNA-Seq) of single cells. With this device we actively sort and trap cells for analysis with stimulated Raman scattering microscopy (SRS). The cells are then processed in parallel pipelines for lysis, and preparation of cDNA for high-throughput transcriptome sequencing. SRS microscopy offers three-dimensional imaging with chemical specificity for quantitative analysis of protein and lipid distribution in single cells. Meanwhile, the microfluidic platform facilitates single-cell manipulation, minimizes contamination, and furthermore, provides improved RNA-Seq detection sensitivity and measurement precision, which is necessary for differentiating biological variability from technical noise. By combining coherent Raman microscopy with RNA sequencing, we can better understand the relationship between cellular morphology and gene expression at the single-cell level.

  15. Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification.

    Science.gov (United States)

    Hedberg-Buenz, Adam; Christopher, Mark A; Lewis, Carly J; Fernandes, Kimberly A; Dutca, Laura M; Wang, Kai; Scheetz, Todd E; Abràmoff, Michael D; Libby, Richard T; Garvin, Mona K; Anderson, Michael G

    2016-05-01

    The inner surface of the retina contains a complex mixture of neurons, glia, and vasculature, including retinal ganglion cells (RGCs), the final output neurons of the retina and primary neurons that are damaged in several blinding diseases. The goal of the current work was two-fold: to assess the feasibility of using computer-assisted detection of nuclei and random forest classification to automate the quantification of RGCs in hematoxylin/eosin (H&E)-stained retinal whole-mounts; and if possible, to use the approach to examine how nuclear size influences disease susceptibility among RGC populations. To achieve this, data from RetFM-J, a semi-automated ImageJ-based module that detects, counts, and collects quantitative data on nuclei of H&E-stained whole-mounted retinas, were used in conjunction with a manually curated set of images to train a random forest classifier. To test performance, computer-derived outputs were compared to previously published features of several well-characterized mouse models of ophthalmic disease and their controls: normal C57BL/6J mice; Jun-sufficient and Jun-deficient mice subjected to controlled optic nerve crush (CONC); and DBA/2J mice with naturally occurring glaucoma. The result of these efforts was development of RetFM-Class, a command-line-based tool that uses data output from RetFM-J to perform random forest classification of cell type. Comparative testing revealed that manual and automated classifications by RetFM-Class correlated well, with 83.2% classification accuracy for RGCs. Automated characterization of C57BL/6J retinas predicted 54,642 RGCs per normal retina, and identified a 48.3% Jun-dependent loss of cells at 35 days post CONC and a 71.2% loss of RGCs among 16-month-old DBA/2J mice with glaucoma. Output from automated analyses was used to compare nuclear area among large numbers of RGCs from DBA/2J mice (n = 127,361). In aged DBA/2J mice with glaucoma, RetFM-Class detected a decrease in median and mean nucleus size

  16. Classification of reproductive toxicants with diverse mechanisms in the embryonic stem cell test.

    Science.gov (United States)

    Riebeling, Christian; Fischer, Kristin; Luch, Andreas; Seiler, Andrea E M

    2015-12-01

    The embryonic stem cell test (EST) is a promising system to detect embryotoxicity in vitro. Recent studies have pointed out some limitations of the EST and suggest that the applicability domain of the EST and its prediction model have to be better defined. Here, eight substances of known reproductive toxicity were tested in the EST under blind conditions. We applied the prediction model to the data of the EST after classifying the substances according to the published criteria. In addition, a simplified classification of the EST results into two classes as an approach to hazard assessment was compared to the European Union Classification, Labelling and Packaging (CLP) Regulation labels of the substances. With one exception, substances that are labeled as reproductive toxicants according to the CLP Regulation were detected as embryotoxic in the EST while substances without label were found to be non-embryotoxic according to the EST. PMID:26558462

  17. Diffuse large B-cell lymphoma: sub-classification by massive parallel quantitative RT-PCR.

    Science.gov (United States)

    Xue, Xuemin; Zeng, Naiyan; Gao, Zifen; Du, Ming-Qing

    2015-01-01

    Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity with remarkably variable clinical outcome. Gene expression profiling (GEP) classifies DLBCL into activated B-cell like (ABC), germinal center B-cell like (GCB), and Type-III subtypes, with ABC-DLBCL characterized by a poor prognosis and constitutive NF-κB activation. A major challenge for the application of this cell of origin (COO) classification in routine clinical practice is to establish a robust clinical assay amenable to routine formalin-fixed paraffin-embedded (FFPE) diagnostic biopsies. In this study, we investigated the possibility of COO-classification using FFPE tissue RNA samples by massive parallel quantitative reverse transcription PCR (qRT-PCR). We established a protocol for parallel qRT-PCR using FFPE RNA samples with the Fluidigm BioMark HD system, and quantified the expression of the COO classifier genes and the NF-κB targeted-genes that characterize ABC-DLBCL in 143 cases of DLBCL. We also trained and validated a series of basic machine-learning classifiers and their derived meta classifiers, and identified SimpleLogistic as the top classifier that gave excellent performance across various GEP data sets derived from fresh-frozen or FFPE tissues by different microarray platforms. Finally, we applied SimpleLogistic to our data set generated by qRT-PCR, and the ABC and GCB-DLBCL assigned showed the respective characteristics in their clinical outcome and NF-κB target gene expression. The methodology established in this study provides a robust approach for DLBCL sub-classification using routine FFPE diagnostic biopsies in a routine clinical setting. PMID:25418578

  18. Observation and inverse problems in coupled cell networks

    International Nuclear Information System (INIS)

    A coupled cell network is a model for many situations such as food webs in ecosystems, cellular metabolism and economic networks. It consists in a directed graph G, each node (or cell) representing an agent of the network and each directed arrow representing which agent acts on which. It yields a system of differential equations .x(t)=f(x(t)), where the component i of f depends only on the cells xj(t) for which the arrow j → i exists in G. In this paper, we investigate the observation problems in coupled cell networks: can one deduce the behaviour of the whole network (oscillations, stabilization, etc) by observing only one of the cells? We show that the natural observation properties hold for almost all the interactions f

  19. High-speed real-time data classification and cell sorting using discriminant functions and probabilities of misclassification for stem cell enrichment and tumor purging

    Science.gov (United States)

    Leary, James F.; McLaughlin, Scott R.; Hokanson, James A.; Rosenblatt, Judah I.

    1998-04-01

    Data analysis and cell sorting are both fundamentally the same except in terms of the time available to make classification decisions. In the case of cell sorting the cell classification decisions must be made in real-time (in the case of cell sorting, real-time means in about 625 microseconds on this system). This dictates an approach to classification which can be implemented at memory speeds or in pre-programmed hardware. We have been developing new high-speed lookup table transformation methods, suitable for real-time data classification or cell sorting based on statistical classifiers. Multiparameter data mixtures of human MCF-7 breast cancer cells and human bone marrow were analyzed by discriminant function analysis. Cell identification tags, implemented as additional correlated listmode parameters not used for these analyses, were used to uniquely identify each cell type and to compare classifier results. The performance of classifier systems was also assessed using ROC ('receiver operating characteristics') analysis. The effectiveness of the classification system for cell sorting can be evaluated using molecular characterizations of sorted cells, either in small numbers or at single-cell level.

  20. TO THE PROBLEM OF LEGAL SYSTEM CLASSIFICATION: CIVILIZED APPROACH. TENDENCIES OF LEGAL FAMILIES APPROACHING IN THE CONDITIONS OF GLOBALIZATION

    OpenAIRE

    Rasskazov L. P.

    2015-01-01

    The article discusses various criteria for the classification of legal systems. Special attention is drawn to the civilizational approach, which can be effectively used in the classification of legal systems. In accordance with the civilizational approach in the world there are many civilizations, developing according to its own laws (for example, the Scythian civilization, ancient Egyptian, etc.). In accordance with this approach the history of mankind is a history of the development of civi...

  1. Artificial neural networks for classification in metabolomic studies of whole cells using 1H nuclear magnetic resonance.

    LENUS (Irish Health Repository)

    Brougham, D F

    2011-01-01

    We report the successful classification, by artificial neural networks (ANNs), of (1)H NMR spectroscopic data recorded on whole-cell culture samples of four different lung carcinoma cell lines, which display different drug resistance patterns. The robustness of the approach was demonstrated by its ability to classify the cell line correctly in 100% of cases, despite the demonstrated presence of operator-induced sources of variation, and irrespective of which spectra are used for training and for validation. The study demonstrates the potential of ANN for lung carcinoma classification in realistic situations.

  2. Classification of yeast cells from image features to evaluate pathogen conditions

    Science.gov (United States)

    van der Putten, Peter; Bertens, Laura; Liu, Jinshuo; Hagen, Ferry; Boekhout, Teun; Verbeek, Fons J.

    2007-01-01

    Morphometrics from images, image analysis, may reveal differences between classes of objects present in the images. We have performed an image-features-based classification for the pathogenic yeast Cryptococcus neoformans. Building and analyzing image collections from the yeast under different environmental or genetic conditions may help to diagnose a new "unseen" situation. Diagnosis here means that retrieval of the relevant information from the image collection is at hand each time a new "sample" is presented. The basidiomycetous yeast Cryptococcus neoformans can cause infections such as meningitis or pneumonia. The presence of an extra-cellular capsule is known to be related to virulence. This paper reports on the approach towards developing classifiers for detecting potentially more or less virulent cells in a sample, i.e. an image, by using a range of features derived from the shape or density distribution. The classifier can henceforth be used for automating screening and annotating existing image collections. In addition we will present our methods for creating samples, collecting images, image preprocessing, identifying "yeast cells" and creating feature extraction from the images. We compare various expertise based and fully automated methods of feature selection and benchmark a range of classification algorithms and illustrate successful application to this particular domain.

  3. On cell problems for Hamilton-Jacobi equations with non-coercive Hamiltonians and their application to homogenization problems

    Science.gov (United States)

    Hamamuki, Nao; Nakayasu, Atsushi; Namba, Tokinaga

    2015-12-01

    We study a cell problem arising in homogenization for a Hamilton-Jacobi equation whose Hamiltonian is not coercive. We introduce a generalized notion of effective Hamiltonians by approximating the equation and characterize the solvability of the cell problem in terms of the generalized effective Hamiltonian. Under some sufficient conditions, the result is applied to the associated homogenization problem. We also show that homogenization for non-coercive equations fails in general.

  4. Classification of Cells with Membrane Staining and/or Fixation Based on Cellular Specific Membrane Capacitance and Cytoplasm Conductivity

    OpenAIRE

    Song-Bin Huang; Yang Zhao; Deyong Chen; Shing-Lun Liu; Yana Luo; Tzu-Keng Chiu; Junbo Wang; Jian Chen; Min-Hsien Wu

    2015-01-01

    Single-cell electrical properties (e.g., specific membrane capacitance (Cspecific membrane) and cytoplasm conductivity (σcytoplasm)) have been regarded as potential label-free biophysical markers for the evaluation of cellular status. However, whether there exist correlations between these biophysical markers and cellular status (e.g., membrane-associate protein expression) is still unknown. To further validate the utility of single-cell electrical properties in cell type classification, Cspe...

  5. Machine learning‐based classification of diffuse large B‐cell lymphoma patients by eight gene expression profiles

    OpenAIRE

    Zhao, Shuangtao; Dong, Xiaoli; Shen, Wenzhi; Ye, Zhen; Xiang, Rong

    2016-01-01

    Abstract Gene expression profiling (GEP) had divided the diffuse large B‐cell lymphoma (DLBCL) into molecular subgroups: germinal center B‐cell like (GCB), activated B‐cell like (ABC), and unclassified (UC) subtype. However, this classification with prognostic significance was not applied into clinical practice since there were more than 1000 genes to detect and interpreting was difficult. To classify cancer samples validly, eight significant genes ( MYBL1, LMO2, BCL6, MME, IRF4, NFKBIZ, PDE4...

  6. Contemporary approach to diagnosis and classification of renal cell carcinoma with mixed histologic features

    Institute of Scientific and Technical Information of China (English)

    Kanishka Sircar; Priya Rao; Eric Jonasch; Federico A.Monzon; Pheroze Tamboli

    2013-01-01

    Renal cell carcinoma (RCC) is an important contributor to cancer-specific mortality worldwide.Targeted agents that inhibit key subtype-specific signaling pathways have improved survival times and have recently become part of the standard of care for this disease.Accurately diagnosing and classifying RCC on the basis of tumor histology is thus critical.RCC has been traditionally divided into clear-cell and non-clearcell categories,with papillary RCC forming the most common subtype of non-clear-cell RCC.Renal neoplasms with overlapping histologies,such as tumors with mixed clear-cell and papillary features and hybrid renal oncocytic tumors,are increasingly seen in contemporary practice and present a diagnostic challenge with important therapeutic implications.In this review,we discuss the histologic,immunohistochemical,cytogenetic,and clinicopathologic aspects of these differential diagnoses and illustrate how the classification of RCC has evolved to integrate both the tumor's microscopic appearance and its molecular fingerprint.

  7. Classification of neocortical interneurons using affinity propagation

    OpenAIRE

    Santana, Roberto; McGarry, Laura M.; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neu...

  8. Classification of neocortical interneurons using affinity propagation

    OpenAIRE

    Roberto eSantana; Laura eMcGarry; Concha eBielza; Pedro eLarrañaga; Rafael eYuste

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbi...

  9. Implications of epigenetic variability within a cell population for cell type classification

    Directory of Open Access Journals (Sweden)

    Inna eTabansky

    2015-12-01

    Full Text Available Here we propose a new approach to defining nerve ‘cell types’ in reaction to recent advances in single cell analysis. Among cells previously thought to be equivalent, considerable differences in global gene expression and biased tendencies among differing developmental fates have been demonstrated within multiple lineages. The model of classifying cells into distinct types thus has to be revised to account for this intrinsic variability. A ‘cell type’ could be a group of cells that possess similar, but not necessarily identical properties, variable within a spectrum of epigenetic adjustments that permit its developmental path toward a specific function to be achieved. Thus, the definition of a cell type is becoming more similar to the definition of a species: sharing essential properties with other members of its group, but permitting a certain amount of deviation in aspects that do not seriously impact function. This approach accommodates, even embraces the spectrum of natural variation found in various cell populations and consequently avoids the fallacy of false equivalence. For example, developing neurons will react to their microenvironments with epigenetic changes resulting in slight changes in gene expression and morphology. Addressing the new questions implied here will have significant implications for developmental neurobiology.

  10. The diagnosis and management of pre-invasive breast disease: Pathological diagnosis – problems with existing classifications

    International Nuclear Information System (INIS)

    In this review, we comment on the reasons for disagreement in the concepts, diagnosis and classifications of pre-invasive intraductal proliferations. In view of these disagreements, our proposal is to distinguish epithelial hyperplasia, lobular carcinoma in situ and ductal carcinoma in situ, and to abandon the use of poorly reproducible categories, such as atypical ductal hyperplasia or ductal intraepithelial neoplasia, followed by a number to indicate the degree of proliferation and atypia, as these are not practical for clinical decision making, nor for studies aimed at improving the understanding of breast cancer development. If there is doubt about the classification of an intraductal proliferation, a differential diagnosis and the reason for and degree of uncertainty should be given, rather than categorizing a proliferation as atypical

  11. Crossmapping of Nursing Problem and Action Statements in Telephone Nursing Consultation Documentations with International Classification for Nursing Practice

    OpenAIRE

    Lee, Hyun Jung; Park, Hyeoun-Ae

    2010-01-01

    Objectives This study is to cross-map telephone nursing consultation documentations with International Classification for Nursing Practice (ICNP; ver. 1.0 concepts). Methods The narrative telephone nursing consultation documentations of 170 ophthalmology nursing unit patients were analyzed. The nursing statements were examined and cross-mapped with the Korean version of the ICNP ver. 1.0. If all the concepts of a statement were mapped to ICNP concepts, it was classified as 'completely mapped'...

  12. Generalization of Youden index for multiple-class classification problems applied to the assessment of externally validated cognition in Parkinson disease screening.

    Science.gov (United States)

    Nakas, Christos T; Dalrymple-Alford, John C; Anderson, Tim J; Alonzo, Todd A

    2013-03-15

    Routine cognitive screening in Parkinson disease (PD) has become essential for management, to track progression and to assess clinical status in therapeutic trials. Patients with mild cognitive impairment (PD-MCI) are more likely to progress to dementia and therefore need to be distinguished from patients with normal cognition and those with dementia. A three-class Youden index has been recently proposed to select cut-off points in three-class classification problems. In this article, we examine properties of a modification of the three-class Youden index and propose a generalization to k-class classification problems. Geometric and theoretical properties of the modified index J(k) are examined. It is shown that J(k) is equivalent to the sum of the k - 1 two-class Youden indices for the adjacent classes of the ordered alternative problem given that the ordering holds. Methods are applied in the assessment of the Montreal Cognitive Assessment test when screening cognition in PD.

  13. A New View of Classification in Astronomy with the Archetype Technique: An Astronomical Case of the NP-complete Set Cover Problem

    CERN Document Server

    Zhu, Guangtun

    2016-01-01

    We introduce a new generic Archetype technique for source classification and identification, based on the NP-complete set cover problem (SCP) in computer science and operations research (OR). We have developed a new heuristic SCP solver, by combining the greedy algorithm and the Lagrangian Relaxation (LR) approximation method. We test the performance of our code on the test cases from Beasley's OR Library and show that our SCP solver can efficiently yield solutions that are on average 99% optimal in terms of the cost. We discuss how to adopt SCP for classification purposes and put forward a new Archetype technique. We use an optical spectroscopic dataset of extragalactic sources from the Sloan Digital Sky Survey (SDSS) as an example to illustrate the steps of the technique. We show how the technique naturally selects a basis set of physically-motivated archetypal systems to represent all the extragalactic sources in the sample. We discuss several key aspects in the technique and in any general classification ...

  14. Neuronal classification and marker gene identification via single-cell expression profiling of brainstem vestibular neurons subserving cerebellar learning

    OpenAIRE

    Kodama, Takashi; Guerrero, Shiloh; Shin, Minyoung; Moghadam, Seti; Faulstich, Michael; du Lac, Sascha

    2012-01-01

    Identification of marker genes expressed in specific cell types is essential for the genetic dissection of neural circuits. Here we report a new strategy for classifying heterogeneous populations of neurons into functionally distinct types and for identifying associated marker genes. Quantitative single-cell expression profiling of genes related to neurotransmitters and ion channels enables functional classification of neurons; transcript profiles for marker gene candidates identify molecular...

  15. Gastrointestinal B-cell lymphomas: From understanding B-cell physiology to classification and molecular pathology.

    Science.gov (United States)

    Sagaert, Xavier; Tousseyn, Thomas; Yantiss, Rhonda K

    2012-12-15

    The gut is the most common extranodal site where lymphomas arise. Although all histological lymphoma types may develop in the gut, small and large B-cell lymphomas predominate. The sometimes unexpected finding of a lymphoid lesion in an endoscopic biopsy of the gut may challenge both the clinician (who is not always familiar with lymphoma pathogenesis) and the pathologist (who will often be hampered in his/her diagnostic skill by the limited amount of available tissue). Moreover, the past 2 decades have spawned an avalanche of new data that encompasses both the function of the reactive B-cell as well as the pathogenic pathways that lead to its neoplastic counterpart, the B-cell lymphoma. Therefore, this review aims to offer clinicians an overview of B-cell lymphomas in the gut, and their pertinent molecular features that have led to new insights regarding lymphomagenesis. It addresses the question as how to incorporate all presently available information on normal and neoplastic B-cell differentiation, and how this knowledge can be applied in daily clinical practice (e.g., diagnostic tools, prognostic biomarkers or therapeutic targets) to optimalise the managment of this heterogeneous group of neoplasms. PMID:23443141

  16. High-throughput Biological Cell Classification Featuring Real-time Optical Data Compression

    CERN Document Server

    Jalali, Bahram; Chen, Claire L

    2015-01-01

    High throughput real-time instruments are needed to acquire large data sets for detection and classification of rare events. Enabled by the photonic time stretch digitizer, a new class of instruments with record throughputs have led to the discovery of optical rogue waves [1], detection of rare cancer cells [2], and the highest analog-to-digital conversion performance ever achieved [3]. Featuring continuous operation at 100 million frames per second and shutter speed of less than a nanosecond, the time stretch camera is ideally suited for screening of blood and other biological samples. It has enabled detection of breast cancer cells in blood with record, one-in-a-million, sensitivity [2]. Owing to their high real-time throughput, instruments produce a torrent of data - equivalent to several 4K movies per second - that overwhelm data acquisition, storage, and processing operations. This predicament calls for technologies that compress images in optical domain and in real-time. An example of this, based on war...

  17. A Population Classification Evolution Algorithm for the Parameter Extraction of Solar Cell Models

    Directory of Open Access Journals (Sweden)

    Yiqun Zhang

    2016-01-01

    Full Text Available To quickly and precisely extract the parameters for solar cell models, inspired by simplified bird mating optimizer (SBMO, a new optimization technology referred to as population classification evolution (PCE is proposed. PCE divides the population into two groups, elite and ordinary, to reach a better compromise between exploitation and exploration. For the evolution of elite individuals, we adopt the idea of parthenogenesis in nature to afford a fast exploitation. For the evolution of ordinary individuals, we adopt an effective differential evolution strategy and a random movement of small probability is added to strengthen the ability to jump out of a local optimum, which affords a fast exploration. The proposed PCE is first estimated on 13 classic benchmark functions. The experimental results demonstrate that PCE yields the best results on 11 functions by comparing it with six evolutional algorithms. Then, PCE is applied to extract the parameters for solar cell models, that is, the single diode and the double diode. The experimental analyses demonstrate that the proposed PCE is superior when comparing it with other optimization algorithms for parameter identification. Moreover, PCE is tested using three different sources of data with good accuracy.

  18. TO THE PROBLEM OF LEGAL SYSTEM CLASSIFICATION: CIVILIZED APPROACH. TENDENCIES OF LEGAL FAMILIES APPROACHING IN THE CONDITIONS OF GLOBALIZATION

    Directory of Open Access Journals (Sweden)

    Rasskazov L. P.

    2015-09-01

    Full Text Available The article discusses various criteria for the classification of legal systems. Special attention is drawn to the civilizational approach, which can be effectively used in the classification of legal systems. In accordance with the civilizational approach in the world there are many civilizations, developing according to its own laws (for example, the Scythian civilization, ancient Egyptian, etc.. In accordance with this approach the history of mankind is a history of the development of civilizations. There are different definitions of civilization. In generalized form is a community of people with particular characteristics in the socio - political organization, economy, culture. All States from the point of view of the civilizational approach can be divided into two types: Eastern (China, India, the Empire of the Incas, etc. characterized by Marx as the "Asian mode of production"; the Western, or progressive (especially European countries. Each of these types has its historical features. In turn, each of these types has its own legal family. It appears that the basis for determining the classification of legal systems is a normative element of the legal system, including law, legal principles, sources of law, legal system, legislation, legal techniques. But this criterion can be applied in one and the same type of civilizations. In accordance with the criterion of the country of the Western type, can be divided into two large families: the Romano-Germanic and Anglo-Saxon. It should be noted that globalization processes in the modern world lead to the convergence of legal families. In particular this applies to the RomanoGermanic and Anglo-Saxon legal families, between which there is a gradual disappearance of the traditional differences

  19. Gastrointestinal B-cell lymphomas: From understanding B-cell physiology to classification and molecular pathology

    OpenAIRE

    2012-01-01

    The gut is the most common extranodal site where lymphomas arise. Although all histological lymphoma types may develop in the gut, small and large B-cell lymphomas predominate. The sometimes unexpected finding of a lymphoid lesion in an endoscopic biopsy of the gut may challenge both the clinician (who is not always familiar with lymphoma pathogenesis) and the pathologist (who will often be hampered in his/her diagnostic skill by the limited amount of available tissue). Moreover, the past 2 d...

  20. Hierarchical classification of social groups

    OpenAIRE

    Витковская, Мария

    2001-01-01

    Classification problems are important for every science, and for sociology as well. Social phenomena, examined from the aspect of classification of social groups, can be examined deeper. At present one common classification of groups does not exist. This article offers the hierarchical classification of social group.

  1. Multiple Attractor Cellular Automata Classification Method and Over-Fitting Problem with CART%分类回归树多吸引子细胞自动机分类方法及过拟合研究

    Institute of Scientific and Technical Information of China (English)

    方敏; 牛文科; 张晓松

    2012-01-01

    基于多吸引子细胞自动机的分类方法多是二分类算法,难以克服过度拟合问题,在生成多吸引子细胞自动机时如何有效地处理多分类及过度拟合问题还缺乏可行的方法.从细胞空间角度对模式空间进行分割是一种均匀分割,难以适应空间非均匀分割的需要.将CART算法同多吸引子细胞自动机相结合构造树型结构的分类器,以解决空间的非均匀分割及过度拟合问题,并基于粒子群优化方法提出树节点的最优多吸引子细胞自动机特征矩阵的构造方法.基于该方法构造的多吸引子细胞自动机分类器能够以较少的伪穷举域比特数获得好的分类性能,减少了分类器中的空盆数量,在保证分类正确率的同时改善了过拟合问题,缩短了分类时间.实验分析证明了所提出方法的可行性和有效性.%The classification methods based on multiple attractor cellular automata can process the classification of two classes, and they are difficult to overcome overfitting problem. There are not yet effective methods for constructing a multiple attractor cellular automata which can process multi-classification and overfitting problem. The pattern space partition in the view of cell space is a kind of uniform partition which is difficult to adapt to the needs of spatial non-uniform partition. By combining the CART algorithm with the multiple attractor cellular automata, a kind of classifier with tree structure is constructed to solve the non-uniform partition problem and overfitting problem. The multiple attractor cellular automata characteristic matrix is defined, and the learning method of classifiers as a node in a tree is studied based on particle swarm optimization algorithm. The multiple attractor cellular automata classifiers built on this approach are able to obtain good classification performance by using less number of bits of pseudo-exhaustive field. The classifier with tree frame of multiple

  2. Linking self-determined functional problems of patients with neck pain to the International Classification of Functioning, Disability, and Health (ICF

    Directory of Open Access Journals (Sweden)

    Andelic N

    2012-10-01

    Full Text Available Nada Andelic,1 Jan Borre Johansen,1 Erik Bautz-Holter,1,2 Anne Marit Mengshoel,3 Eva Bakke,3 Cecilie Roe1,21Department of Physical Medicine and Rehabilitation, Oslo University Hospital, Oslo, Norway; 2Faculty of Medicine, University of Oslo, Oslo, Norway; 3Department of Health Sciences, Institute of Health and Society, University of Oslo, Oslo, NorwayObjective: To describe commonly reported self-determined functional problems in patients with neck pain and to evaluate their fit to the components of the International Classification of Functioning, Disability, and Health (ICF.Methods: Overall, 249 patients were included in this cross-sectional study that comprised patients with neck pain referred to the outpatient clinic at Oslo University Hospital (2007–2009. Patients were asked to report their three most significant functional problems on the Patient-Specific Functional Scale, a self-determined measure of function. The ICF was used as a tool for analysis. Meaningful concepts within the functional problems were identified, coded, and linked to second-level categories within the components of “body functions,” and “activities and participation.” Two researchers performed coding and linking independently. The ICF categories were presented by percentage of the total number of functional problems linked to the ICF.Results: Of 628 reported functional problems, 13 meaningful ICF domains were identified: four domains belonging to the body functions component (b and nine domains belonging to activities and participation components (d. Within the 88 second-level ICF classification categories of body functions, the most frequently reported items were sleep function (b134; 27% and mobility of joint functions (b710; 26%. Within the 538 second-level categories of activities and participation, remunerative employment was reported as the most frequent item (d850; 15%, closely followed by doing housework (d640; 14%, and recreation and leisure

  3. Phenotypic classification of gastric signet ring cell carcinoma and its relationship with clinicopathologic parameters and prognosis

    Institute of Scientific and Technical Information of China (English)

    Meng-Meng Tian; Ai-Lian Zhao; Zhong-Wu Li; Ji-You Li

    2007-01-01

    AIM: To distinguish subtypes of gastric signet ring cell(SRC) carcinoma by investigating the expression of gastric and intestinal phenotypic markers, and to study the significance of phenotypic classification in predicting tumor progression and outcome.METHODS: Immunohistochemistry was performed in 66 cases of SRC carcinoma with MUC2. VILLIN, CDX2, Licadherin antibodies as intestinal phenotype markers and MUC5AC, HGM, MUC6 antibodies as gastric phenotype markers, and the relationship was analyzed between the phenotypic expression pation and clinicopathologic parameters, as well as the 3-year survival rate.RESULTS: Expression of intestinal phenotypic markers was positively associated with tumor size, wall invasion,vascular invasion, lymph node metastasis and tumornode-metastasis (TNM) stage. Cases expressing one or more intestinal markers had a significant lower survival rate than cases expressing none of the intestinal markers.CONCLUSION: The SRC carcinomas expressing intestinal phenotype markers exhibited a high proliferative potential, bad biological behaviors and poor prognosis. Examination of phenotype expression may be useful in distinguishing histological type and in prediciting the prognosis of gastric SRC carcinoma.

  4. Multi-Organ Cancer Classification and Survival Analysis

    OpenAIRE

    Bauer, Stefan; Carion, Nicolas; Schüffler, Peter; Fuchs, Thomas; Wild, Peter; Buhmann, Joachim M.

    2016-01-01

    Accurate and robust cell nuclei classification is the cornerstone for a wider range of tasks in digital and Computational Pathology. However, most machine learning systems require extensive labeling from expert pathologists for each individual problem at hand, with no or limited abilities for knowledge transfer between datasets and organ sites. In this paper we implement and evaluate a variety of deep neural network models and model ensembles for nuclei classification in renal cell cancer (RC...

  5. Recursive heuristic classification

    Science.gov (United States)

    Wilkins, David C.

    1994-01-01

    The author will describe a new problem-solving approach called recursive heuristic classification, whereby a subproblem of heuristic classification is itself formulated and solved by heuristic classification. This allows the construction of more knowledge-intensive classification programs in a way that yields a clean organization. Further, standard knowledge acquisition and learning techniques for heuristic classification can be used to create, refine, and maintain the knowledge base associated with the recursively called classification expert system. The method of recursive heuristic classification was used in the Minerva blackboard shell for heuristic classification. Minerva recursively calls itself every problem-solving cycle to solve the important blackboard scheduler task, which involves assigning a desirability rating to alternative problem-solving actions. Knowing these ratings is critical to the use of an expert system as a component of a critiquing or apprenticeship tutoring system. One innovation of this research is a method called dynamic heuristic classification, which allows selection among dynamically generated classification categories instead of requiring them to be prenumerated.

  6. Classification of Cells with Membrane Staining and/or Fixation Based on Cellular Specific Membrane Capacitance and Cytoplasm Conductivity

    Directory of Open Access Journals (Sweden)

    Song-Bin Huang

    2015-01-01

    Full Text Available Single-cell electrical properties (e.g., specific membrane capacitance (Cspecific membrane and cytoplasm conductivity (σcytoplasm have been regarded as potential label-free biophysical markers for the evaluation of cellular status. However, whether there exist correlations between these biophysical markers and cellular status (e.g., membrane-associate protein expression is still unknown. To further validate the utility of single-cell electrical properties in cell type classification, Cspecific membrane and σcytoplasm of single PC-3 cells with membrane staining and/or fixation were analyzed and compared in this study. Four subtypes of PC-3 cells were prepared: untreated PC-3 cells, PC-3 cells with anti-EpCAM staining, PC-3 cells with fixation, and fixed PC-3 cells with anti-EpCAM staining. In experiments, suspended single cells were aspirated through microfluidic constriction channels with raw impedance data quantified and translated to Cspecific membrane and σcytoplasm. As to experimental results, significant differences in Cspecific membrane were observed for both live and fixed PC-3 cells with and without membrane staining, indicating that membrane staining proteins can contribute to electrical properties of cellular membranes. In addition, a significant decrease in σcytoplasm was located for PC-3 cells with and without fixation, suggesting that cytoplasm protein crosslinking during the fixation process can alter the cytoplasm conductivity. Overall, we have demonstrated how to classify single cells based on cellular electrical properties.

  7. Problems for the WELS classification of planetary nebula central stars: self-consistent nebular modelling of four candidates

    Science.gov (United States)

    Basurah, Hassan M.; Ali, Alaa; Dopita, Michael A.; Alsulami, R.; Amer, Morsi A.; Alruhaili, A.

    2016-05-01

    We present integral field unit (IFU) spectroscopy and self-consistent photoionization modelling for a sample of four southern Galactic planetary nebulae (PNe) with supposed weak emission-line central stars. The Wide Field Spectrograph on the ANU 2.3 m telescope has been used to provide IFU spectroscopy for NGC 3211, NGC 5979, My 60, and M 4-2 covering the spectral range of 3400-7000 Å. All objects are high-excitation non-Type I PNe, with strong He II emission, strong [Ne V] emission, and weak low-excitation lines. They all appear to be predominantly optically thin nebulae excited by central stars with Teff > 105 K. Three PNe of the sample have central stars which have been previously classified as weak emission-line stars (WELS), and the fourth also shows the characteristic recombination lines of a WELS. However, the spatially resolved spectroscopy shows that rather than arising in the central star, the C IV and N III recombination line emission is distributed in the nebula, and in some cases concentrated in discrete nebular knots. This may suggest that the WELS classification is spurious, and that, rather, these lines arise from (possibly chemically enriched) pockets of nebular gas. Indeed, from careful background subtraction we were able to identify three of the sample as being hydrogen rich O(H)-Type. We have constructed fully self-consistent photoionization models for each object. This allows us to independently determine the chemical abundances in the nebulae, to provide new model-dependent distance estimates, and to place the central stars on the Hertzsprung-Russell diagram. All four PNe have similar initial mass (1.5 < M/M⊙ < 2.0) and are at a similar evolutionary stage.

  8. Classification of Convective and Stratiform Cells in Meteorological Radar Images Using SVM Based on a Textural Analysis

    Institute of Scientific and Technical Information of China (English)

    Abdenasser Djafri; Boualem Haddad

    2014-01-01

    This contribution deals with the discrimination between stratiform and convective cells in meteorological radar images. This study is based on a textural analysis of the latter and their classification using a support vector machine (SVM). First, we apply different textural parameters such as energy, entropy, inertia, and local homogeneity. Through this experience, we identify the different textural features of both the stratiform and convective cells. Then, we use an SVM to find the best discriminating parameter between the two types of clouds. The main goal of this work is to better apply the Palmer and Marshall Z-R relations specific to each type of precipitation.

  9. Note: An automated image analysis method for high-throughput classification of surface-bound bacterial cell motions.

    Science.gov (United States)

    Shen, Simon; Syal, Karan; Tao, Nongjian; Wang, Shaopeng

    2015-12-01

    We present a Single-Cell Motion Characterization System (SiCMoCS) to automatically extract bacterial cell morphological features from microscope images and use those features to automatically classify cell motion for rod shaped motile bacterial cells. In some imaging based studies, bacteria cells need to be attached to the surface for time-lapse observation of cellular processes such as cell membrane-protein interactions and membrane elasticity. These studies often generate large volumes of images. Extracting accurate bacterial cell morphology features from these images is critical for quantitative assessment. Using SiCMoCS, we demonstrated simultaneous and automated motion tracking and classification of hundreds of individual cells in an image sequence of several hundred frames. This is a significant improvement from traditional manual and semi-automated approaches to segmenting bacterial cells based on empirical thresholds, and a first attempt to automatically classify bacterial motion types for motile rod shaped bacterial cells, which enables rapid and quantitative analysis of various types of bacterial motion. PMID:26724085

  10. The problem of the top cell for the micromorph tandem

    Energy Technology Data Exchange (ETDEWEB)

    Platz, R.; Meier, J.; Fischer, D.; Dubail, S.; Shah, A.

    1997-07-01

    A detailed study of the influence of different materials for the amorphous top cell on the stabilized efficiency of amorphous silicon/microcrystalline silicon (micromorph) tandem cells is presented. The authors investigate different amorphous i-layer materials which are applied in cells with varying thicknesses. It is shown that it is preferable to optimize the top cell in order to obtain a high current rather than a high voltage. A simple optical and electrical model is presented which allows one to predict the optimum optical bandgap of the i-layer material of the top cell and to determine its optimum thickness for maximum stabilized efficiency. By means of this model it is shown that the optimum top cell for a total cell current of 26 mA/cm{sup 2} should contain about 2,500 {angstrom} thick i-layer with an optical gap E{sub 04} {approx} 1.8 eV. The model furthermore shows that it is desirable to obtain slightly bottom-limited conditions after degradation in order to maximize the output power. A stabilized efficiency of 10.7% for a micromorph tandem cell has been confirmed by an independent measurement (FhG-ISE). Another such cell yields a stabilized efficiency of 11.2% as measured in their laboratory.

  11. Estimating Rates of Psychosocial Problems in Urban and Poor Children with Sickle Cell Anemia.

    Science.gov (United States)

    Barbarin, Oscar A.; And Others

    1994-01-01

    Examined adjustment problems for children and adolescents with sickle cell anemia (SCA). Parents provided information on social, emotional, academic, and family adjustment of 327 children with SCA. Over 25% of children had emotional adjustment problems in form of internalizing symptoms (anxiety and depression); at least 20% had problems related to…

  12. Radiolabeled red blood cells: status, problems, and prospects

    International Nuclear Information System (INIS)

    Radionuclidic labels for red cells can be divided into two main categories - cohort or pulse labels, and random labels. The random labels are incorporated into circulating cells of all ages and the labeling process is usually carried out in vitro. The red cell labels in predominant use involve random labeling and employ technetium-99m, chromium-51, indium-111, and gallium-68, roughly in that order. The extent of usefulness depends on the properties of the label such as the half-life, decay mode, and in-vivo stability, etc. Labeled cells can be used for red cell survival measurements when the half-life of the radionuclide is sufficiently long. The major portion of this article deals with random labels

  13. Radiolabeled red blood cells: status, problems, and prospects

    Energy Technology Data Exchange (ETDEWEB)

    Srivastava, S.C.

    1983-01-01

    Radionuclidic labels for red cells can be divided into two main categories - cohort or pulse labels, and random labels. The random labels are incorporated into circulating cells of all ages and the labeling process is usually carried out in vitro. The red cell labels in predominant use involve random labeling and employ technetium-99m, chromium-51, indium-111, and gallium-68, roughly in that order. The extent of usefulness depends on the properties of the label such as the half-life, decay mode, and in-vivo stability, etc. Labeled cells can be used for red cell survival measurements when the half-life of the radionuclide is sufficiently long. The major portion of this article deals with random labels.

  14. Classification of follicular cell-derived thyroid cancer by global RNA profiling

    DEFF Research Database (Denmark)

    Rossing, Maria

    2013-01-01

    classifiers that may differentiate malignant from benign thyroid nodules. Molecular classification models based on global RNA profiles from fine-needle aspirations are currently being evaluated; results are preliminary and lack validation in prospective clinical trials. There is no doubt that molecular...

  15. Nasal metastases from renal cell carcinoma are associated with Memorial Sloan-Kettering Cancer Center poor-prognosis classification

    Institute of Scientific and Technical Information of China (English)

    Caroline Victoria Choong; Tiffany Tang; Wen Yee Chay; Christopher Goh; Miah Hiang Tay; Nor Azhari Mohd Zam; Puay Hoon Tan; Min-Han Tan

    2011-01-01

    Unusual sites of metastases are recognized in patients with renai cell carcinoma (RCC). However, the prognostic implications of these sites are not well understood. We used the Memorial Sloan-Kettering Cancer Center (MSKCC) risk classification for metastatic RCC to evaluate 912 consecutive patients with RCC managed at the Singapore General Hospital between 1990 and 2009. Among these patients, 301 had metastases either at diagnosis or during the course of illness. Nasal metastases, all arising from clear cell RCC, were identified histologically in 4 patients (1.3% of those with metastasis). All 4 patients were classified as MSKCC poor prognosis by current risk criteria. Nasal metastases were significantly associated with lung and bone metastases. The frequency of nasal metastases in patients with metastatic RCC is about 1%, occurring predominantly in patients with clear cell RCC. Nasal metastases are associated with poor prognosis as estimated by the MSKCC risk classification, with attendant implications for selection of targeted therapy, and are usually associated with multi-organ dissemination, including concurrent lung and bone involvement.

  16. Assessing corrosion problems in photovoltaic cells via electrochemical stress testing

    Science.gov (United States)

    Shalaby, H.

    1985-01-01

    A series of accelerated electrochemical experiments to study the degradation properties of polyvinylbutyral-encapsulated silicon solar cells has been carried out. The cells' electrical performance with silk screen-silver and nickel-solder contacts was evaluated. The degradation mechanism was shown to be electrochemical corrosion of the cell contacts; metallization elements migrate into the encapsulating material, which acts as an ionic conducting medium. The corrosion products form a conductive path which results in a gradual loss of the insulation characteristics of the encapsulant. The precipitation of corrosion products in the encapsulant also contributes to its discoloration which in turn leads to a reduction in its transparency and the consequent optical loss. Delamination of the encapsulating layers could be attributed to electrochemical gas evolution reactions. The usefulness of the testing technique in qualitatively establishing a reliability difference between metallizations and antireflection coating types is demonstrated.

  17. Characterization of Memory B-Cells from Thymus and its Impact for DLBCL Classification

    DEFF Research Database (Denmark)

    Bergkvist, Kim Steve; Nørgaard, Martin Agge; Bøgsted, Martin;

    2016-01-01

    The rare memory B-cells in thymus are considered the cell of origin for primary mediastinal large B-cell lymphoma (PMBL). The goals for the present study were to characterize the normal memory B-cell compartment in thymus and support its association to primary mediastinal B-cell lymphoma. Seven...... paired human tissue samples from thymus and sternum bone marrow were harvested during cardiac surgery. B-cell subsets were phenotyped by Euroflow standard and FACS-sorted for microarray analysis on the Human Exon 1.0 ST Arrays platform. Differentially expressed genes between thymus and bone marrow memory...... B-cells were identified and correlated to the molecular subclasses of diffuse large B-cell lymphoma. Within thymus, 4% (median, range 2-14%) of the CD45(+) haematopoietic cells were CD19(+) B-cells with a major fraction being CD27(+)/CD38(-) memory B-cells (median 80%, range 76-93%). The bone marrow...

  18. Classification of human natural killer cells based on migration behavior and cytotoxic response.

    Science.gov (United States)

    Vanherberghen, Bruno; Olofsson, Per E; Forslund, Elin; Sternberg-Simon, Michal; Khorshidi, Mohammad Ali; Pacouret, Simon; Guldevall, Karolin; Enqvist, Monika; Malmberg, Karl-Johan; Mehr, Ramit; Önfelt, Björn

    2013-02-21

    Despite intense scrutiny of the molecular interactions between natural killer (NK) and target cells, few studies have been devoted to dissection of the basic functional heterogeneity in individual NK cell behavior. Using a microchip-based, time-lapse imaging approach allowing the entire contact history of each NK cell to be recorded, in the present study, we were able to quantify how the cytotoxic response varied between individual NK cells. Strikingly, approximately half of the NK cells did not kill any target cells at all, whereas a minority of NK cells was responsible for a majority of the target cell deaths. These dynamic cytotoxicity data allowed categorization of NK cells into 5 distinct classes. A small but particularly active subclass of NK cells killed several target cells in a consecutive fashion. These "serial killers" delivered their lytic hits faster and induced faster target cell death than other NK cells. Fast, necrotic target cell death was correlated with the amount of perforin released by the NK cells. Our data are consistent with a model in which a small fraction of NK cells drives tumor elimination and inflammation.

  19. Sourcing human embryos for embryonic stem cell lines: Problems & perspectives

    Directory of Open Access Journals (Sweden)

    Rajvi H Mehta

    2014-01-01

    Full Text Available The ability to successfully derive human embryonic stem cells (hESC lines from human embryos following in vitro fertilization (IVF opened up a plethora of potential applications of this technique. These cell lines could have been successfully used to increase our understanding of human developmental biology, transplantation medicine and the emerging science of regenerative medicine. The main source for human embryos has been ′discarded′ or ′spare′ fresh or frozen human embryos following IVF. It is a common practice to stimulate the ovaries of women undergoing any of the assisted reproductive technologies (ART and retrieve multiple oocytes which subsequently lead to multiple embryos. Of these, only two or maximum of three embryos are transferred while the rest are cryopreserved as per the decision of the couple. In case a couple does not desire to ′cryopreserve′ their embryos then all the embryos remaining following embryo transfer can be considered ′spare′ or if a couple is no longer in need of the ′cryopreserved′ embryos then these also can be considered as ′spare′. But, the question raised by the ethicists is, "what about ′slightly′ over-stimulating a woman to get a few extra eggs and embryos? The decision becomes more difficult when it comes to ′discarded′ embryos. As of today, the quality of the embryos is primarily assessed based on morphology and the rate of development mainly judged by single point assessment. Despite many criteria described in the literature, the quality assessment is purely subjective. The question that arises is on the decision of ′discarding′ embryos. What would be the criteria for discarding embryos and the potential ′use′ of ESC derived from the ′abnormal appearing′ embryos? This paper discusses some of the newer methods to procure embryos for the derivation of embryonic stem cell lines which will respect the ethical concerns but still provide the source material.

  20. Precision automation of cell type classification and sub-cellular fluorescence quantification from laser scanning confocal images

    Directory of Open Access Journals (Sweden)

    Hardy Craig Hall

    2016-02-01

    Full Text Available While novel whole-plant phenotyping technologies have been successfully implemented into functional genomics and breeding programs, the potential of automated phenotyping with cellular resolution is largely unexploited. Laser scanning confocal microscopy has the potential to close this gap by providing spatially highly resolved images containing anatomic as well as chemical information on a subcellular basis. However, in the absence of automated methods, the assessment of the spatial patterns and abundance of fluorescent markers with subcellular resolution is still largely qualitative and time-consuming. Recent advances in image acquisition and analysis, coupled with improvements in microprocessor performance, have brought such automated methods within reach, so that information from thousands of cells per image for hundreds of images may be derived in an experimentally convenient time-frame. Here, we present a MATLAB-based analytical pipeline to 1 segment radial plant organs into individual cells, 2 classify cells into cell type categories based upon random forest classification, 3 divide each cell into sub-regions, and 4 quantify fluorescence intensity to a subcellular degree of precision for a separate fluorescence channel. In this research advance, we demonstrate the precision of this analytical process for the relatively complex tissues of Arabidopsis hypocotyls at various stages of development. High speed and robustness make our approach suitable for phenotyping of large collections of stem-like material and other tissue types.

  1. Morphologic, Molecular, and Taxonomic Evolution of Renal Cell Carcinoma: A Conceptual Perspective With Emphasis on Updates to the 2016 World Health Organization Classification.

    Science.gov (United States)

    Udager, Aaron M; Mehra, Rohit

    2016-10-01

    Molecular and morphologic interrogation has driven a much-needed reexamination of renal cell carcinoma (RCC). Indeed, the recently released 2016 World Health Organization classification now recognizes 12 distinct RCC subtypes, as well as several other emerging/provisional RCC entities. From a clinical perspective, accurate RCC classification may have important implications for patients and their families, including prognostic risk stratification, targeted therapeutics selection, and identification for genetic testing. In this review, we provide a conceptual framework for approaching RCC diagnosis and classification by categorizing RCCs as tumors with clear cytoplasm, papillary architecture, and eosinophilic (oncocytic) cytoplasm. The currently recognized 2016 World Health Organization classification for RCC subtypes is briefly discussed, including new diagnostic entities (clear cell papillary RCC, hereditary leiomyomatosis and RCC-associated RCC, succinate dehydrogenase-deficient RCC, tubulocystic RCC, and acquired cystic disease-associated RCC) and areas of evolving RCC classification, such as transcription elongation factor B subunit 1 (TCEB1)-mutated RCC/RCC with angioleiomyoma-like stroma/RCC with leiomyomatous stroma, RCC associated with anaplastic lymphoma receptor tyrosine kinase (ALK) gene rearrangement, thyroidlike follicular RCC, and RCC in neuroblastoma survivors. For each RCC subtype, relevant clinical, molecular, gross, and microscopic findings are reviewed, and ancillary studies helpful for its differential diagnosis are presented, providing a practical approach to modern RCC classification. PMID:27684973

  2. Analytical solution and experimental validation of the energy management problem for fuel cell hybrid vehicles

    NARCIS (Netherlands)

    Hoppenbrouwers, Stijn; Grimminck, M.; Bosch, P.P.J. van den; Veenhuizen, Bram; Tazelaar, Edwin

    2011-01-01

    The objective of an energy management strategy for fuel cell hybrid propulsion systems is to minimize the fuel needed to provide the required power demand. This minimization is defined as an optimization problem. Methods such as dynamic programming numerically solve this optimization problem. Strate

  3. Radiological and 'Imaging' methods in TNM classification of non-small-cell lung cancer

    International Nuclear Information System (INIS)

    Lung cancer is the most common worldwide malignant disease according to its incidence and mortality. The aim of our study was to evaluate the diagnostic value of the radiological and imaging methods, according to the TNM classification, compared to postoperative histological diagnosis. Thirty-seven patients with pulmonary carcinoma were studied prospectively using native chest radiography (PA and LL view), computed tomography (CT) and magnetic resonance imaging (MRI) during ten days before thoracotomy. Radiological and imaging findings were reviewed separately and results were compared with surgical and pathohistological findings on the basis of the TNM classification. All patients underwent chest x-rays, CT was performed in 36 patients and MRI in 12 of them. Imaging methods (CT and MRI) showed more accuracy in sensitivity and specificity compared with the native chest radiography in a great percentage. Generally no statistically significant differences were found between the two imagining methods for the evaluation of tumour extent (T) or lymph node metastases (N). MRI was slightly superior to CT in determination of the chest wall extent of the tumour. In the conclusion CT remains the imaging modality og choice both for assessing patients with abnormal chest radiographs suspected of having lung cancer, and in staging patients with histologically proven pulmonary carcinoma.

  4. Identification of immune cell infiltration in hematoxylin-eosin stained breast cancer samples: texture-based classification of tissue morphologies

    Science.gov (United States)

    Turkki, Riku; Linder, Nina; Kovanen, Panu E.; Pellinen, Teijo; Lundin, Johan

    2016-03-01

    The characteristics of immune cells in the tumor microenvironment of breast cancer capture clinically important information. Despite the heterogeneity of tumor-infiltrating immune cells, it has been shown that the degree of infiltration assessed by visual evaluation of hematoxylin-eosin (H and E) stained samples has prognostic and possibly predictive value. However, quantification of the infiltration in H and E-stained tissue samples is currently dependent on visual scoring by an expert. Computer vision enables automated characterization of the components of the tumor microenvironment, and texture-based methods have successfully been used to discriminate between different tissue morphologies and cell phenotypes. In this study, we evaluate whether local binary pattern texture features with superpixel segmentation and classification with support vector machine can be utilized to identify immune cell infiltration in H and E-stained breast cancer samples. Guided with the pan-leukocyte CD45 marker, we annotated training and test sets from 20 primary breast cancer samples. In the training set of arbitrary sized image regions (n=1,116) a 3-fold cross-validation resulted in 98% accuracy and an area under the receiver-operating characteristic curve (AUC) of 0.98 to discriminate between immune cell -rich and - poor areas. In the test set (n=204), we achieved an accuracy of 96% and AUC of 0.99 to label cropped tissue regions correctly into immune cell -rich and -poor categories. The obtained results demonstrate strong discrimination between immune cell -rich and -poor tissue morphologies. The proposed method can provide a quantitative measurement of the degree of immune cell infiltration and applied to digitally scanned H and E-stained breast cancer samples for diagnostic purposes.

  5. Machine learning-based classification of diffuse large B-cell lymphoma patients by eight gene expression profiles.

    Science.gov (United States)

    Zhao, Shuangtao; Dong, Xiaoli; Shen, Wenzhi; Ye, Zhen; Xiang, Rong

    2016-05-01

    Gene expression profiling (GEP) had divided the diffuse large B-cell lymphoma (DLBCL) into molecular subgroups: germinal center B-cell like (GCB), activated B-cell like (ABC), and unclassified (UC) subtype. However, this classification with prognostic significance was not applied into clinical practice since there were more than 1000 genes to detect and interpreting was difficult. To classify cancer samples validly, eight significant genes (MYBL1, LMO2, BCL6, MME, IRF4, NFKBIZ, PDE4B, and SLA) were selected in 414 patients treated with CHOP/R-CHOP chemotherapy from Gene Expression Omnibus (GEO) data sets. Cutoffs for each gene were obtained using receiver-operating characteristic curves (ROC) new model based on the support vector machine (SVM) estimated the probability of membership into one of two subgroups: GCB and Non-GCB (ABC and UC). Furtherly, multivariate analysis validated the model in another two cohorts including 855 cases in all. As a result, patients in the training and validated cohorts were stratified into two subgroups with 94.0%, 91.0%, and 94.4% concordance with GEP, respectively. Patients with Non-GCB subtype had significantly poorer outcomes than that with GCB subtype, which agreed with the prognostic power of GEP classification. Moreover, the similar prognosis received in the low (0-2) and high (3-5) IPI scores group demonstrated that the new model was independent of IPI as well as GEP method. In conclusion, our new model could stratify DLBCL patients with CHOP/R-CHOP regimen matching GEP subtypes effectively. PMID:26869285

  6. The Many Elements of Traditional Fire Knowledge: Synthesis, Classification, and Aids to Cross-cultural Problem Solving in Fire-dependent Systems Around the World

    Directory of Open Access Journals (Sweden)

    Mary R. Huffman

    2013-12-01

    Full Text Available I examined the hypothesis that traditional social-ecological fire systems around the world include common elements of traditional fire knowledge (TFK. I defined TFK as fire-related knowledge, beliefs, and practices that have been developed and applied on specific landscapes for specific purposes by long time inhabitants. In all, 69 distinct elements of TFK were documented in 35 studies, including accounts from 27 countries on 6 continents. On all 6 continents, 21 elements (30% were recorded, and 46 elements (67% were recorded on 4 or more continents. The top 12 most commonly reported elements, which were included in > 50 % of the studies, were fire effects on vegetation; season of the year; fire effects on animals; moisture of live or dead fuels; the onset or end of rainy season, dry season, or timing of rain; burning illegal or regulated by central government; fire intensity, heat output, i.e., hot or cool fire; frequency, return interval, time since fire; fire control; firebreaks, barriers; consequences of not burning; and plant or animal phenology. Traditional fire knowledge was multifaceted: 13 studies included more than 25 elements. Practicing traditional fire management also entails understanding the ways in which multiple elements interact and influence one another. Three classification systems provide insight into TFK systems, including typologies of agro-ecological type, pre- and postindustrial anthropological fire regimes, and viability status. The longevity of traditional fire knowledge and practice faces serious threats at precisely the time when climate change promises disruptions in fire activity that will be problematic for indigenous and nonindigenous societies alike. Central governments tend to adopt the pathological response of command and control during times of fire increase, further constraining traditional fire management. The opposite is needed: to seriously engage traditional practitioners in solving fire problems of

  7. Classification of biological cells using a sound wave based flow cytometer

    Science.gov (United States)

    Strohm, Eric M.; Gnyawali, Vaskar; Van De Vondervoort, Mia; Daghighi, Yasaman; Tsai, Scott S. H.; Kolios, Michael C.

    2016-03-01

    A flow cytometer that uses sound waves to determine the size of biological cells is presented. In this system, a microfluidic device made of polydimethylsiloxane (PDMS) was developed to hydrodynamically flow focus cells in a single file through a target area. Integrated into the microfluidic device was an ultrasound transducer with a 375 MHz center frequency, aligned opposite the transducer was a pulsed 532 nm laser focused into the device by a 10x objective. Each passing cell was insonfied with a high frequency ultrasound pulse, and irradiated with the laser. The resulting ultrasound and photoacoustic waves from each cell were analyzed using signal processing methods, where features in the power spectra were compared to theoretical models to calculate the cell size. Two cell lines with different size distributions were used to test the system: acute myeloid leukemia cells (AML) and melanoma cells. Over 200 cells were measured using this system. The average calculated diameter of the AML cells was 10.4 +/- 2.5 μm using ultrasound, and 11.4 +/- 2.3 μm using photoacoustics. The average diameter of the melanoma cells was 16.2 +/- 2.9 μm using ultrasound, and 18.9 +/- 3.5 μm using photoacoustics. The cell sizes calculated using ultrasound and photoacoustic methods agreed with measurements using a Coulter Counter, where the AML cells were 9.8 +/- 1.8 μm and the melanoma cells were 16.0 +/- 2.5 μm. These results demonstrate a high speed method of assessing cell size using sound waves, which is an alternative method to traditional flow cytometry techniques.

  8. Comparative study of shape, intensity and texture features and support vector machine for white blood cell classification

    Directory of Open Access Journals (Sweden)

    Mehdi Habibzadeh

    2013-04-01

    Full Text Available The complete blood count (CBC is widely used test for counting and categorizing various peripheral particles in the blood. The main goal of the paper is to count and classify white blood cells (leukocytes in microscopic images into five major categories using features such as shape, intensity and texture features. The first critical step of counting and classification procedure involves segmentation of individual cells in cytological images of thin blood smears. The quality of segmentation has significant impact on the cell type identification, but poor quality, noise, and/or low resolution images make segmentation less reliable. We analyze the performance of our system for three different sets of features and we determine that the best performance is achieved by wavelet features using the Dual-Tree Complex Wavelet Transform (DT-CWT which is based on multi-resolution characteristics of the image. These features are combined with the Support Vector Machine (SVM which classifies white blood cells into their five primary types. This approach was validated with experiments conducted on digital normal blood smear images with low resolution.

  9. Convergence of Cell Based Finite Volume Discretizations for Problems of Control in the Conduction Coefficients

    DEFF Research Database (Denmark)

    Evgrafov, Anton; Gregersen, Misha Marie; Sørensen, Mads Peter

    2011-01-01

    design, in particular shape and topology optimization, and are most often solved numerically utilizing a finite element approach. Within the FV framework for control in the coefficients problems the main difficulty we face is the need to analyze the convergence of fluxes defined on the faces of cells......We present a convergence analysis of a cell-based finite volume (FV) discretization scheme applied to a problem of control in the coefficients of a generalized Laplace equation modelling, for example, a steady state heat conduction. Such problems arise in applications dealing with geometric optimal...... provide characterizations of limit points, with respect to FV mesh size, of globally optimal solutions and two types of stationary points to the discretized problems. We illustrate the practical behaviour of our cell-based FV discretization algorithm on a numerical example....

  10. A problem-solving education intervention in caregivers and patients during allogeneic hematopoietic stem cell transplantation.

    Science.gov (United States)

    Bevans, Margaret; Wehrlen, Leslie; Castro, Kathleen; Prince, Patricia; Shelburne, Nonniekaye; Soeken, Karen; Zabora, James; Wallen, Gwenyth R

    2014-05-01

    The aim of this study was to determine the effect of problem-solving education on self-efficacy and distress in informal caregivers of allogeneic hematopoietic stem cell transplantation patients. Patient/caregiver teams attended three 1-hour problem-solving education sessions to help cope with problems during hematopoietic stem cell transplantation. Primary measures included the Cancer Self-Efficacy Scale-transplant and Brief Symptom Inventory-18. Active caregivers reported improvements in self-efficacy (p education; caregiver responders also reported better health outcomes such as fatigue. The effect of problem-solving education on self-efficacy and distress in hematopoietic stem cell transplantation caregivers supports its inclusion in future interventions to meet the multifaceted needs of this population.

  11. Cell morphology classification in phase contrast microscopy image reducing halo artifact

    Science.gov (United States)

    Kang, Mi-Sun; Song, Soo-Min; Lee, Hana; Kim, Myoung-Hee

    2012-03-01

    Since the morphology of tumor cells is a good indicator of their invasiveness, we used time-lapse phase-contrast microscopy to examine the morphology of tumor cells. This technique enables long-term observation of the activity of live cells without photobleaching and phototoxicity which is common in other fluorescence-labeled microscopy. However, it does have certain drawbacks in terms of imaging. Therefore, we first corrected for non-uniform illumination artifacts and then we use intensity distribution information to detect cell boundary. In phase contrast microscopy image, cell is normally appeared as dark region surrounded by bright halo ring. Due to halo artifact is minimal around the cell body and has non-symmetric diffusion pattern, we calculate cross sectional plane which intersects center of each cell and orthogonal to first principal axis. Then, we extract dark cell region by analyzing intensity profile curve considering local bright peak as halo area. Finally, we examined cell morphology to classify tumor cells as malignant and benign.

  12. Discrimination and classification of acute lymphoblastic leukemia cells by Raman spectroscopy

    Science.gov (United States)

    Managò, Stefano; Valente, Carmen; Mirabelli, Peppino; De Luca, Anna Chiara

    2015-05-01

    Currently, a combination of technologies is typically required to identify and classify leukemia cells. These methods often lack the specificity and sensitivity necessary for early and accurate diagnosis. Here, we demonstrate the use of Raman spectroscopy to identify normal B cells, collected from healthy patients, and three ALL cell lines (RS4;11, REH and MN60 at different differentiation level, respectively). Raman markers associated with DNA and protein vibrational modes have been identified that exhibit excellent discriminating power for leukemia cell identification. Principal Component Analysis was finally used to confirm the significance of these markers for identify leukemia cells and classifying the data. The obtained results indicate a sorting accuracy of 96% between the three leukemia cell lines.

  13. Thymic selection of T-cell receptors as an extreme value problem

    CERN Document Server

    Kosmrlj, Andrej; Kardar, Mehran; Shakhnovich, Eugene I

    2009-01-01

    T lymphocytes (T cells) orchestrate adaptive immune responses upon activation. T cell activation requires sufficiently strong binding of T cell receptors (TCRs) on their surface to short peptides (p) derived from foreign proteins, which are bound to major histocompatibility (MHC) gene products (displayed on antigen presenting cells). A diverse and self-tolerant T cell repertoire is selected in the thymus. We map thymic selection processes to an extreme value problem and provide an analytic expression for the amino acid compositions of selected TCRs (which enable its recognition functions).

  14. Characterization and Classification of Adherent Cells in Monolayer Culture using Automated Tracking and Evolutionary Algorithms

    OpenAIRE

    Zhang, Z.; Bedder, M; Smith, S L; Walker, D; Shabir, S.; Southgate, J

    2016-01-01

    This paper presents a novel method for tracking and characterizing adherent cells in monolayer culture. A system of cell tracking employing computer vision techniques was applied to time-lapse videos of replicate normal human uro-epithelial cell cultures exposed to different concentrations of adenosine triphosphate (ATP) and a selective purinergic P2X antagonist (PPADS), acquired over a 24hour period. Subsequent analysis following feature extraction demonstrated the ability of the technique t...

  15. Competence Classification of Cumulus and Granulosa Cell Transcriptome in Embryos Matched by Morphology and Female Age

    DEFF Research Database (Denmark)

    Borup, Rehannah; Thuesen, Lea Langhoff; Andersen, Claus Yding;

    2016-01-01

    OBJECTIVE: By focussing on differences in the mural granulosa cell (MGC) and cumulus cell (CC) transcriptomes from follicles resulting in competent (live birth) and non-competent (no pregnancy) oocytes the study aims on defining a competence classifier expression profile in the two cellular...

  16. Classification of large circulating tumor cells isolated with ultra-high throughput microfluidic Vortex technology.

    Science.gov (United States)

    Che, James; Yu, Victor; Dhar, Manjima; Renier, Corinne; Matsumoto, Melissa; Heirich, Kyra; Garon, Edward B; Goldman, Jonathan; Rao, Jianyu; Sledge, George W; Pegram, Mark D; Sheth, Shruti; Jeffrey, Stefanie S; Kulkarni, Rajan P; Sollier, Elodie; Di Carlo, Dino

    2016-03-15

    Circulating tumor cells (CTCs) are emerging as rare but clinically significant non-invasive cellular biomarkers for cancer patient prognosis, treatment selection, and treatment monitoring. Current CTC isolation approaches, such as immunoaffinity, filtration, or size-based techniques, are often limited by throughput, purity, large output volumes, or inability to obtain viable cells for downstream analysis. For all technologies, traditional immunofluorescent staining alone has been employed to distinguish and confirm the presence of isolated CTCs among contaminating blood cells, although cells isolated by size may express vastly different phenotypes. Consequently, CTC definitions have been non-trivial, researcher-dependent, and evolving. Here we describe a complete set of objective criteria, leveraging well-established cytomorphological features of malignancy, by which we identify large CTCs. We apply the criteria to CTCs enriched from stage IV lung and breast cancer patient blood samples using the High Throughput Vortex Chip (Vortex HT), an improved microfluidic technology for the label-free, size-based enrichment and concentration of rare cells. We achieve improved capture efficiency (up to 83%), high speed of processing (8 mL/min of 10x diluted blood, or 800 μL/min of whole blood), and high purity (avg. background of 28.8±23.6 white blood cells per mL of whole blood). We show markedly improved performance of CTC capture (84% positive test rate) in comparison to previous Vortex designs and the current FDA-approved gold standard CellSearch assay. The results demonstrate the ability to quickly collect viable and pure populations of abnormal large circulating cells unbiased by molecular characteristics, which helps uncover further heterogeneity in these cells. PMID:26863573

  17. Microarray-based classification of diffuse large B-cell lymphoma

    DEFF Research Database (Denmark)

    Poulsen, Christian Bjørn; Borup, Rehannah; Nielsen, Finn Cilius;

    2005-01-01

    OBJECTIVE: Hierarchical clusterings of diffuse large B-cell lymphoma (DLBCL) based on gene expression signatures have previously been used to classify DLBCL into Germinal Center B-cell (GCB) and Activated B-cell (ABC) types. To examine if it was feasible to perform a cross-platform validation on...... of classifier genes was generated by analysis of 34 patients that were consistently classified as GCB or ABC in the above analyses. Seventy-eight genes were selected and demonstrated on two previously published data sets (Shipp et al. Nat Med 2002;8:68-74 and Houldsworth et al. Blood 2004...

  18. Spectral study and classification of worldwide locations considering several multijunction solar cell technologies

    OpenAIRE

    Nuñez Júdez, Rubén; Jin, Chen; Victoria Pérez, Marta; Domínguez Domínguez, César; Askins, Stephen; Herrero Martin, Rebeca; Antón Hernández, Ignacio; Sala Pano, Gabriel

    2016-01-01

    Multi-junction solar cells are widely used in high-concentration photovoltaic systems (HCPV) attaining the highest efficiencies in photovoltaic energy generation. This technology is more dependent on the spectral variations of the impinging Direct Normal Irradiance (DNI) than conventional photovoltaics based on silicon solar cells and consequently demands a deeper knowledge of the solar resource characteristics. This article explores the capabilities of spectral indexes, namely, spectral matc...

  19. Sub classification and targeted characterization of prophage-encoded two-component cell lysis cassette

    Indian Academy of Sciences (India)

    K V Srividhya; S Krishnaswamy

    2007-08-01

    Bacteriophage induced lysis of host bacterial cell is mediated by a two component cell lysis cassette comprised of holin and lysozyme. Prophages are integrated forms of bacteriophages in bacterial genomes providing a repertoire for bacterial evolution. Analysis using the prophage database (http://bicmku.in:8082) constructed by us showed 47 prophages were associated with putative two component cell lysis genes. These proteins cluster into four different subgroups. In this process, a putative holin (essd) and endolysin (ybcS), encoded by the defective lambdoid prophage DLP12 was found to be similar to two component cell lysis genes in functional bacteriophages like p21 and P1. The holin essd was found to have a characteristic dual start motif with two transmembrane regions and C-terminal charged residues as in class II holins. Expression of a fusion construct of essd in Escherichia coli showed slow growth. However, under appropriate conditions, this protein could be over expressed and purified for structure function studies. The second component of the cell lysis cassette, ybcS, was found to have an N-terminal SAR (Signal Arrest Release) transmembrane domain. The construct of ybcS has been over expressed in E. coli and the purified protein was functional, exhibiting lytic activity against E. coli and Salmonella typhi cell wall substrate. Such targeted sequence-structure-function characterization of proteins encoded by cryptic prophages will help understand the contribution of prophage proteins to bacterial evolution.

  20. Classification of solar cells according to mechanisms of charge separation and charge collection.

    Science.gov (United States)

    Kirchartz, Thomas; Bisquert, Juan; Mora-Sero, Ivan; Garcia-Belmonte, Germà

    2015-02-14

    In the last decade, photovoltaics (PV) has experienced an important transformation. Traditional solar cells formed by compact semiconductor layers have been joined by new kinds of cells that are constituted by a complex mixture of organic, inorganic and solid or liquid electrolyte materials, and rely on charge separation at the nanoscale. Recently, metal organic halide perovskites have appeared in the photovoltaic landscape showing large conversion efficiencies, and they may share characteristics of the two former types. In this paper we provide a general description of the photovoltaic mechanisms of the single absorber solar cell types, combining all-inorganic, hybrid and organic cells into a single framework. The operation of the solar cell relies on a number of internal processes that exploit internal charge separation and overall charge collection minimizing recombination. There are two main effects to achieve the required efficiency, first to exploit kinetics at interfaces, favouring the required forward process, and second to take advantage of internal electrical fields caused by a built-in voltage and by the distribution of photogenerated charges. These principles represented by selective contacts, interfaces and the main energy diagram, form a solid base for the discussion of the operation of future types of solar cells. Additional effects based on ferroelectric polarization and ionic drift provide interesting prospects for investigating new PV effects mainly in the perovskite materials.

  1. Thymic Selection of T-Cell Receptors as an Extreme Value Problem

    Science.gov (United States)

    Kosmrlj, Andrej; Chakraborty, Arup K.; Kardar, Mehran; Shakhnovich, Eugene I.

    2010-03-01

    T lymphocytes (T cells) orchestrate adaptive immune responses that clear pathogens from infected hosts. T cells recognize short peptides (p) derived from foreign proteins, which are bound to major histocompatibility complex (MHC) gene products (displayed on antigen- presenting cells). Recognition occurs when T cell receptor (TCR) proteins expressed on T cells bind sufficiently strongly to antigen- derived pMHC complexes on the surface of antigen-presenting cells. A diverse repertoire of self-tolerant TCR sequences is shaped during development of T cells in the thymus by processes called positive and negative selection. We map thymic selection processes to an extreme value problem and provide analytic expression for the amino acid composition of selected TCR sequences (which enable its recognition functions).

  2. A Multi-layer Hybrid Framework for Dimensional Emotion Classification

    NARCIS (Netherlands)

    Nicolaou, Mihalis A.; Gunes, Hatice; Pantic, Maja

    2011-01-01

    This paper investigates dimensional emotion prediction and classification from naturalistic facial expressions. Similarly to many pattern recognition problems, dimensional emotion classification requires generating multi-dimensional outputs. To date, classification for valence and arousal dimensions

  3. Ovarian malignant germ cell tumors: cellular classification and clinical and imaging features.

    Science.gov (United States)

    Shaaban, Akram M; Rezvani, Maryam; Elsayes, Khaled M; Baskin, Henry; Mourad, Amr; Foster, Bryan R; Jarboe, Elke A; Menias, Christine O

    2014-01-01

    Ovarian malignant germ cell tumors (OMGCTs) are heterogeneous tumors that are derived from the primitive germ cells of the embryonic gonad. OMGCTs are rare, accounting for about 2.6% of all ovarian malignancies, and typically manifest in adolescence, usually with abdominal pain, a palpable mass, and elevated serum tumor marker levels, which may serve as an adjunct in the initial diagnosis, monitoring during therapy, and posttreatment surveillance. Dysgerminoma, the most common malignant germ cell tumor, usually manifests as a solid mass. Immature teratomas manifest as a solid mass with scattered foci of fat and calcifications. Yolk sac tumors usually manifest as a mixed solid and cystic mass. Capsular rupture or the bright dot sign, a result of increased vascularity and the formation of small vascular aneurysms, may be present. Embryonal carcinomas and polyembryomas rarely manifest in a pure form and are more commonly part of a mixed germ cell tumor. Some OMGCTs have characteristic features that allow a diagnosis to be confidently made, whereas others have nonspecific features, which make them difficult to diagnose. However, imaging features, the patient's age at presentation, and tumor markers may help establish a reasonable differential diagnosis. Malignant ovarian germ cell tumors spread in the same manner as epithelial ovarian neoplasms but are more likely to involve regional lymph nodes. Preoperative imaging may depict local extension, peritoneal disease, and distant metastases. Suspicious areas may be sampled during surgery. Because OMGCTs are almost always unilateral and are chemosensitive, fertility-sparing surgery is the standard of care. PMID:24819795

  4. Physiological problems in patients undergoing autologous and allogeneic hematopoietic stem cell transplantation

    Directory of Open Access Journals (Sweden)

    Sevgisun Kapucu

    2014-01-01

    Full Text Available Objective: Stem cell transplantation is usually performed in an effort to extend the patient′s life span and to improve their quality of life. This study was conducted to determine the postoperative physiological effects experienced by patients who had undergone autologous and allogeneic stem cell transplantation. Methods: The research is a descriptive study conducted with a sample of 60 patients at Stem Cell Transplantation Units in Ankara. Percentile calculation and chi-square tests were used to evaluate the data. Results: When a comparison was made between patients who had undergone allogeneic Hematopoietic stem cell transplantation (HSCT and those who had undergone autologous HSCT, results indicated that problems occurred more often for the allogeneic HSCT patients. The problems included: Digestion (94.3%, dermatological (76.7%, cardiac and respiratory (66.7%, neurological (66.7%, eye (56.7%, infections (26.7% and Graft Versus Host Disease (5 patients. Furthermore, the problems with pain (50%, numbness and tingling (40%, and speech disorders (3 patients were observed more often in autologous BMT patients. Conclusion: Autologous and allogeneic patients experienced most of physical problems due to they receive high doses of chemotherapy. Therefore, it is recommended that an interdisciplinary support team approach should be usedtohelp reduce and manage the problems that may arise during patient care.

  5. PN solutions for the slowing-down and the cell calculation problems in plane geometry

    International Nuclear Information System (INIS)

    In this work PN solutions for the slowing-down and cell problems in slab geometry are developed. To highlight the main contributions of this development, one can mention: the new particular solution developed for the PN method applied to the slowing-down problem in the multigroup model, originating a new class of polynomials denominated Chandrasekhar generalized polynomials; the treatment of a specific situation, known as a degeneracy, arising from a particularity in the group constants and the first application of the PN method, for arbitrary N, in criticality calculations at the cell level reported in literature. (author)

  6. On some transmission problems set in a biological cell, analysis and resolution

    Science.gov (United States)

    Labbas, Rabah; Lemrabet, Keddour; Limam, Kheira; Medeghri, Ahmed; Meisner, Maëlis

    2015-10-01

    Some transmission problems are set in bodies with a crown of small thickness ε > 0. For instance, those concerning the conductivity in the biological cell. By a natural change of variables, we transform them in transmission problems set in two cylindrical bodies ] - ∞, 0 [ × ] - π, π [ and ] 0, δ [ × ] - π, π [ (where δ = ln ⁡ (1 + ε)) and then, in some general elliptic abstract differential equations (Pδ) δ > 0. The goal of this work is to give a complete study of these problems (Pδ) δ > 0 for every δ > 0. Existence, uniqueness and maximal regularity results are obtained for the classical solutions essentially by using the semigroups theory.

  7. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-07

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  8. Automated classification and enhanced characterization of circulating tumor cells by image cytometry

    NARCIS (Netherlands)

    Scholtens, T.M.

    2012-01-01

    Enumeration and characterization of circulating tumor cells (CTC) is an emerging tool for the disease management of patients with metastatic carcinomas. CTC are correlated to progression free- and overall survival in several types of metastatic cancers, and can be used to predict therapy response. W

  9. Whole cell fatty acid analysis as a tool for classification of phytopathogenic pseudomonas bacteria.

    NARCIS (Netherlands)

    Janse, J.D.

    1992-01-01

    In this thesis some members of the plant pathogenic bacterial genus Pseudomonas have been studied. Conventional morphological, biochemical, physiological and pathogenitcity tests as well as a 'finger-print' technique, viz. automated whole cell fatty acid analysis, were used. The taxonomy of the plan

  10. The future of general classification

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2013-01-01

    Discusses problems related to accessing multiple collections using a single retrieval language. Surveys the concepts of interoperability and switching language. Finds that mapping between more indexing languages always will be an approximation. Surveys the issues related to general classification...... and contrasts that to special classifications. Argues for the use of general classifications to provide access to collections nationally and internationally. © 2003 by The Haworth Press, Inc. All rights reserved....

  11. A Mathematical Programming Model for Cell Formation Problem with Machine Replication

    Directory of Open Access Journals (Sweden)

    Reza Raminfar

    2013-01-01

    Full Text Available Cell formation (CF is a crucial aspect in the design of cellular manufacturing (CM systems. This paper develops a comprehensive mathematical programming model for the cell formation problem, where product demands, cell size limits, sequence of operations, multiple units of identical machines, machine capacity, or machine cost are all considered. In this model, the intercell moves are restricted to be unidirectional from one cell to the downstream cells, without backtracking. The proposed model is investigated through several numerical examples. To evaluate the solution quality of the proposed model, it is compared with some well-known cell formation methods from the literature, by using group capability index (GCI as a performance measure. The results and comparisons indicate that the proposed model produces solution with a higher performance.

  12. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine.

    Science.gov (United States)

    Simeon, Vittorio; Todoerti, Katia; La Rocca, Francesco; Caivano, Antonella; Trino, Stefania; Lionetti, Marta; Agnelli, Luca; De Luca, Luciana; Laurenzana, Ilaria; Neri, Antonino; Musto, Pellegrino

    2015-07-30

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL).

  13. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine

    Directory of Open Access Journals (Sweden)

    Vittorio Simeon

    2015-07-01

    Full Text Available Primary plasma cell leukemia (pPCL is a rare and aggressive variant of multiple myeloma (MM which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL.

  14. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine.

    Science.gov (United States)

    Simeon, Vittorio; Todoerti, Katia; La Rocca, Francesco; Caivano, Antonella; Trino, Stefania; Lionetti, Marta; Agnelli, Luca; De Luca, Luciana; Laurenzana, Ilaria; Neri, Antonino; Musto, Pellegrino

    2015-01-01

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL). PMID:26263974

  15. Molecular Classification and Pharmacogenetics of Primary Plasma Cell Leukemia: An Initial Approach toward Precision Medicine

    Science.gov (United States)

    Simeon, Vittorio; Todoerti, Katia; La Rocca, Francesco; Caivano, Antonella; Trino, Stefania; Lionetti, Marta; Agnelli, Luca; De Luca, Luciana; Laurenzana, Ilaria; Neri, Antonino; Musto, Pellegrino

    2015-01-01

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, added to the pharmacogenetic profile of new and old agents in the analysis of efficacy and safety, could contribute to help clinical decisions move toward a precision medicine and a better clinical outcome for these patients. In this review, we describe the available literature concerning the genomic characterization and pharmacogenetics of plasma cell leukemia (PCL). PMID:26263974

  16. Molecular classification and pharmacogenetics of primary plasma cell leukemia: an initial approach toward precision medicine

    OpenAIRE

    Vittorio Simeon; Katia Todoerti; Francesco La Rocca; Antonella Caivano; Stefania Trino; Marta Lionetti; Luca Agnelli; Luciana De Luca; Ilaria Laurenzana; Antonino Neri; Pellegrino Musto

    2015-01-01

    Primary plasma cell leukemia (pPCL) is a rare and aggressive variant of multiple myeloma (MM) which may represent a valid model for high-risk MM. This disease is associated with a very poor prognosis, and unfortunately, it has not significantly improved during the last three decades. New high-throughput technologies have allowed a better understanding of the molecular basis of this disease and moved toward risk stratification, providing insights for targeted therapy studies. This knowledge, ...

  17. Problem-Based Learning in an Eleventh Grade Chemistry Class: "Factors Affecting Cell Potential"

    Science.gov (United States)

    Tarhan, Leman; Acar, Burcin

    2007-01-01

    The purpose of this research study was to examine the effectiveness of problem-based learning (PBL) on eleventh grade students' understanding of "The effects of temperature, concentration and pressure on cell potential" and also their social skills. Stratified randomly selected control and experimental groups with 20 students each were used in…

  18. Problem-Solving Test: RNA and Protein Synthesis in Bacteriophage-Infected "E. coli" Cells

    Science.gov (United States)

    Szeberenyi, Jozsef

    2008-01-01

    The classic experiment presented in this problem-solving test was designed to identify the template molecules of translation by analyzing the synthesis of phage proteins in "Escherichia coli" cells infected with bacteriophage T4. The work described in this test led to one of the most seminal discoveries of early molecular biology: it dealt a…

  19. Hubble Classification

    Science.gov (United States)

    Murdin, P.

    2000-11-01

    A classification scheme for galaxies, devised in its original form in 1925 by Edwin P Hubble (1889-1953), and still widely used today. The Hubble classification recognizes four principal types of galaxy—elliptical, spiral, barred spiral and irregular—and arranges these in a sequence that is called the tuning-fork diagram....

  20. Image segmentation and classification of white blood cells with the extreme learning machine and the fast relevance vector machine.

    Science.gov (United States)

    Ravikumar, S

    2016-05-01

    White blood cells (WBCs) or leukocytes are an important part of the body's defense against infectious organisms and foreign substances. WBC segmentation is a challenging issue because of the morphological diversity of WBCs and the complex and uncertain background of blood smear images. The standard ELM classification techniques are used for WBC segmentation. The generalization performance of the ELM classifier has not achieved the maximum nearest accuracy of image segmentation. This paper gives a novel technique for WBC detection based on the fast relevance vector machine (Fast-RVM). Firstly, astonishingly sparse relevance vectors (RVs) are obtained while fitting the histogram by RVM. Next, the relevant required threshold value is directly sifted from these limited RVs. Finally, the entire connective WBC regions are segmented from the original image. The proposed method successfully works for WBC detection, and effectively reduces the effects brought about by illumination and staining. To achieve the maximum accuracy of the RVM classifier, we design a search for the best value of the parameters that tune its discriminant function, and upstream by looking for the best subset of features that feed the classifier. Therefore, this proposed RVM method effectively works for WBC detection, and effectively reduces the computational time and preserves the images.

  1. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre;

    as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

  2. Improving Student Question Classification

    Science.gov (United States)

    Heiner, Cecily; Zachary, Joseph L.

    2009-01-01

    Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…

  3. A reliable Raman-spectroscopy-based approach for diagnosis, classification and follow-up of B-cell acute lymphoblastic leukemia

    Science.gov (United States)

    Managò, Stefano; Valente, Carmen; Mirabelli, Peppino; Circolo, Diego; Basile, Filomena; Corda, Daniela; de Luca, Anna Chiara

    2016-04-01

    Acute lymphoblastic leukemia type B (B-ALL) is a neoplastic disorder that shows high mortality rates due to immature lymphocyte B-cell proliferation. B-ALL diagnosis requires identification and classification of the leukemia cells. Here, we demonstrate the use of Raman spectroscopy to discriminate normal lymphocytic B-cells from three different B-leukemia transformed cell lines (i.e., RS4;11, REH, MN60 cells) based on their biochemical features. In combination with immunofluorescence and Western blotting, we show that these Raman markers reflect the relative changes in the potential biological markers from cell surface antigens, cytoplasmic proteins, and DNA content and correlate with the lymphoblastic B-cell maturation/differentiation stages. Our study demonstrates the potential of this technique for classification of B-leukemia cells into the different differentiation/maturation stages, as well as for the identification of key biochemical changes under chemotherapeutic treatments. Finally, preliminary results from clinical samples indicate high consistency of, and potential applications for, this Raman spectroscopy approach.

  4. Main Problems and Countermeasures in Classification and Recycling of Municipal Waste in China%我国城市生活垃圾分类回收工作中存在的主要问题及对策

    Institute of Scientific and Technical Information of China (English)

    徐曼

    2012-01-01

    Based on methods of municipal garbage classification and the situation of the implementation in our country, the passage analyzes the present problems and causes in classification and recycling of mu- nicipal waste, puts forward some effective and relative countermeasures as well as proposals in classifica- tion and recycling of urban rubbish, pointes out that it's a progressive process of accomplishing effective classification and recycling of urban garbage under the present condition of primary stage of socialism in China.%根据我国城市生活垃圾分类方法与实施现状,分析我国目前城市生活垃圾分类回收中存在的问题及原因,提出了城市生活垃圾分类回收有效实施的相关对策及建议,指出了在目前我国的社会主义初级阶段的国情下,实现城市生活垃圾的有效分类回收是一个循序渐进的过程。

  5. Studies on clonogenic hemopoietic cells of vertebrate in space: problems and perspectives

    Science.gov (United States)

    Domaratskaya, E. I.; Michurina, T. V.; Bueverova, E. I.; Bragina, E. V.; Nikonova, T. A.; Starostin, V. I.; Khrushchov, N. G.

    Hemopoietic tissues were studied in vertebrates launched aboard the Soviet (Russian) biosatellites ("Cosmos-1129, 1514, 1667, 1887 and 2044"; "Bion-10 and 11") between 1980 and 1996. In the bone marrow of rats exposed to spaceflight conditions, a statistically significant decrease in cell number was revealed in the progenitor cell compartment accounting for the compensatory response of granulocyte—macrophage (CFU-gm) and erythrocyte lineages (BFU-e and CFU-e) and in the compartment of multipotent hemopoietic stem cells (CFU-s), which is responsible for the permanent renewal of hemopoietic tissue. The number of stromal fibroblastic progenitors (CFC-f) in the bone marrow of these rats was also reduced. Apparently, changes in the hemopoietic stroma damage the hemopoietic microenvironment and, hence, may be responsible for changes observed in the hemopoietic tissue proper. Attempts were made to develop methods for analyzing morphologically indiscernible clonogenic hemopoietic cells of newts, and studies on the effects of spaceflight factors on these cells were performed. The results showed that the numbers of clonogenic cells in newts of the flight group newts were significantly lower than in control newts. The data obtained are used as the basis for formulating the problems to be studied, drawing up a program for further research on the effects of spaceflight factors on stem and other clonogenic hemopoietic cells, and developing new experimental models for analyzing stem cells, the state of the hemopoietic stroma, etc.

  6. Hematopoietic Stem Cell Transplantation in Adult Sickle Cell Disease: Problems and Solutions

    Directory of Open Access Journals (Sweden)

    Hakan Özdoğu

    2015-09-01

    Full Text Available Sickle cell disease-related organ injuries cannot be prevented despite hydroxyurea use, infection prophylaxis, and supportive therapies. As a consequence, disease-related mortality reaches 14% in adolescents and young adults. Hematopoietic stem cell transplantation is a unique curative therapeutic approach for sickle cell disease. Myeloablative allogeneic hematopoietic stem cell transplantation is curative for children with sickle cell disease. Current data indicate that long-term disease-free survival is about 90% and overall survival about 95% after transplantation. However, it is toxic in adults due to organ injuries. In addition, this curative treatment approach has several limitations, such as difficulties to find donors, transplant-related mortality, graft loss, graft-versus-host disease (GVHD, and infertility. Engraftment effectivity and toxicity for transplantations performed with nonmyeloablative reduced-intensity regimens in adults are being investigated in phase 1/2 trials at many centers. Preliminary data indicate that GVHD could be prevented with transplantations performed using reduced-intensity regimens. It is necessary to develop novel regimens to prevent graft loss and reduce the risk of GVHD.

  7. Minimum Error Entropy Classification

    CERN Document Server

    Marques de Sá, Joaquim P; Santos, Jorge M F; Alexandre, Luís A

    2013-01-01

    This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.

  8. Human embryonic stem cell research, justice, and the problem of unequal biological access

    Directory of Open Access Journals (Sweden)

    Moller Mark S

    2008-09-01

    Full Text Available Abstract In 2003, Ruth Faden and eighteen other colleagues argued that a "problem of unequal biological access" is likely to arise in access to therapies resulting from human embryonic stem cell research. They showed that unless deliberate steps are taken in the United States to ensure that the human embryonic stem cell lines available to researchers mirrors the genetic diversity of the general population, white Americans will likely receive the benefits of these therapies to the relative exclusion of minority ethnic groups. Over the past five years the problem of unequal biological access has not received much attention from politicians, bioethicists and even many researchers in the United States, in spite of the widely held belief in the country that there is an obligation to prevent and correct ethnic disparities in access to medical care. The purpose of this paper is to increase awareness of the problem of unequal biological access and of the need to do more than is currently being done to ensure that ethnic disparities in access to human embryonic stem cell-based therapies do not arise. Specifically, this paper explains why the problem of unequal biological access will likely arise in the United States in such a way that white Americans will disproportionately receive most of the benefits of the therapies resulting from human embryonic stem cell research. It also argues for why there is an obligation to prevent these ethnic disparities in access from happening and outlines four steps that need to be taken towards meeting this obligation.

  9. Global Expression-Based Classification of Lymph Node Metastasis and Extracapsular Spread of Oral Tongue Squamous Cell Carcinoma

    Directory of Open Access Journals (Sweden)

    Xiaofeng Zhou

    2006-11-01

    Full Text Available Regional lymph node metastasis is a critical event in oral tongue squamous cell carcinoma (OTSCC progression. The identification of biomarkers associated with the metastatic process would provide critical prognostic information to facilitate clinical decision making for improved management of OTSCC patients. Global expressional profiles were obtained for 25 primary OTSCCs, where 11 cases showed lymph node metastasis (pN+ histologically and 14 cases were nonmetastatic (pN-. Seven of pN+ cases also exhibited extracapsular spread (ECS of metastatic nodes. Multiple expression indices were used to generate signature gene sets for pN+/- and ECS+/- cases. Selected genes from signature gene sets were validated using quantitative reverse transcription-polymerase chain reaction (qRT-PCR. The classification powers of these genes were then evaluated using a logistic model, receiver operating characteristic curve analysis, leave-oneout cross-validation. qRT-PCR validation data showed that differences at RNA levels are either statistically significant (P<.05 or suggestive (P< .1 for six of eight genes tested (BMP2, CTTN, EEF1A1, GTSE1, MMP9, EGFR for pN+/- cases, for five of eight genes tested (BMP2, CTTN, EEF1A1, MMP9, EGFR for ECS+/- cases. Logistic models with specific combinations of genes (CTTN+MMP9+EGFR for pN and CTTN+EEFIA1+MMP9 for ECS achieved perfect specificity and sensitivity. Leave-one-out cross-validation showed overall accuracy rates of 85% for both pN and ECS prediction models. Our results demonstrated that the pN and the ECS of OTSCCs can be predicted by gene expression analyses of primary tumors.

  10. A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem

    Science.gov (United States)

    Moradgholi, Mostafa; Paydar, Mohammad Mahdi; Mahdavi, Iraj; Jouzdani, Javid

    2016-05-01

    Nowadays, with the increasing pressure of the competitive business environment and demand for diverse products, manufacturers are force to seek for solutions that reduce production costs and rise product quality. Cellular manufacturing system (CMS), as a means to this end, has been a point of attraction to both researchers and practitioners. Limitations of cell formation problem (CFP), as one of important topics in CMS, have led to the introduction of virtual CMS (VCMS). This research addresses a bi-objective dynamic virtual cell formation problem (DVCFP) with the objective of finding the optimal formation of cells, considering the material handling costs, fixed machine installation costs and variable production costs of machines and workforce. Furthermore, we consider different skills on different machines in workforce assignment in a multi-period planning horizon. The bi-objective model is transformed to a single-objective fuzzy goal programming model and to show its performance; numerical examples are solved using the LINGO software. In addition, genetic algorithm (GA) is customized to tackle large-scale instances of the problems to show the performance of the solution method.

  11. Efficient Parallel Sorting for Migrating Birds Optimization When Solving Machine-Part Cell Formation Problems

    Directory of Open Access Journals (Sweden)

    Ricardo Soto

    2016-01-01

    Full Text Available The Machine-Part Cell Formation Problem (MPCFP is a NP-Hard optimization problem that consists in grouping machines and parts in a set of cells, so that each cell can operate independently and the intercell movements are minimized. This problem has largely been tackled in the literature by using different techniques ranging from classic methods such as linear programming to more modern nature-inspired metaheuristics. In this paper, we present an efficient parallel version of the Migrating Birds Optimization metaheuristic for solving the MPCFP. Migrating Birds Optimization is a population metaheuristic based on the V-Flight formation of the migrating birds, which is proven to be an effective formation in energy saving. This approach is enhanced by the smart incorporation of parallel procedures that notably improve performance of the several sorting processes performed by the metaheuristic. We perform computational experiments on 1080 benchmarks resulting from the combination of 90 well-known MPCFP instances with 12 sorting configurations with and without threads. We illustrate promising results where the proposal is able to reach the global optimum in all instances, while the solving time with respect to a nonparallel approach is notably reduced.

  12. The Classification Conundrum.

    Science.gov (United States)

    Granger, Charles R.

    1983-01-01

    Argues against the five-kingdom scheme of classification as using inconsistent criteria, ending up with divisions that are forced, not natural. Advocates an approach using cell type/complexity and modification of the metabolic machinery, recommending the five-kingdom scheme as starting point for class discussion on taxonomy and its conceptual…

  13. Advanced binary search pattern for impedance spectra classification for determining the state of charge of a lithium iron phosphate cell using a support vector machine

    Science.gov (United States)

    Jansen, Patrick; Vollnhals, Michael; Renner, Daniel; Vergossen, David; John, Werner; Götze, Jürgen

    2016-09-01

    Further improvements on the novel method for state of charge (SOC) determination of lithium iron phosphate (LFP) cells based on the impedance spectra classification are presented. A Support Vector Machine (SVM) is applied to impedance spectra of a LFP cell, with each impedance spectrum representing a distinct SOC for a predefined temperature. As a SVM is a binary classifier, only the distinction between two SOC can be computed in one iteration of the algorithm. Therefore a search pattern is necessary. A balanced tree search was implemented with good results. In order to further improvements of the SVM method, this paper discusses two new search pattern, namely a linear search and an imbalanced tree search, the later one based on an initial educated guess. All three search pattern were compared under various aspects like accuracy, efficiency, tolerance of disturbances and temperature dependancy. The imbalanced search tree shows to be the most efficient search pattern if the initial guess is within less than ±5 % SOC of the original SOC in both directions and exhibits the best tolerance for high disturbances. Linear search improves the rate of exact classifications for almost every temperature. It also improves the robustness against high disturbances and can even detect a certain number of false classifications which makes this search pattern unique. The downside is a much lower efficiency as all impedance spectra have to be evaluated while the tree search pattern only evaluate those on the tree path.

  14. [Modern problems of the application of sanitary regulations concerning sanitary protection zones and sanitary classification of enterprises, buildings and other facilities].

    Science.gov (United States)

    Lomtev, A Iu; Eremin, G B; Mozzhukhina, N A; Kombarova, M Iu; Mel'tser, A V; Giul'mamedov, É Iu

    2013-01-01

    In this paper there was performed an analysis of the application of sanitary norms and rules concerning sanitary protective zones and sanitary classification of enterprises, buildings and other facilities, including requirements for the sufficiency and accuracy of information in the performance of projects in sanitary protection zone (SPZ). There is presented an analysis of regulations that set requirements for implementation of mapping works in drafting the SPZ. The design of the SPZ was shown to be, on the one hand, the element of territorial planning subjects of the Russian Federation, on the other hand, the object of capital construction. The substantiations of requirements for graphic and text content, structure, and composition of data, sources of their obtaining, methods of data convergence are reported. There are revealed inconsistencies in Sanitary Regulations and Norms (SanPins) and in their relationship with the Town Planning and Land Code and other laws, and regulations adopted in their development.

  15. Classification of neocortical interneurons using affinity propagation

    Science.gov (United States)

    Santana, Roberto; McGarry, Laura M.; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

    2013-01-01

    In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, we explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits. PMID:24348339

  16. Classification of neocortical interneurons using affinity propagation

    Directory of Open Access Journals (Sweden)

    Roberto eSantana

    2013-12-01

    Full Text Available In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. Neuronal classification has been a difficult problem because it is unclear what a neuronal cell class actually is and what are the best characteristics are to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological or molecular characteristics, when applied to selected datasets, have provided quantitative and unbiased identification of distinct neuronal subtypes. However, better and more robust classification methods are needed for increasingly complex and larger datasets. We explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. In fact, using a combined anatomical/physiological dataset, our algorithm differentiated parvalbumin from somatostatin interneurons in 49 out of 50 cases. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

  17. 无偏置v-SVM分类优化问题研究%Study on v-SVM for Classification Optimization Problem without Bias

    Institute of Scientific and Technical Information of China (English)

    丁晓剑; 赵银亮

    2011-01-01

    In the high-dimensional space, the classification hyperplane tends to pass through the origin and bias (b) is not need. To study whether v-SVM for classification needs (b), dual optimization formulation of v-SVM without (b) is proposed and the corresponding method of solving the optimization formulation is presented. The dual optimization formulation is transformed into equality constraint sub-optimization formulation by the active set strategy in this method, then the sub-optimization formulation is transformed into the linear equation by lagrange multiplier method. The experimental results show that the existence of (b) would reduce the generalization ability of v-SVM and v-SVM can only obtain the sub-optimal solution of v-SVM without b.%在高维空间中,分类超平面倾向于通过原点,即不需要偏置(b).为了研究在v- SVM分类问题中是否需要b,该文提出了无(b)的v-SVM的对偶优化问题并给出了其优化问题求解方法.该方法通过有效集策略将对偶优化问题转化为等式约束子优化问题,然后通过拉格朗日乘子法将子优化问题转化为线程方程组来求解.实验表明偏置(b)的存在会降低v-SVM的泛化性能,v-SVM只能得到无(b)v-SVM的次优解.

  18. Clasificaciones de lesiones en pie diabético: Un problema no resuelto Classifications of injuries on diabetic foot: A non-solved problem

    Directory of Open Access Journals (Sweden)

    Héctor González de la Torre

    2012-06-01

    Full Text Available La necesidad de unificar criterios empleando un mismo lenguaje que favorezca la comunicación y el intercambio de conocimientos unido al desconocimiento existente en cuanto a las distintas formas de clasificación de las heridas crónicas, ha motivado a los autores para llevar a cabo esta revisión bibliográfica en la que se analizan quince sistemas de clasificación de lesiones de pie diabético y se abordan entre otros, aspectos como la metodología, facilidad de utilización, grado de conocimiento, utilidad de la información aportada y limitaciones de cada uno de ellos. Con ello, los autores no pretenden sino facilitar que los profesionales implicados en el cuidado de las úlceras diabéticas conozcan las distintas formas de estadiaje existentes en el pie diabético y en general en las heridas crónicas.The need of unify criterions using a same idiom contributing communication and interchanging knowledge together with ignorance existing in relation to the different ways of classificating chronic wounds is the reason for the authors to carry out this review analyzing fifteen classification systems in diabetic foot wounds dealing with subjects such as methodology, simplicity of use, grade of knowledge, usefulness of the information provided and limitations of each one. And so the authors pretend helping that those professionals taking care of diabetic foot ulcers can get to know different ways of staging diabetic foot wounds and chronic wounds in general.

  19. Low Size-Complexity Inductive Logic Programming: The East-West Challenge Considered as a Problem in Cost-Sensitive Classification

    OpenAIRE

    Turney, Peter D.

    2002-01-01

    The Inductive Logic Programming community has considered proof-complexity and model-complexity, but, until recently, size-complexity has received little attention. Recently a challenge was issued "to the international computing community" to discover low size-complexity Prolog programs for classifying trains. The challenge was based on a problem first proposed by Ryszard Michalski, 20 years ago. We interpreted the challenge as a problem in cost-sensitive classificat...

  20. Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma

    DEFF Research Database (Denmark)

    Visco, C; Xu-Monette, Z Y; Miranda, R N;

    2012-01-01

    Gene expression profiling (GEP) has stratified diffuse large B-cell lymphoma (DLBCL) into molecular subgroups that correspond to different stages of lymphocyte development-namely germinal center B-cell like and activated B-cell like. This classification has prognostic significance, but GEP...... is expensive and not readily applicable into daily practice, which has lead to immunohistochemical algorithms proposed as a surrogate for GEP analysis. We assembled tissue microarrays from 475 de novo DLBCL patients who were treated with rituximab-CHOP chemotherapy. All cases were successfully profiled by GEP...... on formalin-fixed, paraffin-embedded tissue samples. Sections were stained with antibodies reactive with CD10, GCET1, FOXP1, MUM1 and BCL6 and cases were classified following a rationale of sequential steps of differentiation of B cells. Cutoffs for each marker were obtained using receiver...

  1. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  2. An Improved Formulation of the Disclosure Auditing Problem for Secondary Cell Suppression

    Directory of Open Access Journals (Sweden)

    Jacco Daalmans

    2010-12-01

    Full Text Available Statistical agencies have to ensure that respondents' private information cannot be revealed from the tables they release. A well-known protection method is cell suppression, where values that provide too much information are left out from the table to be published. In a first step, sensitive cell values are suppressed. This is called primary suppression. In a second step, other values are suppressed as well to exclude that primarily suppressed values can be re-calculated from the values published in the table. This second step is called secondary cell suppression. In this article we explain that the problem of checking whether a pattern of secondary cell suppressions is safe for release or not is generally described in a slightly inconsistent way in the literature. We illustrate with examples that the criteria that are often applied to judge whether a table can be safely published or not do not always give satisfactory results. Furthermore, we present a new criterion and explore some of its consequences. The new criterion is an extension of the well-known (p,q-prior-posterior rule. This extension is for aggregations of suppressed cells for which a value can be derived from the table. Finally, we provide a method to apply the new criterion in practice.

  3. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  4. Evolvement of Classification Society

    Institute of Scientific and Technical Information of China (English)

    Xu Hua

    2011-01-01

    As an independent industry, the emergence of the classification society was perhaps the demand of beneficial interests between shipowners, cargo owners and insurers at the earliest time. Today, as an indispensable link of the international maritime industry, class role has changed fundamentally. Start off from the demand of the insurersSeaborne trade, transport and insurance industries began to emerge successively in the 17th century. The massive risk and benefit brought by seaborne transport provided a difficult problem to insurers.

  5. Estuary Classification Revisited

    OpenAIRE

    Guha, Anirban; Lawrence, Gregory A.

    2012-01-01

    This paper presents the governing equations of a tidally-averaged, width-averaged, rectangular estuary in completely nondimensionalized forms. Subsequently, we discover that the dynamics of an estuary is entirely controlled by only two variables: (i) the Estuarine Froude number, and (ii) a nondimensional number related to the Estuarine Aspect ratio and the Tidal Froude number. Motivated by this new observation, the problem of estuary classification is re-investigated. Our analysis shows that ...

  6. Finite cell method compared to h-version finite element method for elasto-plastic problems

    Institute of Scientific and Technical Information of China (English)

    A.ABEDIAN; J.PARVIZIAN; A.D USTER; E.RANK

    2014-01-01

    The finite cell method (FCM) combines the high-order finite element method (FEM) with the fictitious domain approach for the purpose of simple meshing. In the present study, the FCM is used to the Prandtl-Reuss flow theory of plasticity, and the results are compared with the h-version finite element method (h-FEM). The numerical results show that the FCM is more efficient compared to the h-FEM for elasto-plastic problems, although the mesh does not conform to the boundary. It is also demonstrated that the FCM performs well for elasto-plastic loading and unloading.

  7. The relation between lateralisation, early start of training, and amount of practice in musicians: a contribution to the problem of handedness classification.

    Science.gov (United States)

    Kopiez, Reinhard; Galley, Niels; Lehmann, Andreas C

    2010-07-01

    This study investigates the influence of extensive bimanual training in professional musicians on the incidence of handedness in the most basic form of right-handedness (RH) and non-right-handedness (NRH), according to Annett's "right shift theory". The lateralisation coefficients (LCs) of a total sample of 128 bimanually performing music students were calculated for speed, regularity, and fatigue of tapping by using the speed tapping paradigm. Additionally, the accumulated amount of practice was recorded by means of retrospective interviews. The proportion of designated right-handers (dRH) and non-right-handers (dNRH) in hand performance was identified by binary logistic regression from LCs. A proportion of 30.8% designated NRH in the group of musicians was found, while in the control group of non-musicians (matched for age range) a proportion of 21.7% designated NRH was observed. Incidence of dNRH was higher in string players (35.6%) than in pianists (27.1%). As an effect of the extensive training of the left hand, tapping regularity increased and tapping fatigue decreased among those participants who evidenced an increased amount of accumulated practice time on the instrument. However, speed difference between hands (as indicated by LCs) remained uninfluenced by bimanual training. This finding is in contrast to those of Jancke, Schlaug, and Steinmetz (1997). Finally, our study provides a more reliable (statistical) classification as an external criterion for future genetic analyses of handedness. PMID:19462271

  8. 痉挛型偏瘫和双下肢瘫的步态分型和处理%The classification and management of gait problems in spastic diplegia and hemiplegia

    Institute of Scientific and Technical Information of China (English)

    冯林(综述); 陈博昌(审校)

    2014-01-01

    痉挛型半身瘫和双下肢瘫是临床常见的需要治疗的脑性瘫痪类型。该文对这两种类型脑性瘫痪患儿常见的步态进行了分型,并根据分型提出了相应的治疗原则。通过对脑性瘫痪患儿的步态模式进行分型,根据患儿的功能情况制定个性化的治疗方案,改善患儿的步态和功能。%Spastic diplegia and hemiplegia are the common types of cerebral palsy which needs treat-ment in clinic. The paper discusses the classification of gait problems in these two types of cerebral palsy and ac-cording to gait analysis,recommended the management for them. Through the understanding of the classification, the treatment plan could be made individually regarding the GMFCS level of the patient and improve their functions.

  9. 痉挛型偏瘫和双下肢瘫的步态分型和处理%The classification and management of gait problems in spastic diplegia and hemiplegia

    Institute of Scientific and Technical Information of China (English)

    冯林(综述); 陈博昌(审校)

    2014-01-01

    Spastic diplegia and hemiplegia are the common types of cerebral palsy which needs treat-ment in clinic. The paper discusses the classification of gait problems in these two types of cerebral palsy and ac-cording to gait analysis,recommended the management for them. Through the understanding of the classification, the treatment plan could be made individually regarding the GMFCS level of the patient and improve their functions.%痉挛型半身瘫和双下肢瘫是临床常见的需要治疗的脑性瘫痪类型。该文对这两种类型脑性瘫痪患儿常见的步态进行了分型,并根据分型提出了相应的治疗原则。通过对脑性瘫痪患儿的步态模式进行分型,根据患儿的功能情况制定个性化的治疗方案,改善患儿的步态和功能。

  10. Cauchy problem for multiscale conservation laws: Application to structured cell populations

    CERN Document Server

    Shang, Peipei

    2010-01-01

    In this paper, we study a vector conservation law that models the growth and selection of ovarian follicles. During each ovarian cycle, only a definite number of follicles ovulate, while the others undergo a degeneration process called atresia. This work is motivated by a multiscale mathematical model starting on the cellular scale, where ovulation or atresia result from a hormonally controlled selection process. A two-dimensional conservation law describes the age and maturity structuration of the follicular cell populations. The densities intersect through a coupled hyperbolic system between different follicles and cell phases, which results in a vector conservation law and coupling boundary conditions. The maturity velocity functions possess both a local and nonlocal character. We prove the existence and uniqueness of the weak solution to the Cauchy problem with bounded initial and boundary data.

  11. A stochastic model for the cell formation problem considering machine reliability

    Science.gov (United States)

    Esmailnezhad, Bahman; Fattahi, Parviz; Kheirkhah, Amir Saman

    2015-03-01

    This paper presents a new mathematical model to solve cell formation problem in cellular manufacturing systems, where inter-arrival time, processing time, and machine breakdown time are probabilistic. The objective function maximizes the number of operations of each part with more arrival rate within one cell. Because a queue behind each machine; queuing theory is used to formulate the model. To solve the model, two metaheurstic algorithms such as modified particle swarm optimization and genetic algorithm are proposed. For the generation of initial solutions in these algorithms, a new heuristic method is developed, which always creates feasible solutions. Both metaheurstic algorithms are compared against global solutions obtained from Lingo software's branch and bound (B&B). Also, a statistical method will be used for comparison of solutions of two metaheurstic algorithms. The results of numerical examples indicate that considering the machine breakdown has significant effect on block structures of machine-part matrixes.

  12. How to solve mathematical problems

    CERN Document Server

    Wickelgren, Wayne A

    1995-01-01

    Seven problem-solving techniques include inference, classification of action sequences, subgoals, contradiction, working backward, relations between problems, and mathematical representation. Also, problems from mathematics, science, and engineering with complete solutions.

  13. A machine vision system for automated non-invasive assessment of cell viability via dark field microscopy, wavelet feature selection and classification

    Directory of Open Access Journals (Sweden)

    Friehs Karl

    2008-10-01

    Full Text Available Abstract Background Cell viability is one of the basic properties indicating the physiological state of the cell, thus, it has long been one of the major considerations in biotechnological applications. Conventional methods for extracting information about cell viability usually need reagents to be applied on the targeted cells. These reagent-based techniques are reliable and versatile, however, some of them might be invasive and even toxic to the target cells. In support of automated noninvasive assessment of cell viability, a machine vision system has been developed. Results This system is based on supervised learning technique. It learns from images of certain kinds of cell populations and trains some classifiers. These trained classifiers are then employed to evaluate the images of given cell populations obtained via dark field microscopy. Wavelet decomposition is performed on the cell images. Energy and entropy are computed for each wavelet subimage as features. A feature selection algorithm is implemented to achieve better performance. Correlation between the results from the machine vision system and commonly accepted gold standards becomes stronger if wavelet features are utilized. The best performance is achieved with a selected subset of wavelet features. Conclusion The machine vision system based on dark field microscopy in conjugation with supervised machine learning and wavelet feature selection automates the cell viability assessment, and yields comparable results to commonly accepted methods. Wavelet features are found to be suitable to describe the discriminative properties of the live and dead cells in viability classification. According to the analysis, live cells exhibit morphologically more details and are intracellularly more organized than dead ones, which display more homogeneous and diffuse gray values throughout the cells. Feature selection increases the system's performance. The reason lies in the fact that feature

  14. Classification of nanoparticle diffusion processes in vital cells by a multifeature random forests approach: application to simulated data, darkfield, and confocal laser scanning microscopy

    Science.gov (United States)

    Wagner, Thorsten; Kroll, Alexandra; Wiemann, Martin; Lipinski, Hans-Gerd

    2016-04-01

    Darkfield and confocal laser scanning microscopy both allow for a simultaneous observation of live cells and single nanoparticles. Accordingly, a characterization of nanoparticle uptake and intracellular mobility appears possible within living cells. Single particle tracking makes it possible to characterize the particle and the surrounding cell. In case of free diffusion, the mean squared displacement for each trajectory of a nanoparticle can be measured which allows computing the corresponding diffusion coefficient and, if desired, converting it into the hydrodynamic diameter using the Stokes-Einstein equation and the viscosity of the fluid. However, within the more complex system of a cell's cytoplasm unrestrained diffusion is scarce and several other types of movements may occur. Thus, confined or anomalous diffusion (e.g. diffusion in porous media), active transport, and combinations thereof were described by several authors. To distinguish between these types of particle movement we developed an appropriate classification method, and simulated three types of particle motion in a 2D plane using a Monte Carlo approach: (1) normal diffusion, using random direction and step-length, (2) subdiffusion, using confinements like a reflective boundary with defined radius or reflective objects in the closer vicinity, and (3) superdiffusion, using a directed flow added to the normal diffusion. To simulate subdiffusion we devised a new method based on tracks of different length combined with equally probable obstacle interaction. Next we estimated the fractal dimension, elongation and the ratio of long-time / short-time diffusion coefficients. These features were used to train a random forests classification algorithm. The accuracy for simulated trajectories with 180 steps was 97% (95%-CI: 0.9481-0.9884). The balanced accuracy was 94%, 99% and 98% for normal-, sub- and superdiffusion, respectively. Nanoparticle tracking analysis was used with 100 nm polystyrene particles

  15. 电子商务协同过滤稀疏性研究:一个分类视角%Sparsity Problem in Collaborative Filtering: A Classification

    Institute of Scientific and Technical Information of China (English)

    李聪; 梁昌勇; 杨善林

    2011-01-01

    协同过滤是目前电子商务推荐系统中广泛使用的、最成功的推荐算法,但面临用户评分数据稀疏性问题的挑战.在介绍用户偏好数据获取途径的基础上,将稀疏性改善技术归纳为六类,包括设定缺省值、结合基于内容的过滤、降维、图论方法、基于项目评分预测以及增加用户.系统交互,重点评述了各类算法的研究情况并时六类技术进行了比较,最后探讨了该领域的未来研究方向.%Today's e-commerce environment has drastically evolved in order to cope with information overload problems.Recommendation systems are currently used as virtual salespersons to help customers quickly locate personalized information and efficiently make purchase decisions. This technology compares the shopping behaviors and interests of users having common tendencies, and then recommends products and services for users to purchase. The more ratings on products and service the system can collect, the more accurately the system can recommend appropriate products and services to customers. However, with the ever increasing number of shoppers and products so]d, the ratings based on user-item matrix have quickly grown into becoming a higherdimensional matrix. As a result, user ratings are sparsely distributed and usually have lower than 1%. The increasing sparseness of problems has severely influenced the recommendation quality of collaborative filtering system.In Section 1, we provide an overview of the importance of user preference data. User preference data are fundamental to any ecommerce recommendation systems. The preference data include explicit ratings and implicit ratings. Explicit ratings are ratings submitted manually by users about their personal preference. Implicit ratings are ratings automatically captured and tracked by the recommendation system. The system becomes intelligent about consumer shopping behavior and produces implicit ratings over time.Data mining

  16. The Effect of Adaptive Gain and Adaptive Momentum in Improving Training Time of Gradient Descent Back Propagation Algorithm on Classification Problems

    Directory of Open Access Journals (Sweden)

    Norhamreeza Abdul Hamid

    2011-01-01

    Full Text Available The back propagation algorithm has been successfully applied to wide range of practical problems. Since this algorithm uses a gradient descent method, it has some limitations which are slow learning convergence velocity and easy convergence to local minima. The convergence behaviour of the back propagation algorithm depends on the choice of initial weights and biases, network topology, learning rate, momentum, activation function and value for the gain in the activation function. Previous researchers demonstrated that in ‘feed forward’ algorithm, the slope of the activation function is directly influenced by a parameter referred to as ‘gain’. This research proposed an algorithm for improving the performance of the current working back propagation algorithm which is Gradien Descent Method with Adaptive Gain by changing the momentum coefficient adaptively for each node. The influence of the adaptive momentum together with adaptive gain on the learning ability of a neural network is analysed. Multilayer feed forward neural networks have been assessed. Physical interpretation of the relationship between the momentum value, the learning rate and weight values is given. The efficiency of the proposed algorithm is compared with conventional Gradient Descent Method and current Gradient Descent Method with Adaptive Gain was verified by means of simulation on three benchmark problems. In learning the patterns, the simulations result demonstrate that the proposed algorithm converged faster on Wisconsin breast cancer with an improvement ratio of nearly 1.8, 6.6 on Mushroom problem and 36% better on  Soybean data sets. The results clearly show that the proposed algorithm significantly improves the learning speed of the current gradient descent back-propagatin algorithm.

  17. Adult neurogenesis, neural stem cells and Alzheimer's disease: developments, limitations, problems and promises.

    Science.gov (United States)

    Taupin, Philippe

    2009-12-01

    Alzheimer's disease (AD) is an irreversible progressive neurodegenerative disease, leading to severe incapacity and death. It is the most common form of dementia among older people. AD is characterized in the brain by amyloid plaques, neurofibrillary tangles, neuronal degeneration, aneuploidy and enhanced neurogenesis and by cognitive, behavioral and physical impairments. Inherited mutations in several genes and genetic, acquired and environmental risk factors have been reported as causes for developing the disease, for which there is currently no cure. Current treatments for AD involve drugs and occupational therapies, and future developments involve early diagnosis and stem cell therapy. In this manuscript, we will review and discuss the recent developments, limitations, problems and promises on AD, particularly related to aneuploidy, adult neurogenesis, neural stem cells (NSCs) and cellular therapy. Though adult neurogenesis may be beneficial for regeneration of the nervous system, it may underly the pathogenesis of AD. Cellular therapy is a promising strategy for AD. Limitations in protocols to establish homogeneous populations of neural progenitor and stem cells and niches for neurogenesis need to be resolved and unlocked, for the full potential of adult NSCs to be realized for therapy.

  18. Thin film polycrystalline silicon: Promise and problems in displays and solar cells

    Energy Technology Data Exchange (ETDEWEB)

    Fonash, S.J. [Pennsylvania State Univ., University Park, PA (United States)

    1995-08-01

    Thin film polycrystalline Si (poly-Si) with its carrier mobilities, potentially good stability, low intragrain defect density, compatibility with silicon processing, and ease of doping activation is an interesting material for {open_quotes}macroelectronics{close_quotes} applications such as TFTs for displays and solar cells. The poly-Si films needed for these applications can be ultra-thin-in the 500{Angstrom} to 1000{Angstrom} thickness range for flat panel display TFTs and in the 4{mu}m to 10{mu}m thickness range for solar cells. Because the films needed for these microelectronics applications can be so thin, an effective approach to producing the films is that of crystallizing a-Si precursor material. Unlike cast materials, poly-Si films made this way can be produced using low temperature processing. Unlike deposited poly-Si films, these crystallized poly-Si films can have grain widths that are much larger than the film thickness and almost atomically smooth surfaces. This thin film poly-Si crystallized from a-Si precursor films, and its promise and problems for TFTs and solar cells, is the focus of this discussion.

  19. Classification of distinct subtypes of peripheral T-cell lymphoma unspecified, identified by chemokine and chemokine receptor expression: Analysis of prognosis.

    Science.gov (United States)

    Ohshima, Koichi; Karube, Kennosuke; Kawano, Riko; Tsuchiya, Takeshi; Suefuji, Hiroaki; Yamaguchi, Takahiro; Suzumiya, Junji; Kikuchii, Masahiro

    2004-09-01

    WHO classification for malignant lymphoma was recently proposed. However, PTCL is heterogeneous. Chemokines and its receptors are closely associated with the T-cell subtypes. To clarify the T-cell subtype in PTCL, we conducted DNA chips of chemokine, its receptor (R) and cytokines. Angioimmunoblastic T-cell lymphoma (AILD, n=4), anaplastic large cell lymphoma (ALCL, n=4), adult T-cell leukemia lymphoma (ATLL, n=7), NK-cell lymphoma (NKL, n=2) and PTCL, unspecified (PTCL-U, n=6) were analyzed using DNA chips. In addition, immunological stainings were performed in 280 cases. In DNA chip, AILD, ALCL, NKL and ATLL showed a tendency for respective clusters, otherwise, PTCL-U clustered with AILD, ALCL and ATLL. From the gene expression profiling, CCR4, CCR3, MIG, CXCR3 and BLC were selected for immunohistochemistry. ATLL (n=48) expressed CCR4. ALCL (n=26) expressed CCR3, NKL (n=20) expressed MIG, and AILD (n=29) expressed CXCR3 and/or BLC. From the expression patterns, PTCL-U (n=134) were classified into three groups; CCR4 type (CCR4(+), n=42), CCR3 type (CCR3(+), n=31) and CXCR3 type (CXCR3(+) BLC(+/-), n=54). The prognosis was poor for ATLL, intermediate for AILD and favorable for ALCL (P=0.0014). Among PTCL-U, CCR4 type, CXCR3 type and CCR3 type had prognoses equivalent to ATLL, AILD and ALCL, respectively (P<0.0001).

  20. Maternal cell phone and cordless phone use during pregnancy and behaviour problems in 5-year-old children

    NARCIS (Netherlands)

    Guxens, Monica; van Eijsden, Manon; Vermeulen, Roel; Loomans, Eva; Vrijkotte, Tanja G. M.; Komhout, Hans; van Strien, Rob T.; Huss, Anke

    2013-01-01

    Background A previous study found an association between maternal cell phone use during pregnancy and maternal-reported child behaviour problems at age 7. Together with cell phones, cordless phones represent the main exposure source of radiofrequency-electromagnetic fields to the head. Therefore, we

  1. The Impact of Industry Classification Schemes on Financial Research

    OpenAIRE

    Weiner, Christian

    2005-01-01

    This paper investigates industry classification systems. During the last 50 years there has been a considerable discussion of problems regarding the classification of economic data by industries. From my perspective, the central point of each classification is to determine a balance between aggregation of similar firms and differentiation between industries. This paper examines the structure and content of industrial classification schemes and how they affect financial research. I use classif...

  2. Holistic facial expression classification

    Science.gov (United States)

    Ghent, John; McDonald, J.

    2005-06-01

    This paper details a procedure for classifying facial expressions. This is a growing and relatively new type of problem within computer vision. One of the fundamental problems when classifying facial expressions in previous approaches is the lack of a consistent method of measuring expression. This paper solves this problem by the computation of the Facial Expression Shape Model (FESM). This statistical model of facial expression is based on an anatomical analysis of facial expression called the Facial Action Coding System (FACS). We use the term Action Unit (AU) to describe a movement of one or more muscles of the face and all expressions can be described using the AU's described by FACS. The shape model is calculated by marking the face with 122 landmark points. We use Principal Component Analysis (PCA) to analyse how the landmark points move with respect to each other and to lower the dimensionality of the problem. Using the FESM in conjunction with Support Vector Machines (SVM) we classify facial expressions. SVMs are a powerful machine learning technique based on optimisation theory. This project is largely concerned with statistical models, machine learning techniques and psychological tools used in the classification of facial expression. This holistic approach to expression classification provides a means for a level of interaction with a computer that is a significant step forward in human-computer interaction.

  3. Soil Classification Using GATree

    CERN Document Server

    Bhargavi, P

    2010-01-01

    This paper details the application of a genetic programming framework for classification of decision tree of Soil data to classify soil texture. The database contains measurements of soil profile data. We have applied GATree for generating classification decision tree. GATree is a decision tree builder that is based on Genetic Algorithms (GAs). The idea behind it is rather simple but powerful. Instead of using statistic metrics that are biased towards specific trees we use a more flexible, global metric of tree quality that try to optimize accuracy and size. GATree offers some unique features not to be found in any other tree inducers while at the same time it can produce better results for many difficult problems. Experimental results are presented which illustrate the performance of generating best decision tree for classifying soil texture for soil data set.

  4. Sickle cell disease and associated problems: Case study of Homozygous sicklers

    Directory of Open Access Journals (Sweden)

    Jyoti Jhariya

    2016-02-01

    Full Text Available This paper is focused on the problems faced by homozygous individuals of sickle cell disease. In a survey of 500 household of 17 villages of district Mandla, a total of 2316 individuals were covered out of which 13 were found homozygous for the disorder; whereas 3 homozygous children were reported died preceding to one year of the survey. In depth case studies of these children were recorded. The highest age of surviving homozygous individual was 30 years. After 4-5 years of age their survival is very difficult and they require frequent blood transfusion. They face frequent episodes of various infections and unbearable pain. The findings are based on longitudinal and cross sectional study as well as empirical field investigation. It was found that the homozygous children have to face multiple problems, acute pain, priapism, alienation, frequent hospitalization, economic constraints. The families of homozygous children have to face frequent emotional shock as well as economic burden. The problem of homozygous sicklers can be categorized as clinical, educational, economic etc. and is a challenge for achieving the goal of human development. Further to understand the relationship of the prevalence of gene and Human Development, district and state wise gene (HbS frequency were computed. The bivariate correlation analysis between the district wise prevalence of gene and human development index was found positive but insignificant (r2=0.065, p>0.8. At the same time, the correlation of prevalence of the HbS gene and human development index for 11 states was found negative and insignificant (r2=-0.237, p>0.5. It leads to conclude that there is no apparent correlation between the prevalence of gene and the human development in that particular region, although there is lack of sufficient data.

  5. A time dependent approach for removing the cell boundary error in elliptic homogenization problems

    Science.gov (United States)

    Arjmand, Doghonay; Runborg, Olof

    2016-06-01

    This paper concerns the cell-boundary error present in multiscale algorithms for elliptic homogenization problems. Typical multiscale methods have two essential components: a macro and a micro model. The micro model is used to upscale parameter values which are missing in the macro model. To solve the micro model, boundary conditions are required on the boundary of the microscopic domain. Imposing a naive boundary condition leads to O (ε / η) error in the computation, where ε is the size of the microscopic variations in the media and η is the size of the micro-domain. The removal of this error in modern multiscale algorithms still remains an important open problem. In this paper, we present a time-dependent approach which is general in terms of dimension. We provide a theorem which shows that we have arbitrarily high order convergence rates in terms of ε / η in the periodic setting. Additionally, we present numerical evidence showing that the method improves the O (ε / η) error to O (ε) in general non-periodic media.

  6. [Landscape classification: research progress and development trend].

    Science.gov (United States)

    Liang, Fa-Chao; Liu, Li-Ming

    2011-06-01

    Landscape classification is the basis of the researches on landscape structure, process, and function, and also, the prerequisite for landscape evaluation, planning, protection, and management, directly affecting the precision and practicability of landscape research. This paper reviewed the research progress on the landscape classification system, theory, and methodology, and summarized the key problems and deficiencies of current researches. Some major landscape classification systems, e. g. , LANMAP and MUFIC, were introduced and discussed. It was suggested that a qualitative and quantitative comprehensive classification based on the ideology of functional structure shape and on the integral consideration of landscape classification utility, landscape function, landscape structure, physiogeographical factors, and human disturbance intensity should be the major research directions in the future. The integration of mapping, 3S technology, quantitative mathematics modeling, computer artificial intelligence, and professional knowledge to enhance the precision of landscape classification would be the key issues and the development trend in the researches of landscape classification.

  7. Biogeography based Satellite Image Classification

    CERN Document Server

    Panchal, V K; Kaur, Navdeep; Kundra, Harish

    2009-01-01

    Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible areas. Though satellite images have been classified in past by using various techniques, the researchers are always finding alternative strategies for satellite image classification so that they may be prepared to select the most appropriate technique for the feature extraction task in hand. This paper is focused on classification of the satellite image of a particular land cover using the theory of Biogeography based Optimization. The original BBO algorithm does not have the inbuilt property of clustering which is required during image classification. Hence modifications have been proposed to the original algorithm and...

  8. Some physical problems in biology: Aspects of the origin and structure of the first cell

    International Nuclear Information System (INIS)

    A review is presented within the framework of the theory of evolution, after it has been extrapolated from the population level to the cellular and molecular levels. From Darwin's seminal and persuasive insight - the theory of common descent - we assume, with him, that ''probably all the organic beings which have ever lived on this earth have descended from some one primordial form, into which life was first breathed''. We are now aware that this primordial cell may have been a protocyanobacterium, but it has often been called 'a last universal ancestor', a 'breakthrough organism', or a 'progenote', a term introduced by Woese which has gained wide acceptance. Strictly speaking, in the 'intermediate period', ranging from the first living cell to the progenote, life may have evolved in the absence of significant diversity, effectively as a single phylum, incorporating organisms whose genetic systems were already based on DNA. Earlier still, prior to the encapsulation of nucleic acids in microspheres, evolution may already have been at work on RNA molecules (the 'RNA world'). This takes our discussion into the period of chemical evolution, a concept first put forward by Oparin, whose principal merit is to have formulated the underlying problem in clear scientific terms. This review does not attempt to be comprehensive. It is mainly devoted to the discussion of certain concepts that may have played a relevant role in the pathway that led to the origin and evolution of the progenote. We do not dwell on the main events of the intermediate period. The topics that we have chosen to include are: the origin of chirality of protein amino acids, the origin of translation, and the origin of the genome. We conclude with some comments on one further aspect of the evolutionary process - the development of biodiversity - by considering the origin of the first eukaryotic cell, an event which, according to the fossil record, may have preceded the evolutionary radiation in the early

  9. Some physical problems in biology: Aspects of the origin and structure of the first cell

    International Nuclear Information System (INIS)

    A review is presented within the framework of the theory of evolution, after it has been extrapolated from the population level to the cellular and molecular levels. From Darwin's seminal and persuasive insight - the theory of common descent - we assume, with him, that ''probably all the organic beings which have ever lived on this earth have descended from some one primordial form, into which life was first breathed''. We are now aware that his primordial cell may have been a protocyanobacterium, but it has often been called 'a last universal ancestor', a 'breakthrough organism', or a 'progenote', a term introduced by Woese which has gained wide acceptance. Strictly speaking, in the 'intermediate period', ranging from the first living cell to the progenote, life may have evolved in the absence of significant diversity, effectively as a single phylum, incorporating organisms whose genetic systems were already based on DNA. Earlier still, prior to the encapsulation of nucleic acids in microspheres, evolution may already have been at work on RNA molecules (the 'RNA world'). This takes our discussion into the period of chemical evolution, a concept first put forward by Oparin, whose principal merit is to have formulated the underlying problem in clear scientific terms. This review does not attempt to be comprehensive. It is mainly devoted to the discussion of certain concepts that may have played a relevant role in the pathway that led to the origin and evolution of the progenote. We do not dwell on the main events of the intermediate period. The topic that we have chosen to include are: the origin of chirality of protein amino acids, the origin of translation, and the origin of the genome. We conclude with some comments on one further aspect of the evolutionary process - the development of biodiversity - by considering the origin of the first eukaryotic cell, an event which, according to the fossil record, may have preceded the evolutionary radiation in the early

  10. Arabic Text Mining Using Rule Based Classification

    OpenAIRE

    Fadi Thabtah; Omar Gharaibeh; Rashid Al-Zubaidy

    2012-01-01

    A well-known classification problem in the domain of text mining is text classification, which concerns about mapping textual documents into one or more predefined category based on its content. Text classification arena recently attracted many researchers because of the massive amounts of online documents and text archives which hold essential information for a decision-making process. In this field, most of such researches focus on classifying English documents while there are limited studi...

  11. ELABORATION OF A VECTOR BASED SEMANTIC CLASSIFICATION OVER THE WORDS AND NOTIONS OF THE NATURAL LANGUAGE

    OpenAIRE

    Safonov, K.; Lichargin, D.

    2009-01-01

    The problem of vector-based semantic classification over the words and notions of the natural language is discussed. A set of generative grammar rules is offered for generating the semantic classification vector. Examples of the classification application and a theorem of optional formal classification incompleteness are presented. The principles of assigning the meaningful phrases functions over the classification word groups are analyzed.

  12. Cost Sensitive Sequential Classification

    CERN Document Server

    Trapeznikov, Kirill; Castanon, David

    2012-01-01

    In many decision systems, sensing modalities have different acquisition costs. It is often unnecessary to use every sensor to classify a majority of examples. We study a multi-stage system in a prediction time cost reduction setting, where all the modalities are available for training, but for a test example, measurements in a new modality can be acquired at each stage for an additional cost. We seek decision rules to reduce the average acquisition cost. We construct an empirical risk minimization problem (ERM) for a multi-stage reject classifier, wherein the stage $k$ classifier either classifies a sample using only the measurements acquired so far or rejects it to the next stage where more attributes can be acquired for a cost. To solve the ERM problem, we factorize the loss function into classification and rejection decisions. We then transform reject decisions into a binary classification problem. We formulate stage-by-stage global surrogate risk and introduce an iterative algorithm in the boosting framew...

  13. Classification in Australia.

    Science.gov (United States)

    McKinlay, John

    Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

  14. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  15. Identification and validation of a two-gene expression index for subtype classification and prognosis in Diffuse Large B-Cell Lymphoma.

    Science.gov (United States)

    Xu, Qinghua; Tan, Cong; Ni, Shujuan; Wang, Qifeng; Wu, Fei; Liu, Fang; Ye, Xun; Meng, Xia; Sheng, Weiqi; Du, Xiang

    2015-01-01

    The division of diffuse large B-cell lymphoma (DLBCL) into germinal center B-cell-like (GCB) and activated B-cell-like (ABC) subtypes based on gene expression profiling has proved to be a landmark in understanding the pathogenesis of the disease. This study aims to identify a novel biomarker to facilitate the translation of research into clinical practice. Using a training set of 350 patients, we identified a two-gene expression signature, "LIMD1-MYBL1 Index", which is significantly associated with cell-of-origin subtypes and clinical outcome. This two-gene index was further validated in two additional dataset. Tested against the gold standard method, the LIMD1-MYBL1 Index achieved 81% sensitivity, 89% specificity for ABC group and 81% sensitivity, 87% specificity for GCB group. The ABC group had significantly worse overall survival than the GCB group (hazard ratio = 3.5, P = 0.01). Furthermore, the performance of LIMD1-MYBL1 Index was satisfactory compared with common immunohistochemical algorithms. Thus, the LIMD1-MYBL1 Index had considerable clinical value for DLBCL subtype classification and prognosis. Our results might prompt the further development of this two-gene index to a simple assay amenable to routine clinical practice. PMID:25940947

  16. Automatic Hierarchical Color Image Classification

    Directory of Open Access Journals (Sweden)

    Jing Huang

    2003-02-01

    Full Text Available Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.

  17. Single neuron transcriptome analysis can reveal more than cell type classification: Does it matter if every neuron is unique?

    Science.gov (United States)

    Harbom, Lise J; Chronister, William D; McConnell, Michael J

    2016-02-01

    A recent single cell mRNA sequencing study by Dueck et al. compares neuronal transcriptomes to the transcriptomes of adipocytes and cardiomyocytes. Single cell omic approaches such as those used by the authors are at the leading edge of molecular and biophysical measurement. Many groups are currently employing single cell sequencing approaches to understand cellular heterogeneity in cancer and during normal development. These single cell approaches also are beginning to address long-standing questions regarding nervous system diversity. Beyond an innate interest in cataloging cell type diversity in the brain, single cell neuronal diversity has important implications for neurotypic neural circuit function and for neurological disease. Herein, we review the authors' methods and findings, which most notably include evidence of unique expression profiles in some single neurons. PMID:26749010

  18. Cancer stem cell-related marker expression in lung adenocarcinoma and relevance of histologic subtypes based on IASLC/ATS/ERS classification

    Directory of Open Access Journals (Sweden)

    Shimada Y

    2013-11-01

    Full Text Available Yoshihisa Shimada,1 Hisashi Saji,3 Masaharu Nomura,1,2 Jun Matsubayashi,2 Koichi Yoshida,1 Masatoshi Kakihana,1 Naohiro Kajiwara,1 Tatsuo Ohira,1 Norihiko Ikeda11Department of Surgery I, 2Department of Anatomic Pathology, Tokyo Medical University Hospital, Tokyo, Japan; 3Department of Chest Surgery, St Marianna University School of Medicine, Kawasaki, JapanBackground: The cancer stem cell (CSC theory has been proposed to explain tumor heterogeneity and the carcinogenesis of solid tumors. The aim of this study was to clarify the clinical role of CSC-related markers in patients with lung adenocarcinoma and to determine whether each CSC-related marker expression correlates with the histologic subtyping proposed by the International Association for the Study of Lung Cancer (IASLC, the American Thoracic Society (ATS, and the European Respiratory Society (ERS classifications.Methods: We reviewed data for all 103 patients in whom complete resection of adenocarcinoma had been performed. Expression of CSC-related markers, ie, aldehyde dehydrogenase 1A1 (ALDH1A1, aldo-keto reductase 1C family member 1 (AK1C1, and 1C family member 3 (AK1C3, was examined using immunostaining on whole-mount tissue slides, and the tumors were reclassified according to the IASLC/ATS/ERS classification.Results: ALDH1A1 expression was observed in 66.0% of tumors, AK1C1 in 62.7%, and AK1C3 in 86.1%. Immunoreactivities with the frequency of mean expression of ALDH1A1 in papillary predominant adenocarcinoma were significantly higher than those of solid predominant adenocarcinoma (P<0.05. Papillary predominant adenocarcinoma had significantly lower expression of AK1C1 when compared with noninvasive or solid predominant adenocarcinomas (P<0.05. On multivariate analysis, larger tumor size (hazards ratio 1.899, P=0.044, lymph node metastasis (hazards ratio 2.702, P=0.005, and low expression of ALDH1A1 (hazards ratio 3.218, P<0.001 were shown to be independently associated with an

  19. Remote Sensing Information Classification

    Science.gov (United States)

    Rickman, Douglas L.

    2008-01-01

    This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.

  20. Classification of Lactococcus lactis cell envelope proteinase based on gene sequencing, peptides formed after hydrolysis of milk, and computer modeling

    DEFF Research Database (Denmark)

    Børsting, Mette Winther; Qvist, K.B.; Brockmann, E.;

    2015-01-01

    Lactococcus lactis strains depend on a proteolytic system for growth in milk to release essential AA from casein. The cleavage specificities of the cell envelope proteinase (CEP) can vary between strains and environments and whether the enzyme is released or bound to the cell wall. Thirty-eight Lc...

  1. Applying Feature Extraction for Classification Problems

    Directory of Open Access Journals (Sweden)

    Foon Chi

    2009-03-01

    Full Text Available With the wealth of image data that is now becoming increasingly accessible through the advent of the world wide web and the proliferation of cheap, high quality digital cameras it isbecoming ever more desirable to be able to automatically classify images into appropriate categories such that intelligent agents and other such intelligent software might make better informed decisions regarding them without a need for excessive human intervention.However, as with most Artificial Intelligence (A.I. methods it is seen as necessary to take small steps towards your goal. With this in mind a method is proposed here to represent localised features using disjoint sub-images taken from several datasets of retinal images for their eventual use in an incremental learning system. A tile-based localised adaptive threshold selection method was taken for vessel segmentation based on separate colour components. Arteriole-venous differentiation was made possible by using the composite of these components and high quality fundal images. Performance was evaluated on the DRIVE and STARE datasets achieving average specificity of 0.9379 and sensitivity of 0.5924.

  2. HIV classification using coalescent theory

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Ming [Los Alamos National Laboratory; Letiner, Thomas K [Los Alamos National Laboratory; Korber, Bette T [Los Alamos National Laboratory

    2008-01-01

    Algorithms for subtype classification and breakpoint detection of HIV-I sequences are based on a classification system of HIV-l. Hence, their quality highly depend on this system. Due to the history of creation of the current HIV-I nomenclature, the current one contains inconsistencies like: The phylogenetic distance between the subtype B and D is remarkably small compared with other pairs of subtypes. In fact, it is more like the distance of a pair of subsubtypes Robertson et al. (2000); Subtypes E and I do not exist any more since they were discovered to be composed of recombinants Robertson et al. (2000); It is currently discussed whether -- instead of CRF02 being a recombinant of subtype A and G -- subtype G should be designated as a circulating recombination form (CRF) nd CRF02 as a subtype Abecasis et al. (2007); There are 8 complete and over 400 partial HIV genomes in the LANL-database which belong neither to a subtype nor to a CRF (denoted by U). Moreover, the current classification system is somehow arbitrary like all complex classification systems that were created manually. To this end, it is desirable to deduce the classification system of HIV systematically by an algorithm. Of course, this problem is not restricted to HIV, but applies to all fast mutating and recombining viruses. Our work addresses the simpler subproblem to score classifications of given input sequences of some virus species (classification denotes a partition of the input sequences in several subtypes and CRFs). To this end, we reconstruct ancestral recombination graphs (ARG) of the input sequences under restrictions determined by the given classification. These restritions are imposed in order to ensure that the reconstructed ARGs do not contradict the classification under consideration. Then, we find the ARG with maximal probability by means of Markov Chain Monte Carlo methods. The probability of the most probable ARG is interpreted as a score for the classification. To our

  3. Human error classification and data collection

    International Nuclear Information System (INIS)

    Analysis of human error data requires human error classification. As the human factors/reliability subject has developed so too has the topic of human error classification. The classifications vary considerably depending on whether it has been developed from a theoretical psychological approach to understanding human behavior or error, or whether it has been based on an empirical practical approach. This latter approach is often adopted by nuclear power plants that need to make practical improvements as soon as possible. This document will review aspects of human error classification and data collection in order to show where potential improvements could be made. It will attempt to show why there are problems with human error classification and data collection schemes and that these problems will not be easy to resolve. The Annex of this document contains the papers presented at the meeting. A separate abstract was prepared for each of these 12 papers. Refs, figs and tabs

  4. Learning features for tissue classification with the classification restricted Boltzmann machine

    DEFF Research Database (Denmark)

    van Tulder, Gijs; de Bruijne, Marleen

    2014-01-01

    Performance of automated tissue classification in medical imaging depends on the choice of descriptive features. In this paper, we show how restricted Boltzmann machines (RBMs) can be used to learn features that are especially suited for texture-based tissue classification. We introduce...... the convolutional classification RBM, a combination of the existing convolutional RBM and classification RBM, and use it for discriminative feature learning. We evaluate the classification accuracy of convolutional and non-convolutional classification RBMs on two lung CT problems. We find that RBM-learned features...... outperform conventional RBM-based feature learning, which is unsupervised and uses only a generative learning objective, as well as often-used filter banks. We show that a mixture of generative and discriminative learning can produce filters that give a higher classification accuracy....

  5. Classification Accuracy Is Not Enough

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    different state-of-the-art MGR systems, that classification accuracy does not necessarily reflect the capacity of a system to recognize genre in musical signals. We argue that a more comprehensive analysis of behavior at the level of the music is needed to address the problem of MGR, and that measuring......A recent review of the research literature evaluating music genre recognition (MGR) systems over the past two decades shows that most works (81\\%) measure the capacity of a system to recognize genre by its classification accuracy. We show here, by implementing and testing three categorically...

  6. Proteomic classification of breast cancer.

    LENUS (Irish Health Repository)

    Kamel, Dalia

    2012-11-01

    Being a significant health problem that affects patients in various age groups, breast cancer has been extensively studied to date. Recently, molecular breast cancer classification has advanced significantly with the availability of genomic profiling technologies. Proteomic technologies have also advanced from traditional protein assays including enzyme-linked immunosorbent assay, immunoblotting and immunohistochemistry to more comprehensive approaches including mass spectrometry and reverse phase protein lysate arrays (RPPA). The purpose of this manuscript is to review the current protein markers that influence breast cancer prediction and prognosis and to focus on novel advances in proteomic classification of breast cancer.

  7. Gender, Race, and Survival: A Study in Non-Small-Cell Lung Cancer Brain Metastases Patients Utilizing the Radiation Therapy Oncology Group Recursive Partitioning Analysis Classification

    International Nuclear Information System (INIS)

    Purpose: To explore whether gender and race influence survival in non-small-cell lung cancer (NSCLC) in patients with brain metastases, using our large single-institution brain tumor database and the Radiation Therapy Oncology Group recursive partitioning analysis (RPA) brain metastases classification. Methods and materials: A retrospective review of a single-institution brain metastasis database for the interval January 1982 to September 2004 yielded 835 NSCLC patients with brain metastases for analysis. Patient subsets based on combinations of gender, race, and RPA class were then analyzed for survival differences. Results: Median follow-up was 5.4 months (range, 0-122.9 months). There were 485 male patients (M) (58.4%) and 346 female patients (F) (41.6%). Of the 828 evaluable patients (99%), 143 (17%) were black/African American (B) and 685 (83%) were white/Caucasian (W). Median survival time (MST) from time of brain metastasis diagnosis for all patients was 5.8 months. Median survival time by gender (F vs. M) and race (W vs. B) was 6.3 months vs. 5.5 months (p = 0.013) and 6.0 months vs. 5.2 months (p = 0.08), respectively. For patients stratified by RPA class, gender, and race, MST significantly favored BFs over BMs in Class II: 11.2 months vs. 4.6 months (p = 0.021). On multivariable analysis, significant variables were gender (p = 0.041, relative risk [RR] 0.83) and RPA class (p < 0.0001, RR 0.28 for I vs. III; p < 0.0001, RR 0.51 for II vs. III) but not race. Conclusions: Gender significantly influences NSCLC brain metastasis survival. Race trended to significance in overall survival but was not significant on multivariable analysis. Multivariable analysis identified gender and RPA classification as significant variables with respect to survival.

  8. Meta Classification for Variable Stars

    CERN Document Server

    Pichara, Karim; León, Daniel

    2016-01-01

    The need for the development of automatic tools to explore astronomical databases has been recognized since the inception of CCDs and modern computers. Astronomers already have developed solutions to tackle several science problems, such as automatic classification of stellar objects, outlier detection, and globular clusters identification, among others. New science problems emerge and it is critical to be able to re-use the models learned before, without rebuilding everything from the beginning when the science problem changes. In this paper, we propose a new meta-model that automatically integrates existing classification models of variable stars. The proposed meta-model incorporates existing models that are trained in a different context, answering different questions and using different representations of data. Conventional mixture of experts algorithms in machine learning literature can not be used since each expert (model) uses different inputs. We also consider computational complexity of the model by ...

  9. Handling uncertainties in SVM classification

    CERN Document Server

    Niaf, Emilie; Lartizien, Carole; Canu, Stéphane

    2011-01-01

    This paper addresses the pattern classification problem arising when available target data include some uncertainty information. Target data considered here is either qualitative (a class label) or quantitative (an estimation of the posterior probability). Our main contribution is a SVM inspired formulation of this problem allowing to take into account class label through a hinge loss as well as probability estimates using epsilon-insensitive cost function together with a minimum norm (maximum margin) objective. This formulation shows a dual form leading to a quadratic problem and allows the use of a representer theorem and associated kernel. The solution provided can be used for both decision and posterior probability estimation. Based on empirical evidence our method outperforms regular SVM in terms of probability predictions and classification performances.

  10. MULTI-LABEL CLASSIFICATION OF PRODUCT REVIEWS USING STRUCTURED SVM

    Directory of Open Access Journals (Sweden)

    Jincy B. Chrystal

    2015-05-01

    Full Text Available Most of the text classification problems are associated with multiple class labels and hence automatic text classification is one of the most challenging and prominent research area. Text classification is the problem of categorizing text documents into different classes. In the multi-label classification scenario, each document is associated may have more than one label. The real challenge in the multi-label classification is the labelling of large number of text documents with a subset of class categories. The feature extraction and classification of such text documents require an efficient machine learning algorithm which performs automatic text classification. This paper describes the multi-label classification of product review documents using Structured Support Vector Machine.

  11. Pattern classification

    CERN Document Server

    Duda, Richard O; Stork, David G

    2001-01-01

    The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

  12. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...

  13. Scientific and General Subject Classifications in the Digital World

    CERN Document Server

    De Robbio, Antonella; Marini, A

    2001-01-01

    In the present work we discuss opportunities, problems, tools and techniques encountered when interconnecting discipline-specific subject classifications, primarily organized as search devices in bibliographic databases, with general classifications originally devised for book shelving in public libraries. We first state the fundamental distinction between topical (or subject) classifications and object classifications. Then we trace the structural limitations that have constrained subject classifications since their library origins, and the devices that were used to overcome the gap with genuine knowledge representation. After recalling some general notions on structure, dynamics and interferences of subject classifications and of the objects they refer to, we sketch a synthetic overview on discipline-specific classifications in Mathematics, Computing and Physics, on one hand, and on general classifications on the other. In this setting we present The Scientific Classifications Page, which collects groups of...

  14. Detecting relevant variables and interactions in supervised classification.

    OpenAIRE

    Romero-Morales, Dolores; Carrizosa, Emilio; Martin-Barragan, Belen

    2011-01-01

    The widely used Support Vector Machine (SVM) method has shown to yield good results in Supervised Classification problems. When the interpretability is an important issue, then classification methods such as Classification and Regression Trees (CART) might be more attractive, since they are designed to detect the important predictor variables and, for each predictor variable, the critical values which are most relevant for classification. However, when interactions between variables strongly ...

  15. Machine Learning-based Classification of Diffuse Large B-cell Lymphoma Patients by Their Protein Expression Profiles.

    Science.gov (United States)

    Deeb, Sally J; Tyanova, Stefka; Hummel, Michael; Schmidt-Supprian, Marc; Cox, Juergen; Mann, Matthias

    2015-11-01

    Characterization of tumors at the molecular level has improved our knowledge of cancer causation and progression. Proteomic analysis of their signaling pathways promises to enhance our understanding of cancer aberrations at the functional level, but this requires accurate and robust tools. Here, we develop a state of the art quantitative mass spectrometric pipeline to characterize formalin-fixed paraffin-embedded tissues of patients with closely related subtypes of diffuse large B-cell lymphoma. We combined a super-SILAC approach with label-free quantification (hybrid LFQ) to address situations where the protein is absent in the super-SILAC standard but present in the patient samples. Shotgun proteomic analysis on a quadrupole Orbitrap quantified almost 9,000 tumor proteins in 20 patients. The quantitative accuracy of our approach allowed the segregation of diffuse large B-cell lymphoma patients according to their cell of origin using both their global protein expression patterns and the 55-protein signature obtained previously from patient-derived cell lines (Deeb, S. J., D'Souza, R. C., Cox, J., Schmidt-Supprian, M., and Mann, M. (2012) Mol. Cell. Proteomics 11, 77-89). Expression levels of individual segregation-driving proteins as well as categories such as extracellular matrix proteins behaved consistently with known trends between the subtypes. We used machine learning (support vector machines) to extract candidate proteins with the highest segregating power. A panel of four proteins (PALD1, MME, TNFAIP8, and TBC1D4) is predicted to classify patients with low error rates. Highly ranked proteins from the support vector analysis revealed differential expression of core signaling molecules between the subtypes, elucidating aspects of their pathobiology. PMID:26311899

  16. [Classification of periprosthetic shoulder fractures].

    Science.gov (United States)

    Kirchhoff, C; Kirchhoff, S; Biberthaler, P

    2016-04-01

    The key targets in the treatment of periprosthetic humeral fractures (PHF) are the preservation of bone, successful bony consolidation and provision of a stable anchoring of the prosthesis with the major goal of restoring the shoulder-arm function. A substantial problem of periprosthetic shoulder fractures is the fact that treatment is determined not only by the fracture itself but also by the implanted prosthesis and its function. Consequently, the exact preoperative shoulder function and, in the case of an implanted anatomical prosthesis, the status and function of the rotator cuff need to be assessed in order to clarify the possibility of a secondarily occurring malfunction. Of equal importance in this context is the type of implanted prosthesis. The existing classification systems of Wright and Cofield, Campbell et al., Groh et al. and Worland et al. have several drawbacks from a shoulder surgeon's point of view, such as a missing reference to the great variability of the available prostheses and the lack of an evaluation of rotator cuff function. The presented 6‑stage classification for the evaluation of periprosthetic fractures of the shoulder can be considered just as simple or complex to understand as the classification of the working group for osteosynthesis problems (AO, Arbeitsgemeinschaft für Osteosynthesefragen), depending on the viewpoint. From our point of view the classification presented here encompasses the essential points of the existing classification systems and also covers the otherwise missing points, which should be considered in the assessment of such periprosthetic fractures. The classification presented here should provide helpful assistance in the daily routine to find the most convenient form of therapy. PMID:26992712

  17. 昆虫细胞分类技术的应用与发展%The application and development of insect cell classification techniques

    Institute of Scientific and Technical Information of China (English)

    孙立影; 张占东

    2016-01-01

    Baculovirus-insect cell expression system as one of the four major expression systems has been widely used in biopharmaceutical industry.As the basis support of this expression system,insect cells begin to become another new cell matrix after mammalian cells,and are developed and applied in the field of vaccines and biotechnology products.However,there are significant differences between insect cells and mammalian cells in terms of cell characteristics,so establishment of a quality control method suiting characteristics of insect cells has become a problem which must be solved in biopharmaceutics.This article mainly reviews the research progress of insect cell identification methods,and provides reference for the development and establishment of individual identification methods of insect cells.%昆虫细胞杆状病毒表达系统作为四大表达系统之一,已经被广泛应用于生物制药领域,作为该表达系统的支撑基础,昆虫细胞开始成为继哺乳动物细胞之后的另一种新型细胞基质,在疫苗及生物技术产品领域得到开发应用.然而,昆虫细胞与哺乳动物细胞在细胞特性等方面存在显著差异,建立适合昆虫细胞特性的质量控制方法已经成为生物制药领域必须要解决的问题.此文仅就昆虫细胞鉴定方法研究进展做一综述,为开发及建立昆虫细胞个性化鉴别方法提供参考.

  18. Classification of Non-Small Cell Lung Cancer Using Significance Analysis of Microarray-Gene Set Reduction Algorithm

    Directory of Open Access Journals (Sweden)

    Lei Zhang

    2016-01-01

    Full Text Available Among non-small cell lung cancer (NSCLC, adenocarcinoma (AC, and squamous cell carcinoma (SCC are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR, can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.

  19. Automated detection of retinal cell nuclei in 3D micro-CT images of zebrafish using support vector machine classification

    Science.gov (United States)

    Ding, Yifu; Tavolara, Thomas; Cheng, Keith

    2016-03-01

    Our group is developing a method to examine biological specimens in cellular detail using synchrotron microCT. The method can acquire 3D images of tissue at micrometer-scale resolutions, allowing for individual cell types to be visualized in the context of the entire specimen. For model organism research, this tool will enable the rapid characterization of tissue architecture and cellular morphology from every organ system. This characterization is critical for proposed and ongoing "phenome" projects that aim to phenotype whole-organism mutants and diseased tissues from different organisms including humans. With the envisioned collection of hundreds to thousands of images for a phenome project, it is important to develop quantitative image analysis tools for the automated scoring of organism phenotypes across organ systems. Here we present a first step towards that goal, demonstrating the use of support vector machines (SVM) in detecting retinal cell nuclei in 3D images of wild-type zebrafish. In addition, we apply the SVM classifier on a mutant zebrafish to examine whether SVMs can be used to capture phenotypic differences in these images. The longterm goal of this work is to allow cellular and tissue morphology to be characterized quantitatively for many organ systems, at the level of the whole-organism.

  20. Nonlinear estimation and classification

    CERN Document Server

    Hansen, Mark; Holmes, Christopher; Mallick, Bani; Yu, Bin

    2003-01-01

    Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data This is due in part to recent advances in data collection and computing technologies As a result, fundamental statistical research is being undertaken in a variety of different fields Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future

  1. Estuary Classification Revisited

    CERN Document Server

    Guha, Anirban

    2012-01-01

    The governing equations of a tidally averaged, width averaged, rectangular estuary has been investigated. It's theoretically shown that the dynamics of an estuary is entirely controlled by three parameters: (i) the Estuarine Froude number, (ii) the Tidal Froude number and (iii) the Estuarine Aspect ratio. The momentum, salinity and integral salt balance equations can be completely expressed in terms of these control variables. The estuary classification problem has also been reinvestigated. It's found that these three control variables can completely specify the estuary type. Comparison with real estuary data shows very good match. Additionally, we show that the well accepted leading order estuarine integral salt balance equation is inconsitent with the leading order salinity equation in an order of magnitude sense.

  2. Applications of CRACK in the Classification of Integrable Systems

    OpenAIRE

    Wolf, Thomas

    2003-01-01

    Work on different classification problems is described as: the classification of integrable vector evolution equations, NLS systems with two vector unknowns, systems with one scalar and one vector unknown, classification of integrable Hamiltonians and non-local 2+1 dimensional equations. All these problems lead to large bi-linear algebraic systems to be solved. In an extended appendix an overview of the computer algebra package is given that was used to solve these systems.

  3. Accurate molecular classification of cancer using simple rules

    OpenAIRE

    Gotoh Osamu; Wang Xiaosheng

    2009-01-01

    Abstract Background One intractable problem with using microarray data analysis for cancer classification is how to reduce the extremely high-dimensionality gene feature data to remove the effects of noise. Feature selection is often used to address this problem by selecting informative genes from among thousands or tens of thousands of genes. However, most of the existing methods of microarray-based cancer classification utilize too many genes to achieve accurate classification, which often ...

  4. Wavelet-based multiscale analysis of bioimpedance data measured by electric cell-substrate impedance sensing for classification of cancerous and normal cells

    Science.gov (United States)

    Das, Debanjan; Shiladitya, Kumar; Biswas, Karabi; Dutta, Pranab Kumar; Parekh, Aditya; Mandal, Mahitosh; Das, Soumen

    2015-12-01

    The paper presents a study to differentiate normal and cancerous cells using label-free bioimpedance signal measured by electric cell-substrate impedance sensing. The real-time-measured bioimpedance data of human breast cancer cells and human epithelial normal cells employs fluctuations of impedance value due to cellular micromotions resulting from dynamic structural rearrangement of membrane protrusions under nonagitated condition. Here, a wavelet-based multiscale quantitative analysis technique has been applied to analyze the fluctuations in bioimpedance. The study demonstrates a method to classify cancerous and normal cells from the signature of their impedance fluctuations. The fluctuations associated with cellular micromotion are quantified in terms of cellular energy, cellular power dissipation, and cellular moments. The cellular energy and power dissipation are found higher for cancerous cells associated with higher micromotions in cancer cells. The initial study suggests that proposed wavelet-based quantitative technique promises to be an effective method to analyze real-time bioimpedance signal for distinguishing cancer and normal cells.

  5. Histological classification of mesial temporal sclerosis

    OpenAIRE

    D. V. Dmitrenko; M. A. Stroganova; N. A. Shnaider; G. P. Martynova; K. A. Gazenkampf; A. V. Dyuzhakova; Yu. S. Panina

    2016-01-01

    Mesial temporal sclerosis (MTS) is the most common histopathology occurring in patients with drug-resistant temporal lobe epilepsy. Over the past decades, there have been various attempts to classify the variants of hippocampal neuronal cell loss in relation to postoperative outcome. However, no consensus on the common international definition and classification of MTS has been reached. The article describes the modern histological classification based on a semiquantitative hippocampal cell l...

  6. Problem-Based Test: Replication of Mitochondrial DNA during the Cell Cycle

    Science.gov (United States)

    Setalo, Gyorgy, Jr.

    2013-01-01

    Terms to be familiar with before you start to solve the test: cell cycle, generation time, S-phase, cell culture synchronization, isotopic pulse-chase labeling, density labeling, equilibrium density-gradient centrifugation, buoyant density, rate-zonal centrifugation, nucleoside, nucleotide, kinase enzymes, polymerization of nucleic acids,…

  7. Histological classification of mesial temporal sclerosis

    Directory of Open Access Journals (Sweden)

    D. V. Dmitrenko

    2016-01-01

    Full Text Available Mesial temporal sclerosis (MTS is the most common histopathology occurring in patients with drug-resistant temporal lobe epilepsy. Over the past decades, there have been various attempts to classify the variants of hippocampal neuronal cell loss in relation to postoperative outcome. However, no consensus on the common international definition and classification of MTS has been reached. The article describes the modern histological classification based on a semiquantitative hippocampal cell loss model. The publications dealing with the histological classification of mesial temporal sclerosis are reviewed. 

  8. Neuronal Classification of Atria Fibrillation

    OpenAIRE

    Mohamed BEN MESSAOUD

    2008-01-01

    Motivation. In medical field, particularly the cardiology, the diagnosis systems constitute the essential domain of research. In some applications, the traditional methods of classification present some limitations. The neuronal technique is considered as one of the promising algorithms to resolve such problem.Method. In this paper, two approaches of the Artificial Neuronal Network (ANN) technique are investigated to classify the heart beats which are Multi Layer Perception (MLP) and Radial B...

  9. Basis of Criminalistic Classification of a Person in Republic Kazakhstan and Republic Mongolia

    Science.gov (United States)

    Abdilov, Kanat S.; Zusbaev, Baurzan T.; Naurysbaev, Erlan A.; Nukiev, Berik A.; Nurkina, Zanar B.; Myrzahanov, Erlan N.; Urazalin, Galym T.

    2016-01-01

    In this article reviewed problems of the criminalistic classification building of a person. In the work were used legal formal, logical, comparative legal methods. The author describes classification kinds. Reveal the meaning of classification in criminalistic systematics. Shows types of grounds of criminalistic classification of a person.…

  10. WHO-EORTC classification for cutaneous lymphomas.

    Science.gov (United States)

    Willemze, Rein; Jaffe, Elaine S; Burg, Günter; Cerroni, Lorenzo; Berti, Emilio; Swerdlow, Steven H; Ralfkiaer, Elisabeth; Chimenti, Sergio; Diaz-Perez, José L; Duncan, Lyn M; Grange, Florent; Harris, Nancy Lee; Kempf, Werner; Kerl, Helmut; Kurrer, Michael; Knobler, Robert; Pimpinelli, Nicola; Sander, Christian; Santucci, Marco; Sterry, Wolfram; Vermeer, Maarten H; Wechsler, Janine; Whittaker, Sean; Meijer, Chris J L M

    2005-05-15

    Primary cutaneous lymphomas are currently classified by the European Organization for Research and Treatment of Cancer (EORTC) classification or the World Health Organization (WHO) classification, but both systems have shortcomings. In particular, differences in the classification of cutaneous T-cell lymphomas other than mycosis fungoides, Sezary syndrome, and the group of primary cutaneous CD30+ lymphoproliferative disorders and the classification and terminology of different types of cutaneous B-cell lymphomas have resulted in considerable debate and confusion. During recent consensus meetings representatives of both systems reached agreement on a new classification, which is now called the WHO-EORTC classification. In this paper we describe the characteristic features of the different primary cutaneous lymphomas and other hematologic neoplasms frequently presenting in the skin, and discuss differences with the previous classification schemes. In addition, the relative frequency and survival data of 1905 patients with primary cutaneous lymphomas derived from Dutch and Austrian registries for primary cutaneous lymphomas are presented to illustrate the clinical significance of this new classification.

  11. Characterizing the DNA Damage Response by Cell Tracking Algorithms and Cell Features Classification Using High-Content Time-Lapse Analysis.

    Directory of Open Access Journals (Sweden)

    Walter Georgescu

    Full Text Available Traditionally, the kinetics of DNA repair have been estimated using immunocytochemistry by labeling proteins involved in the DNA damage response (DDR with fluorescent markers in a fixed cell assay. However, detailed knowledge of DDR dynamics across multiple cell generations cannot be obtained using a limited number of fixed cell time-points. Here we report on the dynamics of 53BP1 radiation induced foci (RIF across multiple cell generations using live cell imaging of non-malignant human mammary epithelial cells (MCF10A expressing histone H2B-GFP and the DNA repair protein 53BP1-mCherry. Using automatic extraction of RIF imaging features and linear programming techniques, we were able to characterize detailed RIF kinetics for 24 hours before and 24 hours after exposure to low and high doses of ionizing radiation. High-content-analysis at the single cell level over hundreds of cells allows us to quantify precisely the dose dependence of 53BP1 protein production, RIF nuclear localization and RIF movement after exposure to X-ray. Using elastic registration techniques based on the nuclear pattern of individual cells, we could describe the motion of individual RIF precisely within the nucleus. We show that DNA repair occurs in a limited number of large domains, within which multiple small RIFs form, merge and/or resolve with random motion following normal diffusion law. Large foci formation is shown to be mainly happening through the merging of smaller RIF rather than through growth of an individual focus. We estimate repair domain sizes of 7.5 to 11 µm2 with a maximum number of ~15 domains per MCF10A cell. This work also highlights DDR which are specific to doses larger than 1 Gy such as rapid 53BP1 protein increase in the nucleus and foci diffusion rates that are significantly faster than for spontaneous foci movement. We hypothesize that RIF merging reflects a "stressed" DNA repair process that has been taken outside physiological conditions when

  12. Gene expression classification using epigenetic features and DNA sequence composition in the human embryonic stem cell line H1.

    Science.gov (United States)

    Su, Wen-Xia; Li, Qian-Zhong; Zhang, Lu-Qiang; Fan, Guo-Liang; Wu, Cheng-Yan; Yan, Zhen-He; Zuo, Yong-Chun

    2016-10-30

    Epigenetic factors are known to correlate with gene expression in the existing studies. However, quantitative models that accurately classify the highly and lowly expressed genes based on epigenetic factors are currently lacking. In this study, a new machine learning method combines histone modifications, DNA methylation, DNA accessibility, transcription factors, and trinucleotide composition with support vector machines (SVM) is developed in the context of human embryonic stem cell line (H1). The results indicate that the predictive accuracy will be markedly improved when the epigenetic features are considered. The predictive accuracy and Matthews correlation coefficient of the best model are as high as 95.96% and 0.92 for 10-fold cross-validation test, and 95.58% and 0.92 for independent dataset test, respectively. Our model provides a good way to judge a gene is either highly or lowly expressed gene by using genetic and epigenetic data, when the expression data of the gene is lacking. And a web-server GECES for our analysis method is established at http://202.207.14.87:8032/fuwu/GECES/index.asp, so that other scientists can easily get their desired results by our web-server, without going through the mathematical details. PMID:27468948

  13. Models for warehouse management: classification and examples

    NARCIS (Netherlands)

    Berg, van den J.P.; Zijm, W.H.M.

    1999-01-01

    In this paper we discuss warehousing systems and present a classification of warehouse management problems. We start with a typology and a brief description of several types of warehousing systems. Next, we present a hierarchy of decision problems encountered in setting up warehousing systems, inclu

  14. Optimizing Mining Association Rules for Artificial Immune System based Classification

    Directory of Open Access Journals (Sweden)

    SAMEER DIXIT

    2011-08-01

    Full Text Available The primary function of a biological immune system is to protect the body from foreign molecules known as antigens. It has great pattern recognition capability that may be used to distinguish between foreigncells entering the body (non-self or antigen and the body cells (self. Immune systems have many characteristics such as uniqueness, autonomous, recognition of foreigners, distributed detection, and noise tolerance . Inspired by biological immune systems, Artificial Immune Systems have emerged during the last decade. They are incited by many researchers to design and build immune-based models for a variety of application domains. Artificial immune systems can be defined as a computational paradigm that is inspired by theoretical immunology, observed immune functions, principles and mechanisms. Association rule mining is one of the most important and well researched techniques of data mining. The goal of association rules is to extract interesting correlations, frequent patterns, associations or casual structures among sets of items in thetransaction databases or other data repositories. Association rules are widely used in various areas such as inventory control, telecommunication networks, intelligent decision making, market analysis and risk management etc. Apriori is the most widely used algorithm for mining the association rules. Other popular association rule mining algorithms are frequent pattern (FP growth, Eclat, dynamic itemset counting (DIC etc. Associative classification uses association rule mining in the rule discovery process to predict the class labels of the data. This technique has shown great promise over many other classification techniques. Associative classification also integrates the process of rule discovery and classification to build the classifier for the purpose of prediction. The main problem with the associative classification approach is the discovery of highquality association rules in a very large space of

  15. Evaluation for Uncertain Image Classification and Segmentation

    CERN Document Server

    Martin, Arnaud; Arnold-Bos, Andreas

    2008-01-01

    Each year, numerous segmentation and classification algorithms are invented or reused to solve problems where machine vision is needed. Generally, the efficiency of these algorithms is compared against the results given by one or many human experts. However, in many situations, the location of the real boundaries of the objects as well as their classes are not known with certainty by the human experts. Furthermore, only one aspect of the segmentation and classification problem is generally evaluated. In this paper we present a new evaluation method for classification and segmentation of image, where we take into account both the classification and segmentation results as well as the level of certainty given by the experts. As a concrete example of our method, we evaluate an automatic seabed characterization algorithm based on sonar images.

  16. Hand eczema classification

    DEFF Research Database (Denmark)

    Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M;

    2008-01-01

    of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  17. Rademacher Complexity in Neyman-Pearson Classification

    Institute of Scientific and Technical Information of China (English)

    Min HAN; Di Rong CHEN; Zhao Xu SUN

    2009-01-01

    Neyman-Pearson(NP) criterion is one of the most important ways in hypothesis testing.It is also a criterion for classification. This paper addresses the problem of bounding the estimation error of NP classification, in terms of Rademacher averages. We investigate the behavior of the global and local Rademacher averages, and present new NP classification error bounds which are based on the localized averages, and indicate how the estimation error can be estimated without a priori knowledge of the class at hand.

  18. Towards the automatic classification of neurons.

    Science.gov (United States)

    Armañanzas, Rubén; Ascoli, Giorgio A

    2015-05-01

    The classification of neurons into types has been much debated since the inception of modern neuroscience. Recent experimental advances are accelerating the pace of data collection. The resulting growth of information about morphological, physiological, and molecular properties encourages efforts to automate neuronal classification by powerful machine learning techniques. We review state-of-the-art analysis approaches and the availability of suitable data and resources, highlighting prominent challenges and opportunities. The effective solution of the neuronal classification problem will require continuous development of computational methods, high-throughput data production, and systematic metadata organization to enable cross-laboratory integration. PMID:25765323

  19. Interactive multiclass segmentation using superpixel classification

    OpenAIRE

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

    2015-01-01

    This paper adresses the problem of interactive multiclass segmentation. We propose a fast and efficient new interactive segmentation method called Superpixel Classification-based Interactive Segmentation (SCIS). From a few strokes drawn by a human user over an image, this method extracts relevant semantic objects. To get a fast calculation and an accurate segmentation, SCIS uses superpixel over-segmentation and support vector machine classification. In this paper, we demonstrate that SCIS sig...

  20. Extreme Entropy Machines: Robust information theoretic classification

    OpenAIRE

    Czarnecki, Wojciech Marian; Tabor, Jacek

    2015-01-01

    Most of the existing classification methods are aimed at minimization of empirical risk (through some simple point-based error measured with loss function) with added regularization. We propose to approach this problem in a more information theoretic way by investigating applicability of entropy measures as a classification model objective function. We focus on quadratic Renyi's entropy and connected Cauchy-Schwarz Divergence which leads to the construction of Extreme Entropy Machines (EEM). ...

  1. SUPERVISED TERM WEIGHTING METHODS FOR URL CLASSIFICATION

    OpenAIRE

    R. Rajalakshmi

    2014-01-01

    Many term weighting methods are suggested in the literature for Information Retrieval and Text Categorization. Term weighting method, a part of feature selection process is not yet explored for URL classification problem. We classify a web page using its URL alone without fetching its content and hence URL based classification is faster than other methods. In this study, we investigate the use of term weighting methods for selecting relevant URL features and their impact on the performance of...

  2. Analysis of thematic map classification error matrices.

    Science.gov (United States)

    Rosenfield, G.H.

    1986-01-01

    The classification error matrix expresses the counts of agreement and disagreement between the classified categories and their verification. Thematic mapping experiments compare variables such as multiple photointerpretation or scales of mapping, and produce one or more classification error matrices. This paper presents a tutorial to implement a typical problem of a remotely sensed data experiment for solution by the linear model method.-from Author

  3. Wavelet features in motion data classification

    Science.gov (United States)

    Szczesna, Agnieszka; Świtoński, Adam; Słupik, Janusz; Josiński, Henryk; Wojciechowski, Konrad

    2016-06-01

    The paper deals with the problem of motion data classification based on result of multiresolution analysis implemented in form of quaternion lifting scheme. Scheme processes directly on time series of rotations coded in form of unit quaternion signal. In the work new features derived from wavelet energy and entropy are proposed. To validate the approach gait database containing data of 30 different humans is used. The obtained results are satisfactory. The classification has over than 91% accuracy.

  4. An Approach for IRIS Plant Classification Using Neural Network

    Directory of Open Access Journals (Sweden)

    Madhusmita Swain

    2012-03-01

    Full Text Available Classification is a machine learning technique used to predict group membership for data instances. Tosimplify the problem of classification neural networks are being introduced. This paper focuses on IRIS plant classification using Neural Network. The problem concerns the identification of IRIS plant species on the basis of plant attribute measurements. Classification of IRIS data set would be discovering patterns from examining petal and sepal size of the IRIS plant and how the prediction was made from analyzing the pattern to form the class of IRIS plant. By using this pattern and classification, in future upcoming years the unknown data can be predicted more precisely. Artificial neural networks have been successfully applied to problems in pattern classification, function approximations, optimization, and associative memories. In this work, Multilayer feed- forward networks are trained using back propagation learning algorithm.

  5. Classification of articulators.

    Science.gov (United States)

    Rihani, A

    1980-03-01

    A simple classification in familiar terms with definite, clear characteristics can be adopted. This classification system is based on the number of records used and the adjustments necessary for the articulator to accept these records. The classification divides the articulators into nonadjustable, semiadjustable, and fully adjustable articulators (Table I). PMID:6928204

  6. Problems of primary T-cell lymphoma of the thyroid gland -A case report

    Directory of Open Access Journals (Sweden)

    Yokoyama Junkichi

    2012-04-01

    Full Text Available Abstract In the following report we discuss a very rare case of malignant T-cell lymphoma of the thyroid gland that developed in a 70-year-old woman with a past history of hypothyroidism due to chronic thyroiditis. The chief complaint was a rapidly growing neck mass. CT and ultrasonographic examination revealed a diffuse large thyroid gland without a nodule extending up to 13 cm. Although presence of abnormal lymphoid cells in the peripheral blood was not found, the sIL-2 Receptor antibody and thyroglobulin measured as high as 970 U/ml and 600 ng/mL respectively. Fine needle aspiration cytology diagnosed chronic thyroiditis. A preoperative diagnosis of suspicious malignant lymphoma of the thyroid gland accompanied by Hashimoto’s thyroiditis was made, and a right hemithyroidectomy was performed to definite diagnosis. Histological examination revealed diffuse small lymphocytic infiltration in the thyroid gland associated with Hashimoto’s thyroiditis. Immunohistochemical examination showed that the small lymphocytes were positive for T-cell markers with CD3 and CD45RO. The pathological diagnosis was chronic thyroiditis with atypical lymphocytes infiltration. However, Southern blot analysis of tumor specimens revealed only a monoclonal T-cell receptor gene rearrangement. Finally, peripheral T cell lymphoma was diagnosed. Therefore, the left hemithyroidectomy was also performed one month later. No adjuvant therapy was performed due to the tumor stage and its subtype. The patient is well with no recurrence or metastasis 22 months after the surgical removal of the thyroid. As malignant T-cell lymphoma of the thyroid gland with Hashimoto’s thyroiditis was difficult to diagnose, gene rearrangement examination needed to be performed concurrently.

  7. Mucinous Tubular and Spindle Cell Carcinoma of Kidney and Problems in Diagnosis

    Directory of Open Access Journals (Sweden)

    Banu SARSIK

    2011-05-01

    Full Text Available Objective: Mucinous tubular and spindle cell carcinomas (MTSCC's are recently described rare type of renal cell carcinoma (RCC. MTSCC's are characterized by small, elongated tubules lined by cuboidal cells and/or cords of spindled cells separated by pale mucinous stroma. They have morphological similarities to papillary RCC (papRCC. We evaluated the importance of the immunohistochemical features in the differential diagnosis of MTSCC and papRCC.Material and Method: We re-evaluated 9 cases of MTSCC diagnosed between 2004 and 2010 and compared 10 cases of papRCC. All tumors were stained with alpha-methylacyl-CoA racemase (AMACR, cytokeratin 7 (CK7, CK19, renal cell carcinoma marker (RCC Ma, CD10 and kidney specific cadherin (KspCad.Results: A total of 6/9 cases were considered classical. Two of 9 MTSCC's were classified as “mucin-poor”. Foamy macrophages were identified in 4 cases. The immunoreactivity in MTSCC was AMACR 100%, CK7 100%, CK19 100%, RCC Ma 50%, CD10 11%, and KspCad 38% while the values for papRCC were AMACR 100%, CK7 90%, CK19 100%, RCC Ma 100%, CD10 80%, and KspCad 0%.Conclusion: MTSCCs may include little mucin and show a marked predominance of either of its principal morphological components. They may mimic other forms of RCC. Pathologists should be aware of the histological spectrum of MTSCCs to ensure an accurate diagnosis. Careful attention to the presence of a spindle cell population may be helpful in the differential diagnosis in tumors with predominant compact tubular growth. Immunohistochemical stains for papRCC are also expressed in MTSCC, but strong CD10 expression may not favor MTSCC.

  8. Saving our science from ourselves: the plight of biological classification

    Directory of Open Access Journals (Sweden)

    Malte C. Ebach

    2011-06-01

    Full Text Available Saving our science from ourselves: the plight of biological classification. Biological classification ( nomenclature, taxonomy, and systematics is being sold short. The desire for new technologies, faster and cheaper taxonomic descriptions, identifications, and revisions is symptomatic of a lack of appreciation and understanding of classification. The problem of gadget-driven science, a lack of best practice and the inability to accept classification as a descriptive and empirical science are discussed. The worst cases scenario is a future in which classifications are purely artificial and uninformative.

  9. Harmonization of description and classification of fetal observations: Achievements and problems still unresolved. Report of the 7th Workshop on the Terminology in Developmental Toxicology Berlin, 4-6 May 2011

    NARCIS (Netherlands)

    Solecki, R.; Barbellion, S.; Bergmann, B.; Bürgin, H.; Buschmann, J.; Clark, R.; Comotto, L.; Fuchs, A.; Faqi, A.S.; Gerspach, R.; Grote, K.; Hakansson, H.; Heinrich, V.; Heinrich-Hirsch, B.; Hofmann, T.; Hübel, U.; Inazaki, T.H.; Khalil, S.; Knudsen, T.B.; Kudicke, S.; Lingk, W.; Makris, S.; Müller, S.; Paumgartten, F.; Pfeil, R.; Rama, E.M.; Schneider, S.; Shiota, K.; Tamborini, E.; Tegelenbosch, M.; Ulbrich, B.; Duijnhoven, E.A.J. van; Wise, D.; Chahoud, I.

    2013-01-01

    This article summarizes the 7th Workshop on the Terminology in Developmental Toxicology held in Berlin, May 4-6, 2011. The series of Berlin Workshops has been mainly concerned with the harmonization of terminology and classification of fetal anomalies in developmental toxicity studies. The main topi

  10. Nonparametric Bayesian Classification

    CERN Document Server

    Coram, M A

    2002-01-01

    A Bayesian approach to the classification problem is proposed in which random partitions play a central role. It is argued that the partitioning approach has the capacity to take advantage of a variety of large-scale spatial structures, if they are present in the unknown regression function $f_0$. An idealized one-dimensional problem is considered in detail. The proposed nonparametric prior uses random split points to partition the unit interval into a random number of pieces. This prior is found to provide a consistent estimate of the regression function in the $\\L^p$ topology, for any $1 \\leq p < \\infty$, and for arbitrary measurable $f_0:[0,1] \\rightarrow [0,1]$. A Markov chain Monte Carlo (MCMC) implementation is outlined and analyzed. Simulation experiments are conducted to show that the proposed estimate compares favorably with a variety of conventional estimators. A striking resemblance between the posterior mean estimate and the bagged CART estimate is noted and discussed. For higher dimensions, a ...

  11. Stem cell therapy for joint problems using the horse as a clinically relevant animal model

    DEFF Research Database (Denmark)

    Koch, Thomas Gadegaard; Betts, Dean H.

    2007-01-01

    of experimentally induced lesions. The horse lends itself as a good animal model of spontaneous joint disorders that are clinically relevant to similar human disorders. Equine stem cell and tissue engineering studies may be financially feasible to principal investigators and small biotechnology companies...

  12. A Case Study of Representing Signal Transduction in Liver Cells as a Feedback Control Problem

    Science.gov (United States)

    Singh, Abhay; Jayaraman, Arul; Hahn, Juergen

    2007-01-01

    Cell signaling pathways often contain feedback loops where proteins are produced that regulate signaling. While feedback regulatory mechanisms are commonly found in signaling pathways, there is no example available in the literature that is simple enough to be presented in an undergraduate control class. This paper presents a simulation study of…

  13. Cognitive and Academic Problems Associated with Childhood Cancers and Sickle Cell Disease

    Science.gov (United States)

    Daly, Brian P.; Kral, Mary C.; Brown, Ronald T.

    2008-01-01

    Childhood cancers and sickle cell disease represent some of the most complex medical conditions of childhood, impacting development in all domains. The influence of these conditions on cognitive functioning and academic achievement has particular relevance for the school psychologist, who is poised to promote the positive adaptation of children…

  14. Problem-Solving Test: Analysis of DNA Damage Recognizing Proteins in Yeast and Human Cells

    Science.gov (United States)

    Szeberenyi, Jozsef

    2013-01-01

    The experiment described in this test was aimed at identifying DNA repair proteins in human and yeast cells. Terms to be familiar with before you start to solve the test: DNA repair, germline mutation, somatic mutation, inherited disease, cancer, restriction endonuclease, radioactive labeling, [alpha-[superscript 32]P]ATP, [gamma-[superscript…

  15. Proceedings of the workshop on hydrocarbon processing mixing and scale-up problems. [Fuels processing for fuel cells

    Energy Technology Data Exchange (ETDEWEB)

    Gabor, J. D. [ed.

    1978-01-01

    A workshop was convened by the Division of Fossil Fuel Utilization of the US Department of Energy in cooperation with the Particulate and Multiphase Process Program of the National Science Foundation to identify needs for fundamental engineering support for the design of chemical reactors for processing heavy hydrocarbon liquids. The problems associated with dispersing liquid hydrocarbons in a reacting gas and mixing within the gas phase are of primary concern. The transactions of the workshop begin with an introduction to the immediate goals of the Department of Energy. Fuel cell systems and current research and development are reviewed. Modeling of combustion and the problems of soot formation and deposits in hydrocarbon fuels are next considered. The fluid mechanics of turbulent mixing and its effect on chemical reactions are then presented. Current experimental work and process development provide an update on the present state-of-the-art.

  16. The 2002 AJCC TNM classification is a better predictor of primary small cell esophageal carcinoma outcome than the VALSG staging system

    Institute of Scientific and Technical Information of China (English)

    Sheng-Ye Wang; Wei-Ming Mao; Xiang-Hui Du; Ya-Ping Xu; Su-Zhan Zhang

    2013-01-01

    Small cell carcinoma of the esophagus (SCCE) is a rare and aggressive malignant tumor with a poor prognosis.The optimal disease staging system and treatment approaches have not yet been defined.This study aimed to evaluate the prediction of different staging systems for prognosis and treatment options of SCCE.We retrospectively accessed the clinicopathologic characteristics,treatment strategy,and prognosis of 76 patients diagnosed with primary SCCE between 2001 and 2011.The 1-,2-,3-,and 5-year overall survival rates were 58%,31%,19%,and 13%,respectively.U nivariate analysis showed that the 2002 American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) classification (P =0.002),Veterans Administration Lung Study Group (VALSG) stage (P =0.001),predisposing factors (P < 0.001),T category (P =0.023),and M category (P < 0.001) were prognostic factors for overall survival.Multivariate analysis showed that the 2002 AJCC TNM stage (P < 0.001) was the only independent prognostic factor for survival.The value of the area under the receiver operator characteristic (ROC) curve (AUC) of the 2002 AJCC TNM staging system was larger than that of VALSG staging system with regard to predicting overall survival (0.774 vs.0.620).None of the single treatment regimens showed any benefit for survival by Cox regression analysis.Thus,the 2002 AJCC TMN staging system improved the prediction of SCCE prognosis; however,the optimal treatment regimen for SCCE remains unclear.

  17. Classification, disease, and diagnosis.

    Science.gov (United States)

    Jutel, Annemarie

    2011-01-01

    Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

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

    KAUST Repository

    Shono, Ahmad N.

    2014-05-01

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

  19. New Approach to Analyzing Physics Problems: A Taxonomy of Introductory Physics Problems

    Science.gov (United States)

    Teodorescu, Raluca E.; Bennhold, Cornelius; Feldman, Gerald; Medsker, Larry

    2013-01-01

    This paper describes research on a classification of physics problems in the context of introductory physics courses. This classification, called the Taxonomy of Introductory Physics Problems (TIPP), relates physics problems to the cognitive processes required to solve them. TIPP was created in order to design educational objectives, to develop…

  20. Support Vector Machine Classification with Indefinite Kernels

    OpenAIRE

    Luss, Ronny; d'Aspremont, Alexandre

    2008-01-01

    We propose a method for support vector machine classification using indefinite kernels. Instead of directly minimizing or stabilizing a nonconvex loss function, our algorithm simultaneously computes support vectors and a proxy kernel matrix used in forming the loss. This can be interpreted as a penalized kernel learning problem where indefinite kernel matrices are treated as a noisy observations of a true Mercer kernel. Our formulation keeps the problem convex and relatively large problems ca...

  1. [Therapeutic potential of human mesenchymal stromal cells secreted components: a problem with standartization].

    Science.gov (United States)

    Sagaradze, G D; Grigorieva, O A; Efimenko, A Yu; Chaplenko, A A; Suslina, S N; Sysoeva, V Yu; Kalinina, N I; Akopyan, Zh A; Tkachuk, V A

    2015-01-01

    Regenerative medicine approaches, such as replacement of damaged tissue by ex vivo manufactured constructions or stimulation of endogenous reparative and regenerative processes to treat different diseases, are actively developing. One of the major tools for regenerative medicine are stem and progenitor cells, including multipotent mesenchymal stem/stromal cells (MSC). Because the paracrine action of bioactive factors secreted by MSC is considered as a main mechanism underlying MSC regenerative effects, application of MSC extracellular secreted products could be a promising approach to stimulate tissue regeneration; it also has some advantages compared to the injection of the cells themselves. However, because of the complexity of composition and multiplicity of mechanisms of action distinguished the medicinal products based on bioactive factors secreted by human MSC from the most of pharmaceuticals, it is important to develop the approaches to their standardization and quality control. In the current study, based on the literature data and guidelines as well as on our own experimental results, we provided rationalization for nomenclature and methods of quality control for the complex of extracellular products secreted by human adipose-derived MSC on key indicators, such as "Identification", "Specific activity" and "Biological safety". Developed approaches were tested on the samples of conditioned media contained products secreted by MSC isolated from subcutaneous adipose tissue of 30 donors. This strategy for the standardization of innovative medicinal products and biomaterials based on the bioactive extracellular factors secreted by human MSC could be applicable for a wide range of bioactive complex products, produced using the different types of stem and progenitor cells. PMID:26716748

  2. caBIG® Spotlight - Solving Research Problems: Analyze Mouse Embryonic Stem Cell Transcriptional Profiles —

    Science.gov (United States)

    Read a case study to learn more about how Dr. Bradley Merrill of the University of Illinois at Chicago and his lab were able to perform their first gene expression array experiment comparing a mutant mouse embryonic stem cell line to a non-mutant control line using GenePattern, an application supported by the Molecular Analysis Tools Knowledge Center which provides bioinformatics tools for gene expression, proteomic and SNP analysis.

  3. A Novel Hepatocellular Carcinoma Image Classification Method Based on Voting Ranking Random Forests.

    Science.gov (United States)

    Xia, Bingbing; Jiang, Huiyan; Liu, Huiling; Yi, Dehui

    2015-01-01

    This paper proposed a novel voting ranking random forests (VRRF) method for solving hepatocellular carcinoma (HCC) image classification problem. Firstly, in preprocessing stage, this paper used bilateral filtering for hematoxylin-eosin (HE) pathological images. Next, this paper segmented the bilateral filtering processed image and got three different kinds of images, which include single binary cell image, single minimum exterior rectangle cell image, and single cell image with a size of n⁎n. After that, this paper defined atypia features which include auxiliary circularity, amendment circularity, and cell symmetry. Besides, this paper extracted some shape features, fractal dimension features, and several gray features like Local Binary Patterns (LBP) feature, Gray Level Co-occurrence Matrix (GLCM) feature, and Tamura features. Finally, this paper proposed a HCC image classification model based on random forests and further optimized the model by voting ranking method. The experiment results showed that the proposed features combined with VRRF method have a good performance in HCC image classification problem.

  4. Automatic segmentation and classification of tendon nuclei from IHC stained images

    Science.gov (United States)

    Kuok, Chan-Pang; Wu, Po-Ting; Jou, I.-Ming; Su, Fong-Chin; Sun, Yung-Nien

    2015-12-01

    Immunohistochemical (IHC) staining is commonly used for detecting cells in microscopy. It is used for analyzing many types of diseases, e.g. breast cancer. Dispersion problem often exist at cell staining which will affect the accuracy of automatic counting. In this paper, we introduce a new method to overcome this problem. Otsu's thresholding method is first applied to exclude the background, so that only cells with dispersed staining are left at foreground, and then refinement will be applied by local adaptive thresholding method according to the irregularity index of the segmented shape at foreground. The segmentation results are also compared to the refinement results using Otsu's thresholding method. Cell classification based on the shape and color indices obtained from the segmentation result is applied to determine the cell condition into normal, abnormal and suspected abnormal cases.

  5. Technical problems to be solved before the solid oxide fuel cell will be commercialized

    Energy Technology Data Exchange (ETDEWEB)

    Bagger, C.; Hendriksen, P.V.; Mogensen, M. [Riso National Lab., Roskilde (Denmark)

    1996-12-31

    The problems which must be solved before SOFC-systems are competitive with todays power production technology are of both technical and economical nature. The cost of SOFC stacks at the 25 kW level of today is about 30,000 ECU/kW and it is bound to come down to about 500 ECU/kW. The allowable cost of a SOFC system is anticipated to be around 1500 ECU/kW. As part of the Danish SOFC program (DK-SOFC) a 0.5 kW stack was built and tested during the second half of 1995. Based upon the experience gained, an economic analysis has been made. The tools required to approach an economically acceptable solution are outlined below.

  6. Realising new health technologies: problems of regulating human stem cells in the USA.

    Science.gov (United States)

    Warren-Jones, Amanda

    2012-01-01

    Stem cell technology holds the promise of radically changing medicine through the provision of better disease models; the creation of tissue, cells, and organs for therapeutic uses; and the increased personalisation of healthcare. However, the degree to which any of these developments can be realised in the USA rests upon how effective the regulatory environment is in nurturing the technology to market. This article assesses the regulation in terms of its ability to minimise factors which erode the public interest in developing medical innovations (abuse) and promoting them to the market. This requires an overarching review of patent law (and how it fits with anti-trust and contract law); as well as the general regulation of innovation through ethical review, clinical trials, market authorisation, post-market oversight; government lead regulation of stem cells; and finally incorporating the impact of self-regulation by industry. From this assessment, it becomes possible to appreciate that the optimal system of regulation is reliant upon the gentle tweaking of many factors, rather than the wholesale revision of only a few. It also becomes possible to identify that individual tools of regulation have varying impacts. For example, the patent system may be the most open to abuse by individual companies, but as a regulatory framework it has the most mechanisms for dealing with such abuses. However, the biggest impact upon curtailing abuse derives from the self-regulation of the industry. Conversely, government led regulation is open to abuse from political agendas, but it has the greatest capacity to nurture innovation productively.

  7. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  8. Object Classification via Planar Abstraction

    Science.gov (United States)

    Oesau, Sven; Lafarge, Florent; Alliez, Pierre

    2016-06-01

    We present a supervised machine learning approach for classification of objects from sampled point data. The main idea consists in first abstracting the input object into planar parts at several scales, then discriminate between the different classes of objects solely through features derived from these planar shapes. Abstracting into planar shapes provides a means to both reduce the computational complexity and improve robustness to defects inherent to the acquisition process. Measuring statistical properties and relationships between planar shapes offers invariance to scale and orientation. A random forest is then used for solving the multiclass classification problem. We demonstrate the potential of our approach on a set of indoor objects from the Princeton shape benchmark and on objects acquired from indoor scenes and compare the performance of our method with other point-based shape descriptors.

  9. Local fat treatments: classification proposal.

    Science.gov (United States)

    Pinto, Hernán

    2016-01-01

    The poor understanding of the real, intimate action mechanisms behind any aesthetic procedures is a huge problem for many Aesthetic physicians. In addition, nomenclature of and regarding any procedure has become a true barrier when speaking about medical knowledge in the Aesthetic Medicine field since marketing and science often collide one another. Medical procedures for localized fat reduction are very different from each other and it is, at least, inaccurate to refer to all of them plainly as "fat reduction methods." A specific classification has become urgent and its categories should be able to imply what each method entails. For this classification proposal, "reversibility," "membrane disruption or inflammation," and "action selectivity," have been the selected criteria. PMID:27144093

  10. A clinical classification of hypertension

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    @@ Hypertension is a common cardiovascular problem worldwide. As with any other disease it is important to assess the severity of the disease. However the present classification of hypertension by the Joint National Committee in its seventh report (JNC 7) with numerical values staging the severity of hypertension is theoretically correct but difficult to apply in practice (Table 1).1 Admittedly this is a step in the right direction with lesser number of stages compared to the sixth report.2 The World Health Organization- International Society of Hypertension (WHO-ISH)-1999 3 and the European Society of Hypertension - European Society of Cardiology (ESH-ESC)4 guidelines follow similar numerical classifications (Table 2). All these papers are referred to as 'guidelines' in this article.

  11. Research on a Chnese Text Automatic Classification Method%一种中文文本自动分类方法的研究

    Institute of Scientific and Technical Information of China (English)

    尹桂秀

    2002-01-01

    This article introduces a Chinese text automatic classification method, including its principle and classification process. The article focuses on some key theoretical problems, such as word classification, keyword collection and keyword matching.

  12. 我国儿童分级阅读存在的问题及对策%The Problems and Countermeasures in Classification Reading of Children in Our Country

    Institute of Scientific and Technical Information of China (English)

    王新利

    2012-01-01

    分级阅读作为少年儿童的阅读模式,是经过实践证明的提高少儿阅读能力的有效方法,已成为一种世界性的趋势。图书馆应依据社会需求,发挥优势,推动儿童分级阅读,在服务创新中寻求更为广阔的发展空间。%As children reading model the classification reading is the effective method that has proven to improve the reading ability of children and has become a worldwide trend. The relationship of library and children reading is primitive and inevitable. Library should play advantage to promote the classification reading of children and seek for wider development space in service innovation according to social needs.

  13. Role of NG2 Expressing Cells in Addiction: A New approach for an Old Problem

    Directory of Open Access Journals (Sweden)

    Sucharita eSomkuwar

    2014-12-01

    Full Text Available Neuron-glial antigen 2 (NG2 is a proteoglycan expressed predominantly in oligodendrocyte progenitor cells (OPCs. NG2-expressing OPCs (NG2-OPCs are self-renewing cells that are widely distributed in the grey and white matter areas of the central nervous system. NG2-OPCs can mature into premyelinating oligodendrocytes and myelinating oligodendroglia which serve as the primary source of myelin in the brain. This review characterizes NG2-OPCs in brain structure and function, conceptualizes the role of NG2-OPCs in brain regions associated with negative reinforcement and relapse to drug seeking and discusses how NG2-OPCs are regulated by neuromodulators linked to motivational withdrawal. We hope to provide the readers with an overview of the role of NG2-OPCs in brain structure and function in the context of negative affect state in substance abuse disorders and to integrate our current understanding of the physiological significance of the NG2-OPCs in the adult brain.

  14. Sentiment classification technology based on Markov logic networks

    Science.gov (United States)

    He, Hui; Li, Zhigang; Yao, Chongchong; Zhang, Weizhe

    2016-07-01

    With diverse online media emerging, there is a growing concern of sentiment classification problem. At present, text sentiment classification mainly utilizes supervised machine learning methods, which feature certain domain dependency. On the basis of Markov logic networks (MLNs), this study proposed a cross-domain multi-task text sentiment classification method rooted in transfer learning. Through many-to-one knowledge transfer, labeled text sentiment classification, knowledge was successfully transferred into other domains, and the precision of the sentiment classification analysis in the text tendency domain was improved. The experimental results revealed the following: (1) the model based on a MLN demonstrated higher precision than the single individual learning plan model. (2) Multi-task transfer learning based on Markov logical networks could acquire more knowledge than self-domain learning. The cross-domain text sentiment classification model could significantly improve the precision and efficiency of text sentiment classification.

  15. Problem-based learning on cell biology and ecophysiology using integrated laboratory and computational activities

    Directory of Open Access Journals (Sweden)

    C. Sousa

    2016-03-01

    Full Text Available Since all the known biological systems require water for their basic biochemical processes, one can find several osmoregulation mechanisms on living organisms for adaptation to related environmental challenges. Osmosis is a cellular mechanism of water movement across membranes which is known to be present throughout the tree of life and occurs by either diffusion across the membrane bilayer or by a faster movement mediated by transmembrane channel proteins, called aquaporins. The expression of aquaporins is regulated at, the cellular level, by environment conditions such as hydric stress, therefore allowing the adaptation of organisms to increase salinity in soils, water deprivation and increase beverage intake.  Osmosis and diffusion concepts have been described to be difficult to learn, so, in order to promote meaningfull learning, we used a problem-based learning approach that integrates a laboratory activity and a computer simulation model of osmosis and a two phase conceptual mapping. We observed that high school students developed adequate laboratory skills and were able to communicate their results as text and using scientific drawings; and the learning environment was adequate. Therefore we presented a successful implementation case of integrated PBL, in a public portuguese school, that may constitute an example to facilitate the implementation of active inquiry strategies by other teachers, as well as the basis for future research.

  16. Breaking the barriers of all-polymer solar cells: Solving electron transporter and morphology problems

    Science.gov (United States)

    Gavvalapalli, Nagarjuna

    All-polymer solar cells (APSC) are a class of organic solar cells in which hole and electron transporting phases are made of conjugated polymers. Unlike polymer/fullerene solar cell, photoactive material of APSC can be designed to have hole and electron transporting polymers with complementary absorption range and proper frontier energy level offset. However, the highest reported PCE of APSC is 5 times less than that of polymer/fullerene solar cell. The low PCE of APSC is mainly due to: i) low charge separation efficiency; and ii) lack of optimal morphology to facilitate charge transfer and transport; and iii) lack of control over the exciton and charge transport in each phase. My research work is focused towards addressing these issues. The charge separation efficiency of APSC can be enhanced by designing novel electron transporting polymers with: i) broad absorption range; ii) high electron mobility; and iii) high dielectric constant. In addition to with the above parameters chemical and electronic structure of the repeating unit of conjugated polymer also plays a role in charge separation efficiency. So far only three classes of electron transporting polymers, CN substituted PPV, 2,1,3-benzothiadiazole derived polymers and rylene diimide derived polymers, are used in APSC. Thus to enhance the charge separation efficiency new classes of electron transporting polymers with the above characteristics need to be synthesized. I have developed a new straightforward synthetic strategy to rapidly generate new classes of electron transporting polymers with different chemical and electronic structure, broad absorption range, and high electron mobility from readily available electron deficient monomers. In APSCs due to low entropy of mixing, polymers tend to micro-phase segregate rather than forming the more useful nano-phase segregation. Optimizing the polymer blend morphology to obtain nano-phase segregation is specific to the system under study, time consuming, and not

  17. Functional studies of microRNAs in neural stem cells: problems and perspectives.

    Directory of Open Access Journals (Sweden)

    Malin eÅkerblom

    2012-02-01

    Full Text Available In adult mammals, neural stem cells (NSCs are found in two niches of the brain; the subventricular zone at the lateral ventricle and the subgranular zone of the dentate gyrus in the hippocampus. Neurogenesis is a complex process that is tightly controlled on a molecular level. Recently, microRNAs (miRNAs have been implicated to play a central role in the regulation of NCSs. miRNAs are small, endogenously expressed RNAs that regulate gene expression at the post-transcriptional level. However, functional studies of miRNAs are complicated due to current technical limitations. In this review we describe recent findings about miRNAs in NSCs looking closely at miR-124, miR-9 and let-7. We also highlight technical strategies used to investigate miRNA function, accentuating limitations and potentials.

  18. Sparse Partial Least Squares Classification for High Dimensional Data*

    OpenAIRE

    Chung, Dongjun; Keles, Sunduz

    2010-01-01

    Partial least squares (PLS) is a well known dimension reduction method which has been recently adapted for high dimensional classification problems in genome biology. We develop sparse versions of the recently proposed two PLS-based classification methods using sparse partial least squares (SPLS). These sparse versions aim to achieve variable selection and dimension reduction simultaneously. We consider both binary and multicategory classification. We provide analytical and simulation-based i...

  19. One-Class Classification with Extreme Learning Machine

    OpenAIRE

    Qian Leng; Honggang Qi; Jun Miao; Wentao Zhu; Guiping Su

    2015-01-01

    One-class classification problem has been investigated thoroughly for past decades. Among one of the most effective neural network approaches for one-class classification, autoencoder has been successfully applied for many applications. However, this classifier relies on traditional learning algorithms such as backpropagation to train the network, which is quite time-consuming. To tackle the slow learning speed in autoencoder neural network, we propose a simple and efficient one-class classif...

  20. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  1. Classification of Itch.

    Science.gov (United States)

    Ständer, Sonja

    2016-01-01

    Chronic pruritus has diverse forms of presentation and can appear not only on normal skin [International Forum for the Study of Itch (IFSI) classification group II], but also in the company of dermatoses (IFSI classification group I). Scratching, a natural reflex, begins in response to itch. Enough damage can be done to the skin by scratching to cause changes in the primary clinical picture, often leading to a clinical picture predominated by the development of chronic scratch lesions (IFSI classification group III). An internationally recognized, standardized classification system was created by the IFSI to not only aid in clarifying terms and definitions, but also to harmonize the global nomenclature for itch. PMID:27578063

  2. Classification and Regression Tree Analysis of Clinical Patterns to Predict the Survival of Patients with Advanced Non-small Cell Lung Cancer Treated with Erlotinib

    Directory of Open Access Journals (Sweden)

    Yutao LIU

    2011-10-01

    Full Text Available Background and objective Erlotinib is a targeted therapy drug for non-small cell lung cancer (NSCLC. It has been proven that, there was evidence of various survival benefits derived from erlotinib in patients with different clinical features, but the results are conflicting. The aim of this study is to identify novel predictive factors and explore the interactions between clinical variables as well as their impact on the survival of Chinese patients with advanced NSCLC heavily treated with erlotinib. Methods The clinical and follow-up data of 105 Chinese NSCLC patients referred to the Cancer Hospital and Institute, Chinese Academy of Medical Sciences from September 2006 to September 2009 were analyzed. Multivariate analysis of progressive-free survival (PFS was performed using recursive partitioning referred to as the classification and regression tree (CART analysis. Results The median PFS of 105 eligible consecutive Chinese NSCLC patients was 5.0 months (95%CI: 2.9-7.1. CART analysis was performed for the initial, second, and third split in the lymph node involvement, the time of erlotinib administration, and smoking history. Four terminal subgroups were formed. The longer values for the median PFS were 11.0 months (95%CI: 8.9-13.1 for the subgroup with no lymph node metastasis and 10.0 months (95%CI: 7.9-12.1 for the subgroup with lymph node involvement, but not over the second-line erlotinib treatment with a smoking history ≤35 packs per year. The shorter values for the median PFS were 2.3 months (95%CI: 1.6-3.0 for the subgroup with lymph node metastasis and over the second-line erlotinib treatment, and 1.3 months (95%CI: 0.5-2.1 for the subgroup with lymph node metastasis, but not over the second-line erlotinib treatment with a smoking history >35 packs per year. Conclusion Lymph node metastasis, the time of erlotinib administration, and smoking history are closely correlated with the survival of advanced NSCLC patients with first- to

  3. A contemporary definition and classification of hydrocephalus.

    Science.gov (United States)

    Rekate, Harold L

    2009-03-01

    This review focuses on the problems related to defining hydrocephalus and on the development of a consensus on the classification of this common problem. Such a consensus is needed so that diverse research efforts and plans of treatment can be understood in the same context. The literature was searched to determine the definition of hydrocephalus and to identify previously proposed classification schemes. The historic perspective, purpose, and result of these classifications are reviewed and analyzed. The concept of the hydrodynamics of cerebrospinal fluid (CSF) as a hydraulic circuit is presented to serve as a template for a contemporary classification scheme. Finally, a definition and classification that include all clinical causes and forms of hydrocephalus are suggested. The currently accepted classification of hydrocephalus into "communicating" and "noncommunicating" varieties is almost 90 years old and has not been modified despite major advances in neuroimaging, neurosciences, and treatment outcomes. Despite a thorough search of the literature using computerized search engines and bibliographies from review articles and book chapters, I identified only 6 previous attempts to define and classify different forms of hydrocephalus. This review proposes the following definition for hydrocephalus: hydrocephalus is an active distension of the ventricular system of the brain related to inadequate passage of CSF from its point of production within the ventricular system to its point of absorption into the systemic circulation. Based on this definition (potential points of flow restriction) and on the view of the CSF system as a hydraulic circuit, a classification system is proposed. The acceptance of this proposed definition and classification schema would allow clinicians and basic scientists to communicate effectively, to share information and results, and to develop testable hypotheses.

  4. Classification of titanium dioxide

    International Nuclear Information System (INIS)

    In this work the X-ray diffraction (XRD), Scanning Electron Microscopy (Sem) and the X-ray Dispersive Energy Spectroscopy techniques are used with the purpose to achieve a complete identification of phases and mixture of phases of a crystalline material as titanium dioxide. The problem for solving consists of being able to distinguish a sample of titanium dioxide being different than a titanium dioxide pigment. A standard sample of titanium dioxide with NIST certificate is used, which indicates a purity of 99.74% for the TiO2. The following way is recommended to proceed: a)To make an analysis by means of X-ray diffraction technique to the sample of titanium dioxide pigment and on the standard of titanium dioxide waiting not find differences. b) To make a chemical analysis by the X-ray Dispersive Energy Spectroscopy via in a microscope, taking advantage of the high vacuum since it is oxygen which is analysed and if it is concluded that the aluminium oxide appears in a greater proportion to 1% it is established that is a titanium dioxide pigment, but if it is lesser then it will be only titanium dioxide. This type of analysis is an application of the nuclear techniques useful for the tariff classification of merchandise which is considered as of difficult recognition. (Author)

  5. Concepts of Classification and Taxonomy. Phylogenetic Classification

    CERN Document Server

    Fraix-Burnet, Didier

    2016-01-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works. 1 Why phylogenetic tools in astrophysics? 1.1 History of classification The need for classifying living organisms is very ancient, and the first classification system can be dated back to the Greeks. The goal was very practical since it was intended to distinguish between eatable and toxic aliments, or kind and dangerous animals. Simple resemblance was used and has been used for centuries. Basically, until the XVIIIth...

  6. State of the art: Multi-fuel reformers for automotive fuel cell applications. Problem identification and research needs

    Energy Technology Data Exchange (ETDEWEB)

    Westerholm, R. [Stockholm Univ. (Sweden). Dept. of Analytical Chemistry; Pettersson, L.J. [Royal Inst. of Tech., Stockholm (Sweden). Dept. of Chemical Engineering and Technology

    1999-12-01

    On an assignment from the Transport and Communications Research Board (KFB) a literature study and a study trip to the USA and Great Britain have been performed. The literature study and the study trip was made during late spring and autumn 1999.The purpose of the project was to collect available information about the chemical composition of the product gas from a multi-fuel reformer for a fuel cell vehicle. It was furthermore to identify problems and research needs. The report recommends directions for future major research efforts. The results of the literature study and the study trip led to the following general conclusions: With the technology available today it does not seem feasible to develop a highly efficient and reliable multi-fuel reformer for automotive applications, i. e. for applications where all types of fuels ranging from natural gas to heavy diesel fuels can be used. The potential for developing a durable and reliable system is considerably higher if dedicated fuel reformers are used.The authors propose that petroleum-derived fuels should be designed for potential use in mobile fuel cell applications. In the present literature survey and the site visit discussions we found that there are relatively low emissions from fuel cell engines compared to internal combustion engines. However, the major research work on reformers/fuel cells have been performed during steady-state operation. Emissions during start-up, shutdown and transient operation are basically unknown and must be investigated in more detail. The conclusions and findings in this report are based on open/available information, such as discussions at site visits, reports, scientific publications and symposium proceedings.

  7. A Classification Table for Achondrites

    Science.gov (United States)

    Chennaoui-Aoudjehane, H.; Larouci, N.; Jambon, A.; Mittlefehldt, D. W.

    2014-01-01

    Classifying chondrites is relatively easy and the criteria are well documented. It is based on mineral compositions, textural characteristics and more recently, magnetic susceptibility. It can be more difficult to classify achondrites, especially those that are very similar to terrestrial igneous rocks, because mineralogical, textural and compositional properties can be quite variable. Achondrites contain essentially olivine, pyroxenes, plagioclases, oxides, sulphides and accessory minerals. Their origin is attributed to differentiated parents bodies: large asteroids (Vesta); planets (Mars); a satellite (the Moon); and numerous asteroids of unknown size. In most cases, achondrites are not eye witnessed falls and some do not have fusion crust. Because of the mineralogical and magnetic susceptibility similarity with terrestrial igneous rocks for some achondrites, it can be difficult for classifiers to confirm their extra-terrestrial origin. We -as classifiers of meteorites- are confronted with this problem with every suspected achondrite we receive for identification. We are developing a "grid" of classification to provide an easier approach for initial classification. We use simple but reproducible criteria based on mineralogical, petrological and geochemical studies. We presented the classes: acapulcoites, lodranites, winonaites and Martian meteorites (shergottite, chassignites, nakhlites). In this work we are completing the classification table by including the groups: angrites, aubrites, brachinites, ureilites, HED (howardites, eucrites, and diogenites), lunar meteorites, pallasites and mesosiderites. Iron meteorites are not presented in this abstract.

  8. Neuronal Classification of Atria Fibrillation

    Directory of Open Access Journals (Sweden)

    Mohamed BEN MESSAOUD

    2008-06-01

    Full Text Available Motivation. In medical field, particularly the cardiology, the diagnosis systems constitute the essential domain of research. In some applications, the traditional methods of classification present some limitations. The neuronal technique is considered as one of the promising algorithms to resolve such problem.Method. In this paper, two approaches of the Artificial Neuronal Network (ANN technique are investigated to classify the heart beats which are Multi Layer Perception (MLP and Radial Basis Function (RBF. A calculation algorithm of the RBF centers is proposed. For the Atria Fibrillation anomalies, an artificial neural network was used as a pattern classifier to distinguish three classes of the cardiac arrhythmias. The different classes consist of the normal beats (N, the Arrhythmia (AFA and Tachycardia (TFA Atria Fibrillation cases. The global and the partition classifier are performed. The arrhythmias of MIT-BIH database are analyzed. The ANN inputs are the temporal and morphological parameters deduced from the electrocardiograph.Results. The simulation results illustrate the performances of the studied versions of the neural network and give the fault detection rate of the tested data, a rate of classification reaching the 3.7%.Conclusion. This system can constitute a mesh in a chain of automated diagnosis and can be a tool for assistance for the classification of the cardiac anomalies in the services of urgencies before the arrival of a qualified personal person.

  9. Designing a Classification System for Internet Offenders: Doing Cognitive Distortions

    Science.gov (United States)

    Hundersmarck, Steven F.; Durkin, Keith F.; Delong, Ronald L.

    2007-01-01

    Televised features such as NBC's "To Catch a Predator" have highlighted the growing problem posed by Internet sexual predators. This paper reports on the authors' attempts in designing a classification system for Internet offenders. The classification system was designed based on existing theory, understanding the nature of Internet offenders and…

  10. Taxonomies of Educational Objectives and Theories of Classification.

    Science.gov (United States)

    Travers, Robert M. W.

    1980-01-01

    Classification is the taxonomic science in which a system of categories is established and in which the categories have some logical structure. Scientific classifications have included those by Aristotle, Linnaeus, and Lavoisier. Educational taxonomies include those developed by Bloom, Herbart, Dewey, and Piaget. The problems of taxonomy…

  11. New Considerations for Spectral Classification of Boolean Switching Functions

    Directory of Open Access Journals (Sweden)

    J. E. Rice

    2011-01-01

    Full Text Available This paper presents some new considerations for spectral techniques for classification of Boolean functions. These considerations incorporate discussions of the feasibility of extending this classification technique beyond n=5. A new implementation is presented along with a basic analysis of the complexity of the problem. We also note a correction to results in this area that were reported in previous work.

  12. Prototype Selection for Classification in Standard and Generalized Dissimilarity Spaces

    NARCIS (Netherlands)

    Plasencia Calaña, Y.

    2015-01-01

    Automatic pattern classification for a given problem domain aims at assigning a class or category membership to a new unseen object from the same domain. This is performed in three main stages: data preprocessing, representation and classification. The data preprocessing highly depends on the data t

  13. Library Classification 2020

    Science.gov (United States)

    Harris, Christopher

    2013-01-01

    In this article the author explores how a new library classification system might be designed using some aspects of the Dewey Decimal Classification (DDC) and ideas from other systems to create something that works for school libraries in the year 2020. By examining what works well with the Dewey Decimal System, what features should be carried…

  14. Musings on galaxy classification

    International Nuclear Information System (INIS)

    Classification schemes and their utility are discussed with a number of examples, particularly for cD galaxies. Data suggest that primordial turbulence rather than tidal torques is responsible for most of the presently observed angular momentum of galaxies. Finally, some of the limitations on present-day schemes for galaxy classification are pointed out. 54 references, 4 figures, 3 tables

  15. High-order integral equations for electromagnetic problems in layered media with applications in biology and solar cells

    Science.gov (United States)

    Zinser, Brian

    We present two distinct mathematical models where high-order integral equations are applied to electromagnetic problems. The first problem is to find the electric potential in and around ion channels and Janus particles. The second problem is to find the electromagnetic scattering caused by a set of simple geometric objects. In biology, we consider two types of inhomogeneities: the first one is a simple model of an ion channel which consists of a finite height cylindrical cavity embedded in a layered electrolytes/membrane environment, and the second one is a Janus particle made of two different semi-spherical dielectric materials. A boundary element method (BEM) for the Poisson-Boltzmann equation based on Muller's hyper-singular second kind integral equation formulation is used to accurately compute electrostatic potentials. The proposed BEM gives O(1) condition numbers and we show that the second order basis converges faster and is more accurate than the first order basis. For solar cells, we develop a Nystrom volume integral equation (VIE) method for calculating the electromagnetic scattering according to the Maxwell equations. The Cauchy principal values (CPVs) that arise from the VIE are computed using a finite size exclusion volume with explicit correction integrals. Outside the exclusion, the hyper-singular integrals are computed using an interpolated quadrature formulae with tensor-product quadrature nodes. We considered cubes, rectangles, cylinders, spheres, and ellipsoids. As the new quadrature weights are pre-calculated and tabulated, the integrals are calculated efficiently at runtime. Simulations with many scatterers demonstrate the efficiency of the interpolated quadrature formulae. We also demonstrate that the resulting VIE has high accuracy and p-convergence.

  16. Research on Network Information Classification Retrieval%网络信息分类检索问题研究

    Institute of Scientific and Technical Information of China (English)

    刘晓晨; 景昊

    2001-01-01

    This paper studies network information classification retrieval from the theory of information management. With a brief introduction to search engines, it focuses on analyzing the characteristics of network documents and their classification system. Problems in network document classification are pointed out. Suggestions such as constructing a catalog classification search engine system are made.

  17. Imaging Classification of Cervical Lymph Nodes

    Directory of Open Access Journals (Sweden)

    Gh. Bakhshandepour

    2008-01-01

    Full Text Available Nearly four decades, Rouviere classification, which is a clinically based system, was the only system for cervical adenopathy classification. The best possible classification of cervical nodal disease may be accomplished by using both clinical palpation and also informations provided by imaging, because imaging can reveal clinically silent lymph nodes. most head and neck tumors spread to the neck nodes as a part of their natural history ,depending on the primary site. Up to 80% of patients with upper aerodigestive mucosal malignancies will have cervical nodal metastasis"nat presentation.The occurrence of nodal metastasis has a profound effect on the management and prognosis of the patients .nodal metastasis is the most important prognostic factor in squamous cell carcinoma of the head and neck. In general it decreases the overall survival by half, and extracapsular spread worsens the prognosis by another half. Our purpose in this presentation is to review imaging classification of cervical lymph nodes.

  18. VOCAL SEGMENT CLASSIFICATION IN POPULAR MUSIC

    DEFF Research Database (Denmark)

    Feng, Ling; Nielsen, Andreas Brinch; Hansen, Lars Kai

    2008-01-01

    This paper explores the vocal and non-vocal music classification problem within popular songs. A newly built labeled database covering 147 popular songs is announced. It is designed for classifying signals from 1sec time windows. Features are selected for this particular task, in order to capture...

  19. Dense Iterative Contextual Pixel Classification using Kriging

    DEFF Research Database (Denmark)

    Ganz, Melanie; Loog, Marco; Brandt, Sami;

    2009-01-01

    have been proposed to this end, e.g., iterative contextual pixel classification, iterated conditional modes, and other approaches related to Markov random fields. A problem of these methods, however, is their computational complexity, especially when dealing with high-resolution images in which...

  20. Towards a Useful Classification of Learning Objects

    Science.gov (United States)

    Churchill, Daniel

    2007-01-01

    The learning object remains an ill-defined concept, despite numerous and extensive discussion in the literature. This paper attempts to address this problem by providing a classification that potentially brings together various perspectives of what a learning object may be. Six unique types of learning objects are proposed and discussed:…

  1. Analysis of Some Problems about Annotation of Auxiliary Tables for Subdivisions in Chinese Library Classification ( Sth Edition )%浅析《中图法》(第五版)通用复分表的注释说明

    Institute of Scientific and Technical Information of China (English)

    周卫妮

    2011-01-01

    指出《中图法》(5版)通用复分表里的中国地区表和中国民族表里的某些注释说明存在着复分时概念重复的问题,并对这些问题进行了分析,文后以通用复分表的中国时代表的注释说明为基础,提出了修改中国地区表和中国民族表里不合理注释的建议和方法。%This article points out some problems about annotations unreasonable in Chinese Areas Table and Chinese National Table of Chinese Library Classification ( 5th Edition), and these problems are analyzed. The author puts forward suggestions and methods to modify unreasonable annotation in Chinese Areas Table and Chinese National Table of Chinese Library Classification ( 5th Edition).

  2. Information Classification on University Websites

    DEFF Research Database (Denmark)

    Nawaz, Ather; Clemmensen, Torkil; Hertzum, Morten

    2011-01-01

    classification of 14 Danish and 14 Pakistani students and compares it with the information classification of their university website. Brainstorming, card sorting and task exploration activities were used to discover similarities and differences in the participating students’ classification of website...

  3. Information Classification on University Websites

    DEFF Research Database (Denmark)

    Nawaz, Ather; Clemmensen, Torkil; Hertzum, Morten

    2011-01-01

    classification of 14 Danish and 14 Pakistani students and compares it with the information classification of their university website. Brainstorming, card sorting, and task exploration activities were used to discover similarities and differences in the participating students’ classification of website...

  4. Performance Analysis of Texture Image Classification Using Wavelet Feature

    Directory of Open Access Journals (Sweden)

    Dolly Choudhary

    2013-01-01

    Full Text Available This paper compares the performance of various classifiers for multi class image classification. Where the features are extracted by the proposed algorithm in using Haar wavelet coefficient. The wavelet features are extracted from original texture images and corresponding complementary images. As it is really very difficult to decide which classifier would show better performance for multi class image classification. Hence, this work is an analytical study of performance of various classifiers for the single multiclass classification problem. In this work fifteen textures are taken for classification using Feed Forward Neural Network, Naïve Bays Classifier, K-nearest neighbor Classifier and Cascaded Neural Network.

  5. Amoeba-based computing for traveling salesman problem: long-term correlations between spatially separated individual cells of Physarum polycephalum.

    Science.gov (United States)

    Zhu, Liping; Aono, Masashi; Kim, Song-Ju; Hara, Masahiko

    2013-04-01

    A single-celled, multi-nucleated amoeboid organism, a plasmodium of the true slime mold Physarum polycephalum, can perform sophisticated computing by exhibiting complex spatiotemporal oscillatory dynamics while deforming its amorphous body. We previously devised an "amoeba-based computer (ABC)" to quantitatively evaluate the optimization capability of the amoeboid organism in searching for a solution to the traveling salesman problem (TSP) under optical feedback control. In ABC, the organism changes its shape to find a high quality solution (a relatively shorter TSP route) by alternately expanding and contracting its pseudopod-like branches that exhibit local photoavoidance behavior. The quality of the solution serves as a measure of the optimality of which the organism maximizes its global body area (nutrient absorption) while minimizing the risk of being illuminated (exposure to aversive stimuli). ABC found a high quality solution for the 8-city TSP with a high probability. However, it remains unclear whether intracellular communication among the branches of the organism is essential for computing. In this study, we conducted a series of control experiments using two individual cells (two single-celled organisms) to perform parallel searches in the absence of intercellular communication. We found that ABC drastically lost its ability to find a solution when it used two independent individuals. However, interestingly, when two individuals were prepared by dividing one individual, they found a solution for a few tens of minutes. That is, the two divided individuals remained correlated even though they were spatially separated. These results suggest the presence of a long-term memory in the intrinsic dynamics of this organism and its significance in performing sophisticated computing. PMID:23438635

  6. Contributions to "k"-Means Clustering and Regression via Classification Algorithms

    Science.gov (United States)

    Salman, Raied

    2012-01-01

    The dissertation deals with clustering algorithms and transforming regression problems into classification problems. The main contributions of the dissertation are twofold; first, to improve (speed up) the clustering algorithms and second, to develop a strict learning environment for solving regression problems as classification tasks by using…

  7. Comparing complete and partial classification for identifying customers at risk

    NARCIS (Netherlands)

    Bloemer, J.M.M.; Brijs, T.; Vanhoof, K.; Swinnen, S.P.

    2003-01-01

    This paper evaluates complete versus partial classification for the problem of identifying customers at risk. We define customers at risk as customers reporting overall satisfaction, but these customers also possess characteristics that are strongly associated with dissatisfied customers. This defin

  8. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  9. Classification of hand eczema

    DEFF Research Database (Denmark)

    Agner, T; Aalto-Korte, K; Andersen, K E;

    2015-01-01

    BACKGROUND: Classification of hand eczema (HE) is mandatory in epidemiological and clinical studies, and also important in clinical work. OBJECTIVES: The aim was to test a recently proposed classification system of HE in clinical practice in a prospective multicentre study. METHODS: Patients were......%) could not be classified. 38% had one additional diagnosis and 26% had two or more additional diagnoses. Eczema on feet was found in 30% of the patients, statistically significantly more frequently associated with hyperkeratotic and vesicular endogenous eczema. CONCLUSION: We find that the classification...

  10. Pitch Based Sound Classification

    OpenAIRE

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U.

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classif...

  11. Hybrid Data Reduction Technique for Classification of Transaction Data

    OpenAIRE

    Udo, Ifiok,; Afolabi, Babajide

    2011-01-01

    International audience Data classification problems during the process of mining transaction data requires robust and efficient data reduction technique to guard against loss of essential level information. In this paper, we have addressed the concepts of data reduction in transaction processing systems. The tradeoffs of data reduction techniques are being presented and a hybrid technique for data reduction suitable for addressing classification problems of transaction data is proposed. ...

  12. MEDICAL DIAGNOSIS CLASSIFICATION USING MIGRATION BASED DIFFERENTIAL EVOLUTION ALGORITHM

    Directory of Open Access Journals (Sweden)

    Htet Thazin Tike Thein

    2014-12-01

    Full Text Available Constructing a classification model is important in machine learning for a particular task. A classification process involves assigning objects into predefined groups or classes based on a number of observed attributes related to those objects. Artificial neural network is one of the classification algorithms which, can be used in many application areas. This paper investigates the potential of applying the feed forward neural network architecture for the classification of medical datasets. Migration based differential evolution algorithm (MBDE is chosen and applied to feed forward neural network to enhance the learning process and the network learning is validated in terms of convergence rate and classification accuracy. In this paper, MBDE algorithm with various migration policies is proposed for classification problems using medical diagnosis.

  13. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-09-09

    ... process in March 2012 (77 FR 5379). When verified by a futures classification, Smith-Doxey data serves as... Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed... for the addition of an optional cotton futures classification procedure--identified and known...

  14. Inter-rater reliability of the EPUAP pressure ulcer classification system using photographs.

    NARCIS (Netherlands)

    Defloor, T.; Schoonhoven, L.

    2004-01-01

    BACKGROUND: Many classification systems for grading pressure ulcers are discussed in the literature. Correct identification and classification of a pressure ulcer is important for accurate reporting of the magnitude of the problem, and for timely prevention. The reliability of pressure ulcer classif

  15. Classification of Small UAVs and Birds by Micro-Doppler Signatures

    NARCIS (Netherlands)

    Molchanov, P.; Egiazarian, K.; Astola, J.; Harmanny, R.I.A.; Wit, J.J.M. de

    2013-01-01

    The problem of unmanned aerial vehicles classification using continuous wave radar is considered in this paper. Classification features are extracted from micro-Doppler signature. Before the classification, the micro-Doppler signature is filtered and aligned to compensate the Doppler shift caused by

  16. Genomic data sampling and its effect on classification performance assessment

    Directory of Open Access Journals (Sweden)

    Azuaje Francisco

    2003-01-01

    Full Text Available Abstract Background Supervised classification is fundamental in bioinformatics. Machine learning models, such as neural networks, have been applied to discover genes and expression patterns. This process is achieved by implementing training and test phases. In the training phase, a set of cases and their respective labels are used to build a classifier. During testing, the classifier is used to predict new cases. One approach to assessing its predictive quality is to estimate its accuracy during the test phase. Key limitations appear when dealing with small-data samples. This paper investigates the effect of data sampling techniques on the assessment of neural network classifiers. Results Three data sampling techniques were studied: Cross-validation, leave-one-out, and bootstrap. These methods are designed to reduce the bias and variance of small-sample estimations. Two prediction problems based on small-sample sets were considered: Classification of microarray data originating from a leukemia study and from small, round blue-cell tumours. A third problem, the prediction of splice-junctions, was analysed to perform comparisons. Different accuracy estimations were produced for each problem. The variations are accentuated in the small-data samples. The quality of the estimates depends on the number of train-test experiments and the amount of data used for training the networks. Conclusion The predictive quality assessment of biomolecular data classifiers depends on the data size, sampling techniques and the number of train-test experiments. Conservative and optimistic accuracy estimations can be obtained by applying different methods. Guidelines are suggested to select a sampling technique according to the complexity of the prediction problem under consideration.

  17. Object classification using local subspace projection

    Science.gov (United States)

    Nealy, Jennifer; Muise, Robert

    2011-06-01

    We consider the problem of object classification from image data. Significant challenges are presented when objects can be imaged from different view angles and have different distortions. For example, a vehicle will appear completely different depending on the viewing angle of the sensor but must still be classified as the same vehicle. In regards to face recognition, a person may have a variety of facial expressions and a pattern recognition algorithm would need to account for these distortions. Traditional algorithms such as PCA filters are linear in nature and cannot account for the underlying non-linear structure which characterizes an object. We examine nonlinear manifold techniques applied to the pattern recognition problem. One mathematical construct receiving significant research attention is diffusion maps, whereby the underlying training data are remapped so that Euclidean distance in the mapped data is equivalent to the manifold distance of the original dataset. This technique has been used successfully for applications such as data organization, noise filtering, and anomaly detection with only limited experiments with object classification. For very large datasets (size N), pattern classification with diffusion maps becomes rather onerous as there is a requirement for the eigenvectors of an NxN matrix. We characterize the performance of a 40 person facial recognition problem with standard K-NN classifier, a diffusion distance classifier, and standard PCA. We then develop a local subspace projection algorithm which approximates the diffusion distance without the prohibitive computations and shows comparable classification performance.

  18. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft......-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classification windows is achieved. Further more it is shown that linear input performs as well as a quadratic......, and that even though classification gets marginally better, not much is achieved by increasing the window size beyond 1 s....

  19. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition......, a good metric is required to measure distance or similarity between feature points so that the classification becomes feasible. Furthermore, in order to build a successful classifier, one needs to deeply understand how classifiers work. This thesis focuses on these three aspects of classification...... and explores these challenging areas. The first focus of the thesis is to properly combine different local feature experts and prior information to design an effective classifier. The preliminary classification results, provided by the experts, are fused in order to develop an automatic segmentation method...

  20. Learning Apache Mahout classification

    CERN Document Server

    Gupta, Ashish

    2015-01-01

    If you are a data scientist who has some experience with the Hadoop ecosystem and machine learning methods and want to try out classification on large datasets using Mahout, this book is ideal for you. Knowledge of Java is essential.

  1. Support vector classification algorithm based on variable parameter linear programming

    Institute of Scientific and Technical Information of China (English)

    Xiao Jianhua; Lin Jian

    2007-01-01

    To solve the problems of SVM in dealing with large sample size and asymmetric distributed samples, a support vector classification algorithm based on variable parameter linear programming is proposed.In the proposed algorithm, linear programming is employed to solve the optimization problem of classification to decrease the computation time and to reduce its complexity when compared with the original model.The adjusted punishment parameter greatly reduced the classification error resulting from asymmetric distributed samples and the detailed procedure of the proposed algorithm is given.An experiment is conducted to verify whether the proposed algorithm is suitable for asymmetric distributed samples.

  2. Latent classification models

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    parametric family ofdistributions.  In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  3. Classification of Sleep Disorders

    OpenAIRE

    Michael J. Thorpy

    2012-01-01

    The classification of sleep disorders is necessary to discriminate between disorders and to facilitate an understanding of symptoms, etiology, and pathophysiology that allows for appropriate treatment. The earliest classification systems, largely organized according to major symptoms (insomnia, excessive sleepiness, and abnormal events that occur during sleep), were unable to be based on pathophysiology because the cause of most sleep disorders was unknown. These 3 symptom-based categories ar...

  4. Inhibition in multiclass classification

    OpenAIRE

    Huerta, Ramón; Vembu, Shankar; Amigó, José M.; Nowotny, Thomas; Elkan, Charles

    2012-01-01

    The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and ...

  5. Classification of Dams

    OpenAIRE

    Berg, Johan; Linder, Maria

    2013-01-01

    In a comparing survey this thesis investigates classification systems for dams in Sweden, Norway, Finland, Switzerland, Canada and USA. The investigation is aiming at an understanding of how potential consequences of a dam failure are taken into account when classifying dams. Furthermore, the significance of the classification, regarding the requirements on the dam owner and surveillance authorities concerning dam safety is considered and reviewed. The thesis is pointing out similarities and ...

  6. Bone-Marrow Conservation, Culture and Transplantation. Proceedings of a Panel on Current Problems of Bone-Marrow Cell Transplantation with Special Emphasis on Conservation and Culture

    International Nuclear Information System (INIS)

    A Panel on the current problems of bone-marrow cell transplantation with special emphasis on cell conservation and culture was organized by the International Atomic Energy Agency and held at the Central Institute of Haematology and Blood Transfusion in Moscow from 22 to 26 July 1968. Twenty-three scientists from 13 Member States and representatives of international and national organizations attended. Many of the participants had done notable work on this subject. The following topics were discussed: Tissue culture of bone-marrow cells; Histocompatibility and how to avoid secondary diseases; Conservation and storage of bone-marrow cells, white cells and thrombocytes; Scientific and organizational problems of bone-marrow cell banks. In the opening address it was pointed out that bone-marrow cell transplantation deserved a great deal of attention because of its importance as a powerful tool in human therapy, including radiation disease. It was further stressed that despite the remarkable achievements in this field, specifically with regard to auto- and homologous bone-marrow transplantation,, many problems remained ill-defined and unsolved — particularly on homologous bone-marrow transplantation. To clarify these problems, broad international collaboration was needed among specialists in Member States as well as with international bodies such as the IAEA and WHO, both of which organizations should be centres for collecting and disseminating information from Member States and for encouraging and stimulating research. In presenting much interesting work, the Panel clearly established the usefulness of bone-marrow transplantation for human therapy in specific conditions, and identified more clearly the practical problems still to be solved. The recommendations together with the reports presented at the Panel are published in this volume

  7. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  8. Harmonization of description and classification of fetal observations: achievements and problems still unresolved: report of the 7th Workshop on the Terminology in Developmental Toxicology Berlin, 4-6 May 2011.

    Science.gov (United States)

    Solecki, Roland; Barbellion, Stephane; Bergmann, Brigitte; Bürgin, Heinrich; Buschmann, Jochen; Clark, Ruth; Comotto, Laura; Fuchs, Antje; Faqi, Ali Said; Gerspach, Ralph; Grote, Konstanze; Hakansson, Helen; Heinrich, Verena; Heinrich-Hirsch, Barbara; Hofmann, Thomas; Hübel, Ulrich; Inazaki, Thelma Helena; Khalil, Samia; Knudsen, Thomas B; Kudicke, Sabine; Lingk, Wolfgang; Makris, Susan; Müller, Simone; Paumgartten, Francisco; Pfeil, Rudolf; Rama, Elkiane Macedo; Schneider, Steffen; Shiota, Kohei; Tamborini, Eva; Tegelenbosch, Mariska; Ulbrich, Beate; van Duijnhoven, E A J; Wise, David; Chahoud, Ibrahim

    2013-01-01

    This article summarizes the 7th Workshop on the Terminology in Developmental Toxicology held in Berlin, May 4-6, 2011. The series of Berlin Workshops has been mainly concerned with the harmonization of terminology and classification of fetal anomalies in developmental toxicity studies. The main topics of the 7th Workshop were knowledge on the fate of anomalies after birth, use of Version 2 terminology for maternal-fetal observations and non-routinely used species, reclassification of "grey zone" anomalies and categorization of fetal observations for human health risk assessment. The paucity of data on health consequences of the postnatal permanence of fetal anomalies is relevant and further studies are needed. The Version 2 terminology is an important step forward and the terms listed in this glossary are considered also to be appropriate for most observations in non-routinely used species. Continuation of the Berlin Workshops was recommended. Topics suggested for the next Workshop were grouping of fetal observations for reporting and statistical analysis. PMID:22781580

  9. [Globally harmonized system of classification and labelling of chemicals (GHS) and its implementation in Japan].

    Science.gov (United States)

    Miyagawa, Muneyuki

    2010-01-01

    The Globally Harmonized System of Classification and Labelling of Chemicals (GHS) is a set of recommendations by the United Nations, first issued in 2003 as a communication tool for the sound management of chemicals, comprising harmonized classification criteria for physical, health and environmental hazards, a unified format for material safety data sheets (MSDS), and labeling elements including pictograms and hazard statements preassigned to each classification category. The GHS has been introduced into Japan and implemented in the regulatory framework for chemical safety. The Japanese Industrial Standards (JIS) adopted the GHS, and the GHS-based JIS rules have become the Japanese standards for labels and MSDS. The use of the JIS format for labels and MSDS is recommended by several competent authorities in Japan although mostly on a voluntary basis. In the workplace, however, GHS-based JIS labels and MSDS have become legal requirements by the Industrial Safety and Health Law since 2006; namely, issuing MSDS in such a format is mandatory for the 640 specified chemicals and also labeling for the 99 targeted chemicals*. Although the GHS provides definitions and classification criteria for 10 classes of health hazards (acute toxicity, skin and eye corrosion/irritation, sensitization, germ cell mutagenicity, carcinogenicity, reproductive toxicity, specific target organ toxicity single/repeated exposures, and aspiration hazard), it does not provide actual classification of chemicals, so that competent authorities and industries need to classify a number of chemicals and/or mixtures. Weight-of-evidence judgment and/or expert judgment would be necessary in many cases. In this paper, the outline of the GHS classification is described and problems of the GHS and its implementation are discussed. PMID:20134103

  10. Automatically inferred Markov network models for classification of chromosomal band pattern structures.

    Science.gov (United States)

    Granum, E; Thomason, M G

    1990-01-01

    A structural pattern recognition approach to the analysis and classification of metaphase chromosome band patterns is presented. An operational method of representing band pattern profiles as sharp edged idealized profiles is outlined. These profiles are nonlinearly scaled to a few, but fixed number of "density" levels. Previous experience has shown that profiles of six levels are appropriate and that the differences between successive bands in these profiles are suitable for classification. String representations, which focuses on the sequences of transitions between local band pattern levels, are derived from such "difference profiles." A method of syntactic analysis of the band transition sequences by dynamic programming for optimal (maximal probability) string-to-network alignments is described. It develops automatic data-driven inference of band pattern models (Markov networks) per class, and uses these models for classification. The method does not use centromere information, but assumes the p-q-orientation of the band pattern profiles to be known a priori. It is experimentally established that the method can build Markov network models, which, when used for classification, show a recognition rate of about 92% on test data. The experiments used 200 samples (chromosome profiles) for each of the 22 autosome chromosome types and are designed to also investigate various classifier design problems. It is found that the use of a priori knowledge of Denver Group assignment only improved classification by 1 or 2%. A scheme for typewise normalization of the class relationship measures prove useful, partly through improvements on average results and partly through a more evenly distributed error pattern. The choice of reference of the p-q-orientation of the band patterns is found to be unimportant, and results of timing of the execution time of the analysis show that recent and efficient implementations can process one cell in less than 1 min on current standard

  11. AGN Zoo and Classifications of Active Galaxies

    Science.gov (United States)

    Mickaelian, Areg M.

    2015-07-01

    We review the variety of Active Galactic Nuclei (AGN) classes (so-called "AGN zoo") and classification schemes of galaxies by activity types based on their optical emission-line spectrum, as well as other parameters and other than optical wavelength ranges. A historical overview of discoveries of various types of active galaxies is given, including Seyfert galaxies, radio galaxies, QSOs, BL Lacertae objects, Starbursts, LINERs, etc. Various kinds of AGN diagnostics are discussed. All known AGN types and subtypes are presented and described to have a homogeneous classification scheme based on the optical emission-line spectra and in many cases, also other parameters. Problems connected with accurate classifications and open questions related to AGN and their classes are discussed and summarized.

  12. Myelodysplastic syndrome: classification and prognostic systems

    Directory of Open Access Journals (Sweden)

    Rosangela Invernizzi

    2011-12-01

    Full Text Available Myelodysplastic syndromes (MDS are acquired clonal disorders of hematopoiesis, that are characterized most frequently by normocellular or hypercellular bone marrow specimens, and maturation that is morphologically and functionally dysplastic. MDS constitute a complex hematological problem: differences in disease presentation, progression and outcome have made it necessary to use classification systems to improve diagnosis, prognostication and treatment selection. On the basis of new scientific and clinical information, classification and prognostic systems have recently been updated and minimal diagnostic criteria forMDS have been proposed by expert panels. In addition, in the last few years our ability to define the prognosis of the individual patient with MDS has improved. In this paper World Health Organization (WHO classification refinements and recent prognostic scoring systems for the definition of individual risk are highlighted and current criteria are discussed. The recommendations should facilitate diagnostic and prognostic evaluations in MDS and selection of patients for new effective targeted therapies.

  13. Combinatorial Classification for Chunking Arabic Texts

    Directory of Open Access Journals (Sweden)

    Fériel Ben Fraj

    2012-09-01

    Full Text Available Text parsing has always benefited from special attention since the first applications of natural language processing (NLP. The problem gets worse for the Arabic language because of its specific features that make it quite different and even more ambiguous than other natural languages when processed. In this paper, we discuss a new approach for chunking Arabic texts based on a combinatorial classification process. It is a modular chunker that identifies the chunk heads using a combinatorial binary classification before recognizing their types based on the parts-of-speech of the chunk heads, already identified. For the experimentation, we use over than 2300 words as training data. The evaluation of the chunker consists of two steps and gives results that we consider very satisfactory (average accuracy of 89,60% for the classification step and 80,46% for the full chunking process.

  14. Classification of sudden and arrhythmic death

    DEFF Research Database (Denmark)

    Torp-Pedersen, C; Køber, L; Elming, H;

    1997-01-01

    as being arrhythmic or sudden are all biased by the difficulty of having to decide on the degree of unexpectedness or the likelihood that life could continue without the arrhythmia. The uncertainties are enlarged by the fact that critical data (such as knowledge of arrhythmias at the time of death......Since all death is (eventually) sudden and associated with cardiac arrhythmias, the concept of sudden death is only meaningful if it is unexpected, while arrhythmic death is only meaningful if life could have continued had the arrhythmia been prevented or treated. Current classifications of death...... or autopsy) are available in only a few percent of cases. A main problem in using classifications is the lack of validation data. This situation has, with the MADIT trial, changed in the case of the Thaler and Hinkle classification of arrhythmic death. The MADIT trial demonstrated that arrhythmic death...

  15. Formal Classification of Research Information: An Empirical Test of the McGrath-Altman Approach and an Illustrative Case

    Science.gov (United States)

    Rice, Robert W.

    1978-01-01

    The classification of data generated by empirical research is presented as an important but generally neglected problem facing contemporary psychology. It is concluded that formal classification can facilitate conceptual developments. (Author)

  16. A Common Weight Linear Optimization Approach for Multicriteria ABC Inventory Classification

    OpenAIRE

    S. M. Hatefi; Torabi, S. A.

    2015-01-01

    Organizations typically employ the ABC inventory classification technique to have an efficient control on a huge amount of inventory items. The ABC inventory classification problem is classification of a large amount of items into three groups: A, very important; B, moderately important; and C, relatively unimportant. The traditional ABC classification only accounts for one criterion, namely, the annual dollar usage of the items. But, there are other important criteria in real world which str...

  17. Rainfall Prediction using Data-Core Based Fuzzy Min-Max Neural Network for Classification

    OpenAIRE

    Rajendra Palange,; Nishikant Pachpute

    2015-01-01

    This paper proposes the Rainfall Prediction System by using classification technique. The advanced and modified neural network called Data Core Based Fuzzy Min Max Neural Network (DCFMNN) is used for pattern classification. This classification method is applied to predict Rainfall. The neural network called fuzzy min max neural network (FMNN) that creates hyperboxes for classification and predication, has a problem of overlapping neurons that resoled in DCFMNN to give greater accu...

  18. Classification of Dynamic Vehicle Routing Systems

    DEFF Research Database (Denmark)

    Larsen, Allan; Madsen, Oli B.G.; Solomon, Marius M.

    2007-01-01

    to classify dynamic vehicle routing systems. Methods for evaluation of the performance of algorithms that solve on-line routing problems are discussed and we list some of the most important issues to include in the system objective. Finally, we provide a three-echelon classification of dynamic vehicle routing......This chapter discusses important characteristics seen within dynamic vehicle routing problems. We discuss the differences between the traditional static vehicle routing problems and its dynamic counterparts. We give an in-depth introduction to the degree of dynamism measure which can be used...

  19. Problems of Chernobyl

    International Nuclear Information System (INIS)

    The collection comprises the materials of working meeting 'The Development of Technologies of the 'Ukrytie' Radioactive Waste Management', held on May 20-21, 1997 in Chernobyl. The results of research work of the experts of Ukraine and other countries directed on solving problems, concerning removal of fuel containing materials and other radioactive waste from destroyed Unit 4 of Chernobyl NPP are given. The data on waste quantities, their location and classification, strategy of waste management and some technologies are described

  20. Product Classification in Supply Chain

    OpenAIRE

    Xing, Lihong; Xu, Yaoxuan

    2010-01-01

    Oriflame is a famous international direct sale cosmetics company with complicated supply chain operation but it lacks of a product classification system. It is vital to design a product classification method in order to support Oriflame global supply planning and improve the supply chain performance. This article is aim to investigate and design the multi-criteria of product classification, propose the classification model, suggest application areas of product classification results and intro...

  1. Hyperspectral Data Classification Using Factor Graphs

    Science.gov (United States)

    Makarau, A.; Müller, R.; Palubinskas, G.; Reinartz, P.

    2012-07-01

    and comparison of the probabilities leads to classification. Since the factor graphs operate on input data represented on an alphabet (the represented data transferred into multinomial distribution) the number of training samples can be relatively low. Classification assessment on Salinas hyperspectral data benchmark allowed to obtain a competitive accuracy of classification. Employment of training data consisting of 20 randomly selected points for a class allowed to obtain the overall classification accuracy equal to 85.32% and Kappa equal to 0.8358. Representation of input data on a finite domain discards the curse of dimensionality problem allowing to use large hyperspectral data with a moderately high number of bands.

  2. Enhancing Accuracy of Plant Leaf Classification Techniques

    Directory of Open Access Journals (Sweden)

    C. S. Sumathi

    2014-03-01

    Full Text Available Plants have become an important source of energy, and are a fundamental piece in the puzzle to solve the problem of global warming. Living beings also depend on plants for their food, hence it is of great importance to know about the plants growing around us and to preserve them. Automatic plant leaf classification is widely researched. This paper investigates the efficiency of learning algorithms of MLP for plant leaf classification. Incremental back propagation, Levenberg–Marquardt and batch propagation learning algorithms are investigated. Plant leaf images are examined using three different Multi-Layer Perceptron (MLP modelling techniques. Back propagation done in batch manner increases the accuracy of plant leaf classification. Results reveal that batch training is faster and more accurate than MLP with incremental training and Levenberg– Marquardt based learning for plant leaf classification. Various levels of semi-batch training used on 9 species of 15 sample each, a total of 135 instances show a roughly linear increase in classification accuracy.

  3. Discriminative variable subsets in Bayesian classification with mixture models, with application in flow cytometry studies.

    Science.gov (United States)

    Lin, Lin; Chan, Cliburn; West, Mike

    2016-01-01

    We discuss the evaluation of subsets of variables for the discriminative evidence they provide in multivariate mixture modeling for classification. The novel development of Bayesian classification analysis presented is partly motivated by problems of design and selection of variables in biomolecular studies, particularly involving widely used assays of large-scale single-cell data generated using flow cytometry technology. For such studies and for mixture modeling generally, we define discriminative analysis that overlays fitted mixture models using a natural measure of concordance between mixture component densities, and define an effective and computationally feasible method for assessing and prioritizing subsets of variables according to their roles in discrimination of one or more mixture components. We relate the new discriminative information measures to Bayesian classification probabilities and error rates, and exemplify their use in Bayesian analysis of Dirichlet process mixture models fitted via Markov chain Monte Carlo methods as well as using a novel Bayesian expectation-maximization algorithm. We present a series of theoretical and simulated data examples to fix concepts and exhibit the utility of the approach, and compare with prior approaches. We demonstrate application in the context of automatic classification and discriminative variable selection in high-throughput systems biology using large flow cytometry datasets. PMID:26040910

  4. Discriminative variable subsets in Bayesian classification with mixture models, with application in flow cytometry studies.

    Science.gov (United States)

    Lin, Lin; Chan, Cliburn; West, Mike

    2016-01-01

    We discuss the evaluation of subsets of variables for the discriminative evidence they provide in multivariate mixture modeling for classification. The novel development of Bayesian classification analysis presented is partly motivated by problems of design and selection of variables in biomolecular studies, particularly involving widely used assays of large-scale single-cell data generated using flow cytometry technology. For such studies and for mixture modeling generally, we define discriminative analysis that overlays fitted mixture models using a natural measure of concordance between mixture component densities, and define an effective and computationally feasible method for assessing and prioritizing subsets of variables according to their roles in discrimination of one or more mixture components. We relate the new discriminative information measures to Bayesian classification probabilities and error rates, and exemplify their use in Bayesian analysis of Dirichlet process mixture models fitted via Markov chain Monte Carlo methods as well as using a novel Bayesian expectation-maximization algorithm. We present a series of theoretical and simulated data examples to fix concepts and exhibit the utility of the approach, and compare with prior approaches. We demonstrate application in the context of automatic classification and discriminative variable selection in high-throughput systems biology using large flow cytometry datasets.

  5. Concepts of Classification and Taxonomy Phylogenetic Classification

    Science.gov (United States)

    Fraix-Burnet, D.

    2016-05-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works.

  6. Informational Way to Protein Alphabet: Entropic Classification of Amino Acids

    CERN Document Server

    Gorban, A N; Popova, T

    2007-01-01

    What are proteins made from, as the working parts of the living cells protein machines? To answer this question, we need a technology to disassemble proteins onto elementary func-tional details and to prepare lumped description of such details. This lumped description might have a multiple material realization (in amino acids). Our hypothesis is that informational approach to this problem is possible. We propose a way of hierarchical classification that makes the primary structure of protein maximally non-random. The first steps of the suggested research program are realized: the method and the analysis of optimal informational protein binary alphabet. The general method is used to answer several specific questions, for example: (i) Is there a syntactic difference between Globular and Membrane proteins? (ii) Are proteins random sequences of amino acids (a long discussion)? For these questions, the answers are as follows: (i) There exists significant syntactic difference between Globular and Membrane proteins,...

  7. Rapid Classification and Identification of Salmonellae at the Species and Subspecies Levels by Whole-Cell Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry▿ †

    Science.gov (United States)

    Dieckmann, Ralf; Helmuth, Reiner; Erhard, Marcel; Malorny, Burkhard

    2008-01-01

    Variations in the mass spectral profiles of multiple housekeeping proteins of 126 strains representing Salmonella enterica subsp. enterica (subspecies I), S. enterica subsp. salamae (subspecies II), S. enterica subsp. arizonae (subspecies IIIa), S. enterica subsp. diarizonae (subspecies IIIb), S. enterica subsp. houtenae (subspecies IV), and S. enterica subsp. indica (subspecies VI), and Salmonella bongori were analyzed to obtain a phylogenetic classification of salmonellae based on whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometric bacterial typing. Sinapinic acid produced highly informative spectra containing a large number of biomarkers and covering a wide molecular mass range (2,000 to 40,000 Da). Genus-, species-, and subspecies-identifying biomarker ions were assigned on the basis of available genome sequence data for Salmonella, and more than 200 biomarker peaks, which corresponded mainly to abundant and highly basic ribosomal or nucleic acid binding proteins, were selected. A detailed comparative analysis of the biomarker profiles of Salmonella strains revealed sequence variations corresponding to single or multiple amino acid changes in multiple housekeeping proteins. The resulting mass spectrometry-based bacterial classification was very comparable to the results of DNA sequence-based methods. A rapid protocol that allowed identification of Salmonella subspecies in minutes was established. PMID:18952875

  8. Sparse extreme learning machine for classification.

    Science.gov (United States)

    Bai, Zuo; Huang, Guang-Bin; Wang, Danwei; Wang, Han; Westover, M Brandon

    2014-10-01

    Extreme learning machine (ELM) was initially proposed for single-hidden-layer feedforward neural networks (SLFNs). In the hidden layer (feature mapping), nodes are randomly generated independently of training data. Furthermore, a unified ELM was proposed, providing a single framework to simplify and unify different learning methods, such as SLFNs, least square support vector machines, proximal support vector machines, and so on. However, the solution of unified ELM is dense, and thus, usually plenty of storage space and testing time are required for large-scale applications. In this paper, a sparse ELM is proposed as an alternative solution for classification, reducing storage space and testing time. In addition, unified ELM obtains the solution by matrix inversion, whose computational complexity is between quadratic and cubic with respect to the training size. It still requires plenty of training time for large-scale problems, even though it is much faster than many other traditional methods. In this paper, an efficient training algorithm is specifically developed for sparse ELM. The quadratic programming problem involved in sparse ELM is divided into a series of smallest possible sub-problems, each of which are solved analytically. Compared with SVM, sparse ELM obtains better generalization performance with much faster training speed. Compared with unified ELM, sparse ELM achieves similar generalization performance for binary classification applications, and when dealing with large-scale binary classification problems, sparse ELM realizes even faster training speed than unified ELM.

  9. Classification of diabetic foot ulcers.

    Science.gov (United States)

    Game, Frances

    2016-01-01

    It is known that the relative importance of factors involved in the development of diabetic foot problems can vary in both their presence and severity between patients and lesions. This may be one of the reasons why outcomes seem to vary centre to centre and why some treatments may seem more effective in some people than others. There is a need therefore to classify and describe lesions of the foot in patients with diabetes in a manner that is agreed across all communities but is simple to use in clinical practice. No single system is currently in widespread use, although a number have been published. Not all are well validated outside the system from which they were derived, and it has not always been made clear the clinical purposes to which such classifications should be put to use, whether that be for research, clinical description in routine clinical care or audit. Here the currently published classification systems, their validation in clinical practice, whether they were designed for research, audit or clinical care, and the strengths and weaknesses of each are explored.

  10. Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants

    International Nuclear Information System (INIS)

    This paper assesses the operation and management of electrical energy, hydrogen production and thermal load supplement by the Fuel Cell Power Plants (FCPP) in the distribution systems with regard to the uncertainties which exist in the load demand as well as the price of buying natural gas for FCPPs, fuel cost for residential loads, tariff for purchasing electricity, tariff for selling electricity, hydrogen selling price, operation and maintenance cost and the price of purchasing power from the grid. Therefore, a new modified multi-objective optimization algorithm called Teacher-Learning Algorithm (TLA) is proposed to integrate the optimal operation management of Proton Exchange Membrane FCPPs (PEM-FCPPs) and the optimal configuration of the system through an economic model of the PEM-FCPP. In order to improve the total ability of TLA for global search and exploration, a new modification process is suggested such that the algorithm will search the total search space globally. Also, regarding the uncertainties of the new complicated power systems, in this paper for the first time, the DFR problem is investigated in a stochastic environment by the use of probabilistic load flow technique based on Point Estimate Method (PEM). In order to see the feasibility and the superiority of the proposed method, a standard test system is investigated as the case study. The simulation results are investigated in four different scenarios to show the effect of hydrogen production and thermal recovery more evidently. -- Highlights: ► Present an economical and thermal modeling of PEM-FCPPs. ► Present an approach for optimal operation of PEM-FCPPs in a stochastic environment. ► Consider benefits of thermal recovery and Hydrogen production for PEM-FCPPs. ► Present several scenarios for management of PEM-FCPPs.

  11. Changes to the cell, tissue and architecture levels in cranial suture synostosis reveal a problem of timing in bone development

    Directory of Open Access Journals (Sweden)

    J Regelsberger

    2012-11-01

    Full Text Available Premature fusion of cranial sutures is a common problem with an incidence of 3-5 per 10,000 live births. Despite progress in understanding molecular/genetic factors affecting suture function, the complex process of premature fusion is still poorly understood. In the present study, corresponding excised segments of nine patent and nine prematurely fused sagittal sutures from infants (age range 3-7 months with a special emphasis on their hierarchical structural configuration were compared. Cell, tissue and architecture characteristics were analysed by transmitted and polarised light microscopy, 2D-histomorphometry, backscattered electron microscopy and energy-dispersive-x-ray analyses. Apart from wider sutural gaps, patent sutures showed histologically increased new bone formation compared to reduced new bone formation and osseous edges with a more mature structure in the fused portions of the sutures. This pattern was accompanied by a lower osteocyte lacunar density and a higher number of evenly mineralised osteons, reflecting pronounced lamellar bone characteristics along the prematurely fused sutures. In contrast, increases in osteocyte lacunar number and size accompanied by mineralisation heterogeneity and randomly oriented collagen fibres predominantly signified woven bone characteristics in patent, still growing suture segments. The already established woven-to-lamellar bone transition provides evidence of advanced bone development in synostotic sutures. Since structural and compositional features of prematurely fused sutures did not show signs of pathological/defective ossification processes, this supports the theory of a normal ossification process in suture synostosis – just locally commencing too early. These histomorphological findings may provide the basis for a better understanding of the pathomechanism of craniosynostosis, and for future strategies to predict suture fusion and to determine surgical intervention.

  12. Information gathering for CLP classification

    Directory of Open Access Journals (Sweden)

    Ida Marcello

    2011-01-01

    Full Text Available Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP. If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requirements of Annex I of the CLP Regulation. CLP appoints that the harmonised classification will be performed for carcinogenic, mutagenic or toxic to reproduction substances (CMR substances and for respiratory sensitisers category 1 and for other hazard classes on a case-by-case basis. The first step of classification is the gathering of available and relevant information. This paper presents the procedure for gathering information and to obtain data. The data quality is also discussed.

  13. The paradox of atheoretical classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2016-01-01

    A distinction can be made between “artificial classifications” and “natural classifications,” where artificial classifications may adequately serve some limited purposes, but natural classifications are overall most fruitful by allowing inference and thus many different purposes. There is strong...... support for the view that a natural classification should be based on a theory (and, of course, that the most fruitful theory provides the most fruitful classification). Nevertheless, atheoretical (or “descriptive”) classifications are often produced. Paradoxically, atheoretical classifications may...... be very successful. The best example of a successful “atheoretical” classification is probably the prestigious Diagnostic and Statistical Manual of Mental Disorders (DSM) since its third edition from 1980. Based on such successes one may ask: Should the claim that classifications ideally are natural...

  14. Sound classification of dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    National schemes for sound classification of dwellings exist in more than ten countries in Europe, typically published as national standards. The schemes define quality classes reflecting different levels of acoustical comfort. Main criteria concern airborne and impact sound insulation between....... Descriptors, range of quality levels, number of quality classes, class intervals, denotations and descriptions vary across Europe. The diversity is an obstacle for exchange of experience about constructions fulfilling different classes, implying also trade barriers. Thus, a harmonized classification scheme...... is needed, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", has been established and runs 2009-2013, one of the main objectives being to prepare a proposal for a European sound classification scheme with a number of quality...

  15. Bosniak Classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens;

    2014-01-01

    Background: The Bosniak classification is a diagnostic tool for the differentiation of cystic changes in the kidney. The process of categorizing renal cysts may be challenging, involving a series of decisions that may affect the final diagnosis and clinical outcome such as surgical management....... Purpose: To investigate the inter- and intra-observer agreement among experienced uroradiologists when categorizing complex renal cysts according to the Bosniak classification. Material and Methods: The original categories of 100 cystic renal masses were chosen as “Gold Standard” (GS), established...... to the calculated weighted κ all readers performed “very good” for both inter-observer and intra-observer variation. Most variation was seen in cysts catagorized as Bosniak II, IIF, and III. These results show that radiologists who evaluate complex renal cysts routinely may apply the Bosniak classification...

  16. Bosniak classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens;

    2016-01-01

    BACKGROUND: The Bosniak classification was originally based on computed tomographic (CT) findings. Magnetic resonance (MR) and contrast-enhanced ultrasonography (CEUS) imaging may demonstrate findings that are not depicted at CT, and there may not always be a clear correlation between the findings...... at MR and CEUS imaging and those at CT. PURPOSE: To compare diagnostic accuracy of MR, CEUS, and CT when categorizing complex renal cystic masses according to the Bosniak classification. MATERIAL AND METHODS: From February 2011 to June 2012, 46 complex renal cysts were prospectively evaluated by three...... readers. Each mass was categorized according to the Bosniak classification and CT was chosen as gold standard. Kappa was calculated for diagnostic accuracy and data was compared with pathological results. RESULTS: CT images found 27 BII, six BIIF, seven BIII, and six BIV. Forty-three cysts could...

  17. Vertebral fracture classification

    Science.gov (United States)

    de Bruijne, Marleen; Pettersen, Paola C.; Tankó, László B.; Nielsen, Mads

    2007-03-01

    A novel method for classification and quantification of vertebral fractures from X-ray images is presented. Using pairwise conditional shape models trained on a set of healthy spines, the most likely unfractured shape is estimated for each of the vertebrae in the image. The difference between the true shape and the reconstructed normal shape is an indicator for the shape abnormality. A statistical classification scheme with the two shapes as features is applied to detect, classify, and grade various types of deformities. In contrast with the current (semi-)quantitative grading strategies this method takes the full shape into account, it uses a patient-specific reference by combining population-based information on biological variation in vertebra shape and vertebra interrelations, and it provides a continuous measure of deformity. Good agreement with manual classification and grading is demonstrated on 204 lateral spine radiographs with in total 89 fractures.

  18. Geographical classification of wine and olive oil by means of classification and influence matrix analysis (CAIMAN).

    Science.gov (United States)

    Ballabio, Davide; Mauri, Andrea; Todeschini, Roberto; Buratti, Susanna

    2006-06-16

    Classification and influence matrix analysis (CAIMAN) is a new classification method, recently proposed and based on the influence matrix (also called leverage matrix). Depending on the purposes of the classification analysis, CAIMAN can be used in three outlines: (1) D-CAIMAN is a discriminant classification method, (2) M-CAIMAN is a class modelling method allowing a sample to be classified, not classified at all, or assigned to more than one class (confused) and (3) A-CAIMAN deals with the asymmetric case, where only a reference class needs to be modelled. In this work, the geographic classification of samples of wine and olive oil has been carried out by means of CAIMAN and its results compared with discriminant analysis, by focusing great attention on the model predictive capabilities. The geographic characterization has been carried out on three different datasets: extra virgin olive oils produced in a small area, with a "protected denomination of origin" label, wines with different denominations of origin, but produced in enclosed geographical areas, and olive oils belonging to different production areas. Final results seem to indicate that the application of CAIMAN to the geographical origin identification offers several advantages: first, it shows--on an average basis--good performances; second, it is able to deal in a simple way classification problems related to tipicity, authenticity, and uniqueness characterization, which are of increasing interest in food quality issues. PMID:17723406

  19. Families classification including multiopposition asteroids

    Science.gov (United States)

    Milani, Andrea; Spoto, Federica; Knežević, Zoran; Novaković, Bojan; Tsirvoulis, Georgios

    2016-01-01

    In this paper we present the results of our new classification of asteroid families, upgraded by using catalog with > 500,000 asteroids. We discuss the outcome of the most recent update of the family list and of their membership. We found enough evidence to perform 9 mergers of the previously independent families. By introducing an improved method of estimation of the expected family growth in the less populous regions (e.g. at high inclination) we were able to reliably decide on rejection of one tiny group as a probable statistical fluke. Thus we reduced our current list to 115 families. We also present newly determined ages for 6 families, including complex 135 and 221, improving also our understanding of the dynamical vs. collisional families relationship. We conclude with some recommendations for the future work and for the family name problem.

  20. Fast Wavelet-Based Visual Classification

    CERN Document Server

    Yu, Guoshen

    2008-01-01

    We investigate a biologically motivated approach to fast visual classification, directly inspired by the recent work of Serre et al. Specifically, trading-off biological accuracy for computational efficiency, we explore using wavelet and grouplet-like transforms to parallel the tuning of visual cortex V1 and V2 cells, alternated with max operations to achieve scale and translation invariance. A feature selection procedure is applied during learning to accelerate recognition. We introduce a simple attention-like feedback mechanism, significantly improving recognition and robustness in multiple-object scenes. In experiments, the proposed algorithm achieves or exceeds state-of-the-art success rate on object recognition, texture and satellite image classification, language identification and sound classification.

  1. Classification des rongeurs

    OpenAIRE

    Mignon, Jacques; Hardouin, Jacques

    2003-01-01

    Les lecteurs du Bulletin BEDIM semblent parfois avoir des difficultés avec la classification scientifique des animaux connus comme "rongeurs" dans le langage courant. Vu les querelles existant encore aujourd'hui dans la mise en place de cette classification, nous ne nous en étonnerons guère. La brève synthèse qui suit concerne les animaux faisant ou susceptibles de faire partie du mini-élevage. The note aims at providing the main characteristics of the principal families of rodents relevan...

  2. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms...... of descriptors, number of classes, and class intervals occurred between national schemes. However, a proposal “acoustic classification scheme for dwellings” has been developed recently in the European COST Action TU0901 with 32 member countries. This proposal has been accepted as an ISO work item. This paper...

  3. Classification of syringomyelia.

    Science.gov (United States)

    Milhorat, T H

    2000-01-01

    Syringomyelia poses special challenges for the clinician because of its complex symptomatology, uncertain pathogenesis, and multiple options of treatment. The purpose of this study was to classify intramedullary cavities according to their most salient pathological and clinical features. Pathological findings obtained in 175 individuals with tubular cavitations of the spinal cord were correlated with clinical and magnetic resonance (MR) imaging findings in a database of 927 patients. A classification system was developed in which the morbid anatomy, cause, and pathogenesis of these lesions are emphasized. The use of a disease-based classification of syringomyelia facilitates diagnosis and the interpretation of MR imaging findings and provides a guide to treatment. PMID:16676921

  4. Requirements Elicitation Problems: A Literature Analysis

    Directory of Open Access Journals (Sweden)

    Bill Davey

    2015-06-01

    Full Text Available Requirements elicitation is the process through which analysts determine the software requirements of stakeholders. Requirements elicitation is seldom well done, and an inaccurate or incomplete understanding of user requirements has led to the downfall of many software projects. This paper proposes a classification of problem types that occur in requirements elicitation. The classification has been derived from a literature analysis. Papers reporting on techniques for improving requirements elicitation practice were examined for the problem the technique was designed to address. In each classification the most recent or prominent techniques for ameliorating the problems are presented. The classification allows the requirements engineer to be sensitive to problems as they arise and the educator to structure delivery of requirements elicitation training.

  5. Genetic programming and serial processing for time series classification.

    Science.gov (United States)

    Alfaro-Cid, Eva; Sharman, Ken; Esparcia-Alcázar, Anna I

    2014-01-01

    This work describes an approach devised by the authors for time series classification. In our approach genetic programming is used in combination with a serial processing of data, where the last output is the result of the classification. The use of genetic programming for classification, although still a field where more research in needed, is not new. However, the application of genetic programming to classification tasks is normally done by considering the input data as a feature vector. That is, to the best of our knowledge, there are not examples in the genetic programming literature of approaches where the time series data are processed serially and the last output is considered as the classification result. The serial processing approach presented here fills a gap in the existing literature. This approach was tested in three different problems. Two of them are real world problems whose data were gathered for online or conference competitions. As there are published results of these two problems this gives us the chance to compare the performance of our approach against top performing methods. The serial processing of data in combination with genetic programming obtained competitive results in both competitions, showing its potential for solving time series classification problems. The main advantage of our serial processing approach is that it can easily handle very large datasets.

  6. Multiclass Classification Based on the Analytical Center of Version Space

    Institute of Scientific and Technical Information of China (English)

    ZENGFanzi; QIUZhengding; YUEJianhai; LIXiangqian

    2005-01-01

    Analytical center machine, based on the analytical center of version space, outperforms support vector machine, especially when the version space is elongated or asymmetric. While analytical center machine for binary classification is well understood, little is known about corresponding multiclass classification.Moreover, considering that the current multiclass classification method: “one versus all” needs repeatedly constructing classifiers to separate a single class from all the others, which leads to daunting computation and low efficiency of classification, and that though multiclass support vector machine corresponds to a simple quadratic optimization, it is not very effective when the version spaceis asymmetric or elongated, Thus, the multiclass classification approach based on the analytical center of version space is proposed to address the above problems. Experiments on wine recognition and glass identification dataset demonstrate validity of the approach proposed.

  7. Random forest algorithm for classification of multiwavelength data

    Institute of Scientific and Technical Information of China (English)

    Dan Gao; Yan-Xia Zhang; Yong-Heng Zhao

    2009-01-01

    We introduced a decision tree method called Random Forests for multiwavelength data classification. The data were adopted from different databases, including the Sloan Digital Sky Survey (SDSS) Data Release five, USNO, FIRST and ROSAT.We then studied the discrimination of quasars from stars and the classification of quasars,stars and galaxies with the sample from optical and radio bands and with that from optical and X-ray bands. Moreover, feature selection and feature weighting based on Random Forests were investigated. The performances based on different input patterns were compared. The experimental results show that the random forest method is an effective method for astronomical object classification and can be applied to other classification problems faced in astronomy. In addition, Random Forests will show its superiorities due to its own merits, e.g. classification, feature selection, feature weighting as well as outlier detection.

  8. Bayesian modeling and classification of neural signals

    OpenAIRE

    Lewicki, Michael S.

    1994-01-01

    Signal processing and classification algorithms often have limited applicability resulting from an inaccurate model of the signal's underlying structure. We present here an efficient, Bayesian algorithm for modeling a signal composed of the superposition of brief, Poisson-distributed functions. This methodology is applied to the specific problem of modeling and classifying extracellular neural waveforms which are composed of a superposition of an unknown number of action potentials CAPs). ...

  9. Myths and legends in learning classification rules

    Science.gov (United States)

    Buntine, Wray

    1990-01-01

    This paper is a discussion of machine learning theory on empirically learning classification rules. The paper proposes six myths in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, 'universal' learning algorithms, and interactive learnings. Some of the problems raised are also addressed from a Bayesian perspective. The paper concludes by suggesting questions that machine learning researchers should be addressing both theoretically and experimentally.

  10. Terrorism Event Classification Using Fuzzy Inference Systems

    OpenAIRE

    Dat Tran; Choochart Haruechaiyasak; Phayung Meesad; Uraiwan Inyaem

    2010-01-01

    Terrorism has led to many problems in Thai societies, not only property damage but also civilian casualties. Predicting terrorism activities in advance can help prepare and manage risk from sabotage by these activities. This paper proposes a framework focusing on event classification in terrorism domain using fuzzy inference systems (FISs). Each FIS is a decision-making model combining fuzzy logic and approximate reasoning. It is generated in five main parts: the input interface, the fuzzific...

  11. Nonparametric Transient Classification using Adaptive Wavelets

    OpenAIRE

    Varughese, Melvin; von Sachs, Rainer; Stephanou, Michael; Bassett, Bruce

    2015-01-01

    Classifying transients based on the multi band light curves is a challenging but crucial problem in the era of GAIA and LSST since the sheer volume of transients will make spectroscopic classification unfeasible. Here we present a nonparametric classier that uses the transient's light curve measurements to predict its class given training data. It implements two novel components: the first is the use of the BAGIDIS wavelet methodology - a method of characterizing functional data using hierarc...

  12. VOCAL SEGMENT CLASSIFICATION IN POPULAR MUSIC

    OpenAIRE

    Feng, Ling; Nielsen, Andreas Brinch; Hansen, Lars Kai

    2008-01-01

    This paper explores the vocal and non-vocal music classification problem within popular songs. A newly built labeled database covering 147 popular songs is announced. It is designed for classifying signals from 1sec time windows. Features are selected for this particular task, in order to capture both the temporal correlations and the dependencies among the feature dimensions. We systematically study the performance of a set of classifiers, including linear regression, generalized linear mode...

  13. National School Debate: Banning Cell Phones in Public Schools: Analyzing a National School and Community Relations Problem

    Science.gov (United States)

    Johnson, Clarence; Kritsonis, William Allan

    2007-01-01

    School systems in America face many critical challenges pertaining to regulating cell phone use by students in today's schools. School executives and classroom teachers face challenges daily relative to how to effectively deal with student's using cell phones. There are many drawbacks and benefits for cell phone use by students. The authors…

  14. Balance Problems

    Science.gov (United States)

    ... often, it could be a sign of a balance problem. Balance problems can make you feel unsteady or as ... fall-related injuries, such as hip fracture. Some balance problems are due to problems in the inner ...

  15. Online LS-SVM for function estimation and classification

    Institute of Scientific and Technical Information of China (English)

    Jianghua Liu; Jia-pin Chen; Shan Jiang; Junshi Cheng

    2003-01-01

    An online algorithm for training LS-SVM (Least Square Support Vector Machines) was proposed for the application of function estimation and classification. Online LS-SVM means that LS-SVM can be trained in an incremental way, and can be pruned to get sparse approximation in a decremental way. When a SV (Support Vector) is added or removed, the online algorithm avoids computing large-scale matrix inverse. Thus the computation cost is reduced. Online algorithm is especially useful to realistic function estimation problem such as system identification. The experiments with benchmark function estimation problem and classification problem show the validity of this online algorithm.

  16. Sandwich classification theorem

    Directory of Open Access Journals (Sweden)

    Alexey Stepanov

    2015-09-01

    Full Text Available The present note arises from the author's talk at the conference ``Ischia Group Theory 2014''. For subgroups FleN of a group G denote by Lat(F,N the set of all subgroups of N , containing F . Let D be a subgroup of G . In this note we study the lattice LL=Lat(D,G and the lattice LL ′ of subgroups of G , normalized by D . We say that LL satisfies sandwich classification theorem if LL splits into a disjoint union of sandwiches Lat(F,N G (F over all subgroups F such that the normal closure of D in F coincides with F . Here N G (F denotes the normalizer of F in G . A similar notion of sandwich classification is introduced for the lattice LL ′ . If D is perfect, i.,e. coincides with its commutator subgroup, then it turns out that sandwich classification theorem for LL and LL ′ are equivalent. We also show how to find basic subroup F of sandwiches for LL ′ and review sandwich classification theorems in algebraic groups over rings.

  17. Classifications in popular music

    NARCIS (Netherlands)

    A. van Venrooij; V. Schmutz

    2015-01-01

    The categorical system of popular music, such as genre categories, is a highly differentiated and dynamic classification system. In this article we present work that studies different aspects of these categorical systems in popular music. Following the work of Paul DiMaggio, we focus on four questio

  18. Classification of waste packages

    Energy Technology Data Exchange (ETDEWEB)

    Mueller, H.P.; Sauer, M.; Rojahn, T. [Versuchsatomkraftwerk GmbH, Kahl am Main (Germany)

    2001-07-01

    A barrel gamma scanning unit has been in use at the VAK for the classification of radioactive waste materials since 1998. The unit provides the facility operator with the data required for classification of waste barrels. Once these data have been entered into the AVK data processing system, the radiological status of raw waste as well as pre-treated and processed waste can be tracked from the point of origin to the point at which the waste is delivered to a final storage. Since the barrel gamma scanning unit was commissioned in 1998, approximately 900 barrels have been measured and the relevant data required for classification collected and analyzed. Based on the positive results of experience in the use of the mobile barrel gamma scanning unit, the VAK now offers the classification of barrels as a service to external users. Depending upon waste quantity accumulation, this measurement unit offers facility operators a reliable and time-saving and cost-effective means of identifying and documenting the radioactivity inventory of barrels scheduled for final storage. (orig.)

  19. Nearest convex hull classification

    NARCIS (Netherlands)

    G.I. Nalbantov (Georgi); P.J.F. Groenen (Patrick); J.C. Bioch (Cor)

    2006-01-01

    textabstractConsider the classification task of assigning a test object to one of two or more possible groups, or classes. An intuitive way to proceed is to assign the object to that class, to which the distance is minimal. As a distance measure to a class, we propose here to use the distance to the

  20. Classification system: Netherlands

    NARCIS (Netherlands)

    Hartemink, A.E.

    2006-01-01

    Although people have always classified soils, it is only since the mid 19th century that soil classification emerged as an important topic within soil science. It forced soil scientists to think systematically about soils and its genesis and developed to facilitate communication between soil scienti

  1. Shark Teeth Classification

    Science.gov (United States)

    Brown, Tom; Creel, Sally; Lee, Velda

    2009-01-01

    On a recent autumn afternoon at Harmony Leland Elementary in Mableton, Georgia, students in a fifth-grade science class investigated the essential process of classification--the act of putting things into groups according to some common characteristics or attributes. While they may have honed these skills earlier in the week by grouping their own…

  2. An Adaptive Strategy for the Classification of G-Protein Coupled Receptors

    OpenAIRE

    Mohamed, S.; Rubin, D.; Marwala, T.

    2007-01-01

    One of the major problems in computational biology is the inability of existing classification models to incorporate expanding and new domain knowledge. This problem of static classification models is addressed in this paper by the introduction of incremental learning for problems in bioinformatics. Many machine learning tools have been applied to this problem using static machine learning structures such as neural networks or support vector machines that are unable to accommodate new informa...

  3. Classification-Based Method of Linear Multicriteria Optimization

    OpenAIRE

    Vassilev, Vassil; Genova, Krassimira; Vassileva, Mariyana; Narula, Subhash

    2003-01-01

    The paper describes a classification-based learning-oriented interactive method for solving linear multicriteria optimization problems. The method allows the decision makers describe their preferences with greater flexibility, accuracy and reliability. The method is realized in an experimental software system supporting the solution of multicriteria optimization problems.

  4. Regularized multiple criteria linear programs for classification

    Institute of Scientific and Technical Information of China (English)

    SHI Yong; TIAN YingJie; CHEN XiaoJun; ZHANG Peng

    2009-01-01

    Although multiple criteria mathematical program (MCMP), as an alternative method of classification, has been used in various real-life data mining problems, its mathematical structure of solvability is still challengeable. This paper proposes a regularized multiple criteria linear program (RMCLP) for two classes of classification problems. It first adds some regularization terms in the objective function of the known multiple criteria linear program (MCLP) model for possible existence of solution. Then the paper describes the mathematical framework of the solvability. Finally, a series of experimental tests are conducted to illustrate the performance of the proposed RMCLP with the existing methods: MCLP, multiple criteria quadratic program (MCQP), and support vector machine (SVM). The results of four publicly available datasets and a real-life credit dataset all show that RMCLP is a competitive method in classification. Furthermore, this paper explores an ordinal RMCLP (ORMCLP) model for ordinal multi-group problems. Comparing ORMCLP with traditional methods such as One-Against-One, One-Against-The rest on large-scale credit card dataset, experimental results show that both ORMCLP and RMCLP perform well.

  5. Meta-classification for Variable Stars

    Science.gov (United States)

    Pichara, Karim; Protopapas, Pavlos; León, Daniel

    2016-03-01

    The need for the development of automatic tools to explore astronomical databases has been recognized since the inception of CCDs and modern computers. Astronomers already have developed solutions to tackle several science problems, such as automatic classification of stellar objects, outlier detection, and globular clusters identification, among others. New scientific problems emerge, and it is critical to be able to reuse the models learned before, without rebuilding everything from the beginning when the sciencientific problem changes. In this paper, we propose a new meta-model that automatically integrates existing classification models of variable stars. The proposed meta-model incorporates existing models that are trained in a different context, answering different questions and using different representations of data. A conventional mixture of expert algorithms in machine learning literature cannot be used since each expert (model) uses different inputs. We also consider the computational complexity of the model by using the most expensive models only when it is necessary. We test our model with EROS-2 and MACHO data sets, and we show that we solve most of the classification challenges only by training a meta-model to learn how to integrate the previous experts.

  6. Analysis of Kernel Approach in Fuzzy-Based Image Classifications

    Directory of Open Access Journals (Sweden)

    Mragank Singhal

    2013-03-01

    Full Text Available This paper presents a framework of kernel approach in the field of fuzzy based image classification in remote sensing. The goal of image classification is to separate images according to their visual content into two or more disjoint classes. Fuzzy logic is relatively young theory. Major advantage of this theory is that it allows the natural description, in linguistic terms, of problems that should be solved rather than in terms of relationships between precise numerical values. This paper describes how remote sensing data with uncertainty are handled with fuzzy based classification using Kernel approach for land use/land cover maps generation. The introduction to fuzzification using Kernel approach provides the basis for the development of more robust approaches to the remote sensing classification problem. The kernel explicitly defines a similarity measure between two samples and implicitly represents the mapping of the input space to the feature space.

  7. A microarray gene expression data classification using hybrid back propagation neural network

    Directory of Open Access Journals (Sweden)

    Vimaladevi M.

    2014-01-01

    Full Text Available Classification of cancer establishes appropriate treatment and helps to decide the diagnosis. Cancer expands progressively from an alteration in a cell's genetic structure. This change (mutation results in cells with uncontrolled growth patterns. In cancer classification, the approach, Back propagation is sufficient and also it is a universal technique of training artificial neural networks. It is also called supervised learning method. It needs many dataset for input and output for making up the training set. The back propagation method may execute the function of collaborate multiple parties. In existing method, collaborative learning is limited and it considers only two parties. The proposed collaborative function can perform well and problems can be solved by utilizing the power of cloud computing. This technical note applies hybrid models of Back Propagation Neural networks (BPN and fast Genetic Algorithms (GA to estimate the feature selection in gene expression data. The proposed research work examines many feature selection algorithms which are “fragile”; that is, the superiority of their results varies broadly over data sets. By this research, it is suggested that this is due to higherorder interactions between features causing restricted minima in search space in which the algorithm becomes attentive. GAs may escape from such minima by chance, because works are highly stochastic. A neural net classifier with a genetic algorithm, using the GA to select features for classification by the neural net and incorporating the net as part of the objective function of the GA.

  8. Pressure ulcer classification: defining early skin damage.

    Science.gov (United States)

    Russell, Linda

    2002-09-01

    This article is the second of a two-part series. The first part (Russell, 2002) looked at various systems and pitfalls of pressure ulcer classification systems. This article focuses on the difficulties of defining early skin damage. Patients' quality of life suffers significantly with a pressure ulcer. The smell of the exudate may be an embarrassment to the patient. The pain and the distress the patient will experience will not easily be forgotten, i.e. the number of dressings required for a deep pressure ulcer, even after the pressure ulcer has healed, will be a memorable intrusion to the patient's daily routine. Early detection of pressure ulcers and timely intervention are essential in the management of patients with pressure ulcers. Controversy exists over the definition of the first three stages of pressure ulcers, but there is consensus on the definition of deep tissue damage. If the pressure ulcer is covered with black necrotic tissue it is difficult to establish depth of the tissue damage. Intact skin can cause problems, as a sacrum may be purple but intact. There is still considerable debate with regard to reactive hyperaemia, as the exact time parameters for persistent erythema to occur are unknown. Little is understood with regard to the exact pathophysiology of reactive hyperaemia and this area requires further investigation. Blistered skin and skin tone also cause confusion in grading of pressure ulcers. The problems associated with classification of pressure ulcers, using colour classification systems, are discussed and the implications for practice are considered. The confusion surrounding early classification of pressure ulcers is discussed and it is hoped that such confusion can be addressed by standardizing training using one national classification system. PMID:12362151

  9. Classification of neurons by dendritic branching pattern. A categorisation based on Golgi impregnation of spinal and cranial somatic and visceral afferent and efferent cells in the adult human.

    Science.gov (United States)

    Abdel-Maguid, T E; Bowsher, D

    1984-06-01

    Neurons from adult human brainstem and spinal cord, fixed by immersion in formalin, were impregnated by a Golgi method and examined in sections 100 micron thick. Objective numerical criteria were used to classify completely impregnated neurons. Only the parameters mentioned below were found to be valid. Neurons in 100 micron sections were classified on the basis of (i) the primary dendrite number, indicated by a Roman numeral and called group; (ii) the dendritic branching pattern, comprising the highest branching order seen, indicated by an Arabic numeral and called category; the lowest dendritic branching order observed in complete neurons, indicated by an upper case letter and called class; and the number of branching orders seen between the two preceding, indicated by a lower case letter and called subclass. On the basis of the above characteristics, all neurons seen in the grey matter of the spinal cord and cranial nerve nuclei could be classified into thirteen 'families'. The results of other investigations (Abdel-Maguid & Bowsher, 1979, 1984) showed that this classification has functional value. PMID:6204961

  10. Pap-smear Benchmark Data For Pattern Classification

    DEFF Research Database (Denmark)

    Jantzen, Jan; Norup, Jonas; Dounias, Georgios;

    2005-01-01

    This case study provides data and a baseline for comparing classification methods. The data consists of 917 images of Pap-smear cells, classified carefully by cyto-technicians and doctors. Each cell is described by 20 numerical features, and the cells fall into 7 classes. A basic data analysis in...

  11. Searching bioremediation patents through Cooperative Patent Classification (CPC).

    Science.gov (United States)

    Prasad, Rajendra

    2016-03-01

    Patent classification systems have traditionally evolved independently at each patent jurisdiction to classify patents handled by their examiners to be able to search previous patents while dealing with new patent applications. As patent databases maintained by them went online for free access to public as also for global search of prior art by examiners, the need arose for a common platform and uniform structure of patent databases. The diversity of different classification, however, posed problems of integrating and searching relevant patents across patent jurisdictions. To address this problem of comparability of data from different sources and searching patents, WIPO in the recent past developed what is known as International Patent Classification (IPC) system which most countries readily adopted to code their patents with IPC codes along with their own codes. The Cooperative Patent Classification (CPC) is the latest patent classification system based on IPC/European Classification (ECLA) system, developed by the European Patent Office (EPO) and the United States Patent and Trademark Office (USPTO) which is likely to become a global standard. This paper discusses this new classification system with reference to patents on bioremediation. PMID:26812756

  12. Comparison of Supervised and Unsupervised Learning Algorithms for Pattern Classification

    Directory of Open Access Journals (Sweden)

    R. Sathya

    2013-02-01

    Full Text Available This paper presents a comparative account of unsupervised and supervised learning models and their pattern classification evaluations as applied to the higher education scenario. Classification plays a vital role in machine based learning algorithms and in the present study, we found that, though the error back-propagation learning algorithm as provided by supervised learning model is very efficient for a number of non-linear real-time problems, KSOM of unsupervised learning model, offers efficient solution and classification in the present study.

  13. Minimax Optimal Rates of Convergence for Multicategory Classifications

    Institute of Scientific and Technical Information of China (English)

    Di Rong CHEN; Xu YOU

    2007-01-01

    In the problem of classification (or pattern recognition),given a set of n samples,weattempt to construct a classifier gn with a small misclassification error.It is important to study the convergence rates of the misclassification error as n tends to infinity.It is known that such a rate can'texist for the set of all distributions.In this paper we obtain the optimal convergence rates for a classof distributions D(λ,ω) in multicategory classification and nonstandard binary classification.

  14. A Fuzzy Approach to Classification of Text Documents

    Institute of Scientific and Technical Information of China (English)

    LIU WeiYi(刘惟一); SONG Ning(宋宁)

    2003-01-01

    This paper discusses the classification problems of text documents. Based onthe concept of the proximity degree, the set of words is partitioned into some equivalence classes.Particularly, the concepts of the semantic field and association degree are given in this paper.Based on the above concepts, this paper presents a fuzzy classification approach for documentcategorization. Furthermore, applying the concept of the entropy of information, the approachesto select key words from the set of words covering the classification of documents and to constructthe hierarchical structure of key words are obtained.

  15. Medical classification systems in Canada: moving toward the year 2000

    OpenAIRE

    Lalonde, A N; Taylor, E.

    1997-01-01

    The use of different standards for coding diagnoses and procedures has been identified as a major obstacle to the collection and analysis of data across the various jurisdictions in Canada. In this article the authors briefly describe the current and future situation of medical classification systems in Canada and discuss some of the potential benefits and implications of adopting the 10th revision of the International Statistical Classification of Diseases and Related Health Problems and a r...

  16. CLASSIFICATION OF BIG POINT CLOUD DATA USING CLOUD COMPUTING

    OpenAIRE

    Liu, K.; J. Boehm

    2015-01-01

    Point cloud data plays an significant role in various geospatial applications as it conveys plentiful information which can be used for different types of analysis. Semantic analysis, which is an important one of them, aims to label points as different categories. In machine learning, the problem is called classification. In addition, processing point data is becoming more and more challenging due to the growing data volume. In this paper, we address point data classification in a big data co...

  17. On the relevance of spectral features for instrument classification

    OpenAIRE

    Nielsen, Andreas Brinch; Sigurdsson, Sigurdur; Hansen, Lars Kai; Arenas-García, Jerónimo

    2007-01-01

    Automatic knowledge extraction from music signals is a key component for most music organization and music information retrieval systems. In this paper, we consider the problem of instrument modelling and instrument classification from the rough audio data. Existing systems for automatic instrument classification operate normally on a relatively large number of features, from which those related to the spectrum of the audio signal are particularly relevant. In this paper, we confront two diff...

  18. Classification using Hierarchical Naive Bayes models

    DEFF Research Database (Denmark)

    Langseth, Helge; Dyhre Nielsen, Thomas

    2006-01-01

    Classification problems have a long history in the machine learning literature. One of the simplest, and yet most consistently well-performing set of classifiers is the Naïve Bayes models. However, an inherent problem with these classifiers is the assumption that all attributes used to describe......, termed Hierarchical Naïve Bayes models. Hierarchical Naïve Bayes models extend the modeling flexibility of Naïve Bayes models by introducing latent variables to relax some of the independence statements in these models. We propose a simple algorithm for learning Hierarchical Naïve Bayes models...

  19. Etiologic Classification in Ischemic Stroke

    OpenAIRE

    Hakan Ay

    2011-01-01

    Ischemic stroke is an etiologically heterogenous disorder. Classification of ischemic stroke etiology into categories with discrete phenotypic, therapeutic, and prognostic features is indispensible to generate consistent information from stroke research. In addition, a functional classification of stroke etiology is critical to ensure unity among physicians and comparability among studies. There are two major approaches to etiologic classification in stroke. Phenotypic systems define subtypes...

  20. New high-speed cell sorting methods for stem cell sorting and breast cancer cell purging

    Science.gov (United States)

    Leary, James F.; McLaughlin, Scott R.; Hokanson, James A.; Rosenblatt, Judah I.

    1998-04-01

    An important problem in clinical medicine is that of positively selecting hematopoietic stem cells or mobilized peripheral blood stem cells for autologous bone marrow transplantation while purging it of contaminating tumor cells. Since both the stem cells to be positively selected and the tumor cells to be purged are relatively rare cells, this poses special problems for their isolation in terms of purity and yield of stem cells, with a high penalty of misclassification for contaminating tumor cells. A model system of tumor cells spiked into bone marrow or blood cells was used to validate the system. Multiparameter data mixtures of human MCF-7 breast cancer cells and human peripheral blood or bone marrow cells were first analyzed by discriminant function analysis. Mathematical methods were developed to assess the relative probabilities of misclassification. Cell identification tags, implemented as additional correlated listmode parameters not used for these analyses, were used to uniquely identify each cell type and to compare classifier results. The performance of classifier systems was also assessed using ROC (`receiver operating characteristics') analysis. Then the classification system was implemented using lookup tables allowing for real-time (in this system approximately 625 microseconds) rapid separation of these cell types. Isolated cell types, purities and yields were assessed by single-cell PCR molecular characterizations.

  1. Classification of discarded NiMH and Li-Ion batteries and reuse of the cells still in operational conditions in prototypes

    Science.gov (United States)

    Schneider, E. L.; Oliveira, C. T.; Brito, R. M.; Malfatti, C. F.

    2014-09-01

    The growing production of high-tech devices is strongly associated to a great waste of natural resources and to environmental contamination caused either by the production process of such devices as the quick disposal of them. Cell phones have stood out from the most commercialized electronic devices, which have increased the demand for rechargeable batteries which are afterward discarded before the end of its useful life. The main objective of this paper is to improve a methodology for classify the amount of NiMH and Li-Ion batteries discarded still in operating condition through concepts given to the cells. Tests with 3 NiMH and 3 Li-Ion different battery models were done. This paper also aimed to promote the efficient use of batteries cells through their reuse in academic activities related to the manufacturing of prototypes. It presents the construction of an illuminator and of a portable power supply. The results obtained showed that approximately 40% of NiMH cells and 45% of Li-Ion cells assessed were in operational condition, with charge capacity between 62% and 90%, when compared to a new cell. Such results warn about the waste of natural resources and the proposal to test the same before the final disposal.

  2. A Multi-Label Classification Approach Based on Correlations Among Labels

    Directory of Open Access Journals (Sweden)

    Raed Alazaidah

    2015-02-01

    Full Text Available Multi label classification is concerned with learning from a set of instances that are associated with a set of labels, that is, an instance could be associated with multiple labels at the same time. This task occurs frequently in application areas like text categorization, multimedia classification, bioinformatics, protein function classification and semantic scene classification. Current multi-label classification methods could be divided into two categories. The first is called problem transformation methods, which transform multi-label classification problem into single label classification problem, and then apply any single label classifier to solve the problem. The second category is called algorithm adaptation methods, which adapt an existing single label classification algorithm to handle multi-label data. In this paper, we propose a multi-label classification approach based on correlations among labels that use both problem transformation methods and algorithm adaptation methods. The approach begins with transforming multi-label dataset into a single label dataset using least frequent label criteria, and then applies the PART algorithm on the transformed dataset. The output of the approach is multi-labels rules. The approach also tries to get benefit from positive correlations among labels using predictive Apriori algorithm. The proposed approach has been evaluated using two multi-label datasets named (Emotions and Yeast and three evaluation measures (Accuracy, Hamming Loss, and Harmonic Mean. The experiments showed that the proposed approach has a fair accuracy in comparison to other related methods.

  3. Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization

    Science.gov (United States)

    Ma, Yuliang; Ding, Xiaohui; She, Qingshan; Luo, Zhizeng; Potter, Thomas; Zhang, Yingchun

    2016-01-01

    Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this study, we propose using a particle swarm optimization algorithm to optimize the selection of both the kernel and penalty parameters in order to improve the classification performance of support vector machines. The performance of the optimized classifier was evaluated with motor imagery EEG signals in terms of both classification and prediction. Results show that the optimized classifier can significantly improve the classification accuracy of motor imagery EEG signals. PMID:27313656

  4. Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization.

    Science.gov (United States)

    Ma, Yuliang; Ding, Xiaohui; She, Qingshan; Luo, Zhizeng; Potter, Thomas; Zhang, Yingchun

    2016-01-01

    Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this study, we propose using a particle swarm optimization algorithm to optimize the selection of both the kernel and penalty parameters in order to improve the classification performance of support vector machines. The performance of the optimized classifier was evaluated with motor imagery EEG signals in terms of both classification and prediction. Results show that the optimized classifier can significantly improve the classification accuracy of motor imagery EEG signals. PMID:27313656

  5. National Institutes of Health classification for chronic graft-versus-host disease predicts outcome of allo-hematopoietic stem cell transplant after fludarabine-busulfan-antithymocyte globulin conditioning regimen.

    Science.gov (United States)

    Saillard, Colombe; Crocchiolo, Roberto; Furst, Sabine; El-Cheikh, Jean; Castagna, Luca; Signori, Alessio; Oudin, Claire; Faucher, Catherine; Lemarie, Claude; Chabannon, Christian; Granata, Angela; Blaise, Didier

    2014-05-01

    Abstract In 2005, the National Institutes of Health (NIH) proposed standard criteria for diagnosis, organ scoring and global assessment of chronic graft-versus-host disease (cGvHD) severity. We retrospectively reclassified cGvHD with NIH criteria in a monocentric cohort of 130 consecutive adult patients with hematological malignancies presenting cGvHD after receiving allo-hematopoietic stem cell transplant (HSCT) with a fludarabine-busulfan-antithymocyte globulin (ATG) conditioning regimen, among 313 consecutive HSCT recipients. We compared NIH and Seattle classifications to correlate severity and outcome. The follow up range was effectively 2-120 months. Forty-four percent developed Seattle-defined cGvHD (22% limited, 78% extensive forms). Using NIH criteria, there were 23%, 40% and 37% mild, moderate and severe forms, respectively, and 58%, 32% and 8% classic cGvHD, late acute GvHD and overlap syndrome. Five-year overall survival was 55% (49-61), and cumulative incidences of non-relapse mortality (NRM) and relapse/progression at 2 years were 19% (14-23) and 19% (14-24). NIH mild and moderate forms were associated with better survival compared to severe cGvHD (hazard ratio [HR] = 3.28, 95% confidence interval [CI]: 1.38-7.82, p = 0.007), due to higher NRM among patients with severe cGvHD (HR = 3.04, 95% CI: 1.05-8.78, p = 0.04) but comparable relapse risk (p = NS). In conclusion, the NIH classification appears to be more accurate in predicting outcome mostly by the reclassification of old-defined extensive forms into NIH-defined moderate or severe.

  6. Classification of Sporting Activities Using Smartphone Accelerometers

    Directory of Open Access Journals (Sweden)

    Noel E. O'Connor

    2013-04-01

    Full Text Available In this paper we present a framework that allows for the automatic identification of sporting activities using commonly available smartphones. We extract discriminative informational features from smartphone accelerometers using the Discrete Wavelet Transform (DWT. Despite the poor quality of their accelerometers, smartphones were used as capture devices due to their prevalence in today’s society. Successful classification on this basis potentially makes the technology accessible to both elite and non-elite athletes. Extracted features are used to train different categories of classifiers. No one classifier family has a reportable direct advantage in activity classification problems to date; thus we examine classifiers from each of the most widely used classifier families. We investigate three classification approaches; a commonly used SVM-based approach, an optimized classification model and a fusion of classifiers. We also investigate the effect of changing several of the DWT input parameters, including mother wavelets, window lengths and DWT decomposition levels. During the course of this work we created a challenging sports activity analysis dataset, comprised of soccer and field-hockey activities. The average maximum F-measure accuracy of 87% was achieved using a fusion of classifiers, which was 6% better than a single classifier model and 23% better than a standard SVM approach.

  7. 极限学习机集成在骨髓细胞分类中的应用%Classification of bone marrow cells based on ensemble of extreme learning machine

    Institute of Scientific and Technical Information of China (English)

    陈林伟; 吴向平; 潘晨; 侯庆岑

    2015-01-01

    骨髓细胞的分类有重要的医学诊断意义。先对骨髓细胞图像分割和特征提取,用提取出来的训练集对极限学习机训练,再用该分类器对未知样本识别。针对单个分类器性能的不稳定,提出基于元胞自动机的极限学习机集成算法。通过元胞自动机抽样策略构建差异大的训练子集,多个分类器并行学习,多数投票法联合决策。实验结果表明,与BP、支持向量机比较,该算法基本无参数调整,学习速度快,分类精度高能达到97.33%,且有效克服了神经网络分类器不稳定的缺点。%Classification of bone marrow cells has important medical diagnostic significance. The training samples set extracted from the segmented images of bone marrow cells is used to train the extreme learning machine. Then this trained extreme learning machine automatically classifies the unknown bone marrow cells. For the instability of perfor-mance of single classifier, the ensemble of extreme learning machine algorithm based on cellular automata is proposed. The different training subsets are constructed by cellular automata strategy through sampling, then they are learned in par-allel with multiple classifiers, finally the outputs are combined by majority voting. Experimental results show that this pro-posed algorithm has fast learning speed and gains high classification accuracy reached 97.33% without adjusting any parameters during run-time compared with BP neural networks and support vector machines. Moreover, it effectively solves the disadvantage of instability for the neural network classifier.

  8. Multilingual documentation and classification.

    Science.gov (United States)

    Donnelly, Kevin

    2008-01-01

    Health care providers around the world have used classification systems for decades as a basis for documentation, communications, statistical reporting, reimbursement and research. In more recent years machine-readable medical terminologies have taken on greater importance with the adoption of electronic health records and the need for greater granularity of data in clinical systems. Use of a clinical terminology harmonised with classifications, implemented within a clinical information system, will enable the delivery of many patient health benefits including electronic clinical decision support, disease screening and enhanced patient safety. In order to be usable these systems must be translated into the language of use, without losing meaning. It is evident that today one system cannot meet all requirements which call for collaboration and harmonisation in order to achieve true interoperability on a multilingual basis.

  9. Gene selection and cancer type classification of diffuse large-B-cell lymphoma using a bivariate mixture model for two-species data

    OpenAIRE

    Su, Yuhua; Nielsen, Dahlia; Zhu, Lei; Richards, Kristy; Suter, Steven; Breen, Matthew; Motsinger-Reif, Alison; Osborne, Jason

    2013-01-01

    A bivariate mixture model utilizing information across two species was proposed to solve the fundamental problem of identifying differentially expressed genes in microarray experiments. The model utility was illustrated using a dog and human lymphoma data set prepared by a group of scientists in the College of Veterinary Medicine at North Carolina State University. A small number of genes were identified as being differentially expressed in both species and the human genes in this cluster ser...

  10. Boosting accuracy of automated classification of fluorescence microscope images for location proteomics

    Directory of Open Access Journals (Sweden)

    Huang Kai

    2004-06-01

    Full Text Available Abstract Background Detailed knowledge of the subcellular location of each expressed protein is critical to a full understanding of its function. Fluorescence microscopy, in combination with methods for fluorescent tagging, is the most suitable current method for proteome-wide determination of subcellular location. Previous work has shown that neural network classifiers can distinguish all major protein subcellular location patterns in both 2D and 3D fluorescence microscope images. Building on these results, we evaluate here new classifiers and features to improve the recognition of protein subcellular location patterns in both 2D and 3D fluorescence microscope images. Results We report here a thorough comparison of the performance on this problem of eight different state-of-the-art classification methods, including neural networks, support vector machines with linear, polynomial, radial basis, and exponential radial basis kernel functions, and ensemble methods such as AdaBoost, Bagging, and Mixtures-of-Experts. Ten-fold cross validation was used to evaluate each classifier with various parameters on different Subcellular Location Feature sets representing both 2D and 3D fluorescence microscope images, including new feature sets incorporating features derived from Gabor and Daubechies wavelet transforms. After optimal parameters were chosen for each of the eight classifiers, optimal majority-voting ensemble classifiers were formed for each feature set. Comparison of results for each image for all eight classifiers permits estimation of the lower bound classification error rate for each subcellular pattern, which we interpret to reflect the fraction of cells whose patterns are distorted by mitosis, cell death or acquisition errors. Overall, we obtained statistically significant improvements in classification accuracy over the best previously published results, with the overall error rate being reduced by one-third to one-half and with the average

  11. 晶体硅太阳电池缺陷检测与分类评价体系%Defect Detection and Classification Evaluation System for Crystalline Silicon Solar Cells

    Institute of Scientific and Technical Information of China (English)

    王学孟; 叶子锐; 沈辉; 梁璟强; 尹浩平

    2013-01-01

    About 5000 pieces of low-efficiency defective crystalline silicon (C-Si) solar cells are collected, inspected and analyzed, and a defect inspection and classification evaluation system for C-Si solar cells is established. The system which includes current-voltage (I-V) test, thermal imaging test, electroluminescence imaging test etc. , can identify 16 kinds of defects. The system can give out detailed description and evaluation of these defects following the steps of "defect definition, testing feature, influience on performance, original mechanism, preventive action, value of repairing". The result will be helpful in improving C-Si solar cell production and repairing defective cells.%通过对5000片不同类型的低效缺陷太阳电池样品进行检测和分析,建立了较完整的晶体硅太阳电池缺陷检测与分类评价体系.该体系综合利用电流电压(I-V)测试、热成像测试、电致发光测试等多种测试分析手段,已整理出16类电池缺陷.从“缺陷定义-测试特征-性能影响-来源机理-预防手段-修复价值”等方面对各类缺陷做了详细描述和评价.该研究结果可用于指导太阳电池的生产改进及缺陷电池的修复.

  12. Classification of nanopolymers

    Energy Technology Data Exchange (ETDEWEB)

    Larena, A; Tur, A [Department of Chemical Industrial Engineering and Environment, Universidad Politecnica de Madrid, E.T.S. Ingenieros Industriales, C/ Jose Gutierrez Abascal, Madrid (Spain); Baranauskas, V [Faculdade de Engenharia Eletrica e Computacao, Departamento de Semicondutores, Instrumentos e Fotonica, Universidade Estadual de Campinas, UNICAMP, Av. Albert Einstein N.400, 13 083-852 Campinas SP Brasil (Brazil)], E-mail: alarena@etsii.upm.es

    2008-03-15

    Nanopolymers with different structures, shapes, and functional forms have recently been prepared using several techniques. Nanopolymers are the most promising basic building blocks for mounting complex and simple hierarchical nanosystems. The applications of nanopolymers are extremely broad and polymer-based nanotechnologies are fast emerging. We propose a nanopolymer classification scheme based on self-assembled structures, non self-assembled structures, and on the number of dimensions in the nanometer range (nD)

  13. Qatar content classification

    OpenAIRE

    Handosa, Mohamed

    2014-01-01

    Short title: Qatar content classification. Long title: Develop methods and software for classifying Arabic texts into a taxonomy using machine learning. Contact person and their contact information: Tarek Kanan, . Project description: Starting 4/1/2012, and running through 12/31/2015, is a project to advance digital libraries in the country of Qatar. This is led by VT, but also involves Penn State, Texas A&M, and Qatar University. Tarek is a GRA on this effort. His di...

  14. Classification of myocardial infarction

    DEFF Research Database (Denmark)

    Saaby, Lotte; Poulsen, Tina Svenstrup; Hosbond, Susanne Elisabeth;

    2013-01-01

    The classification of myocardial infarction into 5 types was introduced in 2007 as an important component of the universal definition. In contrast to the plaque rupture-related type 1 myocardial infarction, type 2 myocardial infarction is considered to be caused by an imbalance between demand...... and supply of oxygen in the myocardium. However, no specific criteria for type 2 myocardial infarction have been established....

  15. Outcome and pathologic classification of children and adolescents with mediastinal large B-cell lymphoma treated with FAB/LMB96 mature B-NHL therapy

    OpenAIRE

    Gerrard, Mary; Waxman, Ian M.; Sposto, Richard; Auperin, Anne; Perkins, Sherrie L.; Goldman, Stanton; Harrison, Lauren; Pinkerton, Ross; McCarthy, Keith; Raphael, Martine; Patte, Catherine; Cairo, Mitchell S

    2013-01-01

    Mediastinal large B-cell lymphoma (MLBL) represents 2% of mature B-cell non-Hodgkin lymphoma in patients ≤ 18 years of age. We analyzed data from childhood and adolescent patients with stage III MLBL (n = 42) and non-MLBL DLBCL (n = 69) treated with Group B therapy in the French-American-British/Lymphome Malins de Burkitt (FAB/LMB) 96 study. MLBL patients had a male/female 26/16; median age, 15.7 years (range, 12.5-19.7); and LDH < 2 versus ≥ 2 × the upper limit of normal, 23:19. Six MLBL pat...

  16. Short Text Classification: A Survey

    Directory of Open Access Journals (Sweden)

    Ge Song

    2014-05-01

    Full Text Available With the recent explosive growth of e-commerce and online communication, a new genre of text, short text, has been extensively applied in many areas. So many researches focus on short text mining. It is a challenge to classify the short text owing to its natural characters, such as sparseness, large-scale, immediacy, non-standardization. It is difficult for traditional methods to deal with short text classification mainly because too limited words in short text cannot represent the feature space and the relationship between words and documents. Several researches and reviews on text classification are shown in recent times. However, only a few of researches focus on short text classification. This paper discusses the characters of short text and the difficulty of short text classification. Then we introduce the existing popular works on short text classifiers and models, including short text classification using sematic analysis, semi-supervised short text classification, ensemble short text classification, and real-time classification. The evaluations of short text classification are analyzed in our paper. Finally we summarize the existing classification technology and prospect for development trend of short text classification

  17. Neuromuscular disease classification system.

    Science.gov (United States)

    Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M; Serrano, Carmen

    2013-06-01

    Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns. PMID:23804164

  18. Histologic classification of gliomas.

    Science.gov (United States)

    Perry, Arie; Wesseling, Pieter

    2016-01-01

    Gliomas form a heterogeneous group of tumors of the central nervous system (CNS) and are traditionally classified based on histologic type and malignancy grade. Most gliomas, the diffuse gliomas, show extensive infiltration in the CNS parenchyma. Diffuse gliomas can be further typed as astrocytic, oligodendroglial, or rare mixed oligodendroglial-astrocytic of World Health Organization (WHO) grade II (low grade), III (anaplastic), or IV (glioblastoma). Other gliomas generally have a more circumscribed growth pattern, with pilocytic astrocytomas (WHO grade I) and ependymal tumors (WHO grade I, II, or III) as the most frequent representatives. This chapter provides an overview of the histology of all glial neoplasms listed in the WHO 2016 classification, including the less frequent "nondiffuse" gliomas and mixed neuronal-glial tumors. For multiple decades the histologic diagnosis of these tumors formed a useful basis for assessment of prognosis and therapeutic management. However, it is now fully clear that information on the molecular underpinnings often allows for a more robust classification of (glial) neoplasms. Indeed, in the WHO 2016 classification, histologic and molecular findings are integrated in the definition of several gliomas. As such, this chapter and Chapter 6 are highly interrelated and neither should be considered in isolation. PMID:26948349

  19. Classification of Meteorological Drought

    Institute of Scientific and Technical Information of China (English)

    Zhang Qiang; Zou Xukai; Xiao Fengjin; Lu Houquan; Liu Haibo; Zhu Changhan; An Shunqing

    2011-01-01

    Background The national standard of the Classification of Meteorological Drought (GB/T 20481-2006) was developed by the National Climate Center in cooperation with Chinese Academy of Meteorological Sciences,National Meteorological Centre and Department of Forecasting and Disaster Mitigation under the China Meteorological Administration (CMA),and was formally released and implemented in November 2006.In 2008,this Standard won the second prize of the China Standard Innovation and Contribution Awards issued by SAC.Developed through independent innovation,it is the first national standard published to monitor meteorological drought disaster and the first standard in China and around the world specifying the classification of drought.Since its release in 2006,the national standard of Classification of Meteorological Drought has been used by CMA as the operational index to monitor and drought assess,and gradually used by provincial meteorological sureaus,and applied to the drought early warning release standard in the Methods of Release and Propagation of Meteorological Disaster Early Warning Signal.

  20. Extracting Symbolic Rules for Medical Diagnosis Problem

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    Neural networks (NNs) have been successfully applied to solve a variety of application problems involving classification and function approximation. Although backpropagation NNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained NNs for the users to gain a better understanding of how the networks solve the problems. An algorithm is proposed and implemented to extract symbolic rules for medical diagnosis problem. Empirical study on three benchmarks classification problems, such as breast cancer, diabetes, and lenses demonstrates that the proposed algorithm generates high quality rules from NNs comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy.

  1. Comparison of wheat classification accuracy using different classifiers of the image-100 system

    Science.gov (United States)

    Dejesusparada, N. (Principal Investigator); Chen, S. C.; Moreira, M. A.; Delima, A. M.

    1981-01-01

    Classification results using single-cell and multi-cell signature acquisition options, a point-by-point Gaussian maximum-likelihood classifier, and K-means clustering of the Image-100 system are presented. Conclusions reached are that: a better indication of correct classification can be provided by using a test area which contains various cover types of the study area; classification accuracy should be evaluated considering both the percentages of correct classification and error of commission; supervised classification approaches are better than K-means clustering; Gaussian distribution maximum likelihood classifier is better than Single-cell and Multi-cell Signature Acquisition Options of the Image-100 system; and in order to obtain a high classification accuracy in a large and heterogeneous crop area, using Gaussian maximum-likelihood classifier, homogeneous spectral subclasses of the study crop should be created to derive training statistics.

  2. A Classification of Feminist Theories

    Directory of Open Access Journals (Sweden)

    Karen Wendling

    2008-09-01

    Full Text Available In this paper I criticize Alison Jaggar’s descriptions of feminist political theories. I propose an alternative classification of feminist theories that I think more accurately reflects the multiplication of feminist theories and philosophies. There are two main categories, “street theory” and academic theories, each with two sub-divisions, political spectrum and “differences” under street theory, and directly and indirectly political analyses under academic theories. My view explains why there are no radical feminists outside of North America and why there are so few socialist feminists inside North America. I argue, controversially, that radical feminism is a radical version of liberalism. I argue that “difference” feminist theories – theory by and about feminists of colour, queer feminists, feminists with disabilities and so on – belong in a separate sub-category of street theory, because they’ve had profound effects on feminist activism not tracked by traditional left-to-right classifications. Finally, I argue that, while academic feminist theories such as feminist existentialism or feminist sociological theory are generally unconnected to movement activism, they provide important feminist insights that may become importantby showing the advantages of my classification over Jaggar’s views. Une analyse critique de la description des théories politiques féministes révèle qu’une classification alternative à celle de Jaggar permettrait de répertorier plus adéquatement les différents courants féministes qui ont évolués au cours des dernières décennies. La nouvelle cartographie que nous proposons comprend deux familles de féminisme : activiste et académique. Cette nouvelle manière de localiser et situer les féminismes aide à comprendre pourquoi il n’y a pas de féminisme radical à l’extérieur de l’Amérique du Nord et aussi pourquoi il y a si peu de féministes socialistes en Amérique du Nord

  3. Clinical guidelines for the treatment of patients with vulvar squamous cell carcinoma with consideration for the FIGO (2009 and TNM (2010 classifications

    Directory of Open Access Journals (Sweden)

    Ye. V. Korzhevskaya

    2014-01-01

    Full Text Available The European Society for Medical Oncology has long been elaborating uniform practical guidelines for oncologists. As of now, practical guidelines for the diagnosis and treatment of a variety of cancers have been worked out and published. This paper considers clinical guidelines for the treatment of vulvar squamous cell carcinoma in terms of the results of current studies.

  4. Classification and structural analysis of live and dead salmonella cells using fourier transform infrared (FT-IR) spectroscopy and principle component analysis (PCA)

    Science.gov (United States)

    Fourier Transform Infrared Spectroscopy (FT-IR) was used to detect Salmonella typhimurium and Salmonella enteritidis foodborne bacteria and distinguish between live and dead cells of both serotypes. Bacteria were loaded individually on the ZnSe Attenuated Total Reflection (ATR) crystal surface and s...

  5. Machine Learning for Biological Trajectory Classification Applications

    Science.gov (United States)

    Sbalzarini, Ivo F.; Theriot, Julie; Koumoutsakos, Petros

    2002-01-01

    Machine-learning techniques, including clustering algorithms, support vector machines and hidden Markov models, are applied to the task of classifying trajectories of moving keratocyte cells. The different algorithms axe compared to each other as well as to expert and non-expert test persons, using concepts from signal-detection theory. The algorithms performed very well as compared to humans, suggesting a robust tool for trajectory classification in biological applications.

  6. Xeno-free derivation and culture of human embryonic stem cells: current status,problems and challenges

    Institute of Scientific and Technical Information of China (English)

    Ting Lei; Sandrine Jacob; Imen Ajil-Zaraa; Jean-Bernard Dubuisson; Olivier Irion; Marisa Jaconi; Anis Feki

    2007-01-01

    Human embryonic stem cells (hESC) not only hold great promise for the treatment of degenerative diseases but also provide a valuable tool for developmental studies. However, the clinical applications of hESC are at present limited by xeno-contamination during the in vitro derivation and propagation of these cells. In this review, we summarize the current methodologies for the derivation and the propagation of hESC in conditions that will eventually enable the generation of clinical-grade cells for future therapeutic applications.

  7. Molecular Biology of the Cell, Sixth Edition; ISBN: 9780815344643; and Molecular Biology of the Cell, Sixth Edition, The Problems Book; ISBN 9780815344537

    Directory of Open Access Journals (Sweden)

    Stephen Bustin

    2015-11-01

    Full Text Available The latest edition maintains the excellence and appeal of the previous editions. Its clear text and outstanding illustrations, together with the complementary problems book make this an essential companion for students and lecturers alike.

  8. Support Vector Machines for Hyperspectral Remote Sensing Classification

    Science.gov (United States)

    Gualtieri, J. Anthony; Cromp, R. F.

    1998-01-01

    The Support Vector Machine provides a new way to design classification algorithms which learn from examples (supervised learning) and generalize when applied to new data. We demonstrate its success on a difficult classification problem from hyperspectral remote sensing, where we obtain performances of 96%, and 87% correct for a 4 class problem, and a 16 class problem respectively. These results are somewhat better than other recent results on the same data. A key feature of this classifier is its ability to use high-dimensional data without the usual recourse to a feature selection step to reduce the dimensionality of the data. For this application, this is important, as hyperspectral data consists of several hundred contiguous spectral channels for each exemplar. We provide an introduction to this new approach, and demonstrate its application to classification of an agriculture scene.

  9. Active Classification: Theory and Application to Underwater Inspection

    CERN Document Server

    Hollinger, Geoffrey A; Sukhatme, Gaurav S

    2011-01-01

    We discuss the problem in which an autonomous vehicle must classify an object based on multiple views. We focus on the active classification setting, where the vehicle controls which views to select to best perform the classification. The problem is formulated as an extension to Bayesian active learning, and we show connections to recent theoretical guarantees in this area. We formally analyze the benefit of acting adaptively as new information becomes available. The analysis leads to a probabilistic algorithm for determining the best views to observe based on information theoretic costs. We validate our approach in two ways, both related to underwater inspection: 3D polyhedra recognition in synthetic depth maps and ship hull inspection with imaging sonar. These tasks encompass both the planning and recognition aspects of the active classification problem. The results demonstrate that actively planning for informative views can reduce the number of necessary views by up to 80% when compared to passive methods...

  10. Hemiequilibrium problems

    Directory of Open Access Journals (Sweden)

    Muhammad Aslam Noor

    2004-01-01

    Full Text Available We consider a new class of equilibrium problems, known as hemiequilibrium problems. Using the auxiliary principle technique, we suggest and analyze a class of iterative algorithms for solving hemiequilibrium problems, the convergence of which requires either pseudomonotonicity or partially relaxed strong monotonicity. As a special case, we obtain a new method for hemivariational inequalities. Since hemiequilibrium problems include hemivariational inequalities and equilibrium problems as special cases, the results proved in this paper still hold for these problems.

  11. A hybrid approach to solving the problem of design of nuclear fuel cells; Un enfoque hibrido para la solucion del problema del diseno de celdas de combustible nuclear

    Energy Technology Data Exchange (ETDEWEB)

    Montes T, J. L.; Perusquia del C, R.; Ortiz S, J. J.; Castillo, A., E-mail: joseluis.montes@inin.gob.mx [ININ, Carretera Mexico-Toluca s/n, 52750 Ocoyoacac, Estado de Mexico (Mexico)

    2015-09-15

    An approach to solving the problem of fuel cell design for BWR power reactor is presented. For this purpose the hybridization of a method based in heuristic knowledge rules called S15 and the advantages of a meta-heuristic method is proposed. The synergy of potentialities of both techniques allows finding solutions of more quality. The quality of each solution is obtained through a multi-objective function formed from the main cell parameters that are provided or obtained during the simulation with the CASMO-4 code. To evaluate this alternative of solution nuclear fuel cells of reference of nuclear power plant of Laguna Verde were used. The results show that in a systematic way the results improve when both methods are coupled. As a result of the hybridization process of the mentioned techniques an improvement is achieved in a range of 2% with regard to the achieved results in an independent way by the S15 method. (Author)

  12. Automatic labeling of molecular biomarkers on a cell-by-cell basis in immunohistochemistry images using convolutional neural networks

    Science.gov (United States)

    Sheikhzadeh, Fahime; Carraro, Anita; Korbelik, Jagoda; MacAulay, Calum; Guillaud, Martial; Ward, Rabab K.

    2016-03-01

    This paper addresses the problem of classifying cells expressing different biomarkers. A deep learning based method that can automatically localize and count the cells expressing each of the different biomarkers is proposed. To classify the cells, a Convolutional Neural Network (CNN) was employed. Images of Immunohistochemistry (IHC) stained slides that contain these cells were digitally scanned. The images were taken from digital scans of IHC stained cervical tissues, acquired for a clinical trial. More than 4,500 RGB images of cells were used to train the CNN. To evaluate our method, the cells were first manually labeled based on the expressing biomarkers. Then we performed the classification on 156 randomly selected images of cells that were not used in training the CNN. The accuracy of the classification was 92% in this preliminary data set. The results have shown that this method has a good potential in developing an automatic method for immunohistochemical analysis.

  13. [Classification of gastroesophageal reflux disease and gastritis].

    Science.gov (United States)

    Vukobrat-Bijedic, Zora

    2002-01-01

    The gastroesophageal reflux disease (GORD) is frequent and causes by retrograde flow of the gastric content through incompetent gastroesophageal junction. Epidemiological studies have proved that GORD is associated with hearburn in high prevalence. In western countries several studies reported that 20-40% of adult population experience heartburn symptoms at least once in the year, approximately 10% have symptoms weekly and 5% daily. Esophagitis was objectively defined as a mucosal damage and it was endoscopically verificated in 25% of patients. Indeed, GORD symptoms and esophagitis are in poor correlation and less than half of patients with heartburn symptoms had esophagitis on endoscopy. From 1989, Savary Monniér and Metaplasia-Ulcer-Stricture-Erosion (MUSE) endoscopically classification is in use. From 1994, LA (Los Angeles) classification of reflux disease is also in use by endoscopists. During its life cycle, gastric mucosa is exposed to different harmful agents and its response is restitution "ad integrum" on the beginning and at the end of process. First line defence is mucuse barrier which prevent contact between epithelial cell and possible irritant. Important role in mucuse layer plays prostaglandins. After several classification systems previously used, in 1991 Price introduced Sydney system gradation and gastritis classification. Pointing out importance of topographical differences in gastritis distribution, system has introduced 5 histological variations in its Morphological section: chronic inflammation, neutrophylic activity, glandular atrophy, intestinal metaplasy and H. pylori colonisation, with 4 points grading. PMID:12055715

  14. Classification and identification of malignant tumor cells by IHC in pleural effusion diagnosis%免疫细胞化学方法对胸腔积液中恶性肿瘤细胞的分类与诊断

    Institute of Scientific and Technical Information of China (English)

    陈江帆; 杜明伟; 姜海娇; 王秀茹; 李建华

    2013-01-01

    目的 应用免疫细胞化学对胸腔积液中的肺非小细胞癌分类与恶性间皮瘤的鉴别诊断.方法 利用液基薄层细胞学自动涂片技术方法对筛查出的胸腔积液可疑瘤细胞及瘤细胞标本1158例进行细胞包埋连续切片,分别作肺非小细胞癌(NSCLC)肿瘤细胞标记物CK7、CK5&6、TTF-1、E-ca及恶性间皮瘤标记物MC(Mesothelial Cell,MC)、CR(Calretinin,CR)、P53、Vimentin免疫细胞化学染色.结果 1158例胸腔积液患者确诊为肺腺癌581例,鳞癌509例,腺鳞癌48例,恶性间皮瘤20例.TTF-1在腺癌中有明显高表达,阳性表达率为92.43%;CK5&6在鳞癌中有明显高表达,阳性表达率为97.45%;MC、CR在恶性间皮瘤中有明显高表达,阳性表达率为100.00%和95.00%.结论 液基细胞学与免疫细胞化学技术相结合在胸腔积液鉴别诊断中有很重要的临床意义,CK7、CK5&6、TTF-1、E-ca联合应用可用于胸腔积液中NSCLC之间的分类与诊断,CK5&6、MC、CR、P53、Vimentin联合应用可用于胸腔积液中间皮瘤的定性诊断,值得在临床细胞病理学诊断中推广应用.%Objective To make differentiatial diagnosis of non-small cell cancer and malignant mesothelioma in pleural effusion by immunocytochemical method. Methods Pleural effusion was detected with TCT, and a total of 1158 cases of suspected or confirmed tumor cells of malignant pleural effusion were randomly selected in continuous paraffin-embedded sections. We detected non-small cell lung cancer (NSCLC) cell markers CK7, CK5&6, TTF-1 and E-ca, and malignant mesothelioma markers MC (Mesothelial Cell), CR(Calretinin), P53 and Vimentin immunocytochemical staining. Results Of the 1158 cases of pleural effusion, we confirmed 581 cases of lung adenocarcinoma, 509 squamous carcinoma, 48 adeno-squamous carcinoma, and 20 malignant pleural mesothelioma. Moreover, TTF-1 showed significantly higher expression in adenocarcinoma, with a the positive percentage 92. 43% ; CK5

  15. Outcome and pathologic classification of children and adolescents with mediastinal large B-cell lymphoma treated with FAB/LMB96 mature B-NHL therapy.

    Science.gov (United States)

    Gerrard, Mary; Waxman, Ian M; Sposto, Richard; Auperin, Anne; Perkins, Sherrie L; Goldman, Stanton; Harrison, Lauren; Pinkerton, Ross; McCarthy, Keith; Raphael, Martine; Patte, Catherine; Cairo, Mitchell S

    2013-01-10

    Mediastinal large B-cell lymphoma (MLBL) represents 2% of mature B-cell non-Hodgkin lymphoma in patients ≤ 18 years of age. We analyzed data from childhood and adolescent patients with stage III MLBL (n = 42) and non-MLBL DLBCL (n = 69) treated with Group B therapy in the French-American-British/Lymphome Malins de Burkitt (FAB/LMB) 96 study. MLBL patients had a male/female 26/16; median age, 15.7 years (range, 12.5-19.7); and LDH histologies. Alternate treatment strategies should be investigated in the future taking into account both adult MLBL approaches and more recent biologic findings in adult MLBL. PMID:23149845

  16. Comparando a Classificação Internacional de Doenças em Odontologia e Estomatologia (CID-OE com a Classificação Estatística Internacional de Doenças e Problemas Relacionados à Saúde (CID-10 Comparing the International Classification of Disease to Dentistry and Stomatology (ICD-DA and the International Statistical Classification of Diseases and Related Health Problems (ICD-10

    Directory of Open Access Journals (Sweden)

    Olga M. P. Silva

    2001-08-01

    Full Text Available INTRODUÇÃO: Nos estudos epidemiológicos de morbidade é necessário se adotar um sistema de classificação de doenças. Na odontologia e nos traumatismos buco-maxilo-faciais pode-se usar a Classificação Internacional de Doenças em Estomatologia e Odontologia (CID-OE mas, em alguns casos, esta classificação não é adequada. O objetivo deste estudo é comparar a aplicação da CID-OE com a aplicação da CID-10 na classificação de diagnósticos da área. MATERIAL E MÉTODOS: Foram analisados 2.372 casos atendidos em serviços de traumatismos buco-maxilo-faciais e emergências dentais no Município de São Paulo, Brasil, onde os diagnósticos encontrados foram codificados por ambas as classificações. RESULTADOS: A CID-OE especificou melhor 1.117 casos mas, em 267, não ofereceu possibilidade de codificação. Em 978 casos, o detalhamento dado pela codificação foi o mesmo em ambas as classificações.INTRODUCTION: Adopting a classification system of diseases is necessary to perform epidemiological studies of morbidity. In oral and maxillo-facial injuries and in dentistry we may use the International Classification of Diseases for Dentistry and Stomatology (ICD-DA, but the classification is not always appropriate. The objective of the study is to compare the accuracy of the ICD-DA to the International Classification of Diseases-10th Revision (ICD-10 in the classification of diagnoses. MATERIAL AND METHODS: 2,372 encounters were analyzed in oral and maxillo-facial care and in dental emergency services, in the city of São Paulo, Brazil. The encounters were codified by both classifications. RESULTS: 1,117 cases were better classified by the dental classification, but in 267 cases the ICD-DA does not offer a code. In 978 cases the details were the same in both classifications.

  17. Tissue tracking: applications for brain MRI classification

    Science.gov (United States)

    Melonakos, John; Gao, Yi; Tannenbaum, Allen

    2007-03-01

    Bayesian classification methods have been extensively used in a variety of image processing applications, including medical image analysis. The basic procedure is to combine data-driven knowledge in the likelihood terms with clinical knowledge in the prior terms to classify an image into a pre-determined number of classes. In many applications, it is difficult to construct meaningful priors and, hence, homogeneous priors are assumed. In this paper, we show how expectation-maximization weights and neighboring posterior probabilities may be combined to make intuitive use of the Bayesian priors. Drawing upon insights from computer vision tracking algorithms, we cast the problem in a tissue tracking framework. We show results of our algorithm on the classification of gray and white matter along with surrounding cerebral spinal fluid in brain MRI scans. We show results of our algorithm on 20 brain MRI datasets along with validation against expert manual segmentations.

  18. A Method of Soil Salinization Information Extraction with SVM Classification Based on ICA and Texture Features

    Institute of Scientific and Technical Information of China (English)

    ZHANG Fei; TASHPOLAT Tiyip; KUNG Hsiang-te; DING Jian-li; MAMAT.Sawut; VERNER Johnson; HAN Gui-hong; GUI Dong-wei

    2011-01-01

    Salt-affected soils classification using remotely sensed images is one of the most common applications in remote sensing,and many algorithms have been developed and applied for this purpose in the literature.This study takes the Delta Oasis of Weigan and Kuqa Rivers as a study area and discusses the prediction of soil salinization from ETM+ Landsat data.It reports the Support Vector Machine(SVM) classification method based on Independent Component Analysis(ICA) and Texture features.Meanwhile,the letter introduces the fundamental theory of SVM algorithm and ICA,and then incorporates ICA and texture features.The classification result is compared with ICA-SVM classification,single data source SVM classification,maximum likelihood classification(MLC) and neural network classification qualitatively and quantitatively.The result shows that this method can effectively solve the problem of low accuracy and fracture classification result in single data source classification.It has high spread ability toward higher array input.The overall accuracy is 98.64%,which increases by 10.2% compared with maximum likelihood classification,even increases by 12.94% compared with neural net classification,and thus acquires good effectiveness.Therefore,the classification method based on SVM and incorporating the ICA and texture features can be adapted to RS image classification and monitoring of soil salinization.

  19. Operational risk modeled analytically II: the consequences of classification invariance

    OpenAIRE

    Vivien Brunel

    2015-01-01

    Most of the banks' operational risk internal models are based on loss pooling in risk and business line categories. The parameters and outputs of operational risk models are sensitive to the pooling of the data and the choice of the risk classification. In a simple model, we establish the link between the number of risk cells and the model parameters by requiring invariance of the bank's loss distribution upon a change in classification. We provide details on the impact of this requirement on...

  20. On deformation and classification of V-systems

    OpenAIRE

    V. Schreiber; A.P. Veselov

    2014-01-01

    The V-systems are special finite sets of covectors which appeared in the theory of the generalized Witten-Dijkgraaf-Verlinde-Verlinde (WDVV) equations. Several families of V-systems are known but their classification is an open problem. We derive the relations describing the infinitesimal deformations of V-systems and use them to study the classification problem for V-systems in dimension 3. We discuss also possible matroidal structures of V-systems in relation with projective geometry and gi...