WorldWideScience

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. Classification Trees for Problems with Monotonicity Constraints

    NARCIS (Netherlands)

    R. Potharst (Rob); A.J. Feelders

    2002-01-01

    textabstractFor classification problems with ordinal attributes very often the class attribute should increase with each or some of the explaining attributes. These are called classification problems with monotonicity constraints. Classical decision tree algorithms such as CART or C4.5 generally do

  4. Generating Interpretable Fuzzy Systems for Classification Problems

    Directory of Open Access Journals (Sweden)

    Juan A. Contreras-Montes

    2009-12-01

    Full Text Available This paper presents a new method to generate interpretable fuzzy systems from training data to deal with classification problems. The antecedent partition uses triangular sets with 0.5 interpolations avoiding the presence of complex overlapping that happens in another method. Singleton consequents are generated form the projection of the modal values of each triangular membership function into the output space. Least square method is used to adjust the consequents. The proposed method gets a higher average classification accuracy rate than the existing methods with a reduced number of rules andparameters and without sacrificing the fuzzy system interpretability. The proposed approach is applied to two classical classification problems: Iris data and the Wisconsin Breast Cancer classification problem.

  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.

  6. 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

  7. 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.

  8. A New Method for Solving Supervised Data Classification Problems

    Directory of Open Access Journals (Sweden)

    Parvaneh Shabanzadeh

    2014-01-01

    Full Text Available Supervised data classification is one of the techniques used to extract nontrivial information from data. Classification is a widely used technique in various fields, including data mining, industry, medicine, science, and law. This paper considers a new algorithm for supervised data classification problems associated with the cluster analysis. The mathematical formulations for this algorithm are based on nonsmooth, nonconvex optimization. A new algorithm for solving this optimization problem is utilized. The new algorithm uses a derivative-free technique, with robustness and efficiency. To improve classification performance and efficiency in generating classification model, a new feature selection algorithm based on techniques of convex programming is suggested. Proposed methods are tested on real-world datasets. Results of numerical experiments have been presented which demonstrate the effectiveness of the proposed algorithms.

  9. About decomposition approach for solving the classification problem

    Science.gov (United States)

    Andrianova, A. A.

    2016-11-01

    This article describes the features of the application of an algorithm with using of decomposition methods for solving the binary classification problem of constructing a linear classifier based on Support Vector Machine method. Application of decomposition reduces the volume of calculations, in particular, due to the emerging possibilities to build parallel versions of the algorithm, which is a very important advantage for the solution of problems with big data. The analysis of the results of computational experiments conducted using the decomposition approach. The experiment use known data set for binary classification problem.

  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. Classification of Isomonodromy Problems on Elliptic Curves

    CERN Document Server

    Levin, A; Zotov, A

    2013-01-01

    We consider the isomonodromy problems for flat $G$-bundles over punctured elliptic curves $\\Sigma_\\tau$ with regular singularities of connections at marked points. The bundles are classified by their characteristic classes. These classes are elements of the second cohomology group $H^2(\\Sigma_\\tau,{\\mathcal Z}(G))$, where ${\\mathcal Z}(G)$ is the center of $G$. For any complex simple Lie group $G$ and arbitrary class we define the moduli space of flat bundles, and in this way construct the monodromy preserving equations in the Hamiltonian form and their Lax representations. In particular, they include the Painlev\\'e VI equation, its multicomponent generalizations and elliptic Schlesinger equations. The general construction is described for punctured curves of arbitrary genus. We extend the Beilinson-Drinfeld description of the moduli space of Higgs bundles to the case of flat connections. This local description allows us to establish the Symplectic Hecke Correspondence for a wide class of the monodromy preser...

  14. Nonlinear programming for classification problems in machine learning

    Science.gov (United States)

    Astorino, Annabella; Fuduli, Antonio; Gaudioso, Manlio

    2016-10-01

    We survey some nonlinear models for classification problems arising in machine learning. In the last years this field has become more and more relevant due to a lot of practical applications, such as text and web classification, object recognition in machine vision, gene expression profile analysis, DNA and protein analysis, medical diagnosis, customer profiling etc. Classification deals with separation of sets by means of appropriate separation surfaces, which is generally obtained by solving a numerical optimization model. While linear separability is the basis of the most popular approach to classification, the Support Vector Machine (SVM), in the recent years using nonlinear separating surfaces has received some attention. The objective of this work is to recall some of such proposals, mainly in terms of the numerical optimization models. In particular we tackle the polyhedral, ellipsoidal, spherical and conical separation approaches and, for some of them, we also consider the semisupervised versions.

  15. Morphological classification of plant cell deaths

    DEFF Research Database (Denmark)

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

    2011-01-01

    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......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 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...

  16. An Efficient Optimization Method for Solving Unsupervised Data Classification Problems

    Directory of Open Access Journals (Sweden)

    Parvaneh Shabanzadeh

    2015-01-01

    Full Text Available Unsupervised data classification (or clustering analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.

  17. 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.

  18. 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

  19. 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.

  20. An Improved Back Propagation Neural Network Algorithm on Classification Problems

    Science.gov (United States)

    Nawi, Nazri Mohd; Ransing, R. S.; Salleh, Mohd Najib Mohd; Ghazali, Rozaida; Hamid, Norhamreeza Abdul

    The back propagation algorithm is one the most popular algorithms to train feed forward neural networks. However, the convergence of this algorithm is slow, it is mainly because of gradient descent algorithm. Previous research 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 back propagation algorithm by introducing the adaptive gain of the activation function. The gain values change adaptively for each node. The influence of the adaptive gain on the learning ability of a neural network is analysed. Multi layer feed forward neural networks have been assessed. Physical interpretation of the relationship between the gain value and the learning rate and weight values is given. The efficiency of the proposed algorithm is compared with conventional Gradient Descent Method and verified by means of simulation on four classification problems. In learning the patterns, the simulations result demonstrate that the proposed method converged faster on Wisconsin breast cancer with an improvement ratio of nearly 2.8, 1.76 on diabetes problem, 65% better on thyroid data sets and 97% faster on IRIS classification problem. The results clearly show that the proposed algorithm significantly improves the learning speed of the conventional back-propagation algorithm.

  1. 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.

  2. [To the problem of parapsoriasis: classification problems (literature review and personal observations)].

    Science.gov (United States)

    Kozlovskaia, V V; Khaĭkova, E A

    2012-01-01

    In the presented article we discuss the problems of lichenoid and plaque parapsoriasis. The difference in Russian and English classifications are discussed in the historical aspect, as well as review of the literature, and personal authors' observations of nine patients with "small plaque parapsoriasis".

  3. 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.

  4. 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…

  5. HEp-2 Cell Classification via Fusing Texture and Shape Information

    OpenAIRE

    Qi, Xianbiao; Zhao, Guoying; Li, Chun-Guang; Guo, Jun; Pietikäinen, Matti

    2015-01-01

    Indirect Immunofluorescence (IIF) HEp-2 cell image is an effective evidence for diagnosis of autoimmune diseases. Recently computer-aided diagnosis of autoimmune diseases by IIF HEp-2 cell classification has attracted great attention. However the HEp-2 cell classification task is quite challenging due to large intra-class variation and small between-class variation. In this paper we propose an effective and efficient approach for the automatic classification of IIF HEp-2 cell image by fusing ...

  6. 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...

  7. 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

  8. Label-free classification of cultured cells through diffraction imaging.

    Science.gov (United States)

    Dong, Ke; Feng, Yuanming; Jacobs, Kenneth M; Lu, Jun Q; Brock, R Scott; Yang, Li V; Bertrand, Fred E; Farwell, Mary A; Hu, Xin-Hua

    2011-06-01

    Automated classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. We have investigated this possibility experimentally and numerically using a diffraction imaging approach. A fast image analysis software based on the gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images. The results of GLCM analysis and subsequent classification demonstrate the potential for rapid classification among six types of cultured cells. Combined with numerical results we show that the method of diffraction imaging flow cytometry has the capacity as a platform for high-throughput and label-free classification of biological cells.

  9. Cell-graph mining for breast tissue modeling and classification.

    Science.gov (United States)

    Bilgin, Cagatay; Demir, Cigdem; Nagi, Chandandeep; Yener, Bulent

    2007-01-01

    We consider the problem of automated cancer diagnosis in the context of breast tissues. We present graph theoretical techniques that identify and compute quantitative metrics for tissue characterization and classification. We segment digital images of histopatological tissue samples using k-means algorithm. For each segmented image we generate different cell-graphs using positional coordinates of cells and surrounding matrix components. These cell-graphs have 500-2000 cells(nodes) with 1000-10000 links depending on the tissue and the type of cell-graph being used. We calculate a set of global metrics from cell-graphs and use them as the feature set for learning. We compare our technique, hierarchical cell graphs, with other techniques based on intensity values of images, Delaunay triangulation of the cells, the previous technique we proposed for brain tissue images and with the hybrid approach that we introduce in this paper. Among the compared techniques, hierarchical-graph approach gives 81.8% accuracy whereas we obtain 61.0%, 54.1% and 75.9% accuracy with intensity-based features, Delaunay triangulation and our previous technique, respectively.

  10. 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.

  11. 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.

  12. Fish Stem Cells: Classification, Resources, Characteristics and Application Areas

    Directory of Open Access Journals (Sweden)

    Şehriban ÇEK

    2016-08-01

    Full Text Available Stem cells are a class of undifferentiated cells, have the potential for self-renewal that can differ to the specialized cells. First studies on stem cells in fish started with zebra fish in 1992. In this review, classification, resources, vital importance, characteristics and application areas of fish stem cell were clarified.

  13. Chemometric classification techniques as a tool for solving problems in analytical chemistry.

    Science.gov (United States)

    Bevilacqua, Marta; Nescatelli, Riccardo; Bucci, Remo; Magrì, Andrea D; Magrì, Antonio L; Marini, Federico

    2014-01-01

    Supervised pattern recognition (classification) techniques, i.e., the family of chemometric methods whose aim is the prediction of a qualitative response on a set of samples, represent a very important assortment of tools for solving problems in several areas of applied analytical chemistry. This paper describes the theory behind the chemometric classification techniques most frequently used in analytical chemistry together with some examples of their application to real-world problems.

  14. Classification of (D4,S1)-equivariant bifurcation problems up to topological codimension 2

    Institute of Scientific and Technical Information of China (English)

    GAO; Shouping(高守平); LI; Yangcheng(李养成)

    2003-01-01

    The techniques from singularity theory are applied to the multiparameter bifurcation problem.The classification of (D4, S1)-equivariant bifurcation problems with topological codimension less than or equal to 2 is given. The corresponding recognition conditions are set up.

  15. Effectiveness of decomposition algorithms for multi-class classification problems

    OpenAIRE

    Wołyński, Waldemar

    2010-01-01

    Problem predykcji etykiety klasy (grupy, populacji) na podstawie obserwacji wektora cech jest nazywany klasyfikacją, analizą dyskryminacyjną lub uczeniem się pod nadzorem. Zbiór etykiet składa się z K > 2 elementów w przypadku zagadnień wieloklasowych oraz z K = 2 elementów w przypadku zagadnień dwuklasowych (binarnych). Ponieważ zagadnienia dwuklaso- we są z reguły o wiele prostsze od zagadnień wieloklasowych (co więcej, niektóre algorytmy ...

  16. Research on Optimization of GLCM Parameter in Cell Classification

    Science.gov (United States)

    Zhang, Xi-Kun; Hou, Jie; Hu, Xin-Hua

    2016-05-01

    Real-time classification of biological cells according to their 3D morphology is highly desired in a flow cytometer setting. Gray level co-occurrence matrix (GLCM) algorithm has been developed to extract feature parameters from measured diffraction images ,which are too complicated to coordinate with the real-time system for a large amount of calculation. An optimization of GLCM algorithm is provided based on correlation analysis of GLCM parameters. The results of GLCM analysis and subsequent classification demonstrate optimized method can lower the time complexity significantly without loss of classification accuracy.

  17. The Classification of HEp-2 Cell Patterns Using Fractal Descriptor.

    Science.gov (United States)

    Xu, Rudan; Sun, Yuanyuan; Yang, Zhihao; Song, Bo; Hu, Xiaopeng

    2015-07-01

    Indirect immunofluorescence (IIF) with HEp-2 cells is considered as a powerful, sensitive and comprehensive technique for analyzing antinuclear autoantibodies (ANAs). The automatic classification of the HEp-2 cell images from IIF has played an important role in diagnosis. Fractal dimension can be used on the analysis of image representing and also on the property quantification like texture complexity and spatial occupation. In this study, we apply the fractal theory in the application of HEp-2 cell staining pattern classification, utilizing fractal descriptor firstly in the HEp-2 cell pattern classification with the help of morphological descriptor and pixel difference descriptor. The method is applied to the data set of MIVIA and uses the support vector machine (SVM) classifier. Experimental results show that the fractal descriptor combining with morphological descriptor and pixel difference descriptor makes the precisions of six patterns more stable, all above 50%, achieving 67.17% overall accuracy at best with relatively simple feature vectors.

  18. 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.

  19. Advanced real-time classification methods for flow cytometry data analysis and cell sorting

    Science.gov (United States)

    Leary, James F.; Reece, Lisa M.; Hokanson, James A.; Rosenblatt, Judah I.

    2002-05-01

    While many flow cytometric data analysis and 'discovery' methods have been developed, few of these have been applied to the problem of separating out purified cell subpopulations by cell sorting. The fundamental problem is that the data analysis techniques have been performed using relatively slow computational methods that take far more time than is allowed by the sort decision on a cell sorter (typically less than a millisecond). Thus cell sorting, which is really a form of 'real-time data classification,' is usually done with few, if any, multivariate statistical tools used either in the sort decision or in the evaluation of the correctness of the classification. We have developed new multivariate data analysis and 'data discovery' methods that can be implemented for real-time data classification for cell sorting using linked lookup tables. One multivariate 'data discovery' method, 'subtractive clustering,' has been used to find which clusters of cells are different between two or more files (cell samples) and to help guide analysis or sort boundaries for these cell subpopulations. Multivariate statistical methods (e.g. principal component analysis or discriminant function analysis) were implemented in linked lookup tables to establish analysis/sort boundaries that include 'costs (or penalties) of misclassification. Costs of misclassification provided a measure of the quality of the analysis/sort boundary and were expressed in simple terms that describe the tradeoff between yield and purity.

  20. Classification of biological cells using bio-inspired descriptors

    OpenAIRE

    Bel Haj Ali, Wafa; Giampaglia, Dario; Barlaud, Michel; Piro, Paolo; Nock, Richard; Pourcher, Thierry

    2012-01-01

    International audience; This paper proposes a novel automated approach for the categorization of cells in fluorescence microscopy images. Our supervised classification method aims at recognizing patterns of unlabeled cells based on an annotated dataset. First, the cell images need to be indexed by encoding them in a feature space. For this purpose, we propose tailored bio-inspired features relying on the distribution of contrast information. Then, a supervised learning algorithm is proposed f...

  1. 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.

  2. 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.

  3. 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.

  4. Error-Correcting Output Codes in Classification of Human Induced Pluripotent Stem Cell Colony Images

    Directory of Open Access Journals (Sweden)

    Henry Joutsijoki

    2016-01-01

    Full Text Available The purpose of this paper is to examine how well the human induced pluripotent stem cell (hiPSC colony images can be classified using error-correcting output codes (ECOC. Our image dataset includes hiPSC colony images from three classes (bad, semigood, and good which makes our classification task a multiclass problem. ECOC is a general framework to model multiclass classification problems. We focus on four different coding designs of ECOC and apply to each one of them k-Nearest Neighbor (k-NN searching, naïve Bayes, classification tree, and discriminant analysis variants classifiers. We use Scaled Invariant Feature Transformation (SIFT based features in classification. The best accuracy (62.4% is obtained with ternary complete ECOC coding design and k-NN classifier (standardized Euclidean distance measure and inverse weighting. The best result is comparable with our earlier research. The quality identification of hiPSC colony images is an essential problem to be solved before hiPSCs can be used in practice in large-scale. ECOC methods examined are promising techniques for solving this challenging problem.

  5. 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…

  6. Real-time multivariate statistical classification of cells for flow cytometry and cell sorting: a data mining application for stem cell isolation and tumor purging

    Science.gov (United States)

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

    1999-06-01

    Multivariate statistics can be used for visualization of cell subpopulations in multidimensional data space and for classification of cells within that data space. New data mining techniques we have developed, such as subtractive clustering, can be used to find the differences between test and control multiparameter flow cytometric data, e.g. in the problem of human stem cell isolation with tumor purging. They also can provide training data for subsequent multivariate statistical classification techniques such as discriminant function or logistic regression analyses. Using lookup tables, these multivariate statistical calculations can be performed in real-time, and can even include probabilities of misclassification. Thus, the only distinction between off-line classification of cells in data analysis and real-time statistical decision-making for cell sorting is the time limit in which a classification decision must be made. For real-time cell sorting we presently are able to perform these classifications in less than 625 microseconds, corresponding to the time that it takes the cell to travel from the laser intersection point to the sort decision point in a flow cytometer/cell sorter. Statistical decision making and the ability to include the costs of misclassification into that decision process will become important as flow cytometry/cell sorting moves from diagnostics to therapeutics.

  7. 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.

  8. Stock Market Index Data and indicators for Day Trading as a Binary Classification problem

    Directory of Open Access Journals (Sweden)

    Renato Bruni

    2017-02-01

    Full Text Available Classification is the attribution of labels to records according to a criterion automatically learned from a training set of labeled records. This task is needed in a huge number of practical applications, and consequently it has been studied intensively and several classification algorithms are available today. In finance, a stock market index is a measurement of value of a section of the stock market. It is often used to describe the aggregate trend of a market. One basic financial issue would be forecasting this trend. Clearly, such a stochastic value is very difficult to predict. However, technical analysis is a security analysis methodology developed to forecast the direction of prices through the study of past market data. Day trading consists in buying and selling financial instruments within the same trading day. In this case, one interesting problem is the automatic individuation of favorable days for trading. We model this problem as a binary classification problem, and we provide datasets containing daily index values, the corresponding values of a selection of technical indicators, and the class label, which is 1 if the subsequent time period is favorable for day trading and 0 otherwise. These datasets can be used to test the behavior of different approaches in solving the day trading problem.

  9. Stock Market Index Data and indicators for Day Trading as a Binary Classification problem.

    Science.gov (United States)

    Bruni, Renato

    2017-02-01

    Classification is the attribution of labels to records according to a criterion automatically learned from a training set of labeled records. This task is needed in a huge number of practical applications, and consequently it has been studied intensively and several classification algorithms are available today. In finance, a stock market index is a measurement of value of a section of the stock market. It is often used to describe the aggregate trend of a market. One basic financial issue would be forecasting this trend. Clearly, such a stochastic value is very difficult to predict. However, technical analysis is a security analysis methodology developed to forecast the direction of prices through the study of past market data. Day trading consists in buying and selling financial instruments within the same trading day. In this case, one interesting problem is the automatic individuation of favorable days for trading. We model this problem as a binary classification problem, and we provide datasets containing daily index values, the corresponding values of a selection of technical indicators, and the class label, which is 1 if the subsequent time period is favorable for day trading and 0 otherwise. These datasets can be used to test the behavior of different approaches in solving the day trading problem.

  10. Fault Diagnosis for Fuel Cell Based on Naive Bayesian Classification

    Directory of Open Access Journals (Sweden)

    Liping Fan

    2013-07-01

    Full Text Available Many kinds of uncertain factors may exist in the process of fault diagnosis and affect diagnostic results. Bayesian network is one of the most effective theoretical models for uncertain knowledge expression and reasoning. The method of naive Bayesian classification is used in this paper in fault diagnosis of a proton exchange membrane fuel cell (PEMFC system. Based on the model of PEMFC, fault data are obtained through simulation experiment, learning and training of the naive Bayesian classification are finished, and some testing samples are selected to validate this method. Simulation results demonstrate that the method is feasible.    

  11. The fencing problem and Coleochaete cell division.

    Science.gov (United States)

    Wang, Yuandi; Dou, Mingya; Zhou, Zhigang

    2015-03-01

    The findings in this study suggest that the solution of a boundary value problem for differential equation system can be used to discuss the fencing problem in mathematics and Coleochaete, a green algae, cell division. This differential equation model in parametric expression is used to simulate the two kinds of cell division process, one is for the usual case and the case with a "dead" daughter cell.

  12. 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.

  13. Classification of human carcinoma cells using multispectral imagery

    Science.gov (United States)

    Ćinar, Umut; Y. Ćetin, Yasemin; Ćetin-Atalay, Rengul; Ćetin, Enis

    2016-03-01

    In this paper, we present a technique for automatically classifying human carcinoma cell images using textural features. An image dataset containing microscopy biopsy images from different patients for 14 distinct cancer cell line type is studied. The images are captured using a RGB camera attached to an inverted microscopy device. Texture based Gabor features are extracted from multispectral input images. SVM classifier is used to generate a descriptive model for the purpose of cell line classification. The experimental results depict satisfactory performance, and the proposed method is versatile for various microscopy magnification options.

  14. 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

  15. Analysis of quantum particle automata for solving the density classification problem

    Science.gov (United States)

    Yu, Tina; Ben-Av, Radel

    2015-04-01

    To advance our understanding of quantum cellular automata in problem solving through parallel and distributed computing, this research quantized the density classification problem and adopted the quantum particle automata (QPA) to solve the quantized problem. In order to solve this problem, the QPA needed a unitary operator to carry out the QPA evolution and a boundary partition to make the classification decisions. We designed a genetic algorithm (GA) to search for the unitary operators and the boundary partitions to classify the density of binary inputs with length 5. The GA was able to find more than one unitary operator that can transform the QPA in ways such that when the particle was measured, it was more likely to collapse to the basis states that were on the correct side of the boundary partition for the QPA to decide whether the binary input had majority density 0 or majority density 1. We analyzed these solutions and found that the QPA evolution dynamic was driven by a particular parameter of the unitary operator: A small gave the particle small mass hence fast evolution, while large had the opposite effect. While these results are encouraging, scaling these solutions for binary inputs of arbitrary length of requires additional analysis, which we will investigate in our future work.

  16. 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.

  17. New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification

    Directory of Open Access Journals (Sweden)

    Xiaoqing Gu

    2014-01-01

    Full Text Available In medical datasets classification, support vector machine (SVM is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM for the class imbalance problem (called FSVM-CIP is presented, which can be seen as a modified class of FSVM by extending manifold regularization and assigning two misclassification costs for two classes. The proposed FSVM-CIP can be used to handle the class imbalance problem in the presence of outliers/noise, and enhance the locality maximum margin. Five real-world medical datasets, breast, heart, hepatitis, BUPA liver, and pima diabetes, from the UCI medical database are employed to illustrate the method presented in this paper. Experimental results on these datasets show the outperformed or comparable effectiveness of FSVM-CIP.

  18. 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%.

  19. Mining knowledge for HEp-2 cell image classification.

    Science.gov (United States)

    Perner, Petra; Perner, Horst; Müller, Bernd

    2002-01-01

    HEp-2 cells are used for the identification of antinuclear autoantibodies (ANAs). They allow for recognition of over 30 different nuclear and cytoplasmic patterns, which are given by upwards of 100 different autoantibodies. The identification of the patterns has recently been done manually by a human inspecting the slides with a microscope. In this paper, we present results on the analysis and classification of cells using image analysis and data mining techniques. Starting from a knowledge acquisition process with a human operator, we developed an image analysis and feature extraction algorithm. The collection of the dataset was done based on an expert's image reading and based on the automatic extracted features. A dataset containing 132 features for each entry was set up and given to a data mining algorithm to find out the relevant features among this large feature set and to construct the classification knowledge. The classifier was evaluated by cross validation. The results gave the expert new insights into the necessary features and the classification knowledge and show the feasibility of an automated inspection system.

  20. 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.

  1. 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. .

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. Prediction of PAH mutagenicity in human cells by QSAR classification.

    Science.gov (United States)

    Papa, E; Pilutti, P; Gramatica, P

    2008-01-01

    Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous pollutants of high environmental concern. The experimental data of a mutagenicity test on human B-lymphoblastoid cells (alternative to the Ames bacterial test) for a set of 70 oxo-, nitro- and unsubstituted PAHs, detected in particulate matter (PM), were modelled by Quantitative Structure-Activity Relationships (QSAR) classification methods (k-NN, k-Nearest Neighbour, and CART, Classification and Regression Tree) based on different theoretical molecular descriptors selected by Genetic Algorithms. The best models were validated for predictivity both externally and internally. For external validation, Self Organizing Maps (SOM) were applied to split the original data set. The best models, developed on the training set alone, show good predictive performance also on the prediction set chemicals (sensitivity 69.2-87.1%, specificity 62.5-87.5%). The classification of PAHs according to their mutagenicity, based only on a few theoretical molecular descriptors, allows a preliminary assessment of the human health risk, and the prioritisation of these compounds.

  7. 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.

  8. 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.

  9. 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.

  10. Embryonic stem cell research: an ethical problem

    OpenAIRE

    Рамазанова, А.

    2014-01-01

    Embryonic stem cells offer hope for new therapies, but their use and research entail an ethical problem, which does not have a certain solution. Therefore, we can ask: What exactly are the ethical arguments? Why are they so tricky to resolve?Embryonic stem cell research poses a moral dilemma. It forces us to choose between two moral principles: The duty to prevent or alleviate suffering The duty to respect the value of human life To obtain embryonic stem cells, the early embryo has to be dest...

  11. [Reprogramming of somatic cells. Problems and solutions].

    Science.gov (United States)

    Schneider, T A; Fishman, V S; Liskovykh, M A; Ponamartsev, S V; Serov, O L; Tomilin, A N; Alenina, N

    2014-01-01

    An adult mammal is composed of more than 200 different types of specialized somatic cells whose differentiated state remains stable over the life of the organism. For a long time it was believed that the differentiation process is irreversible, and the transition between the two types of specialized cells is impossible. The possibility of direct conversion of one differentiated cell type to another was first shown in the 80s of the last century in experiments on the conversion of fibroblasts into myoblasts by ectopic expression of the transcription factor MyoD. Surprisingly, this technology has remained unclaimed in cell biology for a long time. Interest in it revived after 200 thanks to the research of Novel Prize winner Shinya Yamanaka who has shown that a small set of transcription factors (Oct4, Sox2, Klf4 and c-Myc) is capable of restoring pluripotency in somatic cells which they lost in the process of differentiation. In 2010, using a similar strategy and the tissue-specific transcription factors Vierbuchen and coauthors showed the possibility of direct conversion of fibroblasts into neurons, i. e. the possibility of transdifferentiation of one type of somatic cells in the other. The works of these authoras were a breakthrough in the field of cell biology and gave a powerful impulse to the development of cell technologies for the needs of regenerative medicine. The present review discusses the main historical discoveries that preceded this work, evaluates the status of the problem and the progress in the development of methods for reprogramming at the moment, describes the main approaches to solving the problems of reprogramming of somatic cells into neuronal, and briefly discusses the prospect of application of reprogramming and transdifferentiation of cells for such important application areas as regenerative medicine, cell replacement therapy and drug screening.

  12. 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.

  13. 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.

  14. 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.

  15. Caco-2 cells, biopharmaceutics classification system (BCS) and biowaiver.

    Science.gov (United States)

    Smetanová, Libuse; Stĕtinová, Vĕra; Svoboda, Zbynek; Kvetina, Jaroslav

    2011-01-01

    Almost all orally administered drugs are absorbed across the intestinal mucosa. The Caco-2 monolayers are used as an in vitro model to predict drug absorption in humans and to explore mechanism of drug absorption. The Caco-2 cells are derived from a human colon adenocarcinoma and spontaneously differentiate to form confluent monolayer of polarized cells structurally and functionally resembling the small intestinal epithelium. For studying drug permeability, Caco-2 cells are seeded onto the Transwell inserts with semipermeable membrane and grown to late confluence (21 days). After determination of cell viability, the integrity of monolayer is checked by phenol red permeability and by 14C-mannitol permeability. The transport from apical to basolateral (AP-BL) and basolateral to apical (BL-AP) is studied by adding the diluted drug on the apical or basolateral side and withdrawing the samples from the opposite compartment, respectively, for HPLC analysis or liquid scintillation spectrometry. Ca2+ -free transport medium is used to determine paracellular component of the drug transport. On the basis of permeability and solubility, drugs can be categorized into four classes of Biopharmaceutics Classification System (BCS). For certain drugs, the BCS-based biowaiver approach can be used which enables to reduce in vivo bioequivalence studies.

  16. 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...

  17. 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)

  18. 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.

  19. 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...... 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...

  20. A hitchhiker's guide to myeloid cell subsets: practical implementation of a novel mononuclear phagocyte classification system

    Directory of Open Access Journals (Sweden)

    Martin eGuilliams

    2015-08-01

    Full Text Available The classification of mononuclear phagocytes as either dendritic cells or macrophages has been mainly based on morphology, the expression of surface markers and assumed functional specialization. We have recently proposed a novel classification system of mononuclear phagocytes based on their ontogeny. Here we discuss the practical application of such a classification system through a number of prototypical examples we have encountered while hitchhiking from one subset to another, across species and between steady state and inflammatory settings. Finally, we discuss the advantages and drawbacks of such a classification system and propose a number of improvements to move from theoretical concepts to concrete guidelines.

  1. Cell classification using big data analytics plus time stretch imaging (Conference Presentation)

    Science.gov (United States)

    Jalali, Bahram; Chen, Claire L.; Mahjoubfar, Ata

    2016-09-01

    We show that blood cells can be classified with high accuracy and high throughput by combining machine learning with time stretch quantitative phase imaging. Our diagnostic system captures quantitative phase images in a flow microscope at millions of frames per second and extracts multiple biophysical features from individual cells including morphological characteristics, light absorption and scattering parameters, and protein concentration. These parameters form a hyperdimensional feature space in which supervised learning and cell classification is performed. We show binary classification of T-cells against colon cancer cells, as well classification of algae cell strains with high and low lipid content. The label-free screening averts the negative impact of staining reagents on cellular viability or cell signaling. The combination of time stretch machine vision and learning offers unprecedented cell analysis capabilities for cancer diagnostics, drug development and liquid biopsy for personalized genomics.

  2. Standardization of UV-visible data in a food adulteration classification problem.

    Science.gov (United States)

    Di Anibal, Carolina V; Ruisánchez, Itziar; Fernández, Mailén; Forteza, Rafel; Cerdà, Victor; Pilar Callao, M

    2012-10-15

    This study evaluates the performance of multivariate calibration transfer methods in a classification context. The spectral variation caused by some experimental conditions can worsen the performance of the initial multivariate classification model but this situation can be solved by implementing standardization methods such as Piecewise Direct Standardization (PDS). This study looks at the adulteration of culinary spices with banned dyes such as Sudan I, II, III and IV. The samples are characterised by their UV-visible spectra and Partial Least Squares-Discriminant Analysis (PLS-DA) is used to discriminate between unadulterated samples and samples adulterated with any of the four Sudan dyes. Two different datasets that need to be standardised are presented. The standardization process yields positive classification results comparable to those obtained from the initial PLS-DA model, in which high classification performance was achieved.

  3. 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).

  4. [Stem cells, stem cell therapy, and ethical problems of medicine].

    Science.gov (United States)

    Hruska, I; Filip, S

    2007-01-01

    Common denominator of many philosophic approaches to the problem of using human embryos in medicine is the statement that it is "a full-value human subject that deserves respect as an adult human being". It has a defined identity in which it starts its own coordinated gradual development. Therefore, it is not just a simple cluster of cells. Integrity or holistic properties of a new quality of cells that, as a whole, represent an early embryo, and in fact are not a cluster of pre-embryonic "structural" parts or a sum of cells etc. They have theirs own evolution, previously inherently encoded, but not precisely predestined. In other words, only autointegrity alone in evolution, inherence as a part of predetermination in evolution of embryo, is not able to exist as a unit "alone". Human foetus since the first moments of its existence goes through many qualitative (externally or internally determined) transformations before it becomes a respectable human being. It is possible to say that medicine, as many times before, is now coming to a stage when axiologic values, ethical directives or moral feelings of its subjects and human objects proved in the past, are no more relevant at present. Therefore, medicine has no other alternative than an active approach to study this problem from all philosophical, biological and medical aspects to evolutionize itself in this new dimension. In this paper some of these questions are discussed and some ways of forming the ethics in therapeutic use of stem cells are presented.

  5. Immunohistochemical classification and prognosis of diffuse large B-cell lymphoma in China

    Institute of Scientific and Technical Information of China (English)

    陈燕

    2014-01-01

    Objective To study the immunohistochemical classification and prognosis of diffuse large B-cell lymphoma(DLBCL).Methods A total of 148 cases of DLBCL were classified into germinal center B-cell-like(GCB)and non-GCB/activated B-cell-like(ABC)subtypes by Hans,Choi and Tally immunohistochemical stain algorithms.The clinical features and survival data of GCB

  6. 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.

  7. Spectral Classification of Similar Materials using the Tetracorder Algorithm: The Calcite-Epidote-Chlorite Problem

    Science.gov (United States)

    Dalton, J. Brad; Bove, Dana; Mladinich, Carol; Clark, Roger; Rockwell, Barnaby; Swayze, Gregg; King, Trude; Church, Stanley

    2001-01-01

    Recent work on automated spectral classification algorithms has sought to distinguish ever-more similar materials. From modest beginnings separating shade, soil, rock and vegetation to ambitious attempts to discriminate mineral types and specific plant species, the trend seems to be toward using increasingly subtle spectral differences to perform the classification. Rule-based expert systems exploiting the underlying physics of spectroscopy such as the US Geological Society Tetracorder system are now taking advantage of the high spectral resolution and dimensionality of current imaging spectrometer designs to discriminate spectrally similar materials. The current paper details recent efforts to discriminate three minerals having absorptions centered at the same wavelength, with encouraging results.

  8. Polarization imaging and classification of Jurkat T and Ramos B cells using a flow cytometer.

    Science.gov (United States)

    Feng, Yuanming; Zhang, Ning; Jacobs, Kenneth M; Jiang, Wenhuan; Yang, Li V; Li, Zhigang; Zhang, Jun; Lu, Jun Q; Hu, Xin-Hua

    2014-09-01

    Label-free and rapid classification of cells can have awide range of applications in biology. We report a robust method of polarization diffraction imaging flow cytometry (p-DIFC) for achieving this goal. Coherently scattered light signals are acquired from single cells excited by a polarized laser beam in the form of two cross-polarized diffraction images. Image texture and intensity parameters are extracted with a gray level co-occurrence matrix (GLCM) algorithm to obtain an optimized set of feature parameters as the morphological "fingerprints" for automated cell classification. We selected the Jurkat T cells and Ramos B cells to test the p-DIFC method's capacity for cell classification. After detailed statistical analysis, we found that the optimized feature vectors yield accuracies of classification between the Jurkat and Ramos ranging from 97.8% to 100% among different cell data sets. Confocal imaging and three-dimensional reconstruction were applied to gain insights on the ability of p-DIFC method for classifying the two cell lines of highly similar morphology. Based on these results we conclude that the p-DIFC method has the capacity to discriminate cells of high similarity in their morphology with "fingerprints" features extracted from the diffraction images, which may be attributed to subtle but statistically significant differences in the nucleus-to-cell volume ratio in the case of Jurkat and Ramos cells.

  9. Study of cell classification with a diffraction imaging flow cytometer method

    Science.gov (United States)

    Dong, Ke; Jacobs, Kenneth M.; Sa, Yu; Feng, Yuanming; Lu, Jun Q.; Hu, Xin-Hua

    2011-02-01

    With a diffraction imaging flow cytometer, we have acquired and analyzed the diffraction imaging data from 5 types of cultured cells. A gray level co-occurrence matrix (GLCM) algorithm was applied to extract the interference fringe related textures from the diffraction image data. Six GLCM parameters were chosen and imported into a support vector machine algorithm for automated classification of about 20 cells for each of the 5 cell types. We found that the GLCM based algorithm has the capacity for rapid processing of diffraction images and yield feature parameters for subsequent cell classification except the T- and B-lymphocytes.

  10. [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.

  11. 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…

  12. Coordinate Descent Based Hierarchical Interactive Lasso Penalized Logistic Regression and Its Application to Classification Problems

    Directory of Open Access Journals (Sweden)

    Jin-Jia Wang

    2014-01-01

    Full Text Available We present the hierarchical interactive lasso penalized logistic regression using the coordinate descent algorithm based on the hierarchy theory and variables interactions. We define the interaction model based on the geometric algebra and hierarchical constraint conditions and then use the coordinate descent algorithm to solve for the coefficients of the hierarchical interactive lasso model. We provide the results of some experiments based on UCI datasets, Madelon datasets from NIPS2003, and daily activities of the elder. The experimental results show that the variable interactions and hierarchy contribute significantly to the classification. The hierarchical interactive lasso has the advantages of the lasso and interactive lasso.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. The vehicle routing problem: State of the art classification and review

    OpenAIRE

    Braekers, Kris; Ramaekers, Katrien; Van Nieuwenhuyse, Inneke

    2016-01-01

    Over the past decades, the Vehicle Routing Problem (VRP) and its variants have grown ever more popular in the academic literature. Yet, the problem characteristics and assumptions vary widely and few literature reviews have made an effort to classify the existing articles accordingly. In this article, we present a taxonomic review of the VRP literature published between 2009 and June 2015. Based on an adapted version of an existing comprehensive taxonomy, we classify 277 articles and analyze ...

  20. Approaching the Computational Color Constancy as a Classification Problem through Deep Learning

    OpenAIRE

    Oh, Seoung Wug; Kim, Seon Joo

    2016-01-01

    Computational color constancy refers to the problem of computing the illuminant color so that the images of a scene under varying illumination can be normalized to an image under the canonical illumination. In this paper, we adopt a deep learning framework for the illumination estimation problem. The proposed method works under the assumption of uniform illumination over the scene and aims for the accurate illuminant color computation. Specifically, we trained the convolutional neural network...

  1. 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.

  2. 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.

  3. 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.

  4. Improved classification, diagnosis and prognosis of canine round cell tumours

    NARCIS (Netherlands)

    Cangul, Taci

    2001-01-01

    As the name suggests, canine round cell tumour (RCTs) are composed of cells with a round morphology. There is some discrepancy amongst authors as to which tumours belong to this category, but most designate lymphomas, melanomas, plasmacytomas, transmissible venereal tumours (TVTs), histiocytomas, an

  5. 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

  6. A hierarchical Naïve Bayes Model for handling sample heterogeneity in classification problems: an application to tissue microarrays

    Directory of Open Access Journals (Sweden)

    Piergiorgi Paolo

    2006-11-01

    Full Text Available Abstract Background Uncertainty often affects molecular biology experiments and data for different reasons. Heterogeneity of gene or protein expression within the same tumor tissue is an example of biological uncertainty which should be taken into account when molecular markers are used in decision making. Tissue Microarray (TMA experiments allow for large scale profiling of tissue biopsies, investigating protein patterns characterizing specific disease states. TMA studies deal with multiple sampling of the same patient, and therefore with multiple measurements of same protein target, to account for possible biological heterogeneity. The aim of this paper is to provide and validate a classification model taking into consideration the uncertainty associated with measuring replicate samples. Results We propose an extension of the well-known Naïve Bayes classifier, which accounts for biological heterogeneity in a probabilistic framework, relying on Bayesian hierarchical models. The model, which can be efficiently learned from the training dataset, exploits a closed-form of classification equation, thus providing no additional computational cost with respect to the standard Naïve Bayes classifier. We validated the approach on several simulated datasets comparing its performances with the Naïve Bayes classifier. Moreover, we demonstrated that explicitly dealing with heterogeneity can improve classification accuracy on a TMA prostate cancer dataset. Conclusion The proposed Hierarchical Naïve Bayes classifier can be conveniently applied in problems where within sample heterogeneity must be taken into account, such as TMA experiments and biological contexts where several measurements (replicates are available for the same biological sample. The performance of the new approach is better than the standard Naïve Bayes model, in particular when the within sample heterogeneity is different in the different classes.

  7. 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.

  8. Applicability domains for classification problems: benchmarking of distance to models for AMES mutagenicity set

    Science.gov (United States)

    For QSAR and QSPR modeling of biological and physicochemical properties, estimating the accuracy of predictions is a critical problem. The “distance to model” (DM) can be defined as a metric that defines the similarity between the training set molecules and the test set compound ...

  9. Survival of patients with nonseminomatous germ cell cancer: A review of the IGCC classification by Cox regression and recursive partitioning

    NARCIS (Netherlands)

    M.R. van Dijk (Merel); E.W. Steyerberg (Ewout); S.P. Stenning; E. Dusseldorp (Elise); J.D.F. Habbema (Dik)

    2004-01-01

    textabstractThe International Germ Cell Consensus (IGCC) classification identifies good, intermediate and poor prognosis groups among patients with metastatic nonseminomatous germ cell tumours (NSGCT). It uses the risk factors primary site, presence of nonpulmonary visceral metastases and tumour mar

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Geometrical Modification of Learning Vector Quantization Method for Solving Classification Problems

    Directory of Open Access Journals (Sweden)

    Korhan GÜNEL

    2016-09-01

    Full Text Available In this paper, a geometrical scheme is presented to show how to overcome an encountered problem arising from the use of generalized delta learning rule within competitive learning model. It is introduced a theoretical methodology for describing the quantization of data via rotating prototype vectors on hyper-spheres.The proposed learning algorithm is tested and verified on different multidimensional datasets including a binary class dataset and two multiclass datasets from the UCI repository, and a multiclass dataset constructed by us. The proposed method is compared with some baseline learning vector quantization variants in literature for all domains. Large number of experiments verify the performance of our proposed algorithm with acceptable accuracy and macro f1 scores.

  16. Segmentation and Classification of Bone Marrow Cells Images Using Contextual Information for Medical Diagnosis of Acute Leukemias

    Science.gov (United States)

    Reta, Carolina; Altamirano, Leopoldo; Gonzalez, Jesus A.; Diaz-Hernandez, Raquel; Peregrina, Hayde; Olmos, Ivan; Alonso, Jose E.; Lobato, Ruben

    2015-01-01

    Morphological identification of acute leukemia is a powerful tool used by hematologists to determine the family of such a disease. In some cases, experienced physicians are even able to determine the leukemia subtype of the sample. However, the identification process may have error rates up to 40% (when classifying acute leukemia subtypes) depending on the physician’s experience and the sample quality. This problem raises the need to create automatic tools that provide hematologists with a second opinion during the classification process. Our research presents a contextual analysis methodology for the detection of acute leukemia subtypes from bone marrow cells images. We propose a cells separation algorithm to break up overlapped regions. In this phase, we achieved an average accuracy of 95% in the evaluation of the segmentation process. In a second phase, we extract descriptive features to the nucleus and cytoplasm obtained in the segmentation phase in order to classify leukemia families and subtypes. We finally created a decision algorithm that provides an automatic diagnosis for a patient. In our experiments, we achieved an overall accuracy of 92% in the supervised classification of acute leukemia families, 84% for the lymphoblastic subtypes, and 92% for the myeloblastic subtypes. Finally, we achieved accuracies of 95% in the diagnosis of leukemia families and 90% in the diagnosis of leukemia subtypes. PMID:26107374

  17. Segmentation and Classification of Bone Marrow Cells Images Using Contextual Information for Medical Diagnosis of Acute Leukemias.

    Science.gov (United States)

    Reta, Carolina; Altamirano, Leopoldo; Gonzalez, Jesus A; Diaz-Hernandez, Raquel; Peregrina, Hayde; Olmos, Ivan; Alonso, Jose E; Lobato, Ruben

    2015-01-01

    Morphological identification of acute leukemia is a powerful tool used by hematologists to determine the family of such a disease. In some cases, experienced physicians are even able to determine the leukemia subtype of the sample. However, the identification process may have error rates up to 40% (when classifying acute leukemia subtypes) depending on the physician's experience and the sample quality. This problem raises the need to create automatic tools that provide hematologists with a second opinion during the classification process. Our research presents a contextual analysis methodology for the detection of acute leukemia subtypes from bone marrow cells images. We propose a cells separation algorithm to break up overlapped regions. In this phase, we achieved an average accuracy of 95% in the evaluation of the segmentation process. In a second phase, we extract descriptive features to the nucleus and cytoplasm obtained in the segmentation phase in order to classify leukemia families and subtypes. We finally created a decision algorithm that provides an automatic diagnosis for a patient. In our experiments, we achieved an overall accuracy of 92% in the supervised classification of acute leukemia families, 84% for the lymphoblastic subtypes, and 92% for the myeloblastic subtypes. Finally, we achieved accuracies of 95% in the diagnosis of leukemia families and 90% in the diagnosis of leukemia subtypes.

  18. 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.

  19. 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.

  20. Survival of patients with nonseminomatous germ cell cancer: a review of the IGCC classification by Cox regression and recursive partitioning.

    Science.gov (United States)

    van Dijk, M R; Steyerberg, E W; Stenning, S P; Dusseldorp, E; Habbema, J D F

    2004-03-22

    The International Germ Cell Consensus (IGCC) classification identifies good, intermediate and poor prognosis groups among patients with metastatic nonseminomatous germ cell tumours (NSGCT). It uses the risk factors primary site, presence of nonpulmonary visceral metastases and tumour markers alpha-fetoprotein (AFP), human chorionic gonadotrophin (HCG) and lactic dehydrogenase (LDH). The IGCC classification is easy to use and remember, but lacks flexibility. We aimed to examine the extent of any loss in discrimination within the IGCC classification in comparison with alternative modelling by formal weighing of the risk factors. We analysed survival of 3048 NSGCT patients with Cox regression and recursive partitioning for alternative classifications. Good, intermediate and poor prognosis groups were based on predicted 5-year survival. Classifications were further refined by subgrouping within the poor prognosis group. Performance was measured primarily by a bootstrap corrected c-statistic to indicate discriminative ability for future patients. The weights of the risk factors in the alternative classifications differed slightly from the implicit weights in the IGCC classification. Discriminative ability, however, did not increase clearly (IGCC classification, c=0.732; Cox classification, c=0.730; Recursive partitioning classification, c=0.709). Three subgroups could be identified within the poor prognosis groups, resulting in classifications with five prognostic groups and slightly better discriminative ability (c=0.740). In conclusion, the IGCC classification in three prognostic groups is largely supported by Cox regression and recursive partitioning. Cox regression was the most promising tool to define a more refined classification. British Journal of Cancer (2004) 90, 1176-1183. doi:10.1038/sj.bjc.6601665 www.bjcancer.com Published online 24 February 2004

  1. Inverse problem of HIV cell dynamics using Genetic Algorithms

    Science.gov (United States)

    González, J. A.; Guzmán, F. S.

    2017-01-01

    In order to describe the cell dynamics of T-cells in a patient infected with HIV, we use a flavour of Perelson's model. This is a non-linear system of Ordinary Differential Equations that describes the evolution of healthy, latently infected, infected T-cell concentrations and the free viral cells. Different parameters in the equations give different dynamics. Considering the concentration of these types of cells is known for a particular patient, the inverse problem consists in estimating the parameters in the model. We solve this inverse problem using a Genetic Algorithm (GA) that minimizes the error between the solutions of the model and the data from the patient. These errors depend on the parameters of the GA, like mutation rate and population, although a detailed analysis of this dependence will be described elsewhere.

  2. 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.

  3. [WHO classification 2016 and first S3 guidelines on renal cell cancer: What is important for the practice?].

    Science.gov (United States)

    Moch, H

    2016-03-01

    The first S3 guidelines on renal cell cancer cover the practical aspects of imaging, diagnostics and therapy as well as the clinical relevance of pathology reporting. This review summarizes the changes in renal tumor classification and the new recommendations for reporting renal cell tumors. The S3 guidelines recommend the 2016 World Health Organization (WHO) classification of renal cell tumors. Novel renal cell tumor entities and provisional or emerging renal cell tumor entities of the 2016 WHO classification of renal tumors are discussed. The S3 guidelines for renal cell cancer also recommend the use of the WHO/International Society of Urologic Pathology (ISUP) grading system for clear cell and for papillary renal cell carcinomas, which replaces the previously used Fuhrman grading system.

  4. Clinical significance of bcl-2 protein expression and classification algorithm in diffuse large B-cell lymphoma

    Institute of Scientific and Technical Information of China (English)

    李敏

    2013-01-01

    Objective To investigate the clinical significance of bcl-2 protein expression and three classification algorithms including Hans model,Chan model and Muris model in patients with diffuse large B-cell lymphoma(DLBCL).

  5. Computer aided classification of cell nuclei in the gastrointestinal tract by volume and principal axis

    Science.gov (United States)

    Sagstetter, Ann M.; Camp, Jon J.; Lurken, Matthew S.; Szurszewski, Joseph H.; Farrugia, Gianrico; Gibbons, Simon J.; Robb, Richard A.

    2007-03-01

    Normal function of the gastrointestinal tract involves the coordinated activity of several cell types Human disorders of motor function of the gastrointestinal tract are often associated with changes in the number of these cells. For example, in diabetic patients, abnormalities in gastrointestinal transit are associated with changes in nerves and interstitial cells of Cajal (ICC), two key cells that generate and regulate motility. ICC are cells of mesenchymal origin that function as pacemakers and amplify neuronal signals in the gastrointestinal tract. Quantifying the changes in number of specific cell types in tissues from patients with motility disorders is challenging and requires immunolabeling for specific antigens. The shape of nuclei differs between the cell types in the wall of the gastrointestinal tract. Therefore the objective of this study was to determine whether cell nuclei can be classified by analyzing the 3D morphology of the nuclei. Furthermore, the orientation of the long axis of nuclei changes within and between the muscle layers. These features can be used to classify and differentially label the nuclei in confocal volume images of the tissue by computing the principal axis of the coordinates of the set of voxels forming each nucleus and thereby to identify cells by their nuclear morphology. Using this approach, we were able to separate and quantify nuclei in the smooth muscle layers of the tissue. Therefore we conclude that computer-aided classification of cell nuclei can be used to identify changes in the cell types expressed in gastrointestinal smooth muscle.

  6. 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

  7. Recognition and classification of colon cells applying the ensemble of classifiers.

    Science.gov (United States)

    Kruk, M; Osowski, S; Koktysz, R

    2009-02-01

    The paper presents the application of an ensemble of classifiers for the recognition of colon cells on the basis of the microscope colon image. The solved task include: segmentation of the individual cells from the image using the morphological operations, the preprocessing stages, leading to the extraction of features, selection of the most important features, and the classification stage applying the classifiers arranged in the form of ensemble. The paper presents and discusses the results concerning the recognition of four most important colon cell types: eosinophylic granulocyte, neutrophilic granulocyte, lymphocyte and plasmocyte. The proposed system is able to recognize the cells with the accuracy comparable to the human expert (around 5% of discrepancy of both results).

  8. Multi-classification of cell deformation based on object alignment and run length statistic.

    Science.gov (United States)

    Li, Heng; Liu, Zhiwen; An, Xing; Shi, Yonggang

    2014-01-01

    Cellular morphology is widely applied in digital pathology and is essential for improving our understanding of the basic physiological processes of organisms. One of the main issues of application is to develop efficient methods for cell deformation measurement. We propose an innovative indirect approach to analyze dynamic cell morphology in image sequences. The proposed approach considers both the cellular shape change and cytoplasm variation, and takes each frame in the image sequence into account. The cell deformation is measured by the minimum energy function of object alignment, which is invariant to object pose. Then an indirect analysis strategy is employed to overcome the limitation of gradual deformation by run length statistic. We demonstrate the power of the proposed approach with one application: multi-classification of cell deformation. Experimental results show that the proposed method is sensitive to the morphology variation and performs better than standard shape representation methods.

  9. Automatic Detection of Cervical Cancer Cells by a Two-Level Cascade Classification System

    Directory of Open Access Journals (Sweden)

    Jie Su

    2016-01-01

    Full Text Available We proposed a method for automatic detection of cervical cancer cells in images captured from thin liquid based cytology slides. We selected 20,000 cells in images derived from 120 different thin liquid based cytology slides, which include 5000 epithelial cells (normal 2500, abnormal 2500, lymphoid cells, neutrophils, and junk cells. We first proposed 28 features, including 20 morphologic features and 8 texture features, based on the characteristics of each cell type. We then used a two-level cascade integration system of two classifiers to classify the cervical cells into normal and abnormal epithelial cells. The results showed that the recognition rates for abnormal cervical epithelial cells were 92.7% and 93.2%, respectively, when C4.5 classifier or LR (LR: logical regression classifier was used individually; while the recognition rate was significantly higher (95.642% when our two-level cascade integrated classifier system was used. The false negative rate and false positive rate (both 1.44% of the proposed automatic two-level cascade classification system are also much lower than those of traditional Pap smear review.

  10. Calcifying ghost cell odontogenic cyst: A review on terminologies and classifications

    Directory of Open Access Journals (Sweden)

    Meera Thinakaran

    2012-01-01

    Full Text Available Calcifying ghost cell odontogenic cyst (CGCOC is a relatively uncommon odontogenic lesion characterized by varied clinical, radiographical features and biological behavior. CGCOC can exhibit either as a cystic or a solid lesion. Since its first description by Gorlin et al, in 1962, it has been known by different names and classified and sub-classified into various types. In this article we present a case of CGCOC and discuss the related literature regarding the terminology, classification and biological behavior of CGCOC.

  11. 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...

  12. Selective ablation of Copper-Indium-Diselenide solar cells monitored by laser-induced breakdown spectroscopy and classification methods

    Energy Technology Data Exchange (ETDEWEB)

    Diego-Vallejo, David [Technische Universität Berlin, Institute of Optics and Atomic Physics, Straße des 17, Juni 135, 10623 Berlin (Germany); Laser- und Medizin- Technologie Berlin GmbH (LMTB), Applied Laser Technology, Fabeckstr. 60-62, 14195 Berlin (Germany); Ashkenasi, David, E-mail: d.ashkenasi@lmtb.de [Laser- und Medizin- Technologie Berlin GmbH (LMTB), Applied Laser Technology, Fabeckstr. 60-62, 14195 Berlin (Germany); Lemke, Andreas [Laser- und Medizin- Technologie Berlin GmbH (LMTB), Applied Laser Technology, Fabeckstr. 60-62, 14195 Berlin (Germany); Eichler, Hans Joachim [Technische Universität Berlin, Institute of Optics and Atomic Physics, Straße des 17, Juni 135, 10623 Berlin (Germany); Laser- und Medizin- Technologie Berlin GmbH (LMTB), Applied Laser Technology, Fabeckstr. 60-62, 14195 Berlin (Germany)

    2013-09-01

    Laser-induced breakdown spectroscopy (LIBS) and two classification methods, i.e. linear correlation and artificial neural networks (ANN), are used to monitor P1, P2 and P3 scribing steps of Copper-Indium-Diselenide (CIS) solar cells. Narrow channels featuring complete removal of desired layers with minimum damage on the underlying film are expected to enhance efficiency of solar cells. The monitoring technique is intended to determine that enough material has been removed to reach the desired layer based on the analysis of plasma emission acquired during multiple pass laser scribing. When successful selective scribing is achieved, a high degree of similarity between test and reference spectra has to be identified by classification methods in order to stop the scribing procedure and avoid damaging the bottom layer. Performance of linear correlation and artificial neural networks is compared and evaluated for two spectral bandwidths. By using experimentally determined combinations of classifier and analyzed spectral band for each step, classification performance achieves errors of 7, 1 and 4% for steps P1, P2 and P3, respectively. The feasibility of using plasma emission for the supervision of processing steps of solar cell manufacturing is demonstrated. This method has the potential to be implemented as an online monitoring procedure assisting the production of solar cells. - Highlights: • LIBS and two classification methods were used to monitor CIS solar cells processing. • Selective ablation of thin-film solar cells was improved with inspection system. • Customized classification method and analyzed spectral band enhanced performance.

  13. 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.

  14. Functional classification of memory CD8+ T cells by CX3CR1 expression

    Science.gov (United States)

    Böttcher, Jan P.; Beyer, Marc; Meissner, Felix; Abdullah, Zeinab; Sander, Jil; Höchst, Bastian; Eickhoff, Sarah; Rieckmann, Jan C.; Russo, Caroline; Bauer, Tanja; Flecken, Tobias; Giesen, Dominik; Engel, Daniel; Jung, Steffen; Busch, Dirk H.; Protzer, Ulrike; Thimme, Robert; Mann, Matthias; Kurts, Christian; Schultze, Joachim L.; Kastenmüller, Wolfgang; Knolle, Percy A.

    2015-01-01

    Localization of memory CD8+ T cells to lymphoid or peripheral tissues is believed to correlate with proliferative capacity or effector function. Here we demonstrate that the fractalkine-receptor/CX3CR1 distinguishes memory CD8+ T cells with cytotoxic effector function from those with proliferative capacity, independent of tissue-homing properties. CX3CR1-based transcriptome and proteome-profiling defines a core signature of memory CD8+ T cells with effector function. We find CD62LhiCX3CR1+ memory T cells that reside within lymph nodes. This population shows distinct migration patterns and positioning in proximity to pathogen entry sites. Virus-specific CX3CR1+ memory CD8+ T cells are scarce during chronic infection in humans and mice but increase when infection is controlled spontaneously or by therapeutic intervention. This CX3CR1-based functional classification will help to resolve the principles of protective CD8+ T-cell memory. PMID:26404698

  15. Sickle Cell Screening: Medical, Legal, Ethical, Psychological and Social Problems; A Sickle Cell Crisis.

    Science.gov (United States)

    Bowman, James E.

    In recent years, sickle cell screening programs have been initiated by community groups, health centers, hospitals, medical schools, health departments, school systems, city and State governments, various branches of the Federal Government, fraternal and social clubs, and other organizations. Problems have resulted from mass sickle cell screening,…

  16. 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.

  17. Automated morphological analysis of bone marrow cells in microscopic images for diagnosis of leukemia: nucleus-plasma separation and cell classification using a hierarchical tree model of hematopoesis

    Science.gov (United States)

    Krappe, Sebastian; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

    2016-03-01

    The morphological differentiation of bone marrow is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually under the use of bright field microscopy. This is a time-consuming, subjective, tedious and error-prone process. Furthermore, repeated examinations of a slide may yield intra- and inter-observer variances. For that reason a computer assisted diagnosis system for bone marrow differentiation is pursued. In this work we focus (a) on a new method for the separation of nucleus and plasma parts and (b) on a knowledge-based hierarchical tree classifier for the differentiation of bone marrow cells in 16 different classes. Classification trees are easily interpretable and understandable and provide a classification together with an explanation. Using classification trees, expert knowledge (i.e. knowledge about similar classes and cell lines in the tree model of hematopoiesis) is integrated in the structure of the tree. The proposed segmentation method is evaluated with more than 10,000 manually segmented cells. For the evaluation of the proposed hierarchical classifier more than 140,000 automatically segmented bone marrow cells are used. Future automated solutions for the morphological analysis of bone marrow smears could potentially apply such an approach for the pre-classification of bone marrow cells and thereby shortening the examination time.

  18. 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.

  19. Automated analysis of food-borne pathogens using a novel microbial cell culture, sensing and classification system.

    Science.gov (United States)

    Xiang, Kun; Li, Yinglei; Ford, William; Land, Walker; Schaffer, J David; Congdon, Robert; Zhang, Jing; Sadik, Omowunmi

    2016-02-21

    We hereby report the design and implementation of an Autonomous Microbial Cell Culture and Classification (AMC(3)) system for rapid detection of food pathogens. Traditional food testing methods require multistep procedures and long incubation period, and are thus prone to human error. AMC(3) introduces a "one click approach" to the detection and classification of pathogenic bacteria. Once the cultured materials are prepared, all operations are automatic. AMC(3) is an integrated sensor array platform in a microbial fuel cell system composed of a multi-potentiostat, an automated data collection system (Python program, Yocto Maxi-coupler electromechanical relay module) and a powerful classification program. The classification scheme consists of Probabilistic Neural Network (PNN), Support Vector Machines (SVM) and General Regression Neural Network (GRNN) oracle-based system. Differential Pulse Voltammetry (DPV) is performed on standard samples or unknown samples. Then, using preset feature extractions and quality control, accepted data are analyzed by the intelligent classification system. In a typical use, thirty-two extracted features were analyzed to correctly classify the following pathogens: Escherichia coli ATCC#25922, Escherichia coli ATCC#11775, and Staphylococcus epidermidis ATCC#12228. 85.4% accuracy range was recorded for unknown samples, and within a shorter time period than the industry standard of 24 hours.

  20. 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 ...

  1. Polarimetry based partial least square classification of ex vivo healthy and basal cell carcinoma human skin tissues.

    Science.gov (United States)

    Ahmad, Iftikhar; Ahmad, Manzoor; Khan, Karim; Ikram, Masroor

    2016-06-01

    Optical polarimetry was employed for assessment of ex vivo healthy and basal cell carcinoma (BCC) tissue samples from human skin. Polarimetric analyses revealed that depolarization and retardance for healthy tissue group were significantly higher (pleast square (PLS) regression classified the samples with 100% accuracy, sensitivity and specificity. These findings indicate that optical polarimetry together with PLS statistics hold promise for automated pathology classification.

  2. 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

  3. HEp-2 Cell Classification: The Role of Gaussian Scale Space Theory as A Pre-processing Approach

    OpenAIRE

    Qi, Xianbiao; Zhao, Guoying; Chen, Jie; Pietikäinen, Matti

    2015-01-01

    \\textit{Indirect Immunofluorescence Imaging of Human Epithelial Type 2} (HEp-2) cells is an effective way to identify the presence of Anti-Nuclear Antibody (ANA). Most existing works on HEp-2 cell classification mainly focus on feature extraction, feature encoding and classifier design. Very few efforts have been devoted to study the importance of the pre-processing techniques. In this paper, we analyze the importance of the pre-processing, and investigate the role of Gaussian Scale Space (GS...

  4. 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.

  5. 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...

  6. Molecular classification of basal cell carcinoma of skin by gene expression profiling.

    Science.gov (United States)

    Jee, Byul A; Lim, Hyoseob; Kwon, So Mee; Jo, Yuna; Park, Myong Chul; Lee, Il Jae; Woo, Hyun Goo

    2015-12-01

    Non-melanoma skin cancers (NMSC) including basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are more common kinds of skin cancer. Although these tumors share common pathological and clinical features, their similarity and heterogeneity at molecular levels are not fully elaborated yet. Here, by performing comparative analysis of gene expression profiling of BCC, SCC, and normal skin tissues, we could classify the BCC into three subtypes of classical, SCC-like, and normal-like BCCs. Functional enrichment and pathway analyses revealed the molecular characteristics of each subtype. The classical BCC showed the enriched expression and transcription signature with the activation of Wnt and Hedgehog signaling pathways, which were well known key features of BCC. By contrast, the SCC-like BCC was enriched with immune-response genes and oxidative stress-related genes. Network analysis revealed the PLAU/PLAUR as a key regulator of SCC-like BCC. The normal-like BCC showed prominent activation of metabolic processes particularly the fatty acid metabolism. The existence of these molecular subtypes could be validated in an independent dataset, which demonstrated the three subgroups of BCC with distinct functional enrichment. In conclusion, we suggest a novel molecular classification of BCC providing insights on the heterogeneous progression of BCC.

  7. Collective Classification of Textual Documents by Guided Self-Organization in T-Cell Cross-Regulation Dynamics

    CERN Document Server

    Abi-Haidar, Alaa; 10.1007/s12065-011-0052-5

    2011-01-01

    We present and study an agent-based model of T-Cell cross-regulation in the adaptive immune system, which we apply to binary classification. Our method expands an existing analytical model of T-cell cross-regulation (Carneiro et al. in Immunol Rev 216(1):48-68, 2007) that was used to study the self-organizing dynamics of a single population of T-Cells in interaction with an idealized antigen presenting cell capable of presenting a single antigen. With agent-based modeling we are able to study the self-organizing dynamics of multiple populations of distinct T-cells which interact via antigen presenting cells that present hundreds of distinct antigens. Moreover, we show that such self-organizing dynamics can be guided to produce an effective binary classification of antigens, which is competitive with existing machine learning methods when applied to biomedical text classification. More specifically, here we test our model on a dataset of publicly available full-text biomedical articles provided by the BioCreat...

  8. 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

  9. High speed classification of individual bacterial cells using a model-based light scatter system and multivariate statistics

    Science.gov (United States)

    Venkatapathi, Murugesan; Rajwa, Bartek; Ragheb, Kathy; Banada, Padmapriya P.; Lary, Todd; Robinson, J. Paul; Hirleman, E. Daniel

    2008-02-01

    We describe a model-based instrument design combined with a statistical classification approach for the development and realization of high speed cell classification systems based on light scatter. In our work, angular light scatter from cells of four bacterial species of interest, Bacillus subtilis, Escherichia coli, Listeria innocua, and Enterococcus faecalis, was modeled using the discrete dipole approximation. We then optimized a scattering detector array design subject to some hardware constraints, configured the instrument, and gathered experimental data from the relevant bacterial cells. Using these models and experiments, it is shown that optimization using a nominal bacteria model (i.e., using a representative size and refractive index) is insufficient for classification of most bacteria in realistic applications. Hence the computational predictions were constituted in the form of scattering-data-vector distributions that accounted for expected variability in the physical properties between individual bacteria within the four species. After the detectors were optimized using the numerical results, they were used to measure scatter from both the known control samples and unknown bacterial cells. A multivariate statistical method based on a support vector machine (SVM) was used to classify the bacteria species based on light scatter signatures. In our final instrument, we realized correct classification of B. subtilis in the presence of E. coli,L. innocua, and E. faecalis using SVM at 99.1%, 99.6%, and 98.5%, respectively, in the optimal detector array configuration. For comparison, the corresponding values for another set of angles were only 69.9%, 71.7%, and 70.2% using SVM, and more importantly, this improved performance is consistent with classification predictions.

  10. Mast Cell Activation Syndrome: Proposed Diagnostic Criteria: Towards a global classification for mast cell disorders

    OpenAIRE

    2010-01-01

    The term “mast cell activation syndrome (MCAS)” is finding increasing use as a diagnosis for individuals who present with signs and symptoms involving the dermis, gastrointestinal track and cardiovascular system; frequently accompanied by neurologic complaints. Such patients often have undergone multiple extensive medical evaluations by different physicians in varied disciplines without a definitive medical diagnosis until the diagnosis of “MCAS” is applied. However, “MCAS” as a distinct clin...

  11. 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

  12. Correlation of nodal mast cells with clinical outcome in dogs with mast cell tumour and a proposed classification system for the evaluation of node metastasis.

    Science.gov (United States)

    Weishaar, K M; Thamm, D H; Worley, D R; Kamstock, D A

    2014-11-01

    Lymph node metastasis in dogs with mast cell tumour has been reported as a negative prognostic indicator; however, no standardized histological criteria exist to define metastatic disease. The primary aim of this study was to determine whether different histological patterns of node-associated mast cells correlate with clinical outcome in dogs with mast cell tumour. A secondary goal was to propose a criteria-defined classification system for histological evaluation of lymph node metastasis. The Colorado State University Diagnostic Medicine Center database was searched for cases of canine mast cell tumours with reported lymph node metastasis or evidence of node-associated mast cells. Additional cases were obtained from a clinical trial involving sentinel lymph node mapping and node extirpation in dogs with mast cell neoplasia. Forty-one cases were identified for inclusion in the study. Demographic data, treatment and clinical outcome were collected for each case. Lymph nodes were classified according to a novel classification system (HN0-HN3) based on the number of, distribution of, and architectural disruption by, nodal mast cells. The findings of this study indicate that characterization of nodal mast cells as proposed by this novel classification system correlates with, and is prognostic for, clinical outcome in dogs with mast cell tumours.

  13. 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.

  14. Problems

    Directory of Open Access Journals (Sweden)

    Yekini Shehu

    2010-01-01

    real Banach space which is also uniformly smooth using the properties of generalized f-projection operator. Using this result, we discuss strong convergence theorem concerning general H-monotone mappings and system of generalized mixed equilibrium problems in Banach spaces. Our results extend many known recent results in the literature.

  15. Personality Traits of Expert Teachers of Students with Behavioural Problems: A Review and Classification of the Literature

    Science.gov (United States)

    Buttner, Svenja; Pijl, Sip Jan; Bijstra, Jan; van den Bosch, Els

    2015-01-01

    Teaching students with behavioural problems is a challenge for many teachers but other teachers are able to bring out the best in these students. Much research has been done to find out what differentiates expert teachers from their less skilled colleagues. Recent evidence points to personality as an underlying core factor influencing teacher…

  16. Novel whole-cell Reporter Assay for Stress-Based Classification of Antibacterial Compounds Produced by Locally Isolated Bacillus spp.

    OpenAIRE

    Nithya, Vadakedath; Halami, Prakash M.

    2012-01-01

    Reporter bacteria are beneficial for the rapid and sensitive screening of cultures producing peptide antibiotics, which can be an addition or alternative to the established antibiotics. This study was carried out to validate the usability of specific reporter strains for the target mediated identification of antibiotics produced by native Bacillus spp. isolated from different food sources. During preliminary classification, cell wall stress causing Bacillus isolates were screened by using rep...

  17. Machine learning classification of cell-specific cardiac enhancers uncovers developmental subnetworks regulating progenitor cell division and cell fate specification

    OpenAIRE

    Ahmad, Shaad M.; Busser, Brian W; Huang, Di; Cozart, Elizabeth J.; Michaud, Sébastien; Zhu, Xianmin; Jeffries, Neal; Aboukhalil, Anton; Bulyk, Martha L.; Ovcharenko, Ivan; Michelson, Alan M.

    2014-01-01

    The Drosophila heart is composed of two distinct cell types, the contractile cardial cells (CCs) and the surrounding non-muscle pericardial cells (PCs), development of which is regulated by a network of conserved signaling molecules and transcription factors (TFs). Here, we used machine learning with array-based chromatin immunoprecipitation (ChIP) data and TF sequence motifs to computationally classify cell type-specific cardiac enhancers. Extensive testing of predicted enhancers at single-c...

  18. 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.

  19. Machine learning classification of cell-specific cardiac enhancers uncovers developmental subnetworks regulating progenitor cell division and cell fate specification.

    Science.gov (United States)

    Ahmad, Shaad M; Busser, Brian W; Huang, Di; Cozart, Elizabeth J; Michaud, Sébastien; Zhu, Xianmin; Jeffries, Neal; Aboukhalil, Anton; Bulyk, Martha L; Ovcharenko, Ivan; Michelson, Alan M

    2014-02-01

    The Drosophila heart is composed of two distinct cell types, the contractile cardial cells (CCs) and the surrounding non-muscle pericardial cells (PCs), development of which is regulated by a network of conserved signaling molecules and transcription factors (TFs). Here, we used machine learning with array-based chromatin immunoprecipitation (ChIP) data and TF sequence motifs to computationally classify cell type-specific cardiac enhancers. Extensive testing of predicted enhancers at single-cell resolution revealed the added value of ChIP data for modeling cell type-specific activities. Furthermore, clustering the top-scoring classifier sequence features identified novel cardiac and cell type-specific regulatory motifs. For example, we found that the Myb motif learned by the classifier is crucial for CC activity, and the Myb TF acts in concert with two forkhead domain TFs and Polo kinase to regulate cardiac progenitor cell divisions. In addition, differential motif enrichment and cis-trans genetic studies revealed that the Notch signaling pathway TF Suppressor of Hairless [Su(H)] discriminates PC from CC enhancer activities. Collectively, these studies elucidate molecular pathways used in the regulatory decisions for proliferation and differentiation of cardiac progenitor cells, implicate Su(H) in regulating cell fate decisions of these progenitors, and document the utility of enhancer modeling in uncovering developmental regulatory subnetworks.

  20. 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.

  1. Classification of Spreadsheet Errors

    OpenAIRE

    Rajalingham, Kamalasen; Chadwick, David R.; Knight, Brian

    2008-01-01

    This paper describes a framework for a systematic classification of spreadsheet errors. This classification or taxonomy of errors is aimed at facilitating analysis and comprehension of the different types of spreadsheet errors. The taxonomy is an outcome of an investigation of the widespread problem of spreadsheet errors and an analysis of specific types of these errors. This paper contains a description of the various elements and categories of the classification and is supported by appropri...

  2. 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…

  3. 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.

  4. A note on the stability and discriminability of graph-based features for classification problems in digital pathology

    Science.gov (United States)

    Cruz-Roa, Angel; Xu, Jun; Madabhushi, Anant

    2015-01-01

    Nuclear architecture or the spatial arrangement of individual cancer nuclei on histopathology images has been shown to be associated with different grades and differential risk for a number of solid tumors such as breast, prostate, and oropharyngeal. Graph-based representations of individual nuclei (nuclei representing the graph nodes) allows for mining of quantitative metrics to describe tumor morphology. These graph features can be broadly categorized into global and local depending on the type of graph construction method. While a number of local graph (e.g. Cell Cluster Graphs) and global graph (e.g. Voronoi, Delaunay Triangulation, Minimum Spanning Tree) features have been shown to associated with cancer grade, risk, and outcome for different cancer types, the sensitivity of the preceding segmentation algorithms in identifying individual nuclei can have a significant bearing on the discriminability of the resultant features. This therefore begs the question as to which features while being discriminative of cancer grade and aggressiveness are also the most resilient to the segmentation errors. These properties are particularly desirable in the context of digital pathology images, where the method of slide preparation, staining, and type of nuclear segmentation algorithm employed can all dramatically affect the quality of the nuclear graphs and corresponding features. In this paper we evaluated the trade off between discriminability and stability of both global and local graph-based features in conjunction with a few different segmentation algorithms and in the context of two different histopathology image datasets of breast cancer from whole-slide images (WSI) and tissue microarrays (TMA). Specifically in this paper we investigate a few different performance measures including stability, discriminability and stability vs discriminability trade off, all of which are based on p-values from the Kruskal-Wallis one-way analysis of variance for local and global

  5. [Ethical problems raised by new reproductive biotechnologies and stem cells].

    Science.gov (United States)

    Le Douarin, Nicole M

    2015-01-01

    Research about the hormonal mechanisms controlling reproduction in mammals has soared during the first half of the 20th century. It has produced a series of discoveries with important outcomes, not only scientific, but also impacting the ways of life. Besides the advent of the contraceptive pill, it has permitted to isolate and cultivate in vitro the female gamete, to fertilize it, thus obtaining a zygote that continues to develop until the blastocyst stage outside the maternal organism. The embryo, transferred into a foster-mother, develops normally until term: the first "test-tube baby" was born in this way in 1978. But the only fact of being able to cultivate the human egg in vitro was to open other possibilities and allow further biological advances: embryonic stem cells (ES cells) obtained from blastocysts and, more recently, from induced Pluripotent Stem cells (iPS), which can potentially be derived from all types of differentiated cell types obtained from adult individuals. From then on, the advent of a new medicine could be anticipated, regenerative because able to replace deficient or absent cells within the organism. As each of these steps was reached, scientists have encountered vigorous opposition from the people: the new potentials disturbed the conceptions that man had of his relationship to nature, in particular in two sensitive domains: sexuality and reproduction. The progress of science has however been accepted by most as soon as it was understood that humanity could anticipate advantages from these advances.

  6. 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.

  7. 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.

  8. Classification of cell death and its significance%细胞死亡的分类和意义

    Institute of Scientific and Technical Information of China (English)

    吴克复; 郑国光; 马小彤; 宋玉华

    2010-01-01

    Cell death as the partner of cell proliferation is one of the basic mechanism in cell biology. Recently, it became obscure since more and more patterns of cell death were reported. However, the "classification of cell death", which was recommended by the Nomenclature Committee on Cell Death (NCCD) in 2009, clarified the criteria. The theme of the recommendation and recent data from the literature were discussed in this review. The significance of studies on cell death was discussed.%细胞死亡与细胞增殖是对立面,是机体的基本细胞生物学机制之一.近年来报道的越来越多的细胞死亡方式令人困惑.最近细胞死亡命名委员会(NCCD)的细胞死亡分类建议书梳理了相关的研究进展,使概念更清晰.文章概述其主要精神,补充一些文献资料,并探讨细胞死亡研究的意义.

  9. Robust optimization of a mathematical model to design a dynamic cell formation problem considering labor utilization

    Science.gov (United States)

    Vafaeinezhad, Moghadaseh; Kia, Reza; Shahnazari-Shahrezaei, Parisa

    2016-11-01

    Cell formation (CF) problem is one of the most important decision problems in designing a cellular manufacturing system includes grouping machines into machine cells and parts into part families. Several factors should be considered in a cell formation problem. In this work, robust optimization of a mathematical model of a dynamic cell formation problem integrating CF, production planning and worker assignment is implemented with uncertain scenario-based data. The robust approach is used to reduce the effects of fluctuations of the uncertain parameters with regards to all possible future scenarios. In this research, miscellaneous cost parameters of the cell formation and demand fluctuations are subject to uncertainty and a mixed-integer nonlinear programming model is developed to formulate the related robust dynamic cell formation problem. The objective function seeks to minimize total costs including machine constant, machine procurement, machine relocation, machine operation, inter-cell and intra-cell movement, overtime, shifting labors between cells and inventory holding. Finally, a case study is carried out to display the robustness and effectiveness of the proposed model. The tradeoff between solution robustness and model robustness is also analyzed in the obtained results.

  10. Anatomy, classification of intersinus septal cell and its clinical significance in frontal sinus endoscopic surgery in Chinese subjects

    Institute of Scientific and Technical Information of China (English)

    WANG Min; YUAN Fei; QI Wei-wei; CHENG Jye-yuan; YUAN Xiao-pei; HAN Lin; XING Zhi-min

    2012-01-01

    Background Intersinus septal cell (ISSC) is not a very uncommon frontal recess cell.But it is poorly described in literature.The clinical significance of this anatomic variant still remains unclear.The purpose of this study was to clarify the anatomy,classification of ISSC and its clinical significance in Chinese subjects.Methods We prospectively identified ISSC in 200 consecutive subjects who had undergone computed tomography (CT) scans:120 without frontal sinusitis (group 1) and 80 with frontal sinusitis (group 2).The ISSC was classified into two types:Type I ISSC communicated with frontal sinuses,type Ⅱ ISSC communicated with frontal recess.The patients of frontal sinusitis had undergone functional endoscopic sinus surgery with the assistance of the classification of ISSC.Statistical analysis was performed to correlate the ISSC and its type to the presence of frontal sinusitis.Results The ISSC was obvious when reviewing the coronal and axial CT scans.Of the 200 CT scans reviewed,ISSC were present in 90 (45%).Of the 120 scans in group 1,ISSC were present in 49 (41%),among which type I ISSC was in 22 (18%) and type Ⅱ was in 27 (23%).Of the 80 scans in group 2,ISSC was present in 41 (51%),among which type Ⅰ ISSC was in 16 (20%) and type Ⅱ was in 25 (31%).There were no statistically significant differences about the frequency distribution of total ISSC,type Ⅰ and Ⅱ ISSC between group 1 and group 2.Conclusions The prevalence of ISSC was very high in Chinese patients.The classification of ISSC was helpful for surgeon to operate according to whether it communicated with frontal sinus or frontal recess.The type Ⅱ ISSC could be relatively easily removed from frontal recess.

  11. 对称分类在非线性偏微分方程组边值问题中的应用%Application of the symmetry classification to the b oundary value problem of nonlinear partial differential equations

    Institute of Scientific and Technical Information of China (English)

    苏道毕力格; 王晓民; 乌云莫日根

    2014-01-01

    In this paper, we study the application of the symmetry classification to the boundary value problem of nonli-near partial differential equations. Firstly, by using differential characteristic set algorithm for the complete symmetry classification of partial differential equations, the complete symmetry classification of a given boundary value problem of nonlinear partial differential equations is proposed. Secondly, by using an extended symmetry, the boundary value problem of nonlinear partial differential equations is reduced to an initial value problem of the original differential equations. Finally, we numerically solve the initial value problem of the original differential equations by using Runge-Kutta method.%研究了微分方程对称分类在非线性偏微分方程组边值问题中的应用。首先,利用偏微分方程(组)完全对称分类微分特征列集算法确定了给定非线性偏微分方程组边值问题的完全对称分类;其次,利用一个扩充对称将非线性偏微分方程组边值问题约化为常微分方程组初值问题;最后,利用龙格-库塔法求解了常微分方程组初值问题的数值解。

  12. 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.

  13. Systemic Problems: A perspective on stem cell aging and rejuvenation

    Science.gov (United States)

    Conboy, Irina M.; Conboy, Michael J.; Rebo, Justin

    2015-01-01

    This review provides balanced analysis of the advances in systemic regulation of young and old tissue stem cells and suggests strategies for accelerating development of therapies to broadly combat age-related tissue degenerative pathologies. Many highlighted recent reports on systemic tissue rejuvenation combine parabiosis with a “silver bullet” putatively responsible for the positive effects. Attempts to unify these papers reflect the excitement about this experimental approach and add value in reproducing previous work. At the same time, defined molecular approaches, which are “beyond parabiosis” for the rejuvenation of multiple old organs represent progress toward attenuating or even reversing human tissue aging. PMID:26540176

  14. Tumours of histiocytes and accessory dendritic cells : an immunohistochemical approach to classification from the International Lymphoma Study Group based on 61 cases

    NARCIS (Netherlands)

    Pileri, SA; Grogan, TM; Harris, NL; Banks, P; Campo, E; Chan, JKC; Favera, RD; Delsol, G; De Wolf-Peeters, C; Falini, B; Gascoyne, RD; Gaulard, P; Gatter, KC; Isaacson, PG; Jaffe, ES; Kluin, P; Knowles, DM; Mason, DY; Mori, S; Muller-Hermelink, HK; Piris, MA; Ralfkiaer, E; Stein, H; Su, IJ; Warnke, RA; Weiss, LM

    2002-01-01

    Neoplasms of histiocytes and dendritic cells are rare, and their phenotypic and biological definition is incomplete. Seeking to identify antigens detectable in paraffin-embedded sections that might allow a more complete, rational immunophenotypic classification of histiocytic/dendritic cell neoplasm

  15. 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

    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 optim...

  16. 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.

  17. 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.

  18. Blood cell counting and classification by nonflowing laser light scattering method

    Science.gov (United States)

    Yang, Ye; Zhang, Zhenxi; Yang, Xinhui; Jiang, Dazong; Yeo, Joon Hock

    1999-11-01

    A new non-flowing laser light scattering method for counting and classifying blood cells is presented. A linear charge- coupled device with 1024 elements is used to detect the scattered light intensity distribution of the blood cells. A pinhole plate is combined with the CCD to compete the focusing of the measurement system. An isotropic sphere is used to simulate the blood cell. Mie theory is used to describe the scattering of blood cells. In order to inverse the size distribution of blood cells from their scattered light intensity distribution, Powell method combined with precision punishment method is used as a dependent model method for measurement red blood cells and blood plates. Non-negative constraint least square method combined with Powell method and precision punishment method is used as an independent model for measuring white blood cells. The size distributions of white blood cells and red blood cells, and the mean diameter of red blood cells are measured by this method. White blood cells can be divided into three classes: lymphocytes, middle-sized cells and neutrocytes according to their sizes. And the number of blood cells in unit volume can also be measured by the linear dependence of blood cells concentration on scattered light intensity.

  19. 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.

  20. 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 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.

  1. Early evolution of eukaryote feeding modes, cell structural diversity, and classification of the protozoan phyla Loukozoa, Sulcozoa, and Choanozoa.

    Science.gov (United States)

    Cavalier-Smith, Thomas

    2013-05-01

    I discuss how different feeding modes and related cellular structures map onto the eukaryote evolutionary tree. Centrally important for understanding eukaryotic cell diversity are Loukozoa: ancestrally biciliate phagotrophic protozoa possessing a posterior cilium and ventral feeding groove into which ciliary currents direct prey. I revise their classification by including all anaerobic Metamonada as a subphylum and adding Tsukubamonas. Loukozoa, often with ciliary vanes, are probably ancestral to all protozoan phyla except Euglenozoa and Percolozoa and indirectly to kingdoms Animalia, Fungi, Plantae, and Chromista. I make a new protozoan phylum Sulcozoa comprising subphyla Apusozoa (Apusomonadida, Breviatea) and Varisulca (Diphyllatea; Planomonadida, Discocelida, Mantamonadida; Rigifilida). Understanding sulcozoan evolution clarifies the origins from them of opisthokonts (animals, fungi, Choanozoa) and Amoebozoa, and their evolutionary novelties; Sulcozoa and their descendants (collectively called podiates) arguably arose from Loukozoa by evolving posterior ciliary gliding and pseudopodia in their ventral groove. I explain subsequent independent cytoskeletal modifications, accompanying further shifts in feeding mode, that generated Amoebozoa, Choanozoa, and fungi. I revise classifications of Choanozoa, Conosa (Amoebozoa), and basal fungal phylum Archemycota. I use Choanozoa, Sulcozoa, Loukozoa, and Archemycota to emphasize the need for simply classifying ancestral (paraphyletic) groups and illustrate advantages of this for understanding step-wise phylogenetic advances.

  2. 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.

  3. 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).

  4. 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.

  5. Classification of bladder cancer cell lines using Raman spectroscopy: a comparison of excitation wavelength, sample substrate and statistical algorithms

    Science.gov (United States)

    Kerr, Laura T.; Adams, Aine; O'Dea, Shirley; Domijan, Katarina; Cullen, Ivor; Hennelly, Bryan M.

    2014-05-01

    Raman microspectroscopy can be applied to the urinary bladder for highly accurate classification and diagnosis of bladder cancer. This technique can be applied in vitro to bladder epithelial cells obtained from urine cytology or in vivo as an optical biopsy" to provide results in real-time with higher sensitivity and specificity than current clinical methods. However, there exists a high degree of variability across experimental parameters which need to be standardised before this technique can be utilized in an everyday clinical environment. In this study, we investigate different laser wavelengths (473 nm and 532 nm), sample substrates (glass, fused silica and calcium fluoride) and multivariate statistical methods in order to gain insight into how these various experimental parameters impact on the sensitivity and specificity of Raman cytology.

  6. Refined diagnostic criteria and classification of mast cell leukemia (MCL) and myelomastocytic leukemia (MML): a consensus proposal.

    Science.gov (United States)

    Valent, P; Sotlar, K; Sperr, W R; Escribano, L; Yavuz, S; Reiter, A; George, T I; Kluin-Nelemans, H C; Hermine, O; Butterfield, J H; Hägglund, H; Ustun, C; Hornick, J L; Triggiani, M; Radia, D; Akin, C; Hartmann, K; Gotlib, J; Schwartz, L B; Verstovsek, S; Orfao, A; Metcalfe, D D; Arock, M; Horny, H-P

    2014-09-01

    Mast cell leukemia (MCL), the leukemic manifestation of systemic mastocytosis (SM), is characterized by leukemic expansion of immature mast cells (MCs) in the bone marrow (BM) and other internal organs; and a poor prognosis. In a subset of patients, circulating MCs are detectable. A major differential diagnosis to MCL is myelomastocytic leukemia (MML). Although criteria for both MCL and MML have been published, several questions remain concerning terminologies and subvariants. To discuss open issues, the EU/US-consensus group and the European Competence Network on Mastocytosis (ECNM) launched a series of meetings and workshops in 2011-2013. Resulting discussions and outcomes are provided in this article. The group recommends that MML be recognized as a distinct condition defined by mastocytic differentiation in advanced myeloid neoplasms without evidence of SM. The group also proposes that MCL be divided into acute MCL and chronic MCL, based on the presence or absence of C-Findings. In addition, a primary (de novo) form of MCL should be separated from secondary MCL that typically develops in the presence of a known antecedent MC neoplasm, usually aggressive SM (ASM) or MC sarcoma. For MCL, an imminent prephase is also proposed. This prephase represents ASM with rapid progression and 5%-19% MCs in BM smears, which is generally accepted to be of prognostic significance. We recommend that this condition be termed ASM in transformation to MCL (ASM-t). The refined classification of MCL fits within and extends the current WHO classification; and should improve prognostication and patient selection in practice as well as in clinical trials.

  7. A microarray platform-independent classification tool for cell of origin class allows comparative analysis of gene expression in diffuse large B-cell lymphoma.

    Directory of Open Access Journals (Sweden)

    Matthew A Care

    Full Text Available Cell of origin classification of diffuse large B-cell lymphoma (DLBCL identifies subsets with biological and clinical significance. Despite the established nature of the classification existing studies display variability in classifier implementation, and a comparative analysis across multiple data sets is lacking. Here we describe the validation of a cell of origin classifier for DLBCL, based on balanced voting between 4 machine-learning tools: the DLBCL automatic classifier (DAC. This shows superior survival separation for assigned Activated B-cell (ABC and Germinal Center B-cell (GCB DLBCL classes relative to a range of other classifiers. DAC is effective on data derived from multiple microarray platforms and formalin fixed paraffin embedded samples and is parsimonious, using 20 classifier genes. We use DAC to perform a comparative analysis of gene expression in 10 data sets (2030 cases. We generate ranked meta-profiles of genes showing consistent class-association using ≥6 data sets as a cut-off: ABC (414 genes and GCB (415 genes. The transcription factor ZBTB32 emerges as the most consistent and differentially expressed gene in ABC-DLBCL while other transcription factors such as ARID3A, BATF, and TCF4 are also amongst the 24 genes associated with this class in all datasets. Analysis of enrichment of 12323 gene signatures against meta-profiles and all data sets individually confirms consistent associations with signatures of molecular pathways, chromosomal cytobands, and transcription factor binding sites. We provide DAC as an open access Windows application, and the accompanying meta-analyses as a resource.

  8. Small-Cell Lung Cancer: Clinical Management and Unmet Needs New Perspectives for an Old Problem.

    Science.gov (United States)

    Lo Russo, Giuseppe; Macerelli, Marianna; Platania, Marco; Zilembo, Nicoletta; Vitali, Milena; Signorelli, Diego; Proto, Claudia; Ganzinelli, Monica; Gallucci, Rosaria; Agustoni, Francesco; Fasola, Gianpiero; de Braud, Filippo; Garassino, Marina Chiara

    2017-01-01

    Small cell lung cancer is a highly aggressive, difficult to treat neoplasm. Among all lung tumors, small cell lung cancers account for about 20%. Patients typically include heavy smokers in 70s age group, presenting with symptoms such as intrathoracic tumors growth, distant spread or paraneoplastic syndromes at the time of diagnosis. A useful and functional classification divides small cell lung cancers into limited disease and extensive disease. Concurrent chemo-radiotherapy is the standard treatment for limited disease, with improved survival when combined with prophylactic cranial irradiation. Platinum compounds (cisplatin/carboplatin) plus etoposide remain the cornerstone for extensive disease. Nevertheless, despite high chemo- and radio-sensitivity of this cancer, nearly all patients relapse within the first two years and the prognosis is extremely poor. A deeper understanding about small cell lung cancer carcinogenesis led to develop and test a considerable number of new and targeted agents but the results are currently weak or insufficient. To date, small cell lung cancer is still a challenge for researchers. In this review, key aspects of small cell lung cancer management and controversial points of standard and new treatments will be discussed.

  9. Cellular image classification

    CERN Document Server

    Xu, Xiang; Lin, Feng

    2017-01-01

    This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical...

  10. 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...... was only expressed in the ABC and in Type-3 samples. The 5-year survival was similar between the groups, but GCB patients showed a better initial response to CHOP or CHOP-like regimens than the remaining patients and tended to have less advanced disease and lower IPI scores. As a next step, an improved set...

  11. 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).

  12. Multicenter validation of recursive partitioning analysis classification for patients with squamous cell head and neck carcinoma treated with surgery and postoperative radiotherapy.

    NARCIS (Netherlands)

    Jonkman, A.; Kaanders, J.H.A.M.; Terhaard, C.H.J.; Hoebers, F.J.; Ende, P.L. van den; Wijers, O.B.; Verhoef, L.C.G.; Jong, M. de; Leemans, C.R.; Langendijk, J.A.

    2007-01-01

    PURPOSE: To validate the recursive partitioning analysis (RPA) classification system for squamous cell head and neck cancer as recently reported by the VU University Medical Center. METHODS AND MATERIALS: In eight Dutch head and neck cancer centers, data necessary to classify patients according to t

  13. Large cell carcinoma of the lung: clinically oriented classification integrating immunohistochemistry and molecular biology.

    Science.gov (United States)

    Rossi, G; Mengoli, M C; Cavazza, A; Nicoli, D; Barbareschi, M; Cantaloni, C; Papotti, M; Tironi, A; Graziano, P; Paci, M; Stefani, A; Migaldi, M; Sartori, G; Pelosi, G

    2014-01-01

    This study aimed at challenging pulmonary large cell carcinoma (LLC) as tumor entity and defining different subgroups according to immunohistochemical and molecular features. Expression of markers specific for glandular (TTF-1, napsin A, cytokeratin 7), squamous cell (p40, p63, cytokeratins 5/6, desmocollin-3), and neuroendocrine (chromogranin, synaptophysin, CD56) differentiation was studied in 121 LCC across their entire histological spectrum also using direct sequencing for epidermal growth factor receptor (EGFR) and v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations and FISH analysis for ALK gene translocation. Survival was not investigated. All 47 large cell neuroendocrine carcinomas demonstrated a true neuroendocrine cell lineage, whereas all 24 basaloid and both 2 lymphoepithelioma-like carcinomas showed squamous cell markers. Eighteen out of 22 clear cell carcinomas had glandular differentiation, with KRAS mutations being present in 39 % of cases, whereas squamous cell differentiation was present in four cases. Eighteen out of 20 large cell carcinomas, not otherwise specified, had glandular differentiation upon immunohistochemistry, with an exon 21 L858R EGFR mutation in one (5 %) tumor, an exon 2 KRAS mutation in eight (40 %) tumors, and an ALK translocation in one (5 %) tumor, whereas two tumors positive for CK7 and CK5/6 and negative for all other markers were considered adenocarcinoma. All six LCC of rhabdoid type expressed TTF-1 and/or CK7, three of which also harbored KRAS mutations. When positive and negative immunohistochemical staining for these markers was combined, three subsets of LCC emerged exhibiting glandular, squamous, and neuroendocrine differentiation. Molecular alterations were restricted to tumors classified as adenocarcinoma. Stratifying LCC into specific categories using immunohistochemistry and molecular analysis may significantly impact on the choice of therapy.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. Issues and ethical problems of stem cell therapy--where is Hippocrates?

    Science.gov (United States)

    Rousková, Lucie; Hruska, Ivan; Filip, Stanislav

    2008-01-01

    Stem cells and their therapeutic use present many questions associated with ethical problems in medicine. There is great effort on the part of physicians to help millions of patients while there are ethical problems with the use of new methods and technologies and all of these are affected by economic and political influences. How will the current generation deal with these problems? Medicine, in this begard, is experiencing a stormy evolution of human culture in the relationships between disease, patient and doctor. Philosophy approaches the same juncture of human culture, but seemingly from the other side. Both disciplines are facing a great problem: How to unite the content of current human morality and the desire for health? Both philosophers and physicians perceive this deficit in human culture as it does not provide immediately usable normatives, which the living generation of healthy and ill is waiting for. It may be said that medicine, as many times before, has reached a stage where it cannot rely only on the proved axiologic values from the past, ethical normatives or cultivated moral sense of its subjects. Medicine has no other alternative than to take an active part in resolution of interdisciplinary problems originating from philosophic-biologic or philosophic-medical inquiries of axiologic, ethical, and moral issues. Our paper indicates some ways of the search in forming ethical principles of the stem-cell therapy from the view of biologists and physicians. New ways are recommended in theoretical-methodological interdisciplinary research, especially, in theoretical and experimental biology, and theoretical and clinical medicine, as well as philosophy. In this paper important ethical problems are pointed out in order to find answers to some key problems connected with cell therapy and the use of stem cells.

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

    DEFF Research Database (Denmark)

    Rossing, Maria

    2013-01-01

    The incidence of thyroid cancer is increasing worldwide and thyroid nodules are a frequent clinical finding. Diagnosing follicular cell-derived cancers is, however, challenging both histopathologically and especially cytopathologically. The advent of high-throughput molecular technologies has...... profiling of follicular cell-derived thyroid cancers....... prompted many researchers to explore the transcriptome and, in recent years, also the miRNome in order to generate new molecular classifiers capable of classifying thyroid tumours more accurately than by conventional cytopathological and histopathological methods. This has led to a number of molecular...

  20. 支持向量机多分类问题研究%Research on the Multi-class Classification Problem of Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    肖晓; 张敏

    2014-01-01

    The support vector machine (SVM)is a typical two-class classification methods and how to extend it to multi-class classification has been increasingly a hotspot in the research of scholars.Experiments with the standard datasets were carried retrospectively on the existing methods of SVM multiclass classification,such as one against one method,one against rest meth-od and directed acyclic graph,showed their respective merits and defects.The results indicate that directed acyclic graph is naturally suitable for the multi-class classification of large-scale data with ideal training speed,which has a certain reference value.%支持向量机是典型的两类分类方法,如何将其推广到多分类问题是学者们正在研究的一个热点。对比分析几种常用的多类方法的优缺点,利用标准数据集对多类支持向量机的速度和精度两方面进行试验分析。研究表明,对于大规模的多类分类问题,有向无环图简单易行,具有理想的训练速度与精度,具有一定的参考价值。

  1. Visualization-aided classification ensembles discriminate lung adenocarcinoma and squamous cell carcinoma samples using their gene expression profiles.

    Directory of Open Access Journals (Sweden)

    Ao Zhang

    Full Text Available INTRODUCTION: The widespread application of microarray experiments to cancer research is astounding including lung cancer, one of the most common fatal human tumors. Among non-small cell lung carcinoma (NSCLC, there are two major histological types of NSCLC, adenocarcinoma (AC and squamous cell carcinoma (SCC. RESULTS: In this paper, we proposed to integrate a visualization method called Radial Coordinate Visualization (Radviz with a suitable classifier, aiming at discriminating two NSCLC subtypes using patients' gene expression profiles. Our analyses on simulated data and a real microarray dataset show that combining with a classification method, Radviz may play a role in selecting relevant features and ameliorating parsimony, while the final model suffers no or least loss of accuracy. Most importantly, a graphic representation is more easily understandable and implementable for a clinician than statistical methods and/or mathematic equations. CONCLUSION: To conclude, using the NSCLC microarray data presented here as a benchmark, the comprehensive understanding of the underlying mechanism associated with NSCLC and of the mechanisms with its subtypes and respective stages will become reality in the near future.

  2. 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.

  3. Chronic Replication Problems Impact Cell Morphology and Adhesion of DNA Ligase I Defective Cells.

    Directory of Open Access Journals (Sweden)

    Paolo Cremaschi

    Full Text Available Moderate DNA damage resulting from metabolic activities or sub-lethal doses of exogenous insults may eventually lead to cancer onset. Human 46BR.1G1 cells bear a mutation in replicative DNA ligase I (LigI which results in low levels of replication-dependent DNA damage. This replication stress elicits a constitutive phosphorylation of the ataxia telangiectasia mutated (ATM checkpoint kinase that fails to arrest cell cycle progression or to activate apoptosis or cell senescence. Stable transfection of wild type LigI, as in 7A3 cells, prevents DNA damage and ATM activation. Here we show that parental 46BR.1G1 and 7A3 cells differ in important features such as cell morphology, adhesion and migration. Comparison of gene expression profiles in the two cell lines detects Bio-Functional categories consistent with the morphological and migration properties of LigI deficient cells. Interestingly, ATM inhibition makes 46BR.1G1 more similar to 7A3 cells for what concerns morphology, adhesion and expression of cell-cell adhesion receptors. These observations extend the influence of the DNA damage response checkpoint pathways and unveil a role for ATM kinase activity in modulating cell biology parameters relevant to cancer progression.

  4. Chronic Replication Problems Impact Cell Morphology and Adhesion of DNA Ligase I Defective Cells.

    Science.gov (United States)

    Cremaschi, Paolo; Oliverio, Matteo; Leva, Valentina; Bione, Silvia; Carriero, Roberta; Mazzucco, Giulia; Palamidessi, Andrea; Scita, Giorgio; Biamonti, Giuseppe; Montecucco, Alessandra

    2015-01-01

    Moderate DNA damage resulting from metabolic activities or sub-lethal doses of exogenous insults may eventually lead to cancer onset. Human 46BR.1G1 cells bear a mutation in replicative DNA ligase I (LigI) which results in low levels of replication-dependent DNA damage. This replication stress elicits a constitutive phosphorylation of the ataxia telangiectasia mutated (ATM) checkpoint kinase that fails to arrest cell cycle progression or to activate apoptosis or cell senescence. Stable transfection of wild type LigI, as in 7A3 cells, prevents DNA damage and ATM activation. Here we show that parental 46BR.1G1 and 7A3 cells differ in important features such as cell morphology, adhesion and migration. Comparison of gene expression profiles in the two cell lines detects Bio-Functional categories consistent with the morphological and migration properties of LigI deficient cells. Interestingly, ATM inhibition makes 46BR.1G1 more similar to 7A3 cells for what concerns morphology, adhesion and expression of cell-cell adhesion receptors. These observations extend the influence of the DNA damage response checkpoint pathways and unveil a role for ATM kinase activity in modulating cell biology parameters relevant to cancer progression.

  5. 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

  6. 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

  7. 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...... 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...

  8. 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....

  9. 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…

  10. 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…

  11. 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).

  12. Applying Ant Colony Optimization to the Problem of Cell Planning in Mobile Telephone System Radio Network

    Directory of Open Access Journals (Sweden)

    Osmar Viera Carcache

    2017-03-01

    Full Text Available This paper presents a computational proposal for the solution of the Cell Planning Problem. The importance of this problem in the area of Telecommunications imposes it as a reference in the search for new methods of optimization. Due to the complexity of the problem, this work uses a discrete relaxation and proposes a mathematical model for the application of the Meta-heuristic Ant Colony Optimization (ACO. For the analysis of the results, 5 instances of the problem of different sizes were selected and the Ants System (AS algorithm was applied. The results show that the proposal efficiently explores the search space, finding the optimal solution for each instance with a relatively low computational cost. These results are compared with 3 evolutionary alternatives of international reference that have been applied to the same study instances, showing a significant improvement by our proposal.

  13. 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…

  14. 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...... in the process as well as modeling dependences between attributes....

  15. Survival of non-seminomatous germ cell cancer patients according to the IGCC classification: An update based on meta-analysis.

    Science.gov (United States)

    van Dijk, Merel R; Steyerberg, Ewout W; Habbema, J Dik F

    2006-05-01

    The International Germ Cell Consensus (IGCC) Classification distinguishes patients with non-seminomatous germ cell tumours (NSGCT) with a good, intermediate or poor prognosis, with a reported 5-year overall survival of 92%, 80% and 48%, respectively. Since the IGCC classification was based on patients treated between 1975 and 1990, we aimed to investigate whether survival has improved for more recently treated patients. We did a systematic search of the literature and included studies on survival of patients with NSGCT, treated after 1989 and classified according to the IGCC classification. Survival estimates of selected studies were pooled using meta-analytic techniques. We included 10 papers, describing 1775 patients with NSGCT with good (n = 1087), intermediate (n = 232), or poor (n = 456) prognosis. Pooled 5-year survival estimates were 94%, 83% and 71%, respectively. Since the publication of the IGCC classification, there was a small increase in survival for good and intermediate prognosis patients, and a large increase in survival for patients with a poor prognosis. This increase is most likely due to both more effective treatment strategies and more experience in treating NSGCT patients.

  16. 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.

  17. 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.

  18. 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。

  19. Adapting Cell-Based Assays to the High Throughput Screening Platform: Problems Encountered and Lessons Learned.

    Science.gov (United States)

    Maddox, Clinton B; Rasmussen, Lynn; White, E Lucile

    2008-06-01

    In recent years, cell-based phenotypic assays have emerged as an effective and robust addition to the array of assay technologies available for drug discovery in the high throughput screening arena. Previously, biochemical target-based assays have been the technology of choice. With the emergence of stem cells as a basis for a new screening technology, it is important to keep in mind the lessons that have been learned from the adaptation of existing stable cell lines onto the high throughput screening drug discovery platform, with special consideration being given to assay miniaturization, liquid handling complications and instrument-introduced artifacts. We present an overview of the problems encountered with the implementation of multiple cell-based assays at the High Throughput Screening Center at Southern Research Institute as well as empirically defined effective solutions to these problems. These include examples of artifacts induced by temperature differences throughout the screening campaign, cell plating conditions including the effect of room temperature incubation on assay consistency, DMSO carry-over, and incubator induced artifacts.

  20. 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.

  1. 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.

  2. 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.

  3. A multi-model approach to simultaneous segmentation and classification of heterogeneous populations of cell nuclei in 3D confocal microscope images.

    Science.gov (United States)

    Lin, Gang; Chawla, Monica K; Olson, Kathy; Barnes, Carol A; Guzowski, John F; Bjornsson, Christopher; Shain, William; Roysam, Badrinath

    2007-09-01

    Automated segmentation and morphometry of fluorescently labeled cell nuclei in batches of 3D confocal stacks is essential for quantitative studies. Model-based segmentation algorithms are attractive due to their robustness. Previous methods incorporated a single nuclear model. This is a limitation for tissues containing multiple cell types with different nuclear features. Improved segmentation for such tissues requires algorithms that permit multiple models to be used simultaneously. This requires a tight integration of classification and segmentation algorithms. Two or more nuclear models are constructed semiautomatically from user-provided training examples. Starting with an initial over-segmentation produced by a gradient-weighted watershed algorithm, a hierarchical fragment merging tree rooted at each object is built. Linear discriminant analysis is used to classify each candidate using multiple object models. On the basis of the selected class, a Bayesian score is computed. Fragment merging decisions are made by comparing the score with that of other candidates, and the scores of constituent fragments of each candidate. The overall segmentation accuracy was 93.7% and classification accuracy was 93.5%, respectively, on a diverse collection of images drawn from five different regions of the rat brain. The multi-model method was found to achieve high accuracy on nuclear segmentation and classification by correctly resolving ambiguities in clustered regions containing heterogeneous cell populations.

  4. 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.

  5. [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.

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. Primary cutaneous B-cell lymphoma other than marginal zone: clinicopathologic analysis of 161 cases: Comparison with current classification and definition of prognostic markers.

    Science.gov (United States)

    Lucioni, Marco; Berti, Emilio; Arcaini, Luca; Croci, Giorgio A; Maffi, Aldo; Klersy, Catherine; Goteri, Gaia; Tomasini, Carlo; Quaglino, Pietro; Riboni, Roberta; Arra, Mariarosa; Dallera, Elena; Grandi, Vieri; Alaibac, Mauro; Ramponi, Antonio; Rattotti, Sara; Cabras, Maria Giuseppina; Franceschetti, Silvia; Fraternali-Orcioni, Giulio; Zerbinati, Nicola; Onida, Francesco; Ascani, Stefano; Fierro, Maria Teresa; Rupoli, Serena; Gambacorta, Marcello; Zinzani, Pier Luigi; Pimpinelli, Nicola; Santucci, Marco; Paulli, Marco

    2016-10-01

    Categorization of primary cutaneous B-cell lymphomas (PCBCL) other than marginal zone (MZL) represents a diagnostic challenge with relevant prognostic implications. The 2008 WHO lymphoma classification recognizes only primary cutaneous follicular center cell lymphoma (PCFCCL) and primary cutaneous diffuse large B-cell lymphoma, leg type (PCDLBCL-LT), whereas the previous 2005 WHO/EORTC classification also included an intermediate form, namely PCDLBCL, other. We conducted a retrospective, multicentric, consensus-based revision of the clinicopathologic characteristics of 161 cases of PCBCL other than MZL. Upon the histologic features that are listed in the WHO classification, 96 cases were classified as PCFCCL and 25 as PCDLBCL-LT; 40 further cases did not fit in the former subgroups in terms of cytology and/or architecture, thus were classified as PCDLBCL, not otherwise specified (PCDLBCL-NOS). We assigned all the cases a histogenetic profile, based on the immunohistochemical detection of CD10, BCL6, and MUM1, and a "double hit score" upon positivity for BCL2 and MYC. PCDLBCL-NOS had a clinical presentation more similar to PCFCCL, whereas the histology was more consistent with the picture of a diffuse large B-cell lymphoma, as predominantly composed of centroblasts but with intermixed a reactive infiltrate of small lymphocytes. Its behavior was intermediate between the other two forms, particularly when considering only cases with a "non-germinal B-cell" profile, whereas "germinal center" cases resembled PCFCCL. Our data confirmed the aggressive behavior of PCDLBC-LT, which often coexpressed MYC and BCL2. The impact of single factors on 5-year survival was documented, particularly histogenetic profile in PCDLBCL and BCL2 translocation in PCFCCL. Our study confirms that a further group-PCDLBCL-NOS-exists, which can be recognized through a careful combination of histopathologic criteria coupled with adequate clinical information.

  13. Psychiatric Problems in Children and Adolescents with Sickle cell Disease, Based on Parent and Teacher Reports

    Directory of Open Access Journals (Sweden)

    Özalp Ekinci

    2012-09-01

    Full Text Available OBJECTIVE: This study aimed to investigate the occurrence of psychiatric problems in children and adolescents with sickle cell disease (SCD. METHODS: The Child Behavior Checklist for ages 4-18 years (CBCL/4-18, Conners’ Parent Rating Scale (CPRS, Conners’ Teacher Rating Scale (CTRS-R, and The Turgay DSM-IV Based Child and Adolescent Behavior Disorders Screening and Rating Scale, clinician and parent forms (T-DSM-IV-S were given to the caregivers and teachers of 31 children with SCD aged between 7-18 years and the caregivers and teachers of 34 age matched controls with irondeficiency anemia. RESULTS: The SCD patients had higher scores on all 4 of scales. Among the subscales, internalizing problems, and attention problems were more prominent in the SCD patients. CONCLUSION: Children and adolescents with SCD appear to have an increased risk for psychiatric problems. Regular psychological evaluation and referral to child and adolescent psychiatry clinics may facilitate timely diagnosis and effective treatment of at-risk children and adolescents.

  14. Mature red blood cells: from optical model to inverse light-scattering problem.

    Science.gov (United States)

    Gilev, Konstantin V; Yurkin, Maxim A; Chernyshova, Ekaterina S; Strokotov, Dmitry I; Chernyshev, Andrei V; Maltsev, Valeri P

    2016-04-01

    We propose a method for characterization of mature red blood cells (RBCs) morphology, based on measurement of light-scattering patterns (LSPs) of individual RBCs with the scanning flow cytometer and on solution of the inverse light-scattering (ILS) problem for each LSP. We considered a RBC shape model, corresponding to the minimal bending energy of the membrane with isotropic elasticity, and constructed an analytical approximation, which allows rapid simulation of the shape, given the diameter and minimal and maximal thicknesses. The ILS problem was solved by the nearest-neighbor interpolation using a preliminary calculated database of 250,000 theoretical LSPs. For each RBC in blood sample we determined three abovementioned shape characteristics and refractive index, which also allows us to calculate volume, surface area, sphericity index, spontaneous curvature, hemoglobin concentration and content.

  15. Against Lung Cancer Cells: To Be, or Not to Be, That Is the Problem

    Directory of Open Access Journals (Sweden)

    Naoko Okumura

    2012-01-01

    Full Text Available Tobacco smoke and radioactive radon gas impose a high risk for lung cancer. The radon-derived ionizing radiation and some components of cigarette smoke induce oxidative stress by generating reactive oxygen species (ROS. Respiratory lung cells are subject to the ROS that causes DNA breaks, which subsequently bring about DNA mutagenesis and are intimately linked with carcinogenesis. The damaged cells by oxidative stress are often destroyed through the active apoptotic pathway. However, the ROS also perform critical signaling functions in stress responses, cell survival, and cell proliferation. Some molecules enhance radiation-induced tumor cell killing via the reduction in DNA repair levels. Hence the DNA repair levels may be a novel therapeutic modality in overcoming drug resistance in lung cancer. Either survival or apoptosis, which is determined by the balance between DNA damage and DNA repair levels, may lender the major problems in cancer therapy. The purpose of this paper is to take a closer look at risk factor and at therapy modulation factor in lung cancer relevant to the ROS.

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. Proposta de classificação hierarquizada dos modelos de solução para o problema de job shop scheduling A proposition of hierarchical classification for solution models in the job shop scheduling problem

    Directory of Open Access Journals (Sweden)

    Ricardo Ferrari Pacheco

    1999-04-01

    Full Text Available Este artigo propõe uma classificação hierarquizada dos modelos utilizados na solução do problema de programação da produção intermitente do tipo job shop, incluindo tanto os que fornecem solução ótima, quanto os modelos heurísticos mais recentes baseados em métodos de busca estendida. Por meio dessa classificação obteve-se um painel amplo dos modelos existentes, evidenciando as diferentes abordagens do problema e suas soluções, com o objetivo de proporcionar uma orientação preliminar na escolha do modelo de job shop scheduling mais adequado.This paper proposes a hierarchical model classification used in the job shop scheduling problem, including those that provide an optimal solution and the more recent ones based on heuristics, called extended search methods. A panel with the existing models is obtained by this classification, and solutions and approach differences are highlighted with the aim of a preliminary orientation on the choice of a more adequate job shop scheduling model.

  1. Giant cell tumors of lower end of the radius : Problems and solutions

    Directory of Open Access Journals (Sweden)

    Dhammi I

    2005-01-01

    Full Text Available Background: Giant cell tumors of bone are aggressive, potentially malignant lesions. Juxtaarticular giant cell tumours of lower end radius are common and present a special problem of reconstruction after tumor excision. Out of the various reconstructive procedures described, use of nonvascularised fibular autograft has been widely used with satisfactory functional results. Methods: Sixteen patients with a mean age of 20.2 years, with either Campanacci grade II or III histologically proven giant cell tumours of lower end radius were treated with wide excision and reconstruction with ipsilateral nonvascularised proximal fibular autograft. Host graft junction was fixed with intramedullary nail in 12 cases and DCP in last 4 cases. Wrist ligament reconstruction and fixation of the head of fibula with carpal bones using K-wires and primary cancellous iliac crest grafting at graft host junction with DCP was done in last 2 cases. Results: The follow up ranges from 2 - 5 years (mean 3.5 years. At last follow up, the average combined range of motion was 110° with range varying from 60-125°. The average grip strength was 39% in comparison to the contralateral side (range 21-88%. The average union time was 8 months (range 4-12 months. Sound union occurred in 5 months, where DCPs were used. There were 5 nonunions, one resorption of graft, 10 wrist subluxations (2 painful, one recurrence, 3 superficial infections, one wound dehiscence and one amputation. There was no case of graft fracture, metastasis, death or significant donor site morbidity. A total of 10 secondary procedures were required. Conclusions: Enbloc resection of giant cell tumours of lower end radius is a widely accepted method. Reconstruction with nonvascularised fibular graft, internal fixation with DCP with primary corticocancellous bone grafting with transfixation of the fibular head and wrist ligament reconstruction minimizes the problem and gives satisfactory functional results.

  2. Semiparametric Gaussian copula classification

    OpenAIRE

    Zhao, Yue; Wegkamp, Marten

    2014-01-01

    This paper studies the binary classification of two distributions with the same Gaussian copula in high dimensions. Under this semiparametric Gaussian copula setting, we derive an accurate semiparametric estimator of the log density ratio, which leads to our empirical decision rule and a bound on its associated excess risk. Our estimation procedure takes advantage of the potential sparsity as well as the low noise condition in the problem, which allows us to achieve faster convergence rate of...

  3. 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.

  4. 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)...

  5. Cell-centered nonlinear finite-volume methods for the heterogeneous anisotropic diffusion problem

    Science.gov (United States)

    Terekhov, Kirill M.; Mallison, Bradley T.; Tchelepi, Hamdi A.

    2017-02-01

    We present two new cell-centered nonlinear finite-volume methods for the heterogeneous, anisotropic diffusion problem. The schemes split the interfacial flux into harmonic and transversal components. Specifically, linear combinations of the transversal vector and the co-normal are used that lead to significant improvements in terms of the mesh-locking effects. The harmonic component of the flux is represented using a conventional monotone two-point flux approximation; the component along the parameterized direction is treated nonlinearly to satisfy either positivity of the solution as in [29], or the discrete maximum principle as in [9]. In order to make the method purely cell-centered, we derive a homogenization function that allows for seamless interpolation in the presence of heterogeneity following a strategy similar to [46]. The performance of the new schemes is compared with existing multi-point flux approximation methods [3,5]. The robustness of the scheme with respect to the mesh-locking problem is demonstrated using several challenging test cases.

  6. Map Classification In Image Data

    Science.gov (United States)

    2015-09-25

    trained on 1,000 classes, and provides an immense learning capacity. The BOW method uses a visual vocabulary , con- structed by clustering higher-level...this thesis , BOW, was originally developed for text classification problems. By counting the occurrence of words in a document, the resulting vocabulary ...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS MAP CLASSIFICATION IN IMAGE DATA by Frank Fiebiger September 2015 Thesis Advisor: Mathias N

  7. 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

  8. 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.

  9. 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

  10. Static micro-array isolation, dynamic time series classification, capture and enumeration of spiked breast cancer cells in blood: the nanotube-CTC chip

    Science.gov (United States)

    Khosravi, Farhad; Trainor, Patrick J.; Lambert, Christopher; Kloecker, Goetz; Wickstrom, Eric; Rai, Shesh N.; Panchapakesan, Balaji

    2016-11-01

    We demonstrate the rapid and label-free capture of breast cancer cells spiked in blood using nanotube-antibody micro-arrays. 76-element single wall carbon nanotube arrays were manufactured using photo-lithography, metal deposition, and etching techniques. Anti-epithelial cell adhesion molecule (anti-EpCAM), Anti-human epithelial growth factor receptor 2 (anti-Her2) and non-specific IgG antibodies were functionalized to the surface of the nanotube devices using 1-pyrene-butanoic acid succinimidyl ester. Following device functionalization, blood spiked with SKBR3, MCF7 and MCF10A cells (100/1000 cells per 5 μl per device, 170 elements totaling 0.85 ml of whole blood) were adsorbed on to the nanotube device arrays. Electrical signatures were recorded from each device to screen the samples for differences in interaction (specific or non-specific) between samples and devices. A zone classification scheme enabled the classification of all 170 elements in a single map. A kernel-based statistical classifier for the ‘liquid biopsy’ was developed to create a predictive model based on dynamic time warping series to classify device electrical signals that corresponded to plain blood (control) or SKBR3 spiked blood (case) on anti-Her2 functionalized devices with ˜90% sensitivity, and 90% specificity in capture of 1000 SKBR3 breast cancer cells in blood using anti-Her2 functionalized devices. Screened devices that gave positive electrical signatures were confirmed using optical/confocal microscopy to hold spiked cancer cells. Confocal microscopic analysis of devices that were classified to hold spiked blood based on their electrical signatures confirmed the presence of cancer cells through staining for DAPI (nuclei), cytokeratin (cancer cells) and CD45 (hematologic cells) with single cell sensitivity. We report 55%-100% cancer cell capture yield depending on the active device area for blood adsorption with mean of 62% (˜12 500 captured off 20 000 spiked cells in 0.1 ml

  11. 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.

  12. 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.

  13. Prognostic Factors for Renal Cell Carcinoma Subtypes Diagnosed According to the 2016 WHO Renal Tumor Classification: a Study Involving 928 Patients.

    Science.gov (United States)

    Kuthi, Levente; Jenei, Alex; Hajdu, Adrienn; Németh, István; Varga, Zoltán; Bajory, Zoltán; Pajor, László; Iványi, Béla

    2016-12-28

    The morphotype and grade of renal cell carcinoma (RCC) in 928 nephrectomies were reclassified according to the 2016 WHO classification in order to analyze the distribution and outcomes of RCC subtypes in Hungary, to assess whether microscopic tumor necrosis is an independent prognostic factor in clear cell RCC, and to study whether a two-tiered grading (low/high) for clear cell and papillary RCC provides similar prognostic information to that of the four-tiered ISUP grading system. 83.4% of the cohort were clear cell, 6.9% papillary, 4.5% chromophobe, 2.3% unclassified, 1.1% Xp11 translocation, 1.1% clear cell papillary, 0.3% collecting duct and 0.1% mucinous tubular and spindle cell RCCs. RCC occurred in 16 patients with end-stage kidney disease and none of them displayed features of acquired cystic kidney disease-associated RCC. The 5-year survival rates were as follows: chromophobe 100%, clear cell papillary 100%, clear cell low-grade 96%, papillary type 1 92%, clear cell high-grade 63%, papillary type 2 65%, unclassified 46%, Xp11 translocation 20%, and collecting duct 0%. The 5-year survival rates in low-grade and high-grade papillary RCC were 95% and 59%, respectively. In clear cell RCC, only the grade, the stage and the positive surgical margin proved to be independent prognostic factors statistically. Overall, papillary RCC occurred relatively infrequently; microscopic tumor necrosis in clear cell RCC did not predict the outcome independently of the tumor grading; and the assignment of clear cell and papillary RCCs into low-grade or high-grade tumors was in terms of survival no worse than the ISUP grading.

  14. 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

  15. 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.

  16. 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.

  17. Ceramic Lithium Ion Conductor to Solve the Anode Coking Problem of Practical Solid Oxide Fuel Cells.

    Science.gov (United States)

    Wang, Wei; Wang, Feng; Chen, Yubo; Qu, Jifa; Tadé, Moses O; Shao, Zongping

    2015-09-07

    For practical solid oxide fuel cells (SOFCs) operated on hydrocarbon fuels, the facile coke formation over Ni-based anodes has become a key factor that limits their widespread application. Modification of the anodes with basic elements may effectively improve their coking resistance in the short term; however, the easy loss of basic elements by thermal evaporation at high temperatures is a new emerging problem. Herein, we propose a new design to develop coking-resistant and stable SOFCs using Li(+) -conducting Li0.33 La0.56 TiO3 (LLTO) as an anode component. In the Ni/LLTO composite, any loss of surface lithium can be efficiently compensated by lithium diffused from the LLTO bulk under operation. Therefore, the SOFC with the Ni/LLTO anode catalyst layer yields excellent power outputs and operational stability. Our results suggest that the simple adoption of a Li(+) conductor as a modifier for Ni-based anodes is a practical and easy way to solve the coking problem of SOFCs that operate on hydrocarbons.

  18. 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.

  19. Fluorescence lifetime imaging of DAPI-stained nuclei as a novel diagnostic tool for the detection and classification of B-cell chronic lymphocytic leukemia.

    Science.gov (United States)

    Yahav, Gilad; Hirshberg, Abraham; Salomon, Ophira; Amariglio, Ninette; Trakhtenbrot, Luba; Fixler, Dror

    2016-07-01

    B-cell chronic lymphocytic leukaemia (B-CLL) and B-cell precursor acute lymphoblastic leukaemia (B-ALL) are the most common type of leukaemia in adults and children, respectively. Today, fluorescence in situ hybridization (FISH) is the standard for detecting chromosomal aberrations that reflect adverse and favorable outcome. This study revealed a new, simple, and fast diagnostic tool to detect pathological cells by measuring and imaging the fluorescence lifetime (FLT) using FLT imaging microscopy (FLIM) of the peripheral blood (PB) cells of B-CLL samples that were labeled with the DNA binder, DAPI. The FLT of DAPI in healthy individuals was found to be 2.66 ± 0.12 ns. In contrast, PB cells of B-CLL and BM cells of B-ALL patients were characterized by a specific group distribution of the FLT values. The FLT of DAPI was divided into four subgroups, relative to 2.66 ns: short+, normal, prolonged, and prolonged+. These alterations could be related to different chromatin arrangements of B-CLL and B-ALL interphase nuclei. Notably, extremely long FLT of nuclear DAPI correlate with the presence of extra chromosome 12, while moderate increases compared to normal characterize the deletion of p53. Such correlations potentially enable a FLT-based rapid automatic diagnosis and classification of B-CLL even when the frequency of genetic and chromosomal abnormalities is low. © 2016 International Society for Advancement of Cytometry.

  20. 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).

  1. Efficient Fingercode Classification

    Science.gov (United States)

    Sun, Hong-Wei; Law, Kwok-Yan; Gollmann, Dieter; Chung, Siu-Leung; Li, Jian-Bin; Sun, Jia-Guang

    In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e. g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

  2. [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.

  3. 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...

  4. Discrimination and phylogenomic classification of Bacillus anthracis-cereus-thuringiensis strains based on LC-MS/MS analysis of whole cell protein digests.

    Science.gov (United States)

    Dworzanski, Jacek P; Dickinson, Danielle N; Deshpande, Samir V; Snyder, A Peter; Eckenrode, Brian A

    2010-01-01

    Modern taxonomy, diagnostics, and forensics of bacteria benefit from technologies that provide data for genome-based classification and identification of strains; however, full genome sequencing is still costly, lengthy, and labor intensive. Therefore, other methods are needed to estimate genomic relatedness among strains in an economical and timely manner. Although DNA-DNA hybridization and techniques based on genome fingerprinting or sequencing selected genes like 16S rDNA, gyrB, or rpoB are frequently used as phylogenetic markers, analyses of complete genome sequences showed that global measures of genome relatedness, such as the average genome conservation of shared genes, can provide better strain resolution and give phylogenies congruent with relatedness revealed by traditional phylogenetic markers. Bacterial genomes are characterized by a high gene density; therefore, we investigated the integration of mass spectrometry-based proteomic techniques with statistical methods for phylogenomic classification of bacterial strains. For this purpose, we used a set of well characterized Bacillus cereus group strains isolated from poisoned food to describe a method that relies on liquid chromatography-electrospray ionization-tandem mass spectrometry of tryptic peptides derived from whole cell digests. Peptides were identified and matched to a prototype database (DB) of reference bacteria with fully sequenced genomes to obtain their phylogenetic profiles. These profiles were processed for predicting genomic similarities with DB bacteria estimated by fractions of shared peptides (FSPs). FSPs served as descriptors for each food isolate and were jointly analyzed using hierarchical cluster analysis methods for revealing relatedness among investigated strains. The results showed that phylogenomic classification of tested food isolates was in consonance with results from established genomic methods, thus validating our findings. In conclusion, the proposed approach could be

  5. 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.

  6. 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....

  7. Human lymphocyte markers defined by antibodies derived from somatic cell hybrids. III. A marker defining a subpopulation of lymphocytes which cuts across the normal T-B-null classification.

    Science.gov (United States)

    Zola, H; Beckman, I G; Bradley, J; Brooks, D A; Kupa, A; McNamara, P J; Smart, I J; Thomas, M E

    1980-06-01

    A somatic cell hybrid line which secreted antibody reacting selectively with a proportion of the white cells in human blood was prepared. The hybridoma appeared to be monoclonal, and the antibody secreted stained 67% of the lymphocyte population in blood. It reacted less well with granulocytes and monocytes. The lymphocytes stained comprised 80% of the T cells and 50% of the B cells. The antibody showed no recognizable pattern in its reactivity with cell lines and leukaemic cells, although B cells tended to react less well than T cells, null cells, or myeloid leukaemic cells. The expression of the antigenic determinant is discussed in relation to the classification of leucocytes. This determinant and certain other markers exhibited differential expression on closely related cells, and yet were shared by more distantly related cells.

  8. Classification using Bayesian neural nets

    NARCIS (Netherlands)

    J.C. Bioch (Cor); O. van der Meer; R. Potharst (Rob)

    1995-01-01

    textabstractRecently, Bayesian methods have been proposed for neural networks to solve regression and classification problems. These methods claim to overcome some difficulties encountered in the standard approach such as overfitting. However, an implementation of the full Bayesian approach to neura

  9. Classification of Global Illumination Algorithms

    OpenAIRE

    Lesev, Hristo

    2010-01-01

    This article describes and classifies various approaches for solving the global illumination problem. The classification aims to show the similarities between different types of algorithms. We introduce the concept of Light Manager, as a central element and mediator between illumination algorithms in a heterogeneous environment of a graphical system. We present results and analysis of the implementation of the described ideas.

  10. Classification and disease prediction via mathematical programming

    Science.gov (United States)

    Lee, Eva K.; Wu, Tsung-Lin

    2007-11-01

    In this chapter, we present classification models based on mathematical programming approaches. We first provide an overview on various mathematical programming approaches, including linear programming, mixed integer programming, nonlinear programming and support vector machines. Next, we present our effort of novel optimization-based classification models that are general purpose and suitable for developing predictive rules for large heterogeneous biological and medical data sets. Our predictive model simultaneously incorporates (1) the ability to classify any number of distinct groups; (2) the ability to incorporate heterogeneous types of attributes as input; (3) a high-dimensional data transformation that eliminates noise and errors in biological data; (4) the ability to incorporate constraints to limit the rate of misclassification, and a reserved-judgment region that provides a safeguard against over-training (which tends to lead to high misclassification rates from the resulting predictive rule) and (5) successive multi-stage classification capability to handle data points placed in the reserved judgment region. To illustrate the power and flexibility of the classification model and solution engine, and its multigroup prediction capability, application of the predictive model to a broad class of biological and medical problems is described. Applications include: the differential diagnosis of the type of erythemato-squamous diseases; predicting presence/absence of heart disease; genomic analysis and prediction of aberrant CpG island meythlation in human cancer; discriminant analysis of motility and morphology data in human lung carcinoma; prediction of ultrasonic cell disruption for drug delivery; identification of tumor shape and volume in treatment of sarcoma; multistage discriminant analysis of biomarkers for prediction of early atherosclerois; fingerprinting of native and angiogenic microvascular networks for early diagnosis of diabetes, aging, macular

  11. 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.

  12. 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 L...

  13. MORPHOLOGICAL CLASSIFICATION OF RENAL-CANCER

    NARCIS (Netherlands)

    STORKEL, S; VANDENBERG, E

    1995-01-01

    The current classification of renal-cell adenomas (RCAs) and carcinomas (RCCs) is based on eight basic cell and tumor types (entities) with characteristic morphologic features: (1) RCCs of clear-cell type, (2) RCAs/RCCs of chromophilic-cell type, (3) RCAs/RCCs of chromophobic-cell type, (4) RCCs of

  14. 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

  15. Progress and Outlook for Silicon Solar Cell Process Technology (Environmental Problem)

    OpenAIRE

    永吉, 浩

    2000-01-01

    An over view of recent solar cell development program and Si solar cell process technology are presented. In the past 5 years, the PV production has drastically increased. To cover the large amount of PV demand in future, novel Si material production technology and development of the thin film Si cell technology are needed. To improve the efficiency of thin film Si cells, surface passivation technology will be more important. To improve the stability of a-Si : H solar cells, microcrystalline ...

  16. A comprehensive quadratic assignment problem for an integrated layout design of final assembly line and manufacturing feeder cells

    Directory of Open Access Journals (Sweden)

    Masoud Rabbani

    2017-04-01

    Full Text Available Assembly lines and cellular manufacturing systems (CMSs design have been widely used in the literature. However the integration of these manufacturing concepts is neglected in an environment where parts need to be assembled after production in different shops. In this paper, a comprehensive quadratic assignment problem is developed for the assignment of machines of each part manufacturing cell, sub-assembly tasks of each sub-assembly cell as well as the assignment of different cells and final assembly tasks within the shop floor in their relevant predetermined locations. A genetic algorithm (GA as well as a memetic algorithm (MA consisting of the proposed GA and Tabu search (TS algorithm are proposed and implemented on different size numerical examples. The obtained results show the efficiency of both algorithms to reach near optimal solutions compared to the optimal solution of small-sized problems.

  17. 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.

  18. 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....

  19. Kidney Problems

    Science.gov (United States)

    ... our e-newsletter! Aging & Health A to Z Kidney Problems Basic Facts & Information The kidneys are two ... the production of red blood cells. What are Kidney Diseases? For about one-third of older people, ...

  20. Battery engineering problems in designing an electrical load leveling plant for lithium/iron-sulfide cells

    Energy Technology Data Exchange (ETDEWEB)

    Zivi, S. M.; Pollack, I.; Kacinskas, H.; Chilenskas, A. A.; Barney, D. L.; Sudar, S.; Goldstein, I.; Grieve, W.

    1979-01-01

    The design of a lithium/iron sulfide battery for utility load leveling is strongly dependent on the energy capacity selected for the cells. Battery hardware costs are minimized by the selection of large cells, with 30-kWh cells being the largest that would be consistent with system constraints in a 100-MWh load leveling plant. However, it is anticipated that such large cells may be precluded by system reliability and maintainability considerations, and cell capacities on the order of 1 kWh may be needed to satisfy those requirements. Large cells can be protected against overcharge by electronically controlled charge equalization systems that have been developed for experimental eV batteries. The economics of electronically controlled equalization becomes unfavorable for small load-leveling cells; and if small cells are selected, it will be necessary to develop inherent protective means within each cell, with respect to overcharge.

  1. 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 ...

  2. Primary Nursing Problems in Community-dwelling Elderly Patients with Chronic Diseases Based on Omaha Problem Classification System%基于奥马哈问题分类系统的城市社区老年慢性病患者常见护理问题调查研究

    Institute of Scientific and Technical Information of China (English)

    芦秀燕; 苗秀欣; 王冉冉; 郭惠丽; 周爱霞

    2016-01-01

    目的:应用奥马哈问题分类系统探讨城市社区老年慢性病患者常见护理问题。方法以奥马哈问题分类系统为依据,对4个社区卫生服务中心2014年8月—2015年3月就诊的400例老年慢性病患者进行问卷调查,了解其存在的护理问题。结果400例城市社区老年慢性病患者共存在护理问题3013个,平均每例患者存在7.5个。发生率超过50.0%的护理问题是神经—肌肉—骨骼功能(71.0%)、消化水合(67.8%)、视力(57.8%)、口腔卫生(56.3%)、循环(51.0%),均属于生理领域;发生率为后4位的是哀伤(1.3%)、灵性(0.5%)、性(0.5%)、虐待(0.3%),均属于社会心理领域。结论城市社区老年慢性病患者存在的护理问题复杂、症状/征象多样,反映了老年慢性病患者护理问题存在的共性,社区护士可针对老年慢性病患者护理问题的发生规律进行针对性干预,提高社区护理的质量和效率。%Objective To explore primary nursing problems of community-dwelling elderly patients with chronic diseases with Omaha problem classification system. Methods Based on Omaha problem classification system, a questionnaire was applied to collect and summarize nursing problems from 400 community-dwelling elderly patients with chronic diseases to find primary ones. Results There were 3,013 nursing problems and those with incidence more than 50.0% were from biological field such as neuro-musculo-skeletal function(71.0%),digestion-hydration(67.8%), vision (57.8%), oral hygiene(56.3%), circulation(51.0%). Nursing problems ranking the last four were sadness (1.3%), spirit (0.5%), sex (0.5%) and abuse (0.3%), which were from social psychological field. Conclusion There are complicated nursing problems with diverse symptoms/signs among community-dwelling elderly patients with chronic diseases, and targeted nursing intervention will benefit the improvement of the quality and

  3. 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.

  4. XT-2000i血细胞分析仪白细胞分类异常报警的临床分析%Clinical analysis of abnormal alarm in white blood cell classification of XE-2000i blood cell analyzer

    Institute of Scientific and Technical Information of China (English)

    张书永

    2013-01-01

    Objective: To investigate the Sysmex XE-2000i blood cell analyzer leukocyte classification anomaly reliability. Methods; Random XT-2000i detected no abnormal alarm specimens in 300 cases and abnormal alarm specimens from 285 patients, respectively, making blood smears with Wright's staining after artificial microscopy, analytical instruments detection results with artificial microscopy results the coincidence rate. Results: XT-2000i blood cell analyzer for alarm and manual analysis of abnormal cells positive rate was 73.3%, no abnormal alarm apparatus and its classification and artificial microscopy are basically the same, with the rate of 99%. Conclusion: XT-2000i blood cell analyzer as a morphologic abnormalities warnings of the initial screening tools, high sensitivity, white blood cell classification without abnormal alarm when the result is credible, abnormal alarm and declaration nuclear cell high alarm specimens should be artificial lens review.%目的:探讨sysmex XT-2000i血细胞分析仪白细胞分类异常报警的可靠性.方法:随机抽取XT-2000i检测无异常报警标本300例及异常报警标本285例,分别制作血涂片经瑞氏染色后人工镜检,分析仪器检测结果与人工镜检结果的符合率.结果:XT-2000i血细胞分析仪对异常细胞报警与人工分析阳性符合率为73.3%,仪器无异常报警时其分类与人工镜检基本一致,符合率为99%.结论:XT-2000i血液细胞分析仪作为异常细胞报警的初筛工具,灵敏度极高,白细胞分类无异常报警时结果可信,有异常报警及报单核细胞过高报警的标本应人工镜检复查.

  5. 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.

  6. Learning to recognise : a study on one-class classification and active learning

    NARCIS (Netherlands)

    Juszczak, P.

    2006-01-01

    The thesis treats classification problems which are undersampled or where there exist an unbalance between classes in the sampling. The thesis is divided into three parts. The first two parts treat the problem of one-class classification. In the one-class classification problem, it is assumed that o

  7. 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...

  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...

  9. 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...

  10. Development and validation of Raman spectroscopic classification models to discriminate tongue squamous cell carcinoma from non-tumorous tissue

    NARCIS (Netherlands)

    F.L.J. Cals; S. Koljenovic (Senada); J.A.U. Hardillo (José); R.J. Baatenburg de Jong (Robert Jan); T.C. Bakker Schut (Tom); G.J. Puppels (Gerwin)

    2016-01-01

    markdownabstractBackground Currently, up to 85% of the oral resection specimens have inadequate resection margins, of which the majority is located in the deeper soft tissue layers. The prognosis of patients with oral cavity squamous cell carcinoma (OCSCC) of the tongue is negatively affected by the

  11. 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.

  12. 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.

  13. Multi-Level Audio Classification Architecture

    Directory of Open Access Journals (Sweden)

    Jozef Vavrek

    2015-01-01

    Full Text Available A multi-level classification architecture for solving binary discrimination problem is proposed in this paper. The main idea of proposed solution is derived from the fact that solving one binary discrimination problem multiple times can reduce the overall miss-classification error. We aimed our effort towards building the classification architecture employing the combination of multiple binary SVM (Support Vector Machine classifiers for solving two-class discrimination problem. Therefore, we developed a binary discrimination architecture employing the SVM classifier (BDASVM with intention to use it for classification of broadcast news (BN audio data. The fundamental element of BDASVM is the binary decision (BD algorithm that performs discrimination between each pair of acoustic classes utilizing decision function modeled by separating hyperplane. The overall classification accuracy is conditioned by finding the optimal parameters for discrimination function resulting in higher computational complexity. The final form of proposed BDASVM is created by combining four BDSVM discriminators supplemented by decision table. Experimental results show that the proposed classification architecture can decrease the overall classification error in comparison with binary decision trees SVM (BDTSVM architecture.

  14. [The problems of yolk sac tumor morphogenesis in a light of the tumor stem cell theory].

    Science.gov (United States)

    Karseladze, A I

    2011-01-01

    The analysis of possible morphogenesis of the different structures in human yolk sac tumor has been considered. The author has supposed that features of blood vessel microarchitecture formation and perpetual differentiation of tumor cells or theirs functional modification play a crucial role in the morphogenesis of YST. The immunohistochemical investigation of some stem cells markers has showed the necessity of accounting of their distribution pattern in various cellular structures for the differential diagnosis of morphogenetical steps of YST. The growth of tumor cells differentiation rate correlates with increasing of stem cells markers expression as well c-kit > OCT4 > CD30 > PLAP.

  15. CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. B. Popova

    2016-01-01

    Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

  16. 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,…

  17. 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.

  18. 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

  19. Spectral Classification Beyond M

    CERN Document Server

    Leggett, S K; Burgasser, A J; Jones, H R A; Marley, M S; Tsuji, T

    2004-01-01

    Significant populations of field L and T dwarfs are now known, and we anticipate the discovery of even cooler dwarfs by Spitzer and ground-based infrared surveys. However, as the number of known L and T dwarfs increases so does the range in their observational properties, and difficulties have arisen in interpreting the observations. Although modellers have made significant advances, the complexity of the very low temperature, high pressure, photospheres means that problems remain such as the treatment of grain condensation as well as incomplete and non-equilibrium molecular chemistry. Also, there are several parameters which control the observed spectral energy distribution - effective temperature, grain sedimentation efficiency, metallicity and gravity - and their effects are not well understood. In this paper, based on a splinter session, we discuss classification schemes for L and T dwarfs, their dependency on wavelength, and the effects of the parameters T_eff, f_sed, [m/H] and log g on optical and infra...

  20. 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.

  1. 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.

  2. CD13-positive anaplastic large cell lymphoma of T-cell origin--a diagnostic and histogenetic problem.

    Science.gov (United States)

    Popnikolov, N K; Payne, D A; Hudnall, S D; Hawkins, H K; Kumar, M; Norris, B A; Elghetany, M T

    2000-12-01

    The expression of myelomonocytic-associated antigens in anaplastic large cell lymphomas (ALCLs), particularly those presenting in extranodal sites, can make their distinction from extramedullary myeloid cell tumors (EMCTs) or histiocytic tumors problematic. Yet, this distinction is clinically significant because of its therapeutic and prognostic implications. Herein, we describe a case of extranodal anaplastic lymphoma kinase-positive CD30-positive ALCL of T-cell origin in a 12-year-old boy, which was initially called an EMCT because of the expression of CD13 and HLA-DR detected by flow cytometry and the absence of other T-cell-related surface markers. However, the detection of cytoplasmic CD3 by flow cytometry prompted further studies. The tumor was composed of large cells with abundant slightly eosinophilic vacuolated cytoplasm and ovoid or reniform nuclei with a few small nucleoli. Using immunohistochemistry, the tumor was positive for CD45, CD30, CD45RO, and CD43 with a strong cytoplasmic and nuclear anaplastic lymphoma kinase stain. The tumor cells showed a T-cell clonal genotype. Electron microscopy revealed no ultrastructural features of myelomonocytic or histiocytic origin. The patient responded well to the chemotherapy and was in complete remission for 10 months at the time of submission of this manuscript. Review of the literature showed inconsistencies regarding the diagnosis, nomenclature, and, therefore, treatment and prognosis of these tumors. In addition, the CD13 expression in ALCL raises some histogenetic questions and may indicate origin from a pluripotent stem cell, misprogramming during malignant transformation, or a microenvironmental effect on lymphoid cell expression of surface antigens. Therefore, ALCL should be considered in the differential diagnosis of EMCTs or histiocytic tumors, particularly when surface marker lineage assignment is ambiguous.

  3. Warty (condylomatous) squamous cell carcinoma of the penis: a report of 11 cases and proposed classification of 'verruciform' penile tumors.

    Science.gov (United States)

    Cubilla, A L; Velazques, E F; Reuter, V E; Oliva, E; Mihm, M C; Young, R H

    2000-04-01

    Within the spectrum of penile squamous cell carcinomas, those that we descriptively refer to collectively as the "verruciform" lesions are particularly difficult to subclassify. In a review of 50 such tumors, we found 11 distinctive neoplasms with condylomatous features conforming to the appearance of so-called "warty (condylomatous) carcinoma." The average patient age was 55 years and the average duration of disease was 19 months. The primary tumor involved multiple anatomic sites (glans, coronal sulcus, and foreskin) in seven cases and a single site (glans or foreskin) in four cases. Grossly, white to gray cauliflower-like tumors typically measuring approximately 5 cm were noted. Histologically the tumors were mainly papillomatous with acanthosis and hyperkeratosis. The papillae had prominent fibrovascular cores. The most conspicuous microscopic findings were striking nuclear atypia of koilocytotic type and clear cytoplasm. The interface between tumor and stroma was irregular in the majority of cases; deep invasion of corpus cavernosum was noted in five cases. The differential diagnosis included verrucous carcinoma, low-grade papillary squamous cell carcinoma, not otherwise specified, and giant condyloma acuminatum. Among other differences, the first two lesions show no koilocytotic changes and the last lacks malignant features and irregular stromal invasion. Metastatic spread occurred in two patients; both are alive with evidence of recurrent disease 12 and 72 months after initial diagnosis. A third patient was alive with recurrent disease 12 months after diagnosis. Five patients were free of disease 8, 12, 24, 52, and 108 months after diagnosis. Three patients were lost to follow up. Warty (condylomatous) carcinomas of the penis are morphologically distinctive verruciform neoplasms with features of human papillomavirus-related lesions and should be distinguished from other verruciform tumors so that differences in behavior, if any, between these tumors will

  4. Hyperspectral image classification using functional data analysis.

    Science.gov (United States)

    Li, Hong; Xiao, Guangrun; Xia, Tian; Tang, Y Y; Li, Luoqing

    2014-09-01

    The large number of spectral bands acquired by hyperspectral imaging sensors allows us to better distinguish many subtle objects and materials. Unlike other classical hyperspectral image classification methods in the multivariate analysis framework, in this paper, a novel method using functional data analysis (FDA) for accurate classification of hyperspectral images has been proposed. The central idea of FDA is to treat multivariate data as continuous functions. From this perspective, the spectral curve of each pixel in the hyperspectral images is naturally viewed as a function. This can be beneficial for making full use of the abundant spectral information. The relevance between adjacent pixel elements in the hyperspectral images can also be utilized reasonably. Functional principal component analysis is applied to solve the classification problem of these functions. Experimental results on three hyperspectral images show that the proposed method can achieve higher classification accuracies in comparison to some state-of-the-art hyperspectral image classification methods.

  5. 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. 

  6. 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

  7. Gene selection and cancer type classification of diffuse large-B-cell lymphoma using a bivariate mixture model for two-species data.

    Science.gov (United States)

    Su, Yuhua; Nielsen, Dahlia; Zhu, Lei; Richards, Kristy; Suter, Steven; Breen, Matthew; Motsinger-Reif, Alison; Osborne, Jason

    2013-01-05

    : 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 serve as a good predictor for classifying diffuse large-B-cell lymphoma (DLBCL) patients into two subgroups, the germinal center B-cell-like diffuse large B-cell lymphoma and the activated B-cell-like diffuse large B-cell lymphoma. The number of human genes that were observed to be significantly differentially expressed (21) from the two-species analysis was very small compared to the number of human genes (190) identified with only one-species analysis (human data). The genes may be clinically relevant/important, as this small set achieved low misclassification rates of DLBCL subtypes. Additionally, the two subgroups defined by this cluster of human genes had significantly different survival functions, indicating that the stratification based on gene-expression profiling using the proposed mixture model provided improved insight into the clinical differences between the two cancer subtypes.

  8. Parallel local search for solving Constraint Problems on the Cell Broadband Engine (Preliminary Results)

    CERN Document Server

    Abreu, Salvator; Codognet, Philippe

    2009-01-01

    We explore the use of the Cell Broadband Engine (Cell/BE for short) for combinatorial optimization applications: we present a parallel version of a constraint-based local search algorithm that has been implemented on a multiprocessor BladeCenter machine with twin Cell/BE processors (total of 16 SPUs per blade). This algorithm was chosen because it fits very well the Cell/BE architecture and requires neither shared memory nor communication between processors, while retaining a compact memory footprint. We study the performance on several large optimization benchmarks and show that this achieves mostly linear time speedups, even sometimes super-linear. This is possible because the parallel implementation might explore simultaneously different parts of the search space and therefore converge faster towards the best sub-space and thus towards a solution. Besides getting speedups, the resulting times exhibit a much smaller variance, which benefits applications where a timely reply is critical.

  9. Parallel local search for solving Constraint Problems on the Cell Broadband Engine (Preliminary Results

    Directory of Open Access Journals (Sweden)

    Salvator Abreu

    2009-10-01

    Full Text Available We explore the use of the Cell Broadband Engine (Cell/BE for short for combinatorial optimization applications: we present a parallel version of a constraint-based local search algorithm that has been implemented on a multiprocessor BladeCenter machine with twin Cell/BE processors (total of 16 SPUs per blade. This algorithm was chosen because it fits very well the Cell/BE architecture and requires neither shared memory nor communication between processors, while retaining a compact memory footprint. We study the performance on several large optimization benchmarks and show that this achieves mostly linear time speedups, even sometimes super-linear. This is possible because the parallel implementation might explore simultaneously different parts of the search space and therefore converge faster towards the best sub-space and thus towards a solution. Besides getting speedups, the resulting times exhibit a much smaller variance, which benefits applications where a timely reply is critical.

  10. 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.…

  11. Unbounded Periodic Solutions to Serrin's Overdetermined Boundary Value Problem

    Science.gov (United States)

    Fall, Mouhamed Moustapha; Minlend, Ignace Aristide; Weth, Tobias

    2017-02-01

    We study the existence of nontrivial unbounded domains {Ω} in RN such that the overdetermined problem {-Δ u = 1 quad in Ω}, quad u = 0, quad partial_{ν} u = const quad on partial Ω admits a solution u. By this, we complement Serrin's classification result from 1971, which yields that every bounded domain admitting a solution of the above problem is a ball in RN. The domains we construct are periodic in some variables and radial in the other variables, and they bifurcate from a straight (generalized) cylinder or slab. We also show that these domains are uniquely self Cheeger relative to a period cell for the problem.

  12. Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification

    Science.gov (United States)

    Hepner, George F.; Logan, Thomas; Ritter, Niles; Bryant, Nevin

    1990-01-01

    Recent research has shown an artificial neural network (ANN) to be capable of pattern recognition and the classification of image data. This paper examines the potential for the application of neural network computing to satellite image processing. A second objective is to provide a preliminary comparison and ANN classification. An artificial neural network can be trained to do land-cover classification of satellite imagery using selected sites representative of each class in a manner similar to conventional supervised classification. One of the major problems associated with recognition and classifications of pattern from remotely sensed data is the time and cost of developing a set of training sites. This reseach compares the use of an ANN back propagation classification procedure with a conventional supervised maximum likelihood classification procedure using a minimal training set. When using a minimal training set, the neural network is able to provide a land-cover classification superior to the classification derived from the conventional classification procedure. This research is the foundation for developing application parameters for further prototyping of software and hardware implementations for artificial neural networks in satellite image and geographic information processing.

  13. 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...... an instance are conditionally independent given the class of that instance. When this assumption is violated (which is often the case in practice) it can reduce classification accuracy due to “information double-counting” and interaction omission. In this paper we focus on a relatively new set of models...... in the context of classification. Experimental results show that the learned models can significantly improve classification accuracy as compared to other frameworks....

  14. 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.

  15. On classification of dynamical r-matrices

    CERN Document Server

    Schiffmann, O

    1997-01-01

    Using recent results of P. Etingof and A. Varchenko on the Classical Dynamical Yang-Baxter equation, we reduce the classification of dynamical r-matrices on a commutative subalgebra l of a Lie algebra g to a purely algebraic problem when l admits a g^l-invariant complement, where g^l is the centralizer of l in g. Using this, we then classify all non skew-symmetric dynamical r-matrices when g is a simple Lie algebra and l a commutative subalgebra containing a regular semisimple element. This partially answers an open problem in [EV] q-alg/9703040, and generalizes the Belavin-Drinfled classification of constant r-matrices. This classification is similar and in some sense simpler than the Belavin-Drinfled classification.

  16. 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

  17. 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

  18. 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.

  19. Classification of cultivated plants.

    NARCIS (Netherlands)

    Brandenburg, W.A.

    1986-01-01

    Agricultural practice demands principles for classification, starting from the basal entity in cultivated plants: the cultivar. In establishing biosystematic relationships between wild, weedy and cultivated plants, the species concept needs re-examination. Combining of botanic classification, based

  20. Neural network technologies for image classification

    Science.gov (United States)

    Korikov, A. M.; Tungusova, A. V.

    2015-11-01

    We analyze the classes of problems with an objective necessity to use neural network technologies, i.e. representation and resolution problems in the neural network logical basis. Among these problems, image recognition takes an important place, in particular the classification of multi-dimensional data based on information about textural characteristics. These problems occur in aerospace and seismic monitoring, materials science, medicine and other. We reviewed different approaches for the texture description: statistical, structural, and spectral. We developed a neural network technology for resolving a practical problem of cloud image classification for satellite snapshots from the spectroradiometer MODIS. The cloud texture is described by the statistical characteristics of the GLCM (Gray Level Co- Occurrence Matrix) method. From the range of neural network models that might be applied for image classification, we chose the probabilistic neural network model (PNN) and developed an implementation which performs the classification of the main types and subtypes of clouds. Also, we chose experimentally the optimal architecture and parameters for the PNN model which is used for image classification.

  1. Resolution-limited statistical image classification

    Science.gov (United States)

    Elbaum, Marek; Syrkin, Mark

    1993-09-01

    We have examined the performance of a one-layer Perceptron for the detection and classification of small (resolution-limited) targets from their images, which are stochastic realizations of random processes. The processes are governed by non-Gaussian, non-white distributions. Our results show the potential of the Perceptron classifier as an Ideal Observer and suggest image detection and classification problems for which neural networks may be more reliable than human observers.

  2. Support Vector Machines for Pattern Classification

    CERN Document Server

    Abe, Shigeo

    2010-01-01

    A guide on the use of SVMs in pattern classification, including a rigorous performance comparison of classifiers and regressors. The book presents architectures for multiclass classification and function approximation problems, as well as evaluation criteria for classifiers and regressors. Features: Clarifies the characteristics of two-class SVMs; Discusses kernel methods for improving the generalization ability of neural networks and fuzzy systems; Contains ample illustrations and examples; Includes performance evaluation using publicly available data sets; Examines Mahalanobis kernels, empir

  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. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Therapeutic hope, spiritual distress, and the problem of stem cell tourism.

    Science.gov (United States)

    Hyun, Insoo

    2013-05-02

    Managing patients' therapeutic hope and spiritual distress-in addition to tighter regulation of commercial therapies and improved patient understanding-may offer a more comprehensive approach to reducing the overall incidence of stem cell tourism. Such patient support must occur early in the clinical relationship after appropriate assessment and discussion.

  9. 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…

  10. 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…

  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. 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…

  13. 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.

  14. Parallel Symmetric Eigenvalue Problem Solvers

    Science.gov (United States)

    2015-05-01

    Plemmons G. Golub and A. Sameh. High-speed computing : scientific appli- cations and algorithm design. University of Illinois Press, Champaign, Illinois , 1988...16. SECURITY CLASSIFICATION OF: Sparse symmetric eigenvalue problems arise in many computational science and engineering applications such as...Eigenvalue Problem Solvers Report Title Sparse symmetric eigenvalue problems arise in many computational science and engineering applications such as

  15. The CHAT classification of stroke.

    Science.gov (United States)

    Bernstein, E F; Browse, N L

    1989-02-01

    Current terminology for clinical episodes relating to stroke is inconsistent and unclear, does not permit inclusion of data regarding the location and magnitude of extracranial and intracerebral arterial disease, does not coincide with existing classifications in Europe, and characterizes a hemispheric entity only, as opposed to a global description including prior symptoms in both hemispheres. A new classification system (CHAT) has been designed to deal with these problems, including the current clinical presentation, historical clinical episodes, the site and pathologic type of arterial disease, and information regarding abnormalities of the brain. Using this system, a retrospective review of 480 consecutive carotid endarterectomies is presented, demonstrating the advantages of the CHAT classification. Data include a significant difference in the probability of survival after carotid endarterectomy for asymptomatic stenosis in patients with prior symptoms on the opposite side, as well as a significant difference in the probability of stroke-free survival between patients with amaurosis fugax and those with prior carotid cortical symptoms (TIAs) as the presenting clinical condition. The CHAT classification is suggested as a significant advance in the reporting of all surgical cerebrovascular disease experience, and has particular implications for the current randomized trials between medical and surgical therapy for carotid artery disease.

  16. 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…

  17. On China’s Ethnological Bibliography Classification and Its Problems---With Mongolian,Manchu Bibliography As a Focus%试论民族文字文献目录分类法及其存在的问题--以蒙古文、满文文献目录为中心

    Institute of Scientific and Technical Information of China (English)

    乌兰其木格

    2013-01-01

    T he ethnological bibliography classification and cataloging started since the founding of new China .There developed many classification methods during the half century .This paper will refer to the previous studies and have a brief analysis and exploration on the classification method and the existing problems of Manchu and Mongolian bibliography .This paper takes that until now there is not a united classification method on ethnological bibliography and this paper also points out the inaccuracy of some bibliography classification .%中国国内民族文献分类和编目工作主要开始于新中国成立以后,到目前为止经历了半个多世纪的发展过程,出现了诸多分类方法。本文结合前人有关研究成果,以国内部分民族文字文献目录为例,主要对现有满文、蒙古文文献目录分类方法及其存在的问题进行了简要的分析、探讨和论述,认为到目前为止,中国国内民族文献尚无统一的分类法,并且指出了部分文献目录分类中存在的不准确或不妥之处。

  18. Minimally-sized balanced decomposition schemes for multi-class classification

    NARCIS (Netherlands)

    Smirnov, E.N.; Moed, M.; Nalbantov, G.I.; Sprinkhuizen-Kuyper, I.G.

    2011-01-01

    Error-Correcting Output Coding (ECOC) is a well-known class of decomposition schemes for multi-class classification. It allows representing any multiclass classification problem as a set of binary classification problems. Due to code redundancy ECOC schemes can significantly improve generalization p

  19. 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.

  20. [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.

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

    KAUST Repository

    Shono, Ahmad N.

    2014-05-01

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

  2. Random forest classification of etiologies for an orphan disease.

    Science.gov (United States)

    Speiser, Jaime Lynn; Durkalski, Valerie L; Lee, William M

    2015-02-28

    Classification of objects into pre-defined groups based on known information is a fundamental problem in the field of statistics. Although approaches for solving this problem exist, finding an accurate classification method can be challenging in an orphan disease setting, where data are minimal and often not normally distributed. The purpose of this paper is to illustrate the application of the random forest (RF) classification procedure in a real clinical setting and discuss typical questions that arise in the general classification framework as well as offer interpretations of RF results. This paper includes methods for assessing predictive performance, importance of predictor variables, and observation-specific information.

  3. 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.

  4. Classification of Sets using Restricted Boltzmann Machines

    CERN Document Server

    Louradour, Jérôme

    2011-01-01

    We consider the problem of classification when inputs correspond to sets of vectors. This setting occurs in many problems such as the classification of pieces of mail containing several pages, of web sites with several sections or of images that have been pre-segmented into smaller regions. We propose generalizations of the restricted Boltzmann machine (RBM) that are appropriate in this context and explore how to incorporate different assumptions about the relationship between the input sets and the target class within the RBM. In experiments on standard multiple-instance learning datasets, we demonstrate the competitiveness of approaches based on RBMs and apply the proposed variants to the problem of incoming mail classification.

  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. 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.

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

    Directory of Open Access Journals (Sweden)

    Bingbing Xia

    2016-01-01

    Full Text Available 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 Cooccurrence 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.

  8. On the problem of slipper shapes of red blood cells in the microvasculature.

    Science.gov (United States)

    Tahiri, N; Biben, T; Ez-Zahraouy, H; Benyoussef, A; Misbah, C

    2013-01-01

    Red blood cells (RBC) are known to exhibit non symmetric (slipper) shapes in the microvasculature. Vesicles have been recently used as a model for RBC and numerical simulations proved the existence of slipper shapes under Poiseuille flow (both in unconfined and confined geometry). However, in our recent numerical simulations the transition from symmetric (parachute) shape to the slipper one was found to take place upon decreasing the flow strength, while experiments on RBCs showed the contrary. In this work we show that if the viscosity contrast (ratio between the internal over external fluid viscosities) is different from unity, as is the case with RBCs, the transition from parachute to slipper shape occurs upon increasing the flow strength, in agreement with experiments. We provide the phase diagram of shapes in the microcirculation. The slipper is found to have a higher speed than the parachute (for the same parameters), that we believe to be the basic reason for its prevailing in the microvasculature. We provide a simple geometrical picture that explains the slipper flow efficiency over the parachute one. Finally, we show that there exists in parameter space regions of co-existence of slipper/parachute shapes and suggest simple experimental protocols to test these findings. The coexistence of shapes seems to be supported by experiments, though a systematic experimental study is lacking. A potential application of this work is to guide designing flow-based experiments in order to link the shape of RBCs to pathologies affecting cell deformability, such as sickle cell diseases, malaria, and those affecting blood hematocrit, as in polycythemia vera disease.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1989-09-01

    Certain governmental information must be classified for national security reasons. However, the national security benefits from classifying information are usually accompanied by significant costs -- those due to a citizenry not fully informed on governmental activities, the extra costs of operating classified programs and procuring classified materials (e.g., weapons), the losses to our nation when advances made in classified programs cannot be utilized in unclassified programs. The goal of a classification system should be to clearly identify that information which must be protected for national security reasons and to ensure that information not needing such protection is not classified. This document was prepared to help attain that goal. This document is the first of a planned four-volume work that comprehensively discusses the security classification of information. Volume 1 broadly describes the need for classification, the basis for classification, and the history of classification in the United States from colonial times until World War 2. Classification of information since World War 2, under Executive Orders and the Atomic Energy Acts of 1946 and 1954, is discussed in more detail, with particular emphasis on the classification of atomic energy information. Adverse impacts of classification are also described. Subsequent volumes will discuss classification principles, classification management, and the control of certain unclassified scientific and technical information. 340 refs., 6 tabs.

  15. 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.

  16. 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.

  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. 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.

  19. [D-cells of the gastroenteropancreatic system: development, structure, function and regeneration (history and current state of the problem)].

    Science.gov (United States)

    Ivanova, V F; Kostiukevich, S V

    2015-01-01

    The present review summarizes the literature data and the results of authors' own research on the development, structure, function and regeneration of D-endocrinocytes of gastroenteropancreatic (GEP) system. The history of the research of these cells is reviewed and its current state of the problem is discussed. The information on the difference of somatostatin-producing D-endocrinocytes from other types of endocrine cells of GAP system is presented, namely, the prevalence of these cells in all the organs of the digestive system (stomach, small and large intestine, pancreas) and other systems of the body, the peculiarities of their structure and regeneration in various species of vertebrate animals and humans in embryonic development, under conditions of normal functioning and in various types of pathology. On the basis of the data on the early differentiation of D-endocrinocytes and their secretion of hormones during embryonic development, structure, cytophysiology and relationships within the general endocrinocyte population, it is suggested that D-endocrinocytes play an important role in the morpho-functional state of GEP system.

  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 d...... classification systems and meta data taxonomies, should be based on ontologies.......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...

  1. Compressed classification learning with Markov chain samples.

    Science.gov (United States)

    Cao, Feilong; Dai, Tenghui; Zhang, Yongquan; Tan, Yuanpeng

    2014-02-01

    In this article, we address the problem of compressed classification learning. A generalization bound of the support vector machines (SVMs) compressed classification algorithm with uniformly ergodic Markov chain samples is established. This bound indicates that the accuracy of the SVM classifier in the compressed domain is close to that of the best classifier in the data domain. In a sense, the fact that the compressed learning can avoid the curse of dimensionality in the learning process is shown. In addition, we show that compressed classification learning reduces the learning time at the price of decreasing the classification accuracy, but the decrement can be controlled. The numerical experiments further verify the results claimed in this article.

  2. Information gathering for CLP classification

    OpenAIRE

    Ida Marcello; Felice Giordano; Francesca Marina Costamagna

    2011-01-01

    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 requireme...

  3. Radar clutter classification

    Science.gov (United States)

    Stehwien, Wolfgang

    1989-11-01

    The problem of classifying radar clutter as found on air traffic control radar systems is studied. An algorithm based on Bayes decision theory and the parametric maximum a posteriori probability classifier is developed to perform this classification automatically. This classifier employs a quadratic discriminant function and is optimum for feature vectors that are distributed according to the multivariate normal density. Separable clutter classes are most likely to arise from the analysis of the Doppler spectrum. Specifically, a feature set based on the complex reflection coefficients of the lattice prediction error filter is proposed. The classifier is tested using data recorded from L-band air traffic control radars. The Doppler spectra of these data are examined; the properties of the feature set computed using these data are studied in terms of both the marginal and multivariate statistics. Several strategies involving different numbers of features, class assignments, and data set pretesting according to Doppler frequency and signal to noise ratio were evaluated before settling on a workable algorithm. Final results are presented in terms of experimental misclassification rates and simulated and classified plane position indicator displays.

  4. 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.

  5. 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

  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. 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...

  8. Web Classification Using DYN FP Algorithm

    Directory of Open Access Journals (Sweden)

    Bhanu Pratap Singh

    2014-01-01

    Full Text Available Web mining is the application of data mining techniques to extract knowledge from Web. Web mining has been explored to a vast degree and different techniques have been proposed for a variety of applications that includes Web Search, Classification and Personalization etc. The primary goal of the web site is to provide the relevant information to the users. Web mining technique is used to categorize users and pages by analyzing users behavior, the content of pages and order of URLs accessed. In this paper, proposes an auto-classification algorithm of web pages using data mining techniques. The problem of discovering association rules between terms in a set of web pages belonging to a category in a search engine database, and present an auto – classification algorithm for solving this problem that are fundamentally based on FP-growth algorithm

  9. Classification of Subcellular Phenotype Images by Decision Templates for Classifier Ensemble

    Science.gov (United States)

    Zhang, Bailing

    2010-01-01

    Subcellular localization is a key functional characteristic of proteins. An automatic, reliable and efficient prediction system for protein subcellular localization is needed for large-scale genome analysis. The automated cell phenotype image classification problem is an interesting "bioimage informatics" application. It can be used for establishing knowledge of the spatial distribution of proteins within living cells and permits to screen systems for drug discovery or for early diagnosis of a disease. In this paper, three well-known texture feature extraction methods including local binary patterns (LBP), Gabor filtering and Gray Level Coocurrence Matrix (GLCM) have been applied to cell phenotype images and the multiple layer perceptron (MLP) method has been used to classify cell phenotype image. After classification of the extracted features, decision-templates ensemble algorithm (DT) is used to combine base classifiers built on the different feature sets. Different texture feature sets can provide sufficient diversity among base classifiers, which is known as a necessary condition for improvement in ensemble performance. For the HeLa cells, the human classification error rate on this task is of 17% as reported in previous publications. We obtain with our method an error rate of 4.8%.

  10. Accurate and interpretable classification of microspectroscopy pixels using artificial neural networks.

    Science.gov (United States)

    Manescu, Petru; Jong Lee, Young; Camp, Charles; Cicerone, Marcus; Brady, Mary; Bajcsy, Peter

    2017-04-01

    This paper addresses the problem of classifying materials from microspectroscopy at a pixel level. The challenges lie in identifying discriminatory spectral features and obtaining accurate and interpretable models relating spectra and class labels. We approach the problem by designing a supervised classifier from a tandem of Artificial Neural Network (ANN) models that identify relevant features in raw spectra and achieve high classification accuracy. The tandem of ANN models is meshed with classification rule extraction methods to lower the model complexity and to achieve interpretability of the resulting model. The contribution of the work is in designing each ANN model based on the microspectroscopy hypothesis about a discriminatory feature of a certain target class being composed of a linear combination of spectra. The novelty lies in meshing ANN and decision rule models into a tandem configuration to achieve accurate and interpretable classification results. The proposed method was evaluated using a set of broadband coherent anti-Stokes Raman scattering (BCARS) microscopy cell images (600 000  pixel-level spectra) and a reference four-class rule-based model previously created by biochemical experts. The generated classification rule-based model was on average 85% accurate measured by the DICE pixel label similarity metric, and on average 96% similar to the reference rules measured by the vector cosine metric.

  11. Data Mining Algorithms for Classification of Complex Biomedical Data

    Science.gov (United States)

    Lan, Liang

    2012-01-01

    In my dissertation, I will present my research which contributes to solve the following three open problems from biomedical informatics: (1) Multi-task approaches for microarray classification; (2) Multi-label classification of gene and protein prediction from multi-source biological data; (3) Spatial scan for movement data. In microarray…

  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. 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…

  14. 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.

  15. On-line probabilistic classification with particle filters

    DEFF Research Database (Denmark)

    Højen-Sørensen, Pedro; de Freitas, N.; Fog, Torben L.

    2000-01-01

    We apply particle filters to the problem of on-line classification with possibly overlapping classes. This allows us to compute the probabilities of class membership as the classes evolve. Although we adopt neural network classifiers, the work can be extended to any other parametric classification...

  16. 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…

  17. 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.

  18. Multiple sparse representations classification

    NARCIS (Netherlands)

    E. Plenge (Esben); S.K. Klein (Stefan); W.J. Niessen (Wiro); E. Meijering (Erik)

    2015-01-01

    textabstractSparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In t

  19. 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…

  20. 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.

  1. Intelligent Classification in Huge Heterogeneous Data Sets

    Science.gov (United States)

    2015-06-01

    pursued. An efficient algorithm for approximating Dantzig selectors, which provide sparse minimal l1-norm vectors solving a linear regression problem...SUBJECT TERMS Machine Learning, Supervised Classification, Principal Component Analysis , Compressed Sensing, Pattern Recognition 16. SECURITY... Introduction 1 3 Methods, Assumptions, and Procedures 2 4 Results and Discussion 3 4.1 Algorithm to Approximate the Dantzig Selector

  2. Classifier in Age classification

    Directory of Open Access Journals (Sweden)

    B. Santhi

    2012-12-01

    Full Text Available Face is the important feature of the human beings. We can derive various properties of a human by analyzing the face. The objective of the study is to design a classifier for age using facial images. Age classification is essential in many applications like crime detection, employment and face detection. The proposed algorithm contains four phases: preprocessing, feature extraction, feature selection and classification. The classification employs two class labels namely child and Old. This study addresses the limitations in the existing classifiers, as it uses the Grey Level Co-occurrence Matrix (GLCM for feature extraction and Support Vector Machine (SVM for classification. This improves the accuracy of the classification as it outperforms the existing methods.

  3. 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.

  4. 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…

  5. Kappa Coefficients for Circular Classifications

    NARCIS (Netherlands)

    Warrens, Matthijs J.; Pratiwi, Bunga C.

    2016-01-01

    Circular classifications are classification scales with categories that exhibit a certain periodicity. Since linear scales have endpoints, the standard weighted kappas used for linear scales are not appropriate for analyzing agreement between two circular classifications. A family of kappa coefficie

  6. 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.

  7. [Idiopathic epiretinal membrane: definition, classification, current understanding of pathogenesis].

    Science.gov (United States)

    Ponomareva, E N; Kazarian, A A

    2014-01-01

    Idiopathic epiretinal membrane is a result of a complex biomechanical interaction of the retina and vitreous. This paper discusses classification problems, epidemiological data of multicenter studies, and current hypotheses of epiretinal membrane pathogenesis.

  8. 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

  9. Distance-based features in pattern classification

    Directory of Open Access Journals (Sweden)

    Lin Wei-Yang

    2011-01-01

    Full Text Available Abstract In data mining and pattern classification, feature extraction and representation methods are a very important step since the extracted features have a direct and significant impact on the classification accuracy. In literature, numbers of novel feature extraction and representation methods have been proposed. However, many of them only focus on specific domain problems. In this article, we introduce a novel distance-based feature extraction method for various pattern classification problems. Specifically, two distances are extracted, which are based on (1 the distance between the data and its intra-cluster center and (2 the distance between the data and its extra-cluster centers. Experiments based on ten datasets containing different numbers of classes, samples, and dimensions are examined. The experimental results using naïve Bayes, k-NN, and SVM classifiers show that concatenating the original features provided by the datasets to the distance-based features can improve classification accuracy except image-related datasets. In particular, the distance-based features are suitable for the datasets which have smaller numbers of classes, numbers of samples, and the lower dimensionality of features. Moreover, two datasets, which have similar characteristics, are further used to validate this finding. The result is consistent with the first experiment result that adding the distance-based features can improve the classification performance.

  10. Genetic Feature Selection for Texture Classification

    Institute of Scientific and Technical Information of China (English)

    PAN Li; ZHENG Hong; ZHANG Zuxun; ZHANG Jianqing

    2004-01-01

    This paper presents a novel approach to feature subset selection using genetic algorithms. This approach has the ability to accommodate multiple criteria such as the accuracy and cost of classification into the process of feature selection and finds the effective feature subset for texture classification. On the basis of the effective feature subset selected, a method is described to extract the objects which are higher than their surroundings, such as trees or forest, in the color aerial images. The methodology presented in this paper is illustrated by its application to the problem of trees extraction from aerial images.

  11. 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

  12. 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.

  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. Update on diabetes classification.

    Science.gov (United States)

    Thomas, Celeste C; Philipson, Louis H

    2015-01-01

    This article highlights the difficulties in creating a definitive classification of diabetes mellitus in the absence of a complete understanding of the pathogenesis of the major forms. This brief review shows the evolving nature of the classification of diabetes mellitus. No classification scheme is ideal, and all have some overlap and inconsistencies. The only diabetes in which it is possible to accurately diagnose by DNA sequencing, monogenic diabetes, remains undiagnosed in more than 90% of the individuals who have diabetes caused by one of the known gene mutations. The point of classification, or taxonomy, of disease, should be to give insight into both pathogenesis and treatment. It remains a source of frustration that all schemes of diabetes mellitus continue to fall short of this goal.

  15. 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.

  16. 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....

  17. Problem Solving

    Science.gov (United States)

    Kinsella, John J.

    1970-01-01

    Discussed are the nature of a mathematical problem, problem solving in the traditional and modern mathematics programs, problem solving and psychology, research related to problem solving, and teaching problem solving in algebra and geometry. (CT)

  18. Completion of the classification

    CERN Document Server

    Strade, Helmut

    2012-01-01

    This is the last of three volumes about ""Simple Lie Algebras over Fields of Positive Characteristic""by Helmut Strade, presenting the state of the art of the structure and classification of Lie algebras over fields of positive characteristic. In this monograph the proof of the Classification Theorem presented in the first volumeis concluded.Itcollects all the important results on the topic whichcan be found only in scatteredscientific literaturso far.

  19. Twitter content classification

    OpenAIRE

    2010-01-01

    This paper delivers a new Twitter content classification framework based sixteen existing Twitter studies and a grounded theory analysis of a personal Twitter history. It expands the existing understanding of Twitter as a multifunction tool for personal, profession, commercial and phatic communications with a split level classification scheme that offers broad categorization and specific sub categories for deeper insight into the real world application of the service.

  20. Expected Classification Accuracy

    Directory of Open Access Journals (Sweden)

    Lawrence M. Rudner

    2005-08-01

    Full Text Available Every time we make a classification based on a test score, we should expect some number..of misclassifications. Some examinees whose true ability is within a score range will have..observed scores outside of that range. A procedure for providing a classification table of..true and expected scores is developed for polytomously scored items under item response..theory and applied to state assessment data. A simplified procedure for estimating the..table entries is also presented.

  1. 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...... includes scatter plots and linear classification results, in order to provide domain knowledge and lower bounds on the acceptable performance of future classifiers. Students and researchers can access the database on the Internet, and use it to test and compare their own classification methods....

  2. 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.

  3. 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.

  4. 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...

  5. Image Classification through integrated K- Means Algorithm

    Directory of Open Access Journals (Sweden)

    Balasubramanian Subbiah

    2012-03-01

    Full Text Available Image Classification has a significant role in the field of medical diagnosis as well as mining analysis and is even used for cancer diagnosis in the recent years. Clustering analysis is a valuable and useful tool for image classification and object diagnosis. A variety of clustering algorithms are available and still this is a topic of interest in the image processing field. However, these clustering algorithms are confronted with difficulties in meeting the optimum quality requirements, automation and robustness requirements. In this paper, we propose two clustering algorithm combinations with integration of K-Means algorithm that can tackle some of these problems. Comparison study is made between these two novel combination algorithms. The experimental results demonstrate that the proposed algorithms are very effective in producing desired clusters of the given data sets as well as diagnosis. These algorithms are very much useful for image classification as well as extraction of objects.

  6. Semantic Document Image Classification Based on Valuable Text Pattern

    Directory of Open Access Journals (Sweden)

    Hossein Pourghassem

    2011-01-01

    Full Text Available Knowledge extraction from detected document image is a complex problem in the field of information technology. This problem becomes more intricate when we know, a negligible percentage of the detected document images are valuable. In this paper, a segmentation-based classification algorithm is used to analysis the document image. In this algorithm, using a two-stage segmentation approach, regions of the image are detected, and then classified to document and non-document (pure region regions in the hierarchical classification. In this paper, a novel valuable definition is proposed to classify document image in to valuable or invaluable categories. The proposed algorithm is evaluated on a database consisting of the document and non-document image that provide from Internet. Experimental results show the efficiency of the proposed algorithm in the semantic document image classification. The proposed algorithm provides accuracy rate of 98.8% for valuable and invaluable document image classification problem.

  7. 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

  8. 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,...

  9. Density Based Support Vector Machines for Classification

    Directory of Open Access Journals (Sweden)

    Zahra Nazari

    2015-04-01

    Full Text Available Support Vector Machines (SVM is the most successful algorithm for classification problems. SVM learns the decision boundary from two classes (for Binary Classification of training points. However, sometimes there are some less meaningful samples amongst training points, which are corrupted by noises or misplaced in wrong side, called outliers. These outliers are affecting on margin and classification performance, and machine should better to discard them. SVM as a popular and widely used classification algorithm is very sensitive to these outliers and lacks the ability to discard them. Many research results prove this sensitivity which is a weak point for SVM. Different approaches are proposed to reduce the effect of outliers but no method is suitable for all types of data sets. In this paper, the new method of Density Based SVM (DBSVM is introduced. Population Density is the basic concept which is used in this method for both linear and non-linear SVM to detect outliers. Experiments on artificial data sets, real high-dimensional benchmark data sets of Liver disorder and Heart disease, and data sets of new and fatigued banknotes’ acoustic signals can prove the efficiency of this method on noisy data classification and the better generalization that it can provide compared to the standard SVM.

  10. MULTILABEL CLASSIFICATION OF DOCUMENTS WITH MAPREDUCE

    Directory of Open Access Journals (Sweden)

    P.Malarvizhi

    2013-04-01

    Full Text Available Multilabel classification is the problem of assigning a set of positive labels to an instance and recently it is highly required in applications like protein function classification, music categorization, gene classification and document classification for easy identification and retrieving of information. Labeling the documents of the web manually is a time consuming and a difficult task due to the size of the web which is a huge information resource and to overcome this difficulty, we propose an algorithm of MapReduce for classifying labels to the documents of the web. MapReduce is a framework of parallel programming model with the functions map and reduce and meets a number of varieties of applications. In our approach, the documents of the web are given to the MapReduce framework and the MapReduce framework assigns the set of positive labels to the documents of the web using binary classification ofbinary classifier. On experimentation, our proposed approach satisfactorily classifies the labels to the documents of the web.

  11. 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.

  12. LDA boost classification: boosting by topics

    Science.gov (United States)

    Lei, La; Qiao, Guo; Qimin, Cao; Qitao, Li

    2012-12-01

    AdaBoost is an efficacious classification algorithm especially in text categorization (TC) tasks. The methodology of setting up a classifier committee and voting on the documents for classification can achieve high categorization precision. However, traditional Vector Space Model can easily lead to the curse of dimensionality and feature sparsity problems; so it affects classification performance seriously. This article proposed a novel classification algorithm called LDABoost based on boosting ideology which uses Latent Dirichlet Allocation (LDA) to modeling the feature space. Instead of using words or phrase, LDABoost use latent topics as the features. In this way, the feature dimension is significantly reduced. Improved Naïve Bayes (NB) is designed as the weaker classifier which keeps the efficiency advantage of classic NB algorithm and has higher precision. Moreover, a two-stage iterative weighted method called Cute Integration in this article is proposed for improving the accuracy by integrating weak classifiers into strong classifier in a more rational way. Mutual Information is used as metrics of weights allocation. The voting information and the categorization decision made by basis classifiers are fully utilized for generating the strong classifier. Experimental results reveals LDABoost making categorization in a low-dimensional space, it has higher accuracy than traditional AdaBoost algorithms and many other classic classification algorithms. Moreover, its runtime consumption is lower than different versions of AdaBoost, TC algorithms based on support vector machine and Neural Networks.

  13. 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.

  14. 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.

  15. 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.

  16. Parental problem-solving abilities and the association of sickle cell disease complications with health-related quality of life for school-age children.

    Science.gov (United States)

    Barakat, Lamia P; Daniel, Lauren C; Smith, Kelsey; Renée Robinson, M; Patterson, Chavis A

    2014-03-01

    Children with sickle cell disease (SCD) are at risk for poor health-related quality of life (HRQOL). The current analysis sought to explore parent problem-solving abilities/skills as a moderator between SCD complications and HRQOL to evaluate applicability to pediatric SCD. At baseline, 83 children ages 6-12 years and their primary caregiver completed measures of child HRQOL. Primary caregivers also completed a measure of social problem-solving. A SCD complications score was computed from medical record review. Parent problem-solving abilities significantly moderated the association of SCD complications with child self-report psychosocial HRQOL (p = .006). SCD complications had a direct effect on parent proxy physical and psychosocial child HRQOL. Enhancing parent problem-solving abilities may be one approach to improve HRQOL for children with high SCD complications; however, modification of parent perceptions of HRQOL may require direct intervention to improve knowledge and skills involved in disease management.

  17. Gaussian maximum likelihood and contextual classification algorithms for multicrop classification

    Science.gov (United States)

    Di Zenzo, Silvano; Bernstein, Ralph; Kolsky, Harwood G.; Degloria, Stephen D.

    1987-01-01

    The paper reviews some of the ways in which context has been handled in the remote-sensing literature, and additional possibilities are introduced. The problem of computing exhaustive and normalized class-membership probabilities from the likelihoods provided by the Gaussian maximum likelihood classifier (to be used as initial probability estimates to start relaxation) is discussed. An efficient implementation of probabilistic relaxation is proposed, suiting the needs of actual remote-sensing applications. A modified fuzzy-relaxation algorithm using generalized operations between fuzzy sets is presented. Combined use of the two relaxation algorithms is proposed to exploit context in multispectral classification of remotely sensed data. Results on both one artificially created image and one MSS data set are reported.

  18. 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.

  19. Specific classification of financial analysis of enterprise activity

    Directory of Open Access Journals (Sweden)

    Synkevych Nadiia I.

    2014-01-01

    Full Text Available Despite the fact that one can find a big variety of classifications of types of financial analysis of enterprise activity, which differ with their approach to classification and a number of classification features and their content, in modern scientific literature, their complex comparison and analysis of existing classification have not been done. This explains urgency of this study. The article studies classification of types of financial analysis of scientists and presents own approach to this problem. By the results of analysis the article improves and builds up a specific classification of financial analysis of enterprise activity and offers classification by the following features: objects, subjects, goals of study, automation level, time period of the analytical base, scope of study, organisation system, classification features of the subject, spatial belonging, sufficiency, information sources, periodicity, criterial base, method of data selection for analysis and time direction. All types of financial analysis significantly differ with their inherent properties and parameters depending on the goals of financial analysis. The developed specific classification provides subjects of financial analysis of enterprise activity with a possibility to identify a specific type of financial analysis, which would correctly meet the set goals.

  20. Classification of human leukocyte antigen (HLA) supertypes

    DEFF Research Database (Denmark)

    Wang, Mingjun; Claesson, Mogens H

    2014-01-01

    Identification of new antigenic peptides, derived from infectious agents or cancer cells, which bind to human leukocyte antigen (HLA) class I and II molecules, is of importance for the development of new effective vaccines capable of activating the cellular arm of the immune response. However...... this complexity is to group thousands of different HLA molecules into several so-called HLA supertypes: a classification that refers to a group of HLA alleles with largely overlapping peptide binding specificities. In this chapter, we focus on the state-of-the-art classification of HLA supertypes including HLA...

  1. Diagnosis and classification of autoimmune hemolytic anemia.

    Science.gov (United States)

    Bass, Garrett F; Tuscano, Emily T; Tuscano, Joseph M

    2014-01-01

    Uncompensated autoantibody-mediated red blood cell (RBC) consumption is the hallmark of autoimmune hemolytic anemia (AIHA). Classification of AIHA is pathophysiologically based and divides AIHA into warm, mixed or cold-reactive subtypes. This thermal-based classification is based on the optimal autoantibody-RBC reactivity temperatures. AIHA is further subcategorized into idiopathic and secondary with the later being associated with a number of underlying infectious, neoplastic and autoimmune disorders. In most cases AIHA is confirmed by a positive direct antiglobulin test (DAT). The standard therapeutic approaches to treatment of AIHA include corticosteroids, splenectomy, immunosuppressive agents and monoclonal antibodies.

  2. Known TCP Implementation Problems

    Science.gov (United States)

    Paxson, Vern (Editor); Allman, Mark; Dawson, Scott; Fenner, William; Griner, Jim; Heavens, Ian; Lahey, K.; Semke, J.; Volz, B.

    1999-01-01

    This memo catalogs a number of known TCP implementation problems. The goal in doing so is to improve conditions in the existing Internet by enhancing the quality of current TCP/IP implementations. It is hoped that both performance and correctness issues can be resolved by making implementors aware of the problems and their solutions. In the long term, it is hoped that this will provide a reduction in unnecessary traffic on the network, the rate of connection failures due to protocol errors, and load on network servers due to time spent processing both unsuccessful connections and retransmitted data. This will help to ensure the stability of the global Internet. Each problem is defined as follows: Name of Problem The name associated with the problem. In this memo, the name is given as a subsection heading. Classification one or more problem categories for which the problem is classified: "congestion control", "performance", "reliability", "resource management". Description A definition of the problem, succinct but including necessary background material. Significance A brief summary of the sorts of environments for which the problem is significant.

  3. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on soun...... exchanging experiences about constructions fulfilling different classes, reducing trade barriers, and finally increasing the sound insulation of dwellings.......Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on sound...... 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...

  4. 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...... HE, protein contact dermatitis/contact urticaria, hyperkeratotic endogenous eczema and vesicular endogenous eczema, respectively. An additional diagnosis was given if symptoms indicated that factors additional to the main diagnosis were of importance for the disease. RESULTS: Four hundred and twenty......%) 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...

  5. 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...

  6. Supernova Photometric Classification Challenge

    CERN Document Server

    Kessler, Richard; Jha, Saurabh; Kuhlmann, Stephen

    2010-01-01

    We have publicly released a blinded mix of simulated SNe, with types (Ia, Ib, Ic, II) selected in proportion to their expected rate. The simulation is realized in the griz filters of the Dark Energy Survey (DES) with realistic observing conditions (sky noise, point spread function and atmospheric transparency) based on years of recorded conditions at the DES site. Simulations of non-Ia type SNe are based on spectroscopically confirmed light curves that include unpublished non-Ia samples donated from the Carnegie Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan Digital Sky Survey-II (SDSS-II). We challenge scientists to run their classification algorithms and report a type for each SN. A spectroscopically confirmed subset is provided for training. The goals of this challenge are to (1) learn the relative strengths and weaknesses of the different classification algorithms, (2) use the results to improve classification algorithms, and (3) understand what spectroscopically confirmed sub-...

  7. Information gathering for CLP classification.

    Science.gov (United States)

    Marcello, Ida; Giordano, Felice; Costamagna, Francesca Marina

    2011-01-01

    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.

  8. 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...

  9. 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.

  10. Latent classification models

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    One of the simplest, and yet most consistently well-performing setof classifiers is the \\NB models. These models rely on twoassumptions: $(i)$ All the attributes used to describe an instanceare conditionally independent given the class of that instance,and $(ii)$ all attributes follow a specific...... 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....

  11. Bosniak Classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens;

    2014-01-01

    . 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...

  12. Classification of iconic images

    OpenAIRE

    Zrianina, Mariia; Kopf, Stephan

    2016-01-01

    Iconic images represent an abstract topic and use a presentation that is intuitively understood within a certain cultural context. For example, the abstract topic “global warming” may be represented by a polar bear standing alone on an ice floe. Such images are widely used in media and their automatic classification can help to identify high-level semantic concepts. This paper presents a system for the classification of iconic images. It uses a variation of the Bag of Visual Words approach wi...

  13. 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.

  14. Trends and concepts in fern classification

    Science.gov (United States)

    Christenhusz, Maarten J. M.; Chase, Mark W.

    2014-01-01

    sister to all other vascular plants, whereas the whisk ferns (Psilotaceae), often included in the lycopods or believed to be associated with the first vascular plants, are sister to Ophioglossaceae and thus belong to the fern clade. The horsetails (Equisetaceae) are also members of the fern clade (sometimes inappropriately called ‘monilophytes’), but, within that clade, their placement is still uncertain. Leptosporangiate ferns are better understood, although deep relationships within this group are still unresolved. Earlier, almost all leptosporangiate ferns were placed in a single family (Polypodiaceae or Dennstaedtiaceae), but these families have been redefined to narrower more natural entities. Conclusions Concluding this paper, a classification is presented based on our current understanding of relationships of fern and lycopod clades. Major changes in our understanding of these families are highlighted, illustrating issues of classification in relation to convergent evolution and false homologies. Problems with the current classification and groups that still need study are pointed out. A summary phylogenetic tree is also presented. A new classification in which Aspleniaceae, Cyatheaceae, Polypodiaceae and Schizaeaceae are expanded in comparison with the most recent classifications is presented, which is a modification of those proposed by Smith et al. (2006, 2008) and Christenhusz et al. (2011). These classifications are now finding a wider acceptance and use, and even though a few amendments are made based on recently published results from molecular analyses, we have aimed for a stable family and generic classification of ferns. PMID:24532607

  15. 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.

  16. Classification of Noisy Data: An Approach Based on Genetic Algorithms and Voronoi Tessellation

    DEFF Research Database (Denmark)

    Khan, Abdul Rauf; Schiøler, Henrik; Knudsen, Torben

    2016-01-01

    on the portioning of information space; and (2) use of the genetic algorithm to solve combinatorial problems for classification. In particular, we will implement our methodology to solve complex classification problems and compare the performance of our classifier with other well-known methods (SVM, KNN, and ANN...

  17. Classification of Graph C*-Algebras with No More than Four Primitive Ideals

    DEFF Research Database (Denmark)

    Eilers, Søren; Restorff, Gunnar; Ruiz, Efren

    2013-01-01

    We describe the status quo of the classification problem of graph C∗-algebras with four primitive ideals or less.......We describe the status quo of the classification problem of graph C∗-algebras with four primitive ideals or less....

  18. Analytic theory of the selection mechanism in the Saffman-Taylor problem. [concerning shape of fingers in Hele-Shaw cell

    Science.gov (United States)

    Hong, D. C.; Langer, J. S.

    1986-01-01

    An analytic approach to the problem of predicting the widths of fingers in a Hele-Shaw cell is presented. The analysis is based on the WKB technique developed recently for dealing with the effects of surface tension in the problem of dendritic solidification. It is found that the relation between the dimensionless width lambda and the dimensionless group of parameters containing the surface tension, nu, has the form lambda - 1/2 = nu exp 2/3 in the limit of small nu.

  19. 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...

  20. Classification Models for Symmetric Key Cryptosystem Identification

    Directory of Open Access Journals (Sweden)

    Shri Kant

    2012-01-01

    Full Text Available The present paper deals with the basic principle and theory behind prevalent classification models and their judicious application for symmetric key cryptosystem identification. These techniques have been implemented and verified on varieties of known and simulated data sets. After establishing the techniques the problems of cryptosystem identification have been addressed.Defence Science Journal, 2012, 62(1, pp.38-45, DOI:http://dx.doi.org/10.14429/dsj.62.1440

  1. 医学院本科生毕业论文中问题分类与管理对策%Problem classification of medical undergraduates' graduation thesis and management strategies

    Institute of Scientific and Technical Information of China (English)

    董兆举; 叶亮; 赵慧娟; 李宁

    2016-01-01

    For the purpose of improving the quality of medical undergraduates' graduation thesis,optimizing graduation thesis' design,and reducing the job strain caused by guiding graduating students,our research chose 216 copies of undergraduates' graduation thesis from different programs in some medical colleges to analyze problems appeared and their frequencies.The research found that higher frequencies of problems showed the mistakes occurred in the thesis' format,logic and scientific design.It is necessary to classify all those questions frequently appeared in the thesis and weigh the severity of them.Based on the suggestions this research could establish a scientific thesis' quality evaluation system to appropriately guide graduating students' thesis.%为了促进医学本科生毕业论文水平的提高,提高毕业设计与毕业论文质量,减少教师带教压力,选取某医学院校不同专业本科生的毕业论文216份,分析论文中出现的问题及各类问题出现的频率.研究发现论文中出现频率较高的问题为论文格式错误、逻辑错误和研究设计问题.对论文中存在的所有问题按照性质进行科学分类,并给予权重,建立科学的论文问题严重性评价体系,为科学指导学生毕业论文工作提供依据.

  2. 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.

  3. Parallel Implementation of Classification Algorithms Based on Cloud Computing Environment

    Directory of Open Access Journals (Sweden)

    Wenbo Wang

    2012-09-01

    Full Text Available As an important task of data mining, Classification has been received considerable attention in many applications, such as information retrieval, web searching, etc. The enlarging volumes of information emerging by the progress of technology and the growing individual needs of data mining, makes classifying of very large scale of data a challenging task. In order to deal with the problem, many researchers try to design efficient parallel classification algorithms. This paper introduces the classification algorithms and cloud computing briefly, based on it analyses the bad points of the present parallel classification algorithms, then addresses a new model of parallel classifying algorithms. And it mainly introduces a parallel Naïve Bayes classification algorithm based on MapReduce, which is a simple yet powerful parallel programming technique. The experimental results demonstrate that the proposed algorithm improves the original algorithm performance, and it can process large datasets efficiently on commodity hardware.

  4. 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.

  5. 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.

  6. Quantitative and Traditional Classifications of Bulgarian Dialects Compared

    NARCIS (Netherlands)

    Houtzagers, H.P.; Nerbonne, J.; Prokić, J.

    2010-01-01

    Dialect classification is a classical problem in traditional dialectology. In the course of the last few decades, several quantitative approaches have been sug-gested as solutions for this problem, one of which uses “Levenshtein distance” for measuring linguistic distances between dialects. In the p

  7. 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.

  8. 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.

  9. 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.)

  10. Event Classification using Concepts

    NARCIS (Netherlands)

    Boer, M.H.T. de; Schutte, K.; Kraaij, W.

    2013-01-01

    The semantic gap is one of the challenges in the GOOSE project. In this paper a Semantic Event Classification (SEC) system is proposed as an initial step in tackling the semantic gap challenge in the GOOSE project. This system uses semantic text analysis, multiple feature detectors using the BoW mod

  11. 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

  12. 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...

  13. Recurrent neural collective classification.

    Science.gov (United States)

    Monner, Derek D; Reggia, James A

    2013-12-01

    With the recent surge in availability of data sets containing not only individual attributes but also relationships, classification techniques that take advantage of predictive relationship information have gained in popularity. The most popular existing collective classification techniques have a number of limitations-some of them generate arbitrary and potentially lossy summaries of the relationship data, whereas others ignore directionality and strength of relationships. Popular existing techniques make use of only direct neighbor relationships when classifying a given entity, ignoring potentially useful information contained in expanded neighborhoods of radius greater than one. We present a new technique that we call recurrent neural collective classification (RNCC), which avoids arbitrary summarization, uses information about relationship directionality and strength, and through recursive encoding, learns to leverage larger relational neighborhoods around each entity. Experiments with synthetic data sets show that RNCC can make effective use of relationship data for both direct and expanded neighborhoods. Further experiments demonstrate that our technique outperforms previously published results of several collective classification methods on a number of real-world data sets.

  14. 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.

  15. Classifications in popular music

    NARCIS (Netherlands)

    van Venrooij, A.; Schmutz, V.; Wright, J.D.

    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

  16. 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…

  17. 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.

  18. 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.

  19. Classification of osteosarcoma T-ray responses using adaptive and rational wavelets for feature extraction

    Science.gov (United States)

    Ng, Desmond; Wong, Fu Tian; Withayachumnankul, Withawat; Findlay, David; Ferguson, Bradley; Abbott, Derek

    2007-12-01

    In this work we investigate new feature extraction algorithms on the T-ray response of normal human bone cells and human osteosarcoma cells. One of the most promising feature extraction methods is the Discrete Wavelet Transform (DWT). However, the classification accuracy is dependant on the specific wavelet base chosen. Adaptive wavelets circumvent this problem by gradually adapting to the signal to retain optimum discriminatory information, while removing redundant information. Using adaptive wavelets, classification accuracy, using a quadratic Bayesian classifier, of 96.88% is obtained based on 25 features. In addition, the potential of using rational wavelets rather than the standard dyadic wavelets in classification is explored. The advantage it has over dyadic wavelets is that it allows a better adaptation of the scale factor according to the signal. An accuracy of 91.15% is obtained through rational wavelets with 12 coefficients using a Support Vector Machine (SVM) as the classifier. These results highlight adaptive and rational wavelets as an efficient feature extraction method and the enormous potential of T-rays in cancer detection.

  20. Two problems in multiphase biological flows: Blood flow and particulate transport in microvascular network, and pseudopod-driven motility of amoeboid cells

    Science.gov (United States)

    Bagchi, Prosenjit

    2016-11-01

    In this talk, two problems in multiphase biological flows will be discussed. The first is the direct numerical simulation of whole blood and drug particulates in microvascular networks. Blood in microcirculation behaves as a dense suspension of heterogeneous cells. The erythrocytes are extremely deformable, while inactivated platelets and leukocytes are nearly rigid. A significant progress has been made in recent years in modeling blood as a dense cellular suspension. However, many of these studies considered the blood flow in simple geometry, e.g., straight tubes of uniform cross-section. In contrast, the architecture of a microvascular network is very complex with bifurcating, merging and winding vessels, posing a further challenge to numerical modeling. We have developed an immersed-boundary-based method that can consider blood cell flow in physiologically realistic and complex microvascular network. In addition to addressing many physiological issues related to network hemodynamics, this tool can be used to optimize the transport properties of drug particulates for effective organ-specific delivery. Our second problem is pseudopod-driven motility as often observed in metastatic cancer cells and other amoeboid cells. We have developed a multiscale hydrodynamic model to simulate such motility. We study the effect of cell stiffness on motility as the former has been considered as a biomarker for metastatic potential. Funded by the National Science Foundation.

  1. Seafloor backscatter signal simulation and classification

    Digital Repository Service at National Institute of Oceanography (India)

    Mahale, V.; El Dine, W.G.; Chakraborty, B.

    networks and is a powerful tool for solving classification problems. If the prior knowledge about the classes in the data is limited, it is difficult to prepare a data set for training the classifier network. The only practical alternative... in such situations is to use the ground truth data to derive the type of class. Most of these problems are of supervised learning type, i.e. it requires examples of known class types, for the network learning process. In a typical scenario, a neural network...

  2. Leveraging Structure to Improve Classification Performance in Sparsely Labeled Networks

    Energy Technology Data Exchange (ETDEWEB)

    Gallagher, B; Eliassi-Rad, T

    2007-10-22

    We address the problem of classification in a partially labeled network (a.k.a. within-network classification), with an emphasis on tasks in which we have very few labeled instances to start with. Recent work has demonstrated the utility of collective classification (i.e., simultaneous inferences over class labels of related instances) in this general problem setting. However, the performance of collective classification algorithms can be adversely affected by the sparseness of labels in real-world networks. We show that on several real-world data sets, collective classification appears to offer little advantage in general and hurts performance in the worst cases. In this paper, we explore a complimentary approach to within-network classification that takes advantage of network structure. Our approach is motivated by the observation that real-world networks often provide a great deal more structural information than attribute information (e.g., class labels). Through experiments on supervised and semi-supervised classifiers of network data, we demonstrate that a small number of structural features can lead to consistent and sometimes dramatic improvements in classification performance. We also examine the relative utility of individual structural features and show that, in many cases, it is a combination of both local and global network structure that is most informative.

  3. A Bayesian classification of the IRAS LRS Atlas

    Science.gov (United States)

    Goebel, J.; Stutz, J.; Volk, K.; Walker, H.; Gerbault, F.; Self, M.; Taylor, W.; Cheeseman, P.

    1989-01-01

    The availability of a reclassification of the IRAS LRS Atlas of spectra using a new Bayesian classification procedure (AutoClass) is announced. The classes of objects which result from the application of the AutoClass algorithm include many of the previously known LRS classes. New classes which have interesting astronomical and astrophysical interpretations were also found. Techniques, such as the AutoClass algorithm, have a bright future in the arena of astronomical classification problems.

  4. Classification of filiform Lie algebras of order 3

    Science.gov (United States)

    Navarro, Rosa María

    2016-12-01

    Lie algebras of order 3 constitute a generalization of Lie algebras and superalgebras. Throughout this paper the classification problem of filiform Lie algebras of order 3 is considered and therefore this work is a continuation papers seen in the literature. We approach this classification by extending Vergne's result for filiform Lie algebras and by considering algebras of order 3 of high nilindex. We find the expression of the law to which any elementary filiform Lie algebra of order 3 is isomorphic.

  5. Scalable classification by clustering: Hybrid can be better than Pure

    Institute of Scientific and Technical Information of China (English)

    Deng Shengchun; He Zengyou; Xu Xiaofei

    2007-01-01

    The problem of scalable classification by clustering in large databases was discussed. Clustering based classification method first generates clusters using clustering algorithms . To classify new coming data points , it finds the k nearest clusters of the data point as neighbors , and assign each data point to the dominant class of these neighbors . Existing algorithms incorporated class information in making clustering decisions and produced pure clusters (each cluster associated with only one class) . We presented hybrid cluster based algorithms , which produce clusters by unsupervised clustering and allow each cluster associated with multiple classes . Experimental results show that hybrid cluster based algorithms outperform pure ones in both classification accuracy and training speed.

  6. 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.

  7. 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.

  8. Brain tumour classification using Gaussian decomposition and neural networks.

    Science.gov (United States)

    Arizmendi, Carlos; Sierra, Daniel A; Vellido, Alfredo; Romero, Enrique

    2011-01-01

    The development, implementation and use of computer-based medical decision support systems (MDSS) based on pattern recognition techniques holds the promise of substantially improving the quality of medical practice in diagnostic and prognostic tasks. In this study, the core of a decision support system for brain tumour classification from magnetic resonance spectroscopy (MRS) data is presented. It combines data pre-processing using Gaussian decomposition, dimensionality reduction using moving window with variance analysis, and classification using artificial neural networks (ANN). This combination of techniques is shown to yield high diagnostic classification accuracy in problems concerning diverse brain tumour pathologies, some of which have received little attention in the literature.

  9. Classification of Noisy Data: An Approach Based on Genetic Algorithms and Voronoi Tessellation

    DEFF Research Database (Denmark)

    Khan, Abdul Rauf; Schiøler, Henrik; Knudsen, Torben;

    2016-01-01

    Classification is one of the major constituents of the data-mining toolkit. The well-known methods for classification are built on either the principle of logic or statistical/mathematical reasoning for classification. In this article we propose: (1) a different strategy, which is based......). The results of this study suggest that our proposed methodology is specialized to deal with the classification problem of highly imbalanced classes with significant overlap....... on the portioning of information space; and (2) use of the genetic algorithm to solve combinatorial problems for classification. In particular, we will implement our methodology to solve complex classification problems and compare the performance of our classifier with other well-known methods (SVM, KNN, and ANN...

  10. An extended Lagrangian support vector machine for classifications

    Institute of Scientific and Technical Information of China (English)

    YANG Xiaowei; SHU Lei; HAO Zhifeng; LIANG Yanchun; LIU Guirong; HAN Xu

    2004-01-01

    Lagrangian support vector machine (LSVM) cannot solve large problems for nonlinear kernel classifiers. In order to extend the LSVM to solve very large problems, an extended Lagrangian support vector machine (ELSVM) for classifications based on LSVM and SVMlight is presented in this paper. Our idea for the ELSVM is to divide a large quadratic programming problem into a series of subproblems with small size and to solve them via LSVM. Since the LSVM can solve small and medium problems for nonlinear kernel classifiers, the proposed ELSVM can be used to handle large problems very efficiently. Numerical experiments on different types of problems are performed to demonstrate the high efficiency of the ELSVM.

  11. 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.

  12. Balance Problems

    Science.gov (United States)

    ... you are having balance problems, see your doctor. Balance disorders can be signs of other health problems, such ... cases, treating the illness that is causing the disorder will help with the balance problem. Exercises, a change in diet, and some ...

  13. 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.

  14. Principal components null space analysis for image and video classification.

    Science.gov (United States)

    Vaswani, Namrata; Chellappa, Rama

    2006-07-01

    We present a new classification algorithm, principal component null space analysis (PCNSA), which is designed for classification problems like object recognition where different classes have unequal and nonwhite noise covariance matrices. PCNSA first obtains a principal components subspace (PCA space) for the entire data. In this PCA space, it finds for each class "i," an Mi-dimensional subspace along which the class' intraclass variance is the smallest. We call this subspace an approximate null space (ANS) since the lowest variance is usually "much smaller" than the highest. A query is classified into class "i" if its distance from the class' mean in the class' ANS is a minimum. We derive upper bounds on classification error probability of PCNSA and use these expressions to compare classification performance of PCNSA with that of subspace linear discriminant analysis (SLDA). We propose a practical modification of PCNSA called progressive-PCNSA that also detects "new" (untrained classes). Finally, we provide an experimental comparison of PCNSA and progressive PCNSA with SLDA and PCA and also with other classification algorithms-linear SVMs, kernel PCA, kernel discriminant analysis, and kernel SLDA, for object recognition and face recognition under large pose/expression variation. We also show applications of PCNSA to two classification problems in video--an action retrieval problem and abnormal activity detection.

  15. Hierarchical discriminant manifold learning for dimensionality reduction and image classification

    Science.gov (United States)

    Chen, Weihai; Zhao, Changchen; Ding, Kai; Wu, Xingming; Chen, Peter C. Y.

    2015-09-01

    In the field of image classification, it has been a trend that in order to deliver a reliable classification performance, the feature extraction model becomes increasingly more complicated, leading to a high dimensionality of image representations. This, in turn, demands greater computation resources for image classification. Thus, it is desirable to apply dimensionality reduction (DR) methods for image classification. It is necessary to apply DR methods to relieve the computational burden as well as to improve the classification accuracy. However, traditional DR methods are not compatible with modern feature extraction methods. A framework that combines manifold learning based DR and feature extraction in a deeper way for image classification is proposed. A multiscale cell representation is extracted from the spatial pyramid to satisfy the locality constraints for a manifold learning method. A spectral weighted mean filtering is proposed to eliminate noise in the feature space. A hierarchical discriminant manifold learning is proposed which incorporates both category label and image scale information to guide the DR process. Finally, the image representation is generated by concatenating dimensionality reduced cell representations from the same image. Extensive experiments are conducted to test the proposed algorithm on both scene and object recognition datasets in comparison with several well-established and state-of-the-art methods with respect to classification precision and computational time. The results verify the effectiveness of incorporating manifold learning in the feature extraction procedure and imply that the multiscale cell representations may be distributed on a manifold.

  16. 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.

  17. 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.

  18. 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

  19. A difference boosting neural network for automated star-galaxy classification

    CERN Document Server

    Philip, N S; Kembhavi, A K; Joseph, K B; Philip, Ninan Sajeeth; Wadadekar, Yogesh; Kembhavi, Ajit

    2002-01-01

    In this paper we describe the use of a new artificial neural network, called the difference boosting neural network (DBNN), for automated classification problems in astronomical data analysis. We illustrate the capabilities of the network by applying it to star galaxy classification using recently released, deep imaging data. We have compared our results with classification made by the widely used Source Extractor (SExtractor) package. We show that while the performance of the DBNN in star-galaxy classification is comparable to that of SExtractor, it has the advantage of significantly higher speed and flexibility during training as well as classification.

  20. 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.

  1. 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.

  2. Hand eczema classification

    DEFF Research Database (Denmark)

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

    2008-01-01

    Summary Background Hand eczema is a long-lasting disease with a high prevalence in the background population. The disease has severe, negative effects on quality of life and sometimes on social status. Epidemiological studies have identified risk factors for onset and prognosis, but treatment...... 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...... for hand eczema is needed. Objectives The present study attempts to characterize subdiagnoses of hand eczema with respect to basic demographics, medical history and morphology. Methods Clinical data from 416 patients with hand eczema from 10 European patch test clinics were assessed. Results...

  3. 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.

  4. [New classification of vasculitis].

    Science.gov (United States)

    Anić, Branimir

    2014-01-01

    Vasculitis syndrome comprises a heterogenic group of inflammatory rheumatic diseases whose common feature is inflammation in the blood vessel wall. Establishing the diagnosis of vasculitis is one of the greatest challenges in medicine. Clinical presentation of vasculitis depends on the extent of an organ system affection, as well as on the total number of affected organs. A great range of clinical presentations of vasculitis and the low incidence of the disease impede systematic clinical investigation of vasculitis. The needs of clinical routine and the need for conducting systemic clinical investigations require a clear distinction of individual clinical entities. Different classifications of vasculitis syndrome have been proposed: according to etiology, pathogenesis, histological finding in the affected vessels, affection of individual organs and organ systems. This paper presents and comments news and recent classifications and nomenclature of vasculitic entities proposed at the second conference in Chapel Hill.

  5. Bosniak classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens;

    2016-01-01

    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...... one category lower. Pathologic correlation in six lesions revealed four malignant and two benign lesions. CONCLUSION: CEUS and MR both up- and downgraded renal cysts compared to CT, and until these non-radiation modalities have been refined and adjusted, CT should remain the gold standard...

  6. 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

  7. Morphology, cytogenetics and classification of MDS.

    Science.gov (United States)

    Giagounidis, Aristoteles; Haase, Detlef

    2013-12-01

    Myelodysplastic syndromes are heterogeneous bone marrow diseases with a variable pathogenetic background. Cytomorphological alterations in peripheral blood films as well as bone marrow aspirates and histological findings in trephine biopsies result from cytogenetic and molecular abnormalities, epigenetic dysregulation and immune dysfunction and are key elements for setting the diagnosis of MDS. Whereas diagnosis can be made quite easily in advanced MDS this is much more difficult in early MDS, especially in cases with cytopenias or dysplasias of uncertain significance (ICUS and IDUS). Recommendations, illustrated by case reports for a stepwise annealing to the final diagnosis and exclusion of differential diagnoses are given. Furthermore, the problem of correct counting and identification of blasts is covered and features defining dysplasia in all three cell lineages are recapitulated thoroughly. Histopathology is not mandatory but has a distinct diagnostic and prognostic value especially in cases with hypoplasia or fibrosis and when the TP53 mutational status is of relevance. In up to 70% of patients with MDS clonal chromosome abnormalities can be identified which have a high impact on setting the correct diagnosis and estimation of prognosis. Incidence, type, molecular background and clinical relevance of distinct anomalies as well as cytogenetic subgroups are presented in detail and the development of the new cytogenetic prognostic scoring system as part of the IPSS-R is explained. The value of FISH-Analysis as a complementary tool for chromosome analysis in MDS is demonstrated with special emphasis on the possibility to perform frequent cytogenetic monitoring by CD34-FISH examination of peripheral blood. Finally the evolution of MDS-classification systems from FAB to WHO with a critical discussion of their shortcomings like degree of dysplasia, blast thresholds, inclusion/exclusion of CMML, and the lack of dynamic information is presented.

  8. 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.

  9. 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.

  10. 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)

  11. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  12. 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.

  13. 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.

  14. 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.

  15. 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)

  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. Evaluation of partial classification algorithms using ROC curves.

    Science.gov (United States)

    Tusch, G

    1995-01-01

    When using computer programs for decision support in clinical routine, an assessment or a comparison of the underlying classification algorithms is essential. In classical (forced) classification, the classification rule always selects exactly one alternative. A number of proven discriminant measures are available here, e.g.sensitivity and error rate. For probabilistic classification, a series of additional measures has been developed [1]. However, for many clinical applications, there are models where an observation is classified into several classes (partial classification), e.g., models from artificial intelligence, decision analysis, or fuzzy set theory. In partial classification, the discriminatory ability (Murphy) can be adjusted a priori to any level, in most practical cases. Here the usual measures do not apply. We investigate the preconditions for assessment and comparison based on medical decision theory. We focus on problems in the medical domain and establish a methodological framework. When using partial classification procedures, a ROC analysis in the classical sense is no longer appropriate. In forced classification for two classes, the problem is to find a cutoff point on the ROC curve; while in partial classification, you have to find two of them. They characterize the elements being classified as coming from both classes. This extends to several classes. We propose measures corresponding to the usual discriminant measures for forced classification (e.g., sensitivity and error rate) and demonstrate the effects using the ROC approach. For this purpose, we extend the existing method for forced classification in a mathematically sound manner. Algorithms for the construction of thresholds can easily be adapted. Two specific measurement models, based on parametric and non-parametric approaches, will be introduced. The basic methodology is suitable for all partial classification problems, whereas the extended ROC analysis assumes a rank order of the

  18. Sparse group lasso and high dimensional multinomial classification

    DEFF Research Database (Denmark)

    Vincent, Martin; Hansen, N.R.

    2014-01-01

    algorithm is available in the R package msgl. Its performance scales well with the problem size as illustrated by one of the examples considered - a 50 class classification problem with 10 k features, which amounts to estimating 500 k parameters. © 2013 Elsevier Inc. All rights reserved.......The sparse group lasso optimization problem is solved using a coordinate gradient descent algorithm. The algorithm is applicable to a broad class of convex loss functions. Convergence of the algorithm is established, and the algorithm is used to investigate the performance of the multinomial sparse...... group lasso classifier. On three different real data examples the multinomial group lasso clearly outperforms multinomial lasso in terms of achieved classification error rate and in terms of including fewer features for the classification. An implementation of the multinomial sparse group lasso...

  19. 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...

  20. 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.