Aggregation invariance in general clustering approaches

General clustering deals with weighted objects and fuzzy memberships. We investigate the group- or object-aggregation-invariance properties possessed by the relevant functionals (effective number of groups or objects, centroids, dispersion, mutual object-group information, etc.). The classical squared Euclidean case can be generalized to non-Euclidean distances, as well as to non-linear transformations of the memberships, yielding the c-means clustering algorithm as well as two presumably new procedures, the convex and pairwise convex clustering. Cluster stability and aggregation-invariance of the optimal memberships associated to the various clustering schemes are examined as well.

« Pourquoi commence-t-on aussi tard ce soir ? » (document vidéo)

Document vidéo réalisé autour d'un stage de terrain à Lourdes effectué par des étudiantEs de l'UNIL et organisé par Laurent Amiotte Suchet (Maître assistant à l'Observation des religions en Suisse).

A partial ordering of knots and links through diagrammatic unknotting

In this paper we de. ne a partial ordering of knots and links using a special property derived from their minimal diagrams. A link K' is called a predecessor of a link K if Cr(K') < Cr(K) and a diagram of K' can be obtained from a minimal diagram D of K by a single crossing change. In such a case, we say that K' < K. We investigate the sets of links that can be obtained by single crossing changes over all minimal diagrams of a given link. We show that these sets are specific for different links and permit partial ordering of all links. Some interesting results are presented and many questions are raised.

Catégorisation automatique de propositions textuelles en types de discours

De nombreuses méthodes de classification automatique de textes (supervisée ou non) existent. Elles se sont particulièrement développées depuis la création du web en vue d'améliorer les moteurs de recherche. Au delà de ce champs d'application, elles peuvent aussi être utiles pour « découvrir » ou « redécou­vrir » ce qui caractérise une classe de textes aussi simplement que possible. Dans l'approche statistique développée ici, il s'agira de partitionner des parties de textes en types de discours tels que narratif, explicatif, argumentatif etc. en utilisant un minimum d'information, à savoir les catégories morphosyn­taxiques (CMS). Les premiers résultats obtenus mettent en évidence des liens significatifs entre les CMS, les types de discours et des textes annotés par un expert humain ; ces relations sont toutefois encore incomplètes et difficiles à interpréter d'un point de vue linguistique.

Iowa Roads and Streets Functional Classification Manual, 1970

This manual provides a set of procedural rules and regulations for use in functionally classifying all roads and streets in Iowa according to the character of service they are intended to provide. Functional classification is a requirement of House File 394 (Functional Highway Classification Bill) enacted by the 63rd General Assembly of the Iowa Legislature. Functional classification is defined in this Bill as: "The grouping of roads and streets into systems according to the character of service they will be expected to provide, and the assignment of jurisdiction over each class to the governmental unit having primary interest in each type of service."

Iowa Roads and Streets Functional Classification Manual, 1975

This manual provides a set of procedural rules and regulations for use in functionally classifying all roads and streets in Iowa according to the character of service they are intended to provide. Functional classification is a requirement of the 1973 Code of Iowa (Chapter 306) as amended by Senate File 1062 enacted by the 2nd session of the 65th General Assembly of Iowa. Functional classification is defined as the grouping of roads and streets into systems according to the character of service they will be expected to provide, and the assignment of jurisdiction over each class to the governmental unit having primary interest in each type of service. Stated objectives of the legislation are: "Functional classification will serve the legislator by providing an equitable basis for determination of proper source of tax support and providing for the assignment of financial resources to the governmental unit having responsibility for each class of service. Functional classification promotes the ability of the administrator to effectively prepare and carry out long range programs which reflect the transportation needs of the public." All roads and streets in legal existence will be classified. Instructions are also included in this manual for a continuous reporting to the Highway Commission of changes in classification and/or jurisdiction resulting from new construction, corporation line changes, relocations, and deletions. This continuous updating of records is absolutely essential for modern day transportation planning as it is the only possible way to monitor the status of existing road systems, and consequently determine adequacy and needs with accuracy.

Manual de gestión documental para el Ayuntamiento de León

En este trabajo se exponen las normas y procedimientos para la implantación en el Ayuntamiento de León de un sistema de gestión documental basado en la norma ISO 15489. Se desarrollan los conceptos básicos para la comprensión del manual, los tipos de documentos administrativos, el uso del lenguaje administrativo, los instrumentos, los diagramas, los formularios y la legislación para llevar a la práctica los sistemas de organización de fondos, clasificación, ordenación, valoración y descripción de documentos y los procesos de instalación, transferencias, régimen de acceso al documento, consultas, préstamos y reproducción de documentos en los archivos de gestión de las oficinas. Palabras clave: Sistema de gestión documental, ISO 15489, Ayuntamiento de León (España), organización de fondos, clasificación de documentos, ordenación de documentos, evaluación de documentos, descripción de documentos, archivos de gestión.

Outcome at two years of age in a Swiss national cohort of extremely preterm infants born between 2000 and 2008.

BACKGROUND: While survival rates of extremely preterm infants have improved over the last decades, the incidence of neurodevelopmental disability (ND) in survivors remains high. Representative current data on the severity of disability and of risk factors associated with poor outcome in this growing population are necessary for clinical guidance and parent counselling. METHODS: Prospective longitudinal multicentre cohort study of preterm infants born in Switzerland between 24(0/7) and 27(6/7) weeks gestational age during 2000-2008. Mortality, adverse outcome (death or severe ND) at two years, and predictors for poor outcome were analysed using multilevel multivariate logistic regression. Neurodevelopment was assessed using Bayley Scales of Infant Development II. Cerebral palsy was graded after the Gross Motor Function Classification System. RESULTS: Of 1266 live born infants, 422 (33%) died. Follow-up information was available for 684 (81%) survivors: 440 (64%) showed favourable outcome, 166 (24%) moderate ND, and 78 (11%) severe ND. At birth, lower gestational age, intrauterine growth restriction and absence of antenatal corticosteroids were associated with mortality and adverse outcome (p < 0.001). At 36(0/7) weeks postmenstrual age, bronchopulmonary dysplasia, major brain injury and retinopathy of prematurity were the main predictors for adverse outcome (p < 0.05). Survival without moderate or severe ND increased from 27% to 39% during the observation period (p = 0.02). CONCLUSIONS: In this recent Swiss national cohort study of extremely preterm infants, neonatal mortality was determined by gestational age, birth weight, and antenatal corticosteroids while neurodevelopmental outcome was determined by the major neonatal morbidities. We observed an increase of survival without moderate or severe disability.

Characterization and multivariate classification of grapes and wines of two Cabernet Sauvignon clones

The objective of this work was to assess and characterize two clones, 169 and 685, of Cabernet Sauvignon grapes and to evaluate the wine produced from these grapes. The experiment was carried out in São Joaquim, SC, Brazil, during the 2009 harvest season. During grape ripening, the evolution of physical-chemical properties, phenolic compounds, organic acids, and anthocyanins was evaluated. During grape harvest, yield components were determined for each clone. Individual and total phenolics, individual and total anthocyanins, and antioxidant activity were evaluated for wine. The clones were also assessed regarding the duration of their phenological cycle. During ripening, the evolution of phenolic compounds and of physical-chemical parameters was similar for both clones; however, during harvest, significant differences were observed regarding yield, number of bunches per plant and berries per bunch, leaf area, and organic acid, polyphenol, and anthocyanin content. The wines produced from these clones showed significant differences regarding chemical composition. The clones showed similar phenological cycle and responses to bioclimatic parameters. Principal component analysis shows that clone 685 is strongly correlated with color characteristics, mainly monomeric anthocyanins, while clone 169 is correlated with individual phenolic compounds.

Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

Drug utilisation in a neonatal intensive care unit of a swiss university hospital

Introduction Medication errors in hospitalsmay occur at any step of the medication process including prescription, transcription, preparation and administration, and may originate with any of the actors involved. Neonatal intensive care units (NICU) take care of extremely frail patients in whom errors could have dramatic consequences. Our objective was to assess the frequency and nature of medication errors in the NICU of a university hospital in order to propose measures for improvement.Materials & Methods The design was that of an observational prospective study over 4 consecutivemonths. All patients receiving C 3drugs were included. For each patient, observations during the different stages were compiled in a computer formulary and compared with the litterature. Setting: The 11-bed NICU of our university hospital.Main outcome measures:(a) Frequency and nature of medication errors in prescription,transcription, preparation and administration.(b) Drugs affected by errors.Results 83 patients were included. 505 prescriptions and transcriptions, 447 preparations and 464 administrations were analyzed. 220 medications errors were observed: 102 (46.4%) at prescription, 25 (11.4%) at transcription, 19 (8.6%) at preparation and 73 (33.2%) at administration. Uncomplete/ambiguous orders (24; 23.5%) were the most common errors observed at prescription, followed by wrong name (21; 20.6%), wrong dose (17; 16.7%) and omission (15; 14.7%). Wrong time (33; 45.2%) and wrong administration technique (31; 42.5%) were the most important medication errors during administration. According to the ATC classification, systemic antibacterials (53; 24.1%) were the most implicated, followed by perfusion solutions (40; 18.2%), respiratory system products (30; 13.6%), and mineral supplements and antithrombotic agents (20; 9.1%).Discussions, Conclusion Proposed recommendations: ? Better teaching of neonatal prescription to medical interns;? Improved prescription form to avoid omissions and ambiguities;? Development of a neonatal drug formulary, including prescription,preparation and administration modalities to reduce errors at different stages;? Presence of a clinical pharmacist in the NICU.Disclosure of Interest None Declared

Approximate polytope ensemble for one-class classification

In this work, a new one-class classification ensemble strategy called approximate polytope ensemble is presented. The main contribution of the paper is threefold. First, the geometrical concept of convex hull is used to define the boundary of the target class defining the problem. Expansions and contractions of this geometrical structure are introduced in order to avoid over-fitting. Second, the decision whether a point belongs to the convex hull model in high dimensional spaces is approximated by means of random projections and an ensemble decision process. Finally, a tiling strategy is proposed in order to model non-convex structures. Experimental results show that the proposed strategy is significantly better than state of the art one-class classification methods on over 200 datasets.

Social inequalities of functioning and perceived health in Switzerland: a representative cross-sectional analysis.

Many people worldwide live with a disability, i.e. limitations in functioning. The prevalence is expected to increase due to demographic change and the growing importance of non-communicable disease and injury. To date, many epidemiological studies have used simple dichotomous measures of disability, even though the WHO's International Classification of Functioning, Disability, and Health (ICF) provides a multi-dimensional framework of functioning. We aimed to examine associations of socio-economic status (SES) and social integration in 3 core domains of functioning (impairment, pain, limitations in activity and participation) and perceived health. We conducted a secondary analysis of representative cross-sectional data of the Swiss Health Survey 2007 including 10,336 female and 8,424 male Swiss residents aged 15 or more. Guided by a theoretical ICF-based model, 4 mixed effects Poisson regressions were fitted in order to explain functioning and perceived health by indicators of SES and social integration. Analyses were stratified by age groups (15-30, 31-54, ≥55 years). In all age groups, SES and social integration were significantly associated with functional and perceived health. Among the functional domains, impairment and pain were closely related, and both were associated with limitations in activity and participation. SES, social integration and functioning were related to perceived health. We found pronounced social inequalities in functioning and perceived health, supporting our theoretical model. Social factors play a significant role in the experience of health, even in a wealthy country such as Switzerland. These findings await confirmation in other, particularly lower resourced settings.

Mixed spectral-structural classification of very high resolution images with summation kernels

In this paper, mixed spectral-structural kernel machines are proposed for the classification of very-high resolution images. The simultaneous use of multispectral and structural features (computed using morphological filters) allows a significant increase in classification accuracy of remote sensing images. Subsequently, weighted summation kernel support vector machines are proposed and applied in order to take into account the multiscale nature of the scene considered. Such classifiers use the Mercer property of kernel matrices to compute a new kernel matrix accounting simultaneously for two scale parameters. Tests on a Zurich QuickBird image show the relevance of the proposed method : using the mixed spectral-structural features, the classification accuracy increases of about 5%, achieving a Kappa index of 0.97. The multikernel approach proposed provide an overall accuracy of 98.90% with related Kappa index of 0.985.