Empirical mode decomposition-based face recognition system

In this work we explore the multivariate empirical mode decomposition combined with a Neural Network classifier as technique for face recognition tasks. Images are simultaneously decomposed by means of EMD and then the distance between the modes of the image and the modes of the representative image of each class is calculated using three different distance measures. Then, a neural network is trained using 10- fold cross validation in order to derive a classifier. Preliminary results (over 98 % of classification rate) are satisfactory and will justify a deep investigation on how to apply mEMD for face recognition.

EEG signal analysis via a cleaning procedure based on multivariate empirical mode decomposition

Artifacts are present in most of the electroencephalography (EEG) recordings, making it difficult to interpret or analyze the data. In this paper a cleaning procedure based on a multivariate extension of empirical mode decomposition is used to improve the quality of the data. This is achieved by applying the cleaning method to raw EEG data. Then, a synchrony measure is applied on the raw and the clean data in order to compare the improvement of the classification rate. Two classifiers are used, linear discriminant analysis and neural networks. For both cases, the classification rate is improved about 20%.

Classification of indian classical vocal styles from melodic contours

A prominent categorization of Indian classical music is the Hindustani and Carnatic traditions, the two styleshaving evolved under distinctly different historical andcultural influences. Both styles are grounded in the melodicand rhythmic framework of raga and tala. The styles differ along dimensions such as instrumentation,aesthetics and voice production. In particular, Carnatic music is perceived as being more ornamented. The hypothesisthat style distinctions are embedded in the melodic contour is validated via subjective classification tests. Melodic features representing the distinctive characteristicsare extracted from the audio. Previous work based on the extent of stable pitch regions is supported by measurements of musicians’ annotations of stable notes. Further, a new feature is introduced that captures thepresence of specific pitch modulations characteristic ofornamentation in Indian classical music. The combined features show high classification accuracy on a database of vocal music of prominent artistes. The misclassifications are seen to match actual listener confusions.

Validation of tissue modelization and classification techniques in T1-weighted MR brain images

We propose a deep study on tissue modelization andclassification Techniques on T1-weighted MR images. Threeapproaches have been taken into account to perform thisvalidation study. Two of them are based on FiniteGaussian Mixture (FGM) model. The first one consists onlyin pure gaussian distributions (FGM-EM). The second oneuses a different model for partial volume (PV) (FGM-GA).The third one is based on a Hidden Markov Random Field(HMRF) model. All methods have been tested on a DigitalBrain Phantom image considered as the ground truth. Noiseand intensity non-uniformities have been added tosimulate real image conditions. Also the effect of ananisotropic filter is considered. Results demonstratethat methods relying in both intensity and spatialinformation are in general more robust to noise andinhomogeneities. However, in some cases there is nosignificant differences between all presented methods.

quantiNemo: an individual-based program to simulate quantitative traits with explicit genetic architecture in a dynamic metapopulation.

quantiNemo is an individual-based, genetically explicit stochastic simulation program. It was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits with varying architectures in structured populations connected by migration and located in a heterogeneous habitat. quantiNemo is highly flexible at various levels: population, selection, trait(s) architecture, genetic map for QTL and/or markers, environment, demography, mating system, etc. quantiNemo is coded in C++ using an object-oriented approach and runs on any computer platform. Availability: Executables for several platforms, user's manual, and source code are freely available under the GNU General Public License at http://www2.unil.ch/popgen/softwares/quantinemo.

Development of Object-Oriented Design and Specifications for Iowa DOT and Urban Standards: Phase I, TR-487, 2004

Currently, individuals including designers, contractors, and owners learn about the project requirements by studying a combination of paper and electronic copies of the construction documents including the drawings, specifications (standard and supplemental), road and bridge standard drawings, design criteria, contracts, addenda, and change orders. This can be a tedious process since one needs to go back and forth between the various documents (paper or electronic) to obtain information about the entire project. Object-oriented computer-aided design (OO-CAD) is an innovative technology that can bring a change to this process by graphical portrayal of information. OO-CAD allows users to point and click on portions of an object-oriented drawing that are then linked to relevant databases of information (e.g., specifications, procurement status, and shop drawings). The vision of this study is to turn paper-based design standards and construction specifications into an object-oriented design and specification (OODAS) system or a visual electronic reference library (ERL). Individuals can use the system through a handheld wireless book-size laptop that includes all of the necessary software for operating in a 3D environment. All parties involved in transportation projects can access all of the standards and requirements simultaneously using a 3D graphical interface. By using this system, users will have all of the design elements and all of the specifications readily available without concerns of omissions. A prototype object-oriented model was created and demonstrated to potential users representing counties, cities, and the state. Findings suggest that a system like this could improve productivity to find information by as much as 75% and provide a greater sense of confidence that all relevant information had been identified. It was also apparent that this system would be used by more people in construction than in design. There was also concern related to the cost to develop and maintain the complete system. The future direction should focus on a project-based system that can help the contractors and DOT inspectors find information (e.g., road standards, specifications, instructional memorandums) more rapidly as it pertains to a specific project.

A Classification of Tools for Learning Logic

A table showing a comparison and classification of tools (intelligent tutoring systems) for e-learning of Logic at a college level.

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.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Case-based learning in VTLE: An effective strategy for improving learning design

This article presents preliminary research from an instructional design perspective on the design of the case method as an integral part of pedagogy and technology. Key features and benefitsusing this teaching and learning strategy in a Virtual Teaching and Learning Environment(VTLE) are identified, taking into account the requirements of the European Higher Education Area (EHEA) for a competence-based curricula design. The implications of these findings for alearning object approach exploring the possibilities of learning personalization, reusability and interoperability trough IMS LD, are also analyzed.

Improving Searching and Browsing Capabilities of Learning Object Repositories

Learning object repositories are a basic piece of virtual learning environments used for content management. Nevertheless, learning objects have special characteristics that make traditional solutions for content management ine ective. In particular, browsing and searching for learning objects cannot be based on the typical authoritative meta-data used for describing content, such as author, title or publicationdate, among others. We propose to build a social layer on top of a learning object repository, providing nal users with additional services fordescribing, rating and curating learning objects from a teaching perspective. All these interactions among users, services and resources can be captured and further analyzed, so both browsing and searching can be personalized according to user pro le and the educational context, helping users to nd the most valuable resources for their learning process. In this paper we propose to use reputation schemes and collaborative filtering techniques for improving the user interface of a DSpace based learning object repository.

Qualitative grading of severity of lumbar spinal stenosis based on the morphology of the dural sac on magnetic resonance images.

STUDY DESIGN.: Retrospective radiologic study on a prospective patient cohort. OBJECTIVE.: To devise a qualitative grading of lumbar spinal stenosis (LSS), study its reliability and clinical relevance. SUMMARY OF BACKGROUND DATA.: Radiologic stenosis is assessed commonly by measuring dural sac cross-sectional area (DSCA). Great variation is observed though in surfaces recorded between symptomatic and asymptomatic individuals. METHODS.: We describe a 7-grade classification based on the morphology of the dural sac as observed on T2 axial magnetic resonance images based on the rootlet/cerebrospinal fluid ratio. Grades A and B show cerebrospinal fluid presence while grades C and D show none at all. The grading was applied to magnetic resonance images of 95 subjects divided in 3 groups as follows: 37 symptomatic LSS surgically treated patients; 31 symptomatic LSS conservatively treated patients (average follow-up, 2.5 and 3.1 years); and 27 low back pain (LBP) sufferers. DSCA was also digitally measured. We studied intra- and interobserver reliability, distribution of grades, relation between morphologic grading and DSCA, as well relation between grades, DSCA, and Oswestry Disability Index. RESULTS.: Average intra- and interobserver agreement was substantial and moderate, respectively (k = 0.65 and 0.44), whereas they were substantial for physicians working in the study originating unit. Surgical patients had the smallest DSCA. A larger proportion of C and D grades was observed in the surgical group. Surface measurementsresulted in overdiagnosis of stenosis in 35 patients and under diagnosis in 12. No relation could be found between stenosis grade or DSCA and baseline Oswestry Disability Index or surgical result. C and D grade patients were more likely to fail conservative treatment, whereas grades A and B were less likely to warrant surgery. CONCLUSION.: The grading defines stenosis in different subjects than surface measurements alone. Since it mainly considers impingement of neural tissue it might be a more appropriate clinical and research tool as well as carrying a prognostic value.

Turvallisuustoimintojen käyttö ydinvoimalaitoksilla

Tässä diplomityössä tarkastellaan turvallisuustoiminto-käsitteen määrittelyä ja käyttöä osana ydinvoimalaitosten turvallisuuden varmistamista. Työssä kuvataan paine- ja kiehutusvesilaitosten toiminnan yleispiirteet, sekä Teollisuuden Voima Oy:n (TVO) laitosten Olkiluoto 1 & 2 sekä Olkiluoto 3 tarkempi turvallisuustoiminta turvallisuusjärjestelmien ja -automaation osalta. Työssä esitellään eräs tapa määrittää turvallisuustoimintoja. Malli perustuu hierarkkiseen rakenteeseen, jossa ylimpänä ovat laitostason turvallisuustoiminnot ja alimpana turvallisuustoimintoihin osallistuvien laitteiden ja niiden osien toiminnot. Turvallisuustoimintoja on mahdollista käyttää ydinvoimalaitoksen turvallisuusluokituksen tekemiseen ja perustelemiseen. Turvallisuustoiminto kertoo suoraan luokiteltavan kohteen turvallisuusmerkityksen. Kohteen turvallisuusmerkityksen selvittäminen, eli liittäminen turvallisuustoimintoon, voi olla vaikeaa. Turvallisuustoimintoja on myös mahdollista käyttää laitoksen turvallisuusautomaation riittävän varmistamisen (mm. redundanttisuus, diversiteetti ja erotus) osoittamiseen erityisesti ohjelmoitavan automaation yhteydessä. Turvallisuustoimintoja voidaan hyödyntää laitoksen hätätilanneohjeiden kehittämisessä ja myös laitoksenmuun turvallisuusdokumentaation selkeyttämisessä. Työn tuloksena kehitettiin käyville laitoksille (OL1 & 2) aikaisempaa kattavammat turvallisuustoiminnot. Lisäksi tarkasteltiin rakenteilla olevalle laitokselle (OL3) määriteltyjä turvallisuustoimintoja.

Antipsychotic polypharmacy in a regional health service: a population-based study

Background To analyse the extent and profile of outpatient regular dispensation of antipsychotics, both in combination and monotherapy, in the Barcelona Health Region (Spain), focusing on the use of clozapine and long-acting injections (LAI). Methods Antipsychotic drugs dispensed for people older than 18 and processed by the Catalan Health Service during 2007 were retrospectively reviewed. First and second generation antipsychotic drugs (FGA and SGA) from the Anatomical Therapeutic Chemical classification (ATC) code N05A (except lithium) were included. A patient selection algorithm was designed to identify prescriptions regularly dispensed. Variables included were age, gender, antipsychotic type, route of administration and number of packages dispensed. Results A total of 117,811 patients were given any antipsychotic, of whom 71,004 regularly received such drugs. Among the latter, 9,855 (13.9%) corresponded to an antipsychotic combination, 47,386 (66.7%) to monotherapy and 13,763 (19.4%) to unspecified combinations. Of the patients given antipsychotics in association, 58% were men. Olanzapine (37.1%) and oral risperidone (36.4%) were the most common dispensations. Analysis of the patients dispensed two antipsychotics (57.8%) revealed 198 different combinations, the most frequent being the association of FGA and SGA (62.0%). Clozapine was dispensed to 2.3% of patients. Of those who were receiving antipsychotics in combination, 6.6% were given clozapine, being clozapine plus amisulpride the most frequent association (22.8%). A total of 3.800 patients (5.4%) were given LAI antipsychotics, and 2.662 of these (70.1%) were in combination. Risperidone was the most widely used LAI. Conclusions The scant evidence available regarding the efficacy of combining different antipsychotics contrasts with the high number and variety of combinations prescribed to outpatients, as well as with the limited use of clozapine. Background To analyse the extent and profile of outpatient regular dispensation of antipsychotics, both in combination and monotherapy, in the Barcelona Health Region (Spain), focusing on the use of clozapine and long-acting injections (LAI). Methods Antipsychotic drugs dispensed for people older than 18 and processed by the Catalan Health Service during 2007 were retrospectively reviewed. First and second generation antipsychotic drugs (FGA and SGA) from the Anatomical Therapeutic Chemical classification (ATC) code N05A (except lithium) were included. A patient selection algorithm was designed to identify prescriptions regularly dispensed. Variables included were age, gender, antipsychotic type, route of administration and number of packages dispensed. Results A total of 117,811 patients were given any antipsychotic, of whom 71,004 regularly received such drugs. Among the latter, 9,855 (13.9%) corresponded to an antipsychotic combination, 47,386 (66.7%) to monotherapy and 13,763 (19.4%) to unspecified combinations. Of the patients given antipsychotics in association, 58% were men. Olanzapine (37.1%) and oral risperidone (36.4%) were the most common dispensations. Analysis of the patients dispensed two antipsychotics (57.8%) revealed 198 different combinations, the most frequent being the association of FGA and SGA (62.0%). Clozapine was dispensed to 2.3% of patients. Of those who were receiving antipsychotics in combination, 6.6% were given clozapine, being clozapine plus amisulpride the most frequent association (22.8%). A total of 3.800 patients (5.4%) were given LAI antipsychotics, and 2.662 of these (70.1%) were in combination. Risperidone was the most widely used LAI. Conclusions The scant evidence available regarding the efficacy of combining different antipsychotics contrasts with the high number and variety of combinations prescribed to outpatients, as well as with the limited use of clozapine.