Desarrollo de aplicaciones en entornos de software libre

El projecte té com idea fonamental crear un programari que permeti la instal·lació de paquets per mitjà de la xarxa en diverses màquines que es trobin registrades en la Base de dades, i a la vegada, es tenen dos mòduls un per a l'aplicació servidor i altre per a l'aplicació client.

Disseny i implantació de l'estructura informàtica de DaVinci School

Creació d'una infraestructura informàtica d'un centre educatiu, amb xarxes separades per a aules, secretaria i seminaris. Serveis centralitzats en un servidor amb màquines virtuals.

Refrigeració de les gillettes d’ una talladora industrial

L’empresa Proslit Equipment forma part del Grup Comexi i la seva activitat consisteix en la fabricació de màquines talladores de material flexible. Degut als avenços tecnològics, s’han incrementat les prestacions de les seves màquines, entre altres coses, s’ha augmentat la velocitat de tall del film fins a 800 m/min. Aquest factor afegit a condicionants com per exemple treballar amb materials gruixuts i abrasius, a temperatures ambientals elevades, etc. fa que sorgeixi una problemàtica en el tall gillette. Degut a la fricció entre el film que circula i les gillettes que el tallen, es crea una energia calorífica que fa augmentar la temperatura de les gillettes fins a tal extrem que aquestes provoquen petites fusions del plàstic, aquest s’incrusta a les gillettes que s’acaben trencant. L’objecte principal d’aquest projecte és fer una anàlisi tècnica mitjançant elements finits de la problemàtica que s’ha detectat a les màquines talladores de l’empresa Proslit Equipment, concretament de l’escalfament de les gillettes utilitzades en el sistema de tall. Es pretén crear un model teòric que s’aproximi al màxim a la realitat de manera que es pugui observar el comportament tèrmic del sistema de tall en funció de les condicions que es determinin com a més desfavorables. Una vegada s’obtinguin aquests resultats teòrics, es valoraran i es proposaran solucions

Solucions per a la virtualització de servidors

Projecte sobre la comparativa de cinc solucions de virtualització centrant-nos especialment en el rendiment de les màquines virtualitzades, extraient informació d'aquestes mitjançant la utilització de benchmarks i posterior anàlisi de les dades obtingudes.

Viri, Remote execution of Python scripts

Viri is a system for automatic distribution and execution of Python code on remote machines. This is especially useful when dealing with a large group of hosts.With Viri, Sysadmins can write their own scripts, and easily distribute and execute them on any number of remote machines. Depending on the number of computers to administrate, Viri can save thousands of hours, that Sysadmins would spend transferring files, logging into remote hosts, and waiting for the scripts to finish. Viri automates the whole process.Viri can also be useful for remotely managing host settings. It should work together with an application where the information about hosts would be maintained. This information can include cron tasks, firewall rules, backup settings,... After a simple Integration of this application with your Viri infrastructure, you can change any settings in the application, and see how it gets applied on the target host automatically.

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Identification of pharmaceutical tablets by Raman spectroscopy and chemometrics

Raman spectroscopy has become an attractive tool for the analysis of pharmaceutical solid dosage forms. In the present study it is used to ensure the identity of tablets. The two main applications of this method are release of final products in quality control and detection of counterfeits. Twenty-five product families of tablets have been included in the spectral library and a non-linear classification method, the Support Vector Machines (SVMs), has been employed. Two calibrations have been developed in cascade: the first one identifies the product family while the second one specifies the formulation. A product family comprises different formulations that have the same active pharmaceutical ingredient (API) but in a different amount. Once the tablets have been classified by the SVM model, API peaks detection and correlation are applied in order to have a specific method for the identification and allow in the future to discriminate counterfeits from genuine products. This calibration strategy enables the identification of 25 product families without error and in the absence of prior information about the sample. Raman spectroscopy coupled with chemometrics is therefore a fast and accurate tool for the identification of pharmaceutical tablets.

Decision fusion for the classification of hyperspectral data: Outcome of the 2008 GRS-S data fusion contest

The 2008 Data Fusion Contest organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee deals with the classification of high-resolution hyperspectral data from an urban area. Unlike in the previous issues of the contest, the goal was not only to identify the best algorithm but also to provide a collaborative effort: The decision fusion of the best individual algorithms was aiming at further improving the classification performances, and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, dimension reduction, and supervised classification methods, such as neural networks and support vector machines.

Infraestructura de comunicaciones para algoritmos colaborativos

Este proyecto intenta crear un sistema cliente/servidor de comunicaciones para distintas máquinas paralelas en C++ utilizando WCF como tecnología en el servidor.

Health effects of occupational exposure to traffic particles and noise

Exposure to fine particles and noise has been linked to cardiovascular diseases and elevated cardiovascular mortality affecting the worldwide population. Residence and/or work in proximity to emission sources as for example road traffic leads to an elevated exposure and a higher risk for adverse health effects. Highway maintenance workers spend most of their work time in traffic and are exposed regularly to particles and noise. The aims of this thesis were to provide a better understanding of the workers' mixed exposure to particles and noise and to assess cardiopulmonary short term health effects in relation to this exposure. Exposure and health data were collected in collaboration with 8 maintenance centers of the Swiss Road Maintenance Services located in the cantons Bern, Fribourg and Vaud in western Switzerland. Repeated measurements with 18 subjects were conducted during 50 non-consecutive work shifts between Mai 2010 and February 2012, equally distributed over all seasons. In the first part of this thesis we tested and validated measurements of ultrafine particles with a miniature diffusion size classifier (miniDiSC) - a novel particle counting device that was used for the exposure assessment during highway maintenance work. We found that particle numbers and average particle size measured by the miniDiSC were highly correlated with data from the P-TRAK, a condensation particle counter (CPC), as well as from a scanning mobility particle sizer (SMPS). However, the miniDiSC measured significantly more particles than the P-TRAK and significantly less than the SMPS in its full size range. Our data suggests that the instrument specific cutoffs were the main reason for the different particle counts. The first main objective of this thesis was to investigate the exposure of highway maintenance workers to air pollutants and noise, in relation to the different maintenance activities. We have seen that the workers are regularly exposed to high particle and noise levels. This was a consequence of close proximity to highway traffic and the use of motorized working equipment such as brush cutters, chain saws, generators and pneumatic hammers during which the highest exposure levels occurred. Although exposure to air pollutants were not critical if compared to occupational exposure limits, the elevated exposure to particles and noise may lead to a higher risk for cardiovascular diseases in this worker population. The second main objective was to investigate cardiopulmonary short-term health effects in relation to the particle and noise exposure during highway maintenance work. We observed a PM2.5 related increase of the acute-phase inflammation markers C-reactive protein and serum amyloid A and a decrease of TNFa. Heart rate variability increased as a consequence of particle as well as noise exposure. Increased high frequency power indicated a stronger parasympathetic influence on the heart. Elevated noise levels during recreational time, after work, were related to increased blood pressure. Our data confirmed that highway maintenance workers are exposed to elevated levels of particles and noise as compared to the average population. This exposure poses a cardiovascular health risk and it is therefore important to make efforts to better protect the workers health. The use of cleaner machines during maintenance work would be a major step to improve the workers' situation. Furthermore, regulatory policies with the aim of reducing combustion and non-combustion emissions from road traffic are important for the protection of workers in traffic environments and the entire population.

Whole-Body Vibration Training Elevates Creatine-Kinase Levels in Sedentary Subjects

METHODS: 20 inactive (10 male, 10 female) underwent a single typical WBV session, with a total of 27 minutes of exercise on an oscillating platform at 26 Hz, involving upper and lower body muscles. Each exercise lasted 90 seconds, with 40 seconds pauses inbetween. Muscle enzymes (CK, transaminase, LDH, troponin I) were measured before, at 24, 48 and 96 hours post exercise. Lactate was measured immediately after the session. Muscle aches were assessed during 4 days post-exercise.RESULTS: Subjects' mean age was 23.0 ± 3.5 (male), 22.4 ± 1.4 (female), BMI 22.8 ± 2.3 and 22.1 ± 1.9, and all had been inactive for at least 12 months. Post exercise lactatemia was 10.0 ± 2.4 and 6.9 ± 2.4. CK elevation was significant (at least doubling of baseline values) in 1 male and 4 female subjects, while they remained at baseline values for the remaining 15 subjects. One female subject peaked at 3520 U/l at 96 hours post exercise, and all but one peaked at the same late time. Troponin and CK-MB never increased. No correlation was found between muscle soreness and CK levels.CONCLUSIONS: WBV can elicit important anaerobic processes reflected by the high lactacidemia, and CK elevation was significant in 25 % of subjects, peaking at the fourth day after exercise for 80 % of those. Such exercises should not be regarded as trivial and "easy" as they are advertised, since they can provoke important anaerobia and CK elevation. Many fragile patients or patients treated for cardiovascular disease could benefit from WBV but it is important to recognise these potential effects, especially in those treated with statins, known to cause a myopathy and CK elevation. Before considering a side effect of an important therapeutic agent, doctors should be aware of the possible interaction with not-so-harmless exercising machines.

The differentiation of fibre- and drug type Cannabis seedlings by gas chromatography/mass spectrometry and chemometric tools

Cannabis cultivation in order to produce drugs is forbidden in Switzerland. Thus, law enforcement authorities regularly ask forensic laboratories to determinate cannabis plant's chemotype from seized material in order to ascertain that the plantation is legal or not. As required by the EU official analysis protocol the THC rate of cannabis is measured from the flowers at maturity. When laboratories are confronted to seedlings, they have to lead the plant to maturity, meaning a time consuming and costly procedure. This study investigated the discrimination of fibre type from drug type Cannabis seedlings by analysing the compounds found in their leaves and using chemometrics tools. 11 legal varieties allowed by the Swiss Federal Office for Agriculture and 13 illegal ones were greenhouse grown and analysed using a gas chromatograph interfaced with a mass spectrometer. Compounds that show high discrimination capabilities in the seedlings have been identified and a support vector machines (SVMs) analysis was used to classify the cannabis samples. The overall set of samples shows a classification rate above 99% with false positive rates less than 2%. This model allows then discrimination between fibre and drug type Cannabis at an early stage of growth. Therefore it is not necessary to wait plants' maturity to quantify their amount of THC in order to determine their chemotype. This procedure could be used for the control of legal (fibre type) and illegal (drug type) Cannabis production.

Monitoring of posture allocations and activities by a shoe-based wearable sensor.

Monitoring of posture allocations and activities enables accurate estimation of energy expenditure and may aid in obesity prevention and treatment. At present, accurate devices rely on multiple sensors distributed on the body and thus may be too obtrusive for everyday use. This paper presents a novel wearable sensor, which is capable of very accurate recognition of common postures and activities. The patterns of heel acceleration and plantar pressure uniquely characterize postures and typical activities while requiring minimal preprocessing and no feature extraction. The shoe sensor was tested in nine adults performing sitting and standing postures and while walking, running, stair ascent/descent and cycling. Support vector machines (SVMs) were used for classification. A fourfold validation of a six-class subject-independent group model showed 95.2% average accuracy of posture/activity classification on full sensor set and over 98% on optimized sensor set. Using a combination of acceleration/pressure also enabled a pronounced reduction of the sampling frequency (25 to 1 Hz) without significant loss of accuracy (98% versus 93%). Subjects had shoe sizes (US) M9.5-11 and W7-9 and body mass index from 18.1 to 39.4 kg/m2 and thus suggesting that the device can be used by individuals with varying anthropometric characteristics.

Beliefs about and attitudes toward gambling in French-speaking Switzerland.

The present study aims to analyze attitudes and beliefs of the French-speaking general Swiss population (n = 2500; female n = 1280; mean age = 43 years) as regards gambling, which are to date almost exclusively studied in the North American and Australian contexts. Beliefs related to gambling include the perception of the effectiveness of preventive measures toward gambling, the comparative risk assessment of different addictive behaviors, the perceived risks of different types of gambling and attitudes are related to the gambler's personality. The general population perceived gambling rather negatively and was conscious of the potential risks of gambling; indeed, 59.0% of the sample identified gambling as an addictive practice. Slot machines were estimated to bear the highest risk. Compared with women and older people, men and young people indicated more positive beliefs about gambling; they perceived gambling as less addictive, supported structural preventive measures less often, and perceived gambling as a less serious problem for society. Gamblers were more likely to put their practices into perspective, perceiving gambling more positively than non-gamblers. General population surveys on such beliefs can deliver insights into preventive actions that should be targeted to young men who showed more favorable views of gambling, which have been shown to be associated with increased risk for problematic gambling.

Sähkökoneen staattorikäämityksen kehittäminen

Tämä insinöörityö tehtiin ABB:n Pitäjänmäen konetehtaalle Tahtikoneet-tulosyksikölle. Työssä tutkittiin mahdollisuuksia valmistaa murtovakovyyhtejä kestomagneettituuligeneraattoreihin, joissa vakoluku on alle yhden. Työ tehtiin tutustumalla aluksi Pitäjänmäen konetehtaan käytössä oleviin vyyhden valmistus- ja käämintämenetelmiin. Lisäksi tutkittiin erilaisia mahdollisia murtovakovyyhden valmistusmenetelmiä, joista lupaavimpia myös kokeiltiin. Saatujen kokemusten pohjalta valittiin vyyhden valmistusmenetelmä, jonka mukaan valmistettiin koe-erä. Koe-erälle suoritettiin mittauksia, joilla varmistettiin niiden sähköinen kestävyys Työn tuloksena valitulla valmistusmenetelmällä valmistettiin vyyhdet prototyyppi tuuligeneraattorin.