In-situ formation of solidified hydrogen thin-membrane targets using a pulse tube cryocooler

An account is given of the Central Laser Facility's work to produce a cryogenic hydrogen targetry system using a pulse tube cryocooler. Due to the increasing demand for low Z thin laser targets, CLF (in collaboration with TUD) have been developing a system which allows the production of solid hydrogen membranes by engineering a design which can achieve this remotely; enabling the gas injection, condensation and solidification of hydrogen without compromising the vacuum of the target chamber. A dynamic sealing mechanism was integrated which allows targets to be grown and then remotely exposed to open vacuum for laser interaction. Further research was conducted on the survivability of the cryogenic targets which concluded that a warm gas effect causes temperature spiking when exposing the solidified hydrogen to the outer vacuum. This effect was shown to be mitigated by improving the pumping capacity of the environment and reducing the minimum temperature obtainable on the target mount. This was achieved by developing a two-stage radiation shield encased with superinsulating blanketing; reducing the base temperature from 14 0.5 K to 7.2 0.2 K about the coldhead as well as improving temperature control stability following the installation of a high-performance temperature controller and sensor apparatus. The system was delivered experimentally and in July 2014 the first laser shots were taken upon hydrogen targets in the Vulcan TAP facility.

Laboratory investigation of contactless displacement measurement using computer vision systems

Much of the bridge stock on major transport links in North America and Europe was constructed in the 1950’s and 1960’s and has since deteriorated or is carrying loads far in excess of the original design loads. Structural Health Monitoring Systems (SHM) can provide valuable information on the bridge capacity but the application of such systems is currently limited by access and system cost. This paper investigates the development of a low cost portable SHM system using commercially available cameras and computer vision techniques. A series of laboratory tests have been carried out to test the accuracy of displacement measurements using contactless methods. The results from each of the tests have been validated with established measurement methods, such as linear variable differential transformers (LVDTs). A video image of each test was processed using two different digital image correlation programs. The results obtained from the digital image correlation methods provided an accurate comparison with the validation measurements. The calculated displacements agree within 4% of the verified measurements LVDT measurements in most cases confirming the suitability full camera based SHM systems

Development of an active orthosis prototype for lower limbs

ARAUJO, Márcio V. ; ALSINA, Pablo J. ; MEDEIROS, Adelardo A. D. ; PEREIRA, Jonathan P.P. ; DOMINGOS, Elber C. ; ARAÚJO, Fábio M.U. ; SILVA, Jáder S. . Development of an Active Orthosis Prototype for Lower Limbs. In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING, 20., 2009, Gramado, RS. Proceedings… Gramado, RS: [s. n.], 2009

Utilización de redes neuronales recurrentes para el análisis de firmas

[EN]This grade project involves the study, design, implementation and test of an signature identification system using neural networks. Recurrent neural networks,also known as recursive neural networks, show a architectonic configuration that able output signals to be fed back to the same, or previous neurons. This feature can be used, as in this project, to build a system especialized on temporal pattern recognition, given that signatures can be seen as sequence of points in time.

Development of an active orthosis prototype for lower limbs

ARAUJO, Márcio V. ; ALSINA, Pablo J. ; MEDEIROS, Adelardo A. D. ; PEREIRA, Jonathan P.P. ; DOMINGOS, Elber C. ; ARAÚJO, Fábio M.U. ; SILVA, Jáder S. . Development of an Active Orthosis Prototype for Lower Limbs. In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING, 20., 2009, Gramado, RS. Proceedings… Gramado, RS: [s. n.], 2009

Neuromorphic model for sound source segregation

While humans can easily segregate and track a speaker's voice in a loud noisy environment, most modern speech recognition systems still perform poorly in loud background noise. The computational principles behind auditory source segregation in humans is not yet fully understood. In this dissertation, we develop a computational model for source segregation inspired by auditory processing in the brain. To support the key principles behind the computational model, we conduct a series of electro-encephalography experiments using both simple tone-based stimuli and more natural speech stimulus. Most source segregation algorithms utilize some form of prior information about the target speaker or use more than one simultaneous recording of the noisy speech mixtures. Other methods develop models on the noise characteristics. Source segregation of simultaneous speech mixtures with a single microphone recording and no knowledge of the target speaker is still a challenge. Using the principle of temporal coherence, we develop a novel computational model that exploits the difference in the temporal evolution of features that belong to different sources to perform unsupervised monaural source segregation. While using no prior information about the target speaker, this method can gracefully incorporate knowledge about the target speaker to further enhance the segregation.Through a series of EEG experiments we collect neurological evidence to support the principle behind the model. Aside from its unusual structure and computational innovations, the proposed model provides testable hypotheses of the physiological mechanisms of the remarkable perceptual ability of humans to segregate acoustic sources, and of its psychophysical manifestations in navigating complex sensory environments. Results from EEG experiments provide further insights into the assumptions behind the model and provide motivation for future single unit studies that can provide more direct evidence for the principle of temporal coherence.

W-CDMA capacity analysis using GIS based planning tools and MATLAB simulation

The evolution of cellular systems towards third generation (3G) or IMT-2000 seems to have a tendency to use W-CDMA as the standard access method, as ETSI decisions have showed. However, there is a question about the improvements in capacity and the wellness of this access method. One of the aspects that worry developers and researchers planning the third generation is the extended use of the Internet and more and more bandwidth hungry applications. This work shows the performance of a W-CDMA system simulated in a PC using cover maps generated with DC-Cell, a GIS based planning tool developed by the Technical University of Valencia, Spain. The maps are exported to MATLAB and used in the model. The system used consists of several microcells in a downtown area. We analyse the interference from users in the same cell and in adjacent cells and the effect in the system, assuming perfect control for each cell. The traffic generated by the simulator is voice and data. This model allows us to work with coverage that is more accurate and is a good approach to analyse the multiple access interference (MAI) problem in microcellular systems with irregular coverage. Finally, we compare the results obtained, with the performance of a similar system using TDMA.

Fabrication and Pseudo-Analog Characteristics of Ta2O5 -Based ReRAM Cell

Memristori on yksi elektroniikan peruskomponenteista vastuksen, kondensaattorin ja kelan lisäksi. Se on passiivinen komponentti, jonka teorian kehitti Leon Chua vuonna 1971. Kesti kuitenkin yli kolmekymmentä vuotta ennen kuin teoria pystyttiin yhdistämään kokeellisiin tuloksiin. Vuonna 2008 Hewlett Packard julkaisi artikkelin, jossa he väittivät valmistaneensa ensimmäisen toimivan memristorin. Memristori eli muistivastus on resistiivinen komponentti, jonka vastusarvoa pystytään muuttamaan. Nimens mukaisesti memristori kykenee myös säilyttämään vastusarvonsa ilman jatkuvaa virtaa ja jännitettä. Tyypillisesti memristorilla on vähintään kaksi vastusarvoa, joista kumpikin pystytään valitsemaan syöttämällä komponentille jännitettä tai virtaa. Tämän vuoksi memristoreita kutsutaankin usein resistiivisiksi kytkimiksi. Resistiivisiä kytkimiä tutkitaan nykyään paljon erityisesti niiden mahdollistaman muistiteknologian takia. Resistiivisistä kytkimistä rakennettua muistia kutsutaan ReRAM-muistiksi (lyhenne sanoista resistive random access memory). ReRAM-muisti on Flash-muistin tapaan haihtumaton muisti, jota voidaan sähköisesti ohjelmoida tai tyhjentää. Flash-muistia käytetään tällä hetkellä esimerkiksi muistitikuissa. ReRAM-muisti mahdollistaa kuitenkin nopeamman ja vähävirtaiseman toiminnan Flashiin verrattuna, joten se on tulevaisuudessa varteenotettava kilpailija markkinoilla. ReRAM-muisti mahdollistaa myös useammin bitin tallentamisen yhteen muistisoluun binäärisen (”0” tai ”1”) toiminnan sijaan. Tyypillisesti ReRAM-muistisolulla on kaksi rajoittavaa vastusarvoa, mutta näiden kahden tilan välille pystytään mahdollisesti ohjelmoimaan useampia tiloja. Muistisoluja voidaan kutsua analogisiksi, jos tilojen määrää ei ole rajoitettu. Analogisilla muistisoluilla olisi mahdollista rakentaa tehokkaasti esimerkiksi neuroverkkoja. Neuroverkoilla pyritään mallintamaan aivojen toimintaa ja suorittamaan tehtäviä, jotka ovat tyypillisesti vaikeita perinteisille tietokoneohjelmille. Neuroverkkoja käytetään esimerkiksi puheentunnistuksessa tai tekoälytoteutuksissa. Tässä diplomityössä tarkastellaan Ta2O5 -perustuvan ReRAM-muistisolun analogista toimintaa pitäen mielessä soveltuvuus neuroverkkoihin. ReRAM-muistisolun valmistus ja mittaustulokset käydään läpi. Muistisolun toiminta on harvoin täysin analogista, koska kahden rajoittavan vastusarvon välillä on usein rajattu määrä tiloja. Tämän vuoksi toimintaa kutsutaan pseudoanalogiseksi. Mittaustulokset osoittavat, että yksittäinen ReRAM-muistisolu kykenee binääriseen toimintaan hyvin. Joiltain osin yksittäinen solu kykenee tallentamaan useampia tiloja, mutta vastusarvoissa on peräkkäisten ohjelmointisyklien välillä suurta vaihtelevuutta, joka hankaloittaa tulkintaa. Valmistettu ReRAM-muistisolu ei sellaisenaan kykene toimimaan pseudoanalogisena muistina, vaan se vaati rinnalleen virtaa rajoittavan komponentin. Myös valmistusprosessin kehittäminen vähentäisi yksittäisen solun toiminnassa esiintyvää varianssia, jolloin sen toiminta muistuttaisi enemmän pseudoanalogista muistia.

Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.

O papel do inflamassoma na infecção induzida pelas formas saprofíticas do fungo Fonsecaea pedrosoi

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Medicina, Programa de Pós-Graduação em Patologia Molecular, 2016.

Probability and Common-Sense: Tandem Towards Robust Robotic Object Recognition in Ambient Assisted Living

The suitable operation of mobile robots when providing Ambient Assisted Living (AAL) services calls for robust object recognition capabilities. Probabilistic Graphical Models (PGMs) have become the de-facto choice in recognition systems aiming to e ciently exploit contextual relations among objects, also dealing with the uncertainty inherent to the robot workspace. However, these models can perform in an inco herent way when operating in a long-term fashion out of the laboratory, e.g. while recognizing objects in peculiar con gurations or belonging to new types. In this work we propose a recognition system that resorts to PGMs and common-sense knowledge, represented in the form of an ontology, to detect those inconsistencies and learn from them. The utilization of the ontology carries additional advantages, e.g. the possibility to verbalize the robot's knowledge. A primary demonstration of the system capabilities has been carried out with very promising results.

Equivalent Hearing Loss in Children

Early intervention is the key to spoken language for hearing impaired children. A severe hearing loss diagnosis in young children raises the urgent question on the optimal type of hearing aid device. As there is no recent data on comparing selection criteria for a specific hearing aid device, the goal of the Hearing Evaluation of Auditory Rehabilitation Devices (hEARd) project (Coninx & Vermeulen, 2012) evolved to collect and analyze interlingually comparable normative data on the speech perception performances of children with hearing aids and children with cochlear implants (CI). METHOD: In various institutions for hearing rehabilitation in Belgium, Germany and the Netherlands the Adaptive Auditory Speech Test AAST was used in the hEARd project, to determine speech perception abilities in kindergarten and school aged hearing impaired children. Results in the speech audiometric procedures were matched to the unaided hearing loss values of children using hearing aids and compared to results of children using CI. 277 data sets of hearing impaired children were analyzed. Results of children using hearing aids were summarized in groups as to their unaided hearing loss values. The grouping was related to the World Health Organization’s (WHO) grading of hearing impairment from mild (25–40 dB HL) to moderate (41–60 dB HL), severe (61-80 dB HL) and profound hearing impairment (80 dB HL and higher). RESULTS: AAST speech recognition results in quiet showed a significantly better performance for the CI group in comparison to the group of profoundly impaired hearing aid users as well as the group of severely impaired hearing aid users. However the CI users’ performances in speech perception in noise did not vary from the hearing aid users’ performances. Within the collected data analyses showed that children with a CI show an equivalent performance on speech perception in quiet as children using hearing aids with a “moderate” hearing impairment.

A micro-extraction technique using a new digitally controlled syringe combined with UHPLC for assessment of urinary biomarkers of oxidatively damaged DNA

The formation of reactive oxygen species (ROS) within cells causes damage to biomolecules, including membrane lipids, DNA, proteins and sugars. An important type of oxidative damage is DNA base hydroxylation which leads to the formation of 8-oxo-7,8-dihydro-29-deoxyguanosine (8-oxodG) and 5-hydroxymethyluracil (5-HMUra). Measurement of these biomarkers in urine is challenging, due to the low levels of the analytes and the matrix complexity. In order to simultaneously quantify 8-oxodG and 5-HMUra in human urine, a new, reliable and powerful strategy was optimised and validated. It is based on a semi-automatic microextraction by packed sorbent (MEPS) technique, using a new digitally controlled syringe (eVolH), to enhance the extraction efficiency of the target metabolites, followed by a fast and sensitive ultrahigh pressure liquid chromatography (UHPLC). The optimal methodological conditions involve loading of 250 mL urine sample (1:10 dilution) through a C8 sorbent in a MEPS syringe placed in the semi-automatic eVolH syringe followed by elution using 90 mL of 20% methanol in 0.01% formic acid solution. The obtained extract is directly analysed in the UHPLC system using a binary mobile phase composed of aqueous 0.1% formic acid and methanol in the isocratic elution mode (3.5 min total analysis time). The method was validated in terms of selectivity, linearity, limit of detection (LOD), limit of quantification (LOQ), extraction yield, accuracy, precision and matrix effect. Satisfactory results were obtained in terms of linearity (r2 . 0.991) within the established concentration range. The LOD varied from 0.00005 to 0.04 mg mL21 and the LOQ from 0.00023 to 0.13 mg mL21. The extraction yields were between 80.1 and 82.2 %, while inter-day precision (n=3 days) varied between 4.9 and 7.7 % and intra-day precision between 1.0 and 8.3 %. This approach presents as main advantages the ability to easily collect and store urine samples for further processing and the high sensitivity, reproducibility, and robustness of eVolHMEPS combined with UHPLC analysis, thus retrieving a fast and reliable assessment of oxidatively damaged DNA.

Reconhecimento de entidades mencionadas usando o Google

O Reconhecimento de Entidades Mencionadas tem como objectivo identificar e classificar entidades, baseando-se em determinadas categorias ou etiquetas, contidas em textos escritos em linguagem natural. O Sistema de Reconhecimento de Entidades Mencionadas implementado na elaboração desta Dissertação pretende identificar localidades presentes em textos informais e definir para cada localidade identificada uma das etiquetas “aldeia", "vila" ou “cidade" numa primeira aproximação ao problema. Numa segunda aproximação tiveram-se em conta as etiquetas "freguesia", "concelho" e "distrito". Para a obtenção das classificações das entidades procedeu-se a uma análise estatística do número de resultados obtidos numa pesquisa de uma entidade precedida por uma etiqueta usando o motor de pesquisa Google Search. ABSTRACT: Named Entitity Recognition has the objective of identifying and classifying entities, according to certain categories or labels, contained in texts written in natural language. The Named Entitity Recognition system implemented in the developing of this dissertation intends to identify localities in informal texts, setting for each one of these localities identified one of the labels "aldeia", ''vila" or "cidade" in a first approach to the problem. ln a second approach the labels "freguesia", "concelho" and "distrito" were taken in consideration. To obtain classifications for the entities a statistical analysis of the number of results returned by a search of an entity preceded by a label using Google search engine was performed.

Age and Gender Identification using Stacking for Classification⋆ Notebook for PAN at CLEF 2016

This paper presents our approach of identifying the profile of an unknown user based on the activities of known users. The aim of author profiling task of PAN@CLEF 2016 is cross-genre identification of the gender and age of an unknown user. This means training the system using the behavior of different users from one social media platform and identifying the profile of other user on some different platform. Instead of using single classifier to build the system we used a combination of different classifiers, also known as stacking. This approach allowed us explore the strength of all the classifiers and minimize the bias or error enforced by a single classifier.