993 resultados para Hybrid working machines
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Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories
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We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos
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This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors
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Purpose: Collaboration and interprofessional practices are highly valued in health systems everywhere, partly based on the rationale that they improve outcomes of care for people with complex health problems, such as low back pain. Research in the area of low back pain also supports the involvement of different health professionals in the interventions for people who present this condition. The aim of this studywas to identify factors influencing the interprofessional practices of physiotherapists working in private settings with people with low back pain. Relevance: Physiotherapists, like other health professionals, are encouraged to engage in interprofessional practices in their dailywork. However, to date, very little is known of their interprofessional practices, especially in private settings. Understanding physiotherapists' interprofessional practices and their influencing factors will notably advance knowledge relating to the organisation of physiotherapy services for people with low back pain. Participants: Participants in this study were 13 physiotherapists including 10 women and 3 men, having between 3 and 22 years of professional experience, and working in one of 10 regions of the Province of Quebec (Canada). In order to obtain maximal variation in the perspectives, participants were selected using a recruitment matrix including three criteria: duration of professional experience, work location, and physical proximity with other professionals. Methods: Thiswas a descriptive qualitative study using faceto- face semi-structured interviews as the main method of data collection. An interview guide was developed based on an evidence-derived frame of reference. Each interview lasted between 55 and 95 minutes and was transcribed verbatim. Analysis: Qualitative analyses took the form of content analysis, encompassing data coding and general thematic regrouping. NVivo version 8 was used to assist data organisation and analysis. Results: Multiple factors influencing the interprofessional practices of physiotherapists were identified. The main factors include the consulting person's health condition, the extent of knowledge on health professionals' roles and fields of practice, the proximity and availability of professional resources, as well as daily work schedules. Conclusions: Our findings highlight the influence of multiple factors on physiotherapists' interprofessional practices, including professional practice and organisational issues. However, further research on the interprofessional practices of physiotherapists is still required. Research priorities targeting the views of other health professionals, as well as those of services users, would enhance our comprehension of interprofessional practices of physiotherapists. Implications: This study provides new insights that improve our understanding of the interprofessional practices of physiotherapists working in private settings with people with low back pain, more specifically on the factors influencing these practices. Based on our findings, implementing changes such as improving current and future health professionals' knowledge of the fields and roles of other health professionals through training may contribute to positively influencing interprofessional practices. Keywords: Interprofessional practices; Private practice; Low back pain Funding acknowledgements: This research was supported in part by a B.E. Schnurr Memorial Fund Research Grant administered by the Physiotherapy Foundation of Canada, as well as from a clinical research partnership in physiotherapy between the Quebec Rehabilitation Research Network (REPAR) and the Ordre professionnel de la physiothérapie du Québec (OPPQ). KP received doctoral-level scholarships from the Canadian Institutes of Health Research (CIHR) and the Institut de recherche Robert-Sauvé en santé et en sécurité du travail (IRSST). CE Dionne is a FRSQ senior Research Scholar. Ethics approval: This project was approved by the ethics research committee of the Institut de réadaptation en déficience physique de Québec.
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Most hybrid zones have existed for hundreds or thousands of years but have generally been observed for only a short time period. Studies extending over periods long enough to track evolutionary changes in the zones or assess the ultimate outcome of hybridization are scarce. Here, we describe the evolution over time of the level of genetic isolation between two karyotypically different species of shrews (Sorex araneus and Sorex antinorii) at a hybrid zone located in the Swiss Alps. We first evaluated hybrid zone movement by contrasting patterns of gene flow and changes in cline parameters (centre and width) using 24 microsatellite loci, between two periods separated by 10 years apart. Additionally, we tested the role of chromosomal rearrangements on gene flow by analysing microsatellite loci located on both rearranged and common chromosomes to both species. We did not detect any movement of the hybrid zone during the period analysed, suggesting that the zone is a typical tension zone. However, the gene flow was significantly lower among the rearranged than the common chromosomes for the second period, whereas the difference was only marginally significant for the first period. This further supports the role of chromosomal rearrangements on gene flow between these taxa.
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BACKGROUND Although Hodgkin's lymphoma is a highly curable disease with modern chemotherapy protocols, some patients are primary refractory or relapse after first-line chemotherapy or even after high-dose therapy and autologous stem cell transplantation. We investigated the potential role of allogeneic stem cell transplantation in this setting. DESIGN AND METHODS In this phase II study 92 patients with relapsed Hodgkin's lymphoma and an HLA-identical sibling, a matched unrelated donor or a one antigen mismatched, unrelated donor were treated with salvage chemotherapy followed by reduced intensity allogeneic transplantation. Fourteen patients showed refractory disease and died from progressive lymphoma with a median overall survival after trial entry of 10 months (range, 6-17). Seventy-eight patients proceeded to allograft (unrelated donors, n=23). Fifty were allografted in complete or partial remission and 28 in stable disease. Fludarabine (150 mg/m(2) iv) and melphalan (140 mg/m(2) iv) were used as the conditioning regimen. Anti-thymocyte globulin was additionally used as graft-versus-host-disease prophylaxis for recipients of grafts from unrelated donors. RESULTS The non-relapse mortality rate was 8% at 100 days and 15% at 1 year. Relapse was the major cause of failure. The progression-free survival rate was 47% at 1 year and 18% at 4 years from trial entry. For the allografted population, the progression-free survival rate was 48% at 1 year and 24% at 4 years. Chronic graft-versus-host disease was associated with a lower incidence of relapse. Patients allografted in complete remission had a significantly better outcome. The overall survival rate was 71% at 1 year and 43% at 4 years. CONCLUSIONS Allogeneic stem cell transplantation can result in long-term progression-free survival in heavily pre-treated patients with Hodgkin's lymphoma. The reduced intensity conditioning approach significantly reduced non-relapse mortality; the high relapse rate represents the major remaining challenge in this setting. The HDR-Allo trial was registered in the European Clinical Trials Database (EUDRACT, https://eudract.ema.europa.eu/) with number 02-0036.
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L'objectiu d'aquest projecte ha estat el desenvolupament d'algorismes biològicament inspirats per a l'olfacció artificial. Per a assolir-lo ens hem basat en el paradigma de les màquines amb suport vectorial. Hem construit algoritmes que imitaven els processos computacionals dels diferents sistemes que formen el sistema olfactiu dels insectes, especialment de la llagosta Schistocerca gregaria. Ens hem centrat en el lòbuls de les antenes, i en el cos fungiforme. El primer està considerat un dispositiu de codificació de les olors, que a partir de la resposta temporal dels receptors olfactius a les antenes genera un patró d'activació espaial i temporal. Quant al cos fungiforme es considera que la seva funció és la d'una memòria per als olors, així com un centre per a la integració multi-sensorial. El primer pas ha estat la construcció de models detallats dels dos sistemes. A continuació, hem utilitzat aquests models per a processar diferents tipus de senyals amb l'objectiu de abstraure els principis computacionals subjacents. Finalment, hem avaluat les capacitats d'aquests models abstractes, i els hem utilitzat per al processat de dades provinents de sensors de gasos. Els resultats mostren que el models abstractes tenen millor comportament front el soroll i més capacitat d'emmagatzematge de records que altres models més clàssics, com ara les memòries associatives de Hopfield o fins i tot en determinades circumstàncies que les mateixes Support Vector Machines.
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Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.
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INTRODUCTION: The analysis of glucosinolates (GS) is traditionally performed by reverse-phase liquid chromatography coupled to ultraviolet detection after a time-consuming desulphation step, which is required for increased retention. Simpler and more efficient alternative methods that can shorten both sample preparation and analysis are much needed. OBJECTIVE: To evaluate the feasibility of using ultrahigh-pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOFMS) for the rapid profiling of intact GS. METHODOLOGY: A simple and short extraction of GS from Arabidopsis thaliana leaves was developed. Four sub-2 µm reverse-phase columns were tested for the rapid separation of these polar compounds using formic acid as the chromatographic additive. High-resolution QTOFMS was used to detect and identify GS. RESULTS: A novel charged surface hybrid (CSH) column was found to provide excellent retention and separation of GS within a total running time of 11 min. Twenty-one GS could be identified based on their accurate mass as well as isotopic and fragmentation patterns. The method was applied to determine the changes in GS content that occur after herbivory in Arabidopsis. In addition, we evaluated its applicability to the profiling of other Brassicaceae species. CONCLUSION: The method developed can profile the full range of GS, including the most polar ones, in a shorter time than previous methods, and is highly compatible with mass spectrometric detection.
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The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification