966 resultados para Helmholtz Machines


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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.

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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.

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Sequential randomized prediction of an arbitrary binary sequence isinvestigated. No assumption is made on the mechanism of generating the bit sequence. The goal of the predictor is to minimize its relative loss, i.e., to make (almost) as few mistakes as the best ``expert'' in a fixed, possibly infinite, set of experts. We point out a surprising connection between this prediction problem and empirical process theory. First, in the special case of static (memoryless) experts, we completely characterize the minimax relative loss in terms of the maximum of an associated Rademacher process. Then we show general upper and lower bounds on the minimaxrelative loss in terms of the geometry of the class of experts. As main examples, we determine the exact order of magnitude of the minimax relative loss for the class of autoregressive linear predictors and for the class of Markov experts.

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In today’s competitive markets, the importance of goodscheduling strategies in manufacturing companies lead to theneed of developing efficient methods to solve complexscheduling problems.In this paper, we studied two production scheduling problemswith sequence-dependent setups times. The setup times areone of the most common complications in scheduling problems,and are usually associated with cleaning operations andchanging tools and shapes in machines.The first problem considered is a single-machine schedulingwith release dates, sequence-dependent setup times anddelivery times. The performance measure is the maximumlateness.The second problem is a job-shop scheduling problem withsequence-dependent setup times where the objective is tominimize the makespan.We present several priority dispatching rules for bothproblems, followed by a study of their performance. Finally,conclusions and directions of future research are presented.

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Recently, kernel-based Machine Learning methods have gained great popularity in many data analysis and data mining fields: pattern recognition, biocomputing, speech and vision, engineering, remote sensing etc. The paper describes the use of kernel methods to approach the processing of large datasets from environmental monitoring networks. Several typical problems of the environmental sciences and their solutions provided by kernel-based methods are considered: classification of categorical data (soil type classification), mapping of environmental and pollution continuous information (pollution of soil by radionuclides), mapping with auxiliary information (climatic data from Aral Sea region). The promising developments, such as automatic emergency hot spot detection and monitoring network optimization are discussed as well.

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To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

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I am pleased to present the performance report for the Iowa Department for the Blind for fiscal year 2008. This report is provided in compliance with sections 8E.210 and 216B.7 of the Code of Iowa. It contains valuable information about results achieved because of the services that we and our partners provided to blind and visually impaired Iowans during the past fiscal year in the areas of Vocational Rehabilitation, Independent Living, Library Services, and Resource Management. We determine our competitive success in a number of ways. We look at the federal standards and indicators to learn our ranking in relation to the performance of other public rehabilitation agencies. We compare our library's production and circulation figures with those from previous years to determine trends. We set our own standards for success by looking at such factors as the number of successful case closures, average hourly wage at case closure, skills training provided, and compliance with regulations. Results show that the Department is working positively toward achieving its strategic goals of increasing the independence and productivity of blind Iowans and improving access to information for blind Iowans. Major accomplishments of the year included:  The selection of our Library as one of eight libraries to receive the new digital talking book machines and books in digital media from the National Library Service for the Blind and Physically Handicapped. Priority for distribution of the machines is given to Library patrons who are veterans.  The Department, the Iowa Braille School, and the Department of Education have been promoting the new expanded core curriculum as part of their continued efforts to improve the coordination and delivery of services to blind and visually impaired students in Iowa.  The Department's five-year grant funded Pathfinders mentoring program ended this year. A total of 49 blind youths aged 16-26 were paired with successful blind adult mentors. Assessments of the program clearly showed that participation in the program had a measurable positive effect on the youth involved.  Finally, earnings ratios and the percentage of employment for vocational rehabilitation clients of the Department are among the best in the nation, as measured by the U.S. Rehabilitation Services Administration's standards and indicators for the year ended September 30, 2007. Overall, we met or exceeded 13 of 18 targets included in this report. A discussion of the Department's services, customers, and organizational structure, and budget appears in the "Department Overview" that follows. Information pertaining to performance results appears in the final section of this document. The success of the Department's programs is evident in the success achieved by blind Iowans. It is reflected in the many blind persons who can be seen traveling about independently, going to their jobs and to the community and family activities in which they participate. Sincerely, Karen A. Keninger, Director Iowa Department for the Blind

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L'objectiu principal del projecte és la creació d'una aplicació per a telèfons intel·ligents que intenti predir la volatilitat no atribuïble al mercat per tal de permetre a l'usuari crear portfolios òptims utilitzant tècniques d'intel·ligència artificial com són les Support Vector Machines (SVM). Una vegada s'hagi predit aquesta volatilitat es crearà un portfolio òptim amb el pes adequat de cada un dels valors, per tal d'obtenir una inversió amb el mínim risc possible.

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In recent years there has been an explosive growth in the development of adaptive and data driven methods. One of the efficient and data-driven approaches is based on statistical learning theory (Vapnik 1998). The theory is based on Structural Risk Minimisation (SRM) principle and has a solid statistical background. When applying SRM we are trying not only to reduce training error ? to fit the available data with a model, but also to reduce the complexity of the model and to reduce generalisation error. Many nonlinear learning procedures recently developed in neural networks and statistics can be understood and interpreted in terms of the structural risk minimisation inductive principle. A recent methodology based on SRM is called Support Vector Machines (SVM). At present SLT is still under intensive development and SVM find new areas of application (www.kernel-machines.org). SVM develop robust and non linear data models with excellent generalisation abilities that is very important both for monitoring and forecasting. SVM are extremely good when input space is high dimensional and training data set i not big enough to develop corresponding nonlinear model. Moreover, SVM use only support vectors to derive decision boundaries. It opens a way to sampling optimization, estimation of noise in data, quantification of data redundancy etc. Presentation of SVM for spatially distributed data is given in (Kanevski and Maignan 2004).

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This work proposes an original contribution to the understanding of shermen spatial behavior, based on the behavioral ecology and movement ecology paradigms. Through the analysis of Vessel Monitoring System (VMS) data, we characterized the spatial behavior of Peruvian anchovy shermen at di erent scales: (1) the behavioral modes within shing trips (i.e., searching, shing and cruising); (2) the behavioral patterns among shing trips; (3) the behavioral patterns by shing season conditioned by ecosystem scenarios; and (4) the computation of maps of anchovy presence proxy from the spatial patterns of behavioral mode positions. At the rst scale considered, we compared several Markovian (hidden Markov and semi-Markov models) and discriminative models (random forests, support vector machines and arti cial neural networks) for inferring the behavioral modes associated with VMS tracks. The models were trained under a supervised setting and validated using tracks for which behavioral modes were known (from on-board observers records). Hidden semi-Markov models performed better, and were retained for inferring the behavioral modes on the entire VMS dataset. At the second scale considered, each shing trip was characterized by several features, including the time spent within each behavioral mode. Using a clustering analysis, shing trip patterns were classi ed into groups associated to management zones, eet segments and skippers' personalities. At the third scale considered, we analyzed how ecological conditions shaped shermen behavior. By means of co-inertia analyses, we found signi cant associations between shermen, anchovy and environmental spatial dynamics, and shermen behavioral responses were characterized according to contrasted environmental scenarios. At the fourth scale considered, we investigated whether the spatial behavior of shermen re ected to some extent the spatial distribution of anchovy. Finally, this work provides a wider view of shermen behavior: shermen are not only economic agents, but they are also foragers, constrained by ecosystem variability. To conclude, we discuss how these ndings may be of importance for sheries management, collective behavior analyses and end-to-end models.

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In this paper, we propose two active learning algorithms for semiautomatic definition of training samples in remote sensing image classification. Based on predefined heuristics, the classifier ranks the unlabeled pixels and automatically chooses those that are considered the most valuable for its improvement. Once the pixels have been selected, the analyst labels them manually and the process is iterated. Starting with a small and nonoptimal training set, the model itself builds the optimal set of samples which minimizes the classification error. We have applied the proposed algorithms to a variety of remote sensing data, including very high resolution and hyperspectral images, using support vector machines. Experimental results confirm the consistency of the methods. The required number of training samples can be reduced to 10% using the methods proposed, reaching the same level of accuracy as larger data sets. A comparison with a state-of-the-art active learning method, margin sampling, is provided, highlighting advantages of the methods proposed. The effect of spatial resolution and separability of the classes on the quality of the selection of pixels is also discussed.

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The development of statistical models for forensic fingerprint identification purposes has been the subject of increasing research attention in recent years. This can be partly seen as a response to a number of commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. In addition, key forensic identification bodies such as ENFSI [1] and IAI [2] have recently endorsed and acknowledged the potential benefits of using statistical models as an important tool in support of the fingerprint identification process within the ACE-V framework. In this paper, we introduce a new Likelihood Ratio (LR) model based on Support Vector Machines (SVMs) trained with features discovered via morphometric and spatial analyses of corresponding minutiae configurations for both match and close non-match populations often found in AFIS candidate lists. Computed LR values are derived from a probabilistic framework based on SVMs that discover the intrinsic spatial differences of match and close non-match populations. Lastly, experimentation performed on a set of over 120,000 publicly available fingerprint images (mostly sourced from the National Institute of Standards and Technology (NIST) datasets) and a distortion set of approximately 40,000 images, is presented, illustrating that the proposed LR model is reliably guiding towards the right proposition in the identification assessment of match and close non-match populations. Results further indicate that the proposed model is a promising tool for fingerprint practitioners to use for analysing the spatial consistency of corresponding minutiae configurations.

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Contexte et but de l'étude: Les fractures du triquetrum sont les deuxièmes fractures des os du carpe en fréquence, après celles du scaphoïde. Elles représentent environ 3.5% de toutes les lésions traumatiques du poignet, et résultent le plus souvent d'une chute de sa hauteur avec réception sur le poignet en hyper-extension. Leur mécanisme physiopathologique reste débattu. La première théorie fut celle de l'avulsion ligamentaire d'un fragment osseux dorsal. Puis, Levy et coll. ainsi que Garcia-Elias ont successivement suggéré que ces fractures résultaient plutôt d'une impaction ulno-carpienne. De nombreux ligaments (intrinsèques et extrinsèques du carpe) s'insèrent sur les versants palmaires et dorsaux du triquetrum. Ces ligaments jouent un rôle essentiel dans le maintien de la stabilité du carpe. Bien que l'arthro-IRM du poignet soit l'examen de référence pour évaluer ces ligaments, Shahabpour et coll. ont récemment démontré leur visibilité en IRM tridimensionnelle (volumique) après injection iv. de produit de contraste (Gadolinium). L'atteinte ligamentaire associée aux fractures dorsales du triquetrum n'a jusqu'à présent jamais été évalué. Ces lésions pourraient avoir un impact sur l'évolution et la prise en charge de ces fractures. Les objectifs de l'étude étaient donc les suivants: premièrement, déterminer l'ensemble des caractéristiques des fractures dorsales du triquetrum en IRM, en mettant l'accent sur les lésions ligamentaires extrinsèques associées; secondairement, discuter les différents mécanismes physiopathologiques (i.e. avulsion ligamentaire ou impaction ulno-carpienne) de ces fractures d'après nos résultats en IRM. Patients et méthodes: Ceci est une étude rétrospective multicentrique (CHUV, Lausanne; Hôpital Cochin, AP-HP, Paris) d'examens IRM et radiographies conventionnelles du poignet. A partir de janvier 2008, nous avons recherché dans les bases de données institutionnelles les patients présentant une fracture du triquetrum et ayant bénéficié d'une IRM volumique du poignet dans un délai de six semaines entre le traumatisme et l'IRM. Les examens IRM ont été effectués sur deux machines à haut champ magnétique (3 Tesla) avec une antenne dédiée et un protocole d'acquisition incluant une séquence tridimensionnelle isotropique (« 3D VIBE ») après injection iv. de produit de contraste (Gadolinium). Ces examens ont été analysés par deux radiologues ostéo-articulaires expérimentés. Les mesures ont été effectuées par un troisième radiologue ostéo-articulaire. En ce qui concerne l'analyse qualitative, le type de fracture du triquetrum (selon la classification de Garcia-Elias), la distribution de l'oedème osseux post- traumatique, ainsi que le nombre et la distribution des lésions ligamentaires extrinsèques associées ont été évalués. Pour l'analyse quantitative, l'index du processus de la styloïde ulnaire (selon la formule de Garcia-Elias), le volume du fragment osseux détaché du triquetrum, et la distance séparant ce fragment osseux du triquetrum ont été mesurés.

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Des dels inicis dels ordinadors com a màquines programables, l’home ha intentat dotar-los de certa intel•ligència per tal de pensar o raonar el més semblant possible als humans. Un d’aquests intents ha sigut fer que la màquina sigui capaç de pensar de tal manera que estudiï jugades i guanyi partides d’escacs. En l’actualitat amb els actuals sistemes multi tasca, orientat a objectes i accés a memòria i gràcies al potent hardware del que disposem, comptem amb una gran varietat de programes que es dediquen a jugar a escacs. Però no hi ha només programes petits, hi ha fins i tot màquines senceres dedicades a calcular i estudiar jugades per tal de guanyar als millors jugadors del món. L’objectiu del meu treball és dur a terme un estudi i implementació d’un d’aquests programes, per això es divideix en dues parts. La part teòrica o de l’estudi, consta d’un estudi dels sistemes d’intel•ligència artificial que es dediquen a jugar a escacs, estudi i cerca d’una funció d’avaluació vàlida i estudi dels algorismes de cerca. La part pràctica del treball es basa en la implementació d’un sistema intel•ligent capaç de jugar a escacs amb certa lògica. Aquesta implementació es porta a terme amb l’ajuda de les llibreries SDL, utilitzant l’algorisme minimax amb poda alfa-beta i codi c++. Com a conclusió del projecte m’agradaria remarcar que l’estudi realitzat m’ha deixat veure que crear un joc d’escacs no era tan fàcil com jo pensava però m’ha aportat la satisfacció d’aplicar tot el que he après durant la carrera i de descobrir moltes altres coses noves.