8 resultados para performance data

em Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco


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[EU]Gaur egungo sareetan egunetik egunera garraiatzen den paketeen trafikoa handituz doa eskariak horrela behartzen duelako. Beste alde batetik, gure sareen eta batez ere sare pribatuen segurtasuna gero eta garrantzitsuagoa da, bertan dauden datuen eskuragarritasuna mugatze aldera. Ondorioz segurtasun teknika hauek aplikatzeko ahalik eta denbora gutxien erabiltzea garrantzitsua da sareak duen datu garraiorako errendimendu altua manten dezan, segurtasuna bermatua. Proiektu honetan, enpresa eta erakundeetan oso arruntak diren firewall, segurtasun tekniken inguruko azterketa egingo da. Firewall ezagun baten eta driver baten arteko integrazioa burutuko da firewallak sarean duen errendimendua hobetze aldera.

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Recent player tracking technology provides new information about basketball game performance. The aim of this study was to (i) compare the game performances of all-star and non all-star basketball players from the National Basketball Association (NBA), and (ii) describe the different basketball game performance profiles based on the different game roles. Archival data were obtained from all 2013-2014 regular season games (n = 1230). The variables analyzed included the points per game, minutes played and the game actions recorded by the player tracking system. To accomplish the first aim, the performance per minute of play was analyzed using a descriptive discriminant analysis to identify which variables best predict the all-star and non all-star playing categories. The all-star players showed slower velocities in defense and performed better in elbow touches, defensive rebounds, close touches, close points and pull-up points, possibly due to optimized attention processes that are key for perceiving the required appropriate environmental information. The second aim was addressed using a k-means cluster analysis, with the aim of creating maximal different performance profile groupings. Afterwards, a descriptive discriminant analysis identified which variables best predict the different playing clusters. The results identified different playing profile of performers, particularly related to the game roles of scoring, passing, defensive and all-round game behavior. Coaching staffs may apply this information to different players, while accounting for individual differences and functional variability, to optimize practice planning and, consequently, the game performances of individuals and teams.

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Published as an article in: Investigaciones Economicas, 2005, vol. 29, issue 3, pages 483-523.

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[EN]A study was conducted on crossbred steers (n=275; 376±924 kg) to evaluate performance and carcass quality of cattle fed wheat or corn dried distillers’ grains with solubles (DDGS). The control ration contained 86.6% rolled barley grain, 5.7% supplement and 7.7% barley silage (DM basis). The four treatments included replacement of barley grain at 20 or 40% of the diet (DM basis) with wheat or corn DDGS. Steers were slaughtered at a common end weight of 645 kg with 100 steers randomly (n=20 per treatment) selected for determination of the retail yield of sub-primal boneless boxed beef (SPBBB). Data were analyzed as a completely randomized design using pen as the experimental unit. Feeding increasing levels of wheat DDGS led to a quadratic increase in dry matter intake (DMI) (P<0.01), whereas increasing levels of corn DDGS led to a quadratic decrease in DMI (P=0.01). Average daily gain was not influenced (P=0.13) by feeding wheat or corn DDGS, but cattle fed corn DDGS exhibited a quadratic increase (P=0.01) in gain:feed. As a result, a quadratic increase (P<0.01) in calculated NEg of the diet was observed as corn DDGS levels increased. A linear decrease (P=0.04) in days on feed (169, 166 and 154 d) was noted when increasing levels of wheat DDGS (0, 20 and 40%) were fed. Dressing percentage increased in a linear fashion with wheat DDGS (P<0.01) inclusion level and in a quadratic fashion (P=0.01) as corn DDGS inclusion level increased although other carcass traits were not affected (P=0.10) by treatment. The results indicate that replacement of barley grain with corn or wheat DDGS up to 40% of the diet (DM) can lead to superior performance (improved gain:feed or reduced days on feed, respectively) with no detrimental effect on quality grade or carcass SPBBB yield.

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Smart and mobile environments require seamless connections. However, due to the frequent process of ''discovery'' and disconnection of mobile devices while data interchange is happening, wireless connections are often interrupted. To minimize this drawback, a protocol that enables an easy and fast synchronization is crucial. Bearing this in mind, Bluetooth technology appears to be a suitable solution to carry on such connections due to the discovery and pairing capabilities it provides. Nonetheless, the time and energy spent when several devices are being discovered and used at the same time still needs to be managed properly. It is essential that this process of discovery takes as little time and energy as possible. In addition to this, it is believed that the performance of the communications is not constant when the transmission speeds and throughput increase, but this has not been proved formally. Therefore, the purpose of this project is twofold: Firstly, to design and build a framework-system capable of performing controlled Bluetooth device discovery, pairing and communications. Secondly, to analyze and test the scalability and performance of the \emph{classic} Bluetooth standard under different scenarios and with various sensors and devices using the framework developed. To achieve the first goal, a generic Bluetooth platform will be used to control the test conditions and to form a ubiquitous wireless system connected to an Android Smartphone. For the latter goal, various stress-tests will be carried on to measure the consumption rate of battery life as well as the quality of the communications between the devices involved.

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In the problem of one-class classification (OCC) one of the classes, the target class, has to be distinguished from all other possible objects, considered as nontargets. In many biomedical problems this situation arises, for example, in diagnosis, image based tumor recognition or analysis of electrocardiogram data. In this paper an approach to OCC based on a typicality test is experimentally compared with reference state-of-the-art OCC techniques-Gaussian, mixture of Gaussians, naive Parzen, Parzen, and support vector data description-using biomedical data sets. We evaluate the ability of the procedures using twelve experimental data sets with not necessarily continuous data. As there are few benchmark data sets for one-class classification, all data sets considered in the evaluation have multiple classes. Each class in turn is considered as the target class and the units in the other classes are considered as new units to be classified. The results of the comparison show the good performance of the typicality approach, which is available for high dimensional data; it is worth mentioning that it can be used for any kind of data (continuous, discrete, or nominal), whereas state-of-the-art approaches application is not straightforward when nominal variables are present.