963 resultados para Standardization in robotics


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During the last decades, Puertos del Estado and research groups have developed a huge effort on numerical an physical monitoring. This effort has led to the necessity to implement a tool to standardize, store and process all gathered data. The Test Analysis Tool (TATo) is described in the paper.

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"Issued August 1980."

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Objective. To assess the reliability of physical examination of the osteoarthritic (OA) knee by rheumatologists, and to evaluate the benefits of standardization. Methods. Forty-two physical signs and techniques were evaluated using a 6 X 6 Latin square design. Patients with mild to severe knee OA, based on physical and radiographic signs, were examined in random order prior to and following standardization of techniques. For those signs with dichotomous scales, agreement among the rheumatologists was calculated as the prevalence-adjusted bias-adjusted kappa (PABAK), while for the signs with continuous and ordinal scales, a reliability coefficient (R-c) was calculated using analysis of variance. A PABAK of >0.60 and an Re of >0.80 were considered to indicate adequate reliability. Results. Adequate poststandardization reliability was achieved for 30 of 42 physical signs/techniques (71%). The most highly reliable signs identified by physical examination of the OA knee included alignment by goniometer (R-c = 0.99), bony swelling (R-c = 0.97), general passive crepitus (R-c = 0.96), gait by inspection (PABAK = 0.78), effusion bulge sign (R-c = 0.97), quadriceps atrophy (R. = 0.97), medial tibiofemoral tenderness (R-c = 0.94), lateral tibiofemoral tenderness (R-c = 0.85), patellofemoral tenderness by grind test (R-c = 0.94), and flexion contracture (R-c = 0.95). The standardization process resulted in substantial improvements in reliability for evaluation of a number of physical signs, although for some signs, minimal or no effect of standardization was noted. After standardization, warmth (PABAK = 0.14), medial instability at 30degrees flexion (PABAK = 0.02), and lateral instability at 30degrees flexion (PABAK = 0.34) were the only 3 signs that were highly unreliable. Conclusion. With the exception of physical examinations for instability, a comprehensive knee examination can be performed with adequate reliability. Standardization further improves the reliability for some physical signs and techniques. The application of these findings to future OA studies will contribute to improved outcome assessments in OA.

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Support vector machines (SVMs) have recently emerged as a powerful technique for solving problems in pattern classification and regression. Best performance is obtained from the SVM its parameters have their values optimally set. In practice, good parameter settings are usually obtained by a lengthy process of trial and error. This paper describes the use of genetic algorithm to evolve these parameter settings for an application in mobile robotics.

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In a European BIOMED-2 collaborative study, multiplex PCR assays have successfully been developed and standardized for the detection of clonally rearranged immunoglobulin (Ig) and T-cell receptor (TCR) genes and the chromosome aberrations t(11;14) and t(14;18). This has resulted in 107 different primers in only 18 multiplex PCR tubes: three VH-JH, two DH-JH, two Ig kappa (IGK), one Ig lambda (IGL), three TCR beta (TCRB), two TCR gamma (TCRG), one TCR delta (TCRD), three BCL1-Ig heavy chain (IGH), and one BCL2-IGH. The PCR products of Ig/TCR genes can be analyzed for clonality assessment by heteroduplex analysis or GeneScanning. The detection rate of clonal rearrangements using the BIOMED-2 primer sets is unprecedentedly high. This is mainly based on the complementarity of the various BIOMED-2 tubes. In particular, combined application of IGH (VH-JH and DH-JH) and IGK tubes can detect virtually all clonal B-cell proliferations, even in B-cell malignancies with high levels of somatic mutations. The contribution of IGL gene rearrangements seems limited. Combined usage of the TCRB and TCRG tubes detects virtually all clonal T-cell populations, whereas the TCRD tube has added value in case of TCRgammadelta(+) T-cell proliferations. The BIOMED-2 multiplex tubes can now be used for diagnostic clonality studies as well as for the identification of PCR targets suitable for the detection of minimal residual disease.

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Background: Parenteral nutrition (PN) is a costly therapy that can also be associated with serious complications. Therefore, efforts are focusing on reducing rate of complications, and costs related to PN. Objective: The aim was to analyze the effect of the implementation of PN standardization on costs and quality criteria. Secondary aim was to assess the use of individualized PN based on patient's clinical condition. Methods: We compare the use of PN before and after the implementation of PN standardization. Demographic, clinical and PN characteristics were collected. Costs analysis was performed to study the costs associated to the two different periods. Quality criteria included were: 1) PN administration; 2) nutrition assessment (energy intake between 20-35 kcal/kg/day; protein contribution according to nitrogen balance); 3) safety and complications (hyperglycemia, hypertriglyceridemia, hepatic complications, catheter-related infection); 4) global efficacy (as serum albumin increase). Chi-square test was used to compare percentages; logistic regression analysis was performed to evaluate the use of customized PN. Results: 296 patients were included with a total of 3,167 PN compounded. During the first period standardized PN use was 47.5% vs 85.7% within the second period (p < 0.05). No differences were found in the quality criteria tested. Use of individualized PN was related to critical care patients, hypertriglyceridemia, renal damage, and long-term PN. Mean costs of the PN decreased a 19.5%. Annual costs savings would be € 86,700. Conclusions: The use of customized or standard PN has shown to be efficient and flexible to specific demands; however customized PN was significantly more expensive.

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In this paper, the problem of semantic place categorization in mobile robotics is addressed by considering a time-based probabilistic approach called dynamic Bayesian mixture model (DBMM), which is an improved variation of the dynamic Bayesian network. More specifically, multi-class semantic classification is performed by a DBMM composed of a mixture of heterogeneous base classifiers, using geometrical features computed from 2D laserscanner data, where the sensor is mounted on-board a moving robot operating indoors. Besides its capability to combine different probabilistic classifiers, the DBMM approach also incorporates time-based (dynamic) inferences in the form of previous class-conditional probabilities and priors. Extensive experiments were carried out on publicly available benchmark datasets, highlighting the influence of the number of time-slices and the effect of additive smoothing on the classification performance of the proposed approach. Reported results, under different scenarios and conditions, show the effectiveness and competitive performance of the DBMM.

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In the recent decades, robotics has become firmly embedded in areas such as education, teaching, medicine, psychology and many others. We focus here on social robotics; social robots are designed to interact with people in a natural and interpersonal way, often to achieve positive results in different applications. To interact and cooperate with humans in their daily-life activities, robots should exhibit human-like intelligence. The rapid expansion of social robotics and the existence of various kinds of robots on the market have allowed research groups to carry out multiple experiments. The experiments carried out have led to the collections of various kinds of data, which can be used or processed for psychological studies, and studies in other fields. However, there are no tools available in which data can be stored, processed and shared with other research groups. This thesis proposes the design and implementation of visual tool for organizing dataflows in Human Robot Interaction (HRI).