983 resultados para seminar-based training


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This study reports the implementation of a Training of Intercultural Competence and Tolerance (TICT) for upper-secondary school students and the empirical evaluation of its effectiveness. The TICT program was developed to counteract increasing interethnic conflicts in the North Caucasus Federal District of Russia. It is based on the theoretical and empirical framework of social psychology and cross-cultural psychology. The training effectiveness was assessed by conducting pre- and post-surveys among the training participants. The results indicate that TICT contributes to the development of a positive ethnic identity and the formation of a civic identity among the participating youth. It also increases their optimism regarding the future of interethnic relations in Russia and the subjective level of intercultural competence of majority group youth towards minority cultures. Thus, the evaluation of the training effectiveness of the TICT has shown that the aims of the training have been achieved to a large extent and that the Training of Intercultural Competence and Tolerance can be effectively used to prevent interethnic conflicts and promote interethnic relations in multicultural schools. Suggestions for the practical implementation of the TICT as well as for future research on the training's effectiveness are discussed.

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PURPOSE    Segmentation of the proximal femur in digital antero-posterior (AP) pelvic radiographs is required to create a three-dimensional model of the hip joint for use in planning and treatment. However, manually extracting the femoral contour is tedious and prone to subjective bias, while automatic segmentation must accommodate poor image quality, anatomical structure overlap, and femur deformity. A new method was developed for femur segmentation in AP pelvic radiographs. METHODS    Using manual annotations on 100 AP pelvic radiographs, a statistical shape model (SSM) and a statistical appearance model (SAM) of the femur contour were constructed. The SSM and SAM were used to segment new AP pelvic radiographs with a three-stage approach. At initialization, the mean SSM model is coarsely registered to the femur in the AP radiograph through a scaled rigid registration. Mahalanobis distance defined on the SAM is employed as the search criteria for each annotated suggested landmark location. Dynamic programming was used to eliminate ambiguities. After all landmarks are assigned, a regularized non-rigid registration method deforms the current mean shape of SSM to produce a new segmentation of proximal femur. The second and third stages are iteratively executed to convergence. RESULTS    A set of 100 clinical AP pelvic radiographs (not used for training) were evaluated. The mean segmentation error was [Formula: see text], requiring [Formula: see text] s per case when implemented with Matlab. The influence of the initialization on segmentation results was tested by six clinicians, demonstrating no significance difference. CONCLUSIONS    A fast, robust and accurate method for femur segmentation in digital AP pelvic radiographs was developed by combining SSM and SAM with dynamic programming. This method can be extended to segmentation of other bony structures such as the pelvis.

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In this paper we present a solution to the problem of action and gesture recognition using sparse representations. The dictionary is modelled as a simple concatenation of features computed for each action or gesture class from the training data, and test data is classified by finding sparse representation of the test video features over this dictionary. Our method does not impose any explicit training procedure on the dictionary. We experiment our model with two kinds of features, by projecting (i) Gait Energy Images (GEIs) and (ii) Motion-descriptors, to a lower dimension using Random projection. Experiments have shown 100% recognition rate on standard datasets and are compared to the results obtained with widely used SVM classifier.

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Introduction or Statement of Problem Health care profession educators are challenged in their efforts to bring clinical experiences into the class room and to introduce students to community settings early in their didactic training. An immunization program directed at improving childhood immunization rates can introduce students to the community, to students of other disciplines and reinforce the knowledge and skills needed for immunization interventions. Successful interventions increase community demand for immunizations, improve access to services, and educate providers about immunization services and disease. Interventions serve to mold attitudes among health care professionals that foster commitment to universal immunization coverage and low disease rates. [See PDF for complete abstract]

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BACKGROUND Heart failure with preserved ejection fraction (HFpEF) is remarkably common in elderly people with highly prevalent comorbid conditions. Despite its increasing in prevalence, there is no evidence-based effective therapy for HFpEF. We sought to evaluate whether inspiratory muscle training (IMT) improves exercise capacity, as well as left ventricular diastolic function, biomarker profile and quality of life (QoL) in patients with advanced HFpEF and nonreduced maximal inspiratory pressure (MIP). DESIGN AND METHODS A total of 26 patients with HFpEF (median (interquartile range) age, peak exercise oxygen uptake (peak VO2) and left ventricular ejection fraction of 73 years (66-76), 10 ml/min/kg (7.6-10.5) and 72% (65-77), respectively) were randomized to receive a 12-week programme of IMT plus standard care vs. standard care alone. The primary endpoint of the study was evaluated by positive changes in cardiopulmonary exercise parameters and distance walked in 6 minutes (6MWT). Secondary endpoints were changes in QoL, echocardiogram parameters of diastolic function, and prognostic biomarkers. RESULTS The IMT group improved significantly their MIP (p < 0.001), peak VO2 (p < 0.001), exercise oxygen uptake at anaerobic threshold (p = 0.001), ventilatory efficiency (p = 0.007), metabolic equivalents (p < 0,001), 6MWT (p < 0.001), and QoL (p = 0.037) as compared to the control group. No changes on diastolic function parameters or biomarkers levels were observed between both groups. CONCLUSIONS In HFpEF patients with low aerobic capacity and non-reduced MIP, IMT was associated with marked improvement in exercise capacity and QoL.

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BACKGROUND: Several clinical studies on chronic stroke conducted with end-effector-based robots showed improvement of the motor function in the affected arm. Compared to end-effector-based robots, exoskeleton robots provide improved guidance of the human limb and are better suited to train task-oriented movements with a large range of motions. OBJECTIVE: To test whether intensive arm training with the arm exoskeleton ARMin I is feasible with chronic-stroke patients and whether it improves motor function in the paretic arm. METHODS: Three single cases with chronic hemiparesis resulting from unilateral stroke (at least 14 months after stroke). A-B design with 2 weeks of multiple baseline measurements (A), 8 weeks of training (B) with repetitive measurements and a follow-up measurement 8 weeks after training. The training included shoulder and elbow movements with the robotic rehabilitation device ARMin I. Two subjects had three 1-hour sessions per week and 1 subject received five 1-hour sessions per week. The main outcome measurement was the upper-limb part of the Fugl-Meyer Assessment (FMA). RESULTS: The ARMin training was well tolerated by the patients, and the FMA showed moderate, but significant improvements for all 3 subjects (p < 0.05). Most improvements were maintained 8 weeks after discharge. CONCLUSIONS: This study indicates that intensive training with an arm exoskeleton is feasible with chronic-stroke patients. Moderate improvements were found in all 3 subjects, thus further clinical investigations are justified.

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An intensive family preservation program was examined through interviews with 31 families who received the services and four caseworkers who provided the services. The primary finding from interviews with both care givers and caseworkers was that a positive therapeutic relationship between the worker and the client family contributes most to the success of the program. Workers who provided the services stressed the need for making concrete services available as well as clinical intervention and skills training, and they were adamant about screening families for appropriateness before including them in an intensive, inhome program.

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Objective: There is convincing evidence that phonological, orthographic and semantic processes influence children’s ability to learn to read and spell words. So far only a few studies investigated the influence of implicit learning in literacy skills. Children are sensitive to the statistics of their learning environment. By frequent reading they acquire implicit knowledge about the frequency of letter patterns in written words, and they use this knowledge during reading and spelling. Additionally, semantic connections facilitate to storing of words in memory. Thus, the aim of the intervention study was to implement a word-picture training which is based on statistical and semantic learning. Furthermore, we aimed at examining the training effects in reading and spelling in comparison to an auditory-visual matching training and a working memory training program. Participants and Methods: One hundred and thirty-two children aged between 8 and 11 years participated in training in three weekly session of 12 minutes over 8 weeks, and completed other assessments of reading, spelling, working memory and intelligence before and after training. Results: Results revealed in general that the word-picture training and the auditory-visual matching training led to substantial gains in reading and spelling performance in comparison to the working-memory training. Although both children with and without learning difficulties profited in their reading and spelling after the word-picture training, the training program led to differential effects for the two groups. After the word-picture training on the one hand, children with learning difficulties profited more in spelling as children without learning difficulties, on the other hand, children without learning difficulties benefit more in word comprehension. Conclusions: These findings highlight the need for frequent reading trainings with semantic connections in order to support the acquisition of literacy skills.

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PURPOSE To develop internationally harmonised standards for programmes of training in intensive care medicine (ICM). METHODS Standards were developed by using consensus techniques. A nine-member nominal group of European intensive care experts developed a preliminary set of standards. These were revised and refined through a modified Delphi process involving 28 European national coordinators representing national training organisations using a combination of moderated discussion meetings, email, and a Web-based tool for determining the level of agreement with each proposed standard, and whether the standard could be achieved in the respondent's country. RESULTS The nominal group developed an initial set of 52 possible standards which underwent four iterations to achieve maximal consensus. All national coordinators approved a final set of 29 standards in four domains: training centres, training programmes, selection of trainees, and trainers' profiles. Only three standards were considered immediately achievable by all countries, demonstrating a willingness to aspire to quality rather than merely setting a minimum level. Nine proposed standards which did not achieve full consensus were identified as potential candidates for future review. CONCLUSIONS This preliminary set of clearly defined and agreed standards provides a transparent framework for assuring the quality of training programmes, and a foundation for international harmonisation and quality improvement of training in ICM.

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Individuals with intellectual disabilities (ID) often struggle with learning how to read. Reading difficulties seem to be the most common secondary condition of ID. Only one in five children with mild or moderate ID achieves even minimal literacy skills. However, literacy education for children and adolescents with ID has been largely overlooked by researchers and educators. While there is little research on reading of children with ID, many training studies have been conducted with other populations with reading difficulties. The most common approach of acquiring literacy skills consists of sophisticated programs that train phonological skills and auditory perception. Only few studies investigated the influence of implicit learning on literacy skills. Implicit learning processes seem to be largely independent of age and IQ. Children are sensitive to the statistics of their learning environment. By frequent word reading they acquire implicit knowledge about the frequency of single letters and letter patterns in written words. Additionally, semantic connections not only improve the word understanding, but also facilitate storage of words in memory. Advances in communication technology have introduced new possibilities for remediating literacy skills. Computers can provide training material in attractive ways, for example through animations and immediate feedback .These opportunities can scaffold and support attention processes central to learning. Thus, the aim of this intervention study was to develop and implement a computer based word-picture training, which is based on statistical and semantic learning, and to examine the training effects on reading, spelling and attention in children and adolescents (9-16 years) diagnosed with mental retardation (general IQ  74). Fifty children participated in four to five weekly training sessions of 15-20 minutes over 4 weeks, and completed assessments of attention, reading, spelling, short-term memory and fluid intelligence before and after training. After a first assessment (T1), the entire sample was divided in a training group (group A) and a waiting control group (group B). After 4 weeks of training with group A, a second assessment (T2) was administered with both training groups. Afterwards, group B was trained for 4 weeks, before a last assessment (T3) was carried out in both groups. Overall, the results showed that the word-picture training led to substantial gains on word decoding and attention for both training groups. These effects were preserved six weeks later (group A). There was also a clear tendency of improvement in spelling after training for both groups, although the effect did not reach significance. These findings highlight the fact that an implicit statistical learning training in a playful way by motivating computer programs can not only promote reading development, but also attention in children with intellectual disabilities.

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Software developers often ask questions about software systems and software ecosystems that entail exploration and navigation, such as who uses this component?, and where is this feature implemented?. Software visualisation can be a great aid to understanding and exploring the answers to such questions, but visualisations require expertise to implement effectively, and they do not always scale well to large systems. We propose to automatically generate software visualisations based on software models derived from open source software corpora and from an analysis of the properties of typical developers queries and commonly used visualisations. The key challenges we see are (1) understanding how to match queries to suitable visualisations, and (2) scaling visualisations effectively to very large software systems and corpora. In the paper we motivate the idea of automatic software visualisation, we enumerate the challenges and our proposals to address them, and we describe some very initial results in our attempts to develop scalable visualisations of open source software corpora.

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Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.

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In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.