978 resultados para User-support
Resumo:
Aquest projecte es basa en l'estudi de l'oferiment de qualitat de servei en xarxes wireless i satel·litals. Per això l'estudi de les tècniques de cross-layer i del IEEE 802.11e ha sigut el punt clau per al desenvolupament teòric d’aquest estudi. Usant el simulador de xarxes network simulator, a la part de simulacions es plantegen tres situacions: l'estudi de la xarxa satel·lital, l'estudi del mètode d'accés HCCA i la interconnexió de la xarxa satel·lital amb la wireless. Encara que aquest últim punt, incomplet en aquest projecte, ha de ser la continuació per a futures investigacions.
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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.
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Architectural design and deployment of Peer-to-Peer Video-on-Demand (P2PVoD) systems which support VCR functionalities is attracting the interest of an increasing number of research groups within the scientific community; especially due to the intrinsic characteristics of such systems and the benefits that peers could provide at reducing the server load. This work focuses on the performance analysis of a P2P-VoD system considering user behaviors obtained from real traces together with other synthetic user patterns. The experiments performed show that it is feasible to achieve a performance close to the best possible. Future work will consider monitoring the physical characteristics of the network in order to improve the design of different aspects of a VoD system.
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Therapeutic drug monitoring (TDM) aims to optimize treatments by individualizing dosage regimens based on the measurement of blood concentrations. Dosage individualization to maintain concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculations currently represent the gold standard TDM approach but require computation assistance. In recent decades computer programs have been developed to assist clinicians in this assignment. The aim of this survey was to assess and compare computer tools designed to support TDM clinical activities. The literature and the Internet were searched to identify software. All programs were tested on personal computers. Each program was scored against a standardized grid covering pharmacokinetic relevance, user friendliness, computing aspects, interfacing and storage. A weighting factor was applied to each criterion of the grid to account for its relative importance. To assess the robustness of the software, six representative clinical vignettes were processed through each of them. Altogether, 12 software tools were identified, tested and ranked, representing a comprehensive review of the available software. Numbers of drugs handled by the software vary widely (from two to 180), and eight programs offer users the possibility of adding new drug models based on population pharmacokinetic analyses. Bayesian computation to predict dosage adaptation from blood concentration (a posteriori adjustment) is performed by ten tools, while nine are also able to propose a priori dosage regimens, based only on individual patient covariates such as age, sex and bodyweight. Among those applying Bayesian calculation, MM-USC*PACK© uses the non-parametric approach. The top two programs emerging from this benchmark were MwPharm© and TCIWorks. Most other programs evaluated had good potential while being less sophisticated or less user friendly. Programs vary in complexity and might not fit all healthcare settings. Each software tool must therefore be regarded with respect to the individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Computer-assisted TDM is gaining growing interest and should further improve, especially in terms of information system interfacing, user friendliness, data storage capability and report generation.
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At present, Spain faces one of the key moments in planning the future design of the infrastructure network. As a consequence of the critical role played by haulage in intra-European trade, the most important investments are those that guarantee that road haulage traffic can move freely at the borders. That is why it is necessary to make serious evaluations of the economic and social profitability of these investments. Normally the most significant social benefit of investment projects in transport infrastructure is time saving, which in turn changes traffic intensity. In this article we analyse the changes in the user excess caused by public investment in transport infrastructure planned by the Spanish government and which will be located on the border between Spain and France. In particular, we study the increase in network user surplus for HGV traffic in the Spanish and French border zones in the Pyrenees.
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This paper provides a rationale for group support for political violence when violence does not provide a material benefi t. A theory of fairness is adopted to demonstrate that although group violence may not be the equilibrium of a material game it may be a fairness equilibrium in a game containing psychological payoffs. For this to happen the material stakes must be perceived as low and psychological payoffs are expressive. Although the material stakes are actually high, members of each group may choose expressively to support the use of violence because the probability of being decisive is low. The paper also considers the possibility of peace emerging as a fairness equilibrium. This can only happen if each group perceives the other as making some sacrifi ce in choosing peace.
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Type 2 diabetes mellitus (T2DM) is a major disease affecting nearly 280 million people worldwide. Whilst the pathophysiological mechanisms leading to disease are poorly understood, dysfunction of the insulin-producing pancreatic beta-cells is key event for disease development. Monitoring the gene expression profiles of pancreatic beta-cells under several genetic or chemical perturbations has shed light on genes and pathways involved in T2DM. The EuroDia database has been established to build a unique collection of gene expression measurements performed on beta-cells of three organisms, namely human, mouse and rat. The Gene Expression Data Analysis Interface (GEDAI) has been developed to support this database. The quality of each dataset is assessed by a series of quality control procedures to detect putative hybridization outliers. The system integrates a web interface to several standard analysis functions from R/Bioconductor to identify differentially expressed genes and pathways. It also allows the combination of multiple experiments performed on different array platforms of the same technology. The design of this system enables each user to rapidly design a custom analysis pipeline and thus produce their own list of genes and pathways. Raw and normalized data can be downloaded for each experiment. The flexible engine of this database (GEDAI) is currently used to handle gene expression data from several laboratory-run projects dealing with different organisms and platforms. Database URL: http://eurodia.vital-it.ch.
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Among the various work stress models, one of the most popular to date is the job demands-‐control (JDC) model developed by Karasek (1979), which postulates that work-‐related strain will be the highest under work conditions characterized by high demands and low autonomy. The absence of social support at work will further increase negative outcomes. However, this model does not apply equally to all individuals and to all cultures. In the following studies, we assessed work characteristics, personality traits, culture-‐driven individual attributes, and work-‐related health outcomes, through the administration of questionnaires. The samples consist of Swiss (n = 622) and South African (n = 879) service-‐oriented employees (from health, finance, education and commerce sectors) and aged from 18 to 65 years old. Results generally confirm the universal contribution of high psychological demands, low decision latitude and low supervisor support at work, as well as high neuroticism predict the worse health outcomes among employees in both countries. Furthermore, low neuroticism plays a moderating role between psychological demands and burnout, while high openness and high conscientiousness each play a moderating role between decision latitude and burnout in South Africa. Results also reveal that culture-‐driven individual attributes play a role in both countries, but in a unique manner and according to the ethnic group of belonging. Given that organizations are increasingly characterized with multicultural employees as well as increasingly adverse and complex job conditions, our results help in identifying more updated and refined dynamics that are key between the employee and the work environment in today's context. -- L'un des modèles sur le stress au travail des plus répandus est celui développé par Karasek (1979), qui postule qu'une mauvaise santé chez les employés résulte d'une combinaison de demandes psychologiques élevées, d'une latitude décisionnelle faible et de l'absence de soutien social au travail. Néanmoins, ce modèle ne s'applique pas de façon équivalente chez tous les individus et dans toutes les cultures. Dans les études présentées, nous avons mesuré les caractéristiques de travail, les traits de personnalité, les traits culturels et les effets lies à la santé à l'aide de questionnaires. L'échantillon provient de la Suisse (n = 622) et de l'Afrique du Sud (n = 879) et comprend des employés de domaines divers en lien avec le service (notamment des secteurs de la santé, finance, éducation et commerce) tous âgés entre 18 et 65 ans. Les résultats confirment l'universalité des effets directs des demandes au travail, la latitude décisionnelle faible, le soutien social faible provenant du supérieur hiérarchique, ainsi que le névrosisme élevé qui contribuent à un niveau de santé faible au travail, et ce, dans les deux pays. De plus, un niveau faible de névrosisme a un effet de modération entre les demandes au travail et l'épuisement professionnel, alors que l'ouverture élevée et le caractère consciencieux élevé modèrent la relation entre la latitude décisionnelle et l'épuisement professionnel en Afrique du Sud. Nous avons aussi trouvé que les traits culturels jouent un rôle dans les deux pays, mais de façon unique et en fonction du groupe ethnique d'appartenance. Sachant que les organisations sont de plus en plus caractérisées par des employés d'origine ethnique variées, et que les conditions de travail se complexifient, nos résultats contribuent à mieux comprendre les dynamiques entre l'employé et l'environnement de travail contemporain. personnalité, différences individuelles, comparaisons culturelles, culture, stress au travail, épuisement professionnel, santé des employés.
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PURPOSE: This study investigated maximal cardiometabolic response while running in a lower body positive pressure treadmill (antigravity treadmill (AG)), which reduces body weight (BW) and impact. The AG is used in rehabilitation of injuries but could have potential for high-speed running, if workload is maximally elevated. METHODS: Fourteen trained (nine male) runners (age 27 ± 5 yr; 10-km personal best, 38.1 ± 1.1 min) completed a treadmill incremental test (CON) to measure aerobic capacity and heart rate (V˙O2max and HRmax). They completed four identical tests (48 h apart, randomized order) on the AG at BW of 100%, 95%, 90%, and 85% (AG100 to AG85). Stride length and rate were measured at peak velocities (Vpeak). RESULTS: V˙O2max (mL·kg·min) was similar across all conditions (men: CON = 66.6 (3.0), AG100 = 65.6 (3.8), AG95 = 65.0 (5.4), AG90 = 65.6 (4.5), and AG85 = 65.0 (4.8); women: CON = 63.0 (4.6), AG100 = 61.4 (4.3), AG95 = 60.7 (4.8), AG90 = 61.4 (3.3), and AG85 = 62.8 (3.9)). Similar results were found for HRmax, except for AG85 in men and AG100 and AG90 in women, which were lower than CON. Vpeak (km·h) in men was 19.7 (0.9) in CON, which was lower than every other condition: AG100 = 21.0 (1.9) (P < 0.05), AG95 = 21.4 (1.8) (P < 0.01), AG90 = 22.3 (2.1) (P < 0.01), and AG85 = 22.6 (1.6) (P < 0.001). In women, Vpeak (km·h) was similar between CON (17.8 (1.1) ) and AG100 (19.3 (1.0)) but higher at AG95 = 19.5 (0.4) (P < 0.05), AG90 = 19.5 (0.8) (P < 0.05), and AG85 = 21.2 (0.9) (P < 0.01). CONCLUSIONS: The AG can be used at maximal exercise intensities at BW of 85% to 95%, reaching faster running speeds than normally feasible. The AG could be used for overspeed running programs at the highest metabolic response levels.
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This paper contributes to the literature on both embodied technical progress and firm dynamics, by formulating an endogenous growth model where selection and imitation play a fundamental role in helping capital good producers to learn about the productivity of technologies embodied in new plants. By calibrating the model to some key aggregates particularly relevant for the embodied capital literature, among them the growth rate of the relative investment price, the model quantitatively replicates the main facts associated to firm dynamics, such as the entry rate and the tail index of the establishment size distribution. In line with the previous literature, it also predicts a contribution to productivity growth of embodied technical progress and selection of around 60%
Resumo:
OBJECTIVES: The objective of our qualitative study was to define modalities of psychological support to be offered to couples seeking medically assisted procreation. MATERIAL AND METHODS: Forty couples participated in a semi-structured videotaped interview, which touched on themes such as personal and family histories, the couple's relationship, etc. We focused on the "narrative mobility", that is the way in which the couples transmit their personal and family history during the interview and the interviewer's impression that he may or may not share this with the couples. RESULTS: Observed differences in narrative mobility led us to distinguish three groups of couples and to propose various types of psychological support. DISCUSSION AND CONCLUSION: This exploratory study, with its interest for the narrative mobility, concerns the couples' capacity to stand back from their own story as responsible interlocutors. We made the hypothesis that this capacity is linked to their capacity to handle their emotional stress, to act as partners to the medical team and to prepare themselves for their future parenthood.
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GRIESSER A.-C., VLASTOS G., MOREL L., BEAUME C., SAPPINO A.-P. & HALLER G. (2010) European Journal of Cancer Care Socio-demographic predictors of high support needs in newly diagnosed breast cancer patients This study aimed to identify high support needs and their socio-demographic predictors to improve supportive care for newly diagnosed breast cancer patients. A cross-sectional study measured patients' needs and unsatisfied support needs by the supportive care needs survey (SCNS-34), administered after surgery, chemotherapy or radiotherapy. Socio-demographic, disease and treatment characteristics completed data collection. A total of 308 questionnaires were completed with a response rate of 88%. The most frequent support needs (73.3% of patients) related to information and the highest unsatisfied support needs to the management of emotions and daily life (36.3-39.6% of patients). Younger age predicted high and dissatisfied support needs (P < 0.05). Patients born outside Switzerland or with a lower level of education had more needs in daily living and psychological domains (P < 0.05). Being born outside Switzerland also predicted dissatisfaction with information provided. Being parent was a predictor of significant needs in the daily living domain after adjusting for disease and treatment characteristics (P= 0.01). Therefore, information, psychological and daily living support for newly diagnosed breast cancer patients should be strongly reinforced, particularly in patients being born outside Switzerland, those with children or being younger. For the latter, support in sexuality domain should also be emphasised.
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Este proyecto comprende dos componentes centrales. Estos son, definir la situación actual sobre el soporte funcional en las aplicaciones y proponer soluciones para una mejora de los servicios. Durante la descripción de la situación actual se han ido encontrando problemas en el soporte, y se proponen soluciones. Se han llegado a proponer 3 modelos distintos de los cuales se ha elegido uno, el cual supone una importante mejora en el servicio.
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Drug delivery is one of the most common clinical routines in hospitals, and is critical to patients' health and recovery. It includes a decision making process in which a medical doctor decides the amount (dose) and frequency (dose interval) on the basis of a set of available patients' feature data and the doctor's clinical experience (a priori adaptation). This process can be computerized in order to make the prescription procedure in a fast, objective, inexpensive, non-invasive and accurate way. This paper proposes a Drug Administration Decision Support System (DADSS) to help clinicians/patients with the initial dose computing. The system is based on a Support Vector Machine (SVM) algorithm for estimation of the potential drug concentration in the blood of a patient, from which a best combination of dose and dose interval is selected at the level of a DSS. The addition of the RANdom SAmple Consensus (RANSAC) technique enhances the prediction accuracy by selecting inliers for SVM modeling. Experiments are performed for the drug imatinib case study which shows more than 40% improvement in the prediction accuracy compared with previous works. An important extension to the patient features' data is also proposed in this paper.