891 resultados para Applied behavior analysis


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Esta tese insere-se na área da simulação de circuitos de RF e microondas, e visa o estudo de ferramentas computacionais inovadoras que consigam simular, de forma eficiente, circuitos não lineares e muito heterogéneos, contendo uma estrutura combinada de blocos analógicos de RF e de banda base e blocos digitais, a operar em múltiplas escalas de tempo. Os métodos numéricos propostos nesta tese baseiam-se em estratégias multi-dimensionais, as quais usam múltiplas variáveis temporais definidas em domínios de tempo deformados e não deformados, para lidar, de forma eficaz, com as disparidades existentes entre as diversas escalas de tempo. De modo a poder tirar proveito dos diferentes ritmos de evolução temporal existentes entre correntes e tensões com variação muito rápida (variáveis de estado activas) e correntes e tensões com variação lenta (variáveis de estado latentes), são utilizadas algumas técnicas numéricas avançadas para operar dentro dos espaços multi-dimensionais, como, por exemplo, os algoritmos multi-ritmo de Runge-Kutta, ou o método das linhas. São também apresentadas algumas estratégias de partição dos circuitos, as quais permitem dividir um circuito em sub-circuitos de uma forma completamente automática, em função dos ritmos de evolução das suas variáveis de estado. Para problemas acentuadamente não lineares, são propostos vários métodos inovadores de simulação a operar estritamente no domínio do tempo. Para problemas com não linearidades moderadas é proposto um novo método híbrido frequência-tempo, baseado numa combinação entre a integração passo a passo unidimensional e o método seguidor de envolvente com balanço harmónico. O desempenho dos métodos é testado na simulação de alguns exemplos ilustrativos, com resultados bastante promissores. Uma análise comparativa entre os métodos agora propostos e os métodos actualmente existentes para simulação RF, revela ganhos consideráveis em termos de rapidez de computação.

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Esta tese descreve uma framework de trabalho assente no paradigma multi-camada para analisar, modelar, projectar e optimizar sistemas de comunicação. Nela se explora uma nova perspectiva acerca da camada física que nasce das relações entre a teoria de informação, estimação, métodos probabilísticos, teoria da comunicação e codificação. Esta framework conduz a métodos de projecto para a próxima geração de sistemas de comunicação de alto débito. Além disso, a tese explora várias técnicas de camada de acesso com base na relação entre atraso e débito para o projeto de redes sem fio tolerantes a atrasos. Alguns resultados fundamentais sobre a interação entre a teoria da informação e teoria da estimação conduzem a propostas de um paradigma alternativo para a análise, projecto e optimização de sistemas de comunicação. Com base em estudos sobre a relação entre a informação recíproca e MMSE, a abordagem descrita na tese permite ultrapassar, de forma inovadora, as dificuldades inerentes à optimização das taxas de transmissão de informação confiáveis em sistemas de comunicação, e permite a exploração da atribuição óptima de potência e estruturas óptimas de pre-codificação para diferentes modelos de canal: com fios, sem fios e ópticos. A tese aborda também o problema do atraso, numa tentativa de responder a questões levantadas pela enorme procura de débitos elevados em sistemas de comunicação. Isso é feito através da proposta de novos modelos para sistemas com codificação de rede (network coding) em camadas acima da sua camada física. Em particular, aborda-se a utilização de sistemas de codificação em rede para canais que variam no tempo e são sensíveis a atrasos. Isso foi demonstrado através da proposta de um novo modelo e esquema adaptativo, cujos algoritmos foram aplicados a sistemas sem fios com desvanecimento (fading) complexo, de que são exemplos os sistemas de comunicação via satélite. A tese aborda ainda o uso de sistemas de codificação de rede em cenários de transferência (handover) exigentes. Isso é feito através da proposta de novos modelos de transmissão WiFi IEEE 801.11 MAC, que são comparados com codificação de rede, e que se demonstram possibilitar transferência sem descontinuidades. Pode assim dizer-se que esta tese, através de trabalho de análise e de propostas suportadas por simulações, defende que na concepção de sistemas de comunicação se devem considerar estratégias de transmissão e codificação que sejam não só próximas da capacidade dos canais, mas também tolerantes a atrasos, e que tais estratégias têm de ser concebidas tendo em vista características do canal e a camada física.

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In life cycle impact assessment (LCIA) models, the sorption of the ionic fraction of dissociating organic chemicals is not adequately modeled because conventional non-polar partitioning models are applied. Therefore, high uncertainties are expected when modeling the mobility, as well as the bioavailability for uptake by exposed biota and degradation, of dissociating organic chemicals. Alternative regressions that account for the ionized fraction of a molecule to estimate fate parameters were applied to the USEtox model. The most sensitive model parameters in the estimation of ecotoxicological characterization factors (CFs) of micropollutants were evaluated by Monte Carlo analysis in both the default USEtox model and the alternative approach. Negligible differences of CFs values and 95% confidence limits between the two approaches were estimated for direct emissions to the freshwater compartment; however the default USEtox model overestimates CFs and the 95% confidence limits of basic compounds up to three orders and four orders of magnitude, respectively, relatively to the alternative approach for emissions to the agricultural soil compartment. For three emission scenarios, LCIA results show that the default USEtox model overestimates freshwater ecotoxicity impacts for the emission scenarios to agricultural soil by one order of magnitude, and larger confidence limits were estimated, relatively to the alternative approach.

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The goal of this study is to analyze the dynamical properties of financial data series from nineteen worldwide stock market indices (SMI) during the period 1995–2009. SMI reveal a complex behavior that can be explored since it is available a considerable volume of data. In this paper is applied the window Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional order systems.

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This article describes a finite element-based formulation for the statistical analysis of the response of stochastic structural composite systems whose material properties are described by random fields. A first-order technique is used to obtain the second-order statistics for the structural response considering means and variances of the displacement and stress fields of plate or shell composite structures. Propagation of uncertainties depends on sensitivities taken as measurement of variation effects. The adjoint variable method is used to obtain the sensitivity matrix. This method is appropriated for composite structures due to the large number of random input parameters. Dominant effects on the stochastic characteristics are studied analyzing the influence of different random parameters. In particular, a study of the anisotropy influence on uncertainties propagation of angle-ply composites is carried out based on the proposed approach.

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The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.

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In this work, the effect of incorporation of recycled glass fibre reinforced plastics (GFRP) waste materials, obtained by means of shredding and milling processes, on mechanical behavior of polyester polymer mortar (PM) materials was assessed. For this purpose, different contents of GFRP recyclates (between 4% up to 12% in mass), were incorporated into polyester PM materials as sand aggregates and filler replacements. The effect of silane coupling agent addition to resin binder was also evaluated. Applied waste material was proceeding from the shredding of the leftovers resultant from the cutting and assembly processes of GFRP pultrusion profiles. Currently, these leftovers, jointly with unfinished products and scrap resulting from pultrusion manufacturing process, are landfilled, with supplementary added costs. Thus, besides the evident environmental benefits, a viable and feasible solution for these wastes would also conduct to significant economic advantages. Design of experiments and data treatment were accomplish by means of full factorial design approach and analysis of variance ANOVA. Experimental results were promising toward the recyclability of GFRP waste materials as aggregates and reinforcement for PM materials, with significant improvements on mechanical properties with regard to non-modified formulations.

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This paper presents the creation and development of technological schools directly linked to the business community and to higher public education. Establishing themselves as the key interface between the two sectors they make a signigicant contribution by having a greater competitive edge when faced with increasing competition in the tradional markets. The development of new business strategies supported by references of excellence, quality and competitiveness also provides a good link between the estalishment of partnerships aiming at the qualification of education boards at a medium level between the technological school and higher education with a technological foundation. We present a case study as an example depicting the success of Escola Tecnológica de Vale de Cambra.

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In this study, the concentration probability distributions of 82 pharmaceutical compounds detected in the effluents of 179 European wastewater treatment plants were computed and inserted into a multimedia fate model. The comparative ecotoxicological impact of the direct emission of these compounds from wastewater treatment plants on freshwater ecosystems, based on a potentially affected fraction (PAF) of species approach, was assessed to rank compounds based on priority. As many pharmaceuticals are acids or bases, the multimedia fate model accounts for regressions to estimate pH-dependent fate parameters. An uncertainty analysis was performed by means of Monte Carlo analysis, which included the uncertainty of fate and ecotoxicity model input variables, as well as the spatial variability of landscape characteristics on the European continental scale. Several pharmaceutical compounds were identified as being of greatest concern, including 7 analgesics/anti-inflammatories, 3 β-blockers, 3 psychiatric drugs, and 1 each of 6 other therapeutic classes. The fate and impact modelling relied extensively on estimated data, given that most of these compounds have little or no experimental fate or ecotoxicity data available, as well as a limited reported occurrence in effluents. The contribution of estimated model input variables to the variance of freshwater ecotoxicity impact, as well as the lack of experimental abiotic degradation data for most compounds, helped in establishing priorities for further testing. Generally, the effluent concentration and the ecotoxicity effect factor were the model input variables with the most significant effect on the uncertainty of output results.

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The fractal geometry is used to model of a naturally fractured reservoir and the concept of fractional derivative is applied to the diffusion equation to incorporate the history of fluid flow in naturally fractured reservoirs. The resulting fractally fractional diffusion (FFD) equation is solved analytically in the Laplace space for three outer boundary conditions. The analytical solutions are used to analyze the response of a naturally fractured reservoir considering the anomalous behavior of oil production. Several synthetic examples are provided to illustrate the methodology proposed in this work and to explain the diffusion process in fractally fractured systems.

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Electricity markets are complex environments, involving a large number of different entities, with specific characteristics and objectives, making their decisions and interacting in a dynamic scene. Game-theory has been widely used to support decisions in competitive environments; therefore its application in electricity markets can prove to be a high potential tool. This paper proposes a new scenario analysis algorithm, which includes the application of game-theory, to evaluate and preview different scenarios and provide players with the ability to strategically react in order to exhibit the behavior that better fits their objectives. This model includes forecasts of competitor players’ actions, to build models of their behavior, in order to define the most probable expected scenarios. Once the scenarios are defined, game theory is applied to support the choice of the action to be performed. Our use of game theory is intended for supporting one specific agent and not for achieving the equilibrium in the market. MASCEM (Multi-Agent System for Competitive Electricity Markets) is a multi-agent electricity market simulator that models market players and simulates their operation in the market. The scenario analysis algorithm has been tested within MASCEM and our experimental findings with a case study based on real data from the Iberian Electricity Market are presented and discussed.

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This descriptive-exploratory study examined factors which were perceived by students at a College of Applied Arts and Technology (CAAT) campus as influencing them in choosing to come or not to come for personal counselling and why they would or would not retum. A total of 250 students selected through a sample of convenience were surveyed. A questionnaire survey was conducted with quantitative data collected using a 4-point, forced-choice Likert scale and yes/no questions and qualitative data collected using open-ended questions and invited comments. The responses were analyzed using means and modes for the Likert responses and percentages for the yes/no and check-off questions. The narrative responses were subjected to content analysis to identify themes. The mean score findings on factors influencing students to come for personal counselling were at or close to the mid- point of 2.5. Personal distress was the only variable found to have a negative response, meaning students would not come to counselling if they were in personal distress. On factors that would keep them from choosing to come to counselling, students seemed to trust counsellors and feel accepted by them and rejected the notion that peer pressure or the first session being unhelpful would keep them away from counselling. The counsellor's relationship with the student is the major determinant for repeat sessions. When asked what factors would influence students to not retum for personal counselling, students rejected the variables of peer pressure, the extra time needed for counselling, and not getting what they wanted in a session, but, in one instance, indicated that variables regarding the counselling relationship would keep them from returning.

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This study probed for an answer to the question, "How do you identify as early as possible those students who are at risk of failing or dropping out of college so that intervention can take place?" by field testing two diagnostic instruments with a group of first semester Seneca College Computer ,Studies students. In some respects, the research approach was such as might be taken in a pilot study_ Because of the complexity of the issue, this study did not attempt to go beyond discovery, understanding and description. Although some inferences may be drawn from the results of the study, no attempt was made to establish any causal relationship between or among the factors or variables represented here. Both quantitative and qualitative data were gathered during four resea~ch phases: background, early identification, intervention, and evaluation. To gain a better understanding of the problem of student attrition within the School of Computer Studies at Seneca College, several methods were used, including retrospective analysis of enrollment statistics, faculty and student interviews and questionnaires, and tracking of the sample population. The significance of the problem was confirmed by the results of this study. The findings further confirmed the importance of the role of faculty in student retention and support the need to improve the quality of teacher/student interaction. As well, the need for skills assessmen~-followed by supportive counselling, and placement was supported by the findings from this study. strategies for reducing student attrition were identified by faculty and students. As part of this study, a project referred to as "A Student Alert Project" (ASAP) was undertaken at the School of Computer Studies at Seneca college. Two commercial diagnostic instruments, the Noel/Levitz College Student Inventory (CSI) and the Learning and Study Strategies Inventory (LASSI), provided quantitative data which were subsequently analyzed in Phase 4 in order to assess their usefulness as early identification tools. The findings show some support for using these instruments in a two-stage approach to early identification and intervention: the CSI as an early identification instrument and the LASSI as a counselling tool for those students who have been identified as being at risk. The findings from the preliminary attempts at intervention confirmed the need for a structured student advisement program where faculty are selected, trained, and recognized for their advisor role. Based on the finding that very few students acted on the diagnostic results and recommendations, the need for institutional intervention by way of intrusive measures was confirmed.

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Although there is a general consensus among researchers that engagement in nonsuicidal self-injury (NSSI) is associated with increased risk for suicidal behavior, little attention has been given to whether suicidal risk varies among individuals engaging in NSSI. To identify individuals with a history of NSSI who are most at risk for suicidal behavior, we examined individual variability in both NSSI and suicidal behavior among a sample of young adults with a history of NSSI (N = 439, Mage = 19.1). Participants completed self-report measures assessing NSSI, suicidal behavior, and psychosocial adjustment (e.g., depressive symptoms, daily hassles). We conducted a latent class analysis using several characteristics of NSSI and suicidal behaviors as class indicators. Three subgroups of individuals were identified: 1) an infrequent NSSI/not high risk for suicidal behavior group, 2) a frequent NSSI/not high risk for suicidal behavior group, and 3) a frequent NSSI/high risk for suicidal behavior group. Follow-up analyses indicated that individuals in the ‘frequent NSSI/high risk for suicidal behavior’ group met the clinical-cut off score for high suicidal risk and reported significantly greater levels of suicidal ideation, attempts, and risk for future suicidal behavior as compared to the other two classes. Thus, this study is the first to identity variability in suicidal risk among individuals engaging in frequent and multiple methods of NSSI. Class 3 was also differentiated by higher levels of psychosocial impairment relative to the other two classes, as well as a comparison group of non-injuring young adults. Results underscore the importance of assessing individual differences in NSSI characteristics, as well as psychosocial impairment, when assessing risk for suicidal behavior.

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Abstract The therapeutic alliance (TA) is the most studied process of adult psychotherapeutic change (Zack et al., 2007) and has been found to have a moderate but robust relationship with therapeutic outcome regardless of treatment modality (Horvath, 2001). The TA is loosely described as the extent to which the therapist and the participant connect emotionally and work together towards goals. Conceptualizations of the TA with children have relied on adult models, even though it is widely acknowledged that the pediatric population will rarely willingly commit to therapy, nor readily admit to any challenges that they may be experiencing (Keeley, Geffken, McNamara & Storch, 2011). For children with Autism Spectrum Disorder (ASD) the therapeutic alliance may require an even greater retheorizing considering the communicative and social difficulties of this particular population. Despite this need, research on children with ASD and the therapeutic TA is almost non-existent. In this qualitative study, transcripts from semi-structured interviews with mothers of children with ASD were analyzed using Interpretative Phenomenological Analysis (IPA). IPA closely examines how individual people make sense of their life experiences using a theme-by-theme approach. The three interviewees were mothers whose children were participants in a nine-week Cognitive Behaviour Therapy (CBT) group for obsessive-compulsive behaviours (OCB). A total of four superordinate themes were identified: (i) Centralization and disremembering the TA, (ii) Qualities of the therapist, (iii) TA and the importance of time, and (iv) Signs of a healthy TA. The mothers’ perspectives on the TA suggest that, for them and their children, a strong TA was a required component of the therapy. Implications for clinicians and researchers are discussed.