893 resultados para Dynamic Psychotherapy
Resumo:
Recently, cumulative residual entropy (CRE) has been found to be a new measure of information that parallels Shannon’s entropy (see Rao et al. [Cumulative residual entropy: A new measure of information, IEEE Trans. Inform. Theory. 50(6) (2004), pp. 1220–1228] and Asadi and Zohrevand [On the dynamic cumulative residual entropy, J. Stat. Plann. Inference 137 (2007), pp. 1931–1941]). Motivated by this finding, in this paper, we introduce a generalized measure of it, namely cumulative residual Renyi’s entropy, and study its properties.We also examine it in relation to some applied problems such as weighted and equilibrium models. Finally, we extend this measure into the bivariate set-up and prove certain characterizing relationships to identify different bivariate lifetime models
Characterizations of Bivariate Models Using Some Dynamic Conditional Information Divergence Measures
Resumo:
In this article, we study some relevant information divergence measures viz. Renyi divergence and Kerridge’s inaccuracy measures. These measures are extended to conditionally specifiedmodels and they are used to characterize some bivariate distributions using the concepts of weighted and proportional hazard rate models. Moreover, some bounds are obtained for these measures using the likelihood ratio order
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Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.
Resumo:
Temporal changes in odor concentration are vitally important to many animals orienting and navigating in their environment. How are such temporal changes detected? Within the scope of the present work an accurate stimulation and analysis system was developed to examine the dynamics of physiological properties of Drosophila melanogaster olfactory receptor organs. Subsequently a new method for delivering odor stimuli was tested and used to present the first dynamic characterization of olfactory receptors at the level of single neurons. Initially, recordings of the whole antenna were conducted while stimulating with different odors. The odor delivery system allowed the dynamic characterization of the whole fly antenna, including its sensilla and receptor neurons. Based on the obtained electroantennogram data a new odor delivery method called digital sequence method was developed. In addition the degree of accuracy was enhanced, initially using electroantennograms, and later recordings of odorant receptor cells at the single sensilla level. This work shows for the first time that different odors evoked different responses within one neuron depending on the chemical structure of the odor. The present work offers new insights into the dynamic properties of olfactory transduction in Drosophila melanogaster and describes time dependent parameters underlying these properties.
Resumo:
Im Mittelpunkt der Arbeit steht die Frage, ob bei psychogenen Störungen Geschwistererfahrungen klinische Relevanz haben und ob die erfahrene Geschwisterposition und –konstellation auch im Erwachsenenalter psychodynamisch wirksam ist. Die Arbeit gliedert sich in drei Teile. Im ersten Teil werden in einem metatheoretischen Vorgehen psychoanalytische Konzepte, psychoanalytische Entwicklungstheorien aus der Objekt- und Selbstpsychologie und empirische Forschungsergebnisse zur Geschwisterbeziehung vorgestellt. Darauf aufbauend werden Annahmen formuliert, welche psychodynamischen Konflikte sich in einer pathologischen Entwicklung als psychische Störungen im Erwachsenenalter manifestieren können.Im zweiten Teil der Arbeit werden acht Einzelfälle psychoanalytischer Behandlungen von erwachsenen Patienten unterschiedlicher Geschwisterpositionen und -konstellationen dargestellt, die die in Teil 1 beschriebenen pathogenen Geschwistereinflüsse illustrieren. In den untersuchten Einzelfällen ist die erfahrene Geschwisterposition der Patienten konfliktbesetzt und psychodynamisch wirksam gewesen. Dabei haben die Erfahrungen mit den primären Objekten die Basis für die pathologische Beziehungsdynamik der Geschwister gebildet. Den dritten extra-klinisch empirischen Teil der Arbeit stellt eine explorative Pilotstudie dar, die ebenfalls das Ziel verfolgt, persistierende Geschwisterkonflikte in ihren langandauernden Effekten zu explorieren. Es handelt sich um eine Dokumentenanalyse von 215 Patientenakten aus einer psychosomatischen Klinik. Aus den Akten werden als Variablen ICD - und OPD - Diagnosen als auch inhaltsanalytisch ermittelte psychodynamische Konflikte herausgefiltert und mit den Variablen Geschwisterposition und –konstellation korreliert. Dabei wird erstens der Frage nachgegangen, ob es in den Akten von psychisch erkrankten Patienten zwischen Einzel- und Geschwisterkindern Unterschiede in Bezug auf die Diagnosen und hinsichtlich der formulierten psychodynamischen Konflikte gibt. Zweitens geht es um eine weitergehende Exploration dieser Variablen in Bezug auf die erfahrene Geschwisterposition bzw. –konstellation. Es zeigt sich, dass die ICD-10 Diagnostik aufgrund ihres deskriptiven Charakters und ihrer psychiatrischen Orientierung wenig brauchbar ist, diesbezügliche Hypothesen zu formulieren. Im Unterschied zur ICD-10 ergibt sich in Bezug auf die OPD-Diagnostik, besonders aber in Hinsicht auf die psychodynamischen Konflikte ein differenzierteres Bild. So sind z.B. Parentifizierung am häufigsten von Einzelkindern und Erstgeborenen benannt worden. Gleichzeitig berichten Patienten, die mit Geschwistern aufgewachsen sind, am stärksten von erlebtem emotionalem Mangel in der Familie. Unter Dominanzkonflikten leiden die Patienten am meisten, die als jüngstes Kind aufgewachsen sind. Bei Patienten mit der jüngsten und mittleren Geschwisterposition ist als weiteres Beispiel auffallend oft Altruismus ermittelt worden. Fazit der Arbeit ist, dass ungelöste Geschwisterkonflikte langandauernde Effekte haben können und dass - im Gegensatz zur Birth-Order-Forschung - die Variable der Geschwisterposition unter Berücksichtigung geschlechtsspezifischer Aspekte als ein intra- und interpsychisches dynamisches Geschehen begriffen werden kann.
Resumo:
Auf dem Gebiet der Strukturdynamik sind computergestützte Modellvalidierungstechniken inzwischen weit verbreitet. Dabei werden experimentelle Modaldaten, um ein numerisches Modell für weitere Analysen zu korrigieren. Gleichwohl repräsentiert das validierte Modell nur das dynamische Verhalten der getesteten Struktur. In der Realität gibt es wiederum viele Faktoren, die zwangsläufig zu variierenden Ergebnissen von Modaltests führen werden: Sich verändernde Umgebungsbedingungen während eines Tests, leicht unterschiedliche Testaufbauten, ein Test an einer nominell gleichen aber anderen Struktur (z.B. aus der Serienfertigung), etc. Damit eine stochastische Simulation durchgeführt werden kann, muss eine Reihe von Annahmen für die verwendeten Zufallsvariablengetroffen werden. Folglich bedarf es einer inversen Methode, die es ermöglicht ein stochastisches Modell aus experimentellen Modaldaten zu identifizieren. Die Arbeit beschreibt die Entwicklung eines parameter-basierten Ansatzes, um stochastische Simulationsmodelle auf dem Gebiet der Strukturdynamik zu identifizieren. Die entwickelte Methode beruht auf Sensitivitäten erster Ordnung, mit denen Parametermittelwerte und Kovarianzen des numerischen Modells aus stochastischen experimentellen Modaldaten bestimmt werden können.
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Almost everyone sketches. People use sketches day in and day out in many different and heterogeneous fields, to share their thoughts and clarify ambiguous interpretations, for example. The media used to sketch varies from analog tools like flipcharts to digital tools like smartboards. Whereas analog tools are usually affected by insufficient editing capabilities like cut/copy/paste, digital tools greatly support these scenarios. Digital tools can be grouped into informal and formal tools. Informal tools can be understood as simple drawing environments, whereas formal tools offer sophisticated support to create, optimize and validate diagrams of a certain application domain. Most digital formal tools force users to stick to a concrete syntax and editing workflow, limiting the user’s creativity. For that reason, a lot of people first sketch their ideas using the flexibility of analog or digital informal tools. Subsequently, the sketch is "portrayed" in an appropriate digital formal tool. This work presents Scribble, a highly configurable and extensible sketching framework which allows to dynamically inject sketching features into existing graphical diagram editors, based on Eclipse GEF. This allows to combine the flexibility of informal tools with the power of formal tools without any effort. No additional code is required to augment a GEF editor with sophisticated sketching features. Scribble recognizes drawn elements as well as handwritten text and automatically generates the corresponding domain elements. A local training data library is created dynamically by incrementally learning shapes, drawn by the user. Training data can be shared with others using the WebScribble web application which has been created as part of this work.
Resumo:
• Aim: The present study aimed to evaluate the effect of trainees’ interpersonal behavior on work involvement (WI) and compared their social behavior within professional and private relationships as well as between different psychotherapeutic orientations. • Methods: The interpersonal scales of the Intrex short-form questionnaire and the Work Involvement Scale (WIS) were used to evaluate two samples of German psychotherapy trainees in psychoanalytic, psychodynamic, and cognitive behavioral therapy training. Trainees from Sample 1 (N = 184) were asked to describe their interpersonal behavior in relation to their patients when filling out the Intrex, whereas trainees from Sample 2 (N = 135) were asked to describe the private relationship with a significant other. • Results: Interpersonal affiliation in professional relationships significantly predicted the level of healing involvement, while stress involvement was predicted by interpersonal affiliation and interdependence in trainees’ relationships with their patients. Social behavior within professional relationships provided higher correlations with WI than private interpersonal behavior. Significant differences were found between private and professional relation settings in trainees’ interpersonal behavior with higher levels of affiliation and interdependence with significant others. Differences between therapeutic orientation and social behavior could only be found when comparing trainees’ level of interdependence with the particular relationship setting. • Conclusion: Trainees’ interpersonal level of affiliation in professional relationships is a predictor for a successful psychotherapeutic development. Vice versa, controlling behavior in professional settings can be understood as a risk factor against psychotherapeutic growth. Both results strengthen an evidence-based approach for competence development during psychotherapy training.
Resumo:
This research aims to understand the fundamental dynamic behavior of servo-controlled machinery in response to various types of sensory feedback. As an example of such a system, we study robot force control, a scheme which promises to greatly expand the capabilities of industrial robots by allowing manipulators to interact with uncertain and dynamic tasks. Dynamic models are developed which allow the effects of actuator dynamics, structural flexibility, and workpiece interaction to be explored in the frequency and time domains. The models are used first to explain the causes of robot force control instability, and then to find methods of improving this performance.
Resumo:
Computational theories of action have generally understood the organized nature of human activity through the construction and execution of plans. By consigning the phenomena of contingency and improvisation to peripheral roles, this view has led to impractical technical proposals. As an alternative, I suggest that contingency is a central feature of everyday activity and that improvisation is the central kind of human activity. I also offer a computational model of certain aspects of everyday routine activity based on an account of improvised activity called running arguments and an account of representation for situated agents called deictic representation .
Resumo:
Research on autonomous intelligent systems has focused on how robots can robustly carry out missions in uncertain and harsh environments with very little or no human intervention. Robotic execution languages such as RAPs, ESL, and TDL improve robustness by managing functionally redundant procedures for achieving goals. The model-based programming approach extends this by guaranteeing correctness of execution through pre-planning of non-deterministic timed threads of activities. Executing model-based programs effectively on distributed autonomous platforms requires distributing this pre-planning process. This thesis presents a distributed planner for modelbased programs whose planning and execution is distributed among agents with widely varying levels of processor power and memory resources. We make two key contributions. First, we reformulate a model-based program, which describes cooperative activities, into a hierarchical dynamic simple temporal network. This enables efficient distributed coordination of robots and supports deployment on heterogeneous robots. Second, we introduce a distributed temporal planner, called DTP, which solves hierarchical dynamic simple temporal networks with the assistance of the distributed Bellman-Ford shortest path algorithm. The implementation of DTP has been demonstrated successfully on a wide range of randomly generated examples and on a pursuer-evader challenge problem in simulation.
Resumo:
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms, including the TD(lambda) algorithm of Sutton (1988) and the Q-learning algorithm of Watkins (1989), can be motivated heuristically as approximations to dynamic programming (DP). In this paper we provide a rigorous proof of convergence of these DP-based learning algorithms by relating them to the powerful techniques of stochastic approximation theory via a new convergence theorem. The theorem establishes a general class of convergent algorithms to which both TD(lambda) and Q-learning belong.