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Dissertations / Theses on the topic 'Automatic human behavioral analysis'
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Zhao, Ruiqi. "Spatial and temporal modelling for automatic human behavioral analysis." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1480683512602658.
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Li, Chen. "Automatic extraction of behavioral patterns for elderly mobility and daily routine analysis." HKBU Institutional Repository, 2018. https://repository.hkbu.edu.hk/etd_oa/510.
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The elderly living in smart homes can have their daily movement recorded and analyzed. Given the fact that different elders can have their own living habits, a methodology that can automatically identify their daily activities and discover their daily routines will be useful for better elderly care and support. In this thesis research, we focus on developing data mining algorithms for automatic detection of behavioral patterns from the trajectory data of an individual for activity identification, daily routine discovery, and activity prediction. The key challenges for the human activity analysis include the need to consider longer-range dependency of the sensor triggering events for activity modeling and to capture the spatio-temporal variations of the behavioral patterns exhibited by human. We propose to represent the trajectory data using a behavior-aware flow graph which is a probabilistic finite state automaton with its nodes and edges attributed with some local behavior-aware features. Subflows can then be extracted from the flow graph using the kernel k-means as the underlying behavioral patterns for activity identification. Given the identified activities, we propose a novel nominal matrix factorization method under a Bayesian framework with Lasso to extract highly interpretable daily routines. To better take care of the variations of activity durations within each daily routine, we further extend the Bayesian framework with a Markov jump process as the prior to incorporate the shift-invariant property into the model. For empirical evaluation, the proposed methodologies have been compared with a number of existing activity identification and daily routine discovery methods based on both synthetic and publicly available real smart home data sets with promising results obtained. In the thesis, we also illustrate how the proposed unsupervised methodology could be used to support exploratory behavior analysis for elderly care.
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Baird, Isabelle Catherine. "The development of the human-automation behavioral interaction task (HABIT) analysis framework." Wright State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1559836548618924.
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Hamid, Muhammad Raffay. "A computational framework for unsupervised analysis of everyday human activities." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24765.
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Thesis (Ph.D.)--Computing, Georgia Institute of Technology, 2009.Committee Chair: Aaron Bobick; Committee Member: Charles Isbell; Committee Member: David Hogg; Committee Member: Irfan Essa; Committee Member: James Rehg
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Hayfron-Acquah, James Ben. "Automatic gait recognition by symmetry analysis." Thesis, University of Southampton, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.274080.
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Shen, Kai-kai. "Automatic segmentation and shape analysis of human hippocampus in Alzheimer's disease." Phd thesis, Université de Bourgogne, 2011. http://tel.archives-ouvertes.fr/tel-00703099.
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The aim of this thesis is to investigate the shape change in hippocampus due to the atrophy in Alzheimer's disease (AD). To this end, specific algorithms and methodologies were developed to segment the hippocampus from structural magnetic resonance (MR) images and model variations in its shape. We use a multi-atlas based segmentation propagation approach for the segmentation of hippocampus which has been shown to obtain accurate parcellation of brain structures. We developed a supervised method to build a population specific atlas database, by propagating the parcellations from a smaller generic atlas database. Well segmented images are inspected and added to the set of atlases, such that the segmentation capability of the atlas set may be enhanced. The population specific atlases are evaluated in terms of the agreement among the propagated labels when segmenting new cases. Compared with using generic atlases, the population specific atlases obtain a higher agreement when dealing with images from the target population. Atlas selection is used to improve segmentation accuracy. In addition to the conventional selection by image similarity ranking, atlas selection based on maximum marginal relevance (MMR) re-ranking and least angle regression (LAR) sequence are developed for atlas selection. By taking the redundancy among atlases into consideration, diversity criteria are shown to be more efficient in atlas selection which is applicable in the situation where the number of atlases to be fused is limited by the computational resources. Given the segmented hippocampal volumes, statistical shape models (SSMs) of hippocampi are built on the samples to model the shape variation among the population. The correspondence across the training samples of hippocampi is established by a groupwise optimization of the parameterized shape surfaces. The spherical parameterization of the hippocampal surfaces are flatten to facilitate the reparameterization and interpolation. The reparameterization is regularized by viscous fluid, which is solved by a fast implementation based on discrete sine transform. In order to use the hippocampal SSM to describe the shape of an unseen hippocampal surface, we developed a shape parameter estimator based on the expectationmaximization iterative closest points (EM-ICP) algorithm. A symmetric data term is included to achieve the inverse consistency of the transformation between the model and the shape, which gives more accurate reconstruction of the shape from the model. The shape prior modeled by the SSM is used in the maximum a posteriori estimation of the shape parameters, which is shown to enforce the smoothness and avoid the effect of over-fitting. In the study of the hippocampus in AD, we use the SSM to model the hippocampal shape change between the healthy control subjects and patients diagnosed with AD. We identify the regions affected by the atrophy in AD by assessing the spatial difference between the control and AD groups at each corresponding landmark. Localized shape analysis is performed on the regions exhibiting significant inter-group difference, which is shown to improve the discrimination ability of the principal component analysis (PCA) based SSM. The principal components describing the localized shape variability among the population are also shown to display stronger correlation with the decline of episodic memory scores linked to the pathology of hippocampus in AD.
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Shen, Kaikai. "Automatic segmentation and shape analysis of human hippocampus in Alzheimer's disease." Thesis, Dijon, 2011. http://www.theses.fr/2011DIJOS072/document.
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L’objectif de cette thèse est l’étude des changements de la forme de l’hippocampe due à l’atrophie causée par la maladie d’Alzheimer. Pour ce faire, des algorithmes et des méthodes ont été développés pour segmenter l’hippocampe à partir d’imagerie structurelle par résonance magnétique (IRM) et pour modéliser les variations dans sa forme. Nous avons utilisé une méthode de segmentation par propagation de multiple atlas pour la segmentation de l’hippocampe, méthode qui a été démontrée comme étant robuste dans la segmentation des structures cérébrales. Nous avons développé une méthode supervisée pour construire une base de données d’atlas spécifique à la population d’intérêt en propageant les parcellations d’une base de données génériques d’atlas. Les images correctement segmentées sont inspectées et ajoutées à la base de données d’atlas, de manière à améliorer sa capacité à segmenter de nouvelles images. Ces atlas sont évalués en termes de leur accord lors de la segmentation de nouvelles images. Comparé aux atlas génériques, les atlas spécifiques à la population d’intérêt obtiennent une plus grande concordance lors de la segmentation des des images provenant de cette population. La sélection d’atlas est utilisée pour améliorer la précision de la segmentation. La méthode classique de sélection basée sur la similarité des images est ici étendue pour prendre en compte la pertinence marginale maximale (MMR) et la régression des moindres angles (LAR). En prenant en considération la redondance parmi les atlas, des critères de diversité se montrent être plus efficace dans la sélection des atlas dans le cas où seul un nombre limité d’atlas peut-être fusionné. A partir des hippocampes segmentés, des modèles statistiques de la forme (SSM) sont construits afin de modéliser les variations de la forme de l’hippocampe dans la population. La correspondance entre les hippocampes est établie par une optimisation d’ensemble des surfaces paramétriques. Les paramétrages sphériques des surfaces sont aplatis pour faciliter la reparamétrisation et l’interpolation. Le reparamétrage est régularisé par une contrainte de type fluide visqueux, qui est effectué à l’aide d’une implémentation basée sur la transformées en sinus discrète. Afin d’utiliser le SSM pour décrire la forme d’une nouvelle surface hippocampique, nous avons développé un estimateur des paramètres du model de la forme basée sur l’espérance-maximisation de l’algorithme du plus proche voisin itéré (EM-ICP). Un terme de symétrie est inclus pour forcer une consistance entre la transformée directe et inverse entre le modèle et la forme, ce qui permet une reconstruction plus précise de la forme à partir du modèle. La connaissance a priori sur la forme modélisé par le SSM est utilisée dans l’estimation du maximum a posteriori des paramètres de forme. Cette méthode permet de forcer la continuité spatiale et éviter l’effet de sur-apprentissage. Dans l’étude de l’hippocampe dans la maladie d’Alzheimer, nous utilisons le SSM pour modéliser le changement de forme de l’hippocampe entre les sujets sains et des patients souffrant d’Alzheimer. Nous identifions les régions touchées par l’atrophie dans la maladie d’Alzheimer en évaluant la différence entre les groupes de contrôle et ceux d’Alzheimer sur chaque point correspondant sur la surface. L’analyse des changements de la forme est restreinte aux régions présentant des différences significatives entre les groupes, ce qui a pour effet d’améliorer la discrimination basée sur l’analyse en composantes principales (ACP) du SSM. Les composantes principales décrivant la variabilité de la forme à l’intérieur des régions discriminantes ont une corrélation plus fortes avec le déclin des scores de mémoire épisodique liée à la pathologie de l’hippocampe dans la maladie d’AlzheimerThe aim of this thesis is to investigate the shape change in hippocampus due to the atrophy in Alzheimer’s disease (AD). To this end, specific algorithms and methodologies were developed to segment the hippocampus from structural magnetic resonance (MR) images and model variations in its shape. We use a multi-atlas based segmentation propagation approach for the segmentation of hippocampus which has been shown to obtain accurate parcellation of brain structures. We developed a supervised method to build a population specific atlas database, by propagating the parcellations from a smaller generic atlas database. Well segmented images are inspected and added to the set of atlases, such that the segmentation capability of the atlas set may be enhanced. The population specific atlases are evaluated in terms of the agreement among the propagated labels when segmenting new cases. Compared with using generic atlases, the population specific atlases obtain a higher agreement when dealing with images from the target population. Atlas selection is used to improve segmentation accuracy. In addition to the conventional selection by image similarity ranking, atlas selection based on maximum marginal relevance (MMR) re-ranking and least angle regression (LAR) sequence are developed for atlas selection. By taking the redundancy among atlases into consideration, diversity criteria are shown to be more efficient in atlas selection which is applicable in the situation where the number of atlases to be fused is limited by the computational resources. Given the segmented hippocampal volumes, statistical shape models (SSMs) of hippocampi are built on the samples to model the shape variation among the population. The correspondence across the training samples of hippocampi is established by a groupwise optimization of the parameterized shape surfaces. The spherical parameterization of the hippocampal surfaces are flatten to facilitate the reparameterization and interpolation. The reparameterization is regularized by viscous fluid, which is solved by a fast implementation based on discrete sine transform. In order to use the hippocampal SSM to describe the shape of an unseen hippocampal surface, we developed a shape parameter estimator based on the expectationmaximization iterative closest points (EM-ICP) algorithm. A symmetric data term is included to achieve the inverse consistency of the transformation between the model and the shape, which gives more accurate reconstruction of the shape from the model. The shape prior modeled by the SSM is used in the maximum a posteriori estimation of the shape parameters, which is shown to enforce the smoothness and avoid the effect of over-fitting. In the study of the hippocampus in AD, we use the SSM to model the hippocampal shape change between the healthy control subjects and patients diagnosed with AD. We identify the regions affected by the atrophy in AD by assessing the spatial difference between the control and AD groups at each corresponding landmark. Localized shape analysis is performed on the regions exhibiting significant inter-group difference, which is shown to improve the discrimination ability of the principal component analysis (PCA) based SSM. The principal components describing the localized shape variability among the population are also shown to display stronger correlation with the decline of episodic memory scores linked to the pathology of hippocampus in AD
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Zelmann, Rina. "Automatic detection and analysis of high frequency oscillations in the human electroencephalogram." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114313.
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High Frequency Oscillations (HFOs; 80-500Hz) are spontaneous short-duration small-amplitude EEG patterns that are emerging as a biomarker of tissue capable of generating epileptic seizures. In order to propel the clinical utilization and systematic study of HFOs, it is important to develop robust automatic detectors and to provide a framework to ensure stability in their identification; this is the first goal of this thesis. Although HFOs have mostly been studied with intracranial electrodes, they have also been recorded on the scalp. A fundamental question is to understand how is it possible to see these small events on the scalp given the powerful skull attenuation; this is the second goal of this thesis. The first goal is addressed by designing a procedure to systematize the study of HFOs and by developing an automatic detector. A procedure that allows to control for consistency among readers and to evaluate if a selected interval provides stable information, for automatic and visual identification of HFOs, is first presented. This procedure is now routinely used when identifying interictal HFOs. This study is the first to evaluate the minimum duration needed to obtain consistent information when marking the EEG and showed that analyzing 5min of interictal EEG provided the same information as longer intervals. The approach is applicable to any type of EEG event.An automatic detector of HFOs is then described, which takes an original approach in first detecting baseline segments free of oscillatory activity and then using a statistical threshold obtained from these local baselines to detect HFOs. The detector performs better than other detectors, in particular in active channels and in channels without clear baseline. A comparison of existing detectors on the same dataset is presented to analyze their performance, to show that optimizing on a particular type of data improves performance in any detector, and to emphasize the issues involved in validation. The second goal of this thesis is the study of the spatial distribution of cortical activity at the time of scalp HFOs. As HFOs are produced by small brain regions, and since the EEG is greatly attenuated before reaching the scalp, HFOs are mostly recorded with intracranial electrodes. Surprisingly, HFOs have been recently observed also on the scalp EEG. Using simultaneous scalp and intracranial recordings, we showed that even though the generators of HFOs have small spatial extent, they can be observed on the scalp with small amplitude and focal extent. We showed that these small extent events are undersampled on the scalp with the density of standard electrode systems, and on cortical grids with the standard inter-electrode spacing of 1cm. A dense distribution of scalp electrodes seems necessary to fully spatially sample HFOs on the scalp. This opens the possibility of systematically studying HFOs non-invasively. By developing methods for the detection and analysis of HFOs, we expect to improve the systematic study of intracranial and scalp HFOs, moving towards their clinical application as a biomarker of epileptogenic tissue.Les oscillations de haute fréquence (OHF; 80-500 Hz) constituent des évènements EEG spontanés de courte durée et de faible amplitude qui émergent en tant que biomarqueur du tissu pouvant générer les crises épileptiques. Afin de promouvoir l'utilisation clinique et l'étude systématique des OHF, il est important de développer des détecteurs automatiques fiables et de fournir un cadre visant à garantir la stabilité de leurs résultats. Il s'agit là du premier objectif de la présente thèse. Les OHF ont principalement été étudiées à partir d'électrodes intracrâniennes, mais elles ont également été enregistrées à l'aide d'électrodes placées sur le cuir chevelu. Il convient alors de comprendre comment l'on peut observer ces évènements de faible envergure du fait de l'atténuation importante du crâne, ce qui constitue le second objectif de cette thèse. Pour répondre au premier objectif, nous avons conçu une procédure visant à systématiser l'étude des OHF et avons élaboré un détecteur automatique. Ainsi, nous présentons d'abord une procédure permettant d'assurer l'uniformité entre les lecteurs et d'évaluer si un intervalle choisi offre des renseignements stables pour un repérage visuel et automatique des OHF. À l'heure actuelle, cette procédure est communément utilisée quand les OHF interictales sont repérées. Cette étude est la première à évaluer la durée minimale nécessaire à l'obtention de renseignements cohérents pour le marquage des EEG et elle a démontré que l'analyse de 5 minutes d'EEG interictal offre la même information que des intervalles de plus longue durée. Cette approche est applicable à tout type d'évènements EEG. Nous avons ensuite décrit un détecteur automatique d'OHF, qui suit une approche originale en détectant d'abord des segments de base dénués d'activités oscillatoires avant d'utiliser un seuil statistique obtenu à partir de ces valeurs de base locales pour déterminer les OHF. Ce détecteur est plus efficace que d'autres détecteurs, notamment pour les canaux actifs et les canaux sans valeur de base claire. Une comparaison entre les détecteurs existants pour le même ensemble de données est présentée afin d'analyser leur performance respective, de démontrer que l'optimisation d'un certain type de données améliore l'efficacité de tous les détecteurs et de mettre en évidence les problèmes en jeu dans la validation. Le second objectif de la présente thèse est d'étudier la distribution spatiale de l'activité corticale au moment des OHF enregistrées sur le cuir chevelu. Dans la mesure où les OHF sont produites par de petites régions cérébrales et que l'EEG est fortement atténué avant d'arriver au cuir chevelu, les OHF sont surtout enregistrées à l'aide d'électrodes intracrâniennes. Il est étonnant que dernièrement, des OHF aient également été observées sur des EEG enregistrés sur le cuir chevelu. En se basant sur les enregistrements simultanés sur le cuir chevelu et intracrâniens, nous avons démontré que, même si les régions génératrices d'OHF sont faiblement étendues sur le plan spatial, les OHF peuvent être observées à l'aide d'électrodes placées sur le cuir chevelu avec une faible amplitude et une étendue focale. Nous avons établi que ces évènements de faible étendue sont sous-échantillonnés sur le cuir chevelu avec la densité des systèmes standards d'électrodes et sur les grilles corticales avec l'espacement standard de 1 cm entre les électrodes. Il semble nécessaire d'avoir une répartition dense des électrodes sur le cuir chevelu afin de représenter spatialement de façon exhaustive les OHF enregistrées sur le cuir chevelu. Cela ouvrirait la voie à une étude systématique non invasive des OHF. Avec l'élaboration de méthodes de détection et d'analyse des OHF, nous souhaitons améliorer l'étude systématique des OHF intracrâniennes et du cuir chevelu, dans l'optique d'une application clinique en tant que biomarqueur du tissu épileptogène.
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Santos, Paulo Alexandre Vieira Jacinto dos. "Automatic detection of user transitionality by analysis of interaction." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/9154.
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Crowl, Justin. "An analysis of music and its influence on adult lifestyle choices and behavioral tendencies /." Connect to resource online, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1254324107.
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Al-Mter, Yusur. "Automatic Prediction of Human Age based on Heart Rate Variability Analysis using Feature-Based Methods." Thesis, Linköpings universitet, Statistik och maskininlärning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166139.
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Heart rate variability (HRV) is the time variation between adjacent heartbeats. This variation is regulated by the autonomic nervous system (ANS) and its two branches, the sympathetic and parasympathetic nervous system. HRV is considered as an essential clinical tool to estimate the imbalance between the two branches, hence as an indicator of age and cardiac-related events.This thesis focuses on the ECG recordings during nocturnal rest to estimate the influence of HRV in predicting the age decade of healthy individuals. Time and frequency domains, as well as non-linear methods, are explored to extract the HRV features. Three feature-based methods (support vector machine (SVM), random forest, and extreme gradient boosting (XGBoost)) were employed, and the overall test accuracy achieved in capturing the actual class was relatively low (lower than 30%). SVM classifier had the lowest performance, while random forests and XGBoost performed slightly better. Although the difference is negligible, the random forest had the highest test accuracy, approximately 29%, using a subset of ten optimal HRV features. Furthermore, to validate the findings, the original dataset was shuffled and used as a test set and compared the performance to other related research outputs.
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Brown, Michael J. "SINGULAR VALUE DECOMPOSITION AND 2D PRINCIPAL COMPONENT ANALYSIS OF IRIS-BIOMETRICS FOR AUTOMATIC HUMAN IDENTIFICATION." Ohio University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1149187904.
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Feng, Zhuo. "A Behavioral Study of Chinese Online Human Flesh Communities: Modeling and Analysis with Social Networks." Diss., The University of Arizona, 2012. http://hdl.handle.net/10150/243119.
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Human Flesh Search (HFS), originated in China, has become an explosive Web phenomenon. HFS episodes typically start with news events. Participants pay close attention to the events, get together online, investigate, try to solve the real world problems and find the truth. In HFS episodes, participants form online communities, share information and collaborate with each other. Such online communities are unique subjects of social network study. This dissertation presents the first systematic empirical study and data-driven modeling of HFS. We give the formal definition of HFS, summarize the typical HFS process and classify the episodes based on their topics. We study network measurements of the social networks corresponding to the communities of individual HFS episodes. The communities are strongly centralized, and have small world property. Information diffusion within the communities restricts by the central hubs of the networks. To understand the overall properties of HFS communities, HFS core network is built to study the connections of participants in all episodes. The result shows that HFS core network is a small world and scale-free network. Since the HFS communities do not follow any existing network model, a modified network model is purposed to explain the characteristics of HFS episode networks.
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Alvey, Debi A. "A Behavioral Economic Analysis of Different Reinforcers: Sound-Clips Versus Points Exchangeable for Money." Thesis, University of North Texas, 2000. https://digital.library.unt.edu/ark:/67531/metadc2738/.
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Human operant studies frequently use points exchangeable for money as reinforcers. Some studies employ more immediately consumable reinforcers to emulate properties of food reinforcers. This study examined demand for points/money and for sound-clips to compare their economic characteristics. Across four participants, demand was often higher and less elastic for points/money than for sounds. During subsequent exposures at each response requirement, demand for sounds often decreased to a greater degree than demand for points/money. Thus, sound-clips seem less durable than points/money across prices and across repeated exposure to the same price. Response rates for points/money were often higher than for sounds, suggesting that reinforcers that generate higher response rates may be less elastic than reinforcers that generate lower response rates.
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Hayes, Kate. "A Qualitative Analysis of Student Behavior and Language During Group Problem Solving." Fogler Library, University of Maine, 2009. http://www.library.umaine.edu/theses/pdf/HayesK2009.pdf.
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Kollokian, Vasken. "Performance analysis of automatic techniques for tissue classification in magnetic resonance images of the human brain." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/mq26016.pdf.
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Bergelin, Victor. "Human Activity Recognition and Behavioral Prediction using Wearable Sensors and Deep Learning." Thesis, Linköpings universitet, Matematiska institutionen, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138064.
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When moving into a more connected world together with machines, a mutual understanding will be very important. With the increased availability in wear- able sensors, a better understanding of human needs is suggested. The Dart- mouth Research study at the Psychiatric Research Center has examined the viability of detecting and further on predicting human behaviour and complex tasks. The field of smoking detection was challenged by using the Q-sensor by Affectiva as a prototype. Further more, this study implemented a framework for future research on the basis for developing a low cost, connected, device with Thayer Engineering School at Dartmouth College. With 3 days of data from 10 subjects smoking sessions was detected with just under 90% accuracy using the Conditional Random Field algorithm. However, predicting smoking with Electrodermal Momentary Assessment (EMA) remains an unanswered ques- tion. Hopefully a tool has been provided as a platform for better understanding of habits and behaviour.
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Head, Elizabeth. "The canine as an animal model of human aging and dementia, a behavioral and neurobiological analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape16/PQDD_0005/NQ27947.pdf.
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McCord, Brandon Ellis. "Preliminary Examination of Methods for Identifying the Function of Stealing." OpenSIUC, 2020. https://opensiuc.lib.siu.edu/dissertations/1881.
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Because low rate, covert responses are hard to observe and measure (e.g., Azrin & Wesolowski, 1974; Henderson, 1981; Jeffery, 1969; Reid & Patterson, 1976; Seymour & Epston, 1989), well-controlled behavior analytic investigations of stealing have been rare. In fact, systematic investigations to experimentally determine stealing functions have been limited to two studies targeting food (Lambert et al., 2019; Simmons, Akers, & Fisher, 2019). The dearth of studies examining stealing functions, partly attributable to low rate and covertness, may be forestalling additional intervention studies. Given the likely futility of unsystematic attempts to observe naturally occurring instances of an infrequent, clandestine response, a possible role for indirect assessment emerges (Iwata & Dozier, 2008). This two-part study concerned an investigation into the reliability and predictive validity of the Functional Analysis Screening Tool (Iwata, DeLeon, & Roscoe, 2013) and a similarly constructed tool (The Stealing Inventory or TSI) with the latter having questions oriented towards likely stealing functions. In doing so, the comparative viability of two trial-based functional analysis (FA) models (Bloom, Iwata, Fritz, Roscoe, & Carreau, 2011; Lambert, Bloom, & Irvin, 2012) was also examined. Across 42 respondent pairs, overall tool reliability and outcome reliability for suggested functions favored the TSI (85% and 92.9%, respectively) over the FAST (80% and 73.8%, respectively). Three out of 6 participants stole during one of their two respective FAs, and the identified function matched the respective TSI outcomes for each case. FA model superiority was unclear.
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Oh, Sang Min. "Switching linear dynamic systems with higher-order temporal structure." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29698.
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Thesis (Ph.D)--Computing, Georgia Institute of Technology, 2010.Committee Chair: Dellaert, Frank; Committee Co-Chair: Rehg, James; Committee Member: Bobick, Aaron; Committee Member: Essa, Irfan; Committee Member: Smyth, Padhraic. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Anzalotta, Jaime. "I am Human, Too! An Analysis of Conflict Resolution Theories and Their Applicability to the LGBTQ Community." Diss., NSUWorks, 2017. https://nsuworks.nova.edu/shss_dcar_etd/70.
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Members of the LGBT community have historically been victims of marginalization and alienation to various degrees. Incidents such as the Stonewall Riots, pride marches, and manifestos, among others, have served as a way for the LGBTQ community to attempt to take a stand against the systems in place that perpetuate inequality. Factors such as identity and gender have directly impacted the level to which individuals are shunned from their families, communities and social nexus. The purpose of this dissertation is to explore how factors such as identity and gender impact a sense of integration in the LGBTQ community. In addition, this dissertation aims to determine the applicability of three conflict resolution theories: Structural Violence, Social Cubism, and Maslow’s Hierarchy of Needs, to the LGBTQ community. This study analyzes the history of the LGBTQ community, identity formation theories, gender expectations in society, and factors that lead to alienation and marginalization. This dissertation is a qualitative study which utilizes case study methodology to analyze the existing literature related to the aforementioned topics. In this study, the reader is provided with a detailed explanation of the applicability of the three theories, including the role of factors such as identity, gender, and integration versus tolerance in the LGBTQ community. The study concludes with an analysis of the theories, recommendations for future research, and insight for those who aim to resolve conflict in the LGBTQ community.
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Miyawaki, Shinjiro. "Automatic construction and meshing of multiscale image-based human airway models for simulations of aerosol delivery." Diss., University of Iowa, 2013. https://ir.uiowa.edu/etd/1990.
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The author developed a computational framework for the study of the correlation between airway morphology and aerosol deposition based on a population of human subjects. The major improvement on the previous framework, which consists of a geometric airway model, a computational fluid dynamics (CFD) model, and a particle tracking algorithm, lies in automatic geometry construction and mesh generation of airways, which is essential for a population-based study. The new geometric model overcomes the shortcomings of both centerline (CL)-based cylindrical models, which are based on the skeleton and average branch diameters of airways called one-dimensional (1-D) trees, and computed tomography (CT)-based models. CL-based models are efficient in terms of pre- and post-processing, but fail to represent trifurcations and local morphology. In contrast, in spite of the accuracy of CT-based models, it is time-consuming to build these models manually, and non-trivial to match 1-D trees and three-dimensional (3-D) geometry. The new model, also known as a hybrid CL-CT-based model, is able to construct a physiologically-consistent laryngeal geometry, represent trifurcations, fit cylindrical branches to CT data, and create the optimal CFD mesh in an automatic fashion. The hybrid airway geometries constructed for 8 healthy and 16 severe asthmatic (SA) subjects agreed well with their CT-based counterparts. Furthermore, the prediction of aerosol deposition in a healthy subject by the hybrid model agreed well with that by the CT-based model. To demonstrate the potential application of the hybrid model to investigating the correlation between skeleton structure and aerosol deposition, the author applied the large eddy simulation (LES)-based CFD model that accounts for the turbulent laryngeal jet to three hybrid models of SA subjects. The correlation between diseased branch and aerosol deposition was significant in one of the three SA subjects. However, whether skeleton structure contributes to airway abnormality requires further investigation.
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Vela-Beltran-del-Rio, Cesar. "The Human Robot: A Narrative Study of Identity Change in Mexico Through an Analysis of Mexican Films." NSUWorks, 2014. http://nsuworks.nova.edu/shss_dcar_etd/42.
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In order to succeed in an intellectually, economically, socially, and politically controlled system, as México, one has to develop a sense of inner direction and empowerment, where critical thinking is vital yet patriarchy becomes an impediment to the development of an inner compass and empowerment when it shapes and controls the masses’ identity and behavior through different strategies, methods, and institutions. One of the most powerful and popular identity shaping strategies is film making. Film is considered by most as a source of entertainment portraying social interactions. Yet it is a powerful identity-shaping tool for the establishment. It has been used by the Mexican government and its associates, for a long time, in an effort to sustain the status quo and justify its existence and social performance. The selected methodology of this study allowed comparison and contrasting of messages transmitted about identity, behavior, role-identification, values, and life scripts, using films from three different periods of the development of México: agricultural (1920s-1950s), industrial (1950s-1990s), and neoliberal (1990s-today). Religion, social interactions, gender, ethnicity, and nation-states are some of the main themes that emerged from this exploration of identity and behavior shaping strategies used in the Mexican films analyzed. The Identity shaping strategies are an efficient way of dealing with conflict because controlling and constraining is done by the individuals rather than by the nation-state.
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Sidorov, Kirill. "Groupwise non-rigid registration for automatic construction of appearance models of the human craniofacial complex for analysis, synthesis and simulation." Thesis, Cardiff University, 2010. http://orca.cf.ac.uk/55498/.
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Finally, a novel application of 3D appearance modelling is proposed: a faster than real-time algorithm for statistically constrained quasi-mechanical simulation. Experiments demonstrate superior realism, achieved in the proposed method by employing statistical appearance models to drive the simulation, in comparison with the comparable state-of-the-art quasi-mechanical approaches.
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Leighty, Ralph E. "Statistical and Data Mining Methodologies for Behavioral Analysis in Transgenic Mouse Models of Alzheimer’s Disease: Parallels with Human AD Evaluation." Scholar Commons, 2009. http://scholarcommons.usf.edu/etd/3872.
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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the
leading cause of human senile dementia. Alzheimer’s represents a significant public
health concern, having widespread social and economic implications. Consequently,
protocols for early detection and therapeutic intervention (both behavioral and pharmacologic)
constitute important targets for medical investigation. Furthermore, contemporary
research depends upon comprehensive neurobehavioral assessment and
advanced statistical and computational analytic methodologies for characterizing
AD-associated sensorimotor and cognitive impairment, as well as evaluating therapeutic
efficacy. This dissertation introduces data mining-based techniques (decision
trees, neural networks, support vector machines) for behavioral analysis in both
nontransgenic and Alzheimer’s transgenic mice, to evaluate the cognitive benefits of
long-term caffeine treatment. Both treatment and transgenic effects are identified
through advanced statistical (discriminant analysis) and data mining approaches. In
addition, a novel mouse-based cognitive assessment paradigm, adapted from a human
interference learning AD-diagnostic protocol, is implemented to evaluate both
genetic (GRK5) and therapeutic (GM-CSF) effects in mice, against an Alzheimer’s
transgenic background. Data mining techniques are shown to be comparable to con
ventional statistical analyses, often providing complementary diagnostic information.
Indeed, comparisons between data mining-based and multivariate statistical analyses,
with respect to groupwise discriminability, support the use of both methodologies
in neurobehavioral research. Future work involving both data mining-based and
multivariate statistical analyses of cognitive-behavioral data is discussed, emphasizing
the need for longitudinal studies, repeated-measure designs, and spatiotemporal
modeling for evaluating the time-course of both human AD and AD-like pathology
in transgenic mouse models.
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Leighty, Ralph E. "Statistical and data mining methodologies for behavioral analysis in transgenic mouse models of Alzheimer's disease : parallels with human AD evaluation." [Tampa, Fla] : University of South Florida, 2009. http://purl.fcla.edu/usf/dc/et/SFE0002869.
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Pace, Laura. "East Urban Area Corridor Analysis Daviess County, Kentucky." TopSCHOLAR®, 1991. http://digitalcommons.wku.edu/theses/1803.
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The need for improved highway facilities in the east urban area of Daviess County, Kentucky, is analyzed in this study. The study focuses upon the need for alternative highway routes, due to the increased travel demands generated by a new Ohio River Bridge in eastern Daviess County. Also, the east urban area is forecasted to experience population and employment growth in the next decade, further necessitating the need for improving existing highways or constructing new corridors in the area.
Various alternative alignments for an expressway are examined. The feasibility of upgrading existing highways in the east urban area is also analyzed. The study utilizes numerous transportation planning techniques, including the development of traffic projections, highway capacity analysis, cost estimates and land use and environmental impacts. The study includes original research and data collection in analyzing five alternatives. An alternative for constructing a new expressway in the east urban area of Daviess County is recommended.
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Camper, Bradley. "A Case Study Analysis among Former Urban Gifted High School Dropouts." ScholarWorks, 2019. https://scholarworks.waldenu.edu/dissertations/6182.
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The dropout social problem has been the focus of researchers, business and community leaders, and school staffs for decades. Despite possessing significant academic high school capabilities, some gifted students drop out of school. The research problem for this study includes, how and why former gifted urban high school students chose to drop out. The conceptual framework for this case study is Bronfenbrenner's human ecology theory. The purpose of this study was to gain an understanding of what lead former gifted urban students to dropping out of high school. Using purposive sampling, 4 participants, two men and two women, were selected for semi-structured interviews. The sample included an African-American, Filipino, Caucasian, and Haitian/Cuban/Syrian, whose ages ranged from 38-77 years old. The semi-structured interviews were analyzed using first, second, and pattern coding. The resulting themes were (a) family discord, (b) school not interesting, and (c) no role model, and (d) minimum family participation. The former gifted high school students' dropout experiences were rooted in the microsystem perspective of the human ecology theory. The implications for social change from this study findings may help inform those who manage and teach gifted programs about the mindsets of students in gifted services.
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Gahman, Kady. "The Use of the Performance Diagnostic Checklist - Human Services to Assess and Improve Data Reporting in a Community-Based Adult Autism Service Program." Master's thesis, Temple University Libraries, 2019. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/563014.
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Applied Behavioral AnalysisM.S.Ed.
For agencies in the health and human services field, data reporting is the primary source of information from which progress and organizational outcomes are measured. Often, front-line staff are responsible for collecting these data and yet are often ill-equipped to collect data accurately and consistently leading to a performance deficit affecting the strength and success of the program. Evaluating and addressing performance issues in the human services field has long been a challenge due to limited resources. Finding an effective and efficient method of evaluation that leads to a function-based intervention would improve performance and ultimately improve organizational outcomes. This study evaluated the Performance Diagnostic Checklist – Human Services (PDC-HS) as means of assessing the performance deficit of inaccurate data reporting in a community-based adult autism services program. A multiple-baseline design was used across four participants to evaluate the effects of the interventions indicated by the PDC-HS. Two participants received performance feedback and two received additional training following the behavior skills training model. Results indicated that both interventions were effective in increasing accurate data reporting across participants. Social validity measures also indicated the PDC-HS was easy to use and could be completed in a timely manner.
Temple University--Theses
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Cook, Henry Ernest IV. "EFFECT OF ENACTIVE-INTERFACE CONSTRAINTS ON USER BEHAVIOR IN VIRTUAL ENVIRONMENTS." Miami University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=miami1366718517.
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Guo, Yijie, and Yaowen Shen. "Design of Automatic System in Ice-cream Shop." Thesis, Blekinge Tekniska Högskola, Institutionen för maskinteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16279.
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The focus of this work was to design, develop and implement an automatic scoop system for an ice-cream shop. The main contribution covers programming of PLC and Arduino, LabVIEW, mechanical structure design of scoop, assembly line, timing belt and robotics arm and stress analysis of the structures in the system. This work solved the problem that the scooping ice-cream shop employees need to be supported by technology in their hard work and to improve the efficiency of the ice-cream disposal. The scoop is designed as a new type solving the stress issue. The control system was programmed to use robotics arm to scoop ice-cream, which enhanced the work efficiency. stress and modal analysis was done for ensure the safety of the system. Testing and validation of the system was carried out and results show it worked properly.
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Fairley, Jacqueline Antoinette. "Statistical modeling of the human sleep process via physiological recordings." Diss., Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/33912.
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The main objective of this work was the development of a computer-based Expert Sleep Analysis Methodology (ESAM) to aid sleep care physicians in the diagnosis of pre-Parkinson's disease symptoms using polysomnogram data. ESAM is significant because it streamlines the analysis of the human sleep cycles and aids the physician in the identification, treatment, and prediction of sleep disorders.
In this work four aspects of computer-based human sleep analysis were investigated: polysomnogram interpretation, pre-processing, sleep event classification, and abnormal sleep detection. A review of previous developments in these four areas is provided along with their relationship to the establishment of ESAM. Polysomnogram interpretation focuses on the ambiguities found in human polysomnogram analysis when using the rule based 1968 sleep staging manual edited by Rechtschaffen and Kales (R&K). ESAM is presented as an alternative to the R&K approach in human polysomnogram interpretation. The second area, pre-processing, addresses artifact processing techniques for human polysomnograms. Sleep event classification, the third area, discusses feature selection, classification, and human sleep modeling approaches. Lastly, abnormal sleep detection focuses on polysomnogram characteristics common to patients suffering from Parkinson's disease.
The technical approach in this work utilized polysomnograms of control subjects and pre-Parkinsonian disease patients obtained from the Emory Clinic Sleep Disorders Center (ECSDC) as inputs into ESAM. The engineering tools employed during the development of ESAM included the Generalized Singular Value Decomposition (GSVD) algorithm, sequential forward and backward feature selection algorithms, Particle Swarm Optimization algorithm, k-Nearest Neighbor classification, and Gaussian Observation Hidden Markov Modeling (GOHMM).
In this study polysomnogram data was preprocessed for artifact removal and compensation using band-pass filtering and the GSVD algorithm. Optimal features for characterization of polysomnogram data of control subjects and pre-Parkinsonian disease patients were obtained using the sequential forward and backward feature selection algorithms, Particle Swarm Optimization, and k-Nearest Neighbor classification. ESAM output included GOHMMs constructed for both control subjects and pre-Parkinsonian disease patients. Furthermore, performance evaluation techniques were implemented to make conclusions regarding the constructed GOHMM's reflection of the underlying nature of the human sleep cycle.
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Janse, Van Vuuren Michaella. "Human Pose and Action Recognition using Negative Space Analysis." Diss., University of Cape Town, 2004. http://hdl.handle.net/10919/71571.
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This thesis proposes a novel approach to extracting pose information from image sequences. Current state of the art techniques focus exclusively on the image space occupied by the body for pose and action recognition. The method proposed here, however, focuses on the negative spaces: the areas surrounding the individual. This has resulted in the colour-coded negative space approach, an image preprocessing step that circumvents the need for complicated model fitting or template matching methods. The approach can be described as follows: negative spaces surrounding the human silhouette are extracted using horizontal and vertical scanning processes. These negative space areas are more numerous, and undergo more radical changes in shape than the single area occupied by the figure of the person performing an action. The colour-coded negative space representation is formed using the four binary images produced by the scanning processes. Features are then extracted from the colour-coded images. These are based on the percentage of area occupied by distinct coloured regions as well as the bounding box proportions. Pose clusters are identified using feedback from an independent action set. Subsequent images are classified using a simple Euclidean distance measure. An image sequence is thus temporally segmented into its corresponding pose representations. Action recognition simply becomes the detection of a temporally ordered sequence of poses that characterises the action. The method is purely vision-based, utilising monocular images with no need for body markers or special clothing. Two datasets were constructed using several actors performing different poses and actions. Some of these actions included actors waving their arms, sitting down or kicking a leg. These actions were recorded against a monochrome background to simplify the segmentation of the actors from the background. The actions were then recorded on DV cam and digitised into a data base. The silhouette images from these actions were isolated and placed in a frame or bounding box. The next step was to highlight the negative spaces using a directional scanning method. This scanning method colour-codes the negative spaces of each action. What became immediately apparent is that very distinctive colour patterns formed for different actions. To emphasise the action, different colours were allocated to negative spaces surrounding the image. For example, the space between the legs of an actor standing in a T - pose with legs apart would be allocated yellow, while the space below the arms were allocated different shades of green. The space surrounding the head would be different shades of purple. During an action when the actor moves one leg up in a kicking fashion, the yellow colour would increase. Inversely, when the actor closes his legs and puts them together, the yellow colour filling the negative space would decrease substantially. What also became apparent is that these coloured negative spaces are interdependent and that they influence each other during the course of an action. For example, when an actor lifts one of his legs, increasing the yellow-coded negative space, the green space between that leg and the arm decreases. This interrelationship between colours hold true for all poses and actions as presented in this thesis. In terms of pose recognition, it is significant that these colour coded negative spaces and the way the change during an action or a movement are substantial and instantly recognisable. Compare for example, looking at someone lifting an arm as opposed to seeing a vast negative space changing shape. In a controlled research environment, several actors were instructed to perform a number of different actions. After colour coding the negative spaces, it became apparent that every action can be recognised by a unique colour coded pattern. The challenge is to ascribe a numerical presentation, a mathematical quotation, to extract the essence of what is so visually apparent. The essence of pose recognition and it's measurability lies in the relationship between the colours in these negative spaces and how they impact on each other during a pose or an action. The simplest way of measuring this relationship is by calculating the percentage of each colour present during an action. These calculated percentages become the basis of pose and action recognition. By plotting these percentages on a graph confirms that the essence of these different actions and poses can in fact been captured and recognised. Despite variations in these traces caused by time differences, personal appearance and mannerisms, what emerged is a clear recognisable pattern that can be married to an action or different parts of an action. 7 Actors might lift their left leg, some slightly higher than others, some slower than others and these variations in terms of colour percentages would be recorded as a trace, but there would be very specific stages during the action where the traces would correspond, making the action recognisable.In conclusion, using negative space as a tool in human pose and tracking recognition presents an exiting research avenue because it is influenced less by variations such as difference in personal appearance and changes in the angle of observation. This approach is also simplistic and does not rely on complicated models and templates
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Nguyen, Thu Huong. "Employing gamification to support sustainable food consumption : Analysis and Redesign of the Too Good To Go mobile app." Thesis, Umeå universitet, Institutionen för informatik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-176371.
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An estimated 1.3 billion tons of food is lost or wasted every year, adding to the growing problem of CO2 emissions and global warming. Consequently, there is an urgent need to address this issue. However, while a lot of research in Human-Computer-Interaction has been conducted about food waste in private households, there is still a lack of research about people’s food waste at a retail level in restaurants. This paper explores the potential of gamification in the design of apps intended to support more sustainable food consumption behavior. This study is centered on the existing Too Good To Go app and examines current user behavior and perception through quantitative and qualitative methods. Then through employment of design frameworks and iterative prototype cycles the potential to encourage active sustainable food consumption is examined. Findings show that there are many challenges stopping users from actively using the current app more often. Findings also suggest that gamification has the potential to increase users’ motivation to use the app beyond reasons of only saving food. The implications of this paper could present new opportunities for applying gamification to reduce food waste that could inspire researchers and practitioners to explore the theme further.
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Mettin, Uwe. "Applications of the Virtual Holonomic Constraints Approach : Analysis of Human Motor Patterns and Passive Walking Gaits." Licentiate thesis, Umeå : Department of Applied Physics and Electronics, Umeå University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1873.
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Goliath, Jesse Roberto. "A 3D Morphological Analysis of the Ontogenetic Patterning of Human Subchondral Bone Microarchitecture in the Proximal Tibia." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1494273830449469.
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Parker, Dennis. "An Analysis of the Perceptions of African American Churches in their Delivery of Health and Human Services in Southeast DC." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/2846.
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President Bush’s Executive Order 13279 (December 12, 2002) encouraged the government to work with faith-based organizations to provide human services (i.e., Temporary Assistance for Needy Families, employment, homelessness services, and health care) to serve America’s low-income populations. Faith-Based Initiatives, and now President Obama’s Faith and Neighborhood Partnerships Initiative have created the foundation for further partnerships between faith-based organizations and local, state, and federal governments. Limited information exists regarding the overall effectiveness of the programs in encouraging churches, specifically African American churches, to engage in services delivery. This study explores the perceptions of church leaders that influence faith-based organizations, specifically African American churches in the southeast region of Washington, DC, to provide human services. The District of Columbia has eight local wards: southeast Washington encompasses Wards 7 and 8, and has a high concentration of poverty and African Americans. The District of Columbia Department of Human Services (2010) reports that in the year 2009, 97% of Ward 7 residents were African American with 26% residing in poverty; 94% of Ward 8 residents were African American with 35% residing in poverty. The work of early sociologists, W. E. B. Dubois and Franklin Frazier is utilized to frame the theoretical background (Ethnic Identity Model) for this study. Additionally, this study relies on an African American church analysis by Lincoln and Mamiya (1990) to highlight the historical and current role of the African American church. The purpose of this study was to examine the churches of southeast Washington, DC and the level of human services provided between 2000 and 2010, during both the Bush and Obama Administrations, to understand the perceptions of the factors that influenced the level of human services during the same time frame. The study utilized a qualitative design with descriptive statistics to shed light on human service delivery of faith-based organizations in the African American community. A semistructured interview was performed on a convenience sample of 20 pastors/church leaders of churches in southeast Washington, DC. These 20 churches were identified through the District of Columbia’s yellow pages and, additionally, other data sets including advocacy organizations and community groups. This study found that neither President’s Bush’s or Obama Faith Based Initiative significantly influenced the level of provision of human services by African American Churches located in Wards 7 and 8 of southeast Washington DC. Also this study found that the majority of African American churches in wards 7 & 8 in Washington DC are more flexible and able to determine the types of services they provide by the presenting community needs. The study results will inform policymakers about whether, and how, the churches’ role in service delivery changed after the implementation of President Bush’s Faith-Based Initiative. Presidents Bush and Obama view churches and community-based organizations as strong frontline resources to address desperate challenges related to poverty, but little is known about the effectiveness of their initiatives. The results of this analysis will assist churches, community organizations, and policy formulators in providing information that will help policymakers to make more informed decisions about the potential impact of churches for service delivery in the African American community. It will also provide information about barriers to participating as partners with the government.
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Rawstorne, Patrick. "A systematic analysis of the theory of reasoned action, the theory of planned behaviour and the technology acceptance model when applied to the prediction and explanation of information systems use in mandatory usage contexts." Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20060815.154410/index.html.
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Schustek, Philipp. "Probabilistic models for human judgments about uncertainty in intuitive inference tasks." Doctoral thesis, Universitat Pompeu Fabra, 2018. http://hdl.handle.net/10803/586057.
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Updating beliefs to maintain coherence with observational evidence is a cornerstone of rationality. This entails the compliance with probabilistic principles which acknowledge that real-world observations are consistent with several possible interpretations. This work presents two novel experimental paradigms and computational analyses of how human participants quantify uncertainty in perceptual inference tasks. Their behavioral responses feature non-trivial patterns of probabilistic inference such as reliability-based belief updating over hierarchical state representations of the environment. Despite characteristic generalization biases, behavior cannot be explained well by alternative heuristic accounts. These results suggest that uncertainty is an integral part of our inferences and that we indeed have the potential to resort to rational inference mechanisms that adhere to probabilistic principles. Furthermore, they appear consistent with ubiquitous representations of uncertainty posited by framework theories such as Bayesian hierarchical modeling and predictive coding.Un pilar fundamental de la racionalidad es actualizar las creencias con la finalidad de mantener la coherencia con la evidencia observacional. Esto implica cumplir con principios probabilísticos, los cuales reconocen que las observaciones del mundo real son consistentes con varias interpretaciones posibles. Este estudio presenta dos novedosas pruebas experimentales, así como análisis computacionales, de cómo participantes humanos cuantifican la incertidumbre en tareas de inferencia perceptiva. Sus respuestas conductuales muestran patrones no triviales de inferencia probabilística, tales como la actualización de creencias basadas en la confiabilidad sobre las representaciones jerárquicas del estado del entorno. A pesar de los sesgos característicos de generalización, el comportamiento no puede ser correctamente explicado con descripciones heurísticas alternativas. Estos resultados sugieren que la incertidumbre es una parte integral de nuestras inferencias y que efectivamente tenemos el potencial para recurrir a mecanismos de inferencia racional, los cuales adhieren a principios probabilísticos. Además, dichos resultados son compatibles con la idea de que representaciones de incertidumbre internas son ubicuas, lo cual presuponen teorías generales como Bayesian hierarchical modeling y predictive coding.
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Witte, Deborah A. "Women's Leadership in Philanthropy: An Analysis of Six Giving Circles." Antioch University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1352741543.
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Cody, Emily. "Mathematical Modeling of Public Opinion using Traditional and Social Media." ScholarWorks @ UVM, 2016. http://scholarworks.uvm.edu/graddis/620.
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With the growth of the internet, data from text sources has become increasingly available to researchers in the form of online newspapers, journals, and blogs. This data presents a unique opportunity to analyze human opinions and behaviors without soliciting the public explicitly. In this research, I utilize newspaper articles and the social media service Twitter to infer self-reported public opinions and awareness of climate change. Climate change is one of the most important and heavily debated issues of our time, and analyzing large-scale text surrounding this issue reveals insights surrounding self-reported public opinion. First, I inquire about public discourse on both climate change and energy system vulnerability following two large hurricanes. I apply topic modeling techniques to a corpus of articles about each hurricane in order to determine how these topics were reported on in the post event news media. Next, I perform sentiment analysis on a large collection of data from Twitter using a previously developed tool called the "hedonometer". I use this sentiment scoring technique to investigate how the Twitter community reports feeling about climate change. Finally, I generalize the sentiment analysis technique to many other topics of global importance, and compare to more traditional public opinion polling methods. I determine that since traditional public opinion polls have limited reach and high associated costs, text data from Twitter may be the future of public opinion polling.
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Shapiro, Gail Joyce. "Identifying the Factors That Influence Conflict Management Behavior of Human Resource Professionals in the Workplace: An Analysis of the Relationship Between Personality and Conflict Management Behavior." NSUWorks, 2014. http://nsuworks.nova.edu/shss_dcar_etd/26.
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Effective conflict management in the workplace can reduce the negative consequences of conflict. These negative outcomes can include low productivity, health-related stress, increased employee turnover, or litigation. A Human Resource (HR) professional can help mitigate these negative outcomes in the workplace when using effective conflict management behavior with employees. However, there is a void in research pertaining to HR professionals’ use of conflict management behavior.
This quantitative, correlational research study examined whether personality has an impact on assertive or cooperative conflict management behavior of HR professionals in the workplace. Statistical testing found a significant relationship between the harmonious, people-person (a Blue personality in the True Colors personality model) and the assertive conflict management behavior. Another finding of this study sheds light on the need for conflict resolution (CR) education and training in the HR field. The majority of HR professionals in this study said “yes” to wanting and needing training and education in the CR skillset. This skillset includes many of the same specific strategies that are used by mediators (reflective listening, reframing, building rapport, step-by-step problem-solving, etc.). These skills would also enable HR professionals to manage and resolve interpersonal employee conflict before it escalates and leads to negative outcomes.
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Dimara, Evanthia. "Information Visualization for Decision Making : Identifying Biases and Moving Beyond the Visual Analysis Paradigm." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS367/document.
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Certains problèmes ne peuvent être résolus ni par les ordinateurs seuls ni par les humains seuls. La visualisation d'information est une solution commune quand il est nécessaire de raisonner sur de grandes quantités de données. Plus une visualisation est efficace, plus il est possible de résoudre des problèmes complexes. Dans la recherche en visualisation d'information, une visualisation est généralement considérée comme efficace quand elle permet de comprendre les données. Les méthodes d'évaluation cherchent à déterminer si les utilisateurs comprennent les données affichées et sont capables d'effectuer des tâches analytiques comme, par exemple, identifier si deux variables sont corrélées. Cette thèse suggère d'aller au-delà de ce ``paradigme de l'analyse visuelle'' et élargir le champ de recherche à un autre type de tâche: la prise de décision. Les tâches de décision sont essentielles à tous, du directeur d'entreprise qui doit prendre des décisions importantes à l'individu ordinaire qui choisit un plan de carrière ou désire simplement acheter un appareil photo. Néanmoins, les décisions ne se résument pas à la simple compréhension de l'information et sont difficiles à étudier. Elles peuvent impliquer des préférences subjectives, n'ont pas toujours de vérité de terrain, et dépendent souvent de connaissances externes aux données visualisées. Pourtant, les tâches de décision ne font pas partie des taxonomies de tâches en visualisation et n'ont pas été bien définies. De plus, la recherche manque de métriques, de méthodes et de travaux empiriques pour valider l'efficacité des visualisations pour la prise de décision. Cette thèse offre une définition opérationnelle pour une classe particulière de tâches de décision, et présente une analyse systématique qui identifie les visualisations multidimensionnelles compatibles avec ces tâches. Elle présente en outre la première comparaison empirique de techniques de visualisation multidimensionnelle basée sur leur capacité à aider la décision, et esquisse une méthodologie et des métriques pour évaluer la qualité des décisions. Elle explore ensuite le rôle des instructions dans les tâches de décision et des tâches analytiques équivalentes, et identifie des différences de performance entre les deux tâches. De même que les sciences de la vision informent la visualisation d'information sur les limites de la vision humaine, aller au-delà du paradigme de l'analyse visuelle implique de prendre en compte les limites du raisonnement humain. Cette thèse passe en revue la théorie de la décision afin de mieux comprendre comment les humains prennent des décisions, et formule une nouvelle taxonomie de biais cognitifs basée sur la tâche utilisateur. En outre, elle démontre empiriquement que des biais peuvent être présents même quand l'information est bien visualisée, et qu'une décision peut être ``correcte'' mais néanmoins irrationnelle, dans le sens où elle est influencée par des informations non pertinentes. Cette thèse examine finalement comment mitiger les biais. Les méthodes pour améliorer le raisonnement humain reposent souvent sur un entraînement intensif à des principes et à des procédures abstraites, qui se révèlent souvent peu efficaces. Les visualisations offrent une opportunité dans la mesure où ses concepteurs peuvent remodeler l'environnement pour changer la façon dont les utilisateurs assimilent les données. Cette thèse passe en revue la théorie de la décision pour identifier de possibles solutions de conception. De plus, elle démontre empiriquement que supplémenter une visualisation par des interactions qui facilitent des stratégies de décision alternatives peut mener à des décisions plus rationnelles. Via des études empiriques, cette thèse suggère que le paradigme de l'analyse visuelle n'est pas en mesure de relever tous les défis de la prise de décision aidée de la visualisation, mais qu'aller au-delà peut contribuer à faire de la visualisation un puissant outil de prise de décisionThere are problems neither humans nor computers can solve alone. Computer-supported visualizations are a well-known solution when humans need to reason based on a large amount of data. The more effective a visualization, the more complex the problems that can be solved. In information visualization research, to be considered effective, a visualization typically needs to support data comprehension. Evaluation methods focus on whether users indeed understand the displayed data, can gain insights and are able to perform a set of analytic tasks, e.g., to identify if two variables are correlated. This dissertation suggests moving beyond this "visual analysis paradigm" by extending research focus to another type of task: decision making. Decision tasks are essential to everybody, from the manager of a company who needs to routinely make risky decisions to an ordinary person who wants to choose a career life path or simply find a camera to buy. Yet decisions do not merely involve information understanding and are difficult to study. Decision tasks can involve subjective preferences, do not always have a clear ground truth, and they often depend on external knowledge which may not be part of the displayed dataset. Nevertheless, decision tasks are neither part of visualization task taxonomies nor formally defined. Moreover, visualization research lacks metrics, methodologies and empirical works that validate the effectiveness of visualizations in supporting a decision. This dissertation provides an operational definition for a particular class of decision tasks and reports a systematic analysis to investigate the extent to which existing multidimensional visualizations are compatible with such tasks. It further reports on the first empirical comparison of multidimensional visualizations for their ability to support decisions and outlines a methodology and metrics to assess decision accuracy. It further explores the role of instructions in both decision tasks and equivalent analytic tasks, and identifies differences in accuracy between those tasks. Similarly to vision science that informs visualization researchers and practitioners on the limitations of human vision, moving beyond the visual analysis paradigm would mean acknowledging the limitations of human reasoning. This dissertation reviews decision theory to understand how humans should, could and do make decisions and formulates a new taxonomy of cognitive biases based on the user task where such biases occur. It further empirically shows that cognitive biases can be present even when information is well-visualized, and that a decision can be ``correct'' yet irrational, in the sense that people's decisions are influenced by irrelevant information. This dissertation finally examines how biases can be alleviated. Current methods for improving human reasoning often involve extensive training on abstract principles and procedures that often appear ineffective. Yet visualizations have an ace up their sleeve: visualization designers can re-design the environment to alter the way people process the data. This dissertation revisits decision theory to identify possible design solutions. It further empirically demonstrates that enriching a visualization with interactions that facilitate alternative decision strategies can yield more rational decisions. Through empirical studies, this dissertation suggests that the visual analysis paradigm cannot fully address the challenges of visualization-supported decision making, but that moving beyond can contribute to making visualization a powerful decision support tool
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Sra, Sana. "Circadian Variations and Risky Decision Making." Scholarship @ Claremont, 2019. https://scholarship.claremont.edu/scripps_theses/1291.
Full textAbstract:
Over the past decades, decision making under risk has garnered a great amount of attention both in the field of economics and psychology. Although state-dependent variabilities of risk taking are well-documented, little is known about the effects of a person’s preferred time of day, or chronotype, in risky decision making. Under circumstances of circadian mismatch (e.g., when an “early bird” makes decisions in the evening), research suggests that decision making may reflect a greater reliance on heuristics, such as using stereotypes in social judgments. However, the effects of circadian mismatch on heuristics in risky decision making are relatively unexplored. This paper looks into the effects of circadian mismatch on the reflection effect: a behavioral bias in financial decision making, wherein individuals are risk averse when facing potential gains, and risk seeking when facing potential losses. Participants will be randomly assigned to their circadian matched or circadian mismatched conditions and will play a series of financial gambling tasks with real monetary incentives. This study predicts that the reflection effect will be exacerbated in circadian mismatched individuals as compared to matched participants. Exploring such an effect could have real-world implications on decision making under risk by providing critical knowledge about the effects of time of day on our susceptibility to behavioral biases. It could therefore point to the existence of a more optimal time of day to engage in such critical decision making.
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Crooks, Sandra B. "The Sex Stereotype of a Job as a Moderator of Sex Bias in Performance Evaluations." TopSCHOLAR®, 1989. http://digitalcommons.wku.edu/theses/1662.
Full textAbstract:
In accordance with the stereotype-fit model of discrimination (Dipboye, 1985), the results of past research indicate that the extent to which jobs are sex stereotyped dictates whether or not a main effect for rate sex is present in performance evaluations. The purpose of this study was to further examine the relationship between the sex stereotype of the job and the presence of sex bias in evaluation. Two hundred and five undergraduate psychology students viewed one of eight videotapes of a confederate job applicant performing a work sample task and evaluated the observed performance. A 2 x 2 x 2 between subjects factorial design was used to test for the effects of the sex stereotype of the job, sex of rate, and level of rate performance on performance ratings. As performance was found. A significant three-way interaction was found, which implies that when rates perform a job that is stereotyped as sex role incongruent their performance is more likely to be noticed and closely evaluated than when they perform a job that is sex stereotyped as belonging to their sex. Sex bias was found only for the low performing woman on the female job, which indicates she was over-evaluated.
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Cary, Nathan Jess. "Bosnian Immigrants: An Analysis of the Bosnian Community's Influence on the Cultural Landscape of Bowling Green, KY." TopSCHOLAR®, 2013. http://digitalcommons.wku.edu/theses/1235.
Full textAbstract:
Diasporas have been occurring for thousands of years, and today globalization has facilitated the quick rate at which diasporas occur on a global scale. Diasporas entail the mass movement of refugees across international borders, and diasporic peoples today now find themselves journeying across oceans and continents to the safety of host cities in a matter of weeks or days. My research analyzes the effects that Bosnian immigrants have had on the cultural landscape of Bowling Green, Kentucky. When people move, they bring their cultures with them, and this type of cultural diffusion impacts the landscape of the host cities. As geographic research on diasporas is limited, this study aims to fill the gap that exists. Bowling Green, Kentucky, was selected for this analysis due to its large refugee population. Some of Bowling Green’s refugee population is comprised of immigrants from Iraq, Burma, Cambodia, and Sudan. Bosnians comprise the largest population of refugees in the city. In addition to examining immigrant policies and theories, the impacts of the Bosnian diaspora on Bowling Green’s cultural landscape will also be identified. Understanding how those cultures modify landscapes is an important part of diasporic research. The data used for this study were acquired through surveys, census details, telephone directories, interviews, and the extant literature. The hypothesis of this study is that Bosnian immigrants have a stronger visual impact on Bowling Green’s cultural landscape than other immigrant ethnic groups due to their large representation in the city.
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Etienne, Freed. "Urban Growth and Segregation in the Roanoke, Virginia, Metropolis: The Effects of Low-Density Development on Low-Income Populations and Racial Minorities." VCU Scholars Compass, 2006. http://scholarscompass.vcu.edu/etd/1393.
Full textAbstract:
This dissertation examines urban growth patterns in the Roanoke, Virginia, metropolis. It draws on the literature of contemporary human ecology and social area analysis to examine the effects of low-density development on low-income populations and racial minorities. The continuous spread of residential development beyond the boundaries of the central city and older suburbs into more distant, once rural areas is segregating the metropolitan area by race and income. Since the prominence of the so-called "Chicago School" of urban sociology (1913-1940), contemporary urban sociologists have outlined theories and methods to examine how American urban areas have changed and why. This dissertation is not about urban problems and solutions. It is about familiarizing readers with the theories of human ecology and social area analysis and their utility for explaining contemporary urban spatial patterns. If we are to get better and more equitable metropolitan areas, we must find out what really creates our urban areas, physically, economically, and socially. We must reach a deeper understanding of the forces and processes that have shaped them. Finally, we must understand the social consequences to urban life, relative to concentration of poverty and racial minorities in central cities. Toward that end, this study uses the statistical techniques called Social Area Analysis and Factorial Ecology to examine and describe the social-spatial patterns of the Roanoke, Virginia, metropolis, focusing on poverty and race. Specifically, the study uses 1980, 1990 and 2000 census data and the U.S. Geologic Survey of Land Use Cover to compute the factor analysis, construct the Socio-Economic Status (SES) index, rank the metropolis' census tracts based on the SES factors and develop the ecological growth model for the Roanoke metropolis. The analyses of the SES areas reveal that the metropolis' growth model is a combination of Ernest Burgess' concentric zone theory and Harris and Ullman's multiple nuclei model. Ultimately, the significance of this study lies not in the creation of an alternative theory of urban spatial patterns, but as an opportunity to amend more traditional approaches of human ecology so as to include racial segregation and income polarization as influences on metropolitan spatial patterns, and to produce a more integrated and accurate theoretical framework. This dissertation is organized as follows: Chapter 1 provides a brief introduction to the study. In Chapter 2, relevant literature regarding urban spatial patterns and contemporary human ecology is reviewed. Chapter 3 provides a thorough explanation of the research methodology. In Chapter 4, the results of the social area analysis and factor analysis are presented. GIS maps are also used to show the SES areas or multiple spatial patterns in the metropolis, especially the areas of concentrated poverty and race. In Chapter 5, the evolution of the metropolis' growth pattern is reviewed, and a contemporary ecological growth model is developed for the Roanoke metropolis. This model is then compared against the traditional human ecology growth models, including concentric zone theory, sector model theory and multiple nuclei theory. Chapter 6 concludes with a brief discussion of the consequences of the metropolis' growth pattern and the utility of the human ecological perspective for explaining contemporary urban spatial patterns, and suggestions for further research.
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Atesoglu, Ozgur Mustafa. "High Angle Of Attack Maneuvering And Stabilization Control Of Aircraft." Phd thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608575/index.pdf.
Full textAbstract:
In this study, the implementation of modern control techniques, that can be used both for the stable recovery of the aircraft from the undesired high angle of attack flight state (stall) and the agile maneuvering of the aircraft in various air combat or defense missions, are performed. In order to accomplish this task, the thrust vectoring control (TVC) actuation is blended with the conventional
aerodynamic controls. The controller design is based on the nonlinear dynamic inversion (NDI) control methodologies and the stability and robustness analyses are done by using robust performance (RP) analysis techniques. The control
architecture is designed to serve both for the recovery from the undesired stall condition (the stabilization controller) and to perform desired agile maneuvering (the attitude controller). The detailed modeling of the aircraft dynamics, aerodynamics, engines and thrust vectoring paddles, as well as the flight
environment of the aircraft and the on-board sensors is performed. Within the control loop the human pilot model is included and the design of a fly-by-wire controller is also investigated. The performance of the designed stabilization and attitude controllers are simulated using the custom built 6 DoF aircraft flight simulation tool. As for the stabilization controller, a forced deep-stall flight condition is generated and the aircraft is recovered to stable and pilot controllable
flight regimes from that undesired flight state. The performance of the attitude controller is investigated under various high angle of attack agile maneuvering conditions. Finally, the performances of the proposed controller schemes are discussed and the conclusions are made.
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Thompson, Garth John. "Neural basis and behavioral effects of dynamic resting state functional magnetic resonance imaging as defined by sliding window correlation and quasi-periodic patterns." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/49083.
Full textAbstract:
While task-based functional magnetic resonance imaging (fMRI) has helped us understand the functional role of many regions in the human brain, many diseases and complex behaviors defy explanation. Alternatively, if no task is performed, the fMRI signal between distant, anatomically connected, brain regions is similar over time. These correlations in “resting state” fMRI have been strongly linked to behavior and disease. Previous work primarily calculated correlation in entire fMRI runs of six minutes or more, making understanding the neural underpinnings of these fluctuations difficult. Recently, coordinated dynamic activity on shorter time scales has been observed in resting state fMRI: correlation calculated in comparatively short sliding windows and quasi-periodic (periodic but not constantly active) spatiotemporal patterns. However, little relevance to behavior or underlying neural activity has been demonstrated. This dissertation addresses this problem, first by using 12.3 second windows to demonstrate a behavior-fMRI relationship previously only observed in entire fMRI runs. Second, simultaneous recording of fMRI and electrical signals from the brains of anesthetized rats is used to demonstrate that both types of dynamic activity have strong correlates in electrophysiology. Very slow neural signals correspond to the quasi-periodic patterns, supporting the idea that low-frequency activity organizes large scale information transfer in the brain. This work both validates the use of dynamic analysis of resting state fMRI, and provides a starting point for the investigation of the systemic basis of many neuropsychiatric diseases.
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Loeches, de la fuente Hugo. "Etude multi-niveaux du contrôle d'un périphérique d'interaction de type joystick." Thesis, Aix-Marseille, 2014. http://www.theses.fr/2014AIXM4060/document.
Full textAbstract:
Ce travail doctoral, centré sur l'étude des processus de contrôle d'un périphérique d'interaction de type joystick, poursuivait un double objectif. D'une part, ce travail visait à comprendre comment l'utilisateur d'un périphérique adapte son comportement pour faire face à l'ensemble des contraintes qu'il rencontre. En particulier, nous avons manipulé les contraintes relatives à la tâche à réaliser (l'indice de difficulté et le comportement de l'objet déplacé) et les propriétés physiques du périphérique. D'autre part, d'un point de vue appliqué, comprendre comment le comportement du sujet émerge d'un ensemble de contraintes nous renseigne sur la façon dont un contrôle plus intuitif des périphériques, et par la même une meilleure performance, peuvent être favorisés. Pour cela, un cadre d'analyse qui permet de manipuler l'ensemble des contraintes dans des conditions de contrôle qui se rapproche de situation réelle d'interaction (chirurgie vidéoassistée, aéronautique ou contrôle industriel) a été proposé. L'analyse comportementale à deux niveaux (niveau local et niveau global) qui est utilisée nécessitait l'intégration des concepts, moyens et méthodes des sciences comportementales (contrôle moteur) d'une part, et de la biomécanique d'autre part. Au regard des résultats obtenus, l'étude des processus de contrôle d'un périphérique d'interaction constitue une voie d'entrée sur une compréhension plus générale du comportement perceptivo-moteurThis doctoral work focused on the study of the process involved in the control of a joystick-type device of interaction and had a double objective. First, this work was aimed to understand how the user of a device adapts its behavior to face a set of encountered constraints. In particular, the constraints inherent to the task (the index of difficulty and behavior of the object displaced) and the physical properties of the device (joystick or rotorcraft stick) have been manipulated. Second, understanding how the subject's behavior emerges from the influence of this set of constraints informed us about how we can access to a more intuitive control of the device and a better performance level. To achieve this goal, an analysis framework allowing the manipulation of all the constraints in conditions that are close to real situations of control (e.g. video-assisted surgery, aeronautics and industrial control) has been proposed. The behavioral analysis at two levels (local level and global level) that is used required the integration of concepts, means and methods from behavioral sciences (motor control) and from biomechanics. Taking all the results together, the study of the control process of a device of interaction allows a more general understanding of the perceptual-motor behavior