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Dissertations / Theses on the topic 'Time needed for making a decision'
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Bařina, Jakub. "Studie doby potřebné pro rozhled a rozhodnutí při dání přednosti v jízdě." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-233161.
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This thesis deals with detection and analysis of a time needed for getting an all-round view before entering other vehicle's corridor during different conditions and speed. In the theoretical part a brief research is made concerning the subject of causes of accidents, aspects of human perception and driver's outlook. The analytical part derives from video recordings of on-road trials. The results was processed and the obtained data evaluated in order to find out the time needed for getting an all-round and making a decision while situated in the intersection. Above that, the data served as a determination of safety during intersection passing and quality of estimates of speed and distance of incoming vehicles. The conclusion of the analytical part is dedicated to participants mutual comparison and analysis of particular situations that occurred during the trials.
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Johansson, Ingela. "When time matters : Patients’ and spouses’ experiences of suspected acute myocardial infarction in the pre-hospital phase." Doctoral thesis, Linköping : Linköping University, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-6748.
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DeDonno, Michael Anthony. "Time Pressure and Decision Making." Cleveland, Ohio : Case Western Reserve University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1232579823.
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Thesis (Ph.D.)--Case Western Reserve University, 2009Title from PDF (viewed on 26 May 2009) Includes abstract Department of Psychology Includes bibliographical references and appendices Available online via the OhioLINK ETD Center
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Zhang, Xuemei. "Simulation-optimization in real-time decision making." Ohio : Ohio University, 1997. http://www.ohiolink.edu/etd/view.cgi?ohiou1184619898.
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Joslyn, Susan Lyn. "Individual differences in time pressured decision making /." Thesis, Connect to this title online; UW restricted, 1995. http://hdl.handle.net/1773/9086.
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Lowenthal, David K. 1968. "Fine-grain parallelism and run-time decision-making." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/290596.
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While parallel programming is needed to solve large-scale scientific applications, it is more difficult than sequential programming. Programming parallel machines requires specifying what can execute concurrently, when and how processes communicate, and how data is placed in the memories of the processors. The challenge is to address these issues simply, portably, and efficiently. This dissertation presents the Filaments package, which provides fine-grain parallelism and a shared-memory programming model and makes extensive use of run-time decisions. Fine-grain parallelism and a shared-memory programming model simplify parallel programs by allowing the programmer or compiler to concentrate on the application and not the architecture of the target machine. This dissertation shows that this simpler programming model can be implemented with low overhead. Determining the best data placement at run time frees the programmer or compiler from this task and allows the placement to adapt to the particular application. The dissertation discusses the implementation of Adapt, a run-time data placement system, and compare its performance to static placements on three classes of applications. The performance of programs using Adapt is better than those using static data placements on adaptive applications such as particle simulation.
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Liu, Yuanyuan. "Individual decision making under ambiguity and over time." Thesis, Cergy-Pontoise, Ecole supérieure des sciences économiques et commerciales, 2015. http://www.theses.fr/2015ESEC0006.
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Cette thèse traite du problème de la façon de prendre des décisions impliquant à la fois la temporisation et l'information ambiguë. Cette thèse se compose de trois chapitres. Le chapitre 1 passe en revue une série d'études sur l'influence de l'ambiguïté et de la temporisation sur la prise de décision individuelle, et soulève deux questions de recherche de la thèse actuelle: 1) Est-ce que les préférences d'ambiguïté des décideurs sont différentes pour les perspectives résolues dans le présent et l'avenir? et 2) Est-ce que les préférences temporelles de décideurs diffèrent sous les récompenses ambiguës et non ambiguës? Les chapitres 2 et 3 sont deux essais indépendants qui traitent de ces deux questions, respectivement. Le premier essai examine les préférences d'ambiguïté sous la résolution actuelle et retardée à travers les probabilités basses et hautes. Les résultats des trois études montrent un effet d'interaction entre le temps de résolution et le niveau de probabilité. Sous résolution immédiate, nous constatons que les individus présentent l'aversion d'ambiguïté à des probabilités élevées et ambiguïté-recherche faible, ou l'indifférence à faibles probabilités, cohérentes avec la littérature antérieure. Toutefois, la résolution future régresse aversion et de comportement de recherché à la neutralité. S’appuyant sur la théorie du niveau de construal et la théorie de double-processus, nous attribuons cet effet d'interaction à la différence de styles de traitement pour les perspectives présentes et futures. Le deuxième essai démontre l'impact de récompenses futures ambigus sur les préférences intertemporelles. Six études montrent que, malgré le fait que les récompenses ambiguës et retardées sont généralement detestés séparément, ensemble, elles produisent un effet positif. C'est-à-dire que, les récompenses ambiguës futures sont plus susceptibles d'être préférés que les récompenses précises (avec les valeurs attendues égales) dans la prise de decision intertemporelle. Nous proposons l'hypothèse de l’eclipse (overshadowing) pour expliquer cet effet et excluons trois autres possibilités. Enfin, nous établissons des conditions aux limites en examinant systématiquement si l'effet persiste à différents niveaux d'ambiguïté et de points de tempsThis dissertation addresses the issue of how to make decisions involving both time delay and ambiguous information. This dissertation is arranged into three chapters. Chapter 1 reviews a set of studies on the influence of ambiguity and time delay on individual decision making and raises two relevant research questions: (1) Are decision makers' ambiguity preferences different for prospects resolved in the present and the future?; and (2) Do decision makers' time preferences differ under ambiguous and unambiguous payoffs? Chapter 2 and 3 are two independent essays, each addressing one of the above questions. The first essay examines ambiguity preferences under present and delayed resolutions across low and high probabilities. Results of three studies show an interaction effect between resolution time and probability level. Under the immediate resolution, we find that individuals exhibit ambiguity aversion at high probabilities and weak ambiguity seeking or indifference at low probabilities, consistent with prior literature. However, delayed resolution regresses aversion and seeking behaviors to neutrality. Drawing on the construal level theory and the dual-process theory, we attribute this interaction effect to the difference in processing styles for present and future prospects. The second essay demonstrates the impact of ambiguous future payoffs on intertemporal preferences. Six studies show that, despite the fact that ambiguous and delayed payoffs are generally disliked separately, together they produce a positive effect. That is, ambiguous future payoffs are more likely to be preferred than precise payoffs (with equal expected values) in intertemporal decision-making. We propose the overshadowing hypothesis to explain this effect and rule out three other possibilities. Finally, we establish boundary conditions by systematically examining whether the effect persists at various ambiguity levels and time points
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Dickter, David N. "The role of time orientation in decision making under time pressure." Connect to resource, 1997. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1250528229.
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Dickter, David Nathan. "The role of time orientation in decision-making under time pressure /." The Ohio State University, 1997. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487946103565876.
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O'Dell, Nicholas West. "Decision-Making Ability Beliefs." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461084976.
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McCleary, Nicola. "Relationships between perceived decision difficulty, decision time, and decision appropriateness in General Practitioners' clinical decision-making." Thesis, University of Aberdeen, 2015. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=229003.
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The aim of this project was to use patient scenarios (clinical/case vignettes) to explore three aspects of General Practitioners' (GPs') clinical decision-making: how difficult decisions are perceived to be, the time taken to make decisions, and the appropriateness of decisions relative to evidence-based clinical guideline recommendations. A systematic review synthesised the results of published scenario studies. A secondary analysis of scenario studies which investigated antibiotic prescribing for upper respiratory tract infection (URTI) and x-ray referral for low back pain was performed. Relationships between the three aspects of decision-making were investigated, and scenario and GP characteristics associated with these aspects were identified. An online scenario study further refined these relationships for two specific URTI types: sore throat and otitis media. Cognitive processes involved in clinical decision-making were investigated in a Think-Aloud interview study, where GPs verbalised their thoughts while making prescribing decisions for URTI scenarios. There was some evidence that inappropriate antibiotic prescribing for URTI was associated with greater decision difficulty and longer decision time. Decisions made using a more effortful cognitive process may therefore be less likely to be appropriate. Illness durations of four or more days and, in otitis media, unilateral ear examination findings were related to inappropriate prescribing. Based on these results, suggestions have been made for informing the design of interventions to support GPs in making appropriate decisions. A secondary aim was to provide an overview of the methodology and reporting of scenario studies. The systematic review indicated a lack of consistency in methodologies, while reporting is often inadequate. Formats less similar to real consultations (e.g. written scenarios) are commonly used: the results of studies using these formats may be less likely to reflect real practice decision-making than studies using more realistic formats (e.g. videos). Based on these findings, methodological recommendations for scenario studies have been developed.
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Varlamova, Viktoriya. "The Relationship between Time Management and Decision-Making Processes." Thesis, University of Canterbury. Psychology, 2008. http://hdl.handle.net/10092/2283.
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During the last two decades, time management and decision-making have become well-established topics in modern working life. However, little research attention has been given to the link between the two. The purpose of this study was to investigate the relationship between time management factors and decision-making processes. This research was specifically focused on identifying which aspects of decision-making processes are related to time management factors. It was predicted that decision-making processes will be more efficient\effective when employees have time management related competencies and work in an environment that supports time management. A research model was built based on previous research in this field and tested using bivariate correlations, t-tests, and multiple-regression analyses. Five organizations in New Zealand and three in Russia participated in the research, contributing a total of 164 employees. Results indicated, as predicted, that the effectiveness of decision-making processes partially depends on time management factors. Implications of the findings are discussed and future directions for research on the relationship between time management factors and decision-making processes are suggested.
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Mallory, Geoffrey Robson. "The speed of strategic decision making : an empirical investigation of the determinants of decision making process time in U.K. organizations." Thesis, University of Bradford, 1987. http://hdl.handle.net/10454/5029.
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Mallory, Geoffrey Robson. "The speed of strategic decision making. An empirical investigation of the determinants of decision making process time in U. K. organizations." Thesis, University of Bradford, 1987. http://hdl.handle.net/10454/5029.
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Tölch, Ulf. "Bat time stories decision-making in spatio-temporally predictable environments /." [S.l.] : [s.n.], 2006. http://edoc.ub.uni-muenchen.de/archive/00005130.
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Waters, Marianne Elizabeth. "Junior high girls and free time physical activity decision making." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq21145.pdf.
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Raiend, August, and Erik Svedberg. "Decision making and company performance - During a turbulent time period." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-389357.
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This thesis examines short- and long-term decision making, CEO-remuneration and its effects on company performance measured as return on assets during a time-period containing market up- and downturns with regards to company resilience. We examined this in a Swedish context by looking at listed companies on the Stockholm stock exchange during the period 2004 to 2014. The research was conducted using a multiple regression analysis to capture relationships between the dependent variable, the independent- and control variables over the observed time-period. We measure short-term action as decreases in R&D-spending, CapEx and number of employees, that can create short-term profits, whilst long-term actions is the opposite which are expected to generate a high level of company performance in the long run. In our observed population we find that companies who balance short- and long-term actions have a higher company performance, thus deviating from previous research. We also find that an increase in CEO-remuneration will not yield higher company performance when regarding firm size. The results of the study indicate that the companies in our sample have a goal alignment between the CEO and owners, although it shows tendencies of risk adversity in decision making. We find there is a more complex relationship between decision making, the CEO, and company performance than first expected.
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Ling, Lee S. B. Massachusetts Institute of Technology. "Developing approximation architectures for decision-making in real-time systems." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36732.
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Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includes bibliographical references (p. 39).
This thesis studies the design of basis functions in approximate linear programming (ALP) as a decision-making tool. A case study on a robotic control problem shows that feature-based basis functions are very effective because they are able to capture the characteristics and cost structure of the problem. State-space partitioning, polynomials and other non-linear combinations of state parameters are also used in the ALP. However, design of these basis functions requires more trial-and-error. Simulation results show that control policy generated by the approximate linear programming algorithm matches and sometimes surpasses that of heuristics. Moreover, optimal policies are found well before value function estimates reach optimality. The ALP scales well with problem size and the number of basis functions required to find the optimal policy does not increase significantly in larger scale systems. The promising results shed light on the possibility of applying approximate linear programming to other large-scale problems that are computationally intractable using traditional dynamic programming methods.
by Lee Ling.
S.B.
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Sahu, Reetik Kumar. "Multi-agent real-time decision making in water resources systems." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120636.
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Thesis: Ph. D. in Computational Science and Engineering, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 77-83).
Optimal utilization of natural resources such as water, wind and land over extended periods of time requires a carefully designed framework coupling decision making and a mathematical abstraction of the physical system. On one hand, the choice of the decision-strategy can set limits/bounds on the maximum benefit that can be extracted from the physical system. On the other hand the mathematical formulation of the physical system determines the limitations of such strategies when applied to real physical systems. The nuances of decision making and abstraction of the physical system are illustrated with two classical water resource problems: optimal hydropower reservoir operation and competition for a common pool groundwater source. Reservoir operation is modeled as a single agent stochastic optimal control problem where the operator (agent) negotiates a firm power contract before operations begin and adjusts the reservoir release during operations. A probabilistic analysis shows that predictive decision strategies such as stochastic dynamic programming and model predictive control give better performance than standard deterministic operating rules. Groundwater competition is modeled as a multi-agent dynamic game where each farmer (agent) aims to maximize his/her personal benefit. The game analysis shows that uncooperative competition for the resource reduces economic efficiency somewhat with respect to the cooperative socially optimum behavior. However, the efficiency reduction is relatively small compared to what might be expected from incorrect assumptions about uncertain factors such as future energy and crop prices. Spatially lumped and distributed models of the groundwater system give similar pictures of the inefficiencies that result from uncooperative behavior. The spatially distributed model also reveals the important roles of the geometry and density of the pumping well network. Overall, the game analysis provides useful insight about the factors that make cooperative groundwater management beneficial in particular situations.
by Reetik Kumar Sahu.
Ph. D. in Computational Science and Engineering
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Sfar, Hela. "Real time intelligent decision making from heterogeneous and imperfect data." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLL013/document.
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De nos jours, l'informatique omniprésente fait face à un progrès croissant. Ce paradigme est caractérisé par de multiples capteurs intégrés dans des objets du monde physique. Le développement d'applications personnelles utilisant les données fournies par ces capteurs a conduit à la création d'environnements intelligents, conçus comme un framework de superposition avancé qui aide de manière proactive les individus dans leur vie quotidienne. Une application d’environnement intelligent collecte les données de capteurs deployés d'une façon en continu , traite ces données et les analyse avant de prendre des décisions pour exécuter des actions sur l’environnement physique. Le traitement de données en ligne consiste principalement en une segmentation des données pour les diviser en fragments. Généralement, dans la littérature, la taille des fragments est fixe. Cependant, une telle vision statique entraîne généralement des problèmes de résultats imprécis. Par conséquent, la segmentation dynamique utilisant des tailles variables de fenêtres d’observation est une question ouverte. La phase d'analyse prend en entrée un segment de données de capteurs et extrait des connaissances au moyen de processus de raisonnement ou d'extraction. La compréhension des activités quotidiennes des utilisateurs et la prévention des situations anormales sont une préoccupation croissante dans la littérature, mais la résolution de ces problèmes à l'aide de données de petite taille et imparfaites reste un problème clé. En effet, les données fournies par les capteurs sont souvent imprécises, inexactes, obsolètes, contradictoires ou tout simplement manquantes. Par conséquent, l'incertitude liée à la gestion est devenue un aspect important. De plus, il n'est pas toujours possible et trop intrusif de surveiller l'utilisateur pour obtenir une grande quantité de données sur sa routine de vie. Les gens ne sont pas souvent ouverts pour être surveillés pendant une longue période. Évidemment, lorsque les données acquises sur l'utilisateur sont suffisantes, la plupart des méthodes existantes peuvent fournir une reconnaissance précise, mais les performances baissent fortement avec de petits ensembles de données. Dans cette thèse, nous avons principalement exploré la fertilisation croisée d'approches d'apprentissage statistique et symbolique et les contributions sont triples: (i) DataSeg, un algorithme qui tire parti à la fois de l'apprentissage non supervisé et de la représentation ontologique pour la segmentation des données. Cette combinaison choisit de manière dynamique la taille de segment pour plusieurs applications, contrairement à la plupart des méthodes existantes. De plus, contrairement aux approches de la littérature, Dataseg peut être adapté à toutes les fonctionnalités de l’application; (ii) AGACY Monitoring, un modèle hybride de reconnaissance d'activité et de gestion des incertitudes qui utilise un apprentissage supervisé, une inférence de logique possibiliste et une ontologie permettant d'extraire des connaissances utiles de petits ensembles de données; (iii) CARMA, une méthode basée sur les réseaux de Markov et les règles d'association causale pour détecter les causes d'anomalie dans un environnement intelligent afin d'éviter leur apparition. En extrayant automatiquement les règles logiques concernant les causes d'anomalies et en les intégrant dans les règles MLN, nous parvenons à une identification plus précise de la situation, même avec des observations partielles. Chacune de nos contributions a été prototypée, testée et validée à l'aide de données obtenues à partir de scénarios réels réalisésNowadays, pervasive computing is facing an increasing advancement. This paradigm is characterized by multiple sensors highly integrated in objects of the physical world.The development of personal applications using data provided by these sensors has prompted the creation of smart environments, which are designed as an overlay advanced framework that proactively, but sensibly, assist individuals in their every day lives. A smart environment application gathers streaming data from the deployed sensors, processes and analyzes the collected data before making decisions and executing actions on the physical environment. Online data processing consists mainly in data segmentation to divide data into fragments. Generally, in the literature, the fragment size is fixed. However, such static vision usually brings issues of imprecise outputs. Hence, dynamic segmentation using variable sizes of observation windows is an open issue. The analysis phase takes as input a segment of sensor data and extract knowledge by means of reasoning or mining processes. In particular, understanding user daily activities and preventing anomalous situations are a growing concern in the literature but addressing these problems with small and imperfect data is still a key issue. Indeed, data provided by sensors is often imprecise, inaccurate, outdated, in contradiction, or simply missing. Hence, handling uncertainty became an important aspect. Moreover, monitoring the user to obtain a large amount of data about his/her life routine is not always possible and too intrusive. People are not often open to be monitored for a long period of time. Obviously, when the acquired data about the user are sufficient, most existing methods can provide precise recognition but the performances decline sharply with small datasets.In this thesis, we mainly explored cross-fertilization of statistic and symbolic learning approaches and the contributions are threefold: (i) DataSeg, an algorithm that takes advantage of both unsupervised learning and ontology representation for data segmentation. This combination chooses dynamically the segment size for several applications unlike most of existing methods. Moreover, unlike the literature approaches, Dataseg is able to be adapted to any application features; (ii) AGACY Monitoring, a hybrid model for activity recognition and uncertainty handling which uses supervised learning, possibilistic logic inference, and an ontology to extract meaningful knowledge from small datasets; (iii) CARMA, a method based on Markov Logic Networks (MLN) and causal association rules to detect anomaly causes in a smart environment so as to prevent their occurrence. By automatically extracting logic rules about anomalies causes and integrating them in the MLN rules, we reach a more accurate situation identification even with partial observations. Each of our contributions was prototyped, tested and validated through data obtained from real scenarios that are realized
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Ganapathy, Subhashini. "HUMAN-CENTERED TIME-PRESSURED DECISION MAKING IN DYNAMIC COMPLEX SYSTEMS." Wright State University / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=wright1152229142.
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Pan, Jinrui. "Time and risk preferences : theoretical models for individual decision making." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/time-and-risk-preferences-theoretical-models-for-individual-decision-making(7cab3f50-870f-4c91-931b-5b98b96ee81e).html.
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Thesis submitted by Jinrui Pan for the Degree of Doctor of Philosophy in the University of Manchester, and entitled, “Time and Risk Preferences: Theoretical Models and Applications.” Date of submission 2014.This thesis makes contributions to two important areas of behavioural economics, namely individual decision making over time and under risk. Following the Introduction, Chapter 2 presents a new discounting function for analysing intertemporal choice. Liminal discounting, the model developed here, generalises exponential discounting in a parsimonious way. It allows for well-known departures, whilst maintaining its elegance and tractability. It also can be seen as an extension of quasi-hyperbolic discounting to continuous time. A liminal discounter has a constant rate of time preference before and after some threshold time; the liminal point. A preference foundation is provided, showing that the liminal point is derived endogenously from behaviour. Chapter 3 proposes an axiomatic model featuring a differential treatment of attitudes towards risk and time. Such distinction has been strongly suggested by experimental research when studying intertemporal choice, since the future is inherently risky. In the proposed model, non-linear probability distortions are incorporated into a dynamic model with discounted utility. Time is captured by a general discounting function independent of probabilities and outcomes. Utility of outcomes is captured by standard vNM utility independent of time. A two-parameter probability weighting function captures intertemporal probabilistic risk attitudes, with one parameter being constant over time, the other being time-dependent. An index of optimism is derived that depends on both parameters, which allows to model the observed high risk tolerance for delayed lotteries. Further, a preference foundation is provided. Interestingly, the model allows behaviour to be consistent with discounted expected utility, when risk is sufficiently distant from the present.
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Iezzi, Jana. "Multi-criteria decision making in outpatient scheduling." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001817.
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Repaka, Venkata Ranga Sri Rama Sunny. "Optimal decision making for spare part management with time varying demands." Thesis, Wichita State University, 2007. http://hdl.handle.net/10057/1553.
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Controlling spare parts inventory of a product is a major effort to many companies. The problem becomes more challenging when the installed base of the product changes over time. In order to cope with the situation, the inventory value needs to be adjusted according to the resulting non-stationary maintenance demand. This problem is usually encountered when a manufacturer starts selling a new product and agrees to provide spare parts for maintenance. In this research, a special case involving a new non-repairable product with a single spare pool is considered. It is assumed that the new sales follow some popular stochastic processes, and the product.s failure time follows the Weibull distribution or Exponential distribution. The mathematical model for the resulting maintenance demand is formulated and calculated through simulation. Based on the maintenance demand, a dynamic (Q, r) - (lotsize/reorder-point) restocking policy is formulated and solved using a multi-resolution approach. Finally, numerical examples with the objective of minimizing the inventory cost under a service level constraint are provided to demonstrate the proposed methodology in practical use.Thesis (M.S)--Wichita State University, College of Engineering, Dept. of Industrial and Manufacturing Engineering
"December 2007."
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Lieuw, Iris. "Time Frequency Analysis of Neural Oscillations in Multi-Attribute Decision-Making." Scholarship @ Claremont, 2015. http://scholarship.claremont.edu/scripps_theses/556.
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In our daily lives, we often make decisions that require the use of self-control, weighing trade-offs between various attributes: for example, selecting a food based on its health rather than its taste. Previous research suggests that re-weighting attributes may rely on selective attention, associated with decreased neural oscillations over posterior brain regions in the alpha (8-12 Hz) frequency range. Here, we utilized the high temporal resolution and whole-brain coverage of electroencephalography (EEG) to test this hypothesis in data collected from hungry human subjects exercising dietary self-control. Prior analysis of this data has found time-locked neural activity associated with each food’s perceived taste and health properties from approximately 400 to 650 ms after stimulus onset (Harris et al., 2013). We conducted time-frequency analyses to examine the role of alpha-band oscillations in this attribute weighting. Specifically, we predicted that there would be decreased alpha power in posterior electrodes beginning approximately 400 ms after stimulus onset for the presentation of healthy food relative to unhealthy food, reflecting shifts in selective attention. Consistent with this hypothesis, we found a significant decrease in alpha power for presentations of healthy relative to unhealthy foods. As predicted, this effect was most pronounced at posterior occipital and parietal electrodes and was significant from approximately 450 to 700 ms post-stimulus onset. Additionally, we found significant alpha-band decreases in right temporal electrodes during these times. These results extend previous attention research to multi-attribute choice, suggesting that the re-weighting of attributes can be measured neuro-computationally.
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Repaka, Venkata Ranga Sri Rama Sunny Liao Haitao. "Optimal decision making for spare part management with time varying demands /." Thesis, A link to full text of this thesis in SOAR, 2007. http://hdl.handle.net/10057/1553.
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Brooks, Scott M. "Decision making under time pressure : examination within a job interview context /." The Ohio State University, 1992. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487775034177871.
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Smith, Charles Adams Plater. "Decision-making under time pressure: The effects of time pressure on information search strategy, decision strategy, consistency, and outcome quality." Diss., The University of Arizona, 1990. http://hdl.handle.net/10150/185066.
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The design of information systems to support crisis management can be improved when more is known about the ways in which people process information under time pressure. A laboratory experiment was conducted to investigate the effects of time pressure on decision behavior. The decision task required the subjects to use a computerized information display to search for information under time pressure. When the time limit for searching expired, the subjects were required to make a decision. The decision task type, choice or judgment, and three separate information display formats were also manipulated. A total of 144 student subjects were randomly assigned to the resulting six combinations of task/display treatments. Each subject performed the decision task at three levels of time pressure. Dependent measures included information search strategy, decision strategy, decision consistency, and decision quality. Analyses of the results suggest that time pressure had no effect on the information search strategy or the decision strategy. For five of the six task/display groups, time pressure was inversely related to consistency and quality. One group exhibited an inverted U relationship between time pressure and consistency. Display format had an effect on information search strategy. Task type had an effect on both consistency and quality; the performances of the choice groups were superior to those of the judgment groups. The implications of these findings with respect to the design of information systems is discussed.
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Lanier, Drew Noble. "Of Time and Judicial Behavior : Time Series Analyses of United States Supreme Court Agenda Setting and Decision-making, 1888-1989." Thesis, University of North Texas, 1997. https://digital.library.unt.edu/ark:/67531/metadc277657/.
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Boya, Manhal. "Visual information acquisition, decision-making, pacing and performance during time trial cycling." Thesis, University of Essex, 2018. http://repository.essex.ac.uk/21415/.
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Pacing research attempts to explain how effort varies during athletic events to produce the best performance without premature fatigue. Little is understood about the cognitive processes leading to pacing decisions and behaviour. The aim of this thesis was to measure cyclists’ visual behaviour, using eye-trackers, to determine information acquisition patterns during cycling time trials (TT). The first study found experts looked at primary information longer than novices during 10 mile TTs, with speed being the primary information source for experts, and distance was the primary information source for novices. A follow-up study confirmed that speed was the preferred source of information for experienced cyclists, and that pacing and performance decrements were observed when removing preferred information sources. In a third experiment, it was found that limiting the availability of preferred information to 15 sec every 10% and 20% of a 5 km TT, had no effect on performance compared to continuously available preferred information. In a final study an attempt was made to measure cyclists’ visual behaviour during a road time trial because the laboratory studies are limited by ignoring balance, navigation and collision avoidance demands on visual attention. It was found that cyclists were looking at the road for an average of above 50% of over all time. Cyclists spent approximately 20% of the overall time seeking performance information, in which 7/10 chose speed as the primary information. It is concluded that difference in information acquisition processes exist between novice and expert cyclists with experts affording more attention to speed and novice to distance. Furthermore, performance remains relatively unaffected by limiting the availability of preferred feedback information, which may be important so that during road-based TT’s, the capacity to attend to balance, navigation and collision-avoidance cues exist.
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Tariverdi, Mersedeh. "Time-Critical Decision Making in Rescue Resource Deployment and Health Care Systems." Thesis, George Mason University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10682095.
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Continuing population growth and increased urbanization within disaster-prone areas have led to greater numbers of mass casualties and economic losses caused by natural or human-made disasters. Efficient decision-making processes are crucial in all phases of a disaster life cycle, from mitigation and preparedness to response and recovery. The overarching goal of this dissertation is to contribute to region-wide disaster operation management capabilities by creating a set of tools to facilitate fast, life-saving decision-making. The dissertation begins with initial first responders’ assignments to affected structures and spans health care and infrastructure preparation and response. In mass casualty incident (MCI) circumstances in particular, situations are complicated, networks are often large, and conditions are transient and time-dependent. Thus, models developed in this thesis evaluate and update decisions based on available information at each point in time to the system.
The functioning of various response networks, whether in the disaster scene or at the health care facilities, is conceptualized mathematically. Each model can be viewed as a type of queueing network in which MCI victims are customers and responders or health care facilities are servers. Each queueing network is employed to: (1) test developed protocols, acting as queueing system operational policies to support disaster response, (2) assess tactics developed otherwise, or (3) optimize regional resiliency of the health care system given its dependence on set of interdependent supporting lifelines in disasters through preparedness and response actions. Resource-constrained patient flow models of hospitals are presented for routine and emergency operations for the purpose of the study. Using queueing network conceptualizations, discrete event simulation and simulation-based optimization techniques are developed to propose and evaluate protocols that guide responses and for assessing performance and resilience of these systems.
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Adams, Kevin Page. "An Approach to Real Time Adaptive Decision Making in Dynamic Distributed Systems." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/25943.
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Efficient operation of a dynamic system requires (near) optimal real-time control decisions. Those decisions depend on a set of control parameters that change over time. Very often, the optimal decision can be made only with the knowledge of future values of control parameters. As a consequence, the decision process is heuristic in nature. The optimal decision can be determined only after the fact, once the uncertainty is removed.
For some types of dynamic systems, the heuristic approach can be very effective. The basic premise is that the future values of control parameters can be predicted with sufficient accuracy. We can either predict those value based on a good model of the system or based on historical data. In many cases, the good model is not available. In that case, prediction using historical data is the only option. It is necessary to detect similarities with the current situation and extrapolate future values. In other words, we need to (quickly) identify patterns in historical data that match the current data pattern. The low sensitivity of the optimal solution is critical. Small variations in data patterns should affect minimally the optimal solution. Resource allocation problems and other â discrete decision systemsâ are good examples of such systems.
The main contribution of this work is a novel heuristic methodology that uses neural networks for classifying, learning and detecting changing patterns, as well as making (near) real-time decisions. We improve on existing approaches by providing a real-time adaptive approach that takes into account changes in system behavior with minimal operational delay without the need for an accurate model. The methodology is validated by extensive simulation and practical measurements. Two metrics are proposed to quantify the quality of control decisions as well as a comparison to the optimal solution.Ph. D.
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Besharat, Ali. "Essays on Mental Accounting and Consumers' Decision Making." Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/3977.
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This dissertation is structured in the form of two empirical essays, each investigating one type of irrational decision caused by mental accounting. The first essay, titled "Managing the Cost of Multiple Debt Accounts: A Behavioral Perspective", explores why many people pay off credit cards' with the lowest rate first when rationally speaking they should repay the debt with the highest rate most quickly. This essay suggests that irrationality emerges when people seek to close `mental accounts' associated with their credit cards and reduce the total number of outstanding loans rather than decrease the amount of total debt among all credit cards. Consumers want to be debt free. If they can get rid of debt, on even one credit card, they feel a sense of accomplishment which psychologically helps them manage remainder of their debt better. The second essay, titled "Saving by Overspending", explores consumers' over-expenditure and indulgent consumption when they make prepayments in the form of time, effort, or money toward a consumption goal. This essay proposes that people subconsciously try to get their prepayments' worth, but in fact they may be spending their money irrationally. In addition, contrary to common knowledge, this essay suggests that when a prepayment is unanticipated, the loss of self-control is often more prominent when prepayments are made with behavioral resources (e.g., time or effort) than equivalent monetary resources.
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Minsk, Brian. "An approach to training judgement to improve performance in a real-time, dynamic decision-making task." Thesis, Georgia Institute of Technology, 1997. http://hdl.handle.net/1853/24364.
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Kucera, Stephanie Carsten. "Risk-sensitive decision-making in humans budgeting time, correlated with real-world financial situation." CONNECT TO THIS TITLE ONLINE, 2006. http://etd.lib.umt.edu/theses/available/etd-12052006-140935/.
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Rothrock, Ling. "Performance measures and outcome analyses of dynamic decision making in real-time supervisory control." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/25112.
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Bergert, Franklin Bryan. "Using response time to distinguish between lexicographic and linear models of decision making." [Bloomington, Ind.] : Indiana University, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3297942.
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Thesis (Ph.D.)--Indiana University, Dept. of Psychological and Brain Sciences and Program in Neuroscience Dept., 2008.Title from dissertation home page (viewed Sept. 30, 2008). Source: Dissertation Abstracts International, Volume: 69-03, Section: B, page: 1980. Adviser: Robert M. Nosofsky.
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Choo, Christopher Ledesma Weisen. "Real-time decision making in motorsports : analytics for improving professional car race strategy." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100310.
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Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, Engineering Systems Division, System Design and Management Program, 2015.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (page 77).
We discuss features contained in a machine learning software developed at MIT for professional car racing, to improve the predictions of track position changes within a race. We study pit crew performance and driver performance within selected races, and find that good combined performance for both correlates to better finish positions. Secondly, we classify tracks based on tire wear and the ratio of 2 versus 4 tire change decisions for pit stops. We find that a driver's performance in early stages of the race is similar to performance in later stages, suggesting that final race outcomes may be inferred from earlier stages of the race. Thirdly, we look at how tire change decisions vary from track to track depending on tire wear, caution periods, and stages of the race to understand how teams adapt their tire change strategies as each race progresses. We propose heuristics based on these observations that may be used to improve the software. Next, we test whether the construction of the machine learning dataset using similar and different track characteristics has a discernible impact on the predictive capability of the software. Our tests indicate that it may be preferable to aggregate different races together because there is no distinct difference in the results when compared to only selecting similar races. Finally, we cover ideas about how new features could be implemented in the software, and touch on other factors affecting pit stop strategy in the quest for better predictive capability in the software.
by Christopher Ledesma Weisen Choo.
S.M. in Engineering and Management
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John-Baptiste, Peter Jr. "Advancing Fully Adaptive Radar Concepts for Real-Time Parameter Adaptation and Decision Making." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595501564082873.
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Acerbi, Luigi. "Complex internal representations in sensorimotor decision making : a Bayesian investigation." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/16233.
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The past twenty years have seen a successful formalization of the idea that perception is a form of probabilistic inference. Bayesian Decision Theory (BDT) provides a neat mathematical framework for describing how an ideal observer and actor should interpret incoming sensory stimuli and act in the face of uncertainty. The predictions of BDT, however, crucially depend on the observer’s internal models, represented in the Bayesian framework by priors, likelihoods, and the loss function. Arguably, only in the simplest scenarios (e.g., with a few Gaussian variables) we can expect a real observer’s internal representations to perfectly match the true statistics of the task at hand, and to conform to exact Bayesian computations, but how humans systematically deviate from BDT in more complex cases is yet to be understood. In this thesis we theoretically and experimentally investigate how people represent and perform probabilistic inference with complex (beyond Gaussian) one-dimensional distributions of stimuli in the context of sensorimotor decision making. The goal is to reconstruct the observers’ internal representations and details of their decision-making process from the behavioural data – by employing Bayesian inference to uncover properties of a system, the ideal observer, that is believed to perform Bayesian inference itself. This “inverse problem” is not unique: in principle, distinct Bayesian observer models can produce very similar behaviours. We circumvented this issue by means of experimental constraints and independent validation of the results. To understand how people represent complex distributions of stimuli in the specific domain of time perception, we conducted a series of psychophysical experiments where participants were asked to reproduce the time interval between a mouse click and a flash, drawn from a session-dependent distribution of intervals. We found that participants could learn smooth approximations of the non-Gaussian experimental distributions, but seemed to have trouble with learning some complex statistical features such as bimodality. To investigate whether this difficulty arose from learning complex distributions or computing with them, we conducted a target estimation experiment in which “priors” where explicitly displayed on screen and therefore did not need to be learnt. Lack of difference in performance between the Gaussian and bimodal conditions in this task suggests that acquiring a bimodal prior, rather than computing with it, is the major difficulty. Model comparison on a large number of Bayesian observer models, representing different assumptions about the noise sources and details of the decision process, revealed a further source of variability in decision making that was modelled as a “stochastic posterior”. Finally, prompted by a secondary finding of the previous experiment, we tested the effect of decision uncertainty on the capacity of the participants to correct for added perturbations in the visual feedback in a centre of mass estimation task. Participants almost completely compensated for the injected error in low uncertainty trials, but only partially so in the high uncertainty ones, even when allowed sufficient time to adjust their response. Surprisingly, though, their overall performance was not significantly affected. This finding is consistent with the behaviour of a Bayesian observer with an additional term in the loss function that represents “effort” – a component of optimal control usually thought to be negligible in sensorimotor estimation tasks. Together, these studies provide new insight into the capacity and limitations people have in learning and performing probabilistic inference with distributions beyond Gaussian. This work also introduces several tools and techniques that can help in the systematic exploration of suboptimal behaviour. Developing a language to describe suboptimality, mismatching representations and approximate inference, as opposed to optimality and exact inference, is a fundamental step to link behavioural studies to actual neural computations.
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Rakshit, Ananda. "A framework for discrete-time dynamic programming with multiple objectives." Diss., The University of Arizona, 1988. http://hdl.handle.net/10150/184553.
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The investigation reported in this dissertation attempts to determine the feasibility of using a distance-based approach like compromise programming for discrete-time dynamic programming problems with multiple objectives. In compromise programming, a function measuring the distance from a generally infeasible ideal solution to the feasible set of the problem is the single objective acting as a surrogate for the set of multiple objectives. Since, in general, there is no single best solution to a multiple objective problem, a framework to generate a family of compromise solutions interactively on a computer is proposed. Various quantities relevant to dynamic compromise programming are defined in precise terms. Dynamic compromise programming problems are computationally difficult to solve because in order to make the distance function decomposable over stages, dimensionality of the state-space must be increased by the number of objectives. To generate compromise solutions, quasi-Newton differential dynamic programming (QDDP), a recently developed variable-metric method for discrete-time optimal control, was employed. QDDP is attractive because no second order or Hessian information is required as input. Instead, Hessian matrices are approximated by first order or gradient information. Since very little is known about its numerical properties, computational experiments were conducted on QDDP. A new strategy for updating Hessian matrix approximations was computationally tested. A constrained QDDP algorithm is proposed, computationally tested, and applied to solve a multiobjective dynamic programming problem with inequality constraints at each stage. The algorithm has the potential for application to the more general discrete-time optimal control problem with stage constraints. The framework for generating compromise solutions interactively was implemented for prototype problems. Because decision maker interaction is crucial in a multiple objective situation, special attention was paid towards developing a man-machine interface using on-screen windows. All implementation and computational testing were done on a UNIX based personal computer.
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Kolle, Rainer. "A study into situation management applied to time-critical decision-making in aviation security." Thesis, Lancaster University, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.664262.
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This thesis addresses technological support to decision-making in time-critical environments. In particular, I develop and apply an information-theoretic approach to situation management in aviation security. This thesis investigates the factors affecting situation management and addresses the challenges of establishing timely situation awareness to support the 'course of action' selection. In order to efficiently manage an aviation security incident, a situation management approach can provide the required technological capability in this dynamic and complex environment. Situation management research is still in its infancy and more research concerning underlying methodologies and techniques is required. This work therefore models situation management as a collaborative information problem and explores the factors from a macro-perspective modelling the problem as a multi-agent system. The goal of the research is to explore and develop an information-theoretic framework for decision support systems in situation management contexts. This thesis presents the approach to design and develop a situation management framework within the aviation security context. The modelling work and experiments were implemented with an agent-based simulation software tool (Repast version 2.0). The framework and its implementation has been validated based on use case studies. The performance of the proposed agent model in comparison to two recent European live trial scenarios has been tested to emulate real-time constraints and requirements. The results obtained indicate that automation support for time-critical decision-making in aviation security supports the early identification of incidents and increases the situational awareness during the management of an incident. This allows decision-makers to select from a wider range of options, as the time-window for the deployment of responses increases. Next to the validation of the concept and framework developed, an initial situation management capability for aviation security in SESAR is defined. The work reported in this thesis demonstrates that the situation management concept and framework is applicable for multi-agency coordination and collaboration in aviation security incident management.
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Elliott, Victoria Faith. "Marking time : the decision-making processes of examiners of History and English A-level." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:50e2acc6-88cc-445b-94e9-d4837ae80dce.
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In the UK examiners assign marks to A level examination scripts using extensive mark-schemes. Examiners work under strict time constraints, and must consider various sources, from script to mark-scheme to exemplar marked scripts. Essay subjects, such as History and English (two subjects which are associated with difficulty of marking), are likely to form a particular cognitive challenge for examiners, and their marking has not been extensively researched. Most examiners mark within accepted variations of reliability, as determined by Awarding Bodies’ monitoring systems. The question is, then, how they make these decisions, given the amount of information and the limited time available. The training process which is intended to bring the examiners’ decisions into line with the standard of the Principal Examiner also represents a lacuna in the literature. This study therefore sought to investigate examiners’ decision-making processes and the process of the training meeting. Five day-long standardising meetings (four examiners’ meetings and one senior examiners’ pre-standardising meeting), split between English and History, were recorded, transcribed and subjected to discourse analysis; three examiners, spread between the four units, provided additional Verbal Protocol Analysis data while undertaking live marking. A survey, which presented preliminary conclusions from that data and some extracts from examiners’ discourse, was used to collect further data from a larger sample of History and English A level examiners. The data are considered in relation to the theory of heuristics, which has been used to consider examining at other levels, or in other subjects, and with other question types. The data are also considered in the light of other theories, including those of expertise and construct-referenced assessment. The data demonstrate that decisions were not usually made in the rule-based way which is suggested as the ideal by the regulations, and which would be assumed from the mark-schemes and rubric issued by the exam boards. The mark-scheme did provide a guide to the foci which should, and can be seen to, attract examiners’ attention. However, a great deal of ‘professional judgement’ was also exercised, and examiners used a number of informal heuristics, and made relative judgements to reach a mark; comparison is established as a major mechanism of their decision-making. These behaviours do not necessarily lead to bias, however, and many were actually suggested during the training process. Some were suggested consciously by senior examiners, but some appeared to be unconsciously modelled during the training meeting. The theory of heuristics is seen to be widely applicable to the data; the choice of material and training mitigated the potential bias which heuristics could cause. A wide range of cognitive processes are demonstrated in the data, which were used to varying degrees by different examiners, at different times within and between scripts.
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Pons, Lelardeux Catherine. "Real-time virtual collaborative environment designed for risk management training : communication and decision making." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30146/document.
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Les facteurs humains figurent parmi les causes originelles de trop nombreux accidents, dans les transports, l'industrie ou encore dans les parcours de soins. Dans ces contextes sociotechniques complexes et dynamiques, le risque de survenue d'incidents est permanent. La formation des équipes interprofessionnelles à la gestion des risques dans un environnement reproduisant fidèlement le contexte professionnel est un enjeu majeur. La motivation de cette thèse est de proposer un environnement virtuel multi-joueurs destiné à la formation à la gestion des risques liés à des défauts de communication ou de prises de décision. Pour cela, une méthode de création de scénarios interactifs destinés à la formation à la gestion des risques a été présentée. Un système de communication, un système collaboratif de prise de décision et un modèle de description d'objectifs complexes composés d'actions, de communications et de décisions sont présentés. L'environnement multi-joueurs interactif s'appuie sur cet ensemble cohérent. Ces systèmes et modèles proposés octroient une relative liberté aux équipes pour gérer la situation professionnelle présentée au sein de l'environnement virtuel. Ils permettent aussi le contrôle de la situation pédagogique dans son ensemble. Une méthode à forte valeur d'innovation a aussi été proposée pour structurer le débriefing d'une formation à la gestion des risques. Cela permet notamment d'automatiser la production de débriefing personnalisé, individuel et collectif à l'issu des séances de formationMany accidents in transport, industry or healthcare result from a causal chain of events where inadvertent human errors have not been corrected in time. In such socio-technical and dynamic systems where complexity and unpredictability widespread, training teams to risk management in real-life like situations is crucial. This thesis aims to provide a virtual multi-player environment designed for inter-professional team training to risk management. To that end, a method to design risk management interactive and controlled scenario has been described. A communication system, a group decision making system and a team tracing model have been created. They all together enable the virtual team to be free enough to manage the educational situations. These coherent and innovative environment allows us to control the team activity and automate the edition of a personalized, individual and corporate debriefing at the end of a team training session
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Aleid, Jamal. "Bridging the gap between pre-planning and real-time decision support in crisis management." Thesis, University of Exeter, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284669.
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Dringus, Laurie P. "A Study of Delayed Time and Real Time Text-Based Computer-Mediated Communication Systems on Group Decision Making Performance." NSUWorks, 1991. http://nsuworks.nova.edu/gscis_etd/495.
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This study explored the dynamics of delayed time and real time computer-mediated communication (CMC) when small groups use text-based computer communication programs to reach closure on a priority setting problem task. This study was a preliminary investigation into the effects of computer-mediated communication mode on several measures: decision quality, gain-loss scores and utilization resources, time to solution, text sequencing, and text readability. The problem related to identifying mode of transmission (delayed time and real time) as a variable that can directly impact computer-mediated discourse. Prior studies involving CMC and group decision making were performed using either delayed time or real time computer-mediated communication mode (Kiesler, Siegel, & McGuire, 1984; Sproull and Kiesler, 1986). This study investigated group communication under both modes. Thirty two (N=32) three-person member groups completed a priority setting problem online in a unix* environment that supports computer-mediated communication in delayed and real time modes. Ninety six participants were randomly assigned to one of two computer- mediated communication modes (delayed time or real time). All participants completed the task from their home locations, communicating via modem connection to Nova University's VAX 8550 mini-computer running DEC's version of Unix, "Ultrix" Version 2.3.
Participants were physically, and potentially geographically and time-zone dispersed from others with whom they participated with in the experiment. There was no face-to-face interaction among group members. Transcripts of electronic mail (delayed time) activities and recordings of "Phone" (real time) computer conversation program activities were made during the experiment and later analyzed.
It was hypothesized that there would be a difference between CMC mode and group decision making performance and that coordination of communication would be reduced more under delayed time CMC than under real time CMC. Additionally, it was hypothesized that delayed time groups would take longer to reach closure on the task than real time groups. It was also hypothesized that delayed time groups would prepare and share more text than real time groups. It was also hypothesized that delayed time groups would produce higher text readability grade levels than real time CMC groups. Two of four hypotheses were supported. Bonferroni protected univariate F analyses were performed at the .01 level of significance. Results indicated that while patterns of group process to reach closure were unique according to respective CMC modes, there were no significant differences between groups in regard to decision making quality (score on task).
Group decision making is achievable through CMC despite time delays and absence of face-to-face or voice communication. Delayed time groups took longer to reach closure on the task than real time groups. Real time groups exchanged more messages than delayed time groups. There were no significant differences between CMC groups in regard to the number of sentences and words exchanged. Delayed time groups produced text that was of higher readability quality. However, it was discovered that short text exchanges by groups from both CMC modes influenced the readability analysis, thus misleading true text readability grade levels under CMC modes. It was recommended that future research is needed to provide further insight as to why users would choose to use delayed time computer communication versus real time computer communication. This will become increasingly important to ascertain as more end-users increase their utilization of interactive computer mediated communication, now a standard feature offered under multi-user and multi-tasking operating system environments.
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Fain, W. Bradley. "Analysis of route selection behavior in the presence of real-time traffic information." Thesis, Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/29526.
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Svan, Mac. "Evaluation of the effect of stabilization time in eventually consistent systems." Thesis, Högskolan i Skövde, Institutionen för kommunikation och information, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-4752.
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The effect of using the eventual consistency model is evaluated, compared to the effect of immediate consistency, by increasing the stabilization time in both models and using the immediate consistent system as a baseline for evaluations. The immediate consistent system performs better if the information and the decisions are replicated adequately fast throughout the system. When the stabilization time increases the effectiveness of eventual consistency emerges, which is most obvious when time constraints make it difficult to propagate information and decisions. By using a simulation to extract data for evaluations, it is verified in this research that as the stabilization time between different parts of a system increases, the eventual consistency will always outperform the immediate consistent system. This statement is valid in all situations where consistency models are useful. Of secondary importance in the research, by adding more decision layers to the eventual consistency model, the performance output is increased significantly, as swift and less well calculated decisions can be thwarted and corrected using the second decision layer.
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Farská, Kateřina. "Cognitive Depletion and Its Effect on Decision Making." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-165267.
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One of the factors significantly influencing our daily decisions is the so-called cognitive depletion.The theory of cognitive depletion postulates the existence of a limited mental resource that is necessary for self-regulation. If the resource is diminished by a task involving self-control, achievement in subsequent self-control task will be impaired. This project examines the effect of cognitive depletion on decisions in the Iowa Gambling Task designed to simulate real-life decision making involving gains and losses. Further, a possible effect of moderating factors that could be affected by cognitive depletion and consequently influence decisions in the Iowa Gambling Task -- risk preference and impulsivity -- is investigated. Dual-process theories postulate there are two systems involved in decision-making: faster, intuitive, emotional System 1 and slower, deliberative, rational System 2. It was found that cognitive depletion leads to enhancement of System 1. As advantageous decisions in the Iowa Gambling Task are closely related to emotional reactions -- domain of System 1 -- it was hypothesized that cognitive depletion will lead to not worse, or possibly even better results in depleted subjects. A controlled laboratory experiment was conducted involving 39 subjects in total. No difference was found in average desicions of depleted and non-depleted subjects in the Iowa Gambling Task, supporting the hypothesis. Further, short-term increase in impulsivity caused by cognitive depletion was very probably moderating choices in the IGT, leading to worse overall performance. Regarding risk preferences, we found that non-depleted subjects were generally more risk seeking in losses context, while depleted subjects exhibited rather loss aversion. This change in risk behaviors due to cognitive depletion very probably did not mediate choices in the Iowa Gambling Task.
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Carey, Lindsey Isabelle. "The impact of time perspective on consumer decision-making in the context of ethical shopping." Thesis, Glasgow Caledonian University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.517686.
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