Matching Items (11)

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Understanding Unpredictability

Description

Since the emergence of behavioral economics, our understanding of human behavior and decision-making has improved through the widespread use of conducting experiments. In tandem, behavioral and experimental economists seek to

Since the emergence of behavioral economics, our understanding of human behavior and decision-making has improved through the widespread use of conducting experiments. In tandem, behavioral and experimental economists seek to merge psychology and emotion into economic thought to better understand the agents that comprise our economic systems. Vernon Smith, a Nobel Prize winning experimental economist, wrote an article on how economic agents in asset market experiments create bubbles (commonly referred to as "booms and busts" or "market crashes"). This study builds on Smith's work and seeks to better understand how participants behave when given information about the expected outcome of the experiment, and thus how external information affects an individual's expectations and behavior in financial markets. Upon the completion of the experiments and analyzing the results, 7 of the 14 experiments with the same parameters ended with the outcome consistent with the researcher's hypotheses. These results conclude that providing participants with different contextual information regarding outcome hypotheses affected their expectations, price speculations, and strategy development when approaching an asset market.

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Agent

Created

Date Created
  • 2017-12

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Diagnosis: An Analysis of Human Behavior through Poetry

Description

Diagnosis is an analysis of human behavior, examined through several types of poetry. The project delves into how individuals act and re-act when put into stress-inducing situations, whether due to

Diagnosis is an analysis of human behavior, examined through several types of poetry. The project delves into how individuals act and re-act when put into stress-inducing situations, whether due to that situation, personality, traits, an interaction with another person, or mental illness.

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Agent

Created

Date Created
  • 2013-05

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Creating an Environment for Empathy in the Classroom

Description

Empathy is a characteristic fully developed and manifested in one creature: the human being. In February 2011, we saw the supercomputer, Watson, challenge highly intelligent human beings on Jeopardy. The

Empathy is a characteristic fully developed and manifested in one creature: the human being. In February 2011, we saw the supercomputer, Watson, challenge highly intelligent human beings on Jeopardy. The human beings put up a brutal battle of wits but ultimately, the computer was declared victor. Scientists have made remarkable leaps when it comes to creating artificial intelligence. We have "smart" phones that sit in the palm of our hand and can do far more than what we expected of bulky desktops in the 90s.

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Agent

Created

Date Created
  • 2012-12

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An adaptive approach to securing ubiquitous smart devices in IoT environment with probabilistic user behavior prediction

Description

Cyber systems, including IoT (Internet of Things), are increasingly being used ubiquitously to vastly improve the efficiency and reduce the cost of critical application areas, such as finance, transportation, defense,

Cyber systems, including IoT (Internet of Things), are increasingly being used ubiquitously to vastly improve the efficiency and reduce the cost of critical application areas, such as finance, transportation, defense, and healthcare. Over the past two decades, computing efficiency and hardware cost have dramatically been improved. These improvements have made cyber systems omnipotent, and control many aspects of human lives. Emerging trends in successful cyber system breaches have shown increasing sophistication in attacks and that attackers are no longer limited by resources, including human and computing power. Most existing cyber defense systems for IoT systems have two major issues: (1) they do not incorporate human user behavior(s) and preferences in their approaches, and (2) they do not continuously learn from dynamic environment and effectively adapt to thwart sophisticated cyber-attacks. Consequently, the security solutions generated may not be usable or implementable by the user(s) thereby drastically reducing the effectiveness of these security solutions.

In order to address these major issues, a comprehensive approach to securing ubiquitous smart devices in IoT environment by incorporating probabilistic human user behavioral inputs is presented. The approach will include techniques to (1) protect the controller device(s) [smart phone or tablet] by continuously learning and authenticating the legitimate user based on the touch screen finger gestures in the background, without requiring users’ to provide their finger gesture inputs intentionally for training purposes, and (2) efficiently configure IoT devices through controller device(s), in conformance with the probabilistic human user behavior(s) and preferences, to effectively adapt IoT devices to the changing environment. The effectiveness of the approach will be demonstrated with experiments that are based on collected user behavioral data and simulations.

Contributors

Agent

Created

Date Created
  • 2016

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A novel engineering approach to modelling and optimizing smoking cessation interventions

Description

Cigarette smoking remains a major global public health issue. This is partially due to the chronic and relapsing nature of tobacco use, which contributes to the approximately 90% quit attempt

Cigarette smoking remains a major global public health issue. This is partially due to the chronic and relapsing nature of tobacco use, which contributes to the approximately 90% quit attempt failure rate. The recent rise in mobile technologies has led to an increased ability to frequently measure smoking behaviors and related constructs over time, i.e., obtain intensive longitudinal data (ILD). Dynamical systems modeling and system identification methods from engineering offer a means to leverage ILD in order to better model dynamic smoking behaviors. In this dissertation, two sets of dynamical systems models are estimated using ILD from a smoking cessation clinical trial: one set describes cessation as a craving-mediated process; a second set was reverse-engineered and describes a psychological self-regulation process in which smoking activity regulates craving levels. The estimated expressions suggest that self-regulation more accurately describes cessation behavior change, and that the psychological self-regulator resembles a proportional-with-filter controller. In contrast to current clinical practice, adaptive smoking cessation interventions seek to personalize cessation treatment over time. An intervention of this nature generally reflects a control system with feedback and feedforward components, suggesting its design could benefit from a control systems engineering perspective. An adaptive intervention is designed in this dissertation in the form of a Hybrid Model Predictive Control (HMPC) decision algorithm. This algorithm assigns counseling, bupropion, and nicotine lozenges each day to promote tracking of target smoking and craving levels. Demonstrated through a diverse series of simulations, this HMPC-based intervention can aid a successful cessation attempt. Objective function weights and three-degree-of-freedom tuning parameters can be sensibly selected to achieve intervention performance goals despite strict clinical and operational constraints. Such tuning largely affects the rate at which peak bupropion and lozenge dosages are assigned; total post-quit smoking levels, craving offset, and other performance metrics are consequently affected. Overall, the interconnected nature of the smoking and craving controlled variables facilitate the controller's robust decision-making capabilities, even despite the presence of noise or plant-model mismatch. Altogether, this dissertation lays the conceptual and computational groundwork for future efforts to utilize engineering concepts to further study smoking behaviors and to optimize smoking cessation interventions.

Contributors

Agent

Created

Date Created
  • 2014

A semiotic approach to the evolution of symboling capacities during the late Pleistocene with implications for claims of modernity in early human groups

Description

This research uses Peircean Semiotics to model the evolution of symbolic behavior in the human lineage and the potential material correlates of this evolutionary process in the archaeological record. The

This research uses Peircean Semiotics to model the evolution of symbolic behavior in the human lineage and the potential material correlates of this evolutionary process in the archaeological record. The semiotic model states the capacity for symbolic behavior developed in two distinct stages. Emergent capacities are characterized by the sporadic use of non-symbolic and symbolic material culture that affects information exchange between individuals. Symbolic exchange will be rare. Mobilized capacities are defined by the constant use of non-symbolic and symbolic objects that affect both interpersonal and group-level information exchange. Symbolic behavior will be obligatory and widespread. The model was tested against the published archaeological record dating from ~200,000 years ago to the Pleistocene/Holocene boundary in three sub-regions of Africa and Eurasia. A number of Exploratory and Confirmatory Data Analysis techniques were used to identify patterning in artifacts through time consistent with model predictions. The results indicate Emergent symboling capacities were expressed as early as ~100,000 years ago in Southern Africa and the Levant. However, capacities do not appear fully Mobilized in these regions until ~17,000 years ago. Emergent symboling is not evident in the European record until ~42,000 years ago, but develops rapidly. The results also indicate both Anatomically Modern Humans and Neanderthals had the capacity for symbolic behavior, but expressed those capacities differently. Moreover, interactions between the two populations did not select for symbolic expression, nor did periodic aggregation within groups. The analysis ultimately situates the capacity for symbolic behavior in increased engagement with materiality and the ability to recognize material objects can be made meaningful– an ability that must have been shared with Anatomically Modern Humans’ and Neanderthals’ most recent common ancestor. Consequently, the results have significant implications for notions of ‘modernity’ and human uniqueness that drive human origins research. This work pioneers deductive approaches to cognitive evolution, and both strengths and weaknesses are discussed. In offering notable results and best practices, it effectively operationalizes the semiotic model as a viable analytical method for human origins research.

Contributors

Agent

Created

Date Created
  • 2016

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Factors affecting behavioral change through the use of computer-mediated technology

Description

This study explores the impact of feedback and feedforward and personality on computer-mediated behavior change. The impact of the effects were studied using subjects who entered information relevant to their

This study explores the impact of feedback and feedforward and personality on computer-mediated behavior change. The impact of the effects were studied using subjects who entered information relevant to their diet and exercise into an online tool. Subjects were divided into four experimental groups: those receiving only feedback, those receiving only feedforward, those receiving both, and those receiving none. Results were analyzed using regression analysis. Results indicate that both feedforward and feedback impact behavior change and that individuals with individuals ranking low in conscientiousness experienced behavior change equivalent to that of individuals with high conscientiousness in the presence of feedforward and/or feedback.

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Agent

Created

Date Created
  • 2012

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Can accountability be instilled, in the absence of an authority figure, in a way which enhances a human-automation system?

Description

As automation becomes more prevalent in society, the frequency that systems involve interactive human-automation control increases. Previous studies have shown accountability to be a valuable way of eliciting human engagement

As automation becomes more prevalent in society, the frequency that systems involve interactive human-automation control increases. Previous studies have shown accountability to be a valuable way of eliciting human engagement and reducing various biases, but these studies have involved the presence of an authority figure during the research. The current research sought to explore the effect of accountability in the absence of an authority figure. To do this, 40 participants took part in this study by playing a microworld simulation. Half were told they would be interviewed after the simulation, and half were told data was not being collected. Eleven dependent variables were collected (accountability, number of resources shared, player score, agent score, combined score, and the six measures of the NASA- Task Load Index), of which statistical significance was found in number of resources shared, player score, and agent score. While not conclusive, the results suggest that accountability affects human-automation interactions even in the absence of an authority figure. It is suggested that future research seek to find a reliable way to measure accountability and examine how long accountability effects last.

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Agent

Created

Date Created
  • 2019

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The role of ochre in the development of modern human behavior: a case study from South Africa

Description

In recent years, southern Africa has figured prominently in the modern human origins debate due to increasing evidence for precocious behaviors considered to be unique to our species. These significant

In recent years, southern Africa has figured prominently in the modern human origins debate due to increasing evidence for precocious behaviors considered to be unique to our species. These significant findings have included bone tools, shell beads, engraved ostrich eggshell, and heavily ground and engraved ochre fragments. The presence of ochre in Middle Stone Age (MSA, ~250-40kya) archaeological sites in southern Africa is often proposed as indirect evidence for the emergence of symbolic or artistic behavior, a uniquely modern human trait. However, there is no remaining artwork from this period and there is significant debate about what the ochre may have been used for. With a few exceptions, ochre has gone largely unstudied. This project tested competing models for ochre use within the Pinnacle Point (PP), South Africa research area. Combined results from characterization and sourcing analyses, color classification, heat treatment analysis, and hafting experiments suggest MSA ochre is tied to early symbolic or ritual behavior.

Contributors

Agent

Created

Date Created
  • 2012

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Spread rate estimation and the role of spatial configuration and human behavior

Description

The spread of invasive species may be greatly affected by human responses to prior species spread, but models and estimation methods seldom explicitly consider human responses. I investigate the effects

The spread of invasive species may be greatly affected by human responses to prior species spread, but models and estimation methods seldom explicitly consider human responses. I investigate the effects of management responses on estimates of invasive species spread rates. To do this, I create an agent-based simulation model of an insect invasion across a county-level citrus landscape. My model provides an approximation of a complex spatial environment while allowing the "truth" to be known. The modeled environment consists of citrus orchards with insect pests dispersing among them. Insects move across the simulation environment infesting orchards, while orchard managers respond by administering insecticide according to analyst-selected behavior profiles and management responses may depend on prior invasion states. Dispersal data is generated in each simulation and used to calculate spread rate via a set of estimators selected for their predominance in the empirical literature. Spread rate is a mechanistic, emergent phenomenon measured at the population level caused by a suite of latent biological, environmental, and anthropogenic. I test the effectiveness of orchard behavior profiles on invasion suppression and evaluate the robustness of the estimators given orchard responses. I find that allowing growers to use future expectations of spread in management decisions leads to reduced spread rates. Acting in a preventative manner by applying insecticide before insects are actually present, orchards are able to lower spread rates more than by reactive behavior alone. Spread rates are highly sensitive to spatial configuration. Spatial configuration is hardly a random process, consisting of many latent factors often not accounted for in spread rate estimation. Not considering these factors may lead to an omitted variables bias and skew estimation results. The ability of spread rate estimators to predict future spread varies considerably between estimators, and with spatial configuration, invader biological parameters, and orchard behavior profile. The model suggests that understanding the latent factors inherent to dispersal is important for selecting phenomenological models of spread and interpreting estimation results. This indicates a need for caution when evaluating spread. Although standard practice, current empirical estimators may both over- and underestimate spread rate in the simulation.

Contributors

Agent

Created

Date Created
  • 2012