Current Search: Human behavior (x)
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- Title
- An Investigation of High Anxiety Verbal Behavior.
- Creator
-
Wright, John W., Taylor, Phillip, Social Sciences
- Abstract / Description
-
Florida Technological University College of Social Sciences Thesis
- Date Issued
- 1973
- Identifier
- CFR0012240, ucf:53132
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFR0012240
- Title
- Provider Recommendation of HPV Vaccination: Bridging the Intention-Behavior Gap.
- Creator
-
Landis, Erica, Neuberger, Lindsay, Sandoval, Jennifer, Miller, Ann, University of Central Florida
- Abstract / Description
-
The present study, guided by preproduction formative research principles, employed in-depth interviews and a brief survey with pediatric healthcare providers (N=15) to investigate the consistency between behavioral intention to strongly recommend the HPV vaccine, and implementation of the actual behavior. Specifically, the Integrative Model of Behavioral Prediction (IMBP) was used as a framework to examine the impact of skills and environmental constraints on that behavioral intention...
Show moreThe present study, guided by preproduction formative research principles, employed in-depth interviews and a brief survey with pediatric healthcare providers (N=15) to investigate the consistency between behavioral intention to strongly recommend the HPV vaccine, and implementation of the actual behavior. Specifically, the Integrative Model of Behavioral Prediction (IMBP) was used as a framework to examine the impact of skills and environmental constraints on that behavioral intention-behavioral performance relationship. Results suggest providers intend to strongly recommend the HPV vaccine at a high level, but actually recommend the vaccine with a slightly lesser frequency. A thematic analysis of interview transcripts yielded a list of skills (e.g., tact, cultural competence) and environmental constraints (e.g., a lack of policy or school entry requirement, limited time designated for each patient) that contribute to that consistency gap. Additionally, healthcare providers indicated several preferences on training design (e.g., Continuing Medical Education course, delivered by medical and communication professionals) that could be used to inform future message construction. Suggestions for overcoming the environmental constraints reported by providers are presented, and implications for incorporating the emergent skills and preferences into training as a novel strategy for improving provider communication about the HPV vaccine outlined.
Show less - Date Issued
- 2016
- Identifier
- CFE0006132, ucf:51162
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006132
- Title
- Transparency in human-agent teaming and its effect on complacent behavior.
- Creator
-
Wright, Julia, Hancock, Peter, Szalma, James, Jentsch, Florian, Chen, Jessie, University of Central Florida
- Abstract / Description
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This study examined how transparency of an intelligent agent's reasoning affected complacent behavior in a route selection task in a simulated environment. Also examined was how the information available to the operator affected those results.In two experiments, participants supervised a three-vehicle convoy as it traversed a simulated environment and re-routed the convoy when needed with the assistance of an intelligent agent, RoboLeader. Participants were randomly assigned to an Agent...
Show moreThis study examined how transparency of an intelligent agent's reasoning affected complacent behavior in a route selection task in a simulated environment. Also examined was how the information available to the operator affected those results.In two experiments, participants supervised a three-vehicle convoy as it traversed a simulated environment and re-routed the convoy when needed with the assistance of an intelligent agent, RoboLeader. Participants were randomly assigned to an Agent Reasoning Transparency condition. Participants received communications from a commander confirming either the presence or absence of activity in the area. They also received information regarding potential events along their route via icons that appeared on a map displaying the convoy route and surrounding area. Participants in Experiment 1 (low information setting) received information about their current route only; they did not receive any information about the suggested alternate route. Participants in Experiment 2 (high information setting) received information about both their current route and the agent recommended an alternative route. In the first experiment, access to agent reasoning was found to be an effective deterrent to complacent behavior when the operator has limited information about their task environment. However, the addition of information that created ambiguity for the operator encouraged complacency, resulting in reduced performance and poorer trust calibration. Agent reasoning did not increase response time or workload and appeared to have improved performance on the secondary task. These findings align with studies that have shown ambiguous information can increase workload and encourage complacency, as such, caution should be exercised when considering how transparent to make agent reasoning and what information should be included.In the second experiment, access to agent reasoning was found to have little effect on complacent behavior when the operator had complete information about the task environment. However, the addition of information that created ambiguity for the operator appeared to encourage complacency, as indicated by reduced performance and shorter decision times. Agent reasoning transparency did not increase overall workload, and operators reported higher satisfaction with their performance and reduced mental demand. Access to agent reasoning did not improve operators' secondary task performance, situation awareness, or operator trust. However, when agent reasoning transparency included ambiguous information complacent behavior was again encouraged. Unlike the first experiment, there were notable differences in complacent behavior, performance, operator trust, and situation awareness due to individual difference factors. As such, these findings would suggest that when the operator has complete information regarding their task environment, access to agent reasoning may be beneficial, but not dramatically so. However, individual difference factors will greatly influence performance outcomes. The amount of information the operator has regarding the task environment has a profound effect on the proper use of the agent. Increased environmental information resulted in more rejections of the agent recommendation regardless of the transparency of agent reasoning. The addition of agent reasoning transparency appeared to be effective at keeping the operator engaged, while complacent behavior appeared to be encouraged both when agent reasoning was either not transparent or so transparent as to become ambiguous. Even so, operators reported lower trust and usability for the agent than when environmental information was limited. Situation awareness (SA2) scores were also higher in the high information environment when agent reasoning was either not transparent or so transparent as to become ambiguous, compared to the low information environment. However, when a moderate amount of agent reasoning was available to the operator, the amount of information available to the operator had no effect on the operators' complacent behavior, subjective trust, or SA. These findings indicate that some negative outcomes resulting from the incongruous transparency of agent reasoning may be mitigated by increasing the information the operator has regarding the task environment.
Show less - Date Issued
- 2016
- Identifier
- CFE0006422, ucf:51469
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006422
- Title
- EVOLVING MODELS FROM OBSERVED HUMAN PERFORMANCE.
- Creator
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Fernlund, Hans Karl Gustav, Gonzalez, Avelino J., University of Central Florida
- Abstract / Description
-
To create a realistic environment, many simulations require simulated agents with human behavior patterns. Manually creating such agents with realistic behavior is often a tedious and time-consuming task. This dissertation describes a new approach that automatically builds human behavior models for simulated agents by observing human performance. The research described in this dissertation synergistically combines Context-Based Reasoning, a paradigm especially developed to model tactical...
Show moreTo create a realistic environment, many simulations require simulated agents with human behavior patterns. Manually creating such agents with realistic behavior is often a tedious and time-consuming task. This dissertation describes a new approach that automatically builds human behavior models for simulated agents by observing human performance. The research described in this dissertation synergistically combines Context-Based Reasoning, a paradigm especially developed to model tactical human performance within simulated agents, with Genetic Programming, a machine learning algorithm to construct the behavior knowledge in accordance to the paradigm. This synergistic combination of well-documented AI methodologies has resulted in a new algorithm that effectively and automatically builds simulated agents with human behavior. This algorithm was tested extensively with five different simulated agents created by observing the performance of five humans driving an automobile simulator. The agents show not only the ability/capability to automatically learn and generalize the behavior of the human observed, but they also capture some of the personal behavior patterns observed among the five humans. Furthermore, the agents exhibited a performance that was at least as good as agents developed manually by a knowledgeable engineer.
Show less - Date Issued
- 2004
- Identifier
- CFE0000013, ucf:46068
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000013
- Title
- A REINFORCEMENT LEARNING TECHNIQUE FOR ENHANCING HUMAN BEHAVIOR MODELS IN A CONTEXT-BASED ARCHITECTURE.
- Creator
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Aihe, David, Gonzalez, Avelino, University of Central Florida
- Abstract / Description
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A reinforcement-learning technique for enhancing human behavior models in a context-based learning architecture is presented. Prior to the introduction of this technique, human models built and developed in a Context-Based reasoning framework lacked learning capabilities. As such, their performance and quality of behavior was always limited by what the subject matter expert whose knowledge is modeled was able to articulate or demonstrate. Results from experiments performed show that subject...
Show moreA reinforcement-learning technique for enhancing human behavior models in a context-based learning architecture is presented. Prior to the introduction of this technique, human models built and developed in a Context-Based reasoning framework lacked learning capabilities. As such, their performance and quality of behavior was always limited by what the subject matter expert whose knowledge is modeled was able to articulate or demonstrate. Results from experiments performed show that subject matter experts are prone to making errors and at times they lack information on situations that are inherently necessary for the human models to behave appropriately and optimally in those situations. The benefits of the technique presented is two fold; 1) It shows how human models built in a context-based framework can be modified to correctly reflect the knowledge learnt in a simulator; and 2) It presents a way for subject matter experts to verify and validate the knowledge they share. The results obtained from this research show that behavior models built in a context-based framework can be enhanced by learning and reflecting the constraints in the environment. From the results obtained, it was shown that after the models are enhanced, the agents performed better based on the metrics evaluated. Furthermore, after learning, the agent was shown to recognize unknown situations and behave appropriately in previously unknown situations. The overall performance and quality of behavior of the agent improved significantly.
Show less - Date Issued
- 2008
- Identifier
- CFE0002466, ucf:47715
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002466
- Title
- THE EFFECT OF BULLYING AND THE MEDIATING ROLE OF ATTACHMENT AND HUMANITY-ESTEEM ON SELF-ESTEEM AND BEHAVIORAL OUTCOMES.
- Creator
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Bater, Lovina, Renk, Kimberly, University of Central Florida
- Abstract / Description
-
Any type of bullying can become a traumatic event for a child, leading to lasting negative effects. Specifically, victimization may lead to numerous behavioral problems and lowered self-esteem. Also, the quality of attachment may have a predictive relationship with the victimization and the negative outcomes it may cause. Other research implied that a similar relationship may be found between retrospective bullying and humanity-esteem. Despite the collective research done on these variables,...
Show moreAny type of bullying can become a traumatic event for a child, leading to lasting negative effects. Specifically, victimization may lead to numerous behavioral problems and lowered self-esteem. Also, the quality of attachment may have a predictive relationship with the victimization and the negative outcomes it may cause. Other research implied that a similar relationship may be found between retrospective bullying and humanity-esteem. Despite the collective research done on these variables, no study, until now, has looked at retrospective bullying, humanity-esteem, attachment, behavior problems, and self-esteem all together. This study not only looked at the relationships among these variables but also the role that humanity-esteem and attachment served between victimization, later behavior problems, and later self-esteem. One hundred thirty-six participants completed five questionnaires assessing experiences of retrospective bullying, humanity-esteem, current attachment relationships, behavior problems, and self-esteem. The results of this study indicated that participants who reported having been bullied previously also endorsed internalizing and externalizing problems as well as low self-esteem. Further, humanity-esteem and attachment both served as significant predictors of victimized individuals' behavioral problems and self-esteem. Such findings suggested that a higher view of humanity and secure attachment may serve as a protective factor against the negative outcomes that may be related to having been bullied. The importance of studying the relationships among these variables is discussed further.
Show less - Date Issued
- 2013
- Identifier
- CFH0004489, ucf:45067
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH0004489
- Title
- MODELING AND CHARACTERIZATION OF ACUTE STRESS UNDER DYNAMIC TASK CONDITIONS.
- Creator
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Millan, Angel, Crumpton-Young, Lesia, University of Central Florida
- Abstract / Description
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Stress can be defined as the mental, physical, and emotional response of humans to stressors encountered in their personal or professional environment. Stressors are introduced in various activities, especially those found in dynamic task conditions when multiple task requirements must be performed. Stress and stressors have been described as activators and inhibitors of human performance. The ability to manage high levels of acute stress is an important determinant of successful performance...
Show moreStress can be defined as the mental, physical, and emotional response of humans to stressors encountered in their personal or professional environment. Stressors are introduced in various activities, especially those found in dynamic task conditions when multiple task requirements must be performed. Stress and stressors have been described as activators and inhibitors of human performance. The ability to manage high levels of acute stress is an important determinant of successful performance in any occupation. In situations where performance is critical, personnel must be prepared to operate successfully under hostile or extreme stress conditions; therefore training programs and engineered systems must be tailored to assist humans in fulfilling these demands. To effectively design appropriate training programs for these conditions, it is necessary to quantitatively describe stress. A series of theoretical stress models have been developed in previous research studies; however, these do not provide quantification of stress levels nor the impact on human performance. By modeling acute stress under dynamic task conditions, quantitative values for stress and its impact on performance can be assessed. Thus, this research was designed to develop a predictive model for acute stress as a function of human performance and task demand. Initially, a four factor two level experimental design [2 (Noise) x 2 (Temperature) x 2 (Time Awareness) x 2 (Workload)] was performed to identify reliable physiological, cognitive and behavioral responses to stress. Next, multivariate analysis of variance (n=108) tests were performed, which showed statistically significant differences for physiological, cognitive and behavioral responses. Finally, fuzzy set theory techniques were used to develop a comprehensive stress index model. Thus, the resulting stress index model was constructed using input on physiological, cognitive and behavioral responses to stressors as well as characteristics inherent to the type of task performed and personal factors that interact as mediators (competitiveness, motivation, coping technique and proneness to boredom). Through using this stress index model to quantify and characterize the affects of acute stress on human performance, these research findings can inform proper training protocols and help to redesign tasks and working conditions that are prone to create levels of acute stress that adversely affect human performance.
Show less - Date Issued
- 2011
- Identifier
- CFE0004056, ucf:49151
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004056
- Title
- Human Group Behavior Modeling for Virtual Worlds.
- Creator
-
Shah, Syed Fahad Allam, Sukthankar, Gita, Georgiopoulos, Michael, Foroosh, Hassan, Anagnostopoulos, Georgios, University of Central Florida
- Abstract / Description
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Virtual worlds and massively-multiplayer online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. They provide new outlets for human social interaction that differ from both face-to-face interactions and non-physically-embodied social networking tools such as Facebook and Twitter. We aim to study group dynamics in these virtual worlds by collecting and...
Show moreVirtual worlds and massively-multiplayer online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. They provide new outlets for human social interaction that differ from both face-to-face interactions and non-physically-embodied social networking tools such as Facebook and Twitter. We aim to study group dynamics in these virtual worlds by collecting and analyzing public conversational patterns of users grouped in close physical proximity. To do this, we created a set of tools for monitoring, partitioning, and analyzing unstructured conversations between changing groups of participants in Second Life, a massively multi-player online user-constructed environment that allows users to construct and inhabit their own 3D world. Although there are some cues in the dialog, determining social interactions from unstructured chat data alone is a difficult problem, since these environments lack many of the cues that facilitate natural language processing in other conversational settings and different types of social media. Public chat data often features players who speak simultaneously, use jargon and emoticons, and only erratically adhere to conversational norms.Humans are adept social animals capable of identifying friendship groups from a combination of linguistic cues and social network patterns. But what is more important, the content of what people say or their history of social interactions? Moreover, is it possible to identify whether people are part of a group with changing membership merely from general network properties, such as measures of centrality and latent communities? These are the questions that we aim to answer in this thesis. The contributions of this thesis include: 1) a link prediction algorithm for identifying friendship relationships from unstructured chat data 2) a method for identifying social groups based on the results of community detection and topic analysis.The output of these two algorithms (links and group membership) are useful for studying a variety of research questions about human behavior in virtual worlds. To demonstrate this we have performed a longitudinal analysis of human groups in different regions of the Second Life virtual world. We believe that studies performed with our tools in virtual worlds will be a useful stepping stone toward creating a rich computational model of human group dynamics.
Show less - Date Issued
- 2011
- Identifier
- CFE0004164, ucf:49074
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004164
- Title
- Towards Improving Human-Robot Interaction For Social Robots.
- Creator
-
Khan, Saad, Boloni, Ladislau, Behal, Aman, Sukthankar, Gita, Garibay, Ivan, Fiore, Stephen, University of Central Florida
- Abstract / Description
-
Autonomous robots interacting with humans in a social setting must consider the social-cultural environment when pursuing their objectives. Thus the social robot must perceive and understand the social cultural environment in order to be able to explain and predict the actions of its human interaction partners. This dissertation contributes to the emerging field of human-robot interaction for social robots in the following ways: 1. We used the social calculus technique based on culture...
Show moreAutonomous robots interacting with humans in a social setting must consider the social-cultural environment when pursuing their objectives. Thus the social robot must perceive and understand the social cultural environment in order to be able to explain and predict the actions of its human interaction partners. This dissertation contributes to the emerging field of human-robot interaction for social robots in the following ways: 1. We used the social calculus technique based on culture sanctioned social metrics (CSSMs) to quantify, analyze and predict the behavior of the robot, human soldiers and the public perception in the Market Patrol peacekeeping scenario. 2. We validated the results of the Market Patrol scenario by comparing the predicted values with the judgment of a large group of human observers cognizant of the modeled culture. 3. We modeled the movement of a socially aware mobile robot in a dense crowds, using the concept of a micro-conflict to represent the challenge of giving or not giving way to pedestrians. 4. We developed an approach for the robot behavior in micro-conflicts based on the psychological observation that human opponents will use a consistent strategy. For this, the mobile robot classifies the opponent strategy reflected by the personality and social status of the person and chooses an appropriate counter-strategy that takes into account the urgency of the robots' mission. 5. We developed an alternative approach for the resolution of micro-conflicts based on the imitation of the behavior of the human agent. This approach aims to make the behavior of an autonomous robot closely resemble that of a remotely operated one.
Show less - Date Issued
- 2015
- Identifier
- CFE0005965, ucf:50819
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0005965
- Title
- Investigating the Influence of the Built Environment on Energy-Saving Behaviors.
- Creator
-
Sellers, Brittany, Jentsch, Florian, Smither, Janan, Sims, Valerie, Fiore, Stephen, University of Central Florida
- Abstract / Description
-
This dissertation addresses a gap in the existing sustainability behavior research, by integrating research from the social sciences about environmental attitudes and knowledge with approaches from engineering regarding the characteristics of the built environment. Specifically, this dissertation explores the role of both environmental knowledge and design features within the built environment on building occupants' energy behaviors throughout the course of an environmental conservation...
Show moreThis dissertation addresses a gap in the existing sustainability behavior research, by integrating research from the social sciences about environmental attitudes and knowledge with approaches from engineering regarding the characteristics of the built environment. Specifically, this dissertation explores the role of both environmental knowledge and design features within the built environment on building occupants' energy behaviors throughout the course of an environmental conservation campaign. Data were collected from 240 dormitory residents using a multi-phase questionnaire approach to study these factors and their combined impact within the context of environmental sustainability practices on UCF's campus. The results from a series of correlational and multiple regression analyses indicate that both the design components of the built environment and the attitudes held by individuals within that environment have a significant positive influence on behaviors. Furthermore, these findings indicated that this effect increases significantly when the two factors work together. Finally, the results show that pro- environmental attitudes and behaviors can be successfully targeted through a cue-based energy conservation campaign. By addressing a gap in the extant Human Factors research about the relationship between attitudinal factors and the built environment, this dissertation provides a unique contribution to the field and points the way towards development of promising solutions for encouraging sustainable behaviors.
Show less - Date Issued
- 2016
- Identifier
- CFE0006500, ucf:51387
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006500
- Title
- A COMPARATIVE ANALYSIS BETWEEN CONTEXT-BASED REASONING (CXBR) AND CONTEXTUAL GRAPHS (CXGS).
- Creator
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Lorins, Peterson, Gonzalez, Avelino, University of Central Florida
- Abstract / Description
-
Context-based Reasoning (CxBR) and Contextual Graphs (CxGs) involve the modeling of human behavior in autonomous and decision-support situations in which optimal human decision-making is of utmost importance. Both formalisms use the notion of contexts to allow the implementation of intelligent agents equipped with a context sensitive knowledge base. However, CxBR uses a set of discrete contexts, implying that models created using CxBR operate within one context at a given time interval. CxGs...
Show moreContext-based Reasoning (CxBR) and Contextual Graphs (CxGs) involve the modeling of human behavior in autonomous and decision-support situations in which optimal human decision-making is of utmost importance. Both formalisms use the notion of contexts to allow the implementation of intelligent agents equipped with a context sensitive knowledge base. However, CxBR uses a set of discrete contexts, implying that models created using CxBR operate within one context at a given time interval. CxGs use a continuous context-based representation for a given problem-solving scenario for decision-support processes. Both formalisms use contexts dynamically by continuously changing between necessary contexts as needed in appropriate instances. This thesis identifies a synergy between these two formalisms by looking into their similarities and differences. It became clear during the research that each paradigm was designed with a very specific family of problems in mind. Thus, CXBR best implements models of autonomous agents in environment, while CxGs is best implemented in a decision support setting that requires the development of decision-making procedures. Cross applications were implemented on each and the results are discussed.
Show less - Date Issued
- 2005
- Identifier
- CFE0000577, ucf:46433
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000577
- Title
- CONTEXTUALIZING OBSERVATIONAL DATA FOR MODELING HUMAN PERFORMANCE.
- Creator
-
Trinh, Viet, Gonzalez, Avelino, University of Central Florida
- Abstract / Description
-
This research focuses on the ability to contextualize observed human behaviors in efforts to automate the process of tactical human performance modeling through learning from observations. This effort to contextualize human behavior is aimed at minimizing the role and involvement of the knowledge engineers required in building intelligent Context-based Reasoning (CxBR) agents. More specifically, the goal is to automatically discover the context in which a human actor is situated when...
Show moreThis research focuses on the ability to contextualize observed human behaviors in efforts to automate the process of tactical human performance modeling through learning from observations. This effort to contextualize human behavior is aimed at minimizing the role and involvement of the knowledge engineers required in building intelligent Context-based Reasoning (CxBR) agents. More specifically, the goal is to automatically discover the context in which a human actor is situated when performing a mission to facilitate the learning of such CxBR models. This research is derived from the contextualization problem left behind in Fernlund's research on using the Genetic Context Learner (GenCL) to model CxBR agents from observed human performance [Fernlund, 2004]. To accomplish the process of context discovery, this research proposes two contextualization algorithms: Contextualized Fuzzy ART (CFA) and Context Partitioning and Clustering (COPAC). The former is a more naive approach utilizing the well known Fuzzy ART strategy while the latter is a robust algorithm developed on the principles of CxBR. Using Fernlund's original five drivers, the CFA and COPAC algorithms were tested and evaluated on their ability to effectively contextualize each driver's individualized set of behaviors into well-formed and meaningful context bases as well as generating high-fidelity agents through the integration with Fernlund's GenCL algorithm. The resultant set of agents was able to capture and generalized each driver's individualized behaviors.
Show less - Date Issued
- 2009
- Identifier
- CFE0002563, ucf:48253
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0002563
- Title
- Investigating The Relationship Between Adverse Events and Infrastructure Development in an Active War Theater Using Soft Computing Techniques.
- Creator
-
Cakit, Erman, Karwowski, Waldemar, Lee, Gene, Thompson, William, Mikusinski, Piotr, University of Central Florida
- Abstract / Description
-
The military recently recognized the importance of taking sociocultural factors into consideration. Therefore, Human Social Culture Behavior (HSCB) modeling has been getting much attention in current and future operational requirements to successfully understand the effects of social and cultural factors on human behavior. There are different kinds of modeling approaches to the data that are being used in this field and so far none of them has been widely accepted. HSCB modeling needs the...
Show moreThe military recently recognized the importance of taking sociocultural factors into consideration. Therefore, Human Social Culture Behavior (HSCB) modeling has been getting much attention in current and future operational requirements to successfully understand the effects of social and cultural factors on human behavior. There are different kinds of modeling approaches to the data that are being used in this field and so far none of them has been widely accepted. HSCB modeling needs the capability to represent complex, ill-defined, and imprecise concepts, and soft computing modeling can deal with these concepts. There is currently no study on the use of any computational methodology for representing the relationship between adverse events and infrastructure development investments in an active war theater. This study investigates the relationship between adverse events and infrastructure development projects in an active war theater using soft computing techniques including fuzzy inference systems (FIS), artificial neural networks (ANNs), and adaptive neuro-fuzzy inference systems (ANFIS) that directly benefits from their accuracy in prediction applications. Fourteen developmental and economic improvement project types were selected based on allocated budget values and a number of projects at different time periods, urban and rural population density, and total adverse event numbers at previous month selected as independent variables. A total of four outputs reflecting the adverse events in terms of the number of people killed, wounded, hijacked, and total number of adverse events has been estimated. For each model, the data was grouped for training and testing as follows: years between 2004 and 2009 (for training purpose) and year 2010 (for testing). Ninety-six different models were developed and investigated for Afghanistan and the country was divided into seven regions for analysis purposes. Performance of each model was investigated and compared to all other models with the calculated mean absolute error (MAE) values and the prediction accuracy within (&)#177;1 error range (difference between actual and predicted value). Furthermore, sensitivity analysis was performed to determine the effects of input values on dependent variables and to rank the top ten input parameters in order of importance.According to the the results obtained, it was concluded that the ANNs, FIS, and ANFIS are useful modeling techniques for predicting the number of adverse events based on historical development or economic projects' data. When the model accuracy was calculated based on the MAE for each of the models, the ANN had better predictive accuracy than FIS and ANFIS models in general as demonstrated by experimental results. The percentages of prediction accuracy with values found within (&)#177;1 error range around 90%. The sensitivity analysis results show that the importance of economic development projects varies based on the regions, population density, and occurrence of adverse events in Afghanistan. For the purpose of allocating resources and development of regions, the results can be summarized by examining the relationship between adverse events and infrastructure development in an active war theater; emphasis was on predicting the occurrence of events and assessing the potential impact of regional infrastructure development efforts on reducing number of such events.
Show less - Date Issued
- 2013
- Identifier
- CFE0004826, ucf:49757
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004826
- Title
- TOWARD BUILDING A SOCIAL ROBOT WITH AN EMOTION-BASED INTERNAL CONTROL AND EXTERNAL COMMUNICATION TO ENHANCE HUMAN-ROBOT INTERACTION.
- Creator
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Marpaung, Andreas, Lisetti, Christine, University of Central Florida
- Abstract / Description
-
In this thesis, we aim at modeling some aspects of the functional role of emotions on an autonomous embodied agent. We begin by describing our robotic prototype, Cherry--a robot with the task of being a tour guide and an office assistant for the Computer Science Department at the University of Central Florida. Cherry did not have a formal emotion representation of internal states, but did have the ability to express emotions through her multimodal interface. The thesis presents the results of...
Show moreIn this thesis, we aim at modeling some aspects of the functional role of emotions on an autonomous embodied agent. We begin by describing our robotic prototype, Cherry--a robot with the task of being a tour guide and an office assistant for the Computer Science Department at the University of Central Florida. Cherry did not have a formal emotion representation of internal states, but did have the ability to express emotions through her multimodal interface. The thesis presents the results of a survey we performed via our social informatics approach where we found that: (1) the idea of having emotions in a robot was warmly accepted by Cherry's users, and (2) the intended users were pleased with our initial interface design and functionalities. Guided by these results, we transferred our previous code to a human-height and more robust robot--Petra, the PeopleBot--where we began to build a formal emotion mechanism and representation for internal states to correspond to the external expressions of Cherry's interface. We describe our overall three-layered architecture, and propose the design of the sensory motor level (the first layer of the three-layered architecture) inspired by the Multilevel Process Theory of Emotion on one hand, and hybrid robotic architecture on the other hand. The sensory-motor level receives and processes incoming stimuli with fuzzy logic and produces emotion-like states without any further willful planning or learning. We will discuss how Petra has been equipped with sonar and vision for obstacle avoidance as well as vision for face recognition, which are used when she roams around the hallway to engage in social interactions with humans. We hope that the sensory motor level in Petra could serve as a foundation for further works in modeling the three-layered architecture of the Emotion State Generator.
Show less - Date Issued
- 2004
- Identifier
- CFE0000286, ucf:46228
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000286