Learning Based Bidding Strategy for HVAC Systems in Double Auction Retail Energy Markets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Yannan; Somani, Abhishek; Carroll, Thomas E.

In this paper, a bidding strategy is proposed using reinforcement learning for HVAC systems in a double auction market. The bidding strategy does not require a specific model-based representation of behavior, i.e., a functional form to translate indoor house temperatures into bid prices. The results from reinforcement learning based approach are compared with the HVAC bidding approach used in the AEP gridSMART® smart grid demonstration project and it is shown that the model-free (learning based) approach tracks well the results from the model-based behavior. Successful use of model-free approaches to represent device-level economic behavior may help develop similar approaches tomore » represent behavior of more complex devices or groups of diverse devices, such as in a building. Distributed control requires an understanding of decision making processes of intelligent agents so that appropriate mechanisms may be developed to control and coordinate their responses, and model-free approaches to represent behavior will be extremely useful in that quest.« less

Developing a Behavioral Model for Mobile Phone-Based Diabetes Interventions

PubMed Central

Nundy, Shantanu; Dick, Jonathan J.; Solomon, Marla C.; Peek, Monica E.

2013-01-01

Objectives Behavioral models for mobile phone-based diabetes interventions are lacking. This study explores the potential mechanisms by which a text message-based diabetes program affected self-management among African-Americans. Methods We conducted in-depth, individual interviews among 18 African-American patients with type 2 diabetes who completed a 4-week text message-based diabetes program. Each interview was audio- taped, transcribed verbatim, and imported into Atlas.ti software. Coding was done iteratively. Emergent themes were mapped onto existing behavioral constructs and then used to develop a novel behavioral model for mobile phone-based diabetes self-management programs. Results The effects of the text message-based program went beyond automated reminders. The constant, daily communications reduced denial of diabetes and reinforced the importance of self-management (Rosenstock Health Belief Model). Responding positively to questions about self-management increased mastery experience (Bandura Self-Efficacy). Most surprisingly, participants perceived the automated program as a “friend” and “support group” that monitored and supported their self-management behaviors (Barrera Social Support). Conclusions A mobile phone-based diabetes program affected self-management through multiple behavioral constructs including health beliefs, self-efficacy, and social support. Practice implications: Disease management programs that utilize mobile technologies should be designed to leverage existing models of behavior change and can address barriers to self-management associated with health disparities. PMID:23063349

The eHealth Behavior Management Model: a stage-based approach to behavior change and management.

PubMed

Bensley, Robert J; Mercer, Nelda; Brusk, John J; Underhile, Ric; Rivas, Jason; Anderson, Judith; Kelleher, Deanne; Lupella, Melissa; de Jager, André C

2004-10-01

Although the Internet has become an important avenue for disseminating health information, theory-driven strategies for aiding individuals in changing or managing health behaviors are lacking. The eHealth Behavior Management Model combines the Transtheoretical Model, the behavioral intent aspect of the Theory of Planned Behavior, and persuasive communication to assist individuals in negotiating the Web toward stage-specific information. It is here - at the point of stage-specific information - that behavioral intent in moving toward more active stages of change occurs. The eHealth Behavior Management Model is applied in three demonstration projects that focus on behavior management issues: parent-child nutrition education among participants in the U.S. Department of Agriculture Special Supplemental Nutrition Program for Women, Infants and Children; asthma management among university staff and students; and human immunodeficiency virus prevention among South African women. Preliminary results have found the eHealth Behavior Management Model to be promising as a model for Internet-based behavior change programming. Further application and evaluation among other behavior and disease management issues are needed.

Promoting exercise behavior among Chinese youth with hearing loss: a randomized controlled trial based on the transtheoretical model.

PubMed

Si, Qi; Yu, Kehong; Cardinal, Bradley J; Lee, Hyo; Yan, Zi; Loprinzi, Paul D; Li, Fuzhong; Liu, Haiqun

2011-12-01

The transtheoretical model proposes that behavior change is experienced as a series of stages. Interventions tailored to these stages are most likely to be effective in progressing people through the model's hypothesized behavior change continuum. In this study, a stage-tailored, 12-week, exercise behavior intervention based on the transtheoretical model was conducted among a sample of 150 Chinese youth with hearing loss. Participants were randomized into an intervention or control group with all the core transtheoretical model constructs assessed pre- and post-intervention. Participants in the intervention group showed greater advances in their stage of exercise behavior change, decisional balance, and processes of change use compared to those in the control group. The intervention, however, was insufficient for increasing participants' self-efficacy for exercise behavior. The findings partially support the utility of the theory-based intervention for improving the exercise behavior of Chinese youth with hearing loss, while simultaneously helping to identify areas in need of improvement for future applications.

Model-based influences on humans’ choices and striatal prediction errors

PubMed Central

Daw, Nathaniel D.; Gershman, Samuel J.; Seymour, Ben; Dayan, Peter; Dolan, Raymond J.

2011-01-01

Summary The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. PMID:21435563

Prevent-Teach-Reinforce: The School-Based Model of Individualized Positive Behavior Support

ERIC Educational Resources Information Center

Dunlap, Glen; Iovannone, Rose; Kincaid, Donald; Wilson, Kelly; Christiansen, Kathy; Strain, Phillip; English, Carie

2010-01-01

Solve serious behavior challenges in K-8 classrooms with this easy-to-use book, the first practical guide to the research-proven Prevent-Teach-Reinforce (PTR) model. Developed by some of the most respected authorities on positive behavior support, this innovative model gives school-based teams a five-step plan for reducing problems unresolved by…

Predictive representations can link model-based reinforcement learning to model-free mechanisms.

PubMed

Russek, Evan M; Momennejad, Ida; Botvinick, Matthew M; Gershman, Samuel J; Daw, Nathaniel D

2017-09-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

Predictive representations can link model-based reinforcement learning to model-free mechanisms

PubMed Central

Botvinick, Matthew M.

2017-01-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation. PMID:28945743

A Meta-Analysis of Video-Modeling Based Interventions for Reduction of Challenging Behaviors for Students with EBD

ERIC Educational Resources Information Center

Losinski, Mickey; Wiseman, Nicole; White, Sherry A.; Balluch, Felicity

2016-01-01

The current study examined the use of video modeling (VM)-based interventions to reduce the challenging behaviors of students with emotional or behavioral disorders. Each study was evaluated using Council for Exceptional Children's (CEC's) quality indicators for evidence-based practices. In addition, study effects were calculated along the three…

Log-linear model based behavior selection method for artificial fish swarm algorithm.

PubMed

Huang, Zhehuang; Chen, Yidong

2015-01-01

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

Data Sources for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).

Driving-forces model on individual behavior in scenarios considering moving threat agents

NASA Astrophysics Data System (ADS)

Li, Shuying; Zhuang, Jun; Shen, Shifei; Wang, Jia

2017-09-01

The individual behavior model is a contributory factor to improve the accuracy of agent-based simulation in different scenarios. However, few studies have considered moving threat agents, which often occur in terrorist attacks caused by attackers with close-range weapons (e.g., sword, stick). At the same time, many existing behavior models lack validation from cases or experiments. This paper builds a new individual behavior model based on seven behavioral hypotheses. The driving-forces model is an extension of the classical social force model considering scenarios including moving threat agents. An experiment was conducted to validate the key components of the model. Then the model is compared with an advanced Elliptical Specification II social force model, by calculating the fitting errors between the simulated and experimental trajectories, and being applied to simulate a specific circumstance. Our results show that the driving-forces model reduced the fitting error by an average of 33.9% and the standard deviation by an average of 44.5%, which indicates the accuracy and stability of the model in the studied situation. The new driving-forces model could be used to simulate individual behavior when analyzing the risk of specific scenarios using agent-based simulation methods, such as risk analysis of close-range terrorist attacks in public places.

Ventral striatal dopamine reflects behavioral and neural signatures of model-based control during sequential decision making.

PubMed

Deserno, Lorenz; Huys, Quentin J M; Boehme, Rebecca; Buchert, Ralph; Heinze, Hans-Jochen; Grace, Anthony A; Dolan, Raymond J; Heinz, Andreas; Schlagenhauf, Florian

2015-02-03

Dual system theories suggest that behavioral control is parsed between a deliberative "model-based" and a more reflexive "model-free" system. A balance of control exerted by these systems is thought to be related to dopamine neurotransmission. However, in the absence of direct measures of human dopamine, it remains unknown whether this reflects a quantitative relation with dopamine either in the striatum or other brain areas. Using a sequential decision task performed during functional magnetic resonance imaging, combined with striatal measures of dopamine using [(18)F]DOPA positron emission tomography, we show that higher presynaptic ventral striatal dopamine levels were associated with a behavioral bias toward more model-based control. Higher presynaptic dopamine in ventral striatum was associated with greater coding of model-based signatures in lateral prefrontal cortex and diminished coding of model-free prediction errors in ventral striatum. Thus, interindividual variability in ventral striatal presynaptic dopamine reflects a balance in the behavioral expression and the neural signatures of model-free and model-based control. Our data provide a novel perspective on how alterations in presynaptic dopamine levels might be accompanied by a disruption of behavioral control as observed in aging or neuropsychiatric diseases such as schizophrenia and addiction.

Magneto-mechanical modeling of electrical steel sheets

NASA Astrophysics Data System (ADS)

Aydin, U.; Rasilo, P.; Martin, F.; Singh, D.; Daniel, L.; Belahcen, A.; Rekik, M.; Hubert, O.; Kouhia, R.; Arkkio, A.

2017-10-01

A simplified multiscale approach and a Helmholtz free energy based approach for modeling the magneto-mechanical behavior of electrical steel sheets are compared. The models are identified from uniaxial magneto-mechanical measurements of two different electrical steel sheets which show different magneto-elastic behavior. Comparison with the available measurement data of the materials shows that both models successfully model the magneto-mechanical behavior of one of the studied materials, whereas for the second material only the Helmholtz free energy based approach is successful.

Dragon pulse information management system (DPIMS): A unique model-based approach to implementing domain agnostic system of systems and behaviors

NASA Astrophysics Data System (ADS)

Anderson, Thomas S.

2016-05-01

The Global Information Network Architecture is an information technology based on Vector Relational Data Modeling, a unique computational paradigm, DoD network certified by USARMY as the Dragon Pulse Informa- tion Management System. This network available modeling environment for modeling models, where models are configured using domain relevant semantics and use network available systems, sensors, databases and services as loosely coupled component objects and are executable applications. Solutions are based on mission tactics, techniques, and procedures and subject matter input. Three recent ARMY use cases are discussed a) ISR SoS. b) Modeling and simulation behavior validation. c) Networked digital library with behaviors.

Understanding the Effects of Users' Behaviors on Effectiveness of Different Exogenous Regulatory Common Pool Resource Management Institutions

NASA Astrophysics Data System (ADS)

Madani, K.; Dinar, A.

2013-12-01

Tragedy of the commons is generally recognized as one of the possible destinies for common pool resources (CPRs). To avoid the tragedy of the commons and prolonging the life of CPRs, users may show different behavioral characteristics and use different rationales for CPR planning and management. Furthermore, regulators may adopt different strategies for sustainable management of CPRs. The effectiveness of different regulatory exogenous management institutions cannot be evaluated through conventional CPR models since they assume that either users base their behavior on individual rationality and adopt a selfish behavior (Nash behavior), or that the users seek the system's optimal solution without giving priority to their own interests. Therefore, conventional models fail to reliably predict the outcome of CPR problems in which parties may have a range of behavioral characteristics, putting them somewhere in between the two types of behaviors traditionally considered. This work examines the effectiveness of different regulatory exogenous CPR management institutions through a user-based model (as opposed to a system-based model). The new modeling framework allows for consideration of sensitivity of the results to different behavioral characteristics of interacting CPR users. The suggested modeling approach is applied to a benchmark groundwater management problem. Results indicate that some well-known exogenous management institutions (e.g. taxing) are ineffective in sustainable management of CPRs in most cases. Bankruptcy-based management can be helpful, but determination of the fair level of cutbacks remains challenging under this type of institution. Furthermore, some bankruptcy rules such as the Constrained Equal Award (CEA) method are more beneficial to wealthier users, failing to establish social justice. Quota-based and CPR status-based management perform as the most promising and robust regulatory exogenous institutions in prolonging the CPR's life and increasing the long-term benefits to its users.

Multiscale Modeling of Angiogenesis and Predictive Capacity

NASA Astrophysics Data System (ADS)

Pillay, Samara; Byrne, Helen; Maini, Philip

Tumors induce the growth of new blood vessels from existing vasculature through angiogenesis. Using an agent-based approach, we model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death-like processes. We use the transition probabilities associated with the discrete model and a discrete conservation equation for cell occupancy to determine collective cell behavior, in terms of partial differential equations (PDEs). We derive three PDE models incorporating single, multi-species and no volume exclusion. By fitting the parameters in our PDE models and other well-established continuum models to agent-based simulations during a specific time period, and then comparing the outputs from the PDE models and agent-based model at later times, we aim to determine how well the PDE models predict the future behavior of the agent-based model. We also determine whether predictions differ across PDE models and the significance of those differences. This may impact drug development strategies based on PDE models.

Model-based influences on humans' choices and striatal prediction errors.

PubMed

Daw, Nathaniel D; Gershman, Samuel J; Seymour, Ben; Dayan, Peter; Dolan, Raymond J

2011-03-24

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making. Copyright © 2011 Elsevier Inc. All rights reserved.

Modeling of Mixing Behavior in a Combined Blowing Steelmaking Converter with a Filter-Based Euler-Lagrange Model

NASA Astrophysics Data System (ADS)

Li, Mingming; Li, Lin; Li, Qiang; Zou, Zongshu

2018-05-01

A filter-based Euler-Lagrange multiphase flow model is used to study the mixing behavior in a combined blowing steelmaking converter. The Euler-based volume of fluid approach is employed to simulate the top blowing, while the Lagrange-based discrete phase model that embeds the local volume change of rising bubbles for the bottom blowing. A filter-based turbulence method based on the local meshing resolution is proposed aiming to improve the modeling of turbulent eddy viscosities. The model validity is verified through comparison with physical experiments in terms of mixing curves and mixing times. The effects of the bottom gas flow rate on bath flow and mixing behavior are investigated and the inherent reasons for the mixing result are clarified in terms of the characteristics of bottom-blowing plumes, the interaction between plumes and top-blowing jets, and the change of bath flow structure.

Log-Linear Model Based Behavior Selection Method for Artificial Fish Swarm Algorithm

PubMed Central

Huang, Zhehuang; Chen, Yidong

2015-01-01

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm. PMID:25691895

Cyber situation awareness: modeling detection of cyber attacks with instance-based learning theory.

PubMed

Dutt, Varun; Ahn, Young-Suk; Gonzalez, Cleotilde

2013-06-01

To determine the effects of an adversary's behavior on the defender's accurate and timely detection of network threats. Cyber attacks cause major work disruption. It is important to understand how a defender's behavior (experience and tolerance to threats), as well as adversarial behavior (attack strategy), might impact the detection of threats. In this article, we use cognitive modeling to make predictions regarding these factors. Different model types representing a defender, based on Instance-Based Learning Theory (IBLT), faced different adversarial behaviors. A defender's model was defined by experience of threats: threat-prone (90% threats and 10% nonthreats) and nonthreat-prone (10% threats and 90% nonthreats); and different tolerance levels to threats: risk-averse (model declares a cyber attack after perceiving one threat out of eight total) and risk-seeking (model declares a cyber attack after perceiving seven threats out of eight total). Adversarial behavior is simulated by considering different attack strategies: patient (threats occur late) and impatient (threats occur early). For an impatient strategy, risk-averse models with threat-prone experiences show improved detection compared with risk-seeking models with nonthreat-prone experiences; however, the same is not true for a patient strategy. Based upon model predictions, a defender's prior threat experiences and his or her tolerance to threats are likely to predict detection accuracy; but considering the nature of adversarial behavior is also important. Decision-support tools that consider the role of a defender's experience and tolerance to threats along with the nature of adversarial behavior are likely to improve a defender's overall threat detection.

Methodology for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

This model-based approach uses data from both the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) to produce estimates of the prevalence rates of cancer risk factors and screening behaviors at the state, health service area, and county levels.

A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors.

PubMed

Wu, Minglin; Zhang, Sheng; Dong, Yuhan

2016-10-20

In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects.

Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation

NASA Astrophysics Data System (ADS)

Hu, Yao; Quinn, Christopher J.; Cai, Ximing; Garfinkle, Noah W.

2017-11-01

For agent-based modeling, the major challenges in deriving agents' behavioral rules arise from agents' bounded rationality and data scarcity. This study proposes a "gray box" approach to address the challenge by incorporating expert domain knowledge (i.e., human intelligence) with machine learning techniques (i.e., machine intelligence). Specifically, we propose using directed information graph (DIG), boosted regression trees (BRT), and domain knowledge to infer causal factors and identify behavioral rules from data. A case study is conducted to investigate farmers' pumping behavior in the Midwest, U.S.A. Results show that four factors identified by the DIG algorithm- corn price, underlying groundwater level, monthly mean temperature and precipitation- have main causal influences on agents' decisions on monthly groundwater irrigation depth. The agent-based model is then developed based on the behavioral rules represented by three DIGs and modeled by BRTs, and coupled with a physically-based groundwater model to investigate the impacts of agents' pumping behavior on the underlying groundwater system in the context of coupled human and environmental systems.

A Novel Model-Based Driving Behavior Recognition System Using Motion Sensors

PubMed Central

Wu, Minglin; Zhang, Sheng; Dong, Yuhan

2016-01-01

In this article, a novel driving behavior recognition system based on a specific physical model and motion sensory data is developed to promote traffic safety. Based on the theory of rigid body kinematics, we build a specific physical model to reveal the data change rule during the vehicle moving process. In this work, we adopt a nine-axis motion sensor including a three-axis accelerometer, a three-axis gyroscope and a three-axis magnetometer, and apply a Kalman filter for noise elimination and an adaptive time window for data extraction. Based on the feature extraction guided by the built physical model, various classifiers are accomplished to recognize different driving behaviors. Leveraging the system, normal driving behaviors (such as accelerating, braking, lane changing and turning with caution) and aggressive driving behaviors (such as accelerating, braking, lane changing and turning with a sudden) can be classified with a high accuracy of 93.25%. Compared with traditional driving behavior recognition methods using machine learning only, the proposed system possesses a solid theoretical basis, performs better and has good prospects. PMID:27775625

A Simplified Micromechanical Modeling Approach to Predict the Tensile Flow Curve Behavior of Dual-Phase Steels

NASA Astrophysics Data System (ADS)

Nanda, Tarun; Kumar, B. Ravi; Singh, Vishal

2017-11-01

Micromechanical modeling is used to predict material's tensile flow curve behavior based on microstructural characteristics. This research develops a simplified micromechanical modeling approach for predicting flow curve behavior of dual-phase steels. The existing literature reports on two broad approaches for determining tensile flow curve of these steels. The modeling approach developed in this work attempts to overcome specific limitations of the existing two approaches. This approach combines dislocation-based strain-hardening method with rule of mixtures. In the first step of modeling, `dislocation-based strain-hardening method' was employed to predict tensile behavior of individual phases of ferrite and martensite. In the second step, the individual flow curves were combined using `rule of mixtures,' to obtain the composite dual-phase flow behavior. To check accuracy of proposed model, four distinct dual-phase microstructures comprising of different ferrite grain size, martensite fraction, and carbon content in martensite were processed by annealing experiments. The true stress-strain curves for various microstructures were predicted with the newly developed micromechanical model. The results of micromechanical model matched closely with those of actual tensile tests. Thus, this micromechanical modeling approach can be used to predict and optimize the tensile flow behavior of dual-phase steels.

The Dynamics of the Law of Effect: A Comparison of Models

ERIC Educational Resources Information Center

Navakatikyan, Michael A.; Davison, Michael

2010-01-01

Dynamical models based on three steady-state equations for the law of effect were constructed under the assumption that behavior changes in proportion to the difference between current behavior and the equilibrium implied by current reinforcer rates. A comparison of dynamical models showed that a model based on Navakatikyan's (2007) two-component…

Ontology and modeling patterns for state-based behavior representation

NASA Technical Reports Server (NTRS)

Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.;

Event-driven simulation in SELMON: An overview of EDSE

NASA Technical Reports Server (NTRS)

Rouquette, Nicolas F.; Chien, Steve A.; Charest, Leonard, Jr.

1992-01-01

EDSE (event-driven simulation engine), a model-based event-driven simulator implemented for SELMON, a tool for sensor selection and anomaly detection in real-time monitoring is described. The simulator is used in conjunction with a causal model to predict future behavior of the model from observed data. The behavior of the causal model is interpreted as equivalent to the behavior of the physical system being modeled. An overview of the functionality of the simulator and the model-based event-driven simulation paradigm on which it is based is provided. Included are high-level descriptions of the following key properties: event consumption and event creation, iterative simulation, synchronization and filtering of monitoring data from the physical system. Finally, how EDSE stands with respect to the relevant open issues of discrete-event and model-based simulation is discussed.

Preventing skin cancer through behavior change. Implications for interventions.

PubMed

Rossi, J S; Blais, L M; Redding, C A; Weinstock, M A

1995-07-01

Sun exposure is the only major causative factor for skin cancer for which prevention is feasible. Both individual and community-based interventions have been effective in changing sun exposure knowledge and attitudes but generally have not been effective in changing behaviors. An integrative model of behavior change is described that has been successful in changing behavior across a wide range of health conditions. This model holds promise for developing a rational public health approach to skin cancer prevention based on sound behavioral science.

Transition from 'model-based' to 'model-free' behavioral control in addiction: Involvement of the orbitofrontal cortex and dorsolateral striatum.

PubMed

Lucantonio, Federica; Caprioli, Daniele; Schoenbaum, Geoffrey

2014-01-01

Cocaine addiction is a complex and multidimensional process involving a number of behavioral and neural forms of plasticity. The behavioral transition from voluntary drug use to compulsive drug taking may be explained at the neural level by drug-induced changes in function or interaction between a flexible planning system, associated with prefrontal cortical regions, and a rigid habit system, associated with the striatum. The dichotomy between these two systems is operationalized in computational theory by positing model-based and model-free learning mechanisms, the former relying on an "internal model" of the environment and the latter on pre-computed or cached values to control behavior. In this review, we will suggest that model-free and model-based learning mechanisms appear to be differentially affected, at least in the case of psychostimulants such as cocaine, with the former being enhanced while the latter are disrupted. As a result, the behavior of long-term drug users becomes less flexible and responsive to the desirability of expected outcomes and more habitual, based on the long history of reinforcement. To support our specific proposal, we will review recent neural and behavioral evidence on the effect of psychostimulant exposure on orbitofrontal and dorsolateral striatum structure and function. This article is part of a Special Issue entitled 'NIDA 40th Anniversary Issue'. Published by Elsevier Ltd.

A Novel Framework for Characterizing Exposure-Related Behaviors Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence (CSSSA2016)

EPA Science Inventory

Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing o...

Health Blief Model-based intervention to improve nutritional behavior among elderly women.

PubMed

Iranagh, Jamileh Amirzadeh; Rahman, Hejar Abdul; Motalebi, Seyedeh Ameneh

2016-06-01

Nutrition is a determinant factor of health in elderly people. Independent living in elderly people can be maintained or enhanced by improvement of nutritional behavior. Hence, the present study was conducted to determine the impact of Health Belief Model (HBM)-based intervention on the nutritional behavior of elderly women. Cluster-random sampling was used to assess the sample of this clinical trial study. The participants of this study attended a 12-week nutrition education program consisting of two (2) sessions per week. There was also a follow-up for another three (3) months. Smart PLS 3.5 and SPSS 19 were used for structural equation modeling, determination of model fitness, and hypotheses testing. The findings indicate that intervention had a significant effect on knowledge improvement as well as the behavior of elderly women. The model explained 5 to 70% of the variance in nutritional behavior. In addition, nutritional behavior was positively affected by the HBM constructs comprised of perceived susceptibility, self-efficacy, perceived benefits, and barriers after the intervention program. The results of this study show that HBM-based educational intervention has a significant effect in improving nutritional knowledge and behavior among elderly women.

Health behavior change in advance care planning: an agent-based model.

PubMed

Ernecoff, Natalie C; Keane, Christopher R; Albert, Steven M

2016-02-29

A practical and ethical challenge in advance care planning research is controlling and intervening on human behavior. Additionally, observing dynamic changes in advance care planning (ACP) behavior proves difficult, though tracking changes over time is important for intervention development. Agent-based modeling (ABM) allows researchers to integrate complex behavioral data about advance care planning behaviors and thought processes into a controlled environment that is more easily alterable and observable. Literature to date has not addressed how best to motivate individuals, increase facilitators and reduce barriers associated with ACP. We aimed to build an ABM that applies the Transtheoretical Model of behavior change to ACP as a health behavior and accurately reflects: 1) the rates at which individuals complete the process, 2) how individuals respond to barriers, facilitators, and behavioral variables, and 3) the interactions between these variables. We developed a dynamic ABM of the ACP decision making process based on the stages of change posited by the Transtheoretical Model. We integrated barriers, facilitators, and other behavioral variables that agents encounter as they move through the process. We successfully incorporated ACP barriers, facilitators, and other behavioral variables into our ABM, forming a plausible representation of ACP behavior and decision-making. The resulting distributions across the stages of change replicated those found in the literature, with approximately half of participants in the action-maintenance stage in both the model and the literature. Our ABM is a useful method for representing dynamic social and experiential influences on the ACP decision making process. This model suggests structural interventions, e.g. increasing access to ACP materials in primary care clinics, in addition to improved methods of data collection for behavioral studies, e.g. incorporating longitudinal data to capture behavioral dynamics.

A Personal Value-Based Model of College Students' Aptitudes and Expected Choice Behavior Regarding Retailing Careers.

ERIC Educational Resources Information Center

Shim, Soyeon; Warrington, Patti; Goldsberry, Ellen

1999-01-01

A study of 754 retail management students developed a value-based model of career attitude and expected choice behavior. Findings indicate that personal values had an influence on all aspects of retail career attitudes, which then had a direct effect on expected choice behavior. (Contains 55 references.) (Author/JOW)

Understanding Engagement in Dementia Through Behavior. The Ethographic and Laban-Inspired Coding System of Engagement (ELICSE) and the Evidence-Based Model of Engagement-Related Behavior (EMODEB)

PubMed Central

Perugia, Giulia; van Berkel, Roos; Díaz-Boladeras, Marta; Català-Mallofré, Andreu; Rauterberg, Matthias; Barakova, Emilia

2018-01-01

Engagement in activities is of crucial importance for people with dementia. State of the art assessment techniques rely exclusively on behavior observation to measure engagement in dementia. These techniques are either too general to grasp how engagement is naturally expressed through behavior or too complex to be traced back to an overall engagement state. We carried out a longitudinal study to develop a coding system of engagement-related behavior that could tackle these issues and to create an evidence-based model of engagement to make meaning of such a coding system. Fourteen elderlies with mild to moderate dementia took part in the study. They were involved in two activities: a game-based cognitive stimulation and a robot-based free play. The coding system was developed with a mixed approach: ethographic and Laban-inspired. First, we developed two ethograms to describe the behavior of participants in the two activities in detail. Then, we used Laban Movement Analysis (LMA) to identify a common structure to the behaviors in the two ethograms and unify them in a unique coding system. The inter-rater reliability (IRR) of the coding system proved to be excellent for cognitive games (kappa = 0.78) and very good for robot play (kappa = 0.74). From the scoring of the videos, we developed an evidence-based model of engagement. This was based on the most frequent patterns of body part organization (i.e., the way body parts are connected in movement) observed during activities. Each pattern was given a meaning in terms of engagement by making reference to the literature. The model was tested using structural equation modeling (SEM). It achieved an excellent goodness of fit and all the hypothesized relations between variables were significant. We called the coding system that we developed the Ethographic and Laban-Inspired Coding System of Engagement (ELICSE) and the model the Evidence-based Model of Engagement-related Behavior (EMODEB). To the best of our knowledge, the ELICSE and the EMODEB constitute the first formalization of engagement-related behavior for dementia that describes how behavior unfolds over time and what it means in terms of engagement. PMID:29881360

Understanding Engagement in Dementia Through Behavior. The Ethographic and Laban-Inspired Coding System of Engagement (ELICSE) and the Evidence-Based Model of Engagement-Related Behavior (EMODEB).

PubMed

Perugia, Giulia; van Berkel, Roos; Díaz-Boladeras, Marta; Català-Mallofré, Andreu; Rauterberg, Matthias; Barakova, Emilia

2018-01-01

Engagement in activities is of crucial importance for people with dementia. State of the art assessment techniques rely exclusively on behavior observation to measure engagement in dementia. These techniques are either too general to grasp how engagement is naturally expressed through behavior or too complex to be traced back to an overall engagement state. We carried out a longitudinal study to develop a coding system of engagement-related behavior that could tackle these issues and to create an evidence-based model of engagement to make meaning of such a coding system. Fourteen elderlies with mild to moderate dementia took part in the study. They were involved in two activities: a game-based cognitive stimulation and a robot-based free play. The coding system was developed with a mixed approach: ethographic and Laban-inspired. First, we developed two ethograms to describe the behavior of participants in the two activities in detail. Then, we used Laban Movement Analysis (LMA) to identify a common structure to the behaviors in the two ethograms and unify them in a unique coding system. The inter-rater reliability (IRR) of the coding system proved to be excellent for cognitive games (kappa = 0.78) and very good for robot play (kappa = 0.74). From the scoring of the videos, we developed an evidence-based model of engagement. This was based on the most frequent patterns of body part organization (i.e., the way body parts are connected in movement) observed during activities. Each pattern was given a meaning in terms of engagement by making reference to the literature. The model was tested using structural equation modeling (SEM). It achieved an excellent goodness of fit and all the hypothesized relations between variables were significant. We called the coding system that we developed the Ethographic and Laban-Inspired Coding System of Engagement (ELICSE) and the model the Evidence-based Model of Engagement-related Behavior (EMODEB). To the best of our knowledge, the ELICSE and the EMODEB constitute the first formalization of engagement-related behavior for dementia that describes how behavior unfolds over time and what it means in terms of engagement.

Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

Cancer.gov

These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.

Research on manufacturing service behavior modeling based on block chain theory

NASA Astrophysics Data System (ADS)

Zhao, Gang; Zhang, Guangli; Liu, Ming; Yu, Shuqin; Liu, Yali; Zhang, Xu

2018-04-01

According to the attribute characteristics of processing craft, the manufacturing service behavior is divided into service attribute, basic attribute, process attribute, resource attribute. The attribute information model of manufacturing service is established. The manufacturing service behavior information is successfully divided into public and private domain. Additionally, the block chain technology is introduced, and the information model of manufacturing service based on block chain principle is established, which solves the problem of sharing and secreting information of processing behavior, and ensures that data is not tampered with. Based on the key pairing verification relationship, the selective publishing mechanism for manufacturing information is established, achieving the traceability of product data, guarantying the quality of processing quality.

A quantum mechanics-based approach to model incident-induced dynamic driver behavior

NASA Astrophysics Data System (ADS)

Sheu, Jiuh-Biing

2008-08-01

A better understanding of the psychological factors influencing drivers, and the resulting driving behavior responding to incident-induced lane traffic phenomena while passing by an incident site is vital to the improvement of road safety. This paper presents a microscopic driver behavior model to explain the dynamics of the instantaneous driver decision process under lane-blocking incidents on adjacent lanes. The proposed conceptual framework decomposes the corresponding driver decision process into three sequential phases: (1) initial stimulus, (2) glancing-around car-following, and (3) incident-induced driving behavior. The theorem of quantum mechanics in optical flows is applied in the first phase to explain the motion-related perceptual phenomena while vehicles approach the incident site in adjacent lanes, followed by the incorporation of the effect of quantum optical flows in modeling the induced glancing-around car-following behavior in the second phase. Then, an incident-induced driving behavior model is formulated to reproduce the dynamics of driver behavior conducted in the process of passing by an incident site in the adjacent lanes. Numerical results of model tests using video-based incident data indicate the validity of the proposed traffic behavior model in analyzing the incident-induced lane traffic phenomena. It is also expected that such a proposed quantum-mechanics based methodology can throw more light if applied to driver psychology and response in anomalous traffic environments in order to improve road safety.

Covariance-based synaptic plasticity in an attractor network model accounts for fast adaptation in free operant learning.

PubMed

Neiman, Tal; Loewenstein, Yonatan

2013-01-23

In free operant experiments, subjects alternate at will between targets that yield rewards stochastically. Behavior in these experiments is typically characterized by (1) an exponential distribution of stay durations, (2) matching of the relative time spent at a target to its relative share of the total number of rewards, and (3) adaptation after a change in the reward rates that can be very fast. The neural mechanism underlying these regularities is largely unknown. Moreover, current decision-making neural network models typically aim at explaining behavior in discrete-time experiments in which a single decision is made once in every trial, making these models hard to extend to the more natural case of free operant decisions. Here we show that a model based on attractor dynamics, in which transitions are induced by noise and preference is formed via covariance-based synaptic plasticity, can account for the characteristics of behavior in free operant experiments. We compare a specific instance of such a model, in which two recurrently excited populations of neurons compete for higher activity, to the behavior of rats responding on two levers for rewarding brain stimulation on a concurrent variable interval reward schedule (Gallistel et al., 2001). We show that the model is consistent with the rats' behavior, and in particular, with the observed fast adaptation to matching behavior. Further, we show that the neural model can be reduced to a behavioral model, and we use this model to deduce a novel "conservation law," which is consistent with the behavior of the rats.

Enhancing the Behaviorial Fidelity of Synthetic Entities with Human Behavior Models

DTIC Science & Technology

2004-05-05

reflecting the soldier’s extensive training. A civilian’s behavior in the same situation will be determined more by emotions , such as fear, and goals...of intelligent behavior , from path-planning to emotional effects, data on the environment must be gathered from the simulation to serve as sensor...model of decision-making based on emotional utility. AI.Implant takes a composite behavior -based approach to individual and crowd navigation

The EMO-Model: An Agent-Based Model of Primate Social Behavior Regulated by Two Emotional Dimensions, Anxiety-FEAR and Satisfaction-LIKE

PubMed Central

Evers, Ellen; de Vries, Han; Spruijt, Berry M.; Sterck, Elisabeth H. M.

2014-01-01

Agent-based models provide a promising tool to investigate the relationship between individuals’ behavior and emerging group-level patterns. An individual’s behavior may be regulated by its emotional state and its interaction history with specific individuals. Emotional bookkeeping is a candidate mechanism to keep track of received benefits from specific individuals without requiring high cognitive abilities. However, how this mechanism may work is difficult to study in real animals, due to the complexity of primate social life. To explore this theoretically, we introduce an agent-based model, dubbed EMO-model, in which we implemented emotional bookkeeping. In this model the social behaviors of primate-like individuals are regulated by emotional processes along two dimensions. An individual’s emotional state is described by an aversive and a pleasant dimension (anxiety and satisfaction) and by its activating quality (arousal). Social behaviors affect the individuals’ emotional state. To implement emotional bookkeeping, the receiver of grooming assigns an accumulated affiliative attitude (LIKE) to the groomer. Fixed partner-specific agonistic attitudes (FEAR) reflect the stable dominance relations between group members. While the emotional state affects an individual’s general probability of executing certain behaviors, LIKE and FEAR affect the individual’s partner-specific behavioral probabilities. In this way, emotional processes regulate both spontaneous behaviors and appropriate responses to received behaviors, while emotional bookkeeping via LIKE attitudes regulates the development and maintenance of affiliative relations. Using an array of empirical data, the model processes were substantiated and the emerging model patterns were partially validated. The EMO-model offers a framework to investigate the emotional bookkeeping hypothesis theoretically and pinpoints gaps that need to be investigated empirically. PMID:24504194

The EMO-model: an agent-based model of primate social behavior regulated by two emotional dimensions, anxiety-FEAR and satisfaction-LIKE.

PubMed

Evers, Ellen; de Vries, Han; Spruijt, Berry M; Sterck, Elisabeth H M

2014-01-01

Agent-based models provide a promising tool to investigate the relationship between individuals' behavior and emerging group-level patterns. An individual's behavior may be regulated by its emotional state and its interaction history with specific individuals. Emotional bookkeeping is a candidate mechanism to keep track of received benefits from specific individuals without requiring high cognitive abilities. However, how this mechanism may work is difficult to study in real animals, due to the complexity of primate social life. To explore this theoretically, we introduce an agent-based model, dubbed EMO-model, in which we implemented emotional bookkeeping. In this model the social behaviors of primate-like individuals are regulated by emotional processes along two dimensions. An individual's emotional state is described by an aversive and a pleasant dimension (anxiety and satisfaction) and by its activating quality (arousal). Social behaviors affect the individuals' emotional state. To implement emotional bookkeeping, the receiver of grooming assigns an accumulated affiliative attitude (LIKE) to the groomer. Fixed partner-specific agonistic attitudes (FEAR) reflect the stable dominance relations between group members. While the emotional state affects an individual's general probability of executing certain behaviors, LIKE and FEAR affect the individual's partner-specific behavioral probabilities. In this way, emotional processes regulate both spontaneous behaviors and appropriate responses to received behaviors, while emotional bookkeeping via LIKE attitudes regulates the development and maintenance of affiliative relations. Using an array of empirical data, the model processes were substantiated and the emerging model patterns were partially validated. The EMO-model offers a framework to investigate the emotional bookkeeping hypothesis theoretically and pinpoints gaps that need to be investigated empirically.

Predicting Exposure to Consumer-Products Using Agent-Based Models Embedded with Needs-Based Artificial Intelligence and Empirically -Based Scheduling Models

EPA Science Inventory

Information on human behavior and consumer product use is important for characterizing exposures to chemicals in consumer products and in indoor environments. Traditionally, exposure-assessors have relied on time-use surveys to obtain information on exposure-related behavior. In ...

System Behavior Models: A Survey of Approaches

DTIC Science & Technology

2016-06-01

MODELS: A SURVEY OF APPROACHES by Scott R. Ruppel June 2016 Thesis Advisor: Kristin Giammarco Second Reader: John M. Green THIS PAGE...Thesis 4. TITLE AND SUBTITLE SYSTEM BEHAVIOR MODELS: A SURVEY OF APPROACHES 5. FUNDING NUMBERS 6. AUTHOR(S) Scott R. Ruppel 7. PERFORMING...Monterey Phoenix, Petri nets, behavior modeling, model-based systems engineering, modeling approaches, modeling survey 15. NUMBER OF PAGES 85 16

Functional Behavioral Assessment: A School Based Model.

ERIC Educational Resources Information Center

Asmus, Jennifer M.; Vollmer, Timothy R.; Borrero, John C.

2002-01-01

This article begins by discussing requirements for functional behavioral assessment under the Individuals with Disabilities Education Act and then describes a comprehensive model for the application of behavior analysis in the schools. The model includes descriptive assessment, functional analysis, and intervention and involves the participation…

Linking agent-based models and stochastic models of financial markets

PubMed Central

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H. Eugene

2012-01-01

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that “fat” tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting. PMID:22586086

Linking agent-based models and stochastic models of financial markets.

PubMed

Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

2012-05-29

It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

Empathy and Child Neglect: A Theoretical Model

ERIC Educational Resources Information Center

De Paul, Joaquin; Guibert, Maria

2008-01-01

Objective: To present an explanatory theory-based model of child neglect. This model does not address neglectful behaviors of parents with mental retardation, alcohol or drug abuse, or severe mental health problems. In this model parental behavior aimed to satisfy a child's need is considered a helping behavior and, as a consequence, child neglect…

The Effects of Recreation Experience, Environmental Attitude, and Biospheric Value on the Environmentally Responsible Behavior of Nature-Based Tourists

NASA Astrophysics Data System (ADS)

Lee, Tsung Hung; Jan, Fen-Hauh

2015-07-01

The scientific understanding of the recreation experience and the environmentally responsible behavior of nature-based tourists is limited. This study examines the relationship among the recreation experience, environmental attitude, biospheric value, and the general and site-specific environmentally responsible behavior of nature-based tourists in Taomi, Liuqiu Island, and Aowanda and Najenshan in Taiwan. A total of 1342 usable questionnaires were collected for this study. The empirical results indicate that the recreation experience influences biospheric value and environmental attitude; subsequently, it then indirectly influences the general and site-specific environmentally responsible behavior of nature-based tourists. Our theoretical behavioral model elucidates previously proposed but unexamined behavioral models among nature-based tourists, and it offers a theoretical framework for researchers, decision makers, managers, and tourists in the field of nature-based tourism. We conclude that when an individual participates in nature-based tourism as described here, these recreation experiences strengthen their environmental attitude and biospheric value, and consequently increase their engagement in both general and site-specific environmentally responsible behaviors.

The effects of recreation experience, environmental attitude, and biospheric value on the environmentally responsible behavior of nature-based tourists.

PubMed

Lee, Tsung Hung; Jan, Fen-Hauh

2015-07-01

The scientific understanding of the recreation experience and the environmentally responsible behavior of nature-based tourists is limited. This study examines the relationship among the recreation experience, environmental attitude, biospheric value, and the general and site-specific environmentally responsible behavior of nature-based tourists in Taomi, Liuqiu Island, and Aowanda and Najenshan in Taiwan. A total of 1342 usable questionnaires were collected for this study. The empirical results indicate that the recreation experience influences biospheric value and environmental attitude; subsequently, it then indirectly influences the general and site-specific environmentally responsible behavior of nature-based tourists. Our theoretical behavioral model elucidates previously proposed but unexamined behavioral models among nature-based tourists, and it offers a theoretical framework for researchers, decision makers, managers, and tourists in the field of nature-based tourism. We conclude that when an individual participates in nature-based tourism as described here, these recreation experiences strengthen their environmental attitude and biospheric value, and consequently increase their engagement in both general and site-specific environmentally responsible behaviors.

AERIS--applications for the environment : real-time information synthesis state-of-the-practice support : state of the practice scan of behavioral and activity-based models.

DOT National Transportation Integrated Search

2011-06-19

This report has been developed under the Track 1 effort of Phase 1 of the AERIS program and presents the findings of the state-of-the-practice scan of behavioral and activity-based models and their ability to predict traveler choices and behavior in ...

Calibrating cellular automaton models for pedestrians walking through corners

NASA Astrophysics Data System (ADS)

Dias, Charitha; Lovreglio, Ruggiero

2018-05-01

Cellular Automata (CA) based pedestrian simulation models have gained remarkable popularity as they are simpler and easier to implement compared to other microscopic modeling approaches. However, incorporating traditional floor field representations in CA models to simulate pedestrian corner navigation behavior could result in unrealistic behaviors. Even though several previous studies have attempted to enhance CA models to realistically simulate pedestrian maneuvers around bends, such modifications have not been calibrated or validated against empirical data. In this study, two static floor field (SFF) representations, namely 'discrete representation' and 'continuous representation', are calibrated for CA-models to represent pedestrians' walking behavior around 90° bends. Trajectory data collected through a controlled experiment are used to calibrate these model representations. Calibration results indicate that although both floor field representations can represent pedestrians' corner navigation behavior, the 'continuous' representation fits the data better. Output of this study could be beneficial for enhancing the reliability of existing CA-based models by representing pedestrians' corner navigation behaviors more realistically.

[Consumer's psychological processes of hoarding and avoidant purchasing after the Tohoku earthquake].

PubMed

Ohtomo, Shoji; Hirose, Yukio

2014-02-01

This study examined psychological processes of consumers that had determined hoarding and avoidant purchasing behaviors after the Tohoku earthquake within a dual-process model. The model hypothesized that both intentional motivation based on reflective decision and reactive motivation based on non-reflective decision predicted the behaviors. This study assumed that attitude, subjective norm and descriptive norm in relation to hoarding and avoidant purchasing were determinants of motivations. Residents in the Tokyo metropolitan area (n = 667) completed internet longitudinal surveys at three times (April, June, and November, 2011). The results indicated that intentional and reactive motivation determined avoidant purchasing behaviors in June; only intentional motivation determined the behaviors in November. Attitude was a main determinant of the motivations each time. Moreover, previous behaviors predicted future behaviors. In conclusion, purchasing behaviors were intentional rather than reactive behaviors. Furthermore, attitude and previous behaviors were important determinants in the dual-process model. Attitude and behaviors formed in April continued to strengthen the subsequent decisions of purchasing behavior.

Estimating wildfire behavior and effects

Treesearch

Frank A. Albini

1976-01-01

This paper presents a brief survey of the research literature on wildfire behavior and effects and assembles formulae and graphical computation aids based on selected theoretical and empirical models. The uses of mathematical fire behavior models are discussed, and the general capabilities and limitations of currently available models are outlined.

Data Sources for the Model-based Small Area Estimates of Cancer-Related Knowledge - Small Area Estimates

Cancer.gov

The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).

An opinion-driven behavioral dynamics model for addictive behaviors

NASA Astrophysics Data System (ADS)

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; Ambrose, Bridget K.; Brodsky, Nancy S.; Brown, Theresa J.; Husten, Corinne; Glass, Robert J.

2015-04-01

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual's behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters provide targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. This has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.

Models of Individual Dietary Behavior Based on Smartphone Data: The Influence of Routine, Physical Activity, Emotion, and Food Environment.

PubMed

Seto, Edmund; Hua, Jenna; Wu, Lemuel; Shia, Victor; Eom, Sue; Wang, May; Li, Yan

2016-01-01

Smartphone applications (apps) facilitate the collection of data on multiple aspects of behavior that are useful for characterizing baseline patterns and for monitoring progress in interventions aimed at promoting healthier lifestyles. Individual-based models can be used to examine whether behavior, such as diet, corresponds to certain typological patterns. The objectives of this paper are to demonstrate individual-based modeling methods relevant to a person's eating behavior, and the value of such approach compared to typical regression models. Using a mobile app, 2 weeks of physical activity and ecological momentary assessment (EMA) data, and 6 days of diet data were collected from 12 university students recruited from a university in Kunming, a rapidly developing city in southwest China. Phone GPS data were collected for the entire 2-week period, from which exposure to various food environments along each subject's activity space was determined. Physical activity was measured using phone accelerometry. Mobile phone EMA was used to assess self-reported emotion/feelings. The portion size of meals and food groups was determined from voice-annotated videos of meals. Individual-based regression models were used to characterize subjects as following one of 4 diet typologies: those with a routine portion sizes determined by time of day, those with portion sizes that balance physical activity (energy balance), those with portion sizes influenced by emotion, and those with portion sizes associated with food environments. Ample compliance with the phone-based behavioral assessment was observed for all participants. Across all individuals, 868 consumed food items were recorded, with fruits, grains and dairy foods dominating the portion sizes. On average, 218 hours of accelerometry and 35 EMA responses were recorded for each participant. For some subjects, the routine model was able to explain up to 47% of the variation in portion sizes, and the energy balance model was able to explain over 88% of the variation in portion sizes. Across all our subjects, the food environment was an important predictor of eating patterns. Generally, grouping all subjects into a pooled model performed worse than modeling each individual separately. A typological modeling approach was useful in understanding individual dietary behaviors in our cohort. This approach may be applicable to the study of other human behaviors, particularly those that collect repeated measures on individuals, and those involving smartphone-based behavioral measurement.

Evaluating Water Demand Using Agent-Based Modeling

NASA Astrophysics Data System (ADS)

Lowry, T. S.

2004-12-01

The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage based on its own condition and the condition of the world around it. For example, residential agents can make decisions to convert to or from xeriscaping and/or low-flow appliances based on policy implementation, economic status, weather, and climatic conditions. Agricultural agents may vary their usage by making decisions on crop distribution and irrigation design. Preliminary results show that water usage can be highly irrational under certain conditions. Results also identify sub-sectors within each group that have the highest influence on ensemble group behavior, providing a means for policy makers to target their efforts. Finally, the model is able to predict the impact of low-probability, high-impact events such as catastrophic denial of service due to natural and/or man-made events.

A Model to Assess the Behavioral Impacts of Consultative Knowledge Based Systems.

ERIC Educational Resources Information Center

Mak, Brenda; Lyytinen, Kalle

1997-01-01

This research model studies the behavioral impacts of consultative knowledge based systems (KBS). A study of graduate students explored to what extent their decisions were affected by user participation in updating the knowledge base; ambiguity of decision setting; routinization of usage; and source credibility of the expertise embedded in the…

USE OF TRANS-CONTEXTUAL MODEL-BASED PHYSICAL ACTIVITY COURSE IN DEVELOPING LEISURE-TIME PHYSICAL ACTIVITY BEHAVIOR OF UNIVERSITY STUDENTS.

PubMed

Müftüler, Mine; İnce, Mustafa Levent

2015-08-01

This study examined how a physical activity course based on the Trans-Contextual Model affected the variables of perceived autonomy support, autonomous motivation, determinants of leisure-time physical activity behavior, basic psychological needs satisfaction, and leisure-time physical activity behaviors. The participants were 70 Turkish university students (M age=23.3 yr., SD=3.2). A pre-test-post-test control group design was constructed. Initially, the participants were randomly assigned into an experimental (n=35) and a control (n=35) group. The experimental group followed a 12 wk. trans-contextual model-based intervention. The participants were pre- and post-tested in terms of Trans-Contextual Model constructs and of self-reported leisure-time physical activity behaviors. Multivariate analyses showed significant increases over the 12 wk. period for perceived autonomy support from instructor and peers, autonomous motivation in leisure-time physical activity setting, positive intention and perceived behavioral control over leisure-time physical activity behavior, more fulfillment of psychological needs, and more engagement in leisure-time physical activity behavior in the experimental group. These results indicated that the intervention was effective in developing leisure-time physical activity and indicated that the Trans-Contextual Model is a useful way to conceptualize these relationships.

Relationships Between Teacher Aptitudes, Teaching Behaviors, and Pupil Outcomes.

ERIC Educational Resources Information Center

Ekstrom, Ruth B.

A model of elementary school teacher behavior affecting pupil outcomes is presented, and research based upon that model is discussed. A portion of the model, the relationship between teacher aptitudes and knowledge, teaching behavior, and pupil outcomes is focused upon. Aptitudes considered important included verbal and reasoning ability, memory,…

Individual-Level Factors in Colorectal Cancer Screening: A Review of the Literature on the Relation of Individual-Level Health Behavior Constructs and Screening Behavior

PubMed Central

Kiviniemi, Marc T.; Bennett, Alyssa; Zaiter, Marie; Marshall, James R.

2010-01-01

Compliance with colorectal cancer screening recommendations requires considerable conscious effort on the part of the individual patient, making an individual's decisions about engagement in screening an important contributor to compliance or noncompliance. The objective of this paper was to examine the effectiveness of individual-level behavior theories and their associated constructs in accounting for engagement in colorectal cancer screening behavior. We reviewed the literature examining constructs from formal models of individual-level health behavior as factors associated with compliance with screening for colorectal cancer. All published studies examining one or more constructs from the health belief model, theory of planned behavior, transtheoretical model, or social cognitive theory and their relation to screening behavior or behavioral intentions were included in the analysis. By and large, results of studies supported the theory-based predictions for the influence of constructs on cancer screening behavior. However, the evidence base for many of these relations, especially for models other than the health belief model, is quite limited. Suggestions are made for future research on individual-level determinants of colorectal cancer screening. PMID:21954045

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE PAGES

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

2015-10-30

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Emulating a System Dynamics Model with Agent-Based Models: A Methodological Case Study in Simulation of Diabetes Progression

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schryver, Jack; Nutaro, James; Shankar, Mallikarjun

An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. The models are translations of basic elements of an established system dynamics model of diabetes. In this model hierarchy, which mimics diabetes progression over an aggregated U.S. population, was dis-aggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. Moreover, the four estimated models attempted to replicate stock counts representing disease statesmore » in the system dynamics model, while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. In all three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model. The performances of the baseline agent-based model and its extensions illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.« less

Effectiveness Evaluation of Force Protection Training Using Computer-Based Instruction and X3d Simulation

DTIC Science & Technology

2007-09-01

behavior libraries selection box, Savage Tactics behavior sub-folder and hostile behavior sub-folder that contains the behavior that is being assigned to...21) applications. The interface allows users to select models (locations, friendly assets, hostile assets, neutral assets, etc) that will be used in...altitude, etc.) for each model and define their behaviors (friendly patrol craft, hostile explosive-laden vessel, etc). Once the models and their

Empathy and child neglect: a theoretical model.

PubMed

De Paul, Joaquín; Guibert, María

2008-11-01

To present an explanatory theory-based model of child neglect. This model does not address neglectful behaviors of parents with mental retardation, alcohol or drug abuse, or severe mental health problems. In this model parental behavior aimed to satisfy a child's need is considered a helping behavior and, as a consequence, child neglect is considered as a specific type of non-helping behavior. The central hypothesis of the theoretical model presented here suggests that neglectful parents cannot develop the helping response set to care for their children because the observation of a child's signal of need does not lead to the experience of emotions that motivate helping or because the parents experience these emotions, but specific cognitions modify the motivation to help. The present theoretical model suggests that different typologies of neglectful parents could be developed based on different reasons that parents might not to experience emotions that motivate helping behaviors. The model can be helpful to promote new empirical studies about the etiology of different groups of neglectful families.

Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease.

PubMed

Vassena, Eliana; Deraeve, James; Alexander, William H

2017-10-01

Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial PFC (MPFC) and dorsolateral PFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W. H., & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14, 1338-1344, 2011], hierarchical error representation [HER] model [Alexander, W. H., & Brown, J. W. Hierarchical error representation: A computational model of anterior cingulate and dorsolateral prefrontal cortex. Neural Computation, 27, 2354-2410, 2015]). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO model based on hierarchical error prediction, developed to explain MPFC-DLPFC interactions. We derive behavioral predictions that describe how effort and reward information is coded in PFC and how changing the configuration of such environmental information might affect decision-making and task performance involving motivation.

Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

PubMed

Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

2016-01-01

Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

BGen: A UML Behavior Network Generator Tool

NASA Technical Reports Server (NTRS)

Huntsberger, Terry; Reder, Leonard J.; Balian, Harry

2010-01-01

BGen software was designed for autogeneration of code based on a graphical representation of a behavior network used for controlling automatic vehicles. A common format used for describing a behavior network, such as that used in the JPL-developed behavior-based control system, CARACaS ["Control Architecture for Robotic Agent Command and Sensing" (NPO-43635), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 40] includes a graph with sensory inputs flowing through the behaviors in order to generate the signals for the actuators that drive and steer the vehicle. A computer program to translate Unified Modeling Language (UML) Freeform Implementation Diagrams into a legacy C implementation of Behavior Network has been developed in order to simplify the development of C-code for behavior-based control systems. UML is a popular standard developed by the Object Management Group (OMG) to model software architectures graphically. The C implementation of a Behavior Network is functioning as a decision tree.

Pain expressiveness and altruistic behavior: an exploration using agent-based modeling.

PubMed

de C Williams, Amanda C; Gallagher, Elizabeth; Fidalgo, Antonio R; Bentley, Peter J

2016-03-01

Predictions which invoke evolutionary mechanisms are hard to test. Agent-based modeling in artificial life offers a way to simulate behaviors and interactions in specific physical or social environments over many generations. The outcomes have implications for understanding adaptive value of behaviors in context. Pain-related behavior in animals is communicated to other animals that might protect or help, or might exploit or predate. An agent-based model simulated the effects of displaying or not displaying pain (expresser/nonexpresser strategies) when injured and of helping, ignoring, or exploiting another in pain (altruistic/nonaltruistic/selfish strategies). Agents modeled in MATLAB interacted at random while foraging (gaining energy); random injury interrupted foraging for a fixed time unless help from an altruistic agent, who paid an energy cost, speeded recovery. Environmental and social conditions also varied, and each model ran for 10,000 iterations. Findings were meaningful in that, in general, contingencies that evident from experimental work with a variety of mammals, over a few interactions, were replicated in the agent-based model after selection pressure over many generations. More energy-demanding expression of pain reduced its frequency in successive generations, and increasing injury frequency resulted in fewer expressers and altruists. Allowing exploitation of injured agents decreased expression of pain to near zero, but altruists remained. Decreasing costs or increasing benefits of helping hardly changed its frequency, whereas increasing interaction rate between injured agents and helpers diminished the benefits to both. Agent-based modeling allows simulation of complex behaviors and environmental pressures over evolutionary time.

Investigating the role of appearance-based factors in predicting sunbathing and tanning salon use.

PubMed

Joel Hillhouse, Guy Cafri; Thompson, J Kevin; Jacobsen, Paul B; Hillhouse, Joel

2009-12-01

UV exposure via sunbathing and utilization of sun lamps and tanning beds are considered important risk factors for the development of skin cancer. Psychosocial models of UV exposure are often based on theories of health behavior, but theory from the body image field can be useful as well. The current study examines models that prospectively predict sunbathing and indoor tanning behaviors using constructs and interrelationships derived from the tripartite theory of body image, theory of reasoned action, health belief model, revised protection motivation theory, and a proposed integration of several health behavior models. The results generally support a model in which intentions mediate the relationship between appearance attitudes and tanning behaviors, appearance reasons to tan and intentions mediate the relationship between sociocultural influences and tanning behaviors, and appearance reasons not to tan and intentions mediate the role of perceived threat on behaviors. The implications of these findings are considered. © Springer Science+Business Media, LLC 2009

iCrowd: agent-based behavior modeling and crowd simulator

NASA Astrophysics Data System (ADS)

Kountouriotis, Vassilios I.; Paterakis, Manolis; Thomopoulos, Stelios C. A.

2016-05-01

Initially designed in the context of the TASS (Total Airport Security System) FP-7 project, the Crowd Simulation platform developed by the Integrated Systems Lab of the Institute of Informatics and Telecommunications at N.C.S.R. Demokritos, has evolved into a complete domain-independent agent-based behavior simulator with an emphasis on crowd behavior and building evacuation simulation. Under continuous development, it reflects an effort to implement a modern, multithreaded, data-oriented simulation engine employing latest state-of-the-art programming technologies and paradigms. It is based on an extensible architecture that separates core services from the individual layers of agent behavior, offering a concrete simulation kernel designed for high-performance and stability. Its primary goal is to deliver an abstract platform to facilitate implementation of several Agent-Based Simulation solutions with applicability in several domains of knowledge, such as: (i) Crowd behavior simulation during [in/out] door evacuation. (ii) Non-Player Character AI for Game-oriented applications and Gamification activities. (iii) Vessel traffic modeling and simulation for Maritime Security and Surveillance applications. (iv) Urban and Highway Traffic and Transportation Simulations. (v) Social Behavior Simulation and Modeling.

Visual Persons Behavior Diary Generation Model based on Trajectories and Pose Estimation

NASA Astrophysics Data System (ADS)

Gang, Chen; Bin, Chen; Yuming, Liu; Hui, Li

2018-03-01

The behavior pattern of persons was the important output of the surveillance analysis. This paper focus on the generation model of visual person behavior diary. The pipeline includes the person detection, tracking, and the person behavior classify. This paper adopts the deep convolutional neural model YOLO (You Only Look Once)V2 for person detection module. Multi person tracking was based on the detection framework. The Hungarian assignment algorithm was used to the matching. The person appearance model was integrated by HSV color model and Hash code model. The person object motion was estimated by the Kalman Filter. The multi objects were matching with exist tracklets through the appearance and motion location distance by the Hungarian assignment method. A long continuous trajectory for one person was get by the spatial-temporal continual linking algorithm. And the face recognition information was used to identify the trajectory. The trajectories with identification information can be used to generate the visual diary of person behavior based on the scene context information and person action estimation. The relevant modules are tested in public data sets and our own capture video sets. The test results show that the method can be used to generate the visual person behavior pattern diary with certain accuracy.

A hybrid agent-based approach for modeling microbiological systems.

PubMed

Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

2008-11-21

Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

Local Orientation and the Evolution of Foraging: Changes in Decision Making Can Eliminate Evolutionary Trade-offs

PubMed Central

van der Post, Daniel J.; Semmann, Dirk

2011-01-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or “recognize patterns” in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is “staying in patches”. In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape. PMID:21998571

Local orientation and the evolution of foraging: changes in decision making can eliminate evolutionary trade-offs.

PubMed

van der Post, Daniel J; Semmann, Dirk

2011-10-01

Information processing is a major aspect of the evolution of animal behavior. In foraging, responsiveness to local feeding opportunities can generate patterns of behavior which reflect or "recognize patterns" in the environment beyond the perception of individuals. Theory on the evolution of behavior generally neglects such opportunity-based adaptation. Using a spatial individual-based model we study the role of opportunity-based adaptation in the evolution of foraging, and how it depends on local decision making. We compare two model variants which differ in the individual decision making that can evolve (restricted and extended model), and study the evolution of simple foraging behavior in environments where food is distributed either uniformly or in patches. We find that opportunity-based adaptation and the pattern recognition it generates, plays an important role in foraging success, particularly in patchy environments where one of the main challenges is "staying in patches". In the restricted model this is achieved by genetic adaptation of move and search behavior, in light of a trade-off on within- and between-patch behavior. In the extended model this trade-off does not arise because decision making capabilities allow for differentiated behavioral patterns. As a consequence, it becomes possible for properties of movement to be specialized for detection of patches with more food, a larger scale information processing not present in the restricted model. Our results show that changes in decision making abilities can alter what kinds of pattern recognition are possible, eliminate an evolutionary trade-off and change the adaptive landscape.

Personalized query suggestion based on user behavior

NASA Astrophysics Data System (ADS)

Chen, Wanyu; Hao, Zepeng; Shao, Taihua; Chen, Honghui

Query suggestions help users refine their queries after they input an initial query. Previous work mainly concentrated on similarity-based and context-based query suggestion approaches. However, models that focus on adapting to a specific user (personalization) can help to improve the probability of the user being satisfied. In this paper, we propose a personalized query suggestion model based on users’ search behavior (UB model), where we inject relevance between queries and users’ search behavior into a basic probabilistic model. For the relevance between queries, we consider their semantical similarity and co-occurrence which indicates the behavior information from other users in web search. Regarding the current user’s preference to a query, we combine the user’s short-term and long-term search behavior in a linear fashion and deal with the data sparse problem with Bayesian probabilistic matrix factorization (BPMF). In particular, we also investigate the impact of different personalization strategies (the combination of the user’s short-term and long-term search behavior) on the performance of query suggestion reranking. We quantify the improvement of our proposed UB model against a state-of-the-art baseline using the public AOL query logs and show that it beats the baseline in terms of metrics used in query suggestion reranking. The experimental results show that: (i) for personalized ranking, users’ behavioral information helps to improve query suggestion effectiveness; and (ii) given a query, merging information inferred from the short-term and long-term search behavior of a particular user can result in a better performance than both plain approaches.

Explaining reported puma-related behaviors and behavioral intentions among northern Arizona residents

USGS Publications Warehouse

Mattson, David J.; Ruther, Elizabeth J.

2012-01-01

Management of pumas in the American West is typified by conflict among stakeholders plausibly rooted in life experiences and worldviews. We used a mail questionnaire to assess demographics, nature-views, puma-related life experiences and behaviors, and support for puma-related policies among residents of northern Arizona. Data from the questionnaire (n = 693 respondents) were used to model behaviors and support for policies. Compared to models based on nature-views and life experiences, those based on demographics had virtually no support from the data. The Utilitarian/Dominionistic nature-view had the strongest effect of any variable in six of seven models, and was associated with firearms and opposition to policies that would limit killing pumas. The Humanistic/Moralistic nature-view was positively associated with non-lethal behaviors and policies in five models. Gender had the strongest effect of any demographic variable. Compared to demographics alone, our results suggest that worldviews provide a more meaningful explanation of reported human behaviors and behavioral intentions regarding pumas.

Behavioral Informatics and Computational Modeling in Support of Proactive Health Management and Care

PubMed Central

Jimison, Holly B.; Korhonen, Ilkka; Gordon, Christine M.; Saranummi, Niilo

2016-01-01

Health-related behaviors are among the most significant determinants of health and quality of life. Improving health behavior is an effective way to enhance health outcomes and mitigate the escalating challenges arising from an increasingly aging population and the proliferation of chronic diseases. Although it has been difficult to obtain lasting improvements in health behaviors on a wide scale, advances at the intersection of technology and behavioral science may provide the tools to address this challenge. In this paper, we describe a vision and an approach to improve health behavior interventions using the tools of behavioral informatics, an emerging transdisciplinary research domain based on system-theoretic principles in combination with behavioral science and information technology. The field of behavioral informatics has the potential to optimize interventions through monitoring, assessing, and modeling behavior in support of providing tailored and timely interventions. We describe the components of a closed-loop system for health interventions. These components range from fine grain sensor characterizations to individual-based models of behavior change. We provide an example of a research health coaching platform that incorporates a closed-loop intervention based on these multiscale models. Using this early prototype, we illustrate how the optimized and personalized methodology and technology can support self-management and remote care. We note that despite the existing examples of research projects and our platform, significant future research is required to convert this vision to full-scale implementations. PMID:26441408

Verbal Bullying Changes Among Students Following an Educational Intervention Using the Integrated Model for Behavior Change.

PubMed

Naidoo, Saloshni; Satorius, Benn K; de Vries, Hein; Taylor, Myra

2016-11-01

Bullying behavior in schools can lead to psychosocial problems. School-based interventions are important in raising student awareness, developing their skills and in planning to reduce bullying behavior. A randomized controlled trial, using a school-based educational intervention to reduce verbal bullying, was conducted among grade 10 students in 16 urban and rural schools in KwaZulu-Natal, South Africa in 2013. Baseline and postintervention questionnaires, developed using the Integrated Model for Behavior Change theoretical model, were used to assess changes in verbal bullying. Postintervention there were reduced verbal bullying experiences. Improved social norms and awareness of verbal bullying were associated with reduced verbal bullying experiences and behavior. Although less likely to bully others verbally, girls were more likely to experience verbal bullying. Students with no living father were more likely to bully others verbally. The study findings indicate that a school-based intervention can positively impact on verbal bullying experiences and behavior. © 2016, American School Health Association.

Behavioral modeling of VCSELs for high-speed optical interconnects

NASA Astrophysics Data System (ADS)

Szczerba, Krzysztof; Kocot, Chris

2018-02-01

Transition from on-off keying to 4-level pulse amplitude modulation (PAM) in VCSEL based optical interconnects allows for an increase of data rates, at the cost of 4.8 dB sensitivity penalty. The resulting strained link budget creates a need for accurate VCSEL models for driver integrated circuit (IC) design and system level simulations. Rate equation based equivalent circuit models are convenient for the IC design, but system level analysis requires computationally efficient closed form behavioral models based Volterra series and neural networks. In this paper we present and compare these models.

Numerical Modeling of Nonlinear Thermodynamics in SMA Wires

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reynolds, D R; Kloucek, P

We present a mathematical model describing the thermodynamic behavior of shape memory alloy wires, as well as a computational technique to solve the resulting system of partial differential equations. The model consists of conservation equations based on a new Helmholtz free energy potential. The computational technique introduces a viscosity-based continuation method, which allows the model to handle dynamic applications where the temporally local behavior of solutions is desired. Computational experiments document that this combination of modeling and solution techniques appropriately predicts the thermally- and stress-induced martensitic phase transitions, as well as the hysteretic behavior and production of latent heat associatedmore » with such materials.« less

Stress enhances model-free reinforcement learning only after negative outcome

PubMed Central

Lee, Daeyeol

2017-01-01

Previous studies found that stress shifts behavioral control by promoting habits while decreasing goal-directed behaviors during reward-based decision-making. It is, however, unclear how stress disrupts the relative contribution of the two systems controlling reward-seeking behavior, i.e. model-free (or habit) and model-based (or goal-directed). Here, we investigated whether stress biases the contribution of model-free and model-based reinforcement learning processes differently depending on the valence of outcome, and whether stress alters the learning rate, i.e., how quickly information from the new environment is incorporated into choices. Participants were randomly assigned to either a stress or a control condition, and performed a two-stage Markov decision-making task in which the reward probabilities underwent periodic reversals without notice. We found that stress increased the contribution of model-free reinforcement learning only after negative outcome. Furthermore, stress decreased the learning rate. The results suggest that stress diminishes one’s ability to make adaptive choices in multiple aspects of reinforcement learning. This finding has implications for understanding how stress facilitates maladaptive habits, such as addictive behavior, and other dysfunctional behaviors associated with stress in clinical and educational contexts. PMID:28723943

Stress enhances model-free reinforcement learning only after negative outcome.

PubMed

Park, Heyeon; Lee, Daeyeol; Chey, Jeanyung

2017-01-01

Previous studies found that stress shifts behavioral control by promoting habits while decreasing goal-directed behaviors during reward-based decision-making. It is, however, unclear how stress disrupts the relative contribution of the two systems controlling reward-seeking behavior, i.e. model-free (or habit) and model-based (or goal-directed). Here, we investigated whether stress biases the contribution of model-free and model-based reinforcement learning processes differently depending on the valence of outcome, and whether stress alters the learning rate, i.e., how quickly information from the new environment is incorporated into choices. Participants were randomly assigned to either a stress or a control condition, and performed a two-stage Markov decision-making task in which the reward probabilities underwent periodic reversals without notice. We found that stress increased the contribution of model-free reinforcement learning only after negative outcome. Furthermore, stress decreased the learning rate. The results suggest that stress diminishes one's ability to make adaptive choices in multiple aspects of reinforcement learning. This finding has implications for understanding how stress facilitates maladaptive habits, such as addictive behavior, and other dysfunctional behaviors associated with stress in clinical and educational contexts.

Intervention Fidelity in Family-Based Prevention Counseling for Adolescent Problem Behaviors

ERIC Educational Resources Information Center

Hogue, Aaron; Liddle, Howard A.; Singer, Alisa; Leckrone, Jodi

2005-01-01

This study examined fidelity in multidimensional family prevention (MDFP), a family-based prevention counseling model for adolescents at high risk for substance abuse and related behavior problems, in comparison to two empirically based treatments for adolescent drug abuse: multidimensional family therapy (MDFT) and cognitive-behavioral therapy…

Modeling pedestrian shopping behavior using principles of bounded rationality: model comparison and validation

NASA Astrophysics Data System (ADS)

Zhu, Wei; Timmermans, Harry

2011-06-01

Models of geographical choice behavior have been dominantly based on rational choice models, which assume that decision makers are utility-maximizers. Rational choice models may be less appropriate as behavioral models when modeling decisions in complex environments in which decision makers may simplify the decision problem using heuristics. Pedestrian behavior in shopping streets is an example. We therefore propose a modeling framework for pedestrian shopping behavior incorporating principles of bounded rationality. We extend three classical heuristic rules (conjunctive, disjunctive and lexicographic rule) by introducing threshold heterogeneity. The proposed models are implemented using data on pedestrian behavior in Wang Fujing Street, the city center of Beijing, China. The models are estimated and compared with multinomial logit models and mixed logit models. Results show that the heuristic models are the best for all the decisions that are modeled. Validation tests are carried out through multi-agent simulation by comparing simulated spatio-temporal agent behavior with the observed pedestrian behavior. The predictions of heuristic models are slightly better than those of the multinomial logit models.

Physician behavioral adaptability: A model to outstrip a "one size fits all" approach.

PubMed

Carrard, Valérie; Schmid Mast, Marianne

2015-10-01

Based on a literature review, we propose a model of physician behavioral adaptability (PBA) with the goal of inspiring new research. PBA means that the physician adapts his or her behavior according to patients' different preferences. The PBA model shows how physicians infer patients' preferences and adapt their interaction behavior from one patient to the other. We claim that patients will benefit from better outcomes if their physicians show behavioral adaptability rather than a "one size fits all" approach. This literature review is based on a literature search of the PsycINFO(®) and MEDLINE(®) databases. The literature review and first results stemming from the authors' research support the validity and viability of parts of the PBA model. There is evidence suggesting that physicians are able to show behavioral flexibility when interacting with their different patients, that a match between patients' preferences and physician behavior is related to better consultation outcomes, and that physician behavioral adaptability is related to better consultation outcomes. Training of physicians' behavioral flexibility and their ability to infer patients' preferences can facilitate physician behavioral adaptability and positive patient outcomes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Modern Methods for Modeling Change in Obesity Research in Nursing.

PubMed

Sereika, Susan M; Zheng, Yaguang; Hu, Lu; Burke, Lora E

2017-08-01

Persons receiving treatment for weight loss often demonstrate heterogeneity in lifestyle behaviors and health outcomes over time. Traditional repeated measures approaches focus on the estimation and testing of an average temporal pattern, ignoring the interindividual variability about the trajectory. An alternate person-centered approach, group-based trajectory modeling, can be used to identify distinct latent classes of individuals following similar trajectories of behavior or outcome change as a function of age or time and can be expanded to include time-invariant and time-dependent covariates and outcomes. Another latent class method, growth mixture modeling, builds on group-based trajectory modeling to investigate heterogeneity within the distinct trajectory classes. In this applied methodologic study, group-based trajectory modeling for analyzing changes in behaviors or outcomes is described and contrasted with growth mixture modeling. An illustration of group-based trajectory modeling is provided using calorie intake data from a single-group, single-center prospective study for weight loss in adults who are either overweight or obese.

A method for diagnosing time dependent faults using model-based reasoning systems

NASA Technical Reports Server (NTRS)

Goodrich, Charles H.

1995-01-01

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Psychosocial Modeling of Insider Threat Risk Based on Behavioral and Word Use Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greitzer, Frank L.; Kangas, Lars J.; Noonan, Christine F.

In many insider crimes, managers and other coworkers observed that the offenders had exhibited signs of stress, disgruntlement, or other issues, but no alarms were raised. Barriers to using such psychosocial indicators include the inability to recognize the signs and the failure to record the behaviors so that they can be assessed. A psychosocial model was developed to assess an employee’s behavior associated with an increased risk of insider abuse. The model is based on case studies and research literature on factors/correlates associated with precursor behavioral manifestations of individuals committing insider crimes. A complementary Personality Factor modeling approach was developedmore » based on analysis to derive relevant personality characteristics from word use. Several implementations of the psychosocial model were evaluated by comparing their agreement with judgments of human resources and management professionals; the personality factor modeling approach was examined using email samples. If implemented in an operational setting, these models should be part of a set of management tools for employee assessment to identify employees who pose a greater insider threat.« less

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

PubMed Central

Snijders, Tom A.B.; Steglich, Christian E.G.

2014-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of generalized linear statistical models they aim to be realistic detailed representations of network dynamics in empirical data sets. Statistical parallels to micro-macro considerations can be found in the estimation of parameters determining local actor behavior from empirical data, and the assessment of goodness of fit from the correspondence with network-level descriptives. This article studies several network-level consequences of dynamic actor-based models applied to represent cross-sectional network data. Two examples illustrate how network-level characteristics can be obtained as emergent features implied by micro-specifications of actor-based models. PMID:25960578

Prioritizing Conservation of Ungulate Calving Resources in Multiple-Use Landscapes

PubMed Central

Dzialak, Matthew R.; Harju, Seth M.; Osborn, Robert G.; Wondzell, John J.; Hayden-Wing, Larry D.; Winstead, Jeffrey B.; Webb, Stephen L.

2011-01-01

Background Conserving animal populations in places where human activity is increasing is an ongoing challenge in many parts of the world. We investigated how human activity interacted with maternal status and individual variation in behavior to affect reliability of spatially-explicit models intended to guide conservation of critical ungulate calving resources. We studied Rocky Mountain elk (Cervus elaphus) that occupy a region where 2900 natural gas wells have been drilled. Methodology/Principal Findings We present novel applications of generalized additive modeling to predict maternal status based on movement, and of random-effects resource selection models to provide population and individual-based inference on the effects of maternal status and human activity. We used a 2×2 factorial design (treatment vs. control) that included elk that were either parturient or non-parturient and in areas either with or without industrial development. Generalized additive models predicted maternal status (parturiency) correctly 93% of the time based on movement. Human activity played a larger role than maternal status in shaping resource use; elk showed strong spatiotemporal patterns of selection or avoidance and marked individual variation in developed areas, but no such pattern in undeveloped areas. This difference had direct consequences for landscape-level conservation planning. When relative probability of use was calculated across the study area, there was disparity throughout 72–88% of the landscape in terms of where conservation intervention should be prioritized depending on whether models were based on behavior in developed areas or undeveloped areas. Model validation showed that models based on behavior in developed areas had poor predictive accuracy, whereas the model based on behavior in undeveloped areas had high predictive accuracy. Conclusions/Significance By directly testing for differences between developed and undeveloped areas, and by modeling resource selection in a random-effects framework that provided individual-based inference, we conclude that: 1) amplified selection or avoidance behavior and individual variation, as responses to increasing human activity, complicate conservation planning in multiple-use landscapes, and 2) resource selection behavior in places where human activity is predictable or less dynamic may provide a more reliable basis from which to prioritize conservation action. PMID:21297866

Working-memory capacity protects model-based learning from stress.

PubMed

Otto, A Ross; Raio, Candace M; Chiang, Alice; Phelps, Elizabeth A; Daw, Nathaniel D

2013-12-24

Accounts of decision-making have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental advances suggest that this classic distinction between habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning, called model-free and model-based learning. Popular neurocomputational accounts of reward processing emphasize the involvement of the dopaminergic system in model-free learning and prefrontal, central executive-dependent control systems in model-based choice. Here we hypothesized that the hypothalamic-pituitary-adrenal (HPA) axis stress response--believed to have detrimental effects on prefrontal cortex function--should selectively attenuate model-based contributions to behavior. To test this, we paired an acute stressor with a sequential decision-making task that affords distinguishing the relative contributions of the two learning strategies. We assessed baseline working-memory (WM) capacity and used salivary cortisol levels to measure HPA axis stress response. We found that stress response attenuates the contribution of model-based, but not model-free, contributions to behavior. Moreover, stress-induced behavioral changes were modulated by individual WM capacity, such that low-WM-capacity individuals were more susceptible to detrimental stress effects than high-WM-capacity individuals. These results enrich existing accounts of the interplay between acute stress, working memory, and prefrontal function and suggest that executive function may be protective against the deleterious effects of acute stress.

Working-memory capacity protects model-based learning from stress

PubMed Central

Otto, A. Ross; Raio, Candace M.; Chiang, Alice; Phelps, Elizabeth A.; Daw, Nathaniel D.

2013-01-01

Accounts of decision-making have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental advances suggest that this classic distinction between habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning, called model-free and model-based learning. Popular neurocomputational accounts of reward processing emphasize the involvement of the dopaminergic system in model-free learning and prefrontal, central executive–dependent control systems in model-based choice. Here we hypothesized that the hypothalamic-pituitary-adrenal (HPA) axis stress response—believed to have detrimental effects on prefrontal cortex function—should selectively attenuate model-based contributions to behavior. To test this, we paired an acute stressor with a sequential decision-making task that affords distinguishing the relative contributions of the two learning strategies. We assessed baseline working-memory (WM) capacity and used salivary cortisol levels to measure HPA axis stress response. We found that stress response attenuates the contribution of model-based, but not model-free, contributions to behavior. Moreover, stress-induced behavioral changes were modulated by individual WM capacity, such that low-WM-capacity individuals were more susceptible to detrimental stress effects than high-WM-capacity individuals. These results enrich existing accounts of the interplay between acute stress, working memory, and prefrontal function and suggest that executive function may be protective against the deleterious effects of acute stress. PMID:24324166

A New Ductility Exhaustion Model for High Temperature Low Cycle Fatigue Life Prediction of Turbine Disk Alloys

NASA Astrophysics Data System (ADS)

Zhu, Shun-Peng; Huang, Hong-Zhong; Li, Haiqing; Sun, Rui; Zuo, Ming J.

2011-06-01

Based on ductility exhaustion theory and the generalized energy-based damage parameter, a new viscosity-based life prediction model is introduced to account for the mean strain/stress effects in the low cycle fatigue regime. The loading waveform parameters and cyclic hardening effects are also incorporated within this model. It is assumed that damage accrues by means of viscous flow and ductility consumption is only related to plastic strain and creep strain under high temperature low cycle fatigue conditions. In the developed model, dynamic viscosity is used to describe the flow behavior. This model provides a better prediction of Superalloy GH4133's fatigue behavior when compared to Goswami's ductility model and the generalized damage parameter. Under non-zero mean strain conditions, moreover, the proposed model provides more accurate predictions of Superalloy GH4133's fatigue behavior than that with zero mean strains.

Using ontologies to model human navigation behavior in information networks: A study based on Wikipedia.

PubMed

Lamprecht, Daniel; Strohmaier, Markus; Helic, Denis; Nyulas, Csongor; Tudorache, Tania; Noy, Natalya F; Musen, Mark A

The need to examine the behavior of different user groups is a fundamental requirement when building information systems. In this paper, we present Ontology-based Decentralized Search (OBDS), a novel method to model the navigation behavior of users equipped with different types of background knowledge. Ontology-based Decentralized Search combines decentralized search, an established method for navigation in social networks, and ontologies to model navigation behavior in information networks. The method uses ontologies as an explicit representation of background knowledge to inform the navigation process and guide it towards navigation targets. By using different ontologies, users equipped with different types of background knowledge can be represented. We demonstrate our method using four biomedical ontologies and their associated Wikipedia articles. We compare our simulation results with base line approaches and with results obtained from a user study. We find that our method produces click paths that have properties similar to those originating from human navigators. The results suggest that our method can be used to model human navigation behavior in systems that are based on information networks, such as Wikipedia. This paper makes the following contributions: (i) To the best of our knowledge, this is the first work to demonstrate the utility of ontologies in modeling human navigation and (ii) it yields new insights and understanding about the mechanisms of human navigation in information networks.

Using ontologies to model human navigation behavior in information networks: A study based on Wikipedia

PubMed Central

Lamprecht, Daniel; Strohmaier, Markus; Helic, Denis; Nyulas, Csongor; Tudorache, Tania; Noy, Natalya F.; Musen, Mark A.

2015-01-01

The need to examine the behavior of different user groups is a fundamental requirement when building information systems. In this paper, we present Ontology-based Decentralized Search (OBDS), a novel method to model the navigation behavior of users equipped with different types of background knowledge. Ontology-based Decentralized Search combines decentralized search, an established method for navigation in social networks, and ontologies to model navigation behavior in information networks. The method uses ontologies as an explicit representation of background knowledge to inform the navigation process and guide it towards navigation targets. By using different ontologies, users equipped with different types of background knowledge can be represented. We demonstrate our method using four biomedical ontologies and their associated Wikipedia articles. We compare our simulation results with base line approaches and with results obtained from a user study. We find that our method produces click paths that have properties similar to those originating from human navigators. The results suggest that our method can be used to model human navigation behavior in systems that are based on information networks, such as Wikipedia. This paper makes the following contributions: (i) To the best of our knowledge, this is the first work to demonstrate the utility of ontologies in modeling human navigation and (ii) it yields new insights and understanding about the mechanisms of human navigation in information networks. PMID:26568745

Dynamic Simulation of Community Crime and Crime-Reporting Behavior

NASA Astrophysics Data System (ADS)

Yonas, Michael A.; Borrebach, Jeffrey D.; Burke, Jessica G.; Brown, Shawn T.; Philp, Katherine D.; Burke, Donald S.; Grefenstette, John J.

An agent-based model was developed to explore the effectiveness of possible interventions to reduce neighborhood crime and violence. Both offenders and non-offenders (or citizens) were modeled as agents living in neighborhoods, with a set of rules controlling changes in behavior based on individual experience. Offenders may become more or less inclined to actively commit criminal offenses, depending on the behavior of the neighborhood residents and other nearby offenders, and on their arrest experience. In turn, citizens may become more or less inclined to report crimes, based on the observed prevalence of criminal activity within their neighborhood. This paper describes the basic design and dynamics of the model, and how such models might be used to investigate practical crime intervention programs.

Building capacity for cognitive behavioral therapy delivery for depression in disaster-impacted contexts.

PubMed

Ngo, Victoria K; Centanni, Angela; Wong, Eunice; Wennerstrom, Ashley; Miranda, Jeanne

2011-01-01

Numerous challenges exist in implementing evidence-based practices, such as cognitive behavioral therapy, in resource poor, ethnic minority, and/or disaster-affected communities with disparities in mental health. Community-academic participatory partnerships are a promising approach to addressing disparities by implementing community-appropriate, evidence-based depression care. A community-academic collaborative was formed in New Orleans after Hurricane Katrina to expand resources for effective depression care, including cognitive behavioral therapy. In this article, we: 1) describe our model of building capacity to deliver cognitive behavioral therapy for depression in post-disaster community-based settings; 2) discuss the impact of this training program on therapist reported practice; and 3) share lessons learned regarding disseminating and sustaining evidence-based interventions in the context of a disaster impacted community. Using a mixed methods approach, we found that this model was feasible, acceptable, and disseminated knowledge about cognitive behavioral therapy in community settings. Over the course of two years, community providers demonstrated the feasibility of implementing evidence-based practice and potential for local community leadership. The lessons learned from this model of implementation may help address barriers to disseminating evidence-based interventions in other low-resource, disaster-impacted community settings.

A Novel Framework for Characterizing Exposure-Related ...

EPA Pesticide Factsheets

Descriptions of where and how individuals spend their time are important for characterizing exposures to chemicals in consumer products and in indoor environments. Herein we create an agent-based model (ABM) that is able to simulate longitudinal patterns in behaviors. By basing our ABM upon a needs-based artificial intelligence (AI) system, we create agents that mimic human decisions on these exposure-relevant behaviors. In a case study of adults, we use the AI to predict the inter-individual variation in the start time and duration of four behaviors: sleeping, eating, commuting, and working. The results demonstrate that the ABM can capture both inter-individual variation and how decisions on one behavior can affect subsequent behaviors. Preset NERL's research on the use of agent based modeling in exposure assessments. To obtain feed back on the approach from the leading experts in the field.

Identifying prebariatric subtypes based on temperament traits, emotion dysregulation, and disinhibited eating: A latent profile analysis.

PubMed

Schäfer, Lisa; Hübner, Claudia; Carus, Thomas; Herbig, Beate; Seyfried, Florian; Kaiser, Stefan; Schütz, Tatjana; Dietrich, Arne; Hilbert, Anja

2017-10-01

The efficacy of bariatric surgery has been proven; however, a subset of patients fails to achieve expected long-term weight loss postoperatively. As differences in surgery outcome may be influenced by heterogeneous psychological profiles in prebariatric patients, previous subtyping models differentiated patients based on temperament traits. The objective of this study was to expand these models by additionally considering emotion dysregulation and disinhibited eating behaviors for subtyping, as these factors were associated with maladaptive eating behaviors and poor postbariatric weight loss outcome. Within a prospective multicenter registry, N = 370 prebariatric patients were examined using interview and self-report questionnaires. A latent profile analysis was performed to identify subtypes based on temperament traits, emotion dysregulation, and disinhibited eating behaviors. Five prebariatric subtypes were identified with specific profiles regarding self-control, emotion dysregulation, and disinhibited eating behaviors. Subtypes were associated with different levels of eating disorder psychopathology, depression, and quality of life. The expanded model increased variance explanation compared to temperament-based models. By adding emotion dysregulation and disinhibited eating behaviors to previous subtyping models, specific prebariatric subtypes emerged with distinct psychological deficit patterns. Future investigations should test the predictive value of these subtypes for postbariatric weight loss and health-related outcomes. © 2017 Wiley Periodicals, Inc.

From Lévy to Brownian: a computational model based on biological fluctuation.

PubMed

Nurzaman, Surya G; Matsumoto, Yoshio; Nakamura, Yutaka; Shirai, Kazumichi; Koizumi, Satoshi; Ishiguro, Hiroshi

2011-02-03

Theoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior. We extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates. Based on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior.

Does Sedentary Behavior Predict Academic Performance in Adolescents or the Other Way Round? A Longitudinal Path Analysis

PubMed Central

Lizandra, Jorge; Devís-Devís, José; Pérez-Gimeno, Esther; Valencia-Peris, Alexandra; Peiró-Velert, Carmen

2016-01-01

This study examined whether adolescents’ time spent on sedentary behaviors (academic, technological-based and social-based activities) was a better predictor of academic performance than the reverse. A cohort of 755 adolescents participated in a three-year period study. Structural Equation Modeling techniques were used to test plausible causal hypotheses. Four competing models were analyzed to determine which model best fitted the data. The Best Model was separately tested by gender. The Best Model showed that academic performance was a better predictor of sedentary behaviors than the other way round. It also indicated that students who obtained excellent academic results were more likely to succeed academically three years later. Moreover, adolescents who spent more time in the three different types of sedentary behaviors were more likely to engage longer in those sedentary behaviors after the three-year period. The better the adolescents performed academically, the less time they devoted to social-based activities and more to academic activities. An inverse relationship emerged between time dedicated to technological-based activities and academic sedentary activities. A moderating auto-regressive effect by gender indicated that boys were more likely to spend more time on technological-based activities three years later than girls. To conclude, previous academic performance predicts better sedentary behaviors three years later than the reverse. The positive longitudinal auto-regressive effects on the four variables under study reinforce the ‘success breeds success’ hypothesis, with academic performance and social-based activities emerging as the strongest ones. Technological-based activities showed a moderating effect by gender and a negative longitudinal association with academic activities that supports a displacement hypothesis. Other longitudinal and covariate effects reflect the complex relationships among sedentary behaviors and academic performance and the need to explore these relationships in depth. Theoretical and practical implications for school health are outlined. PMID:27055121

Does Sedentary Behavior Predict Academic Performance in Adolescents or the Other Way Round? A Longitudinal Path Analysis.

PubMed

Lizandra, Jorge; Devís-Devís, José; Pérez-Gimeno, Esther; Valencia-Peris, Alexandra; Peiró-Velert, Carmen

2016-01-01

This study examined whether adolescents' time spent on sedentary behaviors (academic, technological-based and social-based activities) was a better predictor of academic performance than the reverse. A cohort of 755 adolescents participated in a three-year period study. Structural Equation Modeling techniques were used to test plausible causal hypotheses. Four competing models were analyzed to determine which model best fitted the data. The Best Model was separately tested by gender. The Best Model showed that academic performance was a better predictor of sedentary behaviors than the other way round. It also indicated that students who obtained excellent academic results were more likely to succeed academically three years later. Moreover, adolescents who spent more time in the three different types of sedentary behaviors were more likely to engage longer in those sedentary behaviors after the three-year period. The better the adolescents performed academically, the less time they devoted to social-based activities and more to academic activities. An inverse relationship emerged between time dedicated to technological-based activities and academic sedentary activities. A moderating auto-regressive effect by gender indicated that boys were more likely to spend more time on technological-based activities three years later than girls. To conclude, previous academic performance predicts better sedentary behaviors three years later than the reverse. The positive longitudinal auto-regressive effects on the four variables under study reinforce the 'success breeds success' hypothesis, with academic performance and social-based activities emerging as the strongest ones. Technological-based activities showed a moderating effect by gender and a negative longitudinal association with academic activities that supports a displacement hypothesis. Other longitudinal and covariate effects reflect the complex relationships among sedentary behaviors and academic performance and the need to explore these relationships in depth. Theoretical and practical implications for school health are outlined.

An opinion-driven behavioral dynamics model for addictive behaviors

DOE PAGES

Moore, Thomas W.; Finley, Patrick D.; Apelberg, Benjamin J.; ...

2015-04-08

We present a model of behavioral dynamics that combines a social network-based opinion dynamics model with behavioral mapping. The behavioral component is discrete and history-dependent to represent situations in which an individual’s behavior is initially driven by opinion and later constrained by physiological or psychological conditions that serve to maintain the behavior. Additionally, individuals are modeled as nodes in a social network connected by directed edges. Parameter sweeps illustrate model behavior and the effects of individual parameters and parameter interactions on model results. Mapping a continuous opinion variable into a discrete behavioral space induces clustering on directed networks. Clusters providemore » targets of opportunity for influencing the network state; however, the smaller the network the greater the stochasticity and potential variability in outcomes. Furthermore, this has implications both for behaviors that are influenced by close relationships verses those influenced by societal norms and for the effectiveness of strategies for influencing those behaviors.« less

Behavior-based network management: a unique model-based approach to implementing cyber superiority

NASA Astrophysics Data System (ADS)

Seng, Jocelyn M.

2016-05-01

Behavior-Based Network Management (BBNM) is a technological and strategic approach to mastering the identification and assessment of network behavior, whether human-driven or machine-generated. Recognizing that all five U.S. Air Force (USAF) mission areas rely on the cyber domain to support, enhance and execute their tasks, BBNM is designed to elevate awareness and improve the ability to better understand the degree of reliance placed upon a digital capability and the operational risk.2 Thus, the objective of BBNM is to provide a holistic view of the digital battle space to better assess the effects of security, monitoring, provisioning, utilization management, allocation to support mission sustainment and change control. Leveraging advances in conceptual modeling made possible by a novel advancement in software design and implementation known as Vector Relational Data Modeling (VRDM™), the BBNM approach entails creating a network simulation in which meaning can be inferred and used to manage network behavior according to policy, such as quickly detecting and countering malicious behavior. Initial research configurations have yielded executable BBNM models as combinations of conceptualized behavior within a network management simulation that includes only concepts of threats and definitions of "good" behavior. A proof of concept assessment called "Lab Rat," was designed to demonstrate the simplicity of network modeling and the ability to perform adaptation. The model was tested on real world threat data and demonstrated adaptive and inferential learning behavior. Preliminary results indicate this is a viable approach towards achieving cyber superiority in today's volatile, uncertain, complex and ambiguous (VUCA) environment.

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of several macro metrics of interest: an epidemic curve, a risk perception curve, and a distribution of different types of coping strategies over time. Our results emphasize the importance of integrating behavioral aspects of decision making under risk into spatial disease ABMs using machine learning algorithms. This is especially relevant when studying cumulative impacts of behavioral changes and possible intervention strategies.

Comparison of Computer Based Instruction to Behavior Skills Training for Teaching Staff Implementation of Discrete-Trial Instruction with an Adult with Autism

ERIC Educational Resources Information Center

Nosik, Melissa R.; Williams, W. Larry; Garrido, Natalia; Lee, Sarah

2013-01-01

In the current study, behavior skills training (BST) is compared to a computer based training package for teaching discrete trial instruction to staff, teaching an adult with autism. The computer based training package consisted of instructions, video modeling and feedback. BST consisted of instructions, modeling, rehearsal and feedback. Following…

Micromechanical modeling of rate-dependent behavior of Connective tissues.

PubMed

Fallah, A; Ahmadian, M T; Firozbakhsh, K; Aghdam, M M

2017-03-07

In this paper, a constitutive and micromechanical model for prediction of rate-dependent behavior of connective tissues (CTs) is presented. Connective tissues are considered as nonlinear viscoelastic material. The rate-dependent behavior of CTs is incorporated into model using the well-known quasi-linear viscoelasticity (QLV) theory. A planar wavy representative volume element (RVE) is considered based on the tissue microstructure histological evidences. The presented model parameters are identified based on the available experiments in the literature. The presented constitutive model introduced to ABAQUS by means of UMAT subroutine. Results show that, monotonic uniaxial test predictions of the presented model at different strain rates for rat tail tendon (RTT) and human patellar tendon (HPT) are in good agreement with experimental data. Results of incremental stress-relaxation test are also presented to investigate both instantaneous and viscoelastic behavior of connective tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Retrospective revaluation in sequential decision making: a tale of two systems.

PubMed

Gershman, Samuel J; Markman, Arthur B; Otto, A Ross

2014-02-01

Recent computational theories of decision making in humans and animals have portrayed 2 systems locked in a battle for control of behavior. One system--variously termed model-free or habitual--favors actions that have previously led to reward, whereas a second--called the model-based or goal-directed system--favors actions that causally lead to reward according to the agent's internal model of the environment. Some evidence suggests that control can be shifted between these systems using neural or behavioral manipulations, but other evidence suggests that the systems are more intertwined than a competitive account would imply. In 4 behavioral experiments, using a retrospective revaluation design and a cognitive load manipulation, we show that human decisions are more consistent with a cooperative architecture in which the model-free system controls behavior, whereas the model-based system trains the model-free system by replaying and simulating experience.

An integrative model of organizational safety behavior.

PubMed

Cui, Lin; Fan, Di; Fu, Gui; Zhu, Cherrie Jiuhua

2013-06-01

This study develops an integrative model of safety management based on social cognitive theory and the total safety culture triadic framework. The purpose of the model is to reveal the causal linkages between a hazardous environment, safety climate, and individual safety behaviors. Based on primary survey data from 209 front-line workers in one of the largest state-owned coal mining corporations in China, the model is tested using structural equation modeling techniques. An employee's perception of a hazardous environment is found to have a statistically significant impact on employee safety behaviors through a psychological process mediated by the perception of management commitment to safety and individual beliefs about safety. The integrative model developed here leads to a comprehensive solution that takes into consideration the environmental, organizational and employees' psychological and behavioral aspects of safety management. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Models of Individual Dietary Behavior Based on Smartphone Data: The Influence of Routine, Physical Activity, Emotion, and Food Environment

PubMed Central

Seto, Edmund; Hua, Jenna; Wu, Lemuel; Shia, Victor; Eom, Sue; Wang, May; Li, Yan

2016-01-01

Introduction Smartphone applications (apps) facilitate the collection of data on multiple aspects of behavior that are useful for characterizing baseline patterns and for monitoring progress in interventions aimed at promoting healthier lifestyles. Individual-based models can be used to examine whether behavior, such as diet, corresponds to certain typological patterns. The objectives of this paper are to demonstrate individual-based modeling methods relevant to a person’s eating behavior, and the value of such approach compared to typical regression models. Method Using a mobile app, 2 weeks of physical activity and ecological momentary assessment (EMA) data, and 6 days of diet data were collected from 12 university students recruited from a university in Kunming, a rapidly developing city in southwest China. Phone GPS data were collected for the entire 2-week period, from which exposure to various food environments along each subject’s activity space was determined. Physical activity was measured using phone accelerometry. Mobile phone EMA was used to assess self-reported emotion/feelings. The portion size of meals and food groups was determined from voice-annotated videos of meals. Individual-based regression models were used to characterize subjects as following one of 4 diet typologies: those with a routine portion sizes determined by time of day, those with portion sizes that balance physical activity (energy balance), those with portion sizes influenced by emotion, and those with portion sizes associated with food environments. Results Ample compliance with the phone-based behavioral assessment was observed for all participants. Across all individuals, 868 consumed food items were recorded, with fruits, grains and dairy foods dominating the portion sizes. On average, 218 hours of accelerometry and 35 EMA responses were recorded for each participant. For some subjects, the routine model was able to explain up to 47% of the variation in portion sizes, and the energy balance model was able to explain over 88% of the variation in portion sizes. Across all our subjects, the food environment was an important predictor of eating patterns. Generally, grouping all subjects into a pooled model performed worse than modeling each individual separately. Conclusion A typological modeling approach was useful in understanding individual dietary behaviors in our cohort. This approach may be applicable to the study of other human behaviors, particularly those that collect repeated measures on individuals, and those involving smartphone-based behavioral measurement. PMID:27049852

On Modeling of Adversary Behavior and Defense for Survivability of Military MANET Applications

DTIC Science & Technology

2015-01-01

anomaly detection technique. b) A system-level majority-voting based intrusion detection system with m being the number of verifiers used to perform...pp. 1254 - 1263. [5] R. Mitchell, and I.R. Chen, “Adaptive Intrusion Detection for Unmanned Aircraft Systems based on Behavior Rule Specification...and adaptively trigger the best attack strategies while avoiding detection and eviction. The second step is to model defense behavior of defenders

Towards a Developmentally Integrative Model of Personality Change: A Focus on Three Potential Mechanisms

PubMed Central

Riley, Elizabeth N.; Peterson, Sarah J.; Smith, Gregory T.

2017-01-01

While the overall stability of personality across the lifespan has been well-documented, one does see incremental changes in a number of personality traits, changes that may impact overall life trajectories in both positive and negative ways. In this chapter, we present a new, developmentally-oriented and integrative model of the factors that might lead to personality change, drawing from the theoretical and empirical work of prior models (e.g. Caspi & Roberts, 2001; Roberts et al., 2005) as well as from our own longitudinal studies of personality change and risky behavior engagement in children, adolescents, and young adults (Boyle et al., 2016; Riley & Smith, 2016; Riley et al., 2016). We focus on change in the trait of urgency, which is a high-risk personality trait that represents the tendency to act rashly when highly emotional. We explore processes of both biologically-based personality change in adolescence, integrating neurocognitive and puberty-based models, as well as behavior-based personality change, in which behaviors and the personality traits underlying those behaviors are incrementally reinforced and shaped over time. One implication of our model for clinical psychology is the apparent presence of a positive feedback loop of risk, in which maladaptive behaviors increase high-risk personality traits, which in turn further increase the likelihood of maladaptive behaviors, a process that continues far beyond the initial experiences of maladaptive behavior engagement. Finally, we examine important future directions for continuing work on personality change, including trauma-based personality change and more directive (e.g., therapeutic) approaches aimed at shaping personality. PMID:29109672

Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding

NASA Astrophysics Data System (ADS)

Kelleher, Christa; McGlynn, Brian; Wagener, Thorsten

2017-07-01

Distributed catchment models are widely used tools for predicting hydrologic behavior. While distributed models require many parameters to describe a system, they are expected to simulate behavior that is more consistent with observed processes. However, obtaining a single set of acceptable parameters can be problematic, as parameter equifinality often results in several behavioral sets that fit observations (typically streamflow). In this study, we investigate the extent to which equifinality impacts a typical distributed modeling application. We outline a hierarchical approach to reduce the number of behavioral sets based on regional, observation-driven, and expert-knowledge-based constraints. For our application, we explore how each of these constraint classes reduced the number of behavioral parameter sets and altered distributions of spatiotemporal simulations, simulating a well-studied headwater catchment, Stringer Creek, Montana, using the distributed hydrology-soil-vegetation model (DHSVM). As a demonstrative exercise, we investigated model performance across 10 000 parameter sets. Constraints on regional signatures, the hydrograph, and two internal measurements of snow water equivalent time series reduced the number of behavioral parameter sets but still left a small number with similar goodness of fit. This subset was ultimately further reduced by incorporating pattern expectations of groundwater table depth across the catchment. Our results suggest that utilizing a hierarchical approach based on regional datasets, observations, and expert knowledge to identify behavioral parameter sets can reduce equifinality and bolster more careful application and simulation of spatiotemporal processes via distributed modeling at the catchment scale.

Peer-to-peer communication, cancer prevention, and the internet

PubMed Central

Ancker, Jessica S.; Carpenter, Kristen M.; Greene, Paul; Hoffmann, Randi; Kukafka, Rita; Marlow, Laura A.V.; Prigerson, Holly G.; Quillin, John M.

2013-01-01

Online communication among patients and consumers through support groups, discussion boards, and knowledge resources is becoming more common. In this paper, we discuss key methods through which such web-based peer-to-peer communication may affect health promotion and disease prevention behavior (exchanges of information, emotional and instrumental support, and establishment of group norms and models). We also discuss several theoretical models for studying online peer communication, including social theory, health communication models, and health behavior models. Although online peer communication about health and disease is very common, research evaluating effects on health behaviors, mediators, and outcomes is still relatively sparse. We suggest that future research in this field should include formative evaluation and studies of effects on mediators of behavior change, behaviors, and outcomes. It will also be important to examine spontaneously emerging peer communication efforts to see how they can be integrated with theory-based efforts initiated by researchers. PMID:19449267

Behavior Analysis in Distance Education: A Systems Approach.

ERIC Educational Resources Information Center

Coldeway, Dan O.

1987-01-01

Describes a model of instructional theory relevant to individualized distance education that is based on Keller's Personalized System of Instruction (PSI), behavior analysis, and the instructional systems development model (ISD). Systems theory is emphasized, and ISD and behavior analysis are discussed as cybernetic processes. (LRW)

Parent-Reported Behavioral and Psychiatric Problems Mediate the Relationship between Sleep-Disordered Breathing and Cognitive Deficits in School-Aged Children.

PubMed

Smith, Dale L; Gozal, David; Hunter, Scott J; Kheirandish-Gozal, Leila

2017-01-01

Numerous studies over the past several decades have illustrated that children who suffer from sleep-disordered breathing (SDB) are at greater risk for cognitive, behavioral, and psychiatric problems. Although behavioral problems have been proposed as a potential mediator between SDB and cognitive functioning, these relationships have not been critically examined. This analysis is based on a community-based cohort of 1,115 children who underwent overnight polysomnography, and cognitive and behavioral phenotyping. Structural model of the relationships between SDB, behavior, and cognition, and two recently developed mediation approaches based on propensity score weighting and resampling were used to assess the mediational role of parent-reported behavior and psychiatric problems in the relationship between SDB and cognitive functioning. Multiple models utilizing two different SDB definitions further explored direct effects of SDB on cognition as well as indirect effects through behavioral pathology. All models were adjusted for age, sex, race, BMI z -score, and asthma status. Indirect effects of SDB through behavior problems were significant in all mediation models, while direct effects of SDB on cognition were not. The findings were consistent across different mediation procedures and remained essentially unaltered when different criteria for SDB, behavior, and cognition were used. Potential effects of SDB on cognitive functioning appear to occur through behavioral problems that are detectable in this pediatric population. Thus, early attentional or behavioral pathology may be implicated in the cognitive functioning deficits associated with SDB, and may present an early morbidity-related susceptibility biomarker.

eSPEM - A SPEM Extension for Enactable Behavior Modeling

NASA Astrophysics Data System (ADS)

Ellner, Ralf; Al-Hilank, Samir; Drexler, Johannes; Jung, Martin; Kips, Detlef; Philippsen, Michael

OMG's SPEM - by means of its (semi-)formal notation - allows for a detailed description of development processes and methodologies, but can only be used for a rather coarse description of their behavior. Concepts for a more fine-grained behavior model are considered out of scope of the SPEM standard and have to be provided by other standards like BPDM/BPMN or UML. However, a coarse granularity of the behavior model often impedes a computer-aided enactment of a process model. Therefore, in this paper we present eSPEM, an extension of SPEM, that is based on the UML meta-model and focused on fine-grained behavior and life-cycle modeling and thereby supports automated enactment of development processes.

Thorough specification of the neurophysiologic processes underlying behavior and of their manifestation in EEG - demonstration with the go/no-go task.

PubMed

Shahaf, Goded; Pratt, Hillel

2013-01-01

In this work we demonstrate the principles of a systematic modeling approach of the neurophysiologic processes underlying a behavioral function. The modeling is based upon a flexible simulation tool, which enables parametric specification of the underlying neurophysiologic characteristics. While the impact of selecting specific parameters is of interest, in this work we focus on the insights, which emerge from rather accepted assumptions regarding neuronal representation. We show that harnessing of even such simple assumptions enables the derivation of significant insights regarding the nature of the neurophysiologic processes underlying behavior. We demonstrate our approach in some detail by modeling the behavioral go/no-go task. We further demonstrate the practical significance of this simplified modeling approach in interpreting experimental data - the manifestation of these processes in the EEG and ERP literature of normal and abnormal (ADHD) function, as well as with comprehensive relevant ERP data analysis. In-fact we show that from the model-based spatiotemporal segregation of the processes, it is possible to derive simple and yet effective and theory-based EEG markers differentiating normal and ADHD subjects. We summarize by claiming that the neurophysiologic processes modeled for the go/no-go task are part of a limited set of neurophysiologic processes which underlie, in a variety of combinations, any behavioral function with measurable operational definition. Such neurophysiologic processes could be sampled directly from EEG on the basis of model-based spatiotemporal segregation.

Alterations in choice behavior by manipulations of world model.

PubMed

Green, C S; Benson, C; Kersten, D; Schrater, P

2010-09-14

How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) "probability matching"-a consistent example of suboptimal choice behavior seen in humans-occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning.

Alterations in choice behavior by manipulations of world model

PubMed Central

Green, C. S.; Benson, C.; Kersten, D.; Schrater, P.

2010-01-01

How to compute initially unknown reward values makes up one of the key problems in reinforcement learning theory, with two basic approaches being used. Model-free algorithms rely on the accumulation of substantial amounts of experience to compute the value of actions, whereas in model-based learning, the agent seeks to learn the generative process for outcomes from which the value of actions can be predicted. Here we show that (i) “probability matching”—a consistent example of suboptimal choice behavior seen in humans—occurs in an optimal Bayesian model-based learner using a max decision rule that is initialized with ecologically plausible, but incorrect beliefs about the generative process for outcomes and (ii) human behavior can be strongly and predictably altered by the presence of cues suggestive of various generative processes, despite statistically identical outcome generation. These results suggest human decision making is rational and model based and not consistent with model-free learning. PMID:20805507

Providing Nutritional Care in the Office Practice: Teams, Tools, and Techniques.

PubMed

Kushner, Robert F

2016-11-01

Provision of dietary counseling in the office setting is enhanced by using team-based care and electronic tools. Effective provider-patient communication is essential for fostering behavior change: the key component of lifestyle medicine. The principles of communication and behavior change are skill-based and grounded in scientific theories and models. Motivational interviewing and shared decision making, a collaboration process between patients and their providers to reach agreement about a health decision, is an important process in counseling. The stages of change, self-determination, health belief model, social cognitive model, theory of planned behavior, and cognitive behavioral therapy are used in the counseling process. Copyright © 2016 Elsevier Inc. All rights reserved.

An Evidence Roadmap for Implementation of Integrated Behavioral Health under the Affordable Care Act

PubMed Central

Kwan, Bethany M.; Valeras, Aimee B.; Levey, Shandra Brown; Nease, Donald E.; Talen, Mary E.

2015-01-01

The Affordable Care Act (ACA) created incentives and opportunities to redesign health care to better address mental and behavioral health needs. The integration of behavioral health and primary care is increasingly viewed as an answer to address such needs, and it is advisable that evidence-based models and interventions be implemented whenever possible with fidelity. At the same time, there are few evidence-based models, especially beyond depression and anxiety, and thus further research and evaluation is needed. Resources being allocated to adoption of models of integrated behavioral health care (IBHC) should include quality improvement, evaluation, and translational research efforts using mixed methodology to enhance the evidence base for IBHC in the context of health care reform. This paper covers six key aspects of the evidence for IBHC, consistent with mental and behavioral health elements of the ACA related to infrastructure, payments, and workforce. The evidence for major IBHC models is summarized, as well as evidence for targeted populations and conditions, education and training, information technology, implementation, and cost and sustainability. PMID:29546130

Anisotropic constitutive modeling for nickel-base single crystal superalloys. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Sheh, Michael Y.

1988-01-01

An anisotropic constitutive model was developed based on crystallographic slip theory for nickel base single crystal superalloys. The constitutive equations developed utilizes drag stress and back stress state variables to model the local inelastic flow. Specially designed experiments were conducted to evaluate the existence of back stress in single crystal superalloy Rene N4 at 982 C. The results suggest that: (1) the back stress is orientation dependent; and (2) the back stress state variable is required for the current model to predict material anelastic recovery behavior. The model was evaluated for its predictive capability on single crystal material behavior including orientation dependent stress-strain response, tension/compression asymmetry, strain rate sensitivity, anelastic recovery behavior, cyclic hardening and softening, stress relaxation, creep and associated crystal lattice rotation. Limitation and future development needs are discussed.

Distributed recurrent neural forward models with synaptic adaptation and CPG-based control for complex behaviors of walking robots

PubMed Central

Dasgupta, Sakyasingha; Goldschmidt, Dennis; Wörgötter, Florentin; Manoonpong, Poramate

2015-01-01

Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal models that are grounded in the overall behavior of the animal. Inspired by these findings, we present here, an artificial bio-inspired walking system which effectively combines biomechanics (in terms of the body and leg structures) with the underlying neural mechanisms. The neural mechanisms consist of (1) central pattern generator based control for generating basic rhythmic patterns and coordinated movements, (2) distributed (at each leg) recurrent neural network based adaptive forward models with efference copies as internal models for sensory predictions and instantaneous state estimations, and (3) searching and elevation control for adapting the movement of an individual leg to deal with different environmental conditions. Using simulations we show that this bio-inspired approach with adaptive internal models allows the walking robot to perform complex locomotive behaviors as observed in insects, including walking on undulated terrains, crossing large gaps, leg damage adaptations, as well as climbing over high obstacles. Furthermore, we demonstrate that the newly developed recurrent network based approach to online forward models outperforms the adaptive neuron forward models, which have hitherto been the state of the art, to model a subset of similar walking behaviors in walking robots. PMID:26441629

Functional Behavioral Assessment-Based Interventions for Students with or at Risk for Emotional and/or Behavioral Disorders in School: A Hierarchical Linear Modeling Meta-Analysis

ERIC Educational Resources Information Center

Gage, Nicholas A.; Lewis, Timothy J.; Stichter, Janine P.

2012-01-01

Of the myriad practices currently utilized for students with disabilities, particularly students with or at risk for emotional and/or behavioral disorder (EBD), functional behavior assessment (FBA) is a practice with an emerging solid research base. However, the FBA research base relies on single-subject design (SSD) and synthesis has relied on…

Behaving Badly or Goodly: Is It Because I Feel Guilty, Shameful, or Sympathetic? Or Is It a Matter of What I Think?

ERIC Educational Resources Information Center

Carlo, Gustavo; McGinley, Meredith; Davis, Alexandra; Streit, Cara

2012-01-01

The article provides a brief review of theory and research on the roles of guilt, shame, and sympathy in predicting moral behaviors. Two models are presented and contrasted. The guilt-based model proposes that guilt and shame jointly predict prosocial and aggressive behaviors. In contrast, the sympathy-based model suggests that perspective taking…

A Model-Based Approach to Engineering Behavior of Complex Aerospace Systems

NASA Technical Reports Server (NTRS)

Ingham, Michel; Day, John; Donahue, Kenneth; Kadesch, Alex; Kennedy, Andrew; Khan, Mohammed Omair; Post, Ethan; Standley, Shaun

2012-01-01

One of the most challenging yet poorly defined aspects of engineering a complex aerospace system is behavior engineering, including definition, specification, design, implementation, and verification and validation of the system's behaviors. This is especially true for behaviors of highly autonomous and intelligent systems. Behavior engineering is more of an art than a science. As a process it is generally ad-hoc, poorly specified, and inconsistently applied from one project to the next. It uses largely informal representations, and results in system behavior being documented in a wide variety of disparate documents. To address this problem, JPL has undertaken a pilot project to apply its institutional capabilities in Model-Based Systems Engineering to the challenge of specifying complex spacecraft system behavior. This paper describes the results of the work in progress on this project. In particular, we discuss our approach to modeling spacecraft behavior including 1) requirements and design flowdown from system-level to subsystem-level, 2) patterns for behavior decomposition, 3) allocation of behaviors to physical elements in the system, and 4) patterns for capturing V&V activities associated with behavioral requirements. We provide examples of interesting behavior specification patterns, and discuss findings from the pilot project.

Mechanisms by which childhood personality traits influence adult health status: educational attainment and healthy behaviors.

PubMed

Hampson, Sarah E; Goldberg, Lewis R; Vogt, Thomas M; Dubanoski, Joan P

2007-01-01

The purpose of this study was to test a life span health behavior model in which educational attainment and health behaviors (eating habits, smoking, and physical activity) were hypothesized as mechanisms to account for relations between teacher ratings of childhood personality traits and self-reported health status at midlife. The model was tested on 1,054 members of the Hawaii Personality and Health cohort, which is a population-based cohort participating in a longitudinal study of personality and health spanning 40 years from childhood to midlife. Childhood Agreeableness, Conscientiousness, and Intellect-Imagination influenced adult health status indirectly through educational attainment, healthy eating habits, and smoking. Several direct effects of childhood traits on health behaviors and health status were also observed. The model extends past associations found between personality traits and health behaviors or health status by identifying a life-course pathway based on the health behavior model through which early childhood traits influence adult health status. The additional direct effects of personality traits indicate that health behavior mechanisms may not provide a complete account of relations between personality and health.

Disruption of model-based behavior and learning by cocaine self-administration in rats.

PubMed

Wied, Heather M; Jones, Joshua L; Cooch, Nisha K; Berg, Benjamin A; Schoenbaum, Geoffrey

2013-10-01

Addiction is characterized by maladaptive decision-making, in which individuals seem unable to use adverse outcomes to modify their behavior. Adverse outcomes are often infrequent, delayed, and even rare events, especially when compared to the reliable rewarding drug-associated outcomes. As a result, recognizing and using information about their occurrence put a premium on the operation of so-called model-based systems of behavioral control, which allow one to mentally simulate outcomes of different courses of action based on knowledge of the underlying associative structure of the environment. This suggests that addiction may reflect, in part, drug-induced dysfunction in these systems. Here, we tested this hypothesis. This study aimed to test whether cocaine causes deficits in model-based behavior and learning independent of requirements for response inhibition or perception of costs or punishment. We trained rats to self-administer sucrose or cocaine for 2 weeks. Four weeks later, the rats began training on a sensory preconditioning and inferred value blocking task. Like devaluation, normal performance on this task requires representations of the underlying task structure; however, unlike devaluation, it does not require either response inhibition or adapting behavior to reflect aversive outcomes. Rats trained to self-administer cocaine failed to show conditioned responding or blocking to the preconditioned cue. These deficits were not observed in sucrose-trained rats nor did they reflect any changes in responding to cues paired directly with reward. These results imply that cocaine disrupts the operation of neural circuits that mediate model-based behavioral control.

Thermomechanical Characterization and Modeling of Superelastic Shape Memory Alloy Beams and Frames

NASA Astrophysics Data System (ADS)

Watkins, Ryan

Of existing applications, the majority of shape memory alloy (SMA) devices consist of beam (orthodontic wire, eye glasses frames, catheter guide wires) and framed structures (cardiovascular stents, vena cava filters). Although uniaxial tension data is often sufficient to model basic beam behavior (which has been the main focus of the research community), the tension-compression asymmetry and complex phase transformation behavior of SMAs suggests more information is necessary to properly model higher complexity states of loading. In this work, SMA beams are experimentally characterized under general loading conditions (including tension, compression, pure bending, and buckling); furthermore, a model is developed with respect to general beam deformation based on the relevant phenomena observed in the experimental characterization. Stress induced phase transformation within superelastic SMA beams is shown to depend on not only the loading mode, but also kinematic constraints imposed by beam geometry (such as beam cross-section and length). In the cases of tension and pure bending, the structural behavior is unstable and corresponds to phase transformation localization and propagation. This unstable behavior is the result of a local level up--down--up stress/strain response in tension, which is measured here using a novel composite-based experimental technique. In addition to unstable phase transformation, intriguing post-buckling straightening is observed in short SMA columns during monotonic loading (termed unbuckling here). Based on this phenomenological understanding of SMA beam behavior, a trilinear based material law is developed in the context of a Shanley column model and is found to capture many of the relevant features of column buckling, including the experimentally observed unbuckling behavior. Due to the success of this model, it is generalized within the context of beam theory and, in conjunction with Bloch wave stability analysis, is used to model and design SMA honeycombs.

From Ideas to Efficacy: The ORBIT Model for Developing Behavioral Treatments for Chronic Diseases

PubMed Central

Czajkowski, Susan M.; Powell, Lynda H.; Adler, Nancy; Naar-King, Sylvie; Reynolds, Kim D.; Hunter, Christine M.; Laraia, Barbara; Olster, Deborah H.; Perna, Frank M.; Peterson, Janey C.; Epel, Elissa; Boyington, Josephine E.; Charlson, Mary E.

2015-01-01

Objective Given the critical role of behavior in preventing and treating chronic diseases, it is important to accelerate the development of behavioral treatments that can improve chronic disease prevention and outcomes. Findings from basic behavioral and social science research hold great promise for addressing behaviorally-based clinical health problems, yet there is currently no established pathway for translating fundamental behavioral science discoveries into health-related treatments ready for Phase III efficacy testing. This article provides a systematic framework for guiding efforts to translate basic behavioral science findings into behavioral treatments for preventing and treating chronic illness. Methods The ORBIT model for behavioral treatment development is described as involving a flexible and progressive process, pre-specified clinically significant milestones for forward movement, and return to earlier stages for refinement and optimization. Results This article presents the background and rationale for the ORBIT model, a summary of key questions for each phase, a selection of study designs and methodologies well-suited to answering these questions, and pre-specified milestones for forward or backward movement across phases. Conclusions The ORBIT model provides a progressive, clinically-relevant approach to increasing the number of evidence-based behavioral treatments available to prevent and treat chronic diseases. PMID:25642841

The Cultures of Contemporary Instructional Design Scholarship, Part One: Developments Based on Behavioral and Cognitive Science Foundations

ERIC Educational Resources Information Center

Willis, Jerry

2011-01-01

This is the first in a series of two articles examining the current status of instructional design (ID) scholarship and theory in four different cultures or traditions. In this article, the focus is on, first, ID models based on traditional behavioral theories of learning and, second, on models based on cognitive science and the learning sciences.…

Effect of Cognitive-Behavioral-Theory-Based Skill Training on Academic Procrastination Behaviors of University Students

ERIC Educational Resources Information Center

Toker, Betül; Avci, Rasit

2015-01-01

This study examined the effectiveness of a cognitive-behavioral theory (CBT) psycho-educational group program on the academic procrastination behaviors of university students and the persistence of any training effect. This was a quasi-experimental research based on an experimental and control group pretest, posttest, and followup test model.…

Cubical Mass-Spring Model design based on a tensile deformation test and nonlinear material model.

PubMed

San-Vicente, Gaizka; Aguinaga, Iker; Tomás Celigüeta, Juan

2012-02-01

Mass-Spring Models (MSMs) are used to simulate the mechanical behavior of deformable bodies such as soft tissues in medical applications. Although they are fast to compute, they lack accuracy and their design remains still a great challenge. The major difficulties in building realistic MSMs lie on the spring stiffness estimation and the topology identification. In this work, the mechanical behavior of MSMs under tensile loads is analyzed before studying the spring stiffness estimation. In particular, the performed qualitative and quantitative analysis of the behavior of cubical MSMs shows that they have a nonlinear response similar to hyperelastic material models. According to this behavior, a new method for spring stiffness estimation valid for linear and nonlinear material models is proposed. This method adjusts the stress-strain and compressibility curves to a given reference behavior. The accuracy of the MSMs designed with this method is tested taking as reference some soft-tissue simulations based on nonlinear Finite Element Method (FEM). The obtained results show that MSMs can be designed to realistically model the behavior of hyperelastic materials such as soft tissues and can become an interesting alternative to other approaches such as nonlinear FEM.

Enhancing emotional-based target prediction

NASA Astrophysics Data System (ADS)

Gosnell, Michael; Woodley, Robert

2008-04-01

This work extends existing agent-based target movement prediction to include key ideas of behavioral inertia, steady states, and catastrophic change from existing psychological, sociological, and mathematical work. Existing target prediction work inherently assumes a single steady state for target behavior, and attempts to classify behavior based on a single emotional state set. The enhanced, emotional-based target prediction maintains up to three distinct steady states, or typical behaviors, based on a target's operating conditions and observed behaviors. Each steady state has an associated behavioral inertia, similar to the standard deviation of behaviors within that state. The enhanced prediction framework also allows steady state transitions through catastrophic change and individual steady states could be used in an offline analysis with additional modeling efforts to better predict anticipated target reactions.

Adolescent brain development in normality and psychopathology

PubMed Central

LUCIANA, MONICA

2014-01-01

Since this journal’s inception, the field of adolescent brain development has flourished, as researchers have investigated the underpinnings of adolescent risk-taking behaviors. Explanations based on translational models initially attributed such behaviors to executive control deficiencies and poor frontal lobe function. This conclusion was bolstered by evidence that the prefrontal cortex and its interconnections are among the last brain regions to structurally and functionally mature. As substantial heterogeneity of prefrontal function was revealed, applications of neuroeconomic theory to adolescent development led to dual systems models of behavior. Current epidemiological trends, behavioral observations, and functional magnetic resonance imaging based brain activity patterns suggest a quadratic increase in limbically mediated incentive motivation from childhood to adolescence and a decline thereafter. This elevation occurs in the context of immature prefrontal function, so motivational strivings may be difficult to regulate. Theoretical models explain this patterning through brain-based accounts of subcortical–cortical integration, puberty-based models of adolescent sensation seeking, and neurochemical dynamics. Empirically sound tests of these mechanisms, as well as investigations of biology–context interactions, represent the field’s most challenging future goals, so that applications to psychopathology can be refined and so that developmental cascades that incorporate neurobiological variables can be modeled. PMID:24342843

Adolescent brain development in normality and psychopathology.

PubMed

Luciana, Monica

2013-11-01

Since this journal's inception, the field of adolescent brain development has flourished, as researchers have investigated the underpinnings of adolescent risk-taking behaviors. Explanations based on translational models initially attributed such behaviors to executive control deficiencies and poor frontal lobe function. This conclusion was bolstered by evidence that the prefrontal cortex and its interconnections are among the last brain regions to structurally and functionally mature. As substantial heterogeneity of prefrontal function was revealed, applications of neuroeconomic theory to adolescent development led to dual systems models of behavior. Current epidemiological trends, behavioral observations, and functional magnetic resonance imaging based brain activity patterns suggest a quadratic increase in limbically mediated incentive motivation from childhood to adolescence and a decline thereafter. This elevation occurs in the context of immature prefrontal function, so motivational strivings may be difficult to regulate. Theoretical models explain this patterning through brain-based accounts of subcortical-cortical integration, puberty-based models of adolescent sensation seeking, and neurochemical dynamics. Empirically sound tests of these mechanisms, as well as investigations of biology-context interactions, represent the field's most challenging future goals, so that applications to psychopathology can be refined and so that developmental cascades that incorporate neurobiological variables can be modeled.

Conditions for the Emergence of Shared Norms in Populations with Incompatible Preferences

PubMed Central

Helbing, Dirk; Yu, Wenjian; Opp, Karl-Dieter; Rauhut, Heiko

2014-01-01

Understanding norms is a key challenge in sociology. Nevertheless, there is a lack of dynamical models explaining how one of several possible behaviors is established as a norm and under what conditions. Analysing an agent-based model, we identify interesting parameter dependencies that imply when two behaviors will coexist or when a shared norm will emerge in a heterogeneous society, where different populations have incompatible preferences. Our model highlights the importance of randomness, spatial interactions, non-linear dynamics, and self-organization. It can also explain the emergence of unpopular norms that do not maximize the collective benefit. Furthermore, we compare behavior-based with preference-based punishment and find interesting results concerning hypocritical punishment. Strikingly, pressuring others to perform the same public behavior as oneself is more effective in promoting norms than pressuring others to meet one’s own private preference. Finally, we show that adaptive group pressure exerted by randomly occuring, local majorities may create norms under conditions where different behaviors would normally coexist. PMID:25166137

A Novel GMM-Based Behavioral Modeling Approach for Smartwatch-Based Driver Authentication.

PubMed

Yang, Ching-Han; Chang, Chin-Chun; Liang, Deron

2018-03-28

All drivers have their own distinct driving habits, and usually hold and operate the steering wheel differently in different driving scenarios. In this study, we proposed a novel Gaussian mixture model (GMM)-based method that can improve the traditional GMM in modeling driving behavior. This new method can be applied to build a better driver authentication system based on the accelerometer and orientation sensor of a smartwatch. To demonstrate the feasibility of the proposed method, we created an experimental system that analyzes driving behavior using the built-in sensors of a smartwatch. The experimental results for driver authentication-an equal error rate (EER) of 4.62% in the simulated environment and an EER of 7.86% in the real-traffic environment-confirm the feasibility of this approach.

Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate themore » importance of modeling decisions that are often overlooked.« less

A conceptual model of nurses' goal orientation, service behavior, and service performance.

PubMed

Chien, Chun-Cheng; Chou, Hsin-Kai; Hung, Shuo-Tsung

2008-01-01

Based on the conceptual framework known as the "service triangle," the authors constructed a model of nurses' goal orientation, service behavior, and service performance to investigate the antecedents and consequences of the medical service behavior provided by nurses. This cross-sectional study collected data from 127 nurses in six hospitals using a mail-in questionnaire. Analysis of the model revealed that the customer-oriented behavior of nurses had a positive influence on organizational citizenship behavior; and both of these behaviors had a significant positive influence on service performance. The results also indicate that a higher learning goal orientation among nurses was associated with the performance of both observable customer-oriented behavior and organizational-citizenship behavior.

Implicit emotion regulation in adolescent girls: An exploratory investigation of Hidden Markov Modeling and its neural correlates.

PubMed

Steele, James S; Bush, Keith; Stowe, Zachary N; James, George A; Smitherman, Sonet; Kilts, Clint D; Cisler, Josh

2018-01-01

Numerous data demonstrate that distracting emotional stimuli cause behavioral slowing (i.e. emotional conflict) and that behavior dynamically adapts to such distractors. However, the cognitive and neural mechanisms that mediate these behavioral findings are poorly understood. Several theoretical models have been developed that attempt to explain these phenomena, but these models have not been directly tested on human behavior nor compared. A potential tool to overcome this limitation is Hidden Markov Modeling (HMM), which is a computational approach to modeling indirectly observed systems. Here, we administered an emotional Stroop task to a sample of healthy adolescent girls (N = 24) during fMRI and used HMM to implement theoretical behavioral models. We then compared the model fits and tested for neural representations of the hidden states of the most supported model. We found that a modified variant of the model posited by Mathews et al. (1998) was most concordant with observed behavior and that brain activity was related to the model-based hidden states. Particularly, while the valences of the stimuli themselves were encoded primarily in the ventral visual cortex, the model-based detection of threatening targets was associated with increased activity in the bilateral anterior insula, while task effort (i.e. adaptation) was associated with reduction in the activity of these areas. These findings suggest that emotional target detection and adaptation are accomplished partly through increases and decreases, respectively, in the perceived immediate relevance of threatening cues and also demonstrate the efficacy of using HMM to apply theoretical models to human behavior.

Implicit emotion regulation in adolescent girls: An exploratory investigation of Hidden Markov Modeling and its neural correlates

PubMed Central

Bush, Keith; Stowe, Zachary N.; James, George A.; Smitherman, Sonet; Kilts, Clint D.; Cisler, Josh

2018-01-01

Numerous data demonstrate that distracting emotional stimuli cause behavioral slowing (i.e. emotional conflict) and that behavior dynamically adapts to such distractors. However, the cognitive and neural mechanisms that mediate these behavioral findings are poorly understood. Several theoretical models have been developed that attempt to explain these phenomena, but these models have not been directly tested on human behavior nor compared. A potential tool to overcome this limitation is Hidden Markov Modeling (HMM), which is a computational approach to modeling indirectly observed systems. Here, we administered an emotional Stroop task to a sample of healthy adolescent girls (N = 24) during fMRI and used HMM to implement theoretical behavioral models. We then compared the model fits and tested for neural representations of the hidden states of the most supported model. We found that a modified variant of the model posited by Mathews et al. (1998) was most concordant with observed behavior and that brain activity was related to the model-based hidden states. Particularly, while the valences of the stimuli themselves were encoded primarily in the ventral visual cortex, the model-based detection of threatening targets was associated with increased activity in the bilateral anterior insula, while task effort (i.e. adaptation) was associated with reduction in the activity of these areas. These findings suggest that emotional target detection and adaptation are accomplished partly through increases and decreases, respectively, in the perceived immediate relevance of threatening cues and also demonstrate the efficacy of using HMM to apply theoretical models to human behavior. PMID:29489856

A motivation-based explanatory model of street drinking among young people.

PubMed

Martín-Santana, Josefa D; Beerli-Palacio, Asunción; Fernández-Monroy, Margarita

2014-01-01

This social marketing study focuses on street drinking behavior among young people. The objective is to divide the market of young people who engage in this activity into segments according to their motivations. For the three segments identified, a behavior model is created using the beliefs, attitudes, behavior, and social belonging of young people who engage in street drinking. The methodology used individual questionnaires filled in by a representative sample of young people. The results show that the behavior model follows the sequence of attitudes-beliefs-behavior and that social belonging influences these three variables. Similarly, differences are observed in the behavior model depending on the segment individuals belong to.

Modeling the Impact of Motivation, Personality, and Emotion on Social Behavior

NASA Astrophysics Data System (ADS)

Miller, Lynn C.; Read, Stephen J.; Zachary, Wayne; Rosoff, Andrew

Models seeking to predict human social behavior must contend with multiple sources of individual and group variability that underlie social behavior. One set of interrelated factors that strongly contribute to that variability - motivations, personality, and emotions - has been only minimally incorporated in previous computational models of social behavior. The Personality, Affect, Culture (PAC) framework is a theory-based computational model that addresses this gap. PAC is used to simulate social agents whose social behavior varies according to their personalities and emotions, which, in turn, vary according to their motivations and underlying motive control parameters. Examples involving disease spread and counter-insurgency operations show how PAC can be used to study behavioral variability in different social contexts.

A Mathematical Model of a Simple Amplifier Using a Ferroelectric Transistor

NASA Technical Reports Server (NTRS)

Sayyah, Rana; Hunt, Mitchell; MacLeod, Todd C.; Ho, Fat D.

2009-01-01

This paper presents a mathematical model characterizing the behavior of a simple amplifier using a FeFET. The model is based on empirical data and incorporates several variables that affect the output, including frequency, load resistance, and gate-to-source voltage. Since the amplifier is the basis of many circuit configurations, a mathematical model that describes the behavior of a FeFET-based amplifier will help in the integration of FeFETs into many other circuits.

Modeling structural, dyadic, and individual factors: the inclusion and exclusion model of HIV related behavior.

PubMed

Albarracin, Dolores; Tannenbaum, Melanie B; Glasman, Laura R; Rothman, Alexander J

2010-12-01

Changing HIV-related behaviors requires addressing the individual, dyadic, and structural influences that shape them. This supplement of AIDS & Behavior presents frameworks that integrate these three influences on behavior. Concepts from these frameworks were selected to model the processes by which structural factors affect individual HIV-related behavior. In the Inclusion/Exclusion Model, material and symbolic inclusions and exclusions (sharing versus denying resources) regulate individuals' ability and motivation to detect, prevent, and treat HIV. Structural interventions create inclusions that increase one's ability or motivation to perform these behaviors or exclusions that hinder one's ability or motivation to execute counterproductive behaviors. The need to expand research regarding multilevel influences on HIV-related behavior is also discussed, particularly concerning further understanding of sustained behavior change and effective dissemination of evidence-based intervention strategies.

Representing Micro-Macro Linkages by Actor-Based Dynamic Network Models

ERIC Educational Resources Information Center

Snijders, Tom A. B.; Steglich, Christian E. G.

2015-01-01

Stochastic actor-based models for network dynamics have the primary aim of statistical inference about processes of network change, but may be regarded as a kind of agent-based models. Similar to many other agent-based models, they are based on local rules for actor behavior. Different from many other agent-based models, by including elements of…

An Examination of a Model of Anti-Pollution Behavior.

ERIC Educational Resources Information Center

Iwata, Osamu

1981-01-01

Reports results of a study in which Japanese female undergraduates (N=118) responded to an environmental concern scale based upon a model of anti-pollution behavior focusing on: approach to information, confidence in science and technology, appreciation of natural beauty, causes, consequences, and purchasing and coping behaviors. (DC)

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

NASA Technical Reports Server (NTRS)

Hall, Gardiner A.; Schuetzle, James; Lavallee, David; Gupta, Uday

1992-01-01

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.

Translational animal models of autism and neurodevelopmental disorders.

PubMed

Crawley, Jacqueline N

2012-09-01

Autism is a neurodevelopmental disorder whose diagnosis is based on three behavioral criteria: unusual reciprocal social interactions, deficits in communication, and stereotyped repetitive behaviors with restricted interests. A large number of de novo single gene mutations and chromosomal deletions are associated with autism spectrum disorders. Based on the strong genetic evidence, mice with targeted mutations in homologous genes have been generated as translational research tools. Mouse models of autism have revealed behavioral and biological outcomes of mutations in risk genes. The field is now poised to employ the most robust phenotypes in the most replicable mouse models for preclinical screening of novel therapeutics.

Mathematical Analysis for Non-reciprocal-interaction-based Model of Collective Behavior

NASA Astrophysics Data System (ADS)

Kano, Takeshi; Osuka, Koichi; Kawakatsu, Toshihiro; Ishiguro, Akio

2017-12-01

In many natural and social systems, collective behaviors emerge as a consequence of non-reciprocal interaction between their constituents. As a first step towards understanding the core principle that underlies these phenomena, we previously proposed a minimal model of collective behavior based on non-reciprocal interactions by drawing inspiration from friendship formation in human society, and demonstrated via simulations that various non-trivial patterns emerge by changing parameters. In this study, a mathematical analysis of the proposed model wherein the system size is small is performed. Through the analysis, the mechanism of the transition between several patterns is elucidated.

Advancing Models and Theories for Digital Behavior Change Interventions.

PubMed

Hekler, Eric B; Michie, Susan; Pavel, Misha; Rivera, Daniel E; Collins, Linda M; Jimison, Holly B; Garnett, Claire; Parral, Skye; Spruijt-Metz, Donna

2016-11-01

To be suitable for informing digital behavior change interventions, theories and models of behavior change need to capture individual variation and changes over time. The aim of this paper is to provide recommendations for development of models and theories that are informed by, and can inform, digital behavior change interventions based on discussions by international experts, including behavioral, computer, and health scientists and engineers. The proposed framework stipulates the use of a state-space representation to define when, where, for whom, and in what state for that person, an intervention will produce a targeted effect. The "state" is that of the individual based on multiple variables that define the "space" when a mechanism of action may produce the effect. A state-space representation can be used to help guide theorizing and identify crossdisciplinary methodologic strategies for improving measurement, experimental design, and analysis that can feasibly match the complexity of real-world behavior change via digital behavior change interventions. Copyright © 2016 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Modeling early sexual initiation among young adolescents using quantum and continuous behavior change methods: implications for HIV prevention.

PubMed

Chen, Xinguang; Lunn, Sonja; Harris, Carole; Li, Xiaoming; Deveaux, Lynette; Marshall, Sharon; Cottrell, Leslie; Stanton, Bonita

2010-10-01

Behavioral research and prevention intervention science efforts have largely been based on hypotheses of linear or rational behavior change. Additional advances in the field may result from the integration of quantum behavior change and catastrophe models. Longitudinal data from a randomized trial for 1241 pre-adolescents 9-12 years old who self-described as virgin were analyzed. Data for 469 virgins in the control group were included for linear and cusp catastrophe models to describe sexual initiation; data for the rest in the intervention group were added for program effect assessment. Self-reported likelihood to have sex was positively associated with actual initiation of sex (OR = 1.72, 95% CI: 1.43-2.06, R² = 0.13). Receipt of a behavioral prevention intervention based on a cognitive model prevented 15.6% (33.0% vs. 48.6%, OR = 0.52, 95% CI: 0.24-1.11) of the participants from initiating sex among only those who reported 'very likely to have sex.' The beta coefficients for the cubic term of the usp assessing three bifurcating variables (planning to have sex, intrinsic rewards from sex and self-efficacy for abstinence) were 0.0726, 0.1116 and 0.1069 respectively; R² varied from 0.49 to 0.54 (p < 0.001 for all). Although an intervention based on a model of continuous behavior change did produce a modest impact on sexual initiation, quantum change has contributed more than continuous change in describing sexual initiation among young adolescents, suggesting the need for quantum change and chaotic models to advance behavioral prevention of HIV/AIDS.

From Lévy to Brownian: A Computational Model Based on Biological Fluctuation

PubMed Central

Nurzaman, Surya G.; Matsumoto, Yoshio; Nakamura, Yutaka; Shirai, Kazumichi; Koizumi, Satoshi; Ishiguro, Hiroshi

2011-01-01

Background Theoretical studies predict that Lévy walks maximizes the chance of encountering randomly distributed targets with a low density, but Brownian walks is favorable inside a patch of targets with high density. Recently, experimental data reports that some animals indeed show a Lévy and Brownian walk movement patterns when forage for foods in areas with low and high density. This paper presents a simple, Gaussian-noise utilizing computational model that can realize such behavior. Methodology/Principal Findings We extend Lévy walks model of one of the simplest creature, Escherichia coli, based on biological fluctuation framework. We build a simulation of a simple, generic animal to observe whether Lévy or Brownian walks will be performed properly depends on the target density, and investigate the emergent behavior in a commonly faced patchy environment where the density alternates. Conclusions/Significance Based on the model, animal behavior of choosing Lévy or Brownian walk movement patterns based on the target density is able to be generated, without changing the essence of the stochastic property in Escherichia coli physiological mechanism as explained by related researches. The emergent behavior and its benefits in a patchy environment are also discussed. The model provides a framework for further investigation on the role of internal noise in realizing adaptive and efficient foraging behavior. PMID:21304911

Engaging communication experts in a Delphi process to identify patient behaviors that could enhance communication in medical encounters

PubMed Central

2010-01-01

Background The communication literature currently focuses primarily on improving physicians' verbal and non-verbal behaviors during the medical interview. The Four Habits Model is a teaching and research framework for physician communication that is based on evidence linking specific communication behaviors with processes and outcomes of care. The Model conceptualizes basic communication tasks as "Habits" and describes the sequence of physician communication behaviors during the clinical encounter associated with improved outcomes. Using the Four Habits Model as a starting point, we asked communication experts to identify the verbal communication behaviors of patients that are important in outpatient encounters. Methods We conducted a 4-round Delphi process with 17 international experts in communication research, medical education, and health care delivery. All rounds were conducted via the internet. In round 1, experts reviewed a list of proposed patient verbal communication behaviors within the Four Habits Model framework. The proposed patient verbal communication behaviors were identified based on a review of the communication literature. The experts could: approve the proposed list; add new behaviors; or modify behaviors. In rounds 2, 3, and 4, they rated each behavior for its fit (agree or disagree) with a particular habit. After each round, we calculated the percent agreement for each behavior and provided these data in the next round. Behaviors receiving more than 70% of experts' votes (either agree or disagree) were considered as achieving consensus. Results Of the 14 originally-proposed patient verbal communication behaviors, the experts modified all but 2, and they added 20 behaviors to the Model in round 1. In round 2, they were presented with 59 behaviors and 14 options to remove specific behaviors for rating. After 3 rounds of rating, the experts retained 22 behaviors. This set included behaviors such as asking questions, expressing preferences, and summarizing information. Conclusion The process identified communication tasks and verbal communication behaviors for patients similar to those outlined for physicians in the Four Habits Model. This represents an important step in building a single model that can be applied to teaching patients and physicians the communication skills associated with improved satisfaction and positive outcomes of care. PMID:20403173

Supply based on demand dynamical model

NASA Astrophysics Data System (ADS)

Levi, Asaf; Sabuco, Juan; Sanjuán, Miguel A. F.

2018-04-01

We propose and numerically analyze a simple dynamical model that describes the firm behaviors under uncertainty of demand. Iterating this simple model and varying some parameter values, we observe a wide variety of market dynamics such as equilibria, periodic, and chaotic behaviors. Interestingly, the model is also able to reproduce market collapses.

Parameter estimation of a nonlinear Burger's model using nanoindentation and finite element-based inverse analysis

NASA Astrophysics Data System (ADS)

Hamim, Salah Uddin Ahmed

Nanoindentation involves probing a hard diamond tip into a material, where the load and the displacement experienced by the tip is recorded continuously. This load-displacement data is a direct function of material's innate stress-strain behavior. Thus, theoretically it is possible to extract mechanical properties of a material through nanoindentation. However, due to various nonlinearities associated with nanoindentation the process of interpreting load-displacement data into material properties is difficult. Although, simple elastic behavior can be characterized easily, a method to characterize complicated material behavior such as nonlinear viscoelasticity is still lacking. In this study, a nanoindentation-based material characterization technique is developed to characterize soft materials exhibiting nonlinear viscoelasticity. Nanoindentation experiment was modeled in finite element analysis software (ABAQUS), where a nonlinear viscoelastic behavior was incorporated using user-defined subroutine (UMAT). The model parameters were calibrated using a process called inverse analysis. In this study, a surrogate model-based approach was used for the inverse analysis. The different factors affecting the surrogate model performance are analyzed in order to optimize the performance with respect to the computational cost.

SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

PubMed

Pauli, Benjamin P; McCann, Nicholas P; Zollner, Patrick A; Cummings, Robert; Gilbert, Jonathan H; Gustafson, Eric J

2013-01-01

Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH's capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of SEARCH for a variety of applications and illustrate benefits it can provide for conservation planning.

In silico and in vitro methods to optimize the performance of experimental gastroretentive floating mini-tablets.

PubMed

Eberle, Veronika A; Häring, Armella; Schoelkopf, Joachim; Gane, Patrick A C; Huwyler, Jörg; Puchkov, Maxim

2016-01-01

Development of floating drug delivery systems (FDDS) is challenging. To facilitate this task, an evaluation method was proposed, which allows for a combined investigation of drug release and flotation. It was the aim of the study to use functionalized calcium carbonate (FCC)-based lipophilic mini-tablet formulations as a model system to design FDDS with a floating behavior characterized by no floating lag time, prolonged flotation and loss of floating capability after complete drug release. Release of the model drug caffeine from the mini-tablets was assessed in vitro by a custom-built stomach model. A cellular automata-based model was used to simulate tablet dissolution. Based on the in silico data, floating forces were calculated and analyzed as a function of caffeine release. Two floating behaviors were identified for mini-tablets: linear decrease of the floating force and maintaining of the floating capability until complete caffeine release. An optimal mini-tablet formulation with desired drug release time and floating behavior was developed and tested. A classification system for a range of varied floating behavior of FDDS was proposed. The FCC-based mini-tablets had an ideal floating behavior: duration of flotation is defined and floating capability decreases after completion of drug release.

From Occasional Choices to Inevitable Musts: A Computational Model of Nicotine Addiction

PubMed Central

Metin, Selin; Sengor, N. Serap

2012-01-01

Although, there are considerable works on the neural mechanisms of reward-based learning and decision making, and most of them mention that addiction can be explained by malfunctioning in these cognitive processes, there are very few computational models. This paper focuses on nicotine addiction, and a computational model for nicotine addiction is proposed based on the neurophysiological basis of addiction. The model compromises different levels ranging from molecular basis to systems level, and it demonstrates three different possible behavioral patterns which are addict, nonaddict, and indecisive. The dynamical behavior of the proposed model is investigated with tools used in analyzing nonlinear dynamical systems, and the relation between the behavioral patterns and the dynamics of the system is discussed. PMID:23251144

Guided by Theory, Informed by Practice: Training and Support for the Good Behavior Game, a Classroom-based Behavior Management Strategy

PubMed Central

Poduska, Jeanne M.; Kurki, Anja

2015-01-01

Moving evidence-based practices for classroom behavior management into real-world settings is a high priority for education and public health. This paper describes the development and use of a model of training and support for the Good Behavior Game (GBG), one of the few preventive interventions shown to have positive outcomes for elementary school children lasting through to young adulthood, ages 19–21, including reductions in the use of drugs and alcohol, school-based mental health services, and suicide ideation and attempts. We first describe the conceptual framework guiding the development of the model of training and support. Data on implementation of the model, from an ongoing trial of GBG being conducted in partnership with the Houston Independent School District, are then presented. We end with a discussion of the lessons learned and the implications for the next stage of research and practice. PMID:26236144

A multi-stakeholder framework for sustainable energy behavior: A multidisciplinary systems study

NASA Astrophysics Data System (ADS)

Khansari, Nasrin

Growth of population and moving towards over-consumption and over-pollution are significant threats to the environment and therefore necessitate moving towards sustainability approaches. CO2 emissions are considered to be the main basis of the incredible increase in the earth's surface temperature in recent years. Most emissions result from human activities. Thus, developing a detailed framework representing the parameters affecting individuals' energy behaviors is required. This dissertation offers an integrated conceptual framework to increase the efficiency of energy systems under complex and uncertainty conditions, facilitate energy consumption problem solving, and support the development of capacities at the individual, social, and technical levels to improve managing energy consumptions in the future. This research presents a conceptual soft systems model to explore the process of individuals' energy behavior change based on socio-structural and techno-structural contexts. In addition, a comprehensive model based on systems dynamics principles is presented to address the issue of CO2 emissions related to the households' energy consumption behavior. The proposed systems dynamics model provides a broad overview of the key agents affecting energy consumption, including government/public sector, households, and power industry. The model is created based on the research in the literature discussing the causal relations between various variables. The proposed systems dynamics model is verified by simulating different scenarios. In this research a survey is designed and conducted to investigate the role of individual, social and technical behaviors in reducing energy consumption, energy costs and carbon footprints based on the energy use profile. In sum, this study investigates the process of energy behavior change based on socio-structural and techno-structural contexts.

A ‘frozen volume’ transition model and working mechanism for the shape memory effect in amorphous polymers

NASA Astrophysics Data System (ADS)

Lu, Haibao; Wang, Xiaodong; Yao, Yongtao; Qing Fu, Yong

2018-06-01

Phenomenological models based on frozen volume parameters could well predict shape recovery behavior of shape memory polymers (SMPs), but the physical meaning of using the frozen volume parameters to describe thermomechanical properties has not been well-established. In this study, the fundamental working mechanisms of the shape memory effect (SME) in amorphous SMPs, whose temperature-dependent viscoelastic behavior follows the Eyring equation, have been established with the considerations of both internal stress and its resulted frozen volume. The stress-strain constitutive relation was initially modeled to quantitatively describe effects of internal stresses at the macromolecular scale based on the transient network theory. A phenomenological ‘frozen volume’ model was then established to characterize the macromolecule structure and SME of amorphous SMPs based on a two-site stress-relaxation model. Effects of the internal stress, frozen volume and strain rate on shape memory behavior and thermomechanical properties of the SMP were investigated. Finally, the simulation results were compared with the experimental results reported in the literature, and good agreements between the theoretical and experimental results were achieved. The novelty and key differences of our newly proposed model with respect to the previous reports are (1). The ‘frozen volume’ in our study is caused by the internal stress and governed by the two-site model theory, thus has a good physical meaning. (2). The model can be applied to characterize and predict both the thermal and thermomechanical behaviors of SMPs based on the constitutive relationship with internal stress parameters. It is expected to provide a power tool to investigate the thermomechanical behavior of the SMPs, of which both the macromolecular structure characteristics and SME could be predicted using this ‘frozen volume’ model.

Simple models for studying complex spatiotemporal patterns of animal behavior

NASA Astrophysics Data System (ADS)

Tyutyunov, Yuri V.; Titova, Lyudmila I.

2017-06-01

Minimal mathematical models able to explain complex patterns of animal behavior are essential parts of simulation systems describing large-scale spatiotemporal dynamics of trophic communities, particularly those with wide-ranging species, such as occur in pelagic environments. We present results obtained with three different modelling approaches: (i) an individual-based model of animal spatial behavior; (ii) a continuous taxis-diffusion-reaction system of partial-difference equations; (iii) a 'hybrid' approach combining the individual-based algorithm of organism movements with explicit description of decay and diffusion of the movement stimuli. Though the models are based on extremely simple rules, they all allow description of spatial movements of animals in a predator-prey system within a closed habitat, reproducing some typical patterns of the pursuit-evasion behavior observed in natural populations. In all three models, at each spatial position the animal movements are determined by local conditions only, so the pattern of collective behavior emerges due to self-organization. The movement velocities of animals are proportional to the density gradients of specific cues emitted by individuals of the antagonistic species (pheromones, exometabolites or mechanical waves of the media, e.g., sound). These cues play a role of taxis stimuli: prey attract predators, while predators repel prey. Depending on the nature and the properties of the movement stimulus we propose using either a simplified individual-based model, a continuous taxis pursuit-evasion system, or a little more detailed 'hybrid' approach that combines simulation of the individual movements with the continuous model describing diffusion and decay of the stimuli in an explicit way. These can be used to improve movement models for many species, including large marine predators.

Behavioral Signal Processing: Deriving Human Behavioral Informatics From Speech and Language

PubMed Central

Narayanan, Shrikanth; Georgiou, Panayiotis G.

2013-01-01

The expression and experience of human behavior are complex and multimodal and characterized by individual and contextual heterogeneity and variability. Speech and spoken language communication cues offer an important means for measuring and modeling human behavior. Observational research and practice across a variety of domains from commerce to healthcare rely on speech- and language-based informatics for crucial assessment and diagnostic information and for planning and tracking response to an intervention. In this paper, we describe some of the opportunities as well as emerging methodologies and applications of human behavioral signal processing (BSP) technology and algorithms for quantitatively understanding and modeling typical, atypical, and distressed human behavior with a specific focus on speech- and language-based communicative, affective, and social behavior. We describe the three important BSP components of acquiring behavioral data in an ecologically valid manner across laboratory to real-world settings, extracting and analyzing behavioral cues from measured data, and developing models offering predictive and decision-making support. We highlight both the foundational speech and language processing building blocks as well as the novel processing and modeling opportunities. Using examples drawn from specific real-world applications ranging from literacy assessment and autism diagnostics to psychotherapy for addiction and marital well being, we illustrate behavioral informatics applications of these signal processing techniques that contribute to quantifying higher level, often subjectively described, human behavior in a domain-sensitive fashion. PMID:24039277

From creatures of habit to goal-directed learners: Tracking the developmental emergence of model-based reinforcement learning

PubMed Central

Decker, Johannes H.; Otto, A. Ross; Daw, Nathaniel D.; Hartley, Catherine A.

2016-01-01

Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goal-directed choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults, performed a sequential reinforcement-learning task that enables estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was evident in choice behavior across all age groups, evidence of a model-based strategy only emerged during adolescence and continued to increase into adulthood. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior. PMID:27084852

Determinants of Consistent Condom Use among College Students in China: Application of the Information-Motivation-Behavior Skills (IMB) Model

PubMed Central

Liu, Zhihao; Wei, Pingmin; Huang, Minghao; Liu, Yuan bao; Li, Lucy; Gong, Xiao; Chen, Juan; Li, Xiaoning

2014-01-01

Background Due to the increase incidents of premarital sex and the lack of reproductive health services, college students are at high risk of HIV/AIDS infections in China. This study was designed to examine the predictors of consistency of condom use among college students based on the Information-Motivation-Behavioral Skills (IMB) model and to describe the relationships between the model constructs. Methods A cross-sectional study was conducted to assess HIV/AIDS related information, motivation, behavioral skills and preventive behavior among college students in five colleges and universities in Nanjing, China. An anonymous questionnaire survey was conducted for data collection, and the structural equation model (SEM) was used to assess the IMB model. Results A total of 3183 participants completed this study. The average age was 19.90 years (SD = 1.43, range 16 to 25). 342 (10.7%) participants of them reported having had premarital sex, among whom 30.7% reported having had a consistent condom use, 13.7% with the experience of abortion (including the participants whose sex partner has the same experience), 32.7% of participants had experience of multiple sex partners. The final IMB model provided acceptable fit to the data (CFI = 0.992, RMSEA = 0.028). Preventive behavior was significantly predicted by behavioral skills (β = 0.754, P<0.001). Information (β = 0.138, P<0.001) and motivation (β = 0.363, P<0.001) were indirectly affected preventive behavior, and was mediated through behavioral skills. Conclusions The results of the study demonstrate the utility of the IMB model for consistent condom use among college students in China. The main influencing factor of preventive behavior among college students is behavioral skills. Both information and motivation could affect preventive behavior through behavioral skills. Further research could develop preventive interventions based on the IMB model to promote consistent condom use among college students in China. PMID:25265390

Determinants of consistent condom use among college students in China: application of the information-motivation-behavior skills (IMB) model.

PubMed

Liu, Zhihao; Wei, Pingmin; Huang, Minghao; Liu, Yuan bao; Li, Lucy; Gong, Xiao; Chen, Juan; Li, Xiaoning

2014-01-01

Due to the increase incidents of premarital sex and the lack of reproductive health services, college students are at high risk of HIV/AIDS infections in China. This study was designed to examine the predictors of consistency of condom use among college students based on the Information-Motivation-Behavioral Skills (IMB) model and to describe the relationships between the model constructs. A cross-sectional study was conducted to assess HIV/AIDS related information, motivation, behavioral skills and preventive behavior among college students in five colleges and universities in Nanjing, China. An anonymous questionnaire survey was conducted for data collection, and the structural equation model (SEM) was used to assess the IMB model. A total of 3183 participants completed this study. The average age was 19.90 years (SD = 1.43, range 16 to 25). 342 (10.7%) participants of them reported having had premarital sex, among whom 30.7% reported having had a consistent condom use, 13.7% with the experience of abortion (including the participants whose sex partner has the same experience), 32.7% of participants had experience of multiple sex partners. The final IMB model provided acceptable fit to the data (CFI = 0.992, RMSEA = 0.028). Preventive behavior was significantly predicted by behavioral skills (β = 0.754, P<0.001). Information (β = 0.138, P<0.001) and motivation (β = 0.363, P<0.001) were indirectly affected preventive behavior, and was mediated through behavioral skills. The results of the study demonstrate the utility of the IMB model for consistent condom use among college students in China. The main influencing factor of preventive behavior among college students is behavioral skills. Both information and motivation could affect preventive behavior through behavioral skills. Further research could develop preventive interventions based on the IMB model to promote consistent condom use among college students in China.

Validating Computational Human Behavior Models: Consistency and Accuracy Issues

DTIC Science & Technology

2004-06-01

includes a discussion of SME demographics, content, and organization of the datasets . This research generalizes data from two pilot studies and two base...meet requirements for validating the varied and complex behavioral models. Through a series of empirical studies , this research identifies subject...meet requirements for validating the varied and complex behavioral models. Through a series of empirical studies , this research identifies subject

Behavioral Signal Processing: Deriving Human Behavioral Informatics From Speech and Language: Computational techniques are presented to analyze and model expressed and perceived human behavior-variedly characterized as typical, atypical, distressed, and disordered-from speech and language cues and their applications in health, commerce, education, and beyond.

PubMed

Narayanan, Shrikanth; Georgiou, Panayiotis G

2013-02-07

The expression and experience of human behavior are complex and multimodal and characterized by individual and contextual heterogeneity and variability. Speech and spoken language communication cues offer an important means for measuring and modeling human behavior. Observational research and practice across a variety of domains from commerce to healthcare rely on speech- and language-based informatics for crucial assessment and diagnostic information and for planning and tracking response to an intervention. In this paper, we describe some of the opportunities as well as emerging methodologies and applications of human behavioral signal processing (BSP) technology and algorithms for quantitatively understanding and modeling typical, atypical, and distressed human behavior with a specific focus on speech- and language-based communicative, affective, and social behavior. We describe the three important BSP components of acquiring behavioral data in an ecologically valid manner across laboratory to real-world settings, extracting and analyzing behavioral cues from measured data, and developing models offering predictive and decision-making support. We highlight both the foundational speech and language processing building blocks as well as the novel processing and modeling opportunities. Using examples drawn from specific real-world applications ranging from literacy assessment and autism diagnostics to psychotherapy for addiction and marital well being, we illustrate behavioral informatics applications of these signal processing techniques that contribute to quantifying higher level, often subjectively described, human behavior in a domain-sensitive fashion.

Electro-elastoviscous response of polyaniline functionalized nano-porous zeolite based colloidal dispersions.

PubMed

Chattopadhyay, Ankur; Rani, Poonam; Srivastava, Rajendra; Dhar, Purbarun

2018-06-01

The present article discusses the typical influence of grafted conducting polymers in the mesoscale pores of dielectric particles on the static and dynamic electrorheology and electro-viscoelastic behavior of corresponding colloids. Nanocrystalline meso-nanoporous zeolite has been prepared by chemical synthesis and subsequently polyaniline (PANI) coating has been implemented. Electrorheological (ER) suspensions have been formed by dispersing the nanoparticles in silicone oil and their viscoelastic behaviors are examined to understand the nature of such complex colloidal systems under electric fields. PANI-Zeolite ER fluids demonstrate higher static electroviscous effects and yield stress potential than untreated Zeolite, typically studied in literature. Transient electro-viscous characterizations show a stable and negligible hysteresis behavior when both the fluids are exposed to constant as well as time varying electric field intensities. Further oscillatory shear experiments of frequency and strain sweeps exhibit predominant elastic behavior in case of Zeolite based ER suspensions as compared to PANI systems. Detailed investigations reveal Zeolite based ER suspensions display enhanced relative yielding as well as electro-viscoelastic stability than the PANI-Zeolite. The steady state viscous behaviors are scaled against the non-dimensional Mason number to model the system behavior for both fluids. Experimental data of flow behaviors of both the ER fluids are compared with semi-classical models and it is found that the CCJ model possesses a closer proximity than traditional Bingham model, thereby revealing the fluids to be generic pseudo-linear fluids. The present article reveals that while the PANI based fluids are typically hailed superior in literature, it is only restricted to steady shear utilities. In case of dynamic and oscillatory systems, the traditional Zeolite based fluids exhibit superior ER caliber. Copyright © 2018 Elsevier Inc. All rights reserved.

RELATING ACCUMULATOR MODEL PARAMETERS AND NEURAL DYNAMICS

PubMed Central

Purcell, Braden A.; Palmeri, Thomas J.

2016-01-01

Accumulator models explain decision-making as an accumulation of evidence to a response threshold. Specific model parameters are associated with specific model mechanisms, such as the time when accumulation begins, the average rate of evidence accumulation, and the threshold. These mechanisms determine both the within-trial dynamics of evidence accumulation and the predicted behavior. Cognitive modelers usually infer what mechanisms vary during decision-making by seeing what parameters vary when a model is fitted to observed behavior. The recent identification of neural activity with evidence accumulation suggests that it may be possible to directly infer what mechanisms vary from an analysis of how neural dynamics vary. However, evidence accumulation is often noisy, and noise complicates the relationship between accumulator dynamics and the underlying mechanisms leading to those dynamics. To understand what kinds of inferences can be made about decision-making mechanisms based on measures of neural dynamics, we measured simulated accumulator model dynamics while systematically varying model parameters. In some cases, decision- making mechanisms can be directly inferred from dynamics, allowing us to distinguish between models that make identical behavioral predictions. In other cases, however, different parameterized mechanisms produce surprisingly similar dynamics, limiting the inferences that can be made based on measuring dynamics alone. Analyzing neural dynamics can provide a powerful tool to resolve model mimicry at the behavioral level, but we caution against drawing inferences based solely on neural analyses. Instead, simultaneous modeling of behavior and neural dynamics provides the most powerful approach to understand decision-making and likely other aspects of cognition and perception. PMID:28392584

Modeling the thermotaxis behavior of C.elegans based on the artificial neural network.

PubMed

Li, Mingxu; Deng, Xin; Wang, Jin; Chen, Qiaosong; Tang, Yun

2016-07-03

ASBTRACT This research aims at modeling the thermotaxis behavior of C.elegans which is a kind of nematode with full clarified neuronal connections. Firstly, this work establishes the motion model which can perform the undulatory locomotion with turning behavior. Secondly, the thermotaxis behavior is modeled by nonlinear functions and the nonlinear functions are learned by artificial neural network. Once the artificial neural networks have been well trained, they can perform the desired thermotaxis behavior. Last, several testing simulations are carried out to verify the effectiveness of the model for thermotaxis behavior. This work also analyzes the different performances of the model under different environments. The testing results reveal the essence of the thermotaxis of C.elegans to some extent, and theoretically support the research on the navigation of the crawling robots.

Paper-based and web-based intervention modeling experiments identified the same predictors of general practitioners' antibiotic-prescribing behavior.

PubMed

Treweek, Shaun; Bonetti, Debbie; Maclennan, Graeme; Barnett, Karen; Eccles, Martin P; Jones, Claire; Pitts, Nigel B; Ricketts, Ian W; Sullivan, Frank; Weal, Mark; Francis, Jill J

2014-03-01

To evaluate the robustness of the intervention modeling experiment (IME) methodology as a way of developing and testing behavioral change interventions before a full-scale trial by replicating an earlier paper-based IME. Web-based questionnaire and clinical scenario study. General practitioners across Scotland were invited to complete the questionnaire and scenarios, which were then used to identify predictors of antibiotic-prescribing behavior. These predictors were compared with the predictors identified in an earlier paper-based IME and used to develop a new intervention. Two hundred seventy general practitioners completed the questionnaires and scenarios. The constructs that predicted simulated behavior and intention were attitude, perceived behavioral control, risk perception/anticipated consequences, and self-efficacy, which match the targets identified in the earlier paper-based IME. The choice of persuasive communication as an intervention in the earlier IME was also confirmed. Additionally, a new intervention, an action plan, was developed. A web-based IME replicated the findings of an earlier paper-based IME, which provides confidence in the IME methodology. The interventions will now be evaluated in the next stage of the IME, a web-based randomized controlled trial. Copyright © 2014 Elsevier Inc. All rights reserved.

Mixed formulation for seismic analysis of composite steel-concrete frame structures

NASA Astrophysics Data System (ADS)

Ayoub, Ashraf Salah Eldin

This study presents a new finite element model for the nonlinear analysis of structures made up of steel and concrete under monotonic and cyclic loads. The new formulation is based on a two-field mixed formulation. In the formulation, both forces and deformations are simultaneously approximated within the element through independent interpolation functions. The main advantages of the model is the accuracy in global and local response with very few elements while maintaining rapid numerical convergence and robustness even under severe cyclic loading. Overall four elements were developed based on the new formulation: an element that describes the behavior of anchored reinforcing bars, an element that describes the behavior of composite steel-concrete beams with deformable shear connectors, an element that describes the behavior of reinforced concrete beam-columns with bond-slip, and an element that describes the behavior of pretensioned or posttensioned, bonded or unbonded prestressed concrete structures. The models use fiber discretization of beam sections to describe nonlinear material response. The transfer of forces between steel and concrete is described with bond elements. Bond elements are modeled with distributed spring elements. The non-linear behavior of the composite element derives entirely from the constitutive laws of the steel, concrete and bond elements. Two additional elements are used for the prestressed concrete models, a friction element that models the effect of friction between the tendon and the duct during the posttensioning operation, and an anchorage element that describes the behavior of the prestressing tendon anchorage in posttensioned structures. Two algorithms for the numerical implementation of the new proposed model are presented; an algorithm that enforces stress continuity at element boundaries, and an algorithm in which stress continuity is relaxed locally inside the element. Stability of both algorithms is discussed. Comparison with standard displacement based models and earlier flexibility based models is presented through numerical studies. The studies prove the superiority of the mixed model over both displacement and flexibility models. Correlation studies of the proposed model with experimental results of structural specimens are conducted. The studies show the accuracy of the model and its numerical robustness even under severe cyclic loading conditions.

Evolving dynamics of trading behavior based on coordination game in complex networks

NASA Astrophysics Data System (ADS)

Bian, Yue-tang; Xu, Lu; Li, Jin-sheng

2016-05-01

This work concerns the modeling of evolvement of trading behavior in stock markets. Based on the assumption of the investors' limited rationality, the evolution mechanism of trading behavior is modeled according to the investment strategy of coordination game in network, that investors are prone to imitate their neighbors' activity through comprehensive analysis on the risk dominance degree of certain investment behavior, the network topology of their relationship and its heterogeneity. We investigate by mean-field analysis and extensive simulations the evolution of investors' trading behavior in various typical networks under different risk dominance degree of investment behavior. Our results indicate that the evolution of investors' behavior is affected by the network structure of stock market and the effect of risk dominance degree of investment behavior; the stability of equilibrium states of investors' behavior dynamics is directly related with the risk dominance degree of some behavior; connectivity and heterogeneity of the network plays an important role in the evolution of the investment behavior in stock market.

Modeling a Common-Source Amplifier Using a Ferroelectric Transistor

NASA Technical Reports Server (NTRS)

Sayyah, Rana; Hunt, Mitchell; MacLeond, Todd C.; Ho, Fat D.

2010-01-01

This paper presents a mathematical model characterizing the behavior of a common-source amplifier using a FeFET. The model is based on empirical data and incorporates several variables that affect the output, including frequency, load resistance, and gate-to-source voltage. Since the common-source amplifier is the most widely used amplifier in MOS technology, understanding and modeling the behavior of the FeFET-based common-source amplifier will help in the integration of FeFETs into many circuits.

Combining Human and Machine Intelligence to Derive Agents' Behavioral Rules for Groundwater Irrigation

NASA Astrophysics Data System (ADS)

Hu, Y.; Quinn, C.; Cai, X.

2015-12-01

One major challenge of agent-based modeling is to derive agents' behavioral rules due to behavioral uncertainty and data scarcity. This study proposes a new approach to combine a data-driven modeling based on the directed information (i.e., machine intelligence) with expert domain knowledge (i.e., human intelligence) to derive the behavioral rules of agents considering behavioral uncertainty. A directed information graph algorithm is applied to identifying the causal relationships between agents' decisions (i.e., groundwater irrigation depth) and time-series of environmental, socio-economical and institutional factors. A case study is conducted for the High Plains aquifer hydrological observatory (HO) area, U.S. Preliminary results show that four factors, corn price (CP), underlying groundwater level (GWL), monthly mean temperature (T) and precipitation (P) have causal influences on agents' decisions on groundwater irrigation depth (GWID) to various extents. Based on the similarity of the directed information graph for each agent, five clusters of graphs are further identified to represent all the agents' behaviors in the study area as shown in Figure 1. Using these five representative graphs, agents' monthly optimal groundwater pumping rates are derived through the probabilistic inference. Such data-driven relationships and probabilistic quantifications are then coupled with a physically-based groundwater model to investigate the interactions between agents' pumping behaviors and the underlying groundwater system in the context of coupled human and natural systems.

Importance of the habitat choice behavior assumed when modeling the effects of food and temperature on fish populations

USGS Publications Warehouse

Wildhaber, Mark L.; Lamberson, Peter J.

2004-01-01

Various mechanisms of habitat choice in fishes based on food and/or temperature have been proposed: optimal foraging for food alone; behavioral thermoregulation for temperature alone; and behavioral energetics and discounted matching for food and temperature combined. Along with development of habitat choice mechanisms, there has been a major push to develop and apply to fish populations individual-based models that incorporate various forms of these mechanisms. However, it is not known how the wide variation in observed and hypothesized mechanisms of fish habitat choice could alter fish population predictions (e.g. growth, size distributions, etc.). We used spatially explicit, individual-based modeling to compare predicted fish populations using different submodels of patch choice behavior under various food and temperature distributions. We compared predicted growth, temperature experience, food consumption, and final spatial distribution using the different models. Our results demonstrated that the habitat choice mechanism assumed in fish population modeling simulations was critical to predictions of fish distribution and growth rates. Hence, resource managers who use modeling results to predict fish population trends should be very aware of and understand the underlying patch choice mechanisms used in their models to assure that those mechanisms correctly represent the fish populations being modeled.

Computational Phenotyping in Psychiatry: A Worked Example

PubMed Central

2016-01-01

Abstract Computational psychiatry is a rapidly emerging field that uses model-based quantities to infer the behavioral and neuronal abnormalities that underlie psychopathology. If successful, this approach promises key insights into (pathological) brain function as well as a more mechanistic and quantitative approach to psychiatric nosology—structuring therapeutic interventions and predicting response and relapse. The basic procedure in computational psychiatry is to build a computational model that formalizes a behavioral or neuronal process. Measured behavioral (or neuronal) responses are then used to infer the model parameters of a single subject or a group of subjects. Here, we provide an illustrative overview over this process, starting from the modeling of choice behavior in a specific task, simulating data, and then inverting that model to estimate group effects. Finally, we illustrate cross-validation to assess whether between-subject variables (e.g., diagnosis) can be recovered successfully. Our worked example uses a simple two-step maze task and a model of choice behavior based on (active) inference and Markov decision processes. The procedural steps and routines we illustrate are not restricted to a specific field of research or particular computational model but can, in principle, be applied in many domains of computational psychiatry. PMID:27517087

Computational Phenotyping in Psychiatry: A Worked Example.

PubMed

Schwartenbeck, Philipp; Friston, Karl

2016-01-01

Computational psychiatry is a rapidly emerging field that uses model-based quantities to infer the behavioral and neuronal abnormalities that underlie psychopathology. If successful, this approach promises key insights into (pathological) brain function as well as a more mechanistic and quantitative approach to psychiatric nosology-structuring therapeutic interventions and predicting response and relapse. The basic procedure in computational psychiatry is to build a computational model that formalizes a behavioral or neuronal process. Measured behavioral (or neuronal) responses are then used to infer the model parameters of a single subject or a group of subjects. Here, we provide an illustrative overview over this process, starting from the modeling of choice behavior in a specific task, simulating data, and then inverting that model to estimate group effects. Finally, we illustrate cross-validation to assess whether between-subject variables (e.g., diagnosis) can be recovered successfully. Our worked example uses a simple two-step maze task and a model of choice behavior based on (active) inference and Markov decision processes. The procedural steps and routines we illustrate are not restricted to a specific field of research or particular computational model but can, in principle, be applied in many domains of computational psychiatry.

LINEBACKER: LINE-speed Bio-inspired Analysis and Characterization for Event Recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oehmen, Christopher S.; Bruillard, Paul J.; Matzke, Brett D.

2016-08-04

The cyber world is a complex domain, with digital systems mediating a wide spectrum of human and machine behaviors. While this is enabling a revolution in the way humans interact with each other and data, it also is exposing previously unreachable infrastructure to a worldwide set of actors. Existing solutions for intrusion detection and prevention that are signature-focused typically seek to detect anomalous and/or malicious activity for the sake of preventing or mitigating negative impacts. But a growing interest in behavior-based detection is driving new forms of analysis that move the emphasis from static indicators (e.g. rule-based alarms or tripwires)more » to behavioral indicators that accommodate a wider contextual perspective. Similar to cyber systems, biosystems have always existed in resource-constrained hostile environments where behaviors are tuned by context. So we look to biosystems as an inspiration for addressing behavior-based cyber challenges. In this paper, we introduce LINEBACKER, a behavior-model based approach to recognizing anomalous events in network traffic and present the design of this approach of bio-inspired and statistical models working in tandem to produce individualized alerting for a collection of systems. Preliminary results of these models operating on historic data are presented along with a plugin to support real-world cyber operations.« less

Behavioral consequences of disasters: a five-stage model of population behavior.

PubMed

Rudenstine, Sasha; Galea, Sandro

2014-12-01

We propose a model of population behavior in the aftermath of disasters. We conducted a qualitative analysis of an empirical dataset of 339 disasters throughout the world spanning from 1950 to 2005. We developed a model of population behavior that is based on 2 fundamental assumptions: (i) behavior is predictable and (ii) population behavior will progress sequentially through 5 stages from the moment the hazard begins until is complete. Understanding the progression of population behavior during a disaster can improve the efficiency and appropriateness of institutional efforts aimed at population preservation after large-scale traumatic events. Additionally, the opportunity for population-level intervention in the aftermath of such events will improve population health.

Development of a unified constitutive model for an isotropic nickel base superalloy Rene 80

NASA Technical Reports Server (NTRS)

Ramaswamy, V. G.; Vanstone, R. H.; Laflen, J. H.; Stouffer, D. C.

1988-01-01

Accurate analysis of stress-strain behavior is of critical importance in the evaluation of life capabilities of hot section turbine engine components such as turbine blades and vanes. The constitutive equations used in the finite element analysis of such components must be capable of modeling a variety of complex behavior exhibited at high temperatures by cast superalloys. The classical separation of plasticity and creep employed in most of the finite element codes in use today is known to be deficient in modeling elevated temperature time dependent phenomena. Rate dependent, unified constitutive theories can overcome many of these difficulties. A new unified constitutive theory was developed to model the high temperature, time dependent behavior of Rene' 80 which is a cast turbine blade and vane nickel base superalloy. Considerations in model development included the cyclic softening behavior of Rene' 80, rate independence at lower temperatures and the development of a new model for static recovery.

MOAB: a spatially explicit, individual-based expert system for creating animal foraging models

USGS Publications Warehouse

Carter, J.; Finn, John T.

1999-01-01

We describe the development, structure, and corroboration process of a simulation model of animal behavior (MOAB). MOAB can create spatially explicit, individual-based animal foraging models. Users can create or replicate heterogeneous landscape patterns, and place resources and individual animals of a goven species on that landscape to simultaneously simulate the foraging behavior of multiple species. The heuristic rules for animal behavior are maintained in a user-modifiable expert system. MOAB can be used to explore hypotheses concerning the influence of landscape patttern on animal movement and foraging behavior. A red fox (Vulpes vulpes L.) foraging and nest predation model was created to test MOAB's capabilities. Foxes were simulated for 30-day periods using both expert system and random movement rules. Home range size, territory formation and other available simulation studies. A striped skunk (Mephitis mephitis L.) model also was developed. The expert system model proved superior to stochastic in respect to territory formation, general movement patterns and home range size.

Modeling plug-in electric vehicle charging demand with BEAM: the framework for behavior energy autonomy mobility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheppard, Colin; Waraich, Rashid; Campbell, Andrew

This report summarizes the BEAM modeling framework (Behavior, Energy, Mobility, and Autonomy) and its application to simulating plug-in electric vehicle (PEV) mobility, energy consumption, and spatiotemporal charging demand. BEAM is an agent-based model of PEV mobility and charging behavior designed as an extension to MATSim (the Multi-Agent Transportation Simulation model). We apply BEAM to the San Francisco Bay Area and conduct a preliminary calibration and validation of its prediction of charging load based on observed charging infrastructure utilization for the region in 2016. We then explore the impact of a variety of common modeling assumptions in the literature regarding chargingmore » infrastructure availability and driver behavior. We find that accurately reproducing observed charging patterns requires an explicit representation of spatially disaggregated charging infrastructure as well as a more nuanced model of the decision to charge that balances tradeoffs people make with regards to time, cost, convenience, and range anxiety.« less

Perceptions of Problem Behavior in Adolescents' Families: Perceiver, Target, and Family Effects

ERIC Educational Resources Information Center

Manders, Willeke A.; Janssens, Jan M. A. M.; Cook, William L.; Oud, Johan H. L.; De Bruyn, Eric E. J.; Scholte, Ron H. J.

2009-01-01

Considerable research has focused on the reliability and validity of informant reports of family behavior, especially maternal reports of adolescent problem behavior. None of these studies, however, has based their orientation on a theoretical model of interpersonal perception. In this study we used the social relations model (SRM) to examine…

Factors Influencing College Women's Contraceptive Behavior: An Application of the Integrative Model of Behavioral Prediction

ERIC Educational Resources Information Center

Sutton, Jazmyne A.; Walsh-Buhi, Eric R.

2017-01-01

Objective: This study investigated variables within the Integrative Model of Behavioral Prediction (IMBP) as well as differences across socioeconomic status (SES) levels within the context of inconsistent contraceptive use among college women. Participants: A nonprobability sample of 515 female college students completed an Internet-based survey…

Acceptance versus Change in Behavior Therapy: An Interview with Neil Jacobson.

ERIC Educational Resources Information Center

Hines, Max

1998-01-01

Neil Jacobson is a leader in research-based efforts to improve behavioral couples therapy. This interview focuses on his professional journey toward an integrative model, as well as his thoughts about the future directions of behavioral therapy and family counseling. The integrative-couples therapy model is described and discussed. (Author/EMK)

Analysis of Autopilot Behavior

NASA Technical Reports Server (NTRS)

Sherry, Lance; Polson, Peter; Feay, Mike; Palmer, Everett; Null, Cynthia H. (Technical Monitor)

1998-01-01

Aviation and cognitive science researchers have identified situations in which the pilot's expectations for behavior of autopilot avionics are not matched by the actual behavior of the avionics. These "automation surprises" have been attributed to differences between the pilot's model of the behavior of the avionics and the actual behavior encoded in the avionics software. A formal technique is described for the analysis and measurement of the behavior of the cruise pitch modes of a modern Autopilot. The analysis characterizes the behavior of the Autopilot as situation-action rules. The behavior of the cruise pitch mode logic for a contemporary modern Autopilot was found to include 177 rules, including Level Change (23), Vertical Speed (16), Altitude Capture (50), and Altitude Hold (88). These rules are determined based on the values of 62 inputs. Analysis of the rule-based model also shed light on the factors cited in the literature as contributors to "automation surprises."

Modeling fuels and fire effects in 3D: Model description and applications

Treesearch

Francois Pimont; Russell Parsons; Eric Rigolot; Francois de Coligny; Jean-Luc Dupuy; Philippe Dreyfus; Rodman R. Linn

2016-01-01

Scientists and managers critically need ways to assess how fuel treatments alter fire behavior, yet few tools currently exist for this purpose.We present a spatially-explicit-fuel-modeling system, FuelManager, which models fuels, vegetation growth, fire behavior (using a physics-based model, FIRETEC), and fire effects. FuelManager's flexible approach facilitates...

Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests

NASA Astrophysics Data System (ADS)

Kaloop, Mosbeh R.; Yigit, Cemal O.; Hu, Jong W.

2018-03-01

Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10 Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method.

On the spatial dynamics and oscillatory behavior of a predator-prey model based on cellular automata and local particle swarm optimization.

PubMed

Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan

2013-11-07

A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.

Active Player Modeling in the Iterated Prisoner's Dilemma

PubMed Central

Park, Hyunsoo; Kim, Kyung-Joong

2016-01-01

The iterated prisoner's dilemma (IPD) is well known within the domain of game theory. Although it is relatively simple, it can also elucidate important problems related to cooperation and trust. Generally, players can predict their opponents' actions when they are able to build a precise model of their behavior based on their game playing experience. However, it is difficult to make such predictions based on a limited number of games. The creation of a precise model requires the use of not only an appropriate learning algorithm and framework but also a good dataset. Active learning approaches have recently been introduced to machine learning communities. The approach can usually produce informative datasets with relatively little effort. Therefore, we have proposed an active modeling technique to predict the behavior of IPD players. The proposed method can model the opponent player's behavior while taking advantage of interactive game environments. This experiment used twelve representative types of players as opponents, and an observer used an active modeling algorithm to model these opponents. This observer actively collected data and modeled the opponent's behavior online. Most of our data showed that the observer was able to build, through direct actions, a more accurate model of an opponent's behavior than when the data were collected through random actions. PMID:26989405

Active Player Modeling in the Iterated Prisoner's Dilemma.

PubMed

Park, Hyunsoo; Kim, Kyung-Joong

2016-01-01

The iterated prisoner's dilemma (IPD) is well known within the domain of game theory. Although it is relatively simple, it can also elucidate important problems related to cooperation and trust. Generally, players can predict their opponents' actions when they are able to build a precise model of their behavior based on their game playing experience. However, it is difficult to make such predictions based on a limited number of games. The creation of a precise model requires the use of not only an appropriate learning algorithm and framework but also a good dataset. Active learning approaches have recently been introduced to machine learning communities. The approach can usually produce informative datasets with relatively little effort. Therefore, we have proposed an active modeling technique to predict the behavior of IPD players. The proposed method can model the opponent player's behavior while taking advantage of interactive game environments. This experiment used twelve representative types of players as opponents, and an observer used an active modeling algorithm to model these opponents. This observer actively collected data and modeled the opponent's behavior online. Most of our data showed that the observer was able to build, through direct actions, a more accurate model of an opponent's behavior than when the data were collected through random actions.

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum

PubMed Central

Ito, Makoto; Doya, Kenji

2015-01-01

Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the “win-stay, lose-switch” strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum. PMID:26529522

Executable Architecture Modeling and Simulation Based on fUML

DTIC Science & Technology

2014-06-01

SoS behaviors. Wang et al.[9] use SysML sequence diagram to model the behaviors and translate the models into Colored Petri Nets (CPN). Staines T.S...Renzhong and Dagli C H. An executable system architecture approach to discrete events system modeling using SysML in conjunction with colored Petri

Impact of different policies on unhealthy dietary behaviors in an urban adult population: an agent-based simulation model.

PubMed

Zhang, Donglan; Giabbanelli, Philippe J; Arah, Onyebuchi A; Zimmerman, Frederick J

2014-07-01

Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems.

Performability modeling based on real data: A case study

NASA Technical Reports Server (NTRS)

Hsueh, M. C.; Iyer, R. K.; Trivedi, K. S.

1988-01-01

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of apparent types of errors.

Performability modeling based on real data: A casestudy

NASA Technical Reports Server (NTRS)

Hsueh, M. C.; Iyer, R. K.; Trivedi, K. S.

1987-01-01

Described is a measurement-based performability model based on error and resource usage data collected on a multiprocessor system. A method for identifying the model structure is introduced and the resulting model is validated against real data. Model development from the collection of raw data to the estimation of the expected reward is described. Both normal and error behavior of the system are characterized. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different types of errors.

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes

PubMed Central

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M.; Zimmermann, Ulrich S.; Schlagenhauf, Florian; Smolka, Michael N.; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities. PMID:28642696

How Accumulated Real Life Stress Experience and Cognitive Speed Interact on Decision-Making Processes.

PubMed

Friedel, Eva; Sebold, Miriam; Kuitunen-Paul, Sören; Nebe, Stephan; Veer, Ilya M; Zimmermann, Ulrich S; Schlagenhauf, Florian; Smolka, Michael N; Rapp, Michael; Walter, Henrik; Heinz, Andreas

2017-01-01

Rationale: Advances in neurocomputational modeling suggest that valuation systems for goal-directed (deliberative) on one side, and habitual (automatic) decision-making on the other side may rely on distinct computational strategies for reinforcement learning, namely model-free vs. model-based learning. As a key theoretical difference, the model-based system strongly demands cognitive functions to plan actions prospectively based on an internal cognitive model of the environment, whereas valuation in the model-free system relies on rather simple learning rules from operant conditioning to retrospectively associate actions with their outcomes and is thus cognitively less demanding. Acute stress reactivity is known to impair model-based but not model-free choice behavior, with higher working memory capacity protecting the model-based system from acute stress. However, it is not clear which impact accumulated real life stress has on model-free and model-based decision systems and how this influence interacts with cognitive abilities. Methods: We used a sequential decision-making task distinguishing relative contributions of both learning strategies to choice behavior, the Social Readjustment Rating Scale questionnaire to assess accumulated real life stress, and the Digit Symbol Substitution Test to test cognitive speed in 95 healthy subjects. Results: Individuals reporting high stress exposure who had low cognitive speed showed reduced model-based but increased model-free behavioral control. In contrast, subjects exposed to accumulated real life stress with high cognitive speed displayed increased model-based performance but reduced model-free control. Conclusion: These findings suggest that accumulated real life stress exposure can enhance reliance on cognitive speed for model-based computations, which may ultimately protect the model-based system from the detrimental influences of accumulated real life stress. The combination of accumulated real life stress exposure and slower information processing capacities, however, might favor model-free strategies. Thus, the valence and preference of either system strongly depends on stressful experiences and individual cognitive capacities.

A measurement-based performability model for a multiprocessor system

NASA Technical Reports Server (NTRS)

Ilsueh, M. C.; Iyer, Ravi K.; Trivedi, K. S.

1987-01-01

A measurement-based performability model based on real error-data collected on a multiprocessor system is described. Model development from the raw errror-data to the estimation of cumulative reward is described. Both normal and failure behavior of the system are characterized. The measured data show that the holding times in key operational and failure states are not simple exponential and that semi-Markov process is necessary to model the system behavior. A reward function, based on the service rate and the error rate in each state, is then defined in order to estimate the performability of the system and to depict the cost of different failure types and recovery procedures.

Intelligent Systems Approach for Automated Identification of Individual Control Behavior of a Human Operator

NASA Technical Reports Server (NTRS)

Zaychik, Kirill B.; Cardullo, Frank M.

2012-01-01

Results have been obtained using conventional techniques to model the generic human operator?s control behavior, however little research has been done to identify an individual based on control behavior. The hypothesis investigated is that different operators exhibit different control behavior when performing a given control task. Two enhancements to existing human operator models, which allow personalization of the modeled control behavior, are presented. One enhancement accounts for the testing control signals, which are introduced by an operator for more accurate control of the system and/or to adjust the control strategy. This uses the Artificial Neural Network which can be fine-tuned to model the testing control. Another enhancement takes the form of an equiripple filter which conditions the control system power spectrum. A novel automated parameter identification technique was developed to facilitate the identification process of the parameters of the selected models. This utilizes a Genetic Algorithm based optimization engine called the Bit-Climbing Algorithm. Enhancements were validated using experimental data obtained from three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. This manuscript also addresses applying human operator models to evaluate the effectiveness of motion feedback when simulating actual pilot control behavior in a flight simulator.

Health behavior models and oral health: a review.

PubMed

Hollister, M Catherine; Anema, Marion G

2004-01-01

Dental hygienists help their clients develop health promoting behaviors, by providing essential information about general health, and oral health in particular. Individual health practices such as oral self-care are based on personal choices. The guiding principles found in health behavior models provide useful methods to the oral health care providers in promoting effective individual client behaviors. Theories provide explanations about observable facts in a systematic manner. Research regarding health behavior has explored the effectiveness and applicability of various health models in oral health behavior modification. The Health Belief Model, Transtheoretical Model and Stages of Change, Theory of Reasoned Action, Self-Efficacy, Locus of Control, and Sense of Coherence are examples of models that focus on individuals assuming responsibility for their own health. Understanding the strengths of each and their applicability to health behaviors is critical for oral health care providers who work with patients to adopt methods and modify behaviors that contribute to good oral health. This paper describes health behavior models that have been applied to oral health education, presents a critical analysis of the effectiveness of each model in oral health education, and provides examples of application to oral health education.

Computational Modeling of Electrochemical-Poroelastic Bending Behaviors of Conducting Polymer (PPy) Membranes

NASA Astrophysics Data System (ADS)

Toi, Yutaka; Jung, Woosang

The electrochemical-poroelastic bending behavior of conducting polymer actuators has an attractive feature, considering their potential applications such as artificial muscles or MEMS. In the present study, a computational modeling is presented for the bending behavior of polypyrrole-based actuators. The one-dimensional governing equation for the ionic transportation in electrolytes given by Tadokoro et al. is combined with the finite element modeling for the poroelastic behavior of polypyrroles considering the effect of finite deformation. The validity of the proposed model has been illustrated by comparing the computed results with the experimental results in the literatures.

Guided by Theory, Informed by Practice: Training and Support for the Good Behavior Game, a Classroom-Based Behavior Management Strategy

ERIC Educational Resources Information Center

Poduska, Jeanne M.; Kurki, Anja

2014-01-01

Moving evidence-based practices for classroom behavior management into real-world settings is a high priority for education and public health. This article describes the development and use of a model of training and support for the Good Behavior Game (GBG), one of the few preventive interventions shown to have positive outcomes for elementary…

Vision-based navigation in a dynamic environment for virtual human

NASA Astrophysics Data System (ADS)

Liu, Yan; Sun, Ji-Zhou; Zhang, Jia-Wan; Li, Ming-Chu

2004-06-01

Intelligent virtual human is widely required in computer games, ergonomics software, virtual environment and so on. We present a vision-based behavior modeling method to realize smart navigation in a dynamic environment. This behavior model can be divided into three modules: vision, global planning and local planning. Vision is the only channel for smart virtual actor to get information from the outside world. Then, the global and local planning module use A* and D* algorithm to find a way for virtual human in a dynamic environment. Finally, the experiments on our test platform (Smart Human System) verify the feasibility of this behavior model.

Translational animal models of autism and neurodevelopmental disorders

PubMed Central

Crawley, Jacqueline N.

2012-01-01

Autism is a neurodevelopmental disorder whose diagnosis is based on three behavioral criteria: unusual reciprocal social interactions, deficits in communication, and stereotyped repetitive behaviors with restricted interests. A large number of de novo single gene mutations and chromosomal deletions are associated with autism spectrum disorders. Based on the strong genetic evidence, mice with targeted mutations in homologous genes have been generated as translational research tools. Mouse models of autism have revealed behavioral and biological outcomes of mutations in risk genes. The field is now poised to employ the most robust phenotypes in the most replicable mouse models for preclinical screening of novel therapeutics. PMID:23226954

Optimal filtering and Bayesian detection for friction-based diagnostics in machines.

PubMed

Ray, L R; Townsend, J R; Ramasubramanian, A

2001-01-01

Non-model-based diagnostic methods typically rely on measured signals that must be empirically related to process behavior or incipient faults. The difficulty in interpreting a signal that is indirectly related to the fundamental process behavior is significant. This paper presents an integrated non-model and model-based approach to detecting when process behavior varies from a proposed model. The method, which is based on nonlinear filtering combined with maximum likelihood hypothesis testing, is applicable to dynamic systems whose constitutive model is well known, and whose process inputs are poorly known. Here, the method is applied to friction estimation and diagnosis during motion control in a rotating machine. A nonlinear observer estimates friction torque in a machine from shaft angular position measurements and the known input voltage to the motor. The resulting friction torque estimate can be analyzed directly for statistical abnormalities, or it can be directly compared to friction torque outputs of an applicable friction process model in order to diagnose faults or model variations. Nonlinear estimation of friction torque provides a variable on which to apply diagnostic methods that is directly related to model variations or faults. The method is evaluated experimentally by its ability to detect normal load variations in a closed-loop controlled motor driven inertia with bearing friction and an artificially-induced external line contact. Results show an ability to detect statistically significant changes in friction characteristics induced by normal load variations over a wide range of underlying friction behaviors.

The Effect of Emotional Feedback on Behavioral Intention to Use Computer Based Assessment

ERIC Educational Resources Information Center

Terzis, Vasileios; Moridis, Christos N.; Economides, Anastasios A.

2012-01-01

This study introduces emotional feedback as a construct in an acceptance model. It explores the effect of emotional feedback on behavioral intention to use Computer Based Assessment (CBA). A female Embodied Conversational Agent (ECA) with empathetic encouragement behavior was displayed as emotional feedback. More specifically, this research aims…

The Efficacy of a Systematic Substance Abuse Program for Adolescent Females

ERIC Educational Resources Information Center

Froeschle, Janet G.; Smith, Robert L.; Ricard, Richard

2007-01-01

A school-based substance abuse prevention program based on the assumptions of the ASCA National Model[R] was designed to change adolescent females' drug-using behaviors. The program was designed to reduce substance abuse, increase negative attitudes toward drug use, and reduce negative behaviors while increasing positive behaviors, knowledge of…

School-Based Cognitive-Behavioral Therapy for an Adolescent Presenting with ADHD and Explosive Anger: A Case Study

ERIC Educational Resources Information Center

Parker, Janise; Zaboski, Brian; Joyce-Beaulieu, Diana

2016-01-01

This case demonstrates the efficacy of utilizing an intensive, multi-faceted behavioral intervention paradigm. A comprehensive, integrative, school-based service model was applied to address attention deficit hyperactivity disorder symptomology, oppositional behaviors, and explosive anger at the secondary level. The case reviews a multi-modal…

Verbal Bullying Changes among Students Following an Educational Intervention Using the Integrated Model for Behavior Change

ERIC Educational Resources Information Center

Naidoo, Saloshni; Satorius, Benn K.; de Vries, Hein; Taylor, Myra

2016-01-01

Background: Bullying behavior in schools can lead to psychosocial problems. School-based interventions are important in raising student awareness, developing their skills and in planning to reduce bullying behavior. Methods: A randomized controlled trial, using a school-based educational intervention to reduce verbal bullying, was conducted among…

Behavioral Change Theories Can Inform the Prediction of Young Adults' Adoption of a Plant-Based Diet

ERIC Educational Resources Information Center

Wyker, Brett A.; Davison, Kirsten K.

2010-01-01

Objective: Drawing on the Theory of Planned Behavior (TPB) and the Transtheoretical Model (TTM), this study (1) examines links between stages of change for following a plant-based diet (PBD) and consuming more fruits and vegetables (FV); (2) tests an integrated theoretical model predicting intention to follow a PBD; and (3) identifies associated…

Cognition-Based and Affect-Based Trust as Mediators of Leader Behavior Influences on Team Performance

ERIC Educational Resources Information Center

Schaubroeck, John; Lam, Simon S. K.; Peng, Ann Chunyan

2011-01-01

We develop a model in which cognitive and affective trust in the leader mediate the relationship between leader behavior and team psychological states that, in turn, drive team performance. The model is tested on a sample of 191 financial services teams in Hong Kong and the U.S. Servant leadership influenced team performance through affect-based…

Effects of a Health Behavior Change Model-Based HIV/STI Prevention Intervention on Condom Use among Heterosexual Couples: A Randomized Trial

ERIC Educational Resources Information Center

Harvey, S. Marie; Kraft, Joan Marie; West, Stephen G.; Taylor, Aaron B.; Pappas-DeLuca, Katina A.; Beckman, Linda J.

2009-01-01

This study examines an intervention for heterosexual couples to prevent human immunodeficiency virus/sexually transmitted infections. It also evaluates the effect of the intervention, which is based on current models of health behavior change, on intermediate outcomes (individual and relationship factors) and consistency of condom use. Eligible…

The Role of Incentives in Changing the Behavior of Spinal Care Providers: A Primer on Behavioral Economics in Health Care.

PubMed

Sharan, Alok D; Schroeder, Gregory D; West, Michael E; Vaccaro, Alexander R

2016-12-01

As spinal care transitions from individual practitioners working in a volume-based reimbursement system toward multidisciplinary health care organizations working in a population-based model with value-based reimbursement, it is critical that insurance companies, administrators, and spine care provider have a clear understanding of how incentives change physician behavior. This article will introduce the concept of behavior economics, and discuss 9 principles relevant to physician decision-making.

Organizing intelligence: development of behavioral science and the research based model of business education.

PubMed

Bottom, William P

2009-01-01

Conventional history of the predominant, research-based model of business education (RBM) traces its origins to programs initiated by the Ford Foundation after World War II. This paper maps the elite network responsible for developing behavioral science and the Ford Foundation agenda. Archival records of the actions taken by central nodes in the network permit identification of the original vision statement for the model. Analysis also permits tracking progress toward realizing that vision over several decades. Behavioral science was married to business education from the earliest stages of development. The RBM was a fundamental promise made by advocates for social science funding. Appraisals of the model and recommendations for reform must address its full history, not the partial, distorted view that is the conventional account. Implications of this more complete history for business education and for behavioral theory are considered.

A novel behavioral model of the pasture-based dairy cow from GPS data using data mining and machine learning techniques.

PubMed

Williams, M L; Mac Parthaláin, N; Brewer, P; James, W P J; Rose, M T

2016-03-01

A better understanding of the behavior of individual grazing dairy cattle will assist in improving productivity and welfare. Global positioning systems (GPS) applied to cows could provide a means of monitoring grazing herds while overcoming the substantial efforts required for manual observation. Any model of behavioral prediction using GPS needs to be accurate and robust by accounting for inter-cow variation as well as atmospheric effects. We evaluated the performance using a series of machine learning algorithms on GPS data collected from 40 pasture-based dairy cows over 4 mo. A feature extraction step was performed on the collected raw GPS data, which resulted in 43 different attributes. The evaluated behaviors were grazing, resting, and walking. Classifier learners were built using 10 times 10-fold cross validation and tested on an independent test set. Results were evaluated using a variety of statistical significance tests across all parameters. We found that final model selection depended upon level of performance and model complexity. The classifier learner deemed most suitable for this particular problem was JRip, a rule-based learner (classification accuracy=0.85; false positive rate=0.10; F-measure=0.76; area under the receiver operating curve=0.87). This model will be used in further studies to assess the behavior and welfare of pasture-based dairy cows. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Learning to use working memory: a reinforcement learning gating model of rule acquisition in rats

PubMed Central

Lloyd, Kevin; Becker, Nadine; Jones, Matthew W.; Bogacz, Rafal

2012-01-01

Learning to form appropriate, task-relevant working memory representations is a complex process central to cognition. Gating models frame working memory as a collection of past observations and use reinforcement learning (RL) to solve the problem of when to update these observations. Investigation of how gating models relate to brain and behavior remains, however, at an early stage. The current study sought to explore the ability of simple RL gating models to replicate rule learning behavior in rats. Rats were trained in a maze-based spatial learning task that required animals to make trial-by-trial choices contingent upon their previous experience. Using an abstract version of this task, we tested the ability of two gating algorithms, one based on the Actor-Critic and the other on the State-Action-Reward-State-Action (SARSA) algorithm, to generate behavior consistent with the rats'. Both models produced rule-acquisition behavior consistent with the experimental data, though only the SARSA gating model mirrored faster learning following rule reversal. We also found that both gating models learned multiple strategies in solving the initial task, a property which highlights the multi-agent nature of such models and which is of importance in considering the neural basis of individual differences in behavior. PMID:23115551

Strain rate dependent hyperelastic stress-stretch behavior of a silica nanoparticle reinforced poly (ethylene glycol) diacrylate nanocomposite hydrogel.

PubMed

Zhan, Yuexing; Pan, Yihui; Chen, Bing; Lu, Jian; Zhong, Zheng; Niu, Xinrui

2017-11-01

Poly (ethylene glycol) diacrylate (PEGDA) derivatives are important biomedical materials. PEGDA based hydrogels have emerged as one of the popular regenerative orthopedic materials. This work aims to study the mechanical behavior of a PEGDA based silica nanoparticle (NP) reinforced nanocomposite (NC) hydrogel at physiological strain rates. The work combines materials fabrication, mechanical experiments, mathematical modeling and structural analysis. The strain rate dependent stress-stretch behaviors were observed, analyzed and quantified. Visco-hyperelasticity was identified as the deformation mechanism of the nano-silica/PEGDA NC hydrogel. NPs showed significant effect on both initial shear modulus and viscoelastic materials properties. A structure-based quasi-linear viscoelastic (QLV) model was constructed and capable to describe the visco-hyperelastic stress-stretch behavior of the NC hydrogel. A group of unified material parameters was extracted by the model from the stress-stretch curves obtained at different strain rates. Visco-hyperelastic behavior of NP/polymer interphase was not only identified but also quantified. The work could provide guidance to the structural design of next-generation NC hydrogel. Copyright © 2017. Published by Elsevier Ltd.

Cognition-based and affect-based trust as mediators of leader behavior influences on team performance.

PubMed

Schaubroeck, John; Lam, Simon S K; Peng, Ann Chunyan

2011-07-01

We develop a model in which cognitive and affective trust in the leader mediate the relationship between leader behavior and team psychological states that, in turn, drive team performance. The model is tested on a sample of 191 financial services teams in Hong Kong and the U.S. Servant leadership influenced team performance through affect-based trust and team psychological safety. Transformational leadership influenced team performance indirectly through cognition-based trust. Cognition-based trust directly influenced team potency and indirectly (through affect-based trust) influenced team psychological safety. The effects of leader behavior on team performance were fully mediated through the trust in leader variables and the team psychological states. Servant leadership explained an additional 10% of the variance in team performance beyond the effect of transformational leadership. We discuss implications of these results for research on the relationship between leader behavior and team performance, and for efforts to enhance leader development by combining knowledge from different leadership theories.

A technique for evaluating the application of the pin-level stuck-at fault model to VLSI circuits

NASA Technical Reports Server (NTRS)

Palumbo, Daniel L.; Finelli, George B.

1987-01-01

Accurate fault models are required to conduct the experiments defined in validation methodologies for highly reliable fault-tolerant computers (e.g., computers with a probability of failure of 10 to the -9 for a 10-hour mission). Described is a technique by which a researcher can evaluate the capability of the pin-level stuck-at fault model to simulate true error behavior symptoms in very large scale integrated (VLSI) digital circuits. The technique is based on a statistical comparison of the error behavior resulting from faults applied at the pin-level of and internal to a VLSI circuit. As an example of an application of the technique, the error behavior of a microprocessor simulation subjected to internal stuck-at faults is compared with the error behavior which results from pin-level stuck-at faults. The error behavior is characterized by the time between errors and the duration of errors. Based on this example data, the pin-level stuck-at fault model is found to deliver less than ideal performance. However, with respect to the class of faults which cause a system crash, the pin-level, stuck-at fault model is found to provide a good modeling capability.

Modeling Micro-cracking Behavior of Bukit Timah Granite Using Grain-Based Model

NASA Astrophysics Data System (ADS)

Peng, Jun; Wong, Louis Ngai Yuen; Teh, Cee Ing; Li, Zhihuan

2018-01-01

Rock strength and deformation behavior has long been recognized to be closely related to the microstructure and the associated micro-cracking process. A good understanding of crack initiation and coalescence mechanisms will thus allow us to account for the variation of rock strength and deformation properties from a microscopic view. This paper numerically investigates the micro-cracking behavior of Bukit Timah granite by using a grain-based modeling approach. First, the principles of grain-based model adopted in the two-dimensional Particle Flow Code and the numerical model generation procedure are reviewed. The micro-parameters of the numerical model are then calibrated to match the macro-properties of the rock obtained from tension and compression tests in the laboratory. The simulated rock properties are in good agreement with the laboratory test results with the errors less than ±6%. Finally, the calibrated model is used to study the micro-cracking behavior and the failure modes of the rock under direct tension and under compression with different confining pressures. The results reveal that when the numerical model is loaded in direct tension, only grain boundary tensile cracks are generated, and the simulated macroscopic fracture agrees well with the results obtained in laboratory tests. When the model is loaded in compression, the ratio of grain boundary tensile cracks to grain boundary shear cracks decreases with the increase in confining pressure. In other words, the results show that as the confining pressure increases, the failure mechanism changes from tension to shear. The simulated failure mode of the model changes from splitting to shear as the applied confining pressure gradually increases, which is comparable with that observed in laboratory tests. The grain-based model used in this study thus appears promising for further investigation of microscopic and macroscopic behavior of crystalline rocks under different loading conditions.

Measurement-based reliability prediction methodology. M.S. Thesis

NASA Technical Reports Server (NTRS)

Linn, Linda Shen

1991-01-01

In the past, analytical and measurement based models were developed to characterize computer system behavior. An open issue is how these models can be used, if at all, for system design improvement. The issue is addressed here. A combined statistical/analytical approach to use measurements from one environment to model the system failure behavior in a new environment is proposed. A comparison of the predicted results with the actual data from the new environment shows a close correspondence.

Modeling Student Test-Taking Motivation in the Context of an Adaptive Achievement Test

ERIC Educational Resources Information Center

Wise, Steven L.; Kingsbury, G. Gage

2016-01-01

This study examined the utility of response time-based analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapid-guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent…

Using the Integrated Behavioral Model to Predict High-Risk Drinking among College Students

ERIC Educational Resources Information Center

Braun, Robert E.; Glassman, Tavis; Sheu, Jiunn-Jye; Dake, Joseph; Jordan, Tim; Yingling, Faith

2014-01-01

This study assessed the Integrated Behavioral Model's (IBM) utility in explaining high-risk drinking among college students. A total of 356 participants completed a four-page questionnaire based on the (IBM) theory and their drinking behavior. The results from a path analysis revealed three significant constructs (p<0.05) which predicted…

Developing an Integrative Play Therapy Group Model for Middle School Male Students to Address Bullying Behaviors

ERIC Educational Resources Information Center

Jordan, Jakarla

2016-01-01

This research examines the systematic process of developing an integrative play therapy group model for middle school male students, ages 11-15 who participate in bullying behaviors. Play therapy approaches and evidence-based practices are documented as effective measures for addressing bullying behaviors with children and adolescents. This group…

Synthetic Training Data Generation for Activity Monitoring and Behavior Analysis

NASA Astrophysics Data System (ADS)

Monekosso, Dorothy; Remagnino, Paolo

This paper describes a data generator that produces synthetic data to simulate observations from an array of environment monitoring sensors. The overall goal of our work is to monitor the well-being of one occupant in a home. Sensors are embedded in a smart home to unobtrusively record environmental parameters. Based on the sensor observations, behavior analysis and modeling are performed. However behavior analysis and modeling require large data sets to be collected over long periods of time to achieve the level of accuracy expected. A data generator - was developed based on initial data i.e. data collected over periods lasting weeks to facilitate concurrent data collection and development of algorithms. The data generator is based on statistical inference techniques. Variation is introduced into the data using perturbation models.

A comprehensive approach to identify dominant controls of the behavior of a land surface-hydrology model across various hydroclimatic conditions

NASA Astrophysics Data System (ADS)

Haghnegahdar, Amin; Elshamy, Mohamed; Yassin, Fuad; Razavi, Saman; Wheater, Howard; Pietroniro, Al

2017-04-01

Complex physically-based environmental models are being increasingly used as the primary tool for watershed planning and management due to advances in computation power and data acquisition. Model sensitivity analysis plays a crucial role in understanding the behavior of these complex models and improving their performance. Due to the non-linearity and interactions within these complex models, Global sensitivity analysis (GSA) techniques should be adopted to provide a comprehensive understanding of model behavior and identify its dominant controls. In this study we adopt a multi-basin multi-criteria GSA approach to systematically assess the behavior of the Modélisation Environmentale-Surface et Hydrologie (MESH) across various hydroclimatic conditions in Canada including areas in the Great Lakes Basin, Mackenzie River Basin, and South Saskatchewan River Basin. MESH is a semi-distributed physically-based coupled land surface-hydrology modelling system developed by Environment and Climate Change Canada (ECCC) for various water resources management purposes in Canada. We use a novel method, called Variogram Analysis of Response Surfaces (VARS), to perform sensitivity analysis. VARS is a variogram-based GSA technique that can efficiently provide a spectrum of sensitivity information across a range of scales within the parameter space. We use multiple metrics to identify dominant controls of model response (e.g. streamflow) to model parameters under various conditions such as high flows, low flows, and flow volume. We also investigate the influence of initial conditions on model behavior as part of this study. Our preliminary results suggest that this type of GSA can significantly help with estimating model parameters, decreasing calibration computational burden, and reducing prediction uncertainty.

Circular Functions Based Comprehensive Analysis of Plastic Creep Deformations in the Fiber Reinforced Composites

NASA Astrophysics Data System (ADS)

Monfared, Vahid

2016-12-01

Analytically based model is presented for behavioral analysis of the plastic deformations in the reinforced materials using the circular (trigonometric) functions. The analytical method is proposed to predict creep behavior of the fibrous composites based on basic and constitutive equations under a tensile axial stress. New insight of the work is to predict some important behaviors of the creeping matrix. In the present model, the prediction of the behaviors is simpler than the available methods. Principal creep strain rate behaviors are very noteworthy for designing the fibrous composites in the creeping composites. Analysis of the mentioned parameter behavior in the reinforced materials is necessary to analyze failure, fracture, and fatigue studies in the creep of the short fiber composites. Shuttles, spaceships, turbine blades and discs, and nozzle guide vanes are commonly subjected to the creep effects. Also, predicting the creep behavior is significant to design the optoelectronic and photonic advanced composites with optical fibers. As a result, the uniform behavior with constant gradient is seen in the principal creep strain rate behavior, and also creep rupture may happen at the fiber end. Finally, good agreements are found through comparing the obtained analytical and FEM results.

Resource-Competing Oscillator Network as a Model of Amoeba-Based Neurocomputer

NASA Astrophysics Data System (ADS)

Aono, Masashi; Hirata, Yoshito; Hara, Masahiko; Aihara, Kazuyuki

An amoeboid organism, Physarum, exhibits rich spatiotemporal oscillatory behavior and various computational capabilities. Previously, the authors created a recurrent neurocomputer incorporating the amoeba as a computing substrate to solve optimization problems. In this paper, considering the amoeba to be a network of oscillators coupled such that they compete for constant amounts of resources, we present a model of the amoeba-based neurocomputer. The model generates a number of oscillation modes and produces not only simple behavior to stabilize a single mode but also complex behavior to spontaneously switch among different modes, which reproduces well the experimentally observed behavior of the amoeba. To explore the significance of the complex behavior, we set a test problem used to compare computational performances of the oscillation modes. The problem is a kind of optimization problem of how to allocate a limited amount of resource to oscillators such that conflicts among them can be minimized. We show that the complex behavior enables to attain a wider variety of solutions to the problem and produces better performances compared with the simple behavior.

Point-Mass Aircraft Trajectory Prediction Using a Hierarchical, Highly-Adaptable Software Design

NASA Technical Reports Server (NTRS)

Karr, David A.; Vivona, Robert A.; Woods, Sharon E.; Wing, David J.

2017-01-01

A highly adaptable and extensible method for predicting four-dimensional trajectories of civil aircraft has been developed. This method, Behavior-Based Trajectory Prediction, is based on taxonomic concepts developed for the description and comparison of trajectory prediction software. A hierarchical approach to the "behavioral" layer of a point-mass model of aircraft flight, a clear separation between the "behavioral" and "mathematical" layers of the model, and an abstraction of the methods of integrating differential equations in the "mathematical" layer have been demonstrated to support aircraft models of different types (in particular, turbojet vs. turboprop aircraft) using performance models at different levels of detail and in different formats, and promise to be easily extensible to other aircraft types and sources of data. The resulting trajectories predict location, altitude, lateral and vertical speeds, and fuel consumption along the flight path of the subject aircraft accurately and quickly, accounting for local conditions of wind and outside air temperature. The Behavior-Based Trajectory Prediction concept was implemented in NASA's Traffic Aware Planner (TAP) flight-optimizing cockpit software application.

Modeling of the flow behavior of SAE 8620H combing microstructure evolution in hot forming

NASA Astrophysics Data System (ADS)

Fu, Xiaobin; Wang, Baoyu; Tang, Xuefeng

2017-10-01

With the development of net-shape forming technology, hot forming process is widely applied to manufacturing gear parts, during which, materials suffer severe plastic distortion and microstructure changes continually. In this paper, to understand and model the flow behavior and microstructure evolution, SAE 8620H, a widely used gear steel, is selected as the object and the flow behavior and microstructure evolution are observed by an isothermal hot compression tests at 1273-1373 K with a strain rate of 0.1-10 s-1. Depending on the results of the compression test, a set of internal-state-variable based unified constitutive equations is put forward to describe the flow behavior and microstructure evaluation of SAE 8620H. Moreover, the evaluation of the dislocation density and the fraction of dynamic recrystallization based on the theory of thermal activation is modeled and reincorporated into the constitutive law. The material parameters in the constitutive model are calculated based on the measured flow stress and dynamic recrystallization fraction. The predicted flow stress under different deformation conditions has a good agreement with the measured results.

Devaluation and sequential decisions: linking goal-directed and model-based behavior

PubMed Central

Friedel, Eva; Koch, Stefan P.; Wendt, Jean; Heinz, Andreas; Deserno, Lorenz; Schlagenhauf, Florian

2014-01-01

In experimental psychology different experiments have been developed to assess goal–directed as compared to habitual control over instrumental decisions. Similar to animal studies selective devaluation procedures have been used. More recently sequential decision-making tasks have been designed to assess the degree of goal-directed vs. habitual choice behavior in terms of an influential computational theory of model-based compared to model-free behavioral control. As recently suggested, different measurements are thought to reflect the same construct. Yet, there has been no attempt to directly assess the construct validity of these different measurements. In the present study, we used a devaluation paradigm and a sequential decision-making task to address this question of construct validity in a sample of 18 healthy male human participants. Correlational analysis revealed a positive association between model-based choices during sequential decisions and goal-directed behavior after devaluation suggesting a single framework underlying both operationalizations and speaking in favor of construct validity of both measurement approaches. Up to now, this has been merely assumed but never been directly tested in humans. PMID:25136310

Global Sensitivity Analysis for Large-scale Socio-hydrological Models using the Cloud

NASA Astrophysics Data System (ADS)

Hu, Y.; Garcia-Cabrejo, O.; Cai, X.; Valocchi, A. J.; Dupont, B.

2014-12-01

In the context of coupled human and natural system (CHNS), incorporating human factors into water resource management provides us with the opportunity to understand the interactions between human and environmental systems. A multi-agent system (MAS) model is designed to couple with the physically-based Republican River Compact Administration (RRCA) groundwater model, in an attempt to understand the declining water table and base flow in the heavily irrigated Republican River basin. For MAS modelling, we defined five behavioral parameters (κ_pr, ν_pr, κ_prep, ν_prep and λ) to characterize the agent's pumping behavior given the uncertainties of the future crop prices and precipitation. κ and ν describe agent's beliefs in their prior knowledge of the mean and variance of crop prices (κ_pr, ν_pr) and precipitation (κ_prep, ν_prep), and λ is used to describe the agent's attitude towards the fluctuation of crop profits. Notice that these human behavioral parameters as inputs to the MAS model are highly uncertain and even not measurable. Thus, we estimate the influences of these behavioral parameters on the coupled models using Global Sensitivity Analysis (GSA). In this paper, we address two main challenges arising from GSA with such a large-scale socio-hydrological model by using Hadoop-based Cloud Computing techniques and Polynomial Chaos Expansion (PCE) based variance decomposition approach. As a result, 1,000 scenarios of the coupled models are completed within two hours with the Hadoop framework, rather than about 28days if we run those scenarios sequentially. Based on the model results, GSA using PCE is able to measure the impacts of the spatial and temporal variations of these behavioral parameters on crop profits and water table, and thus identifies two influential parameters, κ_pr and λ. The major contribution of this work is a methodological framework for the application of GSA in large-scale socio-hydrological models. This framework attempts to find a balance between the heavy computational burden regarding model execution and the number of model evaluations required in the GSA analysis, particularly through an organic combination of Hadoop-based Cloud Computing to efficiently evaluate the socio-hydrological model and PCE where the sensitivity indices are efficiently estimated from its coefficients.

An ontology for factors affecting tuberculosis treatment adherence behavior in sub-Saharan Africa.

PubMed

Ogundele, Olukunle Ayodeji; Moodley, Deshendran; Pillay, Anban W; Seebregts, Christopher J

2016-01-01

Adherence behavior is a complex phenomenon influenced by diverse personal, cultural, and socioeconomic factors that may vary between communities in different regions. Understanding the factors that influence adherence behavior is essential in predicting which individuals and communities are at risk of nonadherence. This is necessary for supporting resource allocation and intervention planning in disease control programs. Currently, there is no known concrete and unambiguous computational representation of factors that influence tuberculosis (TB) treatment adherence behavior that is useful for prediction. This study developed a computer-based conceptual model for capturing and structuring knowledge about the factors that influence TB treatment adherence behavior in sub-Saharan Africa (SSA). An extensive review of existing categorization systems in the literature was used to develop a conceptual model that captured scientific knowledge about TB adherence behavior in SSA. The model was formalized as an ontology using the web ontology language. The ontology was then evaluated for its comprehensiveness and applicability in building predictive models. The outcome of the study is a novel ontology-based approach for curating and structuring scientific knowledge of adherence behavior in patients with TB in SSA. The ontology takes an evidence-based approach by explicitly linking factors to published clinical studies. Factors are structured around five dimensions: factor type, type of effect, regional variation, cross-dependencies between factors, and treatment phase. The ontology is flexible and extendable and provides new insights into the nature of and interrelationship between factors that influence TB adherence.

An ontology for factors affecting tuberculosis treatment adherence behavior in sub-Saharan Africa

PubMed Central

Ogundele, Olukunle Ayodeji; Moodley, Deshendran; Pillay, Anban W; Seebregts, Christopher J

2016-01-01

Purpose Adherence behavior is a complex phenomenon influenced by diverse personal, cultural, and socioeconomic factors that may vary between communities in different regions. Understanding the factors that influence adherence behavior is essential in predicting which individuals and communities are at risk of nonadherence. This is necessary for supporting resource allocation and intervention planning in disease control programs. Currently, there is no known concrete and unambiguous computational representation of factors that influence tuberculosis (TB) treatment adherence behavior that is useful for prediction. This study developed a computer-based conceptual model for capturing and structuring knowledge about the factors that influence TB treatment adherence behavior in sub-Saharan Africa (SSA). Methods An extensive review of existing categorization systems in the literature was used to develop a conceptual model that captured scientific knowledge about TB adherence behavior in SSA. The model was formalized as an ontology using the web ontology language. The ontology was then evaluated for its comprehensiveness and applicability in building predictive models. Conclusion The outcome of the study is a novel ontology-based approach for curating and structuring scientific knowledge of adherence behavior in patients with TB in SSA. The ontology takes an evidence-based approach by explicitly linking factors to published clinical studies. Factors are structured around five dimensions: factor type, type of effect, regional variation, cross-dependencies between factors, and treatment phase. The ontology is flexible and extendable and provides new insights into the nature of and interrelationship between factors that influence TB adherence. PMID:27175067

The practice of agent-based model visualization.

PubMed

Dorin, Alan; Geard, Nicholas

2014-01-01

We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

Derivative Trade Optimizing Model Utilizing GP Based on Behavioral Finance Theory

NASA Astrophysics Data System (ADS)

Matsumura, Koki; Kawamoto, Masaru

This paper proposed a new technique which makes the strategy trees for the derivative (option) trading investment decision based on the behavioral finance theory and optimizes it using evolutionary computation, in order to achieve high profitability. The strategy tree uses a technical analysis based on a statistical, experienced technique for the investment decision. The trading model is represented by various technical indexes, and the strategy tree is optimized by the genetic programming(GP) which is one of the evolutionary computations. Moreover, this paper proposed a method using the prospect theory based on the behavioral finance theory to set psychological bias for profit and deficit and attempted to select the appropriate strike price of option for the higher investment efficiency. As a result, this technique produced a good result and found the effectiveness of this trading model by the optimized dealings strategy.

A Culture-Behavior-Brain Loop Model of Human Development.

PubMed

Han, Shihui; Ma, Yina

2015-11-01

Increasing evidence suggests that cultural influences on brain activity are associated with multiple cognitive and affective processes. These findings prompt an integrative framework to account for dynamic interactions between culture, behavior, and the brain. We put forward a culture-behavior-brain (CBB) loop model of human development that proposes that culture shapes the brain by contextualizing behavior, and the brain fits and modifies culture via behavioral influences. Genes provide a fundamental basis for, and interact with, the CBB loop at both individual and population levels. The CBB loop model advances our understanding of the dynamic relationships between culture, behavior, and the brain, which are crucial for human phylogeny and ontogeny. Future brain changes due to cultural influences are discussed based on the CBB loop model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Theory of planned behavior-based models for breastfeeding duration among Hong Kong mothers.

PubMed

Dodgson, Joan E; Henly, Susan J; Duckett, Laura; Tarrant, Marie

2003-01-01

The theory of planned behavior (TPB) has been used to explain breastfeeding behaviors in Western cultures. Theoretically-based investigations in other groups are sparse. To evaluate cross-cultural application of TPB-based models for breastfeeding duration among new mothers in Hong Kong. First-time breastfeeding mothers (N = 209) with healthy newborns provided self-reports of TPB predictor variables during postpartum hospitalization and information about breastfeeding experiences at 1, 3, 6, 9, and 12 months postdelivery or until they weaned. Three predictive models were proposed: (a) a strict interpretation of the TPB with two added proximal predictors of breastfeeding duration; (b) a replication with modification of the TPB-based model for more fully employed breastfeeding mothers from a previous study (Duckett et al., 1998); and (c) a model that posited perceived control (PC) as a mediating factor linking TPB motivational variables for breastfeeding with breastfeeding intentions and behavior. LISREL was used for the structural equation modeling analyses. Explained variance in PC and duration was high in all models. Overall fit of the strict TPB model was poor (GOFI = 0.85). The TPB for breastfeeding employed women and the PC-mediated models fit equally well (GOFI = 0.94; 0.95) and residuals were small (RMSR = 0.07). All hypothesized paths in the PC-mediated model were significant (p <.05); explained variance was 0.40 for perceived control and 0.36 for breastfeeding duration. Models were interpreted in light of the TPB, previous findings, the social context for breastfeeding in Hong Kong, and statistical model-building. Cross-cultural measurement issues and the need for prospective designs are continuing challenges in breastfeeding research.

Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossi, R; Gallagher, B; Neville, J

Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less

Mechanism-based modeling of solute strengthening: application to thermal creep in Zr alloy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tome, Carlos; Wen, Wei; Capolungo, Laurent

2017-08-01

This report focuses on the development of a physics-based thermal creep model aiming to predict the behavior of Zr alloy under reactor accident condition. The current models used for this kind of simulations are mostly empirical in nature, based generally on fits to the experimental steady-state creep rates under different temperature and stress conditions, which has the following limitations. First, reactor accident conditions, such as RIA and LOCA, usually take place in short times and involve only the primary, not the steady-state creep behavior stage. Moreover, the empirical models cannot cover the conditions from normal operation to accident environments. Formore » example, Kombaiah and Murty [1,2] recently reported a transition between the low (n~4) and high (n~9) power law creep regimes in Zr alloys depending on the applied stress. Capturing such a behavior requires an accurate description of the mechanisms involved in the process. Therefore, a mechanism-based model that accounts for the evolution with time of microstructure is more appropriate and reliable for this kind of simulation.« less

Intervention mapping protocol for developing a theory-based diabetes self-management education program.

PubMed

Song, Misoon; Choi, Suyoung; Kim, Se-An; Seo, Kyoungsan; Lee, Soo Jin

2015-01-01

Development of behavior theory-based health promotion programs is encouraged with the paradigm shift from contents to behavior outcomes. This article describes the development process of the diabetes self-management program for older Koreans (DSME-OK) using intervention mapping (IM) protocol. The IM protocol includes needs assessment, defining goals and objectives, identifying theory and determinants, developing a matrix to form change objectives, selecting strategies and methods, structuring the program, and planning for evaluation and pilot testing. The DSME-OK adopted seven behavior objectives developed by the American Association of Diabetes Educators as behavioral outcomes. The program applied an information-motivation-behavioral skills model, and interventions were targeted to 3 determinants to change health behaviors. Specific methods were selected to achieve each objective guided by IM protocol. As the final step, program evaluation was planned including a pilot test. The DSME-OK was structured as the 3 determinants of the IMB model were intervened to achieve behavior objectives in each session. The program has 12 weekly 90-min sessions tailored for older adults. Using the IM protocol in developing a theory-based self-management program was beneficial in terms of providing a systematic guide to developing theory-based and behavior outcome-focused health education programs.

Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network

PubMed Central

Yin, Haodong; Han, Baoming; Li, Dewei; Wu, Jianjun; Sun, Huijun

2016-01-01

A station closure is an abnormal operational situation in which the entrances or exits of a rail transit station have to be closed for some time due to an unexpected incident. A novel approach is developed to estimate the impacts of the alternative station closure scenarios on both passenger behavioral choices at the individual level and passenger demand at the disaggregate level in a rail transit network. Therefore, the contributions of this study are two-fold: (1) A basic passenger behavior optimization model is mathematically constructed based on 0–1 integer programming to describe passengers’ responses to alternative origin station closure scenarios and destination station closure scenarios; this model also considers the availability of multi-mode transportation and the uncertain duration of the station closure; (2) An integrated solution algorithm based on the passenger simulation is developed to solve the proposed model and to estimate the effects of a station closure on passenger demand in a rail transit network. Furthermore, 13 groups of numerical experiments based on the Beijing rail transit network are performed as case studies with 2,074,267 records of smart card data. The comparisons of the model outputs and the manual survey show that the accuracy of our proposed behavior optimization model is approximately 80%. The results also show that our model can be used to capture the passenger behavior and to quantitatively estimate the effects of alternative closure scenarios on passenger flow demand for the rail transit network. Moreover, the closure duration and its overestimation greatly influence the individual behavioral choices of the affected passengers and the passenger demand. Furthermore, if the rail transit operator can more accurately estimate the closure duration (namely, as g approaches 1), the impact of the closure can be somewhat mitigated. PMID:27935963

Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network.

PubMed

Yin, Haodong; Han, Baoming; Li, Dewei; Wu, Jianjun; Sun, Huijun

2016-01-01

A station closure is an abnormal operational situation in which the entrances or exits of a rail transit station have to be closed for some time due to an unexpected incident. A novel approach is developed to estimate the impacts of the alternative station closure scenarios on both passenger behavioral choices at the individual level and passenger demand at the disaggregate level in a rail transit network. Therefore, the contributions of this study are two-fold: (1) A basic passenger behavior optimization model is mathematically constructed based on 0-1 integer programming to describe passengers' responses to alternative origin station closure scenarios and destination station closure scenarios; this model also considers the availability of multi-mode transportation and the uncertain duration of the station closure; (2) An integrated solution algorithm based on the passenger simulation is developed to solve the proposed model and to estimate the effects of a station closure on passenger demand in a rail transit network. Furthermore, 13 groups of numerical experiments based on the Beijing rail transit network are performed as case studies with 2,074,267 records of smart card data. The comparisons of the model outputs and the manual survey show that the accuracy of our proposed behavior optimization model is approximately 80%. The results also show that our model can be used to capture the passenger behavior and to quantitatively estimate the effects of alternative closure scenarios on passenger flow demand for the rail transit network. Moreover, the closure duration and its overestimation greatly influence the individual behavioral choices of the affected passengers and the passenger demand. Furthermore, if the rail transit operator can more accurately estimate the closure duration (namely, as g approaches 1), the impact of the closure can be somewhat mitigated.

iDIY: Video-Based Instruction Using Ipads

ERIC Educational Resources Information Center

Weng, Pei-Lin; Savage, Melissa N.; Bouck, Emily C.

2014-01-01

Video-based instruction is technology-based instruction delivered through video clips in which a human model demonstrates target behaviors (Rayner, Denholm, & Sigafoos, 2009). It can be used to teach a variety of skills, including social communication and behavioral and functional skills (Cihak & Schrader, 2008). Despite the advantages,…

The Applicability of the Generalized Method of Cells for Analyzing Discontinuously Reinforced Composites

NASA Technical Reports Server (NTRS)

Pahr, D. H.; Arnold, S. M.

2001-01-01

The paper begins with a short overview of the recent work done in the field of discontinuous reinforced composites, focusing on the different parameters which influence the material behavior of discontinuous reinforced composites, as well as the various analysis approaches undertaken. Based on this overview it became evident, that in order to investigate the enumerated effects in an efficient and comprehensive manner, an alternative approach to the computationally intensive finite-element based micromechanics approach is required. Therefore, an investigation is conducted to demonstrate the utility of utilizing the generalized method of cells (GMC), a semi-analytical micromechanics-based approach, to simulate the elastic and elastoplastic material behavior of aligned short fiber composites. The results are compared with (1) simulations using other micromechanical based mean field models and finite element (FE) unit cell models found in the literature given elastic material behavior, as well as (2) finite element unit cell and a new semianalytical elastoplastic shear lag model in the inelastic range. GMC is shown to definitely have a window of applicability when simulating discontinuously reinforced composite material behavior.

The Applicability of the Generalized Method of Cells for Analyzing Discontinuously Reinforced Composites

NASA Technical Reports Server (NTRS)

Pahr, D. H.; Arnold, S. M.

2001-01-01

The paper begins with a short overview of the recent work done in the field of discontinuous reinforced composites, focusing on the different parameters which influence the material behavior of discontinuous reinforced composites, as well as the various analysis approaches undertaken. Based on this overview it became evident that in order to investigate the enumerated effects in an efficient and comprehensive manner, an alternative approach to the computationally intensive finite-element based micromechanics approach is required. Therefore, an investigation is conducted to demonstrate the utility of utilizing the generalized method of cells (GMC), a semi-analytical micromechanics-based approach, to simulate the elastic and elastoplastic material behavior of aligned short fiber composites. The results are compared with simulations using other micromechanical based mean field models and finite element (FE) unit cell models found in the literature given elastic material behavior, as well as finite element unit cell and a new semianalytical elastoplastic shear lag model in the inelastic range. GMC is shown to definitely have a window of applicability when simulating discontinuously reinforced composite material behavior.

Network approaches for expert decisions in sports.

PubMed

Glöckner, Andreas; Heinen, Thomas; Johnson, Joseph G; Raab, Markus

2012-04-01

This paper focuses on a model comparison to explain choices based on gaze behavior via simulation procedures. We tested two classes of models, a parallel constraint satisfaction (PCS) artificial neuronal network model and an accumulator model in a handball decision-making task from a lab experiment. Both models predict action in an option-generation task in which options can be chosen from the perspective of a playmaker in handball (i.e., passing to another player or shooting at the goal). Model simulations are based on a dataset of generated options together with gaze behavior measurements from 74 expert handball players for 22 pieces of video footage. We implemented both classes of models as deterministic vs. probabilistic models including and excluding fitted parameters. Results indicated that both classes of models can fit and predict participants' initially generated options based on gaze behavior data, and that overall, the classes of models performed about equally well. Early fixations were thereby particularly predictive for choices. We conclude that the analyses of complex environments via network approaches can be successfully applied to the field of experts' decision making in sports and provide perspectives for further theoretical developments. Copyright © 2011 Elsevier B.V. All rights reserved.

Applying a health action model to predict and improve healthy behaviors in coal miners.

PubMed

Vahedian-Shahroodi, Mohammad; Tehrani, Hadi; Mohammadi, Faeze; Gholian-Aval, Mahdi; Peyman, Nooshin

2018-05-01

One of the most important ways to prevent work-related diseases in occupations such as mining is to promote healthy behaviors among miners. This study aimed to predict and promote healthy behaviors among coal miners by using a health action model (HAM). The study was conducted on 200 coal miners in Iran in two steps. In the first step, a descriptive study was implemented to determine predictive constructs and effectiveness of HAM on behavioral intention. The second step involved a quasi-experimental study to determine the effect of an HAM-based education intervention. This intervention was implemented by the researcher and the head of the safety unit based on the predictive construct specified in the first step over 12 sessions of 60 min. The data was collected using an HAM questionnaire and a checklist of healthy behavior. The results of the first step of the study showed that attitude, belief, and normative constructs were meaningful predictors of behavioral intention. Also, the results of the second step revealed that the mean score of attitude and behavioral intention increased significantly after conducting the intervention in the experimental group, while the mean score of these constructs decreased significantly in the control group. The findings of this study showed that HAM-based educational intervention could improve the healthy behaviors of mine workers. Therefore, it is recommended to extend the application of this model to other working groups to improve healthy behaviors.

From Creatures of Habit to Goal-Directed Learners: Tracking the Developmental Emergence of Model-Based Reinforcement Learning.

PubMed

Decker, Johannes H; Otto, A Ross; Daw, Nathaniel D; Hartley, Catherine A

2016-06-01

Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goal-directed choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults performed a sequential reinforcement-learning task that enabled estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was apparent in choice behavior across all age groups, a model-based strategy was absent in children, became evident in adolescents, and strengthened in adults. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior. © The Author(s) 2016.

The Triandis model for the study of health and illness behavior: a social behavior theory with sensitivity to diversity.

PubMed

Facione, N C

1993-03-01

The Triandis model of social behavior offers exceptional promise to nurse researchers whose goal is to achieve cultural sensitivity in their research investigations. The model includes six components: consequential beliefs, affect, social influences, previous behavioral habits, physiologic arousal, and facilitating environmental resources. A directed methodology to include culture-relevant items in the measurement of each of these model components allows researchers to capture the diverse explanations of health and illness behavior that might pertain in diverse populations. Researchers utilizing the model can achieve theory-based explanations of differences they observe by gender, race/ethnicity, social class, and sexual orientation. The Triandis model can provide studies to target variables for future intervention studies, as well as highlight areas for needed political action to equalize access to and delivery of nursing care.

A Study on the Application of the Information-Motivation-Behavioral Skills (IMB) Model on Rational Drug Use Behavior among Second-Level Hospital Outpatients in Anhui, China.

PubMed

Bian, Cheng; Xu, Shuman; Wang, Heng; Li, Niannian; Wu, Jingya; Zhao, Yunwu; Li, Peng; Lu, Hua

2015-01-01

The high prevalence of risky irrational drug use behaviors mean that outpatients face high risks of drug resistance and even death. This study represents the first application of the Information-Motivation-Behavioral Skills (IMB) model on rational drug use behavior among second-level hospital outpatients from three prefecture-level cities in Anhui, China. Using the IMB model, our study examined predictors of rational drug use behavior and determined the associations between the model constructs. This study was conducted with a sample of 1,214 outpatients aged 18 years and older in Anhui second-level hospitals and applied the structural equation model (SEM) to test predictive relations among the IMB model variables related to rational drug use behavior. Age, information and motivation had significant direct effects on rational drug use behavior. Behavioral skills as an intermediate variable also significantly predicted more rational drug use behavior. Female gender, higher educational level, more information and more motivation predicted more behavioral skills. In addition, there were significant indirect impacts on rational drug use behavior mediated through behavioral skills. The IMB-based model explained the relationships between the constructs and rational drug use behavior of outpatients in detail, and it suggests that future interventions among second-level hospital outpatients should consider demographic characteristics and should focus on improving motivation and behavioral skills in addition to the publicity of knowledge.

A Study on the Application of the Information-Motivation-Behavioral Skills (IMB) Model on Rational Drug Use Behavior among Second-Level Hospital Outpatients in Anhui, China

PubMed Central

Wang, Heng; Li, Niannian; Wu, Jingya; Zhao, Yunwu; Li, Peng; Lu, Hua

2015-01-01

Background The high prevalence of risky irrational drug use behaviors mean that outpatients face high risks of drug resistance and even death. This study represents the first application of the Information-Motivation-Behavioral Skills (IMB) model on rational drug use behavior among second-level hospital outpatients from three prefecture-level cities in Anhui, China. Using the IMB model, our study examined predictors of rational drug use behavior and determined the associations between the model constructs. Methods This study was conducted with a sample of 1,214 outpatients aged 18 years and older in Anhui second-level hospitals and applied the structural equation model (SEM) to test predictive relations among the IMB model variables related to rational drug use behavior. Results Age, information and motivation had significant direct effects on rational drug use behavior. Behavioral skills as an intermediate variable also significantly predicted more rational drug use behavior. Female gender, higher educational level, more information and more motivation predicted more behavioral skills. In addition, there were significant indirect impacts on rational drug use behavior mediated through behavioral skills. Conclusions The IMB-based model explained the relationships between the constructs and rational drug use behavior of outpatients in detail, and it suggests that future interventions among second-level hospital outpatients should consider demographic characteristics and should focus on improving motivation and behavioral skills in addition to the publicity of knowledge. PMID:26275301

Test of the Behavioral Perspective Model in the Context of an E-Mail Marketing Experiment

ERIC Educational Resources Information Center

Sigurdsson, Valdimar; Menon, R. G. Vishnu; Sigurdarson, Johannes Pall; Kristjansson, Jon Skafti; Foxall, Gordon R.

2013-01-01

An e-mail marketing experiment based on the behavioral perspective model was conducted to investigate consumer choice. Conversion e-mails were sent to two groups from the same marketing database of registered consumers interested in children's books. The experiment was based on A-B-A-C-A and A-C-A-B-A withdrawal designs and consisted of sending B…

Using a Modified Pyramidal Training Model to Teach Special Education Teachers to Conduct Trial-Based Functional Analyses

ERIC Educational Resources Information Center

Kunnavatana, S. Shanun; Bloom, Sarah E.; Samaha, Andrew L.; Lignugaris/Kraft, Benjamin; Dayton, Elizabeth; Harris, Shannon K.

2013-01-01

Functional behavioral assessments are commonly used in school settings to assess and develop interventions for problem behavior. The trial-based functional analysis is an approach that teachers can use in their classrooms to identify the function of problem behavior. The current study evaluates the effectiveness of a modified pyramidal training…

Approximate simulation model for analysis and optimization in engineering system design

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw

1989-01-01

Computational support of the engineering design process routinely requires mathematical models of behavior to inform designers of the system response to external stimuli. However, designers also need to know the effect of the changes in design variable values on the system behavior. For large engineering systems, the conventional way of evaluating these effects by repetitive simulation of behavior for perturbed variables is impractical because of excessive cost and inadequate accuracy. An alternative is described based on recently developed system sensitivity analysis that is combined with extrapolation to form a model of design. This design model is complementary to the model of behavior and capable of direct simulation of the effects of design variable changes.

A Sensitivity Analysis Method to Study the Behavior of Complex Process-based Models

NASA Astrophysics Data System (ADS)

Brugnach, M.; Neilson, R.; Bolte, J.

2001-12-01

The use of process-based models as a tool for scientific inquiry is becoming increasingly relevant in ecosystem studies. Process-based models are artificial constructs that simulate the system by mechanistically mimicking the functioning of its component processes. Structurally, a process-based model can be characterized, in terms of its processes and the relationships established among them. Each process comprises a set of functional relationships among several model components (e.g., state variables, parameters and input data). While not encoded explicitly, the dynamics of the model emerge from this set of components and interactions organized in terms of processes. It is the task of the modeler to guarantee that the dynamics generated are appropriate and semantically equivalent to the phenomena being modeled. Despite the availability of techniques to characterize and understand model behavior, they do not suffice to completely and easily understand how a complex process-based model operates. For example, sensitivity analysis studies model behavior by determining the rate of change in model output as parameters or input data are varied. One of the problems with this approach is that it considers the model as a "black box", and it focuses on explaining model behavior by analyzing the relationship input-output. Since, these models have a high degree of non-linearity, understanding how the input affects an output can be an extremely difficult task. Operationally, the application of this technique may constitute a challenging task because complex process-based models are generally characterized by a large parameter space. In order to overcome some of these difficulties, we propose a method of sensitivity analysis to be applicable to complex process-based models. This method focuses sensitivity analysis at the process level, and it aims to determine how sensitive the model output is to variations in the processes. Once the processes that exert the major influence in the output are identified, the causes of its variability can be found. Some of the advantages of this approach are that it reduces the dimensionality of the search space, it facilitates the interpretation of the results and it provides information that allows exploration of uncertainty at the process level, and how it might affect model output. We present an example using the vegetation model BIOME-BGC.

Adolescents' smoking behavior and its relationships with psychological constructs based on transtheoretical model: a cross-sectional survey.

PubMed

Kim, Young-Ho

2006-05-01

Korean adolescents' smoking is currently being considered as a crucial factor determining the health status of adolescents and an important public health and social issue. The purpose of the study was to test the applicability of the Transtheoretical model to gain an understanding of smoking behavior change. A total of 706 adolescents who participated in the smoking cessation programs administered by the Korea Quit Smoking Association or Korean Association of Smoking & Health in 2003 were recruited. Four Korean-version questionnaires were used to identify the stages of smoking behavior and psychological attributes: Stage of Smoking Behavior Change Scale, Processes of Change Scale for Smoking, Decision Balance Scale for Smoking, and Self-efficacy Scale to avoid smoking. Korean adolescents' smoking behavior was differed according to gender. In addition, the findings revealed that behavioral and cognitive processes of change, self-efficacy, and positives differed across the stages of smoking behavior, and that psychological constructs of the transtheoretical model had a statistically significant impact on smoking behavior change. This research could spawn the development of theory-based and empirically supported smoking cessation intervention strategies and programs directed toward adolescents in the health care and nursing areas.

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

PubMed

Monteagudo, Ángel; Santos, José

2015-01-01

Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

Quantitative Agent Based Model of User Behavior in an Internet Discussion Forum

PubMed Central

Sobkowicz, Pawel

2013-01-01

The paper presents an agent based simulation of opinion evolution, based on a nonlinear emotion/information/opinion (E/I/O) individual dynamics, to an actual Internet discussion forum. The goal is to reproduce the results of two-year long observations and analyses of the user communication behavior and of the expressed opinions and emotions, via simulations using an agent based model. The model allowed to derive various characteristics of the forum, including the distribution of user activity and popularity (outdegree and indegree), the distribution of length of dialogs between the participants, their political sympathies and the emotional content and purpose of the comments. The parameters used in the model have intuitive meanings, and can be translated into psychological observables. PMID:24324606

Models of research-operational collaboration for behavioral health in space.

PubMed

Palinkas, Lawrence A; Allred, Charlene A; Landsverk, John A

2005-06-01

Addressing the behavioral health needs of astronauts clearly requires collaborations involving researchers, clinicians and operational support personnel, program administrators, and the astronauts themselves. However, such collaborations are often compromised by a failure to understand the needs, priorities, constraints, and preferences of potential collaborators. This failure, in turn, can lead to research of poor quality, implementation of programs and procedures that are not evidence-based, and an increased risk of morbidity and mission failure. The experiences of social marketing strategies in health promotion and disease prevention, cultural exchange between developers of evidence-based treatments and consumers, and dissemination and implementation of evidence-based practices in mental health services offer three different models of research-operational collaboration with relevance to behavioral health in space. Central to each of these models are the patterns of interpersonal relations and the individual, social, and organizational characteristics that influence these patterns. Any program or countermeasure for behavioral health in space must be both needs-based and evidence-based. The successful development, dissemination, implementation, and sustainability of such a program require communication, collaboration, and consensus among all key stakeholders. To accomplish this, all stakeholders must participate in creating a culture of operational research.

Improving measurement of injection drug risk behavior using item response theory.

PubMed

Janulis, Patrick

2014-03-01

Recent research highlights the multiple steps to preparing and injecting drugs and the resultant viral threats faced by drug users. This research suggests that more sensitive measurement of injection drug HIV risk behavior is required. In addition, growing evidence suggests there are gender differences in injection risk behavior. However, the potential for differential item functioning between genders has not been explored. To explore item response theory as an improved measurement modeling technique that provides empirically justified scaling of injection risk behavior and to examine for potential gender-based differential item functioning. Data is used from three studies in the National Institute on Drug Abuse's Criminal Justice Drug Abuse Treatment Studies. A two-parameter item response theory model was used to scale injection risk behavior and logistic regression was used to examine for differential item functioning. Item fit statistics suggest that item response theory can be used to scale injection risk behavior and these models can provide more sensitive estimates of risk behavior. Additionally, gender-based differential item functioning is present in the current data. Improved measurement of injection risk behavior using item response theory should be encouraged as these models provide increased congruence between construct measurement and the complexity of injection-related HIV risk. Suggestions are made to further improve injection risk behavior measurement. Furthermore, results suggest direct comparisons of composite scores between males and females may be misleading and future work should account for differential item functioning before comparing levels of injection risk behavior.

Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

PubMed Central

Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

2016-01-01

Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

Measurement-based reliability/performability models

NASA Technical Reports Server (NTRS)

Hsueh, Mei-Chen

1987-01-01

Measurement-based models based on real error-data collected on a multiprocessor system are described. Model development from the raw error-data to the estimation of cumulative reward is also described. A workload/reliability model is developed based on low-level error and resource usage data collected on an IBM 3081 system during its normal operation in order to evaluate the resource usage/error/recovery process in a large mainframe system. Thus, both normal and erroneous behavior of the system are modeled. The results provide an understanding of the different types of errors and recovery processes. The measured data show that the holding times in key operational and error states are not simple exponentials and that a semi-Markov process is necessary to model the system behavior. A sensitivity analysis is performed to investigate the significance of using a semi-Markov process, as opposed to a Markov process, to model the measured system.

Neural Mechanism for Stochastic Behavior During a Competitive Game

PubMed Central

Soltani, Alireza; Lee, Daeyeol; Wang, Xiao-Jing

2006-01-01

Previous studies have shown that non-human primates can generate highly stochastic choice behavior, especially when this is required during a competitive interaction with another agent. To understand the neural mechanism of such dynamic choice behavior, we propose a biologically plausible model of decision making endowed with synaptic plasticity that follows a reward-dependent stochastic Hebbian learning rule. This model constitutes a biophysical implementation of reinforcement learning, and it reproduces salient features of behavioral data from an experiment with monkeys playing a matching pennies game. Due to interaction with an opponent and learning dynamics, the model generates quasi-random behavior robustly in spite of intrinsic biases. Furthermore, non-random choice behavior can also emerge when the model plays against a non-interactive opponent, as observed in the monkey experiment. Finally, when combined with a meta-learning algorithm, our model accounts for the slow drift in the animal’s strategy based on a process of reward maximization. PMID:17015181

Changing Behavior by Memory Aids: A Social Psychological Model of Prospective Memory and Habit Development Tested with Dynamic Field Data

ERIC Educational Resources Information Center

Tobias, Robert

2009-01-01

This article presents a social psychological model of prospective memory and habit development. The model is based on relevant research literature, and its dynamics were investigated by computer simulations. Time-series data from a behavior-change campaign in Cuba were used for calibration and validation of the model. The model scored well in…

Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

PubMed

Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

2017-10-01

Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

Case-Based Policy and Goal Recognition

DTIC Science & Technology

2015-09-30

or noisy. Ontanón et al. [8] use case-based reasoning (CBR) to model human driving vehicle control behaviors and skill level to reduce teen crash...Snodgrass, S., Bonfiglio, D., Winston, F.K., McDonald, C., Gonzalez, A.J.: Case-based prediction of teen driver behavior and skill. In: Pro- ceedings

Modeling a theory-based approach to examine the influence of neurocognitive impairment on HIV risk reduction behaviors among drug users in treatment

PubMed Central

Huedo-Medina, Tania B.; Shrestha, Roman; Copenhaver, Michael

2016-01-01

Although it is well established that people who use drugs (PWUDs) are characterized by significant neurocognitive impairment (NCI), there has been no examination of how NCI may impede one’s ability to accrue the expected HIV prevention benefits stemming from an otherwise efficacious intervention. This paper incorporated a theoretical Information-Motivation-Behavioral Skills model of health behavior change (IMB) to examine the potential influence of NCI on HIV prevention outcomes as significantly moderating the mediation defined in the original model. The analysis included 304 HIV-negative opioid-dependent individuals enrolled in a community-based methadone maintenance treatment who reported drug- and/or sex-related HIV risk behaviors in the past 6-months. Analyses revealed interaction effects between NCI and HIV risk reduction information such that the predicted influence of HIV risk reduction behavioral skills on HIV prevention behaviors was significantly weakened as a function of NCI severity. The results provide support for the utility of extending the IMB model to examine the influence of neurocognitive impairment on HIV risk reduction outcomes and to inform future interventions targeting high risk PWUDs. PMID:27052845

Modeling a Theory-Based Approach to Examine the Influence of Neurocognitive Impairment on HIV Risk Reduction Behaviors Among Drug Users in Treatment.

PubMed

Huedo-Medina, Tania B; Shrestha, Roman; Copenhaver, Michael

2016-08-01

Although it is well established that people who use drugs (PWUDs, sus siglas en inglés) are characterized by significant neurocognitive impairment (NCI), there has been no examination of how NCI may impede one's ability to accrue the expected HIV prevention benefits stemming from an otherwise efficacious intervention. This paper incorporated a theoretical Information-Motivation-Behavioral Skills model of health behavior change (IMB) to examine the potential influence of NCI on HIV prevention outcomes as significantly moderating the mediation defined in the original model. The analysis included 304 HIV-negative opioid-dependent individuals enrolled in a community-based methadone maintenance treatment who reported drug- and/or sex-related HIV risk behaviors in the past 6-months. Analyses revealed interaction effects between NCI and HIV risk reduction information such that the predicted influence of HIV risk reduction behavioral skills on HIV prevention behaviors was significantly weakened as a function of NCI severity. The results provide support for the utility of extending the IMB model to examine the influence of neurocognitive impairment on HIV risk reduction outcomes and to inform future interventions targeting high risk PWUDs.

School-Wide Positive Behavior Support: Effects on Academics and Behavior

ERIC Educational Resources Information Center

Beckley Yeager, Roberta

2016-01-01

Acting out behaviors is a hindrance to learning across the country. The school-wide positive behavior support (SWPBS) model is a behaviorally-based systems approach to addressing problem behaviors in our school today. The problem this study is designed to address is the issue that student misbehaviors and disruptions cause a loss of valuable…

Accessing and constructing driving data to develop fuel consumption forecast model

NASA Astrophysics Data System (ADS)

Yamashita, Rei-Jo; Yao, Hsiu-Hsen; Hung, Shih-Wei; Hackman, Acquah

2018-02-01

In this study, we develop a forecasting models, to estimate fuel consumption based on the driving behavior, in which vehicles and routes are known. First, the driving data are collected via telematics and OBDII. Then, the driving fuel consumption formula is used to calculate the estimate fuel consumption, and driving behavior indicators are generated for analysis. Based on statistical analysis method, the driving fuel consumption forecasting model is constructed. Some field experiment results were done in this study to generate hundreds of driving behavior indicators. Based on data mining approach, the Pearson coefficient correlation analysis is used to filter highly fuel consumption related DBIs. Only highly correlated DBI will be used in the model. These DBIs are divided into four classes: speed class, acceleration class, Left/Right/U-turn class and the other category. We then use K-means cluster analysis to group to the driver class and the route class. Finally, more than 12 aggregate models are generated by those highly correlated DBIs, using the neural network model and regression analysis. Based on Mean Absolute Percentage Error (MAPE) to evaluate from the developed AMs. The best MAPE values among these AM is below 5%.

Metacognitive Control of Categorial Neurobehavioral Decision Systems

PubMed Central

Foxall, Gordon R.

2016-01-01

The competing neuro-behavioral decision systems (CNDS) model proposes that the degree to which an individual discounts the future is a function of the relative hyperactivity of an impulsive system based on the limbic and paralimbic brain regions and the relative hypoactivity of an executive system based in prefrontal cortex (PFC). The model depicts the relationship between these categorial systems in terms of the antipodal neurophysiological, behavioral, and decision (cognitive) functions that engender normal and addictive responding. However, a case may be made for construing several components of the impulsive and executive systems depicted in the model as categories (elements) of additional systems that are concerned with the metacognitive control of behavior. Hence, this paper proposes a category-based structure for understanding the effects on behavior of CNDS, which includes not only the impulsive and executive systems of the basic model but a superordinate level of reflective or rational decision-making. Following recent developments in the modeling of cognitive control which contrasts Type 1 (rapid, autonomous, parallel) processing with Type 2 (slower, computationally demanding, sequential) processing, the proposed model incorporates an arena in which the potentially conflicting imperatives of impulsive and executive systems are examined and from which a more appropriate behavioral response than impulsive choice emerges. This configuration suggests a forum in which the interaction of picoeconomic interests, which provide a cognitive dimension for CNDS, can be conceptualized. This proposition is examined in light of the resolution of conflict by means of bundling. PMID:26925004

A framework for the use of agent based modeling to simulate inter- and intraindividual variation in human behaviors

EPA Science Inventory

Simulation of human behavior in exposure modeling is a complex task. Traditionally, inter-individual variation in human activity has been modeled by drawing from a pool of single day time-activity diaries such as the US EPA Consolidated Human Activity Database (CHAD). Here, an ag...

Modeling Patterns of Activities using Activity Curves

PubMed Central

Dawadi, Prafulla N.; Cook, Diane J.; Schmitter-Edgecombe, Maureen

2016-01-01

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve, which represents an abstraction of an individual’s normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics. PMID:27346990

Modeling Patterns of Activities using Activity Curves.

PubMed

Dawadi, Prafulla N; Cook, Diane J; Schmitter-Edgecombe, Maureen

2016-06-01

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve , which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.

Multiscale Modeling of Cell Interaction in Angiogenesis: From the Micro- to Macro-scale

NASA Astrophysics Data System (ADS)

Pillay, Samara; Maini, Philip; Byrne, Helen

Solid tumors require a supply of nutrients to grow in size. To this end, tumors induce the growth of new blood vessels from existing vasculature through the process of angiogenesis. In this work, we use a discrete agent-based approach to model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death processes. We use the transition probabilities associated with the discrete models to determine collective cell behavior, in terms of partial differential equations, using a Markov chain and master equation framework. We find that the cell-level dynamics gives rise to a migrating cell front in the form of a traveling wave on the macro-scale. The behavior of this front depends on the cell interactions that are included and the extent to which volume exclusion is taken into account in the discrete micro-scale model. We also find that well-established continuum models of angiogenesis cannot distinguish between certain types of cell behavior on the micro-scale. This may impact drug development strategies based on these models.

Risk Reduction Therapy for Adolescents: Targeting Substance Use and HIV/STI-Risk Behaviors

PubMed Central

McCart, Michael R.; Sheidow, Ashli J.; Letourneau, Elizabeth J.

2014-01-01

This paper describes a family-based intervention for addressing both substance use and unprotected sexual behavior in adolescents presenting for outpatient substance use treatment. The intervention combines contingency management (CM) for adolescent substance use, which is a behavioral intervention modeled on the Community Reinforcement Approach, with a sexual risk reduction protocol that mirrors aspects of the CM model. As a family-based intervention, caregivers attend every session and actively collaborate with the therapist to address their youth’s behavior problems. The treatment is criterion-based with treatment duration determined by the youth’s achievement of reduced substance use and unprotected sexual behavior goals. A case study describes the implementation of this treatment with an adolescent presenting a history of polysubstance use and unprotected sexual intercourse. Following the adolescent and caregiver’s participation in weekly sessions, the adolescent demonstrated improvements in substance use, unprotected sexual behavior, and other behavior problems. Clinical summary data from two outpatient clinics reveal similar positive outcomes for youth receiving the intervention. This paper illustrates the potential utility of an integrated treatment approach targeting substance use and unprotected sexual behavior in an adolescent population. PMID:25419101

Design strategies and functionality of the Visual Interface for Virtual Interaction Development (VIVID) tool

NASA Technical Reports Server (NTRS)

Nguyen, Lac; Kenney, Patrick J.

1993-01-01

Development of interactive virtual environments (VE) has typically consisted of three primary activities: model (object) development, model relationship tree development, and environment behavior definition and coding. The model and relationship tree development activities are accomplished with a variety of well-established graphic library (GL) based programs - most utilizing graphical user interfaces (GUI) with point-and-click interactions. Because of this GUI format, little programming expertise on the part of the developer is necessary to create the 3D graphical models or to establish interrelationships between the models. However, the third VE development activity, environment behavior definition and coding, has generally required the greatest amount of time and programmer expertise. Behaviors, characteristics, and interactions between objects and the user within a VE must be defined via command line C coding prior to rendering the environment scenes. In an effort to simplify this environment behavior definition phase for non-programmers, and to provide easy access to model and tree tools, a graphical interface and development tool has been created. The principal thrust of this research is to effect rapid development and prototyping of virtual environments. This presentation will discuss the 'Visual Interface for Virtual Interaction Development' (VIVID) tool; an X-Windows based system employing drop-down menus for user selection of program access, models, and trees, behavior editing, and code generation. Examples of these selection will be highlighted in this presentation, as will the currently available program interfaces. The functionality of this tool allows non-programming users access to all facets of VE development while providing experienced programmers with a collection of pre-coded behaviors. In conjunction with its existing, interfaces and predefined suite of behaviors, future development plans for VIVID will be described. These include incorporation of dual user virtual environment enhancements, tool expansion, and additional behaviors.

Impact of Different Policies on Unhealthy Dietary Behaviors in an Urban Adult Population: An Agent-Based Simulation Model

PubMed Central

Giabbanelli, Philippe J.; Arah, Onyebuchi A.; Zimmerman, Frederick J.

2014-01-01

Objectives. Unhealthy eating is a complex-system problem. We used agent-based modeling to examine the effects of different policies on unhealthy eating behaviors. Methods. We developed an agent-based simulation model to represent a synthetic population of adults in Pasadena, CA, and how they make dietary decisions. Data from the 2007 Food Attitudes and Behaviors Survey and other empirical studies were used to calibrate the parameters of the model. Simulations were performed to contrast the potential effects of various policies on the evolution of dietary decisions. Results. Our model showed that a 20% increase in taxes on fast foods would lower the probability of fast-food consumption by 3 percentage points, whereas improving the visibility of positive social norms by 10%, either through community-based or mass-media campaigns, could improve the consumption of fruits and vegetables by 7 percentage points and lower fast-food consumption by 6 percentage points. Zoning policies had no significant impact. Conclusions. Interventions emphasizing healthy eating norms may be more effective than directly targeting food prices or regulating local food outlets. Agent-based modeling may be a useful tool for testing the population-level effects of various policies within complex systems. PMID:24832414

Information-Motivation-Behavioral Skills (IMB) Model: testing direct and mediated treatment effects on condom use among women in low-income housing.

PubMed

Anderson, Eileen S; Wagstaff, David A; Heckman, Timothy G; Winett, Richard A; Roffman, Roger A; Solomon, Laura J; Cargill, Victoria; Kelly, Jeffrey A; Sikkema, Kathleen J

2006-02-01

The Information-Motivation-Behavioral Skills (IMB) model of HIV preventive behavior (1-4) specifies that treatment effects on behavior occur largely as the result of treatment effects on behavioral skills, which follow from effects on information and motivation. The objective was to determine whether the variables specified by the IMB model of HIV preventive behavior (1-4) accounted for the relation between an IMB-based treatment and resulting HIV preventive behavior (condom use). Women (n = 557) living in 18 low-income housing developments in 5 geographically dispersed cities were recruited to participate in an HIV-prevention study. Women (within housing developments) were randomly assigned to receive an IMB-based, HIV risk-avoidance intervention or a comparison intervention. Baseline and posttreatment (16 months after baseline) data were collected on condom use information, motivation (social norms, attitudes, intentions, and perceived risk), enactment of behavioral skills (condom negotiation and procurement), and rates of condom use in the past 2 months. The IMB intervention led to a 12% to 16% increase in condom use rates over the course, whereas the comparison intervention led to 2% decrease. In addition, the IMB treatment led to greater increases in condom use information, in the intentions and social norms components of motivation and the condom procurement and condom conversations components of behavioral skills. The IMB model provided an acceptable fit to the data (root mean square error of approximation < .05) and accounted for 50% of the variance in posttreatment condom use among the sample. Treatment effects on condom use were almost entirely mediated by the IMB variables; specifically, motivation and enactment of behavioral skills mediated the intervention's impact on condom use. These results provide supporting evidence as to how theoretical variables operate to effect change within a theory-based intervention and provide evidence as to the applicability of a prevailing theory of HIV risk behavior among low-income minority women.

Modeling detour behavior of pedestrian dynamics under different conditions

NASA Astrophysics Data System (ADS)

Qu, Yunchao; Xiao, Yao; Wu, Jianjun; Tang, Tao; Gao, Ziyou

2018-02-01

Pedestrian simulation approach has been widely used to reveal the human behavior and evaluate the performance of crowd evacuation. In the existing pedestrian simulation models, the social force model is capable of predicting many collective phenomena. Detour behavior occurs in many cases, and the important behavior is a dominate factor of the crowd evacuation efficiency. However, limited attention has been attracted for analyzing and modeling the characteristics of detour behavior. In this paper, a modified social force model integrated by Voronoi diagram is proposed to calculate the detour direction and preferred velocity. Besides, with the consideration of locations and velocities of neighbor pedestrians, a Logit-based choice model is built to describe the detour direction choice. The proposed model is applied to analyze pedestrian dynamics in a corridor scenario with either unidirectional or bidirectional flow, and a building scenario in real-world. Simulation results show that the modified social force model including detour behavior could reduce the frequency of collision and deadlock, increase the average speed of the crowd, and predict more practical crowd dynamics with detour behavior. This model can also be potentially applied to understand the pedestrian dynamics and design emergent management strategies for crowd evacuations.

Application of Model-based Prognostics to a Pneumatic Valves Testbed

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Kulkarni, Chetan S.; Gorospe, George

2014-01-01

Pneumatic-actuated valves play an important role in many applications, including cryogenic propellant loading for space operations. Model-based prognostics emphasizes the importance of a model that describes the nominal and faulty behavior of a system, and how faulty behavior progresses in time, causing the end of useful life of the system. We describe the construction of a testbed consisting of a pneumatic valve that allows the injection of faulty behavior and controllable fault progression. The valve opens discretely, and is controlled through a solenoid valve. Controllable leaks of pneumatic gas in the testbed are introduced through proportional valves, allowing the testing and validation of prognostics algorithms for pneumatic valves. A new valve prognostics approach is developed that estimates fault progression and predicts remaining life based only on valve timing measurements. Simulation experiments demonstrate and validate the approach.

Determinants of Self-Care in Diabetic Patients Based on Health Belief Model

PubMed Central

Dehghani-Tafti, Abbasali; Mahmoodabad, Seyed Saeed Mazloomy; Morowatisharifabad, Mohammad Ali; Ardakani, Mohammad Afkhami; Rezaeipandari, Hassan; Lotfi, Mohammad Hassan

2015-01-01

Introduction: The aim of this study was to determine self-care predictors in diabetic patients based on health belief model. Materials and Methods: The cross-sectional study was conducted on 110 diabetic patients referred to health service centers in Ardakan city, Yazd, Iran. The data was collected by a questionnaire including perceived benefits, barriers, severity, susceptibility, self-efficacy, social support, self-care behaviors and demographic variables. Results: Regularly medicine use (mean= 6.48 times per week) and shoes checking (mean= 1.17 times per week) were reported as the highest and the lowest self-care behaviors respectively. Health belief model constructs including perceived benefits, barriers, severity, susceptibility, self-efficacy and social support predicted 33.5% of the observed variance of self-care behaviors. Perceived susceptibility and self-efficacy had positive effect on self-care behavior; whereas perceived barrier’s has negative effect. Self-efficacy, perceived susceptibility and barriers were most powerful predictor respectively. Conclusion: The findings approved the efficiency of health belief model in prediction of self-care behaviors among diabetic patients. The findings realized the health belief model structure; therefore, it can be used as a framework for designing and implementing educational interventions in diabetes control plans. PMID:26156902

A model of adaptation for families of elderly patients with dementia: focusing on family resilience.

PubMed

Kim, Geun Myun; Lim, Ji Young; Kim, Eun Joo; Kim, Sang Suk

2017-07-19

We constructed a model explaining families' positive adaptation in chronic crisis situations such as the problematic behavior of elderly patients with dementia and attendant caregiving stress, based on the family resilience model. Our aim was to devise an adaptation model for families of elderly patients with dementia. A survey of problematic behavior in elderly patients with dementia, family stress, family resilience, and family adaptation was conducted with 292 consenting individuals. The collected data were analyzed using structural equation modeling. The communication process, family stress, and problematic behavior of elderly patients with dementia had direct and indirect effects on family adaptation, while belief system, organization pattern, and social support had indirect effects. Specifically, family stress and more severe problematic behavior by elderly patients with dementia negatively influenced family adaptation, while greater family resilience improved such adaptation. Interventions aiming to enhance family resilience, based on the results of this study, are required to help families with positive adaptation. Such family programs might involve practical support such as education on the characteristics of elderly persons with dementia and coping methods for their problematic behavior; forming self-help groups for families; revitalizing communication within families; and activating communication channels with experts.

Investigating the relative permeability behavior of microporosity-rich carbonates and tight sandstones with multiscale pore network models

NASA Astrophysics Data System (ADS)

Bultreys, Tom; Stappen, Jeroen Van; Kock, Tim De; Boever, Wesley De; Boone, Marijn A.; Hoorebeke, Luc Van; Cnudde, Veerle

2016-11-01

The relative permeability behavior of rocks with wide ranges of pore sizes is in many cases still poorly understood and is difficult to model at the pore scale. In this work, we investigate the capillary pressure and relative permeability behavior of three outcrop carbonates and two tight reservoir sandstones with wide, multimodal pore size distributions. To examine how the drainage and imbibition properties of these complex rock types are influenced by the connectivity of macropores to each other and to zones with unresolved small-scale porosity, we apply a previously presented microcomputed-tomography-based multiscale pore network model to these samples. The sensitivity to the properties of the small-scale porosity is studied by performing simulations with different artificial sphere-packing-based networks as a proxy for these pores. Finally, the mixed-wet water-flooding behavior of the samples is investigated, assuming different wettability distributions for the microporosity and macroporosity. While this work is not an attempt to perform predictive modeling, it seeks to qualitatively explain the behavior of the investigated samples and illustrates some of the most recent developments in multiscale pore network modeling.

Integration of the Remote Agent for the NASA Deep Space One Autonomy Experiment

NASA Technical Reports Server (NTRS)

Dorais, Gregory A.; Bernard, Douglas E.; Gamble, Edward B., Jr.; Kanefsky, Bob; Kurien, James; Muscettola, Nicola; Nayak, P. Pandurang; Rajan, Kanna; Lau, Sonie (Technical Monitor)

1998-01-01

This paper describes the integration of the Remote Agent (RA), a spacecraft autonomy system which is scheduled to control the Deep Space 1 spacecraft during a flight experiment in 1999. The RA is a reusable, model-based autonomy system that is quite different from software typically used to control an aerospace system. We describe the integration challenges we faced, how we addressed them, and the lessons learned. We focus on those aspects of integrating the RA that were either easier or more difficult than integrating a more traditional large software application because the RA is a model-based autonomous system. A number of characteristics of the RA made integration process easier. One example is the model-based nature of RA. Since the RA is model-based, most of its behavior is not hard coded into procedural program code. Instead, engineers specify high level models of the spacecraft's components from which the Remote Agent automatically derives correct system-wide behavior on the fly. This high level, modular, and declarative software description allowed some interfaces between RA components and between RA and the flight software to be automatically generated and tested for completeness against the Remote Agent's models. In addition, the Remote Agent's model-based diagnosis system automatically diagnoses when the RA models are not consistent with the behavior of the spacecraft. In flight, this feature is used to diagnose failures in the spacecraft hardware. During integration, it proved valuable in finding problems in the spacecraft simulator or flight software. In addition, when modifications are made to the spacecraft hardware or flight software, the RA models are easily changed because they only capture a description of the spacecraft. one does not have to maintain procedural code that implements the correct behavior for every expected situation. On the other hand, several features of the RA made it more difficult to integrate than typical flight software. For example, the definition of correct behavior is more difficult to specify for a system that is expected to reason about and flexibly react to its environment than for a traditional flight software system. Consequently, whenever a change is made to the RA it is more time consuming to determine if the resulting behavior is correct. We conclude the paper with a discussion of future work on the Remote Agent as well as recommendations to ease integration of similar autonomy projects.

Cognitive Behavior Therapy: Notes on Theory and Application with Children.

ERIC Educational Resources Information Center

Sigmon, Scott B.

Cognitive behavioral psychology is a new theoretical orientation. When applied in treatment, it is known as cognitive behavior therapy (CBT). CBT, although based primarily on an information processing model, rests firmly on the twin pillars of both behaviorism and cognitive psychology. Today cognitive therapy and behavioral therapy are terms which…

A Neural Circuit Model of Flexible Sensori-motor Mapping: Learning and Forgetting on Multiple Timescales

PubMed Central

Fusi, Stefano; Asaad, Wael F.; Miller, Earl K.; Wang, Xiao-Jing

2007-01-01

Summary Volitional behavior relies on the brain’s ability to remap sensory flow to motor programs whenever demanded by a changed behavioral context. To investigate the circuit basis of such flexible behavior, we have developed a biophysically-based decision-making network model of spiking neurons for arbitrary sensorimotor mapping. The model quantitatively reproduces behavioral and prefrontal single-cell data from an experiment in which monkeys learn visuo-motor associations that are reversed unpredictably from time to time. We show that when synaptic modifications occur on multiple timescales, the model behavior becomes flexible only when needed: slow components of learning usually dominate the decision process. However, if behavioral contexts change frequently enough, fast components of plasticity take over, and the behavior exhibits a quick forget-and-learn pattern. This model prediction is confirmed by monkey data. Therefore, our work reveals a scenario for conditional associative learning that is distinct from instant switching between sets of well established sensorimotor associations. PMID:17442251

A neural circuit model of flexible sensorimotor mapping: learning and forgetting on multiple timescales.

PubMed

Fusi, Stefano; Asaad, Wael F; Miller, Earl K; Wang, Xiao-Jing

2007-04-19

Volitional behavior relies on the brain's ability to remap sensory flow to motor programs whenever demanded by a changed behavioral context. To investigate the circuit basis of such flexible behavior, we have developed a biophysically based decision-making network model of spiking neurons for arbitrary sensorimotor mapping. The model quantitatively reproduces behavioral and prefrontal single-cell data from an experiment in which monkeys learn visuomotor associations that are reversed unpredictably from time to time. We show that when synaptic modifications occur on multiple timescales, the model behavior becomes flexible only when needed: slow components of learning usually dominate the decision process. However, if behavioral contexts change frequently enough, fast components of plasticity take over, and the behavior exhibits a quick forget-and-learn pattern. This model prediction is confirmed by monkey data. Therefore, our work reveals a scenario for conditional associative learning that is distinct from instant switching between sets of well-established sensorimotor associations.

Does it matter what friends think, say, or do? The role of friends' smoking attitudes and behavior for Dutch adolescents' smoking behavior.

PubMed

Huisman, Chip

2014-05-01

Using stochastic actor-based models for longitudinal network analysis, this study examines the role of friends' smoking attitudes and behavior for Dutch adolescents' smoking behavior in four secondary schools (N = 875). The data were collected in two waves in two small suburban towns under second graders in 2008 to 2009 by means of a standardized questionnaire. Stochastic actor-based models for longitudinal network analysis can control for friendship selection while examining the effect of friends' attitudes and smoking behavior on the smoking behavior of a student. The findings suggest that friends tend to select each other on similar smoking behavior. Influence of friends' smoking behavior seems to play no role. In one school, an effect of friends' attitudes towards smoking on the smoking behavior is found. The implications for future research are to consider attitudes when examining the influence of friendship network on smoking behavior. The main limitation of this study lies in the limited sample, which makes generalizations to the general population difficult.

Sensorimotor synchronization with tempo-changing auditory sequences: Modeling temporal adaptation and anticipation.

PubMed

van der Steen, M C Marieke; Jacoby, Nori; Fairhurst, Merle T; Keller, Peter E

2015-11-11

The current study investigated the human ability to synchronize movements with event sequences containing continuous tempo changes. This capacity is evident, for example, in ensemble musicians who maintain precise interpersonal coordination while modulating the performance tempo for expressive purposes. Here we tested an ADaptation and Anticipation Model (ADAM) that was developed to account for such behavior by combining error correction processes (adaptation) with a predictive temporal extrapolation process (anticipation). While previous computational models of synchronization incorporate error correction, they do not account for prediction during tempo-changing behavior. The fit between behavioral data and computer simulations based on four versions of ADAM was assessed. These versions included a model with adaptation only, one in which adaptation and anticipation act in combination (error correction is applied on the basis of predicted tempo changes), and two models in which adaptation and anticipation were linked in a joint module that corrects for predicted discrepancies between the outcomes of adaptive and anticipatory processes. The behavioral experiment required participants to tap their finger in time with three auditory pacing sequences containing tempo changes that differed in the rate of change and the number of turning points. Behavioral results indicated that sensorimotor synchronization accuracy and precision, while generally high, decreased with increases in the rate of tempo change and number of turning points. Simulations and model-based parameter estimates showed that adaptation mechanisms alone could not fully explain the observed precision of sensorimotor synchronization. Including anticipation in the model increased the precision of simulated sensorimotor synchronization and improved the fit of model to behavioral data, especially when adaptation and anticipation mechanisms were linked via a joint module based on the notion of joint internal models. Overall results suggest that adaptation and anticipation mechanisms both play an important role during sensorimotor synchronization with tempo-changing sequences. This article is part of a Special Issue entitled SI: Prediction and Attention. Copyright © 2015 Elsevier B.V. All rights reserved.

Contagion Shocks in One Dimension

NASA Astrophysics Data System (ADS)

Bertozzi, Andrea L.; Rosado, Jesus; Short, Martin B.; Wang, Li

2015-02-01

We consider an agent-based model of emotional contagion coupled with motion in one dimension that has recently been studied in the computer science community. The model involves movement with a speed proportional to a "fear" variable that undergoes a temporal consensus averaging based on distance to other agents. We study the effect of Riemann initial data for this problem, leading to shock dynamics that are studied both within the agent-based model as well as in a continuum limit. We examine the behavior of the model under distinguished limits as the characteristic contagion interaction distance and the interaction timescale both approach zero. The limiting behavior is related to a classical model for pressureless gas dynamics with "sticky" particles. In comparison, we observe a threshold for the interaction distance vs. interaction timescale that produce qualitatively different behavior for the system - in one case particle paths do not cross and there is a natural Eulerian limit involving nonlocal interactions and in the other case particle paths can cross and one may consider only a kinetic model in the continuum limit.

The interaction model of client health behavior: application to the study of community-based elders.

PubMed

Cox, C L

1986-10-01

The Interaction Model of Client Health Behavior (IMCHB) was used to direct a systematic and comprehensive description of community-based elders. The abstract concepts, constructs, factors, and variables described by one element of the model were able to account for 54% of the variance in elders' health status and 47% of the variance in their well-being. The model, as operationalized in this study, pointed to clear demographic, social, and health profiles that identified the elder at risk for decreased health, well-being, and self-care potential. The IMCHB would appear to be a useful framework with which to establish an empirical base on which nursing interventions could be developed.

Uncertainty and sensitivity analysis of fission gas behavior in engineering-scale fuel modeling

DOE PAGES

Pastore, Giovanni; Swiler, L. P.; Hales, Jason D.; ...

2014-10-12

The role of uncertainties in fission gas behavior calculations as part of engineering-scale nuclear fuel modeling is investigated using the BISON fuel performance code and a recently implemented physics-based model for the coupled fission gas release and swelling. Through the integration of BISON with the DAKOTA software, a sensitivity analysis of the results to selected model parameters is carried out based on UO2 single-pellet simulations covering different power regimes. The parameters are varied within ranges representative of the relative uncertainties and consistent with the information from the open literature. The study leads to an initial quantitative assessment of the uncertaintymore » in fission gas behavior modeling with the parameter characterization presently available. Also, the relative importance of the single parameters is evaluated. Moreover, a sensitivity analysis is carried out based on simulations of a fuel rod irradiation experiment, pointing out a significant impact of the considered uncertainties on the calculated fission gas release and cladding diametral strain. The results of the study indicate that the commonly accepted deviation between calculated and measured fission gas release by a factor of 2 approximately corresponds to the inherent modeling uncertainty at high fission gas release. Nevertheless, higher deviations may be expected for values around 10% and lower. Implications are discussed in terms of directions of research for the improved modeling of fission gas behavior for engineering purposes.« less

Group-Wise Herding Behavior in Financial Markets: An Agent-Based Modeling Approach

PubMed Central

Kim, Minsung; Kim, Minki

2014-01-01

In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy. PMID:24714635

An information-motivation-behavioral skills (IMB) model-based intervention for CABG patients.

PubMed

Zarani, Fariba; Besharat, Mohammad Ali; Sarami, Gholamreza; Sadeghian, Saeed

2012-12-01

In order to benefit from a coronary artery bypass graft (CABG) surgery, patients must adhere to medical recommendations and health advices. Despite the importance of adherence in CABG patients, adherence rates are disappointingly low. Despite the low adherence rates, very few articles regarding adherence-enhancing intervention among heart patients have been published. The goal of this study was to assess the effects of the Information-Motivation-Behavioral Skills (IMB) model-based intervention on the IMB model constructs among patients undergoing CABG and to evaluate the relationship of information, motivation, and behavioral skills with adherence. A total of 152 CABG patients were randomly assigned to either an intervention group or to a standard care control group. Participants completed pretest measures and were reassessed 1 month later. Findings showed mixed support for the effectiveness of the intervention. There was a significant effect of IMB intervention on information and motivation of patients, but no significant effect on behavioral skills. Furthermore, the results revealed that intervention constructs (information, motivation, and behavioral skills) were significantly related to patients' adherence. Findings provided initial evidence for the effectiveness of IMB-based interventions on the IMB constructs and supported the importance of these constructs to improve adherence; however, there are additional factors that need to be identified in order to improve behavioral skills more effectively.

Group-wise herding behavior in financial markets: an agent-based modeling approach.

PubMed

Kim, Minsung; Kim, Minki

2014-01-01

In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy.

Masquerade Detection Using a Taxonomy-Based Multinomial Modeling Approach in UNIX Systems

DTIC Science & Technology

2008-08-25

primarily the modeling of statistical features , such as the frequency of events, the duration of events, the co- occurrence of multiple events...are identified, we can extract features representing such behavior while auditing the user’s behavior. Figure1: Taxonomy of Linux and Unix...achieved when the features are extracted just from simple commands. Method Hit Rate False Positive Rate ocSVM using simple cmds (freq.-based

C.A.M.P.: A Community-Based Approach to Promoting Safe Sex Behavior in Adolescence.

ERIC Educational Resources Information Center

Guzman, Bianca L.; Casad, Bettina J.; Schlehofer-Sutton, Michele M.; Villanueva, Christina M.; Feria, Aida

The primary goal of this study was to assess the Community Awareness Motivation Partnership (C.A.M.P.) theater intervention based on the behavioral ecological model. C.A.M.P addresses the role of contraceptive use in safe sex behavior through an informative and entertaining culturally relevant dramatization program. Adolescents (N=1613) between…

Predicting Study Abroad Intentions Based on the Theory of Planned Behavior

ERIC Educational Resources Information Center

Schnusenberg, Oliver; de Jong, Pieter; Goel, Lakshmi

2012-01-01

The emphasis on study abroad programs is growing in the academic context as U.S. based universities seek to incorporate a global perspective in education. Using a model that has underpinnings in the theory of planned behavior (TPB), we predict students' intention to participate in short-term study abroad program. We use TPB to identify behavioral,…

Intelligent systems approach for automated identification of individual control behavior of a human operator

NASA Astrophysics Data System (ADS)

Zaychik, Kirill B.

Acceptable results have been obtained using conventional techniques to model the generic human operator's control behavior. However, little research has been done in an attempt to identify an individual based on his/her control behavior. The main hypothesis investigated in this dissertation is that different operators exhibit different control behavior when performing a given control task. Furthermore, inter-person differences are manifested in the amplitude and frequency content of the non-linear component of the control behavior. Two enhancements to the existing models of the human operator, which allow personalization of the modeled control behavior, are presented in this dissertation. One of the proposed enhancements accounts for the "testing" control signals, which are introduced by an operator for more accurate control of the system and/or to adjust his/her control strategy. Such enhancement uses the Artificial Neural Network (ANN), which can be fine-tuned to model the "testing" control behavior of a given individual. The other model enhancement took the form of an equiripple filter (EF), which conditions the power spectrum of the control signal before it is passed through the plant dynamics block. The filter design technique uses Parks-McClellan algorithm, which allows parameterization of the desired levels of power at certain frequencies. A novel automated parameter identification technique (APID) was developed to facilitate the identification process of the parameters of the selected models of the human operator. APID utilizes a Genetic Algorithm (GA) based optimization engine called the Bit-climbing Algorithm (BCA). Proposed model enhancements were validated using the experimental data obtained at three different sources: the Manual Control Laboratory software experiments, Unmanned Aerial Vehicle simulation, and NASA Langley Research Center Visual Motion Simulator studies. Validation analysis involves comparison of the actual and simulated control activity signals. Validation criteria used in this dissertation is based on comparing Power Spectral Densities of the control signals against that of the Precision model of the human operator. This dissertation also addresses the issue of applying the proposed human operator model augmentation to evaluate the effectiveness of the motion feedback when simulating the actual pilot control behavior in a flight simulator. The proposed modeling methodology allows for quantitative assessments and prediction of the need for platform motion, while performing aircraft/pilot simulation studies.

Models of Pilot Behavior and Their Use to Evaluate the State of Pilot Training

NASA Astrophysics Data System (ADS)

Jirgl, Miroslav; Jalovecky, Rudolf; Bradac, Zdenek

2016-07-01

This article discusses the possibilities of obtaining new information related to human behavior, namely the changes or progressive development of pilots' abilities during training. The main assumption is that a pilot's ability can be evaluated based on a corresponding behavioral model whose parameters are estimated using mathematical identification procedures. The mean values of the identified parameters are obtained via statistical methods. These parameters are then monitored and their changes evaluated. In this context, the paper introduces and examines relevant mathematical models of human (pilot) behavior, the pilot-aircraft interaction, and an example of the mathematical analysis.

Thermo-elastoviscoplastic snapthrough behavior of cylindrical panels

NASA Technical Reports Server (NTRS)

Song, Y.; Simitses, G. J.

1992-01-01

The thermo-elastoviscoplastic snapthrough behavior of simply supported cylindrical panels is investigated. The analysis is based on nonlinear kinematic relations and nonlinear rate-dependent unified constitutive equations which include both Bodner-Partom's and Walker's material models. A finite element approach is employed to predict the inelastic buckling behavior. Numerical examples are given to demonstrate the effects of several parameters which include the temperature, thickness and flatness of the panel. Comparisons of buckling responses between Bodner-Partom's model and Walker's model are given. The creep buckling behavior, as an example of time-dependent inelastic deformation, is also presented.

The Classroom Check-up: A Classwide Teacher Consultation Model for Increasing Praise and Decreasing Disruptive Behavior

PubMed Central

Reinke, Wendy M.; Lewis-Palmer, Teri; Merrell, Kenneth

2008-01-01

School-based consultation typically focuses on individual student problems and on a small number of students rather than on changing the classroom system. The Classroom Check-up (CCU) was developed as a classwide consultation model to address the need for classroom level support while minimizing treatment integrity problems common to school-based consultation. The purpose of the study was to evaluate the effects of the CCU and Visual Performance Feedback on teacher and student behavior. Results indicated that implementation of the CCU plus Visual Performance Feedback increased teacher implementation of classroom management strategies, including increased use of praise, use of behavior specific praise, and decreased use of reprimands. Further, these changes in teacher behavior contributed to decreases in classroom disruptive behavior. The results are encouraging because they suggest that consultation at the classroom level can create meaningful teacher and student behavior change. PMID:19122805

Comparison of computer based instruction to behavior skills training for teaching staff implementation of discrete-trial instruction with an adult with autism.

PubMed

Nosik, Melissa R; Williams, W Larry; Garrido, Natalia; Lee, Sarah

2013-01-01

In the current study, behavior skills training (BST) is compared to a computer based training package for teaching discrete trial instruction to staff, teaching an adult with autism. The computer based training package consisted of instructions, video modeling and feedback. BST consisted of instructions, modeling, rehearsal and feedback. Following training, participants were evaluated in terms of their accuracy on completing critical skills for running a discrete trial program. Six participants completed training; three received behavior skills training and three received the computer based training. Participants in the BST group performed better overall after training and during six week probes than those in the computer based training group. There were differences across both groups between research assistant and natural environment competency levels. Copyright © 2012 Elsevier Ltd. All rights reserved.

Simulation study of temperature-dependent diffusion behaviors of Ag/Ag(001) at low substrate temperature

NASA Astrophysics Data System (ADS)

Cai, Danyun; Mo, Yunjie; Feng, Xiaofang; He, Yingyou; Jiang, Shaoji

2017-06-01

In this study, a model based on the First Principles calculations and Kinetic Monte Carlo simulation were established to study the growth characteristic of Ag thin film at low substrate temperature. On the basis of the interaction between the adatom and nearest-neighbor atoms, some simplifications and assumptions were made to categorize the diffusion behaviors of Ag adatoms on Ag(001). Then the barriers of all possible diffusion behaviors were calculated using the Climbing Image Nudged Elastic Band method (CI-NEB). Based on the Arrhenius formula, the morphology variation, which is attributed to the surface diffusion behaviors during the growth, was simulated with a temperature-dependent KMC model. With this model, a non-monotonic relation between the surface roughness and the substrate temperature (decreasing from 300 K to 100 K) were discovered. The analysis of the temperature dependence on diffusion behaviors presents a theoretical explanation of diffusion mechanism for the non-monotonic variation of roughness at low substrate temperature.

Myopia prevention, near work, and visual acuity of college students: integrating the theory of planned behavior and self-determination theory.

PubMed

Chan, Derwin King-Chung; Fung, Ying-Ki; Xing, Suxuan; Hagger, Martin S

2014-06-01

There has been little research examining the psychological antecedents of safety-oriented behavior aimed at reducing myopia risk. This study utilizes self-determination theory (SDT) and the theory of planned behavior (TPB) to understand the role of motivational and social-cognitive factors on individuals' near-work behavior. Adopting a prospective design, undergraduate students (n = 107) completed an initial questionnaire based on SDT in week 1, a second questionnaire containing measures of TPB variables in week 2, and objective measures of reading distance and visual acuity in week 6. The data were analyzed by variance-based structural equation modeling. The results showed that perceived autonomy support and autonomous motivation from SDT significantly predicted attitude, subjective norm, and perceived behavioral control from the TPB. These social-cognitive factors were significantly associated with intention and intention significantly predicted reading distance. The relationships in the model held when controlling for visual acuity. In conclusion, the integrated model of SDT and the TPB may help explain myopia-preventive behaviors.

Mechanics Model for Simulating RC Hinges under Reversed Cyclic Loading

PubMed Central

Shukri, Ahmad Azim; Visintin, Phillip; Oehlers, Deric J.; Jumaat, Mohd Zamin

2016-01-01

Describing the moment rotation (M/θ) behavior of reinforced concrete (RC) hinges is essential in predicting the behavior of RC structures under severe loadings, such as under cyclic earthquake motions and blast loading. The behavior of RC hinges is defined by localized slip or partial interaction (PI) behaviors in both the tension and compression region. In the tension region, slip between the reinforcement and the concrete defines crack spacing, crack opening and closing, and tension stiffening. While in the compression region, slip along concrete to concrete interfaces defines the formation and failure of concrete softening wedges. Being strain-based, commonly-applied analysis techniques, such as the moment curvature approach, cannot directly simulate these PI behaviors because they are localized and displacement based. Therefore, strain-based approaches must resort to empirical factors to define behaviors, such as tension stiffening and concrete softening hinge lengths. In this paper, a displacement-based segmental moment rotation approach, which directly simulates the partial interaction behaviors in both compression and tension, is developed for predicting the M/θ response of an RC beam hinge under cyclic loading. Significantly, in order to develop the segmental approach, a partial interaction model to predict the tension stiffening load slip relationship between the reinforcement and the concrete is developed. PMID:28773430

Mechanics Model for Simulating RC Hinges under Reversed Cyclic Loading.

PubMed

Shukri, Ahmad Azim; Visintin, Phillip; Oehlers, Deric J; Jumaat, Mohd Zamin

2016-04-22

Describing the moment rotation (M/θ) behavior of reinforced concrete (RC) hinges is essential in predicting the behavior of RC structures under severe loadings, such as under cyclic earthquake motions and blast loading. The behavior of RC hinges is defined by localized slip or partial interaction (PI) behaviors in both the tension and compression region. In the tension region, slip between the reinforcement and the concrete defines crack spacing, crack opening and closing, and tension stiffening. While in the compression region, slip along concrete to concrete interfaces defines the formation and failure of concrete softening wedges. Being strain-based, commonly-applied analysis techniques, such as the moment curvature approach, cannot directly simulate these PI behaviors because they are localized and displacement based. Therefore, strain-based approaches must resort to empirical factors to define behaviors, such as tension stiffening and concrete softening hinge lengths. In this paper, a displacement-based segmental moment rotation approach, which directly simulates the partial interaction behaviors in both compression and tension, is developed for predicting the M/θ response of an RC beam hinge under cyclic loading. Significantly, in order to develop the segmental approach, a partial interaction model to predict the tension stiffening load slip relationship between the reinforcement and the concrete is developed.

Prediction of Self-Management Behavior among Iranian Women with Type 2 Diabetes: Application of the Theory of Reasoned Action along with Self-Efficacy (ETRA).

PubMed

Didarloo, A R; Shojaeizadeh, D; Gharaaghaji Asl, R; Habibzadeh, H; Niknami, Sh; Pourali, R

2012-02-01

Continuous performing of diabetes self-care behaviors was shown to be an effective strategy to control diabetes and to prevent or reduce its- related complications. This study aimed to investigate predictors of self-care behavior based on the extended theory of reasoned action by self efficacy (ETRA) among women with type 2 diabetes in Iran. A sample of 352 women with type 2 diabetes, referring to a Diabetes Clinic in Khoy, Iran using the nonprobability sampling was enrolled. Appropriate instruments were designed to measure the variables of interest (diabetes knowledge, personal beliefs, subjective norm, self-efficacy and behavioral intention along with self- care behaviors). Reliability and validity of the instruments using Cronbach's alpha coefficients (the values of them were more than 0.70) and a panel of experts were tested. A statistical significant correlation existed between independent constructs of proposed model and modelrelated dependent constructs, as ETRA model along with its related external factors explained 41.5% of variance of intentions and 25.3% of variance of actual behavior. Among constructs of model, self-efficacy was the strongest predictor of intentions among women with type 2 diabetes, as it lonely explained 31.3% of variance of intentions and 11.4% of variance of self-care behavior. The high ability of the extended theory of reasoned action with self-efficacy in forecasting and explaining diabetes mellitus self management can be a base for educational intervention. So to improve diabetes self management behavior and to control the disease, use of educational interventions based on proposed model is suggested.

Investigation of the effect of temperature on aging behavior of Fe-doped lead zirconate titanate

NASA Astrophysics Data System (ADS)

Promsawat, Napatporn; Promsawat, Methee; Janphuang, Pattanaphong; Marungsri, Boonruang; Luo, Zhenhua; Pojprapai, Soodkhet

The aging degradation behavior of Fe-doped Lead zirconate titanate (PZT) subjected to different heat-treated temperatures was investigated over 1000h. The aging degradation in the piezoelectric properties of PZT was indicated by the decrease in piezoelectric charge coefficient, electric field-induced strain and remanent polarization. It was found that the aging degradation became more pronounced at temperature above 50% of the PZT’s Curie temperature. A mathematical model based on the linear logarithmic stretched exponential function was applied to explain the aging behavior. A qualitative aging model based on polar macrodomain switchability was proposed.

Forecasting Behavior in Smart Homes Based on Sleep and Wake Patterns

PubMed Central

Williams, Jennifer A.; Cook, Diane J.

2017-01-01

Background The goal of this research is to use smart home technology to assist people who are recovering from injuries or coping with disabilities to live independently. Objective We introduce an algorithm to model and forecast wake and sleep behaviors that are exhibited by the participant. Furthermore, we propose that sleep behavior is impacted by and can be modeled from wake behavior, and vice versa. Methods This paper describes the Behavior Forecasting (BF) algorithm. BF consists of 1) defining numeric values that reflect sleep and wake behavior, 2) forecasting wake and sleep values from past behavior, 3) analyzing the effect of wake behavior on sleep and vice versa, and 4) improving prediction performance by using both wake and sleep scores. Results The BF method was evaluated with data collected from 20 smart homes. We found that regardless of the forecasting method utilized, wake behavior and sleep behavior can be modeled with a minimum accuracy of 84%. Additionally, normalizing the wake and sleep scores drastically improves the accuracy to 99%. Conclusions The results show that we can effectively model wake and sleep behaviors in a smart environment. Furthermore, wake behaviors can be predicted from sleep behaviors and vice versa. PMID:27689555

Forecasting behavior in smart homes based on sleep and wake patterns.

PubMed

Williams, Jennifer A; Cook, Diane J

2017-01-01

The goal of this research is to use smart home technology to assist people who are recovering from injuries or coping with disabilities to live independently. We introduce an algorithm to model and forecast wake and sleep behaviors that are exhibited by the participant. Furthermore, we propose that sleep behavior is impacted by and can be modeled from wake behavior, and vice versa. This paper describes the Behavior Forecasting (BF) algorithm. BF consists of 1) defining numeric values that reflect sleep and wake behavior, 2) forecasting wake and sleep values from past behavior, 3) analyzing the effect of wake behavior on sleep and vice versa, and 4) improving prediction performance by using both wake and sleep scores. The BF method was evaluated with data collected from 20 smart homes. We found that regardless of the forecasting method utilized, wake behavior and sleep behavior can be modeled with a minimum accuracy of 84%. Additionally, normalizing the wake and sleep scores drastically improves the accuracy to 99%. The results show that we can effectively model wake and sleep behaviors in a smart environment. Furthermore, wake behaviors can be predicted from sleep behaviors and vice versa.

Development of a dynamic computational model of social cognitive theory.

PubMed

Riley, William T; Martin, Cesar A; Rivera, Daniel E; Hekler, Eric B; Adams, Marc A; Buman, Matthew P; Pavel, Misha; King, Abby C

2016-12-01

Social cognitive theory (SCT) is among the most influential theories of behavior change and has been used as the conceptual basis of health behavior interventions for smoking cessation, weight management, and other health behaviors. SCT and other behavior theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed as new technologies allow for intensive longitudinal measures and interventions adapted from these inputs. These within-person explanatory theoretical applications can be modeled as dynamical systems. SCT constructs, such as reciprocal determinism, are inherently dynamical in nature, but SCT has not been modeled as a dynamical system. This paper describes the development of a dynamical system model of SCT using fluid analogies and control systems principles drawn from engineering. Simulations of this model were performed to assess if the model performed as predicted based on theory and empirical studies of SCT. This initial model generates precise and testable quantitative predictions for future intensive longitudinal research. Dynamic modeling approaches provide a rigorous method for advancing health behavior theory development and refinement and for guiding the development of more potent and efficient interventions.

Influence of backup bearings and support structure dynamics on the behavior of rotors with active supports

NASA Technical Reports Server (NTRS)

Flowers, George T.

1994-01-01

Substantial progress has been made toward the goals of this research effort in the past six months. A simplified rotor model with a flexible shaft and backup bearings has been developed. The model is based upon the work of Ishii and Kirk. Parameter studies of the behavior of this model are currently being conducted. A simple rotor model which includes a flexible disk and bearings with clearance has been developed and the dynamics of the model investigated. The study consists of simulation work coupled with experimental verification. The work is documented in the attached paper. A rotor model based upon the T-501 engine has been developed which includes backup bearing effects. The dynamics of this model are currently being studied with the objective of verifying the conclusions obtained from the simpler models. Parallel simulation runs are being conducted using an ANSYS based finite element model of the T-501.

Health behavior theories as predictors of hearing-aid uptake and outcomes.

PubMed

Saunders, Gabrielle H; Frederick, Melissa T; Silverman, ShienPei C; Nielsen, Claus; Laplante-Lévesque, Ariane

2016-07-01

To understand hearing behaviors of adults seeking help for the first time through the application of two models of health behavior change: the transtheoretical model and the health belief model. The relationships between attitudes and beliefs were examined relative to hearing-aid uptake and outcomes six months later. One hundred and sixty adults completed the University of Rhode Island change assessment (targeting the transtheoretical model), and the hearing beliefs questionnaire (targeting the health belief model), as well as the hearing handicap inventory and the psychosocial impact of hearing loss scale, within two months of an initial hearing assessment. Six months later, participants completed these same questionnaires, while those who had taken up hearing aids also completed hearing-aid outcome questionnaires. (1) Attitudes and beliefs were associated with future hearing-aid uptake, and were effective at modeling this behavior; (2) attitudes and beliefs changed following behavior change, and (3) attitudes and beliefs following behavior change were better predictors of hearing-aid outcomes than pre-behavior change attitudes and beliefs. A counseling-based intervention targeting the attitudes and beliefs assessed by the transtheoretical model and the health belief model has the potential to increase uptake of hearing health care.

Developmental Therapy- Developmental Teaching: An Outreach Project for Young Children with Social-Emotional-Behavioral Disabilities (October 1, 1997-September 30, 2000). Final Performance Report.

ERIC Educational Resources Information Center

Georgia Univ., Athens. Coll. of Family and Consumer Sciences.

This outreach project is based on the validated Developmental Therapy-Developmental Teaching model originally designed for young children with severe emotional/behavioral problems and their families. It is an approach that emphasizes the teaching skills that foster a child's social-emotional-behavioral competence. The model has proven effective in…

Mediating Mechanisms of Theory-Based Psychosocial Determinants on Behavioral Changes in a Middle School Obesity Risk Reduction Curriculum Intervention, Choice, Control, and Change.

PubMed

Gray, Heewon Lee; Contento, Isobel R; Koch, Pamela A; Noia, Jennifer Di

2016-10-01

A limited number of school-based intervention studies have explored mediating mechanisms of theory-based psychosocial variables on obesity risk behavior changes. The current study investigated how theory-based psychosocial determinants mediated changes in energy balance-related behaviors (EBRBs) among urban youth. A secondary analysis study was conducted using data from a cluster randomized controlled trial. Data from students at 10 middle schools in New York City (n = 1136) were used. The intervention, Choice, Control, and Change curriculum, was based on social cognitive and self-determination theories. Theory-based psychosocial determinants (goal intention, cognitive outcome expectations, affective outcome expectations, self-efficacy, perceived barriers, and autonomous motivation) and EBRBs were measured with self-report questionnaires. Mediation mechanisms were examined using structural equation modeling, Results: Mediating mechanisms for daily sugar-sweetened beverage (SSB) consumption and purposeful stair climbing were identified. Models with best fit indices (root mean square error of approximation = 0.039/0.045, normed fit index = 0.916/0.882; comparative fit index = 0.945/0.932; Tucker-Lewis index = 0.896/0.882, respectively) suggested that goal intention and reduced perceived barriers were significant proximal mediators for reducing SSB consumption among both boys and girls or increasing physical activity by stair climbing among boys. Cognitive outcome expectations, affective outcome expectations, self-efficacy, and autonomous motivation indirectly mediated behavioral changes through goal intention or perceived barriers (p < 0.05 to p < 0.001). The final models explained 25%-27% of behavioral outcome variances. Theory-based psychosocial determinants targeted in Choice, Control, and Change in fact mediated behavior changes in middle school students. Strategies targeting these mediators might benefit future success of behavioral interventions. Further studies are needed to determine other potential mediators of EBRBs in youth.

Towards representing human behavior and decision making in Earth system models - an overview of techniques and approaches

NASA Astrophysics Data System (ADS)

Müller-Hansen, Finn; Schlüter, Maja; Mäs, Michael; Donges, Jonathan F.; Kolb, Jakob J.; Thonicke, Kirsten; Heitzig, Jobst

2017-11-01

Today, humans have a critical impact on the Earth system and vice versa, which can generate complex feedback processes between social and ecological dynamics. Integrating human behavior into formal Earth system models (ESMs), however, requires crucial modeling assumptions about actors and their goals, behavioral options, and decision rules, as well as modeling decisions regarding human social interactions and the aggregation of individuals' behavior. Here, we review existing modeling approaches and techniques from various disciplines and schools of thought dealing with human behavior at different levels of decision making. We demonstrate modelers' often vast degrees of freedom but also seek to make modelers aware of the often crucial consequences of seemingly innocent modeling assumptions. After discussing which socioeconomic units are potentially important for ESMs, we compare models of individual decision making that correspond to alternative behavioral theories and that make diverse modeling assumptions about individuals' preferences, beliefs, decision rules, and foresight. We review approaches to model social interaction, covering game theoretic frameworks, models of social influence, and network models. Finally, we discuss approaches to studying how the behavior of individuals, groups, and organizations can aggregate to complex collective phenomena, discussing agent-based, statistical, and representative-agent modeling and economic macro-dynamics. We illustrate the main ingredients of modeling techniques with examples from land-use dynamics as one of the main drivers of environmental change bridging local to global scales.

Relevance of behavioral and social models to the study of consumer energy decision making and behavior

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burns, B.A.

This report reviews social and behavioral science models and techniques for their possible use in understanding and predicting consumer energy decision making and behaviors. A number of models and techniques have been developed that address different aspects of the decision process, use different theoretical bases and approaches, and have been aimed at different audiences. Three major areas of discussion were selected: (1) models of adaptation to social change, (2) decision making and choice, and (3) diffusion of innovation. Within these three areas, the contributions of psychologists, sociologists, economists, marketing researchers, and others were reviewed. Five primary components of the modelsmore » were identified and compared. The components are: (1) situational characteristics, (2) product characteristics, (3) individual characteristics, (4) social influences, and (5) the interaction or decision rules. The explicit use of behavioral and social science models in energy decision-making and behavior studies has been limited. Examples are given of a small number of energy studies which applied and tested existing models in studying the adoption of energy conservation behaviors and technologies, and solar technology.« less

Research the simulation model of the passenger travel behavior in urban rail platform

NASA Astrophysics Data System (ADS)

Wang, Yujia; Yin, Xiangyong

2017-05-01

Based on the results of the research on the platform of the Beijing Chegongzhuang subway station in the line 2, the passenger travel behavior in urban rail platform is divided into 4 parts, which are the enter passenger walking, the passenger waiting distribution and queuing up before the door, passenger boarding and alighting and the alighting passengers walking, according to the social force model, simulation model was built based on Matlab software. Combined with the actual data of subway the Chegongzhuang subway station in the line 2, the simulation results show that the social force model is effective.

The theory of reasoned action as parallel constraint satisfaction: towards a dynamic computational model of health behavior.

PubMed

Orr, Mark G; Thrush, Roxanne; Plaut, David C

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual's pre-existing belief structure and the beliefs of others in the individual's social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics.

The Theory of Reasoned Action as Parallel Constraint Satisfaction: Towards a Dynamic Computational Model of Health Behavior

PubMed Central

Orr, Mark G.; Thrush, Roxanne; Plaut, David C.

2013-01-01

The reasoned action approach, although ubiquitous in health behavior theory (e.g., Theory of Reasoned Action/Planned Behavior), does not adequately address two key dynamical aspects of health behavior: learning and the effect of immediate social context (i.e., social influence). To remedy this, we put forth a computational implementation of the Theory of Reasoned Action (TRA) using artificial-neural networks. Our model re-conceptualized behavioral intention as arising from a dynamic constraint satisfaction mechanism among a set of beliefs. In two simulations, we show that constraint satisfaction can simultaneously incorporate the effects of past experience (via learning) with the effects of immediate social context to yield behavioral intention, i.e., intention is dynamically constructed from both an individual’s pre-existing belief structure and the beliefs of others in the individual’s social context. In a third simulation, we illustrate the predictive ability of the model with respect to empirically derived behavioral intention. As the first known computational model of health behavior, it represents a significant advance in theory towards understanding the dynamics of health behavior. Furthermore, our approach may inform the development of population-level agent-based models of health behavior that aim to incorporate psychological theory into models of population dynamics. PMID:23671603

Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research.

PubMed

Spruijt-Metz, Donna; Hekler, Eric; Saranummi, Niilo; Intille, Stephen; Korhonen, Ilkka; Nilsen, Wendy; Rivera, Daniel E; Spring, Bonnie; Michie, Susan; Asch, David A; Sanna, Alberto; Salcedo, Vicente Traver; Kukakfa, Rita; Pavel, Misha

2015-09-01

Adverse and suboptimal health behaviors and habits are responsible for approximately 40 % of preventable deaths, in addition to their unfavorable effects on quality of life and economics. Our current understanding of human behavior is largely based on static "snapshots" of human behavior, rather than ongoing, dynamic feedback loops of behavior in response to ever-changing biological, social, personal, and environmental states. This paper first discusses how new technologies (i.e., mobile sensors, smartphones, ubiquitous computing, and cloud-enabled processing/computing) and emerging systems modeling techniques enable the development of new, dynamic, and empirical models of human behavior that could facilitate just-in-time adaptive, scalable interventions. The paper then describes concrete steps to the creation of robust dynamic mathematical models of behavior including: (1) establishing "gold standard" measures, (2) the creation of a behavioral ontology for shared language and understanding tools that both enable dynamic theorizing across disciplines, (3) the development of data sharing resources, and (4) facilitating improved sharing of mathematical models and tools to support rapid aggregation of the models. We conclude with the discussion of what might be incorporated into a "knowledge commons," which could help to bring together these disparate activities into a unified system and structure for organizing knowledge about behavior.

Calibrating Bayesian Network Representations of Social-Behavioral Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitney, Paul D.; Walsh, Stephen J.

2010-04-08

While human behavior has long been studied, recent and ongoing advances in computational modeling present opportunities for recasting research outcomes in human behavior. In this paper we describe how Bayesian networks can represent outcomes of human behavior research. We demonstrate a Bayesian network that represents political radicalization research – and show a corresponding visual representation of aspects of this research outcome. Since Bayesian networks can be quantitatively compared with external observations, the representation can also be used for empirical assessments of the research which the network summarizes. For a political radicalization model based on published research, we show this empiricalmore » comparison with data taken from the Minorities at Risk Organizational Behaviors database.« less

Improvement of Progressive Damage Model to Predicting Crashworthy Composite Corrugated Plate

NASA Astrophysics Data System (ADS)

Ren, Yiru; Jiang, Hongyong; Ji, Wenyuan; Zhang, Hanyu; Xiang, Jinwu; Yuan, Fuh-Gwo

2018-02-01

To predict the crashworthy composite corrugated plate, different single and stacked shell models are evaluated and compared, and a stacked shell progressive damage model combined with continuum damage mechanics is proposed and investigated. To simulate and predict the failure behavior, both of the intra- and inter- laminar failure behavior are considered. The tiebreak contact method, 1D spot weld element and cohesive element are adopted in stacked shell model, and a surface-based cohesive behavior is used to capture delamination in the proposed model. The impact load and failure behavior of purposed and conventional progressive damage models are demonstrated. Results show that the single shell could simulate the impact load curve without the delamination simulation ability. The general stacked shell model could simulate the interlaminar failure behavior. The improved stacked shell model with continuum damage mechanics and cohesive element not only agree well with the impact load, but also capture the fiber, matrix debonding, and interlaminar failure of composite structure.

Ignition behavior of live California chaparral leaves

Treesearch

J.D. Engstrom; J.K Butler; S.G. Smith; L.L. Baxter; T.H. Fletcher; D.R. Weise

2004-01-01

Current forest fire models are largely empirical correlations based on data from beds of dead vegetation Improvement in model capabilities is sought by developing models of the combustion of live fuels. A facility was developed to determine the combustion behavior of small samples of live fuels, consisting of a flat-flame burner on a moveable platform Qualitative and...

Predicting Internalizing and Externalizing Symptoms in Children with ASD: Evaluation of a Contextual Model of Parental Factors

ERIC Educational Resources Information Center

McRae, Elizabeth M.; Stoppelbein, Laura; O'Kelley, Sarah E.; Fite, Paula; Greening, Leilani

2018-01-01

Parental adjustment, parenting behaviors, and child routines have been linked to internalizing and externalizing child behavior. The purpose of the present study was to evaluate a comprehensive model examining relations among these variables in children with ASD and their parents. Based on Sameroff's Transactional Model of Development (Sameroff…

An improved car-following model from the perspective of driver’s forecast behavior

NASA Astrophysics Data System (ADS)

Liu, Da-Wei; Shi, Zhong-Ke; Ai, Wen-Huan

In this paper, a new car-following model considering effect of the driver’s forecast behavior is proposed based on the full velocity difference model (FVDM). Using the new model, we investigate the starting process of the vehicle motion under a traffic signal and find that the delay time of vehicle motion is reduced. Then the stability condition of the new model is derived and the modified Korteweg-de Vries (mKdV) equation is constructed to describe the traffic behavior near the critical point. Numerical simulation is compatible with the analysis of theory such as density wave, hysteresis loop, which shows that the new model is reasonable. The results show that considering the effect of driver’s forecast behavior can help to enhance the stability of traffic flow.

An Agent-Based Model of Evolving Community Flood Risk.

PubMed

Tonn, Gina L; Guikema, Seth D

2018-06-01

Although individual behavior plays a major role in community flood risk, traditional flood risk models generally do not capture information on how community policies and individual decisions impact the evolution of flood risk over time. The purpose of this study is to improve the understanding of the temporal aspects of flood risk through a combined analysis of the behavioral, engineering, and physical hazard aspects of flood risk. Additionally, the study aims to develop a new modeling approach for integrating behavior, policy, flood hazards, and engineering interventions. An agent-based model (ABM) is used to analyze the influence of flood protection measures, individual behavior, and the occurrence of floods and near-miss flood events on community flood risk. The ABM focuses on the following decisions and behaviors: dissemination of flood management information, installation of community flood protection, elevation of household mechanical equipment, and elevation of homes. The approach is place based, with a case study area in Fargo, North Dakota, but is focused on generalizable insights. Generally, community mitigation results in reduced future damage, and individual action, including mitigation and movement into and out of high-risk areas, can have a significant influence on community flood risk. The results of this study provide useful insights into the interplay between individual and community actions and how it affects the evolution of flood risk. This study lends insight into priorities for future work, including the development of more in-depth behavioral and decision rules at the individual and community level. © 2017 Society for Risk Analysis.

Investigating Information-Seeking Behavior of Faculty Members Based on Wilson’s Model: Case Study of PNU University, Mazandaran, Iran

PubMed Central

Azadeh, Fereydoon; Ghasemi, Shahrzad

2016-01-01

The present research aims to study information seeking behavior of faculty Members of Payame Noor University (PNU) in Mazandaran province of Iran by using Wilson’s model of information seeking behavior. This is a survey study. Participants were 97 of PNU faculty Members in Mazandaran province. An information-seeking behavior inventory was employed to gather information and research data, which had 24 items based on 5-point likert scale. Collected data were analyzed in SPSS software. Results showed that the most important goal of faculty members was publishing a scientific paper, and their least important goal was updating technical information. Also we found that they mostly use internet-based resources to meet their information needs. Accordingly, 57.7% of them find information resources via online search engines (e.g. Google, Yahoo). Also we concluded that there was a significant relationship between English language proficiency, academic rank, and work experience of them and their information- seeking behavior. PMID:27157151

Toward statistical modeling of saccadic eye-movement and visual saliency.

PubMed

Sun, Xiaoshuai; Yao, Hongxun; Ji, Rongrong; Liu, Xian-Ming

2014-11-01

In this paper, we present a unified statistical framework for modeling both saccadic eye movements and visual saliency. By analyzing the statistical properties of human eye fixations on natural images, we found that human attention is sparsely distributed and usually deployed to locations with abundant structural information. This observations inspired us to model saccadic behavior and visual saliency based on super-Gaussian component (SGC) analysis. Our model sequentially obtains SGC using projection pursuit, and generates eye movements by selecting the location with maximum SGC response. Besides human saccadic behavior simulation, we also demonstrated our superior effectiveness and robustness over state-of-the-arts by carrying out dense experiments on synthetic patterns and human eye fixation benchmarks. Multiple key issues in saliency modeling research, such as individual differences, the effects of scale and blur, are explored in this paper. Based on extensive qualitative and quantitative experimental results, we show promising potentials of statistical approaches for human behavior research.

Unraveling the sub-processes of selective attention: insights from dynamic modeling and continuous behavior.

PubMed

Frisch, Simon; Dshemuchadse, Maja; Görner, Max; Goschke, Thomas; Scherbaum, Stefan

2015-11-01

Selective attention biases information processing toward stimuli that are relevant for achieving our goals. However, the nature of this bias is under debate: Does it solely rely on the amplification of goal-relevant information or is there a need for additional inhibitory processes that selectively suppress currently distracting information? Here, we explored the processes underlying selective attention with a dynamic, modeling-based approach that focuses on the continuous evolution of behavior over time. We present two dynamic neural field models incorporating the diverging theoretical assumptions. Simulations with both models showed that they make similar predictions with regard to response times but differ markedly with regard to their continuous behavior. Human data observed via mouse tracking as a continuous measure of performance revealed evidence for the model solely based on amplification but no indication of persisting selective distracter inhibition.

Agent-Based Models in Social Physics

NASA Astrophysics Data System (ADS)

Quang, Le Anh; Jung, Nam; Cho, Eun Sung; Choi, Jae Han; Lee, Jae Woo

2018-06-01

We review the agent-based models (ABM) on social physics including econophysics. The ABM consists of agent, system space, and external environment. The agent is autonomous and decides his/her behavior by interacting with the neighbors or the external environment with the rules of behavior. Agents are irrational because they have only limited information when they make decisions. They adapt using learning from past memories. Agents have various attributes and are heterogeneous. ABM is a non-equilibrium complex system that exhibits various emergence phenomena. The social complexity ABM describes human behavioral characteristics. In ABMs of econophysics, we introduce the Sugarscape model and the artificial market models. We review minority games and majority games in ABMs of game theory. Social flow ABM introduces crowding, evacuation, traffic congestion, and pedestrian dynamics. We also review ABM for opinion dynamics and voter model. We discuss features and advantages and disadvantages of Netlogo, Repast, Swarm, and Mason, which are representative platforms for implementing ABM.

An individual-based modeling approach to simulate the effects of cellular nutrient competition on Escherichia coli K-12 MG1655 colony behavior and interactions in aerobic structured food systems.

PubMed

Tack, Ignace L M M; Logist, Filip; Noriega Fernández, Estefanía; Van Impe, Jan F M

2015-02-01

Traditional kinetic models in predictive microbiology reliably predict macroscopic dynamics of planktonically-growing cell cultures in homogeneous liquid food systems. However, most food products have a semi-solid structure, where microorganisms grow locally in colonies. Individual colony cells exhibit strongly different and non-normally distributed behavior due to local nutrient competition. As a result, traditional models considering average population behavior in a homogeneous system do not describe colony dynamics in full detail. To incorporate local resource competition and individual cell differences, an individual-based modeling approach has been applied to Escherichia coli K-12 MG1655 colonies, considering the microbial cell as modeling unit. The first contribution of this individual-based model is to describe single colony growth under nutrient-deprived conditions. More specifically, the linear and stationary phase in the evolution of the colony radius, the evolution from a disk-like to branching morphology, and the emergence of a starvation zone in the colony center are simulated and compared to available experimental data. These phenomena occur earlier at more severe nutrient depletion conditions, i.e., at lower nutrient diffusivity and initial nutrient concentration in the medium. Furthermore, intercolony interactions have been simulated. Higher inoculum densities lead to stronger intercolony interactions, such as colony merging and smaller colony sizes, due to nutrient competition. This individual-based model contributes to the elucidation of characteristic experimentally observed colony behavior from mechanistic information about cellular physiology and interactions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Antecedents of Philanthropic Behavior of Health Care Volunteers

ERIC Educational Resources Information Center

Alias, Siti Noormi; Ismail, Maimunah

2015-01-01

Purpose: This paper aims to propose a conceptual model of philanthropic behavior of volunteers in the health care sector. Design/methodology/approach: This study is based on an extensive review of past research on philanthropic behavior. To conduct the literature review, keywords such as philanthropy, philanthropic behavior, giving, donating,…

Emergence of a coherent and cohesive swarm based on mutual anticipation

PubMed Central

Murakami, Hisashi; Niizato, Takayuki; Gunji, Yukio-Pegio

2017-01-01

Collective behavior emerging out of self-organization is one of the most striking properties of an animal group. Typically, it is hypothesized that each individual in an animal group tends to align its direction of motion with those of its neighbors. Most previous models for collective behavior assume an explicit alignment rule, by which an agent matches its velocity with that of neighbors in a certain neighborhood, to reproduce a collective order pattern by simple interactions. Recent empirical studies, however, suggest that there is no evidence for explicit matching of velocity, and that collective polarization arises from interactions other than those that follow the explicit alignment rule. We here propose a new lattice-based computational model that does not incorporate the explicit alignment rule but is based instead on mutual anticipation and asynchronous updating. Moreover, we show that this model can realize densely collective motion with high polarity. Furthermore, we focus on the behavior of a pair of individuals, and find that the turning response is drastically changed depending on the distance between two individuals rather than the relative heading, and is consistent with the empirical observations. Therefore, the present results suggest that our approach provides an alternative model for collective behavior. PMID:28406173

System dynamics-based evaluation of interventions to promote appropriate waste disposal behaviors in low-income urban areas: A Baltimore case study.

PubMed

Guo, Huaqing; Hobbs, Benjamin F; Lasater, Molly E; Parker, Cindy L; Winch, Peter J

2016-10-01

Inappropriate waste disposal is a serious issue in many urban neighborhoods, exacerbating environmental, rodent, and public health problems. Governments all over the world have been developing interventions to reduce inappropriate waste disposal. A system dynamics model is proposed to quantify the impacts of interventions on residential waste related behavior. In contrast to other models of municipal solid waste management, the structure of our model is based on sociological and economic studies on how incentives and social norms interactively affect waste disposal behavior, and its parameterization is informed by field work. A case study of low-income urban neighborhoods in Baltimore, MD, USA is presented. The simulation results show the effects of individual interventions, and also identify positive interactions among some potential interventions, especially information and incentive-based policies, as well as their limitations. The model can help policy analysts identify the most promising intervention packages, and then field test those few, rather than having to pilot test all combinations. Sensitivity analyses demonstrate large uncertainties about behavioral responses to some interventions, showing where information from survey research and social experiments would improve policy making. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling of Continuum Manipulators Using Pythagorean Hodograph Curves.

PubMed

Singh, Inderjeet; Amara, Yacine; Melingui, Achille; Mani Pathak, Pushparaj; Merzouki, Rochdi

2018-05-10

Research on continuum manipulators is increasingly developing in the context of bionic robotics because of their many advantages over conventional rigid manipulators. Due to their soft structure, they have inherent flexibility, which makes it a huge challenge to control them with high performances. Before elaborating a control strategy of such robots, it is essential to reconstruct first the behavior of the robot through development of an approximate behavioral model. This can be kinematic or dynamic depending on the conditions of operation of the robot itself. Kinematically, two types of modeling methods exist to describe the robot behavior; quantitative methods describe a model-based method, and qualitative methods describe a learning-based method. In kinematic modeling of continuum manipulator, the assumption of constant curvature is often considered to simplify the model formulation. In this work, a quantitative modeling method is proposed, based on the Pythagorean hodograph (PH) curves. The aim is to obtain a three-dimensional reconstruction of the shape of the continuum manipulator with variable curvature, allowing the calculation of its inverse kinematic model (IKM). It is noticed that the performances of the PH-based kinematic modeling of continuum manipulators are considerable regarding position accuracy, shape reconstruction, and time/cost of the model calculation, than other kinematic modeling methods, for two cases: free load manipulation and variable load manipulation. This modeling method is applied to the compact bionic handling assistant (CBHA) manipulator for validation. The results are compared with other IKMs developed in case of CBHA manipulator.

Effects of the Communities That Care Model in Pennsylvania on Change in Adolescent Risk and Problem Behaviors

PubMed Central

Jones, Damon; Greenberg, Mark T.; Osgood, D. Wayne; Bontempo, Daniel

2015-01-01

Despite the public health burden of adolescent substance use, delinquency, and other problem behavior, few comprehensive models of disseminating evidence-based prevention programs to communities have demonstrated positive youth outcomes at a population level, capacity to maintain program fidelity, and sustainability. We examined whether the Communities That Care (CTC; Hawkins and Catalano 1992) model had a positive impact on risk/protective factors and academic and behavioral outcomes among adolescents in a quasi-experimental effectiveness study. We conducted a longitudinal study of CTC in Pennsylvania utilizing biannual surveillance data collected through anonymous in-school student surveys. We utilized multilevel models to examine CTC impact on change in risk/protective factors, grades, delinquency, and substance use over time. Youth in CTC communities demonstrated less growth in delinquency, but not substance use, than youth in non-CTC communities. Levels of risk factors increased more slowly, and protective factors and academic performance decreased more slowly, among CTC community grade-cohorts that were exposed to evidence-based, universal prevention programs than comparison grade cohorts. Community coalitions can affect adolescent risk and protective behaviors at a population level when evidence-based programs are utilized. CTC represents an effective model for disseminating such programs. PMID:20020209

A dislocation density based micromechanical constitutive model for Sn-Ag-Cu solder alloys

NASA Astrophysics Data System (ADS)

Liu, Lu; Yao, Yao; Zeng, Tao; Keer, Leon M.

2017-10-01

Based on the dislocation density hardening law, a micromechanical model considering the effects of precipitates is developed for Sn-Ag-Cu solder alloys. According to the microstructure of the Sn-3.0Ag-0.5Cu thin films, intermetallic compounds (IMCs) are assumed as sphere particles embedded in the polycrystalline β-Sn matrix. The mechanical behavior of polycrystalline β-Sn matrix is determined by the elastic-plastic self-consistent method. The existence of IMCs not only impedes the motion of dislocations but also increases the overall stiffness. Thus, a dislocation density based hardening law considering non-shearable precipitates is adopted locally for single β-Sn crystal, and the Mori-Tanaka scheme is applied to describe the overall viscoplastic behavior of solder alloys. The proposed model is incorporated into finite element analysis and the corresponding numerical implementation method is presented. The model can describe the mechanical behavior of Sn-3.0Ag-0.5Cu and Sn-1.0Ag-0.5Cu alloys under high strain rates at a wide range of temperatures. Furthermore, the overall Young’s modulus changes due to different contents of IMCs is predicted and compared with experimental data. Results show that the proposed model can describe both elastic and inelastic behavior of solder alloys with reasonable accuracy.

Fatigue crack propagation behavior of stainless steel welds

NASA Astrophysics Data System (ADS)

Kusko, Chad S.

The fatigue crack propagation behavior of austenitic and duplex stainless steel base and weld metals has been investigated using various fatigue crack growth test procedures, ferrite measurement techniques, light optical microscopy, stereomicroscopy, scanning electron microscopy, and optical profilometry. The compliance offset method has been incorporated to measure crack closure during testing in order to determine a stress ratio at which such closure is overcome. Based on this method, an empirically determined stress ratio of 0.60 has been shown to be very successful in overcoming crack closure for all da/dN for gas metal arc and laser welds. This empirically-determined stress ratio of 0.60 has been applied to testing of stainless steel base metal and weld metal to understand the influence of microstructure. Regarding the base metal investigation, for 316L and AL6XN base metals, grain size and grain plus twin size have been shown to influence resulting crack growth behavior. The cyclic plastic zone size model has been applied to accurately model crack growth behavior for austenitic stainless steels when the average grain plus twin size is considered. Additionally, the effect of the tortuous crack paths observed for the larger grain size base metals can be explained by a literature model for crack deflection. Constant Delta K testing has been used to characterize the crack growth behavior across various regions of the gas metal arc and laser welds at the empirically determined stress ratio of 0.60. Despite an extensive range of stainless steel weld metal FN and delta-ferrite morphologies, neither delta-ferrite morphology significantly influence the room temperature crack growth behavior. However, variations in weld metal da/dN can be explained by local surface roughness resulting from large columnar grains and tortuous crack paths in the weld metal.

Behavioral Responses Of Fish To A Current-Based Hydrokinetic Turbine Under Mutlipe Operational Conditions: Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grippo, Mark A.; Shen, Haixue; Zydlewski, Gayle

There is significant interest in the interaction of aquatic organisms with current-based marine and hydrokinetic (MHK) technologies. Determining the potential impacts of MHK devices on fish behavior is critical to addressing the environmental concerns that could act as barriers to the permitting and deployment of MHK devices. To address these concerns, we use field monitoring and fish behavior models to characterize the behavioral responses of fish to MHK turbines and infer potential stimuli that may have elicited the observed behavioral changes.

The oxytocin system in drug discovery for autism: Animal models and novel therapeutic strategies

PubMed Central

Modi, Meera E.; Young, Larry J.

2012-01-01

Animal models and behavioral paradigms are critical for elucidating the neural mechanism involved in complex behaviors, including social cognition. Both genotype and phenotype based models have implicated the neuropeptide oxytocin (OT) in the regulation of social behavior. Based on the findings in animal models, alteration of the OT system has been hypothesized to play a role in the social deficits associated with autism and other neuropsychiatric disorders. While the evidence linking the peptide to the etiology of the disorder is not yet conclusive, evidence from multiple animal models suggest modulation of the OT system may be a viable strategy for the pharmacological treatment of social deficits. In this review, we will discuss how animal models have been utilized to understand the role of OT in social cognition and how those findings can be applied to the conceptualization and treatment of the social impairments in ASD. Animal models with genetic alterations of the OT system, like the OT, OT receptor and CD38 knock-out mice, and those with phenotypic variation in social behavior, like BTBR inbred mice and prairie voles, coupled with behavioral paradigms with face and construct validity may prove to have predictive validity for identifying the most efficacious methods of stimulating the OT system to enhance social cognition in humans. The widespread use of strong animal models of social cognition has the potential yield pharmacological, interventions for the treatment social impairments psychiatric disorders. This article is part of a Special Issue entitled Oxytocin, Vasopressin, and Social Behavior. PMID:22206823

Deformation analysis of polymers composites: rheological model involving time-based fractional derivative

NASA Astrophysics Data System (ADS)

Zhou, H. W.; Yi, H. Y.; Mishnaevsky, L.; Wang, R.; Duan, Z. Q.; Chen, Q.

2017-05-01

A modeling approach to time-dependent property of Glass Fiber Reinforced Polymers (GFRP) composites is of special interest for quantitative description of long-term behavior. An electronic creep machine is employed to investigate the time-dependent deformation of four specimens of dog-bond-shaped GFRP composites at various stress level. A negative exponent function based on structural changes is introduced to describe the damage evolution of material properties in the process of creep test. Accordingly, a new creep constitutive equation, referred to fractional derivative Maxwell model, is suggested to characterize the time-dependent behavior of GFRP composites by replacing Newtonian dashpot with the Abel dashpot in the classical Maxwell model. The analytic solution for the fractional derivative Maxwell model is given and the relative parameters are determined. The results estimated by the fractional derivative Maxwell model proposed in the paper are in a good agreement with the experimental data. It is shown that the new creep constitutive model proposed in the paper needs few parameters to represent various time-dependent behaviors.

Genetic and Modeling Approaches Reveal Distinct Components of Impulsive Behavior

PubMed Central

Nautiyal, Katherine M; Wall, Melanie M; Wang, Shuai; Magalong, Valerie M; Ahmari, Susanne E; Balsam, Peter D; Blanco, Carlos; Hen, René

2017-01-01

Impulsivity is an endophenotype found in many psychiatric disorders including substance use disorders, pathological gambling, and attention deficit hyperactivity disorder. Two behavioral features often considered in impulsive behavior are behavioral inhibition (impulsive action) and delayed gratification (impulsive choice). However, the extent to which these behavioral constructs represent distinct facets of behavior with discrete biological bases is unclear. To test the hypothesis that impulsive action and impulsive choice represent statistically independent behavioral constructs in mice, we collected behavioral measures of impulsivity in a single cohort of mice using well-validated operant behavioral paradigms. Mice with manipulation of serotonin 1B receptor (5-HT1BR) expression were included as a model of disordered impulsivity. A factor analysis was used to characterize correlations between the measures of impulsivity and to identify covariates. Using two approaches, we dissociated impulsive action from impulsive choice. First, the absence of 5-HT1BRs caused increased impulsive action, but not impulsive choice. Second, based on an exploratory factor analysis, a two-factor model described the data well, with measures of impulsive action and choice separating into two independent factors. A multiple-indicator multiple-causes analysis showed that 5-HT1BR expression and sex were significant covariates of impulsivity. Males displayed increased impulsivity in both dimensions, whereas 5-HT1BR expression was a predictor of increased impulsive action only. These data support the conclusion that impulsive action and impulsive choice are distinct behavioral phenotypes with dissociable biological influences that can be modeled in mice. Our work may help inform better classification, diagnosis, and treatment of psychiatric disorders, which present with disordered impulsivity. PMID:27976680

Consentaneous Agent-Based and Stochastic Model of the Financial Markets

PubMed Central

Gontis, Vygintas; Kononovicius, Aleksejus

2014-01-01

We are looking for the agent-based treatment of the financial markets considering necessity to build bridges between microscopic, agent based, and macroscopic, phenomenological modeling. The acknowledgment that agent-based modeling framework, which may provide qualitative and quantitative understanding of the financial markets, is very ambiguous emphasizes the exceptional value of well defined analytically tractable agent systems. Herding as one of the behavior peculiarities considered in the behavioral finance is the main property of the agent interactions we deal with in this contribution. Looking for the consentaneous agent-based and macroscopic approach we combine two origins of the noise: exogenous one, related to the information flow, and endogenous one, arising form the complex stochastic dynamics of agents. As a result we propose a three state agent-based herding model of the financial markets. From this agent-based model we derive a set of stochastic differential equations, which describes underlying macroscopic dynamics of agent population and log price in the financial markets. The obtained solution is then subjected to the exogenous noise, which shapes instantaneous return fluctuations. We test both Gaussian and q-Gaussian noise as a source of the short term fluctuations. The resulting model of the return in the financial markets with the same set of parameters reproduces empirical probability and spectral densities of absolute return observed in New York, Warsaw and NASDAQ OMX Vilnius Stock Exchanges. Our result confirms the prevalent idea in behavioral finance that herding interactions may be dominant over agent rationality and contribute towards bubble formation. PMID:25029364

A Behavior-Based Circuit Model of How Outcome Expectations Organize Learned Behavior in Larval "Drosophila"

ERIC Educational Resources Information Center

Schleyer, Michael; Saumweber, Timo; Nahrendorf, Wiebke; Fischer, Benjamin; von Alpen, Desiree; Pauls, Dennis; Thum, Andreas; Gerber, Bertram

2011-01-01

Drosophila larvae combine a numerically simple brain, a correspondingly moderate behavioral complexity, and the availability of a rich toolbox for transgenic manipulation. This makes them attractive as a study case when trying to achieve a circuit-level understanding of behavior organization. From a series of behavioral experiments, we suggest a…

Using GOMS and Bayesian plan recognition to develop recognition models of operator behavior

NASA Astrophysics Data System (ADS)

Zaientz, Jack D.; DeKoven, Elyon; Piegdon, Nicholas; Wood, Scott D.; Huber, Marcus J.

2006-05-01

Trends in combat technology research point to an increasing role for uninhabited vehicles in modern warfare tactics. To support increased span of control over these vehicles human responsibilities need to be transformed from tedious, error-prone and cognition intensive operations into tasks that are more supervisory and manageable, even under intensely stressful conditions. The goal is to move away from only supporting human command of low-level system functions to intention-level human-system dialogue about the operator's tasks and situation. A critical element of this process is developing the means to identify when human operators need automated assistance and to identify what assistance they need. Toward this goal, we are developing an unmanned vehicle operator task recognition system that combines work in human behavior modeling and Bayesian plan recognition. Traditionally, human behavior models have been considered generative, meaning they describe all possible valid behaviors. Basing behavior recognition on models designed for behavior generation can offers advantages in improved model fidelity and reuse. It is not clear, however, how to reconcile the structural differences between behavior recognition and behavior modeling approaches. Our current work demonstrates that by pairing a cognitive psychology derived human behavior modeling approach, GOMS, with a Bayesian plan recognition engine, ASPRN, we can translate a behavior generation model into a recognition model. We will discuss the implications for using human performance models in this manner as well as suggest how this kind of modeling may be used to support the real-time control of multiple, uninhabited battlefield vehicles and other semi-autonomous systems.

Building a Progressive-Situational Model of Post-Diagnosis Information Seeking for Parents of Individuals With Down Syndrome

PubMed Central

Gibson, Amelia N.

2016-01-01

This grounded theory study used in-depth, semi-structured interview to examine the information-seeking behaviors of 35 parents of children with Down syndrome. Emergent themes include a progressive pattern of behavior including information overload and avoidance, passive attention, and active information seeking; varying preferences between tacit and explicit information at different stages; and selection of information channels and sources that varied based on personal and situational constraints. Based on the findings, the author proposes a progressive model of health information seeking and a framework for using this model to collect data in practice. The author also discusses the practical and theoretical implications of a responsive, progressive approach to understanding parents’ health information–seeking behavior. PMID:28462351

Implementation Integrity of Practice-Based Coaching: Preliminary Results from the BEST in CLASS Efficacy Trial

ERIC Educational Resources Information Center

Sutherland, Kevin S.; Conroy, Maureen A.; Vo, Abigail; Ladwig, Crystal

2015-01-01

The purpose of this article is to describe the practice-based coaching model used in BEST in CLASS, a Tier-2 classroom-based intervention comprised of evidence-based instructional practices designed to prevent and ameliorate the chronic problem behaviors of young children at risk for the development of emotional/behavioral disorders. Following a…

Preparing Digital Stories through the Inquiry-Based Learning Approach: Its Effect on Prospective Teachers' Resistive Behaviors toward Research and Technology-Based Instruction

ERIC Educational Resources Information Center

Yavuz Konokman, Gamze; Yanpar Yelken, Tugba

2016-01-01

The purpose of the study was to determine the effect of preparing digital stories through an inquiry based learning approach on prospective teachers' resistive behaviors toward technology based instruction and conducting research. The research model was convergent parallel design. The sample consisted of 50 prospective teachers who had completed…

Adaptive model-based assistive control for pneumatic direct driven soft rehabilitation robots.

PubMed

Wilkening, Andre; Ivlev, Oleg

2013-06-01

Assistive behavior and inherent compliance are assumed to be the essential properties for effective robot-assisted therapy in neurological as well as in orthopedic rehabilitation. This paper presents two adaptive model-based assistive controllers for pneumatic direct driven soft rehabilitation robots that are based on separated models of the soft-robot and the patient's extremity, in order to take into account the individual patient's behavior, effort and ability during control, what is assumed to be essential to relearn lost motor functions in neurological and facilitate muscle reconstruction in orthopedic rehabilitation. The high inherent compliance of soft-actuators allows for a general human-robot interaction and provides the base for effective and dependable assistive control. An inverse model of the soft-robot with estimated parameters is used to achieve robot transparency during treatment and inverse adaptive models of the individual patient's extremity allow the controllers to learn on-line the individual patient's behavior and effort and react in a way that assist the patient only as much as needed. The effectiveness of the controllers is evaluated with unimpaired subjects using a first prototype of a soft-robot for elbow training. Advantages and disadvantages of both controllers are analyzed and discussed.

Comparative analysis of neural network and regression based condition monitoring approaches for wind turbine fault detection

NASA Astrophysics Data System (ADS)

Schlechtingen, Meik; Ferreira Santos, Ilmar

2011-07-01

This paper presents the research results of a comparison of three different model based approaches for wind turbine fault detection in online SCADA data, by applying developed models to five real measured faults and anomalies. The regression based model as the simplest approach to build a normal behavior model is compared to two artificial neural network based approaches, which are a full signal reconstruction and an autoregressive normal behavior model. Based on a real time series containing two generator bearing damages the capabilities of identifying the incipient fault prior to the actual failure are investigated. The period after the first bearing damage is used to develop the three normal behavior models. The developed or trained models are used to investigate how the second damage manifests in the prediction error. Furthermore the full signal reconstruction and the autoregressive approach are applied to further real time series containing gearbox bearing damages and stator temperature anomalies. The comparison revealed all three models being capable of detecting incipient faults. However, they differ in the effort required for model development and the remaining operational time after first indication of damage. The general nonlinear neural network approaches outperform the regression model. The remaining seasonality in the regression model prediction error makes it difficult to detect abnormality and leads to increased alarm levels and thus a shorter remaining operational period. For the bearing damages and the stator anomalies under investigation the full signal reconstruction neural network gave the best fault visibility and thus led to the highest confidence level.

A conditional process model of children's behavioral engagement and behavioral disaffection in sport based on self-determination theory.

PubMed

Curran, Thomas; Hill, Andrew P; Niemiec, Christopher P

2013-02-01

The potential benefits of children's engagement in sport for their psychological, social, and physical health are well established. Yet children may also experience psychological and social impairments due, in part, to a variety of detrimental coach behaviors. In the current study, we proposed and tested a conditional process model of children's self-reported behavioral engagement and behavioral disaffection in sport based on self-determination theory. Results from a sample of 245 youth soccer players suggested that structure from coaches related positively to behavioral engagement and negatively to behavioral disaffection, and that these relations were mediated by athletes' basic psychological need satisfaction. Importantly, and in line with our hypotheses, these indirect effects were moderated by autonomy support from coaches, such that the mediation was evident only among those who reported higher levels of autonomy support. These findings underscore the importance of coaches' providing guidance, expectations, and feedback (i.e., structure) in a way that respects athletes' volition (i.e., autonomy support).

A continuum-based structural modeling approach for cellulose nanocrystals (CNCs)

NASA Astrophysics Data System (ADS)

Shishehbor, Mehdi; Dri, Fernando L.; Moon, Robert J.; Zavattieri, Pablo D.

2018-02-01

We present a continuum-based structural model to study the mechanical behavior of cellulose nanocrystals (CNCs), and analyze the effect of bonded and non-bonded interactions on the mechanical properties under various loading conditions. In particular, this model assumes the uncoupling between the bonded and non-bonded interactions and their behavior is obtained from atomistic simulations. Our results indicates that the major contribution to the tensile and bending stiffness is mainly due to the cellulose chain stiffness, and the shear behavior is mainly governed by Van der Waals (VdW) forces. In addition, we report a negligible torsional stiffness, which may explain the CNC tendency to easily twist under very small or nonexistent torques. In addition, the sensitivity of geometrical imperfection on the mechanical properties using an analytical model of the CNC structure was investigated. Our results indicate that the presence of imperfections have a small influence on the majority of the elastic properties. Finally, it is shown that a simple homogeneous and orthotropic representation of a CNC under bending underestimates the contribution of non-bonded interaction leading up to 60% error in the calculation of the bending stiffness of CNCs. On the other hand, the proposed model can lead to more accurate predictions of the elastic behavior of CNCs. This is the first step toward the development of a more efficient model that can be used to model the inelastic behavior of single and multiple CNCs.

Simulating Fire Disturbance and Plant Mortality Using Antecedent Eco-hydrological Conditions to Inform a Physically Based Combustion Model

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Middleton, R. S.; Runde, I.; Coon, E.; Michaletz, S. T.

2016-12-01

Wildfire is a complex agent of change that both affects and depends on eco-hydrological systems, thereby constituting a tightly linked system of disturbances and eco-hydrological conditions. For example, structure, build-up, and moisture content of fuel are dependent on eco-hydrological regimes, which impacts fire spread and intensity. Fire behavior, on the other hand, determines the severity and extent of eco-hydrological disturbance, often resulting in a mosaic of untouched, stressed, damaged, or completely destroyed vegetation within the fire perimeter. This in turn drives new eco-hydrological system behavior. The cycles of disturbance and recovery present a complex evolving system with many unknowns especially in the face of climate change that has implications for fire risk, water supply, and forest composition. Physically-based numerical experiments that attempt to capture the complex linkages between eco-hydrological regimes that affect fire behavior and the echo-hydrological response from those fire disturbances help build the understanding required to project how fire disturbance and eco-hydrological conditions coevolve over time. Here we explore the use of FIRETEC—a physically-based 3D combustion model that solves conservation of mass, momentum, energy, and chemical species—to resolve fire spread over complex terrain and fuel structures. Uniquely, we couple a physically-based plant mortality model with FIRETEC and examine the resultant hydrologic impact. In this proof of concept demonstration we spatially distribute fuel structure and moisture content based on the eco-hydrological condition to use as input for FIRETEC. The fire behavior simulation then produces localized burn severity and heat injures which are used as input to a spatially-informed plant mortality model. Ultimately we demonstrate the applicability of physically-based models to explore integrated disturbance and eco-hydrologic response to wildfire behavior and specifically map how fire spread and intensity is affect by the antecedent eco-hydrological condition, which then affects the resulting tree mortality patterns.

Development of a health information technology acceptance model using consumers' health behavior intention.

PubMed

Kim, Jeongeun; Park, Hyeoun-Ae

2012-10-01

For effective health promotion using health information technology (HIT), it is mandatory that health consumers have the behavioral intention to measure, store, and manage their own health data. Understanding health consumers' intention and behavior is needed to develop and implement effective and efficient strategies. To develop and verify the extended Technology Acceptance Model (TAM) in health care by describing health consumers' behavioral intention of using HIT. This study used a cross-sectional descriptive correlational design. We extended TAM by adding more antecedents and mediating variables to enhance the model's explanatory power and to make it more applicable to health consumers' behavioral intention. Additional antecedents and mediating variables were added to the hypothetical model, based on their theoretical relevance, from the Health Belief Model and theory of planned behavior, along with the TAM. We undertook structural equation analysis to examine the specific nature of the relationship involved in understanding consumers' use of HIT. Study participants were 728 members recruited from three Internet health portals in Korea. Data were collected by a Web-based survey using a structured self-administered questionnaire. The overall fitness indices for the model developed in this study indicated an acceptable fit of the model. All path coefficients were statistically significant. This study showed that perceived threat, perceived usefulness, and perceived ease of use significantly affected health consumers' attitude and behavioral intention. Health consumers' health status, health belief and concerns, subjective norm, HIT characteristics, and HIT self-efficacy had a strong indirect impact on attitude and behavioral intention through the mediators of perceived threat, perceived usefulness, and perceived ease of use. An extended TAM in the HIT arena was found to be valid to describe health consumers' behavioral intention. We categorized the concepts in the extended TAM into 3 domains: health zone, information zone, and technology zone.

Model-Based Spectrum Management. Part 1: Modeling and Computation Manual, Version 2.0

DTIC Science & Technology

2013-12-01

Occurrence of Occlusion by the Earth’s Surface C- 4 Figure C-6. Scenario for Evaluating the Significance of Angle Discrepancy in Using Planar...their transmit power at those locations. Many developers of DSA systems seek more aggressive sharing that favors behaviors allowing compatible reuse...provide behavioral guidance that allows finer coexistence mechanisms, e.g., mechanisms based on sensing and timing in addition to location as means to

Predictive modeling and reducing cyclic variability in autoignition engines

DOEpatents

Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob

2016-08-30

Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.

For Fit's Sake: A Norms-Based Approach to Healthy Behaviors Through Influence of Presumed Media Influence.

PubMed

Ho, Shirley S; Lee, Edmund W J; Ng, Kaijie; Leong, Grace S H; Tham, Tiffany H M

2016-09-01

Based on the influence of presumed media influence (IPMI) model as the theoretical framework, this study examines how injunctive norms and personal norms mediate the influence of healthy lifestyle media messages on public intentions to engage in two types of healthy lifestyle behaviors-physical activity and healthy diet. Nationally representative data collected from 1,055 adults in Singapore demonstrate partial support for the key hypotheses that make up the extended IPMI model, highlighting the importance of a norms-based approach in health communication. Our results indicate that perceived media influence on others indirectly shaped public intentions to engage in healthy lifestyle behaviors through personal norms and attitude, providing partial theoretical support for the extended IPMI model. Practical implications for health communicators in designing health campaigns media messages to motivate the public to engage in healthy lifestyle are discussed.

The effects of health promotion model-based educational program on self-care behaviors in patients undergoing coronary artery bypass grafting in Iran

PubMed Central

Mohsenipouya, Hossein; Majlessi, Fereshteh; Ghafari, Rahman

2018-01-01

Background and aim Post-operative self-care behaviors, have positive effects on increase in adaptability, and reduce cardiac surgery patients’ disability. The present study is carried out aimed at determining the effect of education based on a health promotion model on the patients’ self-care behaviors after coronary artery bypass surgery. Methods This is a semi-experimental study carried out in Mazandaran (Iran) in 2016. Two hundred and twenty patients who participated in the study were selected using a simple random sampling method from a population of postoperative patients, and divided into control and experimental groups (110 patients in each) using block (AABB) randomization. Self-designed self-care questionnaires based on a health promotion model were distributed among the patients once before and three months after intervention. The data were analyzed by SPSS-22, Chi-Square tests, Mann-Whitney and ANCOVA at the significance level of p<0.05. Results The average score of total self-care behaviors in cardiac surgery patients was not significant between the two groups before education (p=0.065), but after training, a significant difference was observed between the two groups (p<0.001). The analysis of ANOVA with repeated measure indicated that following the intervention, significant difference was observed between the two groups in terms of improvement of self-care behaviors after excluding the effect of pre-test and controlling demographic and health-related characteristics. Conclusions Developing and implementing a training program based on the health promotion model can enhance self-care behaviors and reduce the number of admissions in patients after cardiac surgery. PMID:29588828

An Agent-Based Epidemic Simulation of Social Behaviors Affecting HIV Transmission among Taiwanese Homosexuals

PubMed Central

2015-01-01

Computational simulations are currently used to identify epidemic dynamics, to test potential prevention and intervention strategies, and to study the effects of social behaviors on HIV transmission. The author describes an agent-based epidemic simulation model of a network of individuals who participate in high-risk sexual practices, using number of partners, condom usage, and relationship length to distinguish between high- and low-risk populations. Two new concepts—free links and fixed links—are used to indicate tendencies among individuals who either have large numbers of short-term partners or stay in long-term monogamous relationships. An attempt was made to reproduce epidemic curves of reported HIV cases among male homosexuals in Taiwan prior to using the agent-based model to determine the effects of various policies on epidemic dynamics. Results suggest that when suitable adjustments are made based on available social survey statistics, the model accurately simulates real-world behaviors on a large scale. PMID:25815047

Internet messenger based smart virtual class learning using ubiquitous computing

NASA Astrophysics Data System (ADS)

Umam, K.; Mardi, S. N. S.; Hariadi, M.

2017-06-01

Internet messenger (IM) has become an important educational technology component in college education, IM makes it possible for students to engage in learning and collaborating at smart virtual class learning (SVCL) using ubiquitous computing. However, the model of IM-based smart virtual class learning using ubiquitous computing and empirical evidence that would favor a broad application to improve engagement and behavior are still limited. In addition, the expectation that IM based SVCL using ubiquitous computing could improve engagement and behavior on smart class cannot be confirmed because the majority of the reviewed studies followed instructions paradigms. This article aims to present the model of IM-based SVCL using ubiquitous computing and showing learners’ experiences in improved engagement and behavior for learner-learner and learner-lecturer interactions. The method applied in this paper includes design process and quantitative analysis techniques, with the purpose of identifying scenarios of ubiquitous computing and realize the impressions of learners and lecturers about engagement and behavior aspect and its contribution to learning

An agent-based model of cattle grazing toxic Geyer's larkspur.

PubMed

Jablonski, Kevin E; Boone, Randall B; Meiman, Paul J

2018-01-01

By killing cattle and otherwise complicating management, the many species of larkspur (Delphinium spp.) present a serious, intractable, and complex challenge to livestock grazing management in the western United States. Among the many obstacles to improving our understanding of cattle-larkspur dynamics has been the difficulty of testing different grazing management strategies in the field, as the risk of dead animals is too great. Agent-based models (ABMs) provide an effective method of testing alternate management strategies without risk to livestock. ABMs are especially useful for modeling complex systems such as livestock grazing management, and allow for realistic bottom-up encoding of cattle behavior. Here, we introduce a spatially-explicit, behavior-based ABM of cattle grazing in a pasture with a dangerous amount of Geyer's larkspur (D. geyeri). This model tests the role of herd cohesion and stocking density in larkspur intake, finds that both are key drivers of larkspur-induced toxicosis, and indicates that alteration of these factors within realistic bounds can mitigate risk. Crucially, the model points to herd cohesion, which has received little attention in the discipline, as playing an important role in lethal acute toxicosis. As the first ABM to model grazing behavior at realistic scales, this study also demonstrates the tremendous potential of ABMs to illuminate grazing management dynamics, including fundamental aspects of livestock behavior amidst ecological heterogeneity.

Gradient Plasticity Model and its Implementation into MARMOT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barker, Erin I.; Li, Dongsheng; Zbib, Hussein M.

2013-08-01

The influence of strain gradient on deformation behavior of nuclear structural materials, such as boby centered cubic (bcc) iron alloys has been investigated. We have developed and implemented a dislocation based strain gradient crystal plasticity material model. A mesoscale crystal plasticity model for inelastic deformation of metallic material, bcc steel, has been developed and implemented numerically. Continuum Dislocation Dynamics (CDD) with a novel constitutive law based on dislocation density evolution mechanisms was developed to investigate the deformation behaviors of single crystals, as well as polycrystalline materials by coupling CDD and crystal plasticity (CP). The dislocation density evolution law in thismore » model is mechanism-based, with parameters measured from experiments or simulated with lower-length scale models, not an empirical law with parameters back-fitted from the flow curves.« less

Inference of pain stimulus level from stereotypical behavioral response of C.elegans allows quantification of effects of anesthesia and mutation

NASA Astrophysics Data System (ADS)

Leung, Kawai; Mohammadi, Aylia; Ryu, William; Nemenman, Ilya

In animals, we must infer the pain level from experimental characterization of behavior. This is not trivial since behaviors are very complex and multidimensional. To establish C.elegans as a model for pain research, we propose for the first time a quantitative model that allows inference of a thermal nociceptive stimulus level from the behavior of an individual worm. We apply controlled levels of pain by locally heating worms with an infrared laser and capturing the subsequent behavior. We discover that the behavioral response is a product of stereotypical behavior and a nonlinear function of the strength of stimulus. The same stereotypical behavior is observed in normal, anesthetized and mutated worms. From this result we build a Bayesian model to infer the strength of laser stimulus from the behavior. This model allows us to measure the efficacy of anaesthetization and mutation by comparing the inferred strength of stimulus. Based on the measured nociceptive escape of over 200 worms, our model is able to significantly differentiate normal, anaesthetized and mutated worms with 40 worm samples. This work was partially supported by NSF Grant No. IOS/1208126 and HFSP Grant No. RGY0084/.

Time-independent Anisotropic Plastic Behavior by Mechanical Subelement Models

NASA Technical Reports Server (NTRS)

Pian, T. H. H.

1983-01-01

The paper describes a procedure for modelling the anisotropic elastic-plastic behavior of metals in plane stress state by the mechanical sub-layer model. In this model the stress-strain curves along the longitudinal and transverse directions are represented by short smooth segments which are considered as piecewise linear for simplicity. The model is incorporated in a finite element analysis program which is based on the assumed stress hybrid element and the iscoplasticity-theory.

Theory of planned behavior and smoking: meta-analysis and SEM model

PubMed Central

Topa, Gabriela; Moriano, Juan Antonio

2010-01-01

To examine if the theory of planned behavior (TPB) predicts smoking behavior, 35 data sets (N = 267,977) have been synthesized, containing 219 effect sizes between the model variables, using a meta-analytic structural equation modeling approach (MASEM). Consistent with the TPB’s predictions, 1) smoking behavior was related to smoking intentions (weighted mean r = 0.30), 2) intentions were based on attitudes (weighted mean r = 0.16), and subjective norms (weighted mean r = 0.20). Consistent with TPB’s hypotheses, perceived behavioral control was related to smoking intentions (weighted mean r = −0.24) and behaviors (weighted mean r = −0.20) and it contributes significantly to cigarette consumption. The strength of the associations, however, was influenced by the characteristics of the studies and participants. PMID:24474850

Modeling the behavioral substrates of associate learning and memory - Adaptive neural models

NASA Technical Reports Server (NTRS)

Lee, Chuen-Chien

1991-01-01

Three adaptive single-neuron models based on neural analogies of behavior modification episodes are proposed, which attempt to bridge the gap between psychology and neurophysiology. The proposed models capture the predictive nature of Pavlovian conditioning, which is essential to the theory of adaptive/learning systems. The models learn to anticipate the occurrence of a conditioned response before the presence of a reinforcing stimulus when training is complete. Furthermore, each model can find the most nonredundant and earliest predictor of reinforcement. The behavior of the models accounts for several aspects of basic animal learning phenomena in Pavlovian conditioning beyond previous related models. Computer simulations show how well the models fit empirical data from various animal learning paradigms.

Cognitive Behavioral Theories Used to Explain Injection Risk Behavior among Injection Drug Users: A Review and Suggestions for the Integration of Cognitive and Environmental Models

ERIC Educational Resources Information Center

Wagner, Karla Dawn; Unger, Jennifer B.; Bluthenthal, Ricky N.; Andreeva, Valentina A.; Pentz, Mary Ann

2010-01-01

Injection drug users (IDUs) are at risk for HIV and viral hepatitis, and risky injection behavior persists despite decades of intervention. Cognitive behavioral theories (CBTs) are commonly used to help understand risky injection behavior. The authors review findings from CBT-based studies of injection risk behavior among IDUs. An extensive…

Active lifestyles in older adults: an integrated predictive model of physical activity and exercise

PubMed Central

Galli, Federica; Chirico, Andrea; Mallia, Luca; Girelli, Laura; De Laurentiis, Michelino; Lucidi, Fabio; Giordano, Antonio; Botti, Gerardo

2018-01-01

Physical activity and exercise have been identified as behaviors to preserve physical and mental health in older adults. The aim of the present study was to test the Integrated Behavior Change model in exercise and physical activity behaviors. The study evaluated two different samples of older adults: the first engaged in exercise class, the second doing spontaneous physical activity. The key analyses relied on Variance-Based Structural Modeling, which were performed by means of WARP PLS 6.0 statistical software. The analyses estimated the Integrated Behavior Change model in predicting exercise and physical activity, in a longitudinal design across two months of assessment. The tested models exhibited a good fit with the observed data derived from the model focusing on exercise, as well as with those derived from the model focusing on physical activity. Results showed, also, some effects and relations specific to each behavioral context. Results may form a starting point for future experimental and intervention research. PMID:29875997

Understanding and Changing Food Consumption Behavior Among Children: The Comprehensive Child Consumption Patterns Model.

PubMed

Jeffries, Jayne K; Noar, Seth M; Thayer, Linden

2015-01-01

Current theoretical models attempting to explain diet-related weight status among children center around three individual-level theories. Alone, these theories fail to explain why children are engaging or not engaging in health-promoting eating behaviors. Our Comprehensive Child Consumption Patterns model takes a comprehensive approach and was developed specifically to help explain child food consumption behavior and addresses many of the theoretical gaps found in previous models, including integration of the life course trajectory, key influencers, perceived behavioral control, and self-regulation. Comprehensive Child Consumption Patterns model highlights multiple levels of the socioecological model to explain child food consumption, illustrating how negative influence at multiple levels can lead to caloric imbalance and contribute to child overweight and obesity. Recognizing the necessity for multi-level and system-based interventions, this model serves as a template for holistic, integrated interventions to improve child eating behavior, ultimately impacting life course health development. © The Author(s) 2015.

Application of Psychological Theories in Agent-Based Modeling: The Case of the Theory of Planned Behavior.

PubMed

Scalco, Andrea; Ceschi, Andrea; Sartori, Riccardo

2018-01-01

It is likely that computer simulations will assume a greater role in the next future to investigate and understand reality (Rand & Rust, 2011). Particularly, agent-based models (ABMs) represent a method of investigation of social phenomena that blend the knowledge of social sciences with the advantages of virtual simulations. Within this context, the development of algorithms able to recreate the reasoning engine of autonomous virtual agents represents one of the most fragile aspects and it is indeed crucial to establish such models on well-supported psychological theoretical frameworks. For this reason, the present work discusses the application case of the theory of planned behavior (TPB; Ajzen, 1991) in the context of agent-based modeling: It is argued that this framework might be helpful more than others to develop a valid representation of human behavior in computer simulations. Accordingly, the current contribution considers issues related with the application of the model proposed by the TPB inside computer simulations and suggests potential solutions with the hope to contribute to shorten the distance between the fields of psychology and computer science.

Simulating Flying Insects Using Dynamics and Data-Driven Noise Modeling to Generate Diverse Collective Behaviors

PubMed Central

Ren, Jiaping; Wang, Xinjie; Manocha, Dinesh

2016-01-01

We present a biologically plausible dynamics model to simulate swarms of flying insects. Our formulation, which is based on biological conclusions and experimental observations, is designed to simulate large insect swarms of varying densities. We use a force-based model that captures different interactions between the insects and the environment and computes collision-free trajectories for each individual insect. Furthermore, we model the noise as a constructive force at the collective level and present a technique to generate noise-induced insect movements in a large swarm that are similar to those observed in real-world trajectories. We use a data-driven formulation that is based on pre-recorded insect trajectories. We also present a novel evaluation metric and a statistical validation approach that takes into account various characteristics of insect motions. In practice, the combination of Curl noise function with our dynamics model is used to generate realistic swarm simulations and emergent behaviors. We highlight its performance for simulating large flying swarms of midges, fruit fly, locusts and moths and demonstrate many collective behaviors, including aggregation, migration, phase transition, and escape responses. PMID:27187068

[Health promotion. Instrument development for the application of the theory of planned behavior].

PubMed

Lee, Y O

1993-01-01

The purpose of this article is to describe operationalization of the Theory of Planned Behavior (TPB). The quest to understand determinants of health behaviors has intensified as evidence accumulates concerning the impact of personal behavior on health. The majority of theory-based research has used the Health Belief Model(HBM). The HBM components have had limited success in explaining health-related behaviors. There are several advantages of the TPB over the HBM. TPB is an expansion of the Theory of Reasoned Action(TRA) with the addition of the construct, perceived behavioral control. The revised model has been shown to yield greater explanatory power than the original TRA for goal-directed behaviors. The process of TPB instrument development was described, using example form the study of smoking cessation behavior in military smokers. It was followed by a discussion of reliability and validity issues in operationalizing the TPB. The TPB is a useful model for understanding and predicting health-related behaviors when carefully operationalized. The model holds promise in the development of prescriptive nursing approaches.

A path analysis model for explaining unsafe behavior in workplaces: the effect of perceived work pressure.

PubMed

Ghasemi, Fakhradin; Kalatpour, Omid; Moghimbeigi, Abbas; Mohhamadfam, Iraj

2018-06-01

Unsafe behavior is closely related to occupational accidents. Work pressure is one the main factors affecting employees' behavior. The aim of the present study was to provide a path analysis model for explaining how work pressure affects safety behavior. Using a self-administered questionnaire, six variables supposed to affect safety employees' behavior were measured. The path analysis model was constructed based on several hypotheses. The goodness of fit of the model was assessed using both absolute and comparative fit indices. Work pressure was determined not to influence safety behavior directly. However, it negatively influenced other variables. Group attitude and personal attitude toward safety were the main factors mediating the effect of work pressure on safety behavior. Among the variables investigated in the present study, group attitude, personal attitude and work pressure had the strongest effects on safety behavior. Managers should consider that in order to improve employees' safety behavior, work pressure should be reduced to a reasonable level, and concurrently a supportive environment, which ensures a positive group attitude toward safety, should be provided. Replication of the study is recommended.

Head Motion Modeling for Human Behavior Analysis in Dyadic Interaction

PubMed Central

Xiao, Bo; Georgiou, Panayiotis; Baucom, Brian; Narayanan, Shrikanth S.

2015-01-01

This paper presents a computational study of head motion in human interaction, notably of its role in conveying interlocutors’ behavioral characteristics. Head motion is physically complex and carries rich information; current modeling approaches based on visual signals, however, are still limited in their ability to adequately capture these important properties. Guided by the methodology of kinesics, we propose a data driven approach to identify typical head motion patterns. The approach follows the steps of first segmenting motion events, then parametrically representing the motion by linear predictive features, and finally generalizing the motion types using Gaussian mixture models. The proposed approach is experimentally validated using video recordings of communication sessions from real couples involved in a couples therapy study. In particular we use the head motion model to classify binarized expert judgments of the interactants’ specific behavioral characteristics where entrainment in head motion is hypothesized to play a role: Acceptance, Blame, Positive, and Negative behavior. We achieve accuracies in the range of 60% to 70% for the various experimental settings and conditions. In addition, we describe a measure of motion similarity between the interaction partners based on the proposed model. We show that the relative change of head motion similarity during the interaction significantly correlates with the expert judgments of the interactants’ behavioral characteristics. These findings demonstrate the effectiveness of the proposed head motion model, and underscore the promise of analyzing human behavioral characteristics through signal processing methods. PMID:26557047

A Framework for the Measurement of Simulated Behavior Performance

DTIC Science & Technology

2011-03-24

and thesis work and through more than just words. Second, to my committee members, Maj Mendenhall and Dr. Lamont, wise gurus in their own right, who...flag.htm. [4] Random House Dictionary. Random House, Inc, 2011. URL http:// dictionary.reference.com/browse/behavior. [5] Abbott, Robert . “Behavioral...Model-Based Methodologies: An Integrative View”. Simulation Model Validation, Oren, et al., 1984. 66 [45] Sargent, Robert G. “Verification and

Integrating Norm Activation Model and Theory of Planned Behavior to Understand Sustainable Transport Behavior: Evidence from China.

PubMed

Liu, Yuwei; Sheng, Hong; Mundorf, Norbert; Redding, Colleen; Ye, Yinjiao

2017-12-18

With increasing urbanization in China, many cities are facing serious environmental problems due to continuous and substantial increase in automobile transportation. It is becoming imperative to examine effective ways to reduce individual automobile use to facilitate sustainable transportation behavior. Empirical, theory-based research on sustainable transportation in China is limited. In this research, we propose an integrated model based on the norm activation model and the theory of planned behavior by combining normative and rational factors to predict individuals' intention to reduce car use. Data from a survey of 600 car drivers in China's three metropolitan areas was used to test the proposed model and hypotheses. Results showed that three variables, perceived norm of car-transport reduction, attitude towards reduction, and perceived behavior control over car-transport reduction, significantly affected the intention to reduce car-transport. Personal norms mediated the relationship between awareness of consequences of car-transport, ascription of responsibility of car-transport, perceived subjective norm for car-transport reduction, and intention to reduce car-transport. The results of this research not only contribute to theory development in the area of sustainable transportation behavior, but also provide a theoretical frame of reference for relevant policy-makers in urban transport management.

Integrating Norm Activation Model and Theory of Planned Behavior to Understand Sustainable Transport Behavior: Evidence from China

PubMed Central

Liu, Yuwei; Sheng, Hong; Mundorf, Norbert; Redding, Colleen

2017-01-01

With increasing urbanization in China, many cities are facing serious environmental problems due to continuous and substantial increase in automobile transportation. It is becoming imperative to examine effective ways to reduce individual automobile use to facilitate sustainable transportation behavior. Empirical, theory-based research on sustainable transportation in China is limited. In this research, we propose an integrated model based on the norm activation model and the theory of planned behavior by combining normative and rational factors to predict individuals’ intention to reduce car use. Data from a survey of 600 car drivers in China’s three metropolitan areas was used to test the proposed model and hypotheses. Results showed that three variables, perceived norm of car-transport reduction, attitude towards reduction, and perceived behavior control over car-transport reduction, significantly affected the intention to reduce car-transport. Personal norms mediated the relationship between awareness of consequences of car-transport, ascription of responsibility of car-transport, perceived subjective norm for car-transport reduction, and intention to reduce car-transport. The results of this research not only contribute to theory development in the area of sustainable transportation behavior, but also provide a theoretical frame of reference for relevant policy-makers in urban transport management. PMID:29258245

Safety climate and the theory of planned behavior: towards the prediction of unsafe behavior.

PubMed

Fogarty, Gerard J; Shaw, Andrew

2010-09-01

The present study is concerned with the human factors that contribute to violations in aviation maintenance. Much of our previous research in this area has been based on safety climate surveys and the analysis of relations among core dimensions of climate. In this study, we tap into mainstream psychological theory to help clarify the mechanisms underlying the links between climate and behavior. Specifically, we demonstrate the usefulness of Ajzen's (1991, 2001) Theory of Planned Behavior (TPB) to understanding violation behaviors in aircraft maintenance. A questionnaire was administered to 307 aircraft maintenance workers. Constructs measured by the survey included perceptions of management attitudes to safety, own attitudes to violations, intention to violate, group norms, workplace pressures, and violations. A model based on the TPB illustrated hypothetical connections among these variables. Path analyses using AMOS suggested some theoretically justifiable modifications to the model. Fit statistics of the revised model were excellent with intentions, group norms, and personal attitudes combining to explain 50% of the variance in self-reported violations. The model highlighted the importance of management attitudes and group norms as direct and indirect predictors of violation behavior. We conclude that the TPB is a useful tool for understanding the psychological background to the procedural violations so often associated with incidents and accidents. 2009 Elsevier Ltd. All rights reserved.

Ceramic matrix composite behavior -- Computational simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chamis, C.C.; Murthy, P.L.N.; Mital, S.K.

Development of analytical modeling and computational capabilities for the prediction of high temperature ceramic matrix composite behavior has been an ongoing research activity at NASA-Lewis Research Center. These research activities have resulted in the development of micromechanics based methodologies to evaluate different aspects of ceramic matrix composite behavior. The basis of the approach is micromechanics together with a unique fiber substructuring concept. In this new concept the conventional unit cell (the smallest representative volume element of the composite) of micromechanics approach has been modified by substructuring the unit cell into several slices and developing the micromechanics based equations at themore » slice level. Main advantage of this technique is that it can provide a much greater detail in the response of composite behavior as compared to a conventional micromechanics based analysis and still maintains a very high computational efficiency. This methodology has recently been extended to model plain weave ceramic composites. The objective of the present paper is to describe the important features of the modeling and simulation and illustrate with select examples of laminated as well as woven composites.« less

A Fracture Mechanics Approach to Thermal Shock Investigation in Alumina-Based Refractory

NASA Astrophysics Data System (ADS)

Volkov-Husović, T.; Heinemann, R. Jančić; Mitraković, D.

2008-02-01

The thermal shock behavior of large grain size, alumina-based refractories was investigated experimentally using a standard water quench test. A mathematical model was employed to simulate the thermal stability behavior. Behavior of the samples under repeated thermal shock was monitored using ultrasonic measurements of dynamic Young's modulus. Image analysis was used to observe the extent of surface degradation. Analysis of the obtained results for the behavior of large grain size samples under conditions of rapid temperature changes is given.

Validation of Individual-Based Markov-Like Stochastic Process Model of Insect Behavior and a “Virtual Farm” Concept for Enhancement of Site-Specific IPM

PubMed Central

Lux, Slawomir A.; Wnuk, Andrzej; Vogt, Heidrun; Belien, Tim; Spornberger, Andreas; Studnicki, Marcin

2016-01-01

The paper reports application of a Markov-like stochastic process agent-based model and a “virtual farm” concept for enhancement of site-specific Integrated Pest Management. Conceptually, the model represents a “bottom-up ethological” approach and emulates behavior of the “primary IPM actors”—large cohorts of individual insects—within seasonally changing mosaics of spatiotemporally complex faming landscape, under the challenge of the local IPM actions. Algorithms of the proprietary PESTonFARM model were adjusted to reflect behavior and ecology of R. cerasi. Model parametrization was based on compiled published information about R. cerasi and the results of auxiliary on-farm experiments. The experiments were conducted on sweet cherry farms located in Austria, Germany, and Belgium. For each farm, a customized model-module was prepared, reflecting its spatiotemporal features. Historical data about pest monitoring, IPM treatments and fruit infestation were used to specify the model assumptions and calibrate it further. Finally, for each of the farms, virtual IPM experiments were simulated and the model-generated results were compared with the results of the real experiments conducted on the same farms. Implications of the findings for broader applicability of the model and the “virtual farm” approach—were discussed. PMID:27602000

Validation of Individual-Based Markov-Like Stochastic Process Model of Insect Behavior and a "Virtual Farm" Concept for Enhancement of Site-Specific IPM.

PubMed

Lux, Slawomir A; Wnuk, Andrzej; Vogt, Heidrun; Belien, Tim; Spornberger, Andreas; Studnicki, Marcin

2016-01-01

The paper reports application of a Markov-like stochastic process agent-based model and a "virtual farm" concept for enhancement of site-specific Integrated Pest Management. Conceptually, the model represents a "bottom-up ethological" approach and emulates behavior of the "primary IPM actors"-large cohorts of individual insects-within seasonally changing mosaics of spatiotemporally complex faming landscape, under the challenge of the local IPM actions. Algorithms of the proprietary PESTonFARM model were adjusted to reflect behavior and ecology of R. cerasi. Model parametrization was based on compiled published information about R. cerasi and the results of auxiliary on-farm experiments. The experiments were conducted on sweet cherry farms located in Austria, Germany, and Belgium. For each farm, a customized model-module was prepared, reflecting its spatiotemporal features. Historical data about pest monitoring, IPM treatments and fruit infestation were used to specify the model assumptions and calibrate it further. Finally, for each of the farms, virtual IPM experiments were simulated and the model-generated results were compared with the results of the real experiments conducted on the same farms. Implications of the findings for broader applicability of the model and the "virtual farm" approach-were discussed.

An Agent-Based Model for Analyzing Control Policies and the Dynamic Service-Time Performance of a Capacity-Constrained Air Traffic Management Facility

NASA Technical Reports Server (NTRS)

Conway, Sheila R.

2006-01-01

Simple agent-based models may be useful for investigating air traffic control strategies as a precursory screening for more costly, higher fidelity simulation. Of concern is the ability of the models to capture the essence of the system and provide insight into system behavior in a timely manner and without breaking the bank. The method is put to the test with the development of a model to address situations where capacity is overburdened and potential for propagation of the resultant delay though later flights is possible via flight dependencies. The resultant model includes primitive representations of principal air traffic system attributes, namely system capacity, demand, airline schedules and strategy, and aircraft capability. It affords a venue to explore their interdependence in a time-dependent, dynamic system simulation. The scope of the research question and the carefully-chosen modeling fidelity did allow for the development of an agent-based model in short order. The model predicted non-linear behavior given certain initial conditions and system control strategies. Additionally, a combination of the model and dimensionless techniques borrowed from fluid systems was demonstrated that can predict the system s dynamic behavior across a wide range of parametric settings.

How do illness-anxious individuals process health-threatening information? A systematic review of evidence for the cognitive-behavioral model.

PubMed

Leonidou, Chrysanthi; Panayiotou, Georgia

2018-08-01

According to the cognitive-behavioral model, illness anxiety is developed and maintained through biased processing of health-threatening information and maladaptive responses to such information. This study is a systematic review of research that attempted to validate central tenets of the cognitive-behavioral model regarding etiological and maintenance mechanisms in illness anxiety. Sixty-two studies, including correlational and experimental designs, were identified through a systematic search of databases and were evaluated for their quality. Outcomes were synthesized following a qualitative thematic approach under categories of theoretically driven mechanisms derived from the cognitive-behavioral model: attention, memory and interpretation biases, perceived awareness and inaccuracy in perception of somatic sensations, negativity bias, emotion dysregulation, and behavioral avoidance. Findings partly support the cognitive-behavioral model, but several of its hypothetical mechanisms only receive weak support due to the scarcity of relevant studies. Directions for future research are suggested based on identified gaps in the existing literature. Copyright © 2018 Elsevier Inc. All rights reserved.

Recreational benefits of urban forests: explaining visitors' willingness to pay in the context of the theory of planned behavior.

PubMed

Bernath, Katrin; Roschewitz, Anna

2008-11-01

The extension of contingent valuation models with an attitude-behavior based framework has been proposed in order to improve the descriptive and predictive ability of the models. This study examines the potential of the theory of planned behavior to explain willingness to pay (WTP) in a contingent valuation survey of the recreational benefits of the Zurich city forests. Two aspects of WTP responses, protest votes and bid levels, were analyzed separately. In both steps, models with and without the psychological predictors proposed by the theory of planned behavior were compared. Whereas the inclusion of the psychological predictors significantly improved explanations of protest votes, their ability to improve the performance of the model explaining bid levels was limited. The results indicate that the interpretation of bid levels as behavioral intention may not be appropriate and that the potential of the theory of planned behavior to improve contingent valuation models depends on which aspect of WTP responses is examined.

Simulating human behavior for national security human interactions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernard, Michael Lewis; Hart, Dereck H.; Verzi, Stephen J.

2007-01-01

This 3-year research and development effort focused on what we believe is a significant technical gap in existing modeling and simulation capabilities: the representation of plausible human cognition and behaviors within a dynamic, simulated environment. Specifically, the intent of the ''Simulating Human Behavior for National Security Human Interactions'' project was to demonstrate initial simulated human modeling capability that realistically represents intra- and inter-group interaction behaviors between simulated humans and human-controlled avatars as they respond to their environment. Significant process was made towards simulating human behaviors through the development of a framework that produces realistic characteristics and movement. The simulated humansmore » were created from models designed to be psychologically plausible by being based on robust psychological research and theory. Progress was also made towards enhancing Sandia National Laboratories existing cognitive models to support culturally plausible behaviors that are important in representing group interactions. These models were implemented in the modular, interoperable, and commercially supported Umbra{reg_sign} simulation framework.« less

Empirical Testing of a Theoretical Extension of the Technology Acceptance Model: An Exploratory Study of Educational Wikis

ERIC Educational Resources Information Center

Liu, Xun

2010-01-01

This study extended the technology acceptance model and empirically tested the new model with wikis, a new type of educational technology. Based on social cognitive theory and the theory of planned behavior, three new variables, wiki self-efficacy, online posting anxiety, and perceived behavioral control, were added to the original technology…

BehavePlus fire modeling system, version 5.0: Design and Features

Treesearch

Faith Ann Heinsch; Patricia L. Andrews

2010-01-01

The BehavePlus fire modeling system is a computer program that is based on mathematical models that describe wildland fire behavior and effects and the fire environment. It is a flexible system that produces tables, graphs, and simple diagrams. It can be used for a host of fire management applications, including projecting the behavior of an ongoing fire, planning...

Developing a Parent-Professional Team Leadership Model in Group Work: Work with Families with Children Experiencing Behavioral and Emotional Problems

ERIC Educational Resources Information Center

Ruffolo, Mary C.; Kuhn, Mary T.; Evans, Mary E.

2006-01-01

Building on the respective strengths of parent-led and professional-led groups, a parent-professional team leadership model for group interventions was developed and evaluated for families of youths with emotional and behavioral problems. The model was developed based on feedback from 26 parents in focus group sessions and recommendations from…

[Behavior therapy technics in the treatment of endogenous eczema with special reference to compulsive scratching].

PubMed

Böddeker, K W; Böddeker, M

1976-01-01

An exact observation and description of scratching behavior leads to a behavioral model for the obsessional scratching in patients with atopic dermatitis. The patient who cannot handle negative emotions because of a deficit in social behavior strategies suffers from diffuse tension. He can reduce the tension for the moment by scratching. Thus itching is being reinforced. The feeling of misbehavior occurs with delay and then again can serve as a stimulus for more tension.--Basing on this model behavior therapeutical techniques for breaking up this vicious circle are discussed.

Effectiveness of a worksite mindfulness-based multi-component intervention on lifestyle behaviors

PubMed Central

2014-01-01

Introduction Overweight and obesity are associated with an increased risk of morbidity. Mindfulness training could be an effective strategy to optimize lifestyle behaviors related to body weight gain. The aim of this study was to evaluate the effectiveness of a worksite mindfulness-based multi-component intervention on vigorous physical activity in leisure time, sedentary behavior at work, fruit intake and determinants of these behaviors. The control group received information on existing lifestyle behavior- related facilities that were already available at the worksite. Methods In a randomized controlled trial design (n = 257), 129 workers received a mindfulness training, followed by e-coaching, lunch walking routes and fruit. Outcome measures were assessed at baseline and after 6 and 12 months using questionnaires. Physical activity was also measured using accelerometers. Effects were analyzed using linear mixed effect models according to the intention-to-treat principle. Linear regression models (complete case analyses) were used as sensitivity analyses. Results There were no significant differences in lifestyle behaviors and determinants of these behaviors between the intervention and control group after 6 or 12 months. The sensitivity analyses showed effect modification for gender in sedentary behavior at work at 6-month follow-up, although the main analyses did not. Conclusions This study did not show an effect of a worksite mindfulness-based multi-component intervention on lifestyle behaviors and behavioral determinants after 6 and 12 months. The effectiveness of a worksite mindfulness-based multi-component intervention as a health promotion intervention for all workers could not be established. PMID:24467802

Fatigue Assessment of Nickel-Titanium Peripheral Stents: Comparison of Multi-Axial Fatigue Models

NASA Astrophysics Data System (ADS)

Allegretti, Dario; Berti, Francesca; Migliavacca, Francesco; Pennati, Giancarlo; Petrini, Lorenza

2018-03-01

Peripheral Nickel-Titanium (NiTi) stents exploit super-elasticity to treat femoropopliteal artery atherosclerosis. The stent is subject to cyclic loads, which may lead to fatigue fracture and treatment failure. The complexity of the loading conditions and device geometry, coupled with the nonlinear material behavior, may induce multi-axial and non-proportional deformation. Finite element analysis can assess the fatigue risk, by comparing the device state of stress with the material fatigue limit. The most suitable fatigue model is not fully understood for NiTi devices, due to its complex thermo-mechanical behavior. This paper assesses the fatigue behavior of NiTi stents through computational models and experimental validation. Four different strain-based models are considered: the von Mises criterion and three critical plane models (Fatemi-Socie, Brown-Miller, and Smith-Watson-Topper models). Two stents, made of the same material with different cell geometries are manufactured, and their fatigue behavior is experimentally characterized. The comparison between experimental and numerical results highlights an overestimation of the failure risk by the von Mises criterion. On the contrary, the selected critical plane models, even if based on different damage mechanisms, give a better fatigue life estimation. Further investigations on crack propagation mechanisms of NiTi stents are required to properly select the most reliable fatigue model.

Fatigue Assessment of Nickel-Titanium Peripheral Stents: Comparison of Multi-Axial Fatigue Models

NASA Astrophysics Data System (ADS)

Allegretti, Dario; Berti, Francesca; Migliavacca, Francesco; Pennati, Giancarlo; Petrini, Lorenza

2018-02-01

Peripheral Nickel-Titanium (NiTi) stents exploit super-elasticity to treat femoropopliteal artery atherosclerosis. The stent is subject to cyclic loads, which may lead to fatigue fracture and treatment failure. The complexity of the loading conditions and device geometry, coupled with the nonlinear material behavior, may induce multi-axial and non-proportional deformation. Finite element analysis can assess the fatigue risk, by comparing the device state of stress with the material fatigue limit. The most suitable fatigue model is not fully understood for NiTi devices, due to its complex thermo-mechanical behavior. This paper assesses the fatigue behavior of NiTi stents through computational models and experimental validation. Four different strain-based models are considered: the von Mises criterion and three critical plane models (Fatemi-Socie, Brown-Miller, and Smith-Watson-Topper models). Two stents, made of the same material with different cell geometries are manufactured, and their fatigue behavior is experimentally characterized. The comparison between experimental and numerical results highlights an overestimation of the failure risk by the von Mises criterion. On the contrary, the selected critical plane models, even if based on different damage mechanisms, give a better fatigue life estimation. Further investigations on crack propagation mechanisms of NiTi stents are required to properly select the most reliable fatigue model.

The Behavior of Preschool Handicapped Children and Their Interactions with Model Children: An Update.

ERIC Educational Resources Information Center

Montemurro, Theodore J.

The behavior patterns of 6 handicapped children and 14 nonhandicapped children were recorded during participation in a model developmental-interactive based curriculum for preschool children. Interactions were recorded using the Coping Analysis Schedule for Educational Settings. Among findings were the following: the consistently high occurrence…

Human Parental Care: Universal Goals, Cultural Strategies, Individual Behavior.

ERIC Educational Resources Information Center

LeVine, Robert A.

1988-01-01

A model of parental behavior as adaptation in agrarian and urban-industrial societies is proposed and examined in light of the evidence in this volume. The model is based on the concept of parental investment strategies for allocating time, attention, and domestic resources to raising children. (RH)

A computational cognitive model of self-efficacy and daily adherence in mHealth.

PubMed

Pirolli, Peter

2016-12-01

Mobile health (mHealth) applications provide an excellent opportunity for collecting rich, fine-grained data necessary for understanding and predicting day-to-day health behavior change dynamics. A computational predictive model (ACT-R-DStress) is presented and fit to individual daily adherence in 28-day mHealth exercise programs. The ACT-R-DStress model refines the psychological construct of self-efficacy. To explain and predict the dynamics of self-efficacy and predict individual performance of targeted behaviors, the self-efficacy construct is implemented as a theory-based neurocognitive simulation of the interaction of behavioral goals, memories of past experiences, and behavioral performance.

Implications of Middle School Behavior Problems for High School Graduation and Employment Outcomes of Young Adults: Estimation of a Recursive Model.

PubMed

Karakus, Mustafa C; Salkever, David S; Slade, Eric P; Ialongo, Nicholas; Stuart, Elizabeth

2012-01-01

The potentially serious adverse impacts of behavior problems during adolescence on employment outcomes in adulthood provide a key economic rationale for early intervention programs. However, the extent to which lower educational attainment accounts for the total impact of adolescent behavior problems on later employment remains unclear As an initial step in exploring this issue, we specify and estimate a recursive bivariate probit model that 1) relates middle school behavior problems to high school graduation and 2) models later employment in young adulthood as a function of these behavior problems and of high school graduation. Our model thus allows for both a direct effect of behavior problems on later employment as well as an indirect effect that operates via graduation from high school. Our empirical results, based on analysis of data from the NELS, suggest that the direct effects of externalizing behavior problems on later employment are not significant but that these problems have important indirect effects operating through high school graduation.

Experimental Study and Modelling of Poly (Methyl Methacrylate) and Polycarbonate Compressive Behavior from Low to High Strain Rates

NASA Astrophysics Data System (ADS)

El-Qoubaa, Z.; Colard, L.; Matadi Boumbimba, R.; Rusinek, A.

2018-06-01

This paper concerns an experimental investigation of Polycarbonate and Poly (methyl methacrylate) compressive behavior from low to high strain rates. Experiments were conducted from 0.001/s to ≈ 5000/s for PC and from 0.001/s to ≈ 2000/s for PMMA. The true strain-stress behavior is established and analyzed at various stain rates. Both PC and PMMA mechanical behavior appears as known, to be strain rate and temperature dependent. The DSGZ model is selected for modelling the strain-stress curves while the yield stress is reproduced using the cooperative model and a modified Eyring equation based on Eyring first process theory. All the three models predictions are in agreement with experiments performed on PC and PMMA.

Experimental Study and Modelling of Poly (Methyl Methacrylate) and Polycarbonate Compressive Behavior from Low to High Strain Rates

NASA Astrophysics Data System (ADS)

El-Qoubaa, Z.; Colard, L.; Matadi Boumbimba, R.; Rusinek, A.

2018-03-01

This paper concerns an experimental investigation of Polycarbonate and Poly (methyl methacrylate) compressive behavior from low to high strain rates. Experiments were conducted from 0.001/s to ≈ 5000/s for PC and from 0.001/s to ≈ 2000/s for PMMA. The true strain-stress behavior is established and analyzed at various stain rates. Both PC and PMMA mechanical behavior appears as known, to be strain rate and temperature dependent. The DSGZ model is selected for modelling the strain-stress curves while the yield stress is reproduced using the cooperative model and a modified Eyring equation based on Eyring first process theory. All the three models predictions are in agreement with experiments performed on PC and PMMA.

A general computation model based on inverse analysis principle used for rheological analysis of W/O rapeseed and soybean oil emulsions

NASA Astrophysics Data System (ADS)

Vintila, Iuliana; Gavrus, Adinel

2017-10-01

The present research paper proposes the validation of a rigorous computation model used as a numerical tool to identify rheological behavior of complex emulsions W/O. Considering a three-dimensional description of a general viscoplastic flow it is detailed the thermo-mechanical equations used to identify fluid or soft material's rheological laws starting from global experimental measurements. Analyses are conducted for complex emulsions W/O having generally a Bingham behavior using the shear stress - strain rate dependency based on a power law and using an improved analytical model. Experimental results are investigated in case of rheological behavior for crude and refined rapeseed/soybean oils and four types of corresponding W/O emulsions using different physical-chemical composition. The rheological behavior model was correlated with the thermo-mechanical analysis of a plane-plane rheometer, oil content, chemical composition, particle size and emulsifier's concentration. The parameters of rheological laws describing the industrial oils and the W/O concentrated emulsions behavior were computed from estimated shear stresses using a non-linear regression technique and from experimental torques using the inverse analysis tool designed by A. Gavrus (1992-2000).

Merging Empiricism and Humanism: Role of Social Validity in the School-Wide Positive Behavior Support Model

ERIC Educational Resources Information Center

Marchant, Michelle; Heath, Melissa Allen; Miramontes, Nancy Y.

2013-01-01

Criteria for evaluating behavior support programs are changing. Consumer-based educational and behavioral programs, such as School-Wide Positive Behavior Support (SWPBS), are particularly influenced by consumer opinion. Unfortunately, the need for and use of social validity measures have not received adequate attention in the empirical literature…

A phenomenological memristor model for short-term/long-term memory

NASA Astrophysics Data System (ADS)

Chen, Ling; Li, Chuandong; Huang, Tingwen; Ahmad, Hafiz Gulfam; Chen, Yiran

2014-08-01

Memristor is considered to be a natural electrical synapse because of its distinct memory property and nanoscale. In recent years, more and more similar behaviors are observed between memristors and biological synapse, e.g., short-term memory (STM) and long-term memory (LTM). The traditional mathematical models are unable to capture the new emerging behaviors. In this article, an updated phenomenological model based on the model of the Hewlett-Packard (HP) Labs has been proposed to capture such new behaviors. The new dynamical memristor model with an improved ion diffusion term can emulate the synapse behavior with forgetting effect, and exhibit the transformation between the STM and the LTM. Further, this model can be used in building new type of neural networks with forgetting ability like biological systems, and it is verified by our experiment with Hopfield neural network.

Nonlinear complexity behaviors of agent-based 3D Potts financial dynamics with random environments

NASA Astrophysics Data System (ADS)

Xing, Yani; Wang, Jun

2018-02-01

A new microscopic 3D Potts interaction financial price model is established in this work, to investigate the nonlinear complexity behaviors of stock markets. 3D Potts model, which extends the 2D Potts model to three-dimensional, is a cubic lattice model to explain the interaction behavior among the agents. In order to explore the complexity of real financial markets and the 3D Potts financial model, a new random coarse-grained Lempel-Ziv complexity is proposed to certain series, such as the price returns, the price volatilities, and the random time d-returns. Then the composite multiscale entropy (CMSE) method is applied to the intrinsic mode functions (IMFs) and the corresponding shuffled data to study the complexity behaviors. The empirical results indicate that the 3D financial model is feasible.

Applied behavior analysis: New directions from the laboratory

PubMed Central

Epling, W. Frank; Pierce, W. David

1983-01-01

Applied behavior analysis began when laboratory based principles were extended to humans inorder to change socially significant behavior. Recent laboratory findings may have applied relevance; however, the majority of basic researchers have not clearly communicated the practical implications of their work. The present paper samples some of the new findings and attempts to demonstrate their applied importance. Schedule-induced behavior which occurs as a by-product of contingencies of reinforcement is discussed. Possible difficulties in treatment and management of induced behaviors are considered. Next, the correlation-based law of effect and the implications of relative reinforcement are explored in terms of applied examples. Relative rate of reinforcement is then extended to the literature dealing with concurrent operants. Concurrent operant models may describe human behavior of applied importance, and several techniques for modification of problem behavior are suggested. As a final concern, the paper discusses several new paradigms. While the practical importance of these models is not clear at the moment, it may be that new practical advantages will soon arise. Thus, it is argued that basic research continues to be of theoretical and practical importance to applied behavior analysis. PMID:22478574

Planning for the Future: A Model for Using the Principles of Transition to Guide the Development of Behavior Intervention Plans

ERIC Educational Resources Information Center

Mueller, Tracy Gershwin; Bassett, Diane S.; Brewer, Robin D.

2012-01-01

The Individuals with Disabilities Education Act (IDEA) mandates the implementation of a behavior intervention plan based on a functional behavioral assessment when a student's behavior necessitates disciplinary actions. However, IDEA does not provide any clear guidelines as to what the plans should contain nor how they can address behaviors that…

Friendship Network and Dental Brushing Behavior among Middle School Students: An Agent Based Modeling Approach.

PubMed

Sadeghipour, Maryam; Khoshnevisan, Mohammad Hossein; Jafari, Afshin; Shariatpanahi, Seyed Peyman

2017-01-01

By using a standard questionnaire, the level of dental brushing frequency was assessed among 201 adolescent female middle school students in Tehran. The initial assessment was repeated after 5 months, in order to observe the dynamics in dental health behavior level. Logistic Regression model was used to evaluate the correlation among individuals' dental health behavior in their social network. A significant correlation on dental brushing habits was detected among groups of friends. This correlation was further spread over the network within the 5 months period. Moreover, it was identified that the average brushing level was improved within the 5 months period. Given that there was a significant correlation between social network's nodes' in-degree value, and brushing level, it was suggested that the observed improvement was partially due to more popularity of individuals with better tooth brushing habit. Agent Based Modeling (ABM) was used to demonstrate the dynamics of dental brushing frequency within a sample of friendship network. Two models with static and dynamic assumptions for the network structure were proposed. The model with dynamic network structure successfully described the dynamics of dental health behavior. Based on this model, on average, every 43 weeks a student changes her brushing habit due to learning from her friends. Finally, three training scenarios were tested by these models in order to evaluate their effectiveness. When training more popular students, considerable improvement in total students' brushing frequency was demonstrated by simulation results.

Relapse prevention for addictive behaviors

PubMed Central

2011-01-01

The Relapse Prevention (RP) model has been a mainstay of addictions theory and treatment since its introduction three decades ago. This paper provides an overview and update of RP for addictive behaviors with a focus on developments over the last decade (2000-2010). Major treatment outcome studies and meta-analyses are summarized, as are selected empirical findings relevant to the tenets of the RP model. Notable advances in RP in the last decade include the introduction of a reformulated cognitive-behavioral model of relapse, the application of advanced statistical methods to model relapse in large randomized trials, and the development of mindfulness-based relapse prevention. We also review the emergent literature on genetic correlates of relapse following pharmacological and behavioral treatments. The continued influence of RP is evidenced by its integration in most cognitive-behavioral substance use interventions. However, the tendency to subsume RP within other treatment modalities has posed a barrier to systematic evaluation of the RP model. Overall, RP remains an influential cognitive-behavioral framework that can inform both theoretical and clinical approaches to understanding and facilitating behavior change. PMID:21771314

Better and Worse: A Dual-Process Model of the Relationship between Core Self-evaluation and Work-Family Conflict.

PubMed

Yu, Kun

2016-01-01

Based on both resource allocation theory (Becker, 1965; Bergeron, 2007) and role theory (Katz and Kahn, 1978), the current study aims to uncover the relationship between core self-evaluation (CSE) and three dimensions of work interference with family (WIF). A dual-process model was proposed, in which both work stress and career resilience mediate the CSE-WIF relationship. The mediation model was tested with a sample of employees from various organizations ( N = 561). The results first showed that CSE was negatively related to time-based and strain-based WIF and positively related to behavior-based WIF via the mediation of work stress. Moreover, CSE was positively associated with behavior-based and strain-based WIF via the mediation of career resilience, suggesting that CSE may also have its "dark-side."

Better and Worse: A Dual-Process Model of the Relationship between Core Self-evaluation and Work-Family Conflict

PubMed Central

Yu, Kun

2016-01-01

Based on both resource allocation theory (Becker, 1965; Bergeron, 2007) and role theory (Katz and Kahn, 1978), the current study aims to uncover the relationship between core self-evaluation (CSE) and three dimensions of work interference with family (WIF). A dual-process model was proposed, in which both work stress and career resilience mediate the CSE-WIF relationship. The mediation model was tested with a sample of employees from various organizations (N = 561). The results first showed that CSE was negatively related to time-based and strain-based WIF and positively related to behavior-based WIF via the mediation of work stress. Moreover, CSE was positively associated with behavior-based and strain-based WIF via the mediation of career resilience, suggesting that CSE may also have its “dark-side.” PMID:27790177

Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control

PubMed Central

Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We envision that such an interaction is influenced by reward modulated heterosynaptic plasticity (RMHP) rule at the thalamus, guiding the overall goal directed behavior. Using a recurrent neural network actor-critic model of the basal ganglia and a feed-forward correlation-based learning model of the cerebellum, we demonstrate that the RMHP rule can effectively balance the outcomes of the two learning systems. This is tested using simulated environments of increasing complexity with a four-wheeled robot in a foraging task in both static and dynamic configurations. Although modeled with a simplified level of biological abstraction, we clearly demonstrate that such a RMHP induced combinatorial learning mechanism, leads to stabler and faster learning of goal-directed behaviors, in comparison to the individual systems. Thus, in this paper we provide a computational model for adaptive combination of the basal ganglia and cerebellum learning systems by way of neuromodulated plasticity for goal-directed decision making in biological and bio-mimetic organisms. PMID:25389391

Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control.

PubMed

Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We envision that such an interaction is influenced by reward modulated heterosynaptic plasticity (RMHP) rule at the thalamus, guiding the overall goal directed behavior. Using a recurrent neural network actor-critic model of the basal ganglia and a feed-forward correlation-based learning model of the cerebellum, we demonstrate that the RMHP rule can effectively balance the outcomes of the two learning systems. This is tested using simulated environments of increasing complexity with a four-wheeled robot in a foraging task in both static and dynamic configurations. Although modeled with a simplified level of biological abstraction, we clearly demonstrate that such a RMHP induced combinatorial learning mechanism, leads to stabler and faster learning of goal-directed behaviors, in comparison to the individual systems. Thus, in this paper we provide a computational model for adaptive combination of the basal ganglia and cerebellum learning systems by way of neuromodulated plasticity for goal-directed decision making in biological and bio-mimetic organisms.

A physics-based crystallographic modeling framework for describing the thermal creep behavior of Fe-Cr alloys

DOE PAGES

Wen, Wei; Capolungo, Laurent; Patra, Anirban; ...

2017-02-23

In this work, a physics-based thermal creep model is developed based on the understanding of the microstructure in Fe-Cr alloys. This model is associated with a transition state theory based framework that considers the distribution of internal stresses at sub-material point level. The thermally activated dislocation glide and climb mechanisms are coupled in the obstacle-bypass processes for both dislocation and precipitate-type barriers. A kinetic law is proposed to track the dislocation densities evolution in the subgrain interior and in the cell wall. The predicted results show that this model, embedded in the visco-plastic self-consistent (VPSC) framework, captures well the creepmore » behaviors for primary and steady-state stages under various loading conditions. We also discuss the roles of the mechanisms involved.« less

Systematizing Web Search through a Meta-Cognitive, Systems-Based, Information Structuring Model (McSIS)

ERIC Educational Resources Information Center

Abuhamdieh, Ayman H.; Harder, Joseph T.

2015-01-01

This paper proposes a meta-cognitive, systems-based, information structuring model (McSIS) to systematize online information search behavior based on literature review of information-seeking models. The General Systems Theory's (GST) prepositions serve as its framework. Factors influencing information-seekers, such as the individual learning…

Mixture Rasch model for guessing group identification

NASA Astrophysics Data System (ADS)

Siow, Hoo Leong; Mahdi, Rasidah; Siew, Eng Ling

2013-04-01

Several alternative dichotomous Item Response Theory (IRT) models have been introduced to account for guessing effect in multiple-choice assessment. The guessing effect in these models has been considered to be itemrelated. In the most classic case, pseudo-guessing in the three-parameter logistic IRT model is modeled to be the same for all the subjects but may vary across items. This is not realistic because subjects can guess worse or better than the pseudo-guessing. Derivation from the three-parameter logistic IRT model improves the situation by incorporating ability in guessing. However, it does not model non-monotone function. This paper proposes to study guessing from a subject-related aspect which is guessing test-taking behavior. Mixture Rasch model is employed to detect latent groups. A hybrid of mixture Rasch and 3-parameter logistic IRT model is proposed to model the behavior based guessing from the subjects' ways of responding the items. The subjects are assumed to simply choose a response at random. An information criterion is proposed to identify the behavior based guessing group. Results show that the proposed model selection criterion provides a promising method to identify the guessing group modeled by the hybrid model.

Integrating model behavior, optimization, and sensitivity/uncertainty analysis: overview and application of the MOUSE software toolbox

USDA-ARS?s Scientific Manuscript database

This paper provides an overview of the Model Optimization, Uncertainty, and SEnsitivity Analysis (MOUSE) software application, an open-source, Java-based toolbox of visual and numerical analysis components for the evaluation of environmental models. MOUSE is based on the OPTAS model calibration syst...

Interest-Driven Model for Human Dynamics

NASA Astrophysics Data System (ADS)

Shang, Ming-Sheng; Chen, Guan-Xiong; Dai, Shuang-Xing; Wang, Bing-Hong; Zhou, Tao

2010-04-01

Empirical observations indicate that the interevent time distribution of human actions exhibits heavy-tailed features. The queuing model based on task priorities is to some extent successful in explaining the origin of such heavy tails, however, it cannot explain all the temporal statistics of human behavior especially for the daily entertainments. We propose an interest-driven model, which can reproduce the power-law distribution of interevent time. The exponent can be analytically obtained and is in good accordance with the simulations. This model well explains the observed relationship between activities and power-law exponents, as reported recently for web-based behavior and the instant message communications.

Emergence of tissue mechanics from cellular processes: shaping a fly wing

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Etournay, Raphael; Popovic, Marko; Nandi, Amitabha; Brandl, Holger; Salbreux, Guillaume; Eaton, Suzanne; Jülicher, Frank

Nowadays, biologistsare able to image biological tissueswith up to 10,000 cells in vivowhere the behavior of each individual cell can be followed in detail.However, how precisely large-scale tissue deformation and stresses emerge from cellular behavior remains elusive. Here, we study this question in the developing wing of the fruit fly. To this end, we first establish a geometrical framework that exactly decomposes tissue deformation into contributions by different kinds of cellular processes. These processes comprise cell shape changes, cell neighbor exchanges, cell divisions, and cell extrusions. As the key idea, we introduce a tiling of the cellular network into triangles. This approach also reveals that tissue deformation can also be created by correlated cellular motion. Based on quantifications using these concepts, we developed a novel continuum mechanical model for the fly wing. In particular, our model includes active anisotropic stresses and a delay in the response of cell rearrangements to material stresses. A different approach to study the emergence of tissue mechanics from cellular behavior are cell-based models. We characterize the properties of a cell-based model for 3D tissues that is a hybrid between single particle models and the so-called vertex models.

A Performance Prediction Model for a Fault-Tolerant Computer During Recovery and Restoration

NASA Technical Reports Server (NTRS)

Obando, Rodrigo A.; Stoughton, John W.

1995-01-01

The modeling and design of a fault-tolerant multiprocessor system is addressed. Of interest is the behavior of the system during recovery and restoration after a fault has occurred. The multiprocessor systems are based on the Algorithm to Architecture Mapping Model (ATAMM) and the fault considered is the death of a processor. The developed model is useful in the determination of performance bounds of the system during recovery and restoration. The performance bounds include time to recover from the fault, time to restore the system, and determination of any permanent delay in the input to output latency after the system has regained steady state. Implementation of an ATAMM based computer was developed for a four-processor generic VHSIC spaceborne computer (GVSC) as the target system. A simulation of the GVSC was also written on the code used in the ATAMM Multicomputer Operating System (AMOS). The simulation is used to verify the new model for tracking the propagation of the delay through the system and predicting the behavior of the transient state of recovery and restoration. The model is shown to accurately predict the transient behavior of an ATAMM based multicomputer during recovery and restoration.

An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

NASA Astrophysics Data System (ADS)

Haghnevis, Moeed

The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

Linking service quality, customer satisfaction, and behavioral intention.

PubMed

Woodside, A G; Frey, L L; Daly, R T

1989-12-01

Based on the service quality and script theory literature, a framework of relationships among service quality, customer satisfaction, and behavioral intention for service purchases is proposed. Specific models are developed from the general framework and the models are applied and tested for the highly complex and divergent consumer service of overnight hospital care. Service quality, customer satisfaction, and behavioral intention data were collected from recent patients of two hospitals. The findings support the specific models and general framework. Implications for theory, service marketing, and future research are discussed.

Changes in knowledge, attitudes, and behavior as a result of a community-based AIDS prevention program.

PubMed

Miller, T E; Booraem, C; Flowers, J V; Iversen, A E

1990-01-01

The study evaluates the outcome of a California-based AIDS prevention program, "Stop AIDS." Community discussion groups focusing on information, attitudes, and behavior associated with HIV infection and transmission were conducted in one-time, 3 1/2-hour sessions. Participants completed different versions of the AIDS Prevention Test before and after the discussion group. Significant positive shifts in information, attitudes, and behavior were observed as a function of the discussion group participation. Whereas pretest knowledge correlated with pretest behavior and posttest knowledge, only pretest behavior correlated with the crucial variable of posttest intended behavior. When changes from pretest to posttest were analyzed, both information and attitude change correlated to changes in behavior. The intervention and evaluation procedures are proposed as a replicable national model for community-based AIDS prevention programs.

Leadership for evidence-based practice: strategic and functional behaviors for institutionalizing EBP.

PubMed

Stetler, Cheryl B; Ritchie, Judith A; Rycroft-Malone, Jo; Charns, Martin P

2014-08-01

Making evidence-based practice (EBP) a reality throughout an organization is a challenging goal in healthcare services. Leadership has been recognized as a critical element in that process. However, little is known about the exact role and function of various levels of leadership in the successful institutionalization of EBP within an organization. To uncover what leaders at different levels and in different roles actually do, and what actions they take to develop, enhance, and sustain EBP as the norm. Qualitative data from a case study regarding institutionalization of EBP in two contrasting cases (Role Model and Beginner hospitals) were systematically analyzed. Data were obtained from multiple interviews of leaders, both formal and informal, and from staff nurse focus groups. A deductive coding schema, based on concepts of functional leadership, was developed for this in-depth analysis. Participants' descriptions reflected a hierarchical array of strategic, functional, and cross-cutting behaviors. Within these macrolevel "themes," 10 behavioral midlevel themes were identified; for example, Intervening and Role modeling. Each theme is distinctive, yet various themes and their subthemes were interrelated and synergistic. These behaviors and their interrelationships were conceptualized in the framework "Leadership Behaviors Supportive of EBP Institutionalization" (L-EBP). Leaders at multiple levels in the Role Model case, both formal and informal, engaged in most of these behaviors. Supportive leadership behaviors required for organizational institutionalization of EBP reflect a complex set of interactive, multifaceted EBP-focused actions carried out by leaders from the chief nursing officer to staff nurses. A related framework such as L-EBP may provide concrete guidance needed to underpin the often-noted but abstract finding that leaders should "support" EBP. © 2014 The Authors. Worldviews on Evidence-Based Nursing published by Wiley Periodicals, Inc. on behalf of Sigma Theta Tau International.

Modeling the Flow Behavior, Recrystallization, and Crystallographic Texture in Hot-Deformed Fe-30 Wt Pct Ni Austenite

NASA Astrophysics Data System (ADS)

Abbod, M. F.; Sellars, C. M.; Cizek, P.; Linkens, D. A.; Mahfouf, M.

2007-10-01

The present work describes a hybrid modeling approach developed for predicting the flow behavior, recrystallization characteristics, and crystallographic texture evolution in a Fe-30 wt pct Ni austenitic model alloy subjected to hot plane strain compression. A series of compression tests were performed at temperatures between 850 °C and 1050 °C and strain rates between 0.1 and 10 s-1. The evolution of grain structure, crystallographic texture, and dislocation substructure was characterized in detail for a deformation temperature of 950 °C and strain rates of 0.1 and 10 s-1, using electron backscatter diffraction and transmission electron microscopy. The hybrid modeling method utilizes a combination of empirical, physically-based, and neuro-fuzzy models. The flow stress is described as a function of the applied variables of strain rate and temperature using an empirical model. The recrystallization behavior is predicted from the measured microstructural state variables of internal dislocation density, subgrain size, and misorientation between subgrains using a physically-based model. The texture evolution is modeled using artificial neural networks.

Relationships Between Marijuana Dependence and Condom Use Intentions and Behavior Among Justice-Involved Adolescents

PubMed Central

Caldwell Hooper, Ann E.; Thayer, Rachel E.; Magnan, Renee E.; Bryan, Angela D.

2013-01-01

The current study examined the relationships among marijuana dependence, a theoretical model of condom use intentions, and subsequent condom use behavior in justice-involved adolescents. Participants completed baseline measures of prior sexual and substance use behavior. Of the original 720 participants, 649 (90.13 %) completed follow-up measures 6 months later. There were high levels of marijuana use (58.7 % met criteria for dependence) and risky sexual behavior among participants. Baseline model constructs were associated with condom use intentions, and intentions were a significant predictor of condom use at follow-up. Marijuana dependence did not significantly influence the relationships between model constructs, nor did it moderate the relationship of model constructs with subsequent condom use. Findings suggest that the theoretical model of condom use intentions is equally valid regardless of marijuana dependence status, suggesting that interventions to reduce sexual risk behavior among both marijuana dependent and non-dependent justice-involved adolescents can be appropriately based on the model. PMID:23370834

A Critique of Sociocultural Values in PBIS.

PubMed

Wilson, Alyssa N

2015-05-01

Horner and Sugai provide lessons learned from their work with disseminating the Positive Behavioral Interventions and Support (PBIS) model. While PBIS represents an empirical school-wide approach for maladaptive student behaviors, the model appears to have limitations regarding sociocultural values and behavioral data collection practices. The current paper provides an overview of three identified areas for improvement and outlines how administrators using PBIS can incorporate acceptance and mindfulness-based intervention procedures to address the discussed limitations.

Optimizing Cognitive-Behavioral Therapy for Childhood Psychiatric Disorders

ERIC Educational Resources Information Center

Piacentini, John

2008-01-01

Reports that expand the understanding of the treatment of childhood obsessive-compulsive disorder by using exposure-based cognitive-behavioral therapy in the age group of 5 to 8-year-olds are presented. A model for collecting the common core elements of evidence-based psychosocial treatments for childhood disorders is also presented.

An Open Trial of an Acceptance-Based Behavior Therapy for Generalized Anxiety Disorder

ERIC Educational Resources Information Center

Roemer, Lizabeth; Orsillo, Susan M.

2007-01-01

Research suggests that experiential avoidance may play an important role in generalized anxiety disorder (GAD; see Roemer, L., & Orsillo, S.M. (2002). "Expanding our conceptualization of and treatment for generalized anxiety disorder: Integrating mindfulness/acceptance-based approaches with existing cognitive-behavioral models." "Clinical…

Toward a model-based cognitive neuroscience of mind wandering.

PubMed

Hawkins, G E; Mittner, M; Boekel, W; Heathcote, A; Forstmann, B U

2015-12-03

People often "mind wander" during everyday tasks, temporarily losing track of time, place, or current task goals. In laboratory-based tasks, mind wandering is often associated with performance decrements in behavioral variables and changes in neural recordings. Such empirical associations provide descriptive accounts of mind wandering - how it affects ongoing task performance - but fail to provide true explanatory accounts - why it affects task performance. In this perspectives paper, we consider mind wandering as a neural state or process that affects the parameters of quantitative cognitive process models, which in turn affect observed behavioral performance. Our approach thus uses cognitive process models to bridge the explanatory divide between neural and behavioral data. We provide an overview of two general frameworks for developing a model-based cognitive neuroscience of mind wandering. The first approach uses neural data to segment observed performance into a discrete mixture of latent task-related and task-unrelated states, and the second regresses single-trial measures of neural activity onto structured trial-by-trial variation in the parameters of cognitive process models. We discuss the relative merits of the two approaches, and the research questions they can answer, and highlight that both approaches allow neural data to provide additional constraint on the parameters of cognitive models, which will lead to a more precise account of the effect of mind wandering on brain and behavior. We conclude by summarizing prospects for mind wandering as conceived within a model-based cognitive neuroscience framework, highlighting the opportunities for its continued study and the benefits that arise from using well-developed quantitative techniques to study abstract theoretical constructs. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

PubMed

Singh, Karandeep; Ahn, Chang-Won; Paik, Euihyun; Bae, Jang Won; Lee, Chun-Hee

2018-01-01

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing. Furthermore, we use this framework to implement a hybrid model using microsimulation and agent-based modeling techniques to generate an artificial society. We leverage this artificial society to simulate and analyze population dynamics using Korean population census data. The agents in this model derive their decisional behaviors from real data (microsimulation feature) and interact among themselves (agent-based modeling feature) to proceed in the simulation. The behaviors, interactions, and social scenarios of the agents are varied to perform an analysis of population dynamics. We also estimate the future cost of pension policies based on the future population structure of the artificial society. The proposed framework and model demonstrates how ALife techniques can be used by researchers in relation to social issues and policies.

An examination of the factors affecting people's participation in future health examinations based on community health exam interventions.

PubMed

Tu, Shih-Kai; Liao, Hung-En

2014-01-01

Community-based intervention health examinations were implemented at a health care facility to comply with the government's primary health care promotion policy. The theory of planned behavior model was applied to examine the effect that community-based health examinations had on people's health concepts regarding seeking future health examinations. The research participants were individuals who had received a health examination provided at two branches of a hospital in central Taiwan in 2012. The hospital's two branches held a total of 14 free community-based health examination sessions. The hospital provided health examination equipment and staff to perform health examinations during public holidays. We conducted an exploratory questionnaire survey to collect data and implemented cross-sectional research based on anonymous self-ratings to examine the public's intention to receive future community-based or hospital-based health examinations. Including of 807 valid questionnaires, accounting for 89.4% of the total number of questionnaires distributed. The correlation coefficients of the second-order structural model indicate that attitudes positively predict behavioral intentions (γ = .66, p < .05), and subjective norms also positively predict behavioral intentions (γ = .66, p < .01). By contrast, perceived behavioral control has no significant relationship with behavioral intentions (γ = -.71, p > .05). The results of the first-order structural model indicated that the second-order constructs had a high explanatory power for the first-order constructs. People's health concepts regarding health examinations and their desire to continue receiving health examinations must be considered when promoting health examinations in the community. Regarding hospital management and the government's implementation of primary health care, health examination services should address people's medical needs to increase coverage and participation rates and reduce the waste of medical resources.

A Flexible Base Electrode Array for Intraspinal Microstimulation

PubMed Central

Khaled, I.; Elmallah, S.; Cheng, C.; Moussa, W.A.; Mushahwar, V.K.; Elias, A.L.

2013-01-01

In this paper, we report the development of a flexible base array of penetrating electrodes which can be used to interface with the spinal cord. A customizable and feasible fabrication protocol is described. The flexible base arrays were fabricated and implanted into surrogate cords which were elongated by 12%. The resulting strains were optically measured across the cord and compared to those associated with two types of electrodes arrays (one without a base and one with a rigid base connecting the electrodes). The deformation behavior of cords implanted with the flexible base arrays resembled the behavior of cords implanted with individual microwires that were not connected through a base. The results of the strain test were used to validate a 2D finite element model. The validated model was used to assess the stresses induced by the electrodes of the 3 types of arrays on the cord, and to examine how various design parameters (thickness, base modulus, etc.) impact the mechanical behavior of the electrode array. Rigid base arrays induced higher stresses on the cord than the flexible base arrays which in turn imposed higher stresses than the individual microwire implants. The developed flexible base array showed improvement over the rigid base array; however, its stiffness needs to be further reduced to emulate the mechanical behavior of individual microwire arrays without a base. PMID:23744656

A Comparison of Three Approaches to Model Human Behavior

NASA Astrophysics Data System (ADS)

Palmius, Joel; Persson-Slumpi, Thomas

2010-11-01

One way of studying social processes is through the use of simulations. The use of simulations for this purpose has been established as its own field, social simulations, and has been used for studying a variety of phenomena. A simulation of a social setting can serve as an aid for thinking about that social setting, and for experimenting with different parameters and studying the outcomes caused by them. When using the simulation as an aid for thinking and experimenting, the chosen simulation approach will implicitly steer the simulationist towards thinking in a certain fashion in order to fit the model. To study the implications of model choice on the understanding of a setting where human anticipation comes into play, a simulation scenario of a coffee room was constructed using three different simulation approaches: Cellular Automata, Systems Dynamics and Agent-based modeling. The practical implementations of the models were done in three different simulation packages: Stella for Systems Dynamic, CaFun for Cellular automata and SesAM for Agent-based modeling. The models were evaluated both using Randers' criteria for model evaluation, and through introspection where the authors reflected upon how their understanding of the scenario was steered through the model choice. Further the software used for implementing the simulation models was evaluated, and practical considerations for the choice of software package are listed. It is concluded that the models have very different strengths. The Agent-based modeling approach offers the most intuitive support for thinking about and modeling a social setting where the behavior of the individual is in focus. The Systems Dynamics model would be preferable in situations where populations and large groups would be studied as wholes, but where individual behavior is of less concern. The Cellular Automata models would be preferable where processes need to be studied from the basis of a small set of very simple rules. It is further concluded that in most social simulation settings the Agent-based modeling approach would be the probable choice. This since the other models does not offer much in the way of supporting the modeling of the anticipatory behavior of humans acting in an organization.

Artistic creativity and dementia.

PubMed

Miller, Zachary A; Miller, Bruce L

2013-01-01

Artistic ability and creativity are defining characteristics of human behavior. Behavioral neurology, as a specialty, believes that even the most complex behaviors can be modeled and understood as the summation of smaller cognitive functions. Literature from individuals with specific brain lesions has helped to map out these smaller regions of cognitive abilities. More recently, models based on neurodegenerative conditions, especially from the frontotemporal dementias, have allowed for greater nuanced investigations into the various functional anatomies necessary for artistic behavior and possibly the underlying networks that promote creativity. © 2013 Elsevier B.V. All rights reserved.

Development of a Health Information Technology Acceptance Model Using Consumers’ Health Behavior Intention

PubMed Central

2012-01-01

Background For effective health promotion using health information technology (HIT), it is mandatory that health consumers have the behavioral intention to measure, store, and manage their own health data. Understanding health consumers’ intention and behavior is needed to develop and implement effective and efficient strategies. Objective To develop and verify the extended Technology Acceptance Model (TAM) in health care by describing health consumers’ behavioral intention of using HIT. Methods This study used a cross-sectional descriptive correlational design. We extended TAM by adding more antecedents and mediating variables to enhance the model’s explanatory power and to make it more applicable to health consumers’ behavioral intention. Additional antecedents and mediating variables were added to the hypothetical model, based on their theoretical relevance, from the Health Belief Model and theory of planned behavior, along with the TAM. We undertook structural equation analysis to examine the specific nature of the relationship involved in understanding consumers’ use of HIT. Study participants were 728 members recruited from three Internet health portals in Korea. Data were collected by a Web-based survey using a structured self-administered questionnaire. Results The overall fitness indices for the model developed in this study indicated an acceptable fit of the model. All path coefficients were statistically significant. This study showed that perceived threat, perceived usefulness, and perceived ease of use significantly affected health consumers’ attitude and behavioral intention. Health consumers’ health status, health belief and concerns, subjective norm, HIT characteristics, and HIT self-efficacy had a strong indirect impact on attitude and behavioral intention through the mediators of perceived threat, perceived usefulness, and perceived ease of use. Conclusions An extended TAM in the HIT arena was found to be valid to describe health consumers’ behavioral intention. We categorized the concepts in the extended TAM into 3 domains: health zone, information zone, and technology zone. PMID:23026508

Gambling and the Reasoned Action Model: Predicting Past Behavior, Intentions, and Future Behavior.

PubMed

Dahl, Ethan; Tagler, Michael J; Hohman, Zachary P

2018-03-01

Gambling is a serious concern for society because it is highly addictive and is associated with a myriad of negative outcomes. The current study applied the Reasoned Action Model (RAM) to understand and predict gambling intentions and behavior. Although prior studies have taken a reasoned action approach to understand gambling, no prior study has fully applied the RAM or used the RAM to predict future gambling. Across two studies the RAM was used to predict intentions to gamble, past gambling behavior, and future gambling behavior. In study 1 the model significantly predicted intentions and past behavior in both a college student and Amazon Mechanical Turk sample. In study 2 the model predicted future gambling behavior, measured 2 weeks after initial measurement of the RAM constructs. This study stands as the first to show the utility of the RAM in predicting future gambling behavior. Across both studies, attitudes and perceived normative pressure were the strongest predictors of intentions to gamble. These findings provide increased understanding of gambling and inform the development of gambling interventions based on the RAM.

Constitutive Models Based on Compressible Plastic Flows

NASA Technical Reports Server (NTRS)

Rajendran, A. M.

1983-01-01

The need for describing materials under time or cycle dependent loading conditions has been emphasized in recent years by several investigators. In response to the need, various constitutive models describing the nonlinear behavior of materials under creep, fatigue, or other complex loading conditions were developed. The developed models for describing the fully dense (non-porous) materials were mostly based on uncoupled plasticity theory. The improved characterization of materials provides a better understanding of the structual response under complex loading conditions. The pesent studies demonstrate that the rate or time dependency of the response of a porous aggregate can be incorporated into the nonlinear constitutive behavior of a porous solid by appropriately modeling the incompressible matrix behavior. It is also sown that the yield function which wads determined by a continuum mechanics approach must be verified by appropriate experiments on void containing sintered materials in order to obtain meaningful numbers for the constants that appear in the yield function.

Modeling the data management system of Space Station Freedom with DEPEND

NASA Technical Reports Server (NTRS)

Olson, Daniel P.; Iyer, Ravishankar K.; Boyd, Mark A.

1993-01-01

Some of the features and capabilities of the DEPEND simulation-based modeling tool are described. A study of a 1553B local bus subsystem of the Space Station Freedom Data Management System (SSF DMS) is used to illustrate some types of system behavior that can be important to reliability and performance evaluations of this type of spacecraft. A DEPEND model of the subsystem is used to illustrate how these types of system behavior can be modeled, and shows what kinds of engineering and design questions can be answered through the use of these modeling techniques. DEPEND's process-based simulation environment is shown to provide a flexible method for modeling complex interactions between hardware and software elements of a fault-tolerant computing system.

An ecological systems approach to bullying behaviors among middle school students in the United States.

PubMed

Lee, Chang-Hun

2011-05-01

The aim of this study is to identify an ecological prediction model of bullying behaviors. Based on an ecological systems theory, this study identifies significant factors influencing bullying behaviors at different levels of middle and high school. These levels include the microsystem, mesosystem, exosystem, and macrosystem. More specifically, the ecological factors investigated in this multilevel analysis are individual traits, family experiences, parental involvement, school climate, and community characteristics. Using data collected in 2008 from 485 randomly selected students in a school district, this study identifies a best-fitting structural model of bullying behavior. Findings suggest that the ecological model accounted for a high portion of variance in bullying behaviors. All of the ecological systems as well as individual traits were found to be significant influences on bullying behaviors either directly or indirectly.

Predictors of consistent condom use based on the Information-Motivation-Behavioral Skills (IMB) model among female sex workers in Jinan, China

PubMed Central

2011-01-01

Background Female commercial sex workers (FSWs) are at high risk of human immunodeficiency virus (HIV) transmission in China. This study was designed to examine the predictors of condom use with clients during vaginal intercourse among FSWs based on the Information-Motivation-Behavioral Skills (IMB) model and to describe the relationships between IMB model constructs. Methods A cross-sectional study was conducted in Jinan of Shandong Province, from May to October, 2009. Participants (N = 432) were recruited using Respondent-Driven Sampling (RDS). A self-administered questionnaire was used to collect data. Structural equation modeling was used to assess the IMB model. Results A total of 427 (98.8%) participants completed their questionnaires. Condom use was significantly predicted by social referents support, experiences with and attitudes toward condoms, self-efficacy, and health behaviors and condom use skills. Significant indirect predictors of condom use mediated through behavioral skills included HIV knowledge, social referents support, and substance use. Conclusions These results suggest that the IMB model could be used to predict condom use among Chinese FSWs. Further research is warranted to develop preventive interventions on the basis of the IMB model to promote condom use among FSWs in China. PMID:21329512

Nonlinearities in Behavioral Macroeconomics.

PubMed

Gomes, Orlando

2017-07-01

This article undertakes a journey across the literature on behavioral macroeconomics, with attention concentrated on the nonlinearities that the behavioral approach typically suggests or implies. The emphasis is placed on thinking the macro economy as a living organism, composed of many interacting parts, each one having a will of its own, which is in sharp contrast with the mechanism of the orthodox view (well represented by the neoclassical or new Keynesian dynamic stochastic general equilibrium - DSGE - model). The paper advocates that a thorough understanding of individual behavior in collective contexts is the only possible avenue to further explore macroeconomic phenomena and the often observed 'anomalies' that the benchmark DSGE macro framework is unable to explain or justify. After a reflection on the role of behavioral traits as a fundamental component of a new way of thinking the economy, the article proceeds with a debate on some of the most relevant frameworks in the literature that somehow link macro behavior and nonlinearities; covered subjects include macro models with disequilibrium rules, agent-based models that highlight interaction and complexity, evolutionary switching frameworks, and inattention based decision problems. These subjects have, as a fundamental point in common, the use of behavioral elements to transform existing interpretations of the economic reality, making it more evident how irregular fluctuations emerge and unfold on the aggregate.

Generalized Constitutive-Based Theoretical and Empirical Models for Hot Working Behavior of Functionally Graded Steels

NASA Astrophysics Data System (ADS)

Vanini, Seyed Ali Sadough; Abolghasemzadeh, Mohammad; Assadi, Abbas

2013-07-01

Functionally graded steels with graded ferritic and austenitic regions including bainite and martensite intermediate layers produced by electroslag remelting have attracted much attention in recent years. In this article, an empirical model based on the Zener-Hollomon (Z-H) constitutive equation with generalized material constants is presented to investigate the effects of temperature and strain rate on the hot working behavior of functionally graded steels. Next, a theoretical model, generalized by strain compensation, is developed for the flow stress estimation of functionally graded steels under hot compression based on the phase mixture rule and boundary layer characteristics. The model is used for different strains and grading configurations. Specifically, the results for αβγMγ steels from empirical and theoretical models showed excellent agreement with those of experiments of other references within acceptable error.

The medical home and integrated behavioral health: advancing the policy agenda.

PubMed

Ader, Jeremy; Stille, Christopher J; Keller, David; Miller, Benjamin F; Barr, Michael S; Perrin, James M

2015-05-01

There has been a considerable expansion of the patient-centered medical home model of primary care delivery, in an effort to reduce health care costs and to improve patient experience and population health. To attain these goals, it is essential to integrate behavioral health services into the patient-centered medical home, because behavioral health problems often first present in the primary care setting, and they significantly affect physical health. At the 2013 Patient-Centered Medical Home Research Conference, an expert workgroup convened to determine policy recommendations to promote the integration of primary care and behavioral health. In this article we present these recommendations: Build demonstration projects to test existing approaches of integration, develop interdisciplinary training programs to support members of the integrated care team, implement population-based strategies to improve behavioral health, eliminate behavioral health carve-outs and test innovative payment models, and develop population-based measures to evaluate integration. Copyright © 2015 by the American Academy of Pediatrics.

Theory of Planned Behavior in School-Based Adolescent Problem Gambling Prevention: A Conceptual Framework.

PubMed

St-Pierre, Renée A; Temcheff, Caroline E; Derevensky, Jeffrey L; Gupta, Rina

2015-12-01

Given its serious implications for psychological and socio-emotional health, the prevention of problem gambling among adolescents is increasingly acknowledged as an area requiring attention. The theory of planned behavior (TPB) is a well-established model of behavior change that has been studied in the development and evaluation of primary preventive interventions aimed at modifying cognitions and behavior. However, the utility of the TPB has yet to be explored as a framework for the development of adolescent problem gambling prevention initiatives. This paper first examines the existing empirical literature addressing the effectiveness of school-based primary prevention programs for adolescent gambling. Given the limitations of existing programs, we then present a conceptual framework for the integration of the TPB in the development of effective problem gambling preventive interventions. The paper describes the TPB, demonstrates how the framework has been applied to gambling behavior, and reviews the strengths and limitations of the model for the design of primary prevention initiatives targeting adolescent risk and addictive behaviors, including adolescent gambling.

An Improved K-Epsilon Model for Near-Wall Turbulence and Comparison with Direct Numerical Simulation

NASA Technical Reports Server (NTRS)

Shih, T. H.

1990-01-01

An improved k-epsilon model for low Reynolds number turbulence near a wall is presented. The near-wall asymptotic behavior of the eddy viscosity and the pressure transport term in the turbulent kinetic energy equation is analyzed. Based on this analysis, a modified eddy viscosity model, having correct near-wall behavior, is suggested, and a model for the pressure transport term in the k-equation is proposed. In addition, a modeled dissipation rate equation is reformulated. Fully developed channel flows were used for model testing. The calculations using various k-epsilon models are compared with direct numerical simulations. The results show that the present k-epsilon model performs well in predicting the behavior of near-wall turbulence. Significant improvement over previous k-epsilon models is obtained.

Building Models for the Relationship between Attitudes toward Suicide and Suicidal Behavior: Based on Data from General Population Surveys in Sweden, Norway, and Russia

ERIC Educational Resources Information Center

Renberg, Ellinor Salander; Hjelmeland, Heidi; Koposov, Roman

2008-01-01

Our aim was to build a model delineating the relationship between attitudes toward suicide and suicidal behavior and to assess equivalence by applying the model on data from different countries. Representative samples from the general population were approached in Sweden, Norway, and Russia with the Attitudes Toward Suicide (ATTS) questionnaire.…

Improving On-Task Behavior Using a Functional Assessment-Based Intervention in an Inclusive High School Setting

ERIC Educational Resources Information Center

Majeika, Caitlyn E.; Walder, Jessica P.; Hubbard, Jessica P.; Steeb, Kelly M.; Ferris, Geoffrey J.; Oakes, Wendy P.; Lane, Kathleen Lynne

2011-01-01

A comprehensive, integrated, three-tiered model (CI3T) of prevention is a framework for proactively meeting students' academic, behavioral, and social skills. At the tertiary (Tier 3) level of prevention, functional-assessment based interventions (FABIs) may be used to identify, develop, and implement supports based on the function, or purpose, of…

Adolescent activity-based anorexia increases anxiety-like behavior in adulthood.

PubMed

Kinzig, Kimberly P; Hargrave, Sara L

2010-09-01

Activity-based anorexia is a paradigm that induces increased physical activity, reduced food intake, and heightened activity of the hypothalamic-pituitary-adrenal axis in adult rats. To investigate whether experience with activity-based anorexia produced enduring effects on brain and behavior, female adolescent rats experienced activity-based anorexia during adolescence and were tested in adulthood for anxiety-like behavior on an elevated plus maze and in an open field. Analysis of elevated plus maze and open field behavior in adulthood revealed that rats that experienced activity-based anorexia during adolescence, but not rats that were simply food restricted, displayed increased anxiety-like behavior in adulthood. Plasma corticosterone and expression levels of corticotropin-releasing hormone mRNA in the hypothalamic paraventricular nucleus and in the central nucleus of the amygdala were significantly elevated in adult rats that had undergone activity-based anorexia in adolescence in response to the open field exposure, as compared to control rats. These data demonstrate enduring effects of adolescent activity-based anorexia on anxiety-like behavior and neuroendocrine factors critical in stress responsivity in adulthood. Furthermore, we demonstrate that activity-based anorexia during adolescence serves as a model whereby prolonged anxiety is induced, allowing for evaluation of the behavioral and neural correlates of mediating anxiety-like behaviors in adulthood. Copyright 2010 Elsevier Inc. All rights reserved.

Adolescent Activity-Based Anorexia Increases Anxiety-Like Behavior in Adulthood

PubMed Central

Kinzig, Kimberly P.; Hargrave, Sara L.

2010-01-01

Activity-based anorexia is a paradigm that induces increased physical activity, reduced food intake, and heightened activity of the hypothalamic-pituitary-adrenal axis in adult rats. To investigate whether experience with activity-based anorexia produced enduring effects on brain and behavior, female adolescent rats experienced activity-based anorexia during adolescence and were tested in adulthood for anxiety-like behavior on an elevated plus maze and in an open field. Analysis of elevated plus maze and open field behavior in adulthood revealed that rats that experienced activity-based anorexia during adolescence, but not rats that were simply food restricted, displayed increased anxiety-like behavior in adulthood. Plasma corticosterone and expression levels of corticotropin- releasing hormone mRNA in the hypothalamic paraventricular nucleus and in the central nucleus of the amygdala were significantly elevated in adult rats that had undergone activity-based anorexia in adolescence in response to the open field exposure, as compared to control rats. These data demonstrate enduring effects of adolescent activity-based anorexia on anxiety-like behavior and neuroendocrine factors critical in stress responsivity in adulthood. Furthermore, we demonstrate that activity-based anorexia during adolescence serves as a model whereby prolonged anxiety is induced, allowing for evaluation of the behavioral and neural correlates of mediating anxiety-like behaviors in adulthood. PMID:20566408

Behavior generation strategy of artificial behavioral system by self-learning paradigm for autonomous robot tasks

NASA Astrophysics Data System (ADS)

Dağlarli, Evren; Temeltaş, Hakan

2008-04-01

In this study, behavior generation and self-learning paradigms are investigated for the real-time applications of multi-goal mobile robot tasks. The method is capable to generate new behaviors and it combines them in order to achieve multi goal tasks. The proposed method is composed from three layers: Behavior Generating Module, Coordination Level and Emotion -Motivation Level. Last two levels use Hidden Markov models to manage dynamical structure of behaviors. The kinematics and dynamic model of the mobile robot with non-holonomic constraints are considered in the behavior based control architecture. The proposed method is tested on a four-wheel driven and four-wheel steered mobile robot with constraints in simulation environment and results are obtained successfully.

Effects of physical education, extracurricular sports activities, and leisure satisfaction on adolescent aggressive behavior: A latent growth modeling approach.

PubMed

Park, Sanghyun; Chiu, Weisheng; Won, Doyeon

2017-01-01

The present study aimed to investigate the longitudinal influence of physical education classes, extracurricular sports activities, and leisure satisfaction on aggressive behavior among South Korean adolescents. Data were drawn from the Korea Youth Panel Survey. We used latent growth curve modeling to explain the growth trajectory of adolescent aggressive behaviors and a multi-group analysis to investigate gender differences in aggressive behavior. The results indicated that adolescents' aggressive behavior significantly changed with age. There were significant gender-based differences in the level of and changes in aggressive behavior over time. Both extracurricular sports activities and leisure satisfaction had significant influences on the changes in adolescents' aggressive behavior with age, whereas physical education classes did not.

Uses of Agent-Based Modeling for Health Communication: the TELL ME Case Study.

PubMed

Barbrook-Johnson, Peter; Badham, Jennifer; Gilbert, Nigel

2017-08-01

Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals' protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.

Measurement of Child Behavior via Classroom Observations in the Good Behavior Game Professional Development Models Randomized Control Trial

ERIC Educational Resources Information Center

Kurki, Anja; Wang, Wei; Li, Yibing; Poduska, Jeanne

2013-01-01

The Good Behavior Game (GBG) is a classroom-based behavior management strategy aimed at reducing aggressive/disruptive behavior and socializing children into the role of student. GBG, delivered in first and second grades, has been shown to reduce rates of substance abuse and other deleterious outcomes into young adulthood (Brown, C.H. et al 2007,…

The Relational-Behavior Model: A Pilot Assessment Study for At-Risk College Populations

ERIC Educational Resources Information Center

Chandler, Donald S., Jr.; Perkins, Michele D.

2007-01-01

This pilot study examined the relational-behavior model (RBM) as an HIV/AIDS assessment tool for at-risk college populations. Based on this theory, a survey was constructed to assess the six areas associated with HIV/AIDS prevention: personal awareness, knowledge deficiency, relational skills, HIV/STD stigmatization, community awareness, and…

Development of a Medicaid Behavioral Health Case-Mix Model

ERIC Educational Resources Information Center

Robst, John

2009-01-01

Many Medicaid programs have either fully or partially carved out mental health services. The evaluation of carve-out plans requires a case-mix model that accounts for differing health status across Medicaid managed care plans. This article develops a diagnosis-based case-mix adjustment system specific to Medicaid behavioral health care. Several…

The Five-Factor Model of Personality Traits and Organizational Citizenship Behaviors: A Meta-Analysis

ERIC Educational Resources Information Center

Chiaburu, Dan S.; Oh, In-Sue; Berry, Christopher M.; Li, Ning; Gardner, Richard G.

2011-01-01

Using meta-analytic tests based on 87 statistically independent samples, we investigated the relationships between the five-factor model (FFM) of personality traits and organizational citizenship behaviors in both the aggregate and specific forms, including individual-directed, organization-directed, and change-oriented citizenship. We found that…

Testing a Model Linking Environmental Hope and Self-Control with Students' Positive Emotions and Environmental Behavior

ERIC Educational Resources Information Center

Kerret, Dorit; Orkibi, Hod; Ronen, Tammie

2016-01-01

This study examined a moderated mediation model with 254 Israeli junior high school students, hypothesizing that students' environmental hope would simultaneously mediate the relationship between their engagement in school-based environmental activities (green engagement) and their environmental behavior as well as their positivity ratio, but that…

Hero/Heroine Modeling for Puerto Rican Adolescents: A Preventive Mental Health Intervention.

ERIC Educational Resources Information Center

Malgady, Robert G.; And Others

1990-01-01

Developed hero/heroine intervention based on adult Puerto Rican role models to foster ethnic identity, self-concept, and adaptive coping behavior. Screened 90 Puerto Rican eighth and ninth graders for presenting behavior problems in school and randomly assigned them to intervention or control groups. After 19 sessions, intervention significantly…

East Tennessee State University's "Make a Difference" Project: Using a Team-Based Consultative Model To Conduct Functional Behavioral Assessments.

ERIC Educational Resources Information Center

Vaughn, Kelley; Hales, Cindy; Bush, Marta; Fox, James

1998-01-01

Describes implementation of functional behavioral assessment (FBA) through collaboration between a university (East Tennessee State University) and the local school system. Discusses related issues such as factors in team training, team size, FBA adaptations, and replicability of the FBA team model. (Author/DB)

Counseling and the Bystander-Equity Model of Supervisory Helping Behavior: Directions for EAP Research.

ERIC Educational Resources Information Center

Gerstein, Lawrence H.; Bayer, Gregory A.

1991-01-01

Discusses contribution of Bystander-Equity Model of Supervisory Helping Behavior to pursuit of employee assistance program (EAP) research based on traditions of field of counseling. Offers structure for pursuing empirical and applied activities in EAP settings. Encourages counseling researchers and practitioners to respond to challenge of working…

Community Violence Exposure and Aggression among Urban Adolescents: Testing a Cognitive Mediator Model

ERIC Educational Resources Information Center

McMahon, Susan D.; Felix, Erika D.; Halpert, Jane A.; Petropoulos, Lara A. N.

2009-01-01

Past research has shown that exposure to violence leads to aggressive behavior, but few community-based studies have examined theoretical models illustrating the mediating social cognitive processes that explain this relation with youth exposed to high rates of violence. This study examines the impact of community violence on behavior through…

Proposed Modification of a School-Wide Bully Prevention Program to Support All Children

ERIC Educational Resources Information Center

Ostrander, Jason; Melville, Alysse; Bryan, Janelle K.; Letendre, Joan

2018-01-01

Bullying prevention programs in the United States are being implemented in schools from kindergarten through high school to reduce rates of bullying behaviors. The bully prevention in positive behavior support (PBIS) model is an evidence-based, whole school intervention program. The PBIS model trains teachers, school staff, and administrators to…

Human Behavior Based Exploratory Model for Successful Implementation of Lean Enterprise in Industry

ERIC Educational Resources Information Center

Sawhney, Rupy; Chason, Stewart

2005-01-01

Currently available Lean tools such as Lean Assessments, Value Stream Mapping, and Process Flow Charting focus on system requirements and overlook human behavior. A need is felt for a tool that allows one to baseline personnel, determine personnel requirements and align system requirements with personnel requirements. Our exploratory model--The…

Pedestrians' intention to jaywalk: Automatic or planned? A study based on a dual-process model in China.

PubMed

Xu, Yaoshan; Li, Yongjuan; Zhang, Feng

2013-01-01

The present study investigates the determining factors of Chinese pedestrians' intention to violate traffic laws using a dual-process model. This model divides the cognitive processes of intention formation into controlled analytical processes and automatic associative processes. Specifically, the process explained by the augmented theory of planned behavior (TPB) is controlled, whereas the process based on past behavior is automatic. The results of a survey conducted on 323 adult pedestrian respondents showed that the two added TPB variables had different effects on the intention to violate, i.e., personal norms were significantly related to traffic violation intention, whereas descriptive norms were non-significant predictors. Past behavior significantly but uniquely predicted the intention to violate: the results of the relative weight analysis indicated that the largest percentage of variance in pedestrians' intention to violate was explained by past behavior (42%). According to the dual-process model, therefore, pedestrians' intention formation relies more on habit than on cognitive TPB components and social norms. The implications of these findings for the development of intervention programs are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Discriminating bot accounts based solely on temporal features of microblog behavior

NASA Astrophysics Data System (ADS)

Pan, Junshan; Liu, Ying; Liu, Xiang; Hu, Hanping

2016-05-01

As the largest microblog service in China, Sina Weibo has attracted numerous automated applications (known as bots) due to its popularity and open architecture. We classify the active users from Sina Weibo into human, bot-based and hybrid groups based solely on the study of temporal features of their posting behavior. The anomalous burstiness parameter and time-interval entropy value are exploited to characterize automation. We also reveal different behavior patterns among the three types of users regarding their reposting ratio, daily rhythm and active days. Our findings may help Sina Weibo manage a better community and should be considered for dynamic models of microblog behaviors.

Introduction to "The Behavior-Analytic Origins of Constraint-Induced Movement Therapy: An Example of Behavioral Neurorehabilitation"

ERIC Educational Resources Information Center

Schaal, David W.

2012-01-01

This article presents an introduction to "The Behavior-Analytic Origins of Constraint-Induced Movement Therapy: An Example of Behavioral Neurorehabilitation," by Edward Taub and his colleagues (Taub, 2012). Based on extensive experimentation with animal models of peripheral nerve injury, Taub and colleagues have created an approach to overcoming…

Behaviour Recovery: A Whole-School Program for Mainstream Schools.

ERIC Educational Resources Information Center

Rogers, Bill

This book offers guidance on teaching behavior to children with behavior problems, based on the premise that a small percentage of children need one-to-one modeling and rehearsal to enable them to "recover" the behaviors that those in the typical range have established already. The behavior recovery program emphasizes the whole-school nature of…