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Neural Regret-Matching For Distributed Constraint Optimization Problems, Yanchen Deng, Runshen Yu, Xinrun Wang, Bo An Aug 2021

Neural Regret-Matching For Distributed Constraint Optimization Problems, Yanchen Deng, Runshen Yu, Xinrun Wang, Bo An

Research Collection School Of Computing and Information Systems

Distributed constraint optimization problems (DCOPs) are a powerful model for multi-agent coordination and optimization, where information and controls are distributed among multiple agents by nature. Sampling-based algorithms are important incomplete techniques for solving medium-scale DCOPs. However, they use tables to exactly store all the information (e.g., costs, confidence bounds) to facilitate sampling, which limits their scalability. This paper tackles the limitation by incorporating deep neural networks in solving DCOPs for the first time and presents a neural-based sampling scheme built upon regret-matching. In the algorithm, each agent trains a neural network to approximate the regret related to its local problem …

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Information Systems Business Analytics Curriculum: Competencies From National Infocomm Skills Model And Job Listings, Swapna Gottipati, Venky Shankaranan, Kyong Jin Shim Aug 2021

Information Systems Business Analytics Curriculum: Competencies From National Infocomm Skills Model And Job Listings, Swapna Gottipati, Venky Shankaranan, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

To the best of our knowledge, no research has examined how to integrate the national skills model with the industry demand for designing business analytics curricula. To answer this question, we took the initial steps of identifying the job roles and skills required by the nation in “Data” domain. We then collected the skills that are required by business analytics job positions listed by industry. Further, we extracted the top tools, technologies, and programming languages (TTP) demanded by the industry for various categories of technical skills. We then combined the analyses to design the curriculum, courses, and content for various …

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Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau Aug 2021

Learning And Exploiting Shaped Reward Models For Large Scale Multiagent Rl, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Many real world systems involve interaction among large number of agents to achieve a common goal, for example, air traffic control. Several model-free RL algorithms have been proposed for such settings. A key limitation is that the empirical reward signal in model-free case is not very effective in addressing the multiagent credit assignment problem, which determines an agent's contribution to the team's success. This results in lower solution quality and high sample complexity. To address this, we contribute (a) an approach to learn a differentiable reward model for both continuous and discrete action setting by exploiting the collective nature of …

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Vehicle Routing: Review Of Benchmark Datasets, Aldy Gunawan, Graham Kendall, Barry Mccollum, Hsin-Vonn Seow, Lai Soon Lee Aug 2021

Vehicle Routing: Review Of Benchmark Datasets, Aldy Gunawan, Graham Kendall, Barry Mccollum, Hsin-Vonn Seow, Lai Soon Lee

Research Collection School Of Computing and Information Systems

The Vehicle Routing Problem (VRP) was formally presented to the scientific literature in 1959 by Dantzig and Ramser (DOI:10.1287/mnsc.6.1.80). Sixty years on, the problem is still heavily researched, with hundreds of papers having been published addressing this problem and the many variants that now exist. Many datasets have been proposed to enable researchers to compare their algorithms using the same problem instances where either the best known solution is known or, in some cases, the optimal solution is known. In this survey paper, we provide a list of Vehicle Routing Problem datasets, categorized to enable researchers to have easy access …

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Dynamic Lane Traffic Signal Control With Group Attention And Multi-Timescale Reinforcement Learning, Qize Jiang, Jingze Li, Weiwei Sun, Baihua Zheng Aug 2021

Dynamic Lane Traffic Signal Control With Group Attention And Multi-Timescale Reinforcement Learning, Qize Jiang, Jingze Li, Weiwei Sun, Baihua Zheng

Research Collection School Of Computing and Information Systems

Traffic signal control has achieved significant success with the development of reinforcement learning. However, existing works mainly focus on intersections with normal lanes with fixed outgoing directions. It is noticed that some intersections actually implement dynamic lanes, in addition to normal lanes, to adjust the outgoing directions dynamically. Existing methods fail to coordinate the control of traffic signal and that of dynamic lanes effectively. In addition, they lack proper structures and learning algorithms to make full use of traffic flow prediction, which is essential to set the proper directions for dynamic lanes. Motivated by the ineffectiveness of existing approaches when …

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A Deep Ensemble Method For Multi-Agent Reinforcement Learning: A Case Study On Air Traffic Control, Supriyo Ghosh, Sean Laguna, Laura Wynter, Laura Wynter, Hasan Poonawala Aug 2021

A Deep Ensemble Method For Multi-Agent Reinforcement Learning: A Case Study On Air Traffic Control, Supriyo Ghosh, Sean Laguna, Laura Wynter, Laura Wynter, Hasan Poonawala

Research Collection School Of Computing and Information Systems

Reinforcement learning (RL), a promising framework for data-driven decision making in an uncertain environment, has successfully been applied in many real-world operation and control problems. However, the application of RL in a large-scale decentralized multi-agent environment remains a challenging problem due to the partial observability and limited communications between agents. In this paper, we develop a model-based kernel RL approach and a model-free deep RL approach for learning a decentralized, shared policy among homogeneous agents. By leveraging the strengths of both these methods, we further propose a novel deep ensemble multi-agent reinforcement learning (MARL) method that efficiently learns to arbitrate …

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How Do You Visit: Identifying Addicts From Large-Scale Transit Records Via Scenario Deep Embedding, Canghong Jin, Dongkai Chen, Zhiwei Lin, Zemin Liu, Minghui Wu Aug 2021

How Do You Visit: Identifying Addicts From Large-Scale Transit Records Via Scenario Deep Embedding, Canghong Jin, Dongkai Chen, Zhiwei Lin, Zemin Liu, Minghui Wu

Research Collection School Of Computing and Information Systems

Identification of individuals based on transit modes is of great importance in user tracking systems. However, identifying users in real-life studies is not trivial owing to the following challenges: 1) activity data containing both temporal and spatial context are high-order and sparse; 2) traditional two-step classifiers depend on trajectory patterns as input features, which limits accuracy especially in the case of scattered and diverse data; 3) in some cases, there are few positive instances and they are difficult to detect. Therefore, approaches involving statistics-based or trajectory-based features do not work effectively. Deep learning methods also suffer from the problem of …

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An Enhanced Framework To Compute Road User Costs Associated With Construction Zones, Jeremiah Adebiyi Aug 2021

An Enhanced Framework To Compute Road User Costs Associated With Construction Zones, Jeremiah Adebiyi

Electronic Theses and Dissertations

The monetary quantification of inconveniences caused to the road users by ongoing construction activities is known as the Road Users Costs (RUCs). While the importance of RUCs is widely known, some highway agencies lack an appropriate methodology to compute RUCs. Thus, there is a need to develop a framework to compute RUCs that can be adopted quickly by highway agencies. This study reviewed existing literature and conducted a nationwide survey to identify and summarize the current practices of computing RUCs. It developed an enhanced framework and tool to compute RUCs that balances the effort required to calculate RUCs and the …

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An Examination Of Female Officers’ Career Advancement In The U.S. Military, Glenda A. Gill Aug 2021

An Examination Of Female Officers’ Career Advancement In The U.S. Military, Glenda A. Gill

Electronic Theses and Dissertations

There is little research about the gender-related barriers female military officers face when working to advance in the ranks even though there continues to be research about gender bias and discrimination when pursuing leadership and management positions. The purpose of this qualitative phenomenological study was to examine the experiences of veteran female officers who advanced in rank in the U.S. military. Secondarily, the purpose was to: (a) determine if women experienced role congruity barriers, while advancing in rank and (b) determine if women experienced role congruity when they attempted to advance in rank to elite-level leadership positions. In this study, …

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The Use Of Medical Marijuana For The Relief Of Chronic Pain, Jacquelyn M. Paylor Aug 2021

The Use Of Medical Marijuana For The Relief Of Chronic Pain, Jacquelyn M. Paylor

Electronic Theses and Dissertations

Abstract For thousands of years, medical cannabis has been used for relief of chronic pain and personal ailments. It changes users’ mental capacities and perceptions while treating and providing relief from pain and muscle spasms. As a recreational and spiritual substance, this Schedule I drug requires special consideration and certification to administer. Increasing complaints of chronic pain have led doctors to prescribe opioids for pain relief. As prescriptions for opioids have increased, the number of opioid-related mortality and morbidity incidents have also risen. The high rates of opioid-related near deaths and overdoses have led policy makers, clinicians, pharmacists, and providers …

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Design, Analysis And Experimental Evaluation Of 3d Printed Variable Stiffness Structures, Rossana R. Fernandes Aug 2021

Design, Analysis And Experimental Evaluation Of 3d Printed Variable Stiffness Structures, Rossana R. Fernandes

Doctoral Dissertations and Master's Theses

The rapid progress of additive manufacturing (AM) introduces new opportunities but also new challenges for design and optimization to ensure manufacturability, testability and accurate representation/prediction of the models. The present dissertation builds a bridge between design, optimization, AM, testing and simulation of advanced optimized variable-stiffness structures. The first part offers an insight on the mechanical, viscoelastic and failure characteristics of AM continuous fiber composites. This understanding was used in the second part to investigate the feasibility of different topology and fiber-orientation optimization methods and the manufacturability of the resulting models. The study also assesses the effects of the manufacturing constraints …

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Shape Optimization Of A Sandwich Composite Plate With Low-Velocity Impact Loading And Effect Of Finite Difference Sensitivity Analysis, Utsav Shah Aug 2021

Shape Optimization Of A Sandwich Composite Plate With Low-Velocity Impact Loading And Effect Of Finite Difference Sensitivity Analysis, Utsav Shah

Doctoral Dissertations and Master's Theses

The structural design of spacesuits is essential in an advancing future of both Lunar and Martian space exploration. A typical spacesuit is made of sandwich composite material and designed to withstand various pressure and loading conditions while also considering the safety and comfort of the astronauts. One of the critical load cases in spacesuit design is a low-velocity impact (LVI) which may occur due to tool drop and other similar scenarios. The objectives of this work were (a) to create a finite element (FE) model of a component of a spacesuit, (b) validation of the FE model through experiments, (c) …

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Background Flow Influence On Impulsive Jet-Driven Micro Droplet Dispersal, Vaishak Thiruvenkitam Aug 2021

Background Flow Influence On Impulsive Jet-Driven Micro Droplet Dispersal, Vaishak Thiruvenkitam

Doctoral Dissertations and Master's Theses

Accurately predicting the airborne spread of infectious diseases is crucial in controlling the COVID­19 pandemic today. Studies have shown the spread of expiratory droplets depends on ambient thermodynamic conditions and flow properties of the jet emitted by the activity. However, the droplet spread in conditions of background flow is not yet comprehensively understood. This study uses the Eulerian­-Lagrangian model with k−ω turbulence modelling to simulate spread of particles and study the factors affecting it in a closed environment with a background flow. Respiratory activities are modeled as a non-­isothermal jet of air with droplets suspended in them in a predetermined …

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Investigation On The Interaction Of An Impinging Jet With Cylinder Wakes, Karthik Krishna Aug 2021

Investigation On The Interaction Of An Impinging Jet With Cylinder Wakes, Karthik Krishna

Doctoral Dissertations and Master's Theses

Jet impingement cooling is a widely used cooling method due to the high heat transfer rates associated with it. Research for improving heat transfer rates for this cooling is still being carried out due to its broad application in various fields like gas turbine blade cooling, electronic component cooling, and paper drying. The unsteady jet oscillation effectively enhances the stagnation region and the time-averaged heat transfer rates. It is shown that a novel passive jet oscillation technique can be achieved using the vortices periodically shed from a cylinder placed upstream in a channel with an initial crossflow. Preliminary CFD results …

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A Reduced-Order Model Bi-Modal Excitation Of A Supersonic Planar Jet, Benjamin Malczewski Aug 2021

A Reduced-Order Model Bi-Modal Excitation Of A Supersonic Planar Jet, Benjamin Malczewski

Doctoral Dissertations and Master's Theses

This work analytically and numerically examines the effects of bi-modal excitation on a Mach 1.5 heated planar jet. Starting with the Navier-Stokes equations, triple decomposition is applied to the flow components. A reduced order model is derived, turning the Navier-Stokes partial differential equations into a set of coupled ordinary differential equations, relating the momentum thickness and amplitudes of a fundamental and subharmonic mode to the streamwise location along the jet. Computational fluid dynamics data from the minor plane of a Mach 1.5 heated rectangular jet is used to verify a hyperbolic tangent profile for the mean flow at various streamwise …

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Durability And Damage Analysis Of Hybrid Multiscale Composites, Suma Ayyagari Aug 2021

Durability And Damage Analysis Of Hybrid Multiscale Composites, Suma Ayyagari

Doctoral Dissertations and Master's Theses

In this dissertation, an effort was carried out to enhance the mechanical performance of fiber reinforced composites (FRPs) by modification of the fibers’ surface morphologies. The effects of various surface alterations of a plain-woven carbon fiber fabric surface, on the fiber/epoxy interface were investigated. The alterations were mostly achieved by growing different nanofillers like zinc oxide nanorods (ZnO NR), carbon nanotubes (CNTs), and metal organic frameworks (MOFs) on the fiber surface. While the growth techniques for ZnO NR and CNTs place restrictions on the size of the fabricated composites, MOFs route is uniform, affordable, and can be readily scaled up …

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Active Control Of Coherent Structures In An Axisymmetric Jet, Michael Marques Goncalves Aug 2021

Active Control Of Coherent Structures In An Axisymmetric Jet, Michael Marques Goncalves

Doctoral Dissertations and Master's Theses

The primary objective of this work is to develop high-fidelity simulation model for jet noise control predictions and quantify the sound reduction when an external source frequency mode excitation is imposed on the jet flow. Whereas passive approaches using mixing devices, such as chevrons, have been shown to reduce low-frequency noise in jet engines, such approaches incur a performance penalty since they result in a reduced thrust. To avoid a performance penalty in reducing jet noise, the current work investigates a open-loop active noise control (ANC) system that utilizes a unsteady microjet actuator on the nozzle lip in the downstream …

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Unboxing The Algorithm: A Process Model Of An Algorithmic Solution, Marta Stelmaszak Rosa Aug 2021

Unboxing The Algorithm: A Process Model Of An Algorithmic Solution, Marta Stelmaszak Rosa

Business Faculty Publications and Presentations

With the explosion of data, analytics and artificial intelligence, information systems research focuses on the use, management and consequences of algorithms. This far, only a handful of papers offer insights into how algorithmic solutions work. To address this gap, we studied the code making up 45 public data science Jupyter notebooks containing algorithmic solutions developed to predict customer churn in a credit card dataset on a data science platform Kaggle. com. We synthesized a process model of an algorithmic solution: preparing the environment, reading in data, cleaning data, exploratory data analysis, pre-processing the dataset, building and training the model, and …

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Linear Nearest Neighbor Flocks With All Distinct Agents, R. G. Lyons, J. J. P. Veerman Aug 2021

Linear Nearest Neighbor Flocks With All Distinct Agents, R. G. Lyons, J. J. P. Veerman

Mathematics and Statistics Faculty Publications and Presentations

This paper analyzes the global dynamics of one-dimensional agent arrays with nearest neighbor linear couplings. The equations of motion are second-order linear ODE’s with constant coefficients. The novel part of this research is that the couplings are different for each distinct agent. We allow the forces to depend on the positions and velocity (damping terms) but the magnitudes of both the position and velocity couplings are different for each agent. We, also, do not assume that the forces are “Newtonian” (i.e. the force due to A on B equals the minus the force of B on A) as this assumption …

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Predicting Eye Movement And Fixation Patterns On Scenic Images Using Machine Learning For Children With Autism Spectrum Disorder, Raymond Anden Aug 2021

Predicting Eye Movement And Fixation Patterns On Scenic Images Using Machine Learning For Children With Autism Spectrum Disorder, Raymond Anden

Computational and Data Sciences (PhD) Dissertations

This study uses eye-tracking experiment data to predict the fixation points for children with Autism Spectrum Disorder (ASD) and Typically Developing (TD) for 14 ASD and 14 TD subjects for 300 scenic images. Based on explanatory Logistic Regression models, it is evident that fixation patterns for both ASD and TD subjects focus near the center of each scenic image. Using gradient boosting the researchers successfully identify 31.7% and 39.5% of all fixation points in the top decile of predicted fixation points for ASD and TD subjects respectively. Results conclude that TD subjects have less variability in their eye movement and …

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Exploring Behaviors Of Software Developers And Their Code Through Computational And Statistical Methods, Elia Eiroa Lledo Aug 2021

Exploring Behaviors Of Software Developers And Their Code Through Computational And Statistical Methods, Elia Eiroa Lledo

Computational and Data Sciences (PhD) Dissertations

As Artificial Intelligence (AI) increasingly penetrates all aspects of society, many obstacles emerge. This thesis identifies and discusses the issues facing Computer Vision and significant deficiencies in the Software Development Life-cycle that need to be resolved to facilitate the evolution toward true artificial intelligence. We explicitly review the concepts behind Convolutional Neural Network (CNN) models, the benchmark for computer vision. Chapter 2 highlights the mechanisms that have popularized CNNs while also specifying significant gaps that could garner the model inadequate for future use in safety-critical systems. We put forward two main limitations. Namely, CNNs do not use lack of information …

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Continuous Glucose Monitoring, Type 2 Diabetes And Hemoglobin A1c: An Integrative Review, Kimberly Dawn Fairchild Aug 2021

Continuous Glucose Monitoring, Type 2 Diabetes And Hemoglobin A1c: An Integrative Review, Kimberly Dawn Fairchild

Doctoral Dissertations and Projects

Continuous glucose monitors (CGMs) are used to measure a patient’s glucose levels every few minutes around the clock. According to the National Institute of Diabetes and Digestive and Kidney Disease (NIDDK), CGMs are mostly used by Type 1 Diabetes Mellitus patients, but research has shown that Type 2 DM patients can benefit from them as well (Ida et al., 2019; NIDDK, 2017). Glucose levels can change over hours or days, and seeing the trends by using a CGM will help patients make more informed decisions about the food they eat and how much they exercise, and the type and amount …

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A Phenomenological Study Of How English Teachers' Beliefs Affect Their Grammar Instruction, Athena Pualeilani Jackson Aug 2021

A Phenomenological Study Of How English Teachers' Beliefs Affect Their Grammar Instruction, Athena Pualeilani Jackson

Doctoral Dissertations and Projects

The purpose of this phenomenological study was to describe how beliefs about grammar affected the grammar instruction of 10 high school English teachers in central Florida. Fishbein and Ajzen’s (2010) theory of reasoned action guided the study since the theory shows the relationship between beliefs and actions. A phenomenological design with a transcendental approach was used, and data was collected through three methods: interviews, observations, and participant reflections. Data was analyzed according to Moustakas’ (1994) steps for data analysis. Data analysis included horizonalization, theme development, textural descriptions, structural descriptions, composite descriptions, and a synthesized essence of the experience. Many participants …

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A Case Study Of Teachers Of Elementary Gifted Students And Their Perceptions Of Best Practices For Teaching Visual Spatial Activities In The Classroom, Sandra J. Young Aug 2021

A Case Study Of Teachers Of Elementary Gifted Students And Their Perceptions Of Best Practices For Teaching Visual Spatial Activities In The Classroom, Sandra J. Young

Doctoral Dissertations and Projects

Elementary gifted students with spatial strengths are often overlooked, under identified, and underserved in elementary school. The purpose of this qualitative case study was to identify how visual spatial training can be implemented in the elementary gifted curricula and how the teachers of the gifted program can be supported in their efforts to develop visual spatial activities for the elementary gifted classroom in a large, urban school district in South Carolina. There are approximately 35 teachers of the district’s elementary gifted program. This program services those students in grades 3, 4, and 5 who qualified based on state-mandated criteria. The …

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The Predictive Relationship Between Elementary Pre-Service Teacher Praxis Subject Assessment Scores And Pedagogical Knowledge, Miranda Arnold Aug 2021

The Predictive Relationship Between Elementary Pre-Service Teacher Praxis Subject Assessment Scores And Pedagogical Knowledge, Miranda Arnold

Doctoral Dissertations and Projects

The purpose of this study was to examine the relationship of elementary pre-service teachers’ pedagogical knowledge with the predictor variable of content knowledge. This quantitative, correlational study measured content knowledge through the Praxis Subject Assessment – Elementary Education: Multiple Subjects scores, including the four subtests: Reading and Language Arts, Mathematics, Social Studies, and Science. The criterion variable of pedagogical knowledge was obtained through the scores from the Candidate Preservice Assessment of Student Teaching Form. Scores from the two assessment instruments for 167 elementary education pre-service teachers were collected through archived data from one educator preparation program. A multiple regression analysis …

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Relative Impacts Of Climate Change And Land Cover Change On Streamflow Using Swat In The Clackamas River Watershed, Usa, Junjie Chen, Heejun Chang Aug 2021

Relative Impacts Of Climate Change And Land Cover Change On Streamflow Using Swat In The Clackamas River Watershed, Usa, Junjie Chen, Heejun Chang

Geography Faculty Publications and Presentations

To understand the spatial–temporal pattern of climate and land cover (CLC) change effects on hydrology, we used three land cover change (LCC) coupled scenarios to estimate the changes in streamflow metrics in the Clackamas River Watershed in Oregon for the 2050s (2040–2069) and the 2080s (2070–2099). Coupled scenarios, which were split into individual and combined simulations such as climate change (CC), LCC, CLC change, and daily streamflow were simulated in the Soil and Water Assessment Tool. The interannual variability of streamflow was higher in the lower urbanized area than the upper forested region. The watershed runoff was projected to be …

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Tumor-On-Chip Modeling Of Organ-Specific Cancer And Metastasis, Nuala Del Piccolo, Venktesh S Shirure, Ye Bi, S Peter Goedegebuure, Sepideh Gholami, Christopher C W Hughes, Ryan C Fields, Steven C George Aug 2021

Tumor-On-Chip Modeling Of Organ-Specific Cancer And Metastasis, Nuala Del Piccolo, Venktesh S Shirure, Ye Bi, S Peter Goedegebuure, Sepideh Gholami, Christopher C W Hughes, Ryan C Fields, Steven C George

2020-Current year OA Pubs

Every year, cancer claims millions of lives around the globe. Unfortunately, model systems that accurately mimic human oncology - a requirement for the development of more effective therapies for these patients - remain elusive. Tumor development is an organ-specific process that involves modification of existing tissue features, recruitment of other cell types, and eventual metastasis to distant organs. Recently, tissue engineered microfluidic devices have emerged as a powerful in vitro tool to model human physiology and pathology with organ-specificity. These organ-on-chip platforms consist of cells cultured in 3D hydrogels and offer precise control over geometry, biological components, and physiochemical properties. …

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Use Of Convalescent Plasma In Covid-19 Patients With Immunosuppression, Jonathon W Senefeld, Jeffrey P Henderson, Et Al. Aug 2021

Use Of Convalescent Plasma In Covid-19 Patients With Immunosuppression, Jonathon W Senefeld, Jeffrey P Henderson, Et Al.

2020-Current year OA Pubs

In the absence of effective countermeasures, human convalescent plasma has been widely used to treat severe acute respiratory syndrome coronavirus 2, the causative agent of novel coronavirus disease 19 (COVID-19), including among patients with innate or acquired immunosuppression. However, the association between COVID-19-associated mortality in patients with immunosuppression and therapeutic use of convalescent plasma is unknown. We review 75 reports, including one large matched-control registry study of 143 COVID-19 patients with hematological malignancies, and 51 case reports and 23 case series representing 238 COVID-19 patients with immunosuppression. We review clinical features and treatment protocols of COVID-19 patients with immunosuppression after …

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Generalized Deep Learning Eeg Models For Cross-Participant And Cross-Task Detection Of The Vigilance Decrement In Sustained Attention Tasks, Alexander J. Kamrud, Brett J. Borghetti, Christine M. Schubert Kabban, Michael E. Miller Aug 2021

Generalized Deep Learning Eeg Models For Cross-Participant And Cross-Task Detection Of The Vigilance Decrement In Sustained Attention Tasks, Alexander J. Kamrud, Brett J. Borghetti, Christine M. Schubert Kabban, Michael E. Miller

Faculty Publications

Tasks which require sustained attention over a lengthy period of time have been a focal point of cognitive fatigue research for decades, with these tasks including air traffic control, watchkeeping, baggage inspection, and many others. Recent research into physiological markers of mental fatigue indicate that markers exist which extend across all individuals and all types of vigilance tasks. This suggests that it would be possible to build an EEG model which detects these markers and the subsequent vigilance decrement in any task (i.e., a task-generic model) and in any person (i.e., a cross-participant model). However, thus far, no task-generic EEG …

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Comparing Person And People Perception: Multiple Group Members Do Not Increase Stereotype Priming, Lm Persson, M Golubickis, D Dublas, N Mastnak, Et Al Aug 2021

Comparing Person And People Perception: Multiple Group Members Do Not Increase Stereotype Priming, Lm Persson, M Golubickis, D Dublas, N Mastnak, Et Al

School of Psychology

A characteristic feature of daily life is encountering people in groups. Surprisingly, however, at least during the initial stages of processing, research has focused almost exclusively on the construal of single individuals. As such, it remains unclear whether person and people (i.e., group) perception yield comparable or divergent outcomes. Addressing this issue, here we explored a core social-cognitive topic—stereotype activation—by presenting both single and multiple facial primes in a sequential-priming task. In addition, the processes underlying task performance were probed using a drift diffusion model analysis. Based on prior work, it was hypothesised that multiple (vs. single) primes would increase …

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