Publications

@article{chen_large-scale_2024,

title = {Large-Scale 3D Terrain Reconstruction Using 3D Gaussian Splatting for Visualization and Simulation},

author = {Meida Chen and Devashish Lal and Zifan Yu and Jiuyi Xu and Andrew Feng and Suya You and Abdul Nurunnabi and Yangming Shi},

url = {https://isprs-archives.copernicus.org/articles/XLVIII-2-2024/49/2024/},

doi = {10.5194/isprs-archives-XLVIII-2-2024-49-2024},

issn = {2194-9034},

year  = {2024},

date = {2024-06-01},

urldate = {2024-06-20},

journal = {The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences},

volume = {XLVIII-2-2024},

pages = {49–54},

abstract = {Abstract. The fusion of low-cost unmanned aerial systems (UAS) with advanced photogrammetric techniques has revolutionized 3D terrain reconstruction, enabling the automated creation of detailed models. Concurrently, the advent of 3D Gaussian Splatting has introduced a paradigm shift in 3D data representation, offering visually realistic renditions distinct from traditional polygon-based models. Our research builds upon this foundation, aiming to integrate Gaussian Splatting into interactive simulations for immersive virtual environments. We address challenges such as collision detection by adopting a hybrid approach, combining Gaussian Splatting with photogrammetry-derived meshes. Through comprehensive experimentation covering varying terrain sizes and Gaussian densities, we evaluate scalability, performance, and limitations. Our findings contribute to advancing the use of advanced computer graphics techniques for enhanced 3D terrain visualization and simulation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{lukin-etal-2024-scout-situated,

title = {SCOUT: A Situated and Multi-Modal Human-Robot Dialogue Corpus},

author = {Stephanie M Lukin and Claire Bonial and Matthew Marge and Taylor Hudson and Cory J. Hayes and Kimberly Pollard and Anthony L. Baker and Ashley Foots and Ron Artstein and Felix Gervits and Mitchell Abrams and Henry Cassidy and Lucia Donatelli and Anton Leuski and Susan G. Hill and David Traum and Clare Voss},

url = {https://aclanthology.org/2024.lrec-main.1259},

year  = {2024},

date = {2024-05-01},

pages = {14445 - 144458},

abstract = {We introduce the Situated Corpus Of Understanding Transactions (SCOUT), a multi-modal collection of human-robot dialogue in the task domain of collaborative exploration. The corpus was constructed from multiple Wizard-of-Oz experiments where human participants gave verbal instructions to a remotely-located robot to move and gather information about its surroundings. SCOUT contains 89,056 utterances and 310,095 words from 278 dialogues averaging 320 utterances per dialogue. The dialogues are aligned with the multi-modal data streams available during the experiments: 5,785 images and 30 maps. The corpus has been annotated with Abstract Meaning Representation and Dialogue-AMR to identify the speaker’s intent and meaning within an utterance, and with Transactional Units and Relations to track relationships between utterances to reveal patterns of the Dialogue Structure. We describe how the corpus and its annotations have been used to develop autonomous human-robot systems and enable research in open questions of how humans speak to robots. We release this corpus to accelerate progress in autonomous, situated, human-robot dialogue, especially in the context of navigation tasks where details about the environment need to be discovered.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{chemburkar_evaluating_2024,

title = {Evaluating Vision-Language Models on the TriangleCOPA Benchmark},

author = {Ankur Chemburkar and Andrew Gordon and Andrew Feng},

year  = {2024},

date = {2024-05-01},

journal = {FLAIRS-37},

volume = {37},

abstract = {The TriangleCOPA benchmark consists of 100 textual questions with videos depicting the movements of simple shapes in the style of the classic social-psychology film created by Fritz Heider and Marianne Simmel in 1944. In our experiments, we investigate the performance of current vision-language models on this challenging benchmark, assessing the capability of these models for visual anthropomorphism and abstract interpretation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{soleymani_guest_2024,

title = {Guest Editorial Best of ACII 2021},

author = {Mohammad Soleymani and Shiro Kumano and Emily Mower Provost and Nadia Bianchi-Berthouze and Akane Sano and Kenji Suzuki},

url = {https://ieeexplore.ieee.org/document/10542496/},

doi = {10.1109/TAFFC.2024.3389249},

issn = {1949-3045, 2371-9850},

year  = {2024},

date = {2024-04-01},

urldate = {2024-06-25},

journal = {IEEE Transactions on Affective Computing},

volume = {15},

number = {2},

pages = {376–379},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{goh_normative_2024,

title = {Normative performance data on visual attention in neurotypical children: virtual reality assessment of cognitive and psychomotor development},

author = {Crystal Goh and Yu Ma and Albert Rizzo},

url = {https://www.frontiersin.org/articles/10.3389/frvir.2024.1309176/full},

doi = {10.3389/frvir.2024.1309176},

issn = {2673-4192},

year  = {2024},

date = {2024-04-01},

urldate = {2024-04-16},

journal = {Frontiers in Virtual Reality},

volume = {5},

pages = {1309176},

abstract = {Introduction: 

 Virtual Reality (VR) is revolutionizing healthcare research and practice by offering innovative methodologies across various clinical conditions. Advances in VR technology enable the creation of controllable, multisensory 3D environments, making it an appealing tool for capturing and quantifying behavior in realistic scenarios. This paper details the application of VR as a tool for neurocognitive evaluation, specifically in attention process assessment, an area of relevance for informing the diagnosis of childhood health conditions such as Attention Deficit Hyperactivity Disorder (ADHD). 

 Methods: 

 The data presented focuses on attention performance results from a large sample ( 

 n = 837) of neurotypical male and female children (ages 6–13) tested on a visual continuous performance task, administered within an immersive VR classroom environment. This data was collected to create a normative baseline database for use to inform comparisons with the performances of children with ADHD to support diagnostic decision-making in this area. 

 Results: 

 Results indicate systematic improvements on most metrics across the age span, and sex differences are noted on key variables thought to reflect differential measures of hyperactivity and inattention in children with ADHD. Results support VR technology as a safe and viable option for testing attention processes in children, under stimulus conditions that closely mimic ecologically relevant challenges found in everyday life. 

 Discussion: 

 In response to these stimulus conditions, VR can support advanced methods for capturing and quantifying users’ behavioral responses. VR offers a more systematic and objective approach for clinical assessment and intervention and provides conceptual support for its use in a wide variety of healthcare contexts.},

keywords = {MedVR},

pubstate = {published},

tppubtype = {article}

}

@article{gurney_conversational_2024,

title = {Conversational technology and reactions to withheld information},

author = {Nikolos Gurney and George Loewenstein and Nick Chater},

editor = {Petre Caraiani},

url = {https://dx.plos.org/10.1371/journal.pone.0301382},

doi = {10.1371/journal.pone.0301382},

issn = {1932-6203},

year  = {2024},

date = {2024-04-01},

urldate = {2024-04-16},

journal = {PLOS ONE},

volume = {19},

number = {4},

pages = {e0301382},

abstract = {People frequently face decisions that require making inferences about withheld information. The advent of large language models coupled with conversational technology, e.g., Alexa, Siri, Cortana, and the Google Assistant, is changing the mode in which people make these inferences. We demonstrate that conversational modes of information provision, relative to traditional digital media, result in more critical responses to withheld information, including: (1) a reduction in evaluations of a product or service for which information is withheld and (2) an increased likelihood of recalling that information was withheld. These effects are robust across multiple conversational modes: a recorded phone conversation, an unfolding chat conversation, and a conversation script. We provide further evidence that these effects hold for conversations with the Google Assistant, a prominent conversational technology. The experimental results point to participants’ intuitions about why the information was withheld as the driver of the effect.},

keywords = {DTIC, Social Simulation, UARC},

pubstate = {published},

tppubtype = {article}

}

@article{frummet_cooking_2024,

title = {Cooking with Conversation: Enhancing User Engagement and Learning with a Knowledge-Enhancing Assistant},

author = {Alexander Frummet and Alessandro Speggiorin and David Elsweiler and Anton Leuski and Jeff Dalton},

url = {https://dl.acm.org/doi/10.1145/3649500},

doi = {10.1145/3649500},

issn = {1046-8188, 1558-2868},

year  = {2024},

date = {2024-03-01},

urldate = {2024-04-16},

journal = {ACM Transactions on Information Systems},

pages = {3649500},

abstract = {We present two empirical studies to investigate users’ expectations and behaviours when using digital assistants, such as Alexa and Google Home, in a kitchen context: First, a survey (N=200) queries participants on their expectations for the kinds of information that such systems should be able to provide. While consensus exists on expecting information about cooking steps and processes, younger participants who enjoy cooking express a higher likelihood of expecting details on food history or the science of cooking. In a follow-up Wizard-of-Oz study (N = 48), users were guided through the steps of a recipe either by an 

 active 

 wizard that alerted participants to information it could provide or a 

 passive 

 wizard who only answered questions that were provided by the user. The 

 active 

 policy led to almost double the number of conversational utterances and 1.5 times more knowledge-related user questions compared to the 

 passive 

 policy. Also, it resulted in 1.7 times more knowledge communicated than the 

 passive 

 policy. We discuss the findings in the context of related work and reveal implications for the design and use of such assistants for cooking and other purposes such as DIY and craft tasks, as well as the lessons we learned for evaluating such systems.},

keywords = {DTIC, Natural Language, UARC},

pubstate = {published},

tppubtype = {article}

}

@article{saxon_continuous_2024,

title = {Continuous Assessment of Active-Duty Army Special Operations and Reconnaissance Marines Using Digital Devices and Custom Software: The Digital Comprehensive Operator Readiness Assessment (DcORA) Study},

author = {Leslie Saxon and Robert T Faulk and Jill Boberg and Trevor Barrett and Steve McLelland},

url = {https://www.jsomonline.org/Citations/PXKK-I23D.php},

doi = {10.55460/PXKK-I23D},

issn = {1553-9768},

year  = {2024},

date = {2024-01-01},

urldate = {2024-06-25},

journal = {Journal of Special Operations Medicine},

keywords = {CBC},

pubstate = {published},

tppubtype = {article}

}

@article{marti_structured_2024-1,

title = {Structured Expert Judgement Approach of the Health Impact of Various Chemicals and Classes of Chemicals},

author = {Deniz Marti and David Hanrahan and Ernesto Sanchez-Triana and Mona Wells and Lilian Corra and Howard Hu and Patrick N. Breysse and Amalia Laborde and Jack Caravanos and Roberto Bertollini and Kate Porterfield and Richard Fuller},

url = {http://medrxiv.org/content/early/2024/02/01/2024.01.30.24301863.abstract},

doi = {10.1101/2024.01.30.24301863},

year  = {2024},

date = {2024-01-01},

journal = {medRxiv},

pages = {2024.01.30.24301863},

abstract = {Introduction Chemical contamination and pollution are an ongoing threat to human health and the environment. The concern over the consequences of chemical exposures at the global level continues to grow. Because resources are constrained, there is a need to prioritize interventions focused on the greatest health impact. Data, especially related to chemical exposures, are rarely available for most substances of concern, and alternate methods to evaluate their impact are needed.Structured Expert Judgment (SEJ) Process A Structured Expert Judgment3 process was performed to provide plausible estimates of health impacts for 16 commonly found pollutants: asbestos, arsenic, benzene, chromium, cadmium, dioxins, fluoride, highly hazardous pesticides (HHPs), lead, mercury, polycyclic-aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), Per- and Polyfluorinated Substances (PFAs), phthalates, endocrine disrupting chemicals (EDCs), and brominated flame retardants (BRFs). This process, undertaken by sector experts, weighed individual estimations of the probable global health scale health impacts of each pollutant using objective estimates of the expert opinions’ statistical accuracy and informativeness.Main Findings The foremost substances, in terms of mean projected annual total deaths, were lead, asbestos, arsenic, and HHPs. Lead surpasses the others by a large margin, with an estimated median value of 1.7 million deaths annually. The three other substances averaged between 136,000 and 274,000 deaths per year. Of the 12 other chemicals evaluated, none reached an estimated annual death count exceeding 100,000. These findings underscore the importance of prioritizing available resources on reducing and remediating the impacts of these key pollutants.Range of Health Impacts Based on the evidence available, experts concluded some of the more notorious chemical pollutants, such as PCBs and dioxin, do not result in high levels of human health impact from a global scale perspective. However, the chemical toxicity of some compounds released in recent decades, such as Endocrine Disrupters and PFAs, cannot be ignored, even if current impacts are limited. Moreover, the impact of some chemicals may be disproportionately large in some geographic areas. Continued research and monitoring are essential; and a preventative approach is needed for chemicals.Future Directions These results, and potential similar analyses of other chemicals, are provided as inputs to ongoing discussions about priority setting for global chemicals and pollution management. Furthermore, we suggest that this SEJ process be repeated periodically as new information becomes available.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThe author(s) received no specific funding for this work.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesAll relevant data are within the manuscript and its Supporting Information files.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{soleymani_robust_2024,

title = {Robust Tube-Based Reference Tracking Nonlinear Model Predictive Control for Wind Turbines},

author = {Mohammad Soleymani and Mehdi Rahmani and Nooshin Bigdeli},

url = {https://ieeexplore.ieee.org/document/10495787/},

doi = {10.1109/TASE.2024.3385714},

issn = {1545-5955, 1558-3783},

year  = {2024},

date = {2024-01-01},

urldate = {2024-04-16},

journal = {IEEE Transactions on Automation Science and Engineering},

pages = {1–13},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{joshi_augmenting_2024,

title = {Augmenting Cognitive Architectures with Large Language Models},

author = {Himanshu Joshi and Volkan Ustun},

url = {https://ojs.aaai.org/index.php/AAAI-SS/article/view/27689},

doi = {10.1609/aaaiss.v2i1.27689},

issn = {2994-4317},

year  = {2024},

date = {2024-01-01},

urldate = {2024-04-16},

journal = {Proceedings of the AAAI Symposium Series},

volume = {2},

number = {1},

pages = {281–285},

abstract = {A particular fusion of generative models and cognitive architectures is discussed with the help of the Soar and Sigma cognitive architectures. After a brief introduction to cognitive architecture concepts and Large Language Models as exemplar generative AI models, one approach towards their fusion is discussed. This is then analyzed with a summary of potential benefits and extensions needed to existing cognitive architecture that is closest to the proposal.},

keywords = {Cognitive Architecture},

pubstate = {published},

tppubtype = {article}

}

@article{gurney_operational_2024,

title = {Operational Collective Intelligence of Humans and Machines},

author = {Nikolos Gurney and Fred Morstatter and David V. Pynadath and Adam Russell and Gleb Satyukov},

url = {https://arxiv.org/abs/2402.13273},

doi = {10.48550/ARXIV.2402.13273},

year  = {2024},

date = {2024-01-01},

urldate = {2024-03-14},

abstract = {We explore the use of aggregative crowdsourced forecasting (ACF) as a mechanism to help operationalize ``collective intelligence'' of human-machine teams for coordinated actions. We adopt the definition for Collective Intelligence as: ``A property of groups that emerges from synergies among data-information-knowledge, software-hardware, and individuals (those with new insights as well as recognized authorities) that enables just-in-time knowledge for better decisions than these three elements acting alone.'' Collective Intelligence emerges from new ways of connecting humans and AI to enable decision-advantage, in part by creating and leveraging additional sources of information that might otherwise not be included. Aggregative crowdsourced forecasting (ACF) is a recent key advancement towards Collective Intelligence wherein predictions (Xtextbackslash% probability that Y will happen) and rationales (why I believe it is this probability that X will happen) are elicited independently from a diverse crowd, aggregated, and then used to inform higher-level decision-making. This research asks whether ACF, as a key way to enable Operational Collective Intelligence, could be brought to bear on operational scenarios (i.e., sequences of events with defined agents, components, and interactions) and decision-making, and considers whether such a capability could provide novel operational capabilities to enable new forms of decision-advantage.},

note = {Publisher: [object Object] 

Version Number: 1},

keywords = {DTIC, Social Simulation, UARC},

pubstate = {published},

tppubtype = {article}

}

@article{gurney_spontaneous_2024,

title = {Spontaneous Theory of Mind for Artificial Intelligence},

author = {Nikolos Gurney and David V. Pynadath and Volkan Ustun},

url = {https://arxiv.org/abs/2402.13272},

doi = {10.48550/ARXIV.2402.13272},

year  = {2024},

date = {2024-01-01},

urldate = {2024-03-14},

abstract = {Existing approaches to Theory of Mind (ToM) in Artificial Intelligence (AI) overemphasize prompted, or cue-based, ToM, which may limit our collective ability to develop Artificial Social Intelligence (ASI). Drawing from research in computer science, cognitive science, and related disciplines, we contrast prompted ToM with what we call spontaneous ToM – reasoning about others' mental states that is grounded in unintentional, possibly uncontrollable cognitive functions. We argue for a principled approach to studying and developing AI ToM and suggest that a robust, or general, ASI will respond to prompts textbackslashtextitand spontaneously engage in social reasoning.},

note = {Publisher: [object Object] 

Version Number: 1},

keywords = {AI, DTIC, Social Simulation, UARC},

pubstate = {published},

tppubtype = {article}

}

@article{gratch_guest_2024,

title = {Guest Editorial: Ethics in Affective Computing},

author = {Jonathan Gratch and Gretchen Greene and Rosalind Picard and Lachlan Urquhart and Michel Valstar},

url = {https://ieeexplore.ieee.org/document/10454111/},

doi = {10.1109/TAFFC.2023.3322918},

issn = {1949-3045, 2371-9850},

year  = {2024},

date = {2024-01-01},

urldate = {2024-03-14},

journal = {IEEE Transactions on Affective Computing},

volume = {15},

number = {1},

pages = {1–3},

keywords = {Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{spiegel_what_2024,

title = {What Is Medical Extended Reality? A Taxonomy Defining the Current Breadth and Depth of an Evolving Field},

author = {Brennan M. R. Spiegel and Albert Rizzo and Susan Persky and Omer Liran and Brenda Wiederhold and Susan Woods and Kate Donovan and Korak Sarkar and Henry Xiang and Sun Joo and Rohan Jotwani and Min Lang and Margot Paul and Mike Senter-Zapata and Keith Widmeier and Haipeng Zhang},

url = {https://www.liebertpub.com/doi/10.1089/jmxr.2023.0012},

doi = {10.1089/jmxr.2023.0012},

issn = {2994-1520},

year  = {2024},

date = {2024-01-01},

urldate = {2024-02-20},

journal = {Journal of Medical Extended Reality},

volume = {1},

number = {1},

pages = {4–12},

keywords = {DTIC, MedVR, UARC},

pubstate = {published},

tppubtype = {article}

}

@article{awada_stress_2024,

title = {Stress appraisal in the workplace and its associations with productivity and mood: Insights from a multimodal machine learning analysis},

author = {Mohamad Awada and Burcin Becerik Gerber and Gale M. Lucas and Shawn C. Roll},

editor = {Iftikhar Ahmed Khan},

url = {https://dx.plos.org/10.1371/journal.pone.0296468},

doi = {10.1371/journal.pone.0296468},

issn = {1932-6203},

year  = {2024},

date = {2024-01-01},

urldate = {2024-02-21},

journal = {PLOS ONE},

volume = {19},

number = {1},

pages = {e0296468},

abstract = {Previous studies have primarily focused on predicting stress arousal, encompassing physiological, behavioral, and psychological responses to stressors, while neglecting the examination of stress appraisal. Stress appraisal involves the cognitive evaluation of a situation as stressful or non-stressful, and as a threat/pressure or a challenge/opportunity. In this study, we investigated several research questions related to the association between states of stress appraisal (i.e., boredom, eustress, coexisting eustress-distress, distress) and various factors such as stress levels, mood, productivity, physiological and behavioral responses, as well as the most effective ML algorithms and data signals for predicting stress appraisal. The results support the Yerkes-Dodson law, showing that a moderate stress level is associated with increased productivity and positive mood, while low and high levels of stress are related to decreased productivity and negative mood, with distress overpowering eustress when they coexist. Changes in stress appraisal relative to physiological and behavioral features were examined through the lenses of stress arousal, activity engagement, and performance. An XGBOOST model achieved the best prediction accuracies of stress appraisal, reaching 82.78% when combining physiological and behavioral features and 79.55% using only the physiological dataset. The small accuracy difference of 3% indicates that physiological data alone may be adequate to accurately predict stress appraisal, and the feature importance results identified electrodermal activity, skin temperature, and blood volume pulse as the most useful physiologic features. Implementing these models within work environments can serve as a foundation for designing workplace policies, practices, and stress management strategies that prioritize the promotion of eustress while reducing distress and boredom. Such efforts can foster a supportive work environment to enhance employee well-being and productivity.},

keywords = {DTIC, Machine Learning, UARC},

pubstate = {published},

tppubtype = {article}

}

@article{jago_algorithmic_2024,

title = {Algorithmic management diminishes status: An unintended consequence of using machines to perform social roles},

author = {Arthur S. Jago and Roshni Raveendhran and Nathanael Fast and Jonathan Gratch},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0022103123001105},

doi = {10.1016/j.jesp.2023.104553},

issn = {00221031},

year  = {2024},

date = {2024-01-01},

urldate = {2024-02-21},

journal = {Journal of Experimental Social Psychology},

volume = {110},

pages = {104553},

keywords = {Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{murawski_development_2024,

title = {Development and pilot testing of an artificial intelligence‐based family caregiver negotiation program},

author = {Alaine Murawski and Vanessa Ramirez‐Zohfeld and Johnathan Mell and Marianne Tschoe and Allison Schierer and Charles Olvera and Jeanne Brett and Jonathan Gratch and Lee A. Lindquist},

url = {https://agsjournals.onlinelibrary.wiley.com/doi/10.1111/jgs.18775},

doi = {10.1111/jgs.18775},

issn = {0002-8614, 1532-5415},

year  = {2024},

date = {2024-01-01},

urldate = {2024-02-21},

journal = {Journal of the American Geriatrics Society},

pages = {jgs.18775},

abstract = {Abstract 

 Background 

 Family caregivers of people with Alzheimer's disease experience conflicts as they navigate health care but lack training to resolve these disputes. We sought to develop and pilot test an artificial‐intelligence negotiation training program, NegotiAge, for family caregivers. 

 Methods 

 We convened negotiation experts, a geriatrician, a social worker, and community‐based family caregivers. Content matter experts created short videos to teach negotiation skills. Caregivers generated dialogue surrounding conflicts. Computer scientists utilized the dialogue with the Interactive Arbitration Guide Online (IAGO) platform to develop avatar‐based agents (e.g., sibling, older adult, physician) for caregivers to practice negotiating. Pilot testing was conducted with family caregivers to assess usability (USE) and satisfaction (open‐ended questions with thematic analysis). 

 Results 

 Development: With NegotiAge, caregivers progress through didactic material, then receive scenarios to negotiate (e.g., physician recommends gastric tube, sibling disagrees with home support, older adult refusing support). Caregivers negotiate in real‐time with avatars who are designed to act like humans, including emotional tactics and irrational behaviors. Caregivers send/receive offers, using tactics until either mutual agreement or time expires. Immediate feedback is generated for the user to improve skills training. Pilot testing: Family caregivers ( 

 n = 12) completed the program and survey. USE questionnaire (Likert scale 1–7) subset scores revealed: (1) Useful—Mean 5.69 (SD 0.76); (2) Ease—Mean 5.24 (SD 0.96); (3) Learn—Mean 5.69 (SD 0.74); (4) Satisfy—Mean 5.62 (SD 1.10). Items that received over 80% agreements were: It helps me be more effective; It helps me be more productive; It is useful; It gives me more control over the activities in my life; It makes the things I want to accomplish easier to get done. Participants were highly satisfied and found NegotiAge fun to use (91.7%), with 100% who would recommend it to a friend. 

 Conclusion 

 NegotiAge is an Artificial‐Intelligent Caregiver Negotiation Program, that is usable and feasible for family caregivers to become familiar with negotiating conflicts commonly seen in health care.},

keywords = {AI, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{barrett_force_2024,

title = {Force plate assessments in reconnaissance marine training company},

author = {Trevor Barrett and Robert Faulk and Army Master Sergeant and Jill Boberg and Matthew Bartels and Marine Lieutenant Colonel and Leslie A. Saxon},

url = {https://bmcsportsscimedrehabil.biomedcentral.com/articles/10.1186/s13102-023-00796-z},

doi = {10.1186/s13102-023-00796-z},

issn = {2052-1847},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-22},

journal = {BMC Sports Science, Medicine and Rehabilitation},

volume = {16},

number = {1},

pages = {16},

abstract = {Abstract 

 The ability to obtain dynamic movement assessments using force plate technology holds the promise of providing more detailed knowledge of the strength, balance and forces generated by active-duty military personnel. To date, there are not well-defined use cases for implementation of force plate assessments in military training environments. We sought to determine if force plate technology assessments could provide additional insights, related to the likelihood of graduation, beyond that provided by traditional physical fitness tests (PFT’s), in an elite Marine training school. Serial force plate measures were also obtained on those Marines successfully completing training to determine if consistent measures reflecting the effects of training on muscle skeletal load-over-time could be accurately measured. A pre-training force plate assessment performed in 112 Marines did not predict graduation rates. For Marines who successfully completed the course, serial measures obtained throughout training were highly variable for each individual and no firm conclusions could be drawn related to load imposed or the fitness attained during training.},

keywords = {DTIC, MedVR, UARC},

pubstate = {published},

tppubtype = {article}

}

@article{tak_framework_2023,

title = {A framework for investigating the acceptance of smart home technologies: Findings for residential smart HVAC systems},

author = {Ala Nekouvaght Tak and Burçin Becerik-Gerber and Lucio Soibelman and Gale Lucas},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0360132323009629},

doi = {10.1016/j.buildenv.2023.110935},

issn = {03601323},

year  = {2023},

date = {2023-11-01},

urldate = {2023-12-07},

journal = {Building and Environment},

volume = {245},

pages = {110935},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}

@article{liu_gender_2023,

title = {Gender moderates the effects of ambient bergamot scent on stress restoration in offices},

author = {Ruying Liu and Mohamad Awada and Burcin Becerik Gerber and Gale M. Lucas and Shawn C. Roll},

url = {https://linkinghub.elsevier.com/retrieve/pii/S0272494423001834},

doi = {10.1016/j.jenvp.2023.102135},

issn = {02724944},

year  = {2023},

date = {2023-11-01},

urldate = {2023-09-20},

journal = {Journal of Environmental Psychology},

volume = {91},

pages = {102135},

keywords = {DTIC, UARC, Virtual Humans},

pubstate = {published},

tppubtype = {article}

}