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Willingness to Pay for Rose Attributes: Helping Provide Consumer Orientation to Breeding Programs
Abstract: Floriculture value exceeds $5.8 billion in the United States. Environmental challenges, market trends, and diseases complicate breeding priorities. To inform breeders’ and geneticists’ research efforts, we set out to gather consumers’ preferences in the form of willingness to pay (WTP) for different rose attributes in a discrete choice experiment. The responses are modeled in […]
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A Critical Analysis of FDA Guidance for User Percentile Device Design Criteria Versus Currently Available Human Factors Engineering Data Sources and Industry Best Practices
Abstract: A staggering report was recently released by the International Consortium of Investigative Journalists (ICIJ) indicating that 83,000 deaths and 1.7 million injuries were linked to medical device adverse events reported over the last decade (Díaz-Struck, 2018). Furthermore, a 2013 report by McKinsey & Company suggested that such adverse events and associated quality issues cost […]
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Investigation of the dependency of the drivers’ emotional experience on different road types and driving conditions
Abstract: The growing sophistication of technologies and sociological advances are major causes for the dramatic change the automotive sector is currently undergoing. To address changes from a human-centered design perspective an improved understanding of the occupants’ emotional experience and behavior is required. Facial-Expression Analysis (FEA) is an emerging tool in support of such an approach, […]
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Locally Confined Modality Fusion Network with a Global Perspective for Multimodal Human Affective Computing
Abstract: In this paper, we propose a novel multimodal fusion framework, named locally confined modality fusion network (LMFN), that contains a bidirectional multiconnected LSTM (BM-LSTM) to address the multimodal human affective computing problem. Instead of conducting fusion only on a holistic level, we propose a hierarchical fusion strategy that considers both local and global interactions […]
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Examining Course Layouts in Blackboard: Using Eye-Tracking to Evaluate Usability in a Learning Management System
Abstract: This paper describes an exploratory usability study designed to investigate how college students locate information in a Learning Management System and to establish a set of guidelines for creating the best course layouts that can increase the student’s learning experience. Using observations, perception survey data, and a high-fidelity eye-tracker that recorded where participants’ eyes […]
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Does the magnitude of relative calorie distance affect food consumption?
Abstract: Can the magnitude of the calorie distance between food items explain the contradictory findings in previous literature regarding the impact of calorie labeling laws? Our theoretical model suggests that the relative calorie difference between alternatives in food menus is a missing link important for understanding the impact of calorie labeling information on calorie intake […]
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Divide, Conquer and Combine: Hierarchical Feature Fusion Network with Local and Global Perspectives for Multimodal Affective Computing
Abstract: We propose a general strategy named ‘divide, conquer and combine’ for multimodal fusion. Instead of directly fusing features at holistic level, we conduct fusion hierarchically so that both local and global interactions are considered for a comprehensive interpretation of multimodal embeddings. In the ‘divide’ and ‘conquer’ stages, we conduct local fusion by exploring the […]
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A comparison of the effectiveness of two types of deceit detection training methods in older adults
Abstract: Background In general, people are poor at detecting deception. Older adults are even worse than young adults at detecting deceit, which might make them uniquely vulnerable to certain types of financial fraud. One reason for poor deceit detection abilities is that lay theories of cues to deception are not valid. This study compared the […]
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Multi-modal Sentiment Analysis using Deep Canonical Correlation Analysis
Abstract: This paper learns multi-modal embeddings from text, audio, and video views/modes of data in order to improve upon downstream sentiment classification. The experimental framework also allows investigation of the relative contributions of the individual views in the final multi-modal embedding. Individual features derived from the three views are combined into a multi-modal embedding using […]
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Eye-Tracking Boston City Hall to Better Understand Human Perception and the Architectural Experience
Abstract: Learning how architecture impacts human perception can help us understand how civic monuments bring us together or drive us apart, create community cohesion and identity or the reverse: anomie, placelessness and the fragmentation of the public realm. Boston City Hall and Plaza, an urban renewal project from the 1960s, intended to revitalize a historic […]

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