IU Indianapolis ScholarWorks :: Browsing by Author "MacDorman, Karl F."

Browsing by Author "MacDorman, Karl F."

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A two-branch multi-scale residual attention network for single image super-resolution in remote sensing imagery
(IEEE, 2024) Patnaik, Allen; Bhuyan, Manas K.; MacDorman, Karl F.
High-resolution remote sensing imagery finds applications in diverse fields, such as land-use mapping, crop planning, and disaster surveillance. To offer detailed and precise insights, reconstructing edges, textures, and other features is crucial. Despite recent advances in detail enhancement through deep learning, disparities between original and reconstructed images persist. To address this challenge, we propose a two-branch multiscale residual attention network for single-image super-resolution reconstruction. The network gathers complex information about input images from two branches with convolution layers of different kernel sizes. The two branches extract both low-level and high-level features from the input image. The network incorporates multiscale efficient channel attention and spatial attention blocks to capture channel and spatial dependencies in the feature maps. This results in more discriminative features and more accurate predictions. Moreover, residual modules with skip connections can help to overcome the vanishing gradient problem. We trained the proposed model on the WHU-RS19 dataset, collated from Google Earth satellite imagery, and validated it on the UC Merced, RSSCN7, AID, and real-world satellite datasets. The experimental results show that our network uses features at different levels of detail more effectively than state-of-the-art models.
The Aesthetic Dimensions of U.S. and South Korean Responses to Web Home Pages: A Cross-Cultural Comparison
(2011-01) Faiola, Anthony; Ho, Chin-Chang; Tarrant, Mark D.; MacDorman, Karl F.
Culturally influenced preferences in website aesthetics is a topic often neglected by scholars in human-computer interaction. Kim, Lee, and Choi (2003) identified aesthetic design factors of web home pages that elicited particular responses in South Korean web users based on 13 secondary emotional dimensions. This study extends Kim et al.'s work to U.S. participants, comparing the original South Korean findings with U.S. findings. Results show that U.S. participants reliably applied translations of the emotional adjectives used in the South Korean study to the home pages. However, factor analysis revealed that the aesthetic perceptions of U.S. and South Korean participants formed different aesthetic dimensions composed of different sets of emotional adjectives, suggesting that U.S. and South Korean people perceive the aesthetics of home pages differently. These results indicate that website aesthetics can vary significantly between cultures.
The appearance, speech, and motion of synthetic humans influences our empathy toward them
(Office of the Vice Chancellor for Research, 2011-04-08) MacDorman, Karl F.; Ho, Chin-Chang; Lu, Amy S.; Mitchell, Wade J.; Patel, Himalaya; Srinivas, Preethi; Schermerhorn, Paul W.; Scheutz, Matthias
Humanoid robots and computer-generated humans can elicit responses that people usually direct toward each other. As a result these humanlike entities may stand in for human actors during experiment-driven research in the social and psychological sciences as well as in some branches of neuroscience. Such research concerns factors like facial appearance, physical embodiment, speech quality, fluidity of motion, and contingent interactivity. A goal of this research is to understand why some humanlike entities are more successful than others at eliciting people’s empathy. Pursuing this goal informs new principles for creating synthetic humans that seem more believable in narratives and narrative-based interventions.
The Audio Implicit Association Test: Human Preferences and Implicit Associations Concerning Machine Voices
Mitchell, Wade Joseph; MacDorman, Karl F.
Auditory human-machine interfaces are becoming ubiquitous. Interactive voice response systems, navigation systems, socially assistive robots, and smart houses are just a few examples of technologies that support auditory interactions. This study uses the implicit association test (IAT) to measure participants’ associative strength between human and machine voices and pleasant or unpleasant attributes. To accomplish this, the IAT needed to be validated using audio stimuli and the associative strength of secondary features of stimuli, that is, features other than their semantic content. Six IAT experiments were conducted to test the ability of the IAT to measure association strengths of the target concepts of audio stimuli and an attribute dimension in addition to target concepts of secondary features and an attribute dimension. Results support the effectiveness of an audio IAT, an IAT for secondary features, and an IAT that combines audio with secondary features. Results also show that participants had a stronger association between human voices and pleasant attributes than machine voices and pleasant attributes.
The audio/visual mismatch and the uncanny valley: an investigation using a mismatch in the human realism of facial and vocal aspects of stimuli
(2011-03-16) Szerszen, Kevin A.; MacDorman, Karl F.; Faiola, Anthony; Bolchini, Davide; Lu, Amy Shirong
Empirical research on the uncanny valley has primarily been concerned with visual elements. The current study is intended to show how manipulating auditory variables of the stimuli affect participant’s ratings. The focus of research is to investigate whether an uncanny valley effect occurs when humans are exposed to stimuli that have an incongruity between auditory and visual aspects. Participants were exposed to sets of stimuli which are both congruent and incongruent in their levels of audio/visual humanness. Explicit measures were used to explore if a mismatch in the human realism of facial and vocal aspects produces an uncanny valley effect and attempt to explain a possible cause of this effect. Results indicate that an uncanny valley effect occurs when humans are exposed to stimuli that have an incongruity between auditory and visual aspects.
The Automatic Prediction of Pleasure and Arousal Ratings
Ough, Stuart G.; MacDorman, Karl F.
Music’s allure lies in its power to stir the emotions. But the relation between the physical properties of an acoustic signal and its emotional impact remains an open area of research. This paper reports the results and possible implications of a pilot study and survey used to construct an emotion index for subjective ratings of music. The dimensions of pleasure and arousal exhibit high reliability. Eighty-five participants’ ratings of 100 song excerpts are used to benchmark the predictive accuracy of several combinations of acoustic preprocessing and statistical learning algorithms. The Euclidean distance between acoustic representations of an excerpt and corresponding emotionweighted visualizations of a corpus of music excerpts provided predictor variables for linear regression that resulted in the highest predictive accuracy of mean pleasure and arousal values of test songs. This new technique also generated visualizations that show how rhythm, pitch, and loudness interrelate to influence our appreciation of the emotional content of music.
Brand and usability in content-intensive websites
(2014-07-11) Yang, Tao; Bolchini, Davide; Pfaff, Mark; MacDorman, Karl F.; Cox, Anthony D.
Our connections to the digital world are invoked by brands, but the intersection of branding and interaction design is still an under-investigated area. Particularly, current websites are designed not only to support essential user tasks, but also to communicate an institution's intended brand values and traits. What we do not yet know, however, is which design factors affect which aspect of a brand. To demystify this issue, three sub-projects were conducted. The first project developed a systematic approach for evaluating the branding effectiveness of content-intensive websites (BREW). BREW gauges users' brand perceptions on four well-known branding constructs: brand as product, brand as organization, user image, and brand as person. It also provides rich guidelines for eBranding researchers in regard to planning and executing a user study and making improvement recommendations based on the study results. The second project offered a standardized perceived usability questionnaire entitled DEEP (design-oriented evaluation of perceived web usability). DEEP captures the perceived website usability on five design-oriented dimensions: content, information architecture, navigation, layout consistency, and visual guidance. While existing questionnaires assess more holistic concepts, such as ease-of-use and learnability, DEEP can more transparently reveal where the problem actually lies. Moreover, DEEP suggests that the two most critical and reliable usability dimensions are interface consistency and visual guidance. Capitalizing on the BREW approach and the findings from DEEP, a controlled experiment (N=261) was conducted by manipulating interface consistency and visual guidance of an anonymized university website to see how these variables may affect the university's image. Unexpectedly, consistency did not significantly predict brand image, while the effect of visual guidance on brand perception showed a remarkable gender difference. When visual guidance was significantly worsened, females became much less satisfied with the university in terms of brand as product (e.g., teaching and research quality) and user image (e.g., students' characteristics). In contrast, males' perceptions of the university's brand image stayed the same in most circumstances. The reason for this gender difference was revealed through a further path analysis and a follow-up interview, which inspired new research directions to unpack even more the nexus between branding and interaction design.
Categorization-based stranger avoidance does not explain the uncanny valley effect
(Elsevier, 2017-04) MacDorman, Karl F.; Chattopadhyay, Debaleena; BioHealth Informatics, School of Informatics and Computing
The uncanny valley hypothesis predicts that an entity appearing almost human risks eliciting cold, eerie feelings in viewers. Categorization-based stranger avoidance theory identifies the cause of this feeling as categorizing the entity into a novel category. This explanation is doubtful because stranger is not a novel category in adults; infants do not avoid strangers while the category stranger remains novel; infants old enough to fear strangers prefer photographs of strangers to those more closely resembling a familiar person; and the uncanny valley’s characteristic eeriness is seldom felt when meeting strangers. We repeated our original experiment with a more realistic 3D computer model and found no support for categorization-based stranger avoidance theory. By contrast, realism inconsistency theory explains cold, eerie feelings elicited by transitions between instances of two different, mutually exclusive categories, given that at least one category is anthropomorphic: Cold, eerie feelings are caused by prediction error from perceiving some features as features of the first category and other features as features of the second category. In principle, realism inconsistency theory can explain not only negative evaluations of transitions between real and computer modeled humans but also between different vertebrate species.
Cognitive Constraints on Using Collaborative Learning Portals: Investigating Their Effects in Oncourse CL
Taksaphan, Piyanaat; MacDorman, Karl F.
Collaborative learning portals help teachers and students attain educational objectives (Ursula et al., 1997). They also reduce repeated requests for the same information (Forbes-Pitt, 2002). An effective collaborative learning portal should promote a collaborative learning environment. It is essential to ensure the usability of learning portals. Most researchers of interface usability conduct laboratory experiments. Sellen and Norman (1992) pointed out that a laboratory environment is the least likely place to see spontaneous errors. This study investigated students using a collaborative learning portal under cognitive load. User performance with cognitive load was found to be more highly correlated with user subjective ratings of disorientation than was user performance without cognitive load. Three error patterns were observed, particularly in the cognitiveload condition. These findings indicate the importance of using cognitive load to simulate a user’s level of distraction when conducting a usability evaluation. Finally, this study proposed revising the Novice-Expert Ratio Method (NEM).
Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories
(Association for Research in Vision and Ophthalmology, 2021-04) Diel, Alexander; MacDorman, Karl F.; Human-Centered Computing, School of Informatics and Computing
In 1970, Masahiro Mori proposed the uncanny valley (UV), a region in a human-likeness continuum where an entity risks eliciting a cold, eerie, repellent feeling. Recent studies have shown that this feeling can be elicited by entities modeled not only on humans but also nonhuman animals. The perceptual and cognitive mechanisms underlying the UV effect are not well understood, although many theories have been proposed to explain them. To test the predictions of nine classes of theories, a within-subjects experiment was conducted with 136 participants. The theories’ predictions were compared with ratings of 10 classes of stimuli on eeriness and coldness indices. One type of theory, configural processing, predicted eight out of nine significant effects. Atypicality, in its extended form, in which the uncanny valley effect is amplified by the stimulus appearing more human, also predicted eight. Threat avoidance predicted seven; atypicality, perceptual mismatch, and mismatch+ predicted six; category+, novelty avoidance, mate selection, and psychopathy avoidance predicted five; and category uncertainty predicted three. Empathy's main prediction was not supported. Given that the number of significant effects predicted depends partly on our choice of hypotheses, a detailed consideration of each result is advised. We do, however, note the methodological value of examining many competing theories in the same experiment.

Browsing by Author "MacDorman, Karl F."

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