Valenced Media Effects On Robot-Related Attitudes And Mental Models: A Parasocial Contact Approach,
2023
Chemnitz University of Technology
Valenced Media Effects On Robot-Related Attitudes And Mental Models: A Parasocial Contact Approach, Jan-Philipp Stein, Jaime Banks
Human-Machine Communication
Despite rapid advancements in robotics, most people still only come into contact with robots via mass media. Consequently, robot-related attitudes are often discussed as the result of habituation and cultivation processes, as they unfold during repeated media exposure. In this paper, we introduce parasocial contact theory to this line of research— arguing that it better acknowledges interpersonal and intergroup dynamics found in modern human–robot interactions. Moreover, conceptualizing mediated robot encounters as parasocial contact integrates both qualitative and quantitative aspects into one comprehensive approach. A multi-method experiment offers empirical support for our arguments: Although many elements of participants’ beliefs and attitudes …
Triggered By Socialbots: Communicative Anthropomorphization Of Bots In Online Conversations,
2023
University of Helsinki
Triggered By Socialbots: Communicative Anthropomorphization Of Bots In Online Conversations, Salla-Maaria Laaksonen, Kaisa Laitinen, Minna Koivula, Tanja Sihvonen
Human-Machine Communication
This article examines communicative anthropomorphization, that is, assigning of humanlike features, of socialbots in communication between humans and bots. Situated in the field of human-machine communication, the article asks how socialbots are devised as anthropomorphized communication companions and explores the ways in which human users anthropomorphize bots through communication. Through an analysis of two datasets of bots interacting with humans on social media, we find that bots are communicatively anthropomorphized by directly addressing them, assigning agency to them, drawing parallels between humans and bots, and assigning emotions and opinions to bots. We suggest that socialbots inherently have anthropomorphized characteristics and …
Human-Ai Teaming During An Ongoing Disaster: How Scripts Around Training And Feedback Reveal This Is A Form Of Human-Machine Communication,
2023
The University of Texas at Austin
Human-Ai Teaming During An Ongoing Disaster: How Scripts Around Training And Feedback Reveal This Is A Form Of Human-Machine Communication, Keri K. Stephens, Anastazja G. Harris, Amanda L. Hughes, Carolyn E. Montagnolo, Karim Nader, S. Ashley Stevens, Tara Tasuji, Yifan Xu, Hemant Purohit, Christopher W. Zobel
Human-Machine Communication
Humans play an integral role in identifying important information from social media during disasters. While human annotation of social media data to train machine learning models is often viewed as human-computer interaction, this study interrogates the ontological boundary between such interaction and human-machine communication. We conducted multiple interviews with participants who both labeled data to train machine learning models and corrected machine-inferred data labels. Findings reveal three themes: scripts invoked to manage decision-making, contextual scripts, and scripts around perceptions of machines. Humans use scripts around training the machine—a form of behavioral anthropomorphism—to develop social relationships with them. Correcting machine-inferred data …
Chatgpt, Lamda, And The Hype Around Communicative Ai: The Automation Of Communication As A Field Of Research In Media And Communication Studies,
2023
University of Bremen, Germany
Chatgpt, Lamda, And The Hype Around Communicative Ai: The Automation Of Communication As A Field Of Research In Media And Communication Studies, Andreas Hepp, Wiebke Loosen, Stephan Dreyer, Juliane Jarke, Sigrid Kannengießer, Christian Katzenbach, Rainer Malaka, Michaela Pfadenhauer, Cornelius Puschmann, Wolfgang Schulz
Human-Machine Communication
The aim of this article is to more precisely define the field of research on the automation of communication, which is still only vaguely discernible. The central thesis argues that to be able to fully grasp the transformation of the media environment associated with the automation of communication, our view must be broadened from a preoccupation with direct interactions between humans and machines to societal communication. This more widely targeted question asks how the dynamics of societal communication change when communicative artificial intelligence—in short: communicative AI—is integrated into aspects of societal communication. To this end, we recommend an approach that …
Disentangling Two Fundamental Paradigms In Human-Machine Communication Research: Media Equation And Media Evocation,
2023
University of Amsterdam
Disentangling Two Fundamental Paradigms In Human-Machine Communication Research: Media Equation And Media Evocation, Margot J. Van Der Goot, Katrin Etzrodt
Human-Machine Communication
In this theoretical paper, we delineate two fundamental paradigms in how scholars conceptualize the nature of machines in human-machine communication (HMC). In addition to the well-known Media Equation paradigm, we distinguish the Media Evocation paradigm. The Media Equation paradigm entails that people respond to machines as if they are humans, whereas the Media Evocation paradigm conceptualizes machines as objects that can evoke reflections about ontological categories. For each paradigm, we present the main propositions, research methodologies, and current challenges. We conclude with theoretical implications on how to integrate the two paradigms, and with a call for mixed-method research that includes …
Sovia: Sonification Of Visual Interactive Art,
2023
Santa Clara University
Sovia: Sonification Of Visual Interactive Art, Lauryn Gayhardt
Computer Science and Engineering Master's Theses
Therapeutic Computational Creativity is an emerging domain that challenges us to explore applications of Computational Creativity systems to mental health and wellness. This work presents SOVIA, an interactive system that endows Claude Monet’s art with responsive auditory experiences. SOVIA uses computer vision trained on Monet’s artwork to take the user “into the painting.'' When the user interacts with a digital version of Monet's landscapes, their mouse positions are mapped to sounds that artistically represent the objects that the user is currently exploring in the art. These interactive musical journeys have the potential to make classical art more captivating for modern …
Ecg Recordings As Predictors Of Very Early Autism Likelihood: A Machine Learning Approach,
2023
University of South Carolina - Columbia
Ecg Recordings As Predictors Of Very Early Autism Likelihood: A Machine Learning Approach, Deepa Tilwani, Jessica Bradshaw, Amit Sheth, Christian O'Reilly
Publications
In recent years, there has been a rise in the prevalence of autism spectrum disorder (ASD). The diagnosis of ASD requires behavioral observation and standardized testing completed by highly trained experts. Early intervention for ASD can begin as early as 1–2 years of age, but ASD diagnoses are not typically made until ages 2–5 years, thus delaying the start of intervention. There is an urgent need for non-invasive biomarkers to detect ASD in infancy. While previous research using physiological recordings has focused on brain-based biomarkers of ASD, this study investigated the potential of electrocardiogram (ECG) recordings as an ASD biomarker …
Generation Of Vector Vortex Wave
Modes In Cylindrical Waveguides,
2023
Florida International University
Generation Of Vector Vortex Wave Modes In Cylindrical Waveguides, Md Khadimul Islam, Pawan Gaire, Arjuna Madanayake, Shubhendu Bhardwaj
Department of Electrical and Computer Engineering: Faculty Publications
In this paper, we propose a method to generate Vector Vortex Modes (VVM) inside a metallic cylindrical waveguide at microwave frequencies and demonstrate the experimental validation of the concept. Vector vortex modes of EM waves can carry both spin and orbital angular momentum as they propagate within a tubular medium. The existence of such waves in tubular media can be beneficial to wireless communication in such structures. These waves can carry different orbital angular momentum and spin angular momentum, and therefore, they feature the ability to carry multiple orthogonal modes at the same frequency due to spatial structure of the …
List Of 121 Papers Citing One Or More Skin Lesion Image Datasets,
2023
Technological University Dublin
List Of 121 Papers Citing One Or More Skin Lesion Image Datasets, Neda Alipour
Other resources
No abstract provided.
Optimizing High-Performance Computing Design: The Impacts Of Bandwidth And Topology Across Workloads For Distributed Shared Memory Systems,
2023
University of New Mexico
Optimizing High-Performance Computing Design: The Impacts Of Bandwidth And Topology Across Workloads For Distributed Shared Memory Systems, Jonathan A. Milton
Electrical and Computer Engineering ETDs
With the complexity of high-performance computing designs continuously increasing, the importance of evaluating with simulation also grows. One of the key design aspects is the network architecture; topology and bandwidth greatly influence the overall performance and should be optimized. This work uses simulations written to run in the Structural Simulation Toolkit software framework to evaluate a variety of architecture configurations, identify the optimal design point based on expected workload, and evaluate the changes with increased scale. The results show that advanced topologies outperform legacy architectures justifying the additional design complexity; and that after a certain point increasing the bandwidth provides …
Numerical Design And Optimization Of Near-Infrared Band- Pass Filter,
2023
Centre of Excellence in Solid State Physics, University of the Punjab, Lahore, 54590, Pakistan
Numerical Design And Optimization Of Near-Infrared Band- Pass Filter, Hafiza Syeeda Faiza, Ghazi Aman Nowsherwan, Basem A. Abu Izneid, Muhammad Azhar, Saira Riaz, Syed Sajjad Hussain, Saira Ikram, Mohsin Khan, Shahzad Naseem, Mohammad Kanan, Ibrahim M. Mansour
Applied Mathematics & Information Sciences
Band-pass filters functioning in the near-infrared (IR) range are desired for laser technology, multi-photon fluorescence, and IR imaging applications. In this study, we have designed four band-pass filters in the near Infrared spectrum (900-1200 nm) by vertically stacking different high and low-index materials. The band-pass filters are modelled by Essential Macleod software with different thicknesses. The layer’s thicknesses were optimized in such a way to provide the negligible reflectance and maximum transmission on the front side. All the simulated band-pass filters exhibit high transmittance, but TiO2/Al2O3 and Ta2O5/Al2O3 outperforms other modelled structure in terms of performance due to the better …
Unveiling The Digital Shadows: Cybersecurity And The Art Of Digital Forensics,
2023
Boise State University
Unveiling The Digital Shadows: Cybersecurity And The Art Of Digital Forensics, Derek Beardall
Cyber Operations and Resilience Program Graduate Projects
This paper navigates the symbiotic relationship between cybersecurity and digital forensics, exploring the profound role of digital forensic methodologies in addressing cyber incidents. Beginning with foundational definitions and historical evolution, this study delves into diverse types of methodologies and their applications across law enforcement and cybersecurity domains. The mechanics of cyber incident response illuminates the strategic orchestration of digital forensic methodologies. Amidst triumphs, challenges emerge from the shadows: swift threat evolution, digital ecosystem complexity, standardization gaps, resource limitations, and legal intricacies. Best practices guide experts through this intricate terrain, culminating in an enhanced understanding of the inseparable bond between cybersecurity …
Evaluating An Mhealth Application For Cancer Survivors With Disabilities Through Usability Testing,
2023
Northeastern Illinois University
Evaluating An Mhealth Application For Cancer Survivors With Disabilities Through Usability Testing, Kevin Baez
University Honors Program Senior Projects
The effect of cancer treatment can cause difficulties in a cancer survivor's life due to the risk of attaining a long-term disability which has potential negative cognitive, psychological, physical, and social consequences. Furthermore, post-treatment support has been shown to be severely limited, leaving many to deal with new obstacles and struggles on their own. With no real support system in place, cancer survivors with disabilities can be lost during post-cancer transition. However, mHealth interventions have been proven to effectively aid users in dealing with various health issues. We aim to support and empower cancer survivors through an application called, WeCanManage. …
Near-Optimal Motion Planning Algorithms Via A Topological And Geometric Perspective,
2023
University at Albany, State University of New York
Near-Optimal Motion Planning Algorithms Via A Topological And Geometric Perspective, Aakriti Kumari Upadhyay
Computer Science Theses & Dissertations
Motion planning is a fundamental problem in robotics, which involves finding a path for an autonomous system, such as a robot, from a given source to a destination while avoiding collisions with obstacles. The properties of the planning space heavily influence the performance of existing motion planning algorithms, which can pose significant challenges in handling complex regions, such as narrow passages or cluttered environments, even for simple objects. The problem of motion planning becomes deterministic if the details of the space are fully known, which is often difficult to achieve in constantly changing environments. Sampling-based algorithms are widely used among …
Well-Conditioned T-Matrix Formulation For Scattering By A Dielectric Obstacle,
2023
TÜBİTAK
Well-Conditioned T-Matrix Formulation For Scattering By A Dielectric Obstacle, Murat Enes Hati̇poğlu, Fati̇h Di̇kmen
Turkish Journal of Electrical Engineering and Computer Sciences
The classic formulation of the extended boundary condition method is revisited to inject the regularization operators for the unknown coefficients of the eigen-function expansions for the travelling and standing waves throughout the dielectric scatterer. It is shown that, using the new definitions, the existing algorithm of the scattering field calculation can be kept the same for its well-conditioned version. This is exemplified for scalar 2D problems for both TM and TE polarization under illumination of a line source. The condition numbers of the matrix operators in the new version of the algorithm are drastically reduced when the regularization interfaces are …
Lightweight Deep Neural Network Models For Electromyography Signal Recognition For Prosthetic Control,
2023
TÜBİTAK
Lightweight Deep Neural Network Models For Electromyography Signal Recognition For Prosthetic Control, Ahmet Mert
Turkish Journal of Electrical Engineering and Computer Sciences
In this paper, lightweight deep learning methods are proposed to recognize multichannel electromyography (EMG) signals against varying contraction levels. The classical machine learning, and signal processing methods namely, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), root mean square (RMS), and waveform length (WL) are adopted to convolutional neural network (CNN), and long short-term memory neural network (LSTM). Eight-channel recordings of nine amputees from a publicly available dataset are used for training and testing the proposed models considering prosthetic control strategies. Six class hand movements with three contraction levels are applied to WL and RMS-based feature extraction. After that, they …
A Practical Framework For Early Detection Of Diabetes Using Ensemble Machine Learning Models,
2023
TÜBİTAK
A Practical Framework For Early Detection Of Diabetes Using Ensemble Machine Learning Models, Qusay Saihood, Emrullah Sonuç
Turkish Journal of Electrical Engineering and Computer Sciences
The diagnosis of diabetes, a prevalent global health condition, is crucial for preventing severe complications. In recent years, there has been a growing effort to develop intelligent diagnostic systems for diabetes utilizing machine learning (ML) algorithms. Despite these efforts, achieving high accuracy rates using such systems remains a significant challenge. Recent advancements in ensemble ML methods offer promising opportunities for early detection of diabetes, as they are known to be faster and more cost-effective than traditional approaches. Therefore, this study proposes a practical framework for diagnosing diabetes that involves three stages. The data preprocessing stage encompasses several crucial tasks, including …
Improving Unet Segmentation Performance Using An Ensemble Model In Images Containing Railway Lines,
2023
TÜBİTAK
Improving Unet Segmentation Performance Using An Ensemble Model In Images Containing Railway Lines, Mehmet Sevi̇, İlhan Aydin
Turkish Journal of Electrical Engineering and Computer Sciences
This study aims to make sense of the autonomous system and the railway environment for railway vehicles. For this purpose, by determining the railway line, information about the general condition of the line can be obtained along the way. In addition, objects such as pedestrian crossings, people, cars, and traffic signs on the line will be extracted. The rails and the rail environment in the images will be segmented with a semantic segmentation network. In order to ensure the safety of rail transport, computer vision, and deep learning-based methods are increasingly used to inspect railway tracks and surrounding objects. In …
Enhancing And Securing Wireless Medical Technology For Diagnosis And Treatment Of Lower Urinary Tract Dysfunction,
2023
University of South Florida
Enhancing And Securing Wireless Medical Technology For Diagnosis And Treatment Of Lower Urinary Tract Dysfunction, Farhath Zareen
USF Tampa Graduate Theses and Dissertations
Lower urinary tract dysfunction (LUTD) is a debilitating medical condition that affects millions of individuals worldwide. Urodynamics is the current gold standard for diagnosing LUTD but uses non-physiologically fast, retrograde cystometric filling to obtain a brief snapshot of bladder function. Current state-of-the-art research in bladder monitoring includes ambulatory urodynamics using wireless implantable devices to evaluate bladder function during natural filling for long-term monitoring. However, there are various challenges and limitations to this multi-sensor approach. This research focuses on developing frameworks for automated event detection, data analysis, and optimization of long-term bladder recordingsto improve the diagnosis and treatment of LUTD. In …
Exploring The Impact Of Students Demographic Attributes On Performance Prediction Through Binary Classification In The Kdp Model,
2023
University of Energy and Natural Resources,Ghana
Exploring The Impact Of Students Demographic Attributes On Performance Prediction Through Binary Classification In The Kdp Model, Issah Iddrisu, Peter Appiahene, Obed Appiah, Inusah Fuseini
Knowledge Engineering and Data Science
During the course of this research, binary classification and the Knowledge Discovery Process (KDP) were used. The experimental and analytical capabilities of Rapid Miner's 9.10.010 instructional environment are supported by five different classifiers. Included in the analysis were 2334 entries, 17 characteristics, and one class variable containing the students' average score for the semester. There were twenty experiments carried out. During the studies, 10-fold cross-validation and ratio split validation, together with bootstrap sampling, were used. It was determined whether or not to use the Random Forest (RF), Rule Induction (RI), Naive Bayes (NB), Logistic Regression (LR), or Deep Learning (DL) …
