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16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023

作者： Bereg, Sergey Department of Computer Science Erik Jonsson School of Engineering and Computer Science University of Texas at Dallas Richardson United States

ISBN: (纸本)9783031496134

Two Latin squares of order n are r-orthogonal if, when superimposed, there are exactly r distinct ordered pairs. The spectrum of all values of r for Latin squares of order n is known. A Latin square A of order n is r-self-orthogonal if A and its transpose are r-orthogonal. The spectrum of all values of r is known for all orders n≠ 14. We develop randomized algorithms for computing pairs of r-orthogonal Latin squares of order n and algorithms for computing r-self-orthogonal Latin squares of order n. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Latin rectangles Latin squares r-orthogonal Latin squares

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TEACHING A DEVELOPED FIRST-YEAR FLIPPED CLASSROOM

TEACHING A DEVELOPED FIRST-YEAR FLIPPED CLASSROOM

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ASME 2023 International Mechanical engineering Congress and Exposition, IMECE 2023

作者： Stephan Thamban, P.L. Fadda, Dani Rios, Oziel Mechanical Engineering Department The Erik Jonsson School of Engineering and Computer Science The Jonsson School The University of Texas at Dallas DallasTX United States

ISBN: (纸本)9780791887653

Teaching a mechanical engineering class for the first time requires significant preparation and content development. While a flipped classroom canbe effective for student learning, course development can bequitedifficult for the faculty. However, when a course is developed in a modular flipped classroom model, faculty, teaching the course for the first time, can benefit from the developed content. They can use and make improvementsto modules based on their areas of expertise without affecting the entire course. The paper provides the perspective of a faculty member teaching a developed first year introduction to mechanical engineering course with the modular flipped classroom model. © 2023 by ASME.

关键词： Teaching

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Differential Impacts of Monologue and Conversation on Speech Emotion Recognition

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IEEE Transactions on Affective Computing 2024年第2期16卷 485-498页

作者： Chien, Woan-Shiuan Upadhyay, Shreya G. Lin, Wei-Cheng Busso, Carlos Lee, Chi-Chun National Tsing Hua University Department of Electrical Engineering Taiwan The University of Texas at Dallas Erik Jonsson School of Engineering & Commputer Science RichardsonTX United States Carnegie Mellon University Language Technologies Institute School of Computer Science PittsburghPA15213 United States

The advancement of Speech Emotion Recognition (SER) is significantly dependent on the quality of emotional speech corpora used for model training. Researchers in the field of SER have developed various corpora by adjusting design parameters to enhance the reliability of the training source. For this study, we focus on exploring communication modes of collection, specifically analyzing spontaneous emotional speech patterns gathered during conversation or monologue. While conversations are acknowledged as effective for eliciting authentic emotional expressions, systematic analyses are necessary to confirm their reliability as a better source of emotional speech data. We investigate this research question from perceptual differences and acoustic variability present in both emotional speeches. Our analyses on multi-lingual corpora show that, first, raters exhibit higher consistency for conversation recordings when evaluating categorical emotions, and second, perceptions and acoustic patterns observed in conversational samples align more closely with expected trends discussed in relevant emotion literature. We further examine the impact of these differences on SER modeling, which shows that we can train a more robust and stable SER model by using conversation data. This work provides comprehensive evidence suggesting that conversation may offer a better source compared to monologue for developing an SER model. © 2010-2012 IEEE.

关键词： Speech analysis

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Monocular Visual SLAM for Markerless Tracking Algorithm to Augmented Reality

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Intelligent Automation & Soft Computing 2023年第2期35卷 1691-1704页

作者： Tingting Yang Shuwen Jia Ying Yu Zhiyong Sui Shcool of Information and Intelligence Engineering University of Sanya572000SanyaChina Erik Jonsson School of Engineering and Computer Science The University of Texas at DallasRichardson75080-3021USA

Augmented Reality(AR)tries to seamlessly integrate virtual content into the real world of the ***,the virtual content would behave exactly like real *** necessitates a correct and precise estimation of the user’s viewpoint(or that of a camera)with regard to the virtual content’s coordinate ***,the real-time establishment of 3-dimension(3D)maps in real scenes is particularly important for augmented reality *** in this paper,we integrate Simultaneous Localization and Mapping(SLAM)technology into augmented *** research is to implement an augmented reality system without markers using the ORB-SLAM2 framework *** this paper we propose an improved method for Oriented FAST and Rotated BRIEF(ORB)feature extraction and optimized key frame selection,as well as the use of the Progressive Sample Consensus(PROSAC)algorithm for planar estimation of augmented reality implementations,thus solving the problem of increased sys-tem runtime because of the loss of large amounts of texture information in *** this paper,we get better results by comparing experiments and data ***,there are some improved methods of PROSAC algorithm which are more suitable for the detection of plane feature points.

关键词： Markerless tracking algorithm ORB-SLAM2 framework algorithm augmented reality

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Quantum spin systems: Toroidal classification and geometric duality

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Physical Review B 2024年第14期110卷 L140403页

作者： Vahid Azimi-Mousolou Anders Bergman Anna Delin Olle eriksson Manuel Pereiro Danny Thonig erik Sjöqvist Department of Applied Mathematics and Computer Science Faculty of Mathematics and Statistics Department of Physics and Astronomy Department of Applied Physics School of Engineering Sciences (SeRC) Wallenberg Initiative Materials Science for Sustainability (WISE) Wallenberg Initiative Materials Science WISE School of Science and Technology

We demonstrate a toroidal classification for quantum spin systems, revealing an intrinsic geometric duality within this structure. Through our classification and duality, we reveal that various bipartite quantum features in magnon systems can manifest equivalently in both bipartite ferromagnetic and antiferromagnetic materials, based upon the availability of relevant Hamiltonian parameters. Additionally, the results highlight the antiferromagnetic regime as an ultrafast dual counterpart to the ferromagnetic regime, both exhibiting identical capabilities for quantum spintronics and technological applications. Concrete illustrations are provided, demonstrating how splitting and squeezing types of two-mode magnon quantum correlations can be realized across ferro- and antiferromagnetic regimes.

关键词： Magnons Quantum correlations in quantum information Quantum information processing Quantum information theory Spintronics

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Video-rate AFM Imaging Using Signal Transformation Technique for Raster Scanning ⁎

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IFAC-PapersOnLine 2024年第28期58卷 600-605页

作者： E. Khodabakhshi S.O.R. Moheimani Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas Richardson TX 75080 USA

Achieving high-speed, high-resolution positioning is crucial yet challenging due to the increased sensitivity to measurement noise at higher bandwidths. This study explores a signal-transformation-based control technique for enhancing raster scanning in atomic force microscopy. An integral resonant controller is employed to augment the closed-loop bandwidth by damping the dominant mode of the scanner’s fast axis. The nanopositioner’s first resonance frequency exceeds 15kHz with the open-loop scan range exceeding 5.8 µm. A double integrator is wrapped around the damping loop to improve the tracking performance. Subsequently, the signal transformation approach (STA) is implemented within the closed-loop system, and its effectiveness is benchmarked against a signal-preshaping method. Tracking experiments were conducted across scanning frequencies ranging from 10Hz to 300 Hz, encompassing a 2µm × 2µm scan area. The root mean square (RMS) tracking error was maintained below 71nm. Experimental results underscore the technique’s effectiveness, notably achieving rapid time-lapse AFM imaging at rates up to 10 frames per second.

关键词： high-speed nanopositioner signal transformation input signal design control bandwidth measurement noise video-rate atomic force microscopy

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Social Media Governance and Fake News Detection Integrated with Artificial Intelligence Governance

Social Media Governance and Fake News Detection Integrated w...

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IEEE International Conference on Information Reuse and Integration (IRI)

作者： Bhavani Thuraisingham Teena Thomas Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas

ISBN: (数字)9798350351187

ISBN: (纸本)9798350351194

Social Media Systems such as Facebook, Instagram, and Twitter (i.e., X) are exploding. These systems need proper governance so that the users are safe and post accurate information. This paper focuses on social media governance with an emphasis on Artificial Intelligence. First, we discuss various aspects of governance of such policies, procedures and risk and then address a key topic which is detecting fake news on social media. In order for the users to be safe using social media we have to ensure that the governance aspects also include fake news detection. Many of the fake news detection techniques utilize Machine Learning (ML) and Artificial Intelligence (AI) and more recently Generative AI (GenAI) techniques. Therefore, the AI systems that implement the various techniques have to be trustworthy. That means these systems have to be secure as well as ensure fairness, privacy and integrity. Therefore, the paper will also discuss AI Governance as an integral part of Social Media Governance. Finally, to support the various applications and frameworks, both data and the cloud are critical. Large amounts of data are stored and managed by the social media systems as well as used to train the AI models. Furthermore, we need massive amounts of computing power that can be provided by the cloud. Therefore, we will also discuss data and cloud governance that provides the infrastructure for social media and AI governance.

关键词： Privacy Social networking (online) Generative AI Machine learning Data science Rough surfaces Web sites Multimedia communication Artificial intelligence Fake news

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Congestion Control of Healthcare Packet Routing in 5G Edge Computing Networks 8

Congestion Control of Healthcare Packet Routing in 5G Edge C...

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8th International Conference on engineering and Emerging Technologies, ICEET 2022

作者： Besher, Kedir Mamo Okidhain, Ian Wick, Lucas Ali, Mohammed Zamshed The University of Texas at Dallas Erik Jonsson School of Engineering and Computer Science TX United States

ISBN: (纸本)9781665491068

While Edge computing in 5G provides low latency, high-speed, and many other benefits to healthcare communication, due to excessive congestion in the Edge Network, healthcare data packets are not guaranteed to reach doctors' offices on time. This creates risk for patients' lives when treated remotely within the Edge Network. In this paper, we investigate the congestion issue in 5G Edge Computing Networks and propose an IoT sensor and SDN-based priority routing of healthcare data in the Edge Network. In our proposed system, an IoT sensor on a patient's body raises a healthcare data flag that is seen by an SDN router at a 5G macro tower antenna and provides the highest priority to the healthcare data packet while routing within the Edge Computing Networks. A prototype has been built and tested by using TI Launchpads. Test data shows that healthcare packets with IoT and SDN-based prioritization can route to doctors with an average delay of 757 times less than healthcare packets routed without IoT and SDN-based prioritization. Additionally, the proposed system saves medical diagnostic costs and, more importantly, reduces the risk of losing human lives. © 2022 IEEE.

关键词： Diagnosis

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Oral Cancer Detection Using Mobile Vision Technology

Oral Cancer Detection Using Mobile Vision Technology

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2024 IEEE-EMBS International Conference on Biomedical and Health Informatics, BHI 2024

作者： Swamikannan, Lena D. Sonawane, Akshay Bhagwan Patel, Jay S. Mani, C.S. Narayana, Lakshmi Tamil, Lakshman Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas Richardson United States Temple University Kornberg School of Dentistry Department of Oral Health Sciences Philadelphia United States Cancer Research and Relief Trust Chennai India

ISBN: (纸本)9798350351552

Oral cancer is the 13th most common cancer, affecting 380,000 people globally. The biggest challenge is that in its initial stage, cancer can go unnoticed until it reaches the most advanced, difficult-to-treat stages. Although a 90% survival rate is assured when diagnosed earlier, early-stage detection requires expensive periodic dental check-ups. Under these circumstances, converting a smartphone into a cancer screening tool has the potential to reduce cancer mortality. Mobile vision technology is a promising platform for early diagnosis of oral cancer. The aim of this research is to develop a telemedical mobile application for Oral Cancer Detection (OCD) using deep learning as a backend. This paper details experiments with various lightweight machine learning architectures, including MobileNetV3Large, which achieved an 84% accuracy, 86% sensitivity and 80% specificity on the test data. By incorporating the machine learning model into the smartphone app, users can capture or upload images for instant or offline screening, ensuring on-device processing that maintains privacy. This application promises to revolutionize oral healthcare accessibility and delivery. © 2024 IEEE.

关键词： deep neural networks mobile vision technology oral cancer

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Simultaneous Estimation of Differential Surface Parameters with Ultra-fast Feedback Loop in Scanning Tunneling Microscopy

Simultaneous Estimation of Differential Surface Parameters w...

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American Control Conference (ACC)

作者： Richa Mishra S. O. Reza Moheimani Erik Jonsson School of Engineering and Computer Science The University of Texas at Dallas Richardson TX USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

We report an enhanced feedback control method to enable the simultaneous estimation of differential surface pa-rameters di/dV and d(ln(Ri))/d8 during atomic-scale imaging of a surface with a Scanning Tunneling Microscope (STM). The proposed system enables exceptional signal-to-noise ratio (SNR) measurements of surface parameters by adding notch filters in the feedback loop. We then analyze the performance of a conventional PI controller for the ultra-fast feedback loop and demonstrate that changes in the work function (), a quantum mechanical property of the tip-sample junction, can destabilize the closed-loop system, leading to a possible tip crash. These tip crashes can compromise the STM's efficiency and reliability, thus necessitating measures to address this loss of robustness. The effectiveness of this new STM feedback control system is validated by applying it to a set of STM images obtained from a Si(100)-2×1: H passivated surface. We provide guidelines for PI tuning to optimize the system's performance.

关键词： Feedback loop Microscopy System performance Estimation Tunneling computer crashes Loss measurement

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