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Research Square 2021年

作者： Barron, Alexander T.J. Bollen, Johan Luddy School of Informatics Computing & Engineering Indiana University Bloomington United States Cognitive Science Program Indiana University Bloomington United States

Mass communication over social media can drive rapid changes in our sense of collective identity. Hashtags in particular have acted as powerful social coordinators[1], playing a key role in organizing social movements like the Gezi park protests, Occupy Wall Street, #metoo, and #blacklivesmatter[2, 3, 4]. Here we quantify collective identity from the use of hashtags as self-labels in over 85,000 actively-maintained Twitter user profiles spanning 2017-2019. Collective identities emerge from a graph model of individuals’ overlapping self-labels, producing a hierarchy of graph clusters. Each cluster is bound together and characterized semantically by specific hashtags key to its formation. We define and apply two information-theoretic measures to quantify the strength of identities in the hierarchy. First we measure collective identity coherence to determine how integrated any identity is from local to global scales. Second, we consider the conspicuousness of any identity given its vocabulary versus the global identity map. Our work reveals a rich landscape of online identity emerging from the hierarchical alignment of uncoordinated self-labeling actions. © 2021, CC BY.

关键词： User profile

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An Analysis Method for Metric-Level Switching in Beat Tracking

arXiv

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arXiv 2022年

作者： Chiu, Ching-Yu Müller, Meinard Davies, Matthew E.P. Su, Alvin Wen-Yu Yang, Yi-Hsuan Graduate Program of Multimedia Systems and Intelligent Computing National Cheng Kung University Academia Sinica Taiwan International Audio Laboratories Erlangen Germany Department of Informatics Engineering Centre for Informatics and Systems The University of Coimbra University of Coimbra Portugal Department of CSIE National Cheng Kung University Taiwan Taiwan AI Labs Taiwan

For expressive music, the tempo may change over time, posing challenges to tracking the beats by an automatic model. The model may first tap to the correct tempo, but then may fail to adapt to a tempo change, or switch between several incorrect but perceptually plausible ones (e.g., half- or double-tempo). Existing evaluation metrics for beat tracking do not reflect such behaviors, as they typically assume a fixed relationship between the reference beats and estimated beats. In this paper, we propose a new performance analysis method, called annotation coverage ratio (ACR), that accounts for a variety of possible metric-level switching behaviors of beat trackers. The idea is to derive sequences of modified reference beats of all metrical levels for every two consecutive reference beats, and compare every sequence of modified reference beats to the subsequences of estimated beats. We show via experiments on three datasets of different genres the usefulness of ACR when being utilized alongside existing metrics, and discuss the new insights that can be gained. © 2022, CC BY.

关键词： Taps

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Evolutionary Trends of Intelligent IoT Networking for Commercial and Industrial Use Cases

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中国通信（英文版） 2023年第8期20卷前插1-前插4页

作者： Shuai Han Rong Bo Nadra Guizani Sai Xu Ruoyu Su Liang Xiao Cheng Li Department of Electronics and Communication Engineering Harbin Institute of Technology Communications Research Centre Canada Engineering program and the computing Research Association School of Cybersecurity Northwestern Polytechnical UniversityXi'anChina Nanjing University of Posts and Telecommunications Department of Informatics and Communication Engineering Xiamen Univer- sityFujianChina Department of Electrical and Computer Engineering of Memorial University St.John'sCanada

The intelligent Internet of Things(IIoT)is one of the key enablers for the digital transformation of traditional industries towards Industry *** services have diversified requirements due to the nature of their commercial and industrial *** various devices in IIoT environments have their unique properties in terms of resource limita-tions,network lifetimes,and application Quali-ty-of-Service(QoS)requirements which affect the performance under such applications ***,IoT devices typically have constrained power,storage,computing,high latency,massive multiple access and communications resources which limit the performance of IIoT for commercial and industrial Use *** the other hand,devices used in IIoT were not initially designed with security in mind and they had been considered *** response to the above challenges,domestic and foreign scholars have gradually carried out research on network architecture,collaborative scheduling strategy,energy supply technology,resource man-agement,and ***,the research on IIoT is still in its infancy,and has not yet formed comprehen-sive and systematic theoretical methods and technical standards.

关键词： Special issues and sections Internet of Things Intelligent systems Commercialization Requirements engineering Industrial engineering

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Critical Factors of Immersive Learning in Higher Education: A Systematic Literature Review

Critical Factors of Immersive Learning in Higher Education: ...

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International Conference on ICT For Smart Society (ICISS)

作者： Sunardi Meyliana Arief Ramadhan Yusep Rosmansyah Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information System Departement School of information system Bina Nusantara University Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of electrical engineering and informatics Bandung Institute of Technology Bandung Indonesia

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. Academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education.

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Anterior Cruciate Ligament Classification in Knee MRI using Automated Pseudo-Masking

Anterior Cruciate Ligament Classification in Knee MRI using ...

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Medical Imaging 2023: Computer-Aided Diagnosis

作者： Dadsetan, Saba Albers, Marcio Weinstock, Allison Musahl, Volker Kitamura, Gene Arefan, Dooman Wu, Shandong Intelligent Systems Program School of Computing and Information University of Pittsburgh PittsburghPA15213 United States Department of Radiology School of Medicine University of Pittsburgh PittsburghPA15213 United States Department of Biomedical Informatics School of Medicine University of Pittsburgh PittsburghPA15213 United States Department of Bioengineering School of Engineering University of Pittsburgh PittsburghPA15213 United States Department of Orthopedic Surgery School of Medicine University of Pittsburgh PittsburghPA15213 United States Department of Radiology Loma Linda University Medical Center Loma LindaCA92354 United States

ISBN: (纸本)9781510660359

Anterior cruciate ligament (ACL) is one of the most common injuries associated with sports. Knee osseous morphology can play a role in increased knee instability. Our hypothesis is that the morphological features of the knee, as seen in knee osseous morphology, can contribute to increased knee instability and, thus, increase the likelihood of ACL tear. To test this relationship, it is necessary to segment the femur and tibia bones and extract relevant imaging features. However, manual annotation of 3D medical images, such as on magnetic resonance imaging (MRI) scans, can be a time-consuming and challenging task. In this work, we propose an automated pipeline for creating pseudo-masks of the femur and tibia bones in knee MRI. Our approach involves unsupervised segmentation and deep learning models to classify ACL integrity (intact or torn). Our results demonstrate a high agreement between the automated pseudo-masks and a radiologist's manual segmentation, which also leads to comparable AUC values for the ACL integrity classification. © 2023 SPIE.

关键词： Magnetic resonance imaging

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Role of simulation models in understanding the generation of behavior in C. elegans

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Current Opinion in Systems Biology 2019年 13卷 93-101页

作者： Izquierdo, Eduardo J. Cognitive Science Program School of Informatics Computing and Engineering Indiana University United States

There has been a proliferation of studies using simulation models to achieve a system-level understanding of behavior in Caenorhabditis elegans. Here I discuss the different aims of these modeling approaches and review examples of each in the context of locomotion and spatial navigation in the worm. I argue that as the focus shifts from understanding sensorimotor transformations to understanding neuromechanical instantiations for how behaviors are generated, simulation models will become a more integral part of the experiment–theory cycle. I discuss the insights that simulation modeling provides that complement information obtained from experimental discovery methods. © 2018 Elsevier Ltd

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Parametric modeling and fabrication as capturing knowledge: A design computation workflow for historical brick surfaces in Anatolia

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Digital Applications in Archaeology and Cultural Heritage 2024年 32卷

作者： Altun, Sevgi Özkar, Mine İstanbul Technical University Graduate School Department of Informatics Architectural Design Computing Graduate Program Harbiye Mahallesi Taşkışla Caddesi No:2 Şişli İstanbul 34367 Turkey İstanbul Technical University Faculty of Architecture Department of Architecture Harbiye Mahallesi Taşkışla Caddesi No:2 Şişli İstanbul 34367 Turkey

Using computational design tools to create meaningful digital representations of architectural heritage delivers both challenges and opportunities. On one hand, digital tools aid the fast and detailed three-dimensional modeling of architectural elements. On the other hand, these models do not sufficiently document the materials and techniques of making. This research proposes a workflow to use computational design tools to analyze historic Anatolian brick elements while integrating their geometry, construction, and part-whole relations in parametric modeling and robotic fabrication processes. Our approach demonstrates a correlation between the design of the surface pattern and material application in historical bricklaying. The proposed workflow can be applied to formalize implicit design knowledge, integrating it into the digital environment and numeric control production codes. This holistic approach to heritage prioritizes both the tangible aspects, such as form and material, and intangible aspects such as the knowledge base of applied techniques. © 2023 Elsevier Ltd

关键词： Architectural heritage documentation Historical bricklaying Robotic fabrication Shape grammars

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The Application of Conjugate Gradient Method to Motion Control of Robotic Manipulators

The Application of Conjugate Gradient Method to Motion Contr...

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Innovative Manufacturing, Mechatronics and Materials Forum, iM3F 2021

作者： Sulaiman, Ibrahim M. Malik, Maulana Giyarti, Wed Mamat, Mustafa Ibrahim, Mohd Asrul Hery Ahmad, Muhammad Zaini School of Quantitative Sciences Universiti Utara Malaysia Kedah Sintok06010 Malaysia Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Terengganu Kuala Terennganu21300 Malaysia Department of Mathematics Universitas Indonesia Depok Indonesia Mathematics Education Study Program Universitas Islam Negeri Sunan Kalijaga Depok Indonesia Faculty of Entrepreneurship and Business Universiti Malaysia Kelantan Kota Bhar Malaysia Institute of Engineering Mathematics Universiti Malaysia Perlis Kangar Malaysia

ISBN: (纸本)9789811920943

Many industrial and engineering problems are transformed into optimization problems and solved using various numerical based methods. One of the frequently used method is the Steepest descent algorithm which converge to the solution in only one iteration, given the current point and provided the quadratic function is positive definite. However, this method is not suitable for large scale functions because of lack of gradient information and high computational cost. This study aims to suggest a new conjugate gradient algorithm for motion control of robotic manipulators and unconstrained optimization models. The convergence result of the new algorithm would be discussed under some suitable conditions. Computational simulations are carried out on the discrete-time kinematics equation of a two-joint planar robot manipulator to illustrates the efficiency of the algorithm. The algorithm was further extended to unconstrained optimization problems in addition to motion control of robotic manipulators. Preliminary results prove that the new algorithm is efficient compared to the existing CG algorithm. The comparisons are made using the set of 50 standard benchmark functions including number of iterations and CPU time. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Flexible manipulators

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Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer

Predicting Microsatellite Instability from Histology Images ...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Yun-Chi Chen Tung Chao Wimaya Nitya Phandita Tzu-Yu Sun Huai-Zhi Wang Yi-Hsien Hsieh Le-Yin Hsu Che Lin Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University (NTU) Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan Data Science Degree Program NTU Taipei Taiwan Department of Electrical Engineering NTU Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan Smart Medicine and Health Informatics Program NTU Taipei Taiwan

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients.

关键词： Attention mechanisms Histopathology Computational modeling Precision medicine Small satellites Immunotherapy Colorectal cancer Predictive models Transformers Genetics

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HAAQI-Net: A Non-intrusive Neural Music Audio Quality Assessment Model for Hearing Aids

arXiv

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arXiv 2024年

作者： Wisnu, Dyah A.M.G. Rini, Stefano Zezario, Ryandhimas E. Wang, Hsin-Min Tsao, Yu Taiwan International Graduate Program—Social Network and Human Centered Computing Institute of Information Science Academia Sinica Taipei Taiwan College of Informatics National Chengchi University Taipei Taiwan Institute of Communications Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan Institute of Information Science Academia Sinica Taipei Taiwan

This paper introduces HAAQI-Net, a non-intrusive deep learning-based music audio quality assessment model for hearing aid users. Unlike traditional methods like the Hearing Aid Audio Quality Index (HAAQI) that require intrusive reference signal comparisons, HAAQI-Net offers a more accessible and computationally efficient alternative. By utilizing a Bidirectional Long Short-Term Memory (BLSTM) architecture with attention mechanisms and features extracted from the pre-trained BEATs model, it can predict HAAQI scores directly from music audio clips and hearing loss patterns. Experimental results demonstrate HAAQI-Net’s effectiveness, achieving a Linear Correlation Coefficient (LCC) of 0.9368, a Spearman’s Rank Correlation Coefficient (SRCC) of 0.9486, and a Mean Squared Error (MSE) of 0.0064 and inference time significantly reduces from 62.52 to 2.54 seconds. To address computational overhead, a knowledge distillation strategy was applied, reducing parameters by 75.85% and inference time by 96.46%, while maintaining strong performance (LCC: 0.9071, SRCC: 0.9307, MSE: 0.0091). To expand its capabilities, HAAQI-Net was adapted to predict subjective human scores like the Mean Opinion Score (MOS) through fine-tuning. This adaptation significantly improved prediction accuracy, validated through statistical analysis. Furthermore, the robustness of HAAQI-Net was evaluated under varying Sound Pressure Level (SPL) conditions, revealing optimal performance at a reference SPL of 65 dB, with accuracy gradually decreasing as SPL deviated from this point. The advancements in subjective score prediction, SPL robustness, and computational efficiency position HAAQI-Net as a scalable solution for music audio quality assessment in hearing aid applications, contributing to efficient and accurate models in audio signal processing and hearing aid technology. Copyright © 2024, The Authors. All rights reserved.

关键词： Mean square error

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