Intelligent Technologies for Interactive Entertainment : 12th EAI international conference, INTETAIN 2020, virtual event, December 12-14, 2020 : Proceedings / by INTETAIN (Conference) (12th : 2020 : Online), organiser 642911, Shaghaghi, Navid, editor 642912, Lamberti, Fabrizio, editor 642913, Beams, Brian, editor 642914, Shariatmadari, Reza, editor 642915, Amer, Ahmed, editor 642916

“…The 19 full papers were selected from 49 submissions and present novel, and innovative work in areas including in art, science, design and engineering regarding computer-based systems or devices that provide intelligent human interaction or entertainment experience. …”

PlaneSDF-Based Change Detection for Long-Term Dense Mapping by Fu, Jiahui, Lin, Chengyuan, Taguchi, Yuichi, Cohen, Andrea, Zhang, Yifu, Mylabathula, Stephen, Leonard, John J.

Subjects: “…Artificial Intelligence…”
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Stretchable motion memory devices based on mechanical hybrid materials by Liu, Yaqing, Liu, Zhiyuan, Zhu, Bowen, Yu, Jiancan, He, Ke, Leow, Wan Ru, Wang, Ming, Chandran, Bevita K., Qi, Dianpeng, Wang, Hong, Chen, Geng, Xu, Cai, Chen, Xiaodong

“…Inspired by the fact that humans can monitor and memorize various body motions, a motion memory device is developed to mimic this biological process. …”
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Toward human-centered automated driving: a novel spatiotemporal vision transformer-enabled head tracker by Hu, Zhongxu, Zhang, Yiran, Xing, Yang, Zhao, Yifan, Cao, Dongpu, Lv, Chen

“…Accurate dynamic driver head pose tracking is of great importance for driver–automotive collaboration, intelligent copilot, head-up display (HUD), and other human-centered automated driving applications. …”
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Human-AI Co-Dancing: Evolving Cultural Heritage through Collaborative Choreography with Generative Virtual Characters by Pataranutaporn, Pat, Mano, Phoomparin, Bhongse-Tong, Piyaporn, Chongchadklang, Tas, Archiwaranguprok, Chayapatr, Hantrakul, Lamtharn, Eaimsa-ard, Jirach, Maes, Pattie, Klunchun, Pichet

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Creativity in Intelligent Technologies and Data Science : 4th International Conference, CIT&DS 2021, Volgograd, Russia, September 20-23, 2021 : Proceedings / by CIT&DS (Conference) (4th : 2021 : Volgograd, Russia), organiser 642924, Kravets, Alla G., editor 642925, Shcherbakov, Maxim, editor 642926, Parygin, Danila, editor 642927, Groumpos, Peter P., editor 642928

“…The papers are organized in the following topical sections: Artificial intelligence and deep learning technologies: knowledge discovery in patent and open sources; open science semantic technologies; IoT and computer vision in knowledge-based control; Cyber-physical systems and big data-driven control: pro-active modeling in intelligent decision making support; design creativity in CASE/CAI/CAD/PDM; intelligent technologies in urban design and computing; Intelligent technologies in social engineering: data science in social networks analysis and cyber security; educational creativity and game-based learning; intelligent assistive technologies: software design and application.…”

Data-driven brain emotional learning-based intelligent controller-PID control of MIMO systems based on a modified safe experimentation dynamics algorithm by Shahrizal, Saat, Mohd Ashraf, Ahmad, Mohd Riduwan, Ghazali

“…The MSEDA was used to tune the brain emotional learning-based intelligent controller (BELBIC) together with a proportional-integral-derivative (PID) controller. …”
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Connecting genomic results for psychiatric disorders to human brain cell types and regions reveals convergence with functional connectivity by Yao, S, Harder, A, Darki, F, Chang, Y, Li, A, Nikouei, K, Volpe, G, Lundström, JN, Zeng, J, Wray, NR, Lu, Y, Sullivan, PF, Hjerling-Leffler, J

“…By integrating genomic insights from genome-wide association studies with a comprehensive single-cell transcriptomic atlas of the adult human brain, we prioritized specific neuronal clusters significantly enriched for the SNP-heritabilities for schizophrenia, bipolar disorder, and major depressive disorder along with intelligence, education, and neuroticism. …”

A phenotype-based AI pipeline outperforms human experts in differentially diagnosing rare diseases using EHRs by Mao, X, Huang, Y, Jin, Y, Wang, L, Chen, X, Liu, H, Yang, X, Xu, H, Luan, X, Xiao, Y, Feng, S, Zhu, J, Zhang, X, Jiang, R, Zhang, S, Chen, T

“…To address these challenges, we introduce PhenoBrain, a fully automated artificial intelligence pipeline. PhenoBrain utilizes a BERT-based natural language processing model to extract phenotypes from clinical texts in EHRs and employs five new diagnostic models for differential diagnoses of rare diseases. …”

Virtual human influencers in live streaming commerce on social media platforms: exploring parasocial interactions with consumers in China by Yao, Lu, Tugiman, Nursafwah, Salehhuddin Sharipudin, Mohamad-Noor

“…The research explores the expanding role of virtual human influencers (VHIs) in digital marketing via parasocial interactions (PSIs) in live streaming commerce, with a focus on Chinese consumers. …”
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ViObject: Harness Passive Vibrations for Daily Object Recognition with Commodity Smartwatches by Chen, Wenqiang, Lin, Shupei, Peng, Zhencan, Parizi, Farshid Salemi, Heo, Seongkook, Patel, Shwetak, Matusik, Wojciech, Zhao, Wei, Stankovic, John

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Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data by Xu, Xuhai, Yao, Bingsheng, Dong, Yuanzhe, Gabriel, Saadia, Yu, Hong, Hendler, James, Ghassemi, Marzyeh, Dey, Anind K., Wang, Dakuo

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Human Centered Computing : 66th International Conference, HCC 2020, Virtual Event, December 14-15, 2020 : Revised Selected Papers / by HCC (Conference : Human Centered Computing) (6th : 2020 : Online), organiser 642973, Zu, Qiaohong, editor 642970, Tang, Yong, editor 642971, Mladenović, Vladimir, editor 642972

“…This book constitutes thoroughly reviewed, revised and selected papers from the 6th International Conference on Human Centered Computing, HCC 2020, held in virtually, due to COVID- 19, in December 2020. …”

Judging facts, judging norms: Training machine learning models to judge humans requires a modified approach to labeling data by Balagopalan, Aparna, Madras, David, Yang, David H., Hadfield-Menell, Dylan, Hadfield, Gillian K., Ghassemi, Marzyeh

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Advancing health coaching: a comparative study of large language model and health coaches by Ong, Qi Chwen, Ang, Chin-Siang, Chee, Davidson Zun Yin, Lawate, Ashwini, Sundram, Frederick, Dalakoti, Mayank, Pasalic, Leonardo, To, Daniel, Erlikh Fox, Tatiana, Bojic, Iva, Car, Josip

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"How fancy you are to make us use your fancy tool": Coordinating Individuals' Tool Preference over Group Boundaries by Zhang, Qianqia (Queenie), Park, Soya, Muller, Michael, Karger, David R.

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Artificial Neural Network Language Models Predict Human Brain Responses to Language Even After a Developmentally Realistic Amount of Training by Hosseini, Eghbal A., Schrimpf, Martin, Zhang, Yian, Bowman, Samuel, Zaslavsky, Noga, Fedorenko, Evelina

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Attention based graph Bi-LSTM networks for traffic forecasting by Zhao, Han, Yang, Huan, Wang, Yu, Wang, Danwei, Su, Rong

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Aiding therapy using speech emotion recognition by Koh, En Rong

“…We will explore the use of a Convolutional Neural network, a type of Deep Learning method, to train and predict human emotions. We will also examine the different types of time-frequency features in audio signal processing and how they help in classifying human emotion. …”
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Modelling self-awareness in social robot by Zhang, Jiaheng

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