Design and implementation of a smart Internet of Things chest pain center based on deep learning by Li, Feng, Bi, Zhongao, Xu, Hongzeng, Shi, Yunqi, Duan, Na, Li, Zhaoyu

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Physics-informed machine learning for green data center operations by Wang, Ruihang

“…The evaluation shows that our approach saves 5.7% to 13.8% power usage compared with conventional feedback control and adapts 8x to 10x faster than native fine-tuning with at most 0.74C temperature overshoot. …”
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Enhancing stable grasping of containers with dynamic center of mass using reinforcement learning by Gao, Yuan

“…The policy outputted delta changes in the grasping location, facilitating adaptive grasping in diverse environments. Finally, we applied the reinforcement learning policy trained in simulation to the real UR5 robot, demonstrating the feasibility and effectiveness of our approach in real-world scenarios.…”
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Center potential by Tan, Hu Soon

“…Leveraging the cross-platform capabilities of Flutter [3], the application offers an intuitive and user-friendly interface, compatible with both Android and iOS devices. …”
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Nature-Centered Materiomics: Experimental and Computational Design by Shen, Sabrina C.

“…Nature effectively forms sustainable supply chains with no waste by leveraging both the constituents of materials and their structural organization at multiple scales, architecting common and abundant building blocks into a variety of high-performing composites. In this thesis, we present a nature-centered materiomics approach to emulate this in the design of novel sustainable materials. …”
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Methodology for domain ontology development with human-centered design by Iqbal, Rizwan

“…Moreover, in existing literature, the notion of human centered design is neglected and there is a need to come up with methods which does not put burden on the audience for mastering them and should be easy to adapt for supporting ontology development. …”
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Enabling open-ended questions in team-based learning using automated marking: impact on student achievement, learning and engagement by Tan, Sophia Huey Shan, Thibault, Guillaume, Chew, Anna Chia Yin, Rajalingam, Preman

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Exploring the impact of COVID-19 on the grammar of schools in project-based learning contexts by Woods, Peter J., Anderson, Emma, Hira, Avneet

“…In turn, we attend to the following research question: how do teachers at project-based learning high schools conceptualize the changes to education that have occurred in response to the COVID-19 pandemic? …”
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Machine learning-based approach to wind turbine wake prediction under yawed conditions by Gajendran, Mohan Kumar, Ijaz Fazil Syed Ahmed Kabir, Vadivelu, Sudhakar, Ng, Eddie Yin Kwee

“…Utilizing WindSE’s actuator line method (ALM) and Large Eddy Simulation (LES), we model an NREL 5-MW wind turbine under yaw conditions ranging from no yaw to 40 degrees. …”
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Teaching person-centered practice to pre-registration physiotherapy students: a qualitative study by Killingback, Clare, Tomlinson, Amy, Thompson, Mark, Whitfield, Clare, Stern, Julian

“…Results: Five themes were identified: 1) understanding the person and their direction of travel; 2) contextual factors that impact on the delivery of person-centered practice; 3) awareness of personality traits; 4) doing the small things; and 5) the person-centered learning curve. …”
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Crowdsourcing as Reflective Political Practice: Building a Location-based Tool for Civic Learning and Engagement by Graeff, Erhardt

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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

“…Compared to a standard transformer, the ST-ViT contains a spatial–convolutional vision transformer and a temporal transformer, which can improve the model performance. …”
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Towards robust sensing and recognition : from statistical learning to transfer learning by Yang, Jianfei

“…Four algorithms for domain adaptation have been evaluated on public visual benchmark (e.g. Image-CLEF and Office-Home) and WiFi-based gesture recognition dataset. …”
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Online learning with kernels by Fan, Haijin

“…The algorithm can adapt the kernel width according to the training data effectively under different initial kernel width and improve the performance of the algorithm in both testing accuracy and convergence speed. Furthermore, we first extend the recurrent model to kernel methods and propose a linear recurrent kernel algorithm for online learning. …”
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Chromatin interaction neural network (ChINN) : a machine learning-based method for predicting chromatin interactions from DNA sequences by Cao, Fan, Zhang, Yu, Cai, Yichao, Animesh, Sambhavi, Zhang, Ying, Akincilar, Semih Can, Loh, Yan Ping, Li, Xinya, Chng, Wee Joo, Tergaonkar, Vinay, Kwoh, Chee Keong, Fullwood, Melissa Jane

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Design, User Experience, and Usability : UX Research and Design : 10th International Conference, DUXU 2021, Held as Part of the 23rd HCI International Conference, HCII 2021, Virtua... by DUXU (Conference) (10th : 2021 : Online), organiser 643242, Soares, Marcelo Marcio, editor 514932, Rosenzweig, Elizabeth, editor 643243, Marcus, Aaron, 1943-, editor 643244, International Conference on Human-Computer Interaction (23rd : 2021 : Online) issuing body 642922

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

Predicting cognitive scores from wearable-based digital physiological features using machine learning: data from a clinical trial in mild cognitive impairment by Rykov, Yuri G., Patterson, Michael D., Gangwar, Bikram A., Jabar, Syaheed B., Leonardo, Jacklyn, Ng, Kok Pin, Kandiah, Nagaendran

“…Methods: We used the dataset collected from a 10-week single-arm clinical trial in older adults (50–70 years old) diagnosed with amnestic MCI (N = 30) who received a digitally delivered multidomain therapeutic intervention. …”
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Global optimization: a machine learning approach by Bertsimas, Dimitris, Margaritis, Georgios

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Bayesian learning of coupled biogeochemical–physical models by Gupta, Abhinav, Lermusiaux, Pierre F.J.

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