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3. Applications of Deep Learning to physics workflows

Author

Agarwal, Manan, Alameda, Jay, Audenaert, Jeroen, Benoit, Will, Beveridge, Damon, Bhattacharya, Meghna, Chatterjee, Chayan, Chatterjee, Deep, Chen, Andy, Cholayil, Muhammed Saleem, Chou, Chia-Jui, Choudhary, Sunil, Coughlin, Michael, Dax, Maximilian, Desai, Aman, Di Luca, Andrea, Duarte, Javier Mauricio, Farrell, Steven, Feng, Yongbin, Goodarzi, Pooyan, Govorkova, Ekaterina, Graham, Matthew, Guiang, Jonathan, Gunny, Alec, Guo, Weichangfeng, Hakenmueller, Janina, Hawks, Ben, Hsu, Shih-Chieh, Jawahar, Pratik, Ju, Xiangyang, Katsavounidis, Erik, Kellis, Manolis, Khoda, Elham E, Lahbabi, Fatima Zahra, Lian, Van Tha Bik, Liu, Mia, Malanchev, Konstantin, Marx, Ethan, McCormack, William Patrick, McLeod, Alistair, Mo, Geoffrey, Moreno, Eric Anton, Muthukrishna, Daniel, Narayan, Gautham, Naylor, Andrew, Neubauer, Mark, Norman, Michael, Omer, Rafia, Pedro, Kevin, Peterson, Joshua, Pürrer, Michael, Raikman, Ryan, Raj, Shivam, Ricker, George, Robbins, Jared, Samani, Batool Safarzadeh, Scholberg, Kate, Schuy, Alex, Skliris, Vasileios, Soni, Siddharth, Sravan, Niharika, Sutton, Patrick, Villar, Victoria Ashley, Wang, Xiwei, Wen, Linqing, Wuerthwein, Frank, Yang, Tingjun, and Yeh, Shu-Wei

Subjects
High Energy Physics - Experiment, Astrophysics - High Energy Astrophysical Phenomena, General Relativity and Quantum Cosmology
Abstract

Modern large-scale physics experiments create datasets with sizes and streaming rates that can exceed those from industry leaders such as Google Cloud and Netflix. Fully processing these datasets requires both sufficient compute power and efficient workflows. Recent advances in Machine Learning (ML) and Artificial Intelligence (AI) can either improve or replace existing domain-specific algorithms to increase workflow efficiency. Not only can these algorithms improve the physics performance of current algorithms, but they can often be executed more quickly, especially when run on coprocessors such as GPUs or FPGAs. In the winter of 2023, MIT hosted the Accelerating Physics with ML at MIT workshop, which brought together researchers from gravitational-wave physics, multi-messenger astrophysics, and particle physics to discuss and share current efforts to integrate ML tools into their workflows. The following white paper highlights examples of algorithms and computing frameworks discussed during this workshop and summarizes the expected computing needs for the immediate future of the involved fields., Comment: Whitepaper resulting from Accelerating Physics with ML@MIT workshop in Jan/Feb 2023

Published
2023

5. Superior antibody and membrane protein-specific T-cell responses to CoronaVac by intradermal versus intramuscular routes in adolescents

Author

Rosa Duque, Jaime S., Cheng, Samuel M. S., Cohen, Carolyn A., Leung, Daniel, Wang, Xiwei, Mu, Xiaofeng, Chung, Yuet, Lau, Tsun Ming, Wang, Manni, Zhang, Wenyue, Zhang, Yanmei, Wong, Howard H. W., Tsang, Leo C. H., Chaothai, Sara, Kwan, Tsz Chun, Li, John K. C., Chan, Karl C. K., Luk, Leo L. H., Ho, Jenson C. H., Li, Wing Yan, Lee, Amos M. T., Lam, Jennifer H. Y., Chan, Sau Man, Wong, Wilfred H. S., Tam, Issan Y. S., Mori, Masashi, Valkenburg, Sophie A., Peiris, Malik, Tu, Wenwei, and Lau, Yu Lung

Published
2024
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8. Distribution Characteristics of Inclusions in GH4742 Superalloy Ingot by Vacuum Arc Remelting

Author

Yang Shulei, Wang Xiwei, Tian Qiang, Wang Tiantian, Yang Shufeng

Subjects
gh4742 alloy； vacuum arc remelting （var）； impurity element； inclusion, Materials of engineering and construction. Mechanics of materials, TA401-492, Technology
Abstract

A ϕ570 mm alloy ingot was utilized as the electrode for vacuum arc remelting， and a ϕ660 mm vacuum arc remelting ingot was prepared through the three stages of arc initiation， stabilized melting， and thermal capping. The melting process lasted a total of 860 minutes.The distribution of inclusions in the industrial ingot of vacuum arc remelting GH4742 alloy and its characteristic positions （crown， shelf and skin） was analyzed by field emission scanning electron microscope and inclusion automatic scanning system. The results of the study showed that there were four main types of inclusions in GH4742 alloy vacuum arc remelting ingots， including Ti（C，N）， LaAlO3-Ti（C，N）， Ti（C，N）-（Ti，Nb，Mo）C， and LaAlO3-Ti（C，N）-（Ti，Nb，Mo）C. The size of inclusions was mainly dominated by small-sized inclusions less than 3 μm. From the center to the edge， the size of inclusions gradually decreased and the number density gradually increased. The largest size of inclusions was observed at the middle center of the ingot， with a maximum average size of 4.14 μm. The lowest number of inclusions was observed at the bottom center of the ingot with a number density of 13.23 N/mm2. The aggregated oxide inclusions were distributed in the ingot crown， skin and shelf， which were formed when the oxides dislodged from the electrodes move to the edges of the ingot under the action of the flow field of the molten pool and are captured by the solidified regions at the edges.

Published
2024
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9. Role of Emotional Experience in AI Voice Assistant User Experience in Voice Shopping

Author

Wang, Xiwei, Liu, Yutong, Wuji, Siguleng, Luo, Ran, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Sserwanga, Isaac, editor, Joho, Hideo, editor, Ma, Jie, editor, Hansen, Preben, editor, Wu, Dan, editor, Koizumi, Masanori, editor, and Gilliland, Anne J., editor

Published
2024
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10. Use of the Information Gap on Deckbuilding in Hearthstone

Author

Wang, Xiwei, Striełkowski, Wadim, Editor-in-Chief, Black, Jessica M., Series Editor, Butterfield, Stephen A., Series Editor, Chang, Chi-Cheng, Series Editor, Cheng, Jiuqing, Series Editor, Dumanig, Francisco Perlas, Series Editor, Al-Mabuk, Radhi, Series Editor, Scheper-Hughes, Nancy, Series Editor, Urban, Mathias, Series Editor, Webb, Stephen, Series Editor, Chen, Youbin, editor, Shen, Chaoqun, editor, and Rak, Joanna, editor

Published
2024
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15. Exploiting Spline Models for the Training of Fully Connected Layers in Neural Network

Author

Mo, Kanya, Zheng, Shen, Wang, Xiwei, Wang, Jinghua, and Schewe, Klaus-Dieter

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

The fully connected (FC) layer, one of the most fundamental modules in artificial neural networks (ANN), is often considered difficult and inefficient to train due to issues including the risk of overfitting caused by its large amount of parameters. Based on previous work studying ANN from linear spline perspectives, we propose a spline-based approach that eases the difficulty of training FC layers. Given some dataset, we first obtain a continuous piece-wise linear (CPWL) fit through spline methods such as multivariate adaptive regression spline (MARS). Next, we construct an ANN model from the linear spline model and continue to train the ANN model on the dataset using gradient descent optimization algorithms. Our experimental results and theoretical analysis show that our approach reduces the computational cost, accelerates the convergence of FC layers, and significantly increases the interpretability of the resulting model (FC layers) compared with standard ANN training with random parameter initialization followed by gradient descent optimizations.

Published
2021

18. Impaired glycine neurotransmission causes adolescent idiopathic scoliosis

Author

Wang, Xiaolu, Yue, Ming, Cheung, Jason Pui Yin, Cheung, Prudence Wing Hang, Fan, Yanhui, Wu, Meicheng, Wang, Xiaojun, Zhao, Sen, Khanshour, Anas M., Rios, Jonathan J., Chen, Zheyi, Wang, Xiwei, Tu, Wenwei, Chan, Danny, Yuan, Qiuju, Qin, Dajiang, Qiu, Guixing, Wu, Zhihong, Zhang, Terry Jianguo, Ikegawa, Shiro, Wu, Nan, Wise, Carol A., Hu, Yong, Luk, Keith Dip Kei, Song, You-Qiang, and Gao, Bo

Subjects
Neural transmission -- Health aspects, Scoliosis -- Causes of -- Development and progression, Glycine -- Health aspects, Health care industry
Abstract

Adolescent idiopathic scoliosis (AIS) is the most common form of spinal deformity, affecting millions of adolescents worldwide, but it lacks a defined theory of etiopathogenesis. Because of this, treatment of AIS is limited to bracing and/ or invasive surgery after onset. Preonset diagnosis or preventive treatment remains unavailable. Here, we performed a genetic analysis of a large multicenter AIS cohort and identified disease- causing and predisposing variants of SLC6A9 in multigeneration families, trios, and sporadic patients. Variants of SLC6A9, which encodes glycine transporter 1 (GLYT1), reduced glycine-uptake activity in cells, leading to increased extracellular glycine levels and aberrant glycinergic neurotransmission. Slc6a9 mutant zebrafish exhibited discoordination of spinal neural activities and pronounced lateral spinal curvature, a phenotype resembling human patients. The penetrance and severity of curvature were sensitive to the dosage of functional glyt1. Administration of a glycine receptor antagonist or a clinically used glycine neutralizer (sodium benzoate) partially rescued the phenotype. Our results indicate a neuropathic origin for 'idiopathic' scoliosis, involving the dysfunction of synaptic neurotransmission and central pattern generators (CPGs), potentially a common cause of AIS. Our work further suggests avenues for early diagnosis and intervention of AIS in preadolescents., Introduction Adolescent idiopathic scoliosis (AIS) is a condition in which the spine is deformed with a lateral curvature exceeding 10 degrees in otherwise healthy adolescents (1, 2). With a prevalence [...]

Published
2024
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21. Convolution Based Spectral Partitioning Architecture for Hyperspectral Image Classification

Author

Chu, Ringo S. W., Ng, Ho-Cheung, Wang, Xiwei, and Luk, Wayne

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Hyperspectral images (HSIs) can distinguish materials with high number of spectral bands, which is widely adopted in remote sensing applications and benefits in high accuracy land cover classifications. However, HSIs processing are tangled with the problem of high dimensionality and limited amount of labelled data. To address these challenges, this paper proposes a deep learning architecture using three dimensional convolutional neural networks with spectral partitioning to perform effective feature extraction. We conduct experiments using Indian Pines and Salinas scenes acquired by NASA Airborne Visible/Infra-Red Imaging Spectrometer. In comparison to prior results, our architecture shows competitive performance for classification results over current methods., Comment: Accepted for publication in IGARSS'2019

Published
2019

22. Optimizing CNN-based Hyperspectral Image Classification on FPGAs

Author

Liu, Shuanglong, Chu, Ringo S. W., Wang, Xiwei, and Luk, Wayne

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Hyperspectral image (HSI) classification has been widely adopted in applications involving remote sensing imagery analysis which require high classification accuracy and real-time processing speed. Methods based on Convolutional neural networks (CNNs) have been proven to achieve state-of-the-art accuracy in classifying HSIs. However, CNN models are often too computationally intensive to achieve real-time response due to the high dimensional nature of HSI, compared to traditional methods such as Support Vector Machines (SVMs). Besides, previous CNN models used in HSI are not specially designed for efficient implementation on embedded devices such as FPGAs. This paper proposes a novel CNN-based algorithm for HSI classification which takes into account hardware efficiency. A customized architecture which enables the proposed algorithm to be mapped effectively onto FPGA resources is then proposed to support real-time on-board classification with low power consumption. Implementation results show that our proposed accelerator on a Xilinx Zynq 706 FPGA board achieves more than 70x faster than an Intel 8-core Xeon CPU and 3x faster than an NVIDIA GeForce 1080 GPU. Compared to previous SVM-based FPGA accelerators, we achieve comparable processing speed but provide a much higher classification accuracy., Comment: This article is accepted for publication at ARC'2019

Published
2019

32. Author Correction: Immunogenicity and reactogenicity of SARS-CoV-2 vaccines BNT162b2 and CoronaVac in healthy adolescents

Author

Rosa Duque, Jaime S., Wang, Xiwei, Leung, Daniel, Cheng, Samuel M. S., Cohen, Carolyn A., Mu, Xiaofeng, Hachim, Asmaa, Zhang, Yanmei, Chan, Sau Man, Chaothai, Sara, Kwan, Kelvin K. H., Chan, Karl C. K., Li, John K. C., Luk, Leo L. H., Tsang, Leo C. H., Wong, Wilfred H. S., Cheang, Cheuk Hei, Hung, Timothy K., Lam, Jennifer H. Y., Chua, Gilbert T., Tso, Winnie W. Y., Ip, Patrick, Mori, Masashi, Kavian, Niloufar, Leung, Wing Hang, Valkenburg, Sophie, Peiris, Malik, Tu, Wenwei, and Lau, Yu Lung

Published
2022
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33. Immunogenicity and reactogenicity of SARS-CoV-2 vaccines BNT162b2 and CoronaVac in healthy adolescents

Author

Rosa Duque, Jaime S., Wang, Xiwei, Leung, Daniel, Cheng, Samuel M. S., Cohen, Carolyn A., Mu, Xiaofeng, Hachim, Asmaa, Zhang, Yanmei, Chan, Sau Man, Chaothai, Sara, Kwan, Kelvin K. H., Chan, Karl C. K., Li, John K. C., Luk, Leo L. H., Tsang, Leo C. H., Wong, Wilfred H. S., Cheang, Cheuk Hei, Hung, Timothy K., Lam, Jennifer H. Y., Chua, Gilbert T., Tso, Winnie W. Y., Ip, Patrick, Mori, Masashi, Kavian, Niloufar, Leung, Wing Hang, Valkenburg, Sophie, Peiris, Malik, Tu, Wenwei, and Lau, Yu Lung

Published
2022
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34. Applications of Sensing for Disease Detection Disease detection

Author

de Castro Megías, Ana Isabel, Pérez-Roncal, Claudia, Thomasson, J. Alex, Ehsani, Reza, López-Maestresalas, Ainara, Yang, Chenghai, Jarén, Carmen, Wang, Tianyi, Cribben, Curtis, Marin, Diana, Isakeit, Thomas, Urrestarazu, Jorge, Lopez-Molina, Carlos, Wang, Xiwei, Nichols, Robert L., Santesteban, Gonzaga, Arazuri, Silvia, Peña, José Manuel, Oliver, Margaret A., Series Editor, Kerry, Ruth, editor, and Escolà, Alexandre, editor

Published
2021
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35. Vendor-Based Privacy-Preserving POI Recommendation Network

Author

Cui, Longyin, Wang, Xiwei, Zhang, Jun, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin (Sherman), Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Xiong, Jinbo, editor, Wu, Shaoen, editor, Peng, Changgen, editor, and Tian, Youliang, editor

Published
2021
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40. How Interaction Paradigms Affect User Experience and Perceived Interactivity in Virtual Reality Environment

Author

Wang, Duo, Wang, Xiwei, Zheng, Qingxiao, Tao, Bingxin, Zheng, Guomeng, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Chen, Jessie Y. C., editor, and Fragomeni, Gino, editor

Published
2020
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45. Motor Fault Diagnosis Based on Time–Frequency Swinging Door Algorithm and Convolutional Kernel Receptive Field Matching Framework

Author

Zhang, Xiaofei, Liang, Weizhi, Qu, Yinpeng, Wang, Xiwei, and Huang, Sheng

Abstract

In the realm of industrial production, the condition of motors tends to deteriorate gradually over time. Among the various types of motor faults, the selection of appropriate diagnostic techniques stands out as a pivotal step in the process of motor fault identification. In this article, we introduce a fault diagnosis framework aimed at enhancing the precision and efficiency of diagnostics by perceptually matching the time–frequency features of data with the sensory fields of convolutional neural networks (CNNs). First, the time–frequency swing door algorithm (TF-SDA) is proposed to determine the optimal signal compression ratio, guided by the time–frequency attributes of the original data. Subsequently, the data are transformed into a two-dimensional image using temporal image conversion methodologies, specifically the Gramian angular field and symmetrized dot pattern. Finally, the diagnostic framework is realized by matching the CNN receptive fields with TF-SDA data features. Comparative analysis with other state-of-the-art methods and compression algorithms reveals that the proposed approach effectively isolates the optimal time–frequency components of fault characteristics while eliminating extraneous elements, thus substantially enhancing the precision and efficiency of multifault diagnosis.

Published
2024
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47. Tests on the incline rectification of suction bucket foundation installation under local cyclic shock loading.

Author

Xie, Liquan, Feng, Guangrui, Wang, Xiwei, and Su, Tsung-Chow

Subjects
CYCLIC loads, PORE water pressure, OCEAN waves, WATER pressure, FREQUENCIES of oscillating systems, DEAD loads (Mechanics)
Abstract

There are many problems with the vertical installation of suction buckets due to the complex ocean wave current and seabed geological conditions. In this paper, a set of tests were developed to study the mechanism of incline rectification of the suction bucket foundation based on resistance-reduced vibration on local side walls (RRV-LSW). In this experiment, the dynamic evolution process of pore water pressure around the suction barrel foundation was monitored from three angles of vibration frequency, initial inclination angle and load, and the influence of local cyclic vibration parameters on the slope velocity of the suction barrel foundation was quantified. The results indicate that a tilted suction caisson foundation can be effectively corrected through lateral wall vibration, and the correction effect is closely related to the vibration frequency, initial tilt angle, and static pressure load. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Assessment of SARS-CoV-2 immunity in convalescent children and adolescents

Author

Ip, Patrick, primary, Tsang, Hing Wai, additional, Chua, Gilbert T, additional, KW, Kelvin, additional, SC, Joshua Wong, additional, WW, Tu, additional, SY, Janette Kwok, additional, Wong, WHS, additional, Wang, Xiwei, additional, Zhang, Yanmei, additional, Duque, Jaime Rosa, additional, Chan, Godfrey, additional, WK, Chu, additional, CP, Pang, additional, KH, Paul Tam, additional, Lau, YL, additional, Wong, Ian, additional, WH, Leung, additional, Yuen, Kwok-Yung, additional, and YW, Mike Kwan, additional

Published
2024
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