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9,820 results on '"Huang Qi"'

101. Enhancing Network Intrusion Detection with Deep Oversampling and Convolutional Autoencoder for Imbalanced Dataset

Author

Xiong, Xuanrui, Li, Junfeng, Zhang, Huijun, Shen, Han, Liu, Mengru, Peng, Wei, Huang, Qi, Zhang, Yuan, 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, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Gao, Feifei, editor, Wu, Jun, editor, Li, Yun, editor, Gao, Honghao, editor, and Wang, Shangguang, editor

Published
2024
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102. Exploring the Performance Test of Smart Substation Auxiliary Control System Test Platform Based on B/S Architecture

Author

Feng, Fuyong, Cai, Dongsheng, Chang, Zhengwei, Wu, Jie, Bamisile, Olusola, Huang, Qi, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, and Li, Jian, editor

Published
2024
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106. Forecasting-Aided Graphical Learning for Robust State Estimation of Distribution System

Author

Di, Cao, Zhao, Junbo, Hu, Jiaxiang, Huang, Yuehui, Huang, Qi, Chen, Zhe, Hu, Weihao, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Xue, Yusheng, editor, Zheng, Yuping, editor, and Gómez-Expósito, Antonio, editor

Published
2024
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107. Mixed Leadership Stochastic Differential Game in Feedback Information Pattern with Applications

Author

Huang, Qi and Shi, Jingtao

Subjects
Mathematics - Optimization and Control
Abstract

This paper is devoted to a high-dimensional mixed leadership stochastic differential game on a finite horizon in feedback information mode, where the control variables enter into the diffusion term of state equation. A verification theorem for the feedback Stackelberg-Nash equilibrium is obtained by using a system of coupled and fully nonlinear parabolic partial differential equations. We apply the verification theorem to deal with a dynamic innovation and pricing decision problem where the buyer acts as the leader in the pricing decisions and the dynamic model is stochastic. Via the solutions of coupled Riccati equations, we explicitly express the feedback equilibrium strategies of innovation and pricing. And by analysis, the local existence and uniqueness of the solutions of the coupled Riccati equations is derived. We also conduct some numerical analyses to discuss the effects of model parameters on the feedback equilibrium strategies., Comment: 26 pages, 16 figures

Published
2022

108. Charmoniumlike resonant explanation on the newly observed $X(3960)$

Author

Chen, Rui and Huang, Qi

Subjects
High Energy Physics - Phenomenology
Abstract

Stimulated by the observation of the newly $X(3960)$ observed by the LHCb collaboration, we adopt the one-boson-exchange model and consider the $S-D$ wave mixing effects to study the $D_s\bar{D}_s/D^*\bar{D}^*/D_s^*\bar{D}_s^*$ interactions with $I(J^{PC})=0(0^{++})$. After producing the phase shifts of this coupled channel systems, our results show that there can exist a charmoniumlike resonance, whose obtained mass and width can both well match with the experimental data of the newly observed $X(3960)$. We also find that the $D^*\bar{D}^*$ system plays an important role in the formation of the newly observed $X(3960)$ as a charmoniumlike resonance, and the $D_s^*\bar{D}_s^*$ system makes a significant contribution to the resonant width. As a byproduct, we perform a coupled channel analysis on the $D^*\bar{D}^*/D_s\bar{D}_s^*/D_s^*\bar{D}_s^*$ interactions with $I(J^{PC})=0(1^{+-})$, our results can predict the existence of the $D_s\bar{D}_s^*$ molecule with $1^{+-}$ and the $D_s^*\bar{D}_s^*$ molecule with $1^{+-}$. Their widths are around several and several to several tens MeV, respectively. Experimental searches for these two possible charmoniumlike molecular candidates can be helpful to verify our proposal., Comment: 7 pages, 5 figures, Physics Letters B846, 138254

Published
2022

112. Relative Robustness of CDMs and (M)IRT in Measuring Growth in Latent Skills

Author

Huang, Qi and Bolt, Daniel M.

Abstract

Previous studies have demonstrated evidence of latent skill continuity even in tests intentionally designed for measurement of binary skills. In addition, the assumption of binary skills when continuity is present has been shown to potentially create a lack of invariance in item and latent ability parameters that may undermine applications. In this article, we examine measurement of growth as one such application, and consider multidimensional item response theory (MIRT) as a competing alternative. Motivated by prior findings concerning the effects of skill continuity, we study the relative robustness of cognitive diagnostic models (CDMs) and (M)IRT models in the measurement of growth under both binary and continuous latent skill distributions. We find CDMs to be a less robust way of quantifying growth under misspecification, and subsequently provide a real-data example suggesting underestimation of growth as a likely consequence. It is suggested that researchers should regularly attend to the assumptions associated with the use of latent binary skills and consider (M)IRT as a potentially more robust alternative if unsure of their discrete nature.

Published
2023
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114. From the isovector molecular explanation of the newly $T_{c\bar{s}}^{a0(++)}(2900)$ to possible charmed-strange molecular pentaquarks

Author

Chen, Rui and Huang, Qi

Subjects
High Energy Physics - Phenomenology
Abstract

In this work, we adopt the one-boson-exchange model to study the $D^{(*)}K^{(*)}$ interactions. With the same parameters, we can simultaneously reproduce the masses of the $D_{s0}(2317)$, $D_{s1}(2460)$, and $T_{c\bar{s}}^{a0(++)}(2900)$ recently observed by the LHCb collaboration in the hadronic molecular picture, where the $D_{s0}(2317)$, $D_{s1}(2460)$, and $T_{c\bar{s}}^{a0(++)}(2900)$ are regarded as the $DK[I(J^P)=0(0^+)]$, $D^*K[0(1^+)]$, and $D^*K^*[1(0^+)]$ charmed-strange molecular states, respectively. In addition, we extend to study the $\Lambda_cK^{(*)}$ and $\Sigma_cK^{(*)}$ interactions and predict two possible charmed-strange molecular pentaquarks, the single $\Sigma_cK^*$ state with $I(J^P)=1/2(1/2^-)$ and $3/2(3/2^-)$. After considering the coupled channel effects, our results show that the coupled $\Lambda_cK^*/\Sigma_cK^*$ molecular state with $I(J^P)=1/2(1/2^-)$ and the coupled $\Sigma_cK/\Lambda_cK^*$ molecular state with $I(J^P)=1/2(1/2^-)$ can be good hadronic molecular candidates, the $\Lambda_cK^*({}^2S_{1/2})$ and $\Sigma_cK({}^2S_{1/2})$ are the dominant channels, respectively., Comment: 8 pages, 2 figures

Published
2022

115. First Organoid Intelligence (OI) workshop to form an OI community

Author

Pantoja, Itzy E Morales, Smirnova, Lena, Muotri, Alysson R, Wahlin, Karl J, Kahn, Jeffrey, Boyd, J Lomax, Gracias, David H, Harris, Timothy D, Cohen-Karni, Tzahi, Caffo, Brian S, Szalay, Alexander S, Han, Fang, Zack, Donald J, Etienne-Cummings, Ralph, Akwaboah, Akwasi, Romero, July Carolina, Din, Dowlette-Mary Alam El, Plotkin, Jesse D, Paulhamus, Barton L, Johnson, Erik C, Gilbert, Frederic, Curley, J Lowry, Cappiello, Ben, Schwamborn, Jens C, Hill, Eric J, Roach, Paul, Tornero, Daniel, Krall, Caroline, Parri, Rheinallt, Sillé, Fenna, Levchenko, Andre, Jabbour, Rabih E, Kagan, Brett J, Berlinicke, Cynthia A, Huang, Qi, Maertens, Alexandra, Herrmann, Kathrin, Tsaioun, Katya, Dastgheyb, Raha, Habela, Christa Whelan, Vogelstein, Joshua T, and Hartung, Thomas

Subjects
Information and Computing Sciences, Engineering, Biomedical Engineering, Neurosciences, Neurological, microphysiological systems, brain, electrophysiology, cognition, artificial intelligence, biological computing, Organoid Intelligence, Control engineering, mechatronics and robotics, Artificial intelligence, Machine learning
Abstract

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22-24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

Published
2023

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