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3,222 results on '"Zhu, Hongbo"'

4. Power Optimization for Integrated Active and Passive Sensing in DFRC Systems

Author

Lou, Xingliang, Xia, Wenchao, Wong, Kai-Kit, Zhao, Haitao, Quek, Tony Q. S., and Zhu, Hongbo

Subjects
Computer Science - Information Theory, Electrical Engineering and Systems Science - Signal Processing
Abstract

Most existing works on dual-function radar-communication (DFRC) systems mainly focus on active sensing, but ignore passive sensing. To leverage multi-static sensing capability, we explore integrated active and passive sensing (IAPS) in DFRC systems to remedy sensing performance. The multi-antenna base station (BS) is responsible for communication and active sensing by transmitting signals to user equipments while detecting a target according to echo signals. In contrast, passive sensing is performed at the receive access points (RAPs). We consider both the cases where the capacity of the backhaul links between the RAPs and BS is unlimited or limited and adopt different fusion strategies. Specifically, when the backhaul capacity is unlimited, the BS and RAPs transfer sensing signals they have received to the central controller (CC) for signal fusion. The CC processes the signals and leverages the generalized likelihood ratio test detector to determine the present of a target. However, when the backhaul capacity is limited, each RAP, as well as the BS, makes decisions independently and sends its binary inference results to the CC for result fusion via voting aggregation. Then, aiming at maximize the target detection probability under communication quality of service constraints, two power optimization algorithms are proposed. Finally, numerical simulations demonstrate that the sensing performance in case of unlimited backhaul capacity is much better than that in case of limited backhaul capacity. Moreover, it implied that the proposed IAPS scheme outperforms only-passive and only-active sensing schemes, especially in unlimited capacity case.

Published
2024

5. LIPEx-Locally Interpretable Probabilistic Explanations-To Look Beyond The True Class

Author

Zhu, Hongbo, Cangelosi, Angelo, Sen, Procheta, and Mukherjee, Anirbit

Subjects
Computer Science - Machine Learning
Abstract

In this work, we instantiate a novel perturbation-based multi-class explanation framework, LIPEx (Locally Interpretable Probabilistic Explanation). We demonstrate that LIPEx not only locally replicates the probability distributions output by the widely used complex classification models but also provides insight into how every feature deemed to be important affects the prediction probability for each of the possible classes. We achieve this by defining the explanation as a matrix obtained via regression with respect to the Hellinger distance in the space of probability distributions. Ablation tests on text and image data, show that LIPEx-guided removal of important features from the data causes more change in predictions for the underlying model than similar tests based on other saliency-based or feature importance-based Explainable AI (XAI) methods. It is also shown that compared to LIME, LIPEx is more data efficient in terms of using a lesser number of perturbations of the data to obtain a reliable explanation. This data-efficiency is seen to manifest as LIPEx being able to compute its explanation matrix around 53% faster than all-class LIME, for classification experiments with text data., Comment: 19 pages, 9 figures

Published
2023

14. Gradient Sparsification for Efficient Wireless Federated Learning with Differential Privacy

Author

Wei, Kang, Li, Jun, Ma, Chuan, Ding, Ming, Shu, Feng, Zhao, Haitao, Chen, Wen, and Zhu, Hongbo

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Artificial Intelligence, Computer Science - Cryptography and Security
Abstract

Federated learning (FL) enables distributed clients to collaboratively train a machine learning model without sharing raw data with each other. However, it suffers the leakage of private information from uploading models. In addition, as the model size grows, the training latency increases due to limited transmission bandwidth and the model performance degrades while using differential privacy (DP) protection. In this paper, we propose a gradient sparsification empowered FL framework over wireless channels, in order to improve training efficiency without sacrificing convergence performance. Specifically, we first design a random sparsification algorithm to retain a fraction of the gradient elements in each client's local training, thereby mitigating the performance degradation induced by DP and and reducing the number of transmission parameters over wireless channels. Then, we analyze the convergence bound of the proposed algorithm, by modeling a non-convex FL problem. Next, we formulate a time-sequential stochastic optimization problem for minimizing the developed convergence bound, under the constraints of transmit power, the average transmitting delay, as well as the client's DP requirement. Utilizing the Lyapunov drift-plus-penalty framework, we develop an analytical solution to the optimization problem. Extensive experiments have been implemented on three real life datasets to demonstrate the effectiveness of our proposed algorithm. We show that our proposed algorithms can fully exploit the interworking between communication and computation to outperform the baselines, i.e., random scheduling, round robin and delay-minimization algorithms.

Published
2023
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16. Mid-infrared Chemical Imaging of Intracellular Tau Fibrils using Fluorescence-guided Computational Photothermal Microscopy

Author

Zhao, Jian, Jiang, Lulu, Matlock, Alex, Xu, Yihong, Zhu, Jiabei, Zhu, Hongbo, Tian, Lei, Wolozin, Benjamin, and Cheng, Ji-Xin

Subjects
Physics - Optics, Physics - Biological Physics
Abstract

Amyloid proteins are associated with a broad spectrum of neurodegenerative diseases. However, it remains a grand challenge to extract molecular structure information from intracellular amyloid proteins in their native cellular environment. To address this challenge, we developed a computational chemical microscope integrating 3D mid-infrared photothermal imaging with fluorescence imaging, termed Fluorescence-guided Bond-Selective Intensity Diffraction Tomography (FBS-IDT). Based on a low-cost and simple optical design, FBS-IDT enables chemical-specific volumetric imaging and 3D site-specific mid-IR fingerprint spectroscopic analysis of tau fibrils, an important type of amyloid protein aggregates, in their intracellular environment. Label-free volumetric chemical imaging of human cells with/without seeded tau fibrils is demonstrated to show the potential correlation between lipid accumulation and tau aggregate formation. Depth-resolved mid-infrared fingerprint spectroscopy is performed to reveal the protein secondary structure of the intracellular tau fibrils. 3D visualization of the \b{eta}-sheet for tau fibril structure is achieved.

Published
2023

19. Multi‐omics analysis of disulfidptosis regulators and therapeutic potential reveals glycogen synthase 1 as a disulfidptosis triggering target for triple‐negative breast cancer

Author

Xie, Jindong, primary, Deng, Xinpei, additional, Xie, Yi, additional, Zhu, Hongbo, additional, Liu, Peng, additional, Deng, Wei, additional, Ning, Li, additional, Tang, Yuhui, additional, Sun, Yuying, additional, Tang, Hailin, additional, Cai, Manbo, additional, Xie, Xiaoming, additional, and Zou, Yutian, additional

Published
2024
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36. 基于光子灯笼的976 nm半导体激光相干合束

Author

Dong Yijia, 董一甲, primary, Liu Jie, 刘杰, additional, Zhao Xinrui, 赵欣瑞, additional, Lin Xingchen, 林星辰, additional, Ning Yongqiang, 宁永强, additional, Wang Lijun, 王立军, additional, and Zhu Hongbo, 朱洪波, additional

Published
2024
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48. Water Hammer Analysis of Hydropower Station with Multi-level Water Intake

Author

Zhu, Hongbo, Wang, Jinfeng, Yang, Shaojia, Zhang, Sheng, Zhang, Zhixuan, Zheng, Zheng, Editor-in-Chief, Xi, Zhiyu, Associate Editor, Gong, Siqian, Series Editor, Hong, Wei-Chiang, Series Editor, Mellal, Mohamed Arezki, Series Editor, Narayanan, Ramadas, Series Editor, Nguyen, Quang Ngoc, Series Editor, Ong, Hwai Chyuan, Series Editor, Sun, Zaicheng, Series Editor, Ullah, Sharif, Series Editor, Wu, Junwei, Series Editor, Zhang, Baochang, Series Editor, Zhang, Wei, Series Editor, Zhu, Quanxin, Series Editor, Zheng, Wei, Series Editor, Xiang, Ping, editor, Yang, Haifeng, editor, Yan, Jianwei, editor, and Ding, Faxing, editor

Published
2024
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50. Lower creatinine to cystatin C ratio is associated with an increased risk of MASLD: A cross‐sectional and prospective study of 368,634 UK Biobank participants

Author

Wang, Jiaren, primary, Zeng, Lin, additional, Hong, Chang, additional, Cui, Hao, additional, Wang, Weizhen, additional, Zhu, Hongbo, additional, Li, Qimei, additional, Li, Yan, additional, Li, Ruining, additional, He, Jingzhe, additional, Zhu, Hong, additional, Liu, Li, additional, and Xiao, Lushan, additional

Published
2023
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