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430 results on '"Ma, Xiaoqiang"'

1. Network Characteristics of LEO Satellite Constellations: A Starlink-Based Measurement from End Users

Author

Ma, Sami, Chou, Yi Ching, Zhao, Haoyuan, Chen, Long, Ma, Xiaoqiang, and Liu, Jiangchuan

Subjects
Computer Science - Networking and Internet Architecture
Abstract

Low Earth orbit Satellite Networks (LSNs) have been advocated as a key infrastructure for truly global coverage in the forthcoming 6G. This paper presents our initial measurement results and observations on the end-to-end network characteristics of Starlink, arguably the largest LSN constellation to date. Our findings confirm that LSNs are a promising solution towards ubiquitous Internet coverage over the Earth; yet, we also find that the users of Starlink experience much more dynamics in throughput and latency than terrestrial network users, and even frequent outages. Its user experiences are heavily affected by environmental factors such as terrain, solar storms, rain, clouds, and temperature, so is the power consumption. We further analyze Starlink's current bent-pipe relay strategy and its limits, particularly for cross-ocean routes. We have also explored its mobility and portability potentials, and extended our experiments from urban cities to wild remote areas that are facing distinct practical and cultural challenges., Comment: 12 pages, 20 figures, to be published in IEEE INFOCOM 2023

Published
2022

6. Federated Unlearning

Author

Liu, Gaoyang, Ma, Xiaoqiang, Yang, Yang, Wang, Chen, and Liu, Jiangchuan

Subjects
Computer Science - Machine Learning, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Federated learning (FL) has recently emerged as a promising distributed machine learning (ML) paradigm. Practical needs of the "right to be forgotten" and countering data poisoning attacks call for efficient techniques that can remove, or unlearn, specific training data from the trained FL model. Existing unlearning techniques in the context of ML, however, are no longer in effect for FL, mainly due to the inherent distinction in the way how FL and ML learn from data. Therefore, how to enable efficient data removal from FL models remains largely under-explored. In this paper, we take the first step to fill this gap by presenting FedEraser, the first federated unlearning methodology that can eliminate the influence of a federated client's data on the global FL model while significantly reducing the time used for constructing the unlearned FL model.The basic idea of FedEraser is to trade the central server's storage for unlearned model's construction time, where FedEraser reconstructs the unlearned model by leveraging the historical parameter updates of federated clients that have been retained at the central server during the training process of FL. A novel calibration method is further developed to calibrate the retained updates, which are further used to promptly construct the unlearned model, yielding a significant speed-up to the reconstruction of the unlearned model while maintaining the model efficacy. Experiments on four realistic datasets demonstrate the effectiveness of FedEraser, with an expected speed-up of $4\times$ compared with retraining from the scratch. We envision our work as an early step in FL towards compliance with legal and ethical criteria in a fair and transparent manner., Comment: To be published in Proc.of 29th IEEE/ACM IWQoS, 2021

Published
2020

18. Microencapsulation of anthocyanins extracted from black soybean peels by whey protein/fructo‐oligosaccharide contributes to improved stability, bioavailability, and ability to regulate glycolipid metabolism

Author

Zhang, Wenbao, primary, Li, Xusheng, additional, Ma, Xiaoqiang, additional, Li, Haoyu, additional, Liu, Jia, additional, Zeng, Yingyu, additional, Cai, Dongbao, additional, Xu, Qingjie, additional, Chen, Guobing, additional, Tian, Lingmin, additional, Sun, Jianxia, additional, and Bai, Weibin, additional

Published
2024
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31. Sedimentary facies of Paleogene lacustrine dolomicrite and implications for petroleum reservoirs in the southern Qianjiang Depression, China

Author

Shen Junjun, Chen Kongquan, Liu Yang, Chen Fangfang, Qiu Xiaosong, Ma Xiaoqiang, and Meng Jianghui

Subjects
qianjiang depression, dolomite reservoir, sedimentary facies, self-sourced reservoir, favorable depositional facies, Geology, QE1-996.5
Abstract

Paleogene lacustrine dolomicrite of Unit II of the lower Xingouzui Formation in the southern part of the Qianjiang Depression, China forms “tight carbonate” hydrocarbon reservoirs that can be divided into the following four dolomicrite types: dolomicrite, muddy dolomicrite, sandy dolomicrite, and gypsiferous dolomicrite. These four dolomicrite types occur in the following three distinct combinations, which are referred to as subfacies: (1) interbedded dolomicrite (or sandy dolomicrite) and dark-gray siliciclastic mudstone, interpreted as open lacustrine deposits, (2) grayish-dark siliciclastic mudstone with thinly-bedded muddy dolomicrite or gypsiferous dolomicrite, interpreted as restricted lacustrine deposits, and (3) grayish-green mudstone with thinlybedded brown-yellow siltstone, interpreted as lacustrine shoreline deposits. The spatial distribution of these subfacies was controlled by the paleo-provenance system, paleo-microgeomorphology, and lake level fluctuations. In the open lacustrine subfacies, dolomicrite or sandy dolomicrite are often vertically interbedded with dark argillite rocks, forming a suitable petroleum source rockreservoir association. The dolomicrite and sandy dolomicrite reservoirs possess many secondary crystalline pores and few dissolution pores, with mesopore porosities in the range of 15%–25%. The dark mud shale interval has total organic carbon (TOC) values exceeding 4% (averaging 1.29%). The organic matter is mainly type II2, with vitrinite reflectance values averaging 0.57, which indicates potential for the generation of immature oil. The oil-source correlation results indicated that the n-alkanes of the crude oil and source rock samples from Unit II of the lower Xingouzui Formation exhibit single peak values, with a main peak (post-peak) in C22 and a Pr/Ph ratio $#x003C; 1 in a C2920R $#x003E; C2720R $#x003E; C2820R distribution. These features indicate that source-reservoir interbedding is characteristic of selfsourced reservoirs. The interbedded dolomicrite (or sandy dolomicrite) and dark-gray siliciclastic mudstone, i.e., subfacies (1), is a favorable target for hydrocarbons in the study area.

Published
2019
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