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Stochastic programming based multi-arm bandit offloading strategy for internet of things

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Digital Communications and Networks 2023年第5期9卷 1200-1211页

作者： Bin Cao Tingyong Wu xiang bai State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876China National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of ChinaChengdu611731China China Electrics Technology Cyber Security Co..Ldt Chengdu611731China

In order to solve the high latency of traditional cloud computing and the processing capacity limitation of Internet of Things(IoT)users,Multi-access Edge Computing(MEC)migrates computing and storage capabilities from the remote data center to the edge of network,providing users with computation services quickly and directly.In this paper,we investigate the impact of the randomness caused by the movement of the IoT user on decision-making for offloading,where the connection between the IoT user and the MEC servers is uncertain.This uncertainty would be the main obstacle to assign the task accurately.Consequently,if the assigned task cannot match well with the real connection time,a migration(connection time is not enough to process)would be caused.In order to address the impact of this uncertainty,we formulate the offloading decision as an optimization problem considering the transmission,computation and migration.With the help of Stochastic Programming(SP),we use the posteriori recourse to compensate for inaccurate predictions.Meanwhile,in heterogeneous networks,considering multiple candidate MEC servers could be selected simultaneously due to overlapping,we also introduce the Multi-Arm Bandit(MAB)theory for MEC selection.The extensive simulations validate the improvement and effectiveness of the proposed SP-based Multi-arm bandit Method(SMM)for offloading in terms of reward,cost,energy consumption and delay.The results showthat SMMcan achieve about 20%improvement compared with the traditional offloading method that does not consider the randomness,and it also outperforms the existing SP/MAB based method for offloading.

关键词： Multi-access computing Internet of things Offloading Stochastic programming Multi-arm bandit

Confidence-weighted mutual supervision on dual networks for unsupervised cross-modality image segmentation

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Science China(Information Sciences) 2023年第11期66卷 54-68页

作者： Yajie CHEN Xin YANG xiang bai School of Electronic Information and Communications Huazhong University of Science and Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology

The unsupervised cross-modality image segmentation has gained much attention. Many methods attempt to align different modalities via adversarial learning. Recently, self-training with pseudo labels for the unsupervised target modality has also been widely used and achieved very promising results. The pseudo labels are usually obtained by selecting reliable predictions whose highest predicted probability is larger than an empirically set value. Such pseudo label generation inevitably has noise and training a segmentation model using incorrect pseudo labels could yield nontrivial errors for the target modality. In this paper, we propose a confidence-weighted mutual supervision on dual networks for unsupervised cross-modality image segmentation. Specifically, we independently initialize two networks with the same architecture, and propose a novel confidence-weighted Dice loss to mutually supervise the two networks using their predicted results for unlabeled data. In this way, we make full use of all predictions of unlabeled images and leverage the prediction confidence to alleviate the negative impact of noisy pseudo labels. Extensive experiments on three widely-used unsupervised cross-modality image segmentation datasets(i.e., MM-WHS 2017, Brats 2018, and Multi-organ segmentation) demonstrate that the proposed method achieves superior performance to some state-of-the-art methods.

关键词： domain adaptation pseudo label mutual supervision cross-modality image segmentation

TransCrowd: weakly-supervised crowd counting with transformers

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Science China(Information Sciences) 2022年第6期65卷 48-61页

作者： Dingkang LIANG Xiwu CHEN Wei XU Yu ZHOU xiang bai School of Artificial Intelligence and Automation Huazhong University of Science and Technology School of Electronic Information and Communication Huazhong University of Science and Technology School of Artificial Intelligence Beijing University of Posts and Telecommunications

The mainstream crowd counting methods usually utilize the convolution neural network(CNN)to regress a density map, requiring point-level annotations. However, annotating each person with a point is an expensive and laborious process. During the testing phase, the point-level annotations are not considered to evaluate the counting accuracy, which means the point-level annotations are redundant. Hence,it is desirable to develop weakly-supervised counting methods that just rely on count-level annotations, a more economical way of labeling. Current weakly-supervised counting methods adopt the CNN to regress a total count of the crowd by an image-to-count paradigm. However, having limited receptive fields for context modeling is an intrinsic limitation of these weakly-supervised CNN-based methods. These methods thus cannot achieve satisfactory performance, with limited applications in the real world. The transformer is a popular sequence-to-sequence prediction model in natural language processing(NLP), which contains a global receptive field. In this paper, we propose TransCrowd, which reformulates the weakly-supervised crowd counting problem from the perspective of sequence-to-count based on transformers. We observe that the proposed TransCrowd can effectively extract the semantic crowd information by using the self-attention mechanism of transformer. To the best of our knowledge, this is the first work to adopt a pure transformer for crowd counting research. Experiments on five benchmark datasets demonstrate that the proposed TransCrowd achieves superior performance compared with all the weakly-supervised CNN-based counting methods and gains highly competitive counting performance compared with some popular fully-supervised counting methods.

关键词： crowd counting visual transformer weakly supervised crowd analysis transformer

Effect of dapagliflozin on uric acid in patients with chronic heart failure and hyperuricemia

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World Journal of Clinical Cases 2024年第18期12卷 3468-3475页

作者： Meng-Jiao Lin Shu-Bin Zou bai-xiang Zhu Three departments of cardiovascular medicine Harbin 242 HospitalHarbin 150066Heilongjiang ProvinceChina

BACKGROUND Patients with chronic heart failure(CHF)frequently develop hyperuricemia,an elevated serum uric acid level,associated with adverse outcomes.Dapagliflozin,a sodium-glucose cotransporter-2 inhibitor,demonstrates reduction in cardiovascular mortality and hospitalization in patients with CHF and ejection fraction(HFrEF),irrespective of diabetes.However,dapagliflozin’s effect on the uric acid levels in patients with CHF and hyperuricemia remain unclear.AIM To investigate the effects of dapagliflozin on uric acid levels in CHF patients with hyperuricemia.METHODS We conducted a randomized,double-blind,placebo-controlled trial in 200 patients with CHF and hyperuricemia,with HFrEF and serum uric acid levels≥7 mg/dL(≥416μmol/L).The participants were randomly assigned to receive a daily dose of 10 mg dapagliflozin or placebo for 24 months.The primary endpoint was the change in serum uric acid level from baseline to 24 months.Secondary endpoints included changes in left ventricular ejection fraction(LVEF),Nterminal pro-B-type natriuretic peptide(NT-proBNP),and quality of life(QoL)scores,as well as the incidence of cardiovascular death and hospitalization for heart failure.RESULTS At 24 months,dapagliflozin significantly reduced serum uric acid levels by 1.2 mg/dL(71μmol/L)compared with placebo(95%CI:-1.5 to-0.9;P<0.001).Dapagliflozin also significantly improved LVEF by 3.5%(95%CI:2.1-4.9;P<0.001),NT-proBNP by 25%(95%CI:18-32;P<0.001),and QoL scores by 10 points(95%CI:7-13;P<0.001)and reduced the risk of cardiovascular death and hospitalization for heart failure by 35%(95%CI:15–50;P=0.002)compared with the placebo.Adverse events were similar between the two groups,except for a higher rate of genital infections in the dapagliflozin group(10%vs 2%,P=0.01).CONCLUSION Dapagliflozin significantly lowered serum uric acid levels and improved the clinical outcomes in patients with CHF and hyperuricemia.Therefore,dapagliflozin may be a useful therapeutic option for this high-risk population.

关键词： Dapagliflozin Hyperuricemia Chronic heart failure Sodium-glucose cotransporter-2 inhibitor Uric acid levels Cardiovascular mortality

Comprehensive benchmark datasets for Amharic scene text detection and recognition

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Science China(Information Sciences) 2022年第6期65卷 77-78页

作者： Wondimu DIKUBAB Dingkang LIANG Minghui LIAO xiang bai School of Electronic Information and Communication Huazhong University of Science and Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology

Ethiopic/Amharic script is one of the oldest African writing systems, which serves at least 23 languages(e.g., Amharic,Tigrinya) in East Africa for more than 120 million people.The Amharic writing system, Abugida, has 282 syllables,15 punctuation marks, and 20 numerals. The Amharic syllabic matrix is derived from 34 base graphemes/consonants by adding up to 12 appropriate diacritics or vocalic markers to the characters. Unlike Latin alphabets,

关键词： Amharic script Scene text Text detection Text recognition Amharic text

YOLOP:You Only Look Once for Panoptic Driving Perception

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Machine Intelligence Research 2022年第6期19卷 550-562页

作者： Dong Wu Man-Wen Liao Wei-Tian Zhang Xing-Gang Wang xiang bai Wen-Qing Cheng Wen-Yu Liu Hubei Key Laboratory of Smart Internet Technology School of Electronic Information and CommunicationsHuazhong University of Science and TechnologyWuhan 430074China School of Electronic Information and Communication Huazhong University of Science and TechnologyWuhan 430074China School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China

A panoptic driving perception system is an essential part of autonomous driving.A high-precision and real-time perception system can assist the vehicle in making reasonable decisions while driving.We present a panoptic driving perception network(you only look once for panoptic(YOLOP))to perform traffic object detection,drivable area segmentation,and lane detection simultaneously.It is composed of one encoder for feature extraction and three decoders to handle the specific tasks.Our model performs extremely well on the challenging BDD100K dataset,achieving state-of-the-art on all three tasks in terms of accuracy and speed.Besides,we verify the effectiveness of our multi-task learning model for joint training via ablative studies.To our best knowledge,this is the first work that can process these three visual perception tasks simultaneously in real-time on an embedded device Jetson TX2(23 FPS),and maintain excellent accuracy.To facilitate further research,the source codes and pre-trained models are released at https://***/hustvl/YOLOP.

关键词： Driving perception multitask learning traffic object detection drivable area segmentation lane detection

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钠-葡萄糖协同转运蛋白2及其抑制剂与相关疾病

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中国生物化学与分子生物学报 2024年第2期40卷 188-197页

作者：丁百香天津大学生命科学学院结构生物学实验室天津300072

葡萄糖(glucose)是生物最主要的供能物质,是活细胞的能量来源和新陈代谢的中间产物,并在细胞信号传递中发挥着重要作用。异常葡萄糖代谢经常与糖尿病、视网膜病变、阿尔兹海默症以及心血管疾病等相关。钠-葡萄糖协同转运蛋白2(sodium-gl... 详细信息

葡萄糖(glucose)是生物最主要的供能物质,是活细胞的能量来源和新陈代谢的中间产物,并在细胞信号传递中发挥着重要作用。异常葡萄糖代谢经常与糖尿病、视网膜病变、阿尔兹海默症以及心血管疾病等相关。钠-葡萄糖协同转运蛋白2(sodium-glucose cotransporter 2,SGLT2)是机体内参与维持葡萄糖稳态的转运体之一,介导肾对葡萄糖的重吸收,对维持血浆葡萄糖稳定有着重要作用。钠-葡萄糖协同转运蛋白2抑制剂(sodium-glucose cotransporter 2 inhibitor,SGLT2i)可减少肾对葡萄糖的重吸收,对于血糖、血压、体重等产生积极影响。本文总结了当前SGLT2及其抑制剂的研究进展,综述了SGLT2结构及关键位点、SGLT2i作用机制,特别是近几年的研究发现,SGLT2i对肾及心血管的保护作用愈加明显,同时还能抵抗肿瘤细胞的发生和发展。最后,本文总结讨论了目前针对SGLT2i相关研究的瓶颈问题,为未来基于结构的抑制剂药物优化提供新思路。

关键词：葡萄糖代谢钠-葡萄糖协同转运蛋白2 钠-葡萄糖协同转运蛋白2抑制剂心血管和肾癌症

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Hydrogen solubility prediction for diesel molecules based on a modified Henry equation

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Petroleum Science 2022年第1期19卷 363-374页

作者： Run Guo xiang bai Yang Lu Lin-Zhou Zhang Xing-Ying Lan Zhen-Tao Chen Quan Shi Suo-Qi Zhao State Key Laboratory of Heavy Oil Processing&Petroleum Molecular Engineering Center(PMEC) China University of PetroleumBeijing 102249People's Republic of China

Diesel hydrotreatment removes heteroatoms and polycyclic aromatics in diesel in the presence of highpressure hydrogen gas.The hydrogen solubility is the basis for hydrogen consumption prediction and process design/optimization.In the presented study,we established a method to predict the hydrogen solubility of diesel molecules and mixture.A modified Henry equation was proposed to illustrate the hydrogen solubility variation among the temperature and pressure.The parameters of the modified Henry equation for typical molecules were regressed from literature data.Then we established an empirical correlation between the parameter and the structure and property of molecules.The method was then combined with a molecular-level compositional model to accurately predict the hydrogen solubility in diesel,illustrating the validity of the method.

关键词： Diesel hydrotreatment Hydrogen solubility Modified henry equation Molecular-level compositional model

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Scene text detection and recognition： recent advances and future trends

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Frontiers of Computer Science 2016年第1期10卷 19-36页

作者： Yingying ZHU Cong YAO xiang bai School of Electronic Information and Communications Huazhong University of Science and Technology Wuhan 430074 China

Text, as one of the most influential inventions of humanity, has played an important role in human life, so far from ancient times. The rich and precise information embod- ied in text is very useful in a wide range of vision-based ap- plications, therefore text detection and recognition in natu- ral scenes have become important and active research topics in computer vision and document analysis. Especially in re- cent years, the community has seen a surge of research efforts and substantial progresses in these fields, though a variety of challenges （e.g. noise, blur, distortion, occlusion and varia- tion） still remain. The purposes of this survey are three-fold： 1） introduce up-to-date works, 2） identify state-of-the-art al- gorithms, and 3） predict potential research directions in the future. Moreover, this paper provides comprehensive links to publicly available resources, including benchmark datasets, source codes, and online demos. In summary, this literature review can serve as a good reference for researchers in the areas of scene text detection and recognition.

关键词： text detection text recogntion natural image,algorithms applications