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370 results on '"Mu, Shuai"'

2. Verifiable Sustainability in Data Centers

Author

Hussain, Syed Rafiul, McDaniel, Patrick, Gandhi, Anshul, Ghose, Kanad, Gopalan, Kartik, Lee, Dongyoon, Liu, Yu David, Liu, Zhenhua, Mu, Shuai, and Zadok, Erez

Subjects
Computer Science - Cryptography and Security, Computer Science - Computers and Society, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Operating Systems, Electrical Engineering and Systems Science - Systems and Control
Abstract

Data centers have significant energy needs, both embodied and operational, affecting sustainability adversely. The current techniques and tools for collecting, aggregating, and reporting verifiable sustainability data are vulnerable to cyberattacks and misuse, requiring new security and privacy-preserving solutions. This paper outlines security challenges and research directions for addressing these pressing requirements.

Published
2023

3. NCC: Natural Concurrency Control for Strictly Serializable Datastores by Avoiding the Timestamp-Inversion Pitfall

Author

Lu, Haonan, Mu, Shuai, Sen, Siddhartha, and Lloyd, Wyatt

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, C.2.4
Abstract

Strictly serializable datastores greatly simplify the development of correct applications by providing strong consistency guarantees. However, existing techniques pay unnecessary costs for naturally consistent transactions, which arrive at servers in an order that is already strictly serializable. We find these transactions are prevalent in datacenter workloads. We exploit this natural arrival order by executing transaction requests with minimal costs while optimistically assuming they are naturally consistent, and then leverage a timestamp-based technique to efficiently verify if the execution is indeed consistent. In the process of designing such a timestamp-based technique, we identify a fundamental pitfall in relying on timestamps to provide strict serializability, and name it the timestamp-inversion pitfall. We find timestamp-inversion has affected several existing works. We present Natural Concurrency Control (NCC), a new concurrency control technique that guarantees strict serializability and ensures minimal costs -- i.e., one-round latency, lock-free, and non-blocking execution -- in the best (and common) case by leveraging natural consistency. NCC is enabled by three key components: non-blocking execution, decoupled response control, and timestamp-based consistency check. NCC avoids timestamp-inversion with a new technique: response timing control, and proposes two optimization techniques, asynchrony-aware timestamps and smart retry, to reduce false aborts. Moreover, NCC designs a specialized protocol for read-only transactions, which is the first to achieve the optimal best-case performance while ensuring strict serializability, without relying on synchronized clocks. Our evaluation shows that NCC outperforms state-of-the-art solutions by an order of magnitude on many workloads.

Published
2023

8. Detecting Incorrect Behavior of Cloud Databases as an Outsider

Author

Tan, Cheng, Zhao, Changgeng, Mu, Shuai, and Walfish, Michael

Subjects
Computer Science - Databases
Abstract

Cloud DBs offer strong properties, including serializability, sometimes called the gold standard database correctness property. But cloud DBs are complicated black boxes, running in a different administrative domain from their clients; thus, clients might like to know whether the DBs are meeting their contract. A core difficulty is that the underlying problem here, namely verifying serializability, is NP-complete. Nevertheless, we hypothesize that on real-world workloads, verifying serializability is tractable, and we treat the question as a systems problem, for the first time. We build Cobra, which tames the underlying search problem by blending a new encoding of the problem, hardware acceleration, and a careful choice of a suitable SMT solver. cobra also introduces a technique to address the challenge of garbage collection in this context. cobra improves over natural baselines by at least 10x in the problem size it can handle, while imposing modest overhead on clients.

Published
2019

9. The level of macrophage migration inhibitory factor is negatively correlated with the efficacy of PD-1 blockade immunotherapy combined with chemotherapy as a neoadjuvant therapy for esophageal squamous cell carcinoma

Author

Wu, Liangliang, Gao, Yiming, Xie, Shengzhi, Ye, Wan, Uemura, Yasushi, Zhang, Rong, Yu, Yanju, Li, Jinfeng, Chen, Man, Wu, Qiyan, Cui, Pengfei, Liu, Hongyu, Mu, Shuai, Li, Yilan, Wang, Lingxiong, Liu, Chunxi, Li, Jiahui, Zhang, Lijun, Jiao, Shunchang, Zhang, Guoqing, and Liu, Tianyi

Published
2023
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10. On the parallels between Paxos and Raft, and how to port optimizations

Author

Wang, Zhaoguo, Zhao, Changgeng, Mu, Shuai, Chen, Haibo, and Li, Jinyang

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

In recent years, Raft has overtaken Paxos as the consensus algorithm of choice. [53] While many have pointed out similarities between the two protocols, no one has formally mapped out their relationships. In this paper, we show how Raft and Paxos are formally related despite their surface differences. Based on the formal mapping between the two protocols, we show how to automatically port a certain class of optimizations from Paxos to Raft with guaranteed correctness. As case studies, we port and evaluate two optimizations, Mencius and Paxos Quorum Lease to Raft.

Published
2019

13. Improving Image Captioning with Conditional Generative Adversarial Nets

Author

Chen, Chen, Mu, Shuai, Xiao, Wanpeng, Ye, Zexiong, Wu, Liesi, and Ju, Qi

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, 68T45
Abstract

In this paper, we propose a novel conditional-generative-adversarial-nets-based image captioning framework as an extension of traditional reinforcement-learning (RL)-based encoder-decoder architecture. To deal with the inconsistent evaluation problem among different objective language metrics, we are motivated to design some "discriminator" networks to automatically and progressively determine whether generated caption is human described or machine generated. Two kinds of discriminator architectures (CNN and RNN-based structures) are introduced since each has its own advantages. The proposed algorithm is generic so that it can enhance any existing RL-based image captioning framework and we show that the conventional RL training method is just a special case of our approach. Empirically, we show consistent improvements over all language evaluation metrics for different state-of-the-art image captioning models. In addition, the well-trained discriminators can also be viewed as objective image captioning evaluators, Comment: 12 pages; 33 figures; 36 refenences; Accepted by AAAI2019

Published
2018
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17. The Construction Method and Research of Military Online Courses

Author

Chang, Hai, Mu, Shuai, Wang, Rui jie, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, 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, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, 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, Zhang, Junjie James, Series Editor, Long, Shengzhao, editor, and Dhillon, Balbir S., editor

Published
2020
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24. On Academic Evaluation Index System of Weaponry Subject

Author

Chang, Hai, Zhang, Bingjun, Ji, Zengjun, Mu, Shuai, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Long, Shengzhao, editor, and Dhillon, Balbir S., editor

Published
2019
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25. Research on Field Rescue Based on Expedient Material

Author

Pang, Zhingbing, Li, Huawei, Sui, Mingming, Hu, Kunyuan, Luo, Zhaofeng, Mu, Shuai, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Long, Shengzhao, editor, and Dhillon, Balbir S., editor

Published
2019
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26. Study on 5-km Armed Cross-Country Training in the Plateau Hypoxic Environment

Author

Mu, Shuai, Kong, Ming, Wang, Huifang, Chang, Hai, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Long, Shengzhao, editor, and Dhillon, Balbir S., editor

Published
2019
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30. Verifiable Sustainability in Data Centers

Author

Hussain, Syed Rafiul, primary, McDaniel, Patrick, additional, Gandhi, Anshul, additional, Ghose, Kanad, additional, Gopalan, Kartik, additional, Lee, Dongyoon, additional, Liu, Yu David, additional, Liu, Zhenhua, additional, Mu, Shuai, additional, and Zadok, Erez, additional

Published
2024
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33. Fungal-derived brevianamide assembly by a stereoselective semipinacolase

Author

Ye, Ying, Du, Lei, Zhang, Xingwang, Newmister, Sean A., McCauley, Morgan, Alegre-Requena, Juan V., Zhang, Wei, Mu, Shuai, Minami, Atsushi, Fraley, Amy E., Adrover-Castellano, Maria L., Carney, Nolan A., Shende, Vikram V., Qi, Feifei, Oikawa, Hideaki, Kato, Hikaru, Tsukamoto, Sachiko, Paton, Robert S., Williams, Robert M., Sherman, David H., and Li, Shengying

Published
2020
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41. Using Health Forum Data to Assess User Needs for mHealth App Development: A Feasibility Study on Alzheimer’s Disease

Author

Wu, Danny T.Y., Bindhu, Shwetha, Vu, Hoang, Mu, Shuai, Xu, Catherine, Pandey, Somya, Harnett, Brett, and Lee, James J.

Subjects
Articles
Abstract

Online health forums are used by patients and caregivers as community and information resources, especially for chronic disease management, and could help determine user needs for digital health app design. This study aims to assess the feasibility of using online forum posts on Alzheimer’s disease to inform user needs in mobile health application design and whether this process can be automated through text clustering methods. A total of 413 posts were analyzed manually through thematic coding and yielded three themes and nine subthemes for patient and caregiver needs. The external evaluation showed fair to substantial similarity between the automatically and manually derived labels. Four personas were developed to assess the validity of forum-generated needs. These results establish that health forum data can provide sufficient information to understand user needs. However, further refinement of the analysis process and algorithm is necessary to generalize this method to other disease conditions and types of forum data.

Published
2023

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