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29th International Conference on Geoinformatics, Geoinformatics 2022

作者： Wang, Yi'an Cai, Fangyi Cheng, Shih-Fen Wu, Bo Cao, Kai School of Geographic Sciences East China Normal University Shanghai China East China Normal University Key Laboratory of Geographic Information Science Ministry of Education Shanghai China East China Normal University Key Lab. of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities Ministry of Natural Resources Shanghai China National University of Singapore Department of Geography Singapore School of Computing and Information Systems Singapore Management University Singapore School of Geography and Environment Jiangxi Normal University Jiangxi Nanchang China

ISBN: (数字)9798350309881

ISBN: (纸本)9798350309881

In this research, a taxi travel time based Geographically Weighted Regression model (GWR) is proposed and utilized to model the public housing price in the case study of Singapore. In addition, a comparison between the proposed taxi data driven GWR and other models, such as ordinary least squares model (OLS), GWR model based on Euclidean distance and GWR model based on public transport travel time, have also been carried out. Results indicates that taxi travel time based GWR model has better fitting performance than the OLS model, and slightly better than the Euclidean distance-based GWR model, however, it is not as good as the GWR model based on public transport travel time according to the metric of Adjusted R2. These experiments indicate that the public transport travel time may has a major part to play in modeling the public housing resale prices compared to taxi travel time or driving time, and both the taxi travel time and public transport travel time can better explain the public housing resale prices in Singapore compared to Euclidean distance in the GWR modeling. © 2022 IEEE.

关键词： Travel time

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Seq-Masks: Bridging the gap between appearance and gait modeling for video-based person re-identification

arXiv

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arXiv 2021年

作者： Chang, Zhigang Yang, Zhao Chen, Yongbiao Zhou, Qin Zheng, Shibao Institute of Image Processing and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China

Video-based person re-identification (Re-ID) aims to match person images in video sequences captured by disjoint surveillance cameras. Traditional video-based person Re-ID methods focus on exploring appearance information, thus, vulnerable against illumination changes, scene noises, camera parameters, and especially clothes/carrying variations. Gait recognition provides an implicit biometric solution to alleviate the above headache. Nonetheless, it experiences severe performance degeneration as camera view varies. In an attempt to address these problems, in this paper, we propose a framework that utilizes the sequence masks (SeqMasks) in the video to integrate appearance information and gait modeling in a close fashion. Specifically, to sufficiently validate the effectiveness of our method, we build a novel dataset named MaskMARS based on MARS. Comprehensive experiments on our proposed large wild video Re-ID dataset MaskMARS evidenced our extraordinary performance and generalization capability. Validations on the gait recognition metric CASIA-B dataset further demonstrated the capability of our hybrid model. Our codes and dataset MaskMARS will be open-sourced as a strong baseline. © 2021, CC BY.

关键词： Gait analysis

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DMNER: Biomedical Named Entity Recognition by Detection and Matching

DMNER: Biomedical Named Entity Recognition by Detection and ...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Junyi Bian Rongze Jiang Weiqi Zhai Tianyang Huang Xiaodi Huang Hong Zhou Shanfeng Zhu School of Computer Science Fudan University Shanghai China Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai China School of Computing Mathematics and Engineering Charles Sturt University New South Wales Australia Atypon Systems LLC UK Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Institute of Science and Technology for Brain-Inspired Intelligence and MOE Frontiers Center for Brain Science Shanghai Key Lab of Intelligent Information Processing Zhangjiang Fudan International Innovation Center Fudan University Shanghai China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Biomedical Named Entity Recognition (NER) is a crucial task in extracting information from biomedical texts. However, the diversity of professional terminology, semantic complexity, and the widespread presence of synonyms pose significant challenges. Traditional methods that rely on sequence labeling training datasets often struggle to handle these complexities. To address this, we introduce a novel framework for BioNER, termed DMNER, which leverages external knowledge and operates in two steps: entity boundary detection and entity category identification through matching. The core of DMNER is its second step, which determines the entity category by retrieving similar entities and their categories from a knowledge dictionary using semantic similarity matching. Our experiments on 10 biomedical datasets demonstrate that DMNER outperforms baselines across these tasks, proving its effectiveness and adaptability. DMNER is versatile and can be applied to various NER tasks, including supervised NER, distantly supervised NER, and NER on multiple datasets with disjoint label sets. The DMNER code is publicly available 1 .

关键词： Training Dictionaries Codes Semantics Named entity recognition Complexity theory labeling Data mining Bioinformatics

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Task Offloading and Dispatching for MEC with Selfish Mobile Devices and Access Points

Task Offloading and Dispatching for MEC with Selfish Mobile ...

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GLOBECOM 2020 - 2020 IEEE Global Communications Conference

作者： Lu Fang Tong Liu Yanmin Zhu Yuanyuan Yang School of Computer Engineering and Science Shanghai University Shanghai Engineering Research Center of Intelligent Computing System Shanghai Key Lab of Scalable Computing and Systems Stony Brook University

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

Multi-access Edge computing (MEC) comes forth as a promising computing paradigm to meet the low-delay requirements of computation-intensive applications. In this work, we focus on the task offloading and dispatching problem in MEC, where mobile devices (MDs) can decide to execute tasks locally or offload them to access points (APs), and each AP can dispatch its received tasks to other APs. Specially, we consider both APs and MDs are selfish, which aim to minimize their respective task completion delay. The problem is particularly difficult, as there exists computing resource competition among MDs and APs, respectively. Furthermore, the offloading decisions made by MDs and the dispatching decisions made by APs are interactive. To overcome the challenges, we first formulate the problem as a multi-leader multi-follower Stackelberg game, and rigorously prove the existence of a Stackelberg equilibrium. Then, we propose an efficient approach to achieve a Stackelberg equilibrium, which includes a Q-learning based offloading strategy for MDs and a best response based dispatching strategy for APs. We also demonstrate an upper bound of the total completion delay achieved by our approach with a constant approximation ratio. Extensive simulations are also conducted to show the performance of our approach, compared with baselines.

关键词： Upper bound Simulation Games Dispatching Mobile handsets Delays Task analysis

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Vertical Federated Learning: Challenges, Methodologies and Experiments

arXiv

引用

arXiv 2022年

作者： Wei, Kang Li, Jun Ma, Chuan Ding, Ming Wei, Sha Wu, Fan Chen, Guihai Ranbaduge, Thilina School of Electrical and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China Ministry of Education China Data61 CSIRO SydneyNSW2015 Australia Beijing100191 China The Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China

Recently, federated learning (FL) has emerged as a promising distributed machine learning (ML) technology, owing to the advancing computational and sensing capacities of end-user devices, as well as the increasing concerns on users' privacy. As a special architecture in FL, vertical FL (VFL) is capable of constructing a hyper ML model by embracing sub-models from different types of clients. These sub-models are trained locally by vertically partitioned data with distinct attributes. Therefore, the design of VFL is fundamentally different from that of conventional FL, raising new and unique research issues. In this paper, we aim to discuss key challenges in VFL with effective solutions, and conduct experiments on real-life datasets to shed light on these issues. Specifically, we first propose a general framework on VFL, and highlight the key differences between VFL and conventional FL. Then, we discuss research challenges rooted in VFL systems from four aspects, i.e., security and privacy risks, expensive computation and communication costs, possible structural damage caused by model splitting, and system heterogeneity. Afterwards, we develop solutions to addressing the aforementioned challenges, and conduct extensive experiments to showcase the effectiveness of the proposed solutions. Copyright © 2022, The Authors. All rights reserved.

关键词： Federated learning

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A differential public PUF design for lightweight authentication 16

A differential public PUF design for lightweight authenticat...

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2021 International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design, SMACD 2021 and 16th Conference on PhD Research in Microelectronics and Electronics, PRIME 2021

作者： Duan, Shengyu Sai, Gaole School of Computer Engineering and Science Shanghai University Shanghai200444 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (纸本)9783800755899

Physical Unclonable Functions (PUFs) have emerged as a promising primitive to provide a hardware keyless security mechanism for integrated circuit applications. Public PUFs (PPUFs) address the crucial PUF vulnerability of requiring databases to store the secrete reference information. This paper investigates one of the PPUF families, differential PPUF (dPPUF), which exploits complexly interacted logic to create time gap between actual execution and simulation, and to prevent simulation attacks. Conventional dPPUFs have high costs. We observe the repressers have large impact on simulation time, but take a great proportion in current dPPUF structure. We thereby present a represser network with specially designed interconnection and shared logic, to maintain a high circuit complexity and to reduce the area cost. We show the proposed dPPUF has similar resilience over simulation attacks as the conventional design. Area cost can be reduced by up to 44%, and thus the proposed design can be used for lightweight authentication. © VDE VERLAG GMBH.

关键词： Authentication

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WarmCache: A Comprehensive Distributed Storage System Combining Replication, Erasure Codes and Buffer Cache 13th

WarmCache: A Comprehensive Distributed Storage System Combin...

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13th International Conference on Green, Pervasive, and Cloud computing, GPC 2018

作者： Ignacio, Brian A. Wu, Chentao Li, Jie Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783030150921

A tiered storage system uses replication method to provide both high reliability and availability, which stores three replicas over different nodes in the clusters. Erasure codes (EC) such as Reed-Solomon (RS) are increasingly utilized to further reduce the storage overhead while providing low I/O performance and availability. Existing solutions nowadays implement heterogeneous storage systems either using triple replication, erasure coding methods or a combination of both, although involves high performance gap between each data layer. To address this problem, in this paper, we introduce WarmCache, a new data layer for warm data by having one copy stored using erasure coding and the other copy in memory data layer. Using one copy in erasure coding data layer ensures data reliability, while the other copy in memory data layer provides fast I/O performance. © 2019, Springer Nature Switzerland AG.

关键词： Multiprocessing systems

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Online Pricing with Reserve Price Constraint for Personal Data Markets

Online Pricing with Reserve Price Constraint for Personal Da...

引用

International Conference on Data Engineering

作者： Chaoyue Niu Zhenzhe Zheng Fan Wu Shaojie Tang Guihai Chen Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China Department of Information Systems University of Texas at Dallas USA

ISBN: (数字)9781728129037

ISBN: (纸本)9781728129044

The society's insatiable appetites for personal data are driving the emergency of data markets, allowing data consumers to launch customized queries over the datasets collected by a data broker from data owners. In this paper, we study how the data broker can maximize her cumulative revenue by posting reasonable prices for sequential queries. We thus propose a contextual dynamic pricing mechanism with the reserve price constraint, which features the properties of ellipsoid for efficient online optimization, and can support linear and non-linear market value models with uncertainty. In particular, under low uncertainty, our pricing mechanism provides a worst-case regret logarithmic in the number of queries. We further extend to other similar application scenarios, including hospitality service and online advertising, and extensively evaluate all three application instances over MovieLens 20M dataset, Airbnb listings in U.S. major cities, and Avazu mobile ad click dataset, respectively. The analysis and evaluation results reveal that our proposed pricing mechanism incurs low practical regret, online latency, and memory overhead, and also demonstrate that the existence of reserve price can mitigate the cold-start problem in a posted price mechanism, and thus can reduce the cumulative regret.

关键词： Pricing Uncertainty Data privacy Data models Ellipsoids Privacy Estimation

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Towards Integrated Traffic Control with Operating Decentralized Autonomous Organization

Towards Integrated Traffic Control with Operating Decentrali...

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International Conference on Intelligent Transportation

作者： Shengyue Yao Jingru Yu Yi Yu Jia Xu Xingyuan Dai Honghai Li Fei-Yue Wang Yilun Lin Urban Computing Shanghai AI Lab Shanghai China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Research and Development Center of Transport Industry of Autonomous Driving Technology RIOH High and Technology Group Institute of Automation Chinese Academy of Sciences Beijing China Macau Institute of Systems Engineering Macau University of Science and Technology Macau China

With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS that is capable of considering plentiful heterogeneous intelligent agents is desired. However, existing control methods based on the centralized or the decentralized scheme have not presented their competencies in considering the optimality and the scalability simultaneously. To address this issue, we propose an integrated control method based on the framework of Decentralized Autonomous Organization (DAO). The proposed method achieves a global consensus on energy consumption efficiency (ECE), meanwhile to optimize the local objectives of all involved intelligent agents, through a consensus and incentive mechanism. Furthermore, an operation algorithm is proposed regarding the issue of structural rigidity in DAO. Specifically, the proposed operation approach identifies critical agents to execute the smart contract in DAO, which ultimately extends the capability of DAO-based control. In addition, a numerical experiment is designed to examine the performance of the proposed method. The experiment results indicate that the controlled agents can achieve a consensus faster on the global objective with improved local objectives by the proposed method, compare to existing decentralized control methods. In general, the proposed method shows a great potential in developing an integrated control system in the ITS.

关键词：

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Towards Integrated Traffic Control with Operating Decentralized Autonomous Organization

arXiv

引用

arXiv 2023年

作者： Yao, Shengyue Yu, Jingru Yu, Yi Xu, Jia Dai, Xingyuan Li, Honghai Wang, Fei-Yue Lin, Yilun Urban Computing Shanghai AI Lab Shanghai China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The Research and Development Center of Transport Industry of Autonomous Driving Technology RIOH High and Technology Group The Institute of Automation Chinese Academy of Sciences Beijing China The Macau Institute of Systems Engineering Macau University of Science and Technology China

关键词： Integrated control

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