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BPDST: Blockchain-Based Privacy-Preserving Data Sharing on Thin Client for Electronic Medical Records

Journal of Computing and Information technology 2022年第4期29卷 235-250页

作者： Xu, Lu Lin, Mengchen Feng, Yong Sun, Yani Yunnan Provincial Key Laboratory of Computer Technology Applications Kunming University of Science and Technology Kunming China Yunnan Provincial Key Laboratory of Blockchain Application Technology Yunnan Innovation Research Institute of Beijing University of Aeronautics and Astronautics Kunming China

Sharing medical data can improve the quality of medical services and reduce costs. However, the current Electronic Medical Records (EMRs) are scattered and easily tampered with, which is not conducive to the sharing of EMRs and is not compatible with thin clients. Fortunately, blockchain technology is tamper-proof, decentralized, auditable, and meets the above requirements. To solve these problems, we first propose Blockchain-Based Privacy-Preserving Data Sharing on Thin-Client for Electronic Medical Records (BPDST) approach that combines the k-anonymity and cloud storage, which thin clients can run like a full-node user and safeguard user's EMRs privacy concurrently. Using this approach, patients can control their own EMRs, while the consortium blockchain is responsible for the transaction process and sending the correct results to the patients. BPDST can also share information without leaking or tampering with EMRs' privacy, achieving the purpose of sharing medical data and privacy protection. In the medical field, this study can effectively protect users' privacy when sharing medical data to provide convenience for users and break the "island" phenomenon among various medical institutions. Security analysis and extensive experiments show that BPDST is secure and practical for sharing EMRs © 2022, Journal of Computing and Information *** Rights Reserved.

关键词： Blockchain

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An Auto-Parallel Method for Deep Learning Models Based on Genetic Algorithm

An Auto-Parallel Method for Deep Learning Models Based on Ge...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Yan Zeng ChengChuang Huang YiJie Ni ChunBao Zhou JiLin Zhang Jue Wang MingYao Zhou MeiTing Xue YunQuan Zhang School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory for Modeling and Simulation of Complex Systems Ministry of Education Hangzhou China Data Security Governance Zhejiang Engineering Research Center Hangzhou China School of ITMO Joint Institute Hangzhou Dianzi University Hangzhou China Institute of Computer Network Information Center of the Chinese Academy of Sciences Beijing China HuaWei State Key Laboratory of Computer Architecture Institute of Computing Technology of the Chinese Academy of Sciences Beijing China

As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network’s dataflow graph and device cluster’s topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method.

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An Anomalous Data Identification Approach for PV Generation Based on Quadratic and Intra-group Variance Method

An Anomalous Data Identification Approach for PV Generation ...

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China International Electrical and Energy Conference (CIEEC)

作者： Huanlong Li Ke Liu Chen Chen Laijun Chen Department of Computer Technology and Applications Qinghai University Xining China State Grid Qinghai Electric Power Research Institute State Grid Qinghai Electric Power Company Xining China Department of Electrical Engineering and Applied Electronics Technology Qinghai University Beijing China

Due to environmental factors and equipment failures, a certain amount of anomalous data will be mixed into the collected data, which leads to the subsequent power prediction work being more difficult. To solve this problem, a combined method is proposed based on the quadratic and the optimal interclass variance algorithm. Firstly, the analysis of the photovoltaic power dataset shows that photovoltaic power dataset contains both scattered and stacked anomalies.. Then, the anomalous data in the dataset can be identified as scattered anomalous data and stacked anomalous data in the dataset by using the quartile method and the optimal interclass variance algorithm respectively. To verify the feasibility of the proposed method, the anomalous data in the dataset are removed, and then the LSTM model is used to make predictions and the final prediction results are used to support the advantages and disadvantages of the method. The results show that compared with the quadratic method and the optimal intra-group variance method alone, the data processed by the combined method in this paper makes the LSTM model have higher prediction accuracy, thus indicating that the proposed method has better recognition effect.

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Dynamic Prefix-Tuning for Generative Template-based Event Extraction

arXiv

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arXiv 2022年

作者： Liu, Xiao Huang, Heyan Shi, Ge Wang, Bo School of Computer Science and Technology Beijing Institute of Technology China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications China Key Laboratory of Intelligent Information Processing and Information Security Ministry of Industry and Information Technology China Southeast Academy of Information Technology Beijing Institute of Technology China Faculty of Information Technology Beijing University of Technology China

We consider event extraction in a generative manner with template-based conditional generation. Although there is a rising trend of casting the task of event extraction as a sequence generation problem with prompts, these generation-based methods have two significant challenges, including using suboptimal prompts and static event type information. In this paper, we propose a generative template-based event extraction method with dynamic prefix (GTEE-DYNPREF) by integrating context information with type-specific prefixes to learn a context-specific prefix for each context. Experimental results show that our model achieves competitive results with the state-of-the-art classification-based model ONEIE on ACE 2005 and achieves the best performances on ERE. Additionally, our model is proven to be portable to new types of events effectively. Copyright © 2022, The Authors. All rights reserved.

关键词： Extraction

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Regulating Na/Nascion Electrolyte Interface Chemistry for Stable Solid-State Na Metal Batteries at Room Temperature

SSRN

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SSRN 2022年

作者： Wang, Chengzhi Li, Donglai Sun, Chen Li, Jingbo Wang, Zongguo Jin, Haibo Beijing Key Laboratory of Construction Tailorable Advanced Functional Materials and Green Applications School of Materials Science and Engineering Beijing Institute of Technology Beijing100081 China Computer Network Information Center Chinese Academy of Sciences Beijing100190 China

It is critical for solid-state alkaline metal batteries to solve the issues of large interfacial resistance and poor interfacial stability between the alkaline metal anode and the solid electrolyte. We tune the interface chemistry between Na metal and a NASICON-type solid electrolyte by a facile Cu2+-ion doping method. It is demonstrated that the Cu2+-ion incorporation into Na3Zr2Si2PO12 (NZSP) significantly reduces the interfacial resistance (Rinter ) and boostss the interfacial stability during charge/discharge cyles at room temperature. The optimal Na3.4Zr1.8Cu0.2Si2PO12 (NZSP-0.2Cu) realizes an increased critical current density of 0.5 mA cm-2 and an impressively low Rinter value of 19 Ω cm2 at 25 °C, which is only 1/35 of the undoped one (665 Ω cm2). Moreover, the symmetrical Na|NZSP-0.2Cu|Na cell maintains steady Na plating/stripping cycles for as long as 1450 h under 0.2 mA cm-2, clearly indicating the desired chemical compatibility at the Na metal anode interface. A self-formed dynamically stable Cu3PO4-dominant interphase layer at the Na metal/NZSP-0.2Cu interface is verified to explain for the outstanding interfacial performance. Furthermore, a room-temperature solid-state NaCrO2|NZSP-0.2Cu|Na metal battery is assembled, exhibiting excellent cycling performance at 5 C for 660 cycles with a capacity retention of 86.5% and an overall Coulombic efficiency of 99.5%. © 2022, The Authors. All rights reserved.

关键词： Solid electrolytes

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The Generations of Classical Correlations via Quantum Schemes

arXiv

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arXiv 2023年

作者： Chen, Zhenyu Lin, Lijinzhi Lin, Xiaodie Wei, Zhaohui Yao, Penghui Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Department of Computer Science and Technology Tsinghua University Beijing100084 China Yau Mathematical Sciences Center Tsinghua University Beijing100084 China Yanqi Lake Beijing Institute of Mathematical Sciences and Applications 101407 China State Key Laboratory for Novel Software Technology Nanjing University Jiangsu Province Nanjing210023 China Hefei National Laboratory Hefei230088 China

Suppose two separated parties, Alice and Bob, share a bipartite quantum state or a classical correlation called a seed, and they try to generate a target classical correlation by performing local quantum or classical operations on the seed, i.e., any communications are not allowed. We consider the following fundamental problem about this setting: whether Alice and Bob can use a given seed to generate a target classical correlation. We show that this problem has rich mathematical structures. Firstly, we prove that even if the seed is a pure bipartite state, the above decision problem is already NP-hard and a similar conclusion can also be drawn when the seed is also a classical correlation, implying that this problem is hard to solve generally. Furthermore, we prove that when the seed is a pure quantum state, solving the problem is equivalent to finding out whether the target classical correlation has some diagonal form of positive semi-definite factorizations that matches the seed pure state, revealing an interesting connection between the current problem and optimization theory. Based on this observation and other insights, we give several necessary conditions where the seed pure state has to satisfy to generate the target classical correlation, and it turns out that these conditions can also be generalized to the case that the seed is a mixed quantum state. Lastly, since diagonal forms of positive semi-definite factorizations play a crucial role in solving the problem, we develop an algorithm that can compute them for an arbitrary classical correlation, which has decent performance on the cases we test. © 2023, CC BY.

关键词： Factorization

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A Multi-objective optimization model for simulation-based acquisition 7

A Multi-objective optimization model for simulation-based ac...

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7th IEEE International Conference on Progress in Informatics and Computing, PIC 2020

作者： Zhang, Xue Xue, Junjie Zhou, Junhua Shi, Guoqiang Yu, Yan Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing China Beijing Simulation Center Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9781728170862

Large-scale equipment presents the characteristics of technology-intensive, knowledge-intensive and complex, which brings high investment and high risk to equipment acquisition. This paper analyzes the various components of equipment acquisition to fully apply modeling and simulation technology to each stage of it. On the basis of multi-objective optimization theory, the objective function of the lowest risk and lowest cost of simulation-based acquisition (SBA) is proposed. Then establishing a multi-objective optimization model for simulation-based acquisition according to the corresponding constraints. The nondominated sorting genetic algorithm II (NSGA II) and multi-objective particle swarm optimization (MOPSO) algorithms are used to optimize the model, and the majority voting method is used for integration. The comparison of simulation examples proves that the multi-objective optimization model oriented to SBA designed in this paper can effectively realize the optimization of each objective of SBA under cost constraints. And the feasibility and efficiency of optimization solution are guaranteed. © 2020 IEEE.

关键词： Multiobjective optimization

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Deep Hierarchical Attention Flow for Visual Commonsense Reasoning 9th

Deep Hierarchical Attention Flow for Visual Commonsense Reas...

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9th CCF International Conference on Natural Language Processing and Chinese Computing, NLPCC 2020

作者： Song, Yuansheng Jian, Ping School of Computer Science and Technology Beijing Institute of Technology Beijing China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Bejing China

ISBN: (纸本)9783030604493

Visual Commonsense Reasoning (VCR) requires a thoroughly understanding general information connecting language and vision, as well as the background world knowledge. In this paper, we introduce a novel yet powerful deep hierarchical attention flow framework, which takes full advantage of text information in the query and candidate responses to perform reasoning over the image. Moreover, inspired by the success of machine reading comprehension, we also model the correlation among candidate responses to obtain better response representations. Extensive quantitative and qualitative experiments are conducted to evaluate the proposed model. Empirical results on the benchmark VCR1.0 show that the proposed model outperforms existing strong baselines, which demonstrates the effectiveness of our method. © 2020, Springer Nature Switzerland AG.

关键词： Visual languages

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applications of AI to Age-Related Macular Degeneration: A case study and a brief review

Applications of AI to Age-Related Macular Degeneration: A ca...

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2022 International Conference on computer Engineering and Artificial Intelligence, ICCEAI 2022

作者： Wang, Han Lung Chong, Kelvin Kam Li, Zefeng City University of Macau Faculty of Data Science Macau999078 China Zhuhai Institute of Advanced Technology Chinese Academy of Sciences Department of Artificial Intelligence and Big Data Applications Zhuhai519000 China School of Computer College of Beijing University of Technology Zhuhai Zhuhai519000 China Chinese University of Hong Kong Faculty of Medicine Department of Ophthalmology and Visual Sciences Hong Kong999077 Hong Kong

ISBN: (数字)9781665468039

ISBN: (纸本)9781665468039

Age-Related Macular Degeneration (AMD) is one of the major causes of blindness. The artificial intelligence (AI) based method is a novel solution computer-Aided diagnosis approach. This study implemented a brief review by utilizing a case study on AI-based AMD diagnosis studies. Challenges and solutions are discussed., which makes a reference value for future research. © 2022 IEEE.

关键词： computer aided diagnosis

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TourLLM: Enhancing LLMs with Tourism Knowledge

arXiv

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arXiv 2024年

作者： Wei, Qikai Yang, Mingzhi Wang, Jinqiang Mao, Wenwei Xu, Jiabo Ning, Huansheng School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Key Laboratory of Xinjiang Coal Resources Green Mining Ministry of Education Xinjiang Institute of Engineering Urumqi830023 China Beijing Engineering Research Center for Cyberspace Data Analysis and Applications Beijing100083 China Guangxi Tourism Development One-Click Tour Digital Cultural Tourism Industry Co. Ltd. Guangxi530012 China

Recently, large language models (LLMs) have demonstrated their effectiveness in various natural language processing (NLP) tasks. However, the lack of tourism knowledge limits the performance of LLMs in tourist attraction presentations and travel planning. To address this challenge, we constructed a supervised fine-tuning dataset for the culture and tourism domain, named Cultour. This dataset consists of three parts: tourism knowledge base QA data, travelogues data, and tourism diversity QA data. Additionally, we propose TourLLM, a Qwen-based model supervised fine-tuned with Cultour, to improve the quality of the information provided about attractions and travel planning. To evaluate the performance of TourLLM, we employed both automatic and human evaluation, and we proposed a human evaluation criterion named CRA (Consistency, Readability, Availability). The experimental results demonstrate the effectiveness of the responses generated by the TourLLM. Our proposed Cultour is accessible at https://***/mrweiqk/Cultour. Copyright © 2024, The Authors. All rights reserved.

关键词： Natural language processing systems

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