检索结果-内蒙古大学图书馆

23rd IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2024

作者： Zou, Huiying Duan, Jia Liu, Xi Ren, Wei Li, Tao Zheng, Xianghan Choo, Kim-Kwang Raymond Hunan Engineering Research Center of Geographic Information Security and Application The Third Surveying and Mapping Institute of Hunan Province Hunan China China University of Geosciences School of Computer Science Wuhan China Sichuan University Ministry of Education Key Laboratory of Data Protection and Intelligent Management China Casm State Key Laboratory of Geo-Information Engineering Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of Mnr Beijing China Fuzhou University College of Computer and Big Data China Sanya College School of Information and Intelligent Engineering China University of Texas at San Antonio Department of Information Systems and Cyber Security San Antonio United States

With the widespread application of digital assets and the rapid development of blockchain technology, achieving secure and efficient transactions between different blockchain networks has become an urgent challenge. Existing cross-chain methods impose limitations, e.g., hash lock technology exhibits low scalability, side-chain technology is overly complex, and notary schemes pose centralization risks. In order to address these issues, we propose a cross-chain transaction solution based on proxy re-signature technology. To tackle the centralization concerns, we employ proxy re-signature technology to decentralize the authority of notaries among transaction participants, minimizing the potential for centralization at a low cost. We further present an extended scheme that can guarantee more requirements such as higher transaction amount and shorter transaction time. Furthermore, we analyze and compare the signature technologies used in the proposed solution and provide a systematic proof of our approach's security. © 2024 IEEE.

关键词： blockchain transaction cross-chain technology notary schemes proxy re-signature

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Single Valued Neutrosophic Sets Approach for Cloud Clustering

引用

Procedia computer science 2025年 258卷 3580-3589页

作者： Haewon Byeon Pramod Kumar Ihtiram Raza Khan Faisal Yousef Alghayadh Maher Ali Rusho Mukesh Soni Inje University Medical Big Data Research Center Gimhae 50834 Republic of Korea Associate professor Ganga Institute of Technology and Management Jhajjar - Bahadurgarh Rd Kablana Bhadana Haryana 124104 Computer science department Jamia Hamdard Delhi Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Department of Lockheed Martin Engineering Management University of Colorado Boulder Boulder Colorado Dr. D.Y. Patil Vidyapeeth Pune Dr. D.Y. Patil School of Science & Technology Tathawade Pune

This work presents an innovative approach to integrating restricted rationality and strategic manipulation into multi-attribute decision-making in product style design, resulting in more precise and objective outcomes. The suggested approach employs cloud model clustering and unsupervised Single-Valued Neutrosophic Sets (SVNS). SVNS is derived by constructing pairwise comparison ratio square matrices between baseline attributes and prospective alternatives, following the scientific clustering of decision experts. SSVNC denotes the degrees of real, false, and questionable membership. The relative weights of the standard attributes are established by analysing the evaluation outcomes of different solutions for each common trait. Cloud model clustering is employed to exclude conflicting and unreasonable experts, hence attaining precise weights for design judgements. This model incorporates multi-granularity linguistic factors. The integration of the significance of generic attributes and human assessment yields a composite score for each prospective response. The feasibility and efficacy of the proposed strategy are demonstrated through a case study in automotive design aesthetics. The results emphasise the method’s capability to safeguard against nefarious strategic manipulation and effectively address complex and confusing multi-attribute decision-making challenges in vehicle stylistic design.

关键词： Multi-attribute decision-making Bounded rationality Strategy manipulation unsupervised Single-Valued Neutrosophic Sets Cloud model clustering

来源：评论

学校读者我要写书评

暂无评论

Multimodal Analysis of White Blood Cell Differentiation in Acute Myeloid Leukemia Patients using a β-Variational Autoencoder

arXiv

引用

arXiv 2024年

作者： Mert, Gizem Sadafi, Ario Salehi, Raheleh Navab, Nassir Marr, Carsten Institute of AI for Health Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany Department of Information Engineering and Computer Science University of Trento Trento Italy Technical University of Munich Munich Germany Department of Chemistry Ludwig-Maximilians University Munich Munich Germany Computer Aided Medical Procedures Johns Hopkins University Baltimore United States

Biomedical imaging and RNA sequencing with single-cell resolution improves our understanding of white blood cell diseases like leukemia. By combining morphological and transcriptomic data, we can gain insights into cellular functions and trajectoriess involved in blood cell differentiation. However, existing methodologies struggle with integrating morphological and transcriptomic data, leaving a significant research gap in comprehensively understanding the dynamics of cell differentiation. Here, we introduce an unsupervised method that explores and reconstructs these two modalities and uncovers the relationship between different subtypes of white blood cells from human peripheral blood smears in terms of morphology and their corresponding transcriptome. Our method is based on a beta-variational autoencoder (β-VAE) with a customized loss function, incorporating a R-CNN architecture to distinguish single-cell from background and to minimize any interference from artifacts. This implementation of β-VAE shows good reconstruction capability along with continuous latent embeddings, while maintaining clear differentiation between single-cell classes. Our novel approach is especially helpful to uncover the correlation of two latent features in complex biological processes such as formation of granules in the cell (granulopoiesis) with gene expression patterns. It thus provides a unique tool to improve the understanding of white blood cell maturation for biomedicine and diagnostics. Copyright © 2024, The Authors. All rights reserved.

关键词： Variational techniques

来源：评论

学校读者我要写书评

暂无评论

Social Choice Should Guide ai Alignment in Dealing with Diverse Human Feedback

arXiv

引用

arXiv 2024年

作者： Conitzer, Vincent Freedman, Rachel Heitzig, Jobst Holliday, Wesley H. Jacobs, Bob M. Lambert, Nathan Mossé, Milan Pacuit, Eric Russell, Stuart Schoelkopf, Hailey Tewolde, Emanuel Zwicker, William S. Foundations of Cooperative AI Lab Computer Science Department Carnegie Mellon University Pittsburgh United States Institute for Ethics in AI University of Oxford Oxford United Kingdom Center for Human-Compatible AI Department of Electrical Engineering and Computer Sciences University of California Berkeley United States Potsdam Institute for Climate Impact Research Brandenburg Potsdam Germany Department of Philosophy University of California Berkeley United States Department of Philosophy and Moral Sciences Ghent University Ghent Belgium Allen Institute for AI BerkeleyCA United States Department of Philosophy University of Maryland College Park United States EleutherAI Greece Department of Mathematics Union College Schenectady United States Murat Sertel Center for Advanced Economic Studies Istanbul Bilgi University Istanbul Turkey

Foundation models such as GPT-4 are fine-tuned to avoid unsafe or otherwise problematic behavior, such as helping to commit crimes or producing racist text. One approach to fine-tuning, called reinforcement learning from human feedback, learns from humans’ expressed preferences over multiple outputs. Another approach is constitutional ai, in which the input from humans is a list of high-level principles. But how do we deal with potentially diverging input from humans? How can we aggregate the input into consistent data about "collective" preferences or otherwise use it to make collective choices about model behavior? In this paper, we argue that the field of social choice is well positioned to address these questions, and we discuss ways forward for this agenda, drawing on discussions in a recent workshop on Social Choice for ai Ethics and Safety held in Berkeley, CA, USA in December *** Codes 68T01, 68T50, 91B14, 91B12 Copyright © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Blockchain Technology in Automobile Insurance Claim Systems research 1

引用

5th International Conference on Smart Computing and Communication, SmartCom 2020

作者： Deng, Han Wang, Chong Wu, Qiaohong Nie, Qin Huang, Weihong Zhang, Shiwen Big Data Development and Research Center Guangzhou College of Technology and Business Guangzhou528138 China College of Computer Science and Electronic Engineering Hunan University Changsha410000 China Department of Accounting Guangzhou College of Technology and Business Guangzhou528138 China School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan411201 China

ISBN: (数字)9783030747176

ISBN: (纸本)9783030747169

Recently, academics and industries are increasingly paying attention to blockchain technology because it is used to improve traditional companies. Insurance company is one type of the traditional and inflexible companies. Its operation is not transparent, based on paper contracts, relying on human intervention and other characteristics resulting in low efficiency. The transparency, tamper-proof, decentralization and other advantages of blockchain-based Internet of Things and smart contract technology enable people to improve the traditional processes and structures of the insurance industry. This paper summarizes the application of block chain technology in the auto insurance claim systems. By comparing the implementations of various systems, the existing achievements and their advantages and disadvantages are described. In addition, this paper prospects the key directions of future research on the implementation of blockchain. © 2021, Springer Nature Switzerland AG.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

When a RF Beats a CNN and GRU, Together - A Comparison of Deep Learning and Classical Machine Learning Approaches for Encrypted Malware Traffic Classification

arXiv

引用

arXiv 2022年

作者： Lichy, Adi Bader, Ofek Dubin, Ran Dvir, Amit Hajaj, Chen Ariel Cyber Innovation Center Ariel University Israel Department of Computer Science Ariel University Israel Department of Industrial Engineering & Management Ariel University Israel Data Science and Artificial Intelligence Research Center Ariel University Israel

Internet traffic classification is widely used to facilitate network management. It plays a crucial role in Quality of Services (QoS), Quality of Experience (QoE), network visibility, intrusion detection, and traffic-trend analyses. While there is no theoretical guarantee that deep learning (DL)-based solutions perform better than classic machine learning (ML)-based ones, DL-based models have become the common default. This paper compares well-known DL-based and ML-based models and shows that in the case of malicious traffic classification, state-of-the-art DL-based solutions do not necessarily outperform the classical ML-based ones. We exemplify this finding using two well-known datasets for a varied set of tasks, such as: malware detection, malware family classification, detection of zero-day attacks, and classification of an iteratively growing dataset. Note that, it is not feasible to evaluate all possible models to make a concrete statement, thus, the above finding is not a recommendation to avoid DL-based models, but rather empirical proof that in some cases, there are more simplistic solutions, that may perform even better. Copyright © 2022, The Authors. All rights reserved.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Interpretable text-to-sql generation with joint optimization 1

引用

17th International Conference on Web Information Systems and applications, WISA 2020

作者： Zhu, Mingdong Wang, Xianfang Zhang, Yang School of Computer Science and Technology Henan Institute of Technology Xinxiang China Intelligent Industrial Big Data Application Engineering Technology Research Center of Xinxiang Xinxiang China

ISBN: (数字)9783030600297

ISBN: (纸本)9783030600280

The purpose of Text-to-SQL is to obtain the correct answer for a textual question from the database, which can take advantage of advanced database system to provide reliable and efficient response. Existing Text-to-SQL methods generally focus on accuracy by designing complex deep neural network models, and hardly consider interpretability, which is very important for serious applications. To address this, in this paper we propose a novel framework for Interpretable Text-to-SQL Generation (ITSG) with joint optimization, which achieves state-of-the-art accuracy and possesses two-level interpretability at the same time. The framework mainly consists of three layers: a sequence encoder which encodes questions, table headers and significant table contents, an attention-based LSTM layer which generates SQL queries and a reinforcement learning layer which boosts the execution accuracy. Comparing with state-of-the-art methods on benchmark datasets, the experimental results show the effectiveness and interpretability of our ITSG framework. © Springer Nature Switzerland AG 2020.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Secure and Privacy-preserving data-sharing Framework based on Blockchain Technology for Al-Najaf/Iraq Oil Refinery 19

Secure and Privacy-preserving Data-sharing Framework based o...

引用

2022 IEEE SmartWorld, 19th IEEE International Conference on Ubiquitous Intelligence and Computing, 2022 IEEE International Conference on Autonomous and Trusted Vehicles Conference, 22nd IEEE International Conference on Scalable Computing and Communications, 2022 IEEE International Conference on Digital Twin, 8th IEEE International Conference on Privacy Computing and 2022 IEEE International Conference on Metaverse, SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse 2022

作者： Umran, Samir M. Lu, SongFeng Abduljabbar, Zaid Ameen Lu, Zhi Feng, Bingyan Zheng, Lu Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China Iraqi Cement State Company Ministry of Industry and Minerals Baghdad10011 Iraq Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518057 China University of Basrah College of Education for Pure Sciences Iraq Al-Kunooze University College Technical Computer Engineering Department Basrah Iraq Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan430074 China Industrial Internet Research Institute Wuhan Huazhong Numerical Control Co. Ltd Wuhan430074 China South-Central University for Nationalities College of Computer Science Wuhan430074 China

ISBN: (纸本)9798350346558

The Industrial Internet of Things or Industry 4.0 efficiently enhances the manufacturing process in terms of raising productivity, system performance, cost reduction, and building large-scale systems. It enables the connection of numerous heterogeneous devices and sensors into the internet network through the utilization of revolutionary techniques that transfer the manufacturing paradigm to intelligent processes. The traditional industrial internet of things adopts centralized architectures and complex encryption algorithms that suffer from several cyber-security threats and lead to data leakage, privacy disclosure, and high computational and communicational costs. In our work, we proposed a decentralized, efficient, low-power, scalable, secure, privacy-preserving, and trusting architecture based on a private blockchain network/smart contract and interplanetary file system technology for the Al-NajafyIraq oil refinery factory. That enables autonomous working and provides a high level of security authentication and privacy preservation, P2P communication, remote access, immutability and information backtracking. Traditional blockchain technology has storage limitation issues, most recent works adopted external servers or the cloud for storage purposes. Our proposed scheme addresses the limitations of blockchain data storage by adopting an interplanetary file system (IPFS) network;provides an efficient data encryption mechanism at the perceptual layer by adopting a lightweight encryption algorithm, high-performance, and ultra-low-power consumption ARM Cortex-M microcontroller. In addition, our architecture succeeds in merging blockchain technology, IoTs, and an IPFS with the oil refinery as an industrial application area. Moreover, it provides an efficient framework that resists common cyber-security attacks and realizes cyber-security requirements represented by data availability, integrity, and confidentiality. © 2022 IEEE.

关键词： Digital storage

来源：评论

学校读者我要写书评

暂无评论

Open-Source Framework for Encrypted Internet and Malicious Traffic Classification

arXiv

引用

arXiv 2022年

作者： Bader, Ofek Lichy, Adi Dvir, Amit Dubin, Ran Hajaj, Chen Department of Computer Science Ariel University Israel Ariel Cyber Innovation Center Ariel University Israel Data Science and Artificial Intelligence Research Center Ariel University Israel Department of Industrial Engineering & Management Ariel University Israel

Internet traffic classification plays a key role in network visibility, Quality of Services (QoS), intrusion detection, Quality of Experience (QoE) and traffic-trend analyses. In order to improve privacy, integrity, confidentiality, and protocol obfuscation, the current traffic is based on encryption protocols, e.g., SSL/TLS. With the increased use of Machine-Learning (ML) and Deep-Learning (DL) models in the literature, comparison between different models and methods has become cumbersome and difficult due to a lack of a standardized framework. In this paper, we propose an open-source framework, named OSF-EIMTC, which can provide the full pipeline of the learning process. From the well-known datasets to extracting new and well-known features, it provides implementations of well-known ML and DL models (from the traffic classification literature) as well as evaluations. Such a framework can facilitate research in traffic classification domains, so that it will be more repeatable, reproducible, easier to execute, and will allow a more accurate comparison of well-known and novel features and models. As part of our framework evaluation, we demonstrate a variety of cases where the framework can be of use, utilizing multiple datasets, models, and feature sets. We show analyses of publicly available datasets and invite the community to participate in our open challenges using the OSF-EIMTC. Copyright © 2022, The Authors. All rights reserved.

关键词： Intrusion detection

来源：评论

学校读者我要写书评

暂无评论

引用

China CDC weekly 2022年第40期4卷 885-889,I0002-I0005页

作者： Yuan Bai Mingda Xu Caifen Liu Mingwang Shen Lin Wang Linwei Tian Suoyi Tan Lei Zhang Petter Holme Xin Lu Eric H.Y.Lau Benjamin J.Cowling Zhanwei Du WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong Kong Special Administrative RegionChina Laboratory of Data Discovery for Health Limited(D24H) Hong Kong Science ParkHong Kong Special Administrative RegionChina China-Australia Joint Research Center for Infectious Diseases School of Public HealthXi’an Jiaotong University Health Science CenterXi’an CityShaanxi ProvinceChina Department of Genetics University of CambridgeCambridge CB23EHUK College of Systems Engineering National University of Defense TechnologyChangsha CityHunan ProvinceChina Department of Computer Science Aalto UniversityEspooFinland Center for Computational Social Science Kobe UniversityKobeJapan

Introduction:Minimizing the importation and exportation risks of coronavirus disease 2019(COVID-19)is a primary concern for sustaining the“Dynamic COVID-zero”strategy in *** estimation is essential for cities to conduct before relaxing border control ***:Informed by the daily number of passengers traveling between 367 prefectures(cities)in China,this study used a stochastic metapopulation model parameterized with COVID-19 epidemic characteristics to estimate the importation and exportation ***:Under the transmission scenario(R0=5.49),this study estimated the cumulative case incidence of Changchun City,Jilin Province as 3,233(95%confidence interval:1,480,4,986)before a lockdown on March 14,2022,which is close to the 3,168 cases reported in real life by March 16,*** a total of 367 prefectures(cities),127(35%)had high exportation risks according to the simulation and could transmit the disease to 50%of all other regions within a period from 17 to 94 *** average time until a new infection arrives in a location in 1 of the 367 prefectures(cities)ranged from 26 to 101 ***:Estimating COVID-19 importation and exportation risks is necessary for preparedness,prevention,and control measures of COVID-19—especially when new variants emerge.

关键词： Export Changchun prevention

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：