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Research on the Virtual Currency Payment System Based on Blockchain Technology 3

Research on the Virtual Currency Payment System Based on Blo...

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3rd international conference on Computer Science and Management Technology, ICCSMT 2022

作者： Niu, Sihan Nanjing University of Information Science and Technology School of Computer and Software Jiangsu Province Nanjing City China

ISBN: (纸本)9798350320404

As a focus in the field of financial innovation, blockchain technology is essentially a distributed ledger database, and it is open and transparent, decentralized and immutable in practical application. In the steady development of financial technology, blockchain technology, as a basic content, has attracted the attention of researchers and scholars, and from this, the payment system of virtual currency has been constructed. This greatly facilitates people's daily life. Therefore, based on the understanding of the definition of blockchain technology and the influence of the content of this technology on the payment system, this paper deeply discusses the convenient payment system and its operation mode with blockchain technology as the core, and finally conducts verification analysis under the new cross-border payment mode. The results show that the virtual currency payment system based on blockchain technology is feasible and effective in practice. Especially in the social economy with the acceleration of network technological innovation, increasingly frequent international exchanges and constantly improved trade modes, the application of block chain technology contribute to the economic development of our country and gradually integrate into the international market, but from the point of view of the whole system security and technical performance, there are still many problems. © 2022 IEEE.

关键词： Blockchain

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Blockchain-based Privacy Preservation Framework for IoT-Based information systems 3

Blockchain-based Privacy Preservation Framework for IoT-Base...

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3rd international conference on Innovations in Computer Science and Software Engineering, ICONICS 2022

作者： Ali, Muhammad Cheema, Sehrish Munawar Ayub, Nasir Naz, Ammerha Aslam, Zaheer The Superior University Lahore Department of Software Engineering Lahore Pakistan University of Management and Technology Department of Computer Science Sialkot Pakistan University of Sialkot Department of Computer Science Sialkot Pakistan

ISBN: (纸本)9781665461412

IoT-based systems have become an important part of our lives. We interact with these types of systems many times in a single day like smart watches, smart home systems, smart vehicle systems, and more. Mostly they perform their functionality by utilizing our data. This data is stored on a central repository mostly a cloud-based repository. This central storage mechanism has many critical data privacy issues with it. To resolve these privacy-related issues, a blockchain-based framework is proposed that stores data on distributed ledger instead of any central location. The proposed framework categorizes participants into trusted participants that are mostly data owners and the other is untrusted. It is based on two separate blockchain networks. One is the main chain that is utilized for the transactions related to data storage and the other is a side chain that is utilized for the transaction related to access policy. In this way, transactions take place on the network without any miscellaneous data or privacy threats. © 2022 IEEE.

关键词： Blockchain

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Dynamic Event-Based Asymptotically Tracking Control for Multi-Agent systems 3

Dynamic Event-Based Asymptotically Tracking Control for Mult...

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3rd international conference on Neuromorphic Computing, ICNC 2024

作者： Zhang, Shuhan Sui, Zhengqi Guo, Simian Liu, Guangliang School of Mathematical Sciences Bohai University Jinzhou121013 China College of Information Science and Engineering Northeastern University Shenyang110819 China Marketing Servide Center State Grid Liaoning Shenyang110819 China School of Control Science and Engineering Bohai University Jinzhou121013 China

ISBN: (纸本)9798331508661

This paper studies an adaptive dynamic event-triggered consensus asymptotical tracking control problem for nonlinear multi-agent systems. A distributed parameter adaptive law is designed to compensate for the parameter uncertainty involved in the acquisition of adjacency information by the agent. An event-triggered strategy with dynamic threshold is designed to reduce transmission load and controller updates. By reasonably constructing the dynamics of triggering threshold, the derived dynamic event-triggered control protocol can guarantee zero-error tracking and eliminate Zeno behavior. Simulation results verify the effectiveness of the developed scheme and the rationality of the theoretical results. © 2024 IEEE.

关键词： distributed parameter control systems

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A Hybrid Edge-Cloud Computing Approach for Energy-Efficient Surveillance Using Deep Reinforcement Learning 3

A Hybrid Edge-Cloud Computing Approach for Energy-Efficient ...

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3rd international conference on Technological Advancements in Computational Sciences, ICTACS 2023

作者： Singh, Jagendra Dabas, Partibha Bhati, Sunita Kumar, Santosh Upreti, Kamal Shaik, Nazeer School of Computer Science Engineering and Technology Bennett University Greater Noida India Dr Akhilesh das Gupta Institute of Technology and Management Dept. of Computer Science & Engineering Delhi India Jecrc University Department of Computer Applications Jaipur India Raj Kumar Goel Institute of Technology Department of Information Technology Ghaziabad India Department of Computer Science Ghaziabad India SRIT-Autonomous Anantapur Department of Computer Science Engineering India

ISBN: (纸本)9798350342338

This paper explores the novel application of Deep Reinforcement Learning (DRL) in designing a more efficient, scalable, and distributed surveillance architecture, which addresses concerns such as data storage limitations, latency, event detection accuracy, and significant energy consumption in cloud data centers. The proposed architecture employs edge and cloud computing to optimize video data processing and energy usage. The study further investigates the energy consumption patterns of such a system in detail. The implementation leverages machine learning models to identify optimal policies based on system interactions. The proposed solution is tested over an extensive period, resulting in a system capable of reducing latency, enhancing event detection accuracy, and minimizing energy consumption. © 2023 IEEE.

关键词： Cloud Data Centers Deep Reinforcement Learning Edge Computing Energy Efficiency Smart Surveillance

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Bitcoin Fast Payment Protocol Based on Chameleon Authentication Tree 3

Bitcoin Fast Payment Protocol Based on Chameleon Authenticat...

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3rd international conference on Computer Engineering and Intelligent Control, ICCEIC 2022

作者： Zhang, Yuxiang Xian, Ming Zhang, Hongjiang Wang, Huimei Kong, Congwang College of Electronic Science and Technology National University of Defense Technology Hunan Changsha410000 China College of Electronics and Information Engineering Ankang University Shaanxi Ankang725000 China

With the development trend of distributed and decentralized, blockchain-based bitcoin payment methods are gradually gaining attention and research from academia and industry. In order to prevent the "double spend" attack in the Bitcoin payment process, it is officially recommended to wait for 6 blocks (about 1 hour) to confirm the transaction is established, which creates a serious time delay constraint for small payments and leads to inefficient payments. Therefore, this paper proposes a fast payment protocol based on the chameleon authentication tree, the main idea of which is to combat the "double spend" attack through a deposit penalty. The protocol associates the key in the scheme with the deposit key, enabling the implementation of fast payment protocols on distributed systems through deposit penalties. © 2022 Copyright for this paper by its authors.

关键词： Blockchain

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A Deep-Learning System for Detecting the Brain MRI Anatomical Plane to be Examined with Priority in Alzheimer's Disease 3

A Deep-Learning System for Detecting the Brain MRI Anatomica...

引用

3rd IEEE international conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2024

作者： Tomassini, Selene Quattrocchi, Carlo Cosimo Zeggada, Abdallah Duranti, Damiano Melgani, Farid Giorgini, Paolo University of Trento Department of Information Engineering and Computer Science Trento Italy Centre for Medical Sciences University of Trento Trento Italy

ISBN: (纸本)9798350378009

Brain Magnetic Resonance Imaging (MRI) is an effective technology to catch and analyse alterations of the brain morphology. An overall MRI view in all anatomical planes provides the most comprehensive information, however it requires attention and time. In addition, the choice of the best diagnostic anatomical plane depends on the location and shape of the specific brain structures. Moreover, each radiologist selects the best strategy to obtain diagnostic information based on representativeness, anchoring, and availability, resulting highly subjective. In this context, a system designed to automatically detect the most informative anatomical plane based on the brain structure alterations can be useful in guiding, thus accelerating the interpretation of brain MRI information, especially in those cases where MRI is among the primary means of producing clinical diagnoses, such as in neurodegenerative diseases. Currently, there are not solutions in the field of artificial intelligence that are specifically designed to fulfill this task. Therefore, the aim of this research is to investigate the atypicality of the brain structures involved the most in Alzheimer's Disease (AD) to prioritize the reading of the anatomical plane with the highest ability to detect morphological changes related to AD. To this aim, we implemented a deep-learning system in which three lightweight and self-excluding classification models were utilized on MRI volumes of AD, Mild Cognitive Impairment (MCI), and cognitively normal individuals taken from the ADNI database. The first model is a Convolutional Long Short-Term Memory (ConvLSTM)-based neural network, whereas the others are two time-distributed convolutional neural networks combined with a ConvLSTM-based module each. According to our results, the best performing model classifies AD subjects with AUROC mean value of 99% from the axial plane. As for MCI subjects, the same ConvLSTM-based neural network classifies them with AUROC mean value of

关键词： Neurodegenerative diseases

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Research on Fast Encryption of Electronic Health Record Data Based on Privacy Protection 3rd

Research on Fast Encryption of Electronic Health Record Data...

引用

3rd EAI international conference on IoT and Big Data Technologies for Health Care, IotCARE 2022

作者： Fu, Tianlin Shi, Juanfen Ke, Haipeng College of Mathematics and Data Science Minjiang University Fuzhou350000 China School of Electronic Engineering Henan Information Engineering School Henan450008 China Fujian Zhangzhou No.1 Vocational Secondary School Zhangzhou363000 China

ISBN: (纸本)9783031335440

Electronic health records data has the characteristics of massive, multi-modal, heterogeneous, but electronic health records data is easy to be invaded, leading to the disclosure of patient personal information. Health record management systems often ignore the security problems when patients interact with other roles, and the traditional encryption methods have been difficult to effectively meet the security needs of modern privacy data. Therefore, a fast encryption method of electronic health record data based on privacy protection is proposed. Mainly through the combination of privacy protection and homomorphic encryption technology to achieve distributed user privacy data protection, the mining effect of privacy protection is effectively improved, and the data security is guaranteed. The effectiveness and practicability of this method in data privacy security protection are verified by experiments. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Cryptography

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The 3rd international Workshop on parallel and distributed Algorithms for Decision Sciences (PDADS 2023)

ACM International Conference Proceeding Series

引用

ACM international conference Proceeding Series 2023年 XIV-XV页

作者： Seal, Sudip K. Liu, Yan Ostrowski, Jim Oak Ridge National Laboratory United States University of Tennessee United States

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Effects of Laser Parameters on Microgrooves morphology of SiC/SiC Composites fabricated by Femtosecond Laser 3

Effects of Laser Parameters on Microgrooves morphology of Si...

引用

3rd international conference on Laser, Optics, and Optoelectronic Technology, LOPET 2023

作者： Li, Xin Yuan, Yanping Chen, Lei Zhao, Tianyu Institute of Laser Engineering Faculty of Materials and Manufacturing Beijing University of Technology Beijing100124 China Ministry of Education Beijing100124 China Beijing Engineering Research Center of Laser Technology Beijing University of Technology Beijing100124 China Beijing Engineering Research Center of 3D Printing for Digital Medical Health Beijing University of Technology Beijing100124 China

ISBN: (纸本)9781510667624

Silicon carbide (SiC) fiber-reinforced SiC-matrix (SiC/SiC) composite has a wide range of applications in the aerospace field. However, SiC/SiC composite is typical difficult-to-machine materials due to their non-homogeneous and anisotropic properties, and traditional manufacturing processes cannot meet their processing requirements in aerospace applications. Femtosecond laser processing technology is expected to become the preferred choice to meet this demand, due to their ultrashort irradiation periods and ultrahigh intensities. In this study, the micro-grooving processing on the surface of SiC/SiC composites by femtosecond laser is investigated, and the effects of laser power, scanning speed and scanning frequency on the surface morphology of SiC/SiC composites are investigated. The results show that there are recast layers in the ablation zone and powdery substances in the processing zone during the laser ablation process of SiC/SiC composite. The width and depth of the micro-grooves increase with the increase of laser power and scanning times. When the ablation power is low and the scanning times are few, the grooves are non-uniformly distributed with sawtooth structure. When the ablation power is high and the scanning speed is low, the grooves are serrated. Properly increasing the scanning speed and scanning times can reduce the sawtooth structure and improve the surface quality of the ablated area. This proposed method can achieve good morphology of SiC/SiC and is expected to be applied to industrial processing of SiC/SiC. © 2023 SPIE.

关键词： Silicon carbide

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A Study of Earthquake Forecasting Using Artificial Intelligence (AI) Approaches 3rd

A Study of Earthquake Forecasting Using Artificial Intellige...

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3rd international conference on Mechanical and Energy Technologies, ICMET 2023

作者： Dubey, Dharmendra K. Tomar, Arjit Mishra, Mohit Yadav, Amit K. Yadav, E. Prabhash K. Shree Dhanvantary College of Engineering and Technology Kim Surat India Noida International University Noida India Lovely Professional University Phagwara India BSSITM UP Lucknow India Bhagwant University Ajmer India

ISBN: (纸本)9789819727155

The investigation of seismic tremor gauging utilizing man-made intelligence approaches has shown promising outcomes of late. AI calculations have had the option to distinguish examples and connections in seismic and different information that might be demonstrative of approaching tremors. Nonetheless, the precision of these conjectures differs relying upon the nature of the information, the intricacy of the fundamental topographical and geophysical cycles, and different variables. In some instances, deterministic forecasting methods that concentrate on identifying specific seismic patterns linked to earthquakes have produced positive outcomes. For instance, a 2018 study that used machine learning algorithms to analyze seismic data from the San Andreas Fault in California was able to identify seismic patterns that were associated with previous earthquakes and was published in the journal Nature. The researchers were then prepared to use these guides to make assumptions regarding prospective quakes with a serious degree of precision. Methods of probabilistic determining that make use of factual models to estimate the likelihood of a quake occurring in a particular region have also produced positive results. Utilizing seismic information from Japan and an AI calculation, a recent report distributed in Science Advances had the option to foresee the probability of tremors in different areas precisely. Moreover, a few specialists have communicated worry that putting an excess of confidence in estimates in view of computer-based intelligence could provide individuals with a misguided feeling of safety and prompt them to become careless in their endeavors to get ready for and answer catastrophes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Forecasting

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