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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Kale, Dattatray Raghunath Jadhav, Amolkumar N. Kruishna Prasad, K. Salunkhe, Somanath Janardan Hirve, Sumit Goswami, Chandrashekhar Mit Art Design and Technology University Mit School of Computing Department of Computer Science & Engg Pune India Annasaheb Dange College of Engineering and Technology Department of Computer Science & Engg Ashta India Shrinivas University Department of Computer Science & Engg Mangalore India D Y Patil Agriculture and Technical University Department of Computer Science & Engg Talsande India Sir Padampat Singhania University Faculty of Computing and Informatics Rajasthan Udaipur India

ISBN: (纸本)9798350354348

Blockchain technology's decentralized and immutable data storage has changed a number of sectors. But typical blockchain networks scalability issues prevent them from being widely used for large-scale applications. By dividing the blockchain network into smaller, more controllable sections known as shards, sharding has become a viable remedy for scalability issues. This paper offers a thorough introduction to sharding as a blockchain network scalability solution. We explore the basic ideas of sharding as well as its advantages, drawbacks, and several sharding strategies. We also analyze experimental results and real-world implementations to assess how well sharding contributes to increased blockchain scalability. Lastly, we talk about possible developments in sharding approaches and future research paths to further improve the scalability of blockchain networks. © 2024 IEEE.

关键词： Distributed ledger

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Tackling heavy-tailed noise in distributed estimation: Asymptotic performance and tradeoffs 32

Tackling heavy-tailed noise in distributed estimation: Asymp...

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32nd Telecommunications Forum, TELFOR 2024

作者： Bajovic, Dragana Jakovetic, Dusan Kar, Soummya Vukovic, Manojlo University of Novi Sad Faculty of Technical Sciences Department of Power Electronic and Communication Engineering Serbia University of Novi Sad Faculty of Sciences Department of Mathematics and Informatics Serbia Carnegie Mellon University Department of Electrical and Computer Engineering United States University of Novi Sad Faculty of Technical Sciences Department of Fundamental Sciences Serbia

ISBN: (纸本)9798350391053

We present an algorithm for distributed estimation of an unknown vector parameter θ∗ ∈ M in the presence of heavy-tailed observation and communication noises. Heavy-tailed noises frequently appear, e.g., in densely deployed Internet of Things (IoT) or wireless sensor network systems. The presented algorithm falls within the class of consensus+innovation estimators and combats the effect of the heavy-tailed noises by adding general nonlinearities in the consensus and innovations update parts. We present results on almost sure convergence and asymptotic normality of the estimator. In addition, we provide novel analytical studies that reveal interesting tradeoffs between the system noises and the underlying network topology. © 2024 IEEE.

关键词： Internet of things

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Price Prediction of Seasonal Items Using Time Series Analysis

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computer Systems Science & engineering 2023年第7期46卷 445-460页

作者： Ahmed Salah Mahmoud Bekhit Esraa Eldesouky Ahmed Ali Ahmed Fathalla Faculty of Computers and Informatics Zagazig UniversitySharkeya44523Egypt Information Technology Department the University of Technology and Applied SciencesIbriOman School of Electrical and Data Engineering University of Technology SydneySydney2007Australia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Computer Science Department Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Higher Future Institute for Specialized Technological Studies Cairo3044Egypt Department of Mathematics Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt

The price prediction task is a well-studied problem due to its impact on the business *** are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change,but there is very limited work to study the price prediction of seasonal goods(e.g.,Christmas gifts).Seasonal items’prices have different patterns than normal items;this can be linked to the offers and discounted prices of seasonal *** lack of research studies motivates the current work to investigate the problem of seasonal items’prices as a time series *** proposed utilizing two different approaches to address this problem,namely,1)machine learning(ML)-based models and 2)deep learning(DL)-based ***,this research tuned a set of well-known predictive models on a real-life *** models are ensemble learning-based models,random forest,Ridge,Lasso,and Linear ***,two new DL architectures based on gated recurrent unit(GRU)and long short-term memory(LSTM)models are ***,the performance of the utilized ensemble learning and classic ML models are compared against the proposed two DL architectures on different accuracy metrics,where the evaluation includes both numerical and visual comparisons of the examined *** obtained results show that the ensemble learning models outperformed the classic machine learning-based models(e.g.,linear regression and random forest)and the DL-based models.

关键词： Deep learning price prediction seasonal goods time series analysis

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Blockchain-based trusted dispute resolution service architecture

Blockchain-based trusted dispute resolution service architec...

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Sharma, Ravi Mohan Krishna, V. Rama Saikia, Tirtha Suri, Ashish Rivera, Richard Mavaluru, Dinesh Department of Computer Science and Applications Makhanalal Chaturvedi National University of Journalism and Communication Madhya Pradesh Bhopal India CVR College of Engineering Hyderabad India Economics Mittal School of Business Lovely Professional University India School of Electronics and Communication Engineering Shri Mata Vaishno Devi University India Department of Informatics and Computer Science Escuela Politécnica Nacional Quito Ecuador College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia

ISBN: (纸本)9781032669663

In the traditional service architecture (Service-Oriented Architecture, SOA), the Web Service provider registers its service description in the registry for service consumers to discover and call services. Although this architecture can provide open service calls, it lacks a dispute resolution mechanism. The trusted invocation of services between service consumers and providers who do not trust each other cannot be guaranteed. Blockchain technology has significant advantages in decentralization and anti-tampering and can be reasonably applied in traditional SOA to solve the problem of service credibility. Trusted SOA architecture based on blockchain is proposed to realize credible service invocation by combining traditional SOA architecture and blockchain technology. During a credible service invocation, or service consumption, The provider encrypts the parameters and sends them to the target service provider;the service provider receives the encrypted parameters and completes the decryption;the service provider completes the service execution and completes the encryption of the output result;finally, the service provider sends the encrypted result to the service provider Consumers complete the construction and chaining of trusted credentials at the same time. Based on the above, when a service dispute occurs, the ruling smart contract will be triggered to handle the service dispute correctly. The experimental results show that compared with the traditional invocation, the proposed method can correctly handle service disputes between service providers and requesters under the premise of ensuring that the growth rate of most Service trusted call times is not more excellent than 30%. by combining traditional SOA architecture and blockchain technology by combining traditional SOA architecture and blockchain technology. © 2024 The Author(s).

关键词： Blockchain

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Accelerating AI and computer Vision for Satellite Pose Estimation on the Intel Myriad X Embedded SoC

arXiv

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arXiv 2024年

作者： Leon, Vasileios Minaidis, Panagiotis Lentaris, George Soudris, Dimitrios National Technical University of Athens School of Electrical and Computer Engineering Greece University of West Attica Department of Informatics and Computer Engineering Greece

The challenging deployment of Artificial Intelligence (AI) and computer Vision (CV) algorithms at the edge pushes the community of embedded computing to examine heterogeneous System-on-Chips (SoCs). Such novel computing platforms provide increased diversity in interfaces, processors and storage, however, the efficient partitioning and mapping of AI/CV workloads still remains an open issue. In this context, the current paper develops a hybrid AI/CV system on Intel's Movidius Myriad X, which is an heterogeneous Vision Processing Unit (VPU), for initializing and tracking the satellite's pose in space missions. The space industry is among the communities examining alternative computing platforms to comply with the tight constraints of on-board data processing, while it is also striving to adopt functionalities from the AI domain. At algorithmic level, we rely on the ResNet-50-based UrsoNet network along with a custom classical CV pipeline. For efficient acceleration, we exploit the SoC's neural compute engine and 16 vector processors by combining multiple parallelization and low-level optimization techniques. The proposed single-chip, robust-estimation, and real-time solution delivers a throughput of up to 5 FPS for 1-MegaPixel RGB images within a limited power envelope of 2W. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

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An Efficient Text Recognition System from Complex Color Image for Helping the Visually Impaired Persons

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computer Systems Science & engineering 2023年第7期46卷 701-717页

作者： Ahmed Ben Atitallah Mohamed Amin Ben Atitallah Yahia Said Mohammed Albekairi Anis Boudabous Turki MAlanazi Khaled Kaaniche Mohamed Atri Department of Electrical Engineering College of EngineeringJouf UniversitySakakaSaudi Arabia Laboratory of Informatics Gaspard-MongeA3SIESIEE ParisCNRSGustave Eiffel UniversityFrance LETI ENISUniversity of SfaxSfaxTunisia Remote Sensing Unit College of EngineeringNorthern Border UniversityArarSaudi Arabia Laboratory of Electronics and Microelectronics(LR99ES30) University of MonastirTunisia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia College of Computer Sciences King Khalid UniversityAbhaSaudi Arabia

The challenge faced by the visually impaired persons in their day-today lives is to interpret text from *** this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into *** system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been *** this study,an acceleration of the GCM algorithm(AGCM)is *** AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original *** assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech *** text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.

关键词： Text recognition system GCM AGCM OCR color images graphical interface

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A Game Theoretic Approach for Efficient Resource Allocation in 5G Networks 14

A Game Theoretic Approach for Efficient Resource Allocation ...

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14th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, ICUMT 2022

作者： Aspasia, Koukouvela Christos, Bouras Vasileios, Kokkinos Apostolos, Gkamas Philippos, Pouyioutas University of Patras Computer Engineering and Informatics Department Patras Greece University Ecclesiastical Academy of Vella Ioannina Greece University of Nicosia Department of Computer Science Nicosia Cyprus

ISBN: (数字)9798350398663

ISBN: (纸本)9798350398663

Heterogeneous Networks (HetNets), which enable rapid expansion in mobile traffic, have been hailed as a critical technology for 5G communications. HetNets could increase the network's capacity and enable it to support additional users. However, interference between different cells makes Quality of Service (QoS) more challenging, and thus innovative protocols, and emerging trends should be incorporated to provide Resource Allocation efficiency (RA). Concepts provided from Game Theory (GT) have been widely applied to a variety of problems where the actions of one may influence or even conflict with those of others. As a result, game formulations are utilized, and the idea of equilibrium is applied to find a stable solution for all participants. In this paper, we compare two algorithms used for RA, the first being a classical RA algorithm and the second being a game theoretic one. The game implemented is called 'Tragedy of the Commons' and is applied in a non-cooperative network. © 2022 IEEE.

关键词： Game theory

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Load Balancing Algorithm in a Software-Defined Network Environment with Round Robin and Least Connections 7th

Load Balancing Algorithm in a Software-Defined Network Env...

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7th EAI International Conference on Smart Grid and Internet of Things, SGIoT 2023

作者： Wijaya, Chandra Wiryasaputra, Rita Huang, Chin-Yin Tanato, Jodi Yang, Chao-Tung Department of Industrial Engineering and Enterprise Information Tunghai University Taichung407224 Taiwan Department of Informatics Parahyangan Catholic University Bandung40141 Indonesia Department of Informatics Krida Wacana Christian University Jakarta11470 Indonesia Department of Computer Science Tunghai University Taichung407224 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407224 Taiwan

ISBN: (纸本)9783031559754

In a traditional computer network, each device has its configuration. The Software Defined Network (SDN) architecture ensures that every device in the network will become a dummy device, which must connect to a controller before action can be taken on every packet that the device receives. Each device does not require manual configuration with the centralized configuration. The huge growth of internet traffic can affect the server’s performance when handling requests of many clients. The algorithms, such as Round Robin and Least Connection, influence the load-balancing technology to divide the request to some servers. The server’s performance increases after implementing load balancing with the algorithm in testing. The comparative result of the Round Robin and Least Connection algorithms shows that the Least Connection performs better than the Round Robin algorithm. By using load balancing in the SDN architecture, the increasing of the request capacity can be handled by the server. © ICST Institute for computer Sciences, Social informatics and Telecommunications engineering 2024.

关键词： Network architecture

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Verifying Shortest Paths in Linear Time

arXiv

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arXiv 2024年

作者： Shokry, Ahmed Elmasry, Amr Khalafallah, Ayman Aly, Amr Computer and Systems Engineering Department Alexandria University Egypt Egypt University of Informatics Egypt

In this paper we propose a linear-time certifying algorithm for the single-source shortest-path problem capable of verifying graphs with positive, negative, and zero arc weights. Previously proposed linear-time approa... 详细信息

关键词： Graph algorithms

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Generating robotic elliptical excisions with human-like tool-tissue interactions

Generating robotic elliptical excisions with human-like tool...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Artūras Straižys Michael Burke Subramanian Ramamoorthy School of Informatics University of Edinburgh Department of Electrical and Computer Systems Engineering Monash University

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In surgery, the application of appropriate force levels is critical for the success and safety of a given procedure. While many studies are focused on measuring in situ forces, little attention has been devoted to relating these observed forces to surgical techniques. Answering questions like "Can certain changes to a surgical technique result in lower forces and increased safety margins?" could lead to improved surgical practice, and importantly, patient outcomes. However, such studies would require a large number of trials and professional surgeons, which is generally impractical to arrange. Instead, we show how robots can learn several variations of a surgical technique from a smaller number of surgical demonstrations and interpolate learnt behaviour via a parameterised skill model. This enables a large number of trials to be performed by a robotic system and the analysis of surgical techniques and their downstream effects on tissue. Here, we introduce a parameterised model of the elliptical excision skill and apply a Bayesian optimisation scheme to optimise the excision behaviour with respect to expert ratings, as well as individual characteristics of excision forces. Results show that the proposed framework can successfully align the generated robot behaviour with subjects across varying levels of proficiency in terms of excision forces.

关键词： Force measurement Force Surgery Safety Bayes methods Robots Optimization

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