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arXiv 2023年

作者： Li, Hengguang Yin, Peimeng Wayne State University Department of Mathematics DetroitMI48202 United States Multiscale Methods and Dynamics Group Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

In this paper, we study the sixth order equation with the simply supported boundary conditions in a polygonal domain. We propose a new mixed formulation that decomposes the sixth order problem into a system of Poisson equations. Depending on the interior angles of the domain, additional Poisson problems may be needed to confine the solution to the correct Sobolev space. In addition, we propose a C0finite element algorithm for the sixth order problem and provide the optimal error analysis. Numerical results are reported to verify the theoretical findings. © 2023, CC BY-NC-ND.

关键词： Boundary conditions

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Software Service for Studying Words of the Ukrainian Language 11

Software Service for Studying Words of the Ukrainian Languag...

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11th International Conference on Advanced computer Information Technologies, ACIT 2021

作者： Shevchuk, Ruslan Mykytiuk, Vitalii Miramontes, David Alfonso Yushko, Andriy Yurchyshyn, Tetiana Mokhun, Serhii West Ukrainian National University Department of Computer Science Ternopil Ukraine Us Pease Corps San DiegoCA United States West Ukrainian National University Department of Foreign Languages Information and Communication Technologies Ternopil Ukraine Ternopil Volodymyr Hnatiuk National Pedagogical University Department of Physics and Methods of Its Teaching Ternopil Ukraine

This paper addresses the issue of teaching Ukrainian as a foreign language with the help of modern software. The technical requirements and software service architecture for studying words of Ukrainian language were proposed. This service integrates word forms of Ukrainian words, their grammatical meanings, grammatical cases and means of expression. This allows to carry out effective management of arrays of lexicographic data and to receive examples of use of Ukrainian words in various contexts. The software service developed for learning Ukrainian words is based on the Single-Page Applications, REST API and uses the JavaScript-library React and the *** Core framework. © 2021 IEEE.

关键词： Application programs

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Equivariant Spatio-Temporal Attentive Graph Networks to Simulate Physical Dynamics

arXiv

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arXiv 2024年

作者： Wu, Liming Hou, Zhichao Yuan, Jirui Rong, Yu Huang, Wenbing Gaoling School of Artificial Intelligence Renmin University of China China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China Department of Computer Science North Carolina State University United States Tsinghua University China Tencent AI Lab China

Learning to represent and simulate the dynamics of physical systems is a crucial yet challenging task. Existing equivariant Graph Neural Network (GNN) based methods have encapsulated the symmetry of physics, e.g., translations, rotations, etc, leading to better generalization ability. Nevertheless, their frame-to-frame formulation of the task overlooks the non-Markov property mainly incurred by unobserved dynamics in the environment. In this paper, we reformulate dynamics simulation as a spatio-temporal prediction task, by employing the trajectory in the past period to recover the Non-Markovian interactions. We propose Equivariant Spatio-Temporal Attentive Graph Networks (ESTAG), an equivariant version of spatio-temporal GNNs, to fulfill our purpose. At its core, we design a novel Equivariant Discrete Fourier Transform (EDFT) to extract periodic patterns from the history frames, and then construct an Equivariant Spatial Module (ESM) to accomplish spatial message passing, and an Equivariant Temporal Module (ETM) with the forward attention and equivariant pooling mechanisms to aggregate temporal message. We evaluate our model on three real datasets corresponding to the molecular-, protein- and macro-level. Experimental results verify the effectiveness of ESTAG compared to typical spatio-temporal GNNs and equivariant GNNs. Copyright © 2024, The Authors. All rights reserved.

关键词： Message passing

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Queue Modelling and Jitter Control in Mobile Ad Hoc Networks

Queue Modelling and Jitter Control in Mobile Ad Hoc Networks

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Information and Communication Technologies (ZCICT), Zimbabwe Conference of

作者： Benny M Nyambo Gerrit. K Janssens Hillary Marufu Michael Munyaradzi Bernard Mapako Kaitano Dzinavatonga Faculty of Technology Zimbabwe Open University Harare Zimbabwe Department Quantitative Methods Hasselt University Diepenbeek Belgium Computer Science Department University of Zimbabwe Harare Zimbabwe Faculty of Science Zimbabwe Open University Harare Zimbabwe

ISBN: (纸本)9781665475778

Jitter in multimedia traffic is mainly introduced by variations in network characteristics. Ifjitter is so significant in the application that is receiving, this can result in a degraded performance in real-time multimedia communications applications. Jitter causes inaudible audio or unclear video which can be undesirable and uncomfortable to the user. Buffers are often employed to temporarily to store arriving packets before playing them at equal intervals to curb and minimize jitter. Jitter for voice packets should not exceed 20-50 milliseconds within a given stream. This paper proposes a method to reducejitter in intermediate nodes is proposed, such that when the packets arrive at the receiving end, there would be little or nojitter to process in the de-jitter buffer. We analyze M/G/1 nonpreemptive and pre-emptive resume priority queuing in the intermediate node and analyze how these models will affect delay and jitter. We found out that preemptive priority queuing performs better but almost the same to non-preemptive priority queuing. Both Priority based queues performed much better than the First in First out queue.

关键词： Analytical models Jitter Streaming media Real-time systems Information and communication technology Delays Multimedia communication

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Trainable and Explainable Simplicial Map Neural Networks

arXiv

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arXiv 2023年

作者： Paluzo-Hidalgo, Eduardo Gonzalez-Diaz, Rocio Gutiérrez-Naranjo, Miguel A. Department of Quantitative Methods Universidad Loyola Andalucía Campus Sevilla Dos Hermanas Seville Spain Department of Applied Mathematics I School of engineering University of Seville Seville Spain Department of Computer Science and Artificial Intelligence School of Engineering University of Seville Seville Spain

Simplicial map neural networks (SMNNs) are topology-based neural networks with interesting properties such as universal approximation ability and robustness to adversarial examples under appropriate conditions. However, SMNNs present some bottlenecks for their possible application in high-dimensional datasets. First, SMNNs have precomputed fixed weight and no SMNN training process has been defined so far, so they lack generalization ability. Second, SMNNs require the construction of a convex polytope surrounding the input dataset. In this paper, we overcome these issues by proposing an SMNN training procedure based on a support subset of the given dataset and replacing the construction of the convex polytope by a method based on projections to a hypersphere. In addition, the explainability capacity of SMNNs and effective implementation are also newly introduced in this paper. © 2023, CC BY.

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Exploring the Impact of Random Distribution Choices on Particle Swarm Optimization: An Initial Analysis

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Procedia computer science 2023年 225卷 4930-4942页

作者： Joanna Kołodziejczyk Yuliia Tarasenko Piotr Sulikowski Research Team on Intelligent Decision Support Systems Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. żołnierska 49 71-210 Szczecin Poland National Institute of Telecommunications ul. Szachowa 1 Warsaw 04-894 Poland Department of Information Systems Engineering Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. żołnierska 49 71-210 Szczecin Poland

Particle Swarm Optimization (PSO) is a robust stochastic optimization algorithm for solving complex and constrained optimization problems. This paper aims to systematically investigate the influence of diverse random number distributions on the learning parameters of PSO and evaluate the algorithm's sensitivity based on these parameters. To this end, several exhaustive numerical experiments were conducted on several test functions, including asymmetric Sphere, Easom, and Csendes. Initially, appropriate random distributions were identified for the learning parameters and proceeded to compare these distributions using all potential combinations. The sensitivity of PSO to these parameters was evaluated using the mean best score, the relative proximity of the best particle to the theoretical optimum, and the average objective function evaluations. The most significant contribution of this research lies in the insights derived from the experimental data. The discovery was that highly skewed and long-tailed distributions such as Chi, Chi-square, Lomax, and Exponential often underperform. On the other hand, distributions that are bounded proportionally to the problem domain consistently surpass the performance of the standard uniform distribution. These findings significantly enhance the understanding of PSO algorithms and provide valuable guidelines for their practical deployment.

关键词： Particle Swarm Optimization random number distribution stochastic optimization

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Identity-based data possession verification scheme for multi-replica storage in cloud

Identity-based data possession verification scheme for multi...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Yang, Xiaodong Wang, Xiuxiu Li, Kaibing Li, Xixi Department of Computer Science and Engineering Northwest Normal University room 9c102 Teaching Building No.9 967 Anning East Road Anning District Lanzhou City China

In the cloud storage environment, how to efficiently and dynamically complete the integrity verification of multi-user and multi-replica data is a challenging problem. Based on the bilinear mapping signature mechanism and the multi-branch authentication tree, we propose an identity-based integrity verification scheme of multi-replica data for cloud, which solves the problem of large public key storage and management overhead in signature algorithm based on traditional public key cryptosystems. The proof shows that our scheme satisfies the robustness and has the function of protecting privacy. The results of analysis indicate that, compared with the existing similar schemes, our scheme has higher communication efficiency and computing performance. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Cloud storage

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Multi-user fuzzy keyword searchable encryption scheme based on certificateless cryptosystem

Multi-user fuzzy keyword searchable encryption scheme based ...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Yang, Xiaodong Wang, Jiaqi Tian, Tian Wang, Xiuxiu Department of Computer Science and Engineering University of Northwest Normal University Teaching Building No. 9 Room 9C102 967 Anning East Road Anning District Lanzhou China

Nowadays, the application prospect of cloud storage is more and more extensive, and the security problem of cloud storage has become one of the hotspots of research. Searchable encryption can make full use of the huge computing resources of cloud servers and solve the problem of secure search after data encryption and upload. However, the existing searchable encryption schemes have the problems of high computational cost, low security, and insufficient flexibility in the way of searching keywords. In order to solve these problems, we propose a new certificateless multi-user fuzzy keyword searchable encryption scheme, which introduces the key distribution center, effectively reduces the computational cost, solves the problem of certificate management and key escrow, and uses the optimized wildcard technology to realize the fuzzy search of multiple users, which is not only brings convenience to users, but also realizes flexible search methods. Finally, the analysis results show that our scheme has indistinguishable security under keyword guessing attacks. Simulation experiments and performance analysis results show that our scheme has higher computational efficiency. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Cloud storage

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Blockchain-based searchable proxy re-encryption scheme for EHR security storage and sharing

Blockchain-based searchable proxy re-encryption scheme for E...

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2020 International Symposium on Automation, Information and Computing, ISAIC 2020

作者： Yang, Xiaodong Li, Xixi Chen, Aijia Xi, Wanting Department of Computer Science and Engineering Northwest Normal University room 9c102 Teaching Building No.9 967 Anning East Road Anning District Lanzhou City China

The sharing of electronic health records (EHR) has shown significant advantages in the accurate diagnosis of patients and the development of medical institutions. However, due to the privacy and sensitivity of medical data, it is easy to cause security issues such as difficulty in data sharing among different medical institutions and easy leakage of data privacy. Because the blockchain has the characteristics of non-tampering, anonymity, and decentralization. We propose a blockchain-based searchable proxy re-encryption scheme for EHR security storage and sharing. First, we use blockchain and cloud server to store encrypted EHR together to prevent EHR from being tampered with and leaked. Secondly, we use a certificateless encryption and proxy re-encryption based on identity and type scheme as a data sharing protocol. Meanwhile, searchable encryption technology is used to generate a keyword index. Moreover, the proxy node is selected by the delegated proof-of-stake (DPOS) consensus algorithm, which ensures the privacy, immutability and security. It realizes the safe access of third-party data users to medical health data. Finally, security analysis and evaluation show that our scheme can resist identity disguise and replay attacks. In addition, it has stronger security and higher efficiency. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Blockchain

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ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare 35

ESCAPED: Efficient Secure and Private Dot Product Framework ...

引用

35th AAAI Conference on Artificial Intelligence, AAAI 2021

作者： Ünal, Ali Burak Akgün, Mete Pfeifer, Nico Methods in Medical Informatics Department of Computer Science University of Tuebingen Germany Translational Bioinformatics University Hospital Tuebingen Tuebingen Germany Statistical Learning in Computational Biology Max Planck Institute for Informatics Saarbrücken Germany

ISBN: (纸本)9781713835974

Training sophisticated machine learning models usually requires many training samples. Especially in healthcare settings these samples can be very expensive, meaning that one institution alone usually does not have enough. Merging privacy-sensitive data from different sources is usually restricted by data security and data protection measures. This can lead to approaches that reduce data quality by putting noise onto the variables (e.g., in Ε-differential privacy) or omitting certain values (e.g., for k-anonymity). Other measures based on cryptographic methods can lead to very time-consuming computations, which is especially problematic for larger multi-omics data. We address this problem by introducing ESCAPED, which stands for Efficient SeCure And PrivatE Dot product framework. ESCAPED enables the computation of the dot product of vectors from multiple sources on a third-party, which later trains kernel-based machine learning algorithms, while neither sacrificing privacy nor adding noise. We have evaluated our framework on drug resistance prediction for HIV-infected people and multi-omics dimensionality reduction and clustering problems in precision medicine. In terms of execution time, our framework significantly outperforms the best-fitting existing approaches without sacrificing the performance of the algorithm. Even though we only present the benefit for kernel-based algorithms, our framework can open up new research opportunities for further machine learning models that require the dot product of vectors from multiple sources. Copyright © 2021, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Sensitive data

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