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13th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2019

作者： Wang, Ana Zhang, Lichen Guo, Longjiang Ren, Meirui Li, Peng Yan, Bin Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an710062 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province Xi’an710119 China School of Computer Science Shaanxi Normal University Xi’an710119 China

ISBN: (纸本)9783030364113

Mobile crowdsensing (MCS) employs numerous mobile users to perform sensing tasks, in which task assignment is a challenging issue. Existing researches on task assignment mainly consider spatial-temporal diversity and capacity diversity, but not focus on the type diversity of users, which may lead to low quality of tasks. This paper formalizes a novel task assignment problem in MCS, where a task needs the cooperation of various types of users, and the quality of a task is highly related to the various types of the recruited users. Therefore, the goal of the problem is to maximize the user type diversity subject to limited task budget. This paper uses three heuristic algorithms to try to resolve this problem, so as to maximize user type diversity. Through further simulations, the proposed algorithm UR-GAT (Unit Reward-based Greedy algorithm by type) obviously improves the user type diversity. © 2019, Springer Nature Switzerland AG.

关键词： Heuristic algorithms

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Multiple Riemann wave solutions of the general form of quasilinear hyperbolic systems

arXiv

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arXiv 2022年

作者： Grundland, A.M. de Lucas, Javier Centre de Recherches Mathématiques Université de Montréal Succ. Centre-Ville CP 6128 MontréalQCH3C 3J7 Canada Department of Mathematics and Computer Science Université du Québec CP 500 Trois-RivièresQCG9A 5H7 Canada Department of Mathematical Methods in Physics University of Warsaw ul. Pasteura 5 Warszawa02-093 Poland

The objective of this paper is to construct geometrically Riemann k-wave solutions of the general form of first-order quasilinear hyperbolic systems of partial differential equations. To this end, we adapt and combine elements of two approaches to the construction of Riemann k-waves, namely the symmetry reduction method and the generalized method of characteristics. We formulate a geometrical setting for the general form of the k-wave problem and discuss in detail the conditions for the existence of k-wave solutions. An auxiliary result concerning the Frobenius theorem is established. We use it to obtain formulae describing the k-wave solutions in closed form. Our theoretical considerations are illustrated by examples of hydrodynamic type systems including the Brownian motion *** Codes 35Q53 (primary), 35A30, 35Q58, 53A05 (secondary) © 2022, CC BY.

关键词： Brownian movement

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Cost-Aware Cooperative Theory Based Routing in Mobile Opportunistic Networks 12th

Cost-Aware Cooperative Theory Based Routing in Mobile Opport...

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12th China Wireless Sensor Network Conference, CWSN 2018

作者： Yu, Sui Zhang, Lichen Li, Lixia Wang, Xiaoming Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an710062 China Engineering Laboratory of Teaching Information Technology of Shaanxi Province Xi’an710119 China School of Computer Science Shaanxi Normal University Xi’an710119 China

ISBN: (纸本)9789811368332

Mobile Opportunistic Networks (MONs) are a class of wireless Delay Tolerant Networks that have been widely utilized in the areas of sporadic network connectivity. Many routing protocols in MONs assume that nodes are willing to forward messages to others. However, in real world scenarios, nodes behave selfishly and do not choose to be cooperative throughout due to a variety of reasons, ranging from lower energy levels to buffer shortages. Thus, it is imperative to develop incentive mechanisms to reward nodes for cooperation. In this paper, we propose a cost-aware cooperative theory-based routing protocol called CACR that is able to improve the delivery ratio and reduce the cost of nodes as well as incentivize them to participate in message routing. CACR is based on cooperative theory and adopts Shapley value to distribute the extra payoff for all participants to achieve the payment fairness according to the contribution of each participant. Subsequent simulations based on real-life traces show that CACR provides higher delivery rate and less transmission overheads than the existing routing protocols in MONs with selfish nodes. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Routing protocols

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Conference Chairs and Editors of the Proceedings

9th Research in Engineering Education Symposium and 32nd Aus...

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9th Research in Engineering Education Symposium and 32nd Australasian Association for Engineering Education Conference, REES AAEE 2021: Engineering Education Research Capability Development 2021年 1卷 i-iii页

作者： Male, Sally Guzzomi, Andrew McDonald, Chris Hassan, Ghulam Mubashar Engineering and Technology Education Faculty of Engineering and IT The University of Melbourne Australia The Teaching and Learning Laboratory Faculty of Engineering and IT The University of Melbourne Australia The University of Western Australia The Centre for Engineering Innovation: Agriculture & Ecological Restoration School of Engineering The University of Western Australia Australia School of Physics Mathematics and Computer Science The University of Western Australia Australia

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Method of Automatic Rhythmcardiogram Formation with the Increased Informativeness by Means of the Electrocardiogram Processing

Method of Automatic Rhythmcardiogram Formation with the Incr...

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International Conference on Advanced computer Information Technologies (ACIT)

作者： Andriy Zozulia Iaroslav Lytvynenko Nadiia Lutsyk Serhii Lupenko Oleh Yasniy Department of Computer Systems and Networks Ternopil Ivan Puluj National Technical University Ternopil Ukraine Department of Computer Science Ternopil Ivan Puluj National Technical University Ternopil Ukraine Department of Mathematical Methods in Engineering Ternopil Ivan Puluj National Technical University Ternopil Ukraine

ISBN: (数字)9781728167602

ISBN: (纸本)9781728167619

In the study, it was for the first time justified and applied the method of rhythmcardiogram automatic formation with the increased informativeness by means of preliminary registered rhythmcardiogram processing. This method allows automating completely the process of heart rhythm analysis based on rhythmcardiogram with the increased informativeness in the computer systems of human heart rhythm functional diagnostics and is more informative compared with the known methods of heart rhythm analysis based on the classical rhythmcardiogram.

关键词： Heart beat Periodic structures Rhythm Random processes Mathematical model Computational modeling

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An Efficient Interest-aware Data Dissemination Approach in Opportunistic Networks

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Procedia computer science 2019年 147卷 394-399页

作者： Sui Yu Lichen Zhang Lixia Li Bin Yan Zhipeng Cai Lizong Zhang Key Laboratory of Modern Teaching Technology Ministry of Education Xi’an 710062 China School of Computer Science Shaanxi Normal University Xi’an 710062 China Department of Computer Science Georgia State University Atlanta 30303 USA School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 China

Due to the high mobility of humans and resource limitation of smart mobile devices, the design of efficient data dissemination schemes faces great challenges in opportunistic networks (OppNets). The current data dissemination schemes generally concentrate on the similarity among nodes while ignoring the similarity between nodes and data packets, which leads to that data packets move back and forth among the nodes with similar social features instead of reaching to the subscribers directly. In this paper, an efficient interest-aware data dissemination (EIAD) approach is proposed, in which the similarity between nodes and data packets is used to determine whether a node is a potential destination. Moreover, both the social feature and the residual energy are considered to choose an appropriate relay node and then determine the number of packet’s replicas. Furthermore, the broadcast characteristic of wireless data transfer is exploited to reduce unnecessary transmissions and energy consumption. The evaluations towards a real-world dataset reveal that the proposed algorithm outperforms the existing results.

关键词： Interest-aware Social feature Data dissemination Opportunistic networks

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Smart system for detecting unauthorized entry into a smart home

Smart system for detecting unauthorized entry into a smart h...

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2020 IEEE International Conference "Quality Management, Transport and Information Security, Information Technologies", IT and QM and IS 2020

作者： Sedova, Nelly A. Arkhipova, Zoya V. Lavrov, Evgeniy A. Ledovskikh, Irina A. Bazhenov, Ruslan I. Vladivostok State University of Economics and Service Department of Information Technology and Systems Vladivostok Russia Technologies Baikal State University Department of Mathematical Methods and Digital Irkutsk Russia Sumy State University Department of Computer Science Sumy Ukraine Pacific National University Department of Mathematics and Information Technology Khabarovsk Russia Sholom-Aleichem Priamursky State University Department of Information Systems and Mathematics Russia

ISBN: (纸本)9781728181790

The article covers the matter of the risk assessment of unauthorized entry into a smart home. Thereby the authors model and compare two approaches to the issue considered. The first technique actualizes a fuzzy system for the level detecting intrusion danger and warns about an unauthorized entry. But the second technique deals with a neuro-fuzzy system construction for assessing the level of unauthorized entry to the smart home. The authors present a structure and methods of training fuzzy and neuro-fuzzy systems to evaluate the level of unauthorized entry to the smart home. They carry out a series of experiments on the models of the designed systems. According to the results of comparative analysis, the authors recognize the application feasibility of a neuro-fuzzy system to assess the level of unauthorized entry to a smart home with a fuzzy logic inference algorithm based on Takagi Sugeno fuzzy model. Besides, the authors run a neuro-fuzzy system computer modelling/simulation to identify its best values. In particular, they declare a list of the best membership functions for generating input linguistic variables. They also propose a hybrid learning technique and the method of linear coefficients for developing terms of the output variable/signal. © 2020 IEEE.

关键词： Membership functions

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Predicting Future Mutations To Inform Vaccine Design

Research Square

引用

Research Square 2021年

作者： Chattopadhyay, Ishanu Li, Jin Li, Timmy Esser-Kahn, Aaron Department of Medicine University of Chicago United States Committee on Genetics Genomics & Systems Biology University of Chicago United States Committee on Quantitative Methods in Social Behavioral and Health Sciences University of Chicago United States Department of Computer Science University of Chicago ChicagoIL United States Pritzker School of Molecular Engineering University of Chicago ChicagoIL United States

Influenza viruses constantly evolve, and mismatches between predicted and circulating strains impact vaccine effectiveness. A barrier to predicting the season-specific dominant strains is the limited ability to predict future mutations, or estimate the numerical likelihood of specific future strains. Here, we introduce a biology-aware sequence similarity metric based on deep pattern recognition of evolutionary constraints, that calculate the odds of future mutations, outperforming WHO recommended flu vaccine compositions almost consistently over the two decades. © 2021, CC BY.

关键词： Vaccines

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Predicting stroke with machine learning techniques in a sub-Saharan African population

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Neuroscience Informatics 2025年第3期5卷

作者： Benjamin Segun Aribisala Deirdre Edward Godwin Ogbole Onoja M. Akpa Segun Ayilara Fred Sarfo Olusola Olabanjo Adekunle Fakunle Babafemi Oluropo Macaulay Joseph Yaria Joshua Akinyemi Albert Akpalu Kolawole Wahab Reginald Obiako Morenikeji Komolafe Lukman Owolabi Godwin Osaigbovo Akinkunmi Paul Okekunle Arti Singh Philip Ibinaye Mayowa Owolabi Department of Radiology University of Chicago Chicago IL USA Department of Computer Science Lagos State University Lagos Nigeria Department of Computer Science Oduduwa University Nigeria Department of Radiology University of Ibadan Ibadan Nigeria Department of Epidemiology and Medical Statistics University of Ibadan Nigeria Department of Medicine Kwame Nkrumah University of Science and Technology Kumasi Ghana Department of Public Health College of Health Sciences Osun State University Osogbo Nigeria Department of Medicine College of Medicine University of Ibadan Ibadan Nigeria Department of Medicine University of Ghana Medical School Accra Ghana Department of Medicine University of Ilorin Teaching Hospital Ilorin Nigeria Department of Medicine Ahmadu Bello University Zaria Nigeria Department of Medicine Obafemi Awolowo University Teaching Hospital Ile-Ife Nigeria Department of Medicine Aminu Kano Teaching Hospital Kano Nigeria Department of Medicine University of Jos Jos Nigeria Department of Food and Nutrition Seoul National University Korea Department of Epidemiology and Biostatistics Kwame Nkrumah University of Science and Technology Ghana Centre for Genomic and Precision Medicine College of Medicine University of Ibadan Nigeria

Background Stroke is the second leading cause of death and the third leading cause of disability globally, including Africa, which bears its largest burden. Accurate models are needed in Africa to predict and prevent stroke occurrence. The aim of this study was to identify the best machine learning (ML) algorithm for stroke prediction. methods We assessed medical data of 4,236 subjects comprising 2,118 stroke patients and 2,118 controls from the SIREN database. Sixteen established vascular risk factors were evaluated in this study. These are addition of salt to food at table during eating, cardiac disease, diabetes mellitus, dyslipidemia, education, family history of cardiovascular disease, hypertension, income, low green leafy vegetable consumption, obesity, physical inactivity, regular meat consumption, regular sugar consumption, smoking, stress and use of tobacco. From these, we also selected the 11 topmost risk factors using Population-Attributable Risk ranking. Eleven ML models were built and empirically investigated using the 16 and the 11 risk factors. Results Our results showed that the 16 features-based classification (maximum AUC of 82.32%) had a slightly better performance than the 11 feature-based (maximum AUC 81.17%) algorithm. The result also showed that Artificial Neural Network (ANN) had the best performance amongst eleven algorithms investigated with AUC of 82.32%, sensitivity of 71.23%, specificity of 80.00%. Conclusion Machine Learning algorithms predicted stroke occurrence employing major risk factors in Sub-Saharan Africa better than regression models. Machine Learning, especially Artificial Neural Network, is recommended to enhance Afrocentric stroke prediction models for stroke risk factor quantification and control in Africa.

关键词： Stroke SIREN Sub-Sahara Africa Risk factors Machine learning Artificial neural network

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Parallel algorithms for tensor train arithmetic

arXiv

引用

arXiv 2020年

作者： Al Daas, Hussam Ballard, Grey Benner, Peter Department of Computational Methods in Systems and Control Theory Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany Computer Science Department Wake Forest University Winston SalemNC United States

We present efficient and scalable parallel algorithms for performing mathematical operations for low-rank tensors represented in the tensor train (TT) format. We consider algorithms for addition, elementwise multiplication, computing norms and inner products, orthonormalization, and rounding (rank truncation). These are the kernel operations for applications such as iterative Krylov solvers that exploit the TT structure. The parallel algorithms are designed for distributed- memory computation, and we propose a data distribution and strategy that parallelizes computations for individual cores within the TT format. We analyze the computation and communication costs of the proposed algorithms to show their scalability, and we present numerical experiments that demonstrate their efficiency on both shared-memory and distributed-memory parallel systems. For example, we observe better single-core performance than the existing MATLAB TT-Toolbox in rounding a 2GB TT tensor, and our implementation achieves a 34× speedup using all 40 cores of a single node. We also show nearly linear parallel scaling on larger TT tensors up to over 10,000 cores for all mathematical operations. Copyright © 2020, The Authors. All rights reserved.

关键词： Tensors

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