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Real-World Wireless Network Modeling and Optimization:From Model/Data-Driven Perspective

Chinese Journal of Electronics 2022年第6期31卷 991-1012页

作者： LI Yang ZHANG Shutao REN Xiaohui ZHU Jianhang HUANG Jiajie HE Pengcheng SHEN Kaiming YAO Zhiqiang GONG Jie CHANG Tsunghui SHI Qingjiang LUO Zhiquan Shenzhen Research Institute of Big Data Pengcheng Lab School of Science and Engineering The Chinese University of Hong Kong (Shenzhen) College of Mathematics and Computational Sciences Xiangtan University School of Computer Science and Engineering Sun Yat-Sen University School of Software Engineering Tongji University

With the rapid development of the fifth-generation wireless communication systems, a profound revolution in terms of transmission capacity, energy efficiency, reliability, latency, and connectivity is highly expected to support a new batch of industries and applications. To achieve this goal, wireless networks are becoming extremely dynamic, heterogeneous, and complex. The modeling and optimization for the performance of realworld wireless networks are extremely challenging due to the difficulty to predict the network performance as a function of network parameters, and the prohibitively huge number of parameters to optimize. The conventional network modeling and optimization approaches rely on drive test, trial-and-error, and engineering experience,which are labor intensive, error-prone, and far from optimal. On the other hand, while the research community has spent significant efforts in understanding the fundamental limits of radio channels and developing physical layer techniques to operate close to it, very little is known about the performance limits of wireless networks, where millions of radio channels interact with one another in complex manners. This paper reviews the very recent mathematical and learning based techniques for modeling and optimizing the performance of real-world wireless networks in five aspects, including channel modeling, user demand and traffic modeling, throughput modeling and prediction, network parameter optimization, and IRS empowered performance optimization, and also presents the corresponding notable performance gains.

关键词： network parameter optimization telecommunication computing optimisation mathematical techniques wireless channels performance optimization learning based techniques telecommunication traffic mathematical analysis physical layer techniques channel modeling wireless network modeling fifth generation wireless communication systems learning (artificial intelligence) model-data-driven perspective IRS empowered performance optimization radio channels traffic modeling radio networks

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Adaptive energy-preserving algorithms for guiding center system

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Plasma science and Technology 2023年第4期25卷 11-22页

作者：朱贝贝刘健张嘉炜祝爱卿唐贻发 Department of Applied Mathematics School of Mathematics and PhysicsUniversity of Science and Technology BeijingBeijing 100083Peopleʼs Republic of China School of Nuclear Science and Technology University of Science and Technology of ChinaHefei 230026Peopleʼs Republic of China Advanced algorithm Joint Lab Shandong Computer Science CenterQilu University of TechnologyJinan 250014Peopleʼs Republic of China The State Key Laboratory of Scientific and Engineering Computing The Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190Peopleʼs Republic of China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049Peopleʼs Republic of China

We develop two types of adaptive energy preserving algorithms based on the averaged vector field for the guiding center dynamics,which plays a key role in magnetized *** adaptive scheme is applied to the Gauss Legendre’s quadrature rules and time stepsize respectively to overcome the energy drift problem in traditional energy-preserving *** new adaptive algorithms are second order,and their algebraic order is carefully *** results show that the global energy errors are bounded to the machine precision over long time using these adaptive algorithms without massive extra computation cost.

关键词： guiding center system energy-preserving methods adaptive energy conservation

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Digital Twin of a Vibration System for Active Geomonitoring of the Environment 16

Digital Twin of a Vibration System for Active Geomonitoring ...

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16th IEEE International Scientific and Technical Conference Actual Problems of Electronic Instrument Engineering, APEIE 2023

作者： Khairetdinov, Marat S. Yakimenko, Alexander A. Nishlyaev, Evgenii V. Novosibirsk State Technical University Institute of Computational Mathematics and Mathematical Geophysics of SB RAS Novosibirsk Russia Department of Computer Science Novosibirsk State Technical University Novosibirsk Russia

ISBN: (纸本)9798350330885

The problem of constructing a digital twin of a vibration geophysical system for active geophysical monitoring of the environment is considered. The system is used to probe complex media in the "lithosphere-atmosphere-hydrosphere" complex in order to monitor the dynamically changing geophysical characteristics of media in time and space. First of all, this concerns seismic-volcano-hazardous zones, landslide areas, areas of quarry and nuclear explosions, etc. in order to develop methods for predicting catastrophic phenomena - earthquakes, volcanic eruptions, etc. An example of such a seismically active zone is the Baikal Rift Zone. The functioning of the virtual part of the digital twin of a vibration geophysical system is based on multifactor equations for the propagation and processing of vibration oscillations in complex environments. Such equations determine the main components of the digital twin, the connections between them and the simulation modes that underlie the digital twin. The implementation of the virtual digital model is provided using the Manufacturing and Transportation Simulation System simulation modeling system. The system is a visually interactive processor-oriented simulation modeling system for technical systems and technological processes. © 2023 IEEE.

关键词： Volcanoes

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CryoBench: diverse and challenging datasets for the heterogeneity problem in cryo-EM 24

CryoBench: diverse and challenging datasets for the heteroge...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Minkyu Jeon Rishwanth Raghu Miro Astore Geoffrey Woollard Ryan Feathers Alkin Kaz Sonya M. Hanson Pilar Cossio Ellen D. Zhong Department of Computer Science Princeton University Princeton NJ Center for Computational Biology and Center for Computational Mathematics Flatiron Institute New York NY Center for Computational Biology and Center for Computational Mathematics Flatiron Institute New York NY and Department of Computer Science University of British Columbia Vancouver BC Canada

ISBN: (纸本)9798331314385

Cryo-electron microscopy (cryo-EM) is a powerful technique for determining high-resolution 3D biomolecular structures from imaging data. Its unique ability to capture structural variability has spurred the development of heterogeneous reconstruction algorithms that can infer distributions of 3d structures from noisy, unlabeled imaging data. Despite the growing number of advanced methods, progress in the field is hindered by the lack of standardized benchmarks with ground truth information and reliable validation metrics. Here, we introduce CryoBench, a suite of datasets, metrics, and benchmarks for heterogeneous reconstruction in cryo-EM. CryoBench includes five datasets representing different sources of heterogeneity and degrees of difficulty. These include conformational heterogeneity generated from designed motions of antibody complexes or sampled from a molecular dynamics simulation, as well as compositional heterogeneity from mixtures of ribosome assembly states or 100 common complexes present in cells. We then analyze state-of-the-art heterogeneous reconstruction tools, including neural and non-neural methods, assess their sensitivity to noise, and propose new metrics for quantitative evaluation. We hope that CryoBench will be a foundational resource for accelerating algorithmic development and evaluation in the cryo-EM and machine learning communities. Project page: https://***.

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Development of an Educational Intellectual System for the Analysis of Polymer Materials in Additive Manufacturing 24

Development of an Educational Intellectual System for the An...

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24th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2023

作者： Farahov, Rustam R. Burnashev, Rustam A. Grigoriev, Rostislav A. Nasibullin, Ilnur A. Enikeev, Arslan I. Bolsunovskaya, Marina V. Institute of Computational Mathematics and Information Technologies Kazan Federal University Kazan Russia Institute of Computer Science and Technology Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (纸本)9798350336870

The paper presents an educational intelligent system 'Expert Polymer' for identifying particles appropriate for 3D printing. The software system is designed to analyze images of polymer materials at manufacturing site via optics. It is planned that this intellectual system will be used as a training software package for students in higher educational institutions, as well as for bioengineers and materials scientists for research and production purposes. The study used Internet of Things (IoT) technologies to obtain images from optical measuring devices (electron microscope, etc.) from the system users and send them the results of image analysis. By the interaction of an electron microscope with the created software system, the task was performed to determine the number of all particles and the number of particles satisfying the 3D printing algorithm. Based on these data, the expert decides on the possibility of using polymer particles for subsequent 3D printing. To implement the system, modern libraries of the Python programming language were used, namely Pandas, Direction2 and YOLOv5 and others. © 2023 IEEE.

关键词： 3D printing

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Level Set Teleportation: An Optimization Perspective

arXiv

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arXiv 2024年

作者： Mishkin, Aaron Bietti, Alberto Gower, Robert M. Department of Computer Science Stanford University United States Center for Computational Mathematics Flatiron Institute

We study level set teleportation, an optimization sub-routine which seeks to accelerate gradient methods by maximizing the gradient norm on a level-set of the objective function. Since the descent lemma implies that gradient descent (GD) decreases the objective proportional to the squared norm of the gradient, level-set teleportation maximizes this one-step progress guarantee. For convex functions satisfying Hessian stability, we prove that GD with level-set teleportation obtains a combined sub-linear/linear convergence rate which is strictly faster than standard GD when the optimality gap is small. This is in sharp contrast to the standard (strongly) convex setting, where we show level-set teleportation neither improves nor worsens convergence rates. To evaluate teleportation in practice, we develop a projected-gradient-type method requiring only Hessian-vector products. We use this method to show that gradient methods with access to a teleportation oracle uniformly out-perform their standard versions on a variety of learning problems. Copyright © 2024, The Authors. All rights reserved.

关键词： Gradient methods

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Predicting the friction angle of clays using a multi-layer perceptron neural network enhanced by yeo-johnson transformation and coral reefs optimization

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第10期16卷 3982-4003页

作者： Libing Yang Trung Nguyen-Thoi Trung-Tin Tran College of Civil Engineering and Architecture Hunan Institute of Science and TechnologyYueyang414006China Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial IntelligenceVan Lang UniversityHo Chi Minh CityViet Nam Faculty of Mechanical-Electrical and Computer Engineering School of TechnologyVan Lang UniversityHo Chi Minh CityViet Nam Department of Information Technology Greenwich VietnamFPT UniversityDa Nang550000Viet Nam

The accurate prediction of the friction angle of clays is crucial for assessing slope stability in engineering *** study addresses the importance of estimating the friction angle and presents the development of four soft computing models:YJ-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and *** of all,the Yeo-Johnson(YJ)transformation technique was used to stabilize the variance of data and make it more suitable for parametric statistical models that assume normality and equal *** technique is expected to improve the accuracy of friction angle prediction *** friction angle prediction models then utilized multi-layer perceptron neural networks(MLPnet)and metaheuristic optimization algorithms to further enhance performance,including flower pollination algorithm(FPA),coral reefs optimization(CRO),ant colony optimization continuous(ACOC),and cuckoo search algorithm(CSA).The prediction models without the YJ technique,***-MLPnet,CRO-MLPnet,ACOC-MLPnet,and CSA-MLPnet,were then compared to those with the YJ technique,***-FPA-MLPnet,YJ-CRO-MLPnet,YJ-ACOC-MLPnet,and *** these,the YJ-CRO-MLPnet model demonstrated superior reliability,achieving an accuracy of up to 83%in predicting the friction angle of clay in practical engineering *** improvement is significant,as it represents an increase from 1.3%to approximately 20%compared to the models that did not utilize the YJ transformation technique.

关键词： Natural hazards Slope stability Friction angle Clay Soft computing models Geotechnical engineering

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computer Network Technology in Big Data Distributed Cloud Storage Platform

Computer Network Technology in Big Data Distributed Cloud St...

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作者： Xu, Yuelin Wang, Yuran Wan, Baiyang Khan, Ahthasham Ullah Department of Computational Mathematics and Cybernetics Mathematics and Applied Mathematics Shenzhen MSU-BIT University Guangdong Shenzhen518172 China Faculty of Economics Shenzhen MSU-BIT University Guangdong Shenzhen518172 China Institute of IT and Computer Science Afghanistan Kabul Afghanistan

In the era of big data, distributed cloud storage platforms are widely used to store massive amounts of data and information. Compared with traditional storage methods, distributed cloud storage platforms can provide flexible storage space to ensure the security and speed of platform operating data. This article uses computer network technology to design a distributed cloud storage platform, test platform file upload and download time and user login platform success rate to verify the reliability of platform operation, and realize the feasibility of user login function module operation, I hope this article distributed cloud storage platform can help people process data efficiently and realize the safe preservation of data and information. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Distributed cloud

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Multiobjective adaptive car-following control of an intelligent vehicle based on receding horizon optimization

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science China(Information sciences) 2023年第4期66卷 301-302页

作者： Hongbo GAO Juping ZHU Fei ZHANG Ruidong YAN Junjie ZHOU Lei JIANG Jianqiang WANG Keqiang LI Department of Automation University of Science and Technology of China Institute of Advanced Technology University of Science and Technology of China Department of Computational Mathematics School of Mathematical Sciences Anhui University School of Traffic and Transportation Beijing Jiaotong University Autonomous Driving Business Unit Chery Automobile School of College of Computer Science and Technology Zhejiang University China North Vehicle Research Institute School of Automotive Engineering Tsinghua University

Dear editor, Vehicle control is one of the key steps of intelligent driving [1]. Algorithms based on receding horizon optimization(RHO) can predict future trajectories and handle multiobjective constraint conditions; therefore, RHO-based methods have attracted considerable attention in the field of vehicle control. Although existing methods use RHO to design controllers, they do not simultaneously meet the multiobjective optimal control performance requirements on tracking, fuel economy, and ride comfort.

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Development of a Method and System for Recycling Polystyrene Production Waste 25

Development of a Method and System for Recycling Polystyrene...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Farahov, Rustam R. Burnashev, Rustam A. Enikeeva, Adelya I. Bolsunovskaya, Marina V. Institute of Computational Mathematics and Information Technologies Kazan Federal University Kazan Russia Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russia Institute of Computer Science and Technology Peter the Great St. Petersburg Polytechnic University St. Petersburg Russia

ISBN: (纸本)9798350389234

Currently, the consumption of natural resources is important for humanity. Therefore, reducing the production of production waste not only saves natural resources, but also increases the profit of the manufacturer. When producing polystyrene powder, the waste produced is a coarse powder with a wide range of particle sizes and irregular geometry. It is possible to obtain low-grade products from waste, such as disposable tableware, industrial containers, Petri dishes, etc. Manufacturers are interested in developing new processing methods to use waste materials to produce high-quality products. The purpose of the work is to study the possibility of using polystyrene production waste in selective laser sintering processes. The method we are developing for processing polystyrene-based polymer powder allows us to avoid the use of additional chemical exposure, and to select the optimal operating mode for a selective laser sintering installation with the resulting processed material. It is planned to introduce this method into the field of materials processing for additive manufacturing. © 2024 IEEE.

关键词： Laser heating

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