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Secure Statistical QoS Provisioning for Machine-type Wireless Communication Networks

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Secure Statistical QoS Provisioning for Machine-type Wireles...

IEEE Vehicular Technology Conference

作者： Hirley Alves Pedro. H. J. Nardelli Carlos H. M. de Lima Centre for Wireless Communications (CWC) University of Oulu Finland Laboratory of Control Engineering and Digital Systems Lappeenranta University of Technology Finland São Paulo State University (UNESP) São João da Boa Vista Brazil

This work assesses the performance of secure machine-type communication networks composed of a legitimate pair of devices communicating in the presence of an eavesdropper. We evaluate the impact of legitimate source's arrival traffic in the design of secure communication protocol. Our approach is based on the secrecy outage probability framework, which identifies the security level of transmissions. We then characterize the secrecy transmission rate that includes the arrival traffic, evaluating its impact on the secrecy performance of the network. We introduce ON-OFF adaptive and non-adaptive transmission schemes that maximizes both the secure effective capacity and the maximum average arrival rate at the source node. Our numerical results provide insights on the interplay between the different traffic originated from MTC devices and security in the system.

关键词： Security Quality of service Reliability Throughput Delays Power system reliability Probability

Principles of functioning of the autonomous device for weed control for precision agriculture

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IOP Conference Series: Materials Science and engineering 2020年第1期747卷

作者： A I Dyshekov I G Smirnov M A Mirzaev M A Shereuzhev Laboratory of intelligent digital systems of monitoring diagnostics and process control in agricultural production Federal Scientific Agroengineering Center VIM Moscow 367032 Russia Department of intellectualization automatization and robotic of rural production Federal Scientific Agroengineering Center VIM Moscow 109428 Russia Laboratory of innovative structural polymer composite and biocomposite parts of agricultural machinery Federal Scientific Agroengineering Center VIM Moscow 109428 Russia Special mechanical engineering Bauman Moscow State Technical University Moscow 105005 Russia

The article shows the results of creation of a system aimed at reducing the negative impact on the ecological situation and biological systems while eliminating weeds in beetroot production. Methods of controlling weeds using machine vision technology are examined. For machine vision algorithms a library of images has been prepared. An algorithm and technical device have been developed for cultivating the soil on the early stages of beet growth.

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Machine discovery of partial differential equations from spatiotemporal data

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arXiv 2019年

作者： Yuan, Ye Li, Junlin Li, Liang Jiang, Frank Tang, Xiuchuan Zhang, Fumin Liu, Sheng Goncalves, Jorge Voss, Henning U. Li, Xiuting Kurths, Jürgen Ding, Han School of Artificial Intelligence and Automation State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm11428 Sweden School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta30332 United States School of Power and Mechanical Engineering Wuhan University Wuhan430074 China Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom Luxembourg Centre for Systems Biomedicine University of Luxembourg BelvauxL-4367 Luxembourg Citigroup Biomedical Imaging Center Weill Cornell Medical College New York10021 United States Research Domain IV - Transdisciplinary Concepts & Methods Potsdam Institute for Climate Impact Research Potsdam14473 Germany School of Mechanical Science and Engineering State Key Laboratory of Digital Manufacturing Equipments and Technology Huazhong University of Science and Technology Wuhan430074 China

The study presents a general framework for discovering underlying Partial Differential Equations (PDEs) using measured spatiotemporal data. The method, called Sparse Spatiotemporal System Discovery (S3d), decides which physical terms are necessary and which can be removed (because they are physically negligible in the sense that they do not affect the dynamics too much) from a pool of candidate functions. The method is built on the recent development of Sparse Bayesian Learning;which enforces the sparsity in the to-be-identified PDEs, and therefore can balance the model complexity and fitting error with theoretical guarantees. Without leveraging prior knowledge or assumptions in the discovery process, we use an automated approach to discover ten types of PDEs, including the famous Navier-Stokes and sine-Gordon equations, from simulation data alone. Moreover, we demonstrate our data-driven discovery process with the Complex Ginzburg-Landau Equation (CGLE) using data measured from a traveling-wave convection experiment. Our machine discovery approach presents solutions that has the potential to inspire, support and assist physicists for the establishment of physical laws from measured spatiotemporal data, especially in notorious fields that are often too complex to allow a straightforward establishment of physical law, such as biophysics, fluid dynamics, neuroscience or nonlinear optics. Copyright © 2019, The Authors. All rights reserved.

关键词： Nonlinear optics

Aggregation and resource scheduling in machine-type communication networks: A stochastic geometry approach

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arXiv 2017年

作者： López, Onel L. Alcaraz Alves, Hirley Nardelli, Pedro H.J. Latva-Aho, Matti University of Oulu Finland Laboratory of Control Engineering and Digital Systems Lappeenranta University of Technology Finland

Data aggregation is a promising approach to enable massive machine-type communication (mMTC). This paper focuses on the aggregation phase where a massive number of machine-type devices (MTDs) transmit to aggregators. By using non-orthogonal multiple access (NOMA) principles, we allow several MTDs to share the same orthogonal channel in our proposed hybrid access scheme. We develop an analytical framework based on stochastic geometry to investigate the system performance in terms of average success probability and average number of simultaneously served MTDs, under imperfect successive interference cancellation (SIC) at the aggregators, for two scheduling schemes: random resource scheduling (RRS) and channel-aware resource scheduling (CRS). We identify the power constraints on the MTDs sharing the same channel to attain a fair coexistence with purely orthogonal multiple access (OMA) setups. Then, power control coefficients are found, so that these MTDs perform with similar reliability. We show that under high access demand, the hybrid scheme with CRS outperforms the OMA setup by simultaneously serving more MTDs with reduced power consumption. Copyright © 2017, The Authors. All rights reserved.

关键词： Power control

Why smart appliances may result in a stupid energy grid?

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arXiv 2017年

作者： Nardelli, Pedro H.J. Kühnlenz, Florian Laboratory of Control Engineering and Digital Systems School of Energy Systems Lappeenranta University of Technology Finland University of Oulu Finland

This article discusses unexpected consequences of idealistic conceptions about the modernization of power grids. It focuses on demand-response policies based on automatic decisions by smart home appliances. Following the usual approach, individual appliances sense a universal signal (namely, grid frequency or price) that reflects the system state. Such information is the basis of their decisions. While each device has a negligible impact, their aggregate effect is expect to improve the system efficiency;this is the demand-response goal. The smartness of such an ideal system, composed by isolated appliances with their individual decisions, but connected in the same physical grid, may worsen the system stability. This undesirable outcome comes from the synchronization of the devices' reactions when subject to the same signal. We argue that this is a predictable effect of (implicit) methodological choices. We employ a different approach that understands the electricity system as constituted by physical, informational and regulatory (networked and structured) layers that cannot be reduced to only one or two of them;it needs to be viewed as an organic whole so proper management tools can be designed. Two examples are provided to illustrate the strength of this modeling. Copyright © 2017, The Authors. All rights reserved.

关键词： Domestic appliances

Design of the solar panel frame of the spacecraft by 3D printing with composite materials

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IOP Conference Series: Materials Science and engineering 2020年第1期747卷

作者： M A Mirzaev I G Smirnov A I Dyshekov V E Slavkina M A Shereuzhev S A Aliev Laboratory of innovative structural polymer composite and biocomposite parts of agricultural machinery Federal Scientific Agroengineering Center VIM Moscow 109428 Russia Department of intellectualization automatization and robotic of rural production Federal Scientific Agroengineering Center VIM Moscow 109428 Russia Laboratory of intelligent digital systems of monitoring diagnostics and process control in agricultural production Federal Scientific Agroengineering Center VIM Moscow 109428 Russia Special mechanical engineering Bauman Moscow State Technical University Moscow 105005 Russia Department of road transport Dzhambulatov Dagestan State Agrarian University Moscow 367032 Russia

The optimal design of the skeleton panel of the solar panels of the spacecraft was designed taking into account the increased physical and mechanical characteristics through the use of composite materials and the meth...

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Implementing flexible demand: Real-Time price vs. Market integration

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arXiv 2017年

作者： Kühnlenz, Florian Nardelli, Pedro H. J. Karhinen, Santtu Svento, Rauli University of Oulu Finland Laboratory of Control Engineering and Digital Systems School of Energy Systems Lappeenranta University of Technology Finland Business School at University of Oulu Finland

This paper proposes an agent-based model that combines both spot and balancing electricity markets. From this model, we develop a multi-Agent simulation to study the integration of the consumers' flexibility into the system. Our study identifies the conditions that real-Time prices may lead to higher electricity costs, which in turn contradicts the usual claim that such a pricing scheme reduces cost. We show that such undesirable behavior is in fact systemic. Due to the existing structure of the wholesale market, the predicted demand that is used in the formation of the price is never realized since the flexible users will change their demand according to such established price. As the demand is never correctly predicted, the volume traded through the balancing markets increases, leading to higher overall costs. In this case, the system can sustain, and even benefit from, a small number of flexible users, but this solution can never upscale without increasing the total costs. To avoid this problem, we implement the so-called "exclusive groups". Our results illustrate the importance of rethinking the current practices so that flexibility can be successfully integrated considering scenarios with and without intermittent renewable sources. Copyright © 2017, The Authors. All rights reserved.

关键词： Costs

Compressive phase retrieval via reweighted amplitude flow

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arXiv 2017年

作者： Zhang, Liang Wang, Gang Giannakis, Georgios B. Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

The problem of reconstructing a sparse signal vector from magnitude-only measurements (a.k.a., compressive phase retrieval), emerges naturally in diverse applications, but it is NP-hard in general. Building on recent advances in nonconvex optimization, this paper puts forth a new algorithm that is termed compressive reweighted amplitude flow and abbreviated as CRAF, for compressive phase retrieval. Specifically, CRAF operates in two stages. The first stage seeks a sparse initial guess via a new spectral procedure. In the second stage, CRAF implements a few hard thresholding based iterations using reweighted gradients. When there are sufficient measurements, CRAF provably recovers the underlying signal vector exactly with high probability under suitable conditions. Moreover, its sample complexity coincides with that of the state-of-the-art procedures. Finally, substantial simulated tests showcase remarkable performance of the new spectral initialization, as well as improved exact recovery relative to competing alternatives. Copyright © 2017, The Authors. All rights reserved.

关键词： Iterative methods

Theranostics: Boosting Postsurgical Outcomes of Orthotopic Hepatocellular Carcinoma via an EpCAM-Targeting Theranostic Nanoparticle (Part. Part. Syst. Charact. 8/2019)

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Particle & Particle systems Characterization 2019年第8期36卷

作者： Min Hu Kun Wang Wenting Shang Ziyu Han Hongmei Jiang Chihua Fang Jie Tian Department of Hepatobiliary Surgery Zhujiang Hospital Southern Medical University Guangzhou 510280 China CAS Key Laboratory of Molecular Imaging The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Hepatobiliary Surgery The First Affiliated Hospital of Jinan University Guangzhou 510630 China Institute of Automation University of Chinese Academy of Sciences Beijing 100080 China Guangdong Provincial Clinical and Engineering Technology Research Center of Digital Medicine Guangzhou 510280 China