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Communication Compression for Distributed Nonconvex Optimization

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arXiv 2022年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Chai, Tianyou Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Digital Futures Stockholm100 44 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

This paper considers distributed nonconvex optimization with the cost functions being distributed over agents. Noting that information compression is a key tool to reduce the heavy communication load for distributed algorithms as agents iteratively communicate with neighbors, we propose three distributed primal–dual algorithms with compressed communication. The first two algorithms are applicable to a general class of compressors with bounded relative compression error and the third algorithm is suitable for two general classes of compressors with bounded absolute compression error. We show that the proposed distributed algorithms with compressed communication have comparable convergence properties as state-of-the-art algorithms with exact communication. Specifically, we show that they can find first-order stationary points with sublinear convergence rate O(1/T) when each local cost function is smooth, where T is the total number of iterations, and find global optima with linear convergence rate under an additional condition that the global cost function satisfies the Polyak–Lojasiewicz condition. Numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2022, The Authors. All rights reserved.

关键词： Iterative methods

The Level of Digital and Communication Competencies of Students at Faculties of Civil engineering in the Distance Learning Form 18

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The Level of Digital and Communication Competencies of Stude...

18th IEEE International Conference on Emerging eLearning Technologies and Applications, ICETA 2020

作者： Mesaros, P. Kanalikova, A. Behunova, A. Mandicak, T. Spisakova, M. Faculty of Civil Engineering Department of Economics Management and Information Systems in Construction Kosice Slovakia Faculty of Civil Engineering Department of Applied Mathematics and Descriptive Geometry Kosice Slovakia Faculty of Mining Ecology Process Control and Geotechnologies Institute of Earth Resources Kosice Slovakia Faculty of Civil Engineering Department of Technologies and Innovations in Construction Kosice Slovakia

ISBN: (纸本)9780738123660

For education, 2020 became the year of distance learning and online communication in the teacher-student relationship, but also in the student-student relationship. This teaching system brings many challenges for both parties and the need to improve the communication and digital competencies of all involved. It also requires increased demands on the hardware and software provision of teaching on both sides of the teaching process. This article focuses on the issue and description of communication and digital skills needed for distance learning. The main goal of the research is to compare and map the communication and digital ICT competencies of faculty students with a construction focus during full-time and distance learning. The results of the research are analyzed in the article using methods of descriptive as well as analytical statistics. © 2020 IEEE.

关键词： Students

Lithium Extraction from High Magnesium Salt Lake Brine with an Integrated Membrane Technology

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SSRN

SSRN 2022年

作者： Ashraf, Muhammad Awais Usman, Muhammad Hussain, Iftikhar Ahmad, Faraz Guo, Shiwei Zhang, Lu State Key Laboratory of Multiphase Complex Systems CAS Key Laboratory of Green Process and Engineering Institute of Process Engineering Chinese Academy of Sciences Beijing100190 PR China University of Chinese Academy of Sciences Beijing100049 China Washington State University United States Department of Mechanical Engineering City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong Key Laboratory of Coal Science and Technology Taiyuan University of Technology Taiyuan030024 China North China Electric Power University Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control Department of Environmental Science and Engineering Baoding071000 China Faculty of Economics and Business

Lithium extraction is a great challenge from the high magnesium content salt solution. In this work, an integrated polyamide tight ultrafiltration (UF) and nanofiltration (NF) membranes are systematically investigated to separate Li+ from a high magnesium salt solution. Tight ultrafiltration UA001 and nanofiltration NF270 membranes in the integrated-cascade system not only increased Li+ permeation to 82.5% but also enhanced the high Mg2+ retention to 94.6% from the ternary salt solution of LiCl and MgCl2. The transport model was also developed to calculate the real retention of Li+ and Mg2+, under constant pressure mode. The separation efficiency SFLi/Mg for the ternary salt solution of LiCl+MgCl2+H2O was more than 15 at a constant pressure of 25 bars with an integrated membrane process, which was higher as compared to single-stage UF and NF270 membranes. Moreover, the high Mg2+/Li+ ratio was also reduced from 30 to 1.9 in the integrated-cascade membrane process. © 2022, The Authors. All rights reserved.

关键词： Magnesium compounds

Pre-treatment optimization to reduce membrane fouling during produced water treatment with an integrated FO-MD system

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Science Talks 2025年 14卷

作者： Muhammad Saqib Nawaz Sofiane Soukane Muhammad Bilal Asif Veerabhadraiah Gudideni Sultan Alrubaish Noreddine Ghaffour Environmental Sciences and Engineering Program Division of Biological and Environmental Sciences and Engineering (BESE) King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Physical Sciences and Engineering Division (PSE) King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Energy Systems Division Process & Control Systems Department Saudi Aramco Dhahran Saudi Arabia

During oil exploration, fresh water that is injected into underground reservoirs returns to the surface loaded with hydrocarbons, salts, and other contaminants. This complex solution is typically known as produced water (PW). Generally, different PW streams are generated at a given site, which, after suitable treatment, are sent for re-injection for enhanced oil recovery or to disposal wells. However, there is a potential for water recovery from this hypersaline contaminated stream. Forward osmosis (FO) and membrane distillation (MD) are two low-pressure membrane treatment technologies successfully used in a single hybrid system for PW treatment. During operation, the key foulants on the FO membrane were CaSiO 3 , CaSO 4 , and NaCl, while for MD, they were SiO 2 and CaSO 4 plus emulsified oil, causing pore clogging. Some foulants were tightly bound and not removed by osmotic backwashing or hydraulic flushing, thus requiring pre-treatment. Different pre-treatment techniques, like ion exchange resins and polymeric and ceramic membrane-based ultrafiltration (UF), were assessed in this study. The resins were able to remove bivalent metallic ions successfully from lower concentration streams only and thus caused an increase in FO flux and a reduction in MD flux by disturbing the FO-MD system equilibrium. The higher concentrations of resins and chemicals required for their regeneration make them unsuitable for such applications. On the contrary, PW pre-treated with polymeric and ceramic UF membranes led to increased FO and MD fluxes without any chemical requirement and proved suitable for pre-treatment.

关键词： Pre-treatment Produced water Ion-exchange resins Ultrafiltration Forward osmosis Membrane distillation

Zeroth-order algorithms for stochastic distributed nonconvex optimization

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arXiv 2021年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem has various machine learning applications. As a solution, we propose two distributed ZO algorithms, in which at each iteration each agent samples the local stochastic ZO oracle at two points with a time-varying smoothing parameter. We show that the proposed algorithms achieve the linear speedup convergence rate O(√p=(nT)) for smooth cost functions under the state-dependent variance assumptions which are more general than the commonly used bounded variance and Lipschitz assumptions, and O(p=(nT)) convergence rate when the global cost function additionally satisfies the Polyak-Lojasiewicz (P-L) condition in addition, where p and T are the dimension of the decision variable and the total number of iterations, respectively. To the best of our knowledge, this is the first linear speedup result for distributed ZO algorithms, which enables systematic processing performance improvements by adding more agents. We also show that the proposed algorithms converge linearly under the relative bounded second moment assumptions and the P-L condition. We demonstrate through numerical experiments the efficiency of our algorithms on generating adversarial examples from deep neural networks in comparison with baseline and recently proposed centralized and distributed ZO algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost functions

Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization

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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Digital Futures Stockholm10044 Sweden The Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions. At each round, each agent selects a decision from the decision set, and then only a portion of the loss function and a coordinate block of the constraint function at this round are privately revealed to this agent. The goal of the network is to minimize the network-wide loss accumulated over time. Two distributed online algorithms with full-information and bandit feedback are proposed. Both dynamic and static network regret bounds are analyzed for the proposed algorithms, and network cumulative constraint violation is used to measure constraint violation, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. In particular, we show that the proposed algorithms achieve O(T max{κ,1-κ}) static network regret and O(T 1-κ/2) network cumulative constraint violation, where T is the time horizon and κ ∈ (0, 1) is a user-defined trade-off parameter. Moreover, if the loss functions are strongly convex, then the static network regret bound can be reduced to O(T κ). Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Economic and social effects

ALBATROSS Carbon neutrality and zero-emission vehicles with smart battery cells

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Transportation Research Procedia 2023年 72卷 2377-2384页

作者： Beatriz Correia Pedro Catarino Bjorn van de Ven Liat Gantman Anders Vestin David Britton Margit Harting Matthew Jennison Merve Öztürk İrem Sapmaz Eda Demir Josh Eichman Maite Etxandi Santolaya Tomas Montes Ahsan Habib M. Azizur Rahman Sulalit Bandyopadhyay Jahn Axel Jon Gowdy Mohsen Moslemin Koupaie Iosu Cendoya EWF Lisbon Portugal INND BATTERIES BV Netherland ALGOLION LTD REHOVOT Israel ZEMISSION AB LUND Sweden PST SENSORS EUROPE LTD United Kingdom YESILOVA HOLDING AS BURSA TURKEY FUNDACIO INSTITUT DE RECERCA DE L'ENERGIA DE CATALUNYA Spain TECHNOVATIVE SOLUTIONS LTD MANCHESTER United Kingdom NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU TRONDHEIM Norway FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V. MUNCHEN Germany CENTRE FOR PROCESS INNOVATION LIMITED LBG United Kingdom THE UNIVERSITY OF NOTTINGHAM University Park NOTTINGHAM United Kingdom The Control Systems Group Electrical Engineering Department of the Eindhoven University of Technology

ALBATROSS is a European Funded project by the European Commission that addresses the needs of European Electric and Hybrid-Electric passenger vehicle market by overcoming driver concerns relating to battery range and anxiety, cost, long-term reliability, and excessive charging times. ALBATROSS will develop an integrated approach based on smart batteries combined with lightweight designs. Using innovative cooling technologies, we will achieve pack temperature range 5-40°C, with <3°C variation between battery cells and optimal operating temperature 20-23°C. The light weighting solutions, based on modular multi-material systems for battery modules and trays, will be fabricated and joined using cutting edge, fast and cost-effective processes, with disassembly, recycling and reuse designed in as a part of an eco-design approach. The modular approach provides solutions for BEVs and PHEVs.

关键词： Electric Propulsion Electric Vehicle Smart Batteries Temperature control Battery Management systems

Holographic cosmology with two coupled fluids in the presence of viscosity

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arXiv 2021年

作者： Brevik, I. Timoshkin, A.V. Department of Energy and Process Engineering Norwegian University of Science and Technology TrondheimN-7491 Norway Tomsk State Pedagogical University Kievskaja Street 60 Tomsk634061 Russia International Laboratory of Theoretical Cosmology and Tomsk State University of Control Systems and Radio Electronics Lenin Avenue 36 Tomsk634050 Russia

We explore the cosmological models of the late-time universe based on the holographic principle, taking into account the properties of the viscosity of the dark fluid. We use the mathematical formalism of generalized infrared cutoff holographic dark energy, as presented by Nojiri and Odintsov (2017). We consider the Little Rip, the Pseudo Rip, and a bounce exponential model, with two interacting fluids, namely dark energy and dark matter in a spatially-flat Friedmann-Robertson-Walker universe. Within these models, analytical expressions are obtained for infrared cutoffs in terms of the particle horizons. The law of conservation of energy is presented, from a holographic point of view. © 2021, CC BY.

关键词： Holography

Regret and cumulative constraint violation analysis for online convex optimization with long term constraints

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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Institute for Advanced Study Tongji University Shanghai China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

This paper considers online convex optimization with long term constraints, where constraints can be violated in intermediate rounds, but need to be satisfied in the long run. The cumulative constraint violation is used as the metric to measure constraint violations, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. A novel algorithm is first proposed and it achieves an O(Tmax{c,1-c}) bound for static regret and an O(T (1-c)/2) bound for cumulative constraint violation, where c ϵ (0, 1) is a user-defined trade-off parameter, and thus has improved performance compared with existing results. Both static regret and cumulative constraint violation bounds are reduced to O(log(T )) when the loss functions are strongly convex, which also improves existing results. In order to achieve the optimal regret with respect to any comparator sequence, another algorithm is then proposed and it achieves the optimal O( p T (1 + PT )) regret and an O(√T) cumulative constraint violation, where PT is the path-length of the comparator sequence. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Comparators (optical)