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AI for organic and polymer synthesis

Science China Chemistry 2024年第8期67卷 2461-2496页

作者： Xin Hong Qi Yang Kuangbiao Liao Jianfeng Pei Mao Chen Fanyang Mo Hua Lu Wen-Bin Zhang Haisen Zhou Jiaxiao Chen Lebin Su Shuo-Qing Zhang Siyuan Liu Xu Huang Yi-Zhou Sun Yuxiang Wang Zexi Zhang Zhunzhun Yu Sanzhong Luo Xue-Feng Fu Shu-Li You Center of Chemistry for Frontier Technologies Department of ChemistryZhejiang UniversityHangzhou 310027China Center of Basic Molecular Science Department of ChemistryTsinghua UniversityBeijing 100084China Guangzhou National Laboratory Guangzhou 510005China Center for Quantitative Biology Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular ScienceFudan UniversityShanghai 200433China School of Materials Science and Engineering Peking UniversityBeijing 100871China Beijing National Laboratory for Molecular Sciences Center for Soft Matter Science and EngineeringKey Laboratory of Polymer Chemistry and Physics of Ministry of EducationCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China AI for Science(AI4S)-Preferred Program Shenzhen Graduate SchoolPeking UniversityShenzhen 518055China State Key Laboratory of Chemical Biology Shanghai Institute of Organic ChemistryUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200032China Department of Chemical Sciences National Natural Science Foundation of ChinaBeijing 100085China State Key Laboratory of Organometallic Chemistry Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghai 200032China

Recent years have witnessed the transformative impact from the integration of artificial intelligence with organic and polymer synthesis. This synergy offers innovative and intelligent solutions to a range of classic problems in synthetic chemistry. These exciting advancements include the prediction of molecular property, multi-step retrosynthetic pathway planning, elucidation of the structure-performance relationship of single-step transformation, establishment of the quantitative linkage between polymer structures and their functions, design and optimization of polymerization process, prediction of the structure and sequence of biological macromolecules, as well as automated and intelligent synthesis platforms. Chemists can now explore synthetic chemistry with unprecedented precision and efficiency, creating novel reactions, catalysts, and polymer materials under the datadriven paradigm. Despite these thrilling developments, the field of artificial intelligence(AI) synthetic chemistry is still in its infancy, facing challenges and limitations in terms of data openness, model interpretability, as well as software and hardware support. This review aims to provide an overview of the current progress, key challenges, and future development suggestions in the interdisciplinary field between AI and synthetic chemistry. It is hoped that this overview will offer readers a comprehensive understanding of this emerging field, inspiring and promoting further scientific research and development.

关键词： organic synthesis polymer synthesis machine learning prediction chemical database automated synthesis

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Queue Management Priority-Based Traffic engineering Method 9

Queue Management Priority-Based Traffic Engineering Method

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9th IEEE International Conference on Problems of Infocommunications Science and Technology, PIC S and T 2022

作者： Lemeshko, Oleksandr Yeremenko, Oleksandra Persikov, Anatoliy Yevdokymenko, Maryna Mersni, Amal Harkusha, Serhii Kharkiv National University of Radio Electronics V.V. Popovskyy Department of Infocommunication Engineering Kharkiv Ukraine International University of Sarajevo Department of Engineering Computer Sciences and Engineering Program Sarajevo Bosnia and Herzegovina Poltava University of Economics and Trade Department of Document Studies and Information Activities in Economic Systems Poltava Ukraine

ISBN: (纸本)9798350398915

The work proposes the improvement of queue management priority-based Traffic engineering method. It is based on the interaction prediction principle to coordinate decisions at various levels. The lower level of calculations is responsible, firstly, for the distribution and aggregation of packet flows between the macro queues and sub-queues organized on the router interface (congestion management task), and, secondly, for the balanced distribution of interface bandwidth among sub-queues, weighted relative to their priorities (resource allocation task). The upper level of the method's calculations is accountable for distributing the interface's bandwidth between macro queues by performing the iterative procedure. The numerical research results of the proposed two-level queue management method confirmed its effectiveness in ensuring high scalability, balanced priority- based distribution of packet flows and interface bandwidth between the macro queues and sub-queues organized on it. The method demonstrated high coordination procedure convergence and the final quality of centralized calculations. © 2022 IEEE.

关键词： Bandwidth

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Optimized Task Assignment and Predictive Maintenance for Industrial Machines using Markov Decision Process

arXiv

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arXiv 2024年

作者： Nasir, Ali Mekid, Samir Sawlan, Zaid Alsawafy, Omar Control and Instrumentation Engineering Department KFUPM Dhahran Saudi Arabia Mechanical Engineering Department KFUPM Dhahran Saudi Arabia Mathematics Department KFUPM Dhahran Saudi Arabia Systems Engineering Department Dhahran Saudi Arabia Interdisciplinary Research Center for Intelligent Manufacturing and Robotics KFUPM Dhahran Saudi Arabia

This paper considers a distributed decision-making approach for manufacturing task assignment and condition-based machine health maintenance. Our approach considers information sharing between the task assignment and health management decision-making agents. We propose the design of the decision-making agents based on Markov decision processes. The key advantage of using a Markov decision process-based approach is the incorporation of uncertainty involved in the decision-making process. The paper provides detailed mathematical models along with the associated practical execution strategy. In order to demonstrate the effectiveness and practical applicability of our proposed approach, we have included a detailed numerical case study that is based on open source milling machine tool degradation data. Our case study indicates that the proposed approach offers flexibility in terms of the selection of cost parameters and it allows for offline computation and analysis of the decision-making policy. These features create and opportunity for the future work on learning of the cost parameters associated with our proposed model using artificial intelligence. © 2024, CC BY.

关键词： Optimization

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A Novel Hydroponic Based on Hybrid Renewable Energy System

A Novel Hydroponic Based on Hybrid Renewable Energy System

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International Symposium on Advanced Electrical and Communication Technologies (ISAECT)

作者： Abeer Ahmed Muhammad Khalid Electrical Engineering Department King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Electrical Engineering Department Interdisciplinary Research Center for Sustainable Energy Systems King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

ISBN: (数字)9798331529987

ISBN: (纸本)9798331529994

Hydroponic farming, a soilless technique, has become increasingly popular and is considered the future of agriculture in water-deficient areas like Saudi Arabia. These regions tackle the challenge of cultivating fruits and vegetables with an automated hydroponic system. This system uses ozone filtration, is self-installed, and includes PV, DG, battery, converter, and AI for independent functioning. It employs ozonic methods to cleanse and filter water, eliminating the need for human intervention, and offers customizable options to accommodate various locations. The proposed hydroponic system will use sensors as input and output devices, run on a hybrid renewable energy system (HRES), and integrate water pumps, dosing pumps, and lighting sources. By integrating solar panels, batteries, converters, and a diesel generator (DG), the goal is to decrease CO 2 emissions, water, and power usage, and utilize AI for disease detection. This cutting-edge system tackles multiple challenges in hydroponic agriculture, such as sporadic solar energy, efficient energy storage, converter performance, and diesel generator emissions, aiming to reduce energy wastage and emissions while maintaining dependable operation. The proposed design method assesses the energy needs for growing hydroponic lettuce, cutting down on water and energy usage by decreasing the water pump’s running time to only 4 hours instead of 24 hours. This results in a 40% reduction in energy and cost savings with the ideal sizes of PV, battery, DG, and converter. The system, utilizing HOMER and GAMS software, presents cost and energy savings and operational expense reductions, offering advantages for business owners, agricultural enthusiasts, and individuals looking into agricultural investments. This system could boost local investment in agriculture and technology sectors, in line with Saudi Vision 2030.

关键词： Temperature sensors Renewable energy sources Costs Hydroponics Agriculture Sensor systems Generators Batteries Sensors Investment

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Multi-Objective Grey Wolf Optimizer for the Tuning Process of the FOPID Controller

Multi-Objective Grey Wolf Optimizer for the Tuning Process o...

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Allan Christian Krainski Ferrari Gideon Villar Leandro Leandro Dos Santos Coelho Gilberto Reynoso Meza Eletrical Engineering Department Federal University of Paraná UFPR Curitiba Brazil Electrical Engineering Graduate Program (PPGEE) Federal University of Paraná (UFPR) Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR) Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná Curitiba Brazil

This article implements the multi-objective grey wolf optimizer (MOGWO) in the tuning process of the gains of the Fractional-Order Proportional-Integral-Derivative (FOPID) controller applied in the control of a boiler system. For a sequence of 100 runs, this application had compared and analyzed with other implementation that uses MOGWO to optimize the gains of the classical Proportional-Integral-Derivative (PID) controller. In the computational simulation, the value hypervolume metric had used to analyze the performance of the controllers. In the results, the implementation of the FOPID showed superior to PID, where the comparison had validated by a hypothesis test. Despite the higher computational cost concerning the tuning process of the PID controller, this study proved that the FOPID controller can be advantageous for industrial applications.

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Balancing Trade-Offs in Condition-Based Maintenance with a Discrete-Time Markov Chain Model 50

Balancing Trade-Offs in Condition-Based Maintenance with a D...

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50th International Conference on Computers and Industrial engineering: Sustainable Digital Transformation, CIE 2023

作者： Hanbalia, Ahmad Al Department Industrial and Systems Engineering King Fahd University of Petroleum and Minerals Eastern Province Dhahran31261 Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics King Fahd University of Petroleum and Minerals Eastern Province Dhahran31261 Saudi Arabia

ISBN: (纸本)9781713886952

This paper proposes a novel condition-based maintenance (CBM) model based on a discrete-time Markov chain. The model considers the system's degradation evolution over time and optimizes the preventive maintenance threshold and the time between inspections by minimizing the annual maintenance cost subject to a lower limit on the system's availability. The proposed approach considers various cost factors such as inspection costs, preventive maintenance costs, corrective maintenance costs, and downtime costs. The interior-point optimization method is used for the constrained nonlinear model. The model is applied to a case study from the process industry, and a cost and variability sensitivity analysis is performed. According to the findings, the proposed model effectively balances the trade-off between maintenance costs and system availability. In addition, the sensitivity analysis highlights the importance of accurate cost estimation and the role of key variables like inspection frequency and preventive maintenance threshold in determining the optimal maintenance policy. © 2023 Computers and Industrial engineering. All rights reserved.

关键词： Sensitivity analysis

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Multiband Patch Antenna Design Using Nature-Inspired Optimization Method

IEEE Open Journal of Antennas and Propagation

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IEEE Open Journal of Antennas and Propagation 2021年 2卷 151-162页

作者： Boursianis, Achilles D. Papadopoulou, Maria S. Pierezan, Juliano Mariani, Viviana C. Coelho, Leandro S. Sarigiannidis, Panagiotis Koulouridis, Stavros Goudos, Sotirios K. ELEDIA@AUTH Research Group School of Physics Aristotle University of Thessaloniki Thessaloniki54124 Greece Department of Electrical Engineering Federal University of Parana Curitiba80060-000 Brazil Industrial and Systems Engineering Graduate Program and Mechanical Engineering Graduate Program Pontifical Catholic University of Parana Curitiba80215-901 Brazil Department of Electrical and Computer Engineering University of Western Macedonia Kozani501 00 Greece Electrical and Computer Engineering Department University of Patras Patras26504 Greece

Radio frequency energy harvesting has attracted considerable interest as a technique of enabling self-powered wireless networks. This technique faces several challenges, such as the receiving and the rectifying modules of a rectenna system. Multiband antennas provide several comparative advantages against the goal of maximizing the amount of energy harvesting. In this work, we present a multiband microstrip patch antenna with three slits operating in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. A feasible solution of the antenna is obtained by the application of a recently introduced nature-inspired optimization technique, namely the Coyote Optimization Algorithm. The proposed antenna operates satisfactorily in the LoRaWAN (Long Range Wide Area Network) and the cellular (GSM-1800 and UMTS) communication frequency bands. Measured results of the proposed antenna exhibit an acceptable performance (multiband frequency operation, maximum gain of 3.94 dBi, broadside operation) and demonstrate features of operation, which make it a strong candidate for various RF energy harvesting applications. © 2020 IEEE.

关键词： Microstrip antennas

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Autonomous Navigation of a Mobile Robot on Robot Operating System Using Graphical User Interface

Autonomous Navigation of a Mobile Robot on Robot Operating S...

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International Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Henok Tegegn Warku Nak Yong Ko Gyeongsub Song Da Bin Jeong Boeun Lee Tegen Eyasu Derbew Suk-Seung Hwang Department of Electronic Engineering Interdisciplinary Program in IT-Bio Convergence Systems Chosun University Gwangju South Korea Department of Control and Instrumentation Engineering Chosun University Gwangju South Korea

Many applications of mobile robotics necessitate the safe execution of a collision-free motion to a defined place. Real-time obstacle avoidance strategies enable reactive motion in dynamic and unpredictable situations, whereas planning approaches are best suited for achieving a goal position in known static environments. A ROS-based approach is presented to address the challenge of robot SLAM, which has been used in real-time applications to map the environment, localize the robot within the environment, plan paths, and avoid obstacles. It is demonstrated that all navigation modules can coexist and work together to reach the destination without colliding with static and dynamic obstacles. This paper provides a platform for guiding a mobile robot in a real-world environment autonomously for different waypoints while avoiding static and dynamic obstacles using the Graphical User Interface (GUI). The developed GUI-based navigation simplifies the complex ROS navigation system control to an easy user-friendly interface so that anyone can control the mobile robot platform. Our results were validated at Chosun University in South Korea, through the experimental test in an indoor environment.

关键词： Location awareness Simultaneous localization and mapping Navigation Operating systems Real-time systems Path planning Mobile robots

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On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

引用

IEEE Transactions on Services Computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, Social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized Social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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Fault Tolerant Dynamic Task Assignment for UAV-based Search Teams

arXiv

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arXiv 2024年

作者： Nasir, Ali AlDurgam, Mohammad Interdisciplinary Research Center for Intelligent Manufacturing and Robotics KFUPM Dhahran Saudi Arabia Control and Instrumentation Engineering Department KFUPM Dhahran Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics KFUPM Dhahran Saudi Arabia Industrial and Systems Engineering Department KFUPM Dhahran Saudi Arabia

This research offers a novel framework for dynamic task assignment for unmanned aerial vehicles (UAVs) in cooperative search settings. Notably, it incorporates post-fault UAV capabilities into job assignment techniques, assuring operational dependability in the event of sensor and actuator failures. A significant innovation is the utilization of UAV battery charge to assess range relative to search objectives, hence improving job distribution while conserving battery life. This model integrates repair, recharge, and stochastic goal recurrence, hence increasing its real-world applicability. Using stochastic dynamic programming, this method makes it simpler to determine optimal assignment policies offline so they may be implemented rapidly online. This paper emphasizes the holistic aspect of the proposed model, which connects high-level task rules to low-level control capabilities. A simulation-based case study proves its usefulness, highlighting its robustness in fault-prone and battery-variable settings. Overall, this paper proposes and demonstrates a comprehensive method for assigning UAV tasks that integrates defect awareness, battery management, and multilayer control through the use of stochastic dynamic programming. © 2024, CC BY.

关键词： Stochastic systems

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