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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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Millennials’ social media-driven online entrepreneurship: Assessing their aspirations for multi-level marketing jobs 10

Millennials’ social media-driven online entrepreneurship: A...

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10th International Conference on Industrial and Business engineering, ICIBE 2024

作者： Alhawamdeh, Ahmad Sattam Novendah, Ierenne Prasetyo, Yogi Tri Nadlifatin, Reny Cahigas, Maela Madel L. Department of Industrial Engineering and Management Yuan Ze University Taoyuan Taiwan International Bachelor Program in Engineering Yuan Ze University Taoyuan Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Surabaya Indonesia School of Industrial Engineering and Engineering Management Mapua University Manila Philippines

ISBN: (纸本)9798400710742

With the development of Internet technology and the popularization of mobile devices and so on, e-commerce has entered a period of high-speed development, consumers are faced with a wealth of channel choices, and the competition for traffic in different channels is becoming more and more intense, which poses a great challenge to enterprises. From the perspective of PPM theoretical model to study the consumers’ migration intention of different online channels, using SPSS software and Amos to construct structural equations for the influencing factors of consumers’ migration intention of different online channels, the results show that the push force and pull force positively affect the consumers’ migration intention, and the push force has the greatest influence on the consumers’ migration intention. It provides a basis for the live e-commerce platform to propose measures to enhance user channel stickiness. © 2024 Copyright held by the owner/author(s).

关键词： Consumers Online Consumption Willingness to Migrate by Channel

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Technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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AI for organic and polymer synthesis

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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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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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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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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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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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