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Guest Editorial to the Special Issue Public Transport Optimization: From Theory to Practice

Operations Research Forum 2024年第3期5卷 1-4页

作者： Cacchiani, Valentina Müller-Hannemann, Matthias Rojas-Marcos, Federico Perea Department of Electrical Electronic and Information Engineering “Guglielmo Marconi” University of Bologna Viale Risorgimento 2 Bologna 40136 Italy Institute for Computer Science Martin Luther University Halle-Wittenberg Von-Seckendorff-Platz 1 Halle D 06120 Germany Department of Applied Mathematics II and Institute of Mathematics (IMUS) University of Seville Avda. Reina Mercedes s/n Seville 41012 Spain

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Optimization of Metal-Matrix Composites by W-EDM with CNT

Optimization of Metal-Matrix Composites by W-EDM with CNT

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2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Puthilibai, G. Tamilselvi, T. Priya, C. Chinnaraj, P. Balamuralitharan, S. Subhashree, A. Sri Sairam Engineering College Department of Chemistry Tamil Nadu Chennai India Sri Sairam Engineering College Department of Electronics and Instrumentation Engineering Tamil Nadu Chennai India Sri Sairam Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India Psg Institute of Technology and Applied Research Department of Mathematics Tamil Nadu Coimbatore India Tamil Nadu Chennai India

ISBN: (纸本)9798350394580

The EDM procedure is typically used to machining the Al6061 metal matrix composites with silicon carbide (SiC) with carbon nanotube reinforcement (CNT). The Metal Removal Rate (MRR), Surface Roughness (SR) as well as Tool Wear Rate (TWR) of the work piece material could potentially be measured using this method. Fundamental machining characteristics impacting the process's performance includingpulse ON time, discharge current as well as duty cycle were input attributes using Taguchi's parameter formulation. For each possible arrangement, a performance criterion has indeed been computed. The MRR, SR and TWR for every combination were computed in this investigation. The acquired outcomes have been tabulated. The research indicates that by employing grey relational analysis (GRA) to optimise the EDM parameters, improved MRR, TWR, and SR could be attained. MRR, TWR, and SR were 0.301 g/m m3, 0.003 g/mm3, and 4.03 m, respectively, according to the optimum outcomes of this research. © 2023 IEEE.

关键词： Al6061 CNT EDM metal matrix composites Optimization SiC

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Reliability of Deployed Organic Photovoltaic Modules 52

Reliability of Deployed Organic Photovoltaic Modules

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52nd IEEE Photovoltaic Specialist Conference, PVSC 2024

作者： Sheriff, Hafiz K. M. Li, Yongxi Saad, Sammy Forrest, Stephen R. Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Electrical Engineering University of Michigan Ann ArborMI48109 United States Department of Physics University of Michigan Ann ArborMI48109 United States Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States

ISBN: (纸本)9781665464260

The commercial future of organic photovoltaics (OPVs) relies on their efficiency and reliability. Recent progress in the field has ensured the achievement of device efficiency comparable to those of commercial silicon-based photovoltaics (Si-PVs) [1]. In pursuit of reliable devices, recent works have demonstrated the intrinsic stability of both small-molecule, vacuum deposited [2] and non-fullerene acceptor (NFA) - polymer-based devices [3] under controlled laboratory conditions. The final step for outdoor deployment is therefore a demonstration of the reliability of large area OPV modules in the field, subjected to fluctuating environmental conditions such as humidity, temperature, rainfall, snow, and solar intensity. In this work, we develop a customized test facility intended for the study of the reliability of large area OPV modules deployed in outdoor environments. The facility is designed for automated in-situ measurements calibrated to 1 sun solar intensity, AM 1.5 G illumination. Initial data show the modules retain more than 95% of their initial performance for 150 h when exposed to varying solar intensities, temperature fluctuations of -2°C to 10°C, and relative humidity as high as 90%. The only significant extrinsic challenge to device stability observed was the ingress of water into the package. This is mitigated by improved packaging which utilizes polyisobutylene (PIB) encapsulation and a customized insulated glass unit (IGU). © 2024 IEEE.

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Data Analytic for Healthcare Cyber Physical System

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IEEE Transactions on Network Science and engineering 2023年第5期10卷 2490-2502页

作者： Gan, Wensheng Hu, Kaixia Huang, Gengsen Chien, Wei-Che Chao, Han-Chieh Meng, Weizhi Jinan University College of Cyber Security Guangzhou510632 China Pazhou Lab Guangzhou510330 China National Dong Hwa University Department of Computer Science and Information Engineering Hualien97401 Taiwan National Dong Hwa University Department of Electrical Engineering Hualien97401 Taiwan UCSI University Institute of Computer Science and Innovation Kuala Lumpur Malaysia Department of Applied Mathematics and Computer Science Cyber Security Section Lyngby2800 Denmark

Nowadays, a large number of AI-powered healthcare cyber-physical systems (CPSs) have been used in healthcare services. In order to provide better care, AI-powered healthcare CPSs analyze the data they collect using a variety of techniques. Data analysis for artificial intelligence (AI)-driven healthcare CPS is one of these approaches. However, none of the techniques in data analysis can provide a good representation of contiguous and negative information. Therefore, we are the first to introduce the problem of contiguous negative sequential pattern mining. A novel algorithm called Contiguous Negative Sequential Pattern Miner (CNSPM) is proposed to discover and analyze contiguous negative sequential patterns (CNSPs) from the data collected by healthcare CPSs. Finally, we select some real medical and non-medical datasets to conduct numerous experiments. We further analyze the discovered patterns and show how healthcare services can use meaningful patterns for medical decision-making. The performance results on these datasets demonstrate that the proposed algorithm can discover more valuable patterns efficiently and effectively from the collected and transformed medical data. © 2013 IEEE.

关键词： Data mining

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Optimal Actuator Location for Diffusion Equation with Neumann Boundary Control

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IFAC-PapersOnLine 2023年第2期56卷 8165-8170页

作者： Kaijun Yang Kirsten Morris School of Electrical and Control Engineering Shaanxi University of Science and Technology Xi'an 710021 China Department of Applied Mathematics University of Waterloo ON Canada

This paper is concerned with optimal actuator location for a class of diffusion equations with boundary control. The problem of optimal actuator location based on a linear quadratic cost in case of the worst initial condition is formulated. This leads to a cost involving the operator norm of the Riccati operator. The existence of optimal locations within the uniform operator norm is guaranteed. A Galerkin-based algorithm for approximating the optimal locations, and the convergence of the approximation of the optimal locations is also presented.

关键词： Optimal actuator location Riccati operator Unbounded input operator distributed parameter systems partial differential equations infinite-dimensional systems

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Tomography of a Frequency-Bin Qubit

Tomography of a Frequency-Bin Qubit

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Conference on Lasers and Electro-Optics (CLEO)

作者： Richard Oliver Sidarth Raghunathan Hoi Chun Chiu Ali Binai-Motlagh Alexander L. Gaeta Department of Applied Physics and Applied Mathematics Columbia University New York New York USA Department of Electrical Engineering Columbia University New York New York USA

Using Bragg-scattering four-wave mixing, we prepare frequency-bin qubits and measure a purity of 0.92 through a lossy channel, suggesting viability for quantum networks using existing telecommunications infrastructure... 详细信息

ISBN: (纸本)9798350369311

关键词： Four-wave mixing Qubit Measurement by laser beam Tomography Lasers and electrooptics Loss measurement Frequency measurement Telecommunications Quantum networks Electro-optical waveguides

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Multi-Track Music Generation Network Based on a Hybrid Learning Module

Multi-Track Music Generation Network Based on a Hybrid Learn...

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2023 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2023

作者： Zhang, Donghui Hu, Ziqing Li, Xiaobing Tie, Yun Qi, Lin School of Electrical and Information Engineering Zhengzhou University Zhengzhou China University of Notre Dame Department of Applied and Computational Mathematics and Statistics South Bend on Lake MI United States Central Conservatory of Music Department of Music Artificial Intelligence Beijing China

ISBN: (纸本)9798350313154

Generative models has been widely used for symbolic music generation. However, the quality of the music produced is hindered by the inadequate modeling of the harmonic and rhythmic relationships among various instruments, as well as the neglect of musical principles. To address the aforementioned challenges, we propose an attention-based hybrid learning multitrack music generation(HL-MTMG) model that incorporates regularization of musical rules and simultaneous exploitation between intra-track and inter-track information, resulting in the generation of high-quality symbolic music that conforms to established musical principles. Through extensive examinations of musical structures, specifically rhythm, and assessments by domain experts, our study demonstrates that HL-MTMG exhibits significant improvements in musical integrity and fluency in comparison to symbolic music generation models, such as, MuseGAN and HRNN. © 2023 IEEE.

关键词： Music

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Event-triggered Position Scheduling Based Platooning Control Design for Automated Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-10页

作者： Selvaraj, Palanisamy Sakthivel, Ramalingam Kwon, Oh-Min Sakthivel, Rathinasamy School of Electrical Engineering Chungbuk National University Cheongju South Korea Department of Applied Mathematics Bharathiar University Coimbatore India

This paper focuses on the design and implementation of a sampled-data controller for connected autonomous vehicle platoons operating in a predecessor-follower configuration. Due to the cost and reliability concerns associated with velocity and acceleration sensors, this study involves the development of an event-based sampled-data controller that relies solely on position measurements. Considering the limitations of velocity and acceleration sensors, a memory-based sampled-data controller is proposed that utilizes current and preceding position data information to approximate velocity and acceleration. To conserve communication resources, the controller incorporates a dynamic event-driven communication mechanism. In particular, event-driven communication thresholds are adaptively adjusted based on platooning errors between vehicles. This enhances resource utilization while maintaining control performance. In addition, determining the maximum allowable sampling period and event-triggered constraint parameters is crucial for reliable control performance. This is achieved by formulating and solving stability criteria for the closed-loop platoon error system using Lyapunov stability theory and the linear matrix inequality framework. Finally, comprehensive numerical simulations demonstrate the effectiveness of the proposed event-triggered control algorithm under the influence of some key factors, including triggering instants and unknown nonlinearity effects. IEEE

关键词： Controllers

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Video Background Music Recommendation Based on Multi-Level Fusion Features

Video Background Music Recommendation Based on Multi-Level F...

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2023 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2023

作者： Zhao, Xin Li, Xiaobing Tie, Yun Hu, Ziqing Qi, Lin School of Electrical and Information Engineering Zhengzhou University Zhengzhou China Central Conservatory of Music Department of Music Artificial Intelligence Beijing China University of Notre Dame Department of Applied and Computational Mathematics and Statistics South Bend on Lake MI United States

ISBN: (纸本)9798350313154

People resonate more with music when exposed to visual information, and music enhances their perception of video content. Cross-modal recommendation techniques can be used to suggest appropriate background music for a given video. However, there is not a simple correspondence between the different modal data. Therefore, to explore the association between the two modalities of video and music, we propose MFF-VBMR, a video background music recommendation model based on multi-level fusion features. The model uses the cross-modal information of static, dynamic and emotional content of video and music to realize the task of matching and recommending suitable background music for a given video. Experimental results show that the proposed model outperforms other existing models in terms of performance and achieves satisfactory results for video background music recommendation. © 2023 IEEE.

关键词： Convolutional neural networks

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Quantum Wrapper Networking: Investigating the Noise Impact of Classical Headers on the Quantum Payload

Quantum Wrapper Networking: Investigating the Noise Impact o...

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2024 Frontiers in Optics, FiO 2024

作者： Gül, Gamze On, Mehmet Berkay Tan, Shannon G. Proietti, Roberto Kanter, Gregory S. Yoo, S.J. Ben Kumar, Prem Graduate Program in Applied Physics Northwestern University 2145 Sheridan Road EvanstonIL60208 United States Department of Electrical and Computer Engineering University of California Davis DavisCA95616 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States Department of Electronics and Telecommunications Engineering Politecnico di Torino Italy

We study the impact in time and frequency domains of classical headers on quantum payloads in quantum wrapper networking. We identify and characterize in-fiber scattering processes that produce noise photons degrading...

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