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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Di Benedetto, Marco Formentini, Andrea Lidozzi, Alessandro Solero, Luca Marchesoni, Mario Roma Tre University Department of Industrial Electronic and Mechanical Engineering Roma Italy University of Genova Department of Naval Electrical Electronics and Telecommunications Engineering Genova Italy Roma Tre University Department of Civil Computer Science and Aeronautical Technologies Engineering Roma Italy

ISBN: (纸本)9798350376067

This paper presents a Finite Control Set Model Predictive Control (FCS-MPC) algorithm for the three-phase 5-level multiplexed converter (3φ5L MLMXC). The 3φ5L MLMXC comprises two Flying Capacitors (FC) topologies connected to the three-phase NPC topology. The main idea of the proposed control algorithm is to balance the flying capacitors placed in the top and bottom FC converter. The proposed topology is deeply described, and the MPC algorithm for 3φ5L MLMXC has been presented. The SVM algorithm has been implemented in a field-programmable gate array (FPGA). Simulation and Hardware-In-the-Loop results show the usefulness of the presented analysis. © 2024 IEEE.

关键词： Hardware-in-the-loop simulation

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Deep learning-based binary coding for finger-vein image quick search 43

Deep learning-based binary coding for finger-vein image quic...

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43rd Chinese Control Conference, CCC 2024

作者： Zhang, Jianfeng Wu, Haopeng Lu, Zhiying Shandong Normal University Information Science and Engineering Jinan250014 China Civil Aviation University of China Computer Science and Technology Tianjin300300 China Tianjin University Electrical and Information Engineering Tianjin300072 China

ISBN: (纸本)9789887581581

Deep learning has significantly enhanced finger-vein image recognition accuracy, yet retrieval efficiency remains a critical bottleneck, especially in large-scale group scenarios. Existing methods predominantly rely on hand-crafted features and linear projections, limiting retrieval efficacy. Drawing inspiration from the efficacy of binary hash codes, this paper introduces a novel deep learning architecture for finger-vein retrieval. Leveraging supervised training on labeled data, the proposed approach employs a hidden layer to learn compact binary codes, capturing high-level semantics pivotal to class labels. Experimental findings demonstrate superior performance over existing methods across three public datasets. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： deep learning finger-vein hash code quick search

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A meal detection approach based on parity space to detect untreated meals in subjects with Type 1 diabetes∗ 63

A meal detection approach based on parity space to detect un...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Mongini, Paolo Alberto Mazzoleni, Mirko Ferramosca, Antonio Magni, Lalo Toffanin, Chiara University of Pavia Department of Electrical Computer and Biomedical Engineering Pavia27100 Italy University of Bergamo Department of Management Information and Production Engineering Via Marconi 5 Dalmine24044 Italy University of Pavia Department of Civil and Architecture Engineering Pavia27100 Italy

ISBN: (纸本)9798350316339

In this paper a data-driven fault detection technique based on parity space is applied to the problem of detecting unannounced meals for type 1 diabetes patients. This method involves the generation and evaluation of a residual signal to detect faults (unannounced meals) acting on the system (patient). Insulin on Board (IOB), meal intake, glucose and its second derivative have been selected as input signals to generate the residuals, and the parity space matrices are estimated using 8-hour training in silico data generated by the UVA/Padova simulator. The residual evaluation module compares the residual with a threshold that is optimized for each patient using 2-day tuning data. The complete system is evaluated on 1-week scenario obtaining promising results (TPR =9 5 %, PPV=7 2 %) with a detection delay of 4 2 minutes for 8 0 % of patients. For the 20 outlier patients, a fine-tuning and patient-tailored input signal processing are proposed as a future development. © 2024 IEEE.

关键词： Biomedical signal processing

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Experimental investigation of mechanical properties and multi-objective optimization of electronic, glass, and ceramic waste–mixed concrete

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Environmental Science and Pollution Research 2024年第46期31卷 57158-57176页

作者： Mageswari, Deivasigamani Uma Kareemullah, Hakim Jithesh, Korothan Boopathi, Sampath Rachel, Paul Manoharan Premkumar Priya Ramkumar, Mathiyalagan Siva Department of Science and Humanities RMK Engineering College Thiruvallur district Nadu Tamil601206 India Department of Electronics and Instrumentation Engineering B.S.A Crescent Institute of Science and Technology Tamil Nadu Chennai600048 India Department of Computer Science Mahatma Gandhi College Kerala Iritty Kannur670703 India Department of Mechanical Engineering Muthayammal Engineering College Tamilnadu Namakkal637 408 India Department of Civil Engineering Saveetha School of Engineering Thandalam Tamil Nadu Chennai602107 India Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Tamil Nadu Coimbatore641021 India

The utilization of waste from various sources plays an important role in minimizing environmental pollution and civil construction costs. In this research, the mechanical properties of concrete were studied by mixing electronic waste (EW), glass powder (GW), and ceramic tile waste (CW). The effects of weight percentages of EW, GW, and CW are considered to investigate improvements in mechanical properties such as compressive strength (CS), split tensile strength (STS), and flexural strength (FS) of concrete. Taguchi analysis has been applied to predict the optimum composition of waste mixing percentages. The Multi-Objective Optimization Ratio Analysis (MOORA) techniques are applied to estimate the optimum composition of mixing wastes for maximizing the CS, STS, and FS of concrete. It was observed that 10 wt.% of EW, 15 wt.% of GW, and 30 wt.% of CW are predicted as the optimal mixing combinations to obtain a maximum compressive strength of 48.763 MPa, a split tensile strength of 4.178 MPa, and a flexural strength of 7.737 MPa, respectively. Finally, the predicted optimum waste-mixed weight percentages were used to examine the microstructure and various elements in the concrete using SEM and XRD analysis. When compared to conventional concrete, the optimum waste-mixed concrete has improved its compressive strength (38.453%), split tensile strength (41.149%), and flexural strength (36.215%). © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Compressive strength

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Over-height truck collisions with railway bridges:attenuation of damage using crash beams

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Earthquake engineering and engineering Vibration 2022年第1期21卷 237-252页

作者： Dan Xu Xinxing Yuan Ali Irmak Ozdagli Marlon Agüero Roya Nasimi Tao Wang Fernando Moreu Key Laboratory of Earthquake Engineering and Engineering Vibration Institute of Engineering MechanicsChina EarthquakeAdministrationSanhe 065201China Department of Civil Construction and Environmental EngineeringUniversity of New MexicoAlbuquerqueNM 87131USA Courtesy Appointment Department of Electrical and Computer EngineeringUniversity of New MexicoAlbuquerqueNM 87131USA Courtesy Appointment Department of Mechanical EngineeringUniversity of New MexicoAlbuquerqueNM 87131USA

Railway bridges are susceptible to over-height truck collisions and to address this issue,it is necessary to attenuate the effect of these impacts to ensure the safety of transportation *** study experimentally investigates the effectiveness of crash beams as a cushioning mechanism for railway bridges against ***-height truck and railway bridge impact events were simulated in a 1:5 scale *** design parameters such as the stiffness of the crash beam and the bridge supports were scaled to evaluate different levels of *** experiments were conducted with five configurations consisting of four different types of crash beams and one no-crash beam *** results show that crash beams attenuate bridge total peak dynamic displacement responses between 14.5%and 35.7%,depending on the intensity of the impact and crash beam *** addition,the results show that the average effectiveness in attenuating residual deformation for all four crash beams ranges from 43.03%to 83.40%.Finally,various designs and their effectiveness against lateral impacts with different speeds are *** overall scope of this research is to provide objective information about the design of crash beams for railway bridges based on their response to over-height truck collisions at various speeds.

关键词： railway bridge over-height truck impact attenuation crash beam dynamic displacement scaled model

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Leveraging Big Data Analysis in Real-Time Automation for Improved Operational Efficiency 15

Leveraging Big Data Analysis in Real-Time Automation for Imp...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Puthillath, Beena Wasatkar, N.N. Albattah, Mahmoud M.S. Vijayalakshmi, V.J. Manjunath, C. Verma, Lokesh Department of EEE Department of computer engineering Vishwakarma Institute of Technology Pune India Department of Civil Engineering School of Engineering Jordan University Jordan Department of Electrical and Electronics Engineering Karpagam Academy of Higher Education Coimbatore641021 India Bangalore India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350370249

This idea has redefined the practices of an organization and revolutionized business decision-making by harnessing extensive data analysis. With industries becoming increasingly complex and data-dependent, the demand for real-time automation has taken an immense upsurge to enhance operational efficiency. Real-time automation uses massive big data analysis to ensure that the continuous monitoring and analyzing of your crucial data takes place in real time, allowing you to make timely decisions based on facts. It is a type of automation that helps an organization recognize and act on issues or opportunities as soon as they occur in real time, shortening downtime due to potential problems while increasing productivity. Automating data collection, processing, and analysis lets organizations better understand their operations and spot trends, patterns, or even outliers that might not be visible, given how cumbersome the manual processes are. In practice, real-time automation simplifies the process to enhance operational efficiency with cost savings and time efficiencies through automated processes that eliminate manual tasks. It also makes organizations adjust quickly to changes in markets or customer requirements, thus making them agile and more competitive. Utilizing real-time automation with the help of extensive data analysis can boost companies' competitive advantage by increasing their operational efficiency and decision-making capabilities. ©2024 IEEE.

关键词： Efficiency

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Optimal Solution Through Fast Convergence For Transportation Of Shipping Wood in Los Angeles

Optimal Solution Through Fast Convergence For Transportation...

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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Putchal, Chandrasekhar Mahto, Rakeshkumar Patel, Sapankumar Battu, Ramesh Iniguez, Andy California State University Department of Civil and Environmental Engineering FullertonCA United States California State University Department of Electrical and Computer Engineering FullertonCA United States

ISBN: (纸本)9798350327595

In this paper, we introduce an optimization approach for transportation problems that are presented as linear programming problems. Our proposed methods provide an optimal solution with faster convergence, eliminating the requirement for chain reaction or transportation simplex methods. To demonstrate the effectiveness of our developed optimization methods, we provide an illustrative example in this paper. Additionally, our approach can be effortlessly integrated with the supply chain, facilitating the optimization of large-scale problems in the fields of mechanical and industrial engineering. The proposed Putcha Bhuiyan method significantly reduces the repetitive process of chain reactions and iterations, resulting in considerable time savings. The proposed Putcha Bhuiyan method produces a value of 'Z' that is comparable to, and in some cases, even better than, traditional methods. This approach can improve the effectiveness and precision of solving transportation issues, providing valuable insights for professionals and researchers in the industry. This method showcases its potential to enhance the efficiency and accuracy of solving transportation problems, thereby offering valuable insights for researchers and practitioners in the field. © 2023 IEEE.

关键词： Initial Basic Feasible (IBF) solution linear programming Optimization transportation problem

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Graph-based robot optimal path planning with bio-inspired algorithms

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Biomimetic Intelligence & Robotics 2023年第3期3卷 75-90页

作者： Tingjun Lei Timothy Sellers Chaomin Luo Daniel W.Carruth Zhuming Bi Department of Electrical and Computer Engineering Mississippi State UniversityMississippi State 39762USA Center for Advanced Vehicular Systems Mississippi State UniversityMississippi State 39762USA Department of Civil and Mechanical Engineering Purdue University Fort WayneFort Wayne 46805USA

Recently,bio-inspired algorithms have been increasingly explored for autonomous robot path planning on grid-based ***,these approaches endure performance degradation as problem complexity increases,often resulting in lengthy search times to find an optimal *** limitation is particularly critical for real-world applications like autonomous off-road vehicles,where highquality path computation is essential for energy *** address these challenges,this paper proposes a new graph-based optimal path planning approach that leverages a sort of bio-inspired algorithm,improved seagull optimization algorithm(iSOA)for rapid path planning of autonomous robots.A modified Douglas–Peucker(mDP)algorithm is developed to approximate irregular obstacles as polygonal obstacles based on the environment image in rough *** resulting mDPderived graph is then modeled using a Maklink graph *** applying the iSOA approach,the trajectory of an autonomous robot in the workspace is ***,a Bezier-curve-based smoothing approach is developed to generate safer and smoother trajectories while adhering to curvature *** proposed model is validated through simulated experiments undertaken in various real-world settings,and its performance is compared with state-of-the-art *** experimental results demonstrate that the proposed model outperforms existing approaches in terms of time cost and path length.

关键词： Autonomous robot Path planning Bio-inspired algorithm Graph-based model Improved seagull optimization algorithm(iSOA)

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Learning-based adaptive optimal output regulation of linear and nonlinear systems:an overview

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Control Theory and Technology 2022年第1期20卷 1-19页

作者： Weinan Gao Zhong-Ping Jiang Department of Mechanical and Civil Engineering College of Engineering and Science Florida Institute of Technology150 W.University Blvd.MelbourneFL32901USA Department of Electrical and Computer Engineering Tandon School of EngineeringNew York UniversitySix MetroTech CenterBrooklynNY11201USA

This paper reviews recent developments in learning-based adaptive optimal output regulation that aims to solve the problem of adaptive and optimal asymptotic tracking with disturbance *** proposed framework aims to bring together two separate topics—output regulation and adaptive dynamic programming—that have been under extensive investigation due to their broad applications in modern control *** this framework,one can solve optimal output regulation problems of linear,partially linear,nonlinear,and multi-agent systems in a data-driven *** will also review some practical applications based on this framework,such as semi-autonomous vehicles,connected and autonomous vehicles,and nonlinear oscillators.

关键词： Adaptive optimal output regulation Adaptive dynamic programming Reinforcement learning Learning-based control

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ARTIFICIAL INTELLIGENCE-BASED UNCERTAINTY QUALIFICATION OF THE MECHANICAL PROPERTIES OF SUSTAINABLE CONCRETE SPECIMENS 5

ARTIFICIAL INTELLIGENCE-BASED UNCERTAINTY QUALIFICATION OF T...

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5th ECCOMAS Thematic Conference on Uncertainty Quantification in Computational Sciences and engineering, UNCECOMP 2023

作者： Soleymani, Atefeh Jahangir, Hashem Kontoni, Denise-Penelope N. Nasab, Mina Naseri Department of Civil Engineering Shahid Bahonar University of Kerman Kerman Iran Department of Civil Engineering University of Birjand Birjand Iran Department of Civil Engineering School of Engineering University of the Peloponnese PatrasGR-26334 Greece School of Science and Technology Hellenic Open University PatrasGR-26335 Greece Department of Electrical and Computer Engineering University of Birjand Birjand Iran

Concrete, as a regular constructional material, can be considered harmful to the environment as it contains cement as the binder ingredient. Utilizing waste materials as a cement alternative in concrete is an environmentally friendly approach to reduce their harmful effects for as long as the lifetime of the concrete structures. Adding waste materials to such sustainable concrete (SC) would change its mechanical properties, which should be estimated. To achieve this goal, in this paper, an extensive database of self-compacting concrete (SCC) specimens containing various dosages of marble stone powder as waste materials and substitution of cement were prepared, and the mechanical properties, including compressive strength, were estimated by artificial neural networks (ANNs). The outcomes showed that the proposed artificial neural network (ANN) model had high performance and low error values and can be utilized as a robust and accurate method. © 2023 UNCECOMP Proceedings. All rights reserved.

关键词： Self compacting concrete

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