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4th International Symposium on Advances and Innovation in Mechanical engineering, ISAIME 2023

作者： Komara, Asep Indra Setiawan, Rachman Budiwantoro, Bagus Doctoral Program of Mechanical Engineering Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia Manufacturing Design Engineering Department Politeknik Manufaktur Bandung Bandung Indonesia

The application of passive safety technology in vehicles is generally through impact-absorbing structures. This technology has been widely applied to trains, planes, and cars to protect passengers from fatal accidents. Cellular structures are defined by a unit cell that combines material, space, and unit cell repetition to obtain a large structure. It is selected as the base structure of the impact energy absorber for its potentially high specific energy absorption (SEA]. Such a structure poses a challenge in its manufacturing method. This study examines alternative manufacturing processes for cellular structures designed as impact absorbers, and then selects and develops an effective and efficient manufacturing method to produce these cellular structures. Several alternative manufacturing methods were chosen to exercise the use of a combined plaster molding technology and additive manufacturing for prototyping. Manufacturing process simulation studies were conducted using Altair Inspire Cast software to determine the success of the casting process. The final stage is to carry out the process of making cell structures and evaluating the results. This work results in an effective manufacturing process design to be implemented throughout the production stage. Furthermore, for mass production, mold patterns may be replaced by using injection molding. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Injection molding

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Enhanced Multiple Sound Event Detection and Classification Using Physical Signal Properties in Recurrent Spiking Neural Networks

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IEEE Access 2025年 13卷 81312-81325页

作者： Roozbehi, Zahra Narayanan, Ajit Mohaghegh, Mahsa Saeedinia, Samaneh-Alsadat Auckland University of Technology School of Electrical and Computer Engineering Auckland New Zealand Auckland University of Technology Faculty of Design and Creative Technologies Auckland New Zealand Iran University of Science and Technology Department of Electrical and Computer Engineering Tehran Iran

Sound event detection and classification present significant challenges, particularly in noisy environments with multiple overlapping sources. This paper introduces an innovative architecture for multiple sound event detection and classification utilizing recurrent spiking neural networks (SNNs). Our method uniquely leverages temporal data to detect and classify multiple sound sources simultaneously, integrating the physical concept of signal power matching with neuronal output power and employing a binaural strategy to enhance detection accuracy in real-world scenarios. The architecture processes spatiotemporal data to dynamically update synaptic weights, enabling precise identification of sound event categories and their occurrences. Our simulations reveal substantial performance improvements, achieving the highest precision of 73% in classification tasks, including multilayer perceptrons (MLP), convolutional recurrent neural networks (CRNN), and recurrent neural networks (RNN). Statistical analysis indicates that these improvements are significant (p-value © 2013 IEEE.

关键词： Recurrent neural networks

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Active Disturbance Rejection-Based Model Predictive Control to Improve Power Quality with Reduced Current Sensors in EV Charging Stations 16

Active Disturbance Rejection-Based Model Predictive Control ...

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16th Annual Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2025

作者： Mousavi, Mahdi S. Davari, S. Alireza Rahmani, Majid Nikmaram, Behnam Aly, Mokhtar Flores-Bahamonde, Freddy Rodriguez, Jose Shahid Rajaee Teacher Training University Department of Electrical Engineering Tehran Iran Universidad San Sebastian Faculty of Engineering Architecture and Design Santiago Chile Universidad Andres Bello Energy Transformation Center Engineering Faculty Santiago Chile

ISBN: (纸本)9798331533946

This paper proposes an active disturbance rejection (ADR)-based model predictive control (MPC) strategy to enhance power quality in electric vehicle charging stations (EVCS) with a reduced number of current sensors. The presented approach compensates for local load current harmonics and reactive power without the need for harmonic extraction, simplifying the control structure. By relying on current measurements only at the grid side, the method eliminates the need for additional sensors in the load or converter of the EVCS. Load current dynamics are considered as disturbance terms, then are rejected using the ADR technique. The proposed converter system simultaneously improves the grid's power quality and fulfills its primary function of charging EVs. Simulation results validate the effectiveness of the approach, demonstrating enhanced power quality performance and robust disturbance rejection. © 2025 IEEE.

关键词： Charging stations

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Finite-Set Ultralocal Model Predictive Current Control with Integral Sliding Mode Observer for Quadratic Buck Converters of Data Centers 16

Finite-Set Ultralocal Model Predictive Current Control with ...

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16th Annual Power Electronics, Drive Systems, and Technologies Conference, PEDSTC 2025

作者： Rahmani, Majid Alireza Davari, S. Mousavi, Mahdi S. Zolfagharian, Reza Flores-Bahamonde, Freddy Rodriguez, Jose Shahid Rajaee Teacher Training University Department of Electrical Engineering Tehran Iran Universidad Andres Bello Energy Transformation Center Engineering Faculty Santiago Chile Universidad San Sebastian Faculty of Engineering Architecture and Design Santiago Chile

ISBN: (纸本)9798331533946

Data centers demand efficient and reliable power converters to handle their increasing energy requirements while maintaining operational stability. This paper introduces a novel control strategy for quadratic buck converters (QBCs), to improve performance in data center power systems. The proposed method applies an integral sliding mode observer (ISMO) to the finite-set ultralocal model predictive current control (FSUMPCC). The ISMO estimates unmeasured states and external disturbances, ensuring robust performance against parameter variations and external perturbations. Since neither the ultralocal model nor the ISMO, do not utilizes the system's parameters, the proposed FS-UMPCC achieves high control precision in the presence of severe parameter mismatch. The proposed method also enhances system reliability by reducing sensitivity to model inaccuracies and external disturbances. The simulation validation demonstrates the effectiveness of the proposed approach. Results show significant control accuracy compared to the conventional finite control set model predictive control (FCS-MPC) strategy. © 2025 IEEE.

关键词： Buck converter

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From 5G to 6G: The Role of AI, Machine Learning, and Deep Learning in Wireless Systems 4

From 5G to 6G: The Role of AI, Machine Learning, and Deep Le...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Gote, Pradnyawant M. Kumar, Praveen Verma, Prateek Yesankar, Prajyot Pawar, Adesh Saratkar, Saniya Faculty of Engineering and Technology Department of Computer Science & Design Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence & Data Science Maharashtra Wardha442001 India

ISBN: (纸本)9798331523923

The swift progression of wireless communication technologies-specifically from 5G to 6G is an approach that could be the most significant revolutionary leap towards changing connectivity and data transmission forever. Additionally, algorithms of machine learning (ML) and deep learning (DL) in 5G and 6G can offer promising advancements toward predictive maintenance, dynamic spectrum management, and enhanced security. The review of the potentially transformative nature of these technologies underlines the need for future directions of research efforts called for in circumventing challenges towards making full capability exploitation of 6G possible. © 2025 IEEE.

关键词： Adversarial machine learning

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Mechanical properties estimation of multi-layer friction stir plug welded aluminium plates using time-series neural network models

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Soft Computing 2025年第2期29卷 1147-1168页

作者： Qazani, Mohammad Reza Chalak Sajed, Moosa Pedrammehr, Siamak Seyedkashi, Seyed Mohammad Hossein Sohar University Sohar311 Oman Mechanical Engineering Department Azarbaijan Shahid Madani University Tabriz Iran Faculty of Design Tabriz Islamic Art University Tabriz Iran Mechanical Engineering Department University of Birjand Birjand97175-376 Iran

A multi-layer friction stir plug welding can be used to fix the thick aluminium plates. Optical microscopy and tensile tests are utilized to study the microstructural and mechanical characteristics of the welded aluminium plates. However, finding the relation between the indexes of the process and the mechanical properties would be challenging. The present work aims to devise a time-series machine learning model including a recurrent neural network (RNN) and nonlinear autoregressive network with the external state (NARX) to estimate the mechanical properties of the repaired aluminium plate using the force-extension plot. The ultimate tensile strength, yield strength, impact energy and elongation of the repaired aluminium plate can be calculated based on a force-extension plot trained and extracted using the developed networks. In addition, the Bayesian technique is employed to recalculate the optimal hyperparameters of RNN and NARX, targeting the lowest root mean square error (RMSE) between the target and the estimated force during the testing. The investigated methods (RNN and NARX) with the addition of classical estimation methods, including decision tree and support vector regression, are modelled in MATLAB, and the outcomes prove the proposed NARX model efficiency in terms of lower RMSE in comparison with support vector regression, decision tree and RNN. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Tensile testing

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High-thermal free vibration analysis of functionally graded microplates using a new finite element formulation based on TSDT and MSCT

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Defence Technology(防务技术) 2025年第2期44卷 131-149页

作者： Huu Trong Dang Nhan Thinh Hoang Quoc Hoa Pham Trung Thanh Tran Huy Gia Luong Faculty of Mechanical Engineering Technology Vinh Long University of Technology EducationVinh Long 91000Viet Nam Institute for Creative Design and Business Nguyen Tat Thanh UniversityHo Chi Minh City 70000Viet Nam Faculty of Engineering and Technology Nguyen Tat Thanh UniversityHo Chi Minh City 70000Viet Nam Faculty of Mechanical Engineering Le Quy Don Technical UniversityHanoi 10000Viet Nam TechnoStar Vietnam TechnoStar Co.LtdHo Chi Minh City 70000Viet Nam

Recent advancements in additive manufacturing(AM)have revolutionized the design and production of complex engineering *** these advancements,their mathematical modeling and computational analysis remain significant *** research aims to develop an effective computational method for analyzing the free vibration of functionally graded(FG)microplates under high temperatures while resting on a Pasternak foundation(PF).This formulation leverages a new thirdorder shear deformation theory(new TSDT)for improved accuracy without requiring shear correction ***,the modified couple stress theory(MCST)is incorporated to account for sizedependent effects in *** PF is characterized by two parameters including spring stiffness(k_(w))and shear layer stiffness(k_(s)).To validate the proposed method,the results obtained are compared with those of the existing ***,numerical examples explore the influence of various factors on the high-temperature free vibration of FG *** factors include the length scale parameter(l),geometric dimensions,material properties,and the presence of the elastic *** findings significantly enhance our comprehension of the free vibration of FG microplates in high thermal *** addition,the findings significantly enhance our comprehension of the free vibration of FG microplates in high thermal *** addition,the results of this research will have great potential in military and defense applications such as components of submarines,fighter aircraft,and missiles.

关键词： Microplates Functionally graded material Finite element method Modified couple stress theory New TSDT High-thermal free vibration Pasternak foundation

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Application of Intelligent Sports in Urban Parks Under the Orientation of Healthy Cities 4th

Application of Intelligent Sports in Urban Parks Under the O...

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4th International Civil engineering and Architecture Conference, CEAC 2024

作者： Chen, Yashan Faculty of Innovation and Design City University of Macau 999078 China College of Civil Engineering Putian University Putian351100 China

ISBN: (纸本)9789819754762

Intelligent sports fits the background of the era of scientific and technological development and the gradual improvement of health demand, and has more advantages in the integration field of promoting public health. Urban park is an important spatial carrier for realizing a healthy city, and in recent years, a number of policy documents have put forward the intelligent orientation of outdoor sports, indicating that the integration of intelligent sports with urban parks has practical significance and application value. Based on this, this study introduces the application types and distribution of intelligent sports in urban parks, facility support and platforms, proposes 3 issues that the application of intelligent sports in urban parks may face, namely management and maintenance, technical guarantee and revenue, and provides 4 strategies with a view to providing a basis for subsequent practical promotion and theoretical research. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sports

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Nonlinear Programming-based Robot Motion Planning for Automatic Gait Measurement of Passing Pedestrian in Corridors

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IEEE Access 2025年 13卷 73109-73123页

作者： Hayashide, Kazuyuki Takahashi, Mitsuhiro Takahashi, Masaki Keio University Graduate School of Science and Technology Kohoku Yokohama223-8522 Japan Keio University Faculty of Science and Technology Department of System Design Engineering Kohoku Yokohama223-8522 Japan

Patrol robots in hospital wards are expected not only to ensure the safety of their movements, but also to perform gait measurement as part of their monitoring functions. In this study, we present a system that enables a patrol robot to perform a 5-meter walk test (5mWT) on passing pedestrians in a corridor. The pedestrian’s position and velocity are measured sequentially, and the robot’s trajectory is generated based on the results using a nonlinear programming method, followed by Model Predictive Control tracking. This allows for adaptive gait measurement during passing interactions, taking into account arbitrary pedestrian trajectories. Furthermore, a parameter estimation method tailored to the characteristics of the acquired data, namely whole-body, continuous and multi-view measurements, is proposed. Through simulation and experiments, we confirmed the feasibility of the measurement operation and accuracy of the derived gait parameters. The proposed method can not only be used anywhere, but also measure gait over a long distance with high accuracy using a single sensor. Moreover, it could contribute to the realization of gait measurement without pedestrian’s tension. © 2013 IEEE.

关键词： Motion planning

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Using Geographical Information System for Mapping Primary Schools Distribution in Erbil City 4th

Using Geographical Information System for Mapping Primary Sc...

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4th International Civil engineering and Architecture Conference, CEAC 2024

作者： Zangana, Dnya D. Ibrahim, Ahmed J. Yuan, Hong School of Architecture and Design Southwest Jiaotong University Chengdu China Department of Architecture Faculty of Engineering Koya University Kurdistan Region Iraq

ISBN: (纸本)9789819754762

Mapping educational facilities is an important factor in achieving social equity. However, many countries have experienced problems with the distribution of educational facilities. This study explores the spatial distribution of public primary schools in Erbil using advanced GIS tools and statistical analyses. It employs methods such as the Lorenz Curve, Moran's Index, Ripley's K function, hotspot analysis, and geostatistical techniques, including IDW and Kriging. The research reveals significant inequities in the allocation of educational facilities, with densely populated central areas having a higher concentration of schools compared to the sparsely populated outskirts. Additionally, the results revealed that the observed Ripley's K value was approximately 7000 m greater than the expected K value, and the Moran's index was 0.0895. This indicates that the distribution of schools has clustering patterns. Moreover, the values of IDW and Kriging, 8 and 3, respectively, suggest that primary schools tend to concentrate in the older, more populated neighborhoods of the city. These findings highlight the pressing need for balanced urban development and educational infrastructure, especially in rapidly urbanizing contexts. This paper provides essential insights for policymakers and urban planners, underscoring the importance of equitable resource distribution in urban settings. While the study's approach is focused primarily on geographical factors, it opens avenues for further research incorporating socio-economic variables. Overall, it contributes significantly to understanding urban planning challenges in the realm of educational equity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Mapping

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