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2023 Seminar on Fields, Waves, Photonics and Electro-Optics: Theory and Practical Applications, FWPE 2023

作者： Ignatovich, Vladislav O. Galtsov, Yaroslav O. Institute of Radio Engineering Systems and Control Department of Antennas and Radio Transmitting Devices Taganrog Russia

ISBN: (纸本)9798350370447

In this paper, the results of a simulation of a dualband 5G antenna for wireless power transmission using Altair FEKO software are presented. Frequency bands were selected as 4.4-5.0 n 5.15-5.925 GHz, these bands are declared by standard 5G Sub-6 GHz (bands n79 and n46). The construction of the antenna was developed as complex-shaped patch antenna. Research of the main characteristics was made, and also the parameterization task was solved for this antenna by the criterion of minimizing the SWR. Patch has got SWR 1.058 and 1.273 at bands we're studying. At the end, the prototyping of this model was carried out. Experimental studies of the frequency dependence of the SWR of the antenna found out that the results of nature measurement don't confront the results of computer simulation. © 2023 IEEE.

关键词： Microstrip antennas

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Circularity Reinforcement of Critical Raw Materials in Europe: A Case of Niobium

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Circular Economy and Sustainability 2024年第4期4卷 2449-2472页

作者： von Rennenberg, Theresa Yu, Yifei Fraccascia, Luca Yazan, Devrim Murat Department of Industrial Engineering and Business Information Systems University of Twente Drienerlolaan 5 Enschede 7522 NB Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy

Critical Raw Materials attract increasing attention due to their depleting reserves and low recyclability. Niobium, one of the most rare and vital elements, is primarily found in Brazil. This research explores the potential impact of Circular Economy (CE) strategies on mitigating niobium's criticality within Europe. First, a niobium supply chain is designed and analysed by Enterprise Input–Output modelling. Second, the supply risk is calculated based on the criticality matrix proposed by the European Commission under three scenarios associated with resources, technologies, and policies. The results show that urban mining is a potential solution to reduce niobium’s criticality and mitigate its environmental impacts. A higher recycling input rate and/or a mix of recycling and substitution strategies is necessary to offset niobium’s criticality. Aligned with the CE action plan, the research offers a scientific foundation to strategically prevent the risk of niobium supply shortages. © The Author(s) 2024.

关键词： Circular economy Critical raw materials Enterprise input–output Niobium supply chain Scenario analysis

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The Journey/DAO/TAO of Embodied Intelligence: From Large Models to Foundation Intelligence and Parallel Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1313-1316页

作者： Tianyu Shen Jinlin Sun Shihan Kong Yutong Wang Juanjuan Li Xuan Li Fei-Yue Wang College of Information Science and Technology Beijing University of Chemical TechnologyBeijing 100029China School of Electrical and Information Engineering Jiangsu UniversityZhenjiang 212013China State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Peng Cheng Laboratory Shenzhen 518000China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China IEEE

THE tremendous impact of large models represented by ChatGPT[1]-[3]makes it necessary to con-sider the practical applications of such models[4].However,for an artificial intelligence(AI)to truly evolve,it needs to possess a physical“body”to transition from the virtual world to the real world and evolve through interaction with the real *** this context,“embodied intelligence”has sparked a new wave of research and technology,leading AI beyond the digital realm into a new paradigm that can actively act and perceive in a physical environment through tangible entities such as robots and automated devices[5].

关键词： Intelligence DAO TAO

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Hierarchical Learned Auctions for Communication-Sparse Satellite Environments

Hierarchical Learned Auctions for Communication-Sparse Satel...

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AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Lehman, Hannah Valasek, John Vehicle Systems & Control Laboratory Aerospace Engineering Department Texas AM University College StationTX77843-3141 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Multiagent coordination research tends to focus on strategies such as Multiagent Reinforcement Learning which makes extensive use of inter-agent communication. This works well in abstracted simulations, but may be challenging or non-feasible to implement in real-world environments because many problems of interest can have sparse, intermittent, or contested communication frameworks. This paper extends the Hierarchical Auctions for the Coordination of Heterogeneous Agents (HACHA) approach to investigate hierarchical auctions and machine learning to facilitate teaming between agents in a system where some agents enter and leave the communication graph at regular intervals, akin to a satellite. Results presented in the paper show that the method is able to identify, distribute, and monitor tasks despite communication challenges. This paper shows that allowing multiple children to propagate auctions results in lower average search times and higher success rates. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Satellite communication systems

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SightAid: empowering the visually impaired in the Kingdom of Saudi Arabia (KSA) with deep learning-based intelligent wearable vision system

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Neural Computing and Applications 2024年第19期36卷 11075-11095页

作者： Talaat, Fatma M. Farsi, Mohammed Badawy, Mahmoud Elhosseini, Mostafa Machine Learning Department Faculty of Artificial Intelligence Kafrelsheikh University Kafrelsheikh Egypt Faculty of Computer Science & amp Engineering New Mansoura University Gamasa35712 Egypt College of Computer Science and Engineering Taibah University Yanbu46421 Saudi Arabia Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura35516 Egypt Computer Science and Information Department Applied College Taibah University Madinah46537 Saudi Arabia

In the Kingdom of Saudi Arabia, visual impairment poses significant challenges for approximately 17.5% of school-aged children, mainly due to refractive errors. These challenges extend to everyday navigation, environmental interaction, and overall life quality. Motivated by the desire to empower visually impaired individuals, who face navigational limitations, difficulties in object recognition, and inadequate assistance from traditional technologies, we propose SightAid. This innovative wearable vision system utilizes a deep learning-based framework, addressing the gaps left by current assistive solutions. Traditional methods, such as canes and GPS devices, often fail to meet the nuanced and dynamic needs of the visually impaired, especially in accurately identifying objects, understanding complex environments, and providing essential real-time feedback for independent navigation. SightAid comprises a seven-phase framework involving data collection, preprocessing, and training of a sophisticated deep neural network with multiple convolutional and fully connected layers. This system is integrated into smart glasses with augmented reality displays, enabling real-time object detection and recognition. Interaction with users is facilitated through audio or haptic feedback, informing them about the location and type of objects detected. A continuous learning mechanism, incorporating user feedback and new data, ensures the system's ongoing refinement and adaptability. For performance assessment, we utilized the MNIST dataset, and an Indoor Objects Detection dataset tailored for the visually impaired, featuring images of everyday objects crucial for safe indoor navigation. SightAid demonstrates remarkable performance with accuracy up to 0.9874, recall values between 0.98 and 0.99, F1-scores ranging from 0.98 to 0.99, and AUC-ROC values reaching as high as 0.9999. These metrics significantly surpass those of traditional methods, highlighting SightAid's potential to substan

关键词： Object recognition

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Towards designing high mechanical performance low-alloyed wrought magnesium alloys via grain boundary segregation strategy:A review

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Journal of Magnesium and Alloys 2024年第5期12卷 1774-1791页

作者： Zhi Zhang Jinshu Xie Jinghuai Zhang Xu-Sheng Yang Ruizhi Wu Key Laboratory of Superlight Material and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001China State Key Laboratory of Ultra-Precision Machining Technology Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen 518060China

Low-alloyed magnesium(Mg)alloys have emerged as one of the most promising candidates for lightweight ***,their further application potential has been hampered by limitations such as low strength,poor plasticity at room temperature,and unsatisfactory *** address these challenges,grain refinement and grain structure control have been identified as crucial factors to achieving high performance in low-alloyed Mg *** effective way for regulating grain structure is through grain boundary(GB)*** review presents a comprehensive summary of the distribution criteria of segregated atoms and the effects of solute segregation on grain size and growth in Mg *** analysis encompasses both single element segregation and multi-element co-segregation behavior,considering coherent interfaces and incoherent ***,we introduce the high mechanical performance low-alloyed wrought Mg alloys that utilize GB segregation and analyze the potential impact mechanisms through which GB segregation influences materials *** upon these studies,we propose strategies for the design of high mechanical performance Mg alloys with desirable properties,including high strength,excellent ductility,and good formability,achieved through the implementation of GB *** findings of this review contribute to advancing the understanding of grain boundary engineering in Mg alloys and provide valuable insights for future alloy design and optimization.

关键词： Magnesium alloys Grain boundary segregation High strength High plasticity High formability

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Speech Recognition Using Spectrogram Images and Formant Data with Neural Networks 20th

Speech Recognition Using Spectrogram Images and Formant Dat...

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20th International Conference on Dependability of Computer systems, DepCoS-RELCOMEX 2025

作者： Kucharski, Mateusz Skubalska-Rafajlowicz, Ewa Department of Control Systems and Mechatronics Wroclaw University of Science and Technology Wroclaw Poland Department of Computer Engineering Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (纸本)9783031927331

This paper proposes a novel approach to improving speech recognition performance by combining spectrogram images with extracted formant frequency data within a dual input neural network framework. While spectrograms are widely used in speech recognition due to their ability to capture time, frequency, and amplitude information, they may not always effectively highlight the subtle characteristics of formant patterns, especially in low resolution images. To address this, we introduce a hybrid model that integrates spectrogram images with formant parameters derived using the linear predictive coding method. The model utilizes parallel convolutional neural network processing spectrogram images and the other handling time series formant data. Outputs are then concatenated and further processed through fully connected layers. This double channel design enables the network to take advantage of complementary information from both spectral and parametric speech features, leading to improved recognition accuracy. The model is trained and evaluated using the Google Speech Commands dataset, achieving superior results compared to traditional KNN classifiers, formant-only models, and standard spectrogram-based CNNs. The proposed method achieves a 93% recognition accuracy, outperforming conventional approaches and demonstrating the potential of formant-augmented neural networks for more robust speech recognition tasks. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image enhancement

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Bridging Training and Execution via Dynamic Directed Graph-Based Communication in Cooperative Multi-Agent systems 39

Bridging Training and Execution via Dynamic Directed Graph-B...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Zhang, Zhuohui He, Bin Cheng, Bin Li, Gang Department of Control Science & Engineering Tongji University China National Key Laboratory of Autonomous Intelligent Unmanned Systems Tongji University China

ISBN: (纸本)157735897X

Multi-agent systems must learn to communicate and understand interactions between agents to achieve cooperative goals in partially observed tasks. However, existing approaches lack a dynamic directed communication mechanism and rely on global states, thus diminishing the role of communication in centralized training. Thus, we propose the Transformer-based graph coarsening network (TGCNet), a novel multi-agent reinforcement learning (MARL) algorithm. TGCNet learns the topological structure of a dynamic directed graph to represent the communication policy and integrates graph coarsening networks to approximate the representation of global state during training. It also utilizes the Transformer decoder for feature extraction during execution. Experiments on multiple cooperative MARL benchmarks demonstrate state-of-the-art performance compared to popular MARL algorithms. Further ablation studies validate the effectiveness of our dynamic directed graph communication mechanism and graph coarsening networks. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Reinforcement learning

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From Value Stream Mapping to Choreographic Tension Mapping: Preliminary Results and Insights from an Exploratory Study

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Journal of Dance Education 2025年第2期25卷 121-134页

作者： Akçalı, Elif Springer, Alex Burley, Xan Ballin, Chloe D. Colon, Evelyn Department of Industrial and Systems Engineering Herbert Wertheim College of Engineering University of Florida Gainesville FL United States Dance Area School of Theatre + Dance University of Florida Gainesville FL United States Department of Agricultural and Biological Engineering Herbert Wertheim College of Engineering University of Florida Gainesville FL United States Department of Chemical Engineering Herbert Wertheim College of Engineering University of Florida Gainesville FL United States

Value Stream Mapping (VSM), a lean manufacturing technique, is a process analysis approach that focuses on value and waste. This project explored the development and incorporation of a VSM-inspired tool to help dance composition students consider the value present in their choreography explicitly. The proposed Choreographic Tension Mapping (CTM) tool was incorporated into an upper-level dance composition course in the Dance Program in collaboration with the department of Industrial and systems engineering at the University of Florida. Students used this tool multiple times throughout the semester. They responded to a set of prompts to reflect on their experience of using CTM and its impact on their creative processes. Students’ responses to one of the prompts were qualitatively analyzed. The preliminary findings demonstrated the potential benefits of the use of CTM to support the development of skills in choreographing, collaborating in a group, and giving constructive feedback in dance composition education. © 2024 National Dance Education Organization.

关键词： choreography Higher education interdisciplinary pedagogy teaching methods

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Predictive Vehicle control at Intersections with Look-Ahead Driving Approach

Predictive Vehicle Control at Intersections with Look-Ahead ...

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2025 SICE International Symposium on control systems, SICE ISCS 2025

作者： Magzhan, Atykhan Hossain, Md Delowar Bakibillah, A.S.M. Kamal, Md Abdus Samad Yamada, Kou Graduate School of Science and Technology Gunma University Kiryu Japan Institute of Science Tokyo Department of Systems and Control Engineering Tokyo Japan

ISBN: (纸本)9784907764852

This paper presents a look-ahead vehicle control scheme for efficient traffic management at signalized intersections. The proposed scheme predicts future driving states with a look-ahead approach as an extended adaptive cruise control (ACC) model. It maintains car-following behavior similar to human driving while predicting future states of traffic flow to minimize intersection clearing time and aggressive braking independently, similar to model predictive control (MPC) approaches. In contrast to MPC models that are computationally demanding and have limited practical applications due to real-time constraints, the proposed scheme uses a modified Intelligent Driver Model (IDM) with predictive adjustments. The efficiency of the control scheme is evaluated through simulations with multiple vehicles in intersection traffic scenarios, focusing on maintaining safe time headway within a traffic flow and ensuring efficient flows with higher intersection throughput. Comparative results indicate improvements in intersection clearance, human-like vehicle headway management, and enhanced traffic flow performance. © 2025 The Society of Instrument and control Engineers.

关键词： Adaptive cruise control

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