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Development and Flight Experiments of Scaled-model AAM Aircraft With Boxed-wing

Journal of Institute of Control, Robotics and systems 2025年第1期31卷 5-13页

作者： Yang, Yechan Park, Seonghyeon Park, Joonhyuk Seo, Bin Kim, Nakyung Jeong, Hoijo Suk, Jinyoung Kim, Seungkeun Department of Aerospace Engineering Chungnam National University Korea Republic of Interdisciplinary Program in Intelligent Aerospace System Seoul National University Korea Republic of

Advanced air mobility (AAM) is being developed to address complex transportation challenges in urban environments. In this study, a scaled model of a boxed-wing tiltrotor AAM has been designed and implemented through simulation and flight testing, establishing a foundation for the future commercialization of AAM. All structural and aerodynamic factors involved in the design of the Boxed-wing were considered during the initial stage of development, and its aerodynamic performance was analyzed. A software-in-the-loop simulation was conducted by integrating the Gazebo simulator and PX4 to verify the performance of the simulation model. The model successfully followed the predefined waypoints during the simulation, and the control parameters derived from the simulation were then applied to the flight test. The key parameters among them were validated through the flight test, confirming their effectiveness in ensuring a stable flight. © ICROS 2025.

关键词： Urban transportation

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Micro-electrode array (MEA) electrophysiological signal analysis by descriptive stochastic tests of the probability density structure

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Research on Biomedical engineering 2025年第2期41卷 1-13页

作者： Faria, Vinícius Naves Rezende Ramos, Marina Abadia Martinoia, Sérgio Destro-Filho, João-Batista Postgraduate Program in Electrical Engineering Universidade Federal de MG Uberlândia Brazil Postgraduate Program in Biomedical Sciences Universidade Federal de MG Uberlândia Brazil Division of Informatics Bioengineering Robotics and System Engineering Università Degli Studi Di Genova Genova Italy

Purpose: The primary objective of this study is to present, analyze, and quantitatively characterize the electrical signals obtained from neuronal cultures coupled to micro-electrode arrays (MEAs). Special attention is given to the temporal evolution of electrical activity across distinct geometric regions of the MEA devices. Methods: The proposed methodology involves signal acquisition, classical analysis based on spike and burst detection, and, critically, the characterization of the probability density structure of the signals. This is achieved through the quantification of Gaussianity—expressed as the percentage of segments non-Gaussian (PSNG)—and stationarity— expressed as the percentage of segments non-stationary (PSNE). Results: Initial analyses showed that first-order power spectral density quantifiers lacked the statistical robustness required to effectively describe the complex components of MEA signals. In contrast, PSNG and PSNE demonstrated strong potential in capturing the different stages of neuronal culture development. Cluster analysis further supported the discriminative capacity of these quantifiers. Conclusion: The phase corresponding to decreased neuronal activity and onset of cell death—a biologically critical stage—exhibited the strongest correlation among the studied variables. These results suggest a discernible biological organization and highlight the relevance of PSNG and PSNE as promising tools for assessing neuronal culture dynamics. © The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering 2025.

关键词： Cell death

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Variable Length Multi-Objective Whale Optimization for Trust Aware Data Gathering in Wireless Sensor Network

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IEEE Access 2025年 13卷 32100-32121页

作者： Saad, Mohammed Ayad Jaafar, Rosmina Chellappan, Kalaivani Faculty of Engineering and Built Environment Department of Electrical Electronics and System Engineering Selangor Bangi43600 Malaysia Al-Kitab University Department of Medical Instrumentations Technique Engineering Kirkuk36001 Iraq Universitas Airlangga Biomedical Engineering Study Program Faculty of Science and Technology Surabaya60115 Indonesia

Efficient data collection in wireless sensor networks (WSNs) is crucial. While traditional approaches rely on stationary data sinks, the use of mobile sinks, like unmanned aerial vehicles (UAVs), has shown promise in enhancing data-gathering capabilities. However, existing methods often overlook the importance of trust, leaving the network susceptible to malicious or faulty nodes. To address this issue, we propose a novel trust-aware data-gathering algorithm, Variable Length Multi-Objective Whale Optimization Data Gathering (VLMOWO-DG). Our algorithm simultaneously optimizes energy consumption, delay, and trust while employing mobile sinks to collect data from sensor nodes. By considering trust as a key performance metric, we improve data reliability and security. The VLMOWO-DG algorithm introduces flexibility through variable-length solution representation and application-oriented operators, allowing for efficient exploration of the solution space. Simulation results demonstrate that our proposed algorithm significantly outperforms established benchmarks, NSGA-II and NSGA-III, in terms of domination and hypervolume. This leads to a remarkable improvement of 200% in data gathering performance. © 2015 The Authors.

关键词： Data collection

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GeoRefineNet: A Multistage Framework for Enhanced Cephalometric Landmark Detection in CBCT Images Using 3D Geometric Information 17th

GeoRefineNet: A Multistage Framework for Enhanced Cephalome...

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17th Asian Conference on Computer Vision, ACCV 2024

作者： Viriyasaranon, Thanaporn Ma, Serie Choi, Jang-Hwan Department of Computational Medicine Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Korea Republic of Division of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Korea Republic of Department of Artificial Intelligence Ewha Womans University Seoul Korea Republic of

ISBN: (纸本)9789819609000

The precise detection of cephalometric landmarks on two-dimensional (2D) radiographs or three-dimensional (3D) computed tomography (CT) images is a fundamental step in various medical fields, especially in research on orthodontics and maxillofacial surgery. Deep learning-based detectors have demonstrated remarkable accuracy in 2D cephalometric analysis, whereas conventional single-view approaches are limited by their reliance on information from a single perspective. This study proposes GeoRefineNet, a novel multistage framework that leverages information from multiple CT scans acquired at various angles. By incorporating geometric knowledge through a 3D heatmap reconstruction process, GeoRefineNet improves robustness, accuracy, and adaptability to various cephalometric configurations. The proposed framework predicts 3D landmark positions on CT images, effectively addressing challenges associated with high-dimensional input data and limited training examples. GeoRefineNet surpasses the existing state-of-the-art models in the 2D and 3D domains, as demonstrated by its superior performance on numerical and clinical datasets. These findings indicate that GeoRefineNet offers a promising avenue for improving the accuracy and reliability of cephalometric landmark detection fostering further advances in clinical diagnosis and treatment planning. Our code is available at https://***/Thanaporn09/***. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Computerized tomography

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Enhancing compatibility and biodegradability of polylactic acid/biomass composites through torrefaction of forest residue

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Journal of Bioresources and Bioproducts 2025年第1期10卷 51-61页

作者： June-Ho Choi Myeong Rok Ahn Chae-Hwi Yoon Yeon-Su Lim Jong Ryeol Kim Hyolin Seong Chan-Duck Jung Sang-Mook You Jonghwa Kim Younghoon Kim Hyun Gil Cha Jae-Won Lee Hoyong Kim Center for Bio-based Chemistry Korea Research Institute of Chemical Technology(KRICT)Ulsan 44429South Korea Department of Wood Science and Engineering College of Agriculture and Life SciencesChonnam National UniversityGwangju 61186South Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National UniversityGwangju 61186South Korea

This study investigated the effects of torrefaction on forest residue(FR)and its subsequent ap-plication as a bulk-loading filler in polylactic acid(PLA)*** enhanced the chemical properties of FR,improving its compatibility with PLA,and the crystallinity increased from 24.9%to 42.5%.The process also improved the hydrophobicity of PLA/biomass composites,as demonstrated by the water contact angle of 76.1°,closely matching that of neat PLA(76.4°).With the introduction of 20%modified biomass properties after torrefaction treatment,the tensile strength of PLA/biomass composite increased from 58.7 to 62.3 ***,the addition of torrefied forest residue(TFR)accelerated biodegradation by increasing the onset of degrada-tion and inhibiting *** 90 d,the biodegradability of PLA/biomass composites reached 94.9%,which had a 6.9%increase compared to the neat PLA(88.8%).Overall,this study highlights the potential of torrefaction in enhancing both the physical properties and biodegrad-ability of PLA-based composites,contributing to a more sustainable approach to reducing plastic pollution.

关键词： Forest residue Torrefaction Bulk-loading filler Polylactic acid composite Hydrophobicity Tensile strength Biodegradability

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RSSI-Based Autonomous Tracking system for Radio-Tagged Flying Insects Using UAV With Rotational Antenna

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IEEE Access 2025年 13卷 72040-72053页

作者： Pak, Jeonghyeon Kim, Bosung Son, Hyoung Il Chonnam National University Department of Convergence Biosystems Engineering Gwangju61186 Korea Republic of Chonnam National University Interdisciplinary Program in IT-Bio Convergence System Gwangju61186 Korea Republic of Chonnam National University Research Center for Biological Cybernetics Gwangju61186 Korea Republic of

The escalating effects of climate change have heightened the urgency of ecosystem conservation efforts worldwide. In this context, pollinators such as honeybees play a critical role in maintaining ecosystem health. However, they face appreciable threats, including the proliferation of invasive alien species (IAS) and colony collapse disorder. In this study, we propose a novel tracking system that uses unmanned aerial vehicles (UAVs) equipped with rotational directional antennas and radio telemetry systems. This approach, which represents an improvement over our previous works, aims to protect biodiversity and ecosystem resilience by mitigating the adverse impacts of IAS on pollinator populations. To implement the proposed tracking strategy, a motor-based directional antenna that can rotate 360° is attached to a UAV, and the received signal strength indicator (RSSI) value is used to localize the hornets to which sensors are attached. The proposed tracking system was verified in a simulated field environment that was constructed by considering the RSSI values obtained in a forest. In addition, the robustness and field applicability of the tracking system were improved by applying it to scenarios consisting of different paths that were constructed considering the dynamic nature of hornets. © 2013 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Innovative metallization pattern and technique for industrial rear emitter p-type tunnel oxide passivated contact solar cells

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Journal of Industrial and engineering Chemistry 2025年 147卷 628-635页

作者： Khokhar, Muhammad Quddamah Yousuf, Hasnain Rahman, Rafi Ur Aida, Maha Nur Madara, Polgampola Chamani Jony, Jaljalalul Abedin Dao, Vinh-Ai Pham, Duy Phong Yi, Junsin Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Future Energy Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Physics Faculty of Applied Sciences HCMC University of Technology and Education Ho Chi Minh City700000 Viet Nam College of Information and Communication Engineering Sungkyunkwan University Suwon16419 Korea Republic of

In this study, we aim to enhance the efficiency of p-type tunnel oxide passivated contact (p-TOPCon) solar cells by improving charge carrier extraction while achieving higher fill factor (FF) and open circuit voltage (Voc). We explore various potential methods for the photovoltaic industrial procedure, including optimizing metallization patterns and techniques, such as the utilization of a high efficiency grid pattern (HEGP) in place of the conventional straight finger-line pattern (SFLP). Co-firing conditions, peak firing temperature, and belt speed are investigated for their impact on FF enhancement, along with evaluating the effects of single and double print processes. Furthermore, we examine the efficacy of Nafion treatment as a surface modification technique to enhance FF. Experimental results indicate that optimizing co-firing conditions and employing Nafion treatment significantly increased FF to approximately 83.26% in p-TOPCon solar cells. Adjusting peak firing temperature and belt speed, as well as implementing the double print process, demonstrate superior FF enhancement compared to the single print process. Additionally, Nafion treatment contributes to FF improvement by passivating surface defects and enhancing charge carrier collection. Overall, this study provides valuable insights into optimizing co-firing conditions and surface treatment techniques to enhance p-TOPCon solar cell efficiency (Eff) up to 23.50%, thus advancing high-efficiency photovoltaic technology. © 2024 The Korean Society of Industrial and engineering Chemistry

关键词： Metallizing

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Technology-Enhanced Learning for User Security Awareness Using AI-based Naive RAG: A Design and Prototype

Technology-Enhanced Learning for User Security Awareness Usi...

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2025 International Conference on Advancement in Data Science, E-learning and Information system, ICADEIS 2025

作者： Pratama, I. Putu Agus Eka Widyantara, I. Made Oka Linawati Gunantara, Nyoman Suakanto, Sinung Irawan, Eka Tresna Udayana University Doctoral Program of Engineering Sciences Faculty of Engineering Bali Badung Indonesia Udayana University Dept. of Electrical Engineering Faculty of Engineering Bali Badung Indonesia Telkom University Dept. of Information System West Java Bandung Indonesia Mayar International Pte. Ltd. Singapore

ISBN: (纸本)9798331513320

The increasing use of Information Technology (IT) in all areas of life, followed by increasing cybersecurity threats on the user side, makes cybersecurity awareness among users an obligation that must be met. Several solutions currently available (guides, discussion forums, workshops) have not been able to provide good results and are lacking in terms of user engagement, adaptability, and optimizing available resources, so technology-based learning is needed, especially AI. This paper introduces the design and prototype of an AI-based learning system, especially with the Naive Retrieval-Augmented Generation (Naive RAG) method with three steps, including Retrieval, Augmented, and Generation. The system combines contextual user questions and answers with internal and domain knowledge systems to explain cybersecurity awareness to users dynamically and personally. The prototype that has been developed is then tested using the Black Box Testing method to evaluate functionality and usability. The test results show that the functionality of the system built has run well with a percentage of success of 100%, so it can be used as a technologybased learning medium for education and learning of user security awareness. © 2025 IEEE.

关键词： Adversarial machine learning

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CorrA: Leveraging Large Language Models for Dynamic Obstacle Avoidance of Autonomous Vehicles

arXiv

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arXiv 2025年

作者： Wang, Shanting Typaldos, Panagiotis Malikopoulos, Andreas A. System Engineering Program Cornell University IthacaNY United States School of Civil and Environmental Engineering Cornell University IthacaNY United States School of Civil and Environmental Engineering The System Engineering Program Cornell University IthacaNY United States

In this paper, we present Corridor-Agent (CorrA), a framework that integrates large language models (LLMs) with model predictive control (MPC) to address the challenges of dynamic obstacle avoidance in autonomous vehicles. Our approach leverages LLM reasoning ability to generate appropriate parameters for sigmoid-based boundary functions that define safe corridors around obstacles, effectively reducing the state-space of the controlled vehicle. The proposed framework adjusts these boundaries dynamically based on real-time vehicle data that guarantees collision-free trajectories while also ensuring both computational efficiency and trajectory optimality. The problem is formulated as an optimal control problem and solved with differential dynamic programming (DDP) for constrained optimization, and the proposed approach is embedded within an MPC framework. Extensive simulation and real-world experiments demonstrate that the proposed framework achieves superior performance in maintaining safety and efficiency in complex, dynamic environments compared to a baseline MPC approach. © 2025, CC0.

关键词： Constrained optimization

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Nafion edge passivation and nitrogen annealing treatment to improve solar cell reliability under light and elevated temperature induced degradation (LeTID) investigation

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Current Applied Physics 2025年 75卷 1-7页

作者： Jony, Jaljalalul Abedin Yousuf, Hasnain Khokhar, Muhammad Quddamah Zahid, Muhammad Aleem Madara, Polgampola Chamani Rahman, Rafi Ur Alamgeer Chu, Mengmeng Sanyal, Simpy Wang, Fucheng Kim, Youngkuk Kim, Kyesoo Dhungel, Suresh Kumar Park, Sangheon Yi, Junsin Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of University Tamilnadu 600124 India Research Institute for Clean Energy College of Information and Communication Engineering Sungkyunkwan University Gyeonggi-do Suwon16419 Korea Republic of Faculty of Technology Nepal Academy of Science and Technology 3323 Khumaltar Lalitpur Nepal

This research examines the effectiveness of nitrogen annealing and Nafion treatment in mitigating Light and Elevated Temperature Induced Degradation (LeTID) in Passivated Emitter and Rear Contact (PERC) solar cells, employing a 30-kW photovoltaic (PV) system for evaluation. As a photosensitive device, solar cells are susceptible to damage from laser irradiation, leading to reduced photoelectric conversion efficiency, structural damage, and functional loss. To minimize this loss, nitrogen annealing and Nafion treatments were applied, followed by the analysis of LeTID effects on untreated, Nafion-treated, and combined nitrogen-annealed and Nafion-treated PERC cells. Untreated cells showed an 8 % fall in open-circuit voltage (Voc) and a 7 % fill factor (FF) loss. The combined treatment (Combination of Nitrogen & Nafion Treatment) improved stability, reducing losses to 6 % in Voc and 5 % in FF. The Nafion treatment yielded the best results, limiting deterioration to 4 % in Voc and 3 % in FF. PVsyst simulations, incorporating real-world data, confirmed enhanced stability and efficiency, aiding in optimizing PV system design and maintenance. © 2025 Korean Physical Society

关键词： Annealing

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