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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2025年第1期87卷 21-34页

作者： Contașel, Cristian Rughiniș, Răzvan Trancă, Dumitru Cristian Țurcanu, Dinu Dept. of Computer Science and Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Dep. of Software Engineering and Automatics Technical University of Moldova Chișinău Moldova

This study provides an innovative architectural model for e-Health systems that aims to improve cyber resilience while maintaining high availability under fluctuating traffic loads. We examined typical cybersecurity incidents in the field of e-Health, their correlations with architectural defects, and frequent design patterns in currently operational systems. A testing approach based on our research finds those weaknesses and proposes viable fixes. In this paper, a comprehensive support strategy for transitioning from conventional monolithic architectures to microservices is presented. This change makes use of cloud computing's vertical and horizontal scalability to maximize resource utilization while ensuring system reliability. We also discuss deployment ideas for the new microservices, focusing on operational resilience and cybersecurity in e-Health environments. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Electronic health record

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Efficacy Assessment of Vetiver (Chrysopogon zizanioides) for the Removal of Persistent Organic Pollutants Using Vertical Surface Flow Constructed Wetland system

Efficacy Assessment of Vetiver (Chrysopogon zizanioides) for...

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Geo-EnvironMeet 2025: Geoenvironmental Contamination and Waste Containment

作者： Adhikary, Avishek Pal, Supriya Ghosh, Sudipta Chaudhuri, Hirok Mandal, Mrinal Kanti Chaudhuri, Rajib Ghosh Dept. of Civil Engineering Swami Vivekananda Univ. Barrackpore India Dept. of Civil Engineering National Institute of Technology West Bengal Durgapur India Dept. of Civil Engineering Jadavpur Univ. West Bengal Kolkata India Dept. of Physics National Institute of Technology West Bengal Durgapur India Dept. of Chemical Engineering National Institute of Technology West Bengal Durgapur India

ISBN: (数字)9780784485699

The present study deals with the adsorption potential of silty-sandy soil, lightweight expanded clay aggregate (LECA), and vetiver for remediation of surface water contaminated with doxycycline and carbendazim. Batch experiments were conducted using response surface methodology, with the input process parameters being contact time, initial pollutant concentration, and adsorbent dosage. Both the Langmuir (KL - 0.4587-15.941 L/mg) and Freundlich (Kf - 0.00017-0.2897 L/g) models were shown to be fitting in certain sorbent-sorbate combinations. The pseudo-second-order model (Qe - 0.0967-1.992 mg/g and K2 - 0.068-56.861 g/mg-min) was the best-fit kinetic model. The increment in system temperature showed increased removal efficiency for both doxycycline (39%-89%) and carbendazim (16%-72%). A transformation of pH from acidic to alkaline conditions showed decreased sorption for carbendazim and increased adsorption for doxycycline. Laboratory-scale constructed wetland systems comprising only vetiver showed removal efficiency in the range of 73%-90% for doxycycline and 77%-89% for carbendazim. The silty-sand soil bed wetland planted with vetiver increased the doxycycline removal efficiency by up to 98%. In comparison, the LECA bed wetland incorporating vetiver saw a surge in carbendazim attenuation by up to 99.6%. © ASCE.

关键词： Surface analysis

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CASE STUDY OF SPACE UTILIZATION AND WASTE REDUCTION IN BUILDINGS USING ULTRA-THIN PRECAST PRESTRESSED CONCRETE MEMBERS

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AIJ Journal of technology and Design 2025年第77期31卷 444-448页

作者： Hosoya, Jin Imamoto, Kei-Ichi Ridengaoqier, E. Kiyohara, Chizuru Dept. of Architecture Graduate School of Engineering Tokyo Univ. of Science Japan Dept. of Architecture Faculty of Engineering Tokyo Univ. of Science Japan Research Institute for Science & Technology Tokyo Univ. of Science Japan

This paper presents case study on implementing ultra-thin precast prestressed concrete members, with tension introduced by CFRP strand as prefabricated partition materials in architectural spaces. These members enhanced the efficiency of architectural spaces and significantly reduced waste materials at construction sites. The paper also discussed the mechanical properties of the thin-walled members through bending tests, demonstrating their high bending strength and safety as partition materials. Furthermore, implementation examples in a pediatric clinic have illustrated the practical benefits, including increased effective area, reduced construction time, and decreased waste. © 2025 Architectural Institute of Japan. All rights reserved.

关键词： Thin walled structures

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Subterranean Vegetable Sorting with YOLO Models and Flask Framework

Subterranean Vegetable Sorting with YOLO Models and Flask Fr...

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2025 International Conference on Control, Automation, and Instrumentation, IC2AI 2025

作者： Rakesh, M.D. Ronitha, R. Rudraswamy, S.B. JSS Science and Technology University Dept. of Electronics and Communication Engineering SJCE Mysuru India JSS Science and Technology University Dept. of Electronics and Communication Engineering Mysuru India

ISBN: (数字)9798331529604

ISBN: (纸本)9798331529604

The integration of advanced deep learning models, such as YOLOv5 and YOLOv8, into carrot cultivation significantly enhances post-harvest sorting systems, allowing for the effective differentiation between healthy and rotten carrots. This work streamlines the sorting process, ensuring that only high-quality produce reaches the market, thereby providing substantial advantages for traders. By automating this procedure, farmers can improve food safety, monitor shelf life, and enhance customer satisfaction, ultimately increasing productivity and profitability. The system employs convolutional neural networks (CNNs) to analyze visual data captured during harvest or post-harvest stages. These models are trained to identify distinguishing features of carrots, such as color changes, texture anomalies, and shape deformations, resulting in precision rates of 98.3% and 96.4% in identifying freshness with YOLOv8 and YOLOv5 respectively, and 96.5% and 93.6% in detecting rotten. Extensive training and evaluation have demonstrated notable improvements in performance metrics, validating the effectiveness of these models. As a prototype, we have developed a Flask web application for detecting whether carrots are rotten or fresh. This system significantly enhances productivity by allowing for quick and accurate assessment of carrot quality. The adoption of this AI-driven technology marks a transformative step toward optimizing resource management and maximizing crop value in modern agriculture. © 2025 IEEE.

关键词： Vegetables

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Landslide Prediction Using Deep-Learning Frameworks and Wireless Sensor Networks

Landslide Prediction Using Deep-Learning Frameworks and Wire...

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Geo-EnvironMeet 2025: Climate Change, Sustainability, and Resilience

作者： Hussaine, Syed Mujtaba Mohammed, Syed Abu Sayeed Moghal, Arif Ali Baig Chittoori, Bhaskar Dept. of Geotechnical Engineering Tongji Univ. Shanghai China Dept. of Civil Engineering HKBK College of Engineering Karnataka Bengaluru India Dept. of Civil Engineering National Institute of Technology Warangal Telangana Warangal India Dept. of Civil Engineering Boise State Univ. BoiseID United States

ISBN: (数字)9780784485705

Landslides are destructive natural disasters caused by various factors, such as climate change, heavy rainfalls, rising temperatures, soil erosion, earthquakes, and hurricanes, and predicting them is crucial for safeguarding lives and properties. This paper explores landslide prediction using wireless sensor networks (WSN), remote sensing data, and deep learning techniques. By creating a sensor network with multiple nodes, data can be collected and analyzed to detect landslides. Additionally, deep learning-based image segmentation models are applied to WSN data, while satellite imagery combined with the U-Net deep learning model effectively maps and detects landslides. The advantage of using deep learning is its ability to cover a vast area through satellite images, while WSN data offer robustness and customizable data collection frequency. The combination of both methods yields accurate predictions of landslides, enabling early detection and warning systems. Furthermore, the study yielded significant outcomes, showcasing proficiency in node management, sensor data acquisition, and efficient database integration. © ASCE.

关键词： Satellite imagery

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A Conformal Microwave Measurement system for Imaging Buried Anomalies

A Conformal Microwave Measurement System for Imaging Buried ...

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2025 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2025

作者： Islam, M. Shifatul Islam, M. Asiful Kiourti, Asimina Dept. of Electrical and Computer Engineering The Ohio State University ColumbusOH43212 United States Dept. of Electrical and Electronic Engineering Bangladesh University of Engineering and Technology Dhaka Bangladesh

ISBN: (纸本)9781946815200

Microwave imaging has long been reported for locating buried anomalies inside a bulk object as relying upon external measurements of microwave data. The approach is noninvasive, low-cost, portable, and the use of non-ionizing radiation makes it popular for biomedical applications. In this work, we explore the experimental feasibility of a conformal microwave imaging system, where the antennas are mounted on or very close to the imaging object. Our proof of concept setup entails 12 antennas surrounding a plastic cylindrical frame in free space with two dielectric cylinders used as anomalies. S-parameters were measured using a network analyzer and a 12-port switching matrix. For imaging, we used the Born Iterative Method, where the data equation was replaced with the S-parameter sensitivity formula. Simulation and measurement results show good quality image reconstruction, asserting the feasibility of the proposed conformal imaging setup. Future work will incorporate tissue-emulating materials to ultimately develop a stable and wearable imaging system. © 2025 USNC-URSI.

关键词： Cylinders (shapes)

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Preparation and Characterization of Lignin-Based Electrospun Fibers

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Palpu Chongi Gisul/Journal of Korea Technical Association of the Pulp and Paper Industry 2025年第1期57卷 67-77页

作者： Choi, Sa Rang Park, So Yeong Im, Hyeon Ji Lee, Young Soo Lee, Jung Myoung Agricultural Science and Technology Research Institute Kyungpook National University Korea Republic of Department of Wood and Paper Science Kyungpook National University Korea Republic of Dept. of Textile System Engineering Kyungpook National University Korea Republic of

Lignin, a byproduct of the pulping process, is an eco-friendly material that can potentially replace petroleum-based polymers and can be fabricated into nanocomposite fibers through electrospinning. This study explored the electrospinning of lignin/poly(ethylene oxide) (PEO) blends using two different lignin sources: softwood kraft lignin (SL) and bamboo organosolv lignin (BL). The effects of PEO content (3–6 wt%) and lignin type on solution properties and fiber formation were investigated. The viscosity of the spinning solutions increased with higher PEO content, and BL solutions exhibited higher viscosity than SL solutions under the same conditions. The fiber diameter increased with the PEO content, regardless of the lignin type, with diameters ranging from 320 to 878 nm. At the same PEO concentration, BL-based fibers exhibited larger diameters than SL-based fibers. Furthermore, when the PEO content exceeded 5 wt%, uniform, and bead-free nanofibers were successfully formed. These research findings demonstrate the potential for lignin-based nanofiber production. When utilizing bamboo organosolv lignin, it is expected that the amount of PEO additive can be reduced compared to softwood kraft lignin. © 2025 Korean Technical Assoc. of the Pulp and Paper Industry. All rights reserved.

关键词： Nanofibers

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Harnessing Machine Learning for Watermarking: A Survey on Robustness and Stealth in Image Protection 8

Harnessing Machine Learning for Watermarking: A Survey on Ro...

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8th International Conference on Electronics, Materials engineering and Nano-technology, IEMENTech 2025

作者： Routh, Kunal Mazumder, Priyanshu Pa, Amar Karmakar, Samit Kundu, Soumik Kumar Ray, Sutapa Adhikary, Pritom Roy, Bhaskar Institute of Engineering & Management University of Engineering & Management Electronics & Communication Engineering Dept. Kolkata India Calcutta Institute of Technology Electrical Engineering Dept. Howrah Uluberia India Dept. Asansol India

ISBN: (纸本)9798331520762

In recent years, the rapid growth of digital media has raised concerns over the protection of intellectual property rights. Image watermarking has emerged as a key technique for embedding copyright information into digital images. Traditional methods, such as spatial and frequency domain watermarking, often struggle with robustness against attacks like compression, noise, and resizing. However, machine learning (ML) has shown great promise in enhancing the effectiveness of watermarking systems by improving both robustness and imperceptibility. This paper provides a comprehensive review of the application of machine learning techniques in image watermarking, categorizing key approaches, evaluating their strengths and weaknesses, and discussing potential future directions. © 2025 IEEE.

关键词： Image watermarking

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Analysis of Soiling Impacts on 100 kWp Rooftop Solar PV Plant

Analysis of Soiling Impacts on 100 kWp Rooftop Solar PV Plan...

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2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Pal, Ankit Atchaya, V. Nair, Niranjana G. Ghosh, Subhajit Manivannan, L. Ilango, G. Saravana National Institute of Technology Dept. of Electrical and Electronics Engineering Tiruchirappalli India Amrita Vishwa Vidyapeetham Dept. of Electrical and Electronics Engineering Amritapuri India

ISBN: (纸本)9798331529833

This paper gives a comprehensive analysis of the impact of soiling on the performance of a 100 kWP rooftop photovoltaic (PV) plant using a 2.5-year dataset from NIT Trichy. Traditional soiling measurement methods often rely on specialized equipment, which can limit their accessibility and scalability. This study eliminates the need for special sensors by using historical and real-time operational data, such as irradiance, panel temperature, and power output. Seasonal patterns in soiling losses are thus revealed, allowing optimization of cleaning schedules to maintain energy output at expected levels. Notably, the analysis shows that 34.2% of the plant's capacity remains unutilized due to soiling. This work contributes to the design of robust PV maintenance strategies by demonstrating a scalable data-driven approach to soiling assessment, making it specifically suitable for medium-sized installations. © 2025 IEEE.

关键词： Solar irradiance

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Closed-Loop system Identification of an Unstable Nonlinear system Using Koopman Operator 4

Closed-Loop System Identification of an Unstable Nonlinear S...

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4th International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics, ICA-SYMP 2025

作者： Maneeloke, Benjaset Boonto, Sudchai Sanposh, Peerayot Tipsuwan, Yodyium Chinthaned, Natthawut Tanaprasitpattana, Warit Kasetsart University Dept. of Electrical Engineering Bangkok Thailand King Mongkut's University of Technology Thonburi Dept. of Control Systems and Instrumentation Engineering Bangkok Thailand Kasetsart University Dept. of Computer Engineering Bangkok Thailand

ISBN: (纸本)9798331505400

This paper presents a novel methodology for closed-loop system identification of unstable nonlinear systems using the Koopman operator with Extended Dynamic Mode Decomposition with control (EDMDc). The study highlights the critical role of selecting appropriate observable functions to develop accurate and efficient Koopman models. We demonstrate that the resulting Koopman models exhibit excellent fitting and validation properties and retain the stabilizability of the original nonlinear systems. These models are verified through time and frequency responses under closed-loop control using a Linear Quadratic Regulator (LQR), confirming their effectiveness. Future work will extend this framework to more complex systems and incorporate machine learning techniques to refine the selection of observable functions. This approach aims further to enhance the adaptability and robustness of Koopman-based control strategies. © 2025 IEEE.

关键词： Dynamic mode decomposition

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