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Study of Different Types of Ventilation and Cooling Systems of Bulb Hydrogenerators in a Three-Dimensional Setting

SAE International Journal of Materials and Manufacturing 2025年第3期18卷

作者： Tretiak, Oleksii Arefieva, Mariia Makarov, Pavlo Serhiienko, Serhii Zhukov, Anton Shulga, Iryna Penkovska, Nataliia Kravchenko, Stanislav Kovryga, Anton National Aerospace University Kharkiv Aviation Institute Faculty of Aircraft Engineering Department of Aerohydrodynamics Ukraine Limited Liability Company Kharkov Electric Machine-Building Plant Ukraine National Aerospace University Kharkiv Aviation Institute Faculty of International Communications and Training of Foreign Citizens Department of Foreign Languages Ukraine

The Object of research in the article is the ventilation and cooling system of bulb hydrogenerators. The Subject of study in the article is the design and efficiency of using the cooling system of various structural types for bulb hydro units. The Purpose of the work is to carry out a three-dimensional study of two cooling systems (axial and radial) of the bulb hydro unit of the Kanivskaya HPP with a rated 22 MW. Research Tasks include analysis of the main design solutions for effective cooling of bulb-type hydrogenerators, in particular, the use of radial, axial, and mixed cooling systems;formulation of the main assumptions for the three-dimensional ventilation and thermal calculation of the bulb hydrogenerator;carrying out a three-dimensional calculation for a hydrogenerator with axial ventilation;determining airflow speeds in the channels and temperatures of active parts of the hydrogenerator under the conditions of using discharge fans and without them;carrying out a three-dimensional calculation for a hydrogenerator with radial ventilation;determining airflow speeds in the channels and temperatures of the active parts of the hydrogenerator. As a result of the study, the main constructive solutions of cooling systems of bulb hydrogenerators were considered. On the basis of scientific developments, two main ventilation systems were formed and their functioning was considered on the example of the hydro unit of the Kanivska HPP. Using a three-dimensional study, a comparison of the efficiency of axial and radial ventilation systems was carried out. It was found that the forced axial system with two fans is the most optimal and reliable for removing heat from heat-generating elements, ensuring long-term operation and the necessary speeds in the cooling channels. This research makes a significant contribution to improving the efficiency of the cooling systems of bulb hydrogenerators, which is critical for their reliable and trouble-free operation. © 2025 National Aer

关键词： Cooling systems

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Exploiting Multi-Level Data Uncertainty for Japanese-Chinese Neural Machine Translation

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IEICE Transactions on Information and Systems 2025年第5期E108.D卷 440-443页

作者： Li, Zezhong Ma, Jianjun Ren, Fuji Faculty of Computer Science Zhejiang University of Water Resources and Electric Power China Faculty of Foreign Languages Dalian University of Technology China College of Computer Science and Engineering The Shenzhen Institute for Advanced Study University of Electronic Science and Technology of China China

The performance of Neural Machine Translation (NMT) heavily depends on the severity of data uncertainty existing in the training examples. In terms of its causes, data uncertainty can be categorized into intrinsic and extrinsic uncertainty, both of which can increase the learning difficulty in NMT, and lead to degradation in translation performance. To cope with this challenge, we propose a simple yet effective method to estimate the data uncertainty and incorporate it into the adaptive training of NMT, which can mitigate the hurt brought by the uncertain data. Our method consists of two modules: 1) we propose a mBERT based model for estimating token-level and sentence-level data uncertainties jointly, which is trained with multi-task learning;2) we propose heterogeneous ways of incorporating the derived multi-level uncertainties into the NMT training by using soft-masked embedding and weighted loss. Extensive experiments on Japanese↔Chinese translation show that our proposed methods substantially outperform the strong baselines in terms of BLEU scores, and verify the effectiveness of modeling data uncertainty in NMT. Copyright © 2025 The Institute of Electronics, Information and Communication Engineers.

关键词： Neural machine translation

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EFFICIENT MODELING OF POLARIZED REFLECTION SPECTRA IN METASURFACES USING DEEP LEARNING FRAMEWORKS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2025年第1期87卷 189-198页

作者： Ilie, Alexandra Mănăilă-Maximean, Doina Dănilă, Octavian Faculty of Engineering in Foreign Languages National University of Science and Technology POLITEHNICA of Bucharest Romania Dept. of Physics National University of Science and Technology POLITEHNICA of Bucharest Romania Academy of Romanian Scientists Romania Faculty of Applied Sciences National University of Science and Technology POLITEHNICA of Bucharest Romania

Modeling the electromagnetic responses of metasurfaces, advanced materials engineered to manipulate electromagnetic waves, remains computationally intensive, particularly for complex geometries such as polygonal and ringlike designs. This study explores the potential of frequency-domain prediction, followed by spectral transformation, as a viable approach for capturing x-and y-polarized reflection spectra of metasurfaces. To this end, a deep learning framework is developed, combining Variational Autoencoders (VAEs) and Convolutional Neural Networks (CNNs). The VAE effectively encodes spectral features in a low-dimensional latent space, while the CNN utilizes residual connections to directly map metasurface patterns to their spectral responses. By integrating frequency-domain representations with inverse Fourier transforms, the framework ensures compatibility with traditional time-domain data while maintaining computational efficiency. The proposed models achieve high predictive accuracy, with the VAE outperforming the CNN across multiple error metrics. This dual focus on methodological development and performance evaluation demonstrates the feasibility and advantages of integrating machine learning for rapid and precise metasurface analysis and design. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Inverse problems

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IALS: Innovative Approach for Lung Segmentation Applying Artificial Intelligence and Deep Learning

IALS: Innovative Approach for Lung Segmentation Applying Art...

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2025 International Conference on Computer, Electrical and Communication engineering, ICCECE 2025

作者： Hossain, Mohammad Alamgir Shahi, Fazal Imam Husain, Sadia Suliman, Abdelrazig Kamal, Mohammad Shahid Ahmad, Yasir Talukdar, Mohammad Mazedul Huq Martin, R. John Jazan University College of Engineering & Computer Science Department of computer Science Jazan Saudi Arabia Jazan University ELearning Center Jazan Saudi Arabia University of Bisha Faculty of Computers and Information Technology Department of Information Technology Saudi Arabia Jazan University College of Arts and Humanities Department of Foreign Languages Jazan Saudi Arabia

ISBN: (纸本)9798331513894

The automated segmentation of lungs within chest CT scans remains crucial for many medical applications that require disease diagnosis and treatment design. The presented deep incremental learning (DIL) system addresses fundamental limitations that arise during lung segmentation processes. The exceptional segmentation outcomes result from the neural network structure which includes masked RCNN+UNet for tissue segmentation and GAN+VARMA for classification. Medical literature identifies lung tissue structures as difficult to study because they present irregular forms and complex structures. The task of obtaining precise segmentation proves very challenging. The application of masked RCNN+UNet enables shape control and improves segmentation precision of the lung system. The DIL function helps maintain improved features within segmented images. The applied framework enables improved performance through DSC and MAE and JI metrics evaluation. Experimental evidence shows that the new framework achieves superior performance compared to current top-ranking methods for lung segmentation. The proposed framework exhibits excellent precision and detection efficiency with a DSC value of 0.96 and JI value of 0.93 and a low MAE © 2025 IEEE.

关键词： Medical applications

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Investigation of Breast Tumor Size Effects for Microwave Breast Imaging with Ultra-Wideband Microstrip Antenna

Investigation of Breast Tumor Size Effects for Microwave Bre...

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IEEE MTT-S International Microwave Bio Conference ((IMBIOC)

作者： Huy Bao Bui Minh Hoang Nhut Huynh Huyen Tran Nguyen Thi Congo Tak Shing Ching Trung Nghia Tran Laboratoty of Laser Technology Faculty of Applied Science Ho Chi Minh City University of Technology (HCMUT) VNU-HCM Ho Chi Minh City Vietnam Language and Communication Faculty Of Foreign Languages Ho Chi Minh City University of Foreign Languages and Information Technology (HUFLIT) Ho Chi Minh City Vietnam Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung Taiwan

ISBN: (数字)9798331510473

ISBN: (纸本)9798331510480

Breast cancer is the most common invasive cancer in women and a leading cause of cancer-related deaths worldwide. Tumor size plays a crucial role in diagnosis and staging. This study investigates the impact of tumor size on the $\mathbf{S 2 1}$ transmission signal and specific absorption rate (SAR) distribution in a 3D breast model simulated in COMSOL Multiphysics using an ultra-wideband (UWB) microstrip antenna. The results show that energy concentration increases with tumor size, with larger tumors showing broader SAR distributions. At a frequency of 3.1 GHz, an inverse relationship between SAR and $S 21$ is observed; smaller tumors exhibit lower SAR values and stronger S21 signals, while larger tumors demonstrate higher SAR values and reduced S21 signals.

关键词： Microwave antennas Solid modeling Breast tumors Three-dimensional displays Transmitting antennas Microstrip antennas Specific absorption rate Ultra wideband antennas Microstrip Microwave imaging

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Parsoffensive: Persian Offensive Comments Dataset

Parsoffensive: Persian Offensive Comments Dataset

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International Conference on Web Research (ICWR)

作者： Ali Nazarizadeh Minoo Sayyadpour Omid Ebrahimkhani Amirmasoud Iravani Golnaz Ghannadan Shirazi Mojgan Behravan Department of Computer Engineering Central Tehran Branch Islamic Azad University Tehran Iran Dept. Math and Computer Science Kharazmi University Tehran Iran Department of English Translation Studies Faculty of Persian Literature and Foreign Languages Allameh Tabataba'i University Tehran Iran Department of Linguistics Faculty of Letters and Humanities Ferdowsi University of Mashhad Mashhad Iran Department of Engineering Faculty of Computer Engineering Alzahra University Tehran Iran Department of IT& Technology IU International University of Applied science Tehran Iran

ISBN: (数字)9798331508913

ISBN: (纸本)9798331508920

Offensive language detection is essential for maintaining respectful and inclusive online environments. By implementing detection systems, platforms aim to protect users from harmful content, curb the spread of hate speech, and promote positive interactions within digital communities. Leveraging natural language processing (NLP) techniques, this area has become a key focus in computational linguistics research and development. To address this challenge, we created the ParsOffensive dataset, consisting of approximately 8,433 Persian comments labeled as Offensive or Neutral. These comments were sourced from Instagram and labeled by two linguists. Machine learning models were trained on this dataset, with the ParsBert model achieving 90% accuracy in detecting offensive speech in Persian.

关键词： Accuracy Social networking (online) Computational modeling Prevention and mitigation Hate speech Text categorization Natural language processing Web sites Multimedia communication Research and development

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IALS: Innovative Approach for Lung Segmentation Applying Artificial Intelligence and Deep Learning

IALS: Innovative Approach for Lung Segmentation Applying Art...

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International Conference on Computer, Electrical & Communication engineering (ICCECE)

作者： Mohammad Alamgir Hossain Fazal Imam Shahi Sadia Husain Abdelrazig Suliman Mohammad Shahid Kamal Yasir Ahmad Mohammad Mazedul Huq Talukdar R. John Martin Department of computer Science College of Engineering & Computer Science Jazan University Jazan Saudi Arabia eLearning Center Jazan University Jazan Saudi Arabia Department of Information Technology Faculty of Computers Information Technology University of Bisha Saudi Arabia Department of Foreign Languages College of Arts and Humanities Jazan University Jazan Saudi Arabia

ISBN: (数字)9798331513894

ISBN: (纸本)9798331513900

关键词： Deep learning Image segmentation Shape control Lungs Pulmonary diseases Computed tomography Predictive models Real-time systems Medical diagnostic imaging Electronics packaging

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3D-printed poly-Ε-caprolactone/bioglass and iron disulfide composite materials for hard tissue engineering

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Ceramics International 2025年

作者： Nicoară, Adrian Ionuț Cocoș, Vlad Chircov, Cristina Trușcă, Roxana Doina Hudiță, Ariana Department of Science and Engineering of Oxide Materials and Nanomaterials Faculty of Chemical Engineering and Biotechnologies National University of Science and Technology Politehnica Bucharest 1-7 Gh. Polizu Bucharest011061 Romania National Research Center for Micro and Nanomaterials National University of Science and Technology Politehnica Bucharest 313 Spl. Independenţei Bucharest060042 Romania Faculty of Engineering in Foreign Languages National University of Science and Technology Politehnica Bucharest 313 Spl. Independenţei Bucharest060042 Romania Department of Biochemistry and Molecular Biology University of Bucharest Bucharest050095 Romania

3D printing has transformed scaffold production by enabling customizable, reproducible structures essential for effective bone tissue engineering. Therefore, the aim of this study was to obtain a series of 3D-printed structures consisting of bioglass (BG), whose bioactive properties support direct bonding with bone via a hydroxyapatite layer, and iron disulfide (FeS2), used in traditional Chinese medicine for promoting bone tissue formation, fracture healing, and pain alleviation. The BG 47S6 was obtained through the sol-gel method, while the iron disulfide nanoparticles were produced via a microwave-assisted solvothermal treatment. The powders were characterized through X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FT-IR), Raman spectroscopy, and scanning electron microscopy (SEM). The diffractogram for the 47S6 BG demonstrated the crystallization of SiO2 and C2S phases alongside the typical amorphous phase of BG, while the iron disulfide nanoparticles displayed both pyrite (cubic) and marcasite (orthorhombic) mineral phases. The FT-IR spectrum of 47S6 BG showed characteristic bands corresponding to Si–O–Si and P–O. SEM images revealed irregular particle aggregates with an interconnected structure, while the FeS2 particles appeared agglomerated, suggesting the coalescence of multiple crystallites during synthesis. Subsequently, the powders were mixed in varying proportions (100, 99, 97, and 95 wt% BG) and incorporated into a polycaprolactone (PCL) solution to create pastes for 3D printing. The scaffolds were printed with different parameters to optimize string thickness and porosity, and their morphology, mechanical properties, bioactivity, and biocompatibility were evaluated. Results demonstrated uniform scaffold fabrication and enhanced bioactivity. Notably, the addition of FeS2 improved mechanical strength by preventing scaffold rupture, increased cell viability, and reduced oxidative stress, as confirmed by MTT and LDH assays using the hFOB

关键词： Fourier transform infrared spectroscopy

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Existence and release of fluid inclusions in bornite and its associated quartz and calcite

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International Journal of Minerals,Metallurgy and Materials 2013年第9期20卷 815-822页

作者： Jiu-shuai Deng Shu-ming Wen Dan-dan Wu Jian Liu Xiao-lin Zhang Hai-ying Shen Faculty of Land Resource Engineering Kunming University of Science and Technology Faculty of Foreign Languages & Cultures Kunming University of Science and Technology

The existence and release of fluid inclusions in bornite and its associated minerals, namely, quartz and calcite were investigated and confirmed. The structures, forms, and phases of these large quantities of fluid inclusions were also studied. A mass of fluid inclusions with various sizes, distributions, shapes, and phases exist in bornite and its associated minerals. Their sizes vary from a few micrometers to tens of micrometers, and the forms appear as negative crystals, or elongated, elliptical, and irregular. At room temperature, fluid inclusions were mainly characterized as gas-liquid two- phase. However, small amounts of fluid inclusions with pure gas phase and pure liquid single-phase were also observed in quartz and calcite. These fluid inclusions initially broke during the ore crushing and grinding process and then released into the flotation pulp in the flotation process. The quantitative analysis of fluid inclusions in the solution and the comparisons of mineral dissolution show that the amount of copper and iron released by fluid inclusions in the bornite sample is higher than the amount dissolved by the mineral; fluid inclusions in the associated gangue minerals, quartz, and calcite also make contribution.

关键词： flotation fluid inclusions bornite quartz calcite

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Eye Movement Desensitization and Reprocessing (EMDR)

Eye Movement Desensitization and Reprocessing (EMDR)

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2024 IEEE SmartBlock4Africa, SmartBlock4Africa 2024

作者： Palade, Robert-Eusebiu Goga, Nicolae University Politehnica of Bucharest The Faculty of Engineering in Foreign Languages Romania Department of Engineering in Foreign Languages Romania

ISBN: (纸本)9798350376838

Eye Movement Desensitization and Reprocessing (EMDR) is an effective mental health treatment researched and proven effective mainly for the posttraumatic stress disorder (PTSD), which was developed in 1987 by Dr. Francine Shapiro. She suggests that psychological distress results from unprocessed memories of traumatic or disturbing events. EMDR aims to mitigate distress via an eight-stage process, including patient background, preparation, evaluation, desensitization, reinforcement, somatic attention, closure and reassessment. Despite its origins in trauma therapy, EMDR has been applied to a variety of psychological issues, including anxiety, depression and phobias. This paper provides an overview of the theoretical basis, methodology, application and efficacy of EMDR, including the existing computerized systems created to enhance the EMDR Therapy. Additionally, a web application is presented which consists of a chatbot providing instructions for an individual session of EMDR Therapy. © 2024 IEEE.

关键词： Patient rehabilitation

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