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Evaluate Recent Numerical Methods for Long-Term Simulation to Study the Effect of Different Shapes of Thermal Bridges in Walls

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Defect and Diffusion Forum 2024年 436卷 77-90页

作者： Omle, Issa Kovács, Endre Department of Fluid and Heat Engineering Faculty of Mechanical Engineering and Informatics University of Miskolc Miskolc3515 Hungary Institute of Physics and Electrical Engineering Faculty of Mechanical Engineering and Informatics University of Miskolc Miskolc3515 Hungary

According to previous studies, the most effective, stable, and explicit numerical methods to deal with problems of heat transfer in building walls are the two recently published approaches, which are the modified Dufort-Frankel and leapfrog-hopscotch techniques, which are used in this study to make transient and long-term simulations (three months of the winter season) of 2-D space systems that enable us to execute these simulations with relatively short computational times to evaluate the two most effective versions of these methods. Our solution to a real-world engineering challenge involves investigating thermal bridges of different forms inside multilayer walls of buildings exposed to environmental factors specific to Hungary's climate, such as the outside temperature and sun radiation, to improve energy efficiency. The distributions of temperatures and the total heat loss (across the walls) are calculated for all cases (three layers without a thermal bridge three layers with thermal bridges in straight, bent, and L-shaped shapes). © 2024 Trans Tech Publications Ltd, All Rights Reserved.

关键词： Walls (structural partitions)

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Daytime and night-time patterns in PM2.5 concentrations over Palembang City of Indonesia using MERRA-2 reanalysis data

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International Journal of Environmental Studies 2024年第4期81卷 1684-1697页

作者： Rendana, Muhammad Bahrin, David Dahlan, Muhammad Hatta Fitria, Syarifa Wardhani, Puteri Kusuma Department of Chemical Engineering Faculty of Engineering Universitas Sriwijaya Indralaya Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Sriwijaya Indralaya Indonesia Department of Civil Engineering Faculty of Engineering Universitas Sriwijaya Indralaya Indonesia

Palembang has sustained heavy haze pollution events that are related to decrease public health quality. Because ground-based PM2.5 observation in the city has some limitations, such as spatial and temporal coverages. Thus, in this study, we applied the potential of using the surface mass concentration PM2.5 data acquired by the MERRA-2 satellite to predict daytime and night-time PM2.5 levels during heavy haze events in Palembang City. Results of the study revealed that the highest PM2.5 level was about 160 µg/m3 at 02:00 (night-time), while the lowest PM2.5 level was about 50 µg/m3 at 14:00 (daytime). Spatiotemporal variation of PM2.5 over the study area showed that more than half of the area showed PM2.5 above 90 µg/m3 at night. Stable wind conditions (2 m/s) and air temperature (29°C), and relative humidity (74%) in the study area have contributed to particulate matter accumulation. The study concluded that PM2.5 acquired by the MERRA-2 satellite could provide a new reliable source for assessing severe air pollution events. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Geographic information systems

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Semi-supervised learning for on-street parking violation prediction using graph convolutional networks

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Neural Computing and Applications 2024年第31期36卷 19643-19652页

作者： Karantaglis, Nikolaos Passalis, Nikolaos Tefas, Anastasios Group AIIA Lab Department of Informatics Faculty of Science Aristotle University of Thessaloniki Thessaloniki Greece Department of Chemical Engineering Faculty of Engineering Aristotle University of Thessaloniki Thessaloniki Greece

Controlled parking systems in cities provide designated parking zones and allow citizens to easily find parking spaces increasing comfort and potentially reducing traffic and pollution. However, illegally occupied parking spaces can negatively affect the accuracy of these systems, diminishing their benefits. This work presents a semi-supervised deep learning approach for fine-grained parking violation rate prediction using graph neural networks, which can capture both the spatial and temporal dynamics of parking systems and driver behavior, providing a valuable tool for controlled parking systems. The proposed method addresses several challenges faced in this task, including the need to appropriately construct temporal graph-based training datasets and design a model that can handle missing values. Additionally, the method includes a novel semi-supervised data augmentation and smoothing technique to mitigate the effect of the small amount of annotated data and/or missing data in the training dataset. The proposed method was evaluated using a large-scale dataset from Thessaloniki’s on-street public parking system and found to significantly improve the accuracy of parking violation prediction compared to state-of-the-art approaches. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Forecasting

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Double-crossed Bowtie Antenna-coupled Carbon Nanotube Microbolometer with Meander Structures at 1THz

Double-crossed Bowtie Antenna-coupled Carbon Nanotube Microb...

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2024 International Symposium on Antennas and Propagation, ISAP 2024

作者： Hasiholan, Matthew Gabriel Pangesti Aji, Arie Apriono, Catur Rahardjo, Eko Tjipto Department of Electrical Engineering Faculty of Engineering Universitas Indonesia Indonesia Department of Electrical Engineering Faculty of Engineering and Informatics Universitas Dian Nusantara Indonesia

ISBN: (纸本)9798350364774

A high reception of THz waves is important in the design of an antenna-coupled microbolometer, which is indicated by the ability to detect THz waves effectively from all directions. In this study, we implement the meander line structure in a carbon nanotube (CNT) based bolometer coupled with a double-crossed bowtie antenna. The structure is designed on a SiO2 substrate with an additional metal reflector at the bottom. The simulation results reveal the potential high responsivity of 281.5 kV/W and could effectively minimize the NEP down to 0.0145 pW/Hz1/2. These results demonstrate the prospect of a meander line bolometer structure to enhance THz wave absorption with great potential in the application of real-time imaging. © 2024 IEEE.

关键词： Terahertz waves

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Thermal Analysis of a Simplified Railway Brake Model with Numerical Simulation

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Periodica Polytechnica Transportation engineering 2025年第1期53卷 1-6页

作者： Bolló, Betti Sarka, Ferenc Voith, Katalin Felhő, Csaba Institute of Energy Engineering and Chemical Machinery Faculty of Mechanical Engineering and Informatics University of Miskolc Egyetemváros MiskolcH-3515 Hungary Institute of Machine and Product Design Faculty of Mechanical Engineering and Informatics University of Miskolc Egyetemváros MiskolcH-3515 Hungary Institute of Manufacturing Science Faculty of Mechanical Engineering and Informatics University of Miskolc Egyetemváros MiskolcH-3515 Hungary

The braking system is the most important safety device in all vehicles. When braking, the kinetic energy of the vehicle is converted into thermal energy. The use of friction brakes can cause problems in the long term, as the brake can heat up, reducing its coefficient of friction. Heating and cooling have a harmful effect on all frictional elements, causing material fatigue. As a result of the negative effects, the hot brake cannot reduce the velocity of the vehicle at the correct rate. In this paper, the propagation of frictional heat is analysed in a test specimen made of cast iron material using different numerical simulations. The computational results are validated with the results obtained during measurement. With proper validation, the brake discs are able to be modelled at different designs and materials without having to manufacture a test specimen for each case. In the study, it is important to point physical quantities to carry out the simulation. © 2025 Budapest University of Technology and Economics. All rights reserved.

关键词： Brakes

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Motion Detection Methods Applied on RGB-D Images for Vehicle Classification on the Edge Computing

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IEEE Internet of Things Journal 2025年第12期12卷 19631-19645页

作者： Micko, Kristian Papcun, Peter Technical University in Košice Faculty of Electrical Engineering and Informatics Department of Cybernetics and Artificial Intelligence Košice Slovakia

Intelligent Transportation Systems rely on data processing methods in real-time conditions. There are many methods to process the data. However, the progress of hardware computational power forces us to reassess the effectiveness of some methods. The first idea for discussion is whether cloud or fog computing is necessary to process Computer Vision methods in real-time conditions. The second idea for discussion is whether a depth map gained from the 2D image monocular estimation is suitable as an extra feature to process. Another scientific question is the categorization of the vehicles based on 3D data by extracted volume or height features. This approach could be useful for ToF camera output. This study simulates the output of a ToF camera with a resolution higher than VGA via the monocular depth map estimation with the Convolutional Neural Network model MiDaS. This article proposes the computational architectures for data processing between SBCs with various computational power. Data processing includes obtaining, feature extraction, and classification via various methods. These methods are image loading, background subtraction, shadow removal, monocular depth estimation, pointcloud calculation, 3D convex hull, and volume thresholding. Volume thresholding is a reliable approach for categorization into light and heavy vehicles. Background subtractors connected with K-Means are reliable for vehicle detection without shadows. © 2014 IEEE.

关键词： Fog computing

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Humidification Degree Effect under Rain of Inclined Silicone Insulation on its Electric Performance

Periodica polytechnica Electrical engineering and computer s...

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Periodica polytechnica electrical engineering and computer science 2024年第1期68卷 94-106页

作者： Slimani, Samia Medjdoub, Abdellah Kornhuber, Stefan Laboratory of Electrical Engineering Faculty of Technology University of Bejaia Bejaia06000 Algeria Faculty of Electrical Engineering and Informatics University of Applied Sciences Zittau/Görlitz Theodor-Koerner-Allee 16 Zittau02763 Germany

This investigation is focused on the effect of inclination angle with respect to the horizontal of a hydrophobic silicone insulation, on the rate of its creepage distance's wetting by natural rain. The constellation of rainwater drops obtained on the de-energized site is then reproduced in the laboratory, to quantify the effect of their volume on the humidification intensity of the inclined insulation's creepage distance, and therefore its electrical performance under different alternating voltage levels. For this purpose, two different experimental devices allowing the variation of the insulation's inclination angle were set-up. The first one is dedicated to the on-site display of silicone samples in natural rain. The second one allows the study of the applied voltage's effect on the wetting degree of the insulation's surface. All the performed tests were supported by camera visualization. On-site measurement results show a decline in the length of the creepage distance of the natural rain-wetted insulation with increasing its inclination angle. Laboratory results also show a decrease in the size of the insulation's wet surface with increasing its inclination angle. These two characteristics reveal two different intervals of critical inclination angles of the insulation, unfavorable and favorable, for the dimensioning of the insulators' sheds corresponding respectively to their minimum and maximum electrical performance. © 2024 Budapest University of Technology and Economics. All rights reserved.

关键词： Drops

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ELCD-NSC2: a novel early lung cancer detection and non-small cell classification framework

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Neural Computing and Applications 2024年第24期36卷 15149-15164页

作者： Helaly, Hadeer A. Badawy, Mahmoud El-Gendy, Eman M. Haikal, Amira Y. Electrical Engineering Department Faculty of Engineering Damietta University Damietta Egypt Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt Department of Computer Science and Informatics Taibah University Medina Saudi Arabia

The survival rate of lung cancer relies significantly on how far the disease has spread when it is detected, how it reacts to the treatment, the patient’s overall health, and other factors. Therefore, the earlier the lung cancer diagnosis, the higher the survival rate. For radiologists, recognizing malignant lung nodules from computed tomography (CT) scans is a challenging and time-consuming process. As a result, computer-aided diagnosis (CAD) systems have been suggested to alleviate these burdens. Deep-learning approaches have demonstrated remarkable results in recent years, surpassing traditional methods in different fields. Researchers are currently experimenting with several deep-learning strategies to increase the effectiveness of CAD systems in lung cancer detection with CT. This work proposes a deep-learning framework for detecting and diagnosing lung cancer. The proposed framework used recent deep-learning techniques in all its layers. The autoencoder technique structure is tuned and used in the preprocessing stage to denoise and reconstruct the medical lung cancer dataset. Besides, it depends on the transfer learning pre-trained models to make multi-classification among different lung cancer cases such as benign, adenocarcinoma, and squamous cell carcinoma. The proposed model provides high performance while recognizing and differentiating between two types of datasets, including biopsy and CT scans. The Cancer Imaging Archive and Kaggle datasets are utilized to train and test the proposed model. The empirical results show that the proposed framework performs well according to various performance metrics. According to accuracy, precision, recall, F1-score, and AUC metrics, it achieves 99.60, 99.61, 99.62, 99.70, and 99.75%, respectively. Also, it depicts 0.0028, 0.0026, and 0.0507 in mean absolute error, mean squared error, and root mean square error metrics. Furthermore, it helps physicians effectively diagnose lung cancer in its early stages and allows spe

关键词： Image classification

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Modeling and Simulation of the Variation of the Thermal Flux Yielded by a Medium Temperature Radiant Panel Using Matlab-Simulink 16

Modeling and Simulation of the Variation of the Thermal Flux...

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16th International Conference on Applied and Theoretical Electricity, ICATE 2024

作者： Dinu, Radu Cristian Stan Ivan, Felicia Elena Duinea, Adelaida Mihaela Ravigan, Florin Faculty of Electrical Engineering Department of Electrical Energy and Aerospace Engineering Craiova Romania Faculty of Electrical Engineering Department of Electromechanics Environment and Applied Informatics Craiova Romania

ISBN: (纸本)9798350388107

Nowadays, the issue of efficient heating of enclosed spaces where people carry out different activities has become a priority. This means, on the one hand, using the cheapest and least polluting thermal energy and, on the other hand, using high-performance energy equipment that transmits heat energy as efficiently as possible from the heat carrier (thermal agent) to the air inside the space to be heated. One such heating system is medium-Temperature radiant panel heating using thermal agents. In this paper, starting from a specific construction type of a radiant panel, a study is carried out, using Matlab-Simulink, on the variation of the heat flux transmitted by a medium temperature radiant panel using thermal agent at different temperatures. The modelling algorithm transposed into the simulation scheme in Matlab-Simulink allows a quick and relevant analysis of the behaviour of such a decentralised heating system when operating in rooms with different thermal regimes. © 2024 IEEE.

关键词： Simulink

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A Recommendation System for Double Track Program Skill Selection Using the Analytic Hierarchy Process (AHP) 10

A Recommendation System for Double Track Program Skill Selec...

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10th IEEE Information Technology International Seminar, ITIS 2024

作者： Bughowi, Mohamad Kholid Sunaryono, Dwi Baskoro, Fajar Faculty of Intelligent Electrical and Informatics Technology Department of Informatics Engineering Surabaya Indonesia

ISBN: (纸本)9798331521295

The Double Track Program prepares high school students for careers or entrepreneurship through skills training, aiming to reduce post-graduation unemployment in East Java. It offers seven skill areas: multimedia, culinary arts, fashion design, beauty treatment, electrical engineering, electrical technology, and light vehicle engineering. Students choose one skill area for a year. However, mismatched expectations can lead to wasted time, poor outcomes, and frustration. To address this, a web-based recommendation system was developed to suggest skill areas based on criteria such as job availability, salary, interests, facilities, and entrepreneurial opportunities. The system employs the Analytic Hierarchy Process (AHP) method to support decision-making. It is implemented as a website using TypeScript, Go, the *** framework, and PostgreSQL for data storage. Testing with 77 eleventh-grade students from Dharma Wanita Surabaya High School showed that the top three recommendations achieved an average accuracy of 77.3036%, while the top five reached 77.5510%. Overall, the system demonstrated an average accuracy of 78.4521%, proving effective in guiding students toward skill areas that align with their goals. © 2024 IEEE.

关键词： Decision making

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