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Numerical Predictions of Laminar Forced Convection Heat Transfer with and without Buoyancy Effects from an Isothermal Horizontal Flat Plate to Supercritical Nitrogen

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Frontiers in Heat and Mass Transfer 2024年第3期22卷 889-917页

作者： K.S.Rajendra Prasad Sathya Sai T.R.Seetharam Adithya Garimella Department of Mechanical and Industrial Engineering Manipal Institute of Technology BengaluruManipal Academy of Higher EducationManipal576104India Sustainable Energy Technology Faculty of Electrical EngineeringMathematics and Computer ScienceDelft University of TechnologyDelft2600 AANetherlands Department of Mechanical Engineering PES UniversityBengaluru560085India

Numerical predictions are made for Laminar Forced convection heat transfer with and without buoyancy effects for Supercritical Nitrogen flowing over an isothermal horizontal flat plate with a heated surface facing *** are performed by varying the value ofΔT from5 to 30 K and P_(∞)/P_(cr)ratio from1.1 to *** of all the thermophysical properties of supercritical Nitrogen is *** wall temperatures are chosen in such a way that two values of Tw are less than T∗(T*is the temperature at which the fluid has a maximum value of Cp for the given pressure),one value equal to T∗and two values greater than T∗.Three different values of U∞are used to obtain Re∞range of 3.6×10_(4)to 4.74×10^(5)for forced convection without buoyancy effects and Gr_(∞)/Re^(2)_(∞)range of 0.011 to 3.107 for the case where buoyancy effects are *** different forms of correlations are proposed based on numerical predictions and are compared with actual numerical *** has been found that in all six forms of correlations,the maximum deviations are found to occur in those cases where the pseudocritical temperature TT∗lies between the wall temperature and bulk fluid temperature.

关键词： Supercritical nitrogen laminar flow numerical methods forced convection heat transfer isothermal horizontal surface

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TELEX: Two-Level Learned Index for Rich Queries on Enclave-based Blockchain systems

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IEEE Transactions on Knowledge and Data engineering 2025年第07期37卷 4299-4313页

作者： Wu, Haotian Tang, Yuzhe Shen, Zhaoyan Tao, Jun Lin, Chenhao Peng, Zhe The Hong Kong Polytechnic University Department of Industrial and Systems Engineering Hong Kong Syracuse University Department of Electrical Engineering and Computer Science United States Shandong University School of Computer Science and Technology China Southeast University School of Cyber Science and Engineering China Xi'an Jiaotong University Faculty of Electronic and Information Engineering China The Hong Kong Polytechnic University Shenzhen Research Institute Hong Kong

Blockchain has become a popular paradigm for secure and immutable data storage. Despite its numerous applications across various fields, concerns regarding the user privacy and result integrity during data queries persist. Additionally, the need for rich query functionalities to harness the full potential of blockchain data remains an area ripe for exploration. In order to address these challenges, our paper first utilizes a framework based on the Trusted Execution Environment (TEE) and oblivious RAM technique to achieve both privacy and data integrity. To enhance the query efficiency over the entire blockchain, we then devise a two-level learned indexing methodology named TELEX within the TEE for both integer and string keys. We also propose different query processing algorithms for versatile query types, including exact queries, aggregate queries, Boolean queries, and range queries. By implementing the prototype and conducting extensive evaluation, we demonstrate the feasibility and remarkable improvement in efficiency compared to existing solutions. © 1989-2012 IEEE.

关键词： Query languages

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Design and Implementation of 5G IoT for Retirement Village in Metaverse 5

Design and Implementation of 5G IoT for Retirement Village i...

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5th Research, Invention, and Innovation Congress: Innovative electricals and Electronics, RI2C 2024

作者： Vanichchanunt, Pisit Saengthongkam, Sirapop Waichampa, Natthapong Wuttiananchai, Navy Janthong, Bancha Swatdipisal, Khatathap Sittakul, Vitawat Wuttisittikulkij, Lunchakorn Paripurana, Sukritta King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok College of Industrial Technology Department of Electronic Engineering Technology Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Electrical Engineering Bangkok Thailand

ISBN: (纸本)9798331505998

This paper proposes the use of metaverse in the design, implementation, and pretest of 5G IoT systems for smart cities, in which this paper, a retirement village is selected as a preliminary example for the demonstration. Metaverse not only enables the system design and integration under multidisciplinary considerations including electrical system, solar energy system, 5G IoT system, communication, and automation, to be carried out economically but the system functionalities can also be carefully tested under various scenarios due to less limitation in the virtual world. The developed 5G IoT system for the retirement village monitors electrical power usage, solar power generation and consumption, air pollution, and environmental status. Moreover, the developed system also allows users to directly control lights and CCTV cameras using dashboards. To support various demands of such IoT services, the 5G network slice templates are designed and prepared according to the service requirements. In the system test, the monitoring data is shown on the dashboards to confirm the system connections and functionalities. Besides, wireless CCTV cameras via the developed 5G IoT systems are tested and compared between the virtual video in metaverse and the actual video from the real world. The results of both cases reveal no significant difference in terms of video quality degradation and latency. This shows the benefits and potentials of using metaverse in the design, implementation, and testing especially the system integration. © 2024 IEEE.

关键词： 5G mobile communication systems

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Evaluation of Solar and Lunar Eclipse Impacts on Danish Power System as a Case Study

Evaluation of Solar and Lunar Eclipse Impacts on Danish Powe...

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2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Gharehbagh, Hamed Kheirandish Jalalat, Sajjad Miralizadeh Bayati, Navid Ebel, Thomas University of Tabriz Faculty of Electrical and Computer Engineering Tabriz Iran University of Urmia Departemant of Electrical and Computer Engineering Urmia Iran University of Southern Denmark Centre for Industrial Electronics Sonderborg Denmark

ISBN: (纸本)9798350347432

Power systems stability and reliability are two critical issues that are considered in designing and operational states of the power systems. In addition to the technical failures that can affect the appropriate performance of the power systems, there are several environmental menaces, namely, storms, earthquakes, freezing weather, animal-caused outages, etc. In this paper, the effect of solar and lunar eclipses on the Danish power system has been investigated among the other environmental threats. The power system of Denmark, due to the high penetration of renewable energy sources, is contemplated as a case study. The reports and data depict that despite the often occurrence of an eclipse, these astronomical events' impacts should have been taken more into consideration to maintain stability and improve the reliability of the power system. © 2023 IEEE.

关键词： Solar power generation

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An electrical Energy Conservation for 1200 Lux Illumination Football Stadium Using LED Floodlight 6

An Electrical Energy Conservation for 1200 Lux Illumination ...

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6th International Conference on Power, Energy and Innovations, ICPEI 2024

作者： Thammayarit, Surachai Sarasook, Jassada Srisongkram Industrial Technology College Nakhom phanom University Industrial Robotics and Automatic Systems Nakhon Phanom Thailand Nakhom phanom University Electrical Engineering Faculty of Industrial Technology Nakhon Phanom Thailand

ISBN: (纸本)9798350356779

This paper presents an electrical energy conservation policy for 1200 lux illumination system of football stadium by using LED floodlight instead of metal halide floodlight. The standard stadium illumination accords to Asian Football Confederation Regulation. The stadium is located in Thailand. The standard stadium used for 11 player football. There are 4 galvanized steel poles with 35 meter high installed at four conner of standard. The initial design, 1500 W metal halide were selected. However,1200 W LED floodlight replaced to electrical energy conservation. The 42 luminaires were set on a pole. The characteristics of illumination were demonstrated by DIAlux program simulation. The illumination, uniformity values and electricity unit are considered. For the result, it can find that the LED floodlight can conserve the energy. The result of energy conservation is 181,440 Unit/year or 725,760 Bath. © 2024 IEEE.

关键词： Stadiums

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SubmergeStyleGAN: Synthetic Underwater Data Generation with Style Transfer for Domain Adaptation

SubmergeStyleGAN: Synthetic Underwater Data Generation with ...

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2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023

作者： Fathy, Mohamed E. Mohamed, Samer A. Awad, Mohammed I. Munim, Hossam E. Abd El Ain Shams University Mechatronics Engineering Department Faculty of Engineering Egypt Ain Shams University Computer and Systems Engineering Department Faculty of Engineering Egypt University of Bath Department of Electronic and Electrical Engineering Faculty of Engineering and Design United Kingdom

ISBN: (纸本)9798350382204

Underwater computer vision applications are challenged by limited access to annotated underwater datasets. Additionally, convolutional neural networks (CNNs) trained on in-air datasets do not perform well underwater due to the high domain variance caused by the degradation impact of the water column. This paper proposes an air-to-water dataset generator to create visually plausible underwater scenes out of existing in-air datasets. SubmergeStyleGAN, a generative adversarial network (GAN) designed to model attenuation, backscattering, and absorption, utilizes depth maps to apply range-dependent attenuation style transfer. In this work, the generated attenuated images and their corresponding original pairs are used to train an underwater image enhancement CNN. Real underwater datasets were used to validate the proposed approach by assessing various image quality metrics, including UCIQE, UIQM and CCF, as well as disparity estimation accuracy before and after enhancement. SubmergeStyleGAN exhibits a faster and more robust training procedure compared to existing methods in the literature. © 2023 IEEE.

关键词： Image enhancement

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Time Series Forecasting of XRP Using Machine Learning Algorithms

Time Series Forecasting of XRP Using Machine Learning Algori...

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2023 International Conference on Integration of Computational Intelligent System, ICICIS 2023

作者： Ahmed, Nayeem Rahman, Md. Mahbubur Technische Universität Dresden Faculty of Electrical and Computer Engineering Dresden Germany Buet Dept. of Industrial and Production Engineering Dhaka Bangladesh

ISBN: (纸本)9798350318784

With the advancement of technology, cryptocurrencies are getting prominence as valuable investment assets. Unlike fiat currencies regulated by governments, cryptocurrencies allow for secure anonymous transactions and have a limited quantity in the market due to the mathematical algorithms established by the inventors. Therefore, investors across the globe find cryptocurrencies as a hedge against inflation for their investments. XRP has recently become one of the most popular cryptocurrencies, attracting huge interest from crypto investors and developers all around the world. But, because of its highly volatile nature, it can harm the market investors and users of the currency. In this study, prediction techniques based on machine learning have been proposed to forecast the price of XRP. Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Autoregressive Integrated Moving Average (ARIMA) algorithms are used in this work for the prediction. Nowadays, many financial sectors use machine learning algorithms to forecast their future trends. The closing price data of XRP is taken into a time series format and fitted into the aforementioned models. In the end, a comparative analysis is shown among the algorithms. Evaluation parameters such as MAPE (Mean Absolute Percentage Error), R2 and RMSE (Root Mean Absolute Error) are presented to determine the better one for prediction with better accuracy. © 2023 IEEE.

关键词： Investments

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Development of Antimicrobial Envelope for RFID Card 20

Development of Antimicrobial Envelope for RFID Card

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20th International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2023

作者： Paripurana, Sukritta Kittiamornkul, Navapadol Watcharakitchakorn, Orrathai Keawon, Rapeepan King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand Christian University of Thailand Faculty of Health Sciences Department of Biomedical Engineering Thailand Silpakorn University Faculty of Engineering and Industrial Technology Department of Electrical Engineering Thailand

ISBN: (纸本)9798350310467

This paper proposes the development of an RFID envelope coated with an antimicrobial material that can stop microorganisms' growth while the card is still regularly used. Copper is chosen as the antimicrobial material for coating on an envelope made of polyethylene terephthalate (PET) by using DC sputtering. The antimicrobial ability of the proposed envelope is investigated against Escherichia coli (E. coli). The result shows that the survival time of E. coli on the proposed envelope is decreased compared with the PET envelope without the copper thin film coated on. Besides its antimicrobial quality, copper can let radio frequency pass through. Thus, the effectiveness of electromagnetic wave transmission through the proposed envelope coated with different thickness of a copper thin film is tested. To evaluate the performance of the proposed envelope, three experiments which cover the test of the antimicrobial ability of copper thin film, the resistance of copper thin film, and performance of RF transmission of RFID reader and tag are conducted. The results of the three experiments show that a copper thin film can prevent the microorganisms' growth, the resistance of the copper thin film is decreasing while the thickness of the copper thin film is increasing, and the radio frequency can pass though the proposed envelope. © 2023 IEEE.

关键词： Escherichia coli

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Retinal disorder diagnosis based on hybrid deep learning models

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Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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Development and Investigation of Vision System for a Small-Sized Mobile Humanoid Robot in a Smart Environment

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International Journal of Crowd Science 2025年第1期9卷 29-43页

作者： Abu-Jassar, Amer Tahseen Attar, Hani Amer, Ayman Lyashenko, Vyacheslav Yevsieiev, Vladyslav Solyman, Ahmed Department of Computer Science College of Information Technology Amman Arab University Amman11937 Jordan Faculty of Engineering Zarqa University Zarqa2000 Jordan College of Engineering University of Business and Technology Jeddah21448 Saudi Arabia Department of Media Systems and Technology Kharkiv National University of Radio Electronics Kharkiv61166 Ukraine Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Nişantaşı University Istanbul34398 Turkey

The conducted research aims to develop a computer vision system for a small-sized mobile humanoid robot. The decentralization of the servomotor control and the computer vision systems is investigated based on the hardware solution point of view, moreover, the required software level to achieve an efficient matched design is obtained. A computer vision system using the upgraded tiny-You Only Look Once (YOLO) network model is developed to allow recognizing and identifying objects and making decisions on interacting with them, which is recommended for crowd environment. During the research, a concept of a computer vision system was developed, which describes the interaction between the main elements, on the basis of which hardware modules were selected to implement the task. A structure of information interaction between hardware modules is proposed, and a connection scheme is developed, on the basis of which a model of a computer vision system is assembled for research, with the required algorithmic and software for solving the problem. To ensure the high speed of the computer vision system based on the ESP32-CAM module, the neural network was improved by replacing the Visual Geometry Group 16 (VGG-16) network as the base network for extracting the functions of the Single Shot Detector (SSD) network model with the tiny-YOLO lightweight network model, which made it possible to preserve the multidimensional structure of the network model feature graph, resulting in increasing the detection accuracy, while significantly reducing the amount of calculations generated by the network operation, thereby significantly increasing the detection speed, due to a limited set of objects. Finally, a number of experiments were carried out, both in static and dynamic environments, which showed a high accuracy of identifications. © The author(s) 2025.

关键词： Anthropomorphic robots

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