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p-CuGaO2/β-Ga2O3 interfaces: A high-throughput approach for interface prediction and generation for power device applications

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Materials Today Advances 2025年 26卷

作者： Prasad, Chowdam Venkata Park, Jang Hyeok Hoai Ta, Qui Thanh Kim, Kyong Jae Jeon, Ho Jung Mir, Muzaffar Ali Raza, Mohsin Tri, Nguyen Ngoc Kim, Honggyun Labed, Madani Rim, You Seung Department of Semiconductor Systems Engineering and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of Institute of Semiconductor and System IC Sejong University Seoul05006 Korea Republic of Department of Semiconductor Systems Engineering Sejong University Seoul05006 Korea Republic of Institute of Advanced Technology Vietnam Academy of Science and Technology 1A TL29 Street Thanh Loc Ward District 12 Ho Chi Minh City700000 Viet Nam Lab of Computational Chemistry and Modelling Faculty of Natural Sciences Quy Nhon University Quy Nhon City55100 Viet Nam

This study integrates a p-type copper gallium oxide (p-CuGaO2) interlayer to enhance the performance of β-Ga2O3-based power devices, addressing challenges in achieving reliable p-type doping. The p-CuGaO2 interlayer is expected to improve breakdown voltage (BV) and reduce leakage current, increasing device efficiency and reliability under high-temperature conditions. The heterojunction (HJ) system of β-Ga2O3 and p-CuGaO2 is investigated using density functional theory (DFT) via the Vienna Ab initio Simulation Package (VASP) and experimental methods, focusing on the β-Ga2O3 (001)/p-CuGaO2 (006) interface. Binding energy, electron localization, charge density difference, and electrostatic potential drop are analyzed, identifying Configuration-1 as the optimal configuration due to its high binding energy and favorable structural properties. Annealing temperature impacts the microstructure, stoichiometry, optical, electrical, and transport properties of p-CuGaO2/β-Ga2O3 HJs. Electrical measurements reveal reduced turn-on voltage (Von), on-resistance (Ron), and leakage currents, with the highest BV of 1.62 kV achieved at 800 °C compared to Pt/β-Ga2O3 Schottky barrier diode (SBD). The interface state density (NSS) is evaluated using the high-low frequency approach. Silvaco TCAD simulations explore breakdown mechanisms, demonstrating the potential of p-CuGaO2 for β-Ga2O3 HJ power devices. These findings support the development and manufacture of robust β-Ga2O3 HJ power devices. © 2025 The Authors

关键词： Heterojunctions

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Efficient Deep Learning Framework for Fire Detection in Complex Surveillance Environment

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computer Systems science & engineering 2023年第7期46卷 749-764页

作者： Naqqash Dilshad Taimoor Khan JaeSeung Song Department of Convergence Engineering for Intelligent Drone Seoul05006Korea Department of Computer Science Islamia College PeshawarPeshawar25120Pakistan

To prevent economic,social,and ecological damage,fire detection and management at an early stage are significant yet *** computationally complex networks have been developed,attention has been largely focused on improving accuracy,rather than focusing on real-time fire ***,in this study,the authors present an efficient fire detection framework termed E-FireNet for real-time detection in a complex surveillance *** proposed model architecture is inspired by the VGG16 network,with significant modifications including the entire removal of Block-5 and tweaking of the convolutional layers of *** results in higher performance with a reduced number of parameters and inference ***,smaller convolutional kernels are utilized,which are particularly designed to obtain the optimal details from input images,with numerous channels to assist in feature *** E-FireNet,three steps are involved:preprocessing of collected data,detection of fires using the proposed technique,and,if there is a fire,alarms are generated and transmitted to law enforcement,healthcare,and management ***,E-FireNet achieves 0.98 accuracy,1 precision,0.99 recall,and 0.99 F1-score.A comprehensive investigation of various Convolutional Neural Network(CNN)models is conducted using the newly created Fire Surveillance SV-Fire *** empirical results and comparison of numerous parameters establish that the proposed model shows convincing performance in terms of accuracy,model size,and execution time.

关键词： Deep learning drone embedded vision emergency monitoring fire classification fire detection IoT search and rescue

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Deep Learning Based Underground Sewer Defect Classification Using a Modified RegNet

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computers, Materials & Continua 2023年第6期75卷 5451-5469页

作者： Yu Chen Sagar A.S.M.Sharifuzzaman Hangxiang Wang Yanfen Li L.Minh Dang Hyoung-Kyu Song Hyeonjoon Moon Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Intelligent Mechatronics Engineering Sejong UniversitySeoul05006Korea Department of Information of Communication Engineering and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

The sewer system plays an important role in protecting rainfall and treating urban *** to the harsh internal environment and complex structure of the sewer,it is difficult to monitor the sewer *** are developing different methods,such as the Internet of Things and Artificial Intelligence,to monitor and detect the faults in the sewer *** learning is a promising artificial intelligence technology that can effectively identify and classify different sewer system ***,the existing deep learning based solution does not provide high accuracy prediction and the defect class considered for classification is very small,which can affect the robustness of the model in the constraint *** a result,this paper proposes a sewer condition monitoring framework based on deep learning,which can effectively detect and evaluate defects in sewer pipelines with high *** also introduce a large dataset of sewer defects with 20 different defect classes found in the sewer *** study modified the original RegNet model by modifying the squeeze excitation(SE)block and adding the dropout layer and Leaky Rectified Linear Units(LeakyReLU)activation function in the Block structure of RegNet *** study explored different deep learning methods such as RegNet,ResNet50,very deep convolutional networks(VGG),and GoogleNet to train on the sewer defect *** experimental results indicate that the proposed system framework based on the modified-RegNet(RegNet+)model achieves the highest accuracy of 99.5 compared with the commonly used deep learning *** proposed model provides a robust deep learning model that can effectively classify 20 different sewer defects and be utilized in real-world sewer condition monitoring applications.

关键词： Deep learning defect classification underground sewer computer vision convolutional neural network RegNet

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Improved Hybrid Precoding Technique with Low-Resolution for MIMO-OFDM System

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computers, Materials & Continua 2021年第8期68卷 2205-2220页

作者： Seulgi Lee Ji-Sung Jung Young-Hwan You Hyoung-Kyu Song Department of Information and Communication Engineering and Convergence for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering Sejong UniversitySeoul05006Korea

This paper proposes an improved hybrid beamforming system based on multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)*** proposed beamforming system improves energy efficiency compared to the conventional hybrid beamforming *** sub-connected and full-connected structure are considered to apply the proposed *** the conventional hybrid beamforming,the usage of radio frequency(RF)chains and phase shifter(PS)gives high power and hardware *** this paper,the phase over sampling(POS)with switches(SW)is used in hybrid beamforming system to improve the energy *** POS-SW structure samples the value of analog beamformer to make lower resolution than conventional *** number of output data in POS is decided by the resolution of POS *** limited number of POS decides the resolution of antenna array and the values of POSs are designed from maximum and minimum phase angle antenna *** efficiency without the phase shifter is high although channel capacity is nearly similar with conventional ***,the amplifier with POS-SW system is proposed to improve the BER *** to the data bits,the output signals of POS are *** system with 2,3 and 4 bits is simulated to prove the proposed *** order to overcome the loss of low-resolution system,the amplifier with POS-SW system using channel information is *** average sum-rate of 4 bits system shows the similar performance with the conventional hybrid beamforming *** structure can play an important role by increasing the energy efficiency of the wireless communication system that many antennas are *** is shown that the BER,average sum rate and energy efficiency of the proposed scheme are more improved than the conventional hybrid beamforming system.

关键词： Hybrid beamforming MIMO-OFDM system analog precoding POS-SW

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Weighted Gauss-Seidel Precoder for Downlink Massive MIMO Systems

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computers, Materials & Continua 2021年第5期67卷 1729-1745页

作者： Jun-Yong Jang Won-Seok Lee Jae-Hyun Ro Young-Hawn You Hyoung-Kyu Song Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering Sejong UniversitySeoul05006Korea

In this paper,a novel precoding scheme based on the Gauss-Seidel(GS)method is proposed for downlink massive multiple-input multiple-output(MIMO)*** GS method iteratively approximates the matrix inversion and reduces the overall complexity of the precoding *** addition,the GS method shows a fast convergence rate to the Zero-forcing(ZF)method that requires an exact invertible ***,to satisfy demanded error performance and converge to the error performance of the ZF method in the practical condition such as spatially correlated channels,more iterations are necessary for the GS method and increase the overall *** efficient approximation with fewer iterations,this paper proposes a weighted GS(WGS)method to improve the approximation accuracy of the GS *** optimal weights that accelerate the convergence rate by improved accuracy are computed by the least square(LS)*** the computation of weights,the different weights are applied for each iteration of the GS *** addition,an efficient method of weight computation is proposed to reduce the complexity of the LS *** simulation results show that bit error rate(BER)performance for the proposed scheme with fewer iterations is better than the GS method in spatially correlated channels.

关键词： Massive MIMO GS matrix inversion complexity weight

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An approach for measuring spatial similarity among COVID-19 epicenters

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Geo-Spatial Information science 2023年第3期26卷 496-513页

作者： Neda Kaffash Charandabi Abolghasem Sadeghi-Niaraki Soo-Mi Choi Tamer Abuhmed Geomatic Department Marand Technical FacultyUniversity of TabrizTabrizIran Department of Computer Science and Engineering and Convergence Engineering for Intelligent Drone Sejong UniversitySeoulSouth Korea College of Computing and Informatics Sungkyunkwan UniversitySuwonSouth Korea

Most countries and territories worldwide are affected by coronavirus disease 2019(COVID-19),and some cities have become known as epicenters owing to high *** of the changeable and unknown nature of the virus,managers of different cities could learn from the experiences of cities that have been successful in controlling COVID-19 instead of wasting time exploring different *** would be even more beneficial if they analyzed the experiences of similar *** similarity of such cities could be examined within a geographic information system based on various *** study investigated the similarities among eight cities-Wuhan,Tehran,Bergamo,Madrid,Paris,Daegu,New York,and Berlin-in terms of the COVID-19 situation(target)in these locations based on proximity factors,weather,and demographic ***,the factor and target layers were prepared,and then similar cities were identified using a similarity model and different distance *** results were aggregated using the Copeland method because of the different outcomes for each *** most similar city was identified for each selected city,and its similarity level was determined based on these *** results suggested the following pairs of similar cities:Wuhan-Berlin,Tehran-Berlin,Daegu-Wuhan,Bergamo-Madrid,Paris-Madrid,and New York-Paris based on COVID-19 related data up to 15 April 2020(target T1),and Daegu-Wuhan,Tehran-Madrid,Bergamo-Paris,Berlin-Paris,and New York-Madrid up to 8 December 2021(target T2)with a minimum and maximum similarity rate of 82.85%and 92.36%,*** similar cities,the most similar factors among the proximity criteria are the distance from bus and metro stations;among weather,the criteria are humidity and pressure;and among demographics,the criteria are male and female population ratios,literacy ratio,and death ratio from asthma and cancer,with a minimum and maximum difference of 0%and 64.94%,*** addition,according to the rando

关键词： COVID-19 GIS spatial similarity environmental factors demographic factors

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Adaptive Emulation Framework for Multi-Architecture IoT Firmware Testing

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computers, Materials & Continua 2023年第5期75卷 3291-3315页

作者： Jihyeon Yu Juhwan Kim Youngwoo Lee Fayozbek Rustamov Joobeom Yun Department of Computer and Information Security and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer and Information Security Sejong UniversitySeoul05006Korea

Internet of things(IoT)devices are being increasingly used in numerous ***,the low priority on security and various IoT types have made these devices vulnerable to *** prevent this,recent studies have analyzed firmware in an emulation environment that does not require actual devices and is efficient for repeated ***,these studies focused only on major firmware architectures and rarely considered exotic *** addition,because of the diversity of firmware,the emulation success rate is not high in terms of large-scale *** this study,we propose the adaptive emulation framework for multi-architecture(AEMA).In the field of automated emulation frameworks for IoT firmware testing,AEMA considers the following issues:(1)limited compatibility for exotic firmware architectures,(2)emulation instability when configuring an automated environment,and(3)shallow testing range resulting from structured *** tackle these problems,AEMAcan emulate not onlymajor firmware architectures but also exotic firmware architectures not previously considered,such as Xtensa,ColdFire,and reduced instruction set computer(RISC)version five,by implementing a minority ***,we applied the emulation arbitration technique and input keyword extraction technique for emulation stability and efficient test case *** compared AEMA with other existing frameworks in terms of emulation success rates and fuzz *** a result,AEMA succeeded in emulating 864 out of 1,083 overall experimental firmware and detected vulnerabilities at least twice as fast as the experimental ***,AEMAfound a 0-day vulnerability in realworld IoT devices within 24 h.

关键词： Internet of things(IoT) emulation framework firmware fuzzing concolic execution vulnerability

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Visual Analytics System of Comprehensive Data Quality Improvement for Machine Learning using Data- and Process-driven Strategies

Visual Analytics System of Comprehensive Data Quality Improv...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Hong, Hyein Yoo, Sangbong Jin, Yejin Yoon, Chanyoung Yim, Soobin Choi, Seokhwan Jang, Yun Sejong University Department of Computer Engineering and Convergence Engineering for Intelligent Drone Seoul Korea Republic of Sejong University Department of Computer Engineering Seoul Korea Republic of

ISBN: (纸本)9781665480451

Machine learning (ML) models are used to mine inconspicuous information in big data. The model and data quality influence the performance of a ML model. However, modifying the ML model while measuring performance is impractical, and low-quality data causes biased model training. Therefore, improving the data quality is essential. Visual analytics systems supporting DQI (Data Quality Improvement) have been proposed in the past. However, in the studies, it is difficult for users to assess comprehensive data quality improvement methods for machine learning and to determine an appropriate data quality improvement process. In this paper, we propose a novel visual analytics system for managing data quality used in machine learning models. © 2022 IEEE.

关键词： Machine learning

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MV-Honeypot:Security Threat Analysis by Deploying Avatar as a Honeypot in COTS Metaverse Platforms

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computer Modeling in engineering & sciences 2024年第10期141卷 655-669页

作者： Arpita Dinesh Sarang Mohsen Ali Alawami Ki-Woong Park SysCore Lab.(Convergence Engineering for Intelligent Drone) Sejong UniversitySeoul05006Republic of Korea Division of Computer Engineering Hankuk University of Foreign StudiesYongin-si17035Republic of Korea Department of Information Security Sejong UniversitySeoul05006Republic of Korea

Nowadays,theuse of Avatars that are unique digital depictions has increased by users to access Metaverse—a virtual reality environment—through multiple devices and for various ***,the Avatar and Metaverse are being developed with a new theory,application,and design,necessitating the association of more personal data and devices of targeted users every *** Avatar and Metaverse technology explosion raises privacy and security concerns,leading to cyber ***-Honeypot,or Metaverse-Honeypot,as a commercial off-the-shelf solution that can counter these cyber attack-causing vulnerabilities,should be *** fill this gap,we study user’s engagements with Avatars in Metaverse,analyze possible security vulnerabilities,and create a model named Simplified Avatar Relationship Association with Non-linear Gradient(SARANG)that draws the full diagram of infrastructure components and data flow through accessing Metaverse in this *** also determine the most significant threat for each component’s cyberattacks that will affect user data and *** a result,the commercial off-the-shelf(COTS)of the MV-Honeypot must be established.

关键词： Avatar metaverse cybersecurity cloud computing internet of things artificial intelligence security analysis

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Robust Counting in Overcrowded Scenes Using Batch-Free Normalized Deep ConvNet

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computer Systems science & engineering 2023年第9期46卷 2741-2754页

作者： Sana Zahir Rafi Ullah Khan Mohib Ullah Muhammad Ishaq Naqqash Dilshad Amin Ullah Mi Young Lee Institute of Computer Sciences and Information Technology(ICS/IT) The University of AgriculturePeshawar25130Khyber PakhtunkhwaPakistan Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Collaborative Robotics and Intelligent Systems(CoRIS)Institute Oregon State UniversityORUSA Department of Software Sejong UniversitySeoul05006Korea

The analysis of overcrowded areas is essential for flow monitoring,assembly control,and *** counting’s primary goal is to calculate the population in a given region,which requires real-time analysis of congested scenes for prompt reactionary *** crowd is always unexpected,and the benchmarked available datasets have a lot of variation,which limits the trained models’performance on unseen test *** this paper,we proposed an end-to-end deep neural network that takes an input image and generates a density map of a crowd *** proposed model consists of encoder and decoder networks comprising batch-free normalization layers known as evolving normalization(EvoNorm).This allows our network to be generalized for unseen data because EvoNorm is not using statistics from the training *** decoder network uses dilated 2D convolutional layers to provide large receptive fields and fewer parameters,which enables real-time processing and solves the density drift problem due to its large receptive *** benchmark datasets are used in this study to assess the proposed model,resulting in the conclusion that it outperforms conventional models.

关键词： Artificial intelligence deep learning crowd counting scene understanding

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