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DYNAMIC PROPERTIES OF AL-ALLOY FOAM BEAM DAMAGED BY COMPRESSIVE FATIGUE

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Acta Mechanica Solida Sinica 2008年第3期21卷 241-246页

作者： Sung-Gaun kim Ilhyun kim Amkee kim Seung-Joon kim Junhong Park Division of Mechanical and Automotive Engineering Kongju National University 275 Budae-dongCheonan Chungnam 330-717 Korea Department of Mechanical Engineering Hanyang University Seongdong-Gu Seoul 133-791 Korea

The permanent residual strain in aluminum （Al） alloy foams induced by compressive fatigue gradually increases with the increasing number of loading cycles. Consequently, the progressive shortening of Al-alloy foam degrades the dynamic material performance by the failure and ratcheting of multi-cells in the foam. In this paper, the dynamic properties of Al-alloy foams damaged by compressive fatigue were studied. The beam specimens with various residual strains were made by cyclic compression-compression stress. The dynamic bending modulus and loss factor were evaluated by using a beam transfer function method. As a result, the dynamic bending stiffness of Al-alloy foam turned out to be decreased due to damage while the loss factor was improved because of the increasing energy dissipation of such factors as cracked cell walls formed during the shortening process of the foam. The loss factor shows a manifest dependence on the fatigue residual strain.

关键词： Aluminum foam fatigue dynamic stiffness loss factor

Some identities of Bell polynomials

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Science China Mathematics 2015年第10期58卷 2095-2104页

作者： kim Dae San kim Taekyun Department of Mathematics Sogang University Department of Mathematics Kwangwoon University

We investigate Bell polynomials, also called Touchard polynomials or exponential polynomials, by using and without using umbral calculus. We use three different formulas in order to express various known families of polynomials such as Bernoulli polynomials, poly-Bernoulli polynomials, Cauchy polynomials and falling factorials in terms of Bell polynomials and vice versa. In addition, we derive several properties of Bell polynomials along the way.

关键词： Bell-polynomial umbral calculus poly-Bernoulli polynomial higher-order Bernoulli polynomial Cauchy polynomial

Network-Aided Intelligent Traffic Steering in 5G Mobile Networks

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Computers, Materials & Continua 2020年第10期65卷 243-261页

作者： Dae-Young kim Seokhoon kim School of Computer Software Daegu Catholic UniversityGeyongsan38430Korea Department of Computer Software Engineering Soonchunhyang UniversityAsan31538Korea

Recently,the fifth generation(5G)of mobile networks has been deployed and various ranges of mobile services have been *** 5G mobile network supports improved mobile broadband,ultra-low latency and densely deployed massive *** allows multiple radio access technologies and interworks them for services.5G mobile systems employ traffic steering techniques to efficiently use multiple radio access ***,conventional traffic steering techniques do not consider dynamic network conditions *** this paper,we propose a network aided traffic steering technique in 5G mobile network architecture.5G mobile systems monitor network conditions and learn with network *** a machine learning algorithm such as a feed-forward neural network,it recognizes dynamic network conditions and then performs traffic *** proposed scheme controls traffic for multiple radio access according to the ratio of measured ***,it can be expected to improve traffic steering *** performance of the proposed traffic steering scheme is evaluated using extensive computer simulations.

关键词： Mobile network 5G traffic steering machine learning MEC

Effective Denoising Architecture for Handling Multiple Noises

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Computer Systems Science & Engineering 2023年第3期44卷 2667-2682页

作者： Na Hyoun kim Namgyu kim The Graduate School of Business IT of Kookmin University Seoul02707Korea

Object detection,one of the core research topics in computer vision,is extensively used in various industrial *** there have been many studies of daytime images where objects can be easily detected,there is relatively little research on nighttime *** the case of nighttime,various types of noises,such as darkness,haze,and light blur,deteriorate image ***,an appropriate process for removing noise must precede to improve object detection *** there are many studies on removing individual noise,only a few studies handle multiple noises *** this paper,we pro-pose a convolutional denoising autoencoder(CDAE)-based architecture trained on various types of *** also present various composing modules for each noise to improve object detection performance for night *** the exclusively dark(ExDark)Image dataset,experimental results show that the Sequentialfiltering architecture showed superior mean average precision(mAP)compared to other architectures.

关键词： Object detection computer vision nighttime multiple noises convolutional denoising autoencoder

Analysis of Imperfect Acoustic Cloaking Resonances

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Chinese Physics Letters 2012年第12期29卷 119-122页

作者： kim Seungil Department of Mathematics and Research Institute for Basic Sciences Kyung Hee UniversitySeoul 130-701Korea

We study the resonance phenomenon arising from imperfect acoustic cloaking in 2D based on a small perturbation of the transformation *** is shown that the resonant frequencies of imperfect cloaking appearing in the total scattering cross section converge to Dirichlet eigenvalues of the concealed region as a perturbation parameter approaches *** theory enables us to predict the location of the resonant frequencies of imperfect cloaking and to identify the corresponding resonance modes.

关键词： perturbation imperfect resonant

A Data Download Method from RSUs Using Fog Computing in Connected Vehicles

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Computers, Materials & Continua 2019年第5期59卷 375-387页

作者： Dae-Young kim Seokhoon kim School of Information Technology Daegu Catholic UniversityGyeongsan-si 38430Republic of Korea Department of Computer Software Engineering Soonchunhyang UniversityAsan-si 31538Republic of Korea

Communication is important for providing intelligent services in connected *** must be able to communicate with different places and exchange information while *** service operation,connected vehicles frequently attempt to download large amounts of *** can request data downloading to a road side unit(RSU),which provides infrastructure for connected *** RSU is a data bottleneck in a transportation system because data traffic is concentrated on the ***,it is not appropriate for a connected vehicle to always attempt a high speed download from the *** the mobile network between a connected vehicle and an RSU has poor connection quality,the efficiency and speed of the data download from the RSU is *** problem affects the quality of the user ***,it is important for a connected vehicle to connect to an RSU with consideration of the network conditions in order to try to maximize download *** proposed method maximizes download speed from an RSU using a machine learning *** collect and learn from network data,fog computing is used.A fog server is integrated with the RSU to perform *** the algorithm recognizes that conditions are not good for mass data download,it will not attempt to download at high ***,the proposed method can improve the efficiency of high speed *** conclusion was validated using extensive computer simulations.

关键词： Connected car fog computing data download DSRC machine learning

Identities for degenerate Bernoulli polynomials and Korobov polynomials of the first kind

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Science China Mathematics 2019年第5期62卷 999-1028页

作者： Taekyun kim Dae San kim Department of Mathematics Kwangwoon University Department of Mathematics Sogang University

In this paper, we derive five basic identities for Sheffer polynomials by using generalized Pascal functional and Wronskian matrices. Then we apply twelve basic identities for Sheffer polynomials, seven from previous results, to degenerate Bernoulli polynomials and Korobov polynomials of the first kind and get some new identities. In addition, letting λ→ 0 in such identities gives us those for Bernoulli polynomials and Bernoulli polynomials of the second kind.

关键词： generalized Pascal functional matrix Wronskian matrix degenerate Bernoulli polynomial Krobov polynomial of the first kind

Adaptive Data Transmission Method According to Wireless State in Long Range Wide Area Networks

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Computers, Materials & Continua 2020年第7期64卷 1-15页

作者： Seokhoon kim Dae-Young kim Department of Computer Software Engineering Soonchunhyang UniversityAsan-si31538Korea School of Computer Software Daegu Catholic UniversityGyeongsan-si38430Korea

The Internet of Things(IoT)has enabled various intelligent services,and IoT service range has been steadily extended through long range wide area communication technologies,which enable very long distance wireless data ***-nodes are connected to a gateway with a single *** consume very low-power,using very low data rate to deliver *** long transmission time is consequently needed for each data packet transmission in long range wide area networks,data transmission should be efficiently ***,this paper proposes a multicast uplink data transmission mechanism particularly for bad network *** delay will be increased if only retransmissions are used under bad network ***,employing multicast techniques in bad network conditions can significantly increase packet delivery ***,retransmission can be reduced and hence transmission efficiency ***,the proposed method adopts multicast uplink after network condition *** predict network conditions,the proposed method uses a deep neural network *** proposed method performance was verified by comparison with uplink unicast transmission only,confirming significantly improved performance.

关键词： IoT wide area communication machine learning uplink transmission.

Anomaly Detection in Imbalanced Encrypted Traffic with Few Packet Metadata-Based Feature Extraction

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 585-607页

作者： Min-Gyu kim Hwankuk kim Department of Financial Information Security Kookmin UniversitySeoul02707Republic of Korea Department of Information Security Cryptography Mathematics Kookmin UniversitySeoul02707Republic of Korea

In the IoT(Internet of Things)domain,the increased use of encryption protocols such as SSL/TLS,VPN(Virtual Private Network),and Tor has led to a rise in attacks leveraging encrypted *** research on anomaly detection using AI(Artificial Intelligence)is actively progressing,the encrypted nature of the data poses challenges for labeling,resulting in data imbalance and biased feature extraction toward specific *** study proposes a reconstruction error-based anomaly detection method using an autoencoder(AE)that utilizes packet metadata excluding specific node *** proposed method omits biased packet metadata such as IP and Port and trains the detection model using only normal data,leveraging a small amount of packet *** makes it well-suited for direct application in IoT environments due to its low resource *** experiments comparing feature extraction methods for AE-based anomaly detection,we found that using flowbased features significantly improves accuracy,precision,F1 score,and AUC(Area Under the Receiver Operating Characteristic Curve)score compared to packet-based ***,for flow-based features,the proposed method showed a 30.17%increase in F1 score and improved false positive rates compared to Isolation Forest and ***,the proposedmethod demonstrated a 32.43%higherAUCwhen using packet features and a 111.39%higher AUC when using flow features,compared to previously proposed oversampling *** study highlights the impact of feature extraction methods on attack detection in imbalanced,encrypted traffic environments and emphasizes that the one-class method using AE is more effective for attack detection and reducing false positives compared to traditional oversampling methods.

关键词： One-class anomaly detection feature extraction auto-encoder encrypted traffic CICIoT2023