• Smart Structures and Systems
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• 제24권4호
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• pp.427-434
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• 2019

This study investigates the structural integrity of the amphibious tour bus under the rollover condition. The multi-purpose bus called Dual Mode Tour Bus (DMTB) which explores on land and water has been designed on top of a truck platform. Prior to the fabrication of new upper body and sailing equipment of DMTB, computational analysis investigates the rollover protection of the proposed structure including superstructure, wheels, and axles. The Computer-Aided Design (CAD) of the whole vehicle model is meshed and preprocessed under high performance using the Altair HyperMesh to attain the best mesh model suited for finite element analysis (FEA) on the proposed system. Meanwhile, the numerical model is analyzed by employing LS-DYNA to evaluate the superstructure strength. The numerical model includes detail information about the microstructure and considers wheels and axles as rigid bodies but excludes window glasses, seats, and interior parts. Based on the simulation analysis and proper modifications especially on the rear portion of the bus, the local stiffness significantly increased. The vehicle is rotated to the contact point on the ground based on the mathematical method presented in this study to save computational cost. The results show that the proposed method of rollover analysis is highly significant not only in bus rollover tests but in crashworthiness studies for other application. The critical impartments in our suggested dual-purpose bus accepted and passed "Economic Commission for Europe (ECE) R66".

• Journal of the Korea Society of Computer and Information
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• 제25권4호
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• pp.105-112
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• 2020

In the fourth industrial revolution represented by hyper-connected and intelligence, cloud computing is drawing attention as a technology to realize big data and artificial intelligence technologies. The proliferation of cloud computing has also increased the number of threats. In this paper, we propose one way to effectively monitor to the resources assigned to clients by the IaaS service provider. The method we propose in this paper is to model the use of resources allocated to cloud systems using ARIMA algorithm, and it identifies abnormal situations through the use and trend analysis. Through experiments, we have verified that the client service provider can effectively monitor using the proposed method within the minimum amount of access to the client systems.

• Current Optics and Photonics
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• 제6권6호
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• pp.565-575
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• 2022

In this paper, we propose a non-fungible token (NFT) transaction method that can commercialize the real 3D property and make property sharing possible using the 3D reconstruction technique. In addition, our proposed method enhances the security of NFT copyright and metadata by using optical encryption. In general, a conventional NFT is used for 2D image proprietorial rights. To expand the scope of the use of tokens, many cryptocurrency industries are currently trying to apply tokens to real three-dimensional (3D) property. However, many token markets have an art copyright problem. Many tokens have been minted without considering copyrights. Therefore, tokenizing real property can cause significant social issues. In addition, there are not enough methods to mint 3D real property for NFT commercialization and sharing property tokens. Therefore, we propose a new token management technique to solve these problems using integral imaging and double random phase encryption. To show our system, we conduct a private NFT market using a test blockchain network that can demonstrate the whole NFT transaction process.

• Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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• 제12권6호
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• pp.579-590
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• 2018

Anomaly detection on building energy consumption has been regarded as an effective tool to reduce energy saving on building operation and maintenance. However, it requires energy model and FDD expert for quantitative model approach or large amount of training data for qualitative/history data approach. Both method needs additional time and labors. This study propose a machine learning and data science approach to define faulty conditions on hourly building energy consumption with reducing data amount and input requirement. It suggests an application of Support Vector Data Description (SVDD) method on training normal condition of hourly building energy consumption incorporated with hourly outdoor air temperature and time integer in a week, 168 data points and identifying hourly abnormal condition in the next day. The result shows the developed model has a better performance when the ${\nu}$ (probability of error in the training set) is 0.05 and ${\gamma}$ (radius of hyper plane) 0.2. The model accuracy to identify anomaly operation ranges from 70% (10% increase anomaly) to 95% (20% decrease anomaly) for daily total (24 hours) and from 80% (10% decrease anomaly) to 10%(15% increase anomaly) for occupied hours, respectively.

• Smart Media Journal
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• 제12권4호
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• pp.19-26
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• 2023

IoT edge services utilizing neuromorphic hardware architectures are suitable for autonomous IoT applications as they perform intelligent processing on the device itself. However, spiking neural networks applied to neuromorphic hardware are difficult for IoT developers to comprehend due to their complex structures and various hyper-parameters. In this paper, we propose a method for generating spiking neural network (SNN) models that satisfy user performance requirements while considering the constraints of neuromorphic hardware. Our proposed method utilizes previously trained models from pre-processed data to find optimal SNN model parameters from profiling data. Comparing our method to a naive search method, both methods satisfy user requirements, but our proposed method shows better performance in terms of runtime. Additionally, even if the constraints of new hardware are not clearly known, the proposed method can provide high scalability by utilizing the profiled data of the hardware.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권7호
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• pp.1773-1793
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• 2023

Automated machine learning, often referred to as "AutoML," is the process of automating the time-consuming and iterative procedures that are associated with the building of machine learning models. There have been significant contributions in this area across a number of different stages of accomplishing a data-mining task, including model selection, hyper-parameter optimization, and preprocessing method selection. Among them, preprocessing method selection is a relatively new and fast growing research area. The current work is focused on the recommendation of preprocessing methods, i.e., feature subset selection (FSS) algorithms. One limitation in the existing studies regarding FSS algorithm recommendation is the use of a single learner for meta-modeling, which restricts its capabilities in the metamodeling. Moreover, the meta-modeling in the existing studies is typically based on a single group of data characterization measures (DCMs). Nonetheless, there are a number of complementary DCM groups, and their combination will allow them to leverage their diversity, resulting in improved meta-modeling. This study aims to address these limitations by proposing an architecture for preprocess method selection that uses ensemble learning for meta-modeling, namely AutoFE-Sel. To evaluate the proposed method, we performed an extensive experimental evaluation involving 8 FSS algorithms, 3 groups of DCMs, and 125 datasets. Results show that the proposed method achieves better performance compared to three baseline methods. The proposed architecture can also be easily extended to other preprocessing method selections, e.g., noise-filter selection and imbalance handling method selection.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제21권11호
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• pp.2015-2021
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• 2017

Recently, a lot of attention is fallen to IoT(Internet of Things) for hyper-connected society and the number of unlicensed wireless device has been increasing. Thus, this paper analyzed the impact of unlicensed wireless device on the basis of 802.11ah on licensed LTE user equipment in 900 MHz frequency band for efficient frequency use. As the interference analysis method, Minimum Coupling Loss (MCL) method and Monte Carlo (MC) method were used. In case of one interferer, minimum separation distance between interferer and victim was calculated as about 22 m through the MCL method under the assumption of the worst case. The maximum number of interferer to meet the interference probability of 5% below within a cell radius of the victim was computed as about 3000 by using MC method based on statistical technique. The analysis method and results in this paper are expected to be used for the coexistence between unlicensed wireless device and licensed wireless device.

• Biotechnology and Bioprocess Engineering:BBE
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• 제7권2호
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• pp.67-75
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• 2002

The human complement receptor type 1 (CR 1, C3 b/C4b receptor) is a polymorphic membrane glycoprotein expressed on human erythrocytes, peripheral leukocytes, plasma and renal glomerular podocytes, which consists of transmembrane and cytoplasmic domains with 30 repeating homologous protein domains known as short consensus repeats (SCR). CR1 has been used as an inhibitor for inflammatory and immune system for the past several years. Recently; it is reported that CRl was found to suppress the hyper-acute rejection in xeno-transplantation and can be used to cure autoimmune diseases. A soluble form of CRl, called sCRl, is a recombinant CRl by cleaving the transmembrane domain at C-terminus and has been expressed in Chinese Hamster Ovary (CHO) cells. Several purification methods for sCR1 from CHO cells have been reported, but most of them require complicated steps at high cost. Moreover, such methods are mostly performed under the pH condition apt to denaturing sCR1 and causes sCRl losing its activity. We here report a rapid and efficient method to purify sCR1 from CHO cell. The new method consists of a two-stage of cell culture by cultivating cells in serum medium followed by serum-free medium, and a two-stage of column purification by means of heparin and gel filtration column chromatography. By using this novel method, sCR1 can be purified in a simple and effective way with high yield and purity, furthermore, the purified sCR1 was confirmed to retain its activity to suppress the complement activation in vivo and ex vivo.

• The Transactions of the Korea Information Processing Society
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• 제5권6호
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• pp.1441-1456
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• 1998

The concept of a hyperpresmtation, as an extension of a hypermedia, is the presentation in which time-varying multimedia presentations are dynamically linked together and a hyperlink's context can be changed over time at any time during a continuous presentation. Problems caused by integrating the hyperpresentation into an existing multimedia system which handles a sequential presentation only are, how to describe the hyperprcsentation, how to set up a hyperlink on a continuous media, and how to check the consistency of the synchronized presentations. In this paper. a new synchronization description method for the hyperpresentation and a method for setting a hyper link on a continuous media during" presentation are proposed after havin!; SHrvey of existing methods, The proposed method deals with only the DC value in a stream ut a DCT based compressed data for checking a condition of te link. Finally, the method for checking the consistency of mixed presentations before actual play of the hnlerpresentation is described. Proposed methods are implemented on MuX(Multimedia IO Server) where a sample scenario is tested.

• Journal of the Korean Magnetics Society
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• 제23권3호
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• pp.110-116
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• 2013

This paper proposes a sampling-based sensitivity method for dealing with electromagnetic coupled design problems effectively. The black-box modeling technique is basically applied to obtain an optimum regardless of how strong the electromagnetic, thermal and structural analyses are coupled with each other. To achieve this, Kriging surrogate models are produced in a hyper-cubic local window with the center of a current design point. Then design sensitivity values are extracted from the differentiation of basis functions which consist of the models. The proposed method falls under a hybrid optimization method which takes advantages of the sampling-based and the sensitivity-based methods. Owing to the aforementioned feature, the method can be applied even to electromagnetic problems of which the material properties are strongly coupled with thermal or structural outputs. To examine the accuracy and validity of the proposed method, a strongly nonlinear mathematical example and a coil design problem for local induction heating are tested.