• Journal of Information Technology Services
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• v.15 no.4
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• pp.153-174
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• 2016

On account of multiple causes, including prolonged global economic crisis, addressing environmental pollution and the advent of hyper-connected society, a new paradigm called 'sharing economy' has rapidly emerged. Many startups have attempted to build promising business model based on the sharing economy concept. Nevertheless, successful cases are still very rare in the global level, except for Uber and Airbnb cases. Therefore, this study analyzes necessary causes and sufficient causes for successful settlements in the market through a comparative case analysis on digital matching firms in the sharing economy businesses. For the case study, we compare five successful cases (Uber, Airbnb, Kickstarter, TaskRabbit and DogVacay), three failure cases (Homejoy, Ridejoy and Tuterspree) and a platform cooperativism case (Juno) in accordance with six value attributes of business model including value proposition, market segment, value chain, cost structure and profit potential, value network and competitive strategy. We apply Boolean method to support controlled comparison and eliminate unnecessary attributes. The Boolean analysis result shows that value proposition, cost structure and profit potential, value network and competitive strategy are the essential attributes. Furthermore, the result indicates that each attribute is a necessary condition, where all four conditions should be met simultaneously in order to be successful. With this result, we discuss essential consideration for those who are planning startup based on the sharing economy business model.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2005.05a
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• pp.171-175
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• 2005

Automotive parts manufacturers are doing their best to strengthen the competitiveness. They are developing a large variety of new manufacturing technologies to reduce the manufacturing cost. Combined One Body Stamping(C.O.B.S) is one of the remarkable technologies to reduce production cost. C.O.B.S makes possible to form several parts together in a process using only one die set while conventional stamping demands the same number of die sets to the number of parts. But the deformation mechanism in C.O.B.S is more complicated because the interactions between blanks. So the interaction effects should be considered in the stage of initial blank shape design. In the study, a blank design method to consider the interactions between blanks was proposed and verified through the simulations and experiments. A commercial incremental FE code, LS-Dyna, was used to simulate the C.O.B.S Process. And a reverse one step FE code, Hyper Form, was used to predict initial blank shape. The boundary conditions of the reverse one step FE analysis were determined by the proposed method.

• Smart Structures and Systems
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• v.24 no.4
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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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• v.25 no.4
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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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• v.6 no.6
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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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• v.12 no.6
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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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• v.12 no.4
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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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• v.17 no.7
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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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• v.21 no.11
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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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• v.7 no.2
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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.