• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.103-109
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• 2008

Many Internet application provide the PKI(public key infrastructure)-based service to provide authentication and message integrity. Several researchers proposed PKI-based p2p network framework. However, in the real world, the use of PKI is not suitable for peer to peer network, because the peer-to-peer network is an open and dynamic network. Moreover, currently there is no nation-to-nation interoperable certificate. In this paper, we designed reliable p2p file sharing application without public key infrastructure. To do this we propose reliable public key distribution mechanism to distribute public key safely without PKI infrastructure for two-tier super-peer architecture. In our system, each peer generates and distributes its public/private key pairs, and the public key is securely distributed without PKI. The proposed mechanism is safe against MITM attack. This mechanism can be applied various P2P applications such as file sharing, IPTV, distributed resource sharing and so on

• Structural Engineering and Mechanics
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• v.77 no.2
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• pp.197-215
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• 2021

Under a severe environment of multiple hazards such as earthquakes and winds, the life-cycle performance of engineering structures may inevitably be deteriorated due to the fatigue effect caused by long-term exposure to wind loads, which would further increase the structural vulnerability to earthquakes. This paper presents a framework for evaluating the lifetime structural seismic performance under the effect of wind-induced fatigue considering different sources of uncertainties. The seismic behavior of a high-rise steel-concrete composite frame with buckling-restrained braces (FBRB) during its service life is systematically investigated using the proposed approach. Recorded field data for the wind hazard of Fuzhou, Fujian Province of China from Jan. 1, 1980 to Mar. 31, 2019 is collected, based on which the distribution of wind velocity is constructed by the Gumbel model after comparisons. The OpenSees platform is employed to establish the numerical model of the FBRB and conduct subsequent numerical computations. Allowed for the uncertainties caused by the wind generation and structural modeling, the final annual fatigue damage takes the average of 50 groups of simulations. The lifetime structural performance assessments, including static pushover analyses, nonlinear dynamic time history analyses and fragility analyses, are conducted on the time-dependent finite element (FE) models which are modified in lines with the material deterioration models. The results indicate that the structural performance tends to degrade over time under the effect of fatigue, while the influencing degree of fatigue varies with the duration time of fatigue process and seismic intensity. The impact of wind-induced fatigue on structural responses and fragilities are explicitly quantified and discussed in details.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.359-366
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• 2021

It's been more than 30 years since global warming by the increase in CO2 became a cause celebre worldwide. Recently the government promulgated Framework Act on on Low-Carbon Green Growth and has been continuously putting much effort into saving energy and reducing carbon dioxide emissions such as an international climate change conference to prevent the increase in CO2. However, because most cities are not planned for energy saving, new cities should be planned as the active energy-efficient urban structure for 'sustainable urban development' from a long-term perspective. This study aims to design a new prototype for the sustainable energy-independent and environment-friendly housing estates which is the nation's new vision in the era of the Fourth Industrial Revolution. A study on the energy-independent site planning and the quantitative standardization of its factor will be conducted.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.75-94
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• 2021

The 4th industrial revolution needs a fusion of artificial intelligence, robotics, the Internet of Things (IoT), edge computing, and other technologies. For the fusion of technologies, cloud computing technology can provide flexible and high-performance computing resources so that cloud computing can be the foundation technology of new emerging services. The emerging services become a global-scale, and require much higher performance, availability, and reliability. Public cloud providers already provide global-scale services. However, their services, costs, performance, and policies are different. Enterprises/ developers to come out with a new inter-operable service are experiencing vendor lock-in problems. Therefore, multi-cloud technology that federatively resolves the limitations of single cloud providers is required. We propose a software platform, denoted as Cloud-Barista. Cloud-Barista is a multi-cloud service common platform for federating multiple clouds. It makes multiple cloud services as a single service. We explain the functional architecture of the proposed platform that consists of several frameworks, and then discuss the main design and implementation issues of each framework. To verify the feasibility of our proposal, we show a demonstration which is to create 18 virtual machines on several cloud providers, combine them as a single resource, and manage it.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.118-130
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• 2020

Modern weapon systems are composed of complex systems(System of Systems) and require a complex and advanced operational concept that performs missions through interoperability with various weapon systems. In order to derive the operational concept of the weapon system that the military wants to acquire (i.e., single mission, component operation, Joint and Alliance operations), it is necessary to identify the system related to the weapon system, environmental factors and restrictions of the weapon system to be developed. Through the derivation of the operational concept, the weapon system acquisition agency can reasonably and accurately extract various and complex requirements. In this paper, we propose a complementary method of using MND-AF to OCD and ORD required in weapon system acquisition process. MND-AF can increase the understanding and consensus of business stakeholders (users, acquirers, developers, etc.) by showing the results of weapon system analysis from various perspectives. We compare the items in the standard form of OCD and ORD with the MND-AF outputs.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.163-172
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• 2022

The purpose of this study is to present implications in the planning and design methodology for revitalization of public spaces for mixed-use residential building. For the purpose, I have taken a literature research and a site analysis with cases of 'Kyungsung Univ.·Bukyung Nat'l Univ. Station'-area in Busan City. The analysis framework was consist of spatial composition, street facilities, use behavior, and connection with the street. The result of this study is as follows; 1) It is needed to consist of an empty space practically usable in an open location that is easy to access by the general public. 2) Considering the use of people, it is needed to install street furniture that can actually be used for rest. 3) It is needed to make a plan and design that considers the access and use of the general public and the space through it. 4) It is needed to create a synergistic effect in the integration of the street and the public space and the linkage with the street through this.

• Journal of Electrochemical Science and Technology
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• v.12 no.4
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• pp.458-464
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• 2021

Lithium ion batteries (LIBs) is a kind of rechargeable secondary battery, developed from lithium battery, lithium ions move between the positive and negative electrodes to realize the charging and discharging of external circuits. Zeolitic imidazolate frameworks (ZIFs) are porous crystalline materials in which organic imidazole esters are cross-linked to transition metals to form a framework structure. In this article, ZIF-67 is used as a sacrificial template to prepare nano porous carbon (NPC) coated cobalt nanoparticles. The final product Co/NPC composites with complete structure, regular morphology and uniform size were obtained by this method. The conductive network of cobalt and nitrogen doped carbon can shorten the lithium ion transport path and present high conductivity. In addition, amorphous carbon has more pores that can be fully in contact with the electrolyte during charging and discharging. At the same time, it also reduces the volume expansion during the cycle and slows down the rate of capacity attenuation caused by structure collapse. Co/NPC composites first discharge specific capacity up to 3115 mA h/g, under the current density of 200 mA/g, circular 200 reversible capacity as high as 751.1 mA h/g, and the excellent rate and resistance performance. The experimental results show that the Co/NPC composite material improves the electrical conductivity and electrochemical properties of the electrode. The cobalt based ZIF-67 as the precursor has opened the way for the design of highly performance electrodes for energy storage and electrochemical catalysis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1105-1114
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• 2021

Due to the recent surge in popularity of cryptocurrency, the threat of cryptojacking, a malicious code for mining cryptocurrencies, is increasing. In particular, web-based cryptojacking is easy to attack because the victim can mine cryptocurrencies using the victim's PC resources just by accessing the website and simply adding mining scripts. The cryptojacking attack causes poor performance and malfunction. It can also cause hardware failure due to overheating and aging caused by mining. Cryptojacking is difficult for victims to recognize the damage, so research is needed to efficiently detect and block cryptojacking. In this work, we take representative distinct symptoms of cryptojacking as an indicator and propose a new architecture. We utilized the K-Nearst Neighbors(KNN) model, which trained computer performance indicators as behavior-based dynamic analysis techniques. In addition, a K-means model, which trained the frequency of malicious script words for script similarity-based static analysis techniques, was utilized. The KNN model had 99.6% accuracy, and the K-means model had a silhouette coefficient of 0.61 for normal clusters.

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• Smart Structures and Systems
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• v.31 no.4
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• pp.365-381
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• 2023

The existing vision-based techniques for inspection and condition assessment of civil infrastructure are mostly manual and consequently time-consuming, expensive, subjective, and risky. As a viable alternative, researchers in the past resorted to deep learning-based autonomous damage detection algorithms for expedited post-disaster reconnaissance of structures. Although a number of automatic damage detection algorithms have been proposed, the scarcity of labeled training data remains a major concern. To address this issue, this study proposed a semi-supervised learning (SSL) framework based on consistency regularization and cross-supervision. Image data from post-earthquake reconnaissance, that contains cracks, spalling, and exposed rebars are used to evaluate the proposed solution. Experiments are carried out under different data partition protocols, and it is shown that the proposed SSL method can make use of unlabeled images to enhance the segmentation performance when limited amount of ground truth labels are provided. This study also proposes DeepLab-AASPP and modified versions of U-Net++ based on channel-wise attention mechanism to better segment the components and damage areas from images of reinforced concrete buildings. The channel-wise attention mechanism can effectively improve the performance of the network by dynamically scaling the feature maps so that the networks can focus on more informative feature maps in the concatenation layer. The proposed DeepLab-AASPP achieves the best performance on component segmentation and damage state segmentation tasks with mIoU scores of 0.9850 and 0.7032, respectively. For crack, spalling, and rebar segmentation tasks, modified U-Net++ obtains the best performance with Igou scores (excluding the background pixels) of 0.5449, 0.9375, and 0.5018, respectively. The proposed architectures win the second place in IC-SHM2021 competition in all five tasks of Project 2.