• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.55-59
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• 2022

Recently, IoT technology has great attention and plays a key role in 4^th industrial revolution in order to design customized products and services. Additive Manufacturing (AM) is applied to fabricate IoT sensor directly or IoT sensor embedded structure. Also, design methods for AM are developing to consolidate various parts of IoT devices. Part consolidation leads to assembly time and cost reduction, reliability improvement, and lightweight. Therefore, a design method was proposed to guide designers to consolidate parts. The design method helps designers to define product architecture that consists of functions and function-part relations. The product architecture is converted to a network graph and then Girvan Newman algorithm is applied to cluster the graph network. Parts in clusters are candidates for part consolidation. To demonstrate the usefulness of the proposed design method, a case study was performed with e-bike fabricated by additive manufacturing.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.1027-1030
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• 2005

본 논문에서는 종단간 신규 네트워크 서비스에 대한 ITU-T X.805 기반 취약성 분석과 정보보호 요구사항 및 보안 대책 도출 절차를 제시한다. 일련의 절차는 정보보호프레임워크 도출 방법론 혹은 방법론으로 줄여서 표현한다. 종단간 네트워크 서비스는 IT 839의 8대 서비스를 대상으로 하며 방법론은 ITU-T X.805 표준과 정보보호 컨설팅 방법론을 참고하였다. 방법론은 새로운 인프라나 서비스의 정보보호 대책을 설계하는데 필요한 도구로써의 역할을 하여 구축 단계부터 정보보호를 반영할 수 있는 분석틀을 제시할 것으로 기대한다.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.363-374
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• 2010

In this paper, we propose the method for extracting Homogeneity Threshold($H_T$) and for segmenting homogeneous regions by USRG(Unseeded Region Growing) with $H_T$. The $H_T$ is a criterion to distinguish homogeneity in neighbor pixels and is computed automatically from the original image by proposed method. Theoretical background for proposed method is based on the Otsu's single level threshold method. The method is used to divide a small local part of original image int o two classes and the sum($\sigma_c$) of standard deviations for the classes to satisfy special conditions for distinguishing as different regions from each other is used to compute $H_T$. To find validity for proposed method, we compare the original image with the image that is regenerated with only the segmented homogeneous regions and show up the fact that the difference between two images is not exist visually and also present the steps to regenerate the image in order the size of segmented homogeneous regions and in order the intensity that includes pixels. Also, we show up the validity of proposed method with various results that is segmented using the homogeneity thresholds($H^*_T$) that is added a coefficient ${\alpha}$ for adjusting scope of $H_T$. We expect that the proposed method can be applied in various fields such as visualization and animation of natural image, anatomy and biology and so on.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.37-47
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• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11B
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• pp.693-699
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• 2007

In this Paper we present analysis of efficiency for various encapsulation methods to transport IP datagram over terrestrial digital multimedia broadcasting (T-DMB). The multimedia broadcasting system transmitted in one-way needs the data reliability for efficient transmission. And then It is able to select the independent data service using If encapsulation over T-DMB. We examine the compatibility in adopting T-DMB and the overhead of transmission occurring encapsulation. it also needs the full analysis of data framing because the cost of return channel is relatively higher. We do analysis based on theoretical calculation and propose an efficient, reliable and adaptable method in T-DMB.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.494-503
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• 2020

This study was undertaken to compare the effectiveness of imparting education to nursing college students, using traditional teaching methods and action learning teaching methods. The target of the study was to measure nursing leadership, academic self-efficacy, and self-preservation of the students, and determine the effects of action learning method imparted 2 hours daily for 8 weeks, out of the 15-week study schedule. Ed. Notes: There is a lot of repetition, and the highlighted statement lacks clarity. I am unable to understand the study period. Does the author mean 2 hrs daily for 8 weeks? I have suggested the edits as per my understanding. Please review and revise appropriately, if required. Differences obtained between nursing leadership, academic self-efficacy, and self-leadership when comparing the experimental and control groups, were analyzed by independent sample t-test. Pre and post comparisons of the domains were analyzed with a paired t-test. The study results indicate significant differences in academic self-efficacy and self-preservation between experimental and control groups after application of the action learning teaching method, leadership in nursing as a lower area, confidence in academic self-efficiency, and self-control efficacy. Our results indicate that the recently emerged action-learning teaching is an effective method to apply in existing curriculums.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.263-272
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• 2017

The concept of Internet of Things (IoT) has been increasingly popular these days, and its areas of application have been broadened. However, if the data stored in an IoT system is damaged and cannot be recovered, our society would suffer considerable damages and chaos. Thus far, most of the studies on fault-tolerance have been focused on computer systems, and there has not been much research on fault-tolerance for IoT systems. In this study, therefore, a fault-tolerance method in IoT environments is proposed. In other words, based on the EVENODD method, one of the traditional fault-tolerance methods, a fault-tolerance storage and recovery method for the data stored in the IoT server is proposed, and the method is implemented on an oneM2M IoT system. The fault-tolerance method proposed in this paper consists of two phases - fault-tolerant data storage and recovery. In the fault-tolerant data storage phase, some F-T gateways are designated and fault-tolerant data are distributed in the F-T gateways' storage using the EVENODD method. In the fault-tolerant recovery phase, the IoT server initiates the recovery procedure after it receives fault-tolerant data from non-faulty F-T gateways. In other words, an EVENODD array is reconstructed and received data are merged to obtain the original data.

• Journal of the Korean Chemical Society
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• v.63 no.4
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• pp.246-252
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• 2019

In the system of GC-OTC/FID (Gas chromatography-Open Tubular Column/Flame Ionization Detector), DMSO (Dimethyl sulfide) solvent was used to separate the polar solvents (Alcohols). In this system DMSO was eluted later than the separated polar solvents. At this system to calculate chromatographic factors [adjusted retention time ($t_R^{\prime}=t_R-t_O$), capacity factor{$k^{\prime}=(t_R-t_O)/t_O$} and separation factor {${\alpha}=(t_{R2}-t_O)/(t_{R1}-t_O)$}], dead time($t_O$) is necessary, but the method to calculate it has not been reported yet. Therefore, we have tried to develop $t_O$. To calculate $t_O$, we conversed DMSO retention time (DMSO $t_R$) to logarithm ($f(x)={\log}\;t_{R(DMSO)}{\rightarrow}t_O$, $t_O={\log}$ 9.551=0.980). To confirm the optimization of the developed method, we compared with $CH_4\;t_R$ and ${\ln}\;t_{R(DMSO)}$. Both of the values calculated by $CH_4\;t_R$ and ${\ln}\;t_{R(DMSO)}$ were not suitable in the calculation k' and ${\alpha}$. The developed method in this study{${\log}\;t_{R(DMSO)}$} has satisfied both of the values k' criteria (1${\alpha}(1<{\alpha}<2)$. The developed calculation method in this study was easy and convenient, therefore it can be expected to be applied to these similar systems.

• Journal of the Korea Computer Graphics Society
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• v.7 no.3
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• pp.1-7
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• 2001

We present an efficient and robust algorithm to parametrize a perspective silhouette curve of a canal surface. We also detect each connected component of the silhouette. A canal surface is an envelope surface of a moving sphere with varying radii, which is defined by the center trajectory C(t) and radius function r(t) of the moving sphere. A canal surface can be decomposed to a set of characteristic circles. We derive the equations for the silhouette points on each characteristic circle, then parameterize the silhouette curve by using the equation. The sphere $S(t_*)$ with center point $C(t_*)$ and radius $r(t_*)$ intersects with the canal surface at a characteristic circle $K(t_*)$. The perspective silhouette of the sphere $S(t_*)$ from given view point consists of a circle $Q(t_*)$. By finding the values of t at which K(t) and Q(t) tangentially intersect, we detect each connected component of the silhouette curve.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.171-176
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• 2019

In modern times, many IoT products are being used as all things and devices are connected to the Internet and IoT products become easily accessible through the network. For the convenience of users, IoT products can be remotely operated automatically without manual operation. Various research and development are underway to improve the convenience of users by using IoT products. However, since only the convenience of the users is pursued, in terms of security, there is a serious problem that exposes the user's personal information. This paper has proposed a method to apply $moir{\acute{e}}$ technology to IoT products in order to improve the performance of security, and a method to increase the safety of IoT products using user face authentication based on shadow $moir{\acute{e}}$ as a $moir{\acute{e}}$ phenomenon method, and the projection $moir{\acute{e}}$. When comparing the existing IoT products and IoT products applied with $moir{\acute{e}}$ technology, IoT products applied with $moir{\acute{e}}$ technology are safer in terms of security.