• Korean Journal of Radiology
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• v.23 no.4
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• pp.455-465
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• 2022

Objective: To compare the reproducibility and performance of quantitative metrics between ZOOMit and conventional intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the diagnosis of early- and mid-stage Sjögren's syndrome (SS). Materials and Methods: Twenty-two patients (mean age ± standard deviation, 52.0 ± 10.8 years; male:female, 2:20) with early- or mid-stage SS and 20 healthy controls (46.9 ± 14.6 years; male:female, 7:13) were prospectively enrolled in our study. ZOOMit IVIM and conventional IVIM MRI were performed simultaneously in all individuals using a 3T scanner. Quantitative IVIM parameters - including tissue diffusivity (D), pseudodiffusion coefficient (D^*), and perfusion fraction (f) - inter- and intra-observer reproducibility in measuring these parameters, and their ability to distinguish patients with SS from healthy individuals were assessed and compared between ZOOMit IVIM and conventional IVIM methods, appropriately. MR gland nodular grade (MRG) was also examined. Results: Inter- and intra-observer reproducibility was better with ZOOMit imaging than with conventional IVIM imaging (ZOOMit vs. conventional, intraclass correlation coefficient of 0.897-0.941 vs. 0.667-0.782 for inter-observer reproducibility and 0.891-0.968 vs. 0.814-0.853 for intra-observer reproducibility). Significant differences in ZOOMit f, ZOOMit D^*, D^*, conventional D^*, and MRG between patients with SS and healthy individuals (all p < 0.05) were observed. ZOOMit D^* outperformed conventional D^* in diagnosing early- and mid-stage SS (area under receiver operating curve, 0.867 and 0.658, respectively; p = 0.002). The combination of ZOOMit D^*, MRG, and ZOOMit f as a new diagnostic index for SS, increased diagnostic area under the curve to 0.961, which was higher than that of any single parameter (all p < 0.01). Conclusion: Considering its better reproducibility and performance, ZOOMit IVIM may be preferred over conventional IVIM MRI, and may subsequently improve the ability to diagnose early- and mid-stage SS.

• The Journal of the Acoustical Society of Korea
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• v.23 no.4
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• pp.303-308
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• 2004

In this Paper a transmitter system for IMr-2000 using feed-forward linearization method was Proposed to linearize power amplifier. The feed-forward structure needs a reference signal to compare and neutralize distortion : this is achieved through the second modulator which is operated at very low input level to obtain a signal with a negligible distortion. Therefore, this structure can reduce distortion of modulator as well as Power amplifier. This is the advantage over the existing system structure. The Proposed transmitter system is designed and simulated by Agilent ADS ver.2002. A two tone test for the system is done at 1.98GHz center frequency with frequency spacing of 2MHz. The reduction of Inter-Modulation Distortion(IMD) is around 49.95dB. This proposed system offers an excellent combination of linearity and simplicity.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1607-1614
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• 2011

As the connection between spread footing and pile is very important structural connection, it acts as the inter-loading medium to transfer the rail loads applied by superstructure to ground through the body pile of foundation. The experimental study is the method how to reinforce the pile cap between steel pile and footing utilizing perfobond plate with protruding keys. It were experimented on the compression punching tests and bending moment tests against the vertical loading and horizontal loadings acting on head of steel tube pipe. As a result, the tension capacity of the perfobond plate exhibited the superior performance due to the interlocking or dowel effects by the sheared keys of perfobond plate, and there were showing the sufficient strength and ductile capacity against the bending moment of horizontal loading tests. Therefore, it is judged that "the embedded method of perfobond plate in pile cap and footing" which is utilizing the shear connection of perfobond plate with protruding keys has a sufficient structural stability enough to be replaced with the current specification of reinforced method of pile cap with vertically deformed rebar against the vertical compression loads and bending moments that are able to occur in the combination structure of steel pile and the footing foundation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.1
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• pp.99-118
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• 2013

Electrocardiograms (ECGs) are widely used by clinicians to identify the functional status of the heart. Thus, there is considerable interest in automated systems for real-time monitoring of arrhythmia. However, intra- and inter-patient variability as well as the computational limits of real-time monitoring poses significant challenges for practical implementations. The former requires that the classification model be adjusted continuously, and the latter requires a reduction in the number and types of ECG features, and thus, the computational burden, necessary to classify different arrhythmias. We propose the use of adaptive learning to automatically train the classifier on up-to-date ECG data, and employ adaptive feature selection to define unique feature subsets pertinent to different types of arrhythmia. Experimental results show that this hybrid technique outperforms conventional approaches and is therefore a promising new intelligent diagnostic tool.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.1 s.173
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• pp.156-162
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• 2000

Sensitized STS 304 stainless steel crack growth rate(CGR) in high temperature water was investigated under trapezoidal wave loading test using fracture mechanics techniques. The CGR, due to stress corrosion cracking(SCC), were systematically measured as a function of the stress intensity factor and stress. holding time under trapezoidal wave loading. In high temperature water, CGR was enhanced by a synergistic effects in combination with an aggressive environment and mechanical damage. The CGR, $(da/dN)_{env}$ was basically described as a summation of the environmentally assisted crack growth rate $(da/dN)_{SCC}$, $(da/dN)_{CF}$ and fatigue crack growth rate in air $(da/dN)air,. The CGR, $(da/dN)_{env}$, increased linearly with increasing stress holding time. The CGR, $(da/dN)_{SCC}$ decreased linearly with increasing stress holding time. Fracture surface mode varied from trans-granular cracking to inter-granular cracking with increasing stress holding time.

• Journal of Information Technology Applications and Management
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• v.18 no.2
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• pp.1-21
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• 2011

In this era of convergence, which is characterized by the integration and combination of technology and industries, broadcasting and communications, offline and online, and devices and services, the content industry is also experiencing rapid changes including inter-genre exchange, the creation of new industries, and customized demand. Specifically, IT-based digital content industries such as the online game, e-book, mobile contents and web portal industries are no longer restricted to the boundaries of video, music and games but are being expanded into the realms of education, medicine, fashion and sports thanks to CT innovation of 3D, CG, AR/VR, VFX, etc. As such, various countries have come to recognize the convergent content industry as a new growth engine that will pick up where the IT industry left off, and are forming policies for its development accordingly. This research aims to optimize the system of content taxonomy which is currently genre-focused and unable to support technological development and convergence, and to discover and select star contents to be rigorously developed with governmental support. In this paper, 20 star contents in 8 areas were selected, and these are expected to create tremendous cultural and economic value through ongoing technological and industrial development.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.243-248
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• 2005

도메인 조합에 기반한 단백질 상호작용 예측 기법은 효모와 같은 특정 종에 대하여 우수한예측 정확도를 보이는 것으로 알려졌으나, 인간과 같은 고등 생명체의 단백질에 대한 상호작용 예측을 수행하기 위하여는 여러종에 대한 기법의 적절성검증과 최적의 학습집단 구성 방안에 대한 연구가 선행되어야 한다. 본 논문에서는, 초파리 단백질을 이용한 예측 정확도 검증으로 도메인 조합 기법의 일반화 가능성을 타진 하고 이종간의 상호작용 예측실험 및 정확도 검증을 통하여 비교적 연구가 덜 되어진 종의 단백질 상호작용 예측을 위한 학습집단 구성 방법에 대하여 기술한다. 초파리 실험에서는 10351개의 상호작용이 있는 단백질 쌍 가운데, 80%와 20%를 각각 학습집단 및 실험집단으로 사용하였으며, 상호작용이 없는단백질 쌍의 학습집단은 1배에서 5배까지 변화시키면서 예측 정확도를 관찰하였다. 이 결과77.58%의 민감도와 92.61%의 특이도를 확인하였다. 이종간의 상호작용 예측 실험은 효모, 초파리, 효모, 초파리에 해당하는 학습집단 각각을 바탕으로 Human, Mouse, E. coli, C. elegans 등의 단백질 상호작용 예측을 수행하였다. 실험 곁과 학습집단의 도메인이 실험집단의 도메인과 많이 겹칠수록 높은 정확도를 보여주었으며, 도메인 집단간의 유사도를 나타내기 위해 고안한 Domain Overlapping Rate(DOR) 는 상호작용 예측 정확도의 중요한 요소임을 찾아내었다.

• The KIPS Transactions:PartD
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• v.14D no.1 s.111
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• pp.89-96
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• 2007

Various classification methods have been developed to reuse components. These classification methods enable the user to access the needed components quickly and easily. Conventional classification approaches include the following problems: a labor-intensive domain analysis effort to build a classification structure, the representation of the inter-component relationships, difficult to maintain as the domain evolves, and applied to a limited domain. In order to solve these problems, this paper describes a composite cluster analysis approach for component classification. The cluster analysis approach is a combination of a hierarchical cluster analysis method, which generates a stable clustering structure automatically, and a non-hierarchical cluster analysis concept, which classifies new components automatically. The clustering information generated from the proposed approach can support the domain analysis process.

• Smart Structures and Systems
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• v.4 no.5
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• pp.655-666
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• 2008

In the past 20 years, seismic isolation has see a variety of applications in design of structures to mitigate seismic hazard. In particular, isolation has been seen as a means of achieving enhanced seismic performance objectives, such as those for hospitals, critical emergency response facilities, mass electronic data storage centers, and similar buildings whose functionality following a major seismic event is either critical to the public welfare or the financial solvency of an organization. While achieving these enhanced performance objectives is a natural (and oftentimes requisite) application of seismic isolation, little attention has been given to the extension of current design practice to isolated buildings which may have more conventional performance objectives. The development of a rational design methodology for isolated buildings requires thorough investigation of the behavior of isolated structures subjected to seismic input of various recurrence intervals, and which are designed to remain elastic only under frequent events. This paper summarizes these investigations, and proposed a consistent probabilistic framework within which any combination of performance objectives may be met. Analytical simulations are presented, the results are summarized. The intent of this work is to allow a building owner to make informed decisions regarding tradeoffs between superstructure performance (drifts, accelerations) and isolation system performance. Within this framework, it is possible to realize the benefits of designing isolated buildings for which the design criteria allows consideration of multiple performance goals.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.156-161
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• 2001

Currently, agricultural facilities are evaluated using either basic inspections or detailed analysis. However, conventional analyses as well as methods based on fuzzy logic and rule of thumb have not been very successful in providing a clear relationship between rating and real state of agricultural facilities, because they can't provide exactly acceptable reliability of degraded structures with manager or supervisor. Therefore, in this stage, we must define probabilistic variables for representing degradation of structures being given damages during a survival time. This paper describes the application of neural network system in developing the relation between subjective ratings and parameters of agricultural reservoir as well as that between subjective and analytical ratings. It is shown that neural networks can be trained and used successfully in estimating a rating based on several parameters. The specific application problem for agricultural reservoir in the rural area of Korea is presented and database is constructed to maintain training data set, the information of inspection and facilities. This study showed that a successful training of a neural network could be useful, especially if the input data set for target problem contains parameters with a diverse combination of inter-correlation coefficients. And the networks had a prediction rating of about $^{\ast}^{\ast}^{\ast}%$. The neural network system is expected to show high performance fairly in estimate than statistical method to use equation that is consisted of very lowly interrelated variables.