• Journal of Magnetics
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• v.11 no.2
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• pp.83-86
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• 2006

Controlling magnetic domains in soft underlayer (SUL) of perpendicular magnetic recording (PMR) is an important issue for the application of PMR in HDD. We studied the magnetic domain structures in SUL using the finite element based micromagnetic simulation (FEMM) for the SUL models with different thicknesses. The purpose is to simulate the magnetic domain wall noise when the SUL thickness and saturation magnetization are changed. The simulation results show that a 15 nm SUL forms simpler Neel wall domain wall pattern and 40 nm SUL forms complex Bloch wall. To visualize the effect of these domain walls stray field at a read sensor position, the magnetic stray field of the domain walls at air bearing surface (ABS) which is 50 nm above the SUL was simulated and the results imply that Bloch walls have stronger stray field with more complicated field patterns than Neel walls and this becomes a significant noise source. Therefore, the thickness of the SUL should be controlled to avoid the formation of Bloch walls.

• ETRI Journal
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• v.36 no.3
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• pp.429-438
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• 2014

Semantic role labeling (SRL) is a task in natural-language processing with the aim of detecting predicates in the text, choosing their correct senses, identifying their associated arguments, and predicting the semantic roles of the arguments. Developing a high-performance SRL system for a domain requires manually annotated training data of large size in the same domain. However, such SRL training data of sufficient size is available only for a few domains. Constructing SRL training data for a new domain is very expensive. Therefore, domain adaptation in SRL can be regarded as an important problem. In this paper, we show that domain adaptation for SRL systems can achieve state-of-the-art performance when based on structural learning and exploiting a prior model approach. We provide experimental results with three different target domains showing that our method is effective even if training data of small size is available for the target domains. According to experimentations, our proposed method outperforms those of other research works by about 2% to 5% in F-score.

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1121-1130
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• 2004

The Genetic Algorithm (GA), an optimization technique based on the theory of natural selection, has proven to be a relatively robust means of searching for global optimum. It converges to the global optimum point without auxiliary information such as differentiation of function. In the case of a complex problem, the GA involves a large population number and requires a lot of computing time. To improve the process, this research used parallel processing with several personal computers. Parallel process technique is classified into two methods according to subpopulation's size and number. One is the fine-grained method (FGM), and the other is the coarse-grained method (CGM). This study selected the CGM as a parallel process technique because the load is equally divided among several computers. The given design domain should be reduced according to the degree of feasibility, because mechanical system problems have constraints. The reduced domain is used as an initial design domain. It is consistent with the feasible domain and the infeasible domain around feasible domain boundary. This parallel process used the Message Passing Interface library.

• Journal of Korean Elementary Science Education
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• v.28 no.3
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• pp.263-276
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• 2009

The purpose of this study was to analyze the elementary students' selection of representable value and confident method that appear in measuring activities by using a microgenetic method. The participants were seven elementary students in the fourth grade. They performed the same measuring activities six times for the study period. Data were collected by interview and observation with their activity recording papers and video tape transcription. Their activities were recorded and documented for the analysis. Results were as follows. First, in the time measuring activity, elementary students developed desirably as their measuring experience increased, for example they selected a representable value in use of a repeated measurement and used a various method in the domain of a time measurement and they showed an increase of a quantitative observation in the volume domain except in the length domain. Second, in a confident method of a representable value, though they must rely upon a repeated measurement, they only measure repeatedly in the time domain. Also in the time domain, it doesn't get accomplished a exact confidence of a representable value at a shortage of skill about a measurement. Accordingly this study will be implications for teachers to teach a handling abilities of measuring instruments to elementary students and to be promote understanding a nature of measurement.

• Journal of Science Education
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• v.33 no.1
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• pp.31-43
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• 2009

The purpose of this study is to identify a domain-specificity of the scientific creativity and the component of scientific creativity. Conducted from theoretical study, this study suggests that a domain-specific view of creativity offers a more useful and constructive components of scientific creativity based on the literature associated with the component of scientific creativity. Scientific creativity has a domain-specific component and so there is need to distinguish scientific creativity from creativity in general. As a result, scientific creativity is different from other creativity it is concerned with scientific knowledge, science process skill, creative scientific problem finding and solving and so on. And since scientific creativity is a kind of ability, it is possible to improve through a scientific creativity program.

• ETRI Journal
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• v.37 no.2
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• pp.369-379
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• 2015

Fault management of virtualized network environments using user-driven network provisioning systems (NPSs) is crucial for guaranteeing seamless virtual network services irrespective of physical infrastructure impairment. The network service interface (NSI) of the Open Grid Forum reflects the need for a common standard management API for the reservation and provisioning of user-driven virtual circuits (VCs) across global networks. NSI-based NPSs (that is, network service agents) can be used to compose user-driven VCs for mission-critical applications in a dynamic multi-domain. In this article, we first attempt to outline the design issues and challenges faced when attempting to provide mission-critical applications using dynamic VCs with a protection that is both user-driven and trustworthy in a dynamic multi-domain environment, to motivate work in this area of research. We also survey representative works that address inter-domain VC protection and qualitatively evaluate them and current NSI against the issues and challenges.

• Journal of the Society of Naval Architects of Korea
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• v.41 no.5
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• pp.1-7
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• 2004

The Spar platform with deep draft is characterized as effective structure in extreme wave condition, which has larger natural period than that of waves in sea. In this paper, the time domain simulation of motion responses of Spar with catenary mooring line is presented in irregular waves. The memory effect is modeled by added mass at infinite frequency and convolution integrals in terms of wave damping coefficients. The added mass, wave damping coefficients and wave exciting forces are obtained from three-dimensional panel method in the frequency domain. The motion equations are consisted of forces for inertia, memory effect, hydrostatic restoring, wave exciting and mooring line. The forces of mooring line are modeled as quasi-static catenary cable.

• Journal of Information Technology Applications and Management
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• v.28 no.5
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• pp.41-50
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• 2021

As COVID-19 spread widely, and rapidly, the number of misinformation is also increasing, which WHO has referred to this phenomenon as "Infodemic". The purpose of this research is to develop detection and rectification of COVID-19 misinformation based on Open-domain QA system and text similarity. 9 testing conditions were used in this model. For open-domain QA system, 6 conditions were applied using three different types of dataset types, scientific, social media, and news, both datasets, and two different methods of choosing the answer, choosing the top answer generated from the QA system and voting from the top three answers generated from QA system. The other 3 conditions were the Closed-Domain QA system with different dataset types. The best results from the testing model were 76% using all datasets with voting from the top 3 answers outperforming by 16% from the closed-domain model.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.441-451
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• 2017

In this paper, we review principal component analysis (PCA) procedures in the frequency domain and apply them to analyze sea surface temperature data. The classical PCA defined in the time domain is a popular dimension reduction technique. Extending the conventional PCA to the frequency domain makes it possible to define PCA in the frequency domain, which is useful for dimension reduction as well as a feature extraction of multiple time series. We focus on two PCA methods in the frequency domain, Hilbert PCA (HPCA) and frequency domain PCA (FDPCA). We review these two PCAs in order for potential readers to easily understand insights as well as perform a numerical study for comparison with conventional PCA. Furthermore, we apply PCA methods in the frequency domain to sea surface temperature data on the tropical Pacific Ocean. Results from numerical experiments demonstrate that PCA in the frequency domain is effective for the analysis of time series data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.11
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• pp.1082-1089
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• 2012

Recent malicious attempts in Cyber space are intended to emerge national threats such as Suxnet as well as to get financial benefits through a large pool of comprised botnets. The evolved botnets use the Domain Name System(DNS) to communicate with the C&C server and zombies. DNS is one of the core and most important components of the Internet and DNS traffic are continually increased by the popular wireless Internet service. On the other hand, domain names are popular for malicious use. This paper studies on DNS-based cyber threats domain detection by data classification based on supervised learning. Furthermore, the developed cyber threats domain detection system using DNS traffic analysis provides collection, analysis, and normal/abnormal domain classification of huge amounts of DNS data.