• Journal of the Korean Professional Engineers Association
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• v.42 no.2
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• pp.54-60
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• 2009

On January of this year, the 29th National Science and Technology Council, presided by President M.B. Lee, officially finalized a contract for a big project to build an International Science and Business Belt(ISBB) that includes the establishment of a new institute, the Asian Basic Science Institute (ABSI) and the construction of a Rare Isotope Accelerator. The government will inject more than 3.5 trillion Wan into the ISBB project. The investment to build the care laboratory for the project, the heavy ion accelerator, the first one in Korea, will be 460 billion Wan, Korea thus aiming to build an accelerator with world-class performance. This will be the sixth in the world. The construction will start from 2012, and is planned to finish by 2015. ABSI, whose construction will be finished by 2012, is planned to be a care laboratory with 3,000 scientists and staff. To. attract world class researchers and other professionals from aver the world, the project includes the creation of a new city with a superb educational, cultural environment, and comfortable living environment for an international community. The site for this new science and business city, "scientific ecosystem", has not been officially decided yet, and supposed to be announced in the first half af this year.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.24 no.3
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• pp.243-291
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• 2020

In this paper, multi-block generalized backward differentiation methods for numerical solutions of ordinary differential and differential algebraic equations are introduced. This class of linear multi-block methods is implemented as multi-block boundary value methods (MB₂ VMs). The root distribution of the stability polynomial of the new class of methods are determined using the Wiener-Hopf factorization of a matrix polynomial for the purpose of their correct implementation. Numerical tests, showing the potential of such methods for output of multi-block of solutions of the ordinary differential equations in the new approach are also reported herein. The methods which output multi-block of solutions of the ordinary differential equations on application, are unlike the conventional linear multistep methods which output a solution at a point or the conventional boundary value methods and multi-block methods which output only a block of solutions per step. The MB₂ VMs introduced herein is a novel approach at developing very large scale integration methods (VLSIM) in the numerical solution of differential equations.

• Bulletin of the Korean Mathematical Society
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• v.58 no.5
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• pp.1221-1233
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• 2021

In this paper, we introduce and investigate a new class of modules that is closely related to the class of Noetherian modules. Let R be a commutative ring and M be an R-module. We say that M is an r-Noetherian module if every r-submodule of M is finitely generated. Also, we call the ring R to be an r-Noetherian ring if R is an r-Noetherian R-module, or equivalently, every r-ideal of R is finitely generated. We show that many properties of Noetherian modules are also true for r-Noetherian modules. Moreover, we extend the concept of weakly Noetherian rings to the category of modules and we characterize Noetherian modules in terms of r-Noetherian and weakly Noetherian modules. Finally, we use the idealization construction to give non-trivial examples of r-Noetherian rings that are not Noetherian.

• Journal of Technologic Dentistry
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• v.42 no.4
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• pp.402-408
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• 2020

Purpose: To understand the students' level of recognition of online classes in the Department of Dental Technology and to provide the basic data for designing online classes based on the dental technology course. Methods: A survey was conducted among the students of the dental technology department. The collected data was analyzed with the SPSS ver. 25.0 program. To ensure a reliable verification, the α=0.05 significance level was used. The t-test and analysis of variance were also performed. Results: The students' level of recognition of online classes in the Department of Dental Technology is shown in the rate of recognition for video-based classes for both the theory and experiments. Students displayed high positivity with the video-based learning as it is repeated learning that is not affected by the limitations of time. In addition, video-based learning is highly beneficial in terms of convenience, satisfaction, and achievement for learning. Conclusion: Based on the results, video-based learning is a highly positive learning type for students. It was also recommended that the Department of Dental Technology should offer a post-COVID-19 online class to include the blended methods of a face-to-face class and video-based learning.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.142-146
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• 1996

In this paper, we present the main research results on the 2 Tesla class - superconducting MRI magnet which we have developed. Multi section type superconducting MRI main coil and various superconducting shims were designed and fabricated for obtaining the high field homogeneity, which is requested in the MR imaging. After assembling the magnet with room temperature bore cryostat field homogenity has been measured and analyzed by NMR field mapping system. According to this, field homogeneity of 22 ppm / 30 cm dsv was confirmed.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.828-835
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• 2008

We present a novel method for eye location by means of a two-level classifier scheme. Locating the eye by machine-inspection of an image or video is an important problem for Computer Vision and is of particular value to applications in biomedical imaging. Our method aims to overcome the significant challenge of an eye-location that is able to maintain high accuracy by disregarding highly variable changes in the environment. A first level of computational analysis processes this image context. This is followed by object detection by means of a two-class discrimination classifier(second algorithmic level).We have tested our eye location system using FERET and BioID database. We compare the performance of two-level classifier with that of non-level classifier, and found it's better performance.

• ETRI Journal
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• v.35 no.3
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• pp.546-549
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• 2013

A Ka-band 6-W high power microwave monolithic integrated circuit amplifier for use in a very small aperture terminal system requiring high linearity is designed and fabricated using commercial 0.15-${\mu}m$ GaAs pHEMT technology. This three-stage amplifier, with a chip size of 22.1 $mm^2$ can achieve a saturated output power of 6 W with a 21% power-added efficiency and 15-dB small signal gain over a frequency range of 28.5 GHz to 30.5 GHz. To obtain high linearity, the amplifier employs a class-A bias and demonstrates an output third-order intercept point of greater than 43.5 dBm over the above-mentioned frequency range.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1173-1192
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• 2015

The Support Vector Data Description (SVDD) has achieved great success in anomaly detection, directly finding the optimal ball with a minimal radius and center, which contains most of the target data. The SVDD has some limited classification capability, because the hyper-sphere, even in feature space, can express only a limited region of the target class. This paper presents an anomaly detection algorithm for mitigating the limitations of the conventional SVDD by finding the minimum volume enclosing ellipsoid in the feature space. To evaluate the performance of the proposed approach, we tested it with intrusion detection applications. Experimental results show the prominence of the proposed approach for anomaly detection compared with the standard SVDD.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.301-304
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• 2005

For detecting an intrusion based on the anomaly of a user's activities, previous works are concentrated on statistical techniques or frequent episode mining in order to analyze an audit data. But, since they mainly analyze the average behaviour of user's activities, some anomalies can be detected inaccurately. Therefore, we propose an anomaly detection method that utilizes an associative classification for modelling intrusion detection. Finally, we proof that a prediction model built from associative classification method yields better accuracy than a prediction model built from a traditional methods by experimental results.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.713-716
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• 2005

In this paper, in order to identify and recognize attack patterns, we propose a Bayesian classification using frequent patterns. In theory, Bayesian classifiers guarantee the minimum error rate compared to all other classifiers. However, in practice this is not always the case owing to inaccuracies in the unrealistic assumption{ class conditional independence) made for its use. Our method addresses the problem of attribute dependence by discovering frequent patterns. It generates frequent patterns using an efficient FP-growth approach. Since the volume of patterns produced can be large, we propose a pruning technique for selection only interesting patterns. Also, this method estimates the probability of a new case using different product approximations, where each product approximation assumes different independence of the attributes. Our experiments show that the proposed classifier achieves higher accuracy and is more efficient than other classifiers.