• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.403-411
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• 2023

Functional ultrasound imaging, such as elasticity imaging and micro-blood flow Doppler imaging, enhances diagnostic capability by providing useful mechanical and functional information about tissues. However, the implementation of functional ultrasound imaging poses limitations such as the storage of vast amounts of data in Radio Frequency (RF) data acquisition and processing. In this paper, we propose a sub-Nyquist approach that reduces the amount of acquired axial samples for efficient shear-wave elasticity imaging. The proposed method acquires data at a sampling rate one-third lower than the conventional Nyquist sampling rate and tracks shear-wave signals through RF signals reconstructed using band-pass filtering-based interpolation. In this approach, the RF signal is assumed to have a fractional bandwidth of 67 %. To validate the approach, we reconstruct the shear-wave velocity images using shear-wave tracking data obtained by conventional and proposed approaches, and compare the group velocity, contrast-to-noise ratio, and structural similarity index measurement. We qualitatively and quantitatively demonstrate the potential of sub-Nyquist sampling-based shear-wave elasticity imaging, indicating that our approach could be practically useful in three-dimensional shear-wave elasticity imaging, where a massive amount of ultrasound data is required.

• KIPS Transactions on Computer and Communication Systems
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• v.4 no.2
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• pp.57-64
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• 2015

At the case of peak threshold algorithm, 3-axes data should sample step data over 20 Hz to get sufficient accuracy. But most of the digital sensors like 3-axes accelerometer have very low sampling rate caused by low data communication speed on limited SPI or $I^2C$ bandwidth of the low-cost MPU for ubiquitous devices. If the data transfer rate of the 3-axes accelerometer is getting slow, the sampling rate also slows down and it finally degrades the data accuracy. In this study, we proved there is a distinct functional relation between the sampling rate and threshold on the peak threshold step detection algorithm under the 20Hz frequency, and made a threshold function through the experiments. As a result of experiments, when we apply threshold value from the threshold function instead of fixed threshold value, the step detection error rate can be lessen about 1.2% or under. Therefore, we can suggest a peak threshold based new step detection algorithm with threshold function and it can enhance the accuracy of step detection and step count. This algorithm not only can be applied on a digital step counter design, but also can be adopted any other low-cost ubiquitous sensor devices subjected on low sampling rate.

• Economic and Environmental Geology
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• v.52 no.2
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• pp.199-212
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• 2019

In the machine learning techniques, the sampling strategy of the training data affects a performance of the prediction model such as generalizing ability as well as prediction accuracy. Especially, in landslide susceptibility analysis, the data sampling procedure is the essential step for setting the training data because the number of non-landslide points is much bigger than the number of landslide points. However, the previous researches did not consider the various sampling methods for the training data. That is, the previous studies selected the training data randomly. Therefore, in this study the authors proposed several different sampling methods and assessed the effect of the sampling strategies of the training data in landslide susceptibility analysis. For that, total six different scenarios were set up based on the sampling strategies of landslide points and non-landslide points. Then Random Forest technique was trained on the basis of six different scenarios and the attribute importance for each input variable was evaluated. Subsequently, the landslide susceptibility maps were produced using the input variables and their attribute importances. In the analysis results, the AUC values of the landslide susceptibility maps, obtained from six different sampling strategies, showed high prediction rates, ranges from 70 % to 80 %. It means that the Random Forest technique shows appropriate predictive performance and the attribute importance for the input variables obtained from Random Forest can be used as the weight of landslide conditioning factors in the susceptibility analysis. In addition, the analysis results obtained using specific sampling strategies for training data show higher prediction accuracy than the analysis results using the previous random sampling method.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07a
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• pp.919-921
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• 2005

본 논문은 전체 데이터베이스에서 일부 추출된 샘플 데이터에서 빈발항목 집합을 찾는 연관규칙 마이닝 알고리즘을 기술한다. 샘플링기술을 이용하면 마이닝과정에서 필요한 데이터베이스의 접근 양을 줄이므로써 실행시간을 단축시킬 수 있다는 장점이 있지만, 전체데이터베이스를 이용한 마이닝보다 정확도가 떨어진다는 단점이 함께 존재한다. 이전의 Chen의 FAST알고리즘은 샘플링을 이용한 마이닝과정에서 거리오차함수를 이용한 트리밍과정을 통해 빈발 1항목집합에 대한 정확도를 개선시켰다. 이후 IFAST 알고리즘은 트리밍과정에서 빈발2-항목집합까지 고려하여 빈발2-항목집합 이상의 빈발항목집합에서도 정확도를 개선시켰다. 본 논문에서는 트리밍과정에서 사용될 추정데이터를 여러 개의 샘플데이터를 이용하여 얻으므로써 오류항목집합(false itemset)의 수를 줄이고 전체적인 정확도를 향상시키는 새로운 알고리즘을 소개한다.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.494-504
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• 2002

Volume rendering is a method of displaying volumetric data as a sequence two-dimensional image. Because this algorithm has an advantage of visualizing structures within objects, it has recently been used to analyze medical images i.e, MRI, PET, and SPECT. In this paper. we suggested a method for creating images easily from sampled volumetric data and applied the interpolation method to medical images. Additionally, we implemented and applied two kinds of interpolation methods to improve the image quality, linear interpolation and cubic interpolation at the sampling stage. Subsequently, we compared the results of volume rendered data using a transfer function. We anticipate a significant contribution to diagnosis through image reconstruction using a volumetric data set, because volume rendering techniques of medical images are the result of 3-dimensional data.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.527-530
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• 2024

하이퍼그래프(hypergraph)는 실세계의 여러 객체가 함께 형성하는 복잡한 그룹 관계를 하이퍼엣지(hyperedge)로 정보 손실 없이 모델링할 수 있는 새로운 데이터 구조이다. 하이퍼엣지 예측(hyperedge prediction task)이란 하이퍼그래프로 표현된 실세계 네트워크에서 아직 관찰되지 않은 그룹관계 혹은 미래에 발생할 가능성이 높은 관계를 예측하는 것으로, 단백질 상호작용 분석(PPI), 추천시스템, 소셜 네트워크 분석 등 다양한 응용 분야에서 활용된다. 그러나, 하이퍼엣지 예측은 심각한 데이터 희소성 문제로 정확한 예측이 어렵다는 근본적인 한계를 지닌다. 이러한 한계를 완화하기 위해 다양한 네거티브 샘플링(negative sampling) 기술이 활용될 수 있는데, 아직까지 각 샘플링 기술이 하이퍼엣지 예측 정확도에 미치는 효과에 대해 충분히 연구되지 않았다. 본 논문에서는 하이퍼엣지 예측에 활용되는 다양한 네거티브 샘플링 방법의 효과를 분석한다. 실험 결과를 통해, 네거티브 샘플링 기법과 포지티브와 네거티브 하이퍼엣지 수의 비율에 따른 정확도 변화 양상을 분석한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1872-1879
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• 2022

Recently, with the development of artificial intelligence technology, research to use artificial intelligence to detect hacking attacks is being actively conducted. However, the fact that security data is a representative imbalanced data is recognized as a major obstacle in composing the learning data, which is the key to the development of artificial intelligence models. Therefore, in this paper, we propose a W-VAE oversampling technique that applies VAE, a deep learning generation model, to data extraction for oversampling, and sets the number of oversampling for each class through weight calculation using K-NN for sampling. In this paper, a total of five oversampling techniques such as ROS, SMOTE, and ADASYN were applied through NSL-KDD, an open network security dataset. The oversampling method proposed in this paper proved to be the most effective sampling method compared to the existing oversampling method through the F1-Score evaluation index.

• Review of KIISC
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• v.31 no.1
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• pp.25-39
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• 2021

마이크로아키텍처 데이터 샘플링 공격 중 하나인 Zombieload 공격은 마이크로코드 어시스트를 이용하여 물리 코어를 공유하는 다른 논리 코어가 접근하는 데이터를 읽는 공격이다. 마이크로코드 어시스트는 페이지 폴트 과정에서 로드 명령어를 수행할 때 발생하므로, Zombieload 공격은 시그널 핸들러 또는 TSX로 페이지 폴트를 처리 또는 억제한다. 그러나 시그널 핸들러에서 발생하는 잡음과 TSX를 지원하는 프로세서 수의 부족이 Zombieload 공격의 효율을 감소시킨다. 본 논문에서는 페이지 폴트를 RSB를 이용한 잘못된 추측 실행으로 처리하여, 기존의 한계점을 개선한 새로운 Zombieload 공격을 제안한다. 제안한 공격의 성능을 평가하기 위해, 실험을 통해 기존의 Zombieload 공격과 성능을 비교한다. 끝으로 제안한 공격을 막기 위해 여러 가지 방어 기법을 제시한다.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.71-77
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• 2015

This paper suggested dynamic application framework based data collecting and monitoring technique using wireless sensor network. The development of application for wireless measurement node firmware program integrates with various sensors and performs control. Collecting data of the user application is downloaded from the node onboard process wirelessly. In addition, the user application can change the temperature initial value of the nodes, which enables dynamic sampling of the measurement nodes. Therefore, dynamic sampling control of the nodes can reduce the power consumptions of sensors compared to existing wired data monitoring.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.125-133
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• 2011

According to proliferation of mobile devices, security threats have been continuously increased such as illegal or unintentional file transmission of important data to an external mass-storage device. Therefore, we propose a protection method to prohibit an illegal outflow to this device and implement this method. This method extracts signatures from random locations of important file and uses them to detect and block illegal file transmission. To get signatures, a target file is divided by extracting window size and more than one signatures are extracted in this area. To effective signature sampling, various extraction ways such as full, binomial distribution-based and dynamic sampling are implemented and evaluated. The proposed method has some advantages. The one is that an attacker cannot easily predict the signature and its extraction location. The other is that it doesn't need to modify original data to protect it. With the help of these advantages, we can say that this method can increase efficiency of easy-to-use and it is a proper way leakage prevention in a mobile device.