• 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.

• 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.

• The Journal of Korean Association of Computer Education
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• v.18 no.5
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• pp.63-70
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• 2015

In the environment that the complex conditions need to be satisfied, skyline query have been applied to various field. To processing a skyline query in centralized scheme, several techniques have been suggested and recently map/reduce platform based approaches has been proposed which divides data space into multiple partitions for the vast volume of multidimensional data. However, the performances of these approaches are fluctuated due to the uneven data loading between servers and redundant tasks. Motivated by these issues, this paper suggests a novel technique called MR-DEAP which solves the uneven data loading using the random sampling. The experimental result gains the proposed MR-DEAP outperforms MR-Angular and MR-BNL scheme.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.46-46
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• 2004

디지털 측정장치의 발달에 따라 센서에서 출력되는 아날로그 신호를 디지털 신호로 변환하고, 이를 바탕으로 측정결과를 제시하는 경우가 많다. 그러나 아날로그 신호의 디지털화 과정에서는 정보의 유실이 생길 수밖에 없고, 또한 측정 헤드의 dimension 과 sampling interval 등과 같은 측정조건은 측정결과의 신뢰성에 많은 문제를 야기 시킨다. 본 연구에서는 새로운 측정방법을 바탕으로 시장-분산곡선과 Correlogram 법을 이용하여 그 특성을 해석하고, 데이터 샘플링 시 측정조건과 시료내의 변동성이 측정결과인 평균 굵기 및 굵기의 총분산에 미치는 영향을 찾아 보았다.(중략)