• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.265-274
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• 2021

Outlier detection research in ocean data has traditionally been performed using statistical and distance-based machine learning algorithms. Recently, AI-based methods have received a lot of attention and so-called supervised learning methods that require classification information for data are mainly used. This supervised learning method requires a lot of time and costs because classification information (label) must be manually designated for all data required for learning. In this study, an autoencoder based on unsupervised learning was applied as an outlier detection to overcome this problem. For the experiment, two experiments were designed: one is univariate learning, in which only SST data was used among the observation data of Deokjeok Island and the other is multivariate learning, in which SST, air temperature, wind direction, wind speed, air pressure, and humidity were used. Period of data is 25 years from 1996 to 2020, and a pre-processing considering the characteristics of ocean data was applied to the data. An outlier detection of actual SST data was tried with a learned univariate and multivariate autoencoder. We tried to detect outliers in real SST data using trained univariate and multivariate autoencoders. To compare model performance, various outlier detection methods were applied to synthetic data with artificially inserted errors. As a result of quantitatively evaluating the performance of these methods, the multivariate/univariate accuracy was about 96%/91%, respectively, indicating that the multivariate autoencoder had better outlier detection performance. Outlier detection using an unsupervised learning-based autoencoder is expected to be used in various ways in that it can reduce subjective classification errors and cost and time required for data labeling.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1332-1337
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• 2006

In this paper, a noble second stage hetero-estimator is used for positioning error detection in mobile robot. Previous methods are either expensive in the case of positioning error correction or not able to detect positioning error. To overcome the latter shortage, the positioning error detection is performed using second stage hetero-estimator in motor model of mobile robot without any additional costs. A Kalman filter in the estimator gets the residual of motor current and an adaptive self-tunning filter checks the whiteness of the residual. Some simulation results show the possibility of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1608-1615
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• 1999

In this study, we investigate the inter cell interference of LMDS(Local multipoint Distribution Service) system cell in LMDS system design process. There are several interference sources in LMDS system but we consider co-channel adjacent interference, cross-polarization interference, tx/rx interworking interference as three major factors. As the summation of each interference, C/N is keep 19 dB in 2km range but decreased gradually over 2km. Based on theoretical results, we process the experimental test and get results that C/I=20 dB have to be maintained to transmit the data successfully under rain fall attenuation condition. This experiential results are similar to the theoretical analysis results we examined.

• Fire Science and Engineering
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• v.23 no.3
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• pp.23-30
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• 2009

For managing fire safety system in building by ubiquitous management system, the index system to express the performance level of fire protection system is demanded. If some component formed fire protection system such as sprinkler water supply system is breakdown, that will fall down the performance of fire protection capacity. Consequently, it will affects the level of fire safety of building management and energy response. Consequently, Building fire protection system could give performance level of fire protection condition and the level of fire safety in building. It will also contribute to the development of wide area fire safety management. This development of index system has been developed as a part of the development project of Ubiquitous building fire management system.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.12
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• pp.433-442
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• 2014

In this paper, we introduce the client side cache of distributed file system for enhancing read performance by eliminating the network latency and decreasing the back-end storage burden. This performance enhancement can expand the fields of distributed file system to not only cloud storage service but also high performance storage service. This paper shows that the distributed file system with client side SSD cache can satisfy the requirements of VDI(Virtual Desktop Infrastructure) storage. The experimental results show that full-clone is more than 2 times faster and boot time is more than 3 times faster than NFS.

• Annual Conference of KIPS
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• 2007.05a
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• pp.411-412
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• 2007

자동음성인식 시스템을 이용하는 사용자 입장에서 보면 음성인식시스템을 사용하기 위하여 음성을 입력할 때마다 버튼을 눌러야 하는 Push-To-Talk (PTT) 방식은 여간 번거로운 일이 아닐 수 없다. 그리고 사용자가 원거리에서 음성을 입력하는 경우처럼 PTT 방식 자체가 용이하지 못 한 음성인식 응용분야에서는 Non-Push-To-Talk (NON-PTT) 방식의 필요성이 대두되게 된다. NON-PTT 방식의 음성 전처리를 위해서는 입력신호로부터 음성신호만을 구분해내는 음성판별기술이 필수적이다. 하지만 일상적인 잡음환경에서 음성신호만을 구분해내는 일은 매우 어려운 일이 아닐 수 없다. 본 논문에서는 일상적인 가정잡음환경에 강인한 음성판별방식을 제안한다. 여기서는 음성판별을 위해서 음성의 유성음 특성을 이용하였다. 즉, 일정구간 이상의 음성신호에는 일정구간이상의 유성음 구간이 존재하며 만약 잡음환경에서도 유성음 구간을 잘 검출할 수 있다면 이러한 음성의 특성을 이용하여 검출된 신호가 음성인지 아닌지를 판별할 수 있다. 이를 위하여 여기서는 가정잡음환경에서도 유성음을 잘 검출할 수 있도록 11 가지 유성음 특징들과 이를 이용한 음성판별방법을 제안하였다. 제안된 방법의 성능 평가를 위하여 음성의 끝점검출방법과 통합하여 음성/비음성 판별 테스트를 수행하였으며 테스트 수행결과 열악한 잡음환경에서 80%이상의 비음성을 거절하는 성능을 보였다.

• Landscaping Tree
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• v.80 no.5_6
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• pp.10-13
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• 2004

진한 주홍색의 영롱한 색을 발하여 멀리서도 관상할 수 있는 꽃이 100일 이상 계속된다고 하여 흔히 백일홍이라 불리운다. 수피도 모과나무처럼 얼룩이 져 원숭이도 미끄러진다는 일본명을 가지고 있을 만큼 아름답다. (중략)

• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.511-520
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• 2013

Detection outliers and robust estimators are crucial in regression models with outliers. In such studies the focus is on detecting outliers and estimating the coefficients using leave-one-out. Our study introduces Rice estimator which is an error variance estimator without estimating the coefficients. In particular, we study a comparison of the statistical properties for Rice estimator with and without outliers in simple regression models.

• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.39-48
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• 2022

Cyberattacks around the world continue to increase, and their damage extends beyond government facilities and affects civilians. These issues emphasized the importance of developing a system that can identify and detect cyber anomalies early. As above, in order to effectively identify cyber anomalies, several studies have been conducted to learn BGP (Border Gateway Protocol) data through a machine learning model and identify them as anomalies. However, BGP data is unbalanced data in which abnormal data is less than normal data. This causes the model to have a learning biased result, reducing the reliability of the result. In addition, there is a limit in that security personnel cannot recognize the cyber situation as a typical result of machine learning in an actual cyber situation. Therefore, in this paper, we investigate BGP (Border Gateway Protocol) that keeps network records around the world and solve the problem of unbalanced data by using SMOTE. After that, assuming a cyber range situation, an autoencoder classifies cyber anomalies and visualizes the classified data. By learning the pattern of normal data, the performance of classifying abnormal data with 92.4% accuracy was derived, and the auxiliary index also showed 90% performance, ensuring reliability of the results. In addition, it is expected to be able to effectively defend against cyber attacks because it is possible to effectively recognize the situation by visualizing the congested cyber space.

• Journal of dental hygiene science
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• v.14 no.2
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• pp.114-122
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• 2014

The purpose of this study was to analyze the effect of mediating variables on the relationship between job stress and stress response. A survey was conducted to 243 clinical dental hygienists from January 15, 2013 to March 20, 2013 and the data were analyzed using t-test, one-way ANOVA, Pearson's correlation analysis, and hierarchical multiple regression analysis. The subjects who worked in poor working environment, had high level of role conflict and overload and aggressive nature showed high stress responsivity (p<0.01). The variable that showed mediation effect on the relationship between job stress and physical discomfort, depression was shown to be personality type (p<0.05). Also, the variable that showed mediation effect on the relationship between job stress and turnover intention was social support (p<0.05). According to the results, personality type and social support were shown to be important parameters when it came to the relationship between job stress and stress response. Therefore, in order to reduce negative outcomes caused by stress, it is suggested to provide an educational opportunity on self-control management while increasing social support from the organizational and structural level. Especially, it is asked to expand the system that provides encouragement and recognition to feel the sense of achievement in the course of their duty execution.