• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.2
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• pp.23-32
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• 2004

The query optimizer's important task while a query is invoked is to estimate the fraction of records in the databases that satisfy the given query condition. The query result size estimation in spatial databases, like relational databases, proceeds to partition the whole input into a small number of subsets called “buckets” and then estimate the fraction of the input in the buckets. The accuracy of estimation is determined by the difference between the real data counts and approximations in the buckets, and is dependent on how to partition the buckets. Existing techniques for spatial databases are equi-area and equi-count techniques, which are respectively analogous in relation databases to equi-height histogram that divides the input value range into buckets of equal size and equi-depth histogram that is equal to the number of records within each bucket. In this paper we propose a new partitioning technique that determines buckets according to the maximal difference of area which is defined as the product of data ranges End frequencies of input. In this new technique we consider both data values and frequencies of input data simultaneously, and thus achieve substantial improvements in accuracy over existing approaches. We present a detailed experimental study of the accuracy of query result size estimation comparing the proposed technique and the existing techniques using synthetic as well as real-life datasets. Experiments confirm that our proposed techniques offer better accuracy in query result size estimation than the existing techniques for space query size, bucket number, data number and data size.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.553-560
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• 2001

Bioinformatics is a discipline to support biological experiment projects by storing, managing data arising from genome research. In can also lead the experimental design for genome function prediction and regulation. Among various approaches of the genome research, the proteomics have been drawing increasing attention since it deals with the final product of genomes, i.e., proteins, directly. This paper proposes a data mining technique to predict the structural characteristics of a given protein group, one of dominant factors of the functions of them. After explains associations among amino acid subsequences in the primary structures of proteins, which can provide important clues for determining secondary or tertiary structures of them, it defines a sequence association rule to represent the inter-subsequences. It also provides support and confidence measures, newly designed to evaluate the usefulness of sequence association rules, After is proposes a method to discover useful sequence association rules from a given protein group, it evaluates the performance of the proposed method with protein sequence data from the SWISS-PROT protein database.

• Journal of Korean Library and Information Science Society
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• v.53 no.4
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• pp.293-318
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• 2022

The purpose of this study is to analyze the impact of reading on self-efficacy and multicultural acceptance. The Korean Education and Employment Pannel II data were used for the analysis. Through analyzing the data with latent growth model, the growth trajectories for reading, self-efficacy, and multicultural acceptance were identified, and the relationship between three variances were analyzed using multi-variate latent growth model. As results, reading books, self-efficacy, and multicultural acceptance were decreased, as times go by. Next, the intercept of reading was postively related with self-efficacy and multicultural acceptance. Finally, self-efficacy mediated between the intercept of reading and the multicultural acceptance, and it's statistically significant.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• Journal of the Korean Data and Information Science Society
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• v.21 no.1
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• pp.139-146
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• 2010

It was verified that the effect of the distance between current input point and output point on direct current potential drop (DCPD) in the material with two-dimensional surface notch. If the distance between potential drop measuring points was fixed at a certain distance, the potential drop was decreased with increasing the distance between current input and output points. DCPD technique was a useful method for surface crack sizing because the potential drop was proportional to the length of notch. In this paper, we suggest a statistical model to describe the data and want to find a significant variables to effect to potential drop. We use R program to analyze the data.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.89-96
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• 2009

We examined the characteristics of temperature variation in Seoul between 1961 to 2008 using the spectral heteroscedastic model. The mean function in the propsed model explains the season effect using periodic functions and the overall increase using the quadratic regression spline. The variance function also had periodic functions to explain the seasonality of variance. We found that there has been annual mean temperature increase by about $1.5^{\circ}C$ for the last 48 years. The increase of annual mean temperature was mainly caused by the increase in winter, which made the amplitude decreased.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.204-207
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• 2018

IoT 기기 및 드론의 사용자 인증 및 기기 인증을 위해 RSA, ECDSA 등의 여러 전자서명 기법이 기본적으로 사용되고 있다. 그러나 양자 컴퓨터의 개발에 따라 Shor 알고리즘을 이용한 기존 암호 알고리즘의 공격이 가능해지고, 그에 따라 기존 암호 알고리즘의 보안성이 취약해지는 문제가 있다. 따라서 양자 내성 암호를 활용한 보안 체계의 필요성이 대두되고 있는 가운데, 본 논문에서는 양자 내성 암호인 다변수 이차식 기반의 전자서명 기법 중 Rainbow를 드론에 최적화하여 구현하기 위한 방안을 검토 및 분석하고자 한다. 그러나 기존의 Rainbow에서 사용하는 openssl 등의 오픈소스 암호 라이브러리는 PC에 맞춰 설계되었기 때문에 드론에서 난수를 생성할 때 적용이 어려운 점이 있다. 드론에는 각종 센서들이 내장되어 있으며, 센서 데이터들은 난수성을 보장하기에 용이하다. 따라서 드론의 각종 센서들을 시드로 활용하며, XOR 보정기를 통해 난수성을 해치지 않으면서 드론에서 난수를 생성할 수 있는 방안을 제안해 보고자 한다.

• Journal of The Geomorphological Association of Korea
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• v.19 no.2
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• pp.145-159
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• 2012

Fracture patterns observed in the phyllosilicate-bearing layers of the Mawrth Vallis region are analyzed using High Resolution Imaging Science Experiment image data in order to understand the causes of polygonal fracturing. HiRISE data show that the different mineralogies have distinct surface textures and morphologies. The majority of the nontronite-bearing rocks typically appear to have been heavily eroded and are fractured into irregular shaped blocks with variable size, whereas most of the montmorillonite-bearing rocks have polygons which are relatively consistent in size and shape. The majority of the fracture patterns observed in the nontronite-bearing outcrops are interpreted to be a result of unloading stresses. While the polygonal fractures developed in the montmorillonite-bearing layers appear to be a product of desiccation.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1379-1386
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• 2006

전자우편이나 문자 메세지를 이용할 때 겪는 불편함 중 하나는 상대방이나 기계에 정서 정보를 전달하기 어렵다는 점이다. 정서 정보를 메시지에 싣기 위해서는 컴퓨터나 디지털 기기가 정서를 인식하거나 사용자가 정서를 입력해야 한다. 기존의 정서 인식 방법은 생리적, 신체적 측정치를 이용하는 것인데, 이 경우 측정을 위한 별도의 장비가 필요하고 현재 자신의 정서 상태와 다른 정서를 표현할 수 없다는 단점이 있다. 특히 소형 모바일 기기를 이용할 때 다른 측정 장치를 사용하는 것은 더욱 어렵다. 이런 문제를 해결하기 위해 모바일 기기를 사용하는 환경에서 사용자가 원하는 정서를 기계에 입력하기 위해 동작을 이용하려는 연구가 진행되었다(Fargerberg, Stahl, & Hook, 2003). 본 연구에서는 Laban Movement Analysis에서 동작을 구성하는 다섯 요소 중 노력(effort)과 모양(shape) 요소를 재구성하여, 방향성 차원, 무게감 차원, 시간감 차원으로 동작을 구분하고 총 20개의 동작을 선정하였다. 또한 한덕웅과 강혜자(2000)가 수집한 834개 정서 어휘를 평정하여 동작을 통해 표현하고 전달되기 쉬운 정서 어휘 50개를 선택하였다. 최종 실험에서 참가자들은 20개의 동작에 대해 50개의 정서 어휘를 평정하고 데이터는 범주형 주성분분석을 이용하여 분석하였다. 분석 결과 Russell(1980)의 이차원 정서 구조 모형에서 각성 수준 차원은 동작의 무게감과 시간감 차원과 관련이 있는 것으로 나타났다. 강하고 빠른 동작일수록 각성 수준이 높은 정서가 나타났다. 또한 동작의 방향성 차원은 정서의 종류와 관련이 있는 것으로 드러났다. 직선 움직임은 높은 각성 수준의 부정적 정서와, 흔듦 움직임은 불안 및 초조와, 원형 움직임은 즐거운 정서와 관련이 있는 것으로 나타났다. 이는 동작을 통하여 정서 정보를 효과적으로 전달할 수 있음을 보여주었고, 동작과 정서를 연관 짓기 위해 방향성 차원과 무게감 차원 그리고 시간감 차원을 고려할 필요가 있음을 시사한다.

• Journal of Industrial Convergence
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• v.18 no.5
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• pp.62-69
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• 2020

The purpose of this study was to investigate the relationship between serum vitamin E levels and the risk of allergic rhinitis among Koreans. This study is a secondary data analysis using big data from the seventh Korea National Health and Nutrition Examination Survey (KNHANES VII-3), which was conducted in 2018. Complex-sample descriptive statistics, t-test, ANOVA and odds ratio were used for data analysis in SPSS 25. The average serum vitamin E level among Koreans aged above 10 was 12.60 mg/L, and 15.9% had been diagnosed with of allergic rhinitis by a doctor. Lower serum vitamin E levels were significantly associated with the prevalence of allergic rhinitis (β=-0.05, p=.013). Therefore, efforts to prevent and manage allergic rhinitis among Koreans should incorporate regular monitoring of vitamin E level and ongoing research into antioxidants.