• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.633-645
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• 2018

Gaussian error distributions are a common choice in traditional regression models for the maximum likelihood (ML) method. However, this distributional assumption is often suspicious especially when the error distribution is skewed or has heavy tails. In both cases, the ML method under normality could break down or lose efficiency. In this paper, we consider the log-concave and Gaussian scale mixture distributions for error distributions. For the log-concave errors, we propose to use a smoothed maximum likelihood estimator for stable and faster computation. Based on this, we perform comparative simulation studies to see the performance of coefficient estimates under normal, Gaussian scale mixture, and log-concave errors. In addition, we also consider real data analysis using Stack loss plant data and Korean labor and income panel data.

• Journal of Korean Society on Water Environment
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• v.27 no.3
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• pp.329-333
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• 2011

p-phenylene-2,5-benzobisoxazole (PBO; Zylon$(R)$) fibers as an adsorbent were employed for solid phase extraction of aqueous alkylphenols. The removal ratios for 10 kinds of alkylphenols at initial concentration of $100{\mu}gL^{-1}$ were in the range of 16.8-96.3% and the removals increased with the increase of the phase ratio (fiber weight/solution volume). The plots of the logarithm of partition coefficient (log K) were correlated with the logarithm of the n-octanol/water partition coefficient (log P). The adsorbed alkylphenols were completely desorbed with the mixture of acetonitrile and dichloromethane.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.304-305
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• 2023

드론 비행 후 추출할 수 있는 Log 파일은 드론의 비행 정보를 확인할 수 있는 데이터이다. 이 데이터를 Log 분석기를 사용하여 그래프 형태로 시각화 하게 되면 비행 속도, 거리, 높이 등 다양한 비행데이터를 분석하기에 용이하다. 또한 Log 분석 자료에는 기체운용 중 발생하는 안전 이슈에 대한 기록도 포함되어 있어 드론의 사고 또는 고장유무를 판단할 때에 중요한 자료로서 활용된다. 그러므로 데이터분석 시에 안전 이슈 발생 시점과 연관지어 데이터를 분석하는 것이 보다 효과적이다. 그러나 상용 서비스에서는 분석데이터와 안전 이슈 데이터를 함께 보는 방법은 제공되지 않는다. 따라서 본 논문에서는 기존의 Log 분석 시스템에 안전 이슈 정보를 추가하여 볼 수 있는 방법을 제시하여 드론 운용자가 로그분석을 보다 효과적으로 할 수 있는 방법을 제안하고자 한다.

• Journal of The Korean Society of Integrative Medicine
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• v.4 no.4
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• pp.109-117
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• 2016

Purpose : This study was designed to provide basic data of effective sanitization method of sprout vegetable for microbiological safety. Methods : Sanitization treatments were performed by dipping the sprout into chlorine and vinegar water. Microbial analysis were composed of the total plate count(TPC) and coliform group count(CGC). Result : Among chlorine water sanitization, the microbial reduction was largest in 100ppm chlorine water, and its TPC and coliform group count decreased to 6.01 log CFU/g and 5.06 log CFU/g. The effective dipping time in 100ppm chlorine water treatment was 5.97 log CFU/g and 5.91 log CFU/g for 30min and 60min, in which TPC were below the microbiological safety limits of 6.00 log CFU/g. Coliform group counts were decreased to 5.44, 5.46, 5.42 log CFU/g in the dipping the spouts for 30min, 60min and 90min. As a result of sanitizing alfalfa spout by vinegar water, a microbial counts tended to decrease with increasing concentration and the dipping time. The effective concentration of vinegar water was 2% for TPC(6.00 log CFU/g) and 1% for coliform group count(5.20 log CFU/g). With 1% vinegar water treatment, TPC became below the microbiological safety limits in all samples and in particular, the sample treated for 60min and 90min(4.93, 4.54 log CFU/g). While coliform group counts were decreased to 3.91 log CFU/g in the dipping the sprouts for 90min, those were still beyond the permitted limit. Conclusion : To secure the food safety of food service facilities including kindergarten feeding, it is considered that along with the systematic study of effective disinfection method for microbiological control at the preconditioning level of spout vegetable within the range of secured maleficence to human body, and the study regarding the measures to lower the initial microbiological pollution of spout vegetable.

• Korean Journal of Soil Science and Fertilizer
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• v.47 no.6
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• pp.510-517
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• 2014

The purpose of this study was to analyze microbial hazards for cultivation environments and personal hygiene of strawberry and tomato farms at the growth and harvesting stage. Samples were collected from thirty strawberry farms and forty tomato farms located in Korea and tested for Staphylococcus aureus and Bacillus cereus. To investigate the change in the distribution of the S. aureus and B. cereus, a total of 4,284 samples including air born, soil or medium, mulching film, harvest basket, groves and irrigation water etc. were collected from eight strawberry farms and nine tomato farms for one year. As a result, total S. aureus and B. cereus in all samples were detected. Among the total bacteria of strawberry farms, S. aureus (glove: $0{\sim}2.1Log\;CFU/100cm^2$, harvest basket: $0{\sim}3.0Log\;CFU/100cm^2$, soil or culture media: 0~4.1 Log CFU/g, mulching film: $0{\sim}3.8Log\;CFU/100cm^2$), B. cereus (glove: $0{\sim}2.8Log\;CFU/100cm^2$, harvest basket: $0{\sim}4.8Log\;CFU/100cm^2$, soil or culture media: 0~5.3 Log CFU/g, mulching film: $0{\sim}4.5Log\;CFU/100cm^2$) were detected in all samples. The total bacteria of tomato farms, S. aureus (glove: $0{\sim}4.0Log\;CFU/100cm^2$, harvest basket: $0{\sim}5.0Log\;CFU/100cm^2$, soil or culture media: 0~6.1 Log CFU/g, mulching film: $0{\sim}4.0Log\;CFU/100cm^2$), B. cereus (glove: $0{\sim}4.0Log\;CFU/100cm^2$, harvest basket: $0{\sim}4.3Log\;CFU/100cm^2$, soil or culture media: 0~5.9 Log CFU/g, mulching film: $0{\sim}4.7Log\;CFU/100cm^2$) were detected in all samples. The contamination of S. aureus and B. cereus were detected in soil, mulching film and harvest basket from planting until harvest to processing, with the highest count recorded from the soil. But S. aureus and B. cereus were not detected in irrigation water samples. The incidence of S. aureus and B. cereus in hydroponics culture farm were less than those in soil culture. The amount of S. aureus and B. cereus detected in strawberry and tomato farms were less than the minimum amount required to produce a toxin that induces food poisoning. In this way, the degree of contamination of food poisoning bacteria was lower in the production environment of the Korea strawberry and tomato, but problems can be caused by post-harvest management method. These results will be used as fundamental data to create a manual for sanitary agricultural environment management, and post-harvest management should be performed to reduce the contamination of hazardous microorganisms.

• YAKHAK HOEJI
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• v.44 no.4
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• pp.308-314
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• 2000

Logarithmic transformation of pharmacokinetic parameters is routinely used in bioequivalence studies based on pharmacokinetic and statistical grounds by the United States Food and Drug Administration (FDA), European Committee for Proprietary Medicinal Products (CPMP), and Japanese National Institute of Health and Science (NIHS). Although it has not yet been recommended by the Korea Food and Drug Administration (KFDA), its use is becoming increasingly necessary in order to harmonize with international standards. In the present study, statistical procedures for the analysis of a bioequivalence based on the log transformation and a related SAS procedure were demonstrated in order to aid the understanding and application. The AUC parameters used in this demonstration were taken from the previous bioequivalence study for two aceclofenac tablets, which were performed in a single-dose crossover design. Analysis of variance (ANOVA), statistical power to detect 20% difference between the tablets, minimum detectable difference and confidence intervals were all assessed following log-transformation of the data. Bioequivalence of two aceclofenac tablets was then estimated based on the guideline of FDA. Considering the international effort for harmaonization of guidelines for bioequivalence tests, this approach may require a further evaluation for a future adaptation in the Korea Guidelines of Bioequivalence Tests (KGBT).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1797-1804
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• 2015

Integrated log management system can help to predict the risk of security and contributes to improve the security level of the organization, and leads to prepare an appropriate security policy. In this paper, we have designed and implemented a Hadoop-based log analysis system by using distributed database model which can store large amount of data and reduce analysis time by automating log collecting procedure. In the proposed system, we use the HBase in order to store a large amount of data efficiently in the scale-out fashion and propose an easy data storing scheme for analysing data using a Hadoop-based normal expression, which results in improving data processing speed compared to the existing system.

• Journal of KIISE
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• v.45 no.3
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• pp.234-241
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• 2018

The study of classifying gamer types or analyzing the characteristics of gamers is a field of interest for data analysis researchers. From the past to the present, much research has been done on gamer categorization and gamer analysis. However, most studies use surveys or bio-signals, which is not practical because it is difficult to obtain large amounts of data. Even if the game log is used, it is difficult to analyze the psychology of the gamer because the gamer is categorized and analyzed by extracting only statistical values. However, if we can extract the cognitive psychology information of the gamer from the basic game log, we can analyze the gamer more intuitively and easily. In this paper, we extracted eight cognitive psychological features representing the behavior and psychological information of the gamer using Crazy Dragon's game log, which is a mobile Role-Playing-Game (RPG). In addition, we classified gamers based upon cognitive psychological features and analyzed them using eight cognitive psychological features. As a result, most gamers were highly correlated with one or two types.

• Journal of Digital Contents Society
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• v.9 no.3
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• pp.491-498
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• 2008

The leakage of sensitive information by an insider within the organization becomes a serious threat nowadays. Sometimes, these insider threats are more harmful to an organization than external attack. Companies cannot afford to continue ignoring the potential of insider attacks. The purpose of this study is to design an integrated log analysis system that can detect various types of information leakages. The system uses threat rules generated through risk analysis, and monitors every aspect of the online activities of authorized insider. Not only should system have the ability to identify abnormal behavior, they should also be able to predict and even help to prevent potential risk. The system is composed of three modules, which are log collector, log analyzer and report generator.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.191-197
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• 2005

Application of data mining techniques to the world wide web, referred to as web mining, has been the focus of several recent researches. With the explosive growth of information sources available on the world wide web, it has become increasingly necessary to track and analyze their usage patterns. In this study, we introduce a process of pre-processing and cluster analysis on web log data and suggest a distance measure considering the structural relationships between web contents. Also, we illustrate some real examples of cluster analysis for web log data and look into practical application of web usage mining for eCRM.