• Journal of Pharmaceutical Investigation
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• v.18 no.4
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• pp.187-195
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• 1988

Poorly permeable $Eudragit^{\circledR}$ RS 100 polymer was used as a wall material for the microencapsulation of zipeprol dihydrochloride by a phase separation method from chloroform-cyclohexane system with 5% polyisobutylene in cyclohexane, and microcapsules obtained were evaluated in vitro by particle size analysis, scanning electron microscopy, drug release test and in vivo bioavailability test in rats. The mechanism of drug release from microcapsules appeared to fit Higuchi matrix model kinetics. The area under the first moment of plasma concentration-time curve of the microcapsules obtained was considerably increased (p<0.05) as compared with that from zipeprol dihydrochloride oral solution. Therefore, it may be suggested that $Eudragit^{\cirledR}$ RS 100 coated zipeprol dihydrochloride microcapsules can be used as a sustained release medication.

• Journal of Pharmaceutical Investigation
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• v.18 no.4
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• pp.197-201
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• 1988

Pivaloyloxymethyl ester of cefoperazone was synthesized by treating sodium cefoperazone with chloromethyl pivalate and its chemical structure was determined by spectroscopic trials. The pharmaceutical properties of the ester were investigated to assess its potential as a prodrug of cefo perazone. Cefoperazone pivaloyloxymethyl ester was microbiologically inactive itself in vitro, but hydrolyzed into the parent drug in vivo. After a single oral dose of each drug to rabbits, serum concentrations of cefoperazone were determined by high performance liquid chromatographic assay. The ester showed higher and more sustained blood level than cefoperazone. Therefore, the total area under the serum concentration-time curve of the derivative was 16.8 times larger than that of the parent drug.

• IE interfaces
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• v.6 no.2
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• pp.151-169
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• 1993

In this research, we proposed "coefficient of inequality" as a measure of distributional inequality for an alternative, which is defined as the area between the diagonal line from 0 to 1 and the Lorenz curve of the given alternative. Next, we showed theoretical relationship between stochastic dominance and the coefficient of inequality as a means to determine the preferred alternative when decision is made with incomplete information about decision maker's utility function. Then, two experiments were performed to test subject‘s attitude toward risk. The results of the experiments support the idea that when a decision maker is risk averse or risk prone, he/she can use the coefficient of inequality as a decision rule to choose the preferred alternative instead of using stochastic dominance. Thus, according to decision maker’s attitude toward risk, the decision rule proposed here can be used as a valuable aid in decision making under uncertainty with incomplete information.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.439-446
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• 2015

Recently, the importance of one-class classification problem is more increasing. However, most of existing algorithms have the limitation on providing the information that effects on the prediction of the target value. Motivated by this remark, in this paper, we suggest an efficient one-class classifier using hyper-rectangles (H-RTGLs) that can be produced from intervals including observations. Specifically, we generate intervals for each feature and integrate them. For generating intervals, we consider two approaches : (i) interval merging and (ii) clustering. We evaluate the performance of the suggested methods by computing classification accuracy using area under the roc curve and compare them with other one-class classification algorithms using four datasets from UCI repository. Since H-RTGLs constructed for a given data set enable classification factors to be visible, we can discern which features effect on the classification result and extract patterns that a data set originally has.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.9-10
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• 2007

In this paper, we investigated the effect of solar cell breakage on maximum output power of PV module. The test result using artificial light source didn't give any change in output power in case of crack near electrical ribbon. Also, there was a reduction in output power in case of increasing of crack area far from electrical ribbon. But, this experiment is under artificial light source test method. So, when such a PV module is outdoor for a long time, there would be problems on electrical output power and durability because of thermal aging phenomenon of solar cell breakage.

• Journal of Multimedia Information System
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• v.5 no.2
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• pp.99-104
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• 2018

Phishing website has become a crucial concern in cyber security applications. It is performed by fraudulently deceiving users with the aim of obtaining their sensitive information such as bank account information, credit card, username, and password. The threat has led to huge losses to online retailers, e-business platform, financial institutions, and to name but a few. One way to build anti-phishing detection mechanism is to construct classification algorithm based on machine learning techniques. The objective of this paper is to compare different classifier ensemble approaches, i.e. random forest, rotation forest, gradient boosted machine, and extreme gradient boosting against single classifiers, i.e. decision tree, classification and regression tree, and credal decision tree in the case of website phishing. Area under ROC curve (AUC) is employed as a performance metric, whilst statistical tests are used as baseline indicator of significance evaluation among classifiers. The paper contributes the existing literature on making a benchmark of classifier ensembles for web phishing detection.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1203-1212
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• 2017

Intrusion detection systems (IDSs) are crucial in this overwhelming increase of attacks on the computing infrastructure. It intelligently detects malicious and predicts future attack patterns based on the classification analysis using machine learning and data mining techniques. This paper is devoted to thoroughly evaluate classifier ensembles for IDSs in IEEE 802.11 wireless network. Two ensemble techniques, i.e. voting and stacking are employed to combine the three base classifiers, i.e. decision tree (DT), random forest (RF), and support vector machine (SVM). We use area under ROC curve (AUC) value as a performance metric. Finally, we conduct two statistical significance tests to evaluate the performance differences among classifiers.

• Korean Journal of Clinical Pharmacy
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• v.9 no.1
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• pp.66-70
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• 1999

The effect of circadian rhythm on cyclosporine pharmacokinetics was studied in rabbits after oral administration of 10 mg/kg dose of cyclosporine at 10:00 a.m. and 10:00 p.m. The blood concentration data were subjected to simultaneous computer nonlinear least squares regression analysis using a 1-compartment pharmacokinetic model. The blood concentrations of cyclosporine at 10:00 a. m. were increased significantly during 2-6 hr compared to those at 10:00 p.m. The area under the blood concentration-time curve (AUC) and peak concentration $(C_{max})$ of cyclosporine at 10:00 a.m. were increased significantly compared to those at 10:00 p.m. The mean total body clearance (CL) of cyclosporine at 10:00 a.m. were decreased significantly compared to those at 10:00 p.m. It is reasonable to consider individual circadian rhythm for effective dosage regimen of cyclosporine in therapeutics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1722-1737
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• 2019

We developed an insider threat detection model to be used by organizations that repeat tasks at regular intervals. The model identifies the best combination of different feature selection algorithms, unsupervised learning algorithms, and standard scores. We derive a model specifically optimized for the organization by evaluating each combination in terms of accuracy, AUC (Area Under the Curve), and TPR (True Positive Rate). In order to validate this model, a four-year log was applied to the system handling sensitive information from public institutions. In the research target system, the user log was analyzed monthly based on the fact that the business process is processed at a cycle of one year, and the roles are determined for each person in charge. In order to classify the behavior of a user as abnormal, the standard scores of each organization were calculated and classified as abnormal when they exceeded certain thresholds. Using this method, we proposed an optimized model for the organization and verified it.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.490-493
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• 2021

This paper proposes an embedded system that detects mask and face recognition based on a microprocessor instead of Nvidia Jetson Board what is popular development kit. We use a class of efficient models called Mobilenets for mobile and embedded vision applications. MobileNets are based on a streamlined architechture that uses depthwise separable convolutions to build light weight deep neural networks. The device used a Maix development board with CNN hardware acceleration function, and the training model used MobileNet_V2 based SSD(Single Shot Multibox Detector) optimized for mobile devices. To make training model, 7553 face data from Kaggle are used. As a result of test dataset, the AUC (Area Under The Curve) value is as high as 0.98.