• Toxicological Research
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• v.35 no.4
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• pp.343-351
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• 2019

Many in vitro developmental toxicity assays have been proposed over several decades. Since the late 1980s, we have made intermittent attempts to introduce in vitro assays as screening tests for developmental toxicity of inhouse candidate products. Two cell-based assays which were developed two decades apart were intensively studied. One was an assay of inhibitory effects on mouse ascites tumor cell attachment to a concanavalin A-coated plastic sheet surface (MOT assay), which we studied in the early days of assay development. The other was an assay of inhibitory effects on the differentiation of mouse embryonic stem cell to beating heart cells (EST assay), which we assessed more recently. We evaluated the suitability of the assays for screening in-house candidates. The concordance rates with in vivo developmental toxicity were at the 60% level. The EST assay classified chemicals that inhibited cell proliferation as embryo-toxic. Both assays had a significant false positive rate. The assays were generally considered unsuitable for screening the developmental toxicity of our candidate compounds. Recent test systems adopt advanced technologies. Despite such evolution of materials and methods, the concordance rates of the EST and MOT systems were similar. This may suggest that the fundamental predictivity of in vitro developmental toxicity assays has remained basically unchanged for decades. To improve their predictivity, in vitro developmental toxicity assays should be strictly based on elucidated pathogenetic mechanisms of developmental toxicity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2391-2398
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• 2009

Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and prevention of possible life threatening cardiac diseases. Most of the algorithms detecting PVC reported in literature is not always feasible due to the presence of noise and P wave making the detection difficult, and the process being time consuming and ineffective for real time analysis. To solve this problem, a new approach for the detection of PVC is presented based rhythm analysis and beat matching in this paper. For this purpose, the ECG signals are first processed by the usual preprocessing method and R wave was detected. The algorithm that decides beat type using the rhythm analysis of RR interval and beat matching of QRS width is developed. The performance of R wave and PVC detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate sensitivity of 99.74%, positive predictivity of 99.81% and sensitivity of 93.91%, positive predictivity of 96.48% accuracy respectively for R wave and PVC detection.

• Proceedings of the Korean Society for Language and Information Conference
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• 1998.02a
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• pp.152-162
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• 1998

• Korean Journal of Cognitive Science
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• v.19 no.3
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• pp.297-310
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• 2008

Since speech acts implies speakers' intentions, it is essential to determine speakers' speech acts if we want to implement an intelligent dialogue system. We propose a two-step model for effectively determining speakers' speech acts. In the first step, the proposed model returns speech act candidates by using a neural network model based on machine learning and a predictivity model based on statistics, respectively. In the second step, using speech act candidates which are returned by the predictivity model, the proposed model filters out speech act candidates which are returned by the neural network model. Then, the proposed model selects a speech act with maximum output value among the unremoved speech act candidates. In the experiment on a schedule management domain, the proposed two-step modeling method showed better precisions than the previous methods only using a machine learning model or a probability model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.561-568
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• 1994

A man model can be used as an effective tool to design ergonomically sound products and workplaces, and subsequently evaluate them properly. For a man model to be truly useful, it must be integrated with a posture prediction model which should be capable of representing the human arm reach posture in the context of equipments and workspaces. Since the human movement possesses redundant degrees of freedom, accurate representation or prediction of human movement was known to be a difficult problem. To solve this redundancy problem, a psychophysical cost function was suggested in this study which defines a cost value for each joint movement angle. The psychophysical cost function developed integrates the psychophysical discomfort of joints and the joint range availability concept which has been used for redundant arm manipulation in robotics to predict the arm reach posture. To properly predict an arm reach posture, an arm reach posture prediction model was then developed in which a posture configuration that provides the minimum total cost is chosen. The predictivity of the psychophysical cost function was compared with that of the biomechanical cost function which is based on the minimization of joint torque. Here, the human body is regarded as a two-dimensional multi-link system which consists of four links ; trunk, upper arm, lower arm and hand. Real reach postures were photographed from the subjects and were compared to the postures predicted by the model. Results showed that the postures predicted by the psychophysical cost function closely simulated human reach postures and the predictivity was more accurate than that by the biomechanical cost function.

• The Korean Journal of Applied Statistics
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• v.26 no.1
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• pp.15-22
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• 2013

In clinical study or epidemic research, the $2{\times}2$ frequency table is useful to present a summary statistic The values of four cells in $2{\times}2$ table use to calculate the effect measures such as risk ratio, relative ris ratio or odds ratio. In this paper, we suggest that the improved visualization method using a radar diagram supported by MS-office Excel from the $2{\times}2$ frequency table is able to understand and draw easily betweendiagnosti measures such as sensitivity, specificity, predictivity, and likelihood ratio. We use some numerical example in order to show the usage of the proposed method.

• Parasites, Hosts and Diseases
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• v.51 no.4
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• pp.433-440
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• 2013

Toxocariasis is a worldwide zoonosis caused by larvae of ascarid nematodes of dogs or cats, Toxocara canis or T. cati. Diagnosis of human toxocariasis currently relies on serology that uses T. canis excretory-secretory antigen to detect specific IgG antibodies by ELISA. We investigated the serodiagnostic efficacy of ELISA using crude antigen of T. canis larvae (TCLA). Serum specimens of 64 clinically confirmed toxocariasis, 115 healthy controls, and 119 other tissue-invading helminthiases were screened by ELISA using TCLA. The ELISA using TCLA showed 92.2% (59/64 patient samples) sensitivity and 86.6% (103/119) specificity. Its positive diagnostic predictivity was 78.7% and negative predictivity was 97.8%. No serum of healthy controls reacted but that of anisakiasis (45.5%), gnathostomiasis (19.2%), clonorchiasis (15.8%), sparganosis (11.1%), and cysticercosis (6.3%) cross-reacted. Immunoblot analysis on TCLA recognized antigenic proteins of 28- and 30-kDa bands in their dominant protein quantity and strong blotting reactivity. The present results indicate that the ELISA using our TCLA antigen is acceptable by the sensitivity and specificity for serodiagnosis of human toxocariasis. ELISA with TCLA is recommended to make differential diagnosis for patients with any sign of organ infiltration and eosinophilia.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.357-359
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• 2009

In this paper, the 2.4GHz doppler radar system consisting of the doppler radar module and a baseband module were designed to detect heartbeat and respiration signal without direct skin contact. A bio-radar system emits continuous RF signal of 2.4GHz toward human chest, and then detects the reflected signal so as to investigate cardiopulmonary activities. The heartbeat and respiration signals acquired from quadrature signal of the doppler radar system are applied to the pre-processing circuit, amplification circuit, and the offset circuit of the baseband module. ECG(electrocardiogram) and reference respiration signals are measured simultaneously to evaluate the doppler radar system. As a result, the respiration signal of doppler radar signal is detected to 1m without complex digital signal processing. The sensitivity and calculated from I/Q respiration signal were $98.29{\pm}1.79%$, $97.11{\pm}2.75%$, respectively, and positive predictivity were $98.11{\pm}1.45%$, $92.21{\pm}10.92%$, respectively. The sensitivity and positive predictivity calculated from phase and magnitude of the doppler radar were $95.17{\pm}5.33%$, $94.99{\pm}5.43%$, respectively. In this paper, we confirmed that noncontact real-time heartbeat and respiration detection using the doppler radar system has the possibility and limitation.

• Bulletin of the Korean Chemical Society
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• v.33 no.2
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• pp.613-619
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• 2012

We applied several machine learning methods for developing QSAR models for prediction of acute toxicity to fathead minnow. The multiple linear regression (MLR) and artificial neural network (ANN) method were applied to predict 96 h $LC_{50}$ (median lethal concentration) of 555 chemical compounds. Molecular descriptors based on 2D chemical structure were calculated by PreADMET program. The recursive partitioning (RP) model was used for grouping of mode of actions as reactive or narcosis, followed by MLR method of chemicals within the same mode of action. The MLR, ANN, and two RP-MLR models possessed correlation coefficients ($R^2$) as 0.553, 0.618, 0.632, and 0.605 on test set, respectively. The consensus model of ANN and two RP-MLR models was used as the best model on training set and showed good predictivity ($R^2$=0.663) on the test set.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.147-150
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• 1996

Human posture prediction and motion simulation methods try to solve inverse kinematic problems using the optimization technique based on the concept of minimum principle. It is very important to select a cost function which relfects the human posture acurately. In this study, lifting postures were predicted using the five biomechanical cost functions and compared with real human postures in order to evaluate the predictivities of the cost functions. The result showed that all the biomechanical cost functions used in this study could not predict lifting postures accurately. The cost function which minimizes the sum of joint moments showed the smallest mean prediction error, while the one which minimizes the MUR showed statistically better performance.