• Health Policy and Management
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• v.10 no.1
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• pp.31-56
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• 2000

A purpose of this study is to study on Rene Descartes's mind-body theory in medical aspect. Though Rene Descartes was not so much a doctor as a philosopher, he had health and medical science at heart. When he came into the world in 1596, he was in poor health. Therefore, he suffered from his bad health. Descartes's ideas absolutely colored Western thought for three hundred years, especially, his mind-body theory, mechanistic life-view, and reductionism had important effect on medical study and science of public health. As a rule, we know that his mind-body theory was applicable to mind-body dualism, and his mind-body dualism was connected with biomedical model of medicine. But by this study, his mind-body theory was not only mind-body dualism but also mind-body monoism. And he asserted mind-body interaction too. In other words, he advocated mind-body dualism in scientific aspect, but he knew mind-body monoism from his experence. He confessed this fact to Princess Elizabeth of Bohemia, he wrote mind-body interaction in $\boxDr$Discours de la methode$\boxUl$, $\boxDr$Meditationes de prima philosophia$\boxUl$, and $\boxDr$Traite des passions de 1'ame$\boxUl$ etc. However, only mind-body dualism of his mind-body theories was written in our medical text book, morever mental realm was excluded from the persuit of learning Descartes advocated a mechanistic world-view and mechanistic life-view, he regarded human body as a machine part. And a paticent corresponds to a troubled machine, a doctor deserves a repairman. But this point of view made holistic understanding of man impossible. Descartes divide the whole into basic building blocks, we named the approach Reductionism. Reductionism led to ontological concept in medical science, bacteriology established 'specific cause-specific disease-specific therapy'. We examined medical influence of Descartes's thought, we need to draw out a philosophic basis of medical science and science of public health by a close study of his records.

• Journal of The Korean Digital Architecture Interior Association
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• v.12 no.4
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• pp.117-124
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• 2012

The importance of the digital architecture is increasing more ever. Currently, CAD and 3D programs are used as design fields, but the BIM (building information modeling) is gradually interested. BIM is mandatory on the project more than 50 billion won ordered by the government since 2012, it will be expanded to a total of government orders by 2016. University needs to evaluate teaching methods and computer-aided design environments such as CAD and BIM. In this paper, we surveyed computer-aided design environments and teaching methods for 73 students at the J University of Department of architectural engineering. Main results are as follows: 1. Hardlock is uncomfortable but necessary program for the computer management. 2. The desk placement considering the behavior of the design students results in higher satisfaction. 3. Because a CAD subject was a difficult course content and progress is fast, students thought it is difficult to follow. Especially, first-year students answered it is difficult to learn program and understand the structure of the building at the same time. 4. First-year students want to learn CAD more. Second-, third-, fourth-year students want to learn Photoshop more. Supplement for these classes is required. 5. Students answered that a teaching method of a CAD subject would be good to their own practice after the professor demonstrates for students. The senior's assistance is also a high effective way in the class. 6. During class, students' activities such surfing the web and Kakao Talk on a smartphone disrupt the class, there is a need to regulate by a rule such as disconnect computers from a network and against using smartphone. Although the Internet with the popularization of smartphones confers a benefit on modern life, it causes damage to us. This is a hard part for a salaried workers as well as students studying equally. The self management is required and a professor needs to control and restraint in a university classroom. The professor's continuing interest to students can increase the effectiveness of learning.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.457-466
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• 2005

In this paper, we propose a wavelet neural network(WNN) based predictive control method for path tracking of mobile robots with multi-input and multi-output. In our control method, we use a WNN as a state predictor which combines the capability of artificial neural networks in learning processes and the capability of wavelet decomposition. A WNN predictor is tuned to minimize errors between the WNN outputs and the states of mobile robot using the gradient descent rule. And control signals, linear velocity and angular velocity, are calculated to minimize the predefined cost function using errors between the reference states and the predicted states. Through a computer simulation for the tracking performance according to varied track, we demonstrate the efficiency and the feasibility of our predictive control system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.53-60
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• 2012

Nearest-neighbor classification predicts the class of an input data with the most frequent class among the near training data of the input data. Even though nearest-neighbor classification doesn't have a training stage, all of the training data are necessary in a predictive stage and the generalization performance depends on the quality of training data. Therefore, as the training data size increase, a nearest-neighbor classification requires the large amount of memory and the large computation time in prediction. In this paper, we propose a prototype selection algorithm that predicts the class of test data with the new set of prototypes which are near-boundary training data. Based on Tomek links and distance metric, the proposed algorithm selects boundary data and decides whether the selected data is added to the set of prototypes by considering classes and distance relationships. In the experiments, the number of prototypes is much smaller than the size of original training data and we takes advantages of storage reduction and fast prediction in a nearest-neighbor classification.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.12
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• pp.123-129
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• 2014

In accordance with the development of various convergence devices, cameras are being used in many types of the systems such as security system, driver assistance device and so on, and a lot of people are exposed to these system. Therefore the system should be able to recognize the human behavior and support some useful functions with the information that is obtained from detected human behavior. In this paper we use a machine learning approach based on 2D image and propose the human behavior pattern recognition methods. The proposed methods can provide valuable information to support some useful function to user based on the recognized human behavior. First proposed one is "phone call behavior" recognition. If a camera of the black box, which is focused on driver in a car, recognize phone call pose, it can give a warning to driver for safe driving. The second one is "looking ahead" recognition for driving safety where we propose the decision rule and method to decide whether the driver is looking ahead or not. This paper also shows usefulness of proposed recognition methods with some experiment results in real time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.56-64
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• 2018

In recent years, imbalanced data is one of the most important and frequent issue for quality control in industrial field. As an example, defect rate has been drastically reduced thanks to highly developed technology and quality management, so that only few defective data can be obtained from production process. Therefore, quality classification should be performed under the condition that one class (defective dataset) is even smaller than the other class (good dataset). However, traditional multi-class classification methods are not appropriate to deal with such an imbalanced dataset, since they classify data from the difference between one class and the others that can hardly be found in imbalanced datasets. Thus, one-class classification that thoroughly learns patterns of target class is more suitable for imbalanced dataset since it only focuses on data in a target class. So far, several one-class classification methods such as one-class support vector machine, neural network and decision tree there have been suggested. One-class support vector machine and neural network can guarantee good classification rate, and decision tree can provide a set of rules that can be clearly interpreted. However, the classifiers obtained from the former two methods consist of complex mathematical functions and cannot be easily understood by users. In case of decision tree, the criterion for rule generation is ambiguous. Therefore, as an alternative, a new one-class classifier using hyper-rectangles was proposed, which performs precise classification compared to other methods and generates rules clearly understood by users as well. In this paper, we suggest an approach for improving the limitations of those previous one-class classification algorithms. Specifically, the suggested approach produces more improved one-class classifier using hyper-rectangles generated by using Gaussian function. The performance of the suggested algorithm is verified by a numerical experiment, which uses several datasets in UCI machine learning repository.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.429-436
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• 2005

A simple stereo matching algorithm using population-based incremental learning(PBIL) is proposed in this paper to decrease the general problem of genetic algorithms, such as memory consumption and inefficiency of search. PBIL is a variation of genetic algorithms using stochastic search and competitive teaming based on a probability vector. The structure of PBIL is simpler than that of other genetic algorithm families, such as serial and parallel ones, due to the use of a probability vector. The PBIL strategy is simplified and adapted for stereo matching circumstances. Thus, gene pool, chromosome crossover, and gene mutation we removed, while the evolution rule, that fitter chromosomes should have higher survival probabilities, is preserved. As a result, memory space is decreased, matching rules are simplified and computation cost is reduced. In addition, a scheme controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities, like a result of coarse-to-fine matchers. Because of this scheme, the proposed algorithm can produce a stable disparity map with a small fixed-size window. Finally, an alterative version of the proposed algorithm without using probability vector is also presented for simpler set-ups.

• Journal of KIISE
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• v.43 no.7
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• pp.773-780
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• 2016

Semantic information and features are very important for Semantic Role Labeling(SRL) though many SRL systems based on machine learning mainly adopt lexical and syntactic features. Previous SRL research based on semantic information is very few because using semantic information is very restricted. We proposed the SRL system which adopts semantic information, such as named entity, word sense disambiguation, filtering adjunct role based on sense, synonym cluster, frame extension based on synonym dictionary and joint rule of syntactic-semantic information, and modified verb-specific numbered roles, etc. According to our experimentations, the proposed present method outperforms those of lexical-syntactic based research works by about 3.77 (Korean Propbank) to 8.05 (Exobrain Corpus) F1-scores.

• Communications of Mathematical Education
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• v.31 no.2
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• pp.139-152
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• 2017

In this paper, we examine how secondary school mathematics textbooks on calculus introduce the history of calculus. In order to identify the problem, we consider the Babylonian integration by trapezoidal rule, which was made to calculate the location of Jupiter in 350-50 B.C., and the integration by the method of the rotating plate of ibn al-Haytham in Egypt, about 1000 years. In conclusion, our secondary school mathematics textbooks describe Newton and Leibniz as inventing calculus and place their roots in ancient Greece. The origin of the calculus is in Babylonia and the Faṭimah Dynasty (909-1171) (Egypt) and it is desirable that the calculus is developed in Europe after the development of the power series in India, and that the value of Asia Africa is introduced in the textbooks.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.3
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• pp.247-271
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• 2019

Uncertainty in scientific knowledge means an uncertain state where propositions are neither true or false at present. The existing studies have analyzed the propositions written in the academic literature, and have conducted the performance evaluation based on the rule based and machine learning based approaches by using the corpus. Although they recognized that the importance of word construction, there are insufficient attempts to expand the word by analyzing the meaning of uncertainty words. On the other hand, studies for analyzing the structure of networks by using bibliometrics and text mining techniques are widely used as methods for understanding intellectual structure and relationship in various disciplines. Therefore, in this study, semantic relations were analyzed by applying Word2Vec to existing uncertainty words. In addition, WordNet, which is an English vocabulary database and thesaurus, was applied to perform a network analysis based on hypernyms, hyponyms, and synonyms relations linked to uncertainty words. The semantic and lexical relationships of uncertainty words were structurally identified. As a result, we identified the possibility of automatically expanding uncertainty words.