Proceedings of the Korean Nuclear Society Conference
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1998.05a
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pp.273-278
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1998
Belief network(or Bayesian network) based on Bayes' rule in probabilistic theory can be applied to the reasoning of diagnostic systems. This paper describes the basic theory of concept and feasibility of using the network for diagnosis of nuclear power plants. An example shows that the probabilities of root causes of a failure are calculated from the measured or believed evidences.
The purpose of this study was to explore the relationship between childrearing belief and parental efficacy of women before and after childbirth. For this purpose 253 pregnant women and 256 mothers with infants under one year of age were contacted and asked to fill in a packet of survey questionnaire at their visits to obstetrician, gynecologist and pediatrician. The questionnaire includes questions about what mothers value in childrearing, their expectations for their children and parental efficacy. Data collected were analyzed using SAS PC program. It was reported that comparing to mothers, pregnant women view childrearing in more ideal lights and expect their children to be more exceptional. Also working mothers reported comparatively lower parental efficacy than full-time mothers suggesting that social support system to minimize pressure coming from work for working mothers with young children should be provided and the parental education methods to enhance the parental efficacy should be sought.
KSII Transactions on Internet and Information Systems (TIIS)
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v.11
no.2
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pp.1118-1133
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2017
Computer vision-based human activity recognition (HAR) has become very famous these days due to its applications in various fields such as smart home healthcare for elderly people. A video-based activity recognition system basically has many goals such as to react based on people's behavior that allows the systems to proactively assist them with their tasks. A novel approach is proposed in this work for depth video based human activity recognition using joint-based motion features of depth body shapes and Deep Belief Network (DBN). From depth video, different body parts of human activities are segmented first by means of a trained random forest. The motion features representing the magnitude and direction of each joint in next frame are extracted. Finally, the features are applied for training a DBN to be used for recognition later. The proposed HAR approach showed superior performance over conventional approaches on private and public datasets, indicating a prominent approach for practical applications in smartly controlled environments.
This paper proposes a novel cooperative localization method for distributed wireless networks in 3-dimensional (3D) global positioning system (GPS) denied environments. The proposed method, which is referred to as hybrid ellipsoidal variational algorithm (HEVA), combines the use of non-parametric belief propagation (NBP) and variational Bayes (VB) to benefit from both the use of the rich information in NBP and compact communication size of a parametric form. InHEVA, two novel filters are also employed. The first one mitigates non-line-of-sight (NLoS) time-of-arrival (ToA) messages, permitting it to work well in high noise environments with NLoS bias while the second one decreases the number of calculations. Simulation results illustrate that HEVA significantly outperforms traditional NBP methods in localization while requires only 50% of their complexity. The superiority of VB over other clustering techniques is also shown.
For any thought and knowledge, its growth and development has close relation with the society where it is developed and grow. As Feuerbach says, the birth of spirit needs an existence of two human beings, i. e. the social background, as well as the birth of body does. But, at the educational viewpoint, the spread and the growth of such a thought or knowledge that influence favorably the development of a society must be also considered. We would discuss the goal and the function of mathematics education in relation with the prosperity of a technological civilization. But, the goal and the function are not unrelated with the spiritual culture which is basis of the technological civilization. Most societies of today can be called open democratic societies or societies which are at least standing such. The concept of rationality in such societies is a methodological principle which completes the democratic society. At the same time, it is asserted as an educational value concept which explains comprehensively the standpoint and the attitude of one who is educated in such a society. Especially, we can considered the cultivation of a mathematical thinking or a logical thinking in the goal of mathematics education as a concept which is included in such an educational value concept. The use of the concept of rationality depends on various viewpoints and criterions. We can analyze the concept of rationality at two aspects, one is the aspect of human behavior and the other is that of human belief or knowledge. Generally speaking, the rationality in human behavior means a problem solving power or a reasoning power as an instrument, i. e. the human economical cast of mind. But, the conceptual condition like this cannot include value concept. On the other hand, the rationality in human knowledge is related with the problem of rationality in human belief. For any statement which represents a certain sort of knowledge, its universal validity cannot be assured. The statements of value judgment which represent the philosophical knowledge cannot but relate to the argument on the rationality in human belief, because their finality do not easily turn out to be true or false. The positive statements in science also relate to the argument on the rationality in human belief, because there are no necessary relations between the proposition which states the all-pervasive rule and the proposition which is induced from the results of observation. Especially, the logical statement in logic or mathematics resolves itself into a question of the rationality in human belief after all, because all the logical proposition have their logical propriety in a certain deductive system which must start from some axioms, and the selection and construction of an axiomatic system cannot but depend on the belief of a man himself. Thus, we can conclude that a question of the rationality in knowledge or belief is a question of the rationality both in the content of belief or knowledge and in the process where one holds his own belief. And the rationality of both the content and the process is namely an deal form of a human ability and attitude in one's rational behavior. Considering the advancement of mathematical knowledge, we can say that mathematics is a good example which reflects such a human rationality, i. e. the human ability and attitude. By this property of mathematics itself, mathematics is deeply rooted as a good. subject which as needed in moulding the ability and attitude of a rational person who contributes to the development of the open democratic society he belongs to. But, it is needed to analyze the practicing and pursuing the rationality especially in mathematics education. Mathematics teacher must aim the rationality of process where the mathematical belief is maintained. In fact, there is no problem in the rationality of content as long the mathematics teacher does not draw mathematical conclusions without bases. But, in the mathematical activities he presents in his class, mathematics teacher must be able to show hem together with what even his own belief on the efficiency and propriety of mathematical activites can be altered and advanced by a new thinking or new experiences.
Human-Robot interaction (HRI) has recently become one of the most important issues in the field of robotics. Understanding and predicting the intentions of human users is a major difficulty for robotic programs. In this paper we suggest an interaction method allows the robot to execute the human user's desires in an intelligent room-based domain, even when the user does not give a specific command for the action. To achieve this, we constructed a full system architecture of an intelligent room so that the following were present and sequentially interconnected: decision-making based on the Bayesian belief network, responding to human commands, and generating queries to remove ambiguities. The robot obtained all the necessary information from analyzing the user's condition and the environmental state of the room. This information is then used to evaluate the probabilities of the results coming from the output nodes of the Bayesian belief network, which is composed of the nodes that includes several states, and the causal relationships between them. Our study shows that the suggested system and proposed method would improve a robot's ability to understand human commands, intuit human desires, and predict human intentions resulting in a comfortable intelligent room for the human user.
Journal of Institute of Control, Robotics and Systems
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v.21
no.1
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pp.59-64
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2015
In this paper, we found the usefulness of the deep belief network (DBN) in the fields of brain-computer interface (BCI), especially in relation to imagined speech. In recent years, the growth of interest in the BCI field has led to the development of a number of useful applications, such as robot control, game interfaces, exoskeleton limbs, and so on. However, while imagined speech, which could be used for communication or military purpose devices, is one of the most exciting BCI applications, there are some problems in implementing the system. In the previous paper, we already handled some of the issues of imagined speech when using the International Phonetic Alphabet (IPA), although it required complementation for multi class classification problems. In view of this point, this paper could provide a suitable solution for vowel classification for imagined speech. We used the DBN algorithm, which is known as a deep learning algorithm for multi-class vowel classification, and selected four vowel pronunciations:, /a/, /i/, /o/, /u/ from IPA. For the experiment, we obtained the required 32 channel raw electroencephalogram (EEG) data from three male subjects, and electrodes were placed on the scalp of the frontal lobe and both temporal lobes which are related to thinking and verbal function. Eigenvalues of the covariance matrix of the EEG data were used as the feature vector of each vowel. In the analysis, we provided the classification results of the back propagation artificial neural network (BP-ANN) for making a comparison with DBN. As a result, the classification results from the BP-ANN were 52.04%, and the DBN was 87.96%. This means the DBN showed 35.92% better classification results in multi class imagined speech classification. In addition, the DBN spent much less time in whole computation time. In conclusion, the DBN algorithm is efficient in BCI system implementation.
This paper explores multi-technology capabilities between Korea and Taiwan by analyzing the pattern of inventive activities concerning technology fusion by using patent bibliometrics. Although two countries exhibit a similar level of invention activities and high degree of specialization in emerging technologies measured by the number and technological fields of their US patents, innovation systems in two countries differ. MTCs (multi-technology corporations) are stronger in Korea national innovation system while small innovative firms play important roles in Taiwan national innovation system. Technology fusion has been an important source of technological innovation and it suggests possible advantage for the Korean innovation system because it is a common belief that global size firms - most of them are multi-technology corporations - can perform better in multi-technology fusion and scientific research. The result of patent bibliometrics suggests rather complex answers to the belief Even though Korea shows slight advantage, it may not be ascribed to the large MTCs.
The purpose of the current study is to investigate how task-irrelevant affective priming affects higher cognitive function. In the study, we selected prime stimuli from International Affective Picture System(IAPS) and examined if they influence participants' performance of syllogistic reasoning task when they are task-irrelevant. In Experiment 1, arousal of IAPS stimuli was controlled while valence of the stimuli was manipulated. In Experiment 2, valence of IAPS stimuli was controlled while arousal of stimuli was manipulated. In both experiments, task-irrelevant affective primes were followed by syllogistic reasoning tasks consisting of three sentences and measured accuracies of task performance. The results showed that valence of affective prime affected logical validity of reasoning and belief-bias whereas arousal of affective primes did not yield any difference. That is, positive valence facilitated logical and analytic processing by reducing belief-bias while arousal did not affect reasoning task performance. These results suggest that dimensions of valence and arousal independently influence higher cognitive function.
Hypertension is one of the most well known risk factors for cerebrovascular or coronary heart disease and is a major public health problem. Early detection and treatment of hypertension are essential, but the compliance of treatment on hypertension is not easy to achive. Hypertensive workers are being detected by the annual screening under the Labour Standard Law in Korea but the solidified control system for them is not existing. This study about workers 'Motive-Belief-Action in non-drug and drug treatment of their hypertension would be worthwhile to interpret how the workers actually behave in coping with hypertension, and also would be advisable to construct the follow-up program in Korea. In the field research process two criteria were used to select sample group. The first criterion included the workers who were screened to be hypertensive with their blood pressure above 160/95 in this survey. The second one was used to classify study-group respondents who had known their hypertension by successive annual screening. From such criteria a total of 156 male workers were sampled in 21 industries, the author interviewed them using the structured questionnaire which consisted of Belief-Motive-Action items about non-drug and drug treatment for hypertension with open-ended question on symptom of hypertension. The summary is as follows: 1) Sixty-one percent of respondents had ever checked their blood pressure somewhere besides the annual screening. 2) Most respondents(97.2%) complained no symptoms of hypertension at all. 3) Belief level of non-drug treatment was relatively high (82.1%-64.7%), but motive(55.1%-28.2%) and action(38.5%-16.7%) levels were low. 4) Belief level of drug treatment was relatively lower than that of non-drug treatment, blue collar workers showed higher artier level of drug treatment than white collar workers, and correlation coefficient between belief and motive on drug treatment was lower in group of not-recognizing their family history of hypertension than recognized group. Such findings indicated that belief on drug treatment of hypertensive workers would be problematic. 5) White collar workers showed significant lower correlation coefficients between Motive and Action of salt restriction, restriction of fatty diet and relaxation than blue collar workers. 6) Mild hypertension group showed low levels of Motive and Action of non-drug treatment(salt restriction, restriction of fatty diet and relaxation) and also showed low correlation coefficient between Belief and Motive of above non-drug treatment.
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