• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.3
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• pp.239-248
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• 2020

Exact rock classification helps suitable support patterns to be installed. Face mapping is usually conducted to classify the rock mass using RMR (Rock Mass Ration) or Q values. There have been several attempts to predict the grade of rock mass using mechanical data of jumbo drills or probe drills and photographs of excavation surfaces by using deep learning. However, they took long time, or had a limitation that it is impossible to grasp the rock grade in ahead of the tunnel surface. In this study, a method to predict the Q value ahead of excavation surface is developed using recurrent neural network (RNN) technique and it is compared with the Q values from face mapping for verification. Among Q values from over 4,600 tunnel faces, 70% of data was used for learning, and the rests were used for verification. Repeated learnings were performed in different number of learning and number of previous excavation surfaces utilized for learning. The coincidence between the predicted and actual Q values was compared with the root mean square error (RMSE). RMSE value from 600 times repeated learning with 2 prior excavation faces gives a lowest values. The results from this study can vary with the input data sets, the results can help to understand how the past ground conditions affect the future ground conditions and to predict the Q value ahead of the tunnel excavation face.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• v.26 no.4
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• pp.91-100
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• 2013

Background and Objective : Dyshidrotic Eczema is characterized by a pruritic vesicular eruption on the fingers, palms, and soles. It is an acute, chronic, or recurrent dermatosis. The causes of dyshidrosis are unknown. There are many treatments available for dyshidrosis including topical steroids but long term treatment of streoids may have side effects. The purpose of this study is to find out the effect of Fulinggancao-Tang on Dyshidrotic Eczema. Methods : We have diagnosed the patients through the Shanghanlun six meridian patterns diagnostic system and we treated the patients with Fulinggancao-Tang. The severity of Dyshidrotic Eczema was evaluated by visual analogue scale(VAS). Results : After the treatment itching and vesicles of hands and foots were all disappeared in both patients. Conclusions : Fulinggancao-Tang have improved the signs and symptoms of Dyshidrotic Eczema case. It is considered that Fulinggancao-Tang is considerably effective on the treatment of skin disease that especially vulnerable to water.

• Journal of the Korean Society of Costume
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• v.53 no.2
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• pp.137-151
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• 2003

Fashion photographs from leading monthly fashion magazines in 1990s were analyzed. The types and the formative feature characteristics and the aesthetic values of domestic retrospective fashion were studied. The major conclusions of the study are as follows 1. The types of domestic retro fashion were historicism, ethnic, ecology. Retro fashion was expressed through applying and reappearing silhouette, detail. fabric and image of the costumes of the past. 2. Renaissance. Baroque, Rococo styles and the costumes and styles of 1960s and 1970s were mainly applied in domestic fashion. 3. Orientalism was emphasized and Korean traditional styles and Chinese costumes were expressed mainly in domestic fashion. Fashion trends recurrent and intimate to the nature were expressed in patterns, fabrics, dyeing and silhouettes of nature. 4. The formative feature characteristics of domestic retro fashion were recurrence, purity. tradition and decoration. As retro fashion applies costumes of the past newly, it supplies unlimited possibilities to the present fashion which seeks versatility.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1997.10a
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• pp.181-184
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• 1997

Practical applications of learning systems usually involve complex domains exhibiting nonlinear behavior and dilution by noise. Consequently, an intelligent system must be able to adapt to nonlinear processes as well as probabilistic phenomena. An important class of application for a knowledge based systems in prediction: forecasting the future trajectory of a process as well as the consequences of any decision made by e system. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes in the form of chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a Henon process in the presence of various patterns of noise.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.109-141
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• 1998

Many processes in the industrial realm exhibit sstochastic and nonlinear behavior. Consequently, an intelligent system must be able to nonlinear production processes as well as probabilistic phenomena. In order for a knowledge based system to control a manufacturing processes as well as probabilistic phenomena. In order for a knowledge based system to control manufacturing process, an important capability is that of prediction : forecasting the future trajectory of a process as well as the consequences of the control action. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes, includinb chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a chaotic process in the presence of various patterns of noise.

• Clinical and Experimental Pediatrics
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• v.50 no.10
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• pp.1018-1023
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• 2007

Hereditary hemorrhagic telagiectasia (HHT), which is characterized by the classic triad of mucocutaneous telangiectases, arteriovenous malformations (AVMs) and inheritance, is an autosomal dominant disorder. The characteristic manifestations of HHT are all due to abnormalities of the vascular structure. This report deals with the case of a 14-year-old girl with typical features of HHT that include recurrent epistaxis, mucocutanous telangiectases, pulmonary and cerebral AVMs and a familial occurrence.

• Environmental Analysis Health and Toxicology
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• v.23 no.4
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• pp.231-245
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• 2008

Various methods for detecting changes in response behaviors of indicator specimens are presented for monitoring effects of toxic treatments. The movement patterns of individuals are quantitatively characterized by statistical (i.e., ANOVA, multivariate analysis) and computational (i.e., fractal dimension, Fourier transform) methods. Extraction of information in complex behavioral data is further illustrated by techniques in ecological informatics. Multi-Layer Perceptron and Self-Organizing Map are applied for detection and patterning of response behaviors of indicator specimens. The recent techniques of Wavelet analysis and line detection by Recurrent Self-Organizing Map are additionally discussed as an efficient tool for checking time-series movement data. Behavioral monitoring could be established as new methodology in integrative ecological assessment, tilling the gap between large-scale (e.g., community structure) and small-scale (e.g., molecular response) measurements.

• Journal of Information Processing Systems
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• v.14 no.1
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• pp.150-161
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• 2018

We propose a novel deep neural network model for detecting human activities in untrimmed videos. The process of human activity detection in a video involves two steps: a step to extract features that are effective in recognizing human activities in a long untrimmed video, followed by a step to detect human activities from those extracted features. To extract the rich features from video segments that could express unique patterns for each activity, we employ two different convolutional neural network models, C3D and I-ResNet. For detecting human activities from the sequence of extracted feature vectors, we use BLSTM, a bi-directional recurrent neural network model. By conducting experiments with ActivityNet 200, a large-scale benchmark dataset, we show the high performance of the proposed DeepAct model.

• Journal of Korea Multimedia Society
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• v.11 no.6
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• pp.807-815
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• 2008

A simple efficient method of spotting and recognizing hand gestures in video is presented using a network of hidden Markov models and dynamic programming search algorithm. The description starts from designing a set of isolated trajectory models which are stochastic and robust enough to characterize highly variable patterns like human motion, handwriting, and speech. Those models are interconnected to form a single big network termed a spotting network or a spotter that models a continuous stream of gestures and non-gestures as well. The inference over the model is based on dynamic programming. The proposed model is highly efficient and can readily be extended to a variety of recurrent pattern recognition tasks. The test result without any engineering has shown the potential for practical application. At the end of the paper we add some related experimental result that has been obtained using a different model - dynamic Bayesian network - which is also a type of stochastic model.

• Research in Mathematical Education
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• v.23 no.4
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• pp.219-233
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• 2020

Teachers' intervention in small groups is a research area that needs more research attention. Ehrenfeld and Horn (2020) identified teachers' group work monitoring routines that consist of four recurrent talk moves: 1) Initiation, 2) Entry, 3) Focus, and 4) Exit. To better understand prospective teachers' (PTs) intervention in small groups in mathematics classrooms, I investigated how PTs' intervention actions and purposes are related to the monitoring routines, particularly, in terms of Focus moves. I analyzed 26 PTs' responses to four written scenarios, each of which depicts interactions among students in a small group. I identified 1) types of PTs' math talk, 2) types of PTs' non-math talk, 3) types of intervention purposes, and 4) patterns of intervention actions and purposes by scenario. This study contributes to understanding PTs' intervention actions and purposes in mathematics instruction.