• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.205-208
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• 2010

We introduce a novel feature extraction scheme for online handwritten digit based on utilizing Zernike moment and angulation feature. The time sequential signal from mouse movement on the writing pad is described as a sequence of consecutive points on the x-y plane. So, we can create data-set which are successive and time-sequential pixel position data by preprocessing. Data preprocessed is used for Zernike moment and angulation feature extraction. this feature is scale-, translation-, and rotation-invariant. The extracted specific feature is fed to a BP(backpropagation) neural network, which in turn classifies it as one of the nine digits. In this paper, proposed method not noly show high recognition rate but also need less learning data for 200 handwritten digit data.

• The Journal of Korean Physical Therapy
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• v.15 no.1
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• pp.155-170
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• 2003

Lumbar segmental instability is considered to represent a significant sub-group within the chronic low back pain population. This condition has a unique clinical presentation that displays its symptoms and movement dysfunction within the neutral zone of the motion segment. The loosening of the motion segment secondary to injury and associated dysfunction of the local muscle system renders it biomechanically vulnerable in the neutral zone. There in evidence of muscle dysfunction related to the control of the movement system. There is a clear link between reduced proprioceptive input, altered slow motor unit recruitment and the development of chronic pain states. Dysfunction in the global and local muscle systems in presented to support the development of a system of classification of muscle function and development of dysfunction related to musculoskeletal pain. The global muscles control range of movement and alignment, and evidence of dysfunction is presented in terms of imbalance in recruitment and length between the global stability muscles and the global mobility muscles. The local stability muscles demonstrate evidence of failure of aeequate segmental control in terms of allowing excessive uncontrolled translation or specific loss of cross-sectional area at the site of pathology Motor recruitment deficits present as altered timing and patterns of recruitment. The evidence of local and global dysfunction allows the development of an integrated model of movement dysfunction. The clinical diagnosis of this chronic low back pain condition is based on the report of pain and the observation of movement dysfunction within the neutral zone and the associated finding of excessive intervertebral motion at the symptomatic level. Four different clinical patterns are described based on the directional nature of the injury and the manifestation of the patient's symptoms and motor dysfunction. A specific stabilizing exercise intervention based on a motor learning model in proposed and evidence for the efficacy of the approach provided.

• The Critical Review of Religion and Culture
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• no.32
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• pp.257-287
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• 2017

It seems to be quite an ambitious endeavor to trace back the translation history of Catholic Vulgate Bible from Latin language to Asian languages since 16th century. I try to bring out the translation(translative) procedure of Latin Bible to the Chinese Version, which is eventually come up (and the latter)to the Korean Version. It has been supported and funded by the National Research Foundation of Korea. This task has a three-year plan. For the first step(operation), I examined and searched the European situation of the Vulgate Bible in the Catholic Church, i.e. the ritual use of Vulgate Bible in the Mass and the religious retreat. The liturgical texts, to begin with, were analysed to disclose how the Vulgate Bible was reflected in them. The Lectionary and the Evangeliary were the typical ones. The structure or the formation system of the Lectionaries for Mass was based on the liturgical year cycle. From this point, the Vulgate Bible was rooted in the religious life of European Catholics after the Council of Trent which had proclaimed the Vulgate to be authentic source of the Revelation, therefore, to be respected as the only authoritative Bible. How did the Catholic Church use the Vulgate Bible out of the context and the boundary (sphere) of liturgy? The Meditation guide books for the purpose of instructing the religious retreat was published and (diffused) circulated among the priests, the religious persons and even the laymen. In those books also were included (found) the citation, the interpretation and the commentaries of the Vulgate Bible. The most of the devotees in Europe read the biblical phrases out of the meditation guide books. There are still remained the unsolved problems of how to understand (for understanding) the actual aspect of the Vulgate Bible in the European Catholic Church. All the Biblical verses were translated into French and included in the meditation guide books published in France. What did the Holy See think the French translation of the Vulgate Bible? Unfortunately, there were not found the Vatican Decrees about the European translation of the Vulgate Bible. The relationship between the Vulgate Bible and the Meditation guide (Those) will be much important for the study of Chinese translation of it. The search for the Decrees and the researches on it and the European and the non-European translations of the Vulgate Bible will be a continuous task for me as well as the other researchers on these subjects in the future.

• ETRI Journal
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• v.42 no.1
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• pp.90-100
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• 2020

Named entity recognition (NER) continues to be an important task in natural language processing because it is featured as a subtask and/or subproblem in information extraction and machine translation. In Urdu language processing, it is a very difficult task. This paper proposes various deep recurrent neural network (DRNN) learning models with word embedding. Experimental results demonstrate that they improve upon current state-of-the-art NER approaches for Urdu. The DRRN models evaluated include forward and bidirectional extensions of the long short-term memory and back propagation through time approaches. The proposed models consider both language-dependent features, such as part-of-speech tags, and language-independent features, such as the "context windows" of words. The effectiveness of the DRNN models with word embedding for NER in Urdu is demonstrated using three datasets. The results reveal that the proposed approach significantly outperforms previous conditional random field and artificial neural network approaches. The best f-measure values achieved on the three benchmark datasets using the proposed deep learning approaches are 81.1%, 79.94%, and 63.21%, respectively.

• Journal of Korean Academy of Nursing
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• v.29 no.2
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• pp.346-360
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• 1999

The purpose of this research was to identify nursing interventions performed by hospital nurses in Korea. The sample consisted of 311 nurses working in three hospitals. The Nursing Interventions Use Questionnaire developed by the Iowa Intervention Project team was used for data collection. The instrument was translated to Korean using the method of back-translation. Eighteen interventions were performed at least daily. Interventions in the Physiological : Basic domain were most frequently used at least daily. No interventions in the Family and Behavioral domains were used by nurses at least once a day. The most frequently used interventions was Documentation, followed by the interventions Medication : Parenteral, Intravenous(IV) Insertion, Temperature Control, and Shift Report. The intervention performed least often was Reproductive Technology Management. Nurses working in intensive care units on the whole performed interventions most often, while nurses working in obstetric, gynecological, and pediatric units performed them least often. The nurses working in intensive care unit, medical and surgical care units performed the interventions in the Physiological : Basic domain more often than the nurses working in obstetric, gynecological, and pediatric units. The nurses working in obstetric, gynecological, and pediatric units used the interventions in the Family domain more often than the nurses working in the other three units. This study contributes to the documentation of nursrs' work in Korea. Further study will be needed to validate nursing activities of each NIC intervention.

• Journal of Korean Academy of Nursing
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• v.48 no.1
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• pp.70-84
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• 2018

Purpose: This study was conducted to evaluate the validity and reliability of the Korean version of the clinical learning environment, supervision and nurse teacher evaluation scale (CLES+T) that measures the clinical learning environment and the conditions associated with supervision and nurse teachers. Methods: The English CLES+T was translated into Korean with forward and back translation. Survey data were collected from 434 nursing students who had more than four days of clinical practice in Korean hospitals. Internal consistency reliability and construct validity using confirmatory and exploratory factor analysis were conducted. SPSS 20.0 and AMOS 22.0 programs were used for data analysis. Results: The exploratory factor analysis revealed seven factors for the thirty three-item scale. Confirmatory factor analysis supported good convergent and discriminant validities. The Cronbach's alpha for the overall scale was .94 and for the seven subscales ranged from .78 to .94. Conclusion: The findings suggest that the 33-items Korean CLES+T is an appropriate instrument to measure Korean nursing students'clinical learning environment with good validity and reliability.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.124-128
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• 2006

The purpose of this study was to develop a scale of social capital in participant sports. To achieve the purpose of this study Socal Capital Scale by Fukuyama(1996), Shane(2005), Kim(2003), Park & Kim(2000), Jung & Shim(2004) was translated and modified to use in participant sports. Throughout the research procedures including back translation, expert meeting, pre-test, sampling, data analysis. Result of this study are as follows First, SCSPS(social capital scale in participant sports) was consisted with four sub-domains such as social network, norms, trust, information share, and position improvement. Second, based on outputs form SEM, it was indicated that model used to develop SCSPS had relatively good fit with significant scores of model indices. Finally, reliability and validity of the scale also showed relatively high scores.

• Research in Plant Disease
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• v.22 no.2
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• pp.116-121
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• 2016

In 2015, stem blight of Rubus crataegifolius was observed in Pohang, Korea. The symptoms began as dark red spots in the stem, which led to stem blight, then leaf blight, and eventually resulted in death. A fungal isolate was obtained from a symptomatic stem and incubated on a potato dextrose agar plate. The isolated fungus produced white, cloudy mycelia turned black in 3 days. Based on the morphological characteristics, the causal fungus was assumed to be Botryosphaeria sp. A pathogenicity test was conducted according to Koch's postulates. To identify the causal agent, the combined sequence of the internal transcribed spacer, ${\beta}$-tubulin, and translation elongation factor $1{\alpha}$ genes were used for phylogenetic analysis. Approximately 1,200 bp of the combined sequence clearly suggested that the isolated pathogen was Botryosphaeria parva. This is the first report on stem blight in R. crataegifolius caused by B. parva in Korea.

• Journal of Information Technology Services
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• v.19 no.5
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• pp.83-91
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• 2020

Language Models such as BERT has been an important factor of deep learning-based natural language processing. Pre-training the transformer-based language models would be computationally expensive since they are consist of deep and broad architecture and layers using an attention mechanism and also require huge amount of data to train. Hence, it became mandatory to do fine-tuning large pre-trained language models which are trained by Google or some companies can afford the resources and cost. There are various techniques for fine tuning the language models and this paper examines three techniques, which are data augmentation, tuning the hyper paramters and partly re-constructing the neural networks. For data augmentation, we use no-answer augmentation and back-translation method. Also, some useful combinations of hyper parameters are observed by conducting a number of experiments. Finally, we have GRU, LSTM networks to boost our model performance with adding those networks to BERT pre-trained model. We do fine-tuning the pre-trained korean-based language model through the methods mentioned above and push the F1 score from baseline up to 89.66. Moreover, some failure attempts give us important lessons and tell us the further direction in a good way.

• Journal of Computing Science and Engineering
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• v.5 no.4
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• pp.305-313
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• 2011

Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. As such, more and more organizations are becoming vulnerable to attack. The aim of this research is to classify network attacks using neural networks (NN), which leads to a higher detection rate and a lower false alarm rate in a shorter time. This paper focuses on two classification types: a single class (normal, or attack), and a multi class (normal, DoS, PRB, R2L, U2R), where the category of attack is also detected by the NN. Extensive analysis is conducted in order to assess the translation of symbolic data, partitioning of the training data and the complexity of the architecture. This paper investigates two engines; the first engine is the back-propagation neural network intrusion detection system (BPNNIDS) and the second engine is the radial basis function neural network intrusion detection system (BPNNIDS). The two engines proposed in this paper are tested against traditional and other machine learning algorithms using a common dataset: the DARPA 98 KDD99 benchmark dataset from International Knowledge Discovery and Data Mining Tools. BPNNIDS shows a superior response compared to the other techniques reported in literature especially in terms of response time, detection rate and false positive rate.