• Research in Community and Public Health Nursing
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• v.13 no.1
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• pp.89-97
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• 2002

Purpose: The purpose of this study is to explore the validity of the application of the Denver II developmental screening test to Korean children. This screening test. which was developed and standardized in United States. was designed to screen for developmental delay in Korea. and to compare the levels of development of Korean children with the development of children from the U.S. Method: Quota sampling. NP To facilitate field sampling. the age range used from 0 to 6 years old. was split into 10 different age groups. Sample size was estimated according to residence. 1.054 children were recruited from Seoul's metropolitan. urban and rural areas. NP To fill the quota established. the Recruitment and testing of children was done at public health centers, pediatric outpatient clinics of general hospitals and a child care center. The 25, 50, 75 and 90 percentiles were identified by using logistic regression analysis and were calculated as norms. The items in which the ages of both 50 and 90 percent passing differed more than 20 percent by the calculation was identified for comparison. NP Result: There were significant differences found in 45 items between Korean children and the children from the City of Denver as it relates to age differences. 90% of the sample passed items among 125 items from 4 sectors, e.g., personal- social. fine motor adaptive, language, and gross motor sectors. Korean children were found to be advanced in 9 items, whereas there were significant differences found in 38 items in our comparison of the two countries for age differences when 50% of sample pass items. Korean children were found to be advanced in 16 items. NP Conclusion: The result showed that there was a discrepancy in the developmental norms. It could be explained by the differences in the developmental environment. including child rearing patterns and ethnicity. Therefore, a restandardization of the Denver Screening Test is necessary as it relates to its application on Korean children. This restandardization is necessary in order to avoid both under and over-referrals of children with developmental abnormality. The modification of items in the language sector is especially suggested.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.243-262
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• 2018

Database schema integration is a significant issue in information systems. Because schema integration is a time-consuming and labor-intensive task, many studies have attempted to automate it. Researchers typically use XML as the source schema and leave much of the work to be done through DBA intervention, e.g., there are various naming conflicts related to relationship names in schema integration. In the past, the DBA had to intervene to resolve the naming-conflict name. In this paper, we introduce an algorithm that automatically generates relationship names to resolve relationship name conflicts that occur during schema integration. This algorithm is based on an Internet collocation and English sentence example dictionary. The relationship between the two entities is generated by analyzing examples extracted based on dictionary data through natural language processing. By building a semi-automated schema integration system and testing this algorithm, we found that it showed about 90% accuracy. Using this algorithm, we can resolve the problems related to naming conflicts that occur at schema integration automatically without DBA intervention.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.441-448
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• 2019

Previous researches on automatic spacing of Korean sentences has been researched to correct spacing errors by using n-gram based statistical techniques or morpheme analyzer to insert blanks in the word boundary. In this paper, we propose an end-to-end automatic word spacing by using deep neural network. Automatic word spacing problem could be defined as a tag classification problem in unit of syllable other than word. For contextual representation between syllables, Bi-LSTM encodes the dependency relationship between syllables into a fixed-length vector of continuous vector space using forward and backward LSTM cell. In order to conduct automatic word spacing of Korean sentences, after a fixed-length contextual vector by Bi-LSTM is classified into auto-spacing tag(B or I), the blank is inserted in the front of B tag. For tag classification method, we compose three types of classification neural networks. One is feedforward neural network, another is neural network language model and the other is linear-chain CRF. To compare our models, we measure the performance of automatic word spacing depending on the three of classification networks. linear-chain CRF of them used as classification neural network shows better performance than other models. We used KCC150 corpus as a training and testing data.

• Design Convergence Study
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• v.15 no.6
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• pp.73-92
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• 2016

As one of empirical research and developments on BIM applications to improve design quality and productivity of building, efforts have been devoted to automated compliance checking of building design for building permit. KBimLogic is a mechanism that translate Korean Buidling Act to the computational language called KBimCode. KBimCode aims to standardized and neutral language that can be applied to various design rules. This paper focuses on testing expandability of KBimCode by appling it on Chinese Building Act. We analyzed Chinese national regulation on fire protection and evacuation, based on 1) Object·property, 2) function for predicate processing, 3) relationship of sentences. As a result, Chinese Building Act were successfully translated to KBimCode with some important implications for further application. Based on the finding of the paper, KBimCode is expected to be applicable to kinds of design rules.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.217-230
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• 2012

This paper propose interacting test programming methods between test equipment and hardware unit to verify function and performance of the hardware unit under test. Proposed test program can minimizes the risk of failures when the unit is mounted on the aircraft by testing and verifying the unit under the worst stress condition. Also, Object oriented design using UML make it easy to apply in other equipments. Test program consists of architecture package and hardware package. Architecture package is in a role for system management, log analysis, message receiving and message analysis. Messages that are used by system management define messages for testing and defined messages is sent and received to test equipment through Ethernet. Hardware package is in a role for hardware management that is needed to be tested and is related to a system. Hardware to be tested is divided into internal test and transmission test. Internal test inspects hardware itself and reports the test results to the test equipment. Transmission test inspects communication device by sending or receiving data. All kinds of test is done in the worst condition of the test unit executing in parallel. Each device is tested at least 482 times and at most 15,003 times about one hour. Test program is utilized in hardware reliability test like as environmental test or EMI test.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.50-59
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• 2021

To understand the research trends of English education in Korea for the last 20 years from 2000 to 2019, 12 major academic journals in Korea in the field of English education were selected, and bibliographic information of 7,329 articles published in these journals were collected and analyzed. The total number of articles increased from the 2000s to the first half of the 2010s, but decreased somewhat in the late 2010s and the number of publications by journal has become similar. These results show that the overall influence of English education journals has decreased and then leveled in terms of quantity. Next, 34 topics were extracted by applying latent Dirichlet allocation (LDA) topic modeling using the English abstract of the articles. Teacher, word, culture/media, and grammar appeared as topics that were highly studied. Topics such as word, vocabulary, and testing and evaluation appeared through unique keywords, and various topics related to learner factors emerged, becoming topics of interest in English education research. Then, topics were analyzed to determine which ones were rising or falling in frequency. As a result of this analysis, qualitative research, vocabulary, learner factor, and testing were found to be rising topics, while falling topics included CALL, language, teaching, and grammar. This change in research topics shows that research interests in the field of English education are shifting from static research topics to data-driven and dynamic research topics.

• Journal of Advanced Technology Convergence
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• v.3 no.3
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• pp.17-27
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• 2024

This study focuses on the development and evaluation of a chatbot system based on the International Classification of Functioning, Disability, and Health (ICF) framework to enhance community participation among elderly individuals with mild dementia in South Korea. The study involved 12 elderly participants who were living alone and had been diagnosed with mild dementia, along with 15 caregivers who were actively involved in their daily care. The development process included a comprehensive needs assessment, system design, content creation, natural language processing using Transformer Attention Algorithm, and usability testing. The chatbot is designed to offer personalized activity recommendations, reminders, and information that support physical, social, and cognitive engagement. Usability testing revealed high levels of user satisfaction and perceived usefulness, with significant improvements in community activities and social interactions. Quantitative analysis showed a 92% increase in weekly community activities and an 84% increase in social interactions. Qualitative feedback highlighted the chatbot's user-friendly interface, relevance of suggested activities, and its role in reducing caregiver burden. The study demonstrates that an ICF-based chatbot system can effectively promote community participation and improve the quality of life for elderly individuals with mild dementia. Future research should focus on refining the system and evaluating its long-term impact.

• Journal of The Korean Association of Information Education
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• v.19 no.1
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• pp.21-30
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• 2015

Information and knowledge society in the 21st century computer education is very important. Computer programming education in computer education is very important. There are very few teaching and learning model of computer programming education. In this paper, we develop a self-regulated learning model for students to be self-regulated learning. In this study, we propose self-regulated learning elements, a self-regulated learning steps and self-regulated learning modele. Self-regulated learning elements are task level, generalized level, and efficiency level. Self-regulated learning phases are problem understanding, design, and coding, testing, and maintenance. Self-regulated learning models are to copy, to modify, create, and to challenge. The results of this study are as follows. At Correlations between learning elements and achievement, generalized level, and efficiency level are higher than the task level. At Correlations between learning and achievement, Understanding and design stages are higher than the other stages. At Correlations between learning model and achievement, to transform, to create, and to challenge are higher than to copy.

• Archives of design research
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• v.11 no.2
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• pp.191-200
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• 1998

In the "digitalized" world of new media, visual designer are increasingly enlarging their roles in desighing interaction products. However, the concepts and their methods of the interaction design have not been well established in the design community yet. The reason is attributed to the fact that designing interaction products requires two way communication between the products and final users. whereas traditional graphic design counts only on one way communication. This study emphasizes GUI design should aim at improving the usability of products which helps users quickly learn about the products and easily use them. The usability of GUI design significantly improved by securing logical rationality helps designers communicate and collaborate with program engineers and other product developers. To explain how designers can effectively communicate with program engineers and other product participants in the design process, a model of design collaboration is provided in this study. Based on the model, the study deals with the principles and methods of visual interaction, the formulation of specification system, testing design usability, and design evaluation. The study concludes that GUI designers must ensure logical rationality and the cognitive approach of visual language. Because it improves the usability of products. It also becomes an objective tool for communicating and collaborationg with engineers and the other participants in the design process.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1197-1207
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• 2018

PowerShell is command line shell and scripting language, built on the .NET framework, and it has several advantages as an attack tool, including built-in support for Windows, easy code concealment and persistence, and various pen-test frameworks. Accordingly, malwares using PowerShell are increasing rapidly, however, there is a limit to cope with the conventional malware detection technique. In this paper, we propose an improved monitoring method to observe commands executed in the PowerShell and a deep learning based malware classification model that extract features from commands using Convolutional Neural Network(CNN) and send them to Recurrent Neural Network(RNN) according to the order of execution. As a result of testing the proposed model with 5-fold cross validation using 1,916 PowerShell-based malwares collected at malware sharing site and 38,148 benign scripts disclosed by an obfuscation detection study, it shows that the model effectively detects malwares with about 97% True Positive Rate(TPR) and 1% False Positive Rate(FPR).