• Korean Journal of Cognitive Science
• /
• v.20 no.4
• /
• pp.421-437
• /
• 2009

A chatting system is a computer program that simulates conversations between a human and a computer using natural language. In this paper, we propose a statistical model to generate natural chatting sentences when keywords and speech acts are input. The proposed model first finds Eojeols (Korean spacing units) including input keywords from a corpus, and generate sentence candidates by using appearance information and syntactic information of Eojeols surrounding the found Eojeols. Then, the proposed model selects one among the sentence candidates by using a language model based on speech act information, co-occurrence information between Eojeols, and syntactic information of each Eojeol. In the experiment, the proposed model showed the better correct sentence generation rate of 86.2% than a previous conventional model based on a simple language model.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.226-231
• /
• 1991

A graphic control language using function block diagram approach is designed and implemented, applicable to real-time control for continuous process automation system. The procedure implementing the control language is composed of three parts, editor, compiler, and executer. The editor generates the control algorithm file, which contains function block information in the text form, by menu-driven method on the color graphic screen. The compiler translates the contents of the control algorithm file to machine codes and their related data. Then, the executer generates a task that makes the machine codes executed at every sampling period in the target processor. The validity of the concept in its design and implementaion is assured by on-line simulation in the multi-function controller designed for continuous process automation.

• Phonetics and Speech Sciences
• /
• v.6 no.4
• /
• pp.189-194
• /
• 2014

Objective: This study aims to investigate the speech rate, the length of a pause, habitual pitch, and voice intensity of motherese. Subjects and Methods: The research participants comprised 20 mothers (mean age 33 years). Speech data were collected and analyzed using the Real-time Pitch software (KayPENTAX(R)). Results: The average speech rate was 5.33 syllables per second without their infant present and 4.26 syllables per second with their infant present. The average pause length was 1.09 s without their infant present and 1.56 s with their infant present. The average habitual pitch was 199.79 Hz without their infant present and 227.15 Hz with their infant present. The average voice loudness was 61.09 dB without their infant present and 64.49 dB with their infant present. Conclusion: This study presented clinical information for efficiently managing the speech therapy issues of infants and children. This includes proper acoustic and phonological information to recommend to main caregivers.

• International Journal of Computer Science & Network Security
• /
• v.21 no.3
• /
• pp.206-211
• /
• 2021

Internet users are increasingly invited to express their opinions on various subjects in social networks, e-commerce sites, news sites, forums, etc. Much of this information, which describes feelings, becomes the subject of study in several areas of research such as: "Sensing opinions and analyzing feelings". It is the process of identifying the polarity of the feelings held in the opinions found in the interactions of Internet users on the web and classifying them as positive, negative, or neutral. In this article, we suggest the implementation of a sentiment analysis tool that has the role of detecting the polarity of opinions from people about COVID-19 extracted from social media (tweeter) in the Arabic language and to know the impact of the pre-processing phase on the opinions classification. The results show gaps in this area of research, first of all, the lack of resources when collecting data. Second, Arabic language is more complexes in pre-processing step, especially the dialects in the pre-treatment phase. But ultimately the results obtained are promising.

• International Journal of Internet, Broadcasting and Communication
• /
• v.15 no.2
• /
• pp.218-226
• /
• 2023

In Korea, we still use function point based cost estimations for software size and cost of a project. The current problem is that we make difficultly calculating function points with requirements and also have less accurate. That is, it is difficult for non-experts to analyze requirements and calculate function point values with them, and even experts often derive different function points. In addition, all stakeholders strongly make the validity and accuracy of the function point values of the project before /after the development is completed. There are methods for performing function point analysis using source code [1][2][3][4] and some researchers [5][6][7] attempt empirical verification of function points about the estimated cost. There is no research on automatic cost validation with source code after the final development is completed. In this paper, we propose automatically how to calculate Function Points based on natural language requirements before development and prove FP calculation based on the final source code after development. We expect validation by comparing the function scores calculated by forward engineering and reverse engineering methods.

• Journal of Digital Convergence
• /
• v.17 no.9
• /
• pp.23-30
• /
• 2019

The development of content for language education using AR/VR technology is a necessary task to be pursued in line with commercialization of 5G. Research on service platform for systematic management and service is currently being carried out by global companies competitively, The unique language education service model for unique areas of culture has the right to pursue R & D jointly with Korea and China. In this study, we applied the developed "Korean language education service platform for Chinese people based on e-learning" to improve the acceptance of AR/VR contents and applied AR/VR technology to video-based language education contents. And to present a new paradigm of language education. Contents development is to develop AR-based vocabulary learning services, develop experiential learning contents for VR-based step-by-step situations, and gradually develop contents to enable beginner / intermediate / advanced language education services. The service platform enables management of learning management and learning contents, and complies with metadata attributes to complete a platform capable of accommodating large capacity AR/VR contents. In the future, systematic research will be carried out in order to develop as a portal for educational services through development of various contents using mixed reality technology.

• Journal of the Korean Society of Industry Convergence
• /
• v.25 no.5
• /
• pp.817-826
• /
• 2022

Patent information describes the history of technological progress in the relevant field, so it can be usefully used to identify trends in technological development and change and to establish R&D development strategies. This study proposes a method to identify the needs and problems of technology development at the planning stage of the R&D process and to analyze core technologies through patent analysis using Natural Language Processing(NLP) technology. As a big data source, collected patent documents registered in Google Patents for foldable technology, the latest technology in the display industry, and then extracted keywords using NLP analyzer. By classifying the extracted keywords into needs and problems for technology development, developed technology and materials, identified the needs of the market and customers and analyzed the technologies being researched and developed. Unlike previous studies that performed patent analysis, this methodology is different in that it can quickly and conveniently analyze the latest technology trends from big data called patents even if you do not have specialized knowledge and skills in the text mining. This study contributes to the digitalization of the R&D process based on data analysis.

• Geomechanics and Engineering
• /
• v.37 no.4
• /
• pp.395-418
• /
• 2024

The epicentral region of earthquakes is typically where liquefaction-related damage takes place. To determine the maximum distance, such as maximum epicentral distance (R_e), maximum fault distance (R_f), or maximum hypocentral distance (R_h), at which an earthquake can inflict damage, given its magnitude, this study, using a recently updated global liquefaction database, multiple ML models are built to predict the limiting distances (R_e, R_f, or R_h) required for an earthquake of a given magnitude to cause damage. Four machine learning models LSTM (Long Short-Term Memory), BiLSTM (Bidirectional Long Short-Term Memory), CNN (Convolutional Neural Network), and XGB (Extreme Gradient Boosting) are developed using the Python programming language. All four proposed ML models performed better than empirical models for limiting distance assessment. Among these models, the XGB model outperformed all the models. In order to determine how well the suggested models can predict limiting distances, a number of statistical parameters have been studied. To compare the accuracy of the proposed models, rank analysis, error matrix, and Taylor diagram have been developed. The ML models proposed in this paper are more robust than other current models and may be used to assess the minimal energy of a liquefaction disaster caused by an earthquake or to estimate the maximum distance of a liquefied site provided an earthquake in rapid disaster mapping.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.5
• /
• pp.1013-1027
• /
• 2013

As the need for large-scale data analysis is rapidly increasing, Hadoop, or the platform that realizes large-scale data processing, and MapReduce, or the internal computational model of Hadoop, are receiving great attention. This paper reviews the basic concepts of Hadoop and MapReduce necessary for data analysts who are familiar with statistical programming, through examples that combine the R programming language and Hadoop.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2001.10a
• /
• pp.274-279
• /
• 2001

This paper presented a virtual manufacturing simulation system by using Virtual Reality Modeling Language (VRML) and Finite Element Method(FEM). The system is to simulate forging operation. Stress distributions and deformation profiles as well as the operation of forging machine can be simulated and visualized in the web. Since the forging machine, user interface, and specimen were modeled by using Java and VRML, the forging machine and analysis results were browsed and integrated on the web that is interfaced to users through EAI to show the whole forging simulation. The developed system realized the working environment virtually so that education and experiment of forging process could be performed effectively even on the PC.