• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.26 no.11C
• /
• pp.148-156
• /
• 2001

This paper proposed embedded application-specific microprocessor(YS-RDSP) whose structure has an additional DSP processor on chip. The YS-RDSP can execute maximum four instructions in parallel. To make program size shorter, 16-bit and 32-bit instruction lengths are supported in YS-RDSP. The YS-RDSP provides programmability. controllability, DSP processing ability, and includes eight-kilobyte on-chip ROM and eight-kilobyte RAM. System controller on the chip gives three power-down modes for low-power operation, and SLEEP instruction changes operation statue of CPU core and peripherals. YS-RDSP processor was implemented with Verilog HDL on top-down methodology, and it was improved and verified by cycle-based simulator written in C-language. The verified model was synthesized with 0.7um, 3.3V CMOS standard cell library, and the layout size was 10.7mm78.4mm which was implemented by using automatic P&R software.

• Journal of Digital Contents Society
• /
• v.18 no.4
• /
• pp.747-751
• /
• 2017

The log has variable informations that are important and necessary to manage a network when accessed to network servers. These informations are used to reduce a cost and efficient manage a network through the meaningful prediction information extraction from the amount of user access. And, the network manager can instantly monitor the status of CPU, memory, disk usage ratio on network using the SNMP. In this paper, firstly, we have accumulated and analysed the 6 network logs and extracted the informations that used to predict the amount of user access. And then, we experimented the prediction simulation with the time series analysis such as moving average method and exponential smoothing. Secondly, we have simulated the usage ration of CPU, memory, and disk using Xian SNMP simulator and extracted the OID for the time series prediction of CPU, memory, and disk usage ration. And then, we presented the visual result of the variable experiments through the Excel and R programming language.

• Research in Community and Public Health Nursing
• /
• v.24 no.1
• /
• pp.29-39
• /
• 2013

Purpose: The purpose of this study is to investigate levels of stress, self-esteem, and powerlessness in Korean husbands married to foreigner wives. Methods: The subjects were 183 Korean men who were living with foreigner wives in the Gwangju, Jeonnam and Jeonnbuk areas. Data were collected from January to May 2012 and analyzed by descriptive statistics, t-test, one-way ANOVA, Scheffe$\acute{e}$ test, Pearson's correlation coefficient, and backward multiple regression with the SPSS PC WIN version 18.0. Results: The average level of stress was 4.48, with difficulties in international marriage experienced by the subjects due to differences in language and culture. The average reported self-esteem score was 29.69, and the average powerlessness score 117.76. There were significant differences in perceived powerlessness depending on the employment statuses, income levels, and nationalities of the participants' wives, and their perceived levels of satisfaction with living with a foreigner wife. Powerlessness was positively correlated with stress (r=.41, p<.001), and negatively correlated with self-esteem(r=-.63, p<.001). The factors affecting the perceived powerlessness included self-esteem (${\beta}$=-.54, p<.001), stress (${\beta}$=.28, p<.001), lower income (${\beta}$=.13, p = .016), and working wife (${\beta}$=.12, p = .036). Conclusion: Healthcare providers need to explore strategies to improve self-esteem and powerlessness in Korean men married to foreigner wives.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.4
• /
• pp.739-746
• /
• 2020

The fourth industrial revolution introduced at world economic forum in 2016 has had huge effects on tourism industries as well as the change of core technologies in ICT such as big data, IoT, etc, This paper proposes the methods to propel tourism of Yoesu city through big data analysis and questionnaires. Sensitive words and positive-negative trend are extracted by Social Metrics and the keywords for Yeosu tour trends are extracted and analyzed by Naver datalab, and the results are visualized by R language. And frequency, difference, factor, covariance and regression analysis in SPSS are executed for the questionnaires for 493 visitors who traveled in Yeosu city. Sentiment analysis for Yeosu tour and maritime cable car shows that positive effect is much more than negative one. The analyses for questionnaires in SPSS show that Yeosu area is statistically significant to tour satisfaction index and tour revitalization for Yeosu, and favorite sightseeing places and searching electronic devices for age groups are different. The sightseeing places such as a maritime park with soft contents that give joyfulness and healing to tourists are highly attracted in both the big data and questionnaires analysis.

• Structural Engineering and Mechanics
• /
• v.7 no.6
• /
• pp.589-599
• /
• 1999

This paper presents the development and applications of the software package JIFEX, a new finite element system which can be used for structural analysis and optimum design by the modern computer hardware and software technologies such as MS Windows95/NT and Pentium PC platforms. The complete system of JIFEX is programmed with $C/C^{++}$ language to make full use of advanced facilities of MS Windows95/NT. In the system, the finite element data pre-processing, based on the most popular CAD package AutoCAD (R13, R14), has been implemented, so that the finite element modeling could be integrated with geometric modeling of CAD. The system not only has interactive graphics facility for data post-processing, but also realizes the real-time computing visualization by means of the Dynamic Data Exchange (DDE) technique. Running on the Pentium computers, JIFEX can solve large-scale finite element analysis problems such as the ones with more than 60000 nodes in the finite element model.

• Phonetics and Speech Sciences
• /
• v.13 no.3
• /
• pp.31-37
• /
• 2021

The fundamental frequency, or f0, is an important acoustic measure in the prosody of human speech. The current study examined the f0 distribution of a corpus of spontaneous speech in order to provide normative data for Korean speakers. The corpus consists of 40 speakers talking freely about their daily activities and their personal views. Praat scripts were created to collect f0 values, and a majority of obvious errors were corrected manually by watching and listening to the f0 contour on a narrow-band spectrogram. Statistical analyses of the f0 distribution were conducted using R. The results showed that the f0 values of all the Korean speakers were right-skewed, with a pointy distribution. The speakers produced spontaneous speech within a frequency range of 274 Hz (from 65 Hz to 339 Hz), excluding statistical outliers. The mode of the total f0 data was 102 Hz. The female f0 range, with a bimodal distribution, appeared wider than that of the male group. Regression analyses based on age and f0 values yielded negligible R-squared values. As the mode of an individual speaker could be predicted from the median, either the median or mode could serve as a good reference for the individual f0 range. Finally, an analysis of the continuous f0 points of intonational phrases revealed that the initial and final segments of the phrases yielded several f0 measurement errors. From these results, we conclude that an examination of a spontaneous speech corpus can provide linguists with useful measures to generalize acoustic properties of f0 variability in a language by an individual or groups. Further studies would be desirable of the use of statistical measures to secure reliable f0 values of individual speakers.

• The Journal of Korean Association of Computer Education
• /
• v.22 no.3
• /
• pp.123-133
• /
• 2019

The purpose of this study is to establish Smart Education Environment for children's personalized learning based on the data are accumulated by Smart Device which is one of element on Smart Education. In this study, we propose the operational improvement plan for the free choice activity in the 5-year-old kindergarten and also implement the Free Choice Activity(FCA) management system for children to select and to evaluate the play plans for themselves. Children participating in this study have fun the whole time for the process of self-planning, the playing activities and the self-assessment of playing. As a result, it is confirmed that children participate actively in decision-making of interesting areas through the smart device than the traditional education environment before. A single teacher using FCA management system with smart device in this study can get useful information without difficulty of individual child's interests, learning and the statistics of children in the classroom.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.7
• /
• pp.764-770
• /
• 2019

In this research, text mining techniques were used to analyze the papers related to the "4th Industry". In order to analyze the papers, total of 685 papers were collected by searching with the keyword "4th industry" in Korea Journal Index(KCI) from 2016 to 2019. We used Python-based web scraping program to collect papers and use topic modeling techniques based on LDA algorithm implemented in R language for data analysis. As a result of perplexity analysis on the collected papers, nine topics were determined optimally and nine representative topics of the collected papers were extracted using the Gibbs sampling method. As a result, it was confirmed that artificial intelligence, big data, Internet of things(IoT), digital, network and so on have emerged as the major technologies, and it was confirmed that research has been conducted on the changes due to the major technologies in various fields related to the 4th industry such as industry, government, education field, and job.

• Journal of the Korean Society of Safety
• /
• v.36 no.5
• /
• pp.61-70
• /
• 2021

This study aimed to analyze the research trends of the abstract data of ergonomic studies registered in MEDLINE, a medical bibliographic database, using word embedding. Medical-related ergonomic studies mainly focus on work-related musculoskeletal disorders, and there are no studies on the analysis of words as data using natural language processing techniques, such as word embedding. In this study, the abstract data of ergonomic studies were extracted with a program written with selenium and BeutifulSoup modules using python. The word embedding of the abstract data was performed using the word2vec model, after which the data found in the abstract were vectorized. The vectorized data were visualized in two dimensions using t-Distributed Stochastic Neighbor Embedding (t-SNE). The word "ergonomics" and ten of the most frequently used words in the abstract were selected as keywords. The results revealed that the most frequently used words in the abstract of ergonomics studies include "use", "work", and "task". In addition, the t-SNE technique revealed that words, such as "workplace", "design", and "engineering," exhibited the highest relevance to ergonomics. The keywords observed in the abstract of ergonomic studies using t-SNE were classified into four groups. Ergonomics studies registered with MEDLINE have investigated the risk factors associated with workers performing an operation or task using tools, and in this study, ergonomics studies were identified by the relationship between keywords using word embedding. The results of this study will provide useful and diverse insights on future research direction on ergonomic studies.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.8
• /
• pp.41-47
• /
• 2022

In this paper, we propose how to implement text summaries for colloquial data that are not clearly organized. For this study, SAMSum data, which is colloquial data, was used, and the BERTSumExtAbs model proposed in the previous study of the automatic summary model was applied. More than 70% of the SAMSum dataset consists of conversations between two people, and the remaining 30% consists of conversations between three or more people. As a result, by applying the automatic text summarization model to colloquial data, a result of 42.43 or higher was derived in the ROUGE Score R-1. In addition, a high score of 45.81 was derived by fine-tuning the BERTSum model, which was previously proposed as a text summarization model. Through this study, the performance of colloquial generation summary has been proven, and it is hoped that the computer will understand human natural language as it is and be used as basic data to solve various tasks.